Proceedings of the 2019 (9th) International Conference

An official publication of the

Association of Global Management Studies

Proceedings of the 2019 (9th) International Conference

Association of Global Management Studies Saïd Business School

University of Oxford, Oxford United Kingdom

July 1st and July 2nd (Abstracts and Selected Papers)

Conference Proceedings

Editors :

Dr. Daniel Tomiuk

Université du Québec à Montréal, Canada

Dr. Mukesh Srivastava

University of Mary Washington, USA

Print ISSN: 2150-846

Online ISSN: 2150-8488

Print ISSN: 2150-856

Online ISSN: 2150-8488

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Editorial Board

Mukesh Srivastava, DBA

Editor-in-Chief

University of Mary Washington

Camilla Noonan, Ph. D.

University College Dublin, Ireland

C. E. Tapie Rohn, Ph. D.

California State University-San Bernardino

Chang-tseh Hsieh, Ph. D.

University of Southern Mississippi

Daniel Tomiuk, Ph. D.

Université du Québec à Montréal, Canada

Diana Kay Pence, Ph. D.

University of Houston-Downtown

Hamed Motagi, Ph.D.

Université du Québec en Outaouais, Canada

Jack T. Marchewka, Ph. D.

Northern Illinois University

John Saee, Ph. D.

Reutlingen University, Germany

Pascal Ravesteijn, Ph. D.

University of Applied Sciences Utrecht, Netherland

Ramesh Subramanian, Ph. D.

Quinnipiac University

Seamas Kelly, Ph. D.

University College Dublin, Ireland

Stephen C. Wingreen, Ph.D.

University of Canterbury, New Zealand

Van R. Wood, Ph. D.

Virginia Commonwealth University

Contents Commercial Bank’s Recapitalization and Small Scale Enterprises’ (SMEs) Growth in

Nigeria ............................................................................................................................................ 1

Design and Development of Citizens Information System ...................................................... 20

Can Instagram Convince Information to Users? ..................................................................... 30

Complexity Concepts in Market Dynamics; the Evolution of Market Alliances .................. 51

BASEL III implementation on financial performance. Banking in ASEAN. ....................... 65

Financial Behaviour, E-Trading Satisfaction, E-Trust, and E-Loyalty of E-Trading in

Indonesian Stock Exchange with SEM-PLS............................................................................. 80

The relationship of GCG, company size, liquidity, capital structure, and profitability with

SEM-PLS ..................................................................................................................................... 95

The factors that influence financial distress of Indonesia manufacturing company .......... 109

Complexity concepts in market dynamics; the evolution of market alliances .................... 125

Firm trends in markets and their consequences; mapping evolution of firm behavior using

the deep and surface structures of the market ....................................................................... 139

The Relationship Between Ethical Leadership and Nurse Job Performance: Boundary

Conditions and Influence Processes ........................................................................................ 159

Organization or Human Capital Who Understands the System Better .............................. 182

The national business context for industrial SME cluster development in Pakistan:

constraining and facilitating factors........................................................................................ 183

Impact of transformational leadership on employee’s performance, with the mediating role

of job satisfaction and employees’ commitment .................................................................... 219

Toward a Model for Actual Usage of Social Networks Sites for Educational Purposes in

Jordanian Universities .............................................................................................................. 249

Product/Service Complexity and Choice of Channels for Information Search During the

Purchase Process: A Proposed Model Based on Media-Richness Theory.......................... 261

Firm structures in markets and the supporting lifecycle logic: the case for market evolution

..................................................................................................................................................... 273

Commercial Bank’s Recapitalization and Small Scare Enterprise’ (SMEs) Growth in Nigeria

Okhankhuele and Okhankhuele

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© 2019 (9th) International Conference of the AGMS Proceedings

Commercial Bank’s Recapitalization and Small Scale Enterprises’ (SMEs) Growth in

Nigeria

Omonigho Tonia Okhankhuele

Department of Business Administration,

Federal University of Technology,

Akure, Ondo State, Nigeria.

[email protected]

Tel: +234-806-282-4074

Onolenrekhian Philo Okhankhuele

Department of Business Administration,

Joseph Ayo Babalola University,

Ikeji-Arakeji, Osun State, Nigeria.

[email protected]

Tel: +234-803-464-508

Abstract

This paper examined the relationship between the total loan granted to SMEs by commercial banks

and SMEs share in Gross Domestic Product (GDP) before the last banks’ recapitalization (1982-

2005) in Nigeria, after the last banks recapitalization (2006-2012) and assessed the effect of

commercial banks’ recapitalization on SMEs’ growth in Nigeria (1982-2012). Secondary data on

yearly share of the manufacturing SMEs in Nigeria’s GDP and Total loan granted to all SMEs by

commercial banks in Nigeria from 1982 to 2012, were extracted from the Central Bank of

Nigeria (CBN) Statistical Bulletin (2002; 2008; 2013; 2015), CBN Annual Report and Statement

of Accounts (2011a; 2012a) and National Bureau of Statistics–Job Creation and Employment

Surveys (2012a), and utilized for the study. Data collected were analyzed using Pearson Product-

Moment Correlation Coefficient (PPMCC). The results showed that there was a positive

relationship between SMEs’ growth and total loan granted to SMEs before the 2006 commercial

banks’ recapitalization in Nigeria (1982-2005). The calculated value for the Pearson correlation

was 0.740, there was a negative relationship between the two variables after the 2006

commercial banks’ recapitalization (2006-2012), with calculated value for the Pearson

correlation of -0.664, and there was no significant relationship between SMEs contribution to

total GDP and commercial banks’ loans to SMEs in Nigeria for the period between 1982 and

2012. The calculated value for the Pearson correlation was 0.240. However, the level of

significance of 0.194 was attained which was higher than the table value of 0.05. Therefore, the

study concluded that, there was no significant relationship between SMEs’ growth and

Commercial Banks’ Recapitalization in Nigeria. The study recommended that, the government

inquire into the reason for the reduction in the commercial banks’ loan disbursement to SMEs,

especially after the commercial banks’ recapitalization, and takes necessary actions to solve the

problem.

Keywords: Commercial Bank, Recapitalization, Enterprises, Small Scale, Growth





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1) Introduction

Small and Medium Enterprises (SMEs) serve as the nurturing and breeding grounds for

technological transformation, technical know-how, managerial capabilities, domestic

entrepreneurial facilities and advancement of an energetic and industrious economy in every

nation (Small and Medium Scale Enterprises Development Agency in Nigeria (SMEDAN,

2010). SME sector is an incubator for economic advancement, an abode for creating innovations

and where novel ideas grow into economically viable businesses. (Craig, 2005). SMEs serve as a

form of survival to a lot of families in countries where the inhabitants do not feel the presence of

government (Motilewa, Ogbari, and Aka, 2015). They make significant contributions to the

productivity of nations and thus, enhance competitiveness and total economic growth. SMEs

have been acknowledged as the highest employer of labor, with enormous potential for

generating employment and creating wealth in every economy (Abiola, Iyoha, and Joseph,

2011).

Despite the fact that the Nigerian SMEs make up more than 90% of Nigerian businesses,

they contribute below 10% to the Gross Domestic Product (GDP) of the nation (Gbandi and

Amissah, 2014), produce only 10-15 percent of the industrial output, even when they employ

70% of the Industrial labor force. More than 50 % of Nigeria SMEs breakdown within the first

five years, about 25 % go bankrupt or fold up (CBN, 2002).

Recognizing the importance of SMEs to nations, successive governments in Nigeria,

have carried out numerous policies to create enabling environment for SMEs to strive in their

countries, foster, develop, assist in innovation and management. Among these agencies and

funding schemes are: the Nigerian Industrial Development Bank (NIDB) (1964), Small Scale

Industries Credit Scheme (SSICS) (1971), Nigerian Bank for Commerce and Industry (NBCI)

(1973), Bank of Industry (2001), Nigerian Agricultural, Cooperative, and Rural Development

Bank (NACRDB), Bank of Agriculture (BOA) (2000), Nigerian Directorate of Employment

(NDE), National Poverty Eradication Programme (NAPEP), African Development Bank (ADP)

(1989), National Economic Reconstruction Fund (NERFUND) (1989), Small and Medium

Enterprises Development Agency of Nigeria (SMEDAN) (2003), Micro Finance Banks (MFB),

Nigerian Export and Import Bank (NEXIM), Small and Medium Industry Development Agency

(SMIDA) (2003), Small and Medium Enterprises Equity Investment Scheme (SMEEIS) (2001)

among others (Real Sector Division Research Department, Central Bank of Nigeria (CBN),

2014; Soludo, 2008; Evbuomwan, Ikpi, Okoruwa and Akinyosoye, 2013; Terungwa, 2012).

Notwithstanding the numerous government intervention schemes, a lot of SMEs still

struggle to survive let alone contribute satisfactorily to the economy. SMEs in Nigeria have

performed below expectation and have not been able to make the anticipated impact on the

economy (Gbandi and Amissah, 2014; Terungwa, 2012). One of the most hindrances of SMEs in



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Nigeria is the inability to obtain finance from banks and other financial houses, either to start or

expand SMEs.

Although there have been numerous analyses on the impact of bank consolidation,

recapitalization and banking sector reforms on the performance of SMEs in Nigeria (Mamman

and Aminu, 2013; Duru and Lawal, 2012; Obasan and Arikewuyo, 2012; Omah, Durowoju,

Adeoye and Elegunde, 2012), these studies mainly focused on the effect of recapitalization on the

financing of SMEs. In these studies, commercial banks financing before 2006 recapitalization were

compared with their financing after the recapitalization, without comparing the financing with the

SMEs’ output before and after the recapitalization. The idea is that, finance as an input (total loan

granted to SMEs by commercial banks) must be compared with an output (SMEs share in Gross

Domestic Product (GDP)), before the effect of the input on the output can be determine. This is the

area where this study contributed to the already existing literature.

There is no worldwide accepted definition of SMEs. Several common features in the

definition of SMEs include: number of employees, relative size, initial capital outlay, financial

strength, sales value, and types of industry (Carpenter, 2003). The National Policy on MSMEs

(2012) and Small and Medium Enterprises Development Agency of Nigeria (SMEDAN) (2007)

categorised SMEs by Assets and Employment, with Micro Enterprises having below 10

employees and asset base less than 5 million naira (not including land and building), Small

Enterprises, 10 to 49 employees and asset base of 5 to below 50 million naira (not including land

and building), and Medium Enterprises, 50 to 199 employees and asset base of 50 to below 500

million naira (not including land and building). This categorization of SMEs will be adopted for

this study because, SMEs in Nigeria have limited capital and number of employees as depicted

by this categorization.

A commercial bank is a financial institution that has the legal authority to receive and

lend money from institutions, individuals and businesses. Its function among others include:

receiving of deposits from individuals and businesses, disbursing payments, collecting and

transferring funds from and to its customers and other banks on behalf of its customer. That is,

acting as a customer’s agent, safeguard customers ’money, maintaining depositors’ savings and

checking accounts, maintaining custodial accounts (accounts controlled by one person but for the

benefit of another person), lending money, among others. Its role in the economy include among

others, financing capital investment (Wikipedia).

Banking system’s consolidation means a deliberate policy measure to raise the capital

base of banks in order to make the banks sound, safe and viable business entities (Real Sector

Division Research Department, Central Bank of Nigeria (CBN) (2014). Consolidation is a word

used by the Central Bank of Nigeria (CBN) to refer to the collection of some banks within the

country to come together in order to meet CBN’s requisite for capitalization to a minimum of



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N25 billion (16 million US dollar) (Omah et al., 2012).

The main objective of this study is to evaluate the impact of commercial banks’

recapitalization on SMEs’ growth in Nigeria, while the specific objectives include: to identify the

total loan granted to SMEs by commercial banks and SMEs growth (share in Gross Domestic

Product (GDP)) before (1982-2005) and after (2006-2012) the last banks’ recapitalization in Nigeria,

and assess the impact of the loan on SMEs’ growth (share in Gross Domestic Product (GDP)) before

and after the recapitalization, and from 1982-2012. The related theory to this study is Say’s Law

theory (Emori, Nkamare, and Nneji, 2014). This theory proposes that recapitalization of banks

boosts their capital base and increases the availability of loanable funds in the banks, to the

economy. The result of this is that, interest rate will reduce, and SMEs will be able to borrow

more money from the banks, and this will improve their growth.

2) Literature Review

2.1 Reasons for Recapitalization and the Effect of Recapitalization on Banks and the

Economy

Bank consolidation increases the size of banks, upsurges banks’ returns, via revenue and

cost efficiency gains, and may also decrease the risks of industry via the eradication of banks that

are weak and create better opportunities for diversification (Berger, 2000). The outcome of

recapitalization is: the long-term capital stock of the firm is raised extensively to withstand the

operational undertakings of the business which can have a positive impact on the economy;

credit accessibility and financial stability which would aid the growth of the economy and

encourage banks to play critical role of financial intermediation in the Nigerian economy is

improved (Imoughele and Ismaila, 2014); internal and external balances, full employment,

macroeconomic goals of price stability, high economic growth may be attained (Akpansung and

Gidigbi, 2014); cheap credit to the real sector and financial accommodation for SMEs are made

available (Anyanwu, 2010). Recapitalization leads to an increase in capital base of a bank and

this may help to fortify and aid operational efficiency in banks; aids in attaining operational

synergy via mergers and acquisition; assist to upsurge liquidity efficiency and enhance

diversification that may aid macroeconomic stability and sustainability in the long run; aids

economies of scale through the reduction in banks’ cost of operation occasioned from a decrease

in branch networks, staff overheads, among others, upturns the propensity of banks in the

direction of risk taking via increases in leverage and off balance sheet operations; and makes

available, services that guarantee the development of the economy, (Eferakeya, 2014; De Nicoló

et al., 2003).

However, Asedionlen (2004) asserted that ‘‘recapitalization may raise liquidity in short

term but will not guaranty a conducive macroeconomic environment required to ensure high

asset quality and good profitability’’. In the same vein, Adegbaju and Olokoyo (2008) in their



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study, revealed that only a small number of banks experienced significant advancement in their

performances while others were worse or remain the same after recapitalization.

2.2 Effect of Recapitalization on Commercial Banks’ Ability to Finance SMEs and Lead

to their Growth

SMEs in Nigeria rely on banks for funding and are therefore susceptible to all the

changes, developments and reforms that take place in the banking system (Mamman and Aminu

(2013). These changes may be advantageous or disadvantageous to SMEs financing. Banks

consolidation may result to banks efficiency via cost synergies or by takeover of inefficient

banks by efficient ones and upturn market power which may stimulate the supply of credit to

SME’s (Degryse, et al., 2005). Banks’ consolidation improves the flow of credit to SMEs, which

would be noticeable in efficiency gains, which would favour borrowing to small firms in the long

run (Real Sector Division Research Department, Central Bank of Nigeria (CBN) (2014). Under

decentralized structure the banks require the services of additional supervisors to lessen the

information asymmetries that take place within a firm. Therefore, decentralized banks manage to

finance more small firms, but suffer higher costs than centralized banks. However, it is not the

banking size that matters, but the organizational structure is key in small business lending

(Takáts, 2004).

Meanwhile, Obasan and Arikewuyo (2012) disclosed that consolidation has been

unsuccessful in fostering a competitive and energetic SMEs sector that could improve the

creation of job and growth in the Nigerian economy. The advent of mega banks led to: shrinkage

of credit to SMEs (Berger and Udell, 2002; Banaccorsi di Patti and Gobbi; 2001) and substantial

reduction of small businesses’ access to credit, but increased credit limit to SMEs (Craig and

Hardee, 2004). CBN (2012b) disclosed that 6.02 per cent of the entire credit to private sectors

was dispensed to SMEs from 2000 to 2005, while between 2006 and 2011, after the last banks’

recapitalization in Nigeria, the entire credit paid out by Deposit Money Banks (DMBs) to SMEs

as a ratio of private sectors’ credit reduced to an average of 0.41 per cent.

Banaccorsi di Patti and Gobbi (2001) concluded that mergers in Italian banks led to

provisional decrease in outstanding credit to all dimensions of borrowers, and loans received

from commercial banks by SMEs as a percentage of total credits reduced from 48.79% in 1992

to 0.15% in 2010 (Luper, 2012). Bigger banks are less likely to lend to SMEs because they

depend on formal framework for determining whether to give credit to SMEs and the amount of

credit to give to them (Craig and Hardee (2004). Since consolidation decreases the number of

smaller banks, it can be concluded that there will be a decrease in SMEs’ financing because these

loans are considered less profitable for large banks (Marsch, Schmieder and Aerssen, 2007; De

Haas et al., 2010). Larger banks normally have a smaller tendency to give loan to SMEs

(Marsch, et al., 2007). The enormous capital attained by the banks during consolidation exercise

is mainly directed towards non-real sector, non-SMEs, and bad and doubtful loans (Adedayo,

2015). After the Post Bank Consolidation in Nigeria, banks still lend at appalling interest rates of



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about 20% as against zero percent, 5 percent and 3 percent interest rate in China, Japan and

Malaysia (Olutunla and Obamuyi, 2008). While Ojo, (2009) and Duru and Lawal (2012) asserted

that Nigerian banks’ recapitalization led to an increase in SME’s financing and as such increased

their development, Obasan and Arikewuyo (2012), Mamman and Aminu (2013), Eferakeya

(2014), Luper (2013) think otherwise.

3) Research methodology

3.1 The Study Area

The Federal Republic of Nigeria is found in the West Africa region. It lies between

Latitudes 4 o to 14o North and between Longitudes 2o2’ and 14 o 30’ East. It is bounded in the

north by the Niger Republic and Chad; in the west by Benin Republic, in the East by Cameroon

Republic and south by the Atlantic Ocean. The country obtained its name from river Niger, one

of the rivers that divided the country into three. Nigeria has a land area of around 923 769 km2

(Federal Office of Statistics (FOS), 1989; Aregheore, 2005; West African Examinations

Council (WAEC) (2009)). The surface area of Nigeria as 91.07 million hectares (Federal

Ministry of Environment of Nigeria (FMEN), 2001). Nigeria consists of 36 states and the

Federal Capital Territory, Abuja, 744 Local Government Areas and six geographical region

(South-south, South-east, South-west, North-central, North-east, North-west). Today Nigeria is

the most populous country in Africa with an estimated population of 131,859,731 inhabitants

(Aregheore, 2009; West African Examinations Council (WAEC); 2009).

3.2 Methodology

Census sampling was used for this study, because the yearly share of all manufacturing SMEs

(in Nigeria) in GDP (N Million) from 1982-2012 and the Total loan (N Million) granted to all

SMEs by the commercial banks in Nigeria for these years were selected from CBN Statistical

Bulletin (2002; 2008; 2013; 2015), Central Bank of Nigeria, Annual Report and Statement of

Accounts (2011a; 2012a) and National Bureau of Statistics –Job Creation and Employment

Surveys (2012a) and used for the analysis. This means secondary data was used for this study.

The study population comprised all manufacturing SMEs in Nigeria, that contributed to GDP from

1982 to 2012, and all the commercial banks that granted loan to SMEs in Nigeria, within these

years. The Statistical Package for the Social Sciences (SPSS) was used to carry out the analysis

of this research. Data were analyzed with inferential statistics.

Analyses was carried out in three stages. Firstly, the relationship between SMEs growth

(dependent variable) and the commercial bank’s recapitalization (independent variable) was

calculated before the last recapitalization (1982-2005), then after recapitalization (2006-2012),

and then the relationship between the total loan granted by commercial banks to SMEs before



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and after banks’ recapitalization (1982-2012) in Nigeria and SMEs’ share in GDP during the

same period, was analysed and used to examine the impact of recapitalization on SMEs’

growth in Nigeria within the specified period. Pearson Product-Moment Correlation Coefficient

(PPMCC) was used to measure the strength and direction of the linear relationship between the

two variables. The linear relationship is usually represented by “r”, and the value of r is always

between +1 and –1. if r =1, it means that there is a perfect positive linear relationship between

the dependent and independent variables, while 0 means that there is no relationship between

the two variables. A value above 0 means that a positive relationship exists. The closer the

value of r is to +1, the stronger the linear relationship.

3.3 Model Specification

The model below specified that SMEs growth is influenced by commercial bank’s

recapitalization. That means:

SMEs Growth (Y) = f (commercial bank’s recapitalization (x)

Where Y = Dependent Variable

X = Independent variable

4) Findings/results

4.1 Relationship between Small Scale Enterprises’ (SMEs) Share in GDP and Total

Loan Granted to SMEs by Commercial Banks’ Before Recapitalization in Nigeria

in 2006

Table 1 presents SMEs’ Share in GDP (N’ million) and total loan granted to SMEs by

commercial banks (N’ million), before the last (2006) recapitalization (that is from 1982-2005,

which was used to analyse before the recapitalization. However, 2006 to 2012 was used to

analyse after recapitalization, while 1982-2012 was used to analyse before and after

recapitalization. The table revealed that SMEs’ Share in GDP declined from N7,890.70 million

in 1982, to N4,926.20 million in 1984, rose to N5,903.50 million in 1985, dropped a little to

N5,673.90 million in 1986, and continued to rise from N5,963.20 million in 1987 to N8,046.00

million in 1991. It however dropped to N7,657.20 million in 1992 and continued dropping till

1995, to N6,880.00 million. It increased a little to N6,940.00 million in 1996 and continued to

increase till 2005, to N408,367. 52 million.

On the other hand, the total loan granted to SMEs by commercial banks, increased from

N206.70 million in 1982 to N3,587.30 million in 1986, decreased to N1,445.30 million in

1987, increased to N5,090.00 million in 1988 to N5,900.00 million in 1990, to N20,400.0

million in 1992. It however dropped to N15,462.9 million in 1993, increased to N20,552.5



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million in 1994, and kept increasing till it rose to N46,824.0 million in 1999. It dropped to

N44,542.3 million in 2000, and rose from N52,428.4 million in 2001 to N90,176.5 million in

2003. It however, dropped to N54,981.2 million in 2004, and further dropped to N50,672.6

million in 2005. The total loan granted to SMEs from 1982 to 2005 was N667,765.7 million, an

average of N27,823.57 million per annum.

4.1.1 Table 1: SMEs’ Share in GDP (N’ million) and Total Loan Granted to SMEs by

Commercial Banks (N’ million), Before Recapitalization (1982-2005), after

recapitalization (2006-2012), and before and after recapitalization (1982-2012)

Sources: CBN Statistical Bulletin (2002; 2008;2013;2015)

Central Bank of Nigeria, Annual Report and Statement of Accounts (2011;2012).

National Bureau of Statistics –Job Creation and Employment Surveys (2012)

Year SMEs’ Share in GDP (N’m) Total Loan Granted to SMEs by

Commercial Banks (N’m) 1982 7890.70 206.70 1983 5549.40 351.30 1984 4926.20 705.70 1985 5903.50 927.20 1986 5673.90 3587.30 1987 5963.20 1445.30 1988 6729.50 5090.00 1989 6840.20 5789.50 1990 7371.40 5900.00 1991 8046.00 7572.30 1992 7657.20 20400.0 1993 7341.00 15462.9 1994 7280.00 20552.5 1995 6880.00 32374.5 1996 6940.00 42302.1 1997 6960.00 40844.3 1998 6980.00 42260.7 1999 7330.00 46824.0 2000 7180.00 44542.3 2001 7480.00 52428.4 2002 507836.82 82368.4 2003 465811.68 90176.5 2004 349316.32 54981.2 2005 408367.52 50672.6 2006 478524.14 25713.7 2007 520883.03 41100.4 2008 585573.04 13512.2 2009 612308.89 16366.5 2010 643070.22 12550.3 2011 694814.15 15611.7 2012 761467.00 13863.5



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4.1.2 Result of the Correlation Analysis between SMEs’ Share in GDP (N’ million) and

Total Loan Granted to SMEs by Commercial Banks (N’ million), Before 2006 (1982-

2005) Banks’ Recapitalization

H0: There is no significant relationship between SMEs’ growth and Total Loan Granted to

SMEs by Commercial Banks (N’ million), Before the banks’ Recapitalization in Nigeria

Test statistic= Pearson Correlation

Level of significance (α) = 0.05 (5%)

Level of confidence= 0.95 (95%)

Decision rule: The Calculated Value for the Pearson correlation was 0.740 this implies that there

was a positive and strong correlation and therefore a significant and positive relationship

between the dependent variable, SMEs growth and the independent variable (Total loan granted

to SMEs) before the 2006 banks’ recapitalization in Nigeria (1982-2005). Also, the calculated

level of significance was 0.000 which is less than the table value of 0.05, therefore, the null

hypothesis was rejected and the alternate hypothesis which states that, there is a significant

relationship between SMEs’ growth and Total Loan Granted to SMEs by Commercial Banks (N’

million), before the banks’ Recapitalization in Nigeria in 2006, was retained.

4.2 Relationship Between Small Scale Enterprises’(SMEs) Share in GDP and Total

Loan Granted to SMEs by Commercial Banks’ After Recapitalization in Nigeria in

2006

4.2.1 SMEs’ Share in GDP (N’ million) and Total Loan Granted to SMEs by

Commercial Banks (N’ million), After 2006 Recapitalization in Nigeria

On table 1, SMEs’ Share in GDP (N’ million) and total loan granted to SMEs by

commercial banks (N’ million), after the last (2006) recapitalization (from 2006-2012) was also

presented. The table revealed that SMEs’ Share in GDP increased from N478,524.14 N’ million

in 2006, and continued to increase to N761,467.00 million in 2012. While the total loan granted

to SMEs by commercial banks, increased from N25,713.7 million in 2006 to N41,100.4 million

in 2007, declined to N13,512.2 million in 2008, increased to N16,366.5 million in 2009, reduced

to N12,550.3 million in 2010, increased to N15,611.7 million again in 2011, and reduced to

N13,863.5 million in 2012.

These figures revealed that the total loan granted to SMEs by commercial banks, in

Nigeria, reduced after the commercial banks recapitalization in Nigeria in 2006. While the total

loan granted to SMEs from 1982 to 2005 was N667,765.7 million, an average of N27,823.57

million per annum, that of 2006 to 2012 was N138,718.3 million, an average of N19,816.9

million per annum. This is a reduction of 28.78 %, approximately 29% per annum. This result is

not far from that of The CBN (2010) statistics which disclosed that banks loan and advances to



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SMEs have been decreasing over the years. The statistics revealed that loans given to SMEs by

commercial banks as a percentage of total credit reduced from 48.79 % in 1992 to 32.18% in

1993 and 22.19% in 1994. The trend increased a little to 22.94% in 1995 and 25.00% in 1996.

There was a profound reduction from 25.00% to 16.96 % in 1997 and 15.49% in 1998.The

reduction continued until it got to 0.17% in 2009 and 0.15% in 2010.

4.2.2 Result of the Correlation Analysis between SMEs’ Share in GDP (N’ million) and

Total Loan Granted to SMEs by Commercial Banks (N’ million), After 2005

(2006-2012) Banks’ Recapitalization

H0: There is no significant relationship between SMEs’ growth and Total Loan Granted to

SMEs by Commercial Banks (N’ million), After the banks’ Recapitalization in Nigeria in 2006.




Decision rule: The Calculated Value for the Pearson correlation was -0.664 which implies that

there is a high but negative correlation between dependent variable (SMEs growth) and the

independent variable (Total loan granted to SMEs after banks’ recapitalization in Nigeria). Also,

the calculated level of significance was -0.104 which is less than the table value of 0.05. This

means, there is a high but negative relationship between the dependent and independent

variables, therefore, the null hypothesis was accepted, while the alternate hypothesis which states

that, there is a significant relationship between SMEs’ Share in GDP (N’ million) and Total Loan

Granted to SMEs by Commercial Banks (N’ million) after 2006 banks recapitalization in Nigeria

was rejected.

4.3: Relationship between Small Scale Enterprises’ (SMEs) Share in GDP and Total

Loan Granted to SMEs by Commercial Banks’ Before and After Recapitalization

in Nigeria in 2006

In table 1, Small Scale Enterprises’ (SMEs) Share in GDP and Total Loan Granted to

SMEs by Commercial Banks’ Before and After Recapitalization (1982-2012) in Nigeria were

also presented.

4.3.1: Result of the Correlation Analysis between SMEs’ Share in GDP (N’ million) and

Total Loan Granted to SMEs by Commercial Banks (N’ million), Before and After

2005 (2006-2012) Banks’ Recapitalization

H0: There is no significant relationship between SMEs’ growth and Commercial Banks’

Recapitalization in Nigeria



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11





Decision rule: The Calculated Value for the Pearson correlation was 0.240. This implies that

there is a very low correlation, but positive relationship, between SMEs’ growth and Commercial

Banks’ recapitalization in Nigeria from 1982-2012. However, the level of significant 0.194 is

higher than the table value of 0.05. This means that, the null hypothesis which states that there is

no significant relationship between SMEs’ growth and Commercial Banks’ Recapitalization in

Nigeria, from 1982 to 2012 will be retained, while the alternative hypothesis will be rejected.

Hence, it can be concluded that There is no significant relationship between SMEs growth and

commercial banks’ recapitalization in Nigeria.

5) Discussion of findings and conclusion

Finding 1:

There is a significant and positive relationship between SMEs’ growth and Total Loan

Granted to SMEs by Commercial Banks, before the banks’ Recapitalization in Nigeria in 2006.

The Calculated Value for the Pearson correlation was 0.740 which implies that there is a positive

and strong correlation and therefore a significant and positive relationship between the dependent

variable (SMEs growth and the independent variable (Total loan granted by commercial banks to

SMEs) before the 2006 banks’ recapitalization in Nigeria (1982-2005). Also, the calculated level

of significance was 0.000 which is less than the table value of 0.05, therefore, the null hypothesis

was rejected, and the alternate hypothesis was accepted. This finding is in agreement with

Evbuomwan, Okoruwa and Ikpi (2013) and Oleka, Maduagwu and Igwenagu, (2014)’s studies,

which concluded that, credit available to SMEs, has a significant effect on the growth of SMEs,

and their contribution to Nigeria’s GDP. On the other hand, the finding is in disagreement with

Lipsey (2003)’s study, which disclosed that commercial banks in Nigeria could not contribute

significantly to SMEs’ advancement, due to the low entrepreneurial development’s rate of

returns.

Finding 2:

The study also revealed that there is a significant but negative relationship between

SMEs’ Share in GDP and Total Loan Granted to SMEs by Commercial Banks after 2006 banks

recapitalization. The Calculated Value for the Pearson correlation was -0.664 which implies that

there is a high but negative correlation between dependent variable (SMEs growth) and the

independent variable (Total loan granted by commercial banks to SMEs after the banks’

recapitalization in Nigeria). Also, the calculated level of significance was -0.104 which is less

than the table value of 0.05. This means, there is a high but negative relationship between the

dependent and independent variables, therefore, the null hypothesis was accepted.



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12


The revelation from this study is in agreement with Obasan and Arikewuyo (2012),

Mamman and Aminu (2013), Luper (2013), Eferakeya (2014), Omah, et al. (2012), and Real

Sector Division Research Department and Central Bank of Nigeria (CBN) (2014)’s conclusion,

that SMEs received no better financing from commercial banks after their recapitalization, that

recapitalization, reduced SME’s financing and as such restricted their development. Also, the

findings are in accord with Berger and Udell (2002), and Banaccorsi di Patti and Gobbi (2001)’s

assertion that, the advent of mega banks led to shrinkage of credit to SMEs, which led to their

inability to grow. However, the study is in disagreement with those of Ojo (2009), Duru and

Lawal (2012), who concluded that, the Nigerian banks’ recapitalization led to an increase in

SME’s financing and as such increased their development.

Finding 3:

The study again found out that, there is no significant relationship between SMEs

growth and commercial banks’ recapitalization in Nigeria. The Calculated Value for the

Pearson correlation was 0.240. This implies that there was a very low correlation, but positive

relationship, between SMEs’ growth and Commercial Banks’ recapitalization in Nigeria from

1982-2012. However, the level of significance 0.194 was higher than the table value of 0.05.

This means that, the null hypothesis which states that there is no significant relationship

between SMEs’ growth and Commercial Banks’ Recapitalization in Nigeria, from 1982 to

2012 was retained, while the alternative hypothesis was rejected. This finding is in agreement

with Lipsey (2003)’s study, which disclosed that commercial banks in Nigeria could not

contribute significantly to SMEs’ advancement, due to the low entrepreneurial development’s

rate of returns. Also, Agumagu (2006), who stated that, the effect of all the credit schemes

established to provide funds to SMEs and contribute to their continuous advancement have

been barely noticeable. Once more, the finding disagreed with those of Ojo (2009), Duru and

Lawal (2012)’s revelation that, the Nigerian banks’ recapitalization led to an increase in SME’s

financing, therefore improved their development.

Conclusion

It can be inferred from the findings of this study above that, there is no significant

relationship between SMEs growth and commercial banks’ recapitalization in Nigeria. The

calculated value for the Pearson correlation between SMEs contribution to total GDP and

commercial banks’ loans to SMEs in Nigeria from 1982 to 2012, was 0.240. This implies that

there was a very low correlation, but positive relationship between these variables. However, the

level of significance of 0.194 was attained which was higher than the table value of 0.05.

Therefore, the study concluded that, there was no significant relationship between SMEs’ growth

and Commercial Banks’ Recapitalization in Nigeria within the study period.

The study recommended that the Nigerian government to makes inquiry into the cause of

reduction in loans disbursed to SMEs by the commercial banks in Nigeria after the

recapitalization (2006-2012) to 28.78 %, approximately 29% per annum, and take positive steps



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13


to remedy the situation, in order to enable the commercial banks to allocate more funds to SMEs

in Nigeria, on regular basis. This disbursement was less than that which was disbursed to the

SMEs by the commercial banks in Nigeria before the recapitalization. Nigerian government also

needs to come out with more efficient and effective policy on financing SMEs in Nigeria and

improve their growth and contribution to Nigeria’s GDP.

6) Limitations and direction for future research

This research has led to many key findings. However, the major limitation of the research

was the variation in the figures of SMEs’ contribution to Gross Domestic Product (GDP) and

Total Loan Granted to SMEs by Commercial Banks, reported by the various government

institutions including the Central Bank of Nigeria (CBN), National Bureau of Statistics (NBS),

among others. The variations were however not grave enough to affect the outcome of the

analysis.

In addition, efforts to obtain recent data on SMEs’ contribution to Gross Domestic

Product (GDP) in Nigeria proved abortive. It is therefore suggested that further studies be carried

out on the impact of commercial banks’ recapitalization SMEs’ growth in Nigeria from 2013 till

current date, when such data are available.



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14


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Design and Development of Citizens Information System

Yutanto

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Hariadi Yutanto

STIE Perbanas Surabaya-Indonesia

[email protected]

Abstract

The problems that often arise in the neighborhood of Neighborhood Unit (RT) and Rukun Warga

(RW) are the distribution of information on citizen activities, administration, transparent

financial management, and management of citizen databases as an effort to improve services and

information facilities for residents. The purpose of this study is to support the government in

implementing e-Government-based government systems, by developing Good Local

Governance. The specific target of innovation to be achieved is the development of innovation in

the form of a web-based Citizen Information System (SiWarga) application at the RT / RW level.

The method used in this study uses the System Development Life Cycle (SDLC Waterfall)

method, starting from the first is analyzing the needs by conducting a survey and the feasibility

of developing the system, second is to make a detailed list according to system requirements

specifications, third is to design the system by creating workflow designs and programming

design, the fourth is the development of information systems with coding, the fifth is system

testing, the sixth is the implementation and maintenance of the system

Key words: database management, information systems, SiWarga, system integration

JEL code: A14, C31, M31.


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Introduction

In realizing Good Governance the government is currently implementing an e-

government system in a Griya Pesona Asri (GPA) is housing located in Rungkut sub-district and

Medokan Ayu Village, Rukun Warga (RW) 10 Surabaya. The total number of Neighborhood

Unit (RT) is 5 with a population of approximately 400 Head of Families. The housing that has

planned IT-based has made a security system in the residential environment by developing

CCTV security systems in each RT at each vulnerable point that can be monitored online by

residents. The current constraints are administrative management such as managing letters,

paying dues and database of citizens still online even though they have used Microsoft Office

office applications (Word & Excel). The obstacle that many people feel is that every month

residents have to deposit cash payments to the committee.

The implementation of a similar information system, namely the village management

development website, was previously implemented in the village of Bulaksari, which focused on

managing the community database, which can be accessed on the website

http://www.bulaksari7sby.com/, from the previous service program that has been implemented in

more detail with the name of the Citizen information system (SiWarga). The specific objective of

this research is to develop SiWarga in the neighborhood of Neighborhood Groups that can

improve services and information facilities for citizens, in addition residents can also control

citizens' financial statements transparently. It is different from the current conditions which still

use the manual process in carrying out the bookkeeping process and delivering information to

residents by going to the homes of residents one by one. Considering the government's program

in realizing Good Government in Indonesia, the importance of this research must be done to

improve service and comfort of citizens

Theory And Hypotheses

Mainframe Platform

The development of the RT / RW information system has been diverse and has been

implemented in several RT / RW in Indonesia. Broadly speaking, the development of existing

application systems can be divided into three applications. First, desktop-based applications are

applications that can run independently or independently without using a browser or internet

connection on an autonomous computer, with a particular operating system or platform (Akay et

al., 2016; Lin & Lin, 2018). Second, web-based applications are applications that can run on the

basis of web or browser technology. This application can be accessed anywhere as long as there

is an internet connection that supports without the need to install on each computer such as a

desktop application, simply by opening the browser and heading to where the application server

is installed (Bressolles, Durrieu, & Senecal, 2014; Tikno, 2017). Third, mobile based


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applications are applications that are at a glance almost the same as web based, but there are four

differences that make it different when viewed from features, user interaction, location

awareness and push notification. While viewed from the application connection there are two

types of connections, namely online connections, which means we are connected to the internet

or cyberspace, whether it's connected via social media accounts, e-mail and various other types

of accounts that we use or use via the internet. While offline is a term for the term we are not

connected to the internet, more precisely it is not connected. In connection with the application

to be developed, this application is a web based application with an online connection.

E-government

E-government is about delivering government information and organizing services online

through the internet or other digital tools (Chen & Perry, 2003). E-Government can be applied to

the legislature, judiciary, or public administration, to improve internal efficiency, deliver public

services, or democratic governance processes. E-Government in Indonesia began to be glimpsed

since 2001 namely since the emergence of Presidential Instruction No. 6 of 2001 dated April 24,

2001 concerning Telematics which states that government officials must use telematics

technology to support good governance and accelerate the process of democracy. But in the

course of this initiative the central government did not get the support and response from all

government stakeholders, which was marked by the use of information technology that was not

maximal, because the implementation of E-Government in Indonesia was only at the stage of

publication of sites by the government or only at the information delivery stage. The study was

conducted by Anita & Widodo, (2014) in the form of an RT / RW information system as a web-

based citizen communication media which was limited to information delivery. The study was

also conducted by (Lukman, 2015) regarding the management of RT / RW Net applications, the

result of which is the Network Operating Center (NOC) which is useful for connecting all

residents in the RT / RW environment with the various devices needed.


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Figure-1. State of Art

Database

A database is a collection or arrangement of complete operational data from an

organization that is organized or managed and stored in an integrated manner using certain

methods using a computer so that it is able to provide the optimal information needed by the user.

While the database system is a system of compiling and managing records using a computer to

store or record and maintain complete operational data of an organization or company so as to be

able to provide optimal information needed by the user for the decision making process.

According to Marlinda (2004) the understanding of the Database is: "A collection of files that

have a connection between one file and another so that it forms a building of data to inform an

agency company, within certain limits". The conclusion above is the database is a collection of

data that are interconnected with one another, stored in a computer and used software to

manipulate it

PHP

PHP is one of the scripting languages installed in HTML. Most syntax is similar to C,

Java and Perl, plus some specific PHP functions. The main purpose of this language is to enable

web designers to write dynamic web pages quickly. PHP was written and first introduced around

1994 by Rasmus Lerdorf through his website to find out who has accessed the online summary.

PHP is a script-shaped language that is placed on a server and processed on a PHP server is a

script-shaped language that is placed on the server and processed on the server. The results will

be sent to the client, where the user uses the browser. PHP is known as a scripting language,

which integrates with HTML tags, is executed on a server, and is used to create dynamic web

Sistem Informasi RT/RW sebagai

media komunikasi warga berbasis web.

Anita,2014.

Teknologi:

Website online

Fasilitas:

Pengumuman, Saran, Ide, Pengelolaan

Keuangan

Manajemen Aplikasi RT/RW Net

Kampung Haji. Lukman,2015.

Teknologi:

Network Operating Centre, desktop

Fasilitas: Jaringan Internet

setiap warga.

Sistem Manajemen Akuntansi Rukun Tetangga (SMART

Kampung)

Teknologi:

mobile / website based

online internet system

Fasilitas: Pengelolaan keuangan, bisa diakses melalui smartphone,

blog, terintegrasi


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pages such as Active Server Pages (ASP) or Java Server Pages (JSP). PHP is an open source

software. In particular, PHP is designed to form a dynamic web. That is, it can form a display

based on current requests. In principle, PHP has the same functions as scripts such as ASP

(Active Serever Page), Cold Fusion, and Perl.

Research Methodology

Objectives, Sample, and Procedure

The objective of this research is Griya Pesona Asri Housing (GPA), Neighborhood Unit 4,

Rukun Warga (RW) 10 Exit Medokan Ayu sub-district Rungkut, Surabaya- Indonesia. The type

of data in this study is primary data using field research, namely research carried out by

approaching the object of research. In this case data collection is done by:

a. Observation (Observation); In collecting data and information in order to complete the results

of this study, the author looks directly at the object of research.

b. Interview; Data collection by means of interviews, the author conducted question and

answer verbally with RT, RW, Kelurahan and related parties.

Research Framework

Research framework in developing Citizen Information Systems (SiWarga), using the

System Development Life Cycle (SDLC) method with the waterfall model (Kute & Thorat,

2014). The Waterfall Model is a sequential software development method. In addition this model

is the most widely used model by software developers.


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Figure 3.1 SDLC Modelling

The following is an explanation of the phase phase in the waterfall.

1. Planning

In planning is the initial process of a system development, where at this stage planning steps will

be carried out in developing SIWARGA applications such as extracting information about citizen

data, citizen services, RT bookkeeping systems and reports that can be accessed through an

online system

2. Need analysis (Requirement Analysis)

In the needs analysis data collection is carried out in a study, such as a survey in the form of

observing community activities and interviewing administrators and several residents. System

analysts will dig up as much information as possible from citizens so that a system can do the

desired task. At this stage the document will produce user requirements or can be said as data

that relates to what the user wants in making the system.

3. System design (System Design)

Process design will translate the needs of a software design that can be estimated before the

programming language (coding) is made. This process focuses on data structures, software


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architectures, interface representations, and procedural details. At this stage the software

requirment will be produced.

4. Development (Development)

Development or called coding is the translation of design systems in languages that can be

recognized by devices. Programmer who will translate the process requested by the user. At this

stage the programmer starts working on a system in accordance with the design system that has

been designed before

5. Implementation (Testing)

This stage can be said to be final in making a system. After analyzing, designing and coding, the

system that has been created will be used by the user, testing using the black box method ...

6. Maintenance (Maintenance)

At this stage is the process of maintaining the application, starting from the database to the

network, so that the application is user friendly.

Result

E-Government functions to be able to improve the quality of public services, using the

use of information and communication technology in the process of administering local

government so that governance can be formed that is clean, transparent and able to respond to

changing demands effectively, while the criteria of prospects of Information Systems Citizens

(SiWarga) in the neighborhood of neighbors in realizing e-government include the formation of

information networks and public service transactions that are not limited to time and location,

and at a cost that is affordable to the public. In addition, the establishment of a transparent and

efficient management, financial and work process system, thus facilitating transactions,

information and services between government institutions. The impact of the benefits of the

Citizens Information System (SiWarga) in the neighborhood of neighboring neighborhoods is,

among others, improving better service to the community, increasing relations between the

government, business people & the community, the loss of bureaucracy that has become a barrier

for the community to work more effectively and avoid extortion carried out by government

officials and minimize the possibility of corruption.

Implementation and Testing

At the stage of implementation and testing can be done after system development. After

testing the system weaknesses / shortcomings, implementation to users will be carried out in the

form of socialization. To residents who want to connect to the information system server via an

internet connection to the information system and each can download the guide that has been

made. Documentation of the results of the research is also carried out as a guide for making and

implementing the system.


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• The information used as detailed information about the RT includes the RT, RW, District and

sub-district numbers

• All citizen data can be monitored in detail and realtime by the Chairperson of the RT. All data

of residents can input administrative matters in the RT such as a letter of introduction (SP) to

move in, SP KK, SP KTP etc.

• Information about the finances of the RT / RW and information on payment of citizen

contributions

• Report to the Head of the RT no longer needs to interfere with the activities of the

Chairperson of the RT. With this feature, citizens can easily submit reports, criticisms or

suggestions.

• Announcement of info on activities such as community service, healthy walking, or RT

meetings can be easily informed to all residents.

• A citizen database report that can be monitored directly by residents. Thus all citizens can

know the condition of the database & Financial Financing transparently.

Discussion

This research is an applied research that is applied to the smallest sub-sector of society,

the Rukun Tetangga, with this application each Chairperson of the Neighborhood Association

can monitor the development of his area. indirectly the application of this application strongly

supports the efforts of the Indonesian government which is currently developing E-Government,

especially in the city of Surabaya, Indonesia where the governor and mayor are aggressively

socializing e-government and this application is very helpful for the government in its

implementation.


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Conclusions, limitations and suggestions

In addition, this study provides information about improving an area. This research was

conducted in Indonesia as the country with the largest population in Southeast Asia and the city

of Surabaya as the Capital of East Java, where most of the population is migrants, so it can be

used as a representative.


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Politik Dan Masalah Pembangunan, 12(01), 1769–1780.

Can Instagram Convince Information to Users?

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Romi Ilham

STIE Perbanas Surabaya, Indonesia

[email protected]

Abstract

With social networking everyone can give opinions through electronic word of mouth (eWOM),

this experiment explored how users adopt information on Instagram. The ultimate goal is to

investigate the influence of source credibility and information quality on information adoption

through an attitude toward information and information usefulness.

The proposed research model was tested using partial least square with 368 valid questionnaires

collected in Indonesia. According to the literature review and analysis techniques, we conclude

that source credibility and information quality have an influence on the attitudes and usability of

information in adopting information

Key words: source credibility, information quality, attitude information, information usefulness,

information adoption. JEL code: A14, C31, M31.


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1. Introduction

In recent years, our daily life is inseparable from social networking, and with social

networking can make everyone give opinion through electronic word-of-mouth (eWOM),

therefore make people assume whether the information available on social networking can be

trusted (Pan, Litvin, & Goldsmith, 2008). The Internet has provided several appropriate

platforms for eWOM such as blogs, discussion forums, review websites, shopping websites and

lastly social media websites (C. M. K. Cheung & Thadani, 2012). With the advent of internet

technology, WOM's traditional face-to-face behavior has changed to eWOM, and before making

the right buying decision, consumers can get information about products or services through

eWOM that are on social media (Daugherty & Hoffman, 2014). Instagram is one of the fastest

growing online social media services where users share information with their followers (Statista,

2018), but academic research related to media is limited (Sheldon & Bryant, 2016).

Sussman & Siegal, (2003) conducts research on the relationship of objectivity with

source credibility (SC) on attitudes toward advertising, attitudes toward brands and intention to

buy. As a result, they find source credibility can affect attitudes toward advertising, and can

affect purchase intentions. Several research has been evaluated the interaction between eWOM

source credibility and information adoption and, rarely research has focused on food products.

Therefore, this research was proposed to evaluate the consumer information adoption behavior as

presented by Sussman & Siegal, (2003) and Hussain, Ahmed, Jafar, Rabnawaz, & Jianzhou,

(2017) of food products in the Republic of China through eWOM source credibility and

perceived risk mediated by information usefulness and argument quality.

In this research, we investigate the impact of Instagram upon expertness, trustworthiness,

attractiveness and homophily as eWOM source credibility and quality of information on attitudes

toward information and information usefulness in information adoption. This research was

conducted in the Republic of Indonesia, Indonesia is a developing country that has a variety of

tribes with a population of 260 million and more than 130 million users of social media with 50

million active users of Instagram. Currently in Indonesia there are many Instagram accounts that

review food profiles, this is used by sellers as a marketing tool by buying followers and adding

comments from fake accounts. This is one of the reasons why researchers evaluate consumer

information adoption behavior based on information received.

2. Theory And Hypotheses

Source Credibility

Source credibility is the basis for credibility, which is generally used to describe the

positive influence of messages that are communicated to the recipient or transmitter (Ohanian,


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1990). Source credibility is usually investigated using two dimensions, expertise and trust

(Fanoberova & Kuczkowska, 2016; Carl I Hovland, Janis, & Kelley, 1953; Sussman & Siegal,

2003). Expertise can be defined as "the perceived ability of sources to make valid statements"

(McCracken, 1989). This explains the extent to which sources are able to provide valid

information (Carl Ivan Hovland, Janis, & Kelley, 1953). This level can be determined by

assessing aspects of the source, such as knowledge, experience, or skills (Erdogan, 2010). The

characteristics of expertness are, having confidence in a popular review site or forum can provide

useful information, having confidence in the number of reviews written representing knowledge

in evaluating experience, and having confidence in how long the reviewer has registered on the

review site, then rely on useful reviews according to readers. Trustworthiness is defined as "the

perceived willingness of a source to make a valid statement" (McCracken, 1989) and relates to

consumer confidence that the source of information conveys the message in an objective and

honest manner (Ohanian, 1990). Trustworthiness can be seen as perceived motivation from

information sources to communicate messages without bias (Bressolles, Durrieu, & Senecal,

2014), which is related to honesty and trustworthiness of sources (McGinnies & Ward, 1980).

Source trust depends on the motive of the perceived source to share certain information (Dou et

al., 2012). When consumers evaluate the trust of information sources, they build their opinions

about the causal conclusions they make about source motives for writing product reviews (See-

To & Ho, 2014). The characteristics of trustworthiness are, trust the same situation mentioned by

different reviewers to verify the actual level, trust in using first person pronouns (i.e. "I" or

"We") in the review represents the experience of the reviewer, trust that reviewers provide honest

reviews about their experiences, and feel confident that the length of content in the review shows

the level of effort of the reviewer.

However, some researchers include another dimension for their study of source

credibility. For example, (Ohanian, 1990), adds attractiveness as the third dimension of source

credibility, but it is examined as a physical attraction. Researchers argue that attraction creates

personal influence through communication between the source and recipient (Kiecker & Cowles,

2002). Attractiveness is another dimension of source credibility and is defined as the extent to

which the recipient of information considers an interesting source (Kiecker & Cowles, 2002; Z.

Teng, Nie, Guo, & Liu, 2017). Attractiveness considers social values perceived by sources,

including physical appearance, personality, social status, or similarity with the recipient (Valarie

A. Zeithaml, 2002). There are studies that examine the physical attractiveness of sources, such as

in the study of celebrity support (Ohanian, 1990; Roger-Monzó, Martí-Sánchez, & Guijarro-

García, 2015; Sussman & Siegal, 2003), but not many works discuss the attractiveness in terms

of similarity with recipients. McGuire, (1985) distinguishes attractiveness's dimensions as

perceived familiarity, attractiveness, and source similarity to the recipient of the message. In a

similar vein, (Kiecker & Cowles, 2002) examined the influence of interpersonal source

credibility by examining attraction as "perceived similarities between buyers and

recommendations". The authors state that Attractiveness arises when consumers interact when


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shopping online with friends, family, or fellow consumers who are similar, familiar, and

preferred (Kiecker & Cowles, 2002). The characteristics of Attractiveness are, authoritativeness,

availability, believability, honesty, and bias.

Besides that, Hussain et al., (2017) also adds homophily as the fourth dimension of

source credibility, seen as an important variable that affects personal correspondence.

Homophily is seen as an important variable that has an impact on personal correspondence.

Homophily reduces vulnerability, improves true sentiment, and strengthens the well-being of

interpersonal relationships. This refers to reviews written by people their age, gender groups, and

have similar interests (Hansen & Lee, 2013; Mcpherson, Smith-lovin, & Cook, 2001). The

characteristics of Homophily are, rely on reviews written by people in the same age group, rely

on reviews written by people of the same sex, rely on reviews written by people who have

similar interests, and rely on reviews written by people who buy food products in the same way.

In source credibility, expertness and attractiveness are found to play an important role in

information and social influence (Kiecker & Cowles, 2002; Maddux & Rogers, 1980). Previous

research by Erkan & Evans, (2016), Gunawan & Huarng,(2015) and Wixom & Todd, (2005)

showed a positive relationship between credibility and attitude. Therefore, researchers trying to

test source credibility have a positive effect on attitude towards information. Source Credibility

refers to the credibility that someone feels from the source of information, regardless of what the

information contains. Although the credibility of the source is not related to the information itself,

it can affect customer perceptions of the usefulness of information (Di & Luwen, 2012). The

customer's perception of the usefulness of Information will decrease, if the source is less credible.

• Hypotheses 1. Source credibility will be significantly related to attitude toward information.

• Hypotheses 2. Source credibility will be significantly related to information usefulness.

Information Quality

Information today is very easy to reach. The passage of time must be followed by the

continued emergence of information in the world. Information flow is increasingly unstoppable

with the internet. Whenever and wherever everyone can get and disseminate information.

Various possibilities arise from information spread throughout the community. It can occur

because of marketing, sharing, existence and other reasons. Of the many information available,

one must be able to determine which information must be taken or left behind. This must be done

so as not to absorb information that is not true. Therefore, it is necessary to have a person's

perception of the quality of information on the internet, this is an important element to assess the

information. In his book entitled "Management Information Systems" McLeod & Schell, (2008)

stated that there are 4 dimensions needed to add value to information, namely Relevance,

Accuracy, Actual and Completeness. Many studies related to the quality of information online.

This study adopted the dimensions used by (C. M. K. Cheung, Lee, & Rabjohn, 2008) which


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includes dimensions of relevance, accuracy, timeliness and comprehensiveness. In the study,

timeliness was excluded because it was found to be insignificant by (C. M. K. Cheung et al.,

2008). Timeliness is also often overlooked in online review research (Ives, Olson, & Baroudi,

1983), because websites must be updated regularly to provide valuable information. If this

condition is not met, users can view the website less useful (Liu & Suh, 2017). Similarly, users

pay more attention to websites that contain the latest online reviews (Zhao, Wang, Guo, & Law,

2015). When online reviews are considered to contain valid arguments, the recipient will develop

a positive attitude towards information. On the other hand, if an online review is considered to

have an invalid argument, the recipient will develop a negative attitude towards information (M.

Y. Cheung, Luo, Sia, & Chen, 2009). As a result, online reviews that provide valid and strong

arguments can influence attitudes towards information and sources. The way recipients feel the

quality of information can influence their purchasing decisions. That information meets the

needs and requirements of users, he is more likely to follow recommendations during the

decision making process (Olshavsky, 1985).

Relevance was found to have a significant influence on the usefulness of information and

information adoption (C. M. K. Cheung et al., 2008), which means that the probability of

consumers being convinced by online review is higher when information relevance is high (S.

Teng, Khong, & Goh, 2014). Then accurate about "truth information output" (Bailey & Pearson,

1983). This also refers to the extent to which users perceive information as true because they

may be skeptical about certain claims, which can be seen as true or false (C. M. K. Cheung et al.,

2008). This means that if the review presents information that is known to be the wrong user, he

can refuse the review. If the review contains comments that match what the user believes are

correct, he will be more willing to consider the remaining accurate comments. Markopoulos &

Kephart, (2002) states that reviews including information that is more accurate, have greater

value for consumers.

Therefore, the more accurate the information is, the more useful information is felt by

consumers. Comprehensiveness refers to the completeness of the information (C. M. K. Cheung

& Thadani, 2010), which implies that the information is understandable, informative, has

sufficient breadth and depth. (C. M. K. Cheung et al., 2008; S. Teng et al., 2014). C. M. K.

Cheung et al., (2008) found that the completeness of online reviews played an important role in

the adoption of information because the more comprehensive the review, the more people would

adopt it. Information Usefulness can increase with clear information on information. In

accordance with the statement of Di & Luwen, (2012), in the internet world eWOM can

influence purchasing decisions and consumer behavior. After information quality meets the

needs and requirements of recipients of information, information will be considered more useful.

High information quality will be more persuasive than low information quality (Di & Luwen,

2012).


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• Hypotheses 3. Information quality will be significantly related to attitude toward information.

• Hypotheses 4. Information quality will be significantly related to information usefulness.

Attitude toward information sources and information adoption

Information can have different effects on individuals and produce various responses as

recipients vary in perception and experience (Chaiken & Eagly, 1976). To understand the

influence of information on individuals, the information adoption process is developed (C. M. K.

Cheung et al., 2008). Attitudes toward behavior serve as determinants of behavioral intention

(Ajzen & Fishbein, 2005). Building attitudes in the context of technology acceptance are

attitudes towards using technology (Wixom & Todd, 2005). If someone is satisfied with the

quality of information, he or she holds behavioral beliefs that use this information well. This

implies that information is useful and in turn forms a positive attitude towards the use of

information (Wixom & Todd, 2005). The Attitude Using Information Source characteristics are

acceptance of interesting information, acceptance of unattractive information (inverted items),

believe online testimonials, and do not believe online testimonials.

Attitude is widely recognized as an important concept for marketing research because

attitudes serve as predictors of consumer behavior towards products or services (Nisar &

Prabhakar, 2017). The concept of attitude takes its origin from the field of social psychology.

This is defined as the tendency of an individual to evaluate a particular entity with some degree

of goodness or disadvantage (Wan et al., 2015). The concept of attitude has special importance

for marketing research because marketers want to change consumer behavior, and they try to do

it by influencing attitudes(Bilgihan, 2016). Analysis of individual attitudes gives practitioners the

opportunity to explain and estimate their behaviour (Ajzen & Fishbein, 2005). Therefore, the

investigation of the relationship between attitudes and adoption of information to what extent

people receive the content of messages and believe that meaningful information can help to

develop recommendations for marketers, how to influence consumer behavior online and how to

persuade consumers. Previous studies of online shopping show that attitudes have a significant

influence on behavioral intentions. George, (2004) identifies that attitudes toward online

purchasing influence behavior in making actual purchases. Similarly, Liao, Chang, Wu, &

Katrichis, (2011) in their study of consumer behavior intentions to use internet shopping shows

that attitudes toward Internet shopping have a positive influence on intention. Therefore, an

attitude construct has been added to this study to investigate its effect on behavioral intention.

Through the Theory of Reasoned Action considers attitudes toward behavior as determinants of

behavioral intention (Ajzen & Fishbein, 2005).

• Hypotheses 5. Attitude toward information sources will be significantly related to information

adoption.


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Information usefulness and information adoption

Information Usefulness is defined as the extent to which readers understand valuable

information that can help them make better purchasing decisions (C. M. K. Cheung et al., 2008).

The usefulness of information is an important determinant of information adoption. According to

Zheng, Youn, & Kincaid, (2009) 55% of online media readers are looking for comments from

the authors to be used as benefits and bring the information into consideration when making

purchasing decisions. "The usefulness of information is measured through constructs as

developed by Bailey & Pearson, (1983). The usefulness of information refers to individual

perceptions of opinions that can improve performance using new technology. Valuable,

informative and useful are the three keys that make information useful as discussed by

McKinney, Yoon, & Zahedi, (2002) in their web satisfaction model. Likewise, people feel

information to reduce risk, so, the usefulness of information is an important factor to be useful

for any information because reviewers seek information that can help them and reduce the risks

and results of this hypothesis in accordance with the study of C. M. K. Cheung et al., (2008). The

characteristics of information usefulness are value of information (valuable), information

delivery (informative) and benefits of information (helpful).

Information usefulness is the user's perception of the reliability of information, comments

or reviews on the internet that are valuable or not because the usefulness of perception leads to

the customer's intention to adopt information. Adoption of information is an information

procedure that is useful for customers to engage with comments and opinions that are suggested

for decision making (C. M. K. Cheung et al., 2008; Sussman & Siegal, 2003)

• Hypotheses 5. Information Usefulness will be significantly related to information adoption.

3. Research Methodology

Sample and procedure

To test the hypothesis, a survey was conducted through the distribution of questionnaires

with a purposive sampling method in various regions of the Republic of Indonesia to 420

respondents. With the inclusion criteria at least 1 year active user Instagram, and exclusion

criteria for active users of the age above 17 years.

Determination of this condition aims that the selected respondents actively use the

Instagram application and at least have enough age to use the Instagram application wisely.

Surveys are distributed conventionally and electronically, by attaching a letter informing the


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respondent that the data will be treated confidentially and only used for academic research

purposes. Our final sample consisted of 368 respondents dominated by female (62%); with their

average age is 17-30 years and the level of education are bachelor’s degree.

Measure

All the items were scored on a 5‐point Likert response scale ranging from 1 (strongly

disagree) to 5 (strongly agree) unless otherwise noted.

Data Analyses

The analysis technique uses Partial Least Square (PLS) as a data analysis tool with the

help of SMART PLS application, because Smart PLS is based on covariance, then the number of

respondents above 75 is enough to produce good analysis (Joseph F. Hair, Ringle, & Sarstedt,

2011). Following are the steps in analyzing with PLS: 1. preparing a path diagram, 2.

determining structural equations, and 3. Confidentiality Criteria (convergent validity,

discriminant validity, composite reliability, R-Squared).

The variables in this study consisted of demographic variables that were used to

determine the characteristics of respondents and included gender, age, education, occupation.

Exogenous latent variables including source credibility (expert, trustworthy, attractiveness, and

homophily) are used to determine the value of source credibility and information quality. The

endogenous latent variable consists of attitude towards information, information usefulness and

information adoption. And the last is the manifest variable used to explain and measure latent

variables.


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Figure 1. Model Framework

4. Result

Descriptive statistics

Based on table 1, the majority of Instagram users are 229 respondents (62%), this is in

line with research from Acar, (2008); Rakow, (1992); Sheldon, (2008); Szell & Thurner, (2013),

which states that women tend to have many friends online or social networks and spend more

time involved in telephone conversations. The average age of 17-30 year Instagram users is 159

respondents (43%) followed by age 31-40 years as many as 143 respondents (39%), this is in line

with a survey conducted by the Indonesian Internet Service Providers Association - APJII,

(2017), which results that the penetration of internet users in Indonesia is dominated by ages 19-

34 years old. Educational backgrounds using Instagram at the bachelor’s degree level were 192

respondents (52%) with occupation as students 143 respondents (39%), where 210 respondents

(57%) have used Instagram for approximately 1-3 years and have a tendency to read each post as

many as 297 respondents (81%).

Table 1. Respondent’s demographic for information adoption in Instagram

Frequency (n) Percentage

Gender Male 139 38%


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Female 229 62%

Age 17-30 159 43%

31-40 143 39%

41-50 53 14%

51+ 13 4%

Education High School or lower 99 27%

Diploma 33 9%

Bachelor degree 192 52%

Post graduate degree 44 12%

Occupation Student 143 39%

Civil Servant 47 13%

Labor 126 34%

Professional 52 14%

How long to used instagram 1-3 years 210 57%

3-6 years 91 25%

More than six years 67 18%

Read comments on posts Yes 297 81%

No 71 19%

Technique Analysis

Developed conceptual model was drawn in SmartPLS software or simulation work in

assessing the effect of source credibility (expertness, trustworthy, attractiveness, homophily) and

information quality on information adoption through attitude toward information and information

usefulness. Partial least square simulation of the model is carried out by calculating and

assessing various parameters which include item loading, reliability, and validity tests.

Table 2. Validity and reliability analysis

Construct & item description Cross

Loading AVE

Cronbach's

alpha Result

Source Credibility 0.614 0.953 valid & reliabel

Expertness 0.884 0.938 valid & reliabel

EX1. I believe that popular accounts can provide me with useful

information 0.969

EX2. I believe the number of followers account represents

knowledge in evaluating the experience 0.897

EX3. I believe the longer a reviewer account has registered on a

review site 0.917

EX4. I rely on the comment which other readers believe useful 0.890

Trustworthiness 0.735 0.878 valid & reliabel


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TR1. I believe the same situation mentioned by different reviewers

verifies the actual level 0.878

TR2.I believe the comments in the review represent the experience

of the reviewer 0.884

TR3. I believe reviewers will give honest reviews about their

experiences 0.916

TR4. I believe the length of the comments in the review shows the

level of effort of reviewers 0.740

Attractiveness 0.703 0.789 valid & reliabel

AT1. I believe emotions of reviewers affect the readers' perceptions

of information attractiveness 0.834

AT2. I believe the language used by reviewers influences readers'

perceptions of information interactions 0.845

AT3. I believe reviews written by site editors are more convincing

when accompanied by pictures and words 0.837

Homophily 0.570 0.749 valid & reliabel

HO1. I rely on the reviews written by people who are in my age

group 0.768

HO2. I rely on the reviews written by people who have my same

gender 0.760

HO3. I rely on the reviews written by people who have the same

interests as I have 0.731

HO4.I rely on reviews written by people who have equal education 0.761

Information Usefulness 0.662 0.746 valid & reliabel

IU1. I only follow an Instagram account that has useful information

for me 0.863

IU2. The information presented on Instagram is easy to understand 0.841

IU3. I just follow a useful Instagram account useful for me 0.731

Information Adoption 0.771 0.704 valid & reliabel

IA1. You always follow the advice of positive comments 0.900

IA2. You agree with the comments suggested by the reviewer

account 0.855

Information Quality 0.637 0.715 valid & reliabel

IQ1. Instagram provides complete information 0.694

IQ2. Instagram presents relevant information 0.857

IQ3. Instagram provides information that can be accurate and

reliable 0.833

Attitude Toward Information 0.559 0.779 valid & reliabel

ATI1. Instagram presents information that has the attraction force 0.809

ATI2. Instagram provides information content that has the force

appealing 0.619

ATI3. I don't feel bothered by the information on the Instagram

news feed 0.823

ATI4. Instagram is a dynamic social media application 0.816

ATI5. Instagram can be used with one hand 0.646

After determining the variables, the model process is carried out as shown in Figure 2

using smart pls. From the results of table 2 shows all cross loading values greater than 0.6 thus


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all indicators are declared valid for measure each construct (David Garson, 2016). Convergent

validity internal consistency average variance extracted (AVE) greater than 0.50 (Chin, 1998;

Klarner, Sarstedt, Hoeck, & Ringle, 2013). In this research each construct is declared valid

because the average variance value of the source credibility extract is 0.61, expertness 0.88,

trustworthiness 0.73, attractiveness 0.70, homophily 0.50, information usefulness 0.66,

information adoption 0.77, information quality 0.63, and attitude towards information 0.55.

(David Garson, 2016; Hair, Sarstedt, Hopkins, & Kuppelwieser, 2014) explained that the

Cronbach's alpha value considered adequate for confirmatory purposes must be more than 0.7 to

check the reliability of factor analysis. The Cronbach’s alpha of source credibility 0.95,

expertness 0.93, trustworthiness 0.87, attractiveness 0.78, homophily 0.74, information

usefulness 0.74, information adoption 0.70, information quality 0.71, and attitude towards

information 0.77.

After unidimensionally testing for each latent variable by using Confirmatory Factor

Analysis, the next stage is to do Structural Equation Modeling (SEM) analysis with a complete

model. The next stage uses a variance-based SEM method called SEM-PLS.This method is

explorative assuming the assumptions in the SEM-PLS method are nonparametric, which does

not require many assumptions. (Monecke, A. and Leisch, 2012). The hypothesis raised in this

study is:

The measurement model of indicator significance in the construct can be measured

through the factor of loading, and comparing the values of t with t-table using the following

hypothesis:

H0: λi = 0 (loading factor is not significant in measuring latent variables)

H1: λi ≠ 0 (loading factor is significant in measuring latent variables)

The results of the SEM variance test or SEM-PLS are presented in Figure 3 as follows:


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Figure 3. PLS Outer Model

After a Confirmatory Factor Analysis and an indicator can measure well the latent

variables, then the inner model analysis is performed. Inner model analysis is done to determine

the relationship between latent variables and to conclude the research hypothesis is accepted or

rejected. The test criteria for hypothesis testing are, if the t-statistics value> 1.96 with an alpha

assumption (5% error tolerance) then it can be concluded that the relationship between the two

latent variables is significant (accepted hypothesis) and vice versa. The results of the inner model

analysis for the latent variables are presented in the table as follows:

Table 3. PLS inner model

Causal paths Original

Sample (O)

Sample

Mean (M)

T Statistics

(|O/STDEV|)

P

Values Result

Attitude Toward -> Information Adaption 0.479 0.479 7.979 0.000 Significant

Information Quality -> Attitude Toward 0.416 0.405 5.134 0.000 Significant

Information Quality -> Informational Usefulness 0.309 0.306 3.574 0.000 Significant

Informational Usefulness -> Information Adaption 0.279 0.274 4.411 0.000 Significant

Source Credibility -> Attitude Toward 0.472 0.478 5.632 0.000 Significant

Source Credibility -> Informational Usefulness 0.421 0.421 4.940 0.000 Significant

Based on table 3, source credibility have a positive effects on attitude towards

information and information usefulness with values of 5.63 and 4.94, information quality have a

positive effects on the attitude towards information and information usefulness with values of


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5.13 and 3.57, furthermore information adoption is affected by attitude towards information and

information usefulness with values 7.97 and 4.41 accordingly.

5. Discussion

This study aims to find factors in society in adopting information on social media,

especially Instagram so that the information can be trusted by Indonesian people, by analyze

eWOM source credibility to information usefulness, information quality and attitude towards

information that produces information adoption for Instagram users.

Source credibility can describe the positive influence of the message communicated to

the recipient (Ohanian, 1990; Thoumrungroje, 2014). The dimensions of eWOM's credibility,

such as expertise, trust, objectivity and homophily positively affect attitudes toward information

and information usefulness. It has been observed from previous research by Erkan & Evans,

(2016), Gunawan & Huarng,(2015) and Wixom & Todd, (2005) which show a positive

relationship between sources of credibility and attitudes towards information. The perception of

the usefulness information can be influenced by sources of credibility even though it is not

related to that information (Di & Luwen, 2012). The quality information consisting of relevance,

accuracy and completeness also has a positive relationship to attitude toward information and

information usefulness. The attitude of the recipient to the quality of information can influence

their attitude. When that information meets the needs and requirements that are useful to the user,

he is more likely to follow the recommendations during the decision making process (Di &

Luwen, 2012; Lee & Lee, 2009; Olshavsky, 1985). The attitude towards information has a

positive relationship to information adoption, in a previous study on ecommerce showed that

attitudes have a significant influence on information adoption (Ajzen & Fishbein, 2005; George,

2004; Liao et al., 2011). Information usefulness has a positive relationship to information

adoption, user perception of the usefulness of information is an important determinant of the

user's intention for information adoption (C. M. K. Cheung et al., 2008; Sussman & Siegal, 2003;

Zheng et al., 2009).

6. Conclusions, limitations and suggestions

Furthermore, this study provides recommendations for practitioners regarding increasing

sources of perceived credibility, quality of information and information usefulness of each

source of information to increase the number of users who are willing to use the source during

information retrieval. This research was conducted in Indonesia as a country with the most

population in Asia and a customary group with the surrounding countries, Indonesia can be a

reflection and reference in information adoption on Instagram.


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Users are often hesitant in receiving information because there is a lot of trapping

information, such as the phrase "terms and conditions apply" which are written small in the

corner of the picture, therefore as much as possible to avoid this. Increase the number of

Instagram followers, always update the latest information and don't write too many promises but

can't keep up.

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Complexity Concepts in Market Dynamics; the Evolution of Market Alliances

Koplyay, Motaghi, and Hurta

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51



Tamas Michel Koplyay,Ph.D.

[email protected]

Hamed Motaghi, Ph.D. (Corresponding Author)

[email protected]

Hilda Hurta, Ph.D.

[email protected]

Abstract

Market alliances accompany firms during the evolution of the lifecycle and undergo serious

structural transformations from early market ecosystems to late stage value chains. This happens

in an orderly fashion that facilitates the adaptation of the firms to market conditions and

witnesses a migration of complexity from the alliances into the firms. In a sense complexity

migrates from the market into the firm and its immediate neighborhood, such as the value chain.

At some point the firm strategic independence is subsumed by its parent coalition. Along the way

many interesting concepts of complexity arise such as symmetry, random signal-based

adaptation, loose and tight environmental fit, risk mitigation and ability to fend off shock

loading.

This article will examine the principal complexity issues related to this process of market

evolution and significant reasons behind the adaptation logic that correlates with this process.

Key words: Complexity, Market Dynamics, Market Alliances, Structural Transformation






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Introduction

The market appears to function at two distinct levels, the deep and the surface structures,

where the deep structure is defined by the succeeding customer profiles, creates a certain

dynamic of its own (Dobni, C. B., & Luffman, G. (2003)).

Above the deep structure unfolds the surface structure that has a series of crisis points for

the firms, where these are swallowed up progressively at a higher rate into grey holes of deeper

colors and more irreversible nature until the whole market disappears in to black hole which

marks the end of the market.

At the beginning is the white hole that spews firms into the attractive market. This

attractiveness is tied to the high promise of market size, growth, customer price inelasticity and

relative absence of competitors, sort of a blue ocean, although entry rate due to low market

barriers is significant and finally fills the market positions available (Greve 1988).

The lifecycle, the surface structure, follows the deep structure and creates both market

competitive weather and the combines with the deep structure to create the crisis shakeout points

in the market (Klepper, S., & Graddy, E. (1990)).

The succession of crisis points in captured by exhibit 1.

There are two climate zones associated with the lifecycle, an early phase effectiveness

zone where firms try to find their position commensurate with their abilities and the pressures

exercised by competing firms and later the efficiency zone where a position is already acquired



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and firm gets ready to deliver against the inexorable advent of a cost leadership strategy now

given by the market (Cui, Gao, Wang,& Xue (2015)).

Effectiveness zone is associated with marketing positioning whereas efficiency zone is

shaping the productivity capabilities of the firm. A productivity emphasis that is the hallmark of

mature markets.

In effectiveness climate zone the premium is on firm recognition of market possibilities,

nobleness of moves and light baggage to carry around.

This is also the market phase where young firms develop and integrate their functions

starting with product development, marketing and rudimentary supply chain and distribution

channel activities. Later finance, human resources and eventually MIS/IT join into the integrative

process

Therefore, the effectiveness zone is a period of functional development and coordination.

It is a period of integrating the firm’s capabilities into a cohesive whole.

All of this is forged within by the entrepreneurial structural shape of the firm headed by

the critical controller, the outward looking entrepreneur (Simsek, Lubatkin, & Floyd (2003)).

In late stages of the market where the efficiency climate prevails, we see heavier firm

structures, more deliberate moves, if any, and a singular focus on execution of strategy as

opposed to selection thereof.

Furthermore, integration yields to differentiation that creates higher efficiencies for the

firm but also contributes to silo effects among the function s that needs to be countered by better

coordination devices that create more internal structural complexity for the firm (Koplyay, T., Li,

L., & Rochefort, P. (2010)

However, curiously as firm structural development takes place symmetry is preserved

and further enhanced, thereby mitigating some of the effects of internal complexity increases and

pushing the firm towards higher levels of order.

The net effect is a decrease in alliance structure complexity and a corresponding increase

in net structural complexity of firms at the maturity phase of markets (Koplyay, T., & Mitchell,

B. (2014).

The alliance structures evolve from highly complex ecosystems types to simple linear

value chain forms at the end (Pitelis, C. (2012)).



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Ecosystems are ideal for survival, absorption of shocks and replacement of damaged

nodes and offer a good measure of resiliency, whereas value chains respond ideally to demands

of efficiency and productivity signaled by the cost leadership strategy of late markets.

The drawback of value chains is the fact that every component becomes critical, the

structure needs to be actively managed and there’s no recovery from major shocks resiliency is

gone and is replaced by robustness.

It no longer can avid shocks by displacement but rather faces the turbulence with robust

and redundant defenses.

Ecosystems on the other hand, lacking central control, are unpredictable, inefficient and

fragile (Costanza, R., Low, B., Ostrom, E., & Wilson, J. (2000)).

They adapt to shocks by repositioning in the market thereby causing an expenditure of

reserve resources of its constituent members. The future is now.

Exhibit 2 captures the deep structure of the market based on the successive customer

bases.

BowlingAlley

Tornado Tombstone

Shakeout

Mainstreet

Technology Enthusiasts

Visionaries Pragmatists Conservatives Skeptics

Market Dynamics and Customer Base

Chasm

Early market

Of significant interest is a second evolutionary trait of the market that affects firms.

The firms start out in a pure competition environment of the effectiveness zone.

All their moves are dependent on their own awareness of market conditions, but as the

market progresses more and more coordination seeps in to replace the independent early

behavior.

In act a serious coordinative shock is delivered at the platform stage, where firms

coalesce into groups to set standards that is required as a quality assurance to the deep customer



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base, now at the pragmatist stage, and also acts as a defensive measure against further intrusive

innovation by requiring compatibility with the platform standards for all competing firms.

By the time the market reaches the value chain stage, almost all actions of firms are

coordinative.

So, there is a progression form a standalone type competitive stance to one of a collective

effort.

In fact, the value chain comes about just as cost leadership imposes its will on the market

and the linear shape of the chain facilitates the delivery of productivity. The market evolves from

singular competition to collective one as illustrated by the single entrepreneurial firm and later

by the coordinatively constrained value chain.

Exhibit 3 traces the evolution of the market from effectiveness to efficiency climate

zones.

Supply and distribution channels are the most efficient when the structure is linear and

minimal transition times occur between component firms upstream and downstream (Kim, Y.,

Choi, T. Y., Yan, T., & Dooley, K. (2011)).

This quasi linearization happens throughout eh market cycle.

Firms seek out outsourcing, insourcing, offshoring and in shoring to simplify their

resources and product flows upstream and downstream (Kotabe, M., Mol, M. J., & Murray, J. Y.

(2009)).



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UPS has now transformed into a major supplier of insourcing where it enters client

premises and performs all the coordinative tasks of resources acquis ion and product distribution

for medium and small firms that could not afford theses streamlining functions on their own.

UPS in fact provides the economies of scale to these firms (Leamer, E. E. (2007)).

Walmart of course proceeds on its own to develop the most highly integrated global

resources management systems conceivable (Jensen, M. C. (1993)).

Although the chain has a huge disadvantage of having all of its component critical in the

sense that any suppression of a chain component results in failure of the system. However, the

shock loads on the chain are infrequent and defenses can be built to guarantee a reasonable

survival chance under perceived loadings.

This however is not foolproof as Toyota discovered when the transportation links to its

Japan factories were destroyed by a major earthquake.

We can trace the simultaneous development of firm alliances in the market from

ecosystems to value chains and note the remarkable transformation of nonlinear, complex and

resilient structural forms of ecosystems evolve into rigid, efficient, vulnerable and linear forms

of the value chain.

This evolutionary process seems to be imposed by the deep structure, whereas the firm

evolution is dictated by the surface structure (Koplyay, T., Lloyd, D. M., Sanchez, L., & Paquin,

J. P. (2012)).

Exhibit 4 summarizes the structural shapes that accompany firms in their voyage along

the lifecycle



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A related phenomenon, defined by both the deep and surface structures, is the

progression of strategies along the lifecycle (McAdam, M., & McAdam, R. (2008)).

From an open and wide funnel representing the many market position choices of early

markets to the narrowing down of choices to a single one in market maturity. the strategy

funnel is created by an interplay between the deep and surface structures Koplyay, T. M., Lloyd,

D., Jazouli, A., & Farkas, M. F. (2016)).

From the many options available to the firm in early markets to executing at the

acquired final market position in maturity the firms learn how to change their respective

behaviors, structures and critical functions depending on where they are on the curve.

Exhibit 5 shows the continuing whittling down of strategies available as the market

matures.

These are excellent reasons for this curtailed choices as the market evolves.

First of all, there appears to be an anticipatory foresight among all firms to build market

share at any stage of the market.

In fact, the early rush to share and market strength even trumps the eventual need to

produce a profit, the firms know that share price corelates with top line growth and hence

everything is done to buttress revenues, and yet this is not essential to immediate survival but

becomes a factor in late markets. This type of thinking is amply evident in Shopify, where top

line growth is the corporate priority.

So the firms instinctively reach for market share and often dominant market share as

captured by market strength which allows building of brands, a very useful and relatively

inexpensive tool to hold market position ,as it cost a lot more to attack a brand than to defend it.



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The accumulated market share eventually translates into economies of scale and allows

for the implementation of the final strategy, cost leadership (Hitt, M. A., Keats, B. W., &

DeMarie, S. M. (1998)).

The idea to retain here is that the evolution of the firms and their respective adaptive

behaviors anticipate the eventual end game of the market (Lo, A. W. (2004)).

There appears to be a market teleology acting on singular and collective behaviors of

firms and their alliances.

It is almost as if the market had a life of its own and through feedback mechanisms it

guides constituent firms and their alliances to a final resting place, which is known by the time

the market comes into existence.

We can comment on a phase of the market, the M&A phase, that helps fulfil final market

destiny. As the market matures it becomes n more obvious that market share will rule eventually.

Firms try organic growth, but as the market gets depleted of new customers it becomes more

difficult to gain share (Hurta, H., Jazouli, A., Koplyay, T., & Motaghi, H. (2017).

For two reasons, one is the customer acquisition costs go up and retention costs come

down. It’s cheaper to hold on to a customer than to recruit a new one. Second is that share

acquisition becomes zero sum game, the market is not growing anymore and a firms share gain

becomes another firm’s loss. Hence if you can’t beat them you buy them and series of M&A is

unleashed to consolidate the market and often produce an oligopoly, or in the presence of very

strong economies of scale a monopoly, something that government regulators try to prevent,

although often for the wrong reasons.

A further characteristic of market evolution that is worth commenting is the type of

stability available to firms depending on location. In early markets bot the firm and its ecosystem

can relocate under market forces, say competitive pressures or collapse of a customer base, or

even intrusion of an adjacent market. This nomadic ability defines a seeking out of zone stability,

the ability to fine a new competitive position within the developing market.

Later when the first crisis point the chasm is crossed and the blowing alley strategy

developed firm and its alliance become more circumspect and stability can be found only in

limited spaces, the standards platforms to which firms can converge.

There may be several of these standards first but eventually they will decay to one

dominant or maybe two platforms, and then the platforms themselves disintegrate into prototype



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value chains, called clusters that are essentially linear at the core and ecosystem format at the

supplier and distribution channel ends.

The application software providers would fall into the category of suppliers at this stage.

An example being the Sony Beta or a Toshiba VHS platforms, but in the long run this morphed

into one market standard, Toshiba VHS in this case.

By the time the final market phase of maturity arrives, the stability is of a point form, no

chance to move the asset base constraining, the risk avoiding culture and accumulated knowhow

is too heavy to relocate. Just ask GE about its recent experience with software development. The

stability zones in a literal sense define the scope of maneuvering possible for a firm in the

market, and scope decreases until only one option is left in maturity

Exhibit 6 shows the zones of different stability against the market lifecycle.

The small picture; local co-evolution based on complexity

There appears to be a common focus-based evolution of firms and their alliances driving

both towards an unavoidable state of cost leadership where choice of strategy is left behind, and

the execution of the market given strategy prevails. (Koplyay, T., Sanchez, L., & Levy-Mangin,

J. P. (2012)).

Whether the driving force behind this co-evolution is the market or the adaptive behavior

of firms, or both, is immaterial to the final outcome, although of real importance to our

understanding of both market and constituent entities transformations.



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The fact remains firms and their alliances change in an orderly and predictable fashion,

drawn like moths to the flame of final market attractor, markets share based productivity

anchored competition.

If there is a link between the firm’s behavior and the shape of their alliances it should

surface from the study of emergence in the market due to complexity (Koplyay, T. M., Lloyd,

D., Jazouli, A., & Farkas, M. F. (2016)). We shall examine two instances in the market there this

type of evolution does take place. One has to do with the platform and the other with the

emergence of the value chain. For meaningful mergence to occur complexity theory tells us that

we should find phase transition, complexity on the edge of chaos leading to self-organization at

the firm level that eventually produces strong emergence of an alliance that will in turn influence

the lower level conduct of the firms. And in fact, on at least two occasions this happens in

markets.

The first one is the standards platform. After crossing the chasm, the first grey hole in

market where firms are lost, the surviving firms concentrate on building a niche market around a

bowling alley strategy, whereby the firm choses a central customer and starts seeing a complete

product to this customer in the pragmatic segment, and eventually to all other firms in the

customer’s ecosystem.

This vertical marketing where you proceed from the first bowling pin to the next, and in

cautious steps build a whole bowling alley of connected customers, and this contuse until the

market growth takes off where you abandon the vertical marketing for a horizontal one. No more

local customization but ride the tiger through high growth period. So we find two phase

transitions at the same time; One of change for vertical to horizontal marketing And one of study

market growth to high growth. So, the market behavior changes drastically inviting and

evolutionary move from the firm but for such behavior or appear we must have nonlinearity on

the edge of chaos.

Indeed, we just left the highly stable and ordered state of the bowling alley and down-

market looms the chaos, the shakeout. We are on the edge of chaos

The market in of increasing structural complexity, measured by the nonlinearity of

relationships among the firms and their alliances (Koplyay, T., & Mitchell, B. (2014)) with

strong nonlinearities bounding this complexity.

On one side is order and on the other chaos, ripe for some meaningful evolutionary

transition



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And as the firms organize, they give rise to the emergent standards platforms that offers a

way to survive the shakeout by embarking in the life boat of the standards platform, that will

carry them to the other shore of the shakeout

There is emergence and this emergence signals to noncommitted firms the possibility of

survival through various feedback mechanisms such as superior customer commitments to the

platform and equally sustainable growth rates. Hence the emergence is strong

Similarly at the end of the market right after firms transit the M&A phase ,there is strong

stability and order of the oligopoly ,but the execution of the productivity phase still awaits and

for this to occur the supply and distribution relations need to be literally ironed out into linear

shapes (Hurta, H., Jazouli, A., Koplyay, T., & Motaghi, H. (2017)).

Downstream from the M&A lurks the market exit, the final gaping black hole that

swallows all firms, and that point represents chaos. So, we have the stability of the M&A phase,

the edge of chaos of the market exit and in between the nonlinearity of the combined firm and

alliance structures.

By this phase the firms are cooperating seriously with chosen partners and almost value

chain type behavior is evident in the clusters, the end of which need to be ironed out to attain the

value chain. A period on high nonlinearity occurs between the ordered sate and the chaotic exit

that allows for organization the firm level to produce an emerging entity the value chain, which

is markedly different from the firms composing it and endowed with properties that could not be

derived from firm characteristics. Some of these properties are smoothing and tightening of chain

relationships by a dominate member of the chain that henceforth sets chain strategies. The firms

need are submerged into the chain. Although as the chain gains tremendous efficiencies it loses

survival attributes.

It suddenly has, a series of critical nodes, the individual firms, which renders ii equally

exposed to market perturbations at all nodes. Hence it builds redundancy at all nodes of the

linear network, which results in overall robustness. Again, this emergence is occasioned by a

prevailing complexity at the firm level in a period of phase tension between order and chaos

The phase transition is twofold; Transition from mass customization found in oligopolies

and a transition from moderate growth pre and past M&A to zero growth of late markets. Both

marketing and growth conditions change. In anticipation of this event the M&A was unleased to

find market share in a now static market, that faces the calculations of zero-sum market share

changes. Therefore, the competition must shift from further acquisition of share to execution of

productivity at fixed point of interaction with the market



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Conclusions

Market appears to anticipate its own evolutionary profile and exerts forces and creates

adaptive mechanisms for firms and their alliances to proceed I the right direction at the right time

toward a final state where choice is stripped from the firms and a given strategy imposed which

requires a management perspective change from well positioned firms to well managed firms.

From external management emphasis to internal focus. But the market provides the means of

transition at various phases and firms that profit from this opportunity continue to evolve and

arrive well equipped at the final state. The market goes through a series of critical events from

the chasm in early phase to shakeout in mid stage to partial market collapse at M&A and finally

at extinction in market exit. All of them are market exit grey holes for the firms, some go under

some survive. Before each exit point the market allows for preparation by the firms to confront

the crisis and this means is the complex adaptive transitions that lead to emergence of lifeboats

that help navigating the treacherous waters of the grey holes.

Whether it’s the, the platform, the collapse due to M&A or the value chain the transition

prior to these events seems to be based on self-organized based emergence that is initially weak

but later becomes strong by exerting feedback on all firms and draws them to the attractor that

these alliances represent for the firms.



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Koplyay, T., Lloyd, D. M., Sanchez, L., & Paquin, J. P. (2012, January). Strategy making in hi-

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442.

BASEL II Implementation on Financial Performance. Banking in ASEAN.

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BASEL III implementation on financial performance. Banking in ASEAN.

Nanang Shonhadji

STIE Perbanas Surabaya, Nginden Semolo 34-36,

Surabaya, Indonesia

[email protected]

+62 5947151

Abstract

The economic and monetary crisis, a regulation was issued by the Basel Committee on Banking

Supervision (BCBS), which in 2008 was marked by the bankruptcy of Lehman Brothers which

discussed the world financial crisis into the submission of world financial assistance from the

Basel Accord I and Basel II which discussed no able to overcome the crisis. Basel III is related to

capital and liquidity which will take effect in 2019. In Basel III provisions, evaluation of

liquidity management uses two approaches, namely Net Stable Funding Ratio (NSFR) and

Liquidity Coverage Ratio (LCR). This research aims to determine NSFR, LCR, and COF

simultaneously have a significant positive effect on ROA in banking sector companies in

ASEAN. The sample used in this study are banks in six countries in ASEAN. The data used is

secondary data, sample collection technique is purposive sampling and multiple linear regression

analysis using the F test and t test. Using the study period from 2014 to 2018. The result from

this study is that the NSFR and COF have significant effect on ROA simultaneously in banking

sector companies in ASEAN. On the other hand, LCR have unsignificant effect on ROA in

banking sector companies in ASEAN. Signal theory shows how companies give signals to users

of financial statements. The signal itself is an action taken by management aimed at the

stakeholders to show the company's capabilities expressed in the annual report. By showing good

performance, it will give a good signal to investors to invest their capital. Some variables have

different result in each country in ASEAN. The results of hypothesis testing indicate the

existence of several weak independent variable influences. This indicates that there are still other

factors beyond research that can affect the dependent variable. Research implication was

increasing the ability of the banking sector to absorb the potential risk of losses due to the

financial and economic crisis, and to prevent the financial sector crisis from spreading to the

economic sector in ASEAN countries

Key words: Financial Performance, Net Stable Funding Ratio and Liquidity Coverage Ratio and

Cost of Fund



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1. INTRODUCTION

The commercial bank functions as a financial intermediary or collects funds from the

community and distributes them back to the community for the purpose. Special banks as trust

agents or trust-based institutions, development agents or institutions that mobilize funds for the

country's economic development, and service agents or institutions that provide services to the

public (Monang and Inggrita, 2013). However, the growth of the current economic and monetary

crisis, which provides considerable growth for the people and economic growth.

Based on the economic and monetary crisis, a regulation was issued by the Basel

Committee on Banking Supervision (BCBS), which in 2008 was marked by the bankruptcy of

Lehman Brothers which discussed the world financial crisis into the submission of world

financial assistance from the Basel Accord I and Basel II which discussed no able to overcome

the crisis. The bankruptcy of Lehman Brothers shows weak management policies and

government protection, improper incentive structures and excessive banking industry influence.

Because this prompted BCBS to issue a global financial reform package, better known as Basel

III, which was a continuation of the three pillars in Basel II with additional requirements,

including requiring banks to have a minimum general equity and general liquidity ratio.

The regulation is made so that banks are ready to face risks and can improve their

performance. When bank management succeeds in improving performance in banking

institutions, the success will have implications for increasing the profitability of the banking

industry. Therefore, profitability (ROA) can be used as a valid measure in measuring banking

performance in decision making. ROA is a comparison between pre-tax profit and total assets

held. The greater the value of ROA, the better the performance of the banking company because

the return the company gets is getting bigger (Didik and Bambang, 2013).

Basel III is related to capital and liquidity which will take effect in 2019. In Basel III

provisions, evaluation of liquidity management uses two approaches, namely Net Stable Funding

Ratio (NSFR) and Liquidity Coverage Ratio (LCR). In brief, NSFR is a control of long-term

liquidity flows, while LCR is a control of short-term cash flows. In addition, NSFR and LCR

require banks to increase high-quality liquid assets and obtain stable funding sources and ensure

that they are in accordance with the principles of liquidity risk management.

The first approach is the Net Stable Funding Ratio (NSFR) in Basel III intended to

promote medium and long-term funding of assets and activities of banking organizations. Thus,

NSFR tends to reduce exposure to liquidity risk funding. While the second approach is Liquidity

Coverage Ratio (LCR) which was introduced to improve the ability of banks to overcome short-

term liquidity needs and liquidity market risks. The LCR effect on bank profitability will exceed


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the level of net outflows so banks tend to be more careful in investing (Giordana and

Schumacher, 2017).

This study also uses additional variables, namely Cost of Fund (COF), a ratio used to

measure the proportion of own capital compared to external funds in financing banking business

activities. Cost of Fund (COF) is the interest rate that must be paid by a financial institution for

the funds they get (Alfin et al. 2015). Based on research conducted by several previous

researchers, it can be concluded that there are several differences of opinion between several

studies. The purpose of this study is to find out the implementation of Basel III on banking

financial performance in ASEAN.

2. THEORETICAL FRAMEWORK

Signaling Theory

Signal theory is an action taken by a company to provide guidance to investors about how

management views the company's prospects (Brigham and Houston, 2011: 186). According to

Jogiyano (2014) this signal is in the form of information about what has been done by

management to realize the wishes of the owner. Information issued by the company is important

because it has an influence on decision making by parties outside the company. This information

is important for investors and business people because it presents information, notes, or an

overview of both past, present and future conditions for the survival of the company and the

effects on the company. When information is announced, market participants first interpret and

analyze the information as a good news or bad signal. If the announcement of the information is

considered a good signal, the investor will be interested in trading shares, thus the market will

react which is reflected through changes in the volume of stock trading. However, if the

information is a bad signal, investors will become less interested in the company (Suwardjono,

2010).

The relationship between signal theory and financial performance (ROA) is that it can

provide information both inside and outside the company, and can attract investors to invest

because of an increase in profits. If the profit reported by the company increases, the information

can be categorized as a good signal because it indicates a good condition of the company.

Conversely, if reported earnings decline, the company is in a bad condition so that it is

considered a bad signal.

Effect of Net Stable Funding Ratio to Return on Assets

Net Stable Funding Ratio is a comparison ratio of stable funding available or Available

Stable Funding with Required Stable Funding. Available Stable Funding (ASF) is a stable

amount of liabilities and equity for one year to fund bank activities. Whereas what is meant by


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Required Stable Funding (RSF) is the number of assets and administrative account transactions

that need to be funded by stable funding. NSFR is included as long-term funding, namely

funding used to meet the needs of companies whose returns are in the long term and the benefits

can be felt in the old times as well. The NSFR value that must be fulfilled by the bank is at least

100% (Financial Services Authority, 2017). The reason management needs long-term funding is

because of the large amount of funds needed for company investment or retained earnings of

companies that do not exist or meet funding needs.

Long-term funding also affects the profits of a company because it is used for investment

or meeting company needs. The higher the long-term funding owned by the bank, the more

companies have investments so that the profits obtained are greater because banks use long-term

funding to obtain longer benefits. This signal theory shows the signal given by management that

is published in financial statements aims to provide information that can make investors

interested in investing in banks. With a high NSFR value, it can be said that the condition of the

bank is getting better because the bank has a long-term investment that can get bigger profits.

According to previous research conducted by Said (2018), the NSFR has an effect on

ROA. But the research conducted by Giordana and Schumacher (2017) and Asraf, et al. (2016)

shows that NSFR does not affect ROA. The hypotheses formulated for this study are as follows:

H1: Net Stable Funding Ratio (NSFR) has an effect on Return On Assets (ROA).

Effect of Liquidity Coverage Ratio to Return on Assets

Banking liquidity is defined as the ability of banks to fulfill their main obligations in the

form of public deposits and other liquid liabilities. One indicator of banking liquidity monitoring

is Liquidity Coverage Ratio, where banks have sufficient stock of High Quality Liquid Assets

(HQLA) consisting of cash or assets. These assets must be converted into cash with little or no at

all which does not result in losing value in the market to meet the liquidity needs of 30 days.

LCR can affect the profits of a bank. If LCR is high, it means that the bank has a stock of

HQLA containing high cash or assets, the banking profit is also high, and vice versa. Because if

LCR is high, the bank has the ability to fulfill its main obligations and other liquid obligations

based on high profits. Signal theory shows that the signal provided by management which is

published in financial statements has the purpose of providing information that can make

investors interested in investing in banks. With a high LCR value, it can be said that the bank's

condition is getting better.

According to previous research conducted by Bruna and Blahova (2016) shows that LCR

affects ROA. However, research conducted by Giordana and Schumacher (2017) shows that

LCR has no effect on ROA. The hypotheses formulated for this study are as follows:


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H2: Liquidity Coverage Ratio (LCR) affects Return On Assets (ROA).

Effect of Cost of Fund to Return on Assets

Cost of Fund (COF) is the total interest incurred by the bank to obtain deposit funds in

the form of deposits, savings and time deposits. The total cost of funds depends on how much

interest is set to obtain the desired funds. The greater the interest charged on deposit interest, the

higher the cost of funds as well as vice versa. This total interest cost will affect the bank's profit

because the main bank income is derived from the difference between interest on deposits and

interest on loans (Maryam, 2016). Signal theory that shows signals given by management that

are published in financial statements with the aim of providing information that can make

investors interested in investing in banks. With a large COF value, it can be said that the capital

owned by a large bank is also.

According to previous research conducted by Maryam (2016), it was shown that COF

had an effect on ROA, so the hypothesis for this study was:

H3: Cost of Fund (COF) has an effect on Return On Assets (ROA).

The Research Framework as follows:

3. RESEARCH METHODS

Population and Samples

The population in this study were banking companies in ASEAN for the 2014-2018

period with a total of 130 companies consisting of 16 Philippine banks, 22 Malaysian banks, 44

Indonesian banks, 31 Cambodian banks, 6 Singapore banks, and 11 Thai banks. The sampling

technique is done by using a purposive sampling method with the criteria of banking companies

in ASEAN in 2014-2018 listing on the Stock Exchange. Banking companies in ASEAN that

publish audited financial statements include reports on changes in equity, income statements,

financial position reports, cash flow reports and notes to financial statements that are consistent

Net Stable Funding Ratio (X1)

Liquidity Coverage Ratio (X2)

Cost Of Fund (X3)

Return on Assets (Y)


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in 2014-2018, and banking companies in ASEAN that provide data related to the variables in this

study were ROA, NSFR, LCR, and COF.

Research variable

The research variables used in this study include the dependent variable namely return on

assets and the independent variable consisting of the net stable funding ratio, liquidity coverage

ratio, and cost of fund.

Operational Definition of Variables

Return On Assets (ROA)

Return on Assets (ROA) is one indicator of profitability from financial performance that

is used to measure the ability of bank management to obtain profits or profits as a whole. ROA is

a comparison between pre-tax earnings and the average total assets in a period. This ratio can be

used as a measure of financial health. This ratio is very important and is related to the

performance of the bank because it can be used to see the level of business efficiency of a bank

from the profits obtained by using its assets.

𝐑𝐎𝐀 = Earning Before Income Tax

Total Asset

Net Stable Funding Ratio (NSFR)

The net stable funding ratio (NSFR) is the ratio of available Stable Funding (ASF) to

banks that require stable funding (Required Stable Funding).

NSFR = Available Stable Funding (ASF)

Required Stable Funding (RSF)

Liquidity Coverage Ratio (LCR)

Liquidity Coverage Ratio (LCR) is the ratio of liquid assets to estimated cash outflows

under stressful conditions. This standard requires that the ratio is never below 100 percent and

banks are expected to meet these requirements continuously to ensure the bank's resilience to

adverse shocks. Therefore, LCR is used to emphasize that banks hold high quality liquid assets

that are sufficient to meet short-term liquidity needs for at least 30 days.

𝐋𝐂𝐑 =High Quality Liquid Asset

Net Cash Outflows

Cost Of Fund (COF)


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Cost of Fund is the total interest expense incurred by the bank to obtain deposit funds in

the form of deposits, savings and time deposits. This ratio describes the total costs that must be

incurred by the bank for each fund that it collects in various sources before it is reduced by

mandatory liquidity.

𝐂𝐎𝐅 = Interest Expense

Third Parties Fund× 100

Analysis Technique

The analysis technique used in this study is multiple linear regression, because this study

supports the relationship between independent variables and the dependent variable. In addition,

this analysis can prove the relationship between the independent variable and the dependent

variable. The following are the research regression model equations:

ROA = α+β1X1+β2X2+β3X3+ɛ

ROA = Return on Assets

X1 = Net Stable Funding

Ratio (NSFR)

X2 = Liquidity Coverage

Ratio (LCR)

X3 = Cost Of Fund (COF)

β1, β2, β3 = Koefisien Regresi

ε = error

4. RESULTS AND DISCUSSION

Descriptive Analysis

Descriptive statistical analysis provides a description or description of one data seen from the

mean, standard deviation, maximum value, and minimum value (Ghozali, 2013). This analysis is

used to obtain a description or description of a data seen from the mean, standard deviation,

maximum value, and minimum value for each variable in this study, namely ROA, NSFR, LCR,

and COF.


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Table 1

Descriptive Analysis

N Minimum Maximum Mean Std. Deviation

Statistic Statistic Statistic Statistic Statistic

ROA 575 -.0032 .0356 .01341 .00812

NSFR 575 .0052 .91041 .62042 .13152

LCR 575 -5318.4 4310.84 1.88031 501.251

COF 575 .0021 8.11467 .15512 .5274

Valid N

(listwise) 575

Source: Output SPSS, 2019

Return On Assets (ROA)

Return on Assets (ROA) based on table 1 above shows that the sample value in this study

amounted to 546 banks. The minimum value of ROA is -0.0032 owned by India International

Bank Malaysia Berhad. in 2016 which means that the value of profit before tax is negative and

the total value of assets is positive so that the results of ROA are negative, from these results

indicate that the bank's profit before tax suffers a loss, this indicates that the bank is less efficient

in generating profits. The maximum value of ROA of 0.0356 is owned by ACLEDA Bank PLC,

Cambodia in 2015. This shows that ACLEDA Bank PLC, Cambodia is able to optimize its assets

to generate profits.

The mean or mean value of the ROA variable is 0.01341. While the standard deviation is

0.00812. Based on the results of the mean and standard deviation indicate that the mean value is

greater than the standard deviation, for the ROA variable the spread of the data can be said to be

good and the data is homogeneous.

Net Stable Funding Ratio (NSFR)

Table 1 above shows that the minimum NSFR value is 0.0052 which is owned by Krung

Thai Bank PLC, Phnom Penh Branch, Cambodia in 2016, this indicates that the ASF value is

lower than the RSF value. While the maximum value of NSFR is 0.9104 owned by Rizal

Commercial Banking Corporation, Philippines in 2014 and 2015. This shows that Rizal

Commercial Banking Corporation, Philippines in 2014 and 2015 had sufficient stable funding.

The mean or mean value of the NSFR variable is equal to 0.62042. While the standard deviation

is 0.13152. Based on the results of the mean and standard deviation indicate that the mean value

is greater than the standard deviation, for the NSFR variable the spread of the data can be said to

be good and the data is homogeneous.

Liquidity Coverage Ratio (LCR)


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Table 1 above shows that the minimum value of LCR is -5318.4 owned by Philippine

National Bank in 2014, this indicates that the HQLA value has a negative value while the value

of Net Cash Outflows is positive. This shows that the company is unable to overcome the

economic crisis because it has a low LCR value. While the maximum value of LCR is 4310.84

which is owned by PT Bank Mandiri (Persero) Tbk, Indonesia in 2017. This shows that PT Bank

Mandiri (Persero) Tbk, Indonesia in 2017 has high liquid assets and is able to face the economic

crisis. The mean or mean value of the LCR variable is 1.88031 and the standard deviation is

501.2531, this result shows that the mean is lower than the standard deviation so that it indicates

poor results. Because standard deviation is a reflection of a very high deviation, so the spread of

data shows abnormal results and causes bias.

Cost Of Fund (COF)

Table 1 above shows that the minimum value of COF is 0.0021 owned by Security Bank

Philippines in 2014, this shows that the bank's interest is lower than the total third party funds.

While the maximum value of COF is owned by JP Morgan Bank, Singapore in 2013. This

indicates that banks have higher interest costs than third party funds. The mean or mean value of

the COF is equal to 0.15512 and the standard deviation is 0.5274, this results show that the mean

value is lower than the standard deviation so it indicates poor results. Because standard deviation

is a reflection of very high deviation, so the spread of data shows abnormal results and causes

bias.

Table 2

Summary of Hypothesis Tests

Model B Std. Error t Sig.

(Constant) .006 .001 4.332 .000

NSFR .015 .002 5.964 .000

LCR .000000889 .000 1.471 .415

COF .002 .001 3.414 .013

R2 .176

Adjusted R2 .169

F Hitung 13.419

Sig. F .000

Source: Output SPSS, 2019.

Based on Table 2, the results of the F test analysis show that F count has a value of

13.419 with a significance level of 0.000, which means that the data meets the assessment of data

that is fit. Because the significance value is less than 0.05, so the regression model can be used to

predict financial performance or variables NSFR, LCR, and COF jointly affect ROA.


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Based on Table 2 which shows the results of the coefficient of determination test of all

variables obtained an adjusted R square value of 0.169 which means that NSFR, LCR, and COF

are only able to explain variations in ROA of 16.9%. While the rest is explained by other factors

outside of research. The t test aims to determine the effect of independent variables individually

on the dependent variable. The results of this test indicate that LCR and CAR have no significant

effect on ROA, while NSFR and COF have a significant effect on ROA. The following is a

discussion of each variable:

Effect of Net Stable Funding Ratio on Return On Assets

The first hypothesis states that the net stable funding ratio affects the return on assets. Net

stable funding ratio (NSFR) is defined as the ratio of available Stable Funding to banks that

require stable funding (Required Stable Funding). Requirements from the Net Stable Funding

Ratio (NSFR) are introduced where banks are required to maintain sufficient liquid funds.

According to the executive summary issued by the Bank for International Settlements (2018),

stable funding is defined as the type and amount of equity and financing obligations that are

expected to be a reliable source of funds for a period of one year under stressful conditions. This

standard also requires the value of the ASF ratio to exceed RSF to ensure that banks have

sufficiently stable funding in accordance with their medium and long-term loans during the

period evaluated.

Based on hypothesis testing (t test) shows that the results have 0,000 (sig <0.05), which

means that NSFR has an effect on ROA. NSFR has an effect on ROA, meaning that banks can

maintain stable funds that are adjusted to the composition of assets and bank account

administrative activities and are able to face economic crises so that they can show good

performance because the greater the NSFR ratio, the greater the bank's ability to obtain stable

funding. According to the theory used in this study, signal theory shows how companies give

signals to users of financial statements. The signal itself is an action taken by management aimed

at the stakeholders to show the company's capabilities expressed in the annual report. By

showing good performance, it will give a good signal to investors to invest their capital. Vice

versa, if the company shows poor performance, then the signal given to investors is also bad.

Therefore, this test shows that a high NSFR ratio that can show a good signal is because the

NSFR ratio has an effect on financial performance (ROA) so that banks can obtain stable

funding from third parties to get the expected benefits. The results of this study are consistent

with the research conducted by Said (2018) which shows that NSFR has an effect on ROA. But

this result is different from the research conducted by Giordana and Schumacher (2017) and

Asraf, et al. (2016) which shows that NSFR does not affect ROA.

Effect of Liquidity Coverage Ratio to Return On Assets

The second hypothesis states that the influential liquidity coverage ratio is aware of

return on assets. Liquidity Coverage Ratio (LCR) is the ratio of liquid assets to estimated cash


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outflows under stressful conditions. This standard requires that the ratio value is never below

100% and banks are expected to meet these requirements continuously. The aim is to ensure the

bank's resilience to adverse shocks. Therefore, LCR is used to emphasize that banks hold high

quality liquid assets that are sufficient to meet short-term liquidity needs for at least 30 days

(Said, 2018). In searching for LCR values, using the calculation of High Quality Liquid Assets

(HQLA) divided by Net Cash Outflows where HQLA is cash or assets that can be converted into

cash quickly through sales or can be used as collateral. While net cash outflows are cash

outflows minus cash inflows where outflows consist of deposits from individual customers,

micro and small businesses, funding from corporate customers, collateral funding, other cash

outflows and cash inflows consisting of loans with collateral, bills from the opposite party, and

other cash inflows.

Based on hypothesis testing (t test) shows that this test has a yield of 0.415 (sig> 0.05)

which means that LCR does not affect ROA. LCR does not affect ROA, meaning that the bank is

not able to overcome the economic crisis because the bank is unable to fulfill its obligations on

time so that liquidity cannot be fulfilled and does not benefit because of poor financial

performance. According to the theory used in this study, signal theory shows how companies

give signals to users of financial statements. The signal itself is an action taken by management

aimed at the stakeholders to show the company's capabilities expressed in the annual report. By

showing good performance, it will give a good signal to investors to invest their capital. Vice

versa, if the company shows poor performance, then the signal given to investors is also bad.

This theory describes managers or companies having advantages over information compared to

outside parties and they use certain sizes and facilities to give up the quality of the company.

The results of this study are consistent with research conducted by Giordana and

Schumacher (2017) showing that LCR has no effect on ROA. However, this result is different

from the research conducted by Bruna and Blahova (2016) indicating that LCR affects ROA.

Effect of Cost of Fund on Return On Assets

The fourth hypothesis states that the cost of fund has an effect on the return on assets.

Cost of Fund is the total interest expense incurred by the bank to obtain deposit funds in the form

of deposits, savings and time deposits. The total cost of these funds must be reduced by a

mandatory reserve or Reserve Requirement (RR), while the Cost of Loanable Fund (COLF) is

the cost of funds that must be issued by mandatory liquidity (Maryam, 2016). There are three

methods in calculating the cost of funds according to Maryam (2016), namely the method of

weighted average cost of funds, historical average cost of funds methods, and the method of

marginal funding costs. The method of weighted average cost of funds is an approach that first

pays attention to each source of funds which is indicated by the size of the composition of funds

and other factors that affect the amount of funding costs such as reserverequirement. Then the

method of historical average cost of funds is the method that is considered the easiest because the


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bank only sums up the cost of raising funds divided by the total funds raised. However, when

faced with changing interest rates, this method is not applicable because the costs calculated in

this method are past costs. And finally, the marginal cost method is a method that is often used to

make decisions at that time relating to the need for funds or credit to meet prime customers. The

relationship of the COF ratio to financial performance (ROA) is the greater the COF value, the

greater the ROA that is owned because the bank gets funds for bank activities. While the smaller

the COF value, the smaller the ROA owned by the bank is because the bank is less in obtaining

funds used for activities.

Based on hypothesis testing (t test) shows that this test has a result of 0.013 (sig <0.05)

which means COF has an effect on ROA. COF has an effect on ROA, meaning that the bank

obtains funds from third parties used for bank operations. According to the theory used in this

study, signal theory shows how companies give signals to users of financial statements. It can be

said that the high COF ratio shows a good signal because COF has an effect on ROA where

banks have good capital to issue savings funds for the community. The results of this study are

consistent with the research conducted by Maryam (2016) showing that COF has an effect on

ROA. Whereas, the results of research different from the research conducted by Ida and Badera

(2015) indicate that COF does not affect ROA.

5. CONCLUSIONS, LIMITATIONS AND RECOMMENDATIONS

Based on data analysis and hypothesis testing that has been done, conclusions can be

drawn as follows: (1) The ratio of NSFR and COF together has a significant effect on financial

performance (ROA) in the banking sector in ASEAN. Thus the hypothesis which states that

NSFR and COF affect ROA for banks in ASEAN is accepted. (2) The simultaneous NSFR ratio

has a significant positive effect on bank ROA in ASEAN. Thus the hypothesis which states that

Net Stable Fundig Ratio has an effect on Return On Assets is accepted. (3) COF ratio

simultaneously has a significant positive effect on bank ROA in ASEAN. Thus the hypothesis

which states that Cost of Fund has an effect on Return On Assets is accepted. (4) LCR ratio does

not affect bank ROA in ASEAN. This shows that LCR and COF have no effect on ROA because

there are phenomena that occur in bank financial statements in ASEAN.

This study has limitations that can affect the results of the study. The limitations of this

study are: (1) Some annual reports are followed by not using international language (English)

which causes researchers to not be able to read financial statements so that elimination is carried

out. (2) There are several companies in the banking sector whose financial statements cannot be

accessed through a stock exchange but financial statements can be accessed through the web of

each banking sector company. (3) This research has outliers to get data that is normally

distributed, so that the data tested is only a few and the results are not maximal. (4) The results of


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hypothesis testing indicate the existence of several weak independent variable influences. This

indicates that there are still other factors beyond research that can affect the dependent variable.

Based on the conclusions and limitations that have been revealed previously, this research is far

from perfection. For this reason, researchers provide suggestions that can be used for further

research in order to obtain maximum results. Suggestions from this study are: (1) For the next

researcher, it should focus on annual reports that use international or other foreign languages

according to the ability of the researcher. (2) Researchers can use the same topic with more

variables and extend the research period. (3) The banking sector should provide easy access in

accessing annual reports.


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Bruna, K., & Blahova, N. (2016). Systemic Liquidity Shocks and Banking Sector Liquidity

Characteristics on Eve of Liquidity Coverage Ratio Application - The Case of the Czech

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Khaerul, U. (2013). Sharia Banking Management. Bandung: Pustaka Setia Library.

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Financial Behaviour, E-Trading Satisfaction, E-Trust, and E-Loyalty of E-Trading in Indonesian Stock

Exchange with SEM-PLS

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Financial Behaviour, E-Trading Satisfaction, E-Trust, and E-Loyalty of E-Trading in

Indonesian Stock Exchange with SEM-PLS

Rohmad Fuad Armansyah

STIE Perbanas Surabaya-Indonesia

Nginden Semolo 34-36, Surabaya-Indonesia

[email protected]

Abstract

The growth of technology today has caused many entrepreneurs and companies to change their

perspective in conducting business and influencing user behaviour, especially financial behaviour.

The online trading system allows traders to enter orders directly into the system via electronic media

immediately and direct, and this condition will affect the level of customer satisfaction while

increasing customer loyalty. Technological developments in this sector quickly changed the dynamics

and process of transactions. Customers can choose to meet their broker or call the office from home

for a deal. This method is considered to be the most recent in its time, but by telephone, it can become

inefficient due to potential errors in communication, restrictions on customer authentication, the

density of telephone lines in peak trading sessions and costs incurred. The online trading system

allows traders to enter orders directly into the system through electronic media such as laptops,

personal computers, and cellular phones with internet network support. The online trading system

does not necessarily make everything go well. Some obstacles and complaints arose from users, began

to have difficulty accessing, features that were less expected, to systems that did not respond when

peak transactions. Conditions like this will affect the level of customer satisfaction, and as an effort to

increase the level of customer satisfaction, the trading system will be perfected regularly for the

convenience of traders. The purpose of this study aims to examine financial behaviour in terms of

satisfaction, trust and loyalty in the use of e-trading in the Indonesian stock exchange. The data are

collected through electronic questionnaires of the Indonesia Stock Exchange investors which are

processed using outer model and inner model by SEM-PLS (Structural Equation Modeling-Partial

Least Square) approach. The results show that the variable financial behaviour, electronic trust (e-

trust), satisfaction of electronic commerce (e-trading satisfaction) have an effect on the creation of

electronic loyalty (e-loyalty) of e-trading users on the Indonesia Stock Exchange.

Keywords: financial behaviour, e-trading, e-loyalty, e-trust, SEM-PLS.




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Introduction

Today's rapid technological development has caused many entrepreneurs and companies to

change their perspective in doing business. The growth of companies that are lagging in using

technology is lagging in many aspects such as efficiency, connectivity, market expansion, and so on.

The internet has drastically changed the way companies do their business including the financial

industry and capital markets. Technological developments in this sector quickly changed the dynamics

and process of transactions. Customers can choose to meet their broker or call the office from home

for a deal. This method is considered to be the most recent in its time, but by telephone, it can become

inefficient due to potential errors in communication, restrictions on customer authentication, the

density of telephone lines in peak trading sessions and costs incurred.

The online trading system allows traders to enter orders directly into the system through

electronic media such as laptops, personal computers, and cellular phones with internet network

support. The online trading system does not necessarily make everything go well. Some obstacles and

complaints arose from users, began to have difficulty accessing, features that were less expected, to

systems that did not respond when peak transactions. Conditions like this will affect the level of

customer satisfaction, and as an effort to increase the level of customer satisfaction, the trading system

will be perfected regularly for the convenience of traders. Online relationship quality, which is

relationship satisfaction and relationship trust, plays an essential role in strengthening e-loyalty in the

quality of website design (Tsai, 2017). Trust in electronic media or e-trust is believed to increase

online customer loyalty so online merchants must expand their shipping area options and types of

products, so that not only can attract new customers, but also maintain real customer satisfaction, trust

and loyalty (Radionova-Girsa & Lahiža, 2017). Conditions like this will affect the level of customer

satisfaction and as an effort to increase the level of customer satisfaction, the trading system will be

perfected regularly for the convenience of traders. Evaluation of the application of an online trading

system have the aims to improve company performance in an effort to keep the company competitive

against its competitors. This evaluation is needed so that gaps in the system can always be overcome.

This gap will be able to have an impact on the company's image. One negative effect is that poor

system performance can spread and produce a negative image on the company. Furthermore, this

negative image can affect the trust of clients and clients can switch to their competitors thereby

reducing company profits. If the user is not satisfied with the software used, they will look for ways

that the system will no longer be used. In e-commerce, loyal customers are considered very important.

Customer loyalty is generally associated with satisfaction with service quality. Because of online

transactions, trust is a condition for exchange and satisfaction plays an important role in business

continuity.

Belief in electronic media or e-trust is believed to increase online customer loyalty so that

online merchants must expand their shipping area options and product types so that they can not only



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attract new customers, but also maintain existing customer satisfaction, trust and loyalty. The study of

trust, commitment and satisfaction of banking services conducted by Kingshott, Sharma, & Chung

(2018) using data from 336 small and medium business customers in the New Zealand banking

industry found that the quality of offline and online services affected satisfaction with their e-banking

services, which ultimately affects customers' trust and commitment to the service. The level of

satisfaction and loyalty using e-commerce media also differs between gender, age, and motivation in

its use (Fang, Shao, & Wen, 2016). Research related to loyalty, trust, and satisfaction in using

information technology and e-commerce media are still developing in various aspects, both from the

demographic elements and from the aspects of the industry and human behaviour in finance. Research

from Nisar & Prabhakar (2017) found that there is a direct relationship between e-service quality, e-

satisfaction and e-loyalty in terms of online shopping. However, an analysis shows that e-commerce

still faces challenges compared to offline traders because customers cannot feel and try products, and

may eventually choose products they don't want. This condition allows for further study of behaviour,

especially financial behaviour.

The development of research that focuses on financial behaviour is still developing and

interesting to study. Research on financial behaviour is still little done, mainly related to the

satisfaction of electronic media users in decision making. Based on the description above, this

research is expected to provide additional knowledge and knowledge on behavioural economics so

that investors get further insight into the behaviour that might exist in the Indonesian capital market.

Literature Review

Financial Behaviour

Economic behavior is often a problem in the market. Good behavior tends to make the

market stable or lead to growth. Unlike the case with behavior that is classified as deviant in the

perspective of decision making. The process of decision making by investors in the market

involves a variety of thoughts and underlying factors. These thoughts and factors are sometimes

beyond reason. Different thinking can lead to behavioral anomalies in decision making.

Information plays an important role in decision making because of the information received this

is the cause of diverse investor thinking. Information that receive will determine the outcome of

the investment. Investors seek to find information relating to investment opportunities so that

they will create investors who are sufficiently informed and uninformed.

Financial Behaviour appears in line with the development of the world of business and

technology that involves aspects of behaviour in the process of making financial and investment

decisions. Business actors are human beings who have reason and intuition in decision making

so that it involves a little more behaviour in it. Behavioural finance is a science that studies how



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humans uncover and react to information obtained to make decisions that can optimise the rate

of return by paying attention to the risks in it (Lintner, 1998).

Behavioural finance is a scientific discipline in which interdisciplinary interactions are

intertwined and continue to integrate so that the discussion cannot be isolated (Ricciardi &

Simon, 2000). It can be concluded that financial behaviour is the study of how humans take

action in making decisions in investing in response to information obtained. Investors do not

always behave rationally and do not deviate and can be modelled quantitatively.

E-Trading Satisfaction

According to Hansemark & Albinsson (2004), e-satisfaction is the fulfilment of

requirements, goals or desires reflected in the overall attitude of customers towards online

merchants, or emotional interaction by respecting what customers expect online with what they

get. Also, global policymakers must be sure that customer satisfaction is the primary key to the

health of national economic performance (Chen, Martin, & Merchant, 2014). Customer

satisfaction is closely related to interpersonal trust (Geyskens, Steenkamp, Scheer, & Kumar,

1996) and is considered an antecedent of trust (Christodoulides & Michaelidou, 2011). The

positive effects of satisfaction on trust can be expected in the online environment too, although

empirical research in this domain is scarce. The positive impact of customer satisfaction on trust

in service providers has been shown for the book industry (Pavlou, 2018). In analogy with these

findings, the experience of satisfying customers with specific e-tailers is expected to increase

their willingness to do more online purchases of e-tailers, as well as their trust in online media

(Hadi Teymoori, maeyam godarzi, & Hameh ghaebi, 2016) based on trust. Satisfaction with

specific applications of the system will increase trust in the system as a whole (Nisar &

Prabhakar, 2017).

E-Trust

Trust is considered another important part of loyalty (Reichheld & Schefter, 2000). The

concept of trust has been studied in various disciplines, and different definitions have been

proposed (Lewicki, McAllister, & Bies, 1998). Trust is consistently related to the vulnerability

of trustees (Bigley & Pearce, 1998; Singh & Sirdeshmukh, 2000) because, without the

vulnerability of the trustee to the given trust, trust becomes irrelevant. In business studies, trust

is essential for building and maintaining long-term relationships (Geyskens et al., 1996; Singh

& Sirdeshmukh, 2000). The commonly used definition of trust is the definition of Moorman,

Zaltman, & Deshpande (2006), which defines it as the desire to depend on exchange partners

where a person has self-confidence. This definition is consistent with initial research, which

links trust with "beliefs in intentions and motives of others", definitions that are still valid

(Lewicki et al., 1998). This research is also repeated by recent research in offline and online

services (Cheung & Lee, 2002), which defines trust as "the level of trust or certainty of

customers in exchange options". Therefore, E-trust is defined as the level of customer trust in



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online exchanges, or online exchange channels.

Electronic exchange is believed to present many risks to customers (Grabner-Kräuter &

Kaluscha, 2003), while trust seems to be very important to create loyalty when the level of risk

is felt high. Online purchases are considered risky, because customers do not have direct contact

with the company, namely through sales staff or physical stores (Reichheld & Schefter, 2000),

and must submit sensitive information, such as credit card numbers, to complete transactions.

The absence of interpersonal interactions also shows that online trust is mainly cognitive, that is

based on customer judgment about the reliability and ability of traders or exchange channels,

and not trust based on ties between individuals. At present, the lack of empirical studies on trust

in online exchanges is on the effects of e-trust on customer behaviour. Grabner-Kräuter &

Kaluscha (2003) also show a lack of studies on trust in e-tailers, because many previous studies

only investigated website searches, purchase scenario hypotheses, or internet banking. It must

be explicitly acknowledged that there are different types of beliefs, and differences need to be

made between one's disposition, or the tendency to believe, system-based trust and interpersonal

trust (Grabner-Kräuter & Kaluscha, 2003). System-based trust is equal to e-trust and relates to

customer trust in buying or searching for goods/services information online. Lack of trust is

often cited as an excuse not to buy from online traders (Lee & Turban, 2001). In analogy with

findings from traditional loyalty research, positive word of mouth (Hollman, Forrest, Gremler,

& Brown, 1998) can also be expected as a result of trust. However, the lack of e-trust cannot be

directly affected by online traders, which can only affect the trust of their e-tailers.

Trader trust is the most widely studied form of trust in online exchanges, while system-

based trust has been largely ignored (Grabner-Kräuter & Kaluscha, 2003). E-trust is expected to

influence the customer's desire to buy online, but empirical evidence is lacking. A study by

(Radionova-Girsa & Lahiža, 2017) found that e-trust has a significant influence on the use of

internet banking, while trust in the bank itself does not affect.

E-Loyalty

Customer loyalty has been defined as a firm commitment to repurchase or rejuvenate

preferred products/services in the future, thus causing the same brand or purchase of the same

brand, regardless of situational influences and marketing efforts that have the potential to cause

a transition behaviour (Oliver, 2009). This general definition seems to apply to e-loyalty as

well. Another definition, shorter and more specific is given by Rolph E. Anderson & Srini S.

Srinivasan, (2003), who define e-loyalty as an attitude that benefits customers to the electronic

business, which results in repeat buying behaviour. Favorable preferences and attitudes assume

customer satisfaction, which is generally considered to be the primary driver of loyalty (Oliver,

2009; Rolph E. Anderson & Srini S. Srinivasan, 2003), also in online settings (Cho, Im, Hiltz,

& Fjermestad, 2002; Gummerus, Liljander, Pura, & Van Riel, 2004) because it is considered



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difficult to get loyal customers on the internet (Gommans, Krishnan, & Scheffold, 2001),

satisfaction with traders and their services may be more important online than offline (Kingshott

et al., 2018; Shankar, Smith, & Rangaswamy, 2003). E-commerce itself is also still facing

challenges compared to offline traders because online customers cannot feel and try the product,

so they might end up choosing the product they don't want (Nisar & Prabhakar, 2017).

Methodology

The data used are primary data with the technique of collecting data through electronic

questionnaires distributed to investors of the Indonesia Stock Exchange through brokerage companies,

as many as 1000 respondents have been obtained and used in this study, namely Indonesian Stock

Exchange investment actors who use the Indonesia Stock Exchange e-trading. The sampling technique

used was purposive sampling with certain respondent criteria so that the appropriate data was obtained

for this study. The sample data uses investor data held by brokerage companies with e-survey

questionnaires which are processed using outer model and inner model by SEM-PLS (Structural

Equation Modeling-Partial Least Square) approach and path estimate. Outer model in this study was

divided into 2 namely explanatory factor analysis and confirmatory factor analysis. Explanatory factor

analysis (EFA) is used if indicators that measure latent variables are formative while confirmatory

factor analysis (CFA) is used if indicators that measure latent variables are reflective.

This method is specifically designed to overcome problems in multiple regression. Technically

it aims to produce a model that transforms a set of correlated explanatory variables into a new set of

variables that are not mutually correlated. The outer model obtained is then evaluated based on the

substantive content model by comparing the relative weight and significance of the weight, then the

inner model is evaluated by looking at the percentage variance and looking at the R-square value and

seeing the magnitude of the structural path coefficient. The stability of these estimates was evaluated

using a two-way statistical t-test through the bootstrapping procedure. The inner model describes the

relationship between latent variables. Inner model is divided into 2 stages, namely hypothesis testing

and coefficient of determination. In the hypothesis test, the relationship between latent variables is said

to be significant if the value of P value <α = 0.05 or t-count> 1.96. While the coefficient of

determination there are three criteria, namely, the influence between latent variables is said to be strong

if the value of R2> 0.67; moderate if 0.33 <R2 ≤ 0.67; weak if the value is 0.19 <R2 ≤ 0.33 and is said to

be very weak if the value of R2 is ≤ 0.19.

Results and Discussions

This study aims to examine the behaviour of financial behaviour in terms of satisfaction, trust



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and loyalty in the use of e-trading in the Indonesian stock exchange using data from 1000 respondents

of the Indonesia Stock Exchange investors. The variables used are financial behaviour, e-trust, e-

trading satisfaction, and e-loyalty. Data is processed using in several stages with Partial Least Square

(PLS) regression method and path estimation. This method is specifically designed to overcome

problems in multiple regression. Technically it aims to produce a model that transforms a set of

correlated explanatory variables into a new set of variables that are not mutually correlated. The outer

model obtained is then evaluated based on the substantive content model by comparing the relative

weight and significance of the weight, then the inner model is evaluated by looking at the percentage

variance and looking at the R-square value and seeing the magnitude of the structural path coefficient.

The stability of these estimates was evaluated using a two-way statistical t-test through the

bootstrapping procedure. The following is the results from SEM-PLS approach.

Outer Model

Figure. 1 Outer Model

Based on the results found in Figure. 1, table. 1 and 2, show that all values of loading

factors from indicators have values above 0.7 AVE values> 0.6 so that these results indicate that

the validity criteria have been met. In table 1 also shows the composite reliability value and

Cronbach alpha has a value above 0.7 so that this result indicates that the reliability criteria have

been met. It can be concluded that the indicators EL1, EL2, EL3 can measure both e-loyalty

variables as well as ET1, ET2, ET3, ETS1, ETS2, ETS3, FB1, FB2, FB3 also have a loading

factor value above 0.7 so they can measure variables well e-trust, e-tradition satisfaction, and

financial behaviour.



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Table. 1 Outer Model Result

AVE Composite Reliability R Square Cronbach Alpha

EL 0.721286 0.885840 0.597740 0.806997

ET 0.734067 0.892204 0.672735 0.818977

ETS 0.776128 0.912244 0.624007 0.855555

FB 0.796939 0.921712 0.872601

Table. 2 Loading Factor

EL ET ETS FB

EL1 0.829404 0.566301 0.606980 0.597136

EL2 0.875774 0.653058 0.694390 0.667183

EL3 0.842002 0.566554 0.599601 0.610158

ET1 0.655188 0.880877 0.704567 0.711358

ET2 0.608465 0.855642 0.661141 0.647183

ET3 0.537355 0.833146 0.628530 0.628453

ETS1 0.683334 0.663505 0.854622 0.668188

ETS2 0.618327 0.652038 0.884798 0.686898

ETS3 0.675269 0.734999 0.902850 0.730707

FB1 0.647188 0.689461 0.719991 0.884646

FB2 0.621058 0.704345 0.715355 0.897284

FB3 0.707978 0.680151 0.679107 0.896159

Inner Model

Figure.2 Inner Model

Table 3. Hypotheses Test


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Path Coefficients T Statistics P value Information

ET -> EL 0.306866 3.622432 <0.001 Affected

ETS -> EL 0.510133 6.213679 <0.001 Affected

ETS -> ET 0.439673 7.621345 <0.001 Affected

FB -> ET 0.427313 6.713279 <0.001 Affected

FB -> ETS 0.789941 27.496941 <0.001 Affected

T Table 1.96

The inner model describes the relationship between exogenous variables and endogenous

variables. In this section, the Inner model is used as a basis for testing hypotheses by looking at

the coefficient of determination and path analysis. In hypothesis testing, the relationship between

latent variables is said to be significant if the value of P value <α = 0.05 or t-count> 1.96. While

the coefficient of determination has three criteria, namely, the influence between variables is said

to be strong if it has a value of R2> 0.67; moderate if 0.33 <R2 ≤ 0.67; weak if the value is 0.19

<R2 ≤ 0.33 and is said to be very weak if the value of R2 is ≤ 0.19.

Financial Behavior (FB)

The size of the parameter coefficient for the Financial Behavior (FB) variable is (original

sample) 0.427, which means that there is a positive influence between Financial Behavior (FB)

on e-trust (ET), or it can be said that the financial behaviour of investors affects e-trust in e-

trading in the Indonesia Stock Exchange supported by the t-statistic value 6.713 and

SIGNIFICANT with a statistical t value greater than t-table 1.96 (6.713> 1.96). So that the first

hypothesis is accepted namely, there is a significant effect of Financial Behavior on e-trust on the

Indonesia Stock Exchange E-trading. Whereas the coefficient of financial behavior parameter

(FB) towards e-trading satisfaction (ETS) is 0.789 which means that it has a positive and

significant influence with a t-statistic value of 27.496 greater than t-table 1.96, and this result

supports the second hypothesis that there is influence significant Financial Behavior towards E-

trading Satisfaction on the E-trading of the Indonesia Stock Exchange.

The influence of financial behaviour (FB) on e-loyalty (EL) through e-trading satisfaction

(ETS) indicated by the indirect parameter coefficient of 0.402 (0.789x0.50) which means

indirectly financial behaviour through e-trading satisfaction has a positive influence towards e-

loyalty and these results support the third hypothesis of this study, namely there is a significant

effect of Financial Behavior through E-trading Satisfaction on e-loyalty in the E-trading of the

Indonesia Stock Exchange.


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e-trading satisfaction (ETS)

The size of the parameter coefficient for the e-trading satisfaction (ETS) variable is

(original sample) 0.439 which means that there is a positive influence between e-trading

satisfaction on e-trust (ET), or it can be said that e-trading satisfaction affects e-trust investors in

e-trading of the Indonesia Stock Exchange is also supported by t-statistic value of 7,621 and

significant with a statistical t value greater than t-table 1.96 (7.621> 1.96), so that the fourth

hypothesis is accepted i.e. there is a significant effect of E-trading Satisfaction against e-trust on

the Indonesia Stock Exchange E-trading. While the parameter coefficient of e-trading

satisfaction (ETS) for e-loyalty (EL) is 0.510 which means it has a positive and significant

influence with a t-statistic value of 6.213 greater than t-table 1.96 and this result supports the

fifth hypothesis that is significant influence of E-trading Satisfaction on e-loyalty on the E-

trading of the Indonesia Stock Exchange.

The influence of e-trading satisfaction (ETS) on e-loyalty (EL) through e-trust (ET) as

indicated by the indirect parameter coefficient of 0.134 (0.439x0.306) which means that

indirectly e-trading satisfaction through e-trust has the positive influence on e-loyalty, and this

result supports the sixth hypothesis of this study which is that there is a significant effect of E-

trading Satisfaction through e-trust on e-loyalty in the E-trading of the Indonesia Stock

Exchange.

e-trust (ET)

The size of the parameter coefficient for e-trust (ET) variable is 0.306 which means there

is a positive influence between e-trust (ET) on e-loyalty (EL), or it can be said that e-trust

investors influence e-loyalty investors in e-trading of the Indonesia Stock Exchange is also

supported by t-statistic value of 3.622 and significant with a statistical t value greater than t-table

1.96 (3.622> 1.96), so that the seventh hypothesis is accepted i.e. there is a significant effect of

e-trust on e-loyalty on the Indonesia Stock Exchange E-trading.

Table 1 shows that the R-square value has a range between 0.59 to 0.67, this indicates

that the statistical model formed can explain the variables studied more than 59%, in other

words, these variables have an effect of 59%, and the rest is influenced by other variables outside

the model studied. Table 5.3 shows that the p-value obtained shows less than 0.001 and is

smaller than the value of α 0.05; it can be said that each variable has an influence on e-loyalty on

the Indonesia Stock Exchange.

The results of this study provide additional evidence and updates on previous studies. E-

loyalty in the e-trading of the Indonesia Stock Exchange can be influenced by financial

behaviour, e-trust, and e-trading satisfaction using e-trading. E-loyalty as the focus of the

successful use of e-trading used by the Indonesian stock exchange, because it is strongly

influenced by financial behaviour and investor satisfaction in the use of e-trading, so this study


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also supports the statement of Geyskens et al., (1996), Chen et al., (2014) and Christodoulides &

Michaelidou, (2011) where customer satisfaction is the primary key to the health of economic

performance and is an antecedent of trust.

This study also supports the results of research by Radionova-Girsa & Lahiža, (2017)

which states that e-trust has a significant influence on internet use except that the research

focuses on banking, while trust in the institution itself does not affect this is possible because

investors tend to be motivated differently when using e-trading exchanges. Investors have

expectations of the results of their investments in the future, so this thinking will make investors

focus on the type of investment chosen, further encouraging investors to focus on the e-trading

exchange.

This study also supports the research of Ricciardi & Simon, (2000) that finance behaviour

is involved in any activity related to investment decisions or the media used by investments

where the easier it is to obtain information for decision making it will affect investor satisfaction

in using e-trading further influence in trusting the use of e-trading exchanges.

Conclusion and Implication

This research focuses on current technological developments that have increasingly advanced

and influence user behavior, especially financial behavior. Technology that increasingly demands

users to be closer to e-commerce and to make it easier to interact with other users. This study aims to

examine the behaviour of financial behaviour in terms of satisfaction, trust and loyalty in the use of e-

trading in the Indonesian stock exchange using data from 1000 respondents of the Indonesia Stock

Exchange investors that currently active as traders. The variables used are financial behaviour, e-trust,

e-trading satisfaction, and e-loyalty. The results and conclusions obtained are financial behaviour

variables, e-trust, e-trading satisfaction has a significant effect on the creation of e-loyalty e-trading

users of the Indonesia Stock Exchange.

The results of this study provide additional evidence and updates on research on e-loyalty

using e-trading. Investors have considered the convenience and reliability of internet media and e-

trading in making investment decisions so that they can lead to loyalty (e-loyalty). Investors who

understand the investment climate in Indonesia, especially the capital market, will be facilitated in

making decisions and can make good decisions in addition to the availability of information also have

an essential role in the decision-making process.

Suggestions that can be given related to this research are the existence of updates in

methods, data, variables and can more specifically see the scope of the type of investment so

that further research can contribute differently to research specifically related to behavioural


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economics, so that similar research can be developed and able to reduce limitations in this study

to produce more comprehensive analysis related to the creation of trust and loyalty. The use of

other approaches is also suggested in the effort to develop this research so that more renewable

research is achieved which can overcome the limitations that exist.

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The relationship of GCG, company size, liquidity, capital structure, and profitability with

SEM-PLS

Moch Bisyri Effendi

STIE Perbanas Surabaya

Jl. Nginden Semolo No. 34-36, 60118,

Surabaya, Indonesia

Abstract

This study aims to investigate the patterns of relationship among GCG, company size, liquidity,

capital structure and profitability. Profitability is measured by ROA (Return on Assets), ROE

(Return on Equity) and NPM (Net Profit Margin). Capital structure is measured by DER (Debt to

Equity Ratio), DAR (Debt to Asset Ratio) and LTD (Long Term Debt). Liquidity is measured by

CR (Current Ratio), QR (Quick Ratio) and CTR (Cash Turnover Ratio). The size of the company

is measured by ln (total of assets) and Ln (total of sales). Good Corporate Governance (GCG) is

measured by corporate governance disclosure index (CGDI). The sample method was used a

purposive sampling technique. The Partial Least Square (PLS) method was used to analyze the

data. The results of this study indicate that in the GCG variable there is no Confirmatory Factor

Analysis because GCG is measured by one indicator. The results of this study indicate that in the

GCG variable there is no Confirmatory Factor Analysis because GCG is measured by one

indicator. The results of the Confirmatory Factor Analysis on liquidity variables, company size

and profitability indicate that each indicator is able to measure well the variables measured (valid

and reliable). Hypothesis test results show that the relationship of influence between significant

variables namely, GCG on capital structure (H1 is accepted), firm size on capital structure (H2 is

accepted) and liquidity on capital structure (H3 is accepted) and capital structure on profitability

(H4 is accepted). The results of the coefficient of determination indicate that the effect of

liquidity, firm size and GCG on the capital structure is quite strong. Subsequent research can use

other companies so that it can be a comparison to other company sector conditions and can

review the mediation of capital structures on the relationship of liquidity, GCG and company

size to profitability.

Keywords: GCG, Company Size, Liquidity, Capital Structure, Profitability


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Introduction

A company always needs capital both for business opening and business development.

Capital or funding has various problems, one of the funding problems is how much the

company's ability to meet the funding needs that will be used to operate and develop its business.

Brigham and Houston (2011) state that developing companies need capital that can come from

debt or equity. According to Keown (2010) companies must understand the main components of

the capital structure. The optimal capital structure is the capital structure of the company that will

maximize its stock price. Too much debt can hamper the development of the company, which

will also make shareholders think twice about continuing to invest their capital.

Own capital structure is the proportion of use between debt and equity. Management as a

company manager must certainly be able to balance the use of debt and equity to achieve an

optimal capital structure. In realizing optimal capital structure, financial managers must consider

many things that affect the capital structure. Several factors that influence the capital structure

include company size, liquidity, profitability, and asset structure. This study uses multiple linear

regression models with manufacturing companies listed on the Indonesia Stock Exchange as the

object of research.

At this time the business world is experiencing increasingly intense business

competition between companies, therefore every company must be able to perform important

functions that exist in the company such as marketing functions, sales functions, financial

functions, personnel functions, production functions and accounting functions effective and

efficient, so the company can be superior in the competition faced. This is done to achieve the

company's goals which are basically maximizing the welfare of shareholders through investment,

funding and dividend decisions or policies.

In implementing these functions, the aspects that need to be considered are the aspects of

funding. The funding source can come from the company's internal self, namely by using

retained earnings, issuing shares or originating from external companies, one of which is through

debt policy. This policy is very closely related to the company's capital structure. According to

Sartono (2001), what is meant by capital structure is the balance of the amount of permanent

short-term debt, long-term debt, preferred stock and ordinary shares. Companies are required to

carry out appropriate funding strategies in determining the most optimal capital structure, a

condition where companies can use an ideal combination between debt and company capital by

calculating the cost of capital that appears. The optimal capital structure of the company the cost

of capital to be borne will also be smaller.

The company's capital structure is influenced by many factors. From several previous

studies, there are several factors that influence the capital structure, including profitability,


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business risk, insider ownership, growth opportunity, company size, asset structure, liquidity and

so on. Supporting theories about capital structure include agency theory, trade off theory, and

pecking order theory. The variables used in this study are company size, profitability, asset

structure, and liquidity which are tested for their effect on capital structure.

Company size describes the size of a company. Large companies will easily diversify

and tend to have a smaller bankruptcy rate. In large companies with a lot of assets, many would

be more courageous to use capital from loans in buying all assets, compared to companies that

are smaller in size.

Corporate governance is very influential with the acquisition of company capital. If the

corporate governance is good, the capital that will be obtained automatically will be very

optimal. Not only that, good corporate governance can improve the economic stability of the

company itself. Everything can run smoothly if the corporate governance is successful.

Corporate governance also has a major influence on sustainable development and economic

growth, which specifically adds strength from the corporate sector and understands more ability

to attract capital to lubricate the economy (Shleifer and Vishny, 1997)

Liquidity is how much the company's ability to fulfill its short-term obligations.

Liquidity is one of them measured by the debt ratio which is a ratio that measures the percentage

of capital requirements spent with debt (Brigham and Houston, 2006). In accordance with the

pecking order theory, companies will prioritize using internal funds. Companies with high

liquidity will reduce their external funding because the source of internal funds is high.

Profitability is the company's revenue which has been reduced by costs. According to Gitman

(2003), profitability is the relationship between income and costs generated by using company

assets, both smoothly and permanently, in production activities. The company wants a high level

of profitability. From the existing profit the company can allocate it into retained earnings or

business expansion. In accordance with the Pecking order theory, companies that have high

profitability will tend to use funding through internal sources, namely using profits, the higher

the company's profitability, the smaller the proportion of debt usage.

Research on factors that influence capital structure has been done a lot before. Research

conducted by Wimelda and Marlinah (2013) and Adiyana's research (2014), suggested the results

that company size had a positive and significant effect on capital structure. Firnanti (2011)

examines the factors that influence the capital structure which results in the conclusion that

profitability has a negative influence on capital structure. Other research conducted by Liwang

(2011) which proves that asset structure variables have a positive and significant effect on capital

structure, whereas research conducted by Hadianto (2010), shows the results that the asset

structure has a negative and significant effect on capital structure. In the study of Dwilestari

(2010) concluded that liquidity has a negative effect on capital structure.


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Manufacturing companies are used in this study because the company is a company

with a large scale of production or has a large trading volume and requires large capital or funds

to develop its products so that it will affect the capital structure or funding of a company. From

the background above and the inconsistent results from previous studies, the authors are

interested in re-examining these variables with the title of research: Influence of Company Size,

Liquidity, Profitability, and GCG on Capital Structure in Registered Manufacturing Companies

on the Indonesia Stock Exchange.

Literature Review

Liquidity to Capital Structure

Liquidity is a ratio used to measure a company's ability to pay short-term obligations

(Van Horne and Wachowicz, 2007). According to the Pecking order theory, companies that have

high liquidity will tend not to use debt financing because they have large funds for internal

funding. The use of alternative funding starts from the least risky securities, namely retained

earnings, debt, and the issuance of new shares. Retained earnings are reinvested in the hope of

increasing corporate profits in the coming year. Ozkan (2016) says that companies with large

liquid assets can use these assets to invest.

A high asset liquidity ratio can be considered by investors to be a positive signal

because it indicates that the company can fulfill its current obligations and is faced with a low

risk of bankruptcy. With large retained earnings, companies will prefer to use retained earnings

for company operations before using debt or issuing new shares.

Profits that are not distributed as dividends will be used for expansion which usually

means the purchase of assets. This is in accordance with the pecking order theory which says that

managers prefer to use financing with the first order retained earnings, then debt and the last sale

of new shares. Another consideration is that the direct costs of financing from within are those

that are detained cheaper than the cost of capital originating from the issuance of new shares

(Dermawan Sjahrial, 2008). Companies that have high liquidity means they have the ability to

pay debts. From this explanation, it can be concluded that Liquidity has a negative effect on

Capital Structure.

H1 : Liquidity to Capital Structure


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GCG to Capital Structure

According to Law No. 40 of 2007 concerning the company, in general the director has

the task of leading the company by issuing company policies, selecting, stipulating, supervising

the duties of employees and section heads (managers), approving the company's annual budget,

submitting reports to shareholders on the company's performance. The company will choose a

funding policy through debt because it has a lower risk of the company than issuing shares and to

prevent moral hazard. Research conducted by Serghiescu (2014) concluded that the size of the

board of directors influences the capital structure

An independent commissioner is a person appointed based on a GMS decision from an

unaffiliated party with a major shareholder, member of the board of directors and / or other

members of the board of commissioners. An independent commissioner is an outside company

that assesses the performance of the company and makes decisions for the progress of the

company, not for personal or group interests. The stronger the independent commissioner, the

greater the funding of capital, because it affects the decisions taken. Companies will choose debt

to be used as a source of funding for company capital because they have a smaller risk and to

prevent the occurrence of moral hazard. In addition, independent commissioners also consider if

issuing shares, the interests of shareholders will increase. The independent commissioner will

provide the best advice and policies for the company such as the selection of capital.

Managerial ownership is share ownership by company management. Agency problems

will decrease because they are in harmony between the interests of shareholders and company

management. Managers have a large amount of information because they are within the

operational scope. The manager wants profits for the company as the manager itself and profits

as shareholders. Managers will choose debt to be used as a source of capital funding because it

has a smaller company risk and benefits managers as shareholders who are seen based on the

value of share ownership that is not reduced. The research conducted by Ismiyati (2004)

concluded that managerial ownership influences the capital structure. Based on this, the

hypothesis proposed is as follows:

H2 : GCG to Capital Structure

Company Size to Capital Structure

Companies that experience high growth will need large capital. This is because large

companies have large funding needs and one alternative is to use funds from external funds. On

the contrary, the company in low sales growth, the need for capital is also small.

According to Mas'ud (2008) the larger the size of the company that is indicated by total

assets, the company will use large amounts of debt as well. The larger the size of the company

indicates that the company has a higher number of assets. Companies that are relatively large in


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size will tend to use increasingly large external funds. This is because the funding needs also

increase along with the growth of the company. In addition to internal funding, the next

alternative is external funding. This is in line with the pecking order theory which states that, if

the use of internal funds is insufficient, the second alternative is to use debt. The results of this

study are supported by Seftianne and Handayani (2011), Verena and Mulyo (2013) indicating the

size of the company influences the capital structure. Different results from the Firnanti (2011)

study show that the size does not affect the capital structure. Based on this, the hypothesis

proposed is as follows:

H3 : Company Size to Capital Structure

Capital Structure To Profitability

Profitability is the level of net profit that the company can achieve when carrying out

its operations. Profitability reflects the company's ability to generate profits on the management

of company assets which is a comparison between earnings after tax and total assets. Profitability

can be interpreted as a return on capital investment. Companies with high rate of return tend to

use relatively small debt proportions. Because with a high rate of return, funding needs can be

obtained from retained earnings. Companies with high profitability will have more internal funds

than companies with low profitability. The higher profitability shows that the profits obtained by

the company are also high. If the company's profits are high, the company has a substantial

source of funds from within, so the company requires less debt. Besides that, if retained earnings

increase, the debt ratio will naturally decrease, assuming that the company does not add debt.

Therefore, profitability has a negative effect on capital structure. The results of this study are

supported by Verena and Mulyo (2013), Seftiane and Handayani (2011).

H4 : Profitability affects the capital structure

Research Methodology

This research uses quantitative research methods, which means that the study analyzes

data in the form of numbers or statistics with the aim of testing the predetermined hypotheses.

The population used in this study is a manufacturing company listed on the Stock Exchange in

the period 2015 - 2017 .. The selection of samples in this study using purposive sampling

technique. The data collection technique used in this study is documentation. The variables used

in this research consist of 2 variables, namely, endogenous variables and exogenous variables.

The endogenous variable in this study is Profitability measured using ROA (Return on Assets),

ROE (Return on Equity) and NPM (Net Profit Margin). While intervening endogenous variables

in this study are capital structures measured using DER (Debt to Equity Ratio), DAR (Debt to


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Asset Ratio) and LTD (Long Term Debt). The Exogenous variable in this study consisted of

Liquidity, GCG and Company Size. Liquidity is measured using CR (Current Ratio), QR (Quick

Ratio) and CTR (Cash Turnover Ratio). The size of the company is measured using ln (total

assets) and Ln (total sales). Good corporate governance (GCG) is measured using corporate

governance disclosure criteria in the company's annual report. This determination of disclosure

index is based on information disclosed by the company in their annual report to stakeholders.

The disclosure items used in this study are based on the Decree of the Chairperson of Bapepam

and LK Number: Kep-134 / BL / 2006 concerning the Obligation to Submit Annual Reports to

Issuers and Public Companies. So, in this study, there were 26 items of corporate governance

disclosure. The method used to assess corporate governance disclosure index (CGDI) is the value

of 1 for items that are disclosed and the value of 0 for items that are not disclosed.

The data analysis technique used in this study is the Partial Least Square (PLS) method.

Partial Least Square is a model of Structural Equation Modeling (SEM) based on variance or

component. Testing using the PLS method basically consists of 2 types of testing, namely the

measurement model (outer model) and structural models (inner models). Outer models used in

this study used the confirmatory factor analysis (CFA) method to measure validity and reliability

provided that the value of loading factors above 0.4 provided the AVE value> 0.5 and the

composite reability value> 0.7. The inner model in this study is used to see the significance of

the path between latent variables and answer the research hypothesis by looking at statistical

values. A path coefficient is said to be significant if the Tstatistic value is> 1.96 or the

significance value / pvalue <0.05 with an error tolerance of 5%.

Analysis and Discussion

SEM-PLS analysis in this study is divided into 2 stages, namely, Outer model and inner

model. Outer model is used to see the relationship between indicators to latent variables,

indicators are able to measure variables well if criteria of validity and reliability are met while

Inner model is used to see the relationship between latent variables.

Outer Models

Outer models in this study used the Confirmatory Factor Analysis method.

Confirmatory Factor Analysis is used in latent variables that are reflective and have more than

one indicator. Confirmatory Factor Analysis is divided into 2 stages, namely validity and

reliability. The validity criteria are fulfilled if the loading value is more than 0.4 and the value of

Average Variance Extracted (AVE) is more than 0.5 while the reliability criteria are fulfilled if

the composite reliability value is more than 0.7


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Table 1. Nilai Factor Loading

Variabel Laten Indicator Factor

Loading AVE CR

GCG (Good

Corporate

Governance)

Corporate Governance

Disclosure Index (CGDI) 1 1 1

Capital Structure

DER (Debt to Equity

Ratio), 0.876

0,675

DAR (Debt to Asset Ratio) 0.776 0.787

LTD (Long Term Debt) 0.812

Liquidty

CR (Current Ratio), 0.678

0,578

QR (Quick Ratio) 0.775 0.840

CTR (Cash Turnover

Ratio) 0.756

Profitability

ROA (Return on Asset) 0.786

0.654 0.761 ROE (Return on Ekuitas) 0.886

NPM (Net Profit Margin). 0.790

Table 1 informs that all values of the indicator loading factors of lGCG variables,

liquidity, capital structure and profitability are greater than 0.4 with AVE values> 0.5. so that it

can be concluded that each valid indicator measures its latent variables and criteria for the

validity of an indicator against its latent variables. Table 1 shows that all composite reliability

values of more than 0.7 percent indicate that reliable indicators measure their latent variables and

criteria for the reliability of an indicator against its latent variables are met. The results of

validity and reliability above can be concluded that each indicator can measure its latent

variables well. Next, an inner model analysis will be carried out to determine the significance of

each path between the latent variables of the fund to answer the research hypothesis

Inner Model

The inner model describes the relationship between latent variables. Inner model is

divided into 2 stages, namely hypothesis testing and coefficient of determination. In the

hypothesis test, the relationship of the variable is said to be significant if the value of P value <α

= 0.05 while the coefficient of determination is divided into three criteria, namely, the influence

between latent variables is strong if the R2> 0.67, moderate if the value is 0.33 <R2 ≤ 0.67 ,

weak if the value is 0.19 <R2 ≤ 0.33 and is very weak if the value of R2 is ≤ 0.19. The results of

the SEM-PLS using Warp-PLS are as follows:


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Figure 2. Boostraping SEM-PLS

Table 2. Path Coefficient & P Values

Path

Coeicient

P values Infromation

GCG → Capital Structure 0.375 < 0.001 Significant

Company Size → Capital

Structure

0.206 0.011 Significant

Liquidity → Capital Structure 0.350 < 0.001 Significant

GCG → Profitability 0.162 0.038 Significant

Company Size →

Profitability

0.311 < 0.001 Significant

Liqudity → Profitability 0.160 0.039 Significant

Capital Structure →

Profitability

0.366 < 0.001 Significant

H1 : GCG to Capital Structure

The results of testing the first hypothesis indicate that the relationship between the

variables of Good Corporate Governance (GCG) and capital structure shows the path coefficient

value of 0.375 with P value = <0.001 smaller than α = 0.05. These results indicate that Good

Corporate Governance significantly influences the capital structure (Hypothesis 1 is accepted)

and the relationship of Good Corporate Governance to a positive capital structure which means

that any change in improvement in Good Corporate Governance will affect changes in the

increase in capital structure and vice versa.

According to Law No. 40 of 2007 concerning the company, in general the director has

the task of leading the company by issuing company policies, selecting, stipulating, supervising


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the duties of employees and section heads (managers), approving the company's annual budget,

submitting reports to shareholders on the company's performance. The company will choose a

funding policy through debt because it has a lower risk of the company than issuing shares and to

prevent moral hazard. Research conducted by Serghiescu (2014) concluded that the size of the

board of directors influences the capital structure.

An independent commissioner is a person appointed based on a GMS decision from an

unaffiliated party with a major shareholder, member of the board of directors and / or other

members of the board of commissioners. An independent commissioner is an outside company

that assesses the performance of the company and makes decisions for the progress of the

company, not for personal or group interests. The stronger the independent commissioner, the

greater the funding of capital, because it affects the decisions taken. Companies will choose debt

to be used as a source of funding for company capital because they have a smaller risk and to

prevent the occurrence of moral hazzard. In addition, independent commissioners also consider if

issuing shares, the interests of shareholders will increase. The independent commissioner will

provide the best advice and policies for the company such as the selection of capital.

Managerial ownership is share ownership by company management. Agency problems

will decrease because they are in harmony between the interests of shareholders and company

management. Managers have a large amount of information because they are within the

operational scope. The manager wants profits for the company as the manager itself and profits

as shareholders. Managers will choose debt to be used as a source of capital funding because it

has a smaller company risk and benefits managers as shareholders who are seen based on the

value of share ownership that is not reduced. The research conducted by Ismiyati (2004)

concluded that managerial ownership influences the capital structure

H2 : Company size of capital structure

The results of testing the second hypothesis indicate that the relationship of variables

The size of the company influences the capital structure shows the path coefficient value of

0.206 with a value of 0.011 smaller than α = 0.05. These results indicate that the size of the

company has a significant effect on capital structure (Hypothesis 2 is accepted) and the

relationship of firm size to positive capital structure which means that any change in the increase

in company size will affect changes in the increase in capital structure and vice versa.

Companies that experience high growth will need large capital. This is because large

companies have large funding needs and one alternative is to use funds from external funds. On

the contrary, the company in low sales growth, the need for capital is also small.


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According to Mas'ud (2008) the larger the size of the company that is indicated by total

assets, the company will use large amounts of debt as well. The larger the size of the company

indicates that the company has a higher number of assets. Companies that are relatively large in

size will tend to use increasingly large external funds. This is because the funding needs also

increase along with the growth of the company. In addition to internal funding, the next

alternative is external funding. This is in line with the pecking order theory which states that, if

the use of internal funds is insufficient, the second alternative is to use debt. The results of this

study are supported by Seftianne and Handayani (2011), Verena and Mulyo (2013) indicating the

size of the company influences the capital structure. Different results from the Firnanti (2011)

study show that the size does not affect the capital structure.

H3 : Liquidity to apital Structure

The results of testing the third hypothesis show that the relationship of variable

liquidity with capital structure shows the path coefficient value of 0.350 with P value <0.001

smaller than α = 0.05. These results indicate that liquidity is significantly to the capital structure

(Hypothesis 3 is accepted) and the relationship of liquidity to a positive capital structure which

means that any change in the increase in liquidity will affect changes in the increase in capital

structure and vice versa.

Liquidity is a ratio used to measure a company's ability to pay short-term obligations

(Van Horne and Wachowicz, 2007). According to the Pecking order theory, companies that have

high liquidity will tend not to use debt financing because they have large funds for internal

funding. The use of alternative funding starts from the least risky securities, namely retained

earnings, debt, and the issuance of new shares. Retained earnings are reinvested in the hope of

increasing corporate profits in the coming year. Ozkan (2016) says that companies with large

liquid assets can use these assets to invest.

A high asset liquidity ratio can be considered by investors to be a positive signal

because it indicates that the company can fulfill its current obligations and is faced with a low

risk of bankruptcy. With large retained earnings, companies will prefer to use retained earnings

for company operations before using debt or issuing new shares.

Profits that are not distributed as dividends will be used for expansion which usually

means the purchase of assets. This is in accordance with the pecking order theory which says that

managers prefer to use financing with the first order retained earnings, then debt and the last sale

of new shares. Another consideration is that the direct costs of financing from within are those

that are detained cheaper than the cost of capital originating from the issuance of new shares

(Dermawan Sjahrial, 2008). Companies that have high liquidity means they have the ability to

pay debts.


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H4 : Capital Structure to Profitability

The results of testing the third hypothesis indicate that the relationship of capital

structure variables with profitability shows the path coefficient value of 0.366 with P value

<0.001 smaller than α = 0.05. These results indicate that the capital structure has a significant

effect on profitability (Hypothesis 4 is accepted) and the relationship of capital structure to

positive profitability, which means that any changes in the increase in capital structure will affect

changes in increased profitability and vice versa.

Profitability is the level of net profit that the company can achieve when carrying out

its operations. Profitability reflects the company's ability to generate profits on the management

of company assets which is a comparison between earnings after tax and total assets. Profitability

can be interpreted as a return on capital investment. Companies with high rate of return tend to

use relatively small debt proportions. Because with a high rate of return, funding needs can be

obtained from retained earnings. Companies with high profitability will have more internal funds

than companies with low profitability. The higher profitability shows that the profits obtained by

the company are also high. If the company's profits are high, the company has a substantial

source of funds from within, so the company requires less debt. Besides that, if retained earnings

increase, the debt ratio will naturally decrease, assuming that the company does not add debt.

Conclusions and Suggestions

The results of this study indicate that in the GCG variable there is no Confirmatory

Factor Analysis because GCG is measured by one indicator. The results of the Confirmatory

Factor Analysis on liquidity variables, company size and profitability indicate that each indicator

is able to measure well the variables measured (valid and reliable). Hypothesis test results show

that the relationship of influence between significant variables namely, GCG on capital structure

(H1 is accepted), firm size on capital structure (H2 accepted) and liquidity on capital structure

(H3 accepted) and capital structure on profitability (H4 accepted). The results of the coefficient

of determination indicate that the effect of liquidity, firm size and GCG on the capital structure is

quite strong. Subsequent research can use other companies so that it can be a comparison to other

company sector conditions and can review the mediation of capital structures on the relationship

of liquidity, GCG and company size to profitability.


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Firnanti, F (2011). Factors Affecting the Capital Structure of Manufacturing Companies in the

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Seftianne & Handayani, R. (2011). Factors Affecting Capital Structure in Public Manufacturing

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The factors that influence financial distress of Indonesia manufacturing company

Ulum and Nugroho Jati

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Achmad Saiful Ulum and Agustinus Kismet Nugroho Jati

STIE Perbanas Surabaya

Jl. NgindenSemolo No. 34-36, 60118,

Surabaya, Indonesia

Abstract

This research is a quantitative research to determine which independent variables are the most

significant influential in determining the condition of financial distress in the manufacturing

company. The sample of this study is the Manufacturing Industry listed on the Indonesia Stock

Exchange in the period of 2012-2016. The sampling technique was purposive sampling

technique, which is selecting samples based on predetermined criteria. The variables that will be

observed by researchers in examining the effect of financial ratios to predict financial distress

conditions in manufacturing companies are the dependent variables, namely financial distress

(Y) and independent variables, that is liquidity (X1), leverage (X2), Firm Size (X4), Profitability

(X6), Managerial Ownership (X7), Institutional Ownership (X8). The results showed that the

logistic regression conformity test was significant. This indicates that logistic regression is able

to predict the company's financial distress in the study period. Hypothesis test results show that

the variables that influence the company's financial distress are leverage, profitability and

institutional. While variables that do not affect the company's financial distress are liquidity, firm

size and managerial ownership. The results showed that the logistic regression conformity test

was significant, this indicates that logistic regression is able to predict the company's financial

distress in the study period. Hypothesis test results show that the variables that influence the

company's financial distress are leverage, profitability and institutional. while variables that do

not affect the company's financial distress are liquidity, firm size and k. managerial. The results

of the accuracy of the model calcification amounted to 76.4%, this indicates that the model can

precisely predict the manufacturing distress of the manufacturing company in the study period of

76.4% or 422 of the 552 observational data. Furthermore, it can add independent variable

variables that are considered capable of predicting company financial distress and also use other

statistical analysis methods that allow more accurate predictions of corporate financial distress

Keywords: Financial Distress, Manufacturing, Logistic Regression



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INTRODUCTION

At present conditions economic and business developments are characterized by high

levels of competition. In this case, the manager or executive must understand and predict the

condition of the company in the future. It is intended that the company can survive in the long

term and avoid bankruptcy. Some companies that have operated within a certain period of time

often experience bankruptcy due to financial difficulties.

The phenomenon that occurred in Indonesia especially in manufacturing companies in

2015 there were 2 companies that experienced delisting including the PT. Davomas Abadi, Tbk

(DAVO), and PT. Unitex, Tbk (UNTX). In 2017 there is 1 delisting manufacturing company

namely PT. Sorini Agro Asia Corporindo, Tbk (SOBI). PT. Davomas Abadi, Tbk (DAVO) is a

company engaged in cocoa producers who entered the food and beverage sector officially

resigned from the Indonesia Stock Exchange in January 2015. The company resigned because it

was considered to worry about its financial condition. The last few years in the company's

financial statements recorded in the balance sheet show that the equity value is negative, this is

due to an operational loss that has an impact on the company's dividend distribution which will

later be received by the shareholders. In this case it shows that the condition of the company is

experiencing financial difficulties so that later it will impact bankruptcy With the existence of a

company that is delisted from the exchange, it is important for a manager to predict the condition

of financial difficulties which can be known by the company's financial decline in paying off its

obligations prior to liquidation (Widarjo & Setiawan, 2009). According to Rodoni and Ali (2010:

176) to find out the financial condition of the company there are three interrelated conditions as

the cause of financial difficulties, namely insufficient capital, large debt costs and interest, and

suffer losses.

Predicting the condition of financial difficulties of a company can be known by

analyzing financial statements using financial ratios. Financial ratios are a form of financial

statements that describe the company's performance. In this case the financial statements can

provide information and prospects for the company's condition in the future. Based on signaling

theory, if the results of financial statement analysis show good financial performance of the

company, then the company can provide a good signal to external parties such as investors and

creditors.

Widarjo & Setiawan (2009) there are two reasons for conducting research on financial

distress prediction in companies, the first is to examine the relationship and influence between

financial factor variables and measurement of failure or bankruptcy, while the second is to

develop models in forecasting or bankruptcy predictions.



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Rahayu & Winarti (2016) the development of financial security models is important to

do because the signs of a company before going bankrupt will surely experience financial

difficulties. In this case financial difficulties must be predicted from the start by taking action to

anticipate the occurrence of bankruptcy. In detecting financial difficulties, namely by using a

particular model which of the detection models can help investors or creditors in determining

investment decisions.

According to Lin, Liang and Chen (2011) Factors that influence the prediction of

Financial Distress are the variables used. With the many differences in predictor variables tersut

it will give different results. Most of the studies that predict Financial Distress use more financial

variables, but there are several non-financial variables that can also provide influence in

providing research results.

Most of the research on Financial Distress uses financial ratio variables obtained from the

company's financial statements per year. According to Sun, He and Li (2011) a relatively long

period is to predict within a period of one year, while predictions made less than one year or

shorter are still a small part done. Previous research according to Umi Zhahratun, Budi, and

Stefanus (2013) in the study entitled Financial Distress prediction models in Go Public

manufacturing companies in Indonesia that use financial variables, non-financial variables, and

macroeconomic variables with SVM and LDA processing techniques that result in variable

which significantly affects financial difficulties are financial and non-financial variables while

macroeconomic variables do not contribute.

LITERATURE REVIEW

Financial Distress

Part of a financial reporting process is the definition of financial statements according

to SAK No.1. All transactions that occur during one period will be recorded and reported, so that

functionally, financial statements are one of the media of communication to the parties who have

interests in the company that contain financial information of the company. Financial statements

are important for stakeholders, including investors, including knowing the health of the company

or predicting financial difficulties using financial ratios.

Much of the research that has been done relates to the health of the company and

financial difficulties. The ability of a company to operate its business will be reflected through

the health of the company itself, besides that it can also see the potential for bankruptcy. The



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potential for bankruptcy arises due to financial difficulties which if left untreated will lead to

bankruptcy.

Agency Theory

Issues of interest arise because of differences in interests that arise between

management and the owners of capital. In the perspective of agency theory, management should

have an interest in prospering the owner because management is an agent of the owner, but

because of the risks that must be borne by management, they will also consider their importance

in decision making (Hardiningsih and Meita, 2012).

Managers have different personal goals and compete with the company's goals of

maximizing the prosperity of shareholders (Brigham and Houston, 2006). Company owners give

managers the power to make a decision. This actually creates a potential conflict of interest

called agency theory. Brigham and Houston (2006) state that agency problems arise when

company managers have less than 100% of the company's shares.

Liquidity with Financial Distress

Liquidity is the ability of a company to pay off its short-term obligations. Research

conducted by Almilia and Kritijadi (2003), shows that the more liquid a company is, the more

probabilities the company will avoid financial distress.

H1 : Liquidity has a negative effect on financial distress

Financial Leverage with Financial Distress

In practice, the source of corporate funding is divided into two, debt capital (debt

capital) and own capital (equity capital) (Gitman, 2000). Funding needs to run company

activities are carried out with a variety of reasons, one of which is due to non-fulfillment of the

needs of funds originating from internal companies in the form of retained earnings

The form of funding from debt certainly has costs in the form of loan interest. The

bigger the debt, the higher the loan interest or interest expense. Based on research conducted by

Seoki et al (2010), it shows that the higher the level of leverage of the company, the higher the

probability of companies experiencing financial distress.

H2: Financial leverage has a positive effect on financial distress

Firm Size to Financial Distress

Company size is a description of the size of a company (Brigham and Houston, 2011).

Large companies tend to have better ability to maintain their level of liquidity because assets



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owned can be used as collateral. Besides that, companies that have large total assets will easily

diversify so that the probability of companies going bankrupt will be smaller.

H3 : Company size has a negative effect on financial distress

Profitability with Financial Distress

Profitability provides a measure of the level of management effectiveness of a

company, because it shows the ability of profits generated from sales and investment income

(Kasmir, 2012: 197). There are several ratios used to measure profitability, among others, profit

margin on sales, return on total assets, basic earnings power, and return on equity. Research

conducted by Andre (2009) states that the level of profitability has a significant effect on

financial distress. Hapsari's research (2012) shows that profitability has a negative and

significant effect on financial distress. The same thing was also revealed in the results of research

by Widarjo and Doddy (2009).

H4 : Profitability has a negative effect on financial distress

Managerial Ownership with Financial Distress

Managerial ownership is the company's share ownership by the management of the

company (Hartaro and Atahau, 2007). Sujoko and Soebiantoro (2007) revealed that managerial

ownership is the ownership of the company's shares by management which is measured in the

percentage of the number of shares held.

Emiraldi (2007) states that the greater the number of managerial ownership, the greater

the probability of decreasing financial distress potential. In other words, the more the percentage

of share ownership by management will reduce the potential for financial distress.

H5 : Managerial ownership has a negative effect on financial distress

Institutional Ownership with Financial Distress

A high level of ownership by institutions in a company will lead to greater oversight

efforts. This great supervision will directly or indirectly oversee the manager's performance from

decisions that are not in accordance with the interests of the company, in this case the owners of

the company.

Supervision carried out on the management side in carrying out the company's

operations will create opportunities for smaller financial distress (Parulian, 2007). This is also

supported by research conducted by Emiraldi (2007) which states that institutional ownership has

a negative influence on financial distress.

H6 : Institutional ownership has a negative effect on financial distress



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RESEARCH METHODOLOGY

This research is a type of quantitative research to determine which independent variables are the

most significant influential in determining the condition of financial distress in the company.

This research was conducted on the Manufacturing Industry listed on the Indonesia Stock

Exchange in the period 2012-2016. The object of this research is financial distress. The

population in this study are companies in the manufacturing industry listed on the Indonesia

Stock Exchange in the period 2012-2016. The annual financial statements and summary of

company performance in the period 2012-2016 are used for the calculation of the dependent

variable as a determinant of financial distress. The sampling technique in this study used

purposive sampling technique, namely by selecting samples based on predetermined criteria.

The following are the criteria determined by the researcher for sampling:

1. Companies in manufacturing industries that have been listed on the Indonesia Stock

Exchange in the period 2012-2016

2. Has published annual financial reports and annual reports that are complete in accordance

with the needs of researchers relating to financial ratios with financial statements ending on

31 December and the number of institutional ownership and managerial ownership.

3. Companies included in the manufacturing industry listed on the Indonesia Stock Exchange

in 2012-2016 which presented their financial statements in rupiah.

The variables that will be observed by researchers in examining the effect of financial ratios to

predict financial distress conditions in manufacturing companies are the dependent variables

namely financial distress (Y) and independent variables namely liquidity (X1), Laverage (X2),

Firm Size (X4), Profitability (X6), Managerial Ownership (X7), Institutional Ownership (X8)

Financial Distress

Financial distress is a condition faced by a company if the company experiences

financial difficulties in fulfilling its obligations, which causes the company to suffer losses

continuously. In this study the financial distress criteria are based on the argument that if the

company experiences losses for two consecutive years it shows that the company is not good

enough. If the company continues to leave these conditions without improvement, the impact

that must be received by the company is even worse (bankruptcy). The indicator used is pre-tax

profit, due to avoidance.

Liquidity



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The liquidity ratio can be used to measure a company’s ability to pay obligations. But

only within the scope of its short-term obligations. The liquidity ratio can be measured using

several measurement methods, but researchers in predicting the company’s financial distress are

more focused on measuring using the current ratio. The current ratio can explain the extent to

which current liabilities can be covered by current assets. Current ratio can be calculated using

the formula:

Current ratio = Current Assets

Current Debt

Profitability

Profitability Ratios can be used to measure a company's ability to generate profits or

profits in its operations such as in sales activities and so on. For research using profitability ratios

measured using Return on assets to determine asset turnover through sales volume.

Return on assets can be calculated using the formula:

Return on Asset = Net Income

TotalAssets

Good Corporate Governance

In this study Good Corporate Governance is measured using managerial ownership

and institutional ownership variables.

d.1. Managerial ownership

The ownership structure in this study was measured using a proxy used in Xuan-Quang and

Zhong-Xin (2013) studies. The way to measure it is as follows:

d.1. Kepemilikan manajerial (Managerial ownership)

MaOW =Total of Management′s Stock

Total of Stock

d.2. Institutional Ownership

The ownership structure in this study was measured using a proxy used in Xuan-Quang and

Zhong-Xin (2013) studies. The way to measure it is as follows:d.2. Institutional ownership

MaOW =Total of Institutional′s Stock

Total of Stock

Firm Size



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This activity ratio can measure how the company's activities so far include the activities

of companies in sales, purchases, and so on. In predicting financial distress conditions

researchers measure using activity ratios as measured by sales to total assets that can describe

total assets turnover seen from the volume of sales or describe the extent of the ability of all

assets to create sales.

Sales to total assets can be calculated using the formula:

Sales to total assets = Sales

total assets

ANALYSIS AND DISCUSSION

Compatibility Test of the Logistic Regression Model

Suitability test of logistic regression model to find out whether the model is feasible to

use and further analysis can be carried out. The compatibility test of the logistic regression model

consists of 3 tests namely the Hosmer and Lemeshow's test Goodness of Fit Test, the Omnibus

Test of Model Coefficient and -2 log likelihood.

Table 1. Uji -2 log likelihood.

Iteration

-2 Log

likelihoo

d

Coefficients

Const

ant

Likui

ditas

Lever

age

Firm

Size

Profitab

ility

K.

Manaje

rial

K.

Institusi

onal

Step

1

1 574.585 -

1.675

-.326 .424 -.055 .206 .048 -.149

2 569.092 -

2.120

-.388 .549 -.061 .285 .064 -.224

3 569.010 -

2.180

-.391 .565 -.060 .296 .065 -.237

4 569.010 -

2.181

-.391 .565 -.060 .296 .065 -.237

a. Method: Enter

b. Constant is included in the model.

c. Initial -2 Log Likelihood: 597.863

d. Estimation terminated at iteration number 4 because parameter estimates changed by less than

.001.



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The test results of the model suitability test with 2 log likelihood indicate that the

model is feasible to use which means that the model is able to predict the company's financial

distress. Test of suitability of the model can also be seen from the value of the omnibus test and

presented in the table as follows:

Table 4.2. Omnibus Tests of Model Coefficients

Chi-square df Sig.

Step 1 Step 28.854 6 .000

Block 28.854 6 .000

Model 28.854 6 .000

The omnibus test table informs that the significance value of the Omnibus test is less

than 0.05, this can be concluded that the model is feasible to use which means that the model is

able to predict the company's financial distress. Test the suitability of the model can also be seen

from the Hosmer and Lemeshow test and presented in the table as follows:

Table 4.3 Hosmer and Lemeshow Test

Step Chi-square df Sig.

1 11.525 8 .174

The Hosmer and lemeshow test tables inform that the significance value of the Hosmer

test and the free test test is more than 0.05, this can be concluded that the model is feasible to use

which means that the model is able to predict the company's financial distress

Hypothesis Testing

This test is used to determine the effect of independent variables on dependents by using

an error tolerance value of 5%. The research hypothesis is accepted if the independent variable

significance value is less than 0.05. The results of hypothesis testing using logistic regression are

presented in the table as follows:

Table 4.4. Hypothesis testing

B Sig. Exp(B) Keterangan

Step 1a Likuiditas -.391 .060 .677 Not Significant

Leverage .565 .003 1.759 Significant

Firm Size -.060 .348 .942 Not Significant



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Profitabilitas .296 .022 1.345 Significant

Manajerial. O .065 .309 1.067 Not Significant

Institusional.

O

-.237 .009 .789 Significant

Constant -2.181 .000 .113

H1 : Liquidity Influence on financial distress

Based on the results of the study, it shows that the current ratio has a regression

coefficient of -0,391 with a significance level of 0.060> 0.05, so that it can be concluded in this

study that liquidity does not significantly influence the Company's financial distress condition.

Furthermore, it can be concluded that H1 is rejected.

The liquidity ratio shows the company's ability to pay off its short-term debt /

liabilities. This ratio is calculated from working capital, namely current assets and current debt.

The liquidity ratio includes the current ratio, quick ratio and the ratio of cash to current assets.

Current ratio describes the ability of a company to pay off its short-term debt with current assets.

This ratio can be calculated by comparing between current assets divided by current debt. The

greater the value of the current ratio, the less likely the company to experience financial distress

because the company has a number of liquid assets such as cash or money used to pay off its

debt and finance its operational activities both in the transaction period and future period so that

the company does not experience financial difficulties or threatened the continuity of its

business.

The results of this study indicate that the current ratio does not have a significant effect

on financial distress. Based on the results of logistic regression and descriptive statistics of the

current ratio and financial distress, it shows that the current ratio tends to fluctuate while

financial distress increases. A high current ratio signifies the company's high ability to pay off its

current debt using its smooth assets. The results of this study are in line with the research

conducted by Hapsari (2012), Widarjo and Setiawan (2009), Mas'ud and Srengga (2012) and

Widhiari and Aryani (2015) which state that the current ratio does not significantly influence

financial distress. However, it is different from the research conducted by Istiantoro and

Indrawati (2015) and Ray (2011) which states that the current ratio has a significant effect on the

condition of financial distress.

H2 : Leverage Influence onfinancial distress

Based on the results of the study, it shows that the debt ratio has a regression

coefficient of 0.565 with a significance level of 0.003 <0.05, so it can be concluded in this study



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that leverage has a significant effect on predicting financial distress. Furthermore, it can be

concluded that H2 is accepted.

In practice, the source of corporate funding is divided into two, debt capital (debt

capital) and own capital (equity capital) (Gitman, 2000). Funding needs to run company

activities are carried out with a variety of reasons, one of which is the lack of fulfillment of funds

from internal companies in the form of retained earnings.

The form of funding from debt certainly has costs in the form of loan interest. The

bigger the debt, the higher the loan interest or interest expense. Based on the research conducted

by Seoki et al (2010), it shows that the higher the level of leverage of the company, the higher

the probability of companies experiencing financial distress

H3 : Firm Size Influence on financial distress

Based on the results of the study, it shows that Firm Size has a regression coefficient of

-0.060 with a significance level of 0348> 0.05, so that it can be concluded in this study that Firm

Size has no significant effect in predicting financial distress conditions. Furthermore, it can be

concluded that H3 is rejected.

Company size is a description of the size of a company (Brigham and Houston, 2011).

Large companies tend to have better ability to maintain their level of liquidity because assets

owned can be used as collateral. Besides that, companies that have large total assets will easily

diversify so that the probability of companies going bankrupt will be smaller.

H4 : Profitability Influence on financial distress

Based on the results of the study, it shows that Profitability has a regression coefficient

of 0.296 with a significance level of 0.022 <0.05, so that it can be concluded in this study that

Profitability has a significant effect in predicting financial distress conditions. Furthermore, it

can be concluded that H4 is accepted.

This profitability ratio shows the company's ability to generate profits. this ratio is also

often called the operating ratio. The profitability ratio is the profit margin, return on assets, return

on total assets and return on equity. The smaller the value of return on assets can be made

possible by the company's performance is less effective in processing assets owned to generate

profits so that it can cause losses that result in negative cash flow and the company will

experience financial distress if it occurs within a few years. This is due to an imbalance between

operating expenses and income generated

.



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The results of this study indicate that return on assets have a significant effect on

financial distress. Based on the results of logistic regression and descriptive statistics of return on

assets and financial distress, it shows that return on assets tends to decrease while financial

distress increases. Decreasing return on assets is due to the relatively small increase in net

income obtained by companies every year, not comparable to the relatively high number of

assets each year. The results of this study are in line with the research conducted by Hapsari

(2012), Widarjo and Setiawan (2009), Mas'ud and Srengga (2012), Ray (2011) and Gong, Bose

and Chen (2015) which state that return on assets has a significant effect towards financial

distress conditions. However, different from the research conducted by Istiantoro and Indrawati

(2015) which stated that return on assets did not significantly influence financial distress

conditions.

H5 Manjerial O Influence on financial distress

Based on the results of the study, it shows that K. Manjerial has a regression coefficient

of 0.065 with a significance level of 0.309> 0.05, so it can be concluded in this study that K.

Manjerial has no significant effect in predicting financial distress conditions. Furthermore, it can

be concluded that H5 is rejected

Managerial ownership is the company's share ownership by the management of the

company (Hartaro and Atahau, 2007). Sujoko and Soebiantoro (2007) revealed that managerial

ownership is the ownership of the company's shares by management which is measured in the

percentage of the number of shares held.

Emiraldi (2007) states that the greater the number of managerial ownership, the greater

the probability of decreasing financial distress potential. In other words, the more the percentage

of share ownership by management will reduce the potential for financial distress.

H6 : Institusional O. Influence on financial distress

Based on the results of the study, it shows that Institutional K. has a regression

coefficient of -0.237 with a significance level of 0.009 <0.05, so it can be concluded in this study

that Institutional K. has a significant effect in predicting financial distress conditions.

Furthermore, it can be concluded that H6 is accepted.

A high level of ownership by institutions in a company will lead to greater oversight

efforts. This great supervision will directly or indirectly oversee the manager's performance from

decisions that are not in accordance with the interests of the company, in this case the owners of

the company.



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Supervision carried out on the management side in carrying out the company's

operations will create opportunities for smaller financial distress (Parulian, 2007). This is also

supported by research conducted by Emiraldi (2007) which states that institutional ownership has

a negative influence on financial distress

Accuracy of Model Classification

The classification of the model's accuracy shows the accuracy of the model in

predicting the company's finances while the results of the classification of the model's accuracy

are presented in the table as follows

Tabel 4.5 Model Classification

Observed

Predicted

Banking Conditions Percentage

Correct 0 1

Step 1 Banking

Conditions

0 416 8 98.1

1 122 6 4.7

Overall Percentage 76.4

The table above informs that the model is able to predict manufacturing companies that

do not experience financial distress of 416 / (416 + 8) = 98.1%. The model is able to predict

manufacturing companies that experience finacial distress of 6 / (6 + 122) = 4.7%. The accuracy

of the model predicts overall corporate financial distress of (416 + 6) / (416 + 6 + 122 + 8) =

76.4%. Thus it can be concluded that the model correctly predicts financial distress of

manufacturing companies in the study period of 76.4%, namely, 422 of 552 companies.

CONCLUSIONS AND SUGGESTION

The results showed that the logistic regression conformity test was significant, this

indicates that logistic regression is able to predict the company's financial distress in the study

period. Hypothesis test results show that the variables that influence the company's financial

distress are leverage, profitability and institutional. while variables that do not affect the

company's financial distress are liquidity, firm size and k. managerial. The results of the

accuracy of the model calcification amounted to 76.4%, this indicates that the model is able to

predict precisely the manufacturing distress of the manufacturing company in the study period of

76.4% or 422 of the 552 observational data. Furthermore, it can add independent variable



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variables that are considered capable of predicting company financial distrees and also use other

statistical analysis methods that allow more accurate predictions of corporate financial distress.



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Complexity concepts in market dynamics; the evolution of market alliances

Tamas Michel Koplyay, Ph.D.

[email protected]

Hamed Motaghi, Ph.D. (Corresponding Author)

[email protected]

Hilda Hurta, Ph.D.

[email protected]

Abstract

Market alliances accompany firms during the evolution of the lifecycle and undergo serious

structural transformations from early market ecosystems to late stage value chains. This happens

in an orderly fashion that facilitates the adaptation of the firms to market conditions and

witnesses a migration of complexity from the alliances into the firms. In a sense complexity

migrates from the market into the firm and its immediate neighborhood, such as the value chain.

At some point the firm strategic independence is subsumed by its parent coalition. Along the way

many interesting concepts of complexity arise such as symmetry, random signal-based

adaptation, loose and tight environmental fit, risk mitigation and ability to fend off shock

loading.

This article will examine the principal complexity issues related to this process of market

evolution and significant reasons behind the adaptation logic that correlates with this process.

Key words: Complexity, Market Dynamics, Market Alliances, Structural Transformation






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Introduction

The market appears to function at two distinct levels, the deep and the surface structures,

where the deep structure is defined by the succeeding customer profiles, creates a certain

dynamic of its own (Dobni, C. B., & Luffman, G. (2003)).

Above the deep structure unfolds the surface structure that has a series of crisis points for

the firms, where these are swallowed up progressively at a higher rate into grey holes of deeper

colors and more irreversible nature until the whole market disappears in to black hole which

marks the end of the market.

At the beginning is the white hole that spews firms into the attractive market. This

attractiveness is tied to the high promise of market size, growth, customer price inelasticity and

relative absence of competitors, sort of a blue ocean, although entry rate due to low market

barriers is significant and finally fills the market positions available (Greve 1988).

The lifecycle, the surface structure, follows the deep structure and creates both market

competitive weather and the combines with the deep structure to create the crisis shakeout points

in the market (Klepper, S., & Graddy, E. (1990)).

The succession of crisis points in captured by exhibit 1.

There are two climate zones associated with the lifecycle, an early phase effectiveness

zone where firms try to find their position commensurate with their abilities and the pressures

exercised by competing firms and later the efficiency zone where a position is already acquired



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and firm gets ready to deliver against the inexorable advent of a cost leadership strategy now

given by the market (Cui, Gao, Wang,& Xue(2015)).

Effectiveness zone is associated with marketing positioning whereas efficiency zone is

shaping the productivity capabilities of the firm. A productivity emphasis that is the hallmark of

mature markets.

In effectiveness climate zone the premium is on firm recognition of market possibilities,

nobleness of moves and light baggage to carry around.

This is also the market phase where young firms develop and integrate their functions

starting with product development, marketing and rudimentary supply chain and distribution

channel activities. Later finance, human resources and eventually MIS/IT join into the integrative

process.

Therefore, the effectiveness zone is a period of functional development and coordination.

It is a period of integrating the firm’s capabilities into a cohesive whole.

All of this is forged within by the entrepreneurial structural shape of the firm headed by

the critical controller, the outward looking entrepreneur (Simsek, Lubatkin, & Floyd (2003)).

In late stages of the market where the efficiency climate prevails, we see heavier firm

structures, more deliberate moves, if any, and a singular focus on execution of strategy as

opposed to selection thereof.

Furthermore, integration yields to differentiation that creates higher efficiencies for the

firm but also contributes to silo effects among the function s that needs to be countered by better

coordination devices that create more internal structural complexity for the firm (Koplyay, T., Li,

L., & Rochefort, P. (2010)

However, curiously as firm structural development takes place symmetry is preserved

and further enhanced, thereby mitigating some of the effects of internal complexity increases and

pushing the firm towards higher levels of order.

The net effect is a decrease in alliance structure complexity and a corresponding increase

in net structural complexity of firms at the maturity phase of markets (Koplyay, T., & Mitchell,

B. (2014).

The alliance structures evolve from highly complex ecosystems types to simple linear

value chain forms at the end (Pitelis, C. (2012)).



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Ecosystems are ideal for survival, absorption of shocks and replacement of damaged

nodes and offer a good measure of resiliency, whereas value chains respond ideally to demands

of efficiency and productivity signaled by the cost leadership strategy of late markets.

The drawback of value chains is the fact that every component becomes critical, the

structure needs to be actively managed and there’s no recovery from major shocks resiliency is

gone and is replaced by robustness.

It no longer can avid shocks by displacement but rather faces the turbulence with robust

and redundant defenses.

Ecosystems on the other hand, lacking central control, are unpredictable, inefficient and

fragile (Costanza, R., Low, B., Ostrom, E., & Wilson, J. (2000)).

They adapt to shocks by repositioning in the market thereby causing an expenditure of

reserve resources of its constituent members. The future is now.

Exhibit 2 captures the deep structure of the market based on the successive customer

bases

BowlingAlley

Tornado Tombstone

Shakeout

Mainstreet




Chasm

Early market

Of significant interest is a second evolutionary trait of the market that affects firms.

The firms start out in a pure competition environment of the effectiveness zone.

All their moves are dependent on their own awareness of market conditions, but as the

market progresses more and more coordination seeps in to replace the independent early

behavior.

In act a serious coordinative shock is delivered at the platform stage, where firms

coalesce into groups to set standards that is required as a quality assurance to the deep customer



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base, now at the pragmatist stage, and also acts as a defensive measure against further intrusive

innovation by requiring compatibility with the platform standards for all competing firms.

By the time the market reaches the value chain stage, almost all actions of firms are

coordinative.

So, there is a progression form a stand alone type competitive stance to one of a

collective effort.

In fact, the value chain comes about just as cost leadership imposes its will on the market

and the linear shape of the chain facilitates the delivery of productivity. The market evolves from

singular competition to collective one as illustrated by the single entrepreneurial firm and later

by the coordinatively constrained value chain.

Exhibit 3 traces the evolution of the market from effectiveness to efficiency climate

zones

Supply and distribution channels are the most efficient when the structure is linear and

minimal transition times occur between component firms upstream and downstream (Kim, Y.,

Choi, T. Y., Yan, T., & Dooley, K. (2011)).

This quasi linearization happens throughout eh market cycle.

Firms seek out outsourcing, insourcing, offshoring and in shoring to simplify their

resources and product flows upstream and downstream (Kotabe, M., Mol, M. J., & Murray, J. Y.

(2009)).

UPS has now transformed into a major supplier of insourcing where it enters client

premises and performs all the coordinative tasks of resources acquis ion and product distribution

for medium and small firms that could not afford theses streamlining functions on their own.



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UPS in fact provides the economies of scale to these firms (Leamer, E. E. (2007)).

Walmart of course proceeds on its own to develop the most highly integrated global

resources management systems conceivable (Jensen, M. C. (1993)).

Although the chain has a huge disadvantage of having all of its component critical in the

sense that any suppression of a chain component results in failure of the system. However the

shock loads on the chain are infrequent and defenses can be built to guarantee a reasonable

survival chance under perceived loadings.

This however is not foolproof as Toyota discovered when the transportation links to its

Japan factories were destroyed by a major earthquake.

We can trace the simultaneous development of firm alliances in the market from

ecosystems to value chains and note the remarkable transformation of nonlinear, complex and

resilient structural forms of ecosystems evolve into rigid, efficient, vulnerable and linear forms

of the value chain.

This evolutionary process seems to be imposed by the deep structure, whereas the firm

evolution is dictated by the surface structure (Koplyay, T., Lloyd, D. M., Sanchez, L., & Paquin,

J. P. (2012)).

Exhibit 4 summarizes the structural shapes that accompany firms in their voyage along

the lifecycle.

A related phenomenon, defined by both the deep and surface structures, is the

progression of strategies along the lifecycle (McAdam, M., & McAdam, R. (2008)).



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From an open and wide funnel representing the many market position choices of early

markets to the narrowing down of choices to a single one in market maturity. the strategy

funnel is created by an interplay between the deep and surface structures Koplyay, T. M., Lloyd,

D., Jazouli, A., & Farkas, M. F. (2016)).

From the many options available to the firm in early markets to executing at the

acquired final market position in maturity the firms learn how to change their respective

behaviors, structures and critical functions depending on where they are on the curve.

Exhibit 5 shows the continuing whittling down of strategies available as the market

matures.

These are excellent reasons for this curtailed choices as the market evolves.

First of all, there appears to be an anticipatory foresight among all firms to build market

share at any stage of the market.

In fact, the early rush to share and market strength even trumps the eventual need to

produce a profit, the firms know that share price corelates with top line growth and hence

everything is done to buttress revenues, and yet this is not essential to immediate survival but

becomes a factor in late markets. This type of thinking is amply evident in Shopify, where top

line growth is the corporate priority.

So the firms instinctively reach for market share and often dominant market share as

captured by market strength which allows building of brands, a very useful and relatively

inexpensive tool to hold market position ,as it cost a lot more to attack a brand than to defend it.



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The accumulated market share eventually translates into economies of scale and allows

for the implementation of the final strategy, cost leadership (Hitt, M. A., Keats, B. W., &

DeMarie, S. M. (1998)).

The idea to retain here is that the evolution of the firms and their respective adaptive

behaviors anticipate the eventual end game of the market (Lo, A. W. (2004)).

There appears to be a market teleology acting on singular and collective behaviors of

firms and their alliances.

It is almost as if the market had a life of its own and through feedback mechanisms it

guides constituent firms and their alliances to a final resting place, which is known by the time

the market comes into existence.

We can comment on a phase of the market, the M&A phase, that helps fulfil final market

destiny. As the market matures it becomes n more obvious that market share will rule eventually.

Firms try organic growth, but as the market gets depleted of new customers it becomes more

difficult to gain share (Hurta, H., Jazouli, A., Koplyay, T., & Motaghi, H. (2017).

For two reasons, one is the customer acquisition costs go up and retention costs come

down. It’s cheaper to hold on to a customer than to recruit a new one. Second is that share

acquisition becomes zero sum game, the market is not growing anymore and a firms share gain

becomes another firm’s loss. Hence if you can’t beat them you buy them and series of M&A is

unleashed to consolidate the market and often produce an oligopoly, or in the presence of very

strong economies of scale a monopoly, something that government regulators try to prevent,

although often for the wrong reasons.

A further characteristic of market evolution that is worth commenting is the type of

stability available to firms depending on location. In early markets bot the firm and its ecosystem

can relocate under market forces, say competitive pressures or collapse of a customer base, or

even intrusion of an adjacent market. This nomadic ability defines a seeking out of zone stability,

the ability to fine a new competitive position within the developing market.

Later when the first crisis point the chasm is crossed and the blowing alley strategy

developed firm and its alliance become more circumspect and stability can be found only in

limited spaces, the standards platforms to which firms can converge.

There may be several of these standards first but eventually they will decay to one

dominant or maybe two platforms, and then the platforms themselves disintegrate into prototype



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value chains, called clusters that are essentially linear at the core and ecosystem format at the

supplier and distribution channel ends.

The application software providers would fall into the category of suppliers at this stage.

An example being the Sony Beta or a Toshiba VHS platform, but in the long run this morphed

into one market standard, Toshiba VHS in this case.

By the time the final market phase of maturity arrives, the stability is of a point form, no

chance to move the asset base constraining, the risk avoiding culture and accumulated knowhow

is too heavy to relocate. Just ask GE about its recent experience with software development. The

stability zones in a literal sense define the scope of maneuvering possible for a firm in the

market, and scope decreases until only one option is left in maturity

Exhibit 6 shows the zones of different stability against the market lifecycle

The small picture; local co-evolution based on complexity

There appears to be a common focus-based evolution of firms and their alliances driving

both towards an unavoidable state of cost leadership where choice of strategy is left behind, and

the execution of the market given strategy prevails. (Koplyay, T., Sanchez, L., & Levy-Mangin,

J. P. (2012)).

Whether the driving force behind this co-evolution is the market or the adaptive behavior

of firms, or both, is immaterial to the final outcome, although of real importance to our

understanding of both market and constituent entities transformations.



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The fact remains firms and their alliances change in an orderly and predictable fashion,

drawn like moths to the flame of final market attractor, markets share based productivity

anchored competition.

If there is a link between the firm’s behavior and the shape of their alliances it should

surface from the study of emergence in the market due to complexity (Koplyay, T. M., Lloyd,

D., Jazouli, A., & Farkas, M. F. (2016)). We shall examine two instances in the market there this

type of evolution does take place. One has to do with the platform and the other with the

emergence of the value chain. For meaningful mergence to occur complexity theory tells us that

we should find phase transition, complexity on the edge of chaos leading to self-organization at

the firm level that eventually produces strong emergence of an alliance that will in turn influence

the lower level conduct of the firms. And in fact, on at least two occasions this happens in

markets.

The first one is the standards platform. After crossing the chasm, the first grey hole in

market where firms are lost, the surviving firms concentrate on building a niche market around a

bowling alley strategy, whereby the firm choses a central customer and starts seeing a complete

product to this customer in the pragmatic segment, and eventually to all other firms in the

customer’s ecosystem.

This vertical marketing where you proceed from the first bowling pin to the next, and in

cautious steps build a whole bowling alley of connected customers, and this contuse until the

market growth takes off where you abandon the vertical marketing for a horizontal one. No more

local customization but ride the tiger through high growth period. So we find two phase

transitions at the same time; One of change for vertical to horizontal marketing And one of study

market growth to high growth. So, the market behavior changes drastically inviting and

evolutionary move from the firm but for such behavior or appear we must have nonlinearity on

the edge of chaos.

Indeed, we just left the highly stable and ordered state of the bowling alley and down-

market looms the chaos, the shakeout. We are on the edge of chaos.

The market in of increasing structural complexity, measured by the nonlinearity of

relationships among the firms and their alliances (Koplyay, T., & Mitchell, B. (2014)) with

strong nonlinearities bounding this complexity.

On one side is order and on the other chaos, ripe for some meaningful evolutionary

transition.



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And as the firms organize they give rise to the emergent standards platforms that offers a

way to survive the shakeout by embarking in the life boat of the standards platform, that will

carry them to the other shore of the shakeout

There is emergence and this emergence signals to noncommitted firms the possibility of

survival through various feedback mechanisms such as superior customer commitments to the

platform and equally sustainable growth rates. Hence the emergence is strong

Similarly at the end of the market right after firms transit the M&A phase ,there is strong

stability and order of the oligopoly ,but the execution of the productivity phase still awaits and

for this to occur the supply and distribution relations need to be literally ironed out into linear

shapes (Hurta, H., Jazouli, A., Koplyay, T., & Motaghi, H. (2017)).

Downstream from the M&A lurks the market exit, the final gaping black hole that

swallows all firms, and that point represents chaos. So we have the stability of the M&A phase,

the edge of chaos of the market exit and in between the nonlinearity of the combined firm and

alliance structures.

By this phase the firms are cooperating seriously with chosen partners and almost value

chain type behavior is evident in the clusters, the end of which need to be ironed out to attain the

value chain. A period on high nonlinearity occurs between the ordered sate and the chaotic exit

that allows for organization the firm level to produce an emerging entity the value chain, which

is markedly different from the firms composing it and endowed with properties that could not be

derived from firm characteristics. Some of these properties are smoothing and tightening of chain

relationships by a dominate member of the chain that henceforth sets chain strategies. The firms

need are submerged into the chain. Although as the chain gains tremendous efficiencies it loses

survival attributes.

It has all of a sudden a series of critical nodes, the individual firms , which renders ii

equally exposed to market perturbations at all nodes. Hence it builds redundancy at all nodes of

the linear network, which results in overall robustness. Again this emergence is occasioned by a

prevailing complexity at the firm level in a period of phase tension between order and chaos

The phase transition is twofold; Transition from mass customization found in oligopolies

and a transition from moderate growth pre and past M&A to zero growth of late markets. Both

marketing and growth conditions change. In anticipation of this event the M&A was unleased to

find market share in a now static market, that faces the calculations of zero-sum market share

changes. Therefore, the competition must shift from further acquisition of share to execution of

productivity at fixed point of interaction with the market.



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Conclusions

Market appears to anticipate its own evolutionary profile and exerts forces and creates

adaptive mechanisms for firms and their alliances to proceed I the right direction at the right time

toward a final state where choice is stripped from the firms and a given strategy imposed which

requires a management perspective change from well positioned firms to well managed firms.

From external management emphasis to internal focus. But the market provides the means of

transition at various phases and firms that profit from this opportunity continue to evolve and

arrive well equipped at the final state. The market goes through a series of critical events from

the chasm in early phase to shakeout in mid stage to partial market collapse at M&A and finally

at extinction in market exit. All of them are market exit grey holes for the firms, some go under

some survive. Before each exit point the market allows for preparation by the firms to confront

the crisis and this means is the complex adaptive transitions that lead to emergence of lifeboats

that help navigating the treacherous waters of the grey holes.

Whether it’s the, the platform, the collapse due to M&A or the value chain the transition

prior to these events seems to be based on self-organized based emergence that is initially weak

but later becomes strong by exerting feedback on all firms and draws them to the attractor that

these alliances represent for the firms.



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442.

Firm trends in markets and their consequences; mapping evolution of firm behavior using the deep and

surface structures of the market.

Koplyay, Motagh, Hurta, and Malouin

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Firm trends in markets and their consequences; mapping evolution of firm behavior using

the deep and surface structures of the market


[email protected]

Hamed Motaghi, Ph.D.

(Corresponding Author)

[email protected]

Hilda Hurta, Ph.D.

[email protected]

Mario Malouin, CPA

[email protected]

Abstract

At the core of the market, are the customer profiles, which define the demand forces, bubbling

up along the lifecycle? The lifecycle itself pushes the market over the core as if it were a

continental drift. We have deep structure defined by the customer profile, a path of evolution

defined by the lifecycle and a sequence of characteristic events, which are related to both. The

deep structure gives rise to a surface structure that defines specific significant market events;

these events begin with the volcano, a white hole, which spews firms into the young market, then

fades away as the lifecycle moves on to a series of grey holes, ever darker, ever deeper which

culminate in the final black hole and market exit. Furthermore, the surface structure organizes

market collaborative groupings such as platforms, clusters and value chains that result in very

different competitive strategies; from the singular to the collaborative. This paper will review the

structure of these interactions and examine the class of intensifying and diminishing trends at the

firm level that create and constrain market dynamics. Furthermore, it will summarize market

behavior based on both the deep and surface structures, the associated strategies and the market

landscape. Among the key observations is the fact that early markets function in an effectiveness

climate zone and late markets in an efficiency zone. A period of transition connects during the

market leveling off growth.

Key words: Firm evolution, Market trends, Grow Consequences, Market Structure








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Introduction

The market appears be organized at two levels, the deep and surface structures. The first

consists of the customer base that influences what happens at the surface, especially at the

market lifecycle level, providing a template for the market that creates a dynamic independent of

the firms in the market.

This dynamic shapes the behavior of the firms and dictates a consistent development for

the emergence of the many lifecycles that drift over the deep structure. Among these, are the

lifecycles of the firm, its associated alliances that range from ecosystems to value chains and

various behavioral lifecycles of the firm that track its evolution such as HR, finance, innovation,

compensation, decision making, and project management.

The deep structure is analogous to the core of the earth over which float the continents at

the level of the mantle and undergo changes themselves as competitive pressures and the deep

and surface structure combine influences.

We seem to have a succession of surface structure events, climate and weather patterns

that shape the market; with the key features of the deep and market surface structures relatively

immutable but the weather like competitive pressures building and eroding the surface structure

in real time.

This article explains these forces and links the various mechanisms that create market

reality.

The deep structure of the market “the core”

We are going to examine the market dynamics from the perspective of the hi-tech

industry because things happen a lot faster and a lot more often in this sector.

In fact the hi-tech market is on steroids that borders on dynamic overdrive, often

churning through stages of the lifecycle at hurricane pace, leaving both accumulation of

astounding wealth and utter devastation behind; and frequently bipolar firm behavior is evident

when under the same corporate umbrella, two different firms reside; such is the case now with

Blackberry, an almost has been trying to reposition in the late stages of the lifecycle on the back

of its corporate affiliate QNX, the rising star in self-driving vehicles; or Amazon and Whole

Foods (Forbes, 2017), where the acquisition of the latter may lead to its unrecognizable

reorganization as an advanced warehousing staging point for Amazon goods to be shipped to




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customers; and Whole Foods vocation may change from focus on foods to focus on drone and

robot delivery just being developed by Amazon (CNBC, 2015). All of this may end up in

corporate indigestion but right now the collective appetite for online sales and immediate

delivery of goods to the customer is huge. As we note, not incidentally that Whole Foods

acquisition solves an important choke point for Amazon, the backflow or the return of goods.

Having the storage space of the acquisition does an end run of the eternal dilemma of online

sales; where to drop off undesired purchases.

The ample parking surrounding Whole Foods outlets makes for convenient drop off

points, and of course this interim solution will soon be enhanced with much vaster acquisitions

of outlets of similar configuration to Whole Foods, but his time just for the storage and parking

space. Eventually big retailers suffering from precipitous decline in sales such as Sears may yield

their facilities to Amazon, the very competitor that ruined them (Sears actually went through

bankruptcy and its mall locations may up for Amazon occupancy already).

In the first case [Blackberry] a new phoenix rising from inside the firm (Forbes, 2017), in

the second a potential phoenix subsumed to a new parent interests [Amazon] (Forbes, 2017).

At the most fundamental level, at the core of the market, lays the customer profile that

defines much of the dynamics of the market, the firm and its accompanying alliances. The core

consists of successive customer groups with which the firm interacts after it enters the market

(Jazouli, A. (2016)).

Initially the early market is populated by technology enthusiasts and visionaries who seek

out the breakthrough offerings of the young firm (Koplyay & Mitchell, 2014). They even help to

test the offering and provide significant feedback on product or service performance, somewhat

akin to a beta test.

These two groups are risk taking, mostly immune to higher prices, thereby reinforcing

price inelasticity of early market behavior and consequently create richer margins for the firm,

which compensates to some extent for the lack of volume (Koplyay & Mitchell, 2014).

This customer base is quite small compared to the next two groups, the pragmatists and

the conservatives, but they play an extremely important role of signaling the usefulness of the

offering to the customer groups following them.

Furthermore, they assist the firm in making genuine progress towards completing the

product configuration to make it more palatable to the market majority, which is shy of




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experimenting with new product features, is risk averse, and asks for the complete product that

fits seamlessly with the existing internal operations.

To get to the gold mine of the market, majority the firms offering the breakthrough

products need to cross the chasm (Moore, 1995) which is possible when the product is completed

with specific target clientele in mind, accompanied by prototype channels of delivery that are

filled during the growth phase of the market and by a succession of moves, vertical marketing,

where links among target firms are exploited for organic growth purposes. An example may be

the banking industry, where acceptance by the banks of a cyber security sensitive product

becomes an endorsement for banks’ alliance firms (Reuters, 2017).

The market majority, representing about 70% of the market consists of the pragmatics

and the conservatives. The pragmatics will endure new technology and even show willingness to

adopt it if it has been pretested by the preceding two groups, if it shows real promise as a

competitive advantage and comes with seamless integration guarantees.

Moreover, the group asks for the end of all product experimentation and allows only the

complete product, with some local customization, into the firm’s premises. The spirit of

experimentation with new ideas is replaced by the cautious optimism associated with working

with promising ideas that fit the market and competitive reality.

The group will hold back until the competitive pressures unleash a stampede towards the

new technology, such as was with the internet, iPhone, online shopping and the pending invasion

of AI coupled to big data.

The conservatives on the other hand are reluctant customers, although they love

technology as long as it is out of sight and requires zero maintenance, accompanied by good

price/performance or value proposition. As in the technology available in BMW or a Mercedes.

Furthermore, now it’s “we’re going with this unavoidable technology ” and not as with

the pragmatics, “we are going with this useful value added technology”. But the combination of

the pragmatics and conservatives, which together constitute the majority market, about 70%

unleashes the tornado or the period of intensive growth where vertical marketing metamorphoses

into horizontal marketing and all pretense of customization is abandoned and products are

pushed out into the market as fast as possible.

Amazon, as big as it is, may be entering this period of its market, horizontal sales, as it

completes the transformation from online book sales to an online platform of all sales. To

accomplish the final step of this vocational change, it had to acquire Whole Foods (Forbes, 2017)




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to have the storage space for pending shipments and more importantly to deal with backflow of

items, the difference between gross and net sales.

Beyond the previously discussed main market, at the tail end are the skeptics who refuse

to adopt new products, technology or otherwise, until and unless they are compelled.

In general, hi-tech markets ignore this customer base, but occasionally, on a risky basis, a

living can be eked out, as was done by Lucent, which serviced on a legacy basis this laggard

group in the communications sector.

The general market tends to linger with the skeptics until the market collapse but hi-tech

usually undergoes a rejuvenation of the market through breakthrough and disruptive

introductions before this stage is reached.

One of the predictable effects of the coming AI revolution will be the early termination of

markets before the maturity stage is reached. In all markets where AI plays a dominant role or is

at least at the technology core of the market, innovation will rule the market landscape, keeping

firms in constantly rejuvenated young markets where productivity is not an issue, as volumes are

never generated in sufficient quantity to deploy the cost leadership strategy. Rather imagination-

based innovation will rule the unending disruption of markets through new ideas.

We see this phenomenon already in Twitter or Yahoo challenging Facebook and then

flaming out or stagnating or Tesla beating all auto manufacturers in market capitalization then

starting a downward drift (Forbes, 2013).

Competition will shift to the imagination driven innovation, that will keep firms in high

margin and low volume territory, but there may be serious ramping up of volumes during market

high growth stage [tornado] but this will be an unstable period ever likely to be terminated by a

great new disruptive idea flowing from the constant probing of opportunities through AI guided

big data analysis.

Exhibit 1 captures the essence of the deep structure consisting of the succeeding customer

profiles and the associated transition points and phases of the market.




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Exhibit 1. Market Dynamics and Customer Base (adapted from Moore, 1991).

BowlingAlley

Tornado Tombstone

Shakeout

Mainstreet




Chasm

Early market

The strategic choices tracking the deep structure

“A critical manifestation of the deep structure”.

In early markets, the strategic choices are many as the firms jockey for positioning by

trying to balance their core competencies and capabilities with the available market opportunities

[competency is what you can do on your own and capability is what you can enhance with the

help of your ecosystem, essentially the first is what you can do on your own and the second is

what you can do with your partners].

The ecosystem represents the first partnership of the firm in the market and continues

through several transformations of this partnership throughout the market development.

Essentially the partnerships represent what you can do collectively as opposed to just on your

own. These partnerships go from a very lose and shock resistant format of low productivity,

such as the ecosystem, to a brittle yet very efficient structure of the value chain. (Koplyay &

Mitchell, 2015). Exhibit 2 captures the evolution of the market alliances.




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Exhibit 2. Evolution Of Market Alliances (Koplyay et al, 2015)

In early markets, the choices are as many as product variants that can be introduced to the

market. The funnel is wide but is narrowed down to just cost leadership by the mature market

stage. Exhibit 3 summarizes the strategic funnel during the market lifecycle.

Exhibit 3. Strategic Bandwidth Market Customer Base Drivers (Koplyay and Mitchell, 2014a).

Product platforms whittle down the initial positioning choices then developing channels

of distribution further curtail choices. Consolidation of the market during the M&A period

further erodes the range of strategic choices as the underlying customer base, the conservatives

have very real expectations about price/quality, reliability and functionality. The funnel of

convergence of strategies has an interesting implication.




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At first firms must find their right place in the market through positioning and then, in

late markets, their place is given to them and the choice becomes executing the best internal

strategy to deliver against this single choice, cost leadership.

From the M&A phase on, the market rapidly converges to the single choice of cost

leadership, which shifts the focus of the firm from external market conditions, by now quite

simple and predictable, to the internal functioning of the firm to deliver the best price anchored

value proposition. One of the important lessons of the strategic funnel is that in early markets,

finding the best place in the market commensurate with the firm endowments is the key to

success, whereas in late markets, once the choice is whittled down to just one, cost leadership,

the emphasis is on execution of the market dictated strategy.

The surface structure: the landscape of the market

We will now turn to the surface structure as shaped by the deep structure: Early markets

are endowed with low market barriers and much promise embodied in the relative price

inelasticity leading to high gross margins and the usually exaggerated hype of the future.

Different critical tasks await the firms at each stage of the market. Firstly, it must find its

proper place and differentiate itself from competitors to create some market distance and

competitive breathing space. This task is effectiveness imbued and often forgives mistakes of

positioning.

Furthermore, the adaptability and survival chances of the young firms are enhanced by its

relatively flexible ecosystem that yields space under market shocks. Like a spider web, it

deforms and then reforms. A young firm will have flexibility of positioning as it can easily

modify its product designs without having to worry about dragging expensive asset base along

from one position to another; and as its place in the ecosystem is not tightly bounded it can move

and locate a new position in its existing ecosystem or find a new one.

Survival is portable and exactly accommodated by the flexible arrangements of the

ecosystem as opposed to the late stage alliance, the value chain (Koplyay et al, 2015).

Not much has been written on the progression of the alliances on the lifecycle that accompanies

the firm and seems to be tailor made by the market to allow the firm to cope with issues of

effectiveness in early market stages and efficiency in late ones.

For the sake of completeness, we include it here and note that alliances lifecycle

(Koplyay et al, 2015) is an expression of the surface structure dynamic.




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We note that early alliances tend to be nonlinear and complex, which provides some

measure of protection against early market turmoil, and this structure, is resilient, resistant to

shocks but quite inefficient. The alliance flattens out in late market into a simple value chain that

is very efficient, but brittle and subject to real damage due to strong perturbations (Koplyay et al,

2015).

A striking example of disruption is the recent effect of Cambridge Analytics on the

reputation and market value of Facebook, which clearly illustrates the symbiotic relations that

prevail of the net.

We can trace the evolution and transformation of ecosystems into value chains as the

market matures.

The key research question is what causes the flattening of alliances from ecosystems into

value chains?

Is the market sending signals, which the alliances and the firms interpret and adapt to

throughout the cycle and if so what are the adaptive mechanisms and the enabling forces.

We do know that there is high complexity in early markets, many chaotic events and

stable structures that attract the firms .such as platforms and clusters, and that these

circumstances are an essential prerequisite for meaningful adaptation, or purposeful evolution

Exhibit 3. Evolution and transformation of ecosystems into value within The Market Lifecycle

(Koplyay & Mitchell, 2014a&b)




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The market does have a life of its own, and there is very much like a blue ocean behavior

in early markets that provides freedom of movement which only possible for firms with

exceedingly light asset base to drag along (Kim & Mauborgne, 2005). In fact, when the market

starts to demand efficiency and as soon as the concept of productivity is raised escape to blue

ocean markets becomes progressively more difficult and in late mature markets impossible. The

only way a firm can escape the moribund market is to redeploy the assets in nascent new

markets, essentially to incubate a startup, and again the necessity of financial reserves to

accomplish this drastic move must be underlined. In addition, this is what Blackberry is doing

with smart cars affiliate QNX (Forbes, 2017) and Nortel did with its internet security firm

Entrust; but to do it, cash reserves need to be there as borrowing in yet unpromising markets is

problematic, hence the attention to Earnings Before Interest, Taxes, Depreciation and

Amortization and rent (EBITDAR) for firms in declining markets.

Again, to compute the surface structure emergence, evolution and fade out, we have

chosen the powerful unifying capabilities of the lifecycle to illustrate its collective impact (what

we call surface structure is essentially the unfolding market dynamic with its crisis pit stops).

At the earliest stage of the market when the enthusiasts and early adaptor client base

dictate the deep structure dynamic, the market entry is akin to a volcano, in essence a white hole

that spews the young firms in hyperdrive of expectations into the market. In addition, this is

possible as market promise is high with rich margins and high growth potential and barriers are

low, as no real asset base is required to operate, nor usually any IP or license agreements. The

market is pristine and blue with not a shark in sight.

This endures until the chasm (Moore, 1991) is reached and the next stage and most

important stage of customer base needs to be conquered. To cross the chasm the firm must make

a major adjustment and put aside its blue-sky product development, instill some marketing

discipline, complete its product configuration and start thinking price/quality.

Failure to achieve this will leave the firm in the abyss of the chasm, which is the first

grey hole of the market that swallows unresponsive firms.

These grey holes (Koplyay et al, 2014) get bigger and darker throughout the cycle until,

at market exit, it a big yawning black hole from which there is no return [but as in physics if and

when a firm disappears for good, information about it is not lost but lingers on the event horizon,

so we can write the obituary and draw the appropriate lessons.




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The majority client base of the deep structure progressively instills constraints of

price/quality nature and product must be become more reliable, more user friendly, cheaper and

perfectly aligned with existing firm operations.

Among other things, the supplying firms adjust at the surface by transferring more power

to marketing, production and limited customization of offerings. However, before they can

declare victory, they must survive two more grey holes, guaranteed by the sheer size of the

majority customer base, during the high growth phase: The first is the standard setting platform.

As the market settles down after the initial burst of creativity and witnesses the chaotic profusion

of product variants, the merging bigger players start a process to create product platforms that

ensures a competitive advantage by adding real bringing new to the platform by third party

suppliers (applications for iPhone for instance (Tiwana et al, 2010)).

This process also guarantees market leadership for the platform initiator and acts as a

rearguard device to eliminate new breakthrough competition by forcing all to align with the

platform. Usually two of three platforms emerge but one becomes dominant; iPhone, Blu-Ray or

IP protocol. In addition, even Amazon can be thought of as a sales platform. The important

development for future competition is that from this point on platforms compete and not just

individual firms, and ones that don’t find a home linked to a platform struggle and later exit the

market; so the platform’s net effect is reduction of the number of firms.

The platform formation creates the first major entry barrier to the market (Koplyay et al,

2014), but high growth and still reasonable margins keep attracting new entrants. The platform is

also a marketing device to assure large customers that stability of the supplier is increasing and

offers commensurate size to the customer to assure future cordial and competitive relationships;

and this doesn’t stop until the growth levels off and all of a sudden too many firms are trapped in

the market for the given market size. Then an inevitable major reckoning happens with the

formation of the very grey hole, the shakeout, which eliminates numerous firms.

An unquestioned principle of good management is that all firms should always plan, but

during the shakeout, this is not true, in fact planning can get you into deeper trouble.

Planning is a time and effort consuming exercise and you have neither during the

turbulence of the shakeout. When in a hurricane batten down the hatches furl the sails and hope

for the best. Furthermore, for planning or, which is the same, seeking or confirming direction of

evolution of the market requires a quantum of time to draw appropriate conclusions and transfer

the lessons from the planning exercise to the firm. In addition, time is lacking in the hurricane of

the shakeout and this period cautions “life is what happens to you while you are busy making

plans”.




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GE appears to pass this stage now as it tries to reposition from a manufacturing firm

status to one of generation of software, blissfully unaware that these two functions are

incompatible under the same roof as manufacturing is high discipline, efficiency focus and late

market function whereas software is creative, effectiveness and malleable culture market

undertaking

Amazingly in the shakeout, it’s not firms with great technology which tend to survive but

ones with either strong financial reserves or parents with deep pockets, and this proves the old

adage that the cumulative past management acumen, expressed in total profitability has a huge

impact on the future. When shareholders agitate for share buybacks or higher dividends, they

tend to miss this point and could endanger the future of the firm by insisting on higher share

price today at the expense of missing opportunities in the future, or entirely missing the market

beat. Beyond the shakeout, two more major grey holes loom on the horizon; consolidation and

market exit.

Market exit is obvious, but it has an interesting psychology of interim survival to cope

with. Some firms can and do make a good living in declining markets as long as they have a

decent tolerance for risk, however, in general, late stage firms seem to have very little tolerance

for risk (Koplyay et al, 2015). And the risk is the sudden unanticipated collapse of the market as

opposed to a foreseeable fade out, which leaves the asset base stranded as sunk costs; coupled

with this risk is the ramp up of potential new firms from other promising markets; GE in

software (ZDNET, 2015) or Google in smart cars (CNN, 2015).

How fast should we divert funds from our EBITDAR, financial reserves or leverage to

ramp up the new business but not to bleed the old one dry?

Consolidation is a surface expression of the underlying late majority base, the

conservatives who want to have the lowest possible price and to execute on a demand the firm

has to have markets share to be able to use economies of scale, reduce its cost structure, and

thereby create wider margins. Here we see the clear transition zone from positioning, or

effectiveness, to productivity, or efficiency.

By this stage, because of the price sensitivity of the conservative deep structure, the price

is given to all firms, and hence the competitive firms need to deliver on the best cost leadership.

Moreover, the reason is that cost leadership creates the best margins and cumulatively and for

each competitive iteration the best profits.




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Normally to achieve this, the firm needs economies of scale to spread its costs over

higher volumes and this explains the previous round of M&A that has its goal the maximization

of market share.

Among other factors, this implies that during the high growth period of the tornado, the

firm’s growth should be superior to that of competitors to gain not just market volume but

relatively higher volume than its close competitors should, namely market share should.

As the cost of customer retention falls and customer recruitment rises due to the now

stagnant market growth, (each competitor needs the customer for the same reason, to maintain

significant market share) and the firms are faced with a zero-sum game “But if you can’t beat

them, you can buy them”. Hence a major round of M&A is unleashed on the market (Koplyay &

Hurta, 2016), with firms having better financial reserves, debt carrying capacity and higher share

value becoming predators. However, the bolder and more risk tolerant predators may undertake

reverse takeovers by forcing the acquired firm to carry the debt related to the acquisition, and

this is not without risks, as the acquired firm is now hamstrung if a market crisis, demanding

reliance on cash reserves “intrude”. Many M&A unravel due to this curtailing of strategic

financial reserves.

In early markets, the firm can create its own strategy, but by late markets must run with

the given strategy; early markets forgive mistakes due to high margins linked customer price

inelasticity and high growth, which gives recovery time to the firm that, commits a mistake. But

late markets are not forgiving as asset bases to produce goods for the market balloon, hence

mistakes of mismatch between asset base and emerging demand become costly even fatal. From

strategic choice of where to be, to implementation choice of how to produce where we are, is the

evolutionary pattern.

In essence, from our perspective, strategic choice becomes a match between the deep

structure of demand and the surface structure of supply, a supply that is conditioned by the firm’s

ability and the company to keep in step with its associated alliance.

Significant trends in the surface of the market: “the market climate”

As the firm progresses along its lifecycle in a given market, some competitive factors

increase and others decrease, and these have influence on the competitive stance of the firm and

its relationship to the deep and surface structures.

Moreover, the factors become a constraint or an opportunity set for its choice of

strategies vis a vis its competitors (generally in a monopolistic market the firm would choose the




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best profit generating strategy, but in a competitive situation it must cope with both the

shareholder expectations and the constraints imposed by the competitive landscape, so it makes

tradeoffs). Monopolies produce less at a higher price and pure competition produces more at a

lower price, but potentially with more unsold products or waste.

In a conservation of resources, environment monopoly may be preferable to pure

competition.

Early markets are characterized by higher uncertainty, but many options to find the right

niche aligned with the firm’s competencies. This is known as market positioning and is a critical

means to escape the shocks imposed by the market turbulence, young firms yield to pressure and

move out of harm’s way whereas more established firms in late markets build defenses against

perturbations and shock loads and remain at the same market positions.

They cannot move due to the constraints of the significant asset base and shareholders

would not forgive sunk costs occasioned by such moves; older firms stand and fight.

Effectiveness considerations and late one by efficiency dominate the early market

scenario; finding the right place is the key to early success and executing the best cost focuses

strategy is key to late market success and this aligns perfectly with deep and surface structure

signals.

Early market customers exhibit price inelasticity and will pay the premium for the

innovative product, hence productivity is a non-issue, but by mature markets there is complete

price elasticity as products commoditize and the price is given to the firm which must now

execute against a cost leadership strategy that maximizes margins and profits.

Deep structure sends signals from the majority customer base that among other things

demands the best price for the uniform product; and the surface structure that defined the

strategy funnel now progresses to a single choice “cost leadership”.

The regime shift from effectiveness to efficiency seems to occur around the emergence of

the platform (Koplyay, 2015), This is also the emergence point of the collective strategy of an

alliance, the platform in this case, dominating the individual firm strategy.




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Exhibit 5. Zones of effectiveness and efficiency in strategy (Koplyay et al, 2015).

Along with the transition from effectiveness to efficiency, we see another interesting shift

in market profile induced by the surface structure.

As the market landscape settles down and the deep structure eruptions diminish both in

intensity and frequency, market adaptation as defined by the ability to relocate diminishes, and

firm resiliency, the capacity to yield to perturbations decreases (if the capacity is not tested, it

loses its importance and atrophies, sort of an evolutionary trait). However, the robustness, which

represents the firm, is and associated alliance’s ability to resist shocks, in situ, increases.

One of the key features is that the firm gets more submerged and committed to its

alliance, cluster or value chain and in the process loses significant identity and independence of

choice.

Nevertheless, collective defense is gained in the process, it is no longer fight or flight but rather

dig in a fight.

Furthermore, we find that symmetry of both firm and its alliance structure increases (as

we draw a vertical line through mid-structure of a value chain, we find a reflexive symmetry

which implies complexity of the structure is decreasing, and this is also true of its constituent

firms which are now rigid and well defined, symmetric around the center).

The simplicity implied by this symmetry leads to better controls both at the value chain

and the firm level, hence planning and execution of plans is more feasible. This is again in line




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with expanding market horizons and stability of late markets. The effect of market transition

from effectiveness towards efficiency.

As the firm traverses the climate zones of effectiveness and heads for the zone of

efficiency, some influencing factors in its immediate environment evolve. Some increase some

decrease making the transition are inevitable.

Exhibit 6. Firm-level Factors: Decreasing along the Lifecycle

Exhibit 7 firm level factors increasing along the lifecycle




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On the increasing trends side, we note the slow loss of firm identity and the contribution

by its alliance to the value added of the product

The firm is progressively subsumed into its alliance until at the value chain stage it no

longer has strategy independence but must play second violin to the value chain strategy, usually

dictated by the dominant partner.

Honda as an engine company plays a very different role in its chain than Toyota, the car

company

The firm adaptability is also submerged into that of its alliance until at the end it’s the

whole value chain that survives or nothing does.

Transaction costs within the alliance also decrease as the market progresses and the

alliance starts to flatten until it is completely linear making the flow of goods more secure and

cheaper and through supply chain and distribution channels management. But this flattening

makes every component of the chain critical and suppression of any component causes the chain

to fail. Similarly, as the firm progresses along the lifecycle, its need for customers increases just

as its costs to recruit those increases as well.

The market is heading for zero sum game, the customer I lose becomes the customer

some competitor gains.

Yet the firm needs them more than ever to execute against the economies of scale

strategy.

This dilemma is often solved through an intense period of M&A and the net result is a

becalming of market behavior and an oligopolistic equilibrium.

As soon as this event transpires the market horizons become clearer, the customer base

predicable and soon enough the only real strategic insights are gained from following the

competition’s moves resulting tin the rise of competitive benchmarking as the key strategic

function within the firm

The uptake of breakthrough innovation diminished as markets mature and firms start to

focus on incremental innovation to improve productivity. Every diminishing factor seems to

drive the firm to a cost focus that finally slows the evolution of the market into a stalemate.




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Similarly, we see the increasing factors exert similar pressures. As corporate arteries

harden and culture becomes more risk averse and sclerotic, less breakthrough ideas filter into the

firm.

In addition, the risk avoidance instills more corporate inertia and opportunity costs of

dealing with firms outside the prevailing alliance increase until only one option of operating

within the chosen alliance remain.

Nevertheless, this is fortuitous, as the cost leadership strategy will demand a close

cooperation within alliances to produce the best product at the lowest cost, which will create the

competitive margins necessary for survival

From survival of the nimblest in early markets to survival of the fattest in late markets.

As the firm grows in size it gains both width and depth, more functions and more layers

within functional groupings, and again this leads to better execution of efficiency strategies as

narrower tasks and higher repetition of the same task generates learning curves and results in a

better adapted firm to its chosen position in the market.

These efficient and stable structures can now better interact with suppliers that are now

locked into the firm’s universe to help deliver higher productivities. From lose supply chains to

highly integrated ones

In addition, there looms the value chain as soon as distribution channels are mastered the

way the supply chain is.

Conclusions

It appears that in the market universe all roads lead to Rome. There is an amazing

coincidence and correspondence between the various elements of market evolution, from the

deep to the surface structure, from one climate zones the next from the crises points along the

surface to the strategies being pursued by the firm or it is ever tightening alliance.

We see that the singular survival struggle of the firm in the effectiveness zone to the

cooperative and collective survival mode of the efficiency zone, all answer to a logical

imperative of survival through adaptation that is linked both to the strategic acumen of the firm

or its collective house and the market signals that light the way along the lifecycle.




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The market does have a life of its own and it exerts a very plausible discipline on the

firms in the market, furthermore this market life is evolving as the firms move along the lifecycle

in very predictive fashion

If I know where you are on the cycle, I can predict your past and future.

There is very little surprise in market demands and a very standard response to these

demands by the firms.

Our series of articles on this surprising predictability leads to the same conclusion every

time.

Starting with the deep structure and a surface structure supported lifecycle thee market

and firms behavior can be symmetrically forecasted in time once the firm and its accompanying

alliance can be located on the cycle.




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Selected References

Chan Kim, W., & Mauborgne, R. (2005). Value innovation: a leap into the blue ocean. Journal

of business strategy, 26(4), 22-28.

Jazouli, A. (2016). THE DYNAMICS OF ALLIANCES FORMATION IN HIGH-TECH

MARKETS; FROM ECOSYSTEMS TO VALUE CHAINS. In Proceedings of the

International Annual Conference of the American Society for Engineering

Management. (pp. 1-9). American Society for Engineering Management (ASEM).

Koplyay, T., Mitchell, B., & Cohn, S. (2015). Stability of firms under nonlinear and linear

market conditions. In Proceedings of the 2015 Industrial and Systems Engineering Research

Conference.

Koplyay, T., & Hurta, H. (2016). “Clock speed” theory of strategy making along the life

cycle. Polish Journal of Management Studies, 13.

Koplyay, T., Mitchell, B., & Cohn, S. (2015). Stability of firms under nonlinear and linear

market conditions. In Proceedings of the 2015 Industrial and Systems Engineering Research

Conference.

Koplyay, T., & Mitchell, B. (2014). The Evolution of Complexity Within Firms. In Institute of

Industrial Engineers, Proceedings of IEE Conference, Montreal, QC.

Moore, M. H. (1995). Creating public value: Strategic management in government. Harvard

university press.

Tiwana, A., Konsynski, B., & Bush, A. A. (2010). Research commentary—Platform evolution:

Coevolution of platform architecture, governance, and environmental

dynamics. Information systems research, 21(4), 675-687.

The Relationship Between Ethical Leadership and Nurse Job Performance: Boundary Conditions and

Influence Processes

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The Relationship Between Ethical Leadership and Nurse Job Performance: Boundary

Conditions and Influence Processes

Zhihong Chen (Corresponding author)

Institute for International Students, Nanjing University

Address: No. 22, Hankou Road, Nanjing, 210093, China

[email protected]

Telephone: 86-15051892288

Feng Tian

Business School, University of Newcastle

Newcastle, NSW2230, Australia.

[email protected]

Telephone: 61-2-49215981

Abstract

A study was carried out amongst 363 supervisor–subordinate dyads to investigate the effect

mechanism of ethical leadership on nurses’ job performance. It was found that ethical leadership

is positively related to nurses’ job performance, with psychological ownership as the mediator.

Emotional support from colleagues was discovered to moderate the effect on the relationship

between psychological ownership and job performance, while the moderation role of

professional commitment on between psychological ownership and job performance was not

validated. Our findings suggest that ethical leadership not only has a normative role by

encouraging ethical behavior among followers, but also has a positive impact on in-role

performance by strengthening followers’ individual motivational propensity and alignment in

goals between leaders and followers.

Key words: Ethical leadership, Psychological ownership, Emotional support, Professional

commitment, Nurses




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THE RELATIONSHIP BETWEEN ETHICAL LEADERSHIP AND NURSE JOB

PERFORMANCE: BOUNDARY CONDITIONS AND INFLUENCE PROCESSES

I. Introduction

Nursing work is an important part of medical and health undertakings. It plays an

important role in safeguarding the health interests of the people, ensuring the safety of patients,

establishing harmonious doctor-patient relationship and sustainable development of hospitals.

There is a comprehensive recognition that the present status of public healthcare system requires

significant reforms in China. In addition, although the quality of them has great influences on

patients (Lin, Huang & Lu, 2013), the reality sees the deficiency of nursing human resources and

loss of frontline nurses, which negatively influence the function of the whole medial service

system. Therefore, it is an urgent issue to develop strategies to help improve nurses’ work

performance.

In the field of nurse management, the effects of leadership on nurse’s work performance

are validated (Laschinger, Finegan, Wilk, 2009), which can ultimately benefit nursing profession,

the patients and the organization. Most researches focus on transformational leadership

（Salanova et al.，2011; Khan et al., 2018）, authentic leadership (Laschingeret al.，2013;

Dirik et al. 2017; Alilyyani et al., 2018), and empowering leadership（Bobbio et al.，2012;

Freire et al., 2015). However, in the recent two years, with frequent occurrence of ethical and

moral incidents in the field of health care such as hospitals (Aitamaa et al., 2010), which is not

conducive to the sustainable development of hospitals, more and more attention is required to be

paid to the role of ethical leadership in nurse management (Islam et al., 2018; Ozden et al.,

2017). The link between ethical leadership and employee outcomes have been validated in a

number of studies, including citizenship behaviors, deviant behaviors, and employees’ ethical

conduct and cognitions (Avey, Luthans & Youssef-Morgan, 2010; Piccolo, Greenbaum, Hartog

& Folger, 2010; Schaubroeck, Hannah, Avolio, Kozlowski, Lord, Trevino, Dimotakis & Peng,

2012; Walumbwa et al., 2010). However, research on the mechanism and contextual factors of

the impact of ethical leadership on work performance is quite far from enough.

Employees’ psychological ownership for the organization has been proved to be

positively related to job satisfaction, organizational commitment, organizational citizenship

behavior (O’Driscoll, Pierce, & Coghlan, 2006; Van Dyne & Pierce, 2004), and performance

(Park et al. 2015; Aryee et al. 2009). In this sense, it is of certain value and significance for

researches to approach the effect mechanism of ethical leadership, that is boundary conditions

and influence processes with psychological ownership as a potential mediator variable included.


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There are more scholars focusing on the antecedent or outcome variables of

psychological ownership than those discussing the moderating factors between psychological

ownership and employees' outcome variables (Dawkins et al., 2017). Only five researchers are

found to explore the boundary conditions between psychological ownership and work results

(Brown et al., 2014; Ramos et al., 2014). This paper attempts to discuss the boundary conditions

between psychological ownership and employee performance.

More and more researchers realize the importance of support from colleagues in the study

of influencing mechanism on nurses' working attitude and behavior（Li, Early, Rao Evans,，

Goldman Z W, Booth-Butterfield, M., 2017）. Colleague support is expressed as emotional

attention to employees, information provision and the creation of a harmonious interpersonal

atmosphere (Tse, Dasborough, & Ashkanasy, 2008，Morgan, 2011). Working in a stressful

environment, nurses inevitably face negative emotions such as anxiety and fear. Support from

colleagues, especially emotional support, is very important to help nurses relieve stress and

improve self-efficacy.

Moreover, nursing is a humanistic profession with a unique scientific body and needs

theoretical education, practical skill, and professional autonomy (Jafaragaee, Parvizy, Mehrdad

& Rafii, 2012). Nursing has specific criteria, including a strong commitment to offering services

to the society, belief in each individual’s respect and value, commitment to education and

autonomy. Highly committed nurses are more responsible for delivering health care for the

patients，which provides an important factor for the establishment of a sustained doctor-patient

relationship.

Taken together, for the sustainable development of hospitals and to fulfill the social

responsibility, we thus seek to disclose the controlling effect of ethical leadership on employee

work performance and attempt to make certain contributions as follows: firstly, the role of a

motivational resource (i.e., psychological ownership) is identified and verified as a critical

mechanism for ethical leadership to influence work performance positively; secondly, the

moderating role is focused on, yet scarcely investigated, in the ethical leadership–employee work

performance link, that is, affective support from colleagues and career commitment in caring

service. This study addresses the above-mentioned challenges based on the theories of social

exchange and social learning, which help suggest our study’s hypotheses. And the conceptual

framework developed is shown in Figure 1.


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Figure 1. The Conceptual Framework

II. Hypothesis Development

1. Ethical Leadership and Work performance

Leaders' ethical behavior not only affects their own credibility, but also their

subordinates' moral behavior (Brown et al., 2005, p.120). Ethical leadership is defined as “the

demonstration of normatively appropriate conduct through personal actions and interpersonal

relationships, and the promotion of such conduct to followers through two-way communication,

reinforcement, and decision making” (Brown et al., 2005, p.120). Ethical leadership not only

embodies the leader himself as an ethical person characterized by honesty, integrity, fairness and

approachability, but also as an ethical manager sets up a moral example, guides subordinates to

abide by good moral norms, and adopts ethical strategies to influence employees' behavior.

This study suggests that ethical leadership plays a positive role in nurses' work

performance. Social learning theory and social exchange theory can be used as important

explanatory frameworks (Ahn, Lee, &Yun, 2018). According to social learning theory (Bandura,

1977), individuals are influenced by other people's attitudes and behaviors. In other words,

individuals observe other people's behavior and choose acceptable and normative behavior.

Leadership is an important source for subordinates to imitate and learn normative behavior.

Ethical leadership shows high work ethics, caring for subordinates, and two-way communication

psychological

ownership Ethical

leadership

Emotional

support

Job performance

Career

commitment


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with subordinates. (Brown, Treviño & Harrison, 2005; Islam et al., 2018), so it can be a better

source of subordinate behavior guidance (Brown and Treviño, 2006, Brown & Mitchell 2010).

Some empirical studies have also shown that ethical leadership has a positive impact on

organizational commitment (Nuebert et al. 2009) and organizational citizenship behavior (Mayer

et al. 2009). Nurses' work is required to abide by medical ethics, do their best and care for others.

Therefore, a nurse with ethical leadership is often influenced by leadership's role model effect,

and will be more concerned about patients. She/he demands her/his work with higher medical

ethics standards, thus having higher work performance.

According to the theory of social exchange, the exchange between individuals and

organizations includes not only material exchanges (such as remuneration for work, etc.) but also

psychological (or social) ones, such as trust, support, respect, etc. (Blau, 1964). In the process of

social exchange, based on the principle of "reciprocity", individuals will make greater efforts to

behave in favor of organization, which is manifested by high organizational commitment, job

performance, organizational citizenship behavior and so on. Leaders are often seen as agents of

organizations. Studies have indicated that ethical leaders are sincere to their subordinates, care

for their needs, respect their subordinates, and communicate with them fully, thus establishing a

high-quality LMX (Walumbwa et al., 2011). When they establish the relationship of trust with

their leaders, nurses perceive the concern and support of leaders for their work, the fairness of

job performance evaluation, and based on the principle of reciprocity nurses will devote more

efforts to work, and they will be able to solve problems more actively in response to the pressure

of work, showing a higher level of work performance.

Therefore, it is proposed as follows:

H1: Ethical leadership is positively related to work performance.

2. Mediation Effect of Psychological Ownership on the Relationship between Ethical

Leadership and Work performance

In order to explore feasible strategy to reduce the rate of turnover and even eliminate

turnover, group/organizational management perspective can be an important organizational

contextual effect strategy, which highlights ethical leadership in effective changing individual

attitude and behaviors.

Ethical leadership can effectively change individual working attitude and behavior, which

becomes an important group/organizational contextual effect strategy. Treviño et al (2006)

pointed out that an ethical leader is a moral person at first, which means he/she follows a series

of basic ethic morals and puts into effect during daily life and work (Brown, 2007); secondly,

he/she should be a moral manager, urging subordinates to understand the value of ethic morals,


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leading them to do right things by setting up goals, caring about subordinates, sharing power,

emphasizing integrity, upholding justice, ethic guiding and focusing on sustainability

(Kalshoven, K., Den Hartog, D. N., & De Hoogh, A. H., 2011). In addition, ethic leader is

willing to listen to employees’ thinking about work (Kalshoven et. al, 2011), and employees tend

to feedback in time about work schedule. Besides, the work performance is not the only focus of

this kind of leader, and work experience of employees is also concerned by him/her (Brown et

al., 2005).

Specifically, when interacting with contextual factors, ethic leadership in this case,

employees’ psychological ownership is strengthened or weakened, which thereupon create

positive or negative effects on their work performance. Furby (1978) believes that ownership can

stimulate the responsibility effecting on behaviors. When the three basic motives of employees

(place, self-efficacy and self-identity) are satisfied, employees will be active at protecting

organization and completing the actions expected in their roles in the organization (Dyne &

Pierece, 2004). Therefore, the mediation effect of psychological ownership on the relationship

between ethic leadership and work performance is proposed.

H2: Psychological ownership mediates the relationship between ethical leadership and work

performance.

3. Moderation Effect of Career Commitment and Emotional Support

Career commitment (CC). Psychological ownership is concerned about “to what extent

do I feel this organization is mine?”, which is not naturally transferred to positive working

behaviors. The effect of psychological ownership on work performance is still dependent on the

answer to “why do I need to protect my status in the organization”, which we interpret as

career/occupational commitment. Career/occupational commitment is defined as the

“psychological link between an individual and his/her career/occupational that is based on an

affective reaction to that career/occupation” (Lee, Carswell, & Allen, 2000, p. 800).

Studies have indicated that career commitment is positively related with job satisfaction

(Satoh, Asakura, Watanabe, & Shimojo, 2015), and negatively associated with job stress (Lee et

al., 2000; Wang, Smailes, Sareen, Schmitz, Fick G, & Patten, 2012). If an employee experiences

low career commitment, he/she tends to leave the job, easily get stressed and seldom enjoy the

satisfaction from work, it is reasonable for him/her to ensure the quality of work, never to talk

about work performance. On the contrary, an employee can be better able to cope with work-

related stress if he/she has higher career commitment.

Unlike individuals in other fields who might not have the opportunity to use their

professional skills regularly, clinical staff are constantly and actively engaged in the very


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behaviors that define their professional role. Commitment to promoting caring abilities satisfying

of being a nurse and belonging to the nursing profession are identified in the fieldwork phase.

Research found that nurse’s career commitment has a positive impact on patient safety and care

quality (Teng, Dai, Shyu, Wong, Chu, and Tsai ,2009). Therefore, the moderation role of career

commitment in the effects of psychological ownership on work performance is proposed.

H3: Career commitment positively moderates the relationship between psychological ownership

and work performance.

Emotional support (ES). Ethical leadership can create positive working environment,

leading to a certain extent of psychological ownership. However, the direct support from the

peers can exactly decide the final success of the job. Researches validate that social support is

negatively related with work burnout by providing buffer effect (Walsh M, Dolan B, Lewis A,

1998), less of which focus on the support from coworkers. Especially in China's culture of higher

power distance, employees are more likely to talk with colleagues than to leaders when they

encounter difficulties. Therefore, emotional support from colleagues may be an important

contextual factor affecting employee performance. When employees have higher psychological

ownership, they perceive a higher sense of belonging and have self-efficacy in overcoming

difficulties and learning when they encounter difficulties in their work（Avey et al.，2009）.

But at the same time, some scholars have found that high level of PO may also be negatively

related to individual physical and mental health, leading to workaholism (Oates, 1971) and job

burnout (Maslach & Goldberg, 1998). Nurses' work needs more help from colleagues and team

work is the main form, since there are many emergencies and exceptions in their work. When the

level of workplace friendships is high, the positive effect of psychological ownership will be

stronger. In the case of job burnout or depression caused by high psychological ownership,

colleagues' emotional support can effectively alleviate the generation of stress, thus producing

more positive emotions, and thus improving job performance. While if the emotional support of

colleagues is very low, it is easier to enhance the possibility of negative consequences of

psychological ownership and reduce its positive role.

Therefore, the moderation role of emotional support on the effect of psychological

ownership is also proposed.

H4: Emotional support from coworkers positively moderates the relationship between

psychological ownership and work performance.


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III. Methodology

1. Research Design and Setting

A paper-and-pencil questionnaire including measures of ethical leadership, psychological

ownership, career commitment, emotional support, work performance, demographic questions

was administered to nursing staff and their immediate leader of eight Chinese hospitals.

Participation to the study was voluntary and questionnaires were completed during working

hours. Data were collected from two sources to avoid single source bias: one is frontline nurses

and the other is their immediate supervisors. Before the survey was conducted, a training was

delivered by heads of each department to all the participants about the purpose of this survey to

assure the confidentiality and anonymity of the responses, and to emphasize the voluntary nature

of participation.

We number coded the surveys to match the responses of each nurse with those of his/her

supervisor. After deleting invalid, incomplete and unmatched questionnaires, a total of 363 valid

supervisor–subordinate dyad questionnaires constituted the final sample for the study, which

represented 75.6 percent of all the respondents we surveyed. Of the 363 subordinate respondents,

all female nurses, relatively young (aged between 20 and 35 years covered 83.2 percent), and

well educated (holding bachelor degree and above covered 86.2 percent). The average job tenure

was 9.83 years.

2. Measures

The Chinese version of questionnaires were created following the translation and back-

translation procedures (Brislin,1986), which were measured on a 7-point Likert scale by asking

for agreement with the statements (1 = strongly disagree,7 = strongly agree).

Ethical leadership. This was measured by eight items (e.g. ‘my leader listened to what

an employee had to say.’ my leader disciplined an employee who violated ethical standards)

taken from the study from Lin, Ma and Johnson (2016). The Cronbach’s alpha for this scale

was .88.

Psychological ownership. Nurses completed the psychological ownership scale,

Psychological ownership for the organization was measured using Van Dyne and Pierce’s (2004)

Seven-item scale (e.g. This is MY organization; I sense that this organization is OUR hospital).

The Cronbach’s alpha for this scale was .93.


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Career commitment. The Macleod Clark Professional Identity sub-scale (Licata & Klein

2002) was used to measure career commitment. Specifically, five items were taken (e.g. ‘I’m

proud to be a nurse/physician’). Previously reported reliability for the whole scale was a = 0.83.

Emotional support. Emotional Support was measured using the five-item scale

developed by Methot, Lepine, Podsakoff and Christian (2015). Sample items are “My coworkers

share related personal experiences as an alternative perspective to my problems. “My coworkers

listen to me when I’m frustrated about something and need to vent”. The Cronbach’s alphas of

the scale was 0.93.

Work performance. Work performance was measured by the immediate supervisors,

using the six-item scale developed by Singh, Verbeke and Rhoads (1996) with Cronbach’s

reliability coefficient of 0.90.

Control variables. Several control measures were used to eliminate influences related to

outcomes in our model: age, gender, marital status, education level and job tenure.

3. Results

Confirmatory factor analyses. We performed a series of CFAs to assess the

discriminant validity of the study variables. We also compared model with a series of alternative

models. The results indicated that the hypothesized five-factor model (χ2= 1361.48, df= 424; CFI

= 0.89; TLI = 0.88; RMSEA = 0.08) presented a significant change in chi-square compared with

other models.

Table 1. Results of confirmatory factor analyses

Model χ2 Df RMSEA CFI TLI

Five-factor model 1361.48 424 0.08 0.89 0.88

Four-factor modela 1701.18 428 0.09 0.85 0.83

Three-factor

modelb 2407.20 431 0.11 0.76 0.74

Two-factor modelc 3139.12 433 0.13 0.68 0.65

Single-factor

modeld 3761.42 434 0.15 0.60 0.57

a Combines CC and ES into one factor.

b Combines PO, CC, and ES into one factor

c Combines EL and PO into one factor, other variables are combined into one

factor

d Combines all variables into one factor


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Following the suggestions of Podsakoff, Mackenzie, Lee and Podsakoff (2003), the

results of a Harman one-factor test indicated that the fit was unacceptable (χ2/df = 8.67; CFI =

0.60; TLI = 0.57; RMSEA = 0.15). Meanwhile, the data was collected from different sources. In

conclusion, we are assured that our findings were not seriously threatened by common method

bias.

Correlations among study variables. Table 2 displays the means, standard deviation

and correlation Coefficients among the variables. The correlations indicate that ethical leadership

is significantly associated with psychological ownership and work performance (r=0.68, p<0.01;

r=0.45, p<0.01, respectively). We also found that the psychological ownership was significantly

related to work performance (r=0.59, p<0.01).

Table 2 Mean Values, Standard Deviation and Correlation Coefficients

Variables 1 2 3 4 5 6 7 8 9

1.Age 1.00

2.Marital

status 0.08 1.00

3.Educatio

nn

.418*

* 0.03 1.00

4.Tenure .764*

* 0.10 .462

** 1.00

5.EL -0.04 -

0.06 0.01 -

0.05 1.00

6.PO -0.04 -

0.08 0.03 -

0.04

.68*

* 1.00

7.ES -0.08 0.00 -

0.01

-

0.09

.56*

*

.65*

* 1.00

8.CC -0.04 -

0.08 0.04 -

0.08

.35*

*

.42*

*

.34*

* 1.00

9.JP -0.01 -

0.04 0.05 -

0.01

.45*

*

.59*

*

.61*

*

.37*

* 1.00

Mean

value 2.71 1.83 2.38 117.

95 5.07 5.15 5.32 5.19 4.67

SD 0.81 0.47 0.72 100.

30 1.30 1.40 1.46 1.26 1.42

Note：** p < 0.01，* p < 0.05;

Regression models. In addition, we followed Kenny, Kashy and Bolger’s (1998)

procedure to test the mediating effects of psychological ownership. In step 1, ethical leadership is

expected to be significantly related to work performance, which was tested and verified model 2,

r =0.33; P<0.01), offering support for H1. In step 2, the relationship between ethical leadership

and psychological ownership was also validated (model 7, r=0.67; p<0.01). In the last step, for

full mediation of the effect of our mediating variables, the relationship between ethical

leadership and work performance become non-significant (model3, r=0.11, ns). In a word, the

results reveal that the relationship between ethical leadership and work performance was

completely mediated by psychological ownership, offering support for H2.


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Table 3. Model results

Note：** p < 0.01，* p < 0.05;

Hypotheses 3 and 4 predicted that career commitment and emotional support enhanced

the psychological ownership–work performance relationship. From Table 3, We found that the

psychological ownership–career commitment interaction term is not significantly related to work

performance (model 5, r =0.04, ns,), Hypotheses 3 is not supported. We further found that the

Variable JP PO

Control variable M1 M2 M3 M4 M5 M6 M7

Age 0.0

3 0.04 0.06 0.06 0.06 -

.07 -0.03

Marital status -.07 -.05 -0.04 -.041 -0.04 -

.08 -0.04

Education .08 .07 0.05 0.05 0.05 .07 0.04

tenure -.13 -.12 -.11 -.121 -0.12 -

.02 0.01

Independent

variable

EL .33*

* .11 .67**

Mediation

variable

PO .33** 0.28*

*

0.32*

*

CC 0.17*

* 0.14

ES 0.04 0.12

Interaction effect

PO× CC 0.04

PO × ES 0.18*

*

Adjusted R2 0.0

1 0.11 0.17 0.19 0.21 0.0

0 0.45

∆R2 0.0

2

0.11

**

0.06*

* 0.18 0.03*

*

0.0

1

0.44*

* F 1.5

0

9.81

**

12.92

**

12.26

**

11.47

**

1.1

0

56.96

**


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psychological ownership–emotional support interaction term significantly related to work

performance (model 5, r = 0.18, p < .01), thereby supporting Hypothesis 4. Figure 2 was plotted

following Aiken and West’s (1991) procedure to illustrate the nature of the significant

interactions. Figure 2 shows that ethical leadership had stronger positive effects on work

performance when employees received higher levels of emotional support. Such evidence further

supported Hypotheses 4.

Figure 2. Interaction of PS and ES on Job Performance.

IV. Discussion

This study found that ethical leadership has a significant positive impact on nurses' work

performance in the medical system. Based on social learning theory and social exchange theory,

ethical leadership shows integrity, honesty, fairness, concern for subordinates, two-way

communication and a strong sense of ethics and morality, which can improve the performance of

subordinates. Secondly, ethical leadership affects employees' performance through psychological

ownership. Psychological ownership plays a complete mediation role. Ethical leadership

stimulates the improvement of employee's psychological ownership through the satisfaction of

subordinates' place, self-efficacy and self-identity, and then improves the level of work

performance. Thirdly, colleagues' emotional support has a significant moderating effect between

psychological ownership and work performance. Colleagues' emotional support can alleviate the

possible pressure and depression caused by high psychological ownership, thus enlarging the

positive role of psychological ownership.

1. Theoretical Implications

The purpose of this paper is to reveal how ethical leadership of nurses in the medical

system can promote nurses to show higher performance in the workplace. There are three main

theoretical contributions in this study: firstly, this study explores the mediating mechanism and

regulating role of ethical leadership and nurses' work performance, and expands the application

context of existing researches. Most of the existing literatures discuss the impact of ethical

4.0

5.0

6.0

7.0

low PS high PS

Low ES

High ES


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leadership on employees' attitudes and behaviors in the field of enterprises. With the reforming

of China's medical system and increasing concerns about the relationship between doctors and

patients, there are endless violations of medical ethics and social ethics. The impact of ethical

leadership on the hospital system needs to be paid attention to; secondly, in the previous

literature, when discussing the relationship between leadership behavior and work performance,

the main research line is social exchange theory. This study combines social learning theory and

social exchange theory, introduces psychological ownership as an important mediating variable,

and goes deep into the characteristics of nurses' work with job commitment and colleague

support added as contextual factors, which can be beneficial supplement to the existing

researches (Kark & Van Dijk 2007; Schaubroeck et al., 2012); thirdly, this paper also finds that

colleague support has a significant moderating effect between psychological ownership and work

performance, which is also an appeal for the study of moderating factors between psychological

ownership and outcome variables (Dawkins et al.，2017). In a word, this research model has

established close links in leadership, psychological ownership, work performance and other

fields, thus expanding the understanding of the relationship between leadership behavior and

work performance.

2. Managerial Implications

This study’s findings also have substantial practical implications besides the above

theoretical implications,

Firstly, considering the sustainable development of hospitals and better fulfillment of

social responsibility, hospitals should value ethics and treat it as a primary pillar on which the

foundation of their organizational culture is built. Steps need to be taken to enhance supervisors’

agreeableness and conscientiousness, since these two personal traits can lead them to exhibit

higher level of ethical leadership (Walumbwa & Schaubroeck, 2009). The personal traits, such as

integrity, transparent information sharing and accountability, need to be taken into consideration

when recruiting and promoting a nursing manager. Organizations need to invest in ethics training

and guidance on accountability, self-discipline, fairness, communications, and ethical dilemmas

to help managers improve ethical leadership (Grojean, Resick, Dickson, & Smith, 2004; Mayer,

Kuenzi, Greenbaum, Bardes, & Salvador, 2009).

Secondly, it is helpful to promote nurses’ psychological ownership to handle with poor

working environment. psychological ownership influences employees’ in-role behaviors,

promoting their initiative and accordingly reducing the cost of management and enhancing the

performance effectively. Service organizations expect employees to have higher ownership and

feel proud of being members, thus their behaviors can be favorable to the organization.


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In China, nurses are under high stress, behind which the top reasons include huge work

intensity, strained relationship between patients and doctors and nurses and long working hours.

A survey reports that 90.42% nurses work over 40 hours per week and 39% of nurses even over

50 hours with at least 2 night-shifts to take care of dozens of patients per nurse. On the contrary,

the salary for over half of the nurses is less than 4000 yuan, while the average salary in the

society is 6800 yuan. It also shows that more than 50% of the nurses has psychological wounded

caused by work and even 41.2% experience offensive behavior from patients and their families.

With an aim to enhance nurses’ psychological ownership, it is suggested that

management provide vision for front-line nurses in terms of career, improve position working

conditions, and enhance the security system.

Nurses cannot be fully concentrated on their job if they see no hope or future.

Management need to satisfy their career development needs, provide chances of professional

education and training. Organizational should timely release job vacancy information and

promise fair competition. Furthermore, as to the particularity of nurse job targets and contents,

safe and health working environment is the foundation for nurses’ daily work. Regular medical

examination, strengthening disinfection, isolation and protection work and establishing medical

care personnel health files can reduce the frequency of occupational injury. Flexible working

time and shifts can adjust the potential consequences of work intensity. Besides, external buffer

area, linkage with public security early-warning department, psychological counseling activities

can help bolster the sense of security, reduce the risks on work, and relax the pressure of nurses.

From the perspective of relationship between colleagues, the organization can provide

training and guidance to promote positive relationships between colleagues and warm and

supportive work environment.

3. Limitations and Future Research Directions

There exist some limitations in this study, especially about the study design. Firstly,

although the data in this paper are from different sources, the design of the questionnaire is still

cross-sectional design, which cannot explain the causality well. Longitudinal research design can

be adopted in the future to further verify the causality. Secondly, psychological ownership of this

study is mainly at the individual level. With the increasing attention of scholars to collective

psychological ownership, the influence of leadership behavior on collective ownership and team

performance in the future, and expand the research level of the effect of ethical leadership. In

addition, the impact model of ethical leadership and work performance only considers two

contextual factors: individual career commitment and colleague support. In the future, other

factors, such self-management team atmosphere and power distance at team level can be

considered.


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Organization or Human Capital Who Understands the System Better

Mandal

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Organization or Human Capital Who Understands the System Better

Susanta Mandal

Susanta Mandal, VIL Office ,

Xavier Labour Relations Institute (XLRI),

Jamshedpur, C.H. Area (East),

Jamshedpur – 831001, Jharkhand , India

[email protected]

Abstract

The concept of work has to be understood from the aspect of how easily it can be done even if it

means lifting and shifting of workloads through use of roles , structures , technology and

different ways of institutionalizing partnerships . In the course of my work two important factors

have been targeted “Labour” i.e . employee and “Organization” i.e. the way things can be

organized wherein cost dynamics play an important role . Cost factors in employing of labour as

well as in selecting of the processes to get the work done have been explained through a

framework as well as a Cost Dynamics Model .


The national business context for industrial SME cluster development in Pakistan: constraining and

facilitating factors

Fayyaz, Raud, and Syed

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constraining and facilitating factors

Anjum Fayyaz, Assistant Professor

Suleman Dawood School of Business (SDSB),

Lahore University of Management Science (LUMS),

Sector U, DHA Lahore, Pakistan 54792.

[email protected]

Hassan Rauf, Assistant Professor

University of Central Punjab (UCP) Business School,

Khayaban-e-Jinnah Road, Johar Town, Lahore, Pakistan.

[email protected]

Jawad Syed, Professor

Suleman Dawood School of Business (SDSB),

Lahore University of Management Science (LUMS),

Sector U, DHA Lahore, Pakistan 54792.

[email protected]

Abstract

This article adds to the literature of small and medium enterprises (SME) clusters by developing

a framework around the context in which industrial SMEs clusters operate. The study uses a

PESTEL analysis to review and identify the factors which facilitate or constrain the development

of SME clusters in a developing economy like Pakistan. The framework developed in this study

helps to understand how political, economic, social, technological, environmental, and legal

factors interact in either facilitating or constraining the development of SME clusters. The review

is also informed by the experiences and interactions of the authors with SME clusters in

Pakistan. The review suggests that almost all the components under the political, technological,

environmental and legal context constrain the development of SMEs clusters in Pakistan. Only

one out of four economic components, i.e., the performance of small-scale sector, is a facilitating

factor for SME development. Within the social context, the large percentage of the productive

age population and the subcontracting culture are some of the facilitating factors for SME cluster

development.

Keywords: Cluster Development, Context, Facilitating and Constraining Factors, PESTEL

Analysis, SMEs





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Constraining and facilitating factors

Introduction

The literature on small and medium enterprises (SMEs) highlights the importance of

SMEs not only for policy makers but also for the economic growth of developing countries

(Andersson et al., 2004; Nichter & Goldmark, 2009; Wang, 2016). SMEs contribute to

employment generation, poverty reduction, a wider distribution of wealth, and innovation

capabilities (Gray, 2006; Nolan & Garavan, 2016). Therefore, SME development provides a

major window of opportunity for the policy makers of the host country and for international

donors and NGOs in developing countries (UNIDO, 2001). However, while the literature

highlights the importance of SMEs for policy makers and for economic growth, there is dearth of

research (barring a few notable exceptions such as Hazlina Ahmad et al., 2010; Muhammad et

al., 2010) about the context and the business environment in which these SMEs and policy

makers operate.

Cooperation among SMEs provides economies of scale and scope to overcome the

limitations of their size; for example, clusters of SMEs enjoy the advantages of flexibility and

responsiveness. They can be more competitive than large firms (Humphrey & Schmitz, 1995;

Andersson et al., 2004). SMEs that participate in clusters can benefit from a specialized

infrastructure, an increased ability to penetrate new markets, a qualified workforce, the ability to

meet clients’ needs, and cost reduction in manufacturing operations (Malakauskaitė & Navickas,

2009).

The literature on industrial districts and small-firm clusters has focused on interfirm

networks using the examples of Italian industrial districts; in addition, it has emphasized how the

development of small firms can provide high incomes and sustainable growth through

continuous upgrading and development (Humphrey, 2003). The literature provides reasons to

develop clusters and networks to promote SMEs, but it does not shed much light on the macro-

environment in which SMEs operate. Clearly, there is a gap in the literature regarding how SME

cluster development is influenced by the contexts in which such development occurs. This article

addresses this gap by focusing on the particular context of Pakistan.

Pakistani economy has experienced growth over recent decades, but the growth of SME

clusters has been lagging behind. In the early years of Pakistan’s development during the post-

independence period, the manufacturing sector’s growth rate was in the range of 8-10%, but it

decreased to 2.8% because of the 1971 war with India (Hasan, 1997). The overall manufacturing




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sector recorded growth of approximately 10% in the mid-2000s, but the Pakistani government

primarily focused on the large-scale sector instead of SMEs and SME clusters (Saif113sb, 2015).

This article reviews the Pakistani context by conducting a PESTEL analysis of the

national context in which SME clusters operate in Pakistan. It examines the implications of

macro-environmental issues and their effects on SME development in Pakistan. The importance

of this article increases when it explains the context of the Pakistani business environment for

SMEs, remaining mindful of the effect of this environment on SMEs and their attitudes towards

competitors, buyers and support institutions when they respond to the international markets. This

article provides an overall understanding of Pakistan’s business environment.

The article is structured as follows. In the next section, we explore the role of each

component of the PESTEL framework to understand the implications of these components for

SME development in Pakistan and how they positively or negatively affect the development of

SME clusters in Pakistan. In the concluding section, we discuss the constraining and the

facilitating factors, related to the Pakistani macro context and its implications for the

development of SME clusters.

PESTEL Analysis

The article uses a PESTEL (political, economic, socio-cultural, technological,

environmental and legal) analysis to describe a framework of contextual factors that affect SME

cluster development. PESTEL is part of an external analysis when conducting a strategic analysis

or doing market research and gives a holistic overview of relevant macro-environmental factors.

It is a strategic tool for understanding business position, market trends and potential and

direction for operations (CIPD, 2018). The study is informed not only a review of relevant local

and international literature but also by the authors’ extensive work on Pakistani SMEs and SME

clusters.

1. Political context for SME development

The political structure of the Islamic Republic of Pakistan is a federal parliamentary

democracy in which the President (ceremonial Head of State) and the Prime Minister (Head of

Government) are the executives. The National Assembly (the lower house) has 342 members,

and the Senate (the upper house) has 100 members. Historically, whichever party forms the

government tends to implement its own policies and agendas thus disrupting continuity with the

previous rulers’ policies (Ahmed, Saleem & Iftikhar, 2012).




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In the 1990s, at the end of the Afghan War, foreign loans and debt relief were withdrawn

from Pakistan. Debt-servicing pressures caused by the low savings rates and the balance of

payment deficits related to low export growth and poor infrastructure, which combined to reduce

gross domestic product (GDP) growth, resulting in a protracted economic recession (John, 2009).

The 1990s were marked by democratically elected regimes that were kept in strict check by the

military establishment and were also characterised of inefficiencies and corruption (Burki, 1999;

Hussain, 2012). By the late 1990s, three key elements of a crisis threatened the state: (i) a

collapsing economy, (ii) threat to the life and property of citizens resulting from rampant crime

and the emergence of armed militant groups of religious extremists, and (iii) the erosion of many

institutions of effective governance (Hussain, 2012). In May of 1998, Pakistan conducted its first

nuclear test. Economic sanctions were imposed against Pakistan by Western governments

(Ahmad, 2006) and the country was almost at the brink of default on its external payments

(Hussain, 2004).

Pakistan’s industrial policy has a chequered history. Industrial policies were made either

as a part of Pakistan’s medium-term development plans or in response to a crisis. Five industrial

policies or distinct approaches have left a lasting impression on the structure of Pakistan’s

industry (Burki, 2008; Chaudhry, 1996).

The First Five-Year Plan (1955-1960) focused more on new venture creation, the

increase in the production capacities of existing units and enhancements in exports, which

positively affected the industrial sector’s share in Pakistan’s GDP (Bengali, 1999). The Second

Five-Year Plan (1960-1965) shifted the focus of new establishments from consumer goods to

heavy industry to improve industrial performance. The Third Five-Year Plan (1965-1970) was a

partial success because of natural disasters and reduced foreign aid to Pakistan. The period of the

Fourth Five-Year Plan (1970-1975) was disappointing because of the war with India, the

devaluation of Pakistan’s currency, the nationalization of industries by the government, labour

unrest and the unfavourable investment climate (White, 2015). The Fifth Five-Year Plan (1978-

1983) was a failed attempt to rejuvenate the disappointing performance of the Fourth Five-Year

Plan because of the war in Afghanistan, increased international oil prices and increased defence

expenditures. The Sixth Five-Year Plan (1983-1988) shifted towards the private sector with

heavy reliance on imported energy and low spending on health and education (Bengali, 1999).

The Seventh Five-Year Plan (1988-1993) more strongly emphasized private investment but there

was pressure on public-sector corporations to improve their financial performance. The Eighth

Five-Year Plan (1993-1998) was not implemented because of the successive changes in

government during 1993. From 2004 onwards, the government of Pakistan began developing

Medium-Term Development Frameworks (MTDF) instead of Five-Year Plans and developed a

plan for 2005 to 2010 (Chaudhary, Iqbal & Gillani, 2009). In 2015, Pakistan attained a fairly

diversified base of manufactured products ranging from essential consumer goods to chemicals,




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steel, heavy engineering and machine tool industries. The domestic production of items such as

refined sugar steel, fertilizer, cement, etc. has helped in import substitution and has saved a

substantial amount of foreign exchange (IPRI, 2014; Saif113sb, 2015).

There have been various policy approaches to industrialization in Pakistan in the last six

decades, beginning with industrialization by General Ayub Khan through the establishment of

finance companies such as the Pakistan Industrial and Commercial Investment Corporation (the

PICIC) and the Industrial Development Bank of Pakistan (the IDBP) (James & Naya, 1990). The

objective of this approach was to influence the scope of industrialization; this was an era of

growth without development. The second approach to industrialization occurred during the first

few months of Zulfikar Ali Bhutto’s tenure and was based on his decision to nationalize the

large-scale industry, which introduced several distortions into the management of the economy

and included widespread corruption (Noman, 1991). The third approach of the democratic

administrations in the 1990s was to bring back the private sector as the leader in economic

development by privatizing some of the state’s economic assets with minimal impact on

Pakistan’s industrial activity (Burki, 2008). The old industrial families had their assets restored

and went about conducting their business as before. General Pervez Musharraf’s government

played a prominent role in the private sector by providing considerable room to the financial

sector to participate in the industrialization process based on market considerations (Burki, 2008;

Khan et al., 2014).

Despite the above-mentioned approaches to industrial development, the private sector did

not develop enough confidence amongst the entrepreneurial class to stand independently and

address the changes occurring in the global economic system without government intervention

(Khan et al., 2014). Because of the frequent changes in industrial policy noted above, the

industrial sector has remained relatively backward compared to developments in other large

Asian economies (Burki, 2008).

For a long time, the mainstay of Pakistan’s industrialization strategy was large-scale

manufacturing, which recorded an 8.78% growth rate during 1950-2003 because it was

consistently supported by a set of macroeconomic policy measures. The small-scale sector also

registered an impressive growth rate of 5.06% during 1950-2003; that growth also occurred

without the direct benefit of policy support. However, the small-scale sector essentially existed

in the shadow of the large-scale manufacturing sector (Amin, 2004).

In 2009, a politically unstable Pakistan emerged as a new global hub for anti-West

militancy (Yusuf, 2014). Some of the key incidents in Pakistan, including the capture of Osama

Bin Laden on May 2, 2011 from Abbottabad, Pakistan, and the terrorist attack on the Mehran

Naval Base in Karachi, Pakistan, on May 22, 2011 (Shafqat & ul Haque, 2011), shook the




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foundations of the Pakistani security establishment and alarmed the public about the

vulnerability of the Pakistani state (Shafqat, 2011). These incidents created scepticism about the

armed forces’ ability to protect Pakistan’s physical infrastructure, air space and citizens.

Consequently, this concern led to the formation of a joint military offensive by the Pakistan

Armed Forces against various militant groups. The operation was launched on June 15, 2014, in

North Waziristan along the Pakistan-Afghanistan border as a renewed effort against militancy in

the wake of the June 8 attack on the Jinnah International Airport in Karachi by Tehrik-i-Taliban

Pakistan (TTP) and the Islamic Movement of Uzbekistan (Khan, 2010; Shafqat, 2011).

These issues appear to be serious constraining factors for SME development in Pakistan

because it is difficult to expect SME development or any socio-economic development to occur

with inconsistent policies, an unstable government, a poor focus on the small-scale sector and an

insecure business environment in Pakistan. Therefore, the three major constraining factors of

SME cluster development in Pakistan’s political context include: a) inconsistent industrial

policies and unstable political governments; b) the political regimes’ major focus on the large-

scale sector; and c) the poor application of counterterrorism policies.

2. Economic context

Pakistan is one of the few developing countries that achieved an average growth rate of

more than 5% over a four-decade period ending in 1988-89. Consequently, the incidence of

poverty had declined from 40 to 18% by the end of the 1980s (Husain, 2005). Pakistan was a

country with 30 million people in 1947 that could not feed themselves and had to import all food

from abroad. In 2002, Pakistan’s farmers not only were able to fulfil 145 million people’s

domestic needs for wheat, rice, sugar and milk at a much higher per capita consumption level but

also exported wheat and rice to the rest of the world (Lasi, 2008). Pakistan had hardly any

manufacturing industries in 1947 (Hussain, 2004). Five decades later, the manufacturing

production index was 12,000 with a base of 100 in 1947. Steel, cement, automobiles, sugar,

fertilizer, cloth and vegetable ghee, industrial chemicals, refined petroleum and a variety of other

industries manufacture products not only for the domestic market but in many cases for the

world market as well (Ahmad, 2006; Hussain, 2004).

Pakistan’s manufactured exports in the 1960s were higher than those of Malaysia,

Thailand, Philippines and Indonesia, reaching $12 billion in 2003 (Hussain, 2004). In 2014,

agriculture accounted for more than one-fifth of output and two-fifths of employment. Textiles

accounted for most of Pakistan's export earnings (MOF, 2011). Pakistan’s inflation rate averaged

7.99% between 1957 and 2015, reaching an all-time high of 37.81% in December 1973 and a




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record low of -10.32% in February 1959. Pakistan suffered the only economic decline in its GDP

between 1951 and 1952 (Siddiqi, 2007).

Pakistan’s population has grown rapidly from approximately 30 million in 1947 to more

than 130 million in 1996. Its rate of annual growth has averaged 3% since 1960 (Husain, 2010).

Pakistan's average economic growth rate since independence has been higher than the world

economy’s average growth rate during the same period. Average annual real GDP growth rates

were 6.8% in the 1960s, 4.8% in the 1970s, and 6.5% in the 1980s. Average annual growth fell

to 4.6% in the 1990s, with significantly lower growth during the second half of that decade

(Hasan, 1997).

According to the Pakistan Bureau of Statistics (PBS), the manufacturing sector contributes

13.3% to GDP and 14.2% to Pakistan’s total labour force with a decrease in registered growth

from 4.45% in 2013-14 to 3.62% in 2014-15 (Economic Survey of Pakistan 2014-15). The large-

scale manufacturing sector contributes 10.6% to GDP and 20% to Pakistan’s industrial labour

force with a decrease in registered growth from 4.6% in 2013-14 to 2.5% in 2014-15. The small-

scale manufacturing sector contributes 1.7% to GDP and 80% to Pakistan’s industrial labour

force with a minor decrease in registered growth from 8.29% in 2013-14 to 8.24% in 2014-15

(Economic Survey of Pakistan 2014-15). Pakistan’s major economic sectors include textiles,

food, beverages and tobacco, coke and petroleum products, pharmaceuticals, chemicals,

automobiles, iron and steel products, fertilizers, electronics, leather products, paper and board,

engineering products, rubber products, non-metallic mineral products and wood products (see

chapter 3 of the Economic Survey of Pakistan 2014-15).1

Of the fourteen major industrial sectors in Pakistan, nine show a decreased percentage of

registered growth compared to the previous financial year, whereas only five sectors show an

increased percentage. These sectors include light engineering, iron and steel, automobiles,

electronics/information technology (IT) and pharmaceuticals. Therefore, it can be assumed that

there is a possibility of SME development and SME cluster and network development in these

sectors, but there are some additional factors such as inflation, exchange-rate fluctuation and the

number of SMEs in these industries.

The inflation rate measured by the changes in consumer price index in Pakistan averaged

8.7% during July 2013-April 2014 compared to 7.7% in July 2012-April 2013 (PES, 2014a). The

average food inflation in July 2013-April 2014 was estimated at 9.3% and the average non-food

inflation was 8.2% compared to 7.1% and 8.2% in the corresponding period of 2012-13,

respectively (Economic Survey of Pakistan – Budget Special 2014-15). In 2013, the Pakistani

1 http://www.finance.gov.pk/survey_1415.html




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rupee depreciated to an all-time low—i.e., 106 rupees to the dollar—because of the high demand

for import payments (Bilawal et al. 2014). Depreciation of the rupee further inflates the import

bill and increases the domestic price level, thus reducing purchasing power and causing inflation

(Shaheen, 2013).

After independence, Pakistan had no currency, and for at least six months Pakistan used

India’s currency. Pakistan used a fixed exchange rate until the first half of 1982. In 1991, the

Pakistani rupee began to float in the open market as the result of economic and fiscal reforms.

However, there has been constant interference from the State Bank of Pakistan in Pakistan’s

exchange markets to stabilize the exchange rate (PKR/dollar). In 2014, the exchange rate of the

Pakistani rupee to the dollar was approximately 100:1 (Bashir, Shakir, Ashfaq, Hassan, 2014).

This exchange-rate fluctuation also affected the growth of multinational companies in Pakistan

and increased the degree of risk for financial institutions such as banks, stock exchanges and

firms. Moreover, exchange-rate fluctuation affected macroeconomic factors in Pakistan such as

market prices, inflation rates, interest rates, wages, and unemployment and output levels (Bhutt,

ur Rehman & ur Rehman, 2014).

Government statistics showed that Pakistan’s SME sector recorded impressive growth of

14.7% during from 1987/88-1996/97 (Haneef, 2010). In 2005, SMEs’ contribution to Pakistan’s

economy, employment and poverty reduction was noted in the fact that 90% of all private-sector

manufacturing units employed fewer than 99 workers, and SMEs employed 78% of the non-

agricultural labour force. SMEs in Pakistan contributed to approximately 30% of Pakistan’s GDP

and 140 billion rupees to exports, which represented 25% of the total manufactured goods

exported from Pakistan (Husain, 2005).

The literature on the poor growth of Pakistan’s large-scale sector and major industries

does not directly address the effect of that growth on Pakistan’s small-scale sector. In addition,

Pakistan’s rising inflation is not clearly linked to the small-scale sector, but it appears to be a

constraining factor for SME cluster development in Pakistan. Depreciation of the Pakistani rupee

and the fluctuating exchange rate are also constraining factors for SME development in Pakistan.

The only facilitating component linked to economic factors is the positive growth of the small-

scale sector in a developing economy such as Pakistan. Therefore, the major components that

facilitate and/or constrain the development of SMEs and SME clusters in Pakistan include: a)

poor growth of the large-scale sector and the industrial sector; b) inflation; c) depreciation of the

Pakistani rupee and exchange-rate fluctuations; and d) better performance of the small-scale

sector.




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3. Social context

In Pakistan, the 40 most powerful business groups and individuals include 5

conglomerates and 30 family businesses. Of the 30 family businesses, 7 represent the Chinioti

Sheikh Beraderi, 2 represent the Chinioti Vohras Beraderi, 5 represent the Memon Clan, 1

represents the Ismaeeli Sheikh, 1 is headed by the Maliks from the Arian Punjabi family, and the

other 14 represent non-Beraderi and non-clan family businesses. Ten businesses are headed by

individual entrepreneurs, of which only one appears to be an SME cluster-based business. Most

of the Beraderi- or clan-based entrepreneurs have also taken leadership positions in politics

(governor or mayor), chambers of commerce, business associations / societies or government-

formed commissions in partnership with the private sector.

In Pakistan, minority cultures are known for their enterprising behaviour. For example,

Gujratis Karachi are reputed to be brilliant financial managers. The Chiniotis, Memon, Vohras,

Sheikhs, Ismaeelis and Sialkotis were observed to have a flair for trade and textile manufacturing.

Traders in Bara markets could sell almost anything (Sayeed & Memon, 2007).

The country’s gravest problem is its precarious law-and-order situation (Sheikh, 2009;

Mustafa, Akhter & Nasrallah, 2013). At the end of the 1990s, more than one-third of Pakistan’s

households were below the poverty line; that number reached nearly 40% for the rural areas. A

large chunk of the population lives below the poverty line (Arif, 2000) in miserable conditions.

Consequently, we read crime stories in newspapers that characterized the lower orders of society

as going through illegal channels to obtain the financial prosperity that they cannot achieve

otherwise (Sheikh, 2009; Javaid, 2015).

Illiteracy is yet another problem in Pakistan. The literacy rate has stalled at 56%;

ironically, that rate includes people who can read and write their name in Urdu. In the last few

decades, the upward trend in the Pakistan’s illiteracy rate (Sheikh, 2009; SBP, 2002) is

aggravated by the fact that more than 50% of children in Pakistan do not complete their primary

education. Uneducated adults make only a negligible contribution to the national exchequer.

Corruption is another significant social problem. According to the latest report of

Transparency International, Pakistan has been ranked the 42nd most corrupt nation in the world.

From clerics to high officials and bureaucrats, all are involved in corruption of some sort (TIP,

2011; Sheikh, 2009). Corruption in government departments is deeply embedded. There is a lack

of accountability: wealthy people and those in power believe they cannot be held responsible for

their actions. Thus, they continue to loot national treasures and find ways to legalize their black

money (Farooq, Shahbaz, Arouri & Teulon, 2013).




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Unemployment is another major social problem. A major portion of Pakistan’s population

consists of youth, but a large number of young people who have the ability and willingness to

work are unemployed (Ali, 2010). Pakistan’s official unemployment rate is 7.4%, but according

to some private estimates, the rate of unemployment is 12%. There are many reasons for

unemployment, such as technology upgrades and the defective education system. Individuals

who cannot find work in Pakistan migrate to other countries with better prospects (Chaudhary &

Hamid, 1998; Qayyum & Siddiqui, 2007).

Child labour is widespread in Pakistan. In both large cities and small villages, innocent,

malnourished children are employed in various forms of labour (Sheikh, 2009). They work as

welders, mechanics, plumbers, electricians and in industries such as carpet-weaving, glass and

football making. These children receive only meagre wages, and no educational facilities are

provided (Boje & Khan, 2009). Pakistani children, particularly older girls, drop out of school

unable to participate in the labour market (Ray, 2000).

Population expansion has been an issue of concern for all governments (Adil, 2015; Omer,

2014). The decade of 1941-51 experienced a fairly high population increase of 19.4%, because

of excess immigration from India following the partition of the Subcontinent. The exceptional

population increase of 27.0% in the period 1951-61 was primarily the result of an excess of

births over deaths resulting from a sharp decrease in the death rate caused by improved

environmental conditions and health facilities (Afzal & Hussain, 1974). After peaking at more

than 3% in the 1960s and 1970s, reaching approximately 3% in the 1980s and then falling below

3% in the 1990s, annual growth rates have begun to show a declining trend. From 1981-1998,

the annual growth rate was 2.6%. In 2001, the estimated annual growth rate was 2.1%, which

was still one of the highest in the region (Hakim & Mahmood, 2001).

Inflation is another key challenge. According to the Economist Pakistan Report (2007) on

Pakistan’s economic problems, the prices of consumer products in general and food products in

particular are skyrocketing. Core inflation soared to 18.85% in the first quarter of 2009 until the

State Bank of Pakistan took steps to curb inflation through tight monetary policies (Hassan &

Malik, 2014). Increased oil prices internationally and Pakistan’s internally unfavourable business

conditions are two important factors responsible for the high rate of inflation. The Consumer

Price Index (CPI) and the Wholesale Price Index (WPI) are at all-time highs. In contrast, the

purchasing power of the masses is at an all-time low (Sheikh, 2009).

Unemployment is already prevalent, and now the question of providing employment to

internally displaced persons has also become a serious concern. This unproductive population is

a growing economic problem in Pakistan (Shaikh, 2013; Sheikh, 2009; Sonu, 2012).




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Entrepreneurs in the manufacturing industry of Pakistan have been found to operate in a

strong, close-knit “Beradari” system. For example, in the light engineering sector of Punjab,

Mughals, Bhuttas, Lohars, Skeikhs and Kashmiris were the primary castes involved in the

manufacturing business. Although many of them were close relatives, their overall business

environment had a sense of jealousy and leg-pulling (Mehmood & Haroon, 2006). Cut-throat

price competition amongst manufacturers had resulted in products with compromised quality,

reduced value and a culture of mistrust, collectively served as a barrier to the growth of these

industrial clusters (Farooqi & Haroon, 2006; Mehmood & Haroon, 2006).

Like all less-resourceful firms, SMEs typically had skill deficiencies and were unable to

compete with the larger firms’ better-qualified manpower. Inter-firm transfer of skilled labour

was a common phenomenon directly influenced by relative wage levels. In this game, the larger

firms had an advantage over SMEs (Quader & Abdullah, 2009).

The average educational attainment of Pakistan’s labour force was very low. In 2007-2008,

only 55% of the country’s working-age people were literate. The unemployment figures for

2003-04 indicated that 59.2% of the unemployed were literate or semi-literate, with the “pre-

matric” group being the largest at 29.5% (Batool, Naeem & Sana, 2009; Chaudhary & Hamid,

1998; Malik, 2014). The lack of formal management skills at all levels has resulted in poor shop-

floor organization and labour management in Pakistan. Most units were either managed by

entrepreneurs themselves or by the “Munshi” (lower-level managers/supervisors) to run business

operations and day-to-day tasks. The skills were transferred to the newcomers through the

conventional system of “Ustad/Shagird”2. All of the training was essentially provided on the

shop floor (Bhatti, 2006)3.

In 2012-13, 41% of Pakistan’s population was in the 0-14-year-old age group; this group is

economically unproductive and requires food, clothing, education, and medical care. Fifty-one

percent of the population was in the 15-59-year-old age group. This productive-age population

was the main source of accelerated economic growth (Asghar & Javed, 2011). Pakistan has the

tenth-largest labour force in the world. Statistics showed that Pakistan’s total labour force

increased from 50.0 million in 2005-06 to 59.7 million in 2012-13 (PES, 2014b), means that

more than 9 million people joined the labour force during this period. However, the employed

labour force increased from 46.95 million to 56.0 million during the same period, indicating that

the increase in the labour force could not be adjusted for completely in the employment sector;

therefore, there was an increase in unemployment from 3.10 to 3.73 million during this period

2 Conventional way of learning through the supervisor or senior skilled worker on the shop floor. 3 Interviews with the Cluster Development Agent and the Network Development Agent, UNIDO Cluster

Development Programme, Pakistan.




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(Hassan, 2014). In 2012-13, fourteen percent of Pakistan’s total labour force was employed in

the manufacturing sector, which was composed of 15% of the total male labour force and 11% of

the total female labour force in Pakistan (PES, 2014b).

Subcontracting in Pakistan is prevalent in the manufacturing sector and to some extent, in

the trade and service sectors. Sixty-three percent of manufacturing-sector firms practice

subcontracting, which is generally performed for formal-sector enterprises (Kemal & Mahmood,

1998). Subcontractors are sometimes provided with raw materials for processing, primarily

because they want the design and quality of their products to match the specifications (Kemal &

Mahmood, 1998).

When more than 70% of the population is living in villages, a major proportion of them

below the poverty line because of an insufficient ability to supply their basic needs, there is an

increased possibility of crimes instead of business development as Pakistan’s economically

underprivileged adopt illegal methods of achieving financial prosperity (Sheikh, 2009).

Pakistan’s large businesses are not only family-based but also clan/Beraderi-based, thus

aggravating the divide between rich and poor (Tariq & Alamgir, 2013). It is difficult to expect

SME development in an environment in which Chinioties, Memons, Vohras, Sheikhs and

Ismaeelis dominate industries and the big players are reluctant to assist smaller producers.

(Asghar & Javed, 2011).

Two major social-context aspects that are expected to facilitate SME development in

Pakistan include subcontracting and the more than 50% of the productive population that fall into

the age range of 15-59 years.

Social and cultural factors have a direct bearing on the emergence, survival, and growth

of entrepreneurship and SME development in a developing country such as Pakistan. The

cultural factors in the context of Pakistani business communities are driven by a family history of

entrepreneurship, educational background, the entrepreneur’s age and his or her attitude towards

business management (Chachar, De Vita, Parveen, & Chachar, 2013). Although most of the

factors mentioned above negatively affect the development of SME clusters in Pakistan. The

family-based businesses can affect SME cluster development positively because of the

outsourcing of large enterprises in the cluster (Bakunda, 2014). Furthermore, SME clusters are

platforms where the government can improve the education of children working in the factories

and facilitate the skill level of workers in the specific industrial clusters. Government policies,

chambers and associations can also work to facilitate the addition of more females into the

labour force to increase the pool of employable labourers in a specific cluster (Perrons &

Plomien, 2013).




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4. Technological context

Firms in developing countries operate with an imperfect knowledge of technological

alternatives, in addition to lacking new skills and knowledge to efficiently utilize new

technologies (Lall, 2000). To understand more about industrial success, the role of internal

technological factors and their link to the exporting behaviours of enterprises in a developing

economy cannot be ignored. Enterprises’ productivity, growth and trade performance facilitate

the process of obtaining the ability to innovate and utilize new technologies, which is linked to

enterprises’ exporting behaviour in terms of their technological development and export

performance (Ulku, 2007).

Keeping in mind the importance of manufacturing enterprises as the primary actors in the

process of accumulating technological capabilities, Wignaraja (2002) proposes a technology

development index (TDI) based on factors that affect enterprise level, technological development

and export performance (Rodríguez & Rodríguez, 2005). Firm size, technical manpower,

training expenditures, and external technical assistance were some of the ingredients that were

positively related to the technology index. The capability literature emphasizes that enterprises

must make a conscious investment to convert imported technologies into productive use

(Wignaraja, 2002).

Technological capability is also related to R&D capability. Although R&D is necessary

for competitiveness, new strategies include people, their contacts and their skills as a vital basis

for firms’ success both in new technologies and in alliances. Small firms and entrepreneurship

are examined as a crucial part of a well-functioning regional economy (Malecki, 1997;

Braunerhjelm, 2010). Research has demonstrated a close relationship between entrepreneurship

and regional and local development. Innovativeness developed within local interfirm networks

both supports existing firms and presents opportunities for starting new businesses to serve

newly identified markets. Networks of firms complement and sometimes substitute for a firm's

own technological capability (Malecki, 1997). New technological capabilities can also be

acquired through interfirm linkages because network firms complement member firms in these

aspects (Basant, 2004).

The global value chain (GVC) approach shows how international linkages play a crucial

role in accessing technological knowledge and enhancing learning and innovation (Gereffi, 1999;

Kaplinsky, 1998; Humphrey & Schmitz, 2002). While focusing on the internal process of

technological capability, we also must understand the knowledge flow within and between

different GVCs, which in turn will make it easier to unravel why some firms and/or clusters

benefit from being part of GVCs (Morrison, Pietrobelli & Rabellotti, 2008).




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Pakistan’s problem of industrial backwardness is primarily the result of slackness in

productivity growth, which in turn was a result of technological underdevelopment. For Pakistan,

where highly skilled workers, capital, and foreign exchange are scarce, the growth of total factor

productivity is of special significance (Kemal, 2006). Technological development is a key

element in enhancing industrial productivity and growth in Pakistan, which would make it

possible to improve competitiveness and produce new products.

Although Pakistan still lags in the technology index, there were significant improvements

from 2004 to 2006. For example, from 2004-05 to 2005-06, Pakistan’s technology index rank

improved from 87 to 80 and its growth competitive index rank improved from 91 to 83.

Although most Pakistani firms continue to occupy the lower end of the technology spectrum,

domestic firms may be facilitated to compete in the world market through technological up-

gradation, investment, and innovative capabilities (Kemal, 2005). The share of medium- or high-

technology products in manufacturing exports in 2002 remained low at 10 percent in Pakistan

compared to 20 percent for India, 46 percent for China, 70 percent for the Republic of Korea and

76 percent for Malaysia.

UNIDO (2005) has also developed an industrial-cum-technological advance (ITA) index.

In 2002, Pakistan was 0.104 on the index compared to 0.198 for India, 0.235 for China, 0.338 for

the Republic of Korea and 0.269 for Malaysia. Until 2000, Pakistan had ignored or given very

little emphasis to higher education, science and technology and research and development. In

Pakistan, tertiary enrolment (percent of the population aged 17-23 years) levels are

approximately 4 percent compared to 10.5 percent in India and 28.2 percent in Malaysia. On the

index of availability of scientists and engineers, Pakistan’s rank is 61 out of 93 countries. In

2000, Pakistan had 100 scientists and engineers per million people compared to 149 in India, 350

in China and 500 in Malaysia. According to the Global Competitiveness Report (2005),

Pakistan’s position was 87 on the technology index compared to India (63) and China (62), with

the United States on top (Amjad, 2006). Lack of emphasis on higher education in Pakistan has

weakened the linkages between universities, research institutes and industry, which are

considered the soft side of technological intervention (Khan and Anwar, 2013).

Accordingly, most of Pakistan’s problems were related to the software rather than the

hardware side of technology (Mahmood & Siddiqui, 2000). Functional linkages between various

components of the science and technology (S & T) system (universities, research institutes, and

industry) were missing. International alliances of local research institutes (hereinafter RIs) were

missing. Generally, RIs were experiencing funding, planning, and organizational problems.

Consequently, the private sector’s participation in technological development was negligible.

There was a weak conditioning of local customers in favour of better-quality products

(Mahmood, 2000).




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Pakistan scores relatively low on export sophistication, reflecting its specialization in low

technology products. Within these categories, Pakistan performs poorly on products that are at

the low-commodity ends of the sophistication spectrum (Kemal, 2005; Amjad, ul Haque &

Colclough, 2005). Even for textile and clothing exports, Pakistan must match its competitors in

terms of technology, skills, designs and quality, and the main drivers of competitiveness—

human resources, technological effort, technology inflows and supporting institutions—are weak

and not improving over time in response to growing international challenges (ADB, 2002).

SMEs in Pakistan are known to rely on low, obsolete technology. This reality is

associated with the lack of technical skills required to produce quality products. There is a

general absence of information on opportunities for technological up-gradation (Khan &

Qureshi, 2007). One part of the problem is linked to SMEs’ inability to acquire sophisticated

equipment and R&D facilities, which is manifested in the adoption of labour-intensive

production methods associated with lower productivity levels and overall economic efficiency

(Kemal, 2005; Amjad, 2006). A typical small Pakistani firm uses old, indigenous machines,

produce low-quality, low-priced products and sell them accordingly (Sherazi et al., 2013).

Like all less-resourceful firms, SMEs typically have skill deficiencies and are unable to

compete with larger firms’ better-qualified manpower. In this game, the larger firms have

advantages over SMEs, particularly in situations of skill shortages, which may occur in Pakistan

as a result of the migration of labour to the Middle East and other countries (Mian & Qureshi,

2011). Consequently, a smaller firm may not be able to compete with a larger firm because of

limited funds, despite its need for highly skilled workers (Asad, Haider, Akhtar & Javaid, 2011).

The industrial backwardness and technology underdevelopment, a lack of emphasis on

higher education and R&D, Pakistan’s weak performance on sophisticated manufactured exports,

skill deficiencies and the migration of skilled labour to other countries are some of the major

constraining factors on SME cluster development in Pakistan. The literature does not highlight

SMEs’ technological problems, the role of soft-side intervention on SMEs, or the reasons for the

migration of skilled labour and their effects on SME development in Pakistan.

5. Environmental context

Most Pakistani industries are located around major cities and are increasingly polluting

streams, rivers and the Arabian Sea through untreated toxic waste (Luken, 2000). Pakistan’s

tanning industries are causing severe environmental problems because of the disposal of their

untreated effluents on land and in bodies of water. In the past few decades, developing countries

have witnessed a sharp increase in leather production because such activities have declined in the




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developed world because of more stringent environmental pollution-control requirements and

high labour costs. Accordingly, Pakistan witnessed a rise in its leather exports from US$ 672

million in 2002 to 1.13 billion in 2007, which indicated an increase of 68% in a span of 5 years

(Haydar & Aziz, 2009). There are 442 organized textile units in Pakistan and except for a few,

all of the units are discharging effluents without any treatment. As a result, the natural water

bodies, which were rich sources of food and irrigation water a few years ago, have now become

wastewater drainage. (Iqbal, Nadeem & Shafiq, 2007).

In Pakistan, two types of environmental policies directly address environmental problems

(Magsi & Atif, 2012). The first policy is based on command and control to apply environmental

quality standards on emissions, effluents, technology type or input use. Because the regulating

institutions are weak and financial resources and technical know-how for monitoring and

enforcement are scarce in Pakistan, there is no effective implementation of NEQS. The second

policy is based on incentive by using prices to affect pollution and resource use. Pakistan’s

government subsidized energy use by keeping prices below economic levels, thus undermining

incentives for energy conservation. Under this incentive scheme, Pakistan’s government reduced

the gap between petrol and diesel prices to shrink diesel usage to mitigate the problem of air

pollution. The government also increased the price of water to discourage the inefficient use and

waste of water; moreover, they encouraged the implementation of a self-monitoring and -

reporting system (Magsi & Atif, 2012; Luken, 2000).

Industries in Pakistan’s major cities are discharging untreated wastewater into sewerage

or public water sources. In most urban areas, there is no space for individual or combined

wastewater treatment facilities (Kahlown, Ashraf, Hussain, Salam & Bhatti, 2006). Except for

large factories, none of the factories have installed pollution control systems (Luken, 2000).

Although Pakistan’s implementation of environmental protection laws is questionable, SMEs

still face a threat of closure in the case of non-compliance with environmental standards,

particularly in exporting industries. The effect of global standards on local producers is primarily

the result of SMEs’ lack of financial resources, poor awareness and lack of technical capabilities

to comply with environmental requirements (Nadvi, 2004; Lund-Thomsen & Nadvi, 2010).

Since 2013, a massive shortage of electricity, long-continued failures, unreliable service,

rampant corruption, unauthorized connections, and consumers’ refusal to pay for the irregular

power supply are some of the reasons for Pakistan’s energy crisis. Pakistan experienced its worst

energy crisis in 2007, when production fell by 6,000 megawatts (Javaid et al., 2011; Nawaz, Arif

& Masood, 2013). Power shortage is a serious issue in Pakistan. The main problem related to

Pakistan’s poor electricity production results from political instability, coupled with the growing

demand for power and a lack of efficacy (Haque, 2011).




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Power shortages threaten to undermine the government’s credibility and legitimacy and

to further stress Pakistan’s social fabric. The power crisis did not suddenly emerge. It is the

direct result of unwise, inattentive energy policies over the last three decades (Arshad et al.,

2014). Pakistan's energy bankruptcy is ultimately the result of a massive institutional and

governance failure (Kessides, 2013).

Pakistan has a gas-supply shortage of approximately 20%. Natural gas supplies fell by

33% in 2010 compared to 2009 (Mills, 2012). In December of 2001, this situation prompted the

government to announce gas rationing to counter the deficit. It has been estimated that domestic

oil and gas supplies would be exhausted by 2025 and 2030, respectively. Pakistan already

imports approximately 30% of its energy, mainly from Iran (Mills, 2012). Pakistan’s government

is likely to deregulate the CNG sector and its consumer pricing from under the Oil and Gas

Regulatory Authority’s (OGRA) regulation (Malik, 2008).

Water scarcity in Pakistan could threaten all aspects of the national economy. The

International Monetary Fund (IMF) has blamed Pakistan for its lack of proper water

management. Pakistan is amongst the world’s 36 most water-stressed countries, and the situation

will worsen as the population increases (Iqbal, 2015). Pakistan depends on a single source, the

Indus system and its tributaries, for most of its water supply needs (Bhatti & Farooq, 2014). Fed

mostly by snow and glacier melt in the greater Himalayas, water availability in the Indus system

is highly seasonal, with 85% of annual river flows occurring during the June-September period,

which coincides with the concentration of rainfall during monsoon season. Rainfall varies from

1,500 millimetres per year in Northern Punjab to 150 millimetres per year in the upper Sindh

province (Ahmad, 2007). Pakistan is also exposed to extreme weather conditions, including

severe episodes of floods and droughts that wreak significant damage on the country’s

agricultural, livestock, and water infrastructure. Many of these costs have been attributed to the

lack of adequate storage capacity and control structures. Total dam storage in Pakistan represents

only 30 days of average demand, compared to 1,000 days for Egypt and 220 days for India

(Akhtar, 2010).

More than 35% of the population lacks access to safe drinking water. Pakistan has huge

hydro potential through the construction of new dams and hydropower projects (Ali, 2014). The

country’s two existing mega-hydropower dams—Mangla and Tarbela—were commissioned in

1967 and 1976, respectively; however, they are losing their storage capacity because of rapid

silting (Izhar-Ul-Haq & Sheikh and WAPDA, 2011). Pakistan is one of the world’s most arid

countries, with an average rainfall of less than 240 millimetres annually. On the consumption

side, when evaluating 100,000 households (or approximately 900,000 people), Pakistanis use

100 gallons of water per person per day, whereas the world’s average is 10 gallons per day

(Khalid & Begum, 2013; Salman, 2015).




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A major portion of the Pakistani population still resides and works in the agrarian

sector, with poor application of land rights leading to political decisions that have economic

implications (Ali, 2012). In Pakistan, the army is involved in fertilizer production in that

prominent ministers engage in corporate farming. Furthermore, donors are attempting to fund

the computerization of land records to further facilitate agribusiness without addressing the

basic land-tenure rights of the rural poor (Ali, 2012). Analysing the class character of land

reform in India and Pakistan shows that the conflict between the old landlords and Pakistan’s

emerging middle class is not as sharply articulated as in India, and land policy therefore has a

more pronounced pro‐landlord bias than in India. In Pakistan, at best, land policy denotes the

tension between the old declining class and a new, dynamic landlord class (Joshi, 1974).

Pakistan’s industrial sectors are causing serious pollution and hazardous contamination;

however, because of limited financial resources and technical capacity, industry is not able to

implement pollution-control measures (Khan, 1998). Even with the poor implementation of

environmental protection laws, Pakistan’s SMEs are threatened with closure because of their

non-compliance with these standards. SMEs involved in the exporting industrial clusters are

confronted by a lack of financial resources, have poor awareness and lack the technical ability to

comply with international compliance requirements (Nadvi, 2004; Lund-Thomsen & Nadvi,

2010).

The environmental compliance requirements, power crisis, macroeconomic instability,

natural-gas shortages, water scarcity and poor application of land rights in Pakistan are major

constraining factors, but it appears difficult to directly link these factors to the development of

SMEs and SME clusters in Pakistan. Poor access to raw materials is one of the major

constraining factors because of the lack of access to cheaper capital by SMEs. Therefore, the

major environmental factors constraining the development of SMEs and SME cluster

development include the following: electricity shortages, macroeconomic instability, natural-gas

shortages, water scarcity, poor application of land rights and poor access to raw materials.

6. Legal context

The Supreme Court is the highest court of ultimate appeal in Pakistan. There are High

Courts in each province and a High Court for Islamabad. This level is the highest provincial-

level court in Pakistan (Heydarian, 2013; Hussain, 2011). The Federal Shariat Court of Pakistan

has the power to examine and determine whether Pakistan’s laws are in accordance with Islamic

injunctions (Lau, 2002 & 2005). The Subordinate Courts handle the civil and criminal cases

under their jurisdiction pursuant to the powers and functions specified in the statutes creating

them (Hussain, 2011).




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Pakistan’s industry-related laws include procedural laws, competition laws, consumer

laws (Khan & Hafeez, 1999), and labour laws (ILO, 2002). The procedural laws prescribe the

procedure for proceedings in civil cases. The Competition Law enforces an act to provide for

free competition in all spheres of commercial and economic activity to enhance economic

efficiency and to protect consumers from anti-competitive behaviour (Javed, 2012). The

consumer laws are generally absent, although there is a commission called the Consumer Rights

Commission of Pakistan (CRCP), but it is ineffective in protecting consumer rights against

powerful multinationals. Pakistan’s Environmental Protection Act was passed in 1997, but poor

implementation increased Pakistan’s vulnerability to natural disasters (APP, 2012). Finally,

Pakistan’s labour laws are extremely complex and push small enterprises to operate outside the

domain of these laws (Amjad, 2005).

Corruption, nepotism, and political manipulation are widespread and damage the

integrity, credibility, and public image of Pakistan’s judiciary and police. An additional

impediment to criminal law enforcement is the ineptitude of Pakistan’s judicial sector (Abbas,

2011). Criminal litigation in Pakistan is a series of retributive legal actions and as such, the

courts are left with the onerous and uninspiring task of sifting through cases to determine which

are genuine and which are not. Because a very small percentage of litigants are tried for

malicious prosecution, the trend of using the law to settle scores is both very common and

deployed with great tact and skill (Imam, 2011). Similarly, arduous civil litigation is made even

more cumbersome by the delaying tactics that are employed by lawyers. Civil litigation has

become a practice that is widely used by disputing parties as a means of bargaining, i.e., the

process usually entails favourable status quo orders, followed by a deliberate delay (Siddique,

2011). Investigators are poorly trained and lack access to basic data and modern investigation

tools. Prosecutors who are also poorly trained are not closely involved in investigations (Lillah,

2012). Corruption, intimidation and external interference in trials, including by the military’s

intelligence agencies, compromise cases before they even reach court. (Hussain, 2012).

In Pakistan, the police are notorious bullies and are used to control the people instead of

protecting them. Historically, the police were used by the colonial administration as a means of

implementing policy (Imam, 2011). Inevitably, Pakistan’s victims of police brutality lack

influential patronage or support from the legal system of Pakistan. This situation is further

compounded by the low awareness of legal rights and procedures; thus, the poor and vulnerable

are disconnected from the formal justice system, resulting in a glaring trust deficit. The entire

nature of Pakistan’s legal system is oriented towards delaying justice at all costs (Raymond &

Shackelford, 2013).

A good advocate is defined by his ability to prevail upon the judge to obtain a stay order

and how long he can delay matters to force the other party to come to the table (Kardar, 2014).

http://www.brecorder.com/pages/author/waqar-lillah.html




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Consequently, thousands of cases are pending before almost every bench of every High Court in

the country, with no real end in sight. There are cases that have become “infructuous” because

either the litigants have passed away or the cause of action has ceased to exist. In short, there is a

legal crisis in Pakistan (Wasseem, 1992).

SMEs and entrepreneurs experience a complex legal, tax and administrative environment

in Pakistan; thus, every firm is anxious to avoid the economic obligations associated with

registered status. Although small firms’ unregistered status has a negative effect on their access

to institutional finance, they prefer to remain in the informal sector (Fajnzylber, Maloney and

Montes-Rojas, 2011). In this situation, it is difficult to expect SME development when larger

enterprises have leverage to manipulate the system and the markets either by creating cartels or

through other mechanisms (Siddiqui, 2008).

The complex legal, tax and administrative environment are some of the major constraining

component, which is why SMEs are willing to operate in an informal environment, thus

ultimately creates difficulty for the development of SMEs and SME clusters in Pakistan.

Similarly, corruption, nepotism and political manipulation of Pakistan’s judicial system are also

constraining factors for SME development. The poor attitudes of advocates, judges and police

constrain the development of Pakistan’s small-scale sector.

Discussion

To learn how the above factors affected the development of SME clusters in Pakistan, it

is important to understand how political, economic, social, technological, environmental, and

legal factors interact in either facilitating or constraining the development of SME clusters in

Pakistan. The lack of continuity of industrial policies and Pakistan’s unstable government, along

with the government’s policy focus on the large-scale sector, are some of the constraining factors

for SME cluster development in Pakistan. Furthermore, insecurity and terrorism in Pakistan play

a negative role in SME development in Pakistan.

In addition, the poor growth of the large-scale sector, inflation and the depreciation of

Pakistan’s currency and exchange-rate fluctuations are the economic constraining factors for

SME cluster development in Pakistan. The only economic factor that helps grow SME cluster

development in Pakistan is the performance of the small-scale sector despite the government’s

support of the large-scale sector.

On the social side, poverty, illiteracy, corruption, unemployment, child labour and

population expansion are some of the major constraining factors for SME development in a




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developing country such as Pakistan. Furthermore, the power crisis, lack of foreign investment,

economic meltdown and political instability, uncontrolled inflation, the War on Terror, the

strong beradari/clan system, entrepreneurs’ low education, their lack of management skills and

the scarcity of skilled labour are also constraining the development of SMEs in Pakistan.

However, the proportion of the productive-age population and frequent subcontracting facilitate

the process of SME cluster development in Pakistan.

In Pakistan, industry is generally backwards in the area of technological development,

with a poor emphasis on higher education and R&D. Pakistani producers are weak performers

with respect to technology-intensive and sophisticated products; moreover, there is a deficiency

of skilled labour and labourers frequently migrate. All of these factors constrain the development

of SME clusters in Pakistan.

Pakistani SMEs and entrepreneurs fail to comply with international buyers’

environmental requirements, particularly when SMEs are operating in international markets.

Furthermore, the power crisis and macroeconomic instability, shortage of natural gas, scarcity of

water, poor application of land rights and poor access to raw materials are some of the major

constraining factors for SME development in Pakistan.

Pakistan has a complex legal, tax and administrative environment that constrains the

development of SME clusters. Some of the additional factors such as corruption, nepotism,

political manipulation of the judicial system, an incompetent judiciary and delays in criminal and

civil litigation negatively affect SME development in Pakistan. Pakistan’s police system is

notorious for corruption; additionally, manipulative lawyers and judges force people to settle

disputes out of court. These factors also constrain the development of SMEs in Pakistan.

We summarize this review through a conceptual framework to show how political,

economic, social, and technological environmental and legal factors are linked to SME cluster

development in Pakistan. Figure 1 seeks to display both how these factors are interrelated and

their effects on the existence and development of SME clusters. It shows the extent to which

these contextual factors either facilitate or constrain the prospects for collective action by SMEs.




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Figure 1: Link between political, economic, social, technological, environmental and legal

factors and SME cluster development in Pakistan.

POLITICAL FACTORS

1. Lack of continuity of industrial policies

and instable government (Undermining)

2. Focus of government on the large-scale

sector (Undermining)

3. Insecurity and terrorism (Undermining)

SOCIAL FACTORS

1. Poverty; illiteracy; corruption

(Undermining)

2. Unemployment (Undermining) 3. Child labour (Undermining)

4. Population expansion (Undermining)

5. Power crisis and lack of foreign investment (Undermining)

6. Economic meltdown & political

instability (Undermining) 7. Uncontrolled inflation (Undermining)

8. War on terror (Undermining)

9. Strong beradari/clan system (Undermining)

10. Low education of entrepreneurs; lack of

management skills (Undermining) 11. Scarcity of skilled labour (Undermining)

12. More than fifty percent productive

population (Facilitating) 13. Subcontracting (Facilitating)

ENVIRONMENTAL FACTORS

1. Environmental compliance requirements

(Undermining)

2. Power crisis and macroeconomic instability

(Undermining)

3. Natural gas shortage (Undermining)

4. Water scarcity (Undermining) 5. Poor application of land rights (Undermining)

6. Poor access to raw materials (Undermining)

TECHNOLOGICAL FACTORS

1. Industrial backwardness; technology

underdevelopment (Undermining)

2. Poor emphasis on higher education and R&D 3. Weak performance of Pakistan on technology-

intensive, sophisticated products

(Undermining) 4. Skill deficiencies and migration of labour

force (Undermining)

LEGAL FACTORS

1. Complex legal, tax and administrative

environment (Undermining) 2. Corruption, nepotism and political manipulation

of the judicial system (Undermining)

3. Incompetent judiciary (Undermining) 4. Delay in criminal and civil litigations

(Undermining)

5. Notorious police (Undermining) 6. Manipulative lawyers and judges (Undermining)

7. Out of court dispute settlement (Undermining)

SME CLUSTER

DEVELOPMENT

ECONOMIC FACTORS

1. Poor growth of the large-scale sector (Undermining)

2. Inflation (Undermining) 3. Depreciation of Pakistani currency and exchange rate

fluctuation (Undermining) 4. Performance of the small-scale sector (Facilitating)




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205


Managerial Implications

First, it is clear that Pakistani SME managers, support organizations and relevant

stakeholders may improve the business environment for SME cluster development. They may

identify a way to manage Pakistan’s corrupt political setup to improve the predictability of the

country’s policies.

A second implication of this article for SME managers is to change Pakistani policy

makers’ focus from large-scale enterprises to the small-scale sector specifically that of SMEs and

SME clusters, to improve the performance of Pakistan’s SMEs. Keeping in mind the strong SME

base in Pakistan, SME managers should work on profiling both SMEs and SME clusters to

understand the actual number and strength of SMEs in Pakistan.

Third, SME managers may work in close collaboration with local and international

nongovernmental organizations (NGOs) and federal and provincial SME support departments to

improve literacy and reduce the power crisis, particularly in Pakistan’s industrial clusters.

Fourth, SME managers may work on the technological and R&D capabilities of

Pakistan’s entrepreneurs and SMEs in spite of their imperfect knowledge of technological

alternatives, the absence of new skills and their poor access to capital that would allow SMEs to

acquire new technologies.

Fifth, SME managers may pay attention to the variables attached to the information flow,

trust, reciprocity and connectedness of SME network members and how they obtain economic

benefits through collective action. SME managers may also learn how SMEs and entrepreneurs

in Pakistan survive in an environment in which most of the political, economic, social and

environmental indicators constrain the growth and development of SMEs and SME clusters.

Finally, this article highlights the importance for government policy makers to pay

attention to the issues of poverty, inflation, exchange-rate fluctuation, power and gas shortages,

the land mafia and Pakistani SMEs’ poor access to input materials. Policy makers may

investigate the country’s corruption, macro-economic instability, political instability, crimes,

theft and poor law-and-order situation, which is causing poor development of both SMEs and

entrepreneurship.




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206


Research Implications

First, this article has identified some links to the PESTEL factors, but there is no clear

relationship between SME development and SME cluster development with the individual

components of these factors. Future research can explore and test Figure 1 in similar contexts of

developing economies while exploring the co-relations of the subcomponents of political,

economic, social, technological, environmental and legal factors.

Second, it is important to understand the link between poverty, inflation and depreciation

of Pakistan’s currency and the development of SMEs and SME clusters in developing economies

(such as that of Pakistan).

Third, scholars might need to determine how to develop SMEs and SME clusters around

unstable environments and how to initiate the change process in a country such as Pakistan.

Fourth, further exploration is necessary to determine how to improve the tax, legal and

police system for SMEs in a developing country such as Pakistan, where lawsuits are retributive

and individuals are using the law to settle scores by delaying justice at all costs.

Fifth, it may be important to identify the effects of the corrupt judicial system and

unethical decisions on the development of SME clusters and how to improve the trust deficit not

only to bring large, medium and small enterprises into the tax net but also to enable them to grow

and add value to the economy.

Finally, the article highlights the need to explore how to change the mind-set of police in

a developing country such as Pakistan. How do we initiate the change process in Pakistan? Must

we explore the possibility of involving the huge productive population and subcontracting in

Pakistan’s business environment?




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207


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Impact of transformational leadership on employee’s performance, with the mediating role

of job satisfaction and employees’ commitment

by

Muhammad Shahid Khan, Marina Khan, and Rukhsar Khan

Abstract

This study investigates the underlying mechanisms and boundary conditions that explain the

relationship between transformational leadership and employee performance with the mediating

effect of job satisfaction and employee commitment. In this study the data is collected from

Telenor Telecom Pakistan through questionnaires where 220 respondents participated in the

survey. SmartPLS software is used to analyze the data. To check the reliability of the instrument

composite reliability technique is used, and for checking validity, construct validity is being

used. The research shows that transformational leadership plays an important role in enhancing

employee’s interpersonal relationship with his supervisor and also increases job satisfaction in

the organization.

Keywords: transformational leadership, employee performance, job satisfaction, employee

commitment

Corresponding Author, Muhammad Shahid Khan, PLC Group Malaysia,

[email protected]





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1.1 Background of the study

In Pakistan, there are numerous service sectors, Telecommunication sector is one of the

growing service sector. The flow of communication and networking is affected by the smooth

and effective functioning of this sector. Like in other organizations, the role of leadership is

considered quite crucial for it’s success. Similarly, leadership is also found necessary for the

success of Telecommunication companies. If we talk about other factors like that of

advancement in information technology, culture and organizational structure are important for

the success of a firm, just like that role of leadership is also becoming important in the

organizations. In the field of management, it always came forward as an important and

challenging topic. If an employee is highly satisfied with his job then he will definitely perform

well (Walumbwa et al., 2011). Researchers and different analysts focused on finding the

relationship between style of leadership and performance of an employee.

Leadership style also differs from person to person according to different situations and

the requirements (Bass & Bass, 2009). There are various theories of leadership and they give

some sort of knowledge and explanation about leadership process (Bass & Bass, 2009).

Behavioral, trait and contingency theories are known as traditional theories and transformational

leadership theory is now-a-days considered, a quite emerging and new style of leadership theory.

In management researches, transformational leadership theory is getting popular and seeking

more attention.

Different styles of leadership theories and their connection with employee performance is

also getting popular and gaining attention of researchers. Numerous scholars and researchers

have stated that those employees who are highly committed with their jobs often perform well

(Walumbwa & Hartnell, 2011). In order to meet the challenges of growing World and while

being in such a competitive environment, organizations are focusing towards employee’s

performance (Wofford et al., 2001). It is also suggested and assumed that the development of

organization depends on leadership, and there should be love and harmony between the leader

and the employees. The main job of the leader is to run the organization towards fulfilling goals,

tasks and operations. Other researchers have also stated that to improve the performance of

employees, leadership is needed. The main focus of our study is to find out that how

transformational leadership affects and influences the job performance of employees through job

satisfaction and employee commitment in Telecom sector of Pakistan. It is discussed and

expected that transformational leadership style is better than transactional leadership style

because transformational leadership helps employees to work better and produce much more

outcome in the organization (Bass & Bass, 2009). Transactional leadership does not have an

impact in the success of an organization (Bass, 1998; Masi and Cooke, 2000).




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Leadership is considered to be important for the success of organizations (Kouzes &

Posner, 2008), it is necessarily important for those organizations who faces great amount of

change and uncertainty (Bass, 1990), as leadership affects employee commitment towards

change (Waldman et al., 2001). In general, employee commitment is very much important in

achieving the aims of the organizations (Rossy & Archibald, 1992). In the same way

transformational style of leadership also has significant impact on employees’ commitment and

performance (Avolio, Weichun, Koh, & Bhatia, 2004; McColl-Kennedy & Anderson, 2005; G.

Wang, Oh, Courtright, & Colbert, 2011). The main focus of the study is to find out the

relationship of transformational leadership and employee performance while job satisfaction and

employee commitment are there as mediators in Telecom sector of Pakistan.

The previous research done by Naeem and Khanzada (2018) in health sector of Pakistan

has gathered data only from hospitals located at Rawalpindi, Lahore and Islamabad with a small

sample, convenience sampling technique was used and job satisfaction was a mediator between

transformational leadership and employee performance. M. Asrar-ul-Haq (2016) conducted

research in banking sector of Pakistan has collected data from few banks which did not represent

the entire banking sector of Pakistan. The research done by Jyoti and Bhau (2015) was resrtricted

to government degree colleges in Jammu. Gyensare et al., (2016) conducted research in

Ghanaian SLCs also used a small sample. The research should be conducted in other countries

to provide broader insights into the effects of transformational leadership and proactive

personality on employee outcomes, to see the relationship between transformational leadership

and employee performance other factors could be assess as a mediator (Buil, Martínez, &

Matute, 2019) .Therefore, the aim of this study is to identify the relationship between

transformational leadership and employee performance with the mediating effect of job

satisfaction and employee commitment.

All the previous researchers have set few limitations and a gap in the literature i.e.

researches were done on specific sectors, small sample were drawn, and the use of variables and

sampling techniques were different. So, the study aims to fill these gaps.

This research is conducted to add more knowledge in the area and field of leadership that

how transformational leadership impacts employee performance through job satisfaction and

employee commitment. This research aim is also to contribute for further growth of leadership

concepts. It’s basically purpose is to provide both theoretical and practical information to

corporate stakeholders and policy makers who uses it for the growth of an organization and also

the role of transformational leadership should not harm employee as a person while increasing

productivity.




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LITERATURE REVIEW

As competition is increasing day by day and change in business management is calling

for a need of leadership. Leadership has remained one of the most important topic and there are

several definitions which has come forward. As discussed by Jong and Hartog, (2007), explained

leadership as it is a way of persuading and convincing people to achieve what they aim for.

Andersen (2016) highlighted leaders are those people who shows the roadmap to their followers

and encourage them to achieve the aims and objectives of their targeted goals. Different types of

leader uses different methods of leadership in order to encourage their followers. Lok and

Crawford (2004) stated that leaders can easily see and guess the future of an organization. This

research aims to find the impact of transformational leadership on employee’s performance

through job satisfaction and employee commitment in Telecom sector of Pakistan.

Different researchers have different views about leadership and how it brings success and

failure to the firms. But most of them agree that it is quite profitable for the organization to have

transformational style of leadership. There are various theories related to leadership. The first

originated theory was Trait theory which says that leaders are born. Later the second theory

emerged by the name Behavioral Theory which says that leaders have some specific traits and

behavior which can learnt and built. The third theory also came into existence i.e Contingency

Theory which states that there are multiple traits and forms of behavior which leader exhibits in

varying situations. But among all these famous and profound theories, we see that

Transformational leadership theory is the most acceptable and recognizing in research field.

There are two types of leadership theories i.e few are known as traditional and few are

taken as modern. Trait, behavioral, and contingency are known as traditional leadership theories.

On the other side transformational and transactional are known as modern leadership theories.

Leadership is one of the most crucial topic, discussed by the researchers from different

parts of the world (Kuchler, 2008). According to Jong and Hartog (2007) explained leadership in

a way that it is the phenomena which inspires people so that they perform well and get the

desired output. Crawford and Lok (2004) claimed that leadership plays an essential role to

identify the organization’s success and failure. Gill (2006) further discussed that leaders

motivates, to make them more active, develop their interest, encourage their participation and to

highlight their strengths to achieve the desired results.

2.3.1 Transformational Leadership

The word transformational leadership was initially introduced by Burns (1978). He states

that he came up with the word leadership when he observed that it is the leader who encourage

his followers, motivate them, boost up their morale, highlight their strengths and help them




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overcome their weaknesses also their perception and belief by aligning with the objectives of the

firm in order to achieve the key results. Schepers et al. (2005) further stated that transformational

leaders help employees to come up with innovative ideas, give them to room to analyze the

problem from every angle and try to solve the problem through creative and new methods and

allow them to find and explore better solutions to the given problem by accessing technology.

Transformational leadership also reduces the employees’ burn out, burden and stress during

work in the organization Gill et al. (2006). Kirkan (2011) stated that transformational leadership

is that kind of leadership in which leaders change the the current or present situation after

looking towards the problem then he inspires, persuades and make the followers excited enough

to achieve goals of the firm. Ghadi et al. (2013) highlighted four dimensions of transformational

leadership. First one is idealized influence that is leader should know how to increase loyalty,

identification and dedication while ignoring the self-interest. Second is inspirational motivation

that is leader should be capable of creating a vision which will force workers to work diligently

for the success of organization. Third is intellectual stimulation which says that a leader should

also be capable of helping employees in terms of innovation or when it is to take risk. The last

and the fourth one is empowerment where leader should interact and coordinate with employees.

This is done in order to make employees to take decisions and can also deliver them.

There are several researches done on transformational leadership; Abu-Ruman (2016) has

done research on the influence of transformational leadership on crisis management preparedness

in Arab Potash Company and Jordan Phosphate Mines Company. The results which were drawn

from the studies have shown importance of transformational style of leadership that the Jordan

Phosphate Company and the Arab Potash Company’s top management should bring

transformational style of leadership. Para-Gonza`lez et al. (2018) have identified different

meditors i.e learning, innovation and HRM that may found between organizational performance

and transformational leadership. Boamah et al. (2017) identified the influence of nurse

managers’ transformative leadership behavior on patient safety outcome and job satisfaction in

Ontario. It proved that transformational leadership has impact on workplace empowerment

which increases job satisfaction of nurses and avoid risky patient outcomes.

Al-Jeditawi (2014) highlighted the influence of transformational leadership i.e the

president’s role on job satisfaction of the department chairman and dean at Jordanian

universities. The study discovered that the role of transformational style of leadership was

medium. Ghadi et al. (2013) also has done research on impact of transformational leadership on

work engagement where meaning in work is taken as a mediator. Majali (2014) also highlighted

the influence of transformational leadership on performance where entrepreneurial orientation

was taken as a mediator in industrial Jordanian company, it also revealed the same result that

transformational leaders role is again medium. Al-Fattih (2013) also conducted research in




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Saudi security services on the association of transformational leadership with organizational

learning and found out that significant relationship exists between these two variables.

Transformational leaders are the one who creates a vision and then guide and encourage

their employees to achieve the desired results. They also convince their followers to think

beyond limit (Hater & Bass, 1988; Doucet, Fredette, Simard, & Tremblay, 2015). These kinds of

leaders always try to show first a vision to their employees. Transformational leaders fall

somewhat into the category of charismatic leaders because they basically motivate their

followers by showing them their charismatic powers. Burns (1978) was the first person who

came forward with transformational style of leadership. He discussed that this style of leadership

moulds the behavior of an employee. These type of leaders persuade and guide their employees

to achieve their best in life. As discussed by Rouche, Baker, and Rose (1989) and Tajasom,

Hung, Nikbin, and Hyun, (2015), transformational leaders guide, persuade, convince and

encourage their employees to achieve and accomplish goals of the organization. They basically

persuade their followers and mould their behavior. Transformational leader changes a person so

much that he thinks more than getting rewards. Transformational leadership is that kind of

leadership in which followers get emotionally attached with their leader. This get evident when

we see the followers do everything what the leader says. Followers start liking their leader and

respect him. They are ready to do whatever the leader says (Barbuto, 1997).

In 1997, four factors of transformational leadership was presented by Bass. First one was

idealized influence. It is that quality of a leader who always stands as a role model. His

personality is quite different. Every word of a leader is considered important. Second one is

inspirational motivation in which a leader believes that every action will bring good outcomes

and strive to achieve them. He motivates his followers to achieve the goals. Third one is

intellectual stimulation in which they make sure that employees should know their problem and

should also know how to solve them. They are also trained to solve their problem in short period

of time. They make them so smart that they solve them quickly and efficiently (Bass & Avolio,

1997). The fourth one is individual consideration which says that everyone should be

individually treated as people are different from one another. They should be taught separately

and guided individually. By treating them individually they work more diligently and efficiently.

2.3.2 Relation between transformational leadership and employee performance

Transformational leadership is one of the most discussed and commonly used technique

of leadership. Previous researchers also have proved that there is a positive relationship between

transformational leadership and organizational effectiveness (Brand et al., 2000).

Transformational leaders are upright, straight, firm and honest. They also have clear objectives

and insight and can easily communicate with their followers to explain the vision and objectives

(Bass & Bass , 2009). It is also stated that transformational style of leadership will bring success




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to organizations where both the leader and the employee are devoted and passionate for the

development of their organization (Burns, 2003).

Transformational leaders just not only develop the skills and competencies of their

employees, they even combine and relate the objectives of employees with the objectives of

organization. It is also discussed in numerous studies that employees fulfill the obligation of the

organization efficiently when they are lead with transformational style of leadership (Arnold et

al., 2001). Walumbwa et al. (2008) stated that the impact of transformational leadership on

managerial performance in banking sector. Other researchers have also proved the impact of

transformational leadership on the performance of an employee in different sectors (Liao and

Chuang, 2007; Wang et al., 2005).

The employee can only perform well, when he is satisfied and highly committed towards

his job or work task (Walumbwa and Hartnell, 2011). The most important work and concern of

an organization is to increase the performance of an employee, so that he competes in a

challenging and competitive environment. There are numerous theories that came into existence

to represent some sort of connection between employee performance and style of leadership

(Vigoda-Gadot, 2007; Pedraja-Rejas et al., 2006). Leaders are always willing to support and

encourage their followers, i.e employees. Transformational leaders are also kind of trainers

because of their kind nature and great thought and they are also capable of meeting the objectives

of employees with the objectives of organization (Horwitz et al., 2008). With the passage of time

transformational leaders are also getting popular and helpful to educational institutes,

information technology based organizations and hospitals. Previous research and studies have

also shown some of interdependencies between transformational leadership and employee’s

productivity and job satisfaction.

According to Voon et al. (2011) he stated that job satisfaction is basically a different

mind-set of individuals towards the job. Job satisfaction and job contentment is find when an

employee is happy and experience a positive state of mind and it gets apparent when an

employee shows professional skills and perform good while dealing with his work tasks

(Shahzad and Benish, 2017). Voon et al. (2011) also stated that only those employees will

perform well who are satisfied with their job and get rewarded. Job satisfaction always leads to

high employee performance and success of an organization (Belias and Koustelios, 2014). Those

employees who are contented towards their job, experience positive state of mind which gets

apparent from their skills and performance (Rezvani et al., 2016).

It is proved in literature that the behavior of transformational leadership leads to positive

outcome. Transformational leadership has positive impact on employee motivation, self-efficacy,

organizational performance and creativity (Bronkhorst, Steijn, & Vermeeren, 2015; Bronkhorst




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et al., 2015; Newland, Newton, Podlog, Legg, & Tanner, 2015; Kim & Yoon, 2015; Jyoti &

Bhau, 2015).

There is evidence in literature that achievement of goals and group performance is related

to the style of leadership because it directly influences behavior of employee. It makes them to

put extra effort on job and also to perceive and think their leaders influencing and effective. In

literature it shows that the style of transformational leadership has significant relationship with

the willingness of follower’s to put extra effort on job (Spano-Szekely, Griffin, Clavelle, &

Fitzpatrick, 2016; Yahaya & Ebrahim, 2016). The findings of Yahya and Ebrahim (2016) and

Spano-Szekely (2016) identified that when leaders adopted different leadership styles it leads to

different level of job satisfaction e.g leaders’ recognition and encouragement increases job

satisfaction among workers. Since every culture is different from one another so things are not

same across culture it varies (Bhagat & Steers, 2009).

Performance of an employee in his/her job has always been a crucial concern for top

managers in organisations (Kelidbari, Dizgah, & Yusefi, 2011). However employee performance

is a main key for firms therefore those aspects which lead to high performance must be critically

checked by the firms in order to be successful (Abbas & Yaqoob, 2009). Lee, et al., (2011), in

one of his study has defined job performance of an employee is counted as a total performance in

order to meet the challenges and achievement of given tasks within a specific timeframe set by

the organization. Similarly Ahmad and Shahzad (2011) stated that the performance of an

employee embodies the overall belief of an employee about their contributions towards

achieving their tasks and also their code of conduct while doing so and they further added that

compensating employee, his/her performance evaluation and promotions are also the

determinants of employee performance. According to Anitha, (2013) explained that employee

somewhat changes financial condition of a firm by performing according to organization’s goals

and objectives. She further said through teamwork and coordination among colleagues lead

employees to perform efficiently. So, in short those employees who perform well also innovate

new ideas and bring improvement in the organization, by doing this they generate customer

satisfaction (Sadikoglu & Cemal, 2010).

2.3.3 Job Satisfaction

The term Job Satisfaction has not only clicked the minds of employees but also of the

researchers (Lu et al., 2005). It is the emotional feedback of the employee towards his/her task or

the place where he/she works which results from his/her job experience. Luthans (2007, p.141)

stated that job satisfaction is a pleasure or positive vibes of an individual which results from

one’s job appraisal or experiencing job. Job satisfaction results in excellent performance of

employees and their commitment towards organization which guarantees organizational success

and development (Spector, 2003).




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Okpara (2004) who came up with the five parameters of job satisfaction: supervision,

promotion, pay, coworkers and work itself. Oshagbemi (2003) found out in the universities of

UK that there are personal reasons that relate to one’s satisfaction towards his/her job. He also

determined that age, ranking and duration of service and the one’s ability to perform his task has

to do a lot in increasing the level of his satisfaction. Okpara (2004) stated the personal attributes

that were taken in account were age, gender, education and experience in order to determine

whether they are the reasons for the job satisfaction of the IT managers or not.

Job satisfaction is one of the most important factors of an organization to function and it

seems to be affected by organization’s leadership style and internal culture of an organization.

Job satisfaction is derived from a worker’s appreciation towards his/her work or his/her working

experience (Locke, 1976). According to Kennerly (1989) who stated that the behaviors of

employees in an organization e.g unity and togetherness between employees, collaboration and

trust, mutual understanding, respect among superiors and employees are predicted as the

significant and positive elements of the job satisfaction that are experienced mostly by the

employees. Furthermore, Cross and Billingsley (1992) concluded that due to low conflict rates,

support of leadership and employee’s involvement in his/her work can also be the predicting

elements of job satisfaction, job commitment and not to quit his/her job. Generally job

satisfaction is a pleasant and positive emotional state of mind and researchers believe that

relation among job commitment, leadership, job satisfaction and organizational culture are

interrelated to each other and are broadly studied.

There are various tools that are developed to measure the job satisfaction that are mostly

being experienced by the workers in the organization.

2.3.4 Transformational leadership association with Job Satisfaction

Well, there are tremendous styles of leadership that have an influence on employees’

commitment towards organization and job satisfaction, but we mainly focus on transformational

leadership. We have selected transformational leadership since it’s innovative in nature,

productive and supportive. Cumming et al. (2010) exclaimed that leadership that only is

concerned with the outcomes of their employees and does not even care about their emotions and

feelings are unable to achieve diligent efforts from the workers. The study further stated that this

leadership style should be taken into account in order to avoid turnover of employees, work

environment, selection and also to improve employees’ satisfaction. Miles and Mangold (2002)

claimed that employees are satisfied with the performance of the leader and his effective

supervision skills and interaction. Leaders’ ability to spot and solve the problems of the

employees identified how employees’ perceive their leaders’ and his performance. Al-Hussami

(2007) finally summarized that transformational leadership has positive effects on employees’

satisfaction towards his/her job. According to Hamidifar (2009) who conducted his study in the




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University Islamic Azad in Tehran also concluded that out of many leadership styles

transformational leadership style has significant and positive influence on employees’

satisfaction towards his/her job. Among different leadership styles employees are far more

satisfied with the transformational leadership one.

Leadership plays an important role and have significant impact on employee’s job

satisfaction and job contentment (Mujkic et al., 2014). Different scholars and researchers have

identified that different types of leadership styles have different sort of affect on employee’s job

satisfaction according to the varying situations (Voon et al., 2011; Mujkic et al., 2014;

Mangkunejara, 2016). Voon et al. (2011) highlighted that transformational style leader surely

increases job satisfaction and job contentment of employees because it basically increases

employees’ responsibility towards job and intellectual inspiration. Transformational leaders are

capable of motivating their employees as to become more accountable and autonomous towards

work task (Long et al., 2014) which actually increases their job contentment and make them

capable of accomplishing goals.

2.3.5 Job Satisfaction association with employee performance and Job Satisfaction as

mediator among transformational leadership and employee performance

It is justifiable to say that job satisfaction to some extent improves and increases

employee performance (Rezvani et al., 2016). Later and more precisely (Mangkunegara, 2016;

Mujkic et al., 2014) stated that those employees who are contented and happy with their work,

they show more interest and are enthusiastic to achieve mission and vision of the organization.

Furthermore Rezvani et al. (2016) highlighted that those employees who are satisfied with their

job, they often perform well and also participate in problem solving and decision making

activities. Fisher (2003) also stated while engaging in this argument that those employees who

are not happy and contented with their jobs usually perform bad, because they are not

enthusiastic and passionate to work harder and diligently. Discontented employees also will not

work with due responsibility and keenness (Judge, 2001).

Managers who adopt appropriate leadership style can bring improvement and efficiency

in productivity, employee performance and workers job satisfaction. Leadership can be taken as

a code of conduct, behavior, ability of a leader or supervisor who increases the standards of

organization and employee performance (Voon et al., 2011; Shahzad and Benish, 2017).

Leadership is crucial, vital and plays an important role in increasing job satisfaction of

employees. Leadership is basically management because it’s main aim is to control people and

build public relation. It inspires people or employees to perform efficiently and work for

organization’s success (Voon et al., 2011; Mangkunegara, 2016). Researchers have also

concluded this after doing various researches that transformational leadership style has




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significant relationship with job contentment, which also increases employee’s performance and

efficiency of organization (Berson and Linton, 2005; Seo et al., 2004).

The point of view of other researchers, clarifies that transformational leadership actually

increases employee’s job contentment and job fulfillment. Therefore, job satisfaction may act as

a mediator between transformational leadership and employee performance (Kozlowski and

Ilgen, 2006).

2.3.6 Transformational Leadership and Employees’ Commitment

Many researches are conducted on the transformational leadership in the past which

consistently proved that there is a significant associations among transformational leadership and

employees’ attitudes (e.g commitment towards organization and satisfaction level with the

leader) behaviors (e.g followers performance on job) at group, individual and organizational

levels (e.g., Judge and Piccolo, 2004; Wang et al., 2011). Recently researchers have made

significant progress to comprehend that how and when the behaviors of transformational

leadership are more influencing to affect the behaviors and attitudes of employees’ (Avolio et al.,

2009).

In the recent study, Mercurio (2015) in his conceptual framework proposed that the

emotional attachment towards the organization and affective commitment is viewed as the most

important aspect of organizational commitment. Further in the leadership-commitment literature,

the researchers argue that transformational leaders inspire and influence their followers’ to get

emotionally attached and involved in the organization. Leroy et al. (2012), states that the theory

of social exchange which serves as the pillar to show the relation between affective commitment

and transformational leadership. Precisely, leaders continuous communication and sharing values

with employees built trust, norm of reciprocity and identification which implies that employees

are determine with leaders and the qualities and values that leaders possess enroot in them and

organization. According to Braun et al. (2013) further argue that this determination and

identification of followers and their attachment to the leader increase the employees

commitment.Through some studies (Chandna and Krishnan, 2009; Chiun et al., 2009) found out

that transformational leadership have significant impact on employees affective commitment by

using data from Africa.

2.4 Hypothesis

H1: Transformational leadership has significant and positive impact on job satisfaction.

H2: Job satisfaction has significant and positive impact on employee performance.

H3: Job satisfaction has significant mediating role between transformational leadership and

employee performance.




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H4: Transformational leadership has significant and positive impact on employee commitment.

H5: Employee commitment has significant and positive impact on employee performance.

H6: Employee commitment has significant mediating role between transformational leadership

and employee performance.

2.5 Conceptual Framework

Figure 1.1: Conceptual Framework of the Study

The above mentioned model represents transformational leadership as an independent variable

(IV), employee performance as a dependent variable (DV), job satisfaction and employee

commitment are mediating variables (MV). It indicates that transformational leadership has

significant impact on employee performance and job satisfaction and employee commitment are

mediators between the two.

3. METHODOLOGY

3.2 Research Design

It is also known as a plan of action taken by the researchers to gather answers of research

questions and it is also known as the framework of the study or researcher’s blueprint (Kerlinger,

1973). Research design of the study is a survey method. Orodho (2003) defined this method as

Job Satisfaction

(MV)

Employee Performance

(DV)

Employee Commitment

(MV)

Transformational

Leadership

(IV)




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the way of collecting and gathering data or information through questionnaires and interviews.

The aim of survey research design is to present specific characteristics of group of people,

institutions and objects by means of questionnaires (Jaeger, 1988). This research is explanatory

in it’s form as it is conducted to analyze the problem in more detailed manner which was not

studied well before. It is basically to look for those problems which were not identified before or

were not studied in depth. It also helps us to understand the problem more clearly and efficiently.

It is a quantitative research. The quantitative techniques present numerical information. It is a

deductive approach to research as it is testing the theory. It is basically concerned with

developing a hypothesis which is based on existing theory. Deductive approach does not

generate a new phenomenon or theory.

3.3 Target Population

The target population of study is the employees of Telenor (Karachi) and the sample of

220 respondents is taken.

3.4 Sample and Sampling Techniques

A sample is basically a sub-group or a smaller group of the population (Mugenda and

Mugenda. 1990). Each and every member of the sample is known as a respondent, subject or

interviewee. Sampling is basically a method of selecting a sub-group from the population who

will take part in the study as a respondent or participant (Ogula, 2005). It is the procedure or

process of choosing number of respondents for the survey in a way that those respondents will

represent the whole population from where they have been selected. Data is collected by means

of purposive sampling. It is a non-probability sampling. The sample of 220 respondents is taken

and the population is unknown. According to Hair et al. (2010) sample size should be 10 times

of the number of items in the instrument followed by adding 50. So, the sample is drawn by

applying the stated formula.

3.5 Instrument Selection

Questionnaires are used to gather primary quantitative data. It also allow respondents to

take enough time and fill it out with the sense of security i.e confidentiality. It is also free from

the bias that is of revealing personal characteristics of the respondents which mostly happens in

interviews (Owens, 2002).

3.6 Validity and Reliability Tests

Validity is basically to measure what is aim to be measured. According to Mugenda and

Mugenda (1999), it tests the accuracy and meaningfulness of the results. It is validated in terms

of construct validity. To assess scale validity, convergent validity is used in this study.




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On the other hand reliability is checked when the research instrument shows consistent

results when it is measured again and again or after repeated trials. It is also stated that if

researcher runs a test twice and gets the same result in both attempts then reliability is found in

that instrument (Mugenda and Mugenda, 1999). Reliability is found when results are consistent,

dependable and stable (Nachmias & Nachmias, 1996). The test re-test technique is used to

measure or check the reliability of the instrument i.e the same group of respondents is tested

twice in terms of Cronbach Alpha. Composite reliability is also used to assess the internal

consistency

3.7 Data Analysis Tools and Techniques

The data is analyzed by means of descriptive statistics. Tables are used as key tools to

present the data. Data is analyzed by means of linear regression analysis. Smart PLS is used as a

software to analyze the data.

4. Results and Findings

4.2 Reliability and Validity

Table 1

Reliability and Validity

Construct Cronbach's

Alpha rho_A

Composite

Reliability

Average

Variance

Extracted

(AVE)

Employee Commitment 0.909 0.909 0.908 0.665

Employee Performance 0.882 0.882 0.881 0.597

Job Satisfaction 0.879 0.880 0.878 0.547

Transformational

Leadership 0.932 0.936 0.931 0.732




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Figure 2 Factor Analysis

Reliability & Validity:

Table no. 1 shows composite reliability and Cronbach’s Alpha of variable Employee

Commitment have (α = 0.909) reliability, Employee Performance (α = 0.882), Job Satisfaction (α

= 0.879) and Transformational Leadership have (α = 0.932) reliability, hence the data is reliable.

In the above Table 1, Average Variance Extracted (AVE) shows convergent validity, which is

above 0.5 for all variable, the threshold for the convergent validity is 0.5 (Hair et al 2010).

Figure 2 shows the factors loadings for all the items, all factors for each item were above 0.7,

which is the desired level as explained by hair et al., (2010).




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Structure Equation Modeling

Table 2

Mean, STDEV, T-Values, P-

Values

Original

Sample (O)

Sample

Mean (M)

Standard

Deviation

(STDEV)

T Statistics

(|O/STDEV|

)

P

Values

Employee Commitment ->

Employee Performance 0.115 0.113 0.109 1.058 0.290

Job Satisfaction -> Employee

Performance 0.504 0.508 0.096 5.271 0.000

Transformational Leadership ->

Employee Commitment 0.532 0.534 0.061 8.655 0.000


Job Satisfaction 0.624 0.625 0.053 11.733 0.000




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H1: Transformational leadership has significant impact on job satisfaction.

Refer to Table no. 2 and 3, the adjusted R square is 0.387. This shows 38% variances observed in

dependent variable i.e job satisfaction. The significant value p should be less than 0.05. There is

significant relationship between transformational leadership and job satisfaction. Refer to table

no 4.7, (β = 0.624, p = 0 .000). Hence the above hypothesis is justified and we conclude that

there is significant and positive effect of Transformational leadership on job satisfaction.

H2: Job satisfaction has significant impact on employee performance.

Refer to table no 2 and 3, the adjusted R square is 0.344. This shows 34% variances observed in

dependent variable i.e Employee Performance. The significant value p should be less than 0.05.

There is significant relationship between job satisfaction and Employee Performance. Refer to




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236


table no 4.7, (β = 0.504, p = 0 .000). Hence the above hypothesis is justified and we conclude

that there is significant and positive effect of job satisfaction on Employee Performance.

H4: Transformational leadership has significant impact on employee commitment.


dependent variable i.e Employee Commitment. The significant value p should be less than 0.05.

There is significant relationship between transformational leadership and Employee

commitment. Refer to table no 4.7, (β = 0.532, p = 0 .000). Hence the above hypothesis is

justified and we conclude that there is significant and positive effect of transformational

leadership on Employee Commitment.

H5: Employee commitment has significant impact on employee performance.


dependent variable i.e Employee Performance. The significant value p is greater than 0.05. There

is insignificant relationship between Employee Commitment and Employee Performance. Refer

to table no 4.7, (β = 0.115, p = 0 .290). Hence the above hypothesis is not justified and we

conclude that there is insignificant and negative effect of Employee Commitment on Employee

Performance.

4.4 Mediation

Table 4

Specific Indirect Effects

Mean, STDEV, T-Values, P-Values

Original

Sample

(O)

Sample

Mean

(M)

Standard

Deviation

(STDEV)

T

Statistic

s

(|O/STD

EV|)

P

Value

s


Employee Commitment ->

Employee Performance

0.061 0.060 0.059 1.046 0.296

Transformational Leadership -> Job

Satisfaction -> Employee

Performance

0.314 0.318 0.068 4.607 0.000




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237


H3: Job satisfaction has significant mediating role between transformational leadership and

employee performance.

As per Table no. 4.8, Indirect effect (β is 0.314 and p value is 0.000). Hence the above

hypothesis is justified and this study concludes that job satisfaction mediates between

transformational leadership and employee performance. Partial mediation is observed in this

study.

H6: Employee commitment has significant mediating role between transformational leadership

and employee performance

As per table no 4.8, Indirect effect (β is 0.061 and p value is 0.296). Hence the above hypothesis

is not justified because p value is greater than 0.05. This study concludes that employee

commitment does not mediate between transformational leadership and employee performance.

CONCLUSION

5.1 Discussion

The aim of this research was to identify the relationship between transformational

leadership and employee performance through employee commitment and job satisfaction as

mediators. As it was already established and predicted that transformational leadership plays an

important role in the performance of an employee. The qualities of transformational leadership

influence, inspire and motivate employees to perform high through their job satisfaction and

employee commitment.

Hypothesis 1 is tested and analyzed to find the relationship between transformational

leadership and job satisfaction and that was well acknowledged. This study’s findings are similar

to the previous researches. The role of a Transformational leader and its techniques will enhance

workers’ job satisfaction and they will also perform well. This research will also explain and

highlight that employees can only become satisfied and contented with their jobs if the leader

successfully acquires and adopt transformational leadership skills. This study and it’s findings

are quite similar to the previous researches which stated that techniques of transformational

leadership to some extent enhances job satisfaction and job contentment (Bass, 1990; Voon et

al., 2011; Mujkic et al., 2014; Long et al., 2014; Cavazotte et al., 2013; Niehoff, 1990) .

Furthermore Hypothesis 2, results and findings are also similar to the previous researches that

too states and highlights that job satisfaction has significant impact on employee performance.

Because when employees will be satisfied with their jobs the will work with more devotion and

keenness (Rezwani et al., 2016; Mangkunegara, 2016; Fisher, 2003; Cheung et al., 2003).




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238


Hypothesis 3 related to the mediator that there is relationship between transformational

leadership and workers performance and job satisfaction is the mediator. Results related to the

hypothesis are also quite similar to the previous findings. The study found out and recognized

that job satisfaction is vital and important in making managers competent and effective (Shahzad

and Benish, 2017; Mangkunegara, 2016; Berson and Linton, 2005; Chou et al., 2013; Skansi,

2000; Martin, 1990).

H4 is also tested to find the impact of transformational leadership on employee

commitment and the findings were also similar to the previous study. Transformational leaders

do enhance employees’ commitment towards their job. H5 is based on the relationship of

employee commitment and employee performance does not reveal the same results as other

researchers have identified. If employees are committed towards their jobs then it is not

necessary that they will perform well.

H6 is also related to the mediator that there is relationship between transformational

leadership and employee performance and employee commitment is the mediator. Results of the

hypothesis are not similar to the previous researches.

5.2 Theoretical and Practical Implications

This study adds work related to the role of transformational leadership, job satisfaction

and employee commitment as a model in Telecom sector of Pakistan. Findings of this study

explains and states that job satisfaction mediates between transformational leadership and

employee performance, whereas employee commitment does not mediate. The findings of the

study proved our perceptions that transformational leadership has a significant and positive

impact on employee performance and job satisfaction mediates between the two. This research

basically helps in revealing the paths and ways that how qualities and techniques of a

transformational leader takes up the credit for employees’ excellent performance by showing the

importance of job satisfaction as a mediator. Adoption or introduction of transformational style

of leadership helps in increasing job satisfaction that way employees perform well. Employee

performance can only be increased if organizations promote job satisfaction among their

employees. This study’s findings and results indicate that job satisfaction mediates between

transformational leadership and employee performance and employee commitment does not

mediate between them.

Few more results are also found that is managers and employees working in Telenor

Karachi, transformational style of leadership improves their performance through job

satisfaction. Another practical implication of the study is that managers and employees of

Telenor company should be trained to learn the techniques of transformational leadership so that

they can improve their performance and organization’s performance. Training regarding




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239


transformational leadership should focus on increasing job satisfaction among workers in order

to achieve aims and objectives of the firm.

5.3 Limitations and Directions for Future Research

This study set few limitations and the first one is time constraint i.e data is gathered only

from Telenor Karachi. In future if data is gathered from different parts of the country will

overcome this limitation and provide a different result.

The second limitation is data compilation method where questionnaires are only used to

collect the data. In future data can be collected by using multiple techniques.

Again due to time constraint, purposive sampling technique is used to collect the data.

This is why any other sampling technique can be used to collect data in future.

Although, the study has achieved its objectives but in future if researchers are interested

may add other relevant variables to the study.

5.4 Conclusion

Performance and productivity of a firm totally depends upon employees’ satisfaction

towards his job, and only then it can yield high profits. Transformational leadership plays an

important role to enhance employee’s interpersonal relationship with his supervisor and also

increases job satisfaction in the organization. Transformational style of leadership helps workers

to become innovative, creative and generate new ideas which can help organization to compete

in the challenging environment. So, organizations should adopt transformational style of

leadership so that they could improve their workers’ performance. This research’s findings

conclude that managers and employees of Telenor telecom should be trained to learn the

techniques and qualities of transformational style of leadership so that they can bring growth and

development in the organization.




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240


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Toward a Model for Actual Usage of Social Networks Sites for Educational Purposes in Jordanian

Universities

Gharrah, Aljaafreh, Al-Ma’aitah

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Toward a Model for Actual Usage of Social Networks Sites for Educational Purposes in

Jordanian Universities

Ala’a Abu Gharrah, (M.S.), Corresponding Author

Management Information Systems Department, Mutah University, Jordan.

[email protected]

Ali Aljaafreh, Assistant Professor

Management Information Systems Department, Mutah University, Jordan.

[email protected]

Noor Al-Ma'aitah, Assistant Professor

Business Administration Department, Mutah University.

[email protected]

Abstract

Social network sites (SNs) are used to transform the traditional ways of education. Although SNs

is very common in different countries all over the world, its’ adoption by students in Jordan for

educational purposes is still limited. This paper addresses an important issue related to the

factors affecting the students’ actual usage of SNs for educational purposes. The paper proposes

a model aims to understand and analyze the impact of underlying factors (Effort expectancy,

Performance expectancy, Social influence, Facilitating condition, Habit, Hedonic motivation,

lecturer support, and student related factors) on students’ actual usage of SNs for educational

purposes. The proposed model will assist Jordanian Universities in understanding the factors that

may affect their students’ actual usage of SNs for educational purposes.

Keywords: Social network sites, educational purposes, Jordanian universities.





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INTRODUCTION

Due to the rapid development in information technology (IT), companies have been

affected and changed their way of doing business. The tools and capabilities offered by IT have

increased the efficiency and maximized the perceived benefits for users. The educational sector

is one of many other sectors that have benefited from information technology in delivering the

teaching process to learners (students). The interactive and collaborative environment offered by

Web 2.0 technology facilitates the communication process between teachers and students, taking

into account the propagation of these services, especially Social Networking Sites (SNS). These

social web-based sites, such as Twitter, Facebook, YouTube, and other social networking sites

are able to build a network of friends who share reciprocal concerns through blogs, virtual

classes and broadcasting that are provided for free reciprocal (Balakrishnan, 2017; Tan, Shao, &

Yu, 2014)

Social networks (SNs) refer to " a web service(s) that allow individuals to construct a

public or semi-public profile within a system with definite boundaries, articulate a list of other

participants in the system whom they share a connection and, view and explore their list of

connections and of those made by others in the system. "(Moran & Gonyea, 2003) SNs are the

most commonly used services in Web2.0, which allow users to share interests, meet, collaborate,

and interact with others (Seely Brown & Adler, 2008). A number of studies reported the

importance of using SNs in educational settings (Al-Zedjali, Al-Harrasi, & Al-Badi, 2014;

Balakrishnan, 2017). SNs can be used in the learning process; for example, Facebook and

Twitter may be used in order to stimulate thoughtful discussions on specific classroom topics,

and Pinterest website could also be used to share the learning resources. Users may draw upon a

variety of digital learning resources, such as YouTube videos, virtual reality, podcasts and

infographics in order to heighten the content knowledge, nurture an appreciation for a diversity

of viewpoints, and stimulate critical thinking.

However, there is a lack of studies that examined the factors influencing student’s actual

usage of SNs for educational purposes, especially in Middle East, Jordan as a case. The current

paper aims to address an important two-fold gap in the topic under investigation. The first gap is

an empirical one that addresses the lack of studies that examined the factors affecting students'

usage of SNs for educational purposes. Although an extensive body of literature discusses what

the motivations of students for academic usage of SNs are, literature has showed a few studies

that build unified model (Bonilla Polo & Osman, 2017), none of them were conducted in Jordan.

The second gap is a theoretical one; therefore, the current study proposed a new research

model, where an extension to the second version of the Unified Theory of Acceptance and Use

of Technology (UTAUT2) will be added in order to investigate the factors affecting the students’


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intention to use SNs for academic purposes. This extension is represented by the teacher's

(lecturer) support(Bonilla Polo & Osman, 2017),and student related factors(Al-Zedjali et al.,

2014). This paper is organized as follows. Section two addresses the theoretical background and

a literature review for this study. Section three presents the research model. Section four

discusses the research model. Finally, the researchers cited the conclusion of this study.

LITERATURE REVIEW AND BACKGROUND

Social networking sites have developed, where the first site of SixDegrees was launched

in 1996. While SixDegrees attracted millions of users, it failed to become a sustainable company.

In 2000, the service was terminated. Then, there was a development of many networks, such as

Facebook 2004, BitRetit 2010, Astacram 2010 and SnapeSat 2011, in addition to other sites that

the student can use in education. SNs have become an essential part in life (Kaplan & Haenlein,

2012). According to SNs Stats Jordan(lStats, Mar 2018 - Mar 2019), (78.3%) of social media

users in Jordan are using Facebook, almost (18.23%) use YouTube, less than (1.93%) use

Twitter, (.97%) use Pinterest, less than (0.22%) use Instagram (see figure 1 ) There are many

studies which show how social network tools can improve the learning experience by enabling

interaction, collaboration, active participation, information & resource sharing (Selwyn, 2009).


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Figure 1.

Unified Theory for Acceptance and Use of Technology (UTAUT)

Undoubtedly, the previous research has introduced different theoretical models to

examine the individuals’ technology related to accepting, adopting and using such a technology,

as well as the intention of using it. Venkatesh, Morris, Davis, and Davis (2003)reported that

TAM has been the dominant model that investigates new technology acceptance in literature.

However, researchers are recommended to examine different and new constructs and models

beyond TAM (Boyd & Ellison, 2007).

UTAUT has been developed to cover the weaknesses of the previous theoretical models

via combining eight popular models for accepting and using IT. The current model consists of

four main predictors that significantly affect individuals’ behavioural intention which, in turn,

influence the individuals’ usage behaviour. The four core constructs are Effort Expectancy (EE),

Social Influence (SI), Performance Expectancy (PE), and Facilitating Conditions (FC) (see figure

4). The efficiency of UTAUT was empirically tested and proved its superiority over the earlier


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theories. UTAUT is able to account for (70%) of the variance in adopting the behaviour in

comparison with (27%-40%) for the previous theories (Venkatesh et al., 2003).

However, UTAUT has been criticized due to its complexity, its approach was less

parsimonious, as well as its weakness in explaining the usage behaviour (Casey & Wilson-

Evered, 2012; Van Raaij & Schepers, 2008). Therefore, Venkatesh et al. (2012) developed

UTAUT and extended it to UTAUT2 (figure 5). The new version focuses on the factors that

affect specifically on the consumer's behaviour. This includes Habit (HA), Price Value (PV), and

Hedonic Motivation (HM), thus increasing the ability to apply and generalize it in both

organizational and consumer contexts. The efficacy of UTAUT2 exceeded UTAUT in terms of

explaining more variance in technology usage, as well as BI.

The following is an explanation of the dimensions of UTAUT2.

Performance Expectancy

Performance expectancy (PE) is defined as” the degree to which an individual believes

that using the system will help him or her to attain gains in job performance” (Venkatesh et al.,

2003). This factor addresses its usefulness for the students who use social media for academic

purposes. The literature showed that PE has a significant impact on the individual’s intention

towards using technology. For instance, Kijsanayotin et al. (2009) examined PE in the context in

Thailand and suggested that it has a positive impact on the user’s intention to use technology.

Also, Umrani-Khan and Iyer (2009) developed a model called ELAN to examine PE effect on

the student’s intention to use eLearning and found similar results. In the context of this study

related to adopting social media for academic purposes, studies revealed that there is a

significant positive relationship between PE and intention to use (Balakrishnan, 2017; Wang,

Wu, & Wang, 2009)

Effort Expectancy

Effort Expectancy (EE) is referred to “the degree of ease associated with the use of the

system” (Venkatesh et al., 2003 In this study, this factor relates to how easy it is for the student

to use social networking platforms for educational purposes.. Alalwan, Dwivedi, and Rana

(2017) suggested that effort expectancy significantly affected individuals’ intention to use

mobile banking in Jordan. Another study that examined the factors contributing to the acceptance

of social media as a platform among students showed that effort expectancy also had a

significant effect (Nawi, Nasir, & Al Mamun, 2016).

Social influence

Social Influence (SI) is referred as “the degree to which an individual perceives that

important others believe he / she should use the new system”(Venkatesh et al., 2003). This factor


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addresses the ways of encouraging the community, family, friends, and partners to use SNs for

the academic purposes. A study showed that SI has a significant impact on the intention of using

e-commerce in Saudi Arabia.(Alkhunaizan & Love, 2012). In addition, The findings of the study

conducted by (Abelmonaim, 2013)revealed that SI had a significant impact on the Moroccan

student's intention to accept the spirit of e-initiative. The finding of this study is similar to the

results of Al-Zedjali et al. (2014) which revealed that there is a significant positive relationship

between SI and intention to use SNSs in education. According to (Escobar-Rodrguez, Carvajal-

Trujillo, & Monge-Lozano, 2014)the factors which affect the perceived benefits and relevance

of Facebook site as an educational tool suggest that there is a significant impact for the perceived

social impact for Facebook and the perceived benefits related to that.

Facilitating conditions

Facilitating Conditions (FC) is defined as “the degree to which an individual believes that

an organizational and technical infrastructure exists to support use of the system” (Venkatesh et

al. 2003). In UTAUT, facilitating conditions have a direct impact on usage; this factor addresses

whether and to what extent the university environment can provide tools for students in order to

use them for academic purposes, such as electricity, the Internet, computers and others. The

factors affecting the adoption of mobile banking in Jordan were studied and it was suggested that

the facilitating conditions have an important role in predicting the actual usage of mobile

banking services (Alalwan et al., 2017). Also, several studies revealed that there is a significant

positive relationship between FC and actual usage (Nawi et al., 2016; Venkatesh et al., 2003).

Hedonic motivation

In UTAUT2, the hedonic motive is the decisive determinant of behavioral intent. (HM) is

referred to as "fun or pleasure derived from the use of technology" (Brown & Venkatesh, 2005).

HM has been described as the perceived enjoyment of using information technology, which has

manifested its impact on the intention of using technology (Alhazmi, Rahman, & Zafar, 2014;

Nawi et al., 2016)argued that HM is the extent to which a student feels pleasure while using SNs

in the learning process. (Kumar, 2013)demonstrated that the perceived enjoyment has a strong

relationship with the behavioral intention to use 3G technology in Shimla, India. In addition,

Alalwan et al. (2017) suggested that HM was an empirical guide and a decisive factor affecting

the intention of the Jordanian customers to employ mobile banking services.

Habit

Habit is defined as the extent to which people tend to perform behaviors automatically

because of learning (Limayem, Hirt, & Cheung, 2007). This factor investigates whether students'

habits have any influence on their intentions to use social media for the academic purposes. In

many studies, the habit proved its significant impact on the intention of the individual to use new

technologies (Limayem & Hirt, 2003; Venkatesh, Thong, & Xu, 2012). Moreover, Al-Zedjali et


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al. (2014) indicated that habits strongly predict the students' behavioral intention with regard to

using Facebook in their studies.

Actual usage

Actual usage AU is defined as “the actual usage of SNs for learning” (Balakrishnan,

2017)The role of Actual Usage as a predictor has been well established in the literature

(Balakrishnan, 2017; Tan et al., 2014; Venkatesh et al., 2003; Venkatesh et al., 2012)

Model extension variables

This study also attempts to extend UTAUT2 by adding new variables such as lecturer

support (Bonilla Polo & Osman, 2017) and student related factors (Al-Zedjali et al., 2014) which

had significant impact on students’ decisions to use SNS for educational purposes. The following

is an explanation for those factors:

Lecturer Support: Lecturers find SNs as a very useful tool for promoting teaching and

learning(Bexheti, Ismaili, & Cico, 2014). There are many studies that consider lecturer support

as an important factor for students to use SNs for academic purposes (Alhazmi et al., 2014;

Bonilla Polo & Osman, 2017). According to Bryson and Hand (2007), students' participation and

learning is promoted when faculty members actively participate in teaching and learning

activities. Finally, lecturer support is considered as an essential element with regard to the intent

to use SNs for educational purposes.

Student- related-factors: The current study defined this factor in terms of including

collaboration, sharing, and interaction. Firstly, collaboration is defined as "the extent to which

SNs support collaboration activities”; for example, the students' cooperation to do the homework

and study for the exam. Secondly, sharing is defined as “the extent to which SNs support sharing

of academic materials”. Thirdly, student’s interaction is defined as "the extent to which SNs

enhance interaction between students”, such as student interactions through the construction of

educational chat rooms, educational groups or creating pages on SNs to serve other students

(Balakrishnan, 2017; Umrani-Khan &Iyer, 2009). Moreover, Moran and Gonyea (2003)indicated

that peer interaction is the strongest predictor for engagement.


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Research Model

Based on the above discussion, the following research model is proposed (Figure 2).

Model UTAUT2

DISCUSSION

This paper introduced the educational SNs Model in Middle East, Jordan as a case. The

model provided a set of important factors influencing students’ actual usage of social networks

sites for educational purposes and their relationships. The model was also developed based on

the analysis of existing models and theories; and addressed their shortcomings. Most of the

factors of the proposed model were distilled from the related models and theories discussed the

issue of actual usage. However, the research model was distinguished from existing model:

Actual usage of

SNS for

educational

purposes

Effort expectancy

Social influence

Habit

Performance expectancy

Facilitating condition

Hedonic motivation

Student-related

factors Lecturer

support

Model Extension


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firstly, it discussed the research model in the specific context of Jordan, which had not been

studied before. Secondly, the proposed model included UTAUT2 (Effort expectancy,

Performance expectancy, Social influence, Facilitating condition, Habit, Hedonic motivation)

and additional important factors of (Student-related-factors, Lecturer Support). The proposed

model had both academic and practical implications. The model was intended to fill the research

knowledge gap due to the lack of studies in the context of Factors Influencing Students’ Actual

Usage of Social Networks Sites for Educational Purposes.

CONCLUSION

This paper presented educational SNs model in the context of Jordan in the Middle East

region. The paper analyzed and integrated the Unified Theory for Acceptance and Use of

Technology (UTAUT2) with an extension, in order to identify the Factors Influencing Students’

Actual Usage of Social Networks Sites for Educational Purposes. This new model presented a

number of new ideas related to the factors influencing student’s actual use of SNs for educational

purposes. The current study aimed to bridge the research gap due to the lack of studies dealing

with SNs for educational purposes in the context of Jordan. The model would be further

evaluated and updated if necessary; and the research results would be reported as an on-going

contribution to both research and industry.


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Product/Service Complexity and Choice of Channels for Information Search During the Purchase

Process: A Proposed Model Based on Media-Richness Theory

Essebi, Tomiuk, Plaisent, and Bernard

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Product/Service Complexity and Choice of Channels for Information Search During the

Purchase Process: A Proposed Model Based on Media-Richness Theory

Elyes Caid Essebsi

University of Quebec in Montreal

Daniel Tomiuk


Michel Plaisent


Prosper Bernard


Summary

Today, ubiquitous technologies such as smartphones and the Internet enable online purchasing.

This benefits both sellers and buyers (e.g., new markets, greater selection). Consumers' choice of

channels during the purchasing process is influenced by many factors (promotions, previous

channel experience, demographics, product/service characteristics, channel features and

situational factors). To our knowledge, no study has explored whether channel richness helps

explain channel choice for information search during the purchasing process. Our conceptual

model proposes that product/service complexity influences channel choice by increasing buyers'

preference for richer channels. We conclude with a discussion and recommendations for

companies using multiple sales channels.




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Introduction

The Internet and telecommunication networks have become ubiquitous, particularly in

retailing where they enable a company to offer more channels to consumers facilitating their

information search and their purchasing of its products/services (Singh and Swait, 2017). New

online sales channels are made possible through Web and mobile technologies and are

increasingly supported by social media. For companies, these multiple channels offer several

potential advantages, such as, access to new markets, 24/7 availability, cost savings, etc.

However, this also adds to the complexity of running a business. Challenges include how to best

manage multiple channels so as to reduce cannibalisation and create synergies between available

channels (Beck and Rygl, 2015).

Consumers as well can benefit from having access to several channels. These provide

more flexibility during the multiple stages of the purchasing process (Butler and Peppard, 1998,

Kotler and Keller, 2006). Research shows that new buying behaviors have indeed emerged.

Today, consumers use a combination of different channels at different stages of their purchasing

process (Singh and Swait, 2017). According to a study done by CEFRIO (2017), 51% of

consumers are showrooming (searching for information in physical stores before making an

online purchase) while up to 80% do webrooming (search information on the Internet to make a

purchase in store). Reportedly, around 38% of online shoppers pick up their product in a physical

store after having bought it online and up to 27% return products bought online at physical

stores.

Studies reveal that consumers' choice of channels during the purchasing process is

influenced by several factors such as: the promotional activities of the company, the previous

experience of the buyer, demographic factors, social effects, product / service characteristics,

channel characteristics and situational factors, and many more that remain unexplored. In

parallel, e-commerce research shows that making rich information available to consumers on

Websites influences their satisfaction during the purchasing process (Pinsonneault, Li and

Tomiuk, 2010). However, to our knowledge, no study has yet investigated whether media

richness theory (Daft and Lengel, 1986) can help better explain consumers' channel choices

during the purchasing process. The main objective of our study is to propose a model that links

the complexity of the product/service and the information richness supported by the channel

chosen by the buyer when searching for information during the purchasing process. We conclude

our paper by discussing the implications of this study for more effective management of multi-

and omni-channel selling environments.




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The Purchasing Process

Purchasing is a multistage process (see Figure 1). Typically, consumers go through five

stages. Each one includes different decisions (Butler and Peppard, 1998; Kotler and Keller,

2006). The stage that lies at the heart of our study is stage two: information search. Initially

(stage 1), the consumer identifies a need. At stage 2, (s)he collects relevant information about

potential solutions that will satisfy that need. In stage 3, (s)he evaluates and compares among the

alternatives found. A subset of choices can be retained which will then be re-evaluated before

making a final decision. The choice among alternatives happens in stage 4. The last stage (5) is

where post-purchase behaviors occur and is guided by the customer's degree of

satisfaction/dissatisfaction (Butler and Peppard, 1998) at which point the customer may decide to

go on a Website or use social media to leave comments about the product or company (s)he

purchased.

Stage 2 (information search), which is of interest to us in this study, is among the stages

that take the most time. It's based on economic evaluation, a mental calculation done by the

consumer on whether to stop his/her search for additional information (because it engenders

search costs) or to continue in the hope of finding new and useful information (Stigler, 1961).

The search costs include time, effort and money. The benefit attained from searching is the

reduction of risk. As such, stage 2 comes down to a cost-benefit analysis made by the consumer

on whether it is worth it or not to continue to search for additional information in order to further

reduce the risks associated with making a bad or suboptimal purchasing decision (Bugday, Sener

and Babaogul., 2016).




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Figure 1 - The purchasing process

With today's Internet- and mobile-based technologies further facilitating the purchase and

sale of products and services, consumers find themselves with several channels available for use

at each of the stages of the purchasing process. In parallel, companies are increasingly interested

in making the best use of these several when selling their products/services to consumers by

adopting multi- and omni-channel strategies (Rigby, 2011). "Multi"-channel selling is about

better understanding and managing the substitutability among a company's available channels.

"Omni" is from Latin meaning "everything". The challenge for companies is more combinatorial

in nature. It's about better integration between channels. Omni-channel selling consists of

figuring out how to effectively use all physical and virtual channels in complementary ways.

Successful integration among various channels can generate added value, not only for the

customer but for the company as well. For instance, a company that allows its customers to

retrieve, at one of their physical stores, products ordered online, also increases its chances of

making another sale once that customer enters the store to pick up his/her order (Montoya-Weiss,

Voss and Grewal, 2003).

Research into understanding how to best use and combine the several channels available

to companies is increasing in popularity. But it's still in its infancy. Many researchers have

highlighted the importance of better understanding consumer behavior in multi- and omni-

channel environments (e.g., Chatterjee and Kumar 2017; Luo, Fan and Zhang, 2016; Park and

Lee 2017). The factors that explain consumers' choice of channel are still not well understood

1 - Problem recognition

2 - Information search

3 - Evaluation of alternatives

4 - Purchase decision

5 - Post-purchase evaluation/behavior




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(Singh and Swait, 2017). In multi- and omni-channel selling environments, it has become

necessary to investigate, not only the factors that can influence the number of channels used by

customers, but also what factors lead consumers to prefer particular channels relatively to others.

Arguably, such research can help companies develop more optimal portfolios of channels to

better serve its customers throughout the purchasing process while reducing the risk of

cannibalization among the companies' channels.

Factors Influencing Channel Choice

Past research has identifies several factors that can explain customers' channel choices

during the purchasing process (e.g., Gensler, Verhoef, and Böhn, 2012; Hummel, Schacht, and

Maedche, 2016; Neslin et al., 2006; Singh and Swait, 2017; Valentini, Montaguti and Neslin,

2011). A review of these studies reveals the following categories of factors: (1) the company's

promotional activities (2) past consumer experiences with a channel (3) individual differences

(4) demographic factors (5) social influences (6) product/service characteristics (7) channel

characteristics and (8) situational factors. To the best of our knowledge, we did not find any

study that has explored whether Media Richness Theory (Daft and Lengel, 1986) can help

explain channel choice during the purchasing process.

Media Richness Theory

Media Richness Theory (Daft and Lengel, 1986) was developed to explain managers'

choices among available communication channels in organizational settings. According to the

theory, certain channels are better adapted at conveying certain types of messages. Channel

richness reduces message ambiguity. The richer the channel, the better it is in conveying

complex/equivocal messages. The theory proposes that channel richness is characterized by the

following four factors:

1- Multiplicity of cues: Cues include vocal intonations, facial expressions and gesturing. The

greater the cues supported by a channel, the greater its support for more complex

communications between sender and receiver.

2- Immediacy of feedback: Channels that support real-time communications are richer than those

that do not.

3- Personalization: Describes the channel's ability to adjust and shape the message to the needs

and preferences of a user.

4- Linguistic variety: Verbal communications are judged to be richer than a written

communications (Gimpel, Huber and Sarikaya, 2016).




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The theory proposes that companies can hierarchically rank their available channels on a

scale of richness. Accordingly, the richest channel is face-to-face, followed by

videoconferencing, telephone, chat, emails, static Website and written documents, being the

lowest.

Several research studies have attempted to adapt Media Richness Theory to the

context of e-commerce. Pinsonneault et al. (2010) proposed a concept called "information

richness" that can be applied to new electronic channels such as Websites. Jahng, Jain and

Ramamurthy (2007) adopted a similar strategy and proposed the concept of " richness of

interactions" between buyers and sellers operating online. Rukundo, Tomiuk and Motaghi (2018)

showed that richer channels could help companies to better deal with service failure recovery

efforts when the problems were more serious and difficult to solve. Results from these studies

support the usefulness of the richness concept when applied to e-commerce. In sum, all of these

studies show that richness can have a beneficial influence on consumers' attitudes, especially

when the consumer perceives complexity (e.g., message, problem, product) to be high.

Model and Hypotheses

Our proposed model seeks to help explain consumers' choice of channels when

searching for product/service information during the purchasing process. It takes into account the

following constructs: "product/service complexity", "channel richness", "channel convenience",

"use of online channels" and "use of off-line channels" (see Figure 2).

The model proposes that, during the information search stage of the purchasing

process, the greater the perceived complexity of the product/service by the buyer, the more (s)he

will show preference for richer channels. This preference for richer channels will make the buyer

more likely chose offline channels (e.g.., physical store, traditional bank branch where face-to-

face encounters prevail). Our model also predicts that when the product/service complexity

decreases, consumers will prefer more convenient channels instead. All else being equal, when

product/service complexity is low, the desire for convenience (rather than richness) will make

buyers more likely to use online channels rather than to take the time and make the effort to

travel to physical locales.




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Figure 2. Conceptual Model

Product/service complexity is an important factor influencing consumers' channel

choice and promotes multi-channel behaviors (e.g., Frambach, Roest and Krishnan, 2007,

Kushwaha and Shankar, 2013). It's defined as the extent to which the consumer perceives that a

product/service is difficult to understand or use (Nicholson, Clarke and Blakemore, 2002). This

brings us to our first set of hypotheses.

According to Media Richness Theory, complex (equivocal) communications require

rich communication channels so as to reduce ambiguity. In the context of information search for

products/services, the theory suggests that, the more complex the products/services consumers

seek to buy, the more the consumer will tend to choose a rich channel during the information

seeking stage of the purchasing decision process. Moreover, since the traditional store (or

branch) supports the richest communications (i.e., having direct face-to-face access to a

company's representative), we propose the following hypothesis:

H1a: The greater the perceived product/service complexity, the more the consumer will prefer

rich channels when searching for product/service information.

As for less complex products/services, the theory suggests that less rich channels

would be more appropriate information sources. This brings us to our next hypothesis deduced

directly from the theory:

H1b: The lesser the perceived product product/service complexity, the less the consumer will

prefer richer channels when searching for product/service information.

Product/service

Complexity

Preference for

convenient

channel

Preference for

rich channel

Use of online

channels

Use of offline

channels H1a(+)

H1b

H2(-)

H3(+)

H5(+)

H4

H6




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The scientific literature reveals that perceived convenience plays a predominant role in

the choice of channels during the buying process for consumers (Frambach et al., 2007, Gensler

et al., 2012, Nicholson and Van Heems, 2009, Verhoef, Neslin and Vroomen, 2007).

Convenience relates to saving time and minimizing effort (Berry, Poortinga, Segall and Dasen,

2002). We therefore propose that, when product/service complexity is low, it will be

convenience (rather than richness) that will drive channel preference during the information-

seeking step of the purchasing process. This brings us to our next hypothesis:

H2: The lesser the perceived product product/service complexity, the more the consumer will

prefer channels that are convenient to use when searching for product/service information.

We conclude by proposing that there is a direct relationship between channel preference

and actual channel use. Because off-line channels are considered the richest (Pinsonneault et al.,

2010), we expect that:

H3: A positive relationship exists between the preference for rich channels and the use of offline

channels (e.g., store visit / branch) when searching for product/service information.

Although we recognize that, today, online channels can be designed so as to

convey more richness (Pinsonneault et al., 2010) about a company's products/services (e.g., by

adding videos, creating virtual reality environments, and adding chat bots), media richness

theory predicts that face-to-face (interpersonal) interactions are still the richest of channels. We

therefore propose that:

H4: Although a positive relationship between preference for rich channels and use of online

channels may exist, on average, this relationship will be relatively weaker when compared to the

positive and significant relationship between preference for rich channels and use of offline

channels (i.e., traditional stores).

In terms of information retrieval, research indicates that online channels reduce efforts

related to information searches and making it more convenient for users (e.g., Gupta, Su and

Walter, 2004). Arguably, a consumer can more easily browse the Web or his/her smartphone for

information on a product/service they are interested in buying than to physically travel to

physical stores. Consequently, we propose the following two hypotheses:

H5: A positive relationship exists between the preference for more convenient channel (e.g.,

Websites, mobile applications) and the use of online channels when searching for

product/service information.




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H6: Although a positive relationship between preference for convenient channels and use of

offline channels may exist, on average, this relationship will be relatively weaker when

compared to the positive and significant relationship between preference for convenient channels

and use of online channels.

Proposed Methodology

The next step in our research will be to develop and validate our questionnaire.

Definitions of concepts under study will be used to come up with questionnaire items (Churchill,

1979). We will develop Likert type scales with multiple items for each of the constructs being

measured to more richly reflect the complexity of these concepts/constructs (McIver and

Carmines, 1981). Card sorting (Moore and Benbasat, 1991) will be employed for content validity

purposes. The questionnaire will be distributed across various IS/IT classes at the bachelor's

level at the University of Quebec in Montreal during summer 2019.

Partial Least Squares (PLS) (Kock, 2016) is a form of Structural Equation

Modeling (SEM) that is widely used for causal research in several fields such as in IS and

communications. It will be used to test our model. The PLS approach was chosen because it

allows for the estimation of complex causal relationships between latent variables and is

advantageous when used with smaller sized samples (Hair, Ringle and Sarstedt, 2012).

Discussion

The Internet and mobile technologies continue to contribute to the evolution of e-

commerce by providing more purchasing options and affecting the buyer's purchasing process

(Bucklin and Sismeiro, 2009, Singh and Swait, 2017). Many factors have been identified to

explain why consumers chose particular channels during the purchasing process rather than

others. Our study seeks to show that the concept of richness (Daft & Lengel, 1986, Pinsonneault

et al., 2015) can also help explain the choice of channels made by consumers while searching for

information on a product/service. Our model proposes that the selection of richer channels will

be preferred by customers searching for information on more complex products/services. If

supported, our results will be of help to companies looking to more effectively manage their

available sales channels. Information provided for complex products and services are best to be

done using channels such as traditional stores or Websites designed to communicate very rich

information to consumers. For less complex products and services, companies should focus of

providing consumers with convenience rather than richness. The actual empirical results for this

study are expected in the Fall of 2019.




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[email protected]

Hamed Motaghi, Ph.D., Corresponding Author

[email protected]

Hilda Hurta, Ph.D.

[email protected]

Mario Malouin, CPA

[email protected]

Abstract

The structural forms of companies on the market lifecycle change substantially as the lifecycle

unfolds. These changes are both structural and topological in concert with what is happening in

the market. The firm shapes and substance evolve in a fashion that suggests an environmental

adaption dictated by the market or more precisely anticipated by the firms as they read the

market signals. This article traces the logic that defines the modes and results of this adaptation.

The lifecycle itself has been demonstrated to be a powerful device by the principal author and

colleagues, in a series of articles, to be symmetrically predictive in time, forecasting both the

future and the past. This predictive capacity applies to structural evolution of the firm and the

constraints that the distinct organizational shape of the structure will place on the firm.

Furthermore, knowing the present shape, one can define both the past and successor structures

and their fit to the enabling environment. The environment itself can be traced to market deep

and surface structures and the closely correlated strategy landscape dominant at each stage of the

market.

Keywords: Market Lifecycle, evolution of firm, organizational structure, strategy, customer

profile







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The market landscape; the deep and surface structure of the market

The deep structure of the market is defined by the underlying customer base that sends

specific signals to the surface structure captured by the lifecycle , on how to address the needs of

the customer base over which the particular firm is trending along the lifecycle (Vernon 1992).

In high tech markets (Pavitt 1984) the underlying customer profiles define the

fundamental dynamics of the market demand response, and this concept is easily extended to all

markets that are characterized by a succession of demand profiles as the firms drift along the

market lifecycle, which is the surface structure.

The deep structure customer profile is distributed as a bell curve, consisting of innovators

and early adaptors who set the tone for the interactions between the entrepreneur suppliers and

the early risk taking and curious client base.

Exhibit 1 captures the drift of the surface structure, the lifecycle over the deep structure, the

customer base.

BowlingAlley

Tornado Tombstone

Shakeout

Mainstreet




Chasm

Early market

Exhibit 1 – Market dynamics

These represent a small portion of the market and the first major survival test for the

entrepreneurs does not happen until reach the chasm and cross into market client majority with a

complete product, where they need to work of their localized expansion strategy defined by the

bowling alley. This initial breakthrough into the core of the market, consisting of the pragmatics

and the conservatives is a carefully husbanded period of creating significant market traction by



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building customized products defined by a product theme, such as security, as was the case with

Entrust, and cross selling to the core customer’s ecosystem though endorsement of the target

customer.

Entrust, after gaining the confidence of the banks, used their satisfaction to penetrate the

banks’ supply and distribution channel ecosystem and the concept of vertical marketing to move

up and down the banks’ value chains and establish closely knit colony of customers where cross

endorsements became a vital marking tool. Unfortunately Entrust did not build this business fast

enough (Fagerberg 2002) and was bypassed on growth curve by Verisign (W3Techs), which

eventually used its accumulated market value, due to its superior growth, to dominate Entrust.

This cautionary tale illustrates the dual aspect of early market strategy, grow fast to

penetrate the market and grow faster than the immediate competition or face the prospects of

dominance (Schumpeter 2010). Not just market share but relative market share, or market

strength, defines your future.

Once the market growth really takes off, the bowling alley is left behind, growth is

pursued at all costs, in fact in early markets stock price is correlated with market growth and

market strength, and profits don’t matter.

Shopify has been using this concept successfully by creating incentive regimes for

existing customers to recruit others through a well-known concept of “churn”, use every means

to increase the top line and strengthen your share price vis a vis the competition (Shopify 2018).

Once into the high growth phase of the market where the early majority customers,

pragmatics seek you out, marketing stance shifts from carefully designed penetration strategies

through vertical marketing, premised on ample local customization, to horizontal marketing

strategy where the firm abandons all pretext of catering to selected customer groups and tries to

follow the market growth through any path available to reach an eventual dominant market

share.

This race to the top is accompanied by both the opportunity to start building brand

strategies, which are less expensive to defend than to attack and seeking out market partnership

to establish product standards platforms (Porter 2011). This is the first instance of cooperation in

the market as standards slow down subsequent intrusions of new technology, and therefore act as

a defensive measure and send out assurance signals for the cautious clientele, hiding out in the

conservative category.

In fact we have demonstrated in previous articles (Paquin and Koplyay 2007) that market

competition continually shits from a standalone approach in early markets, where a firm is



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loosely linked to an ecosystem, to a full cooperative mode of the value chain where competition

is between chains and the voice of the individual firm is lost, drowned by the needs of the chain.

Somewhere along the growth part of the lifecycle, but when growth slows down and the

exponential portion of growth reaches the inflection point, too many firms are present in the

market and a shakeout ensues. This blind and mad scramble to reduce market supply side to the

prevailing deep structure demand conditions takes a significant toll on the number of

competitors. Usually firms with deeper pockets survive, or ones with parents with deeper

pockets. Once the shakeout dies down the market becomes a much of stable entity, with both

supply and demand side exhibiting reasonable and predictable attributes (Nelson 2009).

When market horizons lengthen, product introductions diminish and innovation assumes

incremental risk aversion mounts and generally a modus vivendi is reached among competitors

(Koplyay and Hurta 2016). At this point to enhance competitive advantage a round of M&A

ensues to build market share as organic growth becomes difficult, and this purchase of

competitors leads to a superior ability to execute against the final strategy of the market, cost

leadership, which are given the to the firms (Nonaka 2008).

Market share acquired through an M&A allows to economies of scale which is the

principal means to respond to cost leadership, by increasing margins, which after a few rounds

leads to superior profits or cash flows, called economic value added, and defines share price. In

early markets the value added is share price increase in late markets its profits. Interestingly there

seems to a rationale to this market encompassing logic and is illustrated by the sequence of

strategies given to the firms ,from early market positioning strategies to find your place to

execute the best you can against the place you occupy. Exhibit 2 provides the overview to the

succession of strategies available during the lifecycle.



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Exhibit 2 – Succession of strategies

An important fact to note is that the strategy funnel is continually decreasing with myriad

of options in early market positioning reduced to one by market maturity. This implies among

other things that the strategic premium in early markets is nimbleness of finding the best market

position for the firm and hence the attention is paid to the market dynamics, whereas in late

markets the position is given, so that essence of strategy shifts from choice of strategy to

execution of strategy, from positioning to execution. In other words, from effectiveness to

efficiency.

The lifecycle then moves from two climate zones in the market; a zone of effectiveness

that starts at incubation and lasts until about just past the standards platform and efficiency that

truly demands attention past the shakeout crisis point and lasts throughout the rest of the market

life. During a brief period they overlap when the standards platform is formed. But the firms in

the market sense this evolution and start aiming for market share right at the beginning of the

market to be able to execute eventually against the requirements of cost leadership (Utterback

1996). Both the market and the instinctive evolution of the firms aim for such long term

transition from effectiveness to efficiency.

It is as if the market forces shaping the competitive universe and the incremental

evolutionary forces of the firms, leading to adaptive behavior, both exert forces on the firms in

the same direction. And we’ll see the effects of this combined effort on the structural succession

of firm organization later. Exhibit 3 displays the two climate zones of the market.



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Exhibit 3 – Climate zones

In general effectiveness zone requires swift adjustments, flexibility under market forces

and adaptive capacity to follow market signals, whereas efficiency zone demands progressively

more focus on delivering against a given strategy, ability to resist and attenuate market forces

and a capacity to cooperate and coordinate with partner firms which eventually coalesce into

value chains and the market offers the right circumstances for both to succeed.

Early markets forgive mistakes of positioning by offering high growth to cover up

mistakes, high margins to compensate for lack of total volumes and late markets offer much

more stable environments, longer planning horizons and sluggish competitive moves to

compensate for the heavy structural burdens now carried by the firms.

The shape and growth of corporate structures under the market climate zones

A well-known fact from organizational theory is the structural forms assume specific

shapes and succeed each other in orderly fashion along the lifecycle (Vernon 1992). Exhibit 4

depicts the evolution of organizational types along the cycle.



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Exhibit 4 – Organizational types

This is quite interesting as the question now that can be raised is why these forms and not

others? Strictly from a network perspective other competing shapes could be selected, but the

firms always assume the same sequence of organizational types, with the controlling entity at the

top and having horizontal and vertical dimensions that mutate as the firm grows.

Why is this? With the central controller at the top, especially in early markets, allows for

the quick decisions that makes real time repositioning possible. One person decides and the firm

follows.

There is a price to pay for this audacious freedom, the firm has a critical component the

CEO, which if suppressed leads to disintegration of the whole firm. But it offers interesting

advantages beyond quick reaction time in turbulent markets.

The average path to any member of the firm is minimized and is equal at any level of the

firm, hence sharing of unfiltered yet critical information is maximized, and everyone remains on

the same level of awareness about the environment.



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In general, when the CEO is suppressed in early markets the firm is in survival danger

whereas in late markets the departure of the CEO may lead to much needed rejuvenation.

However, in late markets, when firms align in value chains, it’s no longer the CEO who

is critical to survival but the rather survival of the whole firm determines the state of the chain.

The critical units become impersonal and much bigger in late markets.

Furthermore, entrepreneurial CEO’s tend to be market focused and constantly weigh their

chances at the market position they occupy, ready to move a slightest uncomfortable conspiracy

of circumstances the market contrives. In addition, the market doesn’t lack surprises, from

intruding new technologies, to market convergence of substitute markets to wild migration of

client bases, the odds of remaining at a position of choice is shim.

In general, we see the importance of the horizontal and vertical dimensions of a firm

structure. The horizontal dimension contributes to the completion of functional elements of the

firm starting with product development, to marketing, to finance and then on to production with

the overhead functions of HR, supply chain/distribution channels management following as

necessary (Penrose 2009). For example, HR does not really materialize until employees can be

retained. And investments in employees can be made, such as training and promotion which

become long term investments in the individual.

Early market employees are nomadic and are often lost to competitors when the

innovation rush is more palpable on competitors’ premises. The first sign of successful retention

possibilities occurs when the firm begins to offer pension, education and savings plans. Being

mostly horizontal in shape, early firms adapt well and fast to changes having just minimal

baggage to drag along. However, once the efficiency climate zone starts intruding the shape

changes drastically

Sensing the eventual need to for productivity the firms begin the vertical process of task

delineation by adding progressively more layers to the organization.

This allows for tighter focusing of tasks, more specialization, higher level of repetition of

the same tasks, resulting in superior execution against productivity demands. However, there is a

price to pay, as the lower levels in the firm lose environmental perspective and a long term

planning capability.

This leads to differentiation of compensation, a CEO is compensated on a five year cycle

a VP, maybe on three and a production worker on a weekly basis. But for a short time period

until the new culture takes hold the firm is on a dual track.



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Strategies are formed, as prescribed Minzberg, by a combination of top down and bottom

up process, and after a period of comingling a compromise strategy emerges (Mintzberg 2000).

This was evident when Compaq fled the Wintel value chain and bought DEC.

The new firm was going to dance to Compaq’s tune, yet the reality that merged, given

DEC’s dominant size compared to Compaq, that the new firm left PC’s far behind and became a

consulting entity with a strong DEC cultural flavor. Exhibit 5 captures the essential features of

design principles along the horizontal and vertical dimensions.

Exhibit 5 – Firm structures

As the vertical dimension begins to dominate in late stages the internal integrative

mechanism, called linkages illustrated by coordinating departments, which spring into existence

to eliminate the silo effect, add considerable complexity to the structure of the firm. (And

complexity here is defined as an increase in nonlinearity of connections among nodes of the

structure)

This is true complexity as opposed to complicatedness because the structure of

coordination is constantly shifting, emerging and disappearing, making the deciphering of the

permanent firm shape almost impossible.

It as if complexity in the market migrated into the firm.



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Exhibit 6 demonstrates the essence of this still unproven proposition; market complexity

migrates in the firm from their respective alliances

The special case of matrix and organizations and merging value chains

We know for a fact that firm resilience associated with effectiveness and firm robustness

required to resist shocks in efficiency zones head in opposite directions. Early firms yield to

market shock by seeking out a different position and in the process absorb shocks by accepting

structure deformations, they are adaptable to the hostile early market turbulence.

Therefore, late stage firm are anchored at specific positions and must remain there to

protect their accumulated asset investments, they resist shocks by robustness of structure their

own and that of their value chain alliance. Nor can they afford structural deformations that

destroys linearity of the alliance as linearity is a prerequisite for efficient flow of resources

through the chain. So they resist any shocks that could deform the alliance structure

Resilience is akin to adaptation by avoiding the full impact of the market force whereas

robustness is equivalent to absorbing the force. Resilience depends on survival after

displacement and robustness indicates building high level of tolerance and redundancy into the

firm and its alliance structure to survive planned magnitude of shocks. Exhibit 7 illustrates the

relative dominance of resilience vs robustness during the lifecycle.

Exhibit 7 – Robustness and resilience

Interestingly both the firm structures under evolution in the market and the associated

alliances, from ecosystems to value chains exhibit a high level of symmetry. This implies an



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importance of symmetry to the firm and its neighborhood. Why? The answer can be found in the

basic property of symmetry, the implication of order which preserves desirable qualities such as

control with minimal information flows.

A symmetric organization (left looks the same as right under a reflection around an axis

in the middle) is easier to inform and direct as the MIS effort is same for both sides. This means

the organization is faster to respond to crisis either of displacement or a resistance nature, in

almost real time as the environmental shock unfolds. So the preservation of firm and alliance

symmetry contributes greatly to survival chances.

Now let us look at a specific instance in the lifecycle where both resilience and

robustness matter and are of equal importance. This is the crossover point of the two curves

where usually matrix type organizations occur on the lifecycle.

The matrix is a compromise structure, neither fish nor fowl that carries attributes of both

curves.

It is reasonably resilient and robust, corresponding to a period of indecision in the market,

when the firm is hesitant about line of business expansion and preservation of resources in light

of uncertain prospects.

The matrix is weak or strong depending whether the functional (horizontal) or the line of

business (vertical0 dimension dominates. It is highly unstable and tends to degenerate into one of

the two modes. It is essentially a resources sharing mechanism, that loses its valued symmetry

temporarily ,is hard to control due to existence of dual direction (either line of business of

functional management can control, and sometimes both).

Furthermore, the matrix goes against the grain of adapting to an efficiency climate that

looms in the market. It is mostly project based where the assignment of functional skills is done

on a temporary basis to the line of business that represents the project but hopefully will grow

into a sustainable business.

Hence the matrix is the ultimate compromise in the market, it’s hedging bets that major

shocks won’t intrude in the expectation, that in the meanwhile, firm resource expenditures can be

husbanded.

Given its instability the matrix takes conscious and substantial effort to manage,

especially to preserve its inherently unstable shape. Whenever a crisis intrudes, such as more

market turbulence, inherent in effectives zones it reverts to a functional form; gives up on the

line of business expansions.



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If the market forces on the other hand strongly signal the advent of the efficiency zone

then the matrix degenerates into the line of businesses dimension, which it does anyway in the

long run to help with the productivity concerns of each line of business. It gives up resources

sharing and develops a resource base for each business. Exhibit 8 shows the essential features of

the matrix.

Exhibit 8 – Matrix structure

Of particular significance are the facts that the matrix exists during a period of high

uncertainty and is adequate a solution to a compromise situation between effectiveness and

efficiency, a period when the two climate zones overlap.

It is not optimal for control or adaptation to change market conditions, but it preserves

firm resources when the market signals become contradictory or conflicting. Indeed most of the

time as the market progresses towards efficiency the matrix transforms into a divisional structure

and the functional units are built within each line of business.

With respect to the emergence of the value chain after eh matrix dilemma is left behind,

some curious phenomena can be observed. The value chain is completely linear network,

implying that everyone of its constituent component is critical. If one is suppressed the chain



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goes under. There is precious little resiliency left and all is invested into robustness, the ability

to withstand shocks.

In contrast the early ecosystem exhibits practically no criticality as no node is essential to

survival, this system is very redundant in structure and hence resilient. The important question is

what in the market forces unfolding compels the linearization of the ecosystem into a value

chain, which of course is necessary to the delivery of productivity? Or if not, market forces is it

then the firm and alliance adaptive process that leads to these changes? Or is it the combination

of the two?

From highly nonlinear, complex structures that are extremely well suited to yielding to

market forces to rigid linear structure that delivers the best efficiency but is vulnerable to shock

loads. The authors best informed intuition is that it is a combination of the market forces and the

adaptive capacities of the firms and their alliances that produces this evolution.

The market has a life of its own and the progression of market circumstances signals

firms to adapt and evolve, although there may be temporary deviances from evolution and

emergence of compromise structures such as the matrix.

Conclusions

The firms evolve in their markets according to the dictates of forces found along the

market lifecycle and this evolution choses certain structural forms that best fit the market

requirements and the firm needs to control and respond (Penrose 2009).

The observed firm structures in markets display a logical response to market pressures

and forms selected form all those available are the optimal in the sense of fitting into market

constraints at the given point of the cycle, while providing the firm with levers to manage its

internal operations, minimize information requirements through preservation of organizational

symmetry and through the changes in horizontal and vertical dimensions of its structure deliver

against the two principal climate zones of its market existence.

Further research should elucidate whether the market forces dominate the process of

adaptation by imposing inescapable constraints or the firms possess an internal mechanism that

responds to market signaling and, unforced, goes through an adaptive process that finds a new

structural equilibrium. Or perhaps it is a combination of the two? An unresolved phenomenon is

still the selection of the classical pattern of a central controller from all the network patterns

available for the firm structure, it’s always central controller at the top.



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This is partly explained by the need to keep communication paths minimal to all levels of

the organization and hence an efficient MIS system, but it’s not enough. Central control is after

all a risky choice in early markets as the suppression of the CEO results most of the time in the

demise of the firm. A solution appears now on the horizon with the advent of AI and blockchain

to guarantee the success of distributed control and transparency (Tapscott and Tapscott 2016).

We can expect therefore that in the future we shall find alternate forms chosen from

available structural patterns that can compete successfully with the classical form and avoid the

risks of central control. Finally, we would like to comment on the important feature of

productivity in late markets. Productivity as key component of efficiency is a must to survive in

a cost leadership environment. It is the basic tool of competition. But is it always necessary?

The answer in short is no. In fact, when intrusive new innovations constantly rejuvenate

the market productivity is a non-issue as the market does not mature but returns to a growth

stage.

This happened when Apple reinvaded the portable communications market with its iX

products. The markets returned to high growth mode and are still on that trajectory, with

productivity nowhere in sight, rather constant innovation rules the day. Similarly Google

transiting to an affiliate status within Alphabet is leading to continued market expansion of the

parent and the new product lines are still some distance from maturity.



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Selected References

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Nonaka, I. (2008). The knowledge-creating company, Harvard Business Review Press.

Paquin, J.-P. and T. Koplyay (2007). "Force field analysis and strategic management: A dynamic

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Penrose, E. T. (2009). The Theory of the Growth of the Firm, Oxford university press.

Porter, M. E. (2011). Competitive advantage of nations: creating and sustaining superior

performance, Simon and Schuster.

Schumpeter, J. A. (2010). Capitalism, socialism and democracy, routledge.

Shopify (2018): https://investors.shopify.com/Investor-News-Details/2018/Shopify-Announces-

First-Quarter-2018-Financial-Results/.

Tapscott, D. and A. Tapscott (2016). Blockchain Revolution: How the Technology Behind

Bitcoin Is Changing Money, Business, and the World, Penguin Publishing Group.

Utterback, J. M. (1996). Mastering the Dynamics of Innovation, Harvard Business School Press.

Vernon, R. (1992). International investment and international trade in the product cycle.

International Economic Policies and their Theoretical Foundations (Second Edition),

Elsevier: 415-435.

W3Techs: https://w3techs.com/technologies/comparison/sc-entrust,sc-verisign.

Retail Customer Experience: A Comparative Study Between Physical, Online, and Omnichannel Retail

Jain, Mora, and Werth

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Retail Customer Experience: A comparative study between Physical, Online and

Omnichannel Retail.

Shubham Jain

AWS-Institut für digitale Produkte und Prozesse,

D 5 1 Uni-campus

Saarbrücken, Germany

[email protected]

Daniel Mora



[email protected]

Dirk Werth



[email protected]

Author Note

This research is a part of the European Training Network project PERFORM

that has received funding from the European Union’s Horizon 2020 research

and innovation programme under the Marie Skłodowska-Curie grant

agreement No 765395. This research reflects only the authors' view, the

European Commission is not responsible for any use that may be made of the information it

contains.






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Abstract

In the 1990s, many retailers went bankrupt in an attempt to transition from traditional to online

retail and currently, retailers are facing the same challenges evolving into the omnichannel model

due to lack of tools and knowledge to facilitate the transition. Retail managers need to

understand the different dynamics and aspects of customer experience in retail as well as how

they differ from previous business models. To address these problems, there is a need to create

knowledge which can be done by reviewing the conceptual and theoretical literature around

customer experience across all retail models as customer experience is considered as the most

important aspect of omnichannel retail. This paper provides a comparative analysis to understand

the differences between traditional physical in-store retail, online e-commerce and omnichannel

retail to facilitate retailers to comprehend the concepts and further create strategies to transition

into the omnichannel retail successfully.

Keywords: Omnichannel Retail, Digital Retail, Customer Experience.



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Difference between Traditional Physical, Online and Omnichannel Retail Customer

Experience

The retail industry, as a sector accounted for $26.29 trillion in sales in 2019 (Statista,

2019) and proliferating, which makes it a significant part of the world economy (Limited,

2018). The industry started with the concept of in-store physical retailing, and eventually, with

the development of different technologies like the Internet and World Wide

Web, concepts like digital retail came into existence. Digital retail started with e-

commerce websites like Amazon in the 1990s (Anderson, 2018) and moved on to

multichannel system when the retailers and researchers pointed out the synergies between the

online and offline channels of retail (Schoenbachler & Gordon, 2002). While the retail sector

saw the birth of e-commerce, there were a lot of retail businesses closing down (Berman, 2019;

Rigby, 2011) due to the abrupt growth of online retailers and the need that the retailers felt to

transition into online retail without dwelling on the dynamics of the transition and the business

model. In the current times, retail is at the verge of transitioning again into the model of

omnichannel retail (von Briel, 2018) which right now is more of a buzzword but is defined in

different ways by different authors (Lazaris and Vrechopoulos, 2014; Juaneda-Ayensa,

Mosquera, & Sierra Murillo, 2016). To facilitate this transition, retail managers and researchers

need to have a complete understanding of the concept and how it differs from the previous

models of retail. This makes a valid motivation in our understanding to study those differences

and motivate researchers to bring out the insights.

Customer experience can be estimated as the single most important factor in omnichannel

retail as it follows a customer-driven approach (Carroll & Guzmán, 2013). It needs to be given

more attention in terms of research to understand the concept of customer experience in

different models of retail and to understand the different constraints attached to it.

Research Question

How can omnichannel retail be differentiated from mono channel-based retail models:

online retail and traditional physical retail in the context of customer experience?

Proposed Solution

We propose to answer the developed question by conducting research in the form of

analysis and review of literature in the sector of customer experience in traditional physical,

online and omnichannel retail and examine those researches to find common grounds for

comparison.

Aim

The paper aims to present a comparative analysis of the three different models of retail

sector: traditional physical retail, online retail and omnichannel retail towards the context of



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customer experience. The conducted research will present the differences explicitly in a tabular

manner, along with a discussion based on those differences and focusing on future challenges

and strategies.

Originality/value

The article adds value to the literature as the three models have not been studied together

to be compared explicitly in terms of the constraints attached to customer experience in different

environments.

Paper Structure

The following content of the paper is divided into five further sections starting with

stating the used methodology followed by the literature and background in the next section.

Analyzation will be done in section three, followed by description and discussion. The article

will be concluded with the ‘Conclusion and Future Work’ section as section five and used

references will be stated at the end of the article.

Methodology

In the presented article, the methods used for selection of search results merged a

protocol-driven methodology in which the search strategy is defined at the beginning of the study

with a snowballing technique, where the search strategy emerges as the study unfolds as

mentioned in Greenhalgh and Peacock (2005) and, Ravasi and Stigliani (2012).

The search strategy consisted of individual searches as stated in Table 1. The articles

were selected and handpicked by reviewing the titles and abstracts and analyzing the relevance to

the proposed research. The ‘Google Scholar’ online database was used to collect the articles. To

scope the concepts and different perspectives present in the literature, a combination of the retail

model and the term ‘customer experience’ was used to form usable keywords. The term

“Omnichannel Retail Customer Experience” collected 17 articles, while “Online Retail Customer

Experience” brought 35 articles, making an initial set of 52 articles.

In the case of traditional physical retail, a number of searches had to be done to collect

relevant articles. As the term “traditional” is vague in the scientific literature, we used different

synonyms to the concept that had to be analyzed. A search session with three different

combinations of keywords: “Physical Retail customer experience”, “In-store customer

Experience” and “Brick and Mortar Retail customer experience” contributed to the literature set

with 21 articles, extending the set to 73 articles.



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Following the references and citations of the collected articles, we collected a sum of 14

other articles collectively reaching out to all the three models. Hence, the final collection was 87

articles.

Table 1: Search and collection of research articles.

d

Search terms s

“Omnichannel

Retail

Customer

Experience”

s “Online Retail

Customer

Experience”

a “Physical

Retail

Customer

Experience”

s “In-Store

Retail

Customer

Experience”

s “Brick and

Mortar Retail

Customer

Experience”

Results

6,400

553,000

520,000

526,000

33,500

Initial

collection

17

35

21

Final

collection

73+14 = 87

Note: Source: Google Scholar (http://scholar.google.de/) on January 2019; advanced search

options: “[Search Terms]” and including citations.

The research strategy and article presentation are based and inspired on the structure

followed in Verhoef, Kannan, and Inman (2015) and Mirsch, Lehrer, and Jung (2016) where the

articles are collected to review the present literature and analyzed to form a tabular

representation of different comparative concepts. The articles were studied focusing more on

defining and analyzing of the concepts retail customer experience and less on the individual pros

and cons of the studies. These articles were analyzed, clustered and coded to propose an explicit

table, followed by a discussion.

Literature and Background

Research and development in retail have been going on since long to optimize the

industry. Different authors have used different terminologies, taxonomies and different criterions

to develop models to help retailers and researchers to understand the domain better and take the

businesses forward such as Newman and Foxall (2003) established the behavioral perspective

model and new innovative methodology to optimize store performance. Healy, Beverland,



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Oppewal, and Sands (2007) defends the use of ethnography for researchers to understand the

customer within the holistic context. In our understanding, understanding the customer and

working on holistic customer experience is one of the major constraints in retail that needs to be

optimized, and the most important constraint for the future of retail (Verhoef, Kannan, & Inman,

2015). Petermans, Janssens, and Van Cleempoel (2012) provides insights into different aspects

of theoretical conceptualization of customer experience. Wang and Hsiao (2012) also provided a

theoretical foundation for in-store shopping and examine different impacts on the consumer flow

experience (concentration, control, and enjoyment) and subsequent future shopping intentions.

Sachdeva and Goel (2015) points out that it is essential to focus on engaging the customer both

emotionally and behaviorally, and Russo Spena, Caridà, Colurcio, and Melia (2012) argues that

temporary shops provide a locus of value co-creation in which the interactive and experiential

relationship between the firm and the customer is engaged, and value co-creation emerges.

Other individual constraints that affect the customer experience has been studied like

Wall and Berry (2007) presented the combined effects of the constraints like physical

environment and employee behavior on customer perception while Morrison, Gan, Dubelaar, and

Oppewal (2011) studied music volume and aroma in retail stores which are a part of the physical

environment. Background music has also been studied by Garlin and Owen (2006). Andreu,

Bigné, Chumpitaz, and Swaen (2006) examined customer’s emotions, satisfaction and behavioral

intentions in a shopping setting. Benhamza Nsairi (2012), along with testing the effect of

situational factors (store atmosphere, accompanying, motivation, mood and time of visit) on

browsing’s perceived value, also contributed to identifying value’s sources which lead to

browser’s satisfaction and loyalty. Sherman, Mathur, and Smith (1997) also studied the effect of

store environment on consumer emotions and the resulting influence on aspects of consumer

behavior. Rapp, Baker, Bachrach, Ogilvie, and Beitelspacher (2015) suggests that the adverse

effects of showrooming can be combated through specific salesperson behaviors and strategies.

They also point out a negative relationship between perceived showrooming behaviors and

performance. Thomas (2013) validated the measurement model of customer satisfaction and

studied its impact on customer loyalty. Bustamante and Rubio (2017) provides evidence that a

formative third-order scale with a reflective second-order dimension (social experience) and

three reflective first-order dimensions (cognitive, affective, and physical experience) has

satisfactory psychometric properties. Burke (2002) investigated 128 different aspects of the

shopping experience in physical and virtual stores and concluded statements like an optimal

implementation of technologies could improve customer experience, like RFID (Melià-Seguı et

al., 2013; Bodhani, 2012).

There are studies that have been made to facilitate researchers in specific, like

Applebaum (1951) shows how customer behavior studies can be made in retail stores.

Bustamante and Rubio (2017) provides useful information on the effect of the ISCX (in-store



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customer experience) scale on key performance variables such as satisfaction and loyalty to the

store.

Traditional physical in-store retail has been compared to online retail, and this

comparison has been studied in different ways. Enders and Jelassi (2000) discusses the

advantages and disadvantages of traditional store-based and online retailing. Rajamma, Paswan,

and Ganesh (2007) suggests that services are more likely to be associated with the online

shopping mode, whereas more tangible products are likely to be associated with bricks and

mortar stores.

The authors that worked on customer experience in the context of online retail pointed

out some other constraints that could affect customer reaction and perception like Hausman and

Siekpe (2009) talks about the visual dynamics of online retail and discussed the effect of web

pages on customer experience in online retail. Hernández, Jiménez, and Martın (2010) worked

along with the technology acceptance model (TAM) and provided significant insights for the

effect of perception of customers on the e-commerce experience and Çelik (2011) tried to find

the impact on PU (perceived usefulness), PEOU (perceived ease of use) and BI (behavioral

intentions) in online customer experience. (Morgan-Thomas and Veloutsou (2013)) demonstrates

that trust and perceived usefulness positively affect online brand experience. Grewal, Levy, and

Kumar (2009) provides seven articles that contribute to customer experience: promotion, pricing,

merchandise and brand, supply chain, location, retail metrics, and customer behavior. Insley and

Nunan (2014) point out the importance of including game elements to enhance the retail

experience. Chang and Chen (2008) proposed an integrating conceptual framework focusing on

the relationships among customer interface quality, satisfaction, switching costs, and e-loyalty.

Rose, Clark, Samouel, and Hair (2012) describes online customer experience (OCE) to be

“a psychological state manifested as a subjective response to the e-retailer’s website” and Martin,

Mortimer, and Andrews (2015) proposed an extended model of OCE. Rose, Hair, and Clark

(2011) also add to the understanding of OCE in the purchase context. (Hsu, 2008) provides an

evolved ACSI (American Customer Satisfaction Index) mode: E-CSI (Trust, E-SQ (service

quality) and Perceived Value). In (Pentina, Amialchuk, & Taylor, 2011), a new type of online

shopping experience (interactive/engagement) was identified. Online service quality and trust

have also been studied in (Herington & Weaven, 2007; Nusair & Kandampully, 2008; Janda,

Trocchia, & Gwinner, 2002), though Herington & Weaven (2007) proposes different conclusions

as to Hsu (2008).

Ofir & Simonson (2007) studies effects of stating expectations on customer satisfaction

and shopping experience and O. Pappas, G. Pateli, N. Giannakos, and Chrissikopoulos (2014)

studied prior experience in retail and related it with expectancy and intention to purchase.

Bagdare and Jain (2013) conceptualizes retail customer experience as a reliable and valid



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multidimensional construct, explained in four dimensions: leisure, joy, distinctive and mood.

Gilmore and Pine (2002) and Bridges and Florsheim (2008) discussed customer experience from

a more progressive point of view to provide customers a more hedonic and social experience to

keep up with the current scenario. Trevinal and Stenger (2014) defines online shopping

experience (OSE) through four core dimensions: the physical, ideological, pragmatic and social

dimension. Philipp Klaus (2013) identifies functionality and psychological factors as the two

main dimensions of online customer service experience. Liu, He, Gao, and Xie (2008) suggests

that eight constructs – information quality, web site design, merchandise attributes, transaction

capability, security/privacy, payment, delivery, and customer service – are strongly predictive of

online shopping customer satisfaction, while the effect of response time is not significant. Kim

(2005) defines e-customer satisfaction and develops an index using a weighted sum model.

Customer loyalty in online retail is studied by Bilgihan (2016). Chen and Chang (2003) identifies

three common online shopping components: interactivity, transaction, and fulfillment.

There are certain strategies researchers and retailers can follow to study and work with

these aspects like Petre, Minocha, and Roberts (2006) developed an empirically-grounded

evaluation instrument: E-SEQUAL. Nambisan and Watt (2011) proposed a four-dimensional

construct – online community experience (OCE) examined its impact on customer attitudes

regarding the product, the company, and the quality of service. Novak, Hoffman, and Yung

(2000) developed a structural model that embodies the components of what makes for a

compelling online experience. Richardson (2010) talks about how to use customer journey maps

to improve and asses customer experience using a four-fold Framework. Phil Klaus and Nguyen

(2013) highlights current and future roles of online channels, social media and their strategic

implications for the retail banking services sector, and subsequent segmentation practices.

Rowley (2009) discusses online branding that could be useful for retailers to work on.

Other factors like impact of service system design and flow experience on customer

satisfaction (Xin Ding, Hu, Verma, & Wardell, 2010) and relationship between a customer’s

experience of product returns, subsequent shopping behavior (Griffis, Rao, Goldsby, & Niranjan,

2012) have been studied in the context of online customer experience.

As the sector is transitioning into omnichannel retail, which is still a developing concept,

researchers are putting up articles to make retailers understand the future of retail. The concept of

omnichannel customer experience differs from both online and physical retail in a way that it

integrates both the channels. Bell, Gallino, and Moreno (2014) developed a customer-focused

framework based on product delivery and fulfillment, creating a matrix of 4 quadrants where all

retail models can be put. Frazer and Stiehler (2014) expanded the body of knowledge of

omnichannel retail customer experience, talking about the “Shopper experience” and the

omnichannel experience.



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There is enough evidence to make sure that omnichannel concept works like in

(Sopadjieva, Dholakia, & Benjamin, 2017), authors presented a study of 46,000 shoppers and

argued that customers like to use multiple channels and the system is more efficient and every

customer is more valuable in an omnichannel or multichannel system. (Carroll & Guzmán, 2013)

is a report by Accenture where they go over the concept of omnichannel retail strategies and

understanding for communication service providers. They discuss the funnel system, and about

the customer-driven cyclic methodology. (Hansen & Sia, 2015) mentions key lessons Hummer, a

European sports fashion company learned from the transition into an omnichannel business.

Their total sales increased from $170 million in 2010 to $240 million in 2013. They mentioned

the roles of Chief Executive Officer (CEO), Chief Information Officer (CIO), Chief Digitization

Officer (CDO) along with the extent of change requires and the need to embrace industry

partners.

Cook (2014) discuss the omnichannel customer and its attributes and mentions the

dynamics of the change to the omnichannel environment that needs to be understood. The paper

also mentions the role of physical stores in retail and how it will change in the coming future.

Parise, Guinan, and Kafka (2016) mention the “crisis of immediacy” where customers want

immediate services in omnichannel retailing and suggested solutions to improve customer

experience in the context of immersion, flow, cognitive fit and emotional fit. Von Briel (2018)

presents a four-stage Delphi study concluding major challenges, trends, technologies, and

customer touchpoints. Bennett and El Azhari (2015) discusses omnichannel customer experience

and analyze the in-store shopping experience and the impact of different digital technologies and

other changes in the store.

Different authors tried to publish on customer experience in the context of omnichannel

retailing such as Juaneda-Ayensa, Mosquera, and Sierra Murillo (2016) worked on different

constraints that could affect the purchase intention of customers namely: Habit, Hedonic

influence, social influence, effort expectancy and performance expectancy. They also provide

different constraints on which different models of retail can be compared while comparing

multichannel and omnichannel systems. Lazaris and Vrechopoulos (2014) also provides a

literature review for the comparison between multichannel to omnichannel retail and the

transition. They propose an elongated multidisciplinary research agenda for logical outcomes in

the domain while Picot-Coupey, Huré, and Piveteau (2016) sheds light on the concept of multi,

cross and omnichannel retail and talks about the challenges retailers face and the solutions to

overcome them and to provide a good customer experience. Verhoef, Kannan, and Inman (2015)

provides literature for multichannel retail and compares it with omnichannel. They study the

literature in three different contexts: (1) Impact of channels on performance, (2) Shopper

behavior across channels and (3) Retail mix across channels.



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Peltola, Vainio, and Nieminen (2015) argues that providing a good omnichannel

experience has two key factors: (1) Reducing the risk of losing the customer during customer

journey by providing a unified and integrated services and customer experience and (2)

Encouraging the customer to proceed in the customer journey with the company by providing

seamless and intuitive transitions across channels in each touch-point to match customer

preferences, needs, and behavior. Brynjolfsson, Hu, and Rahman (2013) provides seven different

strategies to compete in the omnichannel system and to enrich and deliver customer experience.

Krueger (2015) stipulates a brief report on the omnichannel transition and to understand

consumer behavior. Piotrowicz and Cuthbertson (2014) mentioned another seven different

themes to be studied in the omnichannel system.

To sum up, within the scope of our research, traditional retail can be understood as a

mono-channel physical store-based retail system. Considering traditional retail before the arrival

of online-based retailers in the 90s (Anderson, 2018), traditional brick and mortar stores follows

a company-centric and product-centric approach (Kotler and Armstrong, 2010) to sell the right

products to the customers optimizing three main sectors: What to produce? Where to sell? And,

how to cover a broader market. As there is no specific definition for “traditional retail”, the term

is changeably used with physical store retail with no to a minimal use of technology and

customer preferences.

Similarly, online retail can be understood as a form of electronic commerce which allows

consumers to directly buy goods or services from a seller over the internet using a web browser.

In online retail, consumers find a product of interest by visiting the website of the retailer

directly or by searching among alternative vendors using a shopping search engine, which

displays the same product's availability and pricing at different e-retailers. Customers can shop

online using a range of different computers and devices, including desktop computers, laptops,

tablet computers, and smartphones.

Omnichannel retail refers to the integration of retail channels like stores, online, and

mobile into a single, seamless customer experience. The term started to get popularity after 2011,

when Rigby (2011) presented the future of shopping.

In the current scenario, mono-channel retailers are trying to expand by introducing

different channels into the architecture of their business models to form an omnichannel

experience (Piotrowicz & Cuthbertson, 2014). Omnichannel systems are customer-centric

systems providing the right touch points for the right services (Lemon & Verhoef, 2016).

Wiener, Hoßbach, and Saunders (2018) discuss the different synergies and tensions that

arise when online and offline channels co-exist in an industry although it specifically talks about

those attributes in publishing and retailing industries. As omnichannel approach of retail offers



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an efficient integration of all the channels present in the system, we can expect that it aims to

contain the advantages of every individual channel along with providing the customer the option

to switch between channels/touch points and helping them to get over the disadvantages present

in the channel/touch point they switched from.

Analysis

The analysis of the collected literature to compare and synthesize the three different retail

models were done by reading and critically analyzing the core concepts of customer experience

mentioned in each paper. To keep the process structural, a list was made to summarize every

article and different criterions and constraints of customer experience mentioned in the articles

with a brief explanation of how those constraints relate to customer experience. The next step

was to cluster down the different aspects that were found in the literature.

To cluster down the different factors that appeared during the analysis, we used the clusters

used in (Willems, Smolders, Brengman, Luyten, & Schöning, 2017) as the criterions can be

perfectly summed up in these three clusters. In combination of knowledge and dynamics of these

clusters, the Affinity Diagram method was used to further validate the clusters. The results

obtained from the process could easily be translated into the formation of these groups:

1. Product Level

2. Customer Level

3. Retail Level.

Described in (Willems, Smolders, Brengman, Luyten, & Schöning, 2017), these clusters

deviate a little from the original context in this article. Originally these clusters talk about retail

technologies and how they can be deployed on different levels to improve customer experience.

While here we morph the context of these clusters to validate them in the present article. The

identified constraints or criterions in the literature can be clustered in one of these categories.

During the analysis, some constraints were found to be ambiguous due to the relevance of those

factors in more than one aspect. The same factors can be studied in myriad of manners.

Product Level: Groups all the factors that affect the customer experience which runs

along the customer journey or the purchase path of a product. The product or customer journey is

divided into pre, during and post purchase sections in the product life cycle as mentioned by

Vandermerwe (2000).

Customer Level: These include the constraints that are mostly customer dependent which

includes customer attributes, how does a customer interact with the whole retail environment and



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how does the individuality and subjective constraints of a customer affect the customer

experience. The subcategories are based on the discussions made in the previous section.

Retail Level: Clusters the general attributes of the retail model and how those

characteristics and strategies affects customer experience. These are mostly the factors that are

driven by retailers that affect the experience of the customer. These also include the attributes of

the retail model which develops because of the theoretical concept around the particular retail

environment.

Based on the discussion made above and in the previous section, the differences between

traditional physical retailing, online retail and omnichannel retail customer experience are

summarized in Table 2.



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Table 2: Differences between Physical, Online and Omnichannel Retail.

Cluster Constraints Physical Online Omnichannel

Product Pre

Physical stores,

catalogs and flyers.

Web pages and

social media.

Store and multiple

remote digital

channels.

During

Staff assistance

and

physical

information.

Fulfillment in

physical stores.

Access to physical

attributes.

Recommender

Systems and

digital

information.

Fulfillment by

delivery.

Access to only

digital attributes.

Physical and

online

information.

Fulfillment by

pickup, in-store or

delivery.

Optimal attribute-

oriented product

placement.

Post

Complaint desks.

Feedback Forms.

Physical Returns.

Online and

telephone

customer support.

Data collection

and reviews.

Postal returns.

Multiple

touchpoints to

facilitate support,

feedback and

returns.

Customer Attributes

Part of the product/

retail driven

approach and

hence has minimal

to no role in

shaping the

business.

Characterized by

the need for

efficiency, ease

of use.

Mostly driven by

cost, speed and

quality of service.

Knowledgeable,

Demanding,

Empowered,

Collaborative,

Diverse,

Interactive.

Increasingly on

the move.

Expectations and

perception.

Product-oriented. Service-oriented. Experience-

oriented.

Interaction Single physical Single channel Multiple channels:



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channel interaction

based.

interaction:

online.

integrated

interaction.

Technology

acceptance

Doesn’t play a role

in physical retail.

Internet.

TAM

Different

technologies.

Retail Customer

journey

Funnel Funnel Cyclic

Services and

information

consistency

Working hours. 24 hours of

information.

24 hours of

information and

delivery.

Role of physical

facilities

The only touch

point.

Warehousing and

administration.

Transformed to

facilitate research,

pleasure, etc.

Staff

characteristics

Interactive and

decision making.

Facilitates

support.

More technical

and interactive.

Marketing

Physical and social

mouth to mouth.

Social media and

service.

Experience stores,

along with digital

and physical

mediums.

Management

CEO CEO & CIO CEO, CIO and

CDO

Distributions and

supply chain

Warehouse to

shelves.

Warehouse to

customers.

Flexible and

dynamic.

Layout and

infrastructure

Physical

No third parties.

Digital

Third parties

usually for

payment.

Integrated

Multiple third

parties.



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Customer

experience value

Hedonic: Store

aesthetics and store

environment.

Utilitarian: Product

value

Hedonic: Web

page interface.

Utilitarian: Fast

and lower-price

oriented service.

Hedonic: Making

the customer

journey enjoyable.

Utilitarian:

Shopping

assistance

Social /

Community

Human physical

interaction.

Online

communities,

social media.

Communities

based on different

touch points.

Description and Discussion

Product Level

The three different retail models differ on the product level extensively. This cluster of

differences is based on the buying behavior stages from (Kalakota & Whinston, 1996), the

customer-activity cycle (Vandermerwe, 2000), and customer delivery value chain as stated by

Kalyanaram and Aung (2015). These also include all the dynamic of the interaction with the

product which is the soul of the retail industry. ‘Pre’ means the information collection before the

actual shopping process. These can include product research, need analysis, and identification.

While ‘During’ means the shopping process in a store or a digital channel which can be

identification, assessing options and payment. ‘Post’ includes the feedback, returns (Griffis, Rao,

Goldsby, & Niranjan, 2012), and reviews. The pre-purchase phase in physical retail is more

towards community (Bustamante & Rubio, 2017) and physical mediums like flyers (Wiener,

Hoßbach, & Saunders, 2018), direct mails, and catalogs. In online retail, digital is the only

medium; thus, information for products are only prompted through digital interfaces (Nambisan

& Watt, 2011), and communication channels like e-mail, cellphones, etc. During purchase, the

physical retail assistance and decision making rely on staff (Healy, Beverland, Oppewal, &

Sands, 2007) and physical information on products. Likewise, online retail uses reviews,

recommender system, and products description. Under the same circumstances, omnichannel

integrates all the channels allowing customers to fulfill their necessities in both channels (in-

store and delivery) and matching them based on preferences such as click and collect. In brick

and mortar, post-purchase is done through physical mediums. Besides, in the online setting, the

post-purchase is done by assistance on phone or online support. In the omnichannel retail system,

there are multiple touchpoints which facilitate customers in terms of support and returns, both in



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physical and digital settings. Product fulfilment in physical and online retail is done in stores and

by delivery respectively while as stated above, an omnichannel customer can choose either of

them or other services like click and collect for product fulfilment. Bell, Gallino, and Moreno

(2014) described this relationship of product information and delivery, which also mentions the

difference of data gathered by the customer during the shopping process based on product

attributes i.e., digital channels of retail impose uncertainty about non-digital attributes for the

customer.

Customer Level

Customers perspectives can differ in different retail settings. Customer experience is

studied with varying terminologies by different authors like experience, satisfaction, perceived

value, etc. Different attributes define a consumer in different retail settings. As Carroll and

Guzmán (2013) stated as future of omnichannel systems, due to the presence of a plethora of

information at the fingertips of every user, a progressive customer is more aware. The futuristic

customer is more driven by service quality and experience instead. Perception and expectations

of a customer is an essential part of the ACSI model used to asses customer satisfaction in retail

settings. The traditional ACSI model uses ‘Expectations’, ‘Perceived value’ and ‘Perceived

quality’ where the approach is more product and staff-oriented while in online retail, as

described in the e-CSI model (Hsu, 2008), service quality and trust, plays a major role in

determining the satisfaction. As omnichannel retail concept is centered around customer

experience, the expectations and perceptions of an omnichannel system will surround the

experience factor focusing majorly on the hedonic and holistic value of the service provided by

the retailer. The Interaction between the retail system and the customer which is basically the

channel difference between the retail models is the most explicit difference among others, as

physical retail system uses only single channel, which is the physical medium, while online retail

system uses internet as the only channel. Omnichannel retail system deploys an integrated

customer journey which is characterized by touch points and includes multiple channels of

interaction between the retailer and the customer. Also, technology acceptance has a different

role in the three models in a way that traditional in-store retail involves no use of technology,

hence it cannot affect the customer experience while in online retail, a customer’s perception on

internet and usability of the web pages plays an important role. Technologies are an integral part

of omnichannel retail, hence customer’s perception over those different technologies could affect

over their holistic customer experience.

Retail Level

In the last decades, different retail models have led the retail sector to have different roles

concerning the way they address the business needs. These can vary from enhancing customers

and staff needs to the way they use their infrastructure.



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Traditionally, retailers have understood the shopping journey as a linear path, which

followed the classic funnel approach from marketing, this has changed with the arrival of

omnichannel which interprets that buyers “continuously cycle through the stages of the journey,

without ever exiting the evaluation process” (Carroll & Guzmán, 2013). Other than that, physical

stores conventionally had limitations offering services to consumers for more than 8 hours a day

and one of the advantages that online retailers have taken to disrupt the market is offering

shopping services 24 hours a day, allowing their customers to have more flexibility that led even

loyal customers of physical stores to switch, as stated by Enders and Jelassi (2000). Omnichannel

retail also follows the same concept of continuity of information and services. These primary

differences also led managers to adopt different marketing strategies for their businesses.

Marketing in physical retail is more product oriented and as mentioned in pre-purchase section of

the product level cluster, is based on social trend and physical flyers, etc. While online retail

marketing is hugely based on digital mediums like social media (Phil Klaus & Nguyen, 2013)

and service. Omnichannel retail is based on marketing the experience of shopping and providing

the customers with a holistic experience.

In contemplation of management perspectives, physical stores have relied on the

conventional role of the chief executive officer (CEO), to direct the company's strategies. In

online, businesses have had to include the role of the chief informatic officer (CIO) in addition to

the CEO to support the retail goals related to information technology. Taking into consideration

that the CIO needs to evolve having more information technology (IT) capacities, omnichannel

retail needs to integrate a chief digital officer (CDO) in charge of the digital department (Hansen

& Sia, 2015).

Management must also take care of the transitioning role of staff in the hours of customer

service changes depending on the model they follow. In traditional physical stores, employees

tend to be a means of social interaction and support when making decisions related to purchases

(Healy, Beverland, Oppewal, & Sands, 2007), and the staff of the online stores is based on

giving support to the customer. In contrast, the role of omnichannel staff is more technical and is

towards technological assistance (Cook, 2014). The staff also allows customers to experience a

better shopping experience in different channels by providing utilitarian and hedonic support.

In the context of physical facilities, brick and mortar stores are the point where

consumers can go, analyze the available products, interact with staff, make their purchases and

go if they need to return any product, making the store as a single point of contact with

customers. While in online retail, the physical facilities are used as warehousing and operations

center. In omnichannel retail, these facilities are transformed to facilitate research of products

and a center of pleasure for customers, etc. (Juaneda-Ayensa, Mosquera, & Sierra Murillo,

2016). Regarding the use of these facilities for distribution and supply chain frameworks, brick

and mortar stores are more focused to maneuver large volumes of products from warehouses to



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the store racks. On the other hand, the online retailer is selling over the web, this demands an

entirely different framework which is capable of delivering consumers' goods to their preferred

locations, as claimed by the authors in (Enders and Jelassi, 2000). More recently, omnichannel

retail has evolved to use the stores as points of distribution too (Cook, 2014).

The physical stores traditionally have been designed for product visibility, which means

the store layout design is product-oriented and stores for economic reasons “typically adopt a

standardized approach to interior layouts and format designs” (Newman & Foxall, 2003). On the

other hand, the design of the website for online retailers is more customer-oriented (Petre,

Minocha, & Roberts, 2006). In omnichannel retail, the design of the channels needs to be

customer experience oriented both in online and physical channels which can be achieved by

strategies like hiring a third-party company to create hedonic or utilitarian value to the customer

journey. Brynjolfsson, Hu, and Rahman (2013) describes that “in some cases, the location-based

applications aren’t managed by the retailers but by third parties. For instance, RedLaser, an eBay

company, allows consumers to scan UPC codes to determine whether specific products are

available nearby and at what price”. Third parties have almost no involvement in traditional

retail, while online retailers can use third parties like PayPal to ease out payments, etc.

Although stores are product-oriented in traditional retail, stores are also a space that can

add hedonic value to the customer experience by stimulating the customer esthetically and

influencing the purchase intentions of the customers positively (Russo Spena, Caridà, Colurcio,

& Melia, 2012). Store environment needs to have pleasing interiors for the customer (Petermans,

Janssens, & Van Cleempoel, 2012). In contrast, online retailers provide hedonic value through

the website interface, focusing and elaborating on the relationships among customer interface

quality and satisfaction (Chang & Chen, 2008). In (Hausman & Siekpe, 2009), the authors

suggested strategies to optimize web design to provide a better experience to customers. In

omnichannel retail, making the customer journey enjoyable is the primary strategy for hedonic

value. Also, as a part of customer experience, utilitarian experience value in physical retail is

affected by products and how customers perceive them during the actual purchase. While online

customer perception is more service-oriented, it offers faster purchasing and lower-price

(Rajamma, Paswan, & Ganesh, 2007). This is due to the deficiency of physical contact with

products and staff, and the time gap between delivery and arrival of the shopping products. This

utilitarian value has been evolved in the recent past to be shopping experience-oriented for the

customer in omnichannel retail.

In (Bustamante & Rubio, 2017), the authors discuss different dimensions of in-store

customer experience and conclude “physical retail service environment offer an extraordinary

opportunity for human interaction” on the grounds that “a variety of customers enjoy themselves

when they socialize with others (shoppers or employees) when they visit the store, essentially

seeking the opportunity to socialize outside the monotony of their everyday lives”, which suggest



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that social experience in-stores provides a great significance in determining the psychometrics

properties of satisfaction. The online retailers consider online communities as a medium for the

customer to socialize between each other and interact with the vendor representatives (Nambisan

& Watt, 2011). The online community experience “can play a crucial role in shaping customers'

perceptions regarding the product, the company, as well as the service quality”. Regarding social

media, Phil Klaus and Nguyen (2013) stated that retailers can use it to gain customer insights,

which could help them to provide a better customer experience. Creating the omnichannel

communities, as mentioned by Hansen and Sia (2015) creates new challenges for the retailers

since all the campaigns need to be coordinated in the different channels available based on the

customer experience expectations.

Challenges

The most common consequences of the retail system are described in the ACSI model as

customer loyalty and customer complaints. Customer loyalty has been defined as a ‘‘deeply held

commitment to re-buy or re-patronize a preferred product/service consistently in the future’’

(Oliver, 1999) while a “complaint can be defined as a conflict between the customer and the

organization” (Oliver, 1999). Retailers need to manage these issues and figure out how to

develop trust among users in the business which could be associated with several factors in retail.

As the omnichannel system is surrounded around customer experience, retailers need to

study their customers to provide tailored services. The literature suggests that the concept of

tailored services imposes another problem of personalization vs. privacy. With the introduction

of different privacy laws, retailers need to find a balance between personalization and

compromising the privacy of the user, which could be subjective. These subjective constraints in

retail could be handled by clustering the customers based on different criterions. Though, with all

these advanced strategies and technological development, it imposes another problem of a raised

customer expectation. An omnichannel customer starting the purchase journey with a lot of

expectations could be affected at his satisfaction level.

The literature points out several factors that affect customer experience: Physical

environment, social, cognitive, emotional, etc. These factors could contain a lot of complexity

which retailers need to tackle by optimizing these aspects of customer experience to sustain their

businesses. The differences pointed out in the above section could be interpreted as challenges

which needs to be strategized, for example transitioning the role of physical facilities/space,

administration strategies, staff characteristics, etc. needs to be transformed to form a relevant

omnichannel business. Implementation of technologies has proved to be beneficial in businesses,

though deployment and assessing the acceptance of them can pose as a big challenge for retail

managers as the deployment should be optimal in terms of finances and value to contribute to

businesses. The differences can be interpreted as the theoretical explanation of what retailers can

aim for in terms of results of strategies, and work on each of them to have a perfect omnichannel



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system. Omnichannel retail promises a seamlessly integrated customer experience, and this

integration is both of a challenge, and a blessing to business owners as proper execution of these

strategies to convert into an omnichannel environment can lead businesses to profit higher.

.

Conclusions and Future Work

In the article, three different retail models that are based in different eras of history have

been studied in the context of customer experience. It was established between the review that

the modern era of retail is centered around customer experience, and it is an essential part of the

retail transition. The findings in the article answers the proposed research question: “How can

omnichannel retail be differentiated from mono channel-based retail models: online retail and

traditional physical retail in the context of customer experience?” by presenting a definitive and

explicit comparison between the retail models in terms of how the constraints work in context to

customer experience. As stated in the literature section, there have been a lot of authors

publishing about customer experience and different models and terminologies have been used to

define various aspects of customer experience. Omnichannel retail is the buzzword in current

times and most anticipated future of the retail sector. The literature suggests that there is a

plethora of challenges in front of retailers to understand the dynamics of the transition that is

happening before them. In the article, we tried to solve the problem by explicitly pointing out the

differences between traditional physical retailing, online retailing and omnichannel retailing. The

differences can be studied in the form of 3 clusters: Product level, Customer level, and Retail

level. Each cluster deals with a different set of constraints that are attached to customer

experience. Sometimes these constraints can be ambiguous as physical and omnichannel being

on the extreme ends of the retail timeline cannot be directly compared in some ways. The

differences pointed out in the article extends the contemporary literature and facilities the

understanding of the different dynamics to asses retail sector. This understanding and differences

can facilitate retail managers to understand better the steps they need to take to move to

omnichannel retail.

In the article, the impact of retail transition was briefly discussed as consequences and

challenges of the model. Taking into account this literature, retail managers can save their

businesses from a fall back in the age of change by keeping up with the trends in the sector and

bending their ways to create efficient firms. Though the article discusses only the factors which

contribute to customer experience, which could fall as a limitation of this research. Some aspects

like marketing and operations, can be addressed further, which we propose as a part of the future

research agenda. Also, the study of other factors than customer experience like business models

(value creation, value architecture, value finance, value network) can be done to extend the

literature further. The constraints discussed in the paper can also be studied further for more

descriptive and deep explanations. Technology implementation and providing a seamless



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experience to customers is the goal of retailers, and we motivate researchers to contribute both

research and development in the field to take the sector forward as a whole.



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Shubham Jain

Early Stage Researcher in project PERFORM with the research title “Using Mixed Reality for

Enhanced Product Experience”.

AWS-Institut für digitale Produkte und Prozesse

Daniel Mora

Early Stage Researcher in project PERFORM with the research title “Recommender Systems for

a Connected Customer Journey”.


Dr. Dirk Werth

Managing and Scientific director,



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Proceedings of the 2019 (9th) International Conference

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