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Author version

E-readiness assessment of non-profit ICT SMEs in a developing country: the case of Iran

Mohammad Fathian , Peyman Akhavan , and Maryam Hoorali

Citation: Fathian, Mohammad, Akhavan, Peyman and Maryam Hoorali (2008), E-readiness assessment of non-profit ICT SMEs in a developing country: The case of Iran, Technovation, Vol. 28, No. 9, pp. 578-590.

Abstract

We are experiencing a new kind of commerce in the recent era, known as e-commerce, which

considers Information and Communication Technology (ICT) as the main enabler of commerce.

Considering Small and Medium Enterprises (SMEs) as micro elements of society and part of

macro economy, ICT becomes crucial for e-commerce companies to attain sustainable

competitiveness.

Towards this, organizations must re-evaluate every aspect of their strategies and quickly adapt

their working models to incorporate e-commerce as an essential factor for their success.

SMEs are critical to the economies of all countries, and specially the developing ones. They

cannot be left behind and many of them are already demonstrating their entrepreneurship

strength by grasping the opportunities offered by ICT.

E-readiness assessment is an evaluation tool that can be used for measuring the diffusion rate of

ICT. However, critical issues for e-readiness assessment of SMEs have not been systematically

investigated for developing countries. Some existing studies have derived their critical factors

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from macro perspectives at country level and have not considered the important factors at micro

level for SMEs in an integrated way This paper aims to bridge this gap.

This research paper first reviews the e-readiness assessment models proposed for countries at

macro scale and then identifies the critical factors for SMEs e-readiness assessment. This is

achieved through factor analysis at the micro perspective of some Iranian non-profit ICT SMEs.

The extracted factors are organizational features, ICT infrastructures, ICT availability and

security and legal environment.

This study is probably the first to provide a perspective of critical issues for e-readiness

assessment in SMEs based on macro models in a developing country. It gives valuable insight

and guidelines which hopefully will help the managers in developing countries to consider the

critical issues for e-readiness assessment of their organization in an effective way.

Key words: Information and Communication Technology, E-readiness Assessment, Small and

Medium Enterprise, Developing country, Iran.

Introduction

E-readiness can mean different things to different people, in different contexts, and for different

purposes (Peters, 2001). Thus, it is important to define e-readiness in the context of this paper.

E-readiness of an SME is defined here as the ability of an SME to successfully adopt, use and

benefit from information technologies such as e-commerce.

Information Technology (IT) is a term that generally covers the harnessing of electronic

technology for the information needs of a business at all levels. It utilizes computer-based

systems as well as telecommunication technologies for the storage, processing and

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communication (Anderson, 1990; Claus and Schwill, 1992). While an information system (IS) is

a group of formal processes that together collect, retrieve, process, store and disseminate

information for the purpose of facilitating, planning, control, coordination and decision-making

in organizations, IT on the other hand provides the technical solutions identified in an IS,

including the networks, hardware and software (Grainger-Smith and Oppenheim, 1994). IT today

is basically electronics based on integrated circuits or silicon chips. Hanson and Narula further

identified two major forms of IT as Telematics (meaning ‘big media’) and Ethnotronics

(meaning ‘small media’). Telematics consist of technologies such as computers, telephone,

satellites, television, radio, video and those that rely on large-scale infrastructures. Ethnotronics

include technologies such as typewriters, audio cassette recorders, fax machines, paper copiers,

calculators, digital watches and other more personal types of technology (Hanson and Narula,

1990).

Morgan et al (2006) identified three main features of ICT initiatives in SMEs, including the

operation and structure, the success from a participant’s perspective and the development of a

model of blended learning to support and continue developing the program.

IT creates many new inter-relationships among businesses, expands the scope of industries in

which a company must compete to achieve competitive advantage. Information systems and

technology allow companies to coordinate their activities in distant geographic locations. Thus,

one could say that IT is also changing the way companies operate (Porter and Miller, 1985).

Grandon and Pearson (2004) conducted a survey between managers and owners of some SMEs

and identified four factors that influence e-commerce adoption including organizational

readiness, external pressure, perceived ease of use and perceived usefulness.

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IT has an essential role in supporting the current and common operations in most of the

contemporary organizations. Nowadays, the time cycle of these operations keep shrinking. The

risk of missing opportunities that negatively impact businesses is very high. In this situation,

because of the increasing rate of changes, the role of IT becomes much more profound.

The potential contribution of ICT to improving the competitiveness of SMEs has long been

recognized (Morgan et al, 2006).

Information and communication technologies are today generally recognized as one of the

central forces in the transition toward a new economic system.

During the height of the techno-enthusiasm that underpinned the dot.com phenomenon, this

transition tended to be identified with e-business which mostly meant the ‘transfer’ of existing

business processes onto an online environment (Maksoud and Aziz Youssef, 2003). A number of

studies have been conducted for assessing a country’s e-readiness, addressing the preparations

for using IT and entering the digital world. Assessments were based on a variety of indicators

such as e-connectivity, human capital, business climate, leadership and others.

Bayo-Moriones and Lera-Lopez (2007) explored ICT adoption by looking at five factors such as

environment, firm structural characteristics, human capital, competitive strategy, and internal

organization. Quantitative and qualitative indices were devised and used to evaluate and rank

countries on the e-readiness scale.

Oyelaran-Oyeyinka and Lal (2006a) found evidence of ICT investment and learning processes in

some selected developing countries such as India, Nigeria, and Uganda. Their study showed that

there is clear evidence of increasing complexity in adapting and using ICT in developing

countries firms. In addition to the above findings Oyelaran-Oyeyinka and Lal (2006b) identified

that technological progress requires skills upgrading through explicit learning of the new

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technologies; and finally, firm performance is highly associated with learning capabilities, levels

of technology, and a host of firm-level knowledge, skills and experience.

Haj Bakry (2003) cited that e-readiness assessments, for various countries, are associated with

the investigation of their state of readiness for digital integration which includes ICT

infrastructure and applications of e-government, e-commerce, e-learning, and other e-

applications.

Tarantolaand Gatelli (2006) also developed a methodology for sensitivity analysis and then

tested that technique on a case study involving the construction of a composite indicator of e-

business readiness of European enterprises.

Although there are many studies looking at e-readiness of countries, few studies have attempted

to evaluate e-readiness from a micro perspective. In particular, a relatively small number of

studies have undertaken assessments of the e-commerce adoption in SMEs in the United States,

Australia, some European and Asian countries (www.bridges.org).

Ruikar et al (2006) developed an e-readiness assessment prototype application for construction

companies. It assessed the e-readiness of construction companies in terms of their management,

people, processes and technology perspective.

Tan et al (2007) extended the e-readiness Model of Molla (Molla et al,2005a; Molla et al, 2005b)

which had been implemented between 150 businesses from South Africa as depicted in Figure 1,

to e-commerce in China in an empirical study of 134 Chinese SMEs. Findings showed that the

dominant inhibiting factors in China are: restricted access to computers; lack of internal trust;

lack of enterprise-wide information sharing; intolerance towards failure and incapability of

dealing with rapid change.

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The main objective of this research is to present a model that assesses the e-readiness of non-

profit SMEs in a developing country, particularly their preparedness for adoption of electronic

commerce.

Figure 1. E-readiness Model of Molla et al, 2005a

E-readiness models and concepts

Over the past last years, a number of models for e-readiness assessment of countries at macro

level have been developed by different organizations. On the surface, each model gauges how

ready a society or economy is to benefit from information technology and e-commerce. On

closer examination, the models use varying definitions for e-readiness and different methods for

measurement. These e-readiness assessment models are mainly grouped in four categories

according to bridges website (www.bridges.org):

1. Ready-to-use tools: There are few ready-to-use tools freely available on the web.

2. Case studies: There are numerous case studies assessing specific countries’ e-readiness,

and many of these could be used as bases for e-readiness tools.

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3. Third party surveys and reports: These reports aim to rank and rate countries based on

various measures held to indicate e-readiness.

4. Other e-readiness assessment models: In addition to the formal tools and surveys

described above, there is a range of other frameworks such as digital divide reports and

position papers that can be similarly used for e-readiness assessment.

Table 1 summarizes some important e-readiness assessment models.

Table1- e-readiness assessment models

Model Name Author Website Focus

APEC

Electronic Commerce Steering Group-The Asian

Pacific Economic Cooperation (APEC)

www.brigge

s.org

E-Commerce Readiness

CSPP Computer Systems Policy Project www.cspp.o

rg

Existing Infrastructure

CID

The Center for International Development at

Harvard and IBM.

www.readin

essguide.org

Society

McConnell

International

McConnell International prepared this report in

collaboration with World Information

Technology and Services Alliance (WITSA)

www.brigge

s.org

Infrastructure, Digital

Economy, Education and

Government

MQ Mosaic Group http://mosai

c.unomaha.e

du/gdi.html

Internet

CIDCM

University of Maryland, Center for International

Development and Conflict Management

http://www.

bsos.umd.ed

u/cidcm/proj

ects/leland.h

tm

Qualitative Assessment based

on past performance and

current internet pervasiveness

EIU The Economist Intelligence Unit http://www. E-Business Readiness

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ebusinessfor

um.com/ind

ex.asp

IDC International Data Corporation (World Times /

IDC's Information Society Index)

www.brigge

s.org

Infrastructure

KAM World Bank, Knowledge Assessment Matrix http://www1

.worldbank.

org/gdln/ka

m.htm

K-Economy

NRI Center for International Development (CID) at

Harvard and the World Economic Forum

http://www.

cid.harvard.e

du/cr/gitrr_0

30202.html

Infrastructure, E-Society,

Policies, Digital Economy,

Education and Government

ITU International Telecommunications Union's

Internet Country Case Studies

http://www.i

tu.int/ITU-

D/ict/cs

Telecommunications

Sida

Swedish International Development Cooperation

Agency (Sida)

http://www.s

ida.se

Mainly SWOT analysis of a

Nation

USAID U.S. Agency for International Development http://www.

usaid.gov/re

gions

Access, Government, People

There are several definitions for e-readiness. The CSPP model defines an ‘e-ready’ community

as one that has: high-speed access in a competitive market; with constant access and application

of ICTs in schools, government offices, businesses, healthcare facilities and homes; user privacy;

online security and government policies which are favorable to promoting connectedness and

using the network. The Asian Pacific Economic Cooperation (APEC) group defines a country as

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e-ready if it demonstrates e-commerce, has free trade, industry self-regulation, ease of exports

and compliance with international standards and trade agreements. McConnell International

defines e-readiness as the capacity of nations to participate in the digital economy. Finally, the

Center for International Development (CID) at Harvard University, the most acclaimed

institution in e-readiness research, defines an ‘e-ready’ society as one that has the necessary

physical infrastructure (high bandwidth, reliability, and affordable prices); integrated current

ICTs throughout businesses (e-commerce, local ICT sector), communities (local content, many

organizations online, ICTs used in everyday life, ICTs taught in schools), and the government (e-

government); strong telecommunications competition; independent regulation with a

commitment to universal access and no limits on trade or foreign investment.

While the above mentioned models focus on assessing readiness of countries, governments and

policies for adopting information technologies, some others such as IQ Net Readiness Scorecard

assess the readiness to adopt other different concepts. IQ Net Readiness Scorecard was

developed by CISCO and is a Web-based application that assesses an organization's ability to

migrate to an Internet Business model. It is based on the book Net Ready (Hartman et al, 2000),

which gauges the readiness of IT service providers.

E-readiness of small and medium enterprises

There are a number of definitions of what constitutes an SME. Some of these definitions are

based on quantitative measures such as staffing levels, turnover or assets, while others employ a

qualitative approach. Some researchers suggest that any description or definition must include a

quantitative component that takes into account staff levels, turnover, assets together with

financial and non-financial measurements, but the description must also include a qualitative

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component that reflects how the business is organized and how it operates (MacGregor and

Vrazalic, 2004). One of the SME definitions is shown in Table 2 (Damaskopoulos and Evgeniou,

2003).

Table2- Definition of SMEs

Enterprise category Headcount Turnover or Balance sheet total

medium-sized < 250 ≤ € 50 million ≤ € 43 million

Small < 50 ≤ € 10 million ≤ € 10 million

micro < 10 ≤ € 2 million ≤ € 2 million

Until the mid-seventies, SMEs had a minor role in economic development due to the dominance

of the mass production paradigm in industry. After this period, this paradigm was increasingly

challenged, leading to large firms’ fragmentation, unemployment growth and creation of new

SMEs (Acs, 1992). Empirical studies show a clear trend towards reduction of size of

manufacturing firms in developed countries. Possible reasons for this are the diffusion of flexible

modes of production and the downsizing of large firms (Acs, 1992; Khan and Khan, 1992).

There are two main findings in the literature that have implications for economic policy

concerning SMEs. The first is that the nature of innovation adoption differs according to the size

of the firm. The second is that clusters of small firms or industrial districts can be important for

regional development (La Rovere, 1998).

As Rothwell and Dodgson (1993) suggest, both SMEs and large firms have some advantages in

innovation adoption, but these advantages differ. While large firms have material advantages,

due to their greater capability to support Research and Development (R&D), SMEs have

behavioral advantages that stem from their greater flexibility and ability to adapt changes in the

market.

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SMEs can be classified in four different types, according to their market sector, their location,

their prevalent innovation rate and their organization. SMEs can be organized individually in

competitive markets with low innovation rates. They can also be organized individually in highly

dynamic industries with high innovation rates. On the other hand, SMEs can be organized as

production cooperatives (clusters), or in networks under the dominance of a large firm. Each type

of SME has specific contributions to economic growth, and will accordingly perceive IT in

different ways. The first type perceives IT as a cost reduction tool, while the second perceives IT

as a business opportunity. The third and the fourth use IT in their productive processes and in

their relations with the other firms, thus improving their interface with the market (La Rovere,

1998).

The differences between SMEs and their larger counterparts are highlighted even more when

their approaches to IT are considered. Khan and Khan (1992) suggest that most SMEs avoid

sophisticated software and applications. This view is supported by studies carried out by Chen

(1993), Cragg and King (1993), Holzinger and Hotch (1993) and Delvecchio (1994). In addition,

the SMEs locations are also important. Gillespie et al. (1995) noted that the use of IT

applications can vary in different regions of a country.

A combined study of Danish, Irish and Greek SMEs carried out in the early 1990’s by Neergaard

(1992) concluded that there were four main reasons for the acquisition of IT by SMEs. These

were increased productivity, streamlining work procedures, better client service and better record

keeping. Fink and Tjarka (1994) in a study of Australian executives described their three reasons

for IT acquisition as ‘doing the right thing’, ‘doing things right’ and ‘improving the bottom line’.

Auger and Gallaugher (1997) noted that improvement in customer services and improvement to

internal control of the business were strong criteria for e-commerce acquisition in SMEs. The

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strong desire for control was also noted in studies carried out by Reimenschneider and Mykytyn

(2000), Poon & Joseph (2001) and Domke-Damonte and Levsen (2002). A number of studies

have been found that some SMEs have adopted e-commerce following customer pressure (Power

and Sohal , 2002).

In our view, SMEs’ e-readiness is the ability of an SME to successfully adopt, use and benefit

from information technologies (IT) such as e-commerce. It is related to the level of IT

acquisition or adoption (especially e-commerce) by them. Many other studies have attempted to

describe the factors influencing IT adoption in SMEs. For example, Iacovou et al. (1995) studied

factors influencing the adoption of electronic data interchange (EDI) by seven SMEs in different

industries, they included perceived benefits, organizational readiness, and external pressure. To

measure perceived benefits they used awareness of both direct and indirect benefits. Variables

measuring organizational readiness were the financial and technological resources. In order to

measure external pressure, they considered competitive pressure and its imposition by partners.

The results suggested that a major reason that small firms become EDI-capable is due to external

pressure (trading partners). The adoption of the Internet was also studied by Mehrtens et al.

(2001). In order to develop a model of Internet adoption, they conducted a case study with seven

SMEs. They devised their model using perceived benefits, organizational readiness and external

pressure as determinant factors. All the factors were found to affect Internet adoption by the

small firms. Mirchandani and Motwani (2001) investigated the factors that differentiate adopters

from non-adopters of e-commerce in small businesses. The relevant factors included enthusiasm

of top management, compatibility of e-commerce with the work of the company, relative

advantage perceived from e-commerce, and knowledge of the company’s employees about

computers. The degree of dependence of the company on information, managerial time required

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to plan and implement the e-commerce application, the nature of the company’s competition, as

well as the financial cost of implementing and operating the e-commerce application were not

influencing factors.

However, SMEs also confronted barriers in e-commerce adoption. Hadjimanolis (1999), in a

study of SMEs in Cyprus, considers barriers to e-commerce adoption to be as either external or

internal to the organization. External barriers include difficulties in obtaining finance, difficulties

in obtaining technological information and difficulties of choosing the appropriate hardware and

software. Hadjimanolis (1999) further nominates two other sub-categories of external barriers

which are termed as demand barriers and environmental barriers. Demand barriers include e-

commerce not fitting with products and services offered or not fitting with the way their

customers wished to conduct their business. Environmental barriers included complicated

governmental regulations and security concerns. He subdivided the internal barriers into two

categories as well. They are termed resource barriers (which included lack of management

enthusiasm and lack of technical expertise) and systems barriers (which included e-commerce

not fitting with current business practices).

Lawrence (1997) defined three categories for e-commerce barriers in SMEs, company, personal

and industry barriers. Company barriers, included low level of technology use within the

business, limited financial and technical resources available, organizational resistance to change

and lack of perceived return on investment. Personal barriers included lack of information on e-

commerce, management preferring conventional approaches to business practice and inability to

see the advantages of using e-commerce. Industry barriers included some respondents believing

that the industry, as a whole was not ready for e-commerce technology.

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Other more recent studies have shown that many of the barriers reported in the late 1990’s by

Lawrence and Hadjimanolis, still exist in today’s SMEs. Tambini (1999) and Eid et al (2002)

found that SME managers are still not convinced that e-commerce fits the products or services

that their businesses offer. Studies by Bakos and Brynjolfsson (2000), Sawhney and Zabin

(2002), and Merhtens et al (2001) have found that there is still a reluctance for SME managers to

adjust their businesses to the requirements and demands placed on it by e-commerce

participation. Some of these barriers are summarized in Table 3.

Table 3 - Barriers to e-commerce adoption in SMEs

Barriers References

E-commerce doesn’t fit with products/services Eid et al (2002) , Kendall and Kendall (2001), Tambini

(1999), Hadjimanolis (1999)

E-commerce doesn’t fit with the way we do

business

Sawhney & Zabin (2002),Mehrtens et al (2001), Bakos &

Brynjolfsson (2000), Farhoomand et al (2000), Poon &

Swatman (1997)

E-commerce doesn’t fit the way our customers

work

Bakos & Brynjolfsson (2000), Hadjimanolis (1999)

We don’t see the advantages of using E-

commerce

Lee & Runge (2001), Chau & Hui (2001), Purao &

Campbell (1998),Lawrence (1997), Hadjimanolis (1999)

Lack of technical know how Mirchandani & Motwani (2000), Hadjimanolis (1999),

Farhoomand et al (2000), Purao & Campbell (1998)

Security risks

Oxley & Yeung (2001), Reimenschneider & McKinney

(2001), Purao & Campbell (1998), Hadjimanolis (1999)

Cost too high Reimenschneider & McKinney (2001), Ratnasingam (2000)

, Hadjimanolis (1999), Purao & Campbell (1998),Lawrence

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(2002)

Not sure what hardware/software to choose Farhoomand et al (2000), Hadjimanolis (1999)

E-readiness of SMEs (ESME) is related to the level of IT acquisition or adoption especially

e-commerce by them. SMEs must remove the above mentioned barriers and also pay attention to

the factors influencing IT adoption for achieving a good level of e-readiness.

In this paper, we try to extract critical factors of e-readiness assessment for SMEs with regarding

the e-readiness assessment models at macro level. In this way, the authors try to extract the

critical factors from macro level and validate it through some strong statistical tools such as

factor analysis. Table 4 shows important areas for e-readiness assessment at macro level.

Table 4- Important areas for e-readiness assessment at macro level

Area E-readiness assessment models

Information Infrastructure CID, APEC, CSPP, McConnell,

EIU,ITU,USAID,CIDCM,NRI

Internet Availability and Affordability CID, APEC, CSPP, McConnell,

EIU,USAID,CIDCM,NRI

Network Speed and Quality CID, APEC,CSPP, McConnell, EIU,

ITU,USAID,NRI

Hardware and Software CID, APEC, CSPP, McConnell, EIU,NRI

ICT Services and Support CID, EIU

Skills and Human Resources(Information

Literacy)

CID, APEC, CSPP, McConnell,

EIU,ITU,USAID,NRI

People and Organizations Online (employees

and divisions)

CID, APEC, CSPP, McConnell, NRI

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Locally Relevant Content CID, APEC,EIU,

Investment and Financial Support for ICT

Development

McConnell, EIU,ITU,USAID

Information and Communication

Technologies in the Workplace

CID, APEC,CSPP,EIU

ICT Employment Opportunities CID, EIU

Business-to-Consumer (B2C) Electronic

Commerce( relation to consumers)

CID, APEC,CSPP, EIU

Business-to-Business (B2B) Electronic

Commerce(relation to the other enterprises)

CID, APEC, EIU

E-Government CID, APEC, McConnell, USAID, NRI

Legal Environment and Regulations (such as

copy right, intellectual property...)

CID, APEC, McConnell, EIU,USAID,NRI

ICT Management and Policy CID,CSPP, EIU, ,CIDCM

Revenue on Electronic Services (cost, charge

and tariff)

APEC,ITU

Degree of Innovation EIU,CSPP

Industry Standards(for ICT Development) APEC, EIU

Security and Encryption (such as public key

infrastructure, digital signature, privacy...)

APEC, CSPP, McConnell, EIU, USAID

Research methodology

This research applies a statistical approach based on factor analysis. Factor analysis is a

technique particularly suitable for analyzing the patterns of complex, multidimensional

relationships encountered by researchers. It defines and explains in broad, conceptual terms the

fundamental aspects of factor analytic techniques. Factor analysis can be utilized to examine the

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underlying patterns or relationships for a large number of variables and to determine whether the

information can be condensed or summarized in a smaller set of factors or components. To

further clarify the methodological concepts, basic guidelines for presenting and interpreting the

results of these techniques are also included.

Factor analysis is also known as a generic name given to a class of multivariate statistical

methods whose primary purpose is to define the underlying structure in a data matrix. Broadly

speaking, it addresses the problem of analyzing the structure of the interrelationships

(correlations) among a large number of variables (e.g., test scores, test items, questionnaire

responses) by defining a set of common underlying dimensions, known as factors. With factor

analysis, the researcher can first identify the separate dimensions of the structure and then

determine the extent to which each variable is explained by each dimension. Once these

dimensions and the explanation of each variable are determined, the two primary uses for factor

analysis, summarization and data reduction can be achieved. In summarizing the data, factor

analysis derives underlying dimensions that, when interpreted and understood, describe the data

in a much smaller number of concepts than the original individual variables. Data reduction can

be achieved by calculating scores for each underlying dimension and substituting them for the

original variables (Hair et al, 1998).

In this way, a questionnaire was designed based on the factor analysis principles whilst

incorporating the important areas of e-readiness assessment listed in Table 4, with 20 questions

measuring attitude and the available responses evaluated by Likert Scale (Likert, 1974) are:

strongly disagree, disagree, no opinion, agree, or strongly agree .

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It is important to say that our question will be made according to the mentioned area listed in

Table 4 and the same 20 criteria will be considered as the questions of our questionnaire. For

example our first question will be as follows:

H1: Information infrastructure is positively associated with the e-readiness of SMEs.

Table 5 summarizes the content of the 20 questions. The content of the questions has been

summarized for better readability (all questions have a format such as above H1).

A research framework was designed according to all these features, as shown in Figure 2. In

addition, information related to the basic profile of the interviewees was requested at the end of

the questionnaire.

To evaluate the questionnaire, eleven experts participated in a pilot test. All the pre-test

participants expressed strong agreement with the suitability of the questionnaire. The

questionnaire was considered finalized after some minor modifications.

Data collection

The research targets were members of 45 non-profit SME organizations in Iran, specializing and

working in an ICT domain including hardware and software, ICT consulting and ICT services.

As most of the SMEs in Iran are non-profit especially in the IT area, we implemented our

research through these kinds of SMEs. Furthermore, the selected IT SMEs are more familiar with

“e” activities and are seen as pioneers in this area in Iran.

In order to understand the viewpoints on e-readiness from all sectors of these organizations,

questionnaires were sent to information, finance, research and development, academic and

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human resource departments of these organizations. The main sampling targets were senior

managers, department managers and personnel who were involved in decision making.

Table 5- The 20 criteria of the research questionnaire (based on table 4)

Criteria

H1 Information Infrastructure

H2 Internet Availability and affordability

H3 Network Speed and Quality.

H4 Hardware and Software.

H5 ICT Services and Support.

H6 Information and Communication Technologies in the Workplace

H7 Skills and Human Resources(Information Literacy)

H8 People and Organizations Online(employees and divisions)

H9 ICT Employment Opportunities.

H10 ICT Management and Policy.

H11 Investment and Financial Support for ICT Development

H12 Revenue on Electronic Services(cost, charge and tariff)

H13 Degree of Innovation

H14 E-Government

H15 Security and Encryption (such as public key infrastructure, digital signature, privacy,...)

H16 Business-to-Consumer (B2C) Electronic Commerce ( relation to consumers)

H17 Business-to-Business (B2B) Electronic Commerce(relation to the other enterprises)

H18 Locally Relevant Content(contents for e-services)

H19 Industry Standards(for ICT Development)

H20 Legal Environment and Regulations (such as copy right, intellectual property...).

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Three hundred and ninety, 390, questionnaires were sent out and 175 returned showing a 44.8%

return rate. Seven of the returned questionnaires were incomplete and thus discarded, which

made the number of valid questionnaires returned 168 or 43% of the total sent out.

Figure 2. Research framework

Statistical analysis

This research used the Kolmogorov-Smirnov test to determine whether the significance levels of

sample data fitted a normal distribution (Hollander and Wolfe, 1973). The Kolmogorov-Smirnov

statistical test shows the maximum difference (absolute value) of an observed and theory-based

distribution function under normal distribution and the absolute value of the statistics close to

zero. According to the test results, the p-value of all the questions was less than 0.05, which

showed that the distribution was not normal. The Cronbach's alpha was equal to 91.6.

Analysis of variables in e-readiness assessment of SMEs

The analytical process included a questionnaire reliability analysis, factor analysis and

identification of the factors.

The Cronbach’s Alpha calculated from the 20 variables of this research was 0.916, which

showed high reliability for designed scale. In order to determine whether the partial correlation

Critical factors affecting e-readiness

Factor analysis

E-readiness assessment model

The 20 criteria of the research

(20 questions)

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of the variables was small, the authors used the Kaiser Meyer Olkin (KMO) measure of sampling

adequacy (Kaiser, 1958) and Bartlett’s Chi-Square test of Sphericity (Bartlett, 1950) before

conducting the factor analysis. The result was a KMO of 0.837 and less than 0.05 for Bartlett

test, which showed a good correlation as depicted in Table 6.

Table 6. KMO and Bartlett test results

Kaiser-Meyer-Olkin Measure of Sampling

Adequacy. .837

Bartlett's Test of

Sphericity

Approx. Chi-Square 2055.556

df

190

Sig.

.000

Factor analysis

Factor analysis provides direct insight into the interrelationships between variables or

respondents and empirical support for addressing conceptual issues relating to the underlying

structure of the data. It also plays an important complementary role with other multivariate

techniques through both data summarization and data reduction. From the data summarization

perspective, factor analysis provides the researcher with a clear understanding of which variables

may act together and how many variables may actually be expected to have impacts in the

analysis. For example, variables determined to be highly correlated and members of the same

factor would be expected to have similar profiles of differences across groups in multivariate

analysis of variance or in discriminant analysis. Examples that highlight the impact of correlated

variables are the stepwise procedures discriminant analysis. These techniques sequentially enter

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variables based on their additional predictive power over variables in the model. As one variable

from a factor is entered, it becomes less likely that additional variables from that same factor

would also be included because they are highly correlated and potentially have less additional

predictive power than the variables which are not appeared in that factor. This does not mean

that the other variables of the factor are less important or have less impact, but instead that their

effect is already represented by the included variable from the factor. The researcher would

better understand the reasoning behind the entry of variables in this technique with knowledge of

the structure of the variables.

According to Hair et al (1998), the insight provided by data summarization can be directly

incorporated into other multivariate techniques through any of the data reduction techniques.

Factor analysis provides the basis for creating a new set of variables that incorporate the

character and nature of the original variables in a much smaller number of new variables,

whether using representative variables, factor scores, or summated scales. In this manner,

problems associated with large numbers of variables or high inter-correlations among variables

can be substantially reduced by substitution of the new variables. The researcher can benefit

from both the empirical estimation of relationships and the insight into the conceptual foundation

and interpretation of the results.

The Factor analysis method, here applied is “Principle Component Analysis (PCA)” developed

by Hotteling (1935) and the condition for selecting factors was based on the principle proposed

by Kaiser (1958): eigenvalue larger than one, and an absolute value of factor loading greater than

0.5. The 20 variables were grouped into four factors; the results can be seen in Tables 7 and 8.

Four factors had an eigenvalue greater than one and the interpretation variable was 65.4 percent.

23

An important tool in interpreting factors is factor rotation. The term rotation means exactly what

it implies. Specifically, the reference axes of the factors are turned about the origin until some

other position has been reached. The un-rotated factor solutions extract factors in the order of

their importance. The first factor tends to be a general factor with almost every variable loading

significantly, and it accounts for the largest amount of variance. The second and subsequent

factors are then based on the residual amount of variance. Each accounts for successively smaller

portions of variance. The ultimate effect of rotating the factor matrix is to redistribute the

variance from earlier factors to later ones to achieve a simpler, theoretically more meaningful

factor pattern. The simplest case of rotation is an orthogonal rotation, in which the axes are

maintained at 90 degrees Hair et al (1998). The results are shown in Table 7 and Table 8.

Table 7- Results of factor analysis

Component Initial Eigenvalues Rotation Sums of Squared Loadings

Total % of Variance Cumulative % Total % of Variance Cumulative %

1 8.021 40.104 40.104 8.021 40.104 40.104

2 2.280 11.400 51.504 2.280 11.400 51.504

3 1.515 7.577 59.082 1.515 7.577 59.082

4 1.259 6.294 65.376 1.259 6.294 65.376

5 .892 5.027 70.402

6 .751 4.256 74.658

7 .730 3.649 78.307

8 .602 3.009 81.316

9 .568 2.842 84.158

10 .493 2.463 86.621

11 .481 2.404 89.025

12 .436 2.178 91.204

13 .357 1.784 92.988

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14 .292 1.460 94.448

15 .267 1.335 95.783

16 .229 1.146 96.929

17 .200 .998 97.927

18 .159 .797 98.724

19 .136 .680 99.404

20 .119 .596 100.000

Extraction Method: Principal Component Analysis.

Factor loading of each variable on the resulted four factors is depicted in Table 8. Each variable

should have significant factor loading only on one factor (for this research we consider the items

which are greater than 0.6 for more strength). Therefore, factors 1, 2, 3, 4, had 4, 4, 3, 2

variables, respectively; So H7, H10, H11, and H12 are significant for factor 1; H1, H3, H5, H9

are significant for factor 2; H2, H6, and H8 are significant for factor 3; and H15 and H20 are

significant for factor 4.

Table 8- Rotated component matrix

Component

1 2 3 4

H1 .491 .615 .403 -.176

H2 .240 .418 .777 .148

H3 .272 .721 .103 .036

H4 -.013 .335 .238 .149

H5 .489 .657 .078 .121

H6 .291 .504 .740 .424

H7 .872 .195 .052 .465

H8 .418 .138 .631 .106

25

H9 .387 .768 -.078 .250

H10 .749 .411 .076 .029

H11 .749 .345 .271 .083

H12 .706 .521 .284 .281

H13 .420 .361 -.059 .142

H14 .408 -.110 .123 .336

H15 .399 .237 .024 .655

H16 .092 .078 .226 .043

H17 .485 .149 .197 .081

H18 .312 .317 .182 -.029

H19 -.010 .082 .251 .0403

H20 .412 .111 .470 .820

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Discussion

Before analyzing the results, an overview of IT plans in Iran is provided to increase familiarity

with this developing country. A comprehensive program has been defined and confirmed for all

executives' offices, government departments and ministries in Iran as the priorities of ICT

operational planning in 2002.

This program and the related strategies are known in Iran as TAKFA1 plan which was defined

five years ago. This plan includes seven objectives as follows:

1. e-government plan (system, virtual network, security and laws)

2. deployment of ICT in training and development of digital skills of human resources in

Iran

3. deployment of ICT in higher educations, hygiene, treatment, and doctoral training

4. the plan of ICT deployment in social services

1 TACFA is a Persian abbreviation and stands for "The plan of ICT development"

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5. development of ICT in economy and commerce

6. ICT deployment in cultural and art area, and reinforcement of Persian language in IT

environment

7. support and development of SMEs in ICT area through incubators and technology parks

As mentioned above, one of the main aims in TACFA plan, is the supporting of IT development

through Iranian SMEs. Therefore, e-readiness assessment of these kinds of enterprises is of great

importance in Iran. It is necessary to say that after confirmation of TAKFA planning, IT

development was accelerated in Iran, and as a result, the e-readiness of the most corporations and

SMEs was increased. On the other hand, the five years economic and social development

planning of Iran is based on the knowledge economy and emphasizes IT deployment in all parts

of society.

It is important to say that because of the dynamic management of private non-profit companies

in contrast with governmental agencies, positive changes through these private companies are

more tangible in ICT area. This explains the phenomenon that e-readiness of these companies is

much more advanced than the corresponding one in governmental corporations.

Generally, we can conclude that there are not many problems in e-readiness of non-profit Iranian

SMEs. Problems such as software, hardware or brainware (skilled human resources) are not

evident however issues such as the lack of a suitable legal environment, the lack of strong

electronic communication platform and some weak management perspectives are prevalent.

The current research aimed to extract critical issues of e-readiness assessment for Iranian SMEs.

The research design was based on a questionnaire of 20 questions, 13 of which were confirmed

through the factor analysis results and the rest of them (7 questions) were rejected.

27

The authors attempted to identify and name the confirmed factors based on the principle of being

concise without losing clarity of meaning. When a factor solution has been obtained in which all

variables have a significant loading, the researcher attempts to assign some meaning to the

pattern of factor loading. Variables with higher loadings are considered more important and have

greater influence on the name or label selected to present a factor. In this way, the researcher will

attempt to assign a name or label to a factor that accurately reflects the variable loading on the

factor [68]. In this way, the names and content of the final four factors are as follows:

• Factor 1 consists of H7, H10, H11, and H12 which are “Skills and Human Resources”,

“ICT Management and Policy”, “Investment and Financial Support for ICT

Development”, and “Revenue on electronic services”. This factor is named

“organizational features” ,

• Factor 2 consists of H1, H3, H5, H9, which are “Information Infrastructure”, “Network

Speed and Quality”, “ICT Services and Support”, and “ICT Employment Opportunities”.

This factor is named as “Information and communication technology infrastructures”,

• Factor 3, that includes H2, H6, and H8, which are “Internet Availability and

affordability”, “Information and Communication Technologies in the Workplace”, and

“People and Organizations Online”. This factor is named “IT availability”, and finally

• Factor 4, which inludes H15 and H20; “Security and Encryption”, and “Legal

Environment and Regulations”. This factor is named “Security and legal environment”.

A model can be conceptualized according to the findings of the research, which shows the

critical issues of e-readiness assessment (Figure 3). This new conceptual model is based on data

analysis of this research and provides a micro model for e-readiness assessment developed for

SMEs through the factors of e-readiness at macro level.

28

According to the study findings, the critical issues for assessment of ESME in Iran were

extracted, based on selected e-readiness assessment models in national level such as APEC,

CSPP, NRI, etc and have been confirmed for micro level (SMEs).

The conceptualized model can also be used for presenting a general view for the assessment and

comparison of e-readiness of the considered SMEs.

Figure3. Conceptual model for assessment of ESME

(Based on research results)

Organizational features

Security and legal environment

ICT availability

Skills and Human Resources

ICT Management and Policy

Investment and Financial Support

Revenue on electronic services

People and organization online

Internet Availability and affordability

ICT in the workplace

ICT infrastructures

Information Infrastructure

ICT Employment Opportunities

ICT Services and Support

Network Speed and Quality

Security and Encryption Legal Environment and Regulations

ESME

29

This research findings have several policy implications. Firstly, SMEs need robust, available

ICT infrastructures with high network speed and quality, ICT services and support, ICT

employment opportunities, Internet availability and affordability in the workplace.

Secondly, the organizational features should be noticed carefully. It includes skills and human

resources, ICT management and policy, investment and financial support for ICT development,

and revenue on electronic services and finally, the regulations and legal operations should not be

forgotten. A legal environment can facilitate the e-adoption in organizations.

In addition to the above, the study results suggest that SMEs in Iran need much greater

infrastructural support in order to reap the benefits of ICT and to develop the capabilities to

contribute to economic development. Associated policies and programs aimed at providing

required infrastructure need to be initiated in developing countries in order to make SMEs more

competitive in the domestic and international markets.

Furthermore, ICT management and policy and the effective support of management are a key to

competitive advantage and further growth.

Nevertheless, our explorative study of Iranian SMEs indicates that innovation activities within

Iranian SMEs seems to be at an early stage as the innovation criteria didn’t appear in the final

results. Given the potential benefits and the pressure to further innovation, we expect a growing

need for Iranian SMEs to increase their know-how concerning creativity factors in order to

improve their innovation processes and hence their competitiveness.

An interesting point in this research is that “industry standards” criteria could not be traced in our

research results. This may be because of the low level of importance towards standards between

the surveyed SMEs as the industries in Iran have recently started new disciplines on quality and

standards.

30

Although the military and some important industries are forced to apply standards and are

considered as pioneers in Iran, average industrial companies have not embarked on

standardisation. It is the authors view that in order to achieve competitiveness in the world

markets, all SMEs in Iran should move towards standards and new quality disciplines.

B2B and B2C models didn’t appear as critical issues in the research results as these models are

not known enough for business leaders.

Another interesting finding is that e-services are not distinguished. E-services are very weak in

Iran and few companies started to present their services in “e” way. It seems to be at an early

stage and people also hardly believe that they can reach their requirements through electronic

infrastructures.

Conclusion

Recent empirical evidence across countries shows a substantial and increasing return to IT

investment. New technologies open up opportunities for small firms to expand their markets

beyond national borders.

Nevertheless, most SMEs in Iran are still traditional and their school of thought belongs to the

past few decades. Today’s global changes dictate a new model of thinking as a basic

requirement. The SMEs in Iran have to restructure their way of thinking which has a deeply roots

in their culture. The difference between culture in east and west is under the influence of school

of thought they have been growing up under. In this way, to succeed when introducing a change

in SMEs, the culture and beliefs need to be altered first. Following that processes, approaches,

techniques, methodologies, etc. could be re-engineered on the base of change management

program.

31

The way the SMEs in west are behaving in the case of change, is under the influence of the

techniques and thoughts commonly used in that environment. The preliminary instruments used

in daily activities in SMEs in west, is a big project in the SMEs in east. For example, the topic of

e-commerce commonly used in SMEs in the west as a daily routine process, if is traced in

eastern SMEs, little trace can be monitored.

As e-commerce is in it’s infancy in Iran, it necessary to be start the introduction of ICTs in

micro and macro levels to bring and ease of related change in Iranian SMEs. The first step is

assumed to be an e-readiness assessment.

E-readiness of an SME is defined here as the ability of a company to successfully adopt, use and

benefit from Information Technologies such as e-commerce. In this paper, we extract the critical

issues for e-readiness assessment of non-profit ICT SMEs in Iran. We reviewed the important

areas of different countries e-readiness assessment according to some established models (macro

level). Afterwards, we designed a research protocol for SMEs, including 20 questions based on

important areas of e-readiness assessment for macro level. In other words, we designed a

questionnaire that asked the experts about e-readiness assessment factors in SMEs with regarding

the important items of e-readiness assessment for macro level. The analysis results showed the

experts believed that some of those items can also be considered for SMEs.

The authors applied factor analysis technique in this research. Four important factors were

extracted which show the critical issues for ESME assessment. The first factor includes “Skills

and Human Resources”, “ICT Management and Policy”, “Investment and Financial Support for

ICT Development”, and “Revenue on electronic services”, that was named as "Organizational

features".

Factor 2 consists of “Information Infrastructure”, “Network Speed and Quality”, “ICT Services

32

and Support”, and “ICT Employment Opportunities” and was named as "Information and

communication technology infrastructures".

The third factor includes “Internet Availability and affordability”, “Information and

Communication Technologies in the Workplace”, and “People and Organizations Online”. This

factor was named as "IT availability"; and finally factor 4 including "Security and Encryption”,

and “Legal Environment and Regulations” was named "Security and legal environment".

This study is probably the first to provide a perspective of critical issues for e-readiness

assessment in SMEs based on macro models in a developing country. It gives valuable

information and guidelines which hopefully will help the leaders in developing countries to

consider the critical issues for e-readiness assessment through their organization in an effective

way.

It is a future proposition that these recommendations be verified by a larger sample of SMEs and

innovation software producers to confirm the preliminary state of knowledge. While the current

survey cannot be said to be complete, it provides a relatively good overview of the SMEs’ status

in Iran.

Since the study only covers non-profit ICT SMEs, it is suggested that the further studies be

expanded to all kinds of SMEs for more comprehensive follow-up studies.

For achieving more exact results, the research findings must be further examined especially for

different types of SMEs. Future research can compare the results between different types of

SMEs.

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