An Empirical Investigation of TQM Barriers in Indian ICT and Banking Industries

Proceedings of SOM 2014 December 12-14, 2014 Department of Management Studies, IIT Roorkee pp.251-262

XVIII Annual International Conference of the Society of Operations Management (SOM 2014) ♦ 251 ♦

An Empirical Investigation of TQM Barriers in Indian ICT and Banking Industries

Faisal Talib1, Zillur Rahman2

1Mechanical Engineering Section, University Polytechnic, Faculty of Engineering and Technology, Aligarh Muslim University, Aligarh, U.P., India

[email protected] 2Department of Management Studies, Indian Institute of Technology, Roorkee, U.Kh., India

[email protected]

Abstract: From past two decades, information and communication technology (ICT) and banking industries have become two most rapidly growing organizations of the Indian service sector. Though other service industries such as hospitality, real estate and many others also contributes an important role in the growth and development of Indian service sector but these two industries provide substantial employment as well as generates enough revenue and therefore, act as two pillars of Indian service sector. The current research literature on the subject have shown that ICT and banking industries are trying hard to position themselves at the top-level across globe and to achieve this goal managers and practitioners are utilizing different quality tools and techniques, one of them is total quality management (TQM). TQM is widely excepted approach and is being implemented across different organizations whether manufacturing or service as it affects business performance, competitiveness and ultimately the customer satisfaction. Previous research studies have shown that there are certain barriers also which hinders the successful implementation of TQM program in various service organizations and therefore, these organizations have either failed to implement TQM or have hesitation to adopt it.

This research work report the results of a survey study on identification and ranking of barriers to TQM implementation and investigates their presence across ICT and banking industries. The research methodology adopted was comprehensive literature review on TQM barriers followed by a self-administered questionnaire survey of the identified Indian ICT and banking companies. A total of 121 complete responses were obtained which comprises of 84 ICT companies and 37 banks. A stratified sampling plan was used for calculating a sample size and to carry out further study. Descriptive statistics, reliability test and independent-sample t-test analysis were used to analyze the collected data. The literature identified 12 TQM barriers which were further categorized into three categories namely extensively present, moderately present and rarely present in ICT industry and two categories i.e. extensively present and moderately present in banking industry. The result shows that "employees' resistance to change"; "attitude of employees towards quality"; "inadequate use of empowerment and teamwork" and "lack of continuous improvement culture" are some of the major barriers which are extensively present in these two industries and affects the successful implementation of TQM program. This research also revealed that out of 12 TQM barriers, six barriers namely "inadequate use of empowerment and teamwork"; ''lack of continuous improvement culture''; ''lack of proper training and education''; ''no benchmarking''; ''poor planning''; and ''lack of top-management commitment" showed significant difference in their presence across Indian ICT and banking industries while rest six barriers have no significant difference in their presence. Finally, the study ends by highlighting some of the managerial implications as well as presents the further research study scope in the area.

Keywords: TQM; TQM barriers; ICT industry; Banking Industry; Identification; Investigation; Indian.

1. INTRODUCTION

Today's global business environment has challenged many organizations to improve quality of products and services, performance, higher market share, concentrate on attaining excellence, creating a right first-time attitude acquiring

effective and efficient business solutions, achieving zero defects, delight customers and suppliers etc. to gain a sustainable competitive advantage (Al-Zaabi et al., 2013; Shen et al., 2013; Lee, 2012. Sit et al., 2009). As business activities are becoming more internationalized, organizations are forced to restructure their processes and systems such that they are



more customer-oriented and focused towards their need and requirement (Sit et al., 2011). In order to cope-up the above issues, total quality management (TQM) is understood to be a well recognized management strategy applicable to every organization sector through which many benefits such as improved organization performance and customer satisfaction could be achieved by applying TQM tools and techniques (Mosadeghrad, 2014; Sit et al., 2011; Talib et al., 2013; Talib, 2013).

While several studies on TQM have claimed that it is an effective approach for improving performance of a business, but its practical implementation involves many difficulties especially in service sector (Bhat and Rajashekhar, 2009; Mosadeghrad, 2014; Talib et al., 2011a, b&c). Due to indifferent characteristics and nature of the product and services (Talib et al., 2012), service organizations find it difficult to implement TQM in a satisfactory and efficient way as they notice various obstacles, which hinder implementation of TQM (Bhat and Rajashekhar, 2009; Talib et al., 2011b). Along these lines, a stream of service organizations, in particular the information and communication technology (ICT) and banking industries are taking initiatives to implement TQM to help them reap its valuable benefits and identify and understand the possible barriers which may effect the proper implementation of TQM program in their organizations and hence possibly the business performance.

The ICT and banking industries in India has experienced a great transformation due to its highly competitive, complex and dynamic environment. First, take the case of Indian ICT industry which shares about a GDP of 12 percent at factor cost in Indian service sector (Economic Survey, 2013). From past two decades it has shown a rapid growth in revenue generation, employment opportunities and business expansion (Economic Survey, 2013). Indian ICT industry comprises of information technology (IT), information technology enabled services (ITeS), software development industries and telecommunication services. The rapid emergence of Indian ICT industry has played a significant role in transforming India's image from slow moving economy to a highly developed market (OIFC, 2014). As per the international data corporation (IDC), the IT market size is expected to rise from US$ 35.1 billion in 2012 to US$ 44.8 billion in 2014. Further, the Business Process Management (BPM) sector, an important sibling of ICT, is continuously growing its revenue generation which is presently marked at 8 percent as compared to 1.2 percent in 1997-98 (NASSCOM, 2013). Finally, with the issuance of more attractive and investors-friendly industry policies, India and foreign direct investment (FDI) policies, India has become one of the favorite destination for ICT investment portfolios (OIFC, 2014).

Similarly, another major contributor of Indian service sector is banking industry. It forms the biggest financial system of the nation and is the life-line of commercial activity. Banks

directly hits the productivity and economic growth of the country and thus, the policy makers and economy watchers are always concerned towards this sector (RBI, 2013). As per the Economic Survey (2013), Indian banking industry shares a 13.2 percent GDP at factor cost in service sector and is value at US$ 1.30 trillion. Further, the revenues of Indian banks have almost grew four-fold over the decade spanning 2001-2010 (IBEF, 2013) and as per Indian Bank's Association (IBA) report, it will become the third largest by 2025 (IBA, 2013). In the next 5-10 years, it is predicted that this industry will create upto two million new jobs driven by the efforts of RBI and the government of India as they are in the way to expand financial services into rural segment (IBEF, 2013). As per RBI (2013) report, new initiatives are also being taken towards popular area like internet banking, mobile banking, customer relationship management (CRM) and data warehousing to drive the next wave of banking technology in the country.

In context to the above statistics and observations of the two industries, study of TQM barriers have become essential in order to implement TQM successfully and achieve sustainable competitive advantage. Implementation of TQM in ICT and banking industries represents a formidable challenge for IT, ITeS, software development and telecommunication, and banks stakeholders and marketers seeking to which barriers will hinder successful implementation of TQM and how they could be dealt as they may drastically affect the performance of these two industries. Thus, understanding barriers to TQM in ICT and banking industries should not be ignored. Further, the literature review also show that no study have been conducted on the identification of TQM barriers and their presence across Indian ICT and banking industry (combined). Thus, there is enough scope to undertake this study and answer some questions emerged from this study: What are the major TQM barriers present in the Indian ICT and banking industries? Which barriers are extensively present, moderately present and rarely present in ICT and banking industries? Is there any difference in the presence of the identified TQM barriers across Indian ICT and banking industries? Therefore, following objectives were formulated to conduct this study in order to answer the above questions:

• To identify and rank the TQM barriers in Indian ICT industry;

• To identify and rank the TQM barriers in Indian banking industry and;

• To investigate the presence of identified TQM barriers across ICT and banking industries.

Rest of the paper is organized as follows. Next section present the review of literature on TQM barriers. Subsequently, research questions and hypotheses were formulated followed by research methodology used is discussed in detail. Thereafter, results and discussions were presented. Finally, the paper ends with the conclusions, some managerial implications, and scope for future research.



2. LITERATURE REVIEW

Enormous literature is available on barriers to TQM implementation. Many researchers identified some major barriers which significantly effects the successful implementation of TQM program in the organizations and were treated as vital for managers and practitioners. If these barriers are overlooked or proper attention is not given then chances of TQM failure is optimum. Moreover, looking into the benefits of TQM implementation (Talib, 2013; Singh et al., 2007; Hietschold et al., 2014; Ng et al., 2014; Salaheldin. 2009), its application in practice involves many difficulties. Several studies have reported failure rate, partial improvement in productivity, ineffective business performance and less favorable approach (Rigby and Bilodeau, 2007; Tata and Prasad. 1998; Kearvey, 1992; Mosadeghrad, 2014). Considering the above facts, there is an emergent need to identify some major TQM barriers in service sector, especially in ICT and banking industries and understand whether the same TQM barriers have their presence in these two industries. This section therefore presents an extent literature review on the studies available on TQM barriers and their affects on TQM implementation program which could help in identification of TQM barriers.

3. TQM BARRIERS

The idea behind the identification of TQM barrier is to understand these barriers that are likely to hinder TQM implementation and enable managers and practitioners to develop more effective strategies to deal with them so as to implement TQM successfully.

A qualitative case study developed by Yamada et al. (2013) present the results of a research about the main barriers that causes the failure of the implementation of quality management (QM) practices. The study was conducted in Brazilian companies using semi-structured interview. They found lack of support of the company leadership, lack of communication and plenty of bureaucracy as main barriers that are responsible for implementation of QM practices failure.

Naghshbandi et al. (2012) assesses the readiness of the police staff of Tehran in accepting TQM. The result of the research indicates that there was a significant difference between the amount of readiness in accepting TQM among males and females. It was also found that significant difference between efficiency regarding their work experiences in accepting the TQM.

A recent study by Mosadeghrad (2014) adopted a pathological approach to understand why TQM programs fail. He identified 54 obstacles to successful TQM implementation. The most frequently mentioned reasons for TQM implementation failures include insufficient education and training, lack of employees' involvement, lack of top-management support,

inadequate resources, deficient leadership, lack of a quality-oriented culture, poor communication, lack of plan for change, and employee resistance to the change program.

Malik et al. (2013) analyzed TQM barriers in a manufacturing firm of Pakistan and observed that lack of resources is the most critical barrier for large manufacturing firms. They survey both ISO and non-ISO certified firms and data was analyzed in terms of large size as well as certified firms.

Ali et al. (2008) in their qualitative study on Malaysian universities discuss the theoretical and research evidence related to the issue of the people barriers covering problems and pitfalls in TQM implementation. A qualitative survey was taken on universities of Malaysia and it was observed that lack of knowledge and information on the quality program, lack of motivation and complacency attitudes, and the quality program being perceived to cause more burden rather benefit.

Mosadeghrad (2013) in his another study explored the barriers to successful implementation of TQM in healthcare sector. He reported that unsuccessful TQM efforts in healthcare organizations is attributed to the strongly departmentalized, bureaucratic and hierarchical structure, professional autonomy, tensions between managers and professionals, and the difficulties involved in evaluating healthcare processes and outcomes. The other obstacles that he found were lack of consistent manager's and employees' commitment to and involvement in TQM implementation, poor leadership and management, lack of a quality-oriented culture, insufficient training and inadequate resources. Further review of previous studies on TQM barrier are summarized and presented in Table 1.

TABLE 1: Selected Studies on TQM Barriers

Researchers Focus/Study Area

Nwabueze (2014) TQM Barriers in the National Health Service (NHS)

Rahman et al. (2012) TQM obstacles in Bangladesh Power Development Board (BPDB)

Abdolshah and Abdolshah (2011)

Barriers to the successful implementation of TQM in Iranian manufacturing organizations

Raj and Attri (2011) Modelling of barriers in the implementation of TQM

Huq (2005) Change management issues to TQM implementation in service industries

Yeung and Armstrong (2003)

Adoption of Economic Value Management (EVM) principles and practices leading to TQM barriers



From the above review of literature on TQM barriers, it was observed that numerous reasons and problems were presented by authors of TQM and they vary from one researcher to another and were used to carry out further study. Present study utilizes 12 valid and reliable TQM barriers studied by Talib et al. (2011a, b&c) for service industries as presented in Table 2. Further, many of them were previously utilized by the researchers like Mosadeghrad (2005); Bhat and Rajashekhar, (2009); Tamimi and Sebastianelli (1998); Amar and Zain (2002); Jun et al. (2004) and several others.

TABLE 2: Major TQM Barriers

Barrier No. TQM Barrier

1. Employee’s resistance to change

2. Attitude of employees towards quality

3. Human resource barrier

4. Inadequate use of empowerment and teamwork

5. High turnover at management level

6. Lack of coordination between department

7. No benchmarking

8. Lack of continuous improvement culture

9. Lack of proper training and education

10. Lack of communication

11. Poor planning

12. Lack of top-management commitment

(Source: Talib et al., 2011a, b&c)

4. RESEARCH QUESTIONS AND HYPOTHESES FORMULATION

Based on the above literature review and as per the designed objectives of present study, following questions were articulated.

Research Question 1 (RQ1): What are the major barriers to successful TQM implementation in the Indian ICT and Banking industries?

Research Question 2 (RQ2): Is there any significant difference in the presence of identified TQM barriers across Indian ICT and banking industries?

Following hypotheses were formulated to answer the above research questions:

H1: Major barriers to the TQM implementation in Indian ICT and banking industries consist of a set of 12 potential barriers.

H2: There is no significant difference in the presence of identified 12 TQM barriers across Indian ICT and banking industries.

5. RESEARCH METHODOLOGY ADOPTED

An empirical research methodology was utilized focusing on outcome of the framed research questions through analyzing the primary data so collected (Goodwin, 2005). In order to carry out the objectives of the present study, a self-administered questionnaire survey using a descriptive cross-sectional study design was performed to collect the primary data which is then used to answer research questions (Talib and Rahman, 2014). This approach was in-line with the similar studies conducted by Boateng-Okrah and Fening, 2012; Kumar et al., 2011, Mosadeghrad, 2005; Malik et al., 2013; Talib et al., 2011c&d.

The designed questionnaire was as per the previous studies (Antony et al., 2002; Brah et al., 2000; Bhat and Rajashekhar, 2009; Mosadeghrad, 2005). It contains two sections. First section presents the respondents demographic information. Second section collects information on identification and ranking of TQM barriers in the company and investigates their presence across the two industries by listing 12 major barriers to successful implementation of TQM program. A 5-point likert scale, with 1= very low, 3= moderate, and 5= very high, was adopted in the study.

The selected Indian ICT and banking companies forms the sampling frame of this survey published by the i3 (i-cube, Information Infrastructure for Institutions), Centre for Monitoring Indian Economy Private Limited, India (CMIE, 2011). The final list consists of 1111 and 200 ICT and banking companies respectively during the study period. The reasons for choosing these two industries were explained in literature review section. Further, one of the well known probability sampling technique, called as stratified sampling methodology was deployed as it ensures that the samples represents the varied population of ICT and banking companies across India (Talib and Rahman, 2014).

In this method, the total population is divided into two stratum. The minimum sample size was calculated as per the GDP contribution of each service industry from the total contribution of GDP in the service sector (Talib and Rahman, 2014). From Table 3, it was observed that the minimum sample size was found to be 471 representing 399 ICT and 72 banking companies. A simple random sample approach was chosen to select a company from a given sample size (Talib and Rahman, 2014).



TABLE 3: Population and Sample Size for ICT and Banking Industries

Industry Population (N)

Sample Size Based on GDP Contribution

(n)

Stratum Sample Size Based on Proportionate

Stratified Sampling Technique

ICT 1111 424 399

Banking 200 47 72

Total 1311 471 471

(Source: Talib and Rahman, 2014)

Officers of upper and middle level management as well as administrators of both the industries were chosen as target responders (Talib and Rahman, 2014). It is assumed that they have enough knowledge and experience in TQM program and were aware of its barriers. Following this strategy, the questionnaires were e-mailed to 471 Indian ICT and banking companies (Table 4). After several follow-ups, a total of 135 companies responded which were approximately 28.6 percent of the sample size, were selected for the study. After critically analyzing each and every questionnaire, only 121 questionnaires were found to be complete and hence, selected for further analysis, rest 14 questionnaires were removed due to either they were incomplete or filled incorrectly and were finally discarded this reduces the response rate from 28.6 to 25.7 percent (Table 4). Some of the main characteristics of respondents are depicted in Table 5.

TABLE 4: Responses Received

Service Industr

y Catego

ry

Population Size (N)

Instrument

Delivered

Responses

Received

Response

Rate (perce

nt)

Valid Responses

Percentage of Total Valid

Responses

ICT 1111 399 95 20.1 84 17.8

Banking

200 72 40 8.5 37 7.9

Total 1311 471 135 28.6 n=121 25.7 (Source: Talib and Rahman, 2014)

6. RESULTS AND DISCUSSION

After following the above process, the responses were entered into the Statistical Package for Social Sciences (SPSS) version 16.0 for further analyses. The statistical methods used in this study were: 1. Descriptive statistics (means, standard deviation, skewness and kurtosis); 2. Reliability test

(Cronbach's Alpha); 3. Levene’s Test (homogeneity of variance); and 4. Independent-samples t-test of hypotheses testing for the mean difference. These test were adopted as per the need and requirement of the study to accomplish the listed objectives. The hypotheses H1 and H2 were judged at two confidence levels i.e. p=0.01 (99%) and 0.05 (95%) (Talib and Rahman, 2014).

7. RESPONDENTS CHARACTERISTICS

A brief summary of profile of the respondents is presented in Table 5. The main variables of the company chosen were: position of respondents; working experience; gender; department/section; and type of company (Talib and Rahman, 2014). Critically observing Table 5, it was found that 30.5 percent of the respondents were holding a position of Quality Managers/HRM/Quality Engineers/Executive Managers, second largest respondents (24 percent) belongs to a position of Project Architect/Consultants/Customer Relation Officers/Service Managers/Assistant Managers and the remaining respondents were from the positions like Project Managers/Senior Engineer Manager/Senior Managers (21.5 percent); Manager/Technical Manager/Operations Manager (16.5 percent); and Directors/Managing Directors/Executive Directors/Chief Executive Officer/General Managers (7.5 percent). Similarly, for the variable service experience, majority of the respondents were having large experience (57.9 percent) while other having 42.1 percent service experience. Viewing the gender indices, it can be observed that the majority of the Indian ICT and banking companies are male dominated companies in their quality department. Which is a red signal for those companies who are not employing or neglecting the females at managerial or administrable posts. Lastly, the responses received from different departments/sections suggests that the study covers all sections/departments of the two industries evenly.

TABLE 5: Characteristics of Respondents

Position/Role of the Respondent Number Percentage

Director/Managing Director/Executive Director/CEO/General Manager

9 7.5

Project Manager/Senior Engineer Manager/Senior Manager

26 21.5

Manager/Technical Manager/Operations Manager

20 16.5

Quality Manager/Human Resource Manager/Quality Engineer/Market Manager/Executive Manager

37 30.5

Others (Like Project Architect, Consultant; Customer Relation

29 24.0



Position/Role of the Respondent Number Percentage

Officer; Service Manager; Assistant Manager)

Total n=121 100

Years of experience Frequency Percentage

Less than 5 years 51 42.1

More than 5 years 70 57.9

Total n=121 100

Gender Frequency Percentage

Male 106 87.6

Female 15 12.4

Total n=121 100

Department/Section Frequency Percentage

Quality 11 9.0

Product and Services 27 22.4

Customer Relation 17 14.0

Marketing 23 19.0

Information Management Services

12 10.0

Others 31 25.6

Total n=121 100

Type of Company Frequency Percentage

ICT 84 69.4

Banking 37 30.6

Total n=121 100

(Source: Talib and Rahman, 2014)

Instrument's Reliability Test

An internal consistency analysis was performed using the SPSS reliability test on returned questionnaires for 12 TQM barriers separately for both the industries i.e. 84 ICT and 37 banks. The result revealed that the measures (TQM barriers) in the two industries have a Cronbach’s Alpha value greater than 0.70, meaning that the questionnaires reliability is fine (Talib and Rahman, 2014; Nunnally, 1967; Hair et al., 1998). The results of the reliability test are shown in Table 6.

TABLE 6: Internal Consistency of TQM Barriers

Industry Measures Number of Items

α -Value

ICT TQM Barriers 12 0.838

Banking TQM Barriers 12 0.833

Identification and Ranking of TQM Barriers

Descriptive statistics is a procedure to collect data quantitatively and then analyzing it to gather meaningful information so that a pattern or some inferences about the data may emerge (Mann, 1995). Moreover, Coakes et al. (2006) reported that “it is necessary to screen data and use transformation technique in order to make sure that data have been correctly entered and that the distributions of variables that are to be used in analysis are normal”. In-line to Coakes et al. (2006) observation, it is a prerequisite to check the normality of the primary data collected before performing any statistical test and making final conclusions. To accomplish the above requirement, this study adopted two well know tests for judging normality. They were: skewness and kurtosis tests. These tests were performed and normality of the data was assessed. The result reported that their values were mostly very near to zero, implying that the assumption of normality appears not to be violated (Talib and Rahman, 2014; Joanes and Gill, 1998) as depicted in Table 7. Scores of mean and standard deviation were calculated and analyzed to test the hypothesis H1. The outcomes were reported in Table 7. Further, comparative mean scores for the two industries are shown in Figure 1.

Examining the summary of the mean scores (Table 7), it was found that the mean scores of 12 TQM barriers lies between 2.26 to 3.17 for ICT industry, which was much lower than the mean scores of banking industry that range from 3.00 and 3.51. Elaborating further, the mean scores of TQM barriers for the ICT and banking industries were divided into three categories i.e. extensively present representing higher mean score (≥3.00); moderately present where mean scores lies between 2.50 and 3.00; and rarely present with low mean scores (<2.50). Following this criterion, two and nine barriers were found to be extensively present in the ICT industry (''employee’s resistance to change'' and ''attitude of employees towards quality'') and banking industry (''employee’s resistance to change''; ''attitude of employees towards quality''; ''human resource barrier''; ''inadequate use of empowerment and teamwork''; ''high turnover at management level''; ''no benchmarking''; ''lack of continuous improvement culture''; ''lack of proper training and education''; and ''lack of top-management commitment'') respectively. Whereas the set of nine TQM barriers like ''human resource barrier''; ''inadequate use of empowerment and teamwork''; ''high turnover at management level''; ''lack of coordination between department''; ''no benchmarking''; ''lack of continuous improvement culture''; ''lack of proper training and education''; ''lack of communication''; and ''poor planning'' were observed to be moderately present (second category) in ICT industry and for banking industry, there were three barriers in this category namely ''lack of coordination between department''; ''lack of communication''; and ''poor planning''. Third category consist of those barriers which are rarely present in the two industries. From Table 7, it was observed that only one TQM barrier i.e.



''lack of top-management commitment'' was present in the ICT industry whereas no barrier lower than the mean score of 2.50 was found in case of banks. The above findings suggest that in general, majority of the TQM barriers were equally present in both the industries and are affecting the successful implementation of TQM program except for the barrier ''lack of top-management commitment'' which show its weak presence (mean score=2.26) in ICT industry and strong presence (mean score=3.27) in banks. This implies that managers and practitioners who are responsible for implementation of TQM in Indian banking industry should review their policy specially at top-level and give their full efforts in installing quality culture, continuous improvement in quality, and providing training and education to employees' at every level. These are the basic requirements in order to adopt TQM program effectively. Further, it was also concluded that Indian ICT industry upto certain extent is free from this barrier implying that ICT industry's top-management is highly committed to continuous quality improvement systems such as TQM. Overall, from above findings it was concluded that the major barriers for successful implementation of TQM program in Indian ICT and banking industries consist of a set of 12 TQM barriers and thus, the hypothesis H1 is accepted.

Additionally, from Table 7, it was also observed that "employees' resistance to change" and "attitude of employees towards quality" were the major barriers (mean score greater than 3.00) which are extensively present in these two Indian service industries and affects the successful implementation of TQM program. They were ranked at first and second place in ICT industry and second and fifth in banks.

Major actions have to be taken by the top-management to motivate their employees to adopt quality systems and involve in quality improvement programs through organizing brainstorming sessions on CQI, benefits of TQM, management development program (MDP), training and education on advanced quality tools and techniques, improved work culture etc. Similarly, ''inadequate use of empowerment and teamwork''; ''lack of continuous improvement culture''; and ''no benchmarking'' as TQM barriers were observed as major barriers and ranked at third and fourth places in banking industry. Efforts should be made to minimize these two barriers by planning and developing the future actions strategically so that the Indian banks which forms the core of Indian financial system should be improved further.

TABLE 7: Descriptive Statistics of TQM Barriers in Indian ICT and Banking Industries

TQM Barrier ICT Industry Banking Industry

Mean

Std. Deviatio

n

Skewness

Kurtosis Ranking Mean Std. Deviatio

n

Skewness

Kurtosis Ranking

Employee’s resistance to change

3.17 0.834 0.059 -0.845 1 3.39 1.010 -0.162 -0.416 2

Attitude of employees towards quality

3.05 0.904 -0.195 -0.603 2 3.32 1.156 -0.458 -0.539 5

Human resource barrier 2.85 0.963 -0.345 -0.877 3 3.16 0.834 -0.321 0.137 7 Inadequate use of empowerment and teamwork

2.81 1.024 0.187 -0.570 4 3.51 1.096 -0.639 0.391 1

High turnover at management level

2.80 0.773 -0.273 -0.190 5 3.10 0.843 -0.507 0.941 9

Lack of coordination between department

2.79 1.076 -0.152 -0.678 6 2.95 1.080 -0.559 -0.518 12

No benchmarking 2.63 0.847 0.186 -0.136 9 3.35 0.978 -0.782 0.174 4 Lack of continuous improvement culture

2.65 0.967 -0.012 -0.639 7 3.38 1.114 -0.440 -0.069 3

Lack of proper training and education

2.64 1.200 -0.060 -1.118 8 3.11 1.022 -0.227 0.076 8

Lack of communication 2.62 1.074 -0.198 -0.968 10 2.97 1.166 -0.055 -0.694 11 Poor planning 2.58 1.020 0.013 -0.838 11 2.99 1.211 -0.163 -0.973 10 Lack of top-management commitment

2.26 0.958 0.457 0.083 12 3.27 1.122 -0.571 -0.082 6



3.323.16

3.513.35 3.38

3.11 3.03 3.083.27

3.17

3.052.85 2.81 2.80 2.79

2.63 2.65 2.64 2.62 2.58

2.26

3.3

93.10

3.00

0

0.5

1

1.5

2

2.5

3

3.5

4

1 2 3 4 5 6 7 8 9 10 11 12

Barrier Number

Mea

n S

core

ICT Industry Banking Industry

Fig. 1. Comparison of Means of TQM Barriers Between ICT and Banking Industries

Investigation of TQM Barriers

This section of the paper tries to investigate the difference in the presence of identified TQM barriers across Indian ICT and banking industries and to accomplish the third objective of the study. An independent-samples t-test was performed to fulfill this objective and examine the second research question RQ2 as well as to test the corresponding hypothesis H2. An independent-samples t-test is appropriate when the researcher’s goal is to compare the difference between the means of two groups on the same variable (Talib and Rahman, 2014; Coakes et al., 2006; Abusa and Gibson, 2013). Furthermore, another assumption to carry out this test is the test of homogeneity of variance, which must be met by the data. To check the homogeneity of variance assumption, Levene’s test for Equality of Variances was adopted. Table 8 presents the Levene’s test results. The table shows the Levene statistics and the significance p-value result of each TQM barrier. The result further show that all the p-values of 12 TQM barriers obtained from the Levene’s test for Equality of Variances were found to be greater than 0.05 (p>0.05). Meaning that the assumption of equal variance has not been violated. Accordingly, it is assumed that the independent-samples t-test can be performed for further analysis.

Subsequently, an independent-samples t-test was used to investigate whether there exist any significant difference in the presence of 12 TQM barriers in the two groups i.e. ICT and banking industries. The result are presented in Table 9 which shows the two means (ICT and banking) of all the TQM barriers and their t-values as well as significance level. After initial investigation of all the 12 TQM barriers with respect to

t-value and significance level, it was observed that there is no significant difference between six TQM barriers among the two industries. They were: "employee’s resistance to change"; "attitude of employees towards quality"; "human resource barrier"; "high turnover at management level"; "lack of coordination between department"; and "lack of communication". While the remaining six barriers (''inadequate use of empowerment and teamwork''; ''lack of continuous improvement culture''; ''lack of proper training and education''; ''no benchmarking''; ''poor planning''; and ''lack of top-management commitment'') showed significant difference at 0.01 and 0.05 levels. Further analysis of these six significant barriers showed that they have large difference in their mean scores across the two industries (inadequate use of empowerment and teamwork: 2.81 and 3.51; lack of continuous improvement culture: 2.65 and 3.38; lack of proper training and education: 2.64 and 3.11; no benchmarking: 2.63 and 3.35; poor planning: 2.58 and 3.08; and lack of top-management commitment: 2.26 and 3.27) as well as ranked at 4th and 1st places for ''inadequate use of empowerment and teamwork'', 7th and 3rd places for ''lack of continuous improvement culture'', 8th and 8th places for ''lack of proper training and education'', 9th and 4rt places for ''no benchmarking'', 11th and 10th places for ''poor planning'', and 12th and 6th places for ''lack of top-management commitment'' as depicted in Tables 7 and 9 which strengthen the present results further.

Looking into these results, it was observed that out of 12 TQM barriers, six barriers are not significantly different across Indian ICT and banking industries while the remaining six have significant difference in their presence. Thus, the



hypothesis H2 was rejected for the following six barriers: ''inadequate use of empowerment and teamwork'' (H2d); ''lack of continuous improvement culture'' (H2g); ''lack of proper training and education'' (H2h); ''no benchmarking'' (H2i); ''poor planning'' (H2k); and ''lack of top-management commitment'' (H2l) which show significant difference in their presence across the two industries. Further, the six barriers i.e. employee’s resistance to change" (H2a); "attitude of employees towards quality" (H2b); "human resource barrier" (H2c); "high turnover at management level" (H2e); "lack of coordination between

department" (H2f); and "lack of communication" (H2j) which show no significant difference in their presence across the two industries. They also have small mean differences among them implying that almost all these barriers were effectively present in both the industries. Thus, the hypothesis H2 was accepted for these barriers. Additionally, the managers and practitioners of Indian ICT and banking industries have to pay attention to these barriers and efforts should be made to minimize them for successful implementation of TQM program and get maximum benefits of it.

TABLE 8: Homogeneity Test of Variance (Levene’s Test)

TQM Barrier Levene Statistic Significance (p-value)

Employee’s resistance to change 2.569 0.112 Attitude of employees towards quality 5.519 0.055 Human resource barrier 2.077 0.152 Inadequate use of empowerment and teamwork 0.098 0.755 High turnover at management level 0.054 0.816 Lack of coordination between department 0.219 0.641 Lack of continuous improvement culture 0.508 0.477 Lack of proper training and education 5.627 0.089 No benchmarking 1.037 0.311 Lack of communication 0.016 0.901 Poor planning 1.525 0.219 Lack of top-management commitment 0.741 0.391

Note: n=121; *p<0.05.

TABLE 9: Independent Samples t-test Results of TQM Barriers Across Indian ICT and Banking Industries

Hypothesis TQM Barrier Mean Score in Independent Samples t-test Results

Result

ICT Banks ‘t’ Value Significance (p-value)

H2a Employee’s resistance to change 3.17 3.39 -1.205 0.231 (NS) Accepted H2b Attitude of employees towards

quality 3.05 3.32 -1.421 0.158 (NS) Accepted

H2c Human resource barrier 2.85 3.16 -1.735 0.085 (NS) Accepted H2d Inadequate use of empowerment

and teamwork 2.81 3.51 -3.411 0.001** Rejected

H2e High turnover at management level 2.80 3.10 -1.980 0.052 (NS) Accepted H2f Lack of coordination between

department 2.79 3.00 -1.008 0.316 (NS) Accepted

H2g Lack of continuous improvement culture

2.65 3.38 -3.737 0.000** Rejected

H2h Lack of proper training and education

2.64 3.11 -2.105 0.037* Rejected

H2i No benchmarking 2.63 3.35 -4.108 0.000** Rejected H2j Lack of communication 2.62 3.03 -1.875 0.063 (NS) Accepted H2k Poor planning 2.58 3.08 -2.333 0.021* Rejected H2l Lack of top-management

commitment 2.26 3.27 -5.057 0.000** Rejected

Notes: Significant at *p<0.05; **p<0.01; NS=No Significant Difference.



8. CONCLUSIONS

The findings of this study was based on the extent literature review and observations from survey conducted through self-administered questionnaire mailed to different ICT and banking companies to identify and rank the major TQM barriers as well as to investigate the difference in the presence of identified TQM barriers across these two industries. In total, 471 questionnaires were delivered, out of which 399 were sent to ICT companies and 72 to different banks across the country. After several follow-ups, finally 121 valid responses were received consisting of 84 ICT responders and 37 from banks. The 12 identified TQM barriers obtained from review of literature were listed in the questionnaire to accomplish the two objectives of this study. From the findings as presented and discussed in the earlier section, it was concluded that these identified barriers may further be categorized into three categories i.e. extensively present, moderately present, and rarely present based on their mean scores in the two Indian service industries. It was observed that ''employee’s resistance to change'' and ''attitude of employees towards quality'' were the two extensively present TQM barriers in Indian ICT industry whereas nine TQM barriers namely ''employee’s resistance to change''; ''attitude of employees towards quality''; ''human resource barrier''; ''inadequate use of empowerment and teamwork''; ''high turnover at management level''; ''no benchmarking''; ''lack of continuous improvement culture''; ''lack of proper training and education''; and ''lack of top-management commitment'' showed their extensive presence in Indian banks.

Similarly, another nine barriers like ''human resource barrier''; ''inadequate use of empowerment and teamwork''; ''high turnover at management level''; ''lack of coordination between department''; ''no benchmarking''; ''lack of continuous improvement culture''; ''lack of proper training and education''; ''lack of communication''; and ''poor planning'' were perceived to be moderately present in ICT industry and three barriers (''lack of coordination between department''; ''lack of communication''; and ''poor planning'') were moderately present TQM barriers for banking industry. Further, only one barriers i.e. ''lack of top-management commitment'' was found under third category i.e. rarely present. On the other hand, it was observed that in banks no barrier showed their presence in this category implying that majority of the identified barrier were extensively present in the Indian banking industry except the few which showed their presence in moderate category. Further, it was also observed that "employees' resistance to change", "attitude of employees towards quality" and ''human resource barrier'' were found to be ranked at 1st, 2nd and 3rd places and observed to be the three major barriers to TQM implementation in Indian ICT industry. While ''inadequate use of empowerment and teamwork'', ''employee’s resistance to change'', and ''lack of continuous improvement culture'' were judged as top three potential barriers in case of Indian banks.

Furthermore, the study also investigate the presence of 12 TQM barriers across the ICT and banking industries. It was concluded that no significant difference was present in the presence of the following six TQM barriers: "employee’s resistance to change"; "attitude of employees towards quality"; "human resource barrier"; "high turnover at management level"; "lack of coordination between department"; and "lack of communication" except for the remaining six barriers like ''inadequate use of empowerment and teamwork''; ''lack of continuous improvement culture''; ''lack of proper training and education''; ''no benchmarking''; ''poor planning''; and ''lack of top-management commitment'' where they showed a significant difference in their presence. Finally, it was concluded that efforts should be made to minimize and reduce these identified barriers from the two service industries in order to gain maximum benefit of TQM program for enhanced business performance and achieving customer satisfaction. In summary, the present results indicate a direction as well as an alarm for the managers and practitioners of these two Indian service industries to overcome these TQM barriers and put their efforts to minimize them for achieving fruitful result of TQM implementation program.

Managerial Implications

The study also have some important implications for managers of service industries. They are:

• This study may act as a guide to the managers and practitioners of the two Indian service industries in gaining the knowledge of potential barriers which may hinder proper implementation of TQM program.

• Managers and practitioners of both the industries should take into account the importance of change in employees' culture towards quality as it acts as one of the major issue in both ICT and banking industries. They should put their efforts in removing this barrier through motivation, forming team/group, providing training and education etc. This will change this attitude of employee towards quality.

• Through this study, managers and practitioners would be able to identify the critical area where they have to work and remove difficulties to implement TQM program successfully.

• The study results provide a practical understanding of TQM barriers and their presence in these two industries. These barriers would be very helpful for the managers and practitioners in maintaining the current TQM program to sustain.

Future Research Scope

Future scope of this study is to implant this research work to new and emerging service industries where researches are at nascent stage. Some of these are: cultural and creative industries, mobility industries, experience industries, eco-



industries, personalized medicine industries, auto-service providers, and many others where the customers satisfaction is a critical parameter that determines the growth and improvement of industry significantly. Additionally, increasing sample size may affect the present findings in positive way for that personal interviews and telephonic conversations may be the area where attention has to be paid which may further improve the response percentage. Furthermore, this study was conducted in a specific country, future study may include a diversity of other nations to make the study more versatile and generalizable. Finally, adoption of Delphi method or Meta-analysis approach or similar techniques for identification of TQM barriers may help to find out the other potential barriers and may strengthen the findings of the present study. Similarly, application of latest and emerging approaches like Data Envelopment Analysis (DEA), Fuzzy-Quality Function Deployment (FQFD), Fuzzy-Analytic Network Process (FANP), Resource-based View (RBV) etc. which are useful in identification, prioritization, classification, and measurement of efficiency of factors responsible for growth and development of an organization should be deployed to gain and sustain competitive advantage.

REFERENCES

[1] Abdolshah, M. and Abdolshah, S. (2011), "Barriers to the successful implementation of TQM in Iranian manufacturing organisations", International Journal of Productivity and Quality Management, Vol.7, No.3, pp. 358 - 373.

[2] Abusa, F.M. and Gibson, P. (2013), “TQM implementation in developing countries: a case study of the Libyan industrial sector”, Benchmarking: An International Journal, Vol.20, No.5, pp. 693-711.

[3] Ali, N.A., Zairi, M. and Mahat, F. (2008), "People resistance in TQM implementation: a qualitative study on Malaysian universities", International Journal of Productivity and Quality Management, Vol. 3, No.1 pp. 1 - 11.

[4] Al-Zaabi, S., Al-Dhaheri, N. and Diabat, A. (2013) ‘Analysis of interaction between the barriers for the implementation of sustainable supply chain management’, International Journal of Advanced Manufacturing Technology, Vol.68, No.1-4, pp. 895-905.

[5] Amar, K. and Zain, M. Z. (2002), “Barriers to implementing TQM in Indonesian manufacturing organizations”, The TQM Magazine, Vol.14, No.6, pp. 367-372.

[6] Antony, J., Leung, K., Knowles, G. and Gosh, S. (2002), “Critical success factors of TQM implementation in Hong Kong industries”, International Journal of Quality and Reliability Management, Vol.19, No.5, pp. 551-566.

[7] Bhat, K.S. and Rajashekhar, J. (2009), “An empirical study of barriers to total quality management implementation in Indian Industries”, The TQM Magazine, Vol.21, No.3, pp. 261-272.

[8] Boateng-Okrah, E. and Fening, F.A. (2012), “TQM implementation: a case of a mining company in Ghana”, Benchmarking: An International Journal, Vol.19, No.6, pp. 743-759.

[9] Brah, S. A., Wong, J. L. and Rao, B. M. (2000), “TQM and business performance in the service sector: a Singapore study”,

International Journal of Operations and Production Management, Vol.20, No.11, pp. 1293-1312.

[10] CMIE (2011), Centre for Monitoring Indian Economy Private Limited, India Website: http://www.cmie.com/database/?service=database-products/customised-solutions/information-infrastructure-for-institutions.htm.[Assessed 20 May 2011].

[11] Coakes, S.J., Steed, L. and Dzidic, P., 2006. SPSS: Analysis without Anguish: Version 16 for Windows, John-Wiley, India.

[12] Economic Survey (2013), Ministry of Finance, Government of India, http://indiabudget.nic.in [Assessed on 15 December, 2013].

[13] Goodwin, C.J. (2005), Research in Psychology: methods and design, USA: John Wiley and Sons, Inc.

[14] Hair, J.F. Anderson, R.E., Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis, 5th Edition, New Jersey: Prentice Hall.

[15] Hietschold, N., Reinhardt, R. and Gurtner, S. (2014), "Measuring critical success factors of TQM implementation successfully-a systematic literature review", International Journal of Production Reserach, doi: 10.1080/00207543.2014.918288.

[16] IBA (2013), Indian Banks’ Association, www.iba.org, in [Assessed on 15 December, 2013].

[17] IBEF (2013), India Brand Equaity Foundation, http://www.ibef.org/industry/banking-india.aspx [Assesed on: 15 August, 2013].

[18] Joanes, D. N. and Gill, C. A. (1998), “Comparing measures of sample skewness and kurtosis”, Journal of the Royal Statistical Society (Series D): The Statistician Vol.47, No.1, pp.183–189.

[19] Jun, M., Cai, S. and Peterson, R. T. (2004), “Obstacles to TQM implementation in Mexico’s Maquiladora industry”, Total Quality Management, Vol.15, No.1, pp. 59-72.

[20] Kearney, A.T. (1992), Total Quality-Time to take off the Rose-Tinted Spectacles, IFS Publications, London.

[21] Kumar, R., Garg, D. and Garg, T.K. (2011), “TQM success factors in North Indian manufacturing and service industries”, The TQM Journal, Vol.23, No.1, pp. 36-46.

[22] Lee, D.H. (2012), "Implementation of quality programs in health care organizations", Service Business, Vol.6, pp. 387-404.

[23] Malik, S.A., Nasim, K. and Iqbal, M.Z. (2013), "TQM practices in electric fan manufacturing industry of Pakistan", International Journal of Productivity and Quality Management, Vol.12, No.4 pp. 361 - 378.

[24] Mann, P.S. (1995), Introductory Statistics (2nd ed.), Wiley, ISBN: 0-471-31009-3.

[25] Mosadeghrad, A.M. (2005), "A survey of total quality management in Iran: Barriers to successful implementation in health care organizations", Leadership in Health Services, Vol.18, No.3, pp. 12-34.

[26] Mosadeghrad, A.M. (2013), "Obstacles to TQM success in health care systems", International Journal of Health Care Quality Assurance, Vol.26 No.2, pp. 147-173.

[27] Mosadeghrad, A.M. (2014), "Why TQM programmes fail? A pathology approach", The TQM Journal, Vol.26, No.2, pp. 160-187.

[28] Naghshbandi, S., Yousefi, B., Zardoshtian, S. and Moharramzade, M. (2012), "Assessment of military's force staff's readiness for total quality management (TQM) approval in



Tehran Province", Procedia-Social and Behavioral Sciences, Vol.46, pp. 5345-5349.

[29] NASSCOM (2013), National Association of Software and Services Companies. Website: http://www.nasscom.in/. [Assessed on 15 December 2013].

[30] Ng, S.C.H., Zhao, X., Fan, X. and Rungtusanatham, J.M. (2014), "TQM and brand-building by Chinese original brand manufacturers: impact on business performance", International Journal of Production Research, Vol.52, No.3, pp. 825-846.

[31] Nunnally, J.C. (1967), Psychometric Theory. McGraw-Hill, New York, NY.

[32] Nwabueze, U. (2014), "The rise and decline of TQM in the NHS", The TQM Journal, Vol.26, No.5, pp. 499-509.

[33] OIFC (2014), Overseas Indian Facilitator Center, Ministry of Overseas Indian Affairs, www.oifc.in [Assessed on 15 December, 2013].

[34] Rahman, A., Kutubuddin, M., Arif-Uz-Zaman, K. and Shumon, M.R.H. (2012), "Implementation of total quality management in Bangladesh power generating sector: progress and problems", International Journal of Industrial and Systems Engineering, Vol.11, Nos.1/2, pp. 122 - 136.

[35] RBI (2013), Reserve Bank of India, http://www.rbi.org.in/scripts/BS_SpeechesView.aspx?Id=829 [Assesed on: 15 August, 2013].

[36] Rigby, D. and Bilodeau, B.(2007), "Bain's global 2007 management tools and trends survey", Strategy and Leadership, Vol.35, No.5, pp. 9-16.

[37] Salaheldin, S.I., (2009), “Critical success factors for total quality management implementation and their impact on performance of SMEs”, International Journal of Productivity and Quality Management, Vol.58, No.3, pp. 215-237.

[38] Shen, L., Olfat, L., Govindan, K., Khodaverdi, R. and Diabat, A. (2013), "A fuzzy multi criteria approach for evaluating green supplier's performance in green supply chain with linguistic preferences", Resources, Conservation and Recycling, vol. 74, pp. 170–179.

[39] Singh, P.J, Chua, M.W., and Sum, C.C. (2007), Deming management method: Applying theory to public sector organizations and testing refinements. [Available online]http://www.ecom.unimelb.edu.au/downloads/nus_symposium/Singh_paper.pdf.

[40] Sit, W-Y., Ooi, K-B., Lin, B. and Chong, A.Y-L. (2009), "TQM and customer satisfaction in Malaysia's service sector", Industrial Management and Data Systems, Vol.109, No.7, pp.957-975.

[41] Sit, W-Y., Ooi, K-B., Loke, S-P. and Han, G.T.W. (2011), "TQM and service quality: a survey of commercial banking industry in Malaysia", International Journal of Services, Economics and Management, Vol.3, No.1, pp. 78-91.

[42] Talib, F. (2013), “An overview of total quality management: understanding the fundamentals in service organization”, International Journal of Advanced Quality Management, Vol.1 No.1, pp. 1-20.

[43] Talib, F. and Rahman, Z. (2014), "Identification and adoption of total quality management practices in Indian information and

communication technology and banking industries: an empirical study", Proceedings of 3rd International Conference on Sustainability and Management Strategy (ICSMS-2014), organized by Institute of Management Technology (IMT), Nagpur, India in collaboration with California State University SAN BERNARDINO and NEERI during March 21-22, 2014.

[44] Talib, F., Rahman, Z. and Qureshi, M.N. (2011a), “Analysis of interaction among the barriers to total quality management implementation using interpretive structural modeling (ISM) approach”, Benchmarking: An International Journal, Vol.18, No.4, pp. 563-587.

[45] Talib, F., Rahman, Z. and Qureshi, M.N. (2011c), “An Empirical Study of Barriers to TQM Implementation in Indian Service Industries”, Proceedings of First International Conference on Industrial Engineering (ICIE 2011), organized by Department of Mechanical Engineering, S.V. National Institute of Technology, Surat, India in association with Indian Institution of Industrial Engineering (IIIIE), NHQ-Mumbai, India during November17-19, 2011, pp. 1072-1084.

[46] Talib, F., Rahman, Z. and Qureshi, M.N. (2011d), “Identifying the Key Practices of TQM in Indian Service Industries: An Empirical Analysis”, Proceedings of International Conference on Advances in Supply Chain and Manufacturing Management (ASCMM 2011), organized by Department of Industrial Engineering and Management, Indian Institute of Technology Kharagpur (IITKhg), West Bengal, India during December 16-18, 2011.

[47] Talib, F., Rahman, Z. and Qureshi, M.N. (2012), “Total quality management in service sector: a literature review”, International Journal of Business Innovation and Research, Vol.6, No.3, pp. 259-301.

[48] Talib, F., Rahman, Z. and Qureshi, M.N. (2013), “An empirical investigation of relationship between total quality management practices and quality performance in Indian service companies”, International Journal of Quality and Reliability Management, Vol. 30, No.3, pp. 280-318.

[49] Talib, F., Rahman, Z., Quershi, M.N. and Siddique, J. (2011b), “Total quality management and service quality: an exploratory study of management practices and barriers in service industries”, International Journal of Services and Operations Management, Vol.10, No.1, pp. 94-118.

[50] Tamimi, N. and Sebastianelli, R. (1998), “The barriers to total quality management”, Quality Progress, Vol.31, No.6, pp. 57-60.

[51] Tata, J. and Prasad, S. (1998), "Cultural and structural constraints on total quality management implementation", Total Quality Management and Business Excellence, Vol.9, No.8, pp. 703-710.

[52] Yamada, T.T., Poltronieri, C.F., Gambi, L.N. and Gerolamo, M.C. (2013), "Why does the implementation of quality management practices fail? a qualitative study of barriers in Brazilian companies", Procedia-Social and Behavioral Sciences, Vol.81, pp. 366-370.

[53] Yeung, V.W.S. and Armstrong, R.W. (2003), "A key to TQM benefits: manager involvement in customer processes", International Journal of Services Technology and Management, Vol.4, No.1, pp. 14-29.

An Empirical Investigation of TQM Barriers in Indian ICT and Banking Industries

Documents

Transcript of An Empirical Investigation of TQM Barriers in Indian ICT and Banking Industries