Some obstacles that affect the TQM implementation in … · 2018-02-12 · TQM, they become familiar with some obstacles that hinder the TQM implementation. As a result, this RMG

Proceedings of the International Conference on Industrial Engineering and Operations Management

Bandung, Indonesia, March 6-8, 2018

© IEOM Society International

Some obstacles that affect the TQM implementation in

Bangladeshi RMG Sector: An empirical study

Subrata Talapatra1*, Md. Kutub Uddin2 1Industrial Engineering and Management Department

2Mechanical Engineering Department

Khulna University of Engineering & Technology

Khulna-9203, Bangladesh

[email protected]*, [email protected]

Abstract

This paper empirically examines the TQM obstacles faced by the managers of RMG sector in Bangladesh. Now a day, the demand for quality improvement of the product has been raised to cope with

the challenges in marketplaces. TQM implementation has already shown a positive attitude towards

quality improvement. As a result, Bangladeshi RMG firms are trying to implement TQM in their organizations. Unfortunately, they are not able to implement TQM in their organizations. To determine

the exact obstacles, two–pronged approached are used: first, an extensive literature review has been

conducted to find out the obstacles of TQM implementation and second, data have been collected from some selected Bangladeshi RMG firms. 25 obstacles have been identified so far. Finally, five obstacles

have been selected for empirical test according to the expert’s opinion. The findings of this study suggest

that, the most important barriers are lack of: top-management commitment to quality, focus on customer,

continuous improvement, quality management practice, and knowledge about quality cost. This study is unique in terms of investigating TQM obstacles in this sector. Therefore, this paper can contribute to meet

an urgent need of successful implementation of TQM in Bangladesh and other developing countries in the

world.

Keywords

TQM implementation, Continuous improvement, RMG sector.

1. IntroductionBangladeshi firms are getting opportunities to explore their business in abroad due to globalization. For this reason,

several firms are looking for sustainable business environment (Al-Zaabi et. al., 2013; Jaeger and Adair, 2016; Lee,

2012; Shen et. al., 2013; Weckenmann et. al., 2015). They are comparing their firms with other organizations as a

benchmark to improve their quality (Sit et al., 2011). Total quality management (TQM) has played a positive role to

achieve their goal. Now a day, several firms in different sectors are using the TQM philosophy to achieve their

success across the globe (Mosadeghrad, 2014; Sit et al., 2011; Talib et al., 2013; Talib,2013). They are enjoying

several sustainable competitive advantages. Among the several benefits enjoyed by the several successful TQM

implemented firms, customer satisfaction and better organizational structure are most important, because these two

benefits can lead a firm more towards sustainable development (Bhat and Rajashekhar, 2009; Mosadeghrad, 2014;

Talib et al., 2011a, b & c). Similarly, readymade garments (RMG) sector in Bangladesh are trying hard to increase their quality of product through application of TQM. But, in most of the cases, the RMG firms are facing difficulties

to implement TQM successfully in their organizations (Syduzzaman et. al., 2016). During the implementing of

TQM, they become familiar with some obstacles that hinder the TQM implementation. As a result, this RMG sector

fails to achieve the benefits of TQM implementation. To address this gap, it is essential to identify the important

obstacles of TQM implementation in RMG sector in Bangladesh. Therefore, this research has given emphasis on:

i) To investigate the important obstacles of TQM implementation in Bangladeshi RMG sector.

ii) To develop a research framework that will investigate the effect of different barriers.

iii) To validate the framework empirically by exploratory and confirmatory factor analysis followed by structural

equation modeling (SEM).

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It is a survey–based research to study the potential obstacles related to TQM implementation in Bangladeshi RMG

sector.

The rest of the paper is arranged into five sections. The first section covers the literature review relating TQM

obstacles. The second section provides design of current research. Research methodology is discussed in section

three. The next section consists of data analysis and discussion on findings. Finally, in section fifth, limitations and scope of future studies are summarized.

2. Literature ReviewIt is essential to change the culture of the employees in doing their works before implementing TQM in that

organization. There are several reasons for the failure of TQM implementation in an organization. The main aim of

this literature review to find out the potential obstacles of TQM in Bangladeshi RMG sector. There are two common

obstacles responsible for failure of TQM implementation (Bhat and Rajashekhar, 2009). They are lack of strategic

planning and supportive culture to implement TQM. In their study Liu (1998), Rahim and Whalen (1994) have

identified lack of top management support, lack of proper training as most important TQM barriers. The

implementation barriers of TQM are present in all sectors including service, production, Government and education

(Claver et al., 2003; Hansson and Klefsjo, 2003; Seetharaman et al., 2006). Therefore, the necessity of

understanding of these obstacles is very much essential for successful implementation of TQM (Bhat and

Rajashekhar, 2009; Haines III and St. onge, 2012; Sila, 2007; Soltani et al.,2005a&b;Venkatraman,2007). A

comprehensive list of 25 distinct TQM obstacles is prepared through an extensive literature review. This comprehensive list is presented in Table 1.

Table 1. A comprehensive list of TQM obstacles in the TQM literatures.

No Barriers References

1 Lack of top-management

commitment

Bhat and Rajashekhar (2009), Venkatraman (2007), Soltani et al.

(2005), Mosadegh Rad (2005), Jun et al. (2004)

2 High turnover at management level Jun et al. (2006), Soltani et al. (2005), MosadeghRad (2005),Jun

et al. (2004)

3 Attitude of employees towards

quality

Helms and Mayo (2008), Mosadegh Rad (2005)

4 Lack of proper training and

education

Bhat and Rajashekhar (2009), Jun et al. (2004), Huq (2005),

Soltani et al. (2005), Mosadegh Rad (2005),

5 Lack of coordination between

department

Amar and Zain (2002), Salegna and Fazel (2000), Al-Zamany et al.

(2002)

6 Human resource barrier Bhat and Rajashekhar (2009), Jun et al. (2004),

Venkatraman (2007), Mosadegh Rad (2005),

7 No benchmarking Bhat and Rajashekhar (2009), Jun et al. (2004)

8 Poor planning Bhat and Rajashekhar (2009), Jun et al. (2004), Mosadegh Rad

(2005)

9 Employee’s resistance to change Bhat and Rajashekhar (2009), Jun et al. (2004), Venkatraman

(2007), Soltani et al. (2005).

10 Inadequate use of empowerment Bhat and Rajashekhar (2009), Jun et al. (2004), Mosadegh Rad

(2005).

11 Lack of continuous improvement

culture

Huq (2005), Mosadegh Rad (2005)

12 Lack of communication Helms and Mayo (2008), Huq (2005), Mosadegh Rad (2005)

13 Complexity of process Gallacher (1991), Juran (1993), Juran and Gryna (1993)

14 Lack of customer satisfaction Kanji and Asher (1993), Wilkinson et al. (1994)

15 Lack of supplier partnership Kanji (1996), Soltani et al. (2005b), Gijo and Rao (2005)

16 Bureaucracy or Structural rigidity Gallacher (1991), Soltani et al. (2005b), Gijo and Rao (2005)

Cândido and Santos (2011)

17 Lack of effective appraisal system Juran (1993), Kanji (1996), Soltani et al. (2005b),


18 Lack of cross-functional teamwork Cândido and Santos (2011), Gallacher (1991), Kanji (1996), Gijo and Rao (2005)

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No Barriers References

19 Limited resources Soltani et al. (2005b), Cândido and Santos (2011)

20 Inadequate information systems Juran and Gryna (1993), Cândido and Santos (2011), Soltani et al.

(2005b)

21 Inadequate or poor leadership Juran (1993), Kanji (1996), Soltani et al. (2005b), Gijo and Rao

(2005).

22 Lack of time, work overloads Cândido and Santos (2011), Gijo and Rao (2005).

23 Lack of knowledge about quality

cost

Gallacher (1991), Juran (1993), Juran and Gryna (1993), Kanji and

Asher (1993), Kanji (1996), Soltani et al. (2005b), Gijo and Rao

(2005).

24 Inadequate monitoring of processes

improvement

Gallacher (1991), Soltani et al. (2005b), Gijo and Rao (2005)


25 Lack of effective controlling of processes

Kanji (1996), Soltani et al. (2005b), Gijo and Rao (2005), Cândido and Santos (2011)

2.1 Obstacles of TQM implementation in various countries other than Bangladesh Bhat and Rajashekhar (2009) have reported 21 obstacles that are faced by the managers during implementation of

TQM in Indian industries. Their studies are aimed at to understand the barriers followed by a survey of quality

award winning industries in India. Further, a study by Candido and Santos (2011) has identified 22 barriers that

organization might have experienced during TQM implementation. The survey is conducted to access to which

extent the TQM is harder to implement compared to other strategies. Their analyses suggest that there is no ground

to assume that TQM is more difficult to implement than other business strategies. Jun et. al., (2004) examined some

obstacles that the Mexico’s Maquiladora industry experience and compared their findings with similar research on US industries. The findings suggest that, the most important barriers in Maquiladora industry is ”high employee

turnover”.

Again the study conducted by Amar and zain (2002), have listed 11 obstacles that are experienced by the managers

of Indonesian manufacturing firms. The most important barriers are: lack of human resources, resistance to change

organizational culture and attitude towards quality, lack of information and so on. Gunasekaran (1999) has arranged

interview of several employees working at different areas in manufacturing firms in UK. He has given emphasis on

investigating the enablers of TQM implementation empirically. his investigation reveals that, the most important

enabler is poor communication among the departments.

2.2 Obstacles of TQM implementation in Bangladesh TQM philosophy is new for the managers of Bangladeshi firms (Akhter, 2015; Rahman and Masud, 2011; Seddiqe

and Basak, 2014). An extensive literature review suggested that, no study has been conducted to empirically

investigate the obstacles to implement TQM in this sector. It is essential to identify the barriers of TQM in order to

increase its success rate of implementation (Jaeger and Adair, 2016; Ng et al., 2014; Rasid and Taibb, 2016; Wang

et al., 2012).

2.3 Research gap Based on the previous literature review, we have identified two important research gaps. First, no study has been

conducted to investigate TQM obstacles in RMG sector in Bangladesh. Second, no significant model has been developed so far to empirically investigate the TQM barriers in this sector.

To address the research gaps, we have established a model to empirically examine some common obstacles present

in this sector.

3. Research framework and hypothesis developmentDevelopment of a framework is a primary task in each empirical study. We have gone through different models

proposed by the several researchers (Aamer et. al., 2017; Dubey, 2015; Jayram et al.,2010; Koh and Low 2010; Shahin and Dabestani, 2011; Zeng et. al., 2015). As there is no significant model present in this sector, we have find

out the elements of this model as per extant literature review and expert’s opinion. We discussed our model with

five experts of which three from industrial and two from academic. We simply used direct linkage model in this

situation. Our proposed model is shown in the Figure 1. To validate the proposed model, the following hypothesizes

are developed..

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Lack of top management

commitment

Lack of customer focus

Lack of continuous

quality improvement

Lack of quality

management practice

Lack of knowledge

about the cost of quality

TQM implementation

Figure 1. Our proposed model.

3.1 The effect of top management commitment on TQM implementation In most of the cases, the top management feels that, quality is a less important activity than finance, production, and

marketing (Balding, 2005; Harrington and Williams, 2004; Jacobsen, 2008). As a result, they are less committed to

quality. They do not take initiative to make long –term strategy for quality improvement. They simply ignore the

importance of sending their employees for quality training on regular basis (Abdullah, 2010; Ali et al., 2010; Das et

al., 2011; Zelnik et al., 2012). For this reason, the improvement of quality culture is greatly hampered. As per

literature, top management commitment plays a great role in the success of TQM implementation. We have built our

hypothesis:

H1: Top management commitment to quality has a positive role on TQM implementation.

3.2 The effect of customer focus on TQM implementation To bring long-term profit, it is essential to focus on customer-centered business (Mosadeghrad, 2006; Wakefield et

al., 2001). The main principle of customer-centered business is to satisfy the customers by quality products. Very

few firms are doing this kind of business; but in most of the cases, the firms have no idea about this business, even

they have no customer feedback system in their organization (Baird et al., 2011; Gimenez et al., 2013). Beside this,

they actually fears to receive customer complains (Fu et al, 2015). As a result, the firms are not able to satisfy their

customers anymore and finally they are losing their business. The key component of TQM is to make an endless

effort for maintaining the quality of the product (Sila, 2007). Therefore, TQM can help a business organization to do

their customer centered business. As per literature, the customer focus plays a significant role on TQM implementation. Our hypothesis is:

H2: Customer focus has a positive role on TQM implementation.

3.3 The effect of continuous quality improvement practice on TQM implementation Many firms have lost their business due to their ineffective plan for continuous quality improvement (Mosadeghrad,

2005) But, quality is considered as the best way for fighting against competitive business environment (Raja et al.,

2007; Seetharaman et al., 2006). In order to build continuous quality improvement culture, an integration of tools,

techniques, and training is very much essential. This right integration will ensure the improvement of operations in

all disciplines of a firm. Three elements of continuous improvement are process improvement, total involvement, and customer focus. They are also the three best principles of TQM. To establish a continuous quality improvement

culture, it is essential to implement TQM practices in the organization. As per literature, continuous quality

improvement culture plays a significant role on TQM implementation. Our hypothesis is:

H3: Continuous quality improvement has a positive role on TQM implementation.

3.4 The effect of quality management practice on TQM implementation The main aim of a quality management system is to ensure that organization will provide right quality of product

according to the need of the customer (Hamidi and Zamanparvar, 2008; Kozak et al., 2007; Mosadeghrad, 2005).

This can be achievable through regular and strict practice of quality management system (Chan and Ho, 1997; Francois et al., 2003; Hamidi and Zamanparvar, 2008; Oakland, 2011). In other word, quality management system is

a set of requirements to ensure quality to the customers (Dahlgaard-Park, 2012; Zehir and Sadikoglu, 2012). Any

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quality management system is considered as subset of TQM because; there are a lot of philosophical similarities

between them (Mosadeghrad, 2005; Psychogios and Priporas, 2007; Soltani et al.,2005a&b). For example, there are

eight philosophical similarities between ISO 9001:2008 and TQM. They are customer focus, leadership, people

involvement, process improvement, system approach to management, continuous improvement, factual approach in

decision-making, better supplier relationship. Therefore, practice of any quality management system helps to implement TQM easily. As per literature, quality management practice plays a significant role on TQM

implementation. Our hypothesis is:

H4: Quality management practice has a positive role on TQM implementation.

3.5 The effect of quality cost knowledge on TQM implementation Philip Cosby has defined cost of quality as awareness tool of quality importance. The cost of quality is divided into

four categories (Abd-Manaf, 2005;Jain, 2013; Shortell et al., 1995; Zabada et al., 1998). They are prevention,

appraisal, internal failure, external failure cost. The cost of quality has a significant impact on achievement of

organizational goal because the cost of poor quality is alarming. It is usually near about 10 to 15 % of total operational cost (Francois et al., 2003; McNulty and Ferlie, 2002; Tari et al., 2010). So, the knowledge of quality

cost analysis will create an opportunities to identify quality problems and saving the resources involved in poor

quality activities (Mosadeghrad, 2006; Valenstein et al., 2004). The objective of TQM is “Do the right things, right

the first time, every time”. Thus, a good quality management system will make TQM practice effective and

subsequently reduce the risk of cost of poor quality. As per literature, the knowledge about the quality cost plays a

significant role on TQM implementation. Our hypothesis is:

H5: Knowledge on quality cost has a positive role on TQM implementation.

4. Research methodology

4.1 Survey questionnaire A set of questionnaire are placed to the quality managers of some selected RMG firms in Bangladesh through e-mail

and fax. During the formulation of questionnaire, we have gone through the papers of several authors (Jayaram et. al., 2010; Mosadeghrad ,2013; Tari et. al., 2007; Valmohammadi, 2011;Zhang et. al., 2000). The questionnaire

consist of two sections.

First section: This section consists of 15 questions regarding the top management on quality, customer focus, and

continuous quality improvement. Five point Likert scale is used to measure the opinion of respondents (where,

strongly disagree = 1 and strongly agree = 5).

Second section: This section consists of 10 questions regarding the quality management system and knowledge

about the cost of quality. Five point Likert scale is used to measure the opinion of respondents (where, strongly

disagree = 1 and strongly agree = 5).

4.2 Contend validity of questionnaire Twenty-five questionnaires are used to determine the TQM barriers. Five items are measured for each construct.

Five senior experts have reviewed our final questionnaires. We have used multi-item measurement system to

increase reliability. Therefore, extensive literature review and expert’s opinion have ensured the content validity

issue of the study (Hair et. al., 2006). A comprehensive list of six constructs (i.e. five constructs for TQM obstacles

and one constructs for TQM implementation) with their measuring instrument is shown in Table 2 with supportive

literature.

Table 2. Constructs with factor loading, Chronbatch’s alpha, Average Variances Extracted (AVE), Composite

Reliability (SCR), Variance Inflation Factors (VIF). Scales Items Factor

loadings

VIF p-value

Top management

commitment Chronbatch’s alpha 0.636, SCR 0.758, AVE 0.413,

VIF 1.135

Shortage of time 0.793 1.171 <0.001 Lack of long-term planning 0.795 1.586 <0.001 Poor communication 0.715 2.092 <0.001 Lack of information system 0.807 1.313 <0.001 Employee’s resistance to change culture 0.938 1.215 <0.001

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Scales Items Factor

loadings

VIF p-value

Customer focus

Chronbatch’s alpha 0.889, SCR 0.953, AVE 0.689, VIF 1.734

Lack of customer satisfaction 0.678 1.217 <0.001 Lack of customer feedback system 0.855 1.277 <0.001 Poor customer relationship 0.843 1.357 <0.001 Poor controlling of customer feedback system 0.774 2.656 <0.001 Lack of training on customer feedback system 0.637 1.636 <0.001

Continuous quality

improvement practice

Chronbatch’s alpha 0.823, SCR 0.859, AVE 0.598, VIF 2.263

Lack of Continuous improvement culture 0.850 2.225 <0.001 Lack of processes improvement monitoring 0.703 1.418 0.007 Lack of cross-functional teams 0.809 2.835 <0.001 Resistance to change culture 0.803 2.309 <0.001 Lack of empowerment of employees 0.985 1.175 <0.001

Quality management

practice Chronbatch’s alpha 0.753,

SCR 0.836, AVE 0. 495, VIF 1.763

Lack of financial support 0.853 1.530 <0.001 Lack of sufficient physical resources 0.567 1.196 <0.001 Excessive paper work 0.722 1.853 <0.001 Lack of employee training. 0.889 1.351 <0.001 Using quality management certificate for business purpose 0.873 1.310 <0.001

Knowledge on cost of

quality Chronbatch’s alpha 0.725, SCR 0.779, AVE 0. 423,

VIF 1.308

Lack of knowledge about quality cost 0.703 2.375 <0.001 No benchmarking of current process 0.669 1.944 <0.001 Lack of identification of quality problems 0.784 2.331 <0.001 Inappropriate use of resources 0.861 1.659 <0.001 Management turnover 0.791 1.795 <0.001

TQM implementation Chronbatch’s alpha 0.788, SCR 0.872, AVE 0. 596, VIF 1.134

Customer satisfaction 0.841 1.484 <0.001 Employee job satisfaction 0.898 2.953 <0.001 Continuous quality improvement 0.922 2.574 <0.001 Participation in team work 0.929 2.011 <0.001 Communication improvement 0.931 1.437 <0.001

4.3 Sample The database of Bangladesh Garment Manufacturers and Exporters Association, BGMEA, 2015-2016 has been used

for this study. According to the information provided by BGMEA, there are 4300 RMG firms in Bangladesh. A

sample size of 355 firms are selected by Yamme’s formula (1967) with a confidence level of 95%. Hair et. al., 2006

supports that 150 sample size is satisfactory for confirmatory factor analysis (CFA) (Braunscheidel and Suresh,

2009; Schoenherr and Mabert, 2011). Table 3 shows the respondent profile.

Table 3. Respondent profile.

Different levels of management Response rate in Percentage

1. Top management 12.2

2. Middle management 32.5

3. Bottom management 55.3

4.4 Survey method and data collection Split survey methodology has been used for this study (Podsakoff et. al., 2003; Dillman, 2007). We have randomly

chosen 150 RMG firms from the comprehensive list of BGMEA in 2016. 100 out of 150 firms has participated in

this questionnaire survey. Finally, the overall response rate is found 100/150=66% which is adequate for the study

purpose because non-response bias test says that there is no response bias in this survey.

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4.5 Non-response bias test The impact of the non-response bias has been checked (Chen and Paulraj, 2004). For this purpose, 35% of early

replay is compared with its analogous late replay in sample group by chi-square test. It is found that; chi-square test gives a satisfactory result which indicates that this study has passed out the non-response bias issue.

5. Data Analysis and discussion

5.1 Descriptive statistic Calculation of variance, normality, and outliers have been performed on the data set to evaluate the variability in

measuring instruments. Maximum absolute value of skewnes and kurtosis are calculated 1.3 and 4.215

correspondently. It is well within limit found in the previous studies (Curran et.al., 1996; Stevens, 1984; Cohen et

al., 2003). Further p-value for Mardia’s (1970) coefficient is calculated more than 0.05, which indicates the presence

of multivariate normality (DeCarlo, 1997).

5.2 Factor analysis In factor analysis, variables are grouped into factors on the basis of their common correlations. For our study we

proposed principle component analysis method with varimax rotation to extract six latent factors (Eigen value

greater than 1). Adequacy of sample size for factor analysis is ensured by Kaiser-Mayer-Oklin (KMO) value which

is found 0.68. It indicates that 68% of total variance is explained by the six latent factors. As 25% of total variance is

explained by the first factor, there is no common bias issue in this study. Table 2 represents the factor loading,

Chronbatch’s alpha, Average Variances Extracted (AVE), Composite Reliability (SCR), Variance Inflation Factors (VIF) for each construct. To test the reliability of questionnaire with measuring scale, reliability co-efficient such as

Chronbatch’s alpha is commonly used (Nunnaly, 1978). The value of Chronbatch’s alpha in all cases is found well

above the critical limit (i.e. 0.6). Therefore, the latent constructs confirms the convergent validity test (Fornell and

Larcker, 1981). Table 4 represents the discriminant validity matrix. From Table 4 it is found that, values in column

under each diagonal element are not greater than the diagonal value (square root of AVE for each latent construct).

Therefore, this model confirms the discriminant validity test (Fornell and Larcker, 1981). Finally, the current model

fulfill the criteria of good model fit.

Table 4. Discriminant validity matrix. Top

management

commitment

Customer

focus

Continuous

quality

improvement

practice

Quality

management

practice

Knowledge

on cost of

quality

TQM

implementation

Top management commitment 0.645 Customer focus 0.071 0.823 Continuous quality improvement

practice 0.063 0.631 0.741

Quality management practice 0.128 0.401 0.610 0.682 Knowledge on cost of quality 0.254 0.010 0.236 0.321 0.621 TQM implementation 0.241 0.062 0.028 0.091 0.228 0.751

5.3 Hypothesis testing Structural Equation modeling (SEM) technique is used to test the hypothesis (Gupta and Misra, 2016). Some indices

are used to determine the good model fit of structural model which are summarized in Table 5. All hypothesizes are

found statistically significant which are shown in Table 6.

Table 5. Model fit indices

Index Value Acceptable range

Average path coefficient (APC) 0.157 at p=0.002 p<0.001

Average R-squared (ARS) 0.218 at p<0.001 p<0.001

Average block VIF (AVIF) 1.163 acceptable if 5, ideally 3.3

Table 6. Structural equation modeling analysis and support of hypothesis.

Hypothesis VIF p-value Support

H1: Top management commitment TQM implementation 0.215 1.135 p<0.001 yes H2: Customer focus TQM implementation 0.135 1.734 p=0.012 yes

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H3: Continuous quality improvement practice TQM implementation 0.226 2.263 p=0.010 yes H4: Quality management practice TQM implementation 0.326 1.763 p<0.001 yes

H5: Knowledge on cost of quality TQM implementation 0.145 1.308 p<0.001 yes

The first hypothesis is statistically significant at . The value is 0.215. This hypothesis suggests that, the

managers of Bangladeshi RMG firms are spending less time on quality improvement activities. As a result, log term

strategy for quality improvement is always neglected in this sector. Further, the quality improvement policy is not

well communicated through the organization. This finding is also supported by some previous studies (Balding,

2005; Harrington and Williams,2004; Jacobsen, 2008; Mosadeghrad, 2006; Matherlyand Lasater, 1992; Wakefield

et al., 2001).

The second hypothesis is statistically significant at . The value is 0.135. This hypothesis suggests that,

the majority of the RMG firms claim to give customer service, but in reality, they are focusing much on operations

rather than customer. These type of firms spend less time for building relationship with customer. For an example

60% of them have not adequate customer feedback system. This finding is further supported by several past

literatures (Boselie and Wiele, 2002).

The third hypothesis is statistically significant at . The value is 0.226. This hypothesis suggests that,

most of the firms possess different quality management certificates, but actually they are not practicing accordingly.

Unfortunately, they are using this opportunity for marketing purpose rather than continuous quality improvement.

Besides this, the management people are gradually losing their interest on quality improvement practice because of

excessive paper work. Several researchers also have supported this finding (Mosadeghrad, 2005; Raja et al., 2007;

Seetharaman et al., 2006; Valmohammadi, 2011).

The fourth hypothesis is statistically significant at . The value is 0.326. This hypothesis suggests that,

lack of co-operation among the several departments of a firm hampers to build up continuous quality improvement

culture in an organization. Another important reason for the failure of quality culture is the poor mind-setup of the

management people to give importance on process improvement. This finding is further supported by several past

literatures (Balding, 2005; Francois et al., 2003;Hamidi and Zamanparvar, 2008;Jacobsen, 2008; Kozak et al., 2007).

The fifth hypothesis is statistically significant at . The value is 0.145. This hypothesis suggests that,

the majority of the RMG firms fail to identify the quality related problems at the early stage of production process.

As a result, resources are being used to produce poor quality product and incur loss due to cost of poor quality. This

finding further supports the argument of previous studies (Francois et al., 2003; Mosadeghrad, 2006; McNulty and

Ferlie, 2002; Valenstein et al., 2004).

6. ConclusionA survey is conducted in some selected RMG firms in Bangladesh. This survey results are described in this study. A test on reliability and validity are performed on survey instruments and are found satisfactory. The results reviles

that all five obstacles mentioned in the previous discuss have positive influence on TQM implementation in RMG

sector in Bangladesh. They are lack of top management commitment, customer focus, continuous quality

improvement practice, quality management practice, and knowledge about the cost of quality.

6.1 Contribution of the study This study can contribute a lot to those firms that are planning for TQM implementation by shearing the unavailable

experience learnt during the survey on RMG sector in Bangladesh. On other word, the manager of a firm gives much

attention on these five obstacles; it will help to improve the success rate of TQM implementation.

6.2 Limitations and future research There are some limitations of our study. First, the response rate, it is not poor but need to be improved. Second,

accuracy of data, the interviewees are asked to response on their perceive thinking. But in reality, a small portion of

interviewees (top management only) has not given perceive data. Actually it is very difficult to overcome such

situation. Third, survey result, it is based on the context of Bangladeshi RMG sector. Therefore, these findings can

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not be conveyed directly to other sectors, because these obstacles occur to varying degree with frequency in the

context of different types of firms.

It is necessary to perform the replication of this study in other sectors in order to examine whether these obstacles

are present in that sector. There is another scope of integrating different organizational theories with this model so

that the organization can obtain more knowledge from the investigation of new TQM obstacles.

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Biographies

Subrata Talapatra, serving as an Assistant Professor in the department of Industrial Engineering and Management

of Khulna University of Engineering & Technology. He obtained his B.Sc. in Mechanical Engineering from Rajshahi University of Engineering & Technology and M.Sc. in Industrial Engineering and Management from

Khulna University of Engineering & Technology. His areas of research are Statistical Quality Control, Ergonomics,

Operation Research, and 3d-Drawing. He is also a member of Institution of Engineers (Bangladesh) and IEOM.

Md. Kutub Uddin, graduated in Mechanical Engineering from Bangladesh University of Engineering and

Technology (BUET), Bangladesh in 1982. He obtained his M.Eng. Degree in Industrial Engineering and

Management from Asian Institute of Technology (AIT), Bangkok, Thailand in 1986. He received his Ph.D. degree

in Industrial and Management Engineering from Indian Institute of Technology (IIT), Kanpur, India in 1996. He is a

professor in the department of Mechanical Engineering, Khulna University of Engineering and Technology,

Bangladesh. His research topics mainly focus on design of cellular manufacturing systems, supply chain

management, warehouse design, and quality management. He is an active member of IEB, AITAA, and IITKAA.

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Some obstacles that affect the TQM implementation in … · 2018-02-12 · TQM, they become familiar with some obstacles that hinder the TQM implementation. As a result, this RMG