Introduction Paper

Identification and prioritization of barriers to total quality

management implementation in service industry

An analytic hierarchy process approach Faisal Talib

Mechanical Engineering Section, University Polytechnic, Faculty of Engineering and Technology, Aligarh Muslim University,

Aligarh, India, and Zillur Rahman

Department of Management Studies, Indian Institute of Technology Roorkee, Roorkee, India

Abstract Purpose – Despite the potential benefits of total quality management (TQM) articulated by quality experts and practitioners, these benefits are not easy to achieve in practice. Many service industries have found difficult to implement TQM successfully. The present study investigates and categorizes the barriers to a successful implementation of TQM program in the service industry. The purpose of this paper is to understand TQM barriers and prioritize their relative importance by ranking them in the service industry. Design/methodology/approach – Based on previously published literature on TQM barriers in service industry and after discussions with quality experts, this study utilizes a set of 12 barriers to TQM as identified by the authors of TQM barriers to accomplish the objectives of the present study. The 12 barriers were divided into three categories. These barriers were prioritized and ranked using an analytic hierarchy process (AHP) approach, a multi-criteria decision-making process. Findings – In this research, the category “managerial issues” was found to be the most important, followed by “people-oriented issues” and “organizational issues” based on their priority weights. The results have also highlighted that the barrier “lack of communication” was the most significant among all the other barriers. It was followed by “lack of top-management commitment,” “employee’s resistance to change,” and “lack of coordination between departments.” The least significant barrier was “high turnover at management level.” Practical implications – The study ranks the barriers, from the most important to the least important, which will allow managers and practitioners in the service industry to decide which barriers they need to pay attention to and work on for a successful implementation of TQM. Originality/value – The strength of this study is the development of a comprehensive model for the investigation and prioritization of barriers that the service industry experiences when implementing a TQM program. Presenting TQM barriers in the form of AHP-based model and categorizing barriers is a new effort in the area of TQM. Keywords Total quality management, Analytic hierarchy process, Prioritization, Service industry, Lack of communication, TQM barriers Paper type Research paper

1. Introduction Studies on total quality management (TQM) have shown a rise of interest due to various reasons: success in the world market, improved business performance, better customer service, solutions that best suit the company, its continuous development and

The TQM Journal Vol. 27 No. 5, 2015

pp. 591-615 © Emerald Group Publishing Limited

1754-2731 DOI 10.1108/TQM-11-2013-0122

Received 29 November 2013 Revised 11 March 2014

29 May 2014 Accepted 28 August 2014

The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/1754-2731.htm

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it acts as a sustainable alternative to other approaches. There are many more examples that could be listed. In the past two decades, TQM has enjoyed a great popularity in all types of industries, but a recent trend shows it has a greater impact on service industries like healthcare, hospitality, banking and information technology (IT) and information systems (ISs) (Talib et al., 2012a, 2011f ). Antony et al. (2002) and Lewis et al. (2005) have argued that following a TQM program leads to improved employee involvement and communication while Corbett and Rastrick (2000) asserted that TQM promotes continuous improvement and innovation. Similarly, Prajogo and Sohal (2006, 2003) and Arumugam et al. (2008) found that TQM implementation enhances the quality performance of the industry, which was also supported by Talib et al. (2013) in their study on service industries. Yang (2006) reported that the implementation of TQM significantly effects customer satisfaction by analyzing their needs on a continual basis. Furthermore, Talib et al. (2011d) assess in their empirical study on the awareness of TQM in Indian service industries that service managers have shown a strong familiarity with TQM concepts and practices and they believe that TQM is a way of guaranteeing high-quality products and services.

While there are many other success stories about TQM (Chen, 2013; Vanichchinchai and Igel, 2011; Sila, 2007; Grover et al., 2004; Talib et al., 2011d, a; Talib et al., 2012b; Talib et al., 2010; Talib and Rahman, 2010), the majority of the TQM adopters have reported no tangible or marginal improvements in productivity, competitiveness or financial returns (Huq, 2005). Some studies have even found that TQM implementation programs have failed to achieve any positive results (Talib, 2013; David and Strang, 2006; Huq, 2005; Soltani et al., 2005). Furthermore, the difficulties of implementing TQM are even higher in the service industries because of its special characteristics (Ennis and Harrington, 1999). The literature provides enough evidence on the difficulties in the service industries. For instance, Huq and Martin (2000) reported a 60-67 percent failure rate for TQM implementation in the service industry. While Burrows (1992), Bak (1992), Brown (1993) and Rigby and Bilodeau (2007) have reported 95, 80, 65 and 70 percent failure rates, respectively. These findings pose the question: what are the barriers that effect the implementation of a TQM program? In particular, the importance of identifying the major barriers for implementing TQM is frequently mentioned in literature (Chang, 2006; Talib et al., 2011f, c; David and Strang, 2006). Many reasons have been given for the failure of TQM with cited reasons in the literature. Researchers found that the barriers often hindered the proper implementation of TQM and have negatively affected the desired outcomes. As a result, many TQM initiatives have been abandoned, ignored or declared a failure.

While only a few empirical studies have focussed on the identification and analysis of barriers to TQM implementation (Sebastianelli and Tamimi, 2003; Talib et al., 2011c; Bhat and Rajashekhar, 2009; Mosadegh Rad, 2005) in the service industry, a study on the identification and prioritization of TQM barriers in the service industry is at a nascent stage. There is an emerging need to prioritize the relative importance of these TQM barriers so quality mangers and decision makers can understand them and proper care may be taken to minimize these barriers. Further, the present literature also revealed that no study has been undertaken to identify and rank TQM barriers using a multi-criteria decision-making (MCDM) technique like the analytic hierarchy process (AHP) methodology. The AHP provides a framework to cope with multiple criteria situations involving intuitive, rational quantitative and qualitative aspects (Alberto, 2000; Briggs and Tolliver, 2012).

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In order to overcome this gap using the given information, the present study utilizes an AHP approach for determining the relative importance of the barriers to TQM implementation in the service industry. For this purpose, the following objectives have been designed:

• to investigate and categorize the TQM barriers of service industry; and • to prioritize the relative importance of these TQM barriers which could serve

as invaluable lesson to those service industries that are planning to implement TQM or are in the process of its implementation.

The next section discusses the literature review for the identification and categorization of TQM barriers. It is followed by a discussion on the AHP methodology and its relative importance to the barriers for TQM implementation, which is determined via the AHP approach. Finally, the results and a discussion, and the implication of the research findings are discussed, which are followed by the conclusion and scope for future research.

2. Literature review Despite the fact that the critical success factors (CSFs) responsible for a successful implementation of TQM in service industries have helped to achieve the desired results, namely, it increased the firms’ performance, productivity, and improved customer satisfaction, practicing and implementing TQM CSFs are not free from barriers (Talib et al., 2011c). The present literature review identifies the TQM barriers that need to be addressed for the successful implementation of TQM in the service industry, which influences business performance and customer service. Based on previously published literature on the TQM barriers (Talib et al., 2011f, c, b) and several discussions with academia and quality experts in the service industry, 12 barriers were identified. These 12 barriers were utilized by Talib et al. (2011f, c, b) in their studies on the identification and classification of TQM barriers for the service industry that frequently occurred in TQM literature. The 12 barriers are: attitude of employees toward quality; employee’s resistance to change; high turnover at management level; human resource barrier; inadequate use of empowerment and teamwork; lack of communication; lack of continuous improvement culture; lack of coordination between department; lack of proper training and education; lack of top-management commitment; no benchmarking; and poor planning. Table I presents the 12 identified barriers from TQM literature (Talib et al., 2011f, c, b) and were adopted for further study. These barriers can serve as an invaluable lesson to organizations planning to implement TQM or are in the process of its implementation (Talib et al., 2011c, b). After critically reviewing the nature and structure of the 12 TQM barriers, they were grouped into three barrier categories: people-oriented issues; managerial issues; and organizational issues. Thus, this study has a wide coverage of the major TQM barriers.

2.1 Identification of barrier categories and TQM barriers in service industry 2.1.1 Barriers based on people-oriented issues. People-oriented issues are defined as issues that are significant for the successful introduction and integration of TQM in the service industry, since it requires employee involvement, commitment, teamwork and empowerment (Bhat and Rajashekhar, 2009). People-oriented issues in service industries are the lack of human resources and a non-availability of continuous training programs (Ngai and Cheng, 1997) in the organization. Moreover, these issues influence

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other linking issues and critically affect the success of quality improvement programs in the organization. There are four barriers to TQM in this category:

(1) “Lack of proper training and education” in people-oriented issues is crucial since it exists at all levels of an organization and is a major contributor to employees’ resistance (Whalen and Rahim, 1994). It was reported that a lack of proper training and education might become a major barrier in the development and implementation of a quality program. The causes of this barrier are insufficient training on advanced quality tools and techniques, a lack of training in problem identification and problem solving techniques, and management-related training were absent or low.

Barrier no. Barrier name Author(s)

1. Attitude of employees toward quality

Amar and Zain (2002), Helms and Mayo (2008), Mosadegh Rad (2005), Salegna and Fazel (2000), Tamimi and Sebastianelli (1998)

2. Employee’s resistance to change

Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Jun et al. (2004), Whalen and Rahim (1994), Venkatraman (2007), Soltani et al. (2005), Newall and Dale (1990)

3. High turnover at management level

Amar and Zain (2002), Jun et al. (2004), Tamimi and Sebastianelli (1998), Soltani et al. (2005), Mosadegh Rad (2005), Teagarden et al. (1992), Dowlatshahi (1998), McDermott (1994)

4. Human resource barrier Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Amar and Zain (2002), Jun et al. (2004), Whalen and Rahim (1994), Venkatraman (2007), Ljungström and Klefsjö (2002), Mosadegh Rad (2005), Newall and Dale (1990)

5. Inadequate use of empowerment and teamwork

Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Jun et al. (2004), Gunasekaran (1999), Whalen and Rahim (1994), Ljungström and Klefsjö (2002), Mosadegh Rad (2005), Salegna and Fazel (2000), Adebanjo and Kehoe (1998), Newall and Dale (1990)

6. Lack of communication Al-Zamany et al. (2002), Helms and Mayo (2008), Huq (2005), Mosadegh Rad (2005), Salegna and Fazel (2000), Tamimi and Sebastianelli (1998)

7. Lack of continuous improvement culture

Al-Zamany et al. (2002), Amar and Zain (2002), Whalen and Rahim (1994), Huq (2005), Mosadegh Rad (2005)

8. Lack of coordination between department

Amar and Zain (2002), Gunasekaran (1999), Salegna and Fazel (2000), Tamimi and Sebastianelli (1998), Al-Zamany et al. (2002)

9. Lack of proper training and education

Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Jun et al. (2004), Rajashekhar (1999), Liu (1998), Whalen and Rahim (1994), Huq (2005), Ljungström and Klefsjö (2002), Soltani et al. (2005), Mosadegh Rad (2005), Tatikonda and Tatikonda (1996), Adebanjo and Kehoe (1998), Newall and Dale (1990)

10. Lack of top-management commitment

Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Jun et al. (2004), Whalen and Rahim (1994), Liu (1998), Venkatraman (2007), Ljungström and Klefsjö (2002), Soltani et al. (2005), Mosadegh Rad (2005), Salegna and Fazel (2000), Brigham (1993), Kanji (1996), Newall and Dale (1990)

11. No benchmarking Al-Zamany et al. (2002), Rajashekhar (1999), Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Jun et al. (2004)

12. Poor planning Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Jun et al. (2004), Whalen and Rahim (1994), Mosadegh Rad (2005), Salegna and Fazel (2000), Newall and Dale (1990)

Source: Talib et al. (2011d)

Table I. Identified barriers from TQM literature

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(2) A “human resource barrier” is another significant barrier to a successful TQM implementation. Newall and Dale (1990) found many quality departments were overloaded and understaffed, which leads to TQM failure. It includes absenteeism, non-conformance with the procedures, lack of skill and motivation, and low wages and salaries.

(3) “Employee’s resistance to change” is a common barrier that most organizations came across while implementing any quality improvement program. They consider TQM a controlling technique rather than an empowering approach. Mosadegh Rad (2005) found that employees perceive TQM as an approach that asked employees to work continuously with fewer rewards. This misconception regarding employee’s resistance to change can be minimized through a culture of team building and using employees’ ideas, suggestions, motivations and process improvement suggestions.

(4) “Inadequate use of empowerment and teamwork” proved a major barrier to the successful implementation of TQM. The success of TQM starts from employee participation at every level, involving them in strategic decisions that affects their performance and hence, the overall working of the organization. Further, studies in TQM found that the inadequate use of empowerment and teamwork in an organization is due to insufficient teamwork facilitators and team building techniques (Adebanjo and Kehoe, 1998). Therefore, it is important for teams to focus on these issues and use their time as efficiently as possible.

2.1.2 Barriers based on managerial issues. Managerial issues are critical for achieving the organization’s desired objectives and improving organizational performance. These issues are significant since they influence other connecting issues. Furthermore, the implementation of a quality management program itself requires a higher quality of management. Many of the barriers that hinder TQM efforts, such inadequate planning, poor organizational culture, poor communication and inadequate resources are linked to how effectively the quality management chain is managed. TQM implementation and its impact depend on the ability of managers to adopt its values and concepts in different industries. It requires a change in the thought, attitude, behavior and role of the management. There are five barriers to TQM in this category:

(1) “Lack of top-management commitment” is one of the major barriers in both the manufacturing and service industries (Beer, 2003). Top-management should be committed and fully involved in quality management initiatives and continuous quality improvement (CQI) programs. The degree to which employees adopt a TQM strategy will be contingent upon the degree to which top managers are involved and committed to TQM principles. Van der Wiele and Brown (2002) found that management-related issues are at the core of what affects the long-term sustainability of quality management. Lack of top-management commitment may originate from various reasons like a lack of experience and training, resistance to change, and a hesitation to initiate improvement programs.

(2) “Lack of coordination between department” is also one of the critical barriers that an organization experiences. Amar and Zain (2002) found that the culture and interdepartmental relations impede TQM. Further, weak internal communication within departments can cause a lack of coordination between departments leading to a major barrier to TQM implementation.

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(3) “No benchmarking” leads to a culture of lacking CQIs and competitiveness. This is one of the most important managerial issues and directly relates to the effectiveness of a TQM program. Organizations can achieve world-class status when benchmarking is directed at the key business processes. Some of the reasons for this barrier are when there are no targets or there is no attitude for attaining higher productivity and implementing the best practices of other organizations.

(4) “Poor planning” is the fourth major barrier under the managerial issue category. Whalen and Rahim (1994) revealed that the absence of strong strategic planning leads to ineffective quality improvement. It was observed that a large number of organizations are either unable or not willing to plan effectively for the improvement of quality. Therefore, careful and detailed planning is needed prior to the implementation of any quality program and organizations should study or identify beforehand the stages that their processes undergo (Talib et al., 2011c). The reasons for this barrier are not having a strategy or there have been no new developments, inadequate resources to effectively employ TQM, and vague quality action plans.

(5) “Lack of communication” is one of the most frequently mentioned reasons for TQM failure in the literature. The reason behind it is the working style of the management. Moghaddam and Moballeghi (2008) found that poor communication between departments within an organization and management attitudes toward staff are basic difficulties for developing a quality culture. Further, lack of communication across the organization often results in dissatisfied customers, unfulfilled customer requirements, an environment of mistrust, and no knowledge sharing.

2.1.3 Barriers based on organizational issues. Organizational issues are issues that reflect the culture, territorialism, organizational politics, high turnover, changes in key executives and the quality consciousness of the organization. It is argued that in order for TQM to be adopted successfully, the organizational issues must be clearly understood with the ability to sustain and nurture them. There are three barriers to TQM in this category:

(1) High turnover and absenteeism at the management level creates afflictions and nuisances in many organizations and hinder a successful implementation of TQM initiatives (Dowlatshahi, 1998; Talib et al., 2011c). Some of the basic explanations for failing to return to work as scheduled and absenteeism are structural problems, organizational hierarchies, leadership instability and ineffective employee selection practices as well as a lack of appraisal schemes (Talib et al., 2011f ).

(2) “Attitude of employees towards quality” is a big barrier, which critically affects the implementation of quality program in an organization. Numerous studies have shown that the attitude of employees toward quality such as: non-participation of employees, low level of knowledge and experience about TQM, lack of work discipline, lack of teamwork, resistance and disregard of the quality guidelines, lack of culture and geographic homogeneity, do not easily accept advanced quality training and education. In addition, changing employees work habits, and the lack of motivation are barriers to successfully implementing TQM

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(Mosadegh Rad, 2005). Employees have to understand and accept that quality tools and techniques enhance productivity, profitability and employee performance, and ultimately customer satisfaction (Talib et al., 2011c).

(3) The “lack of a continuous improvement culture” in the organization leads to the total failure of a TQM program. TQM stands mainly on the culture, attitude and continuous improvement of quality throughout the organization and aims to provide its customers with products and services that satisfy their needs and expectations. The culture requires quality in all aspects of the organization’s operations, with things being done right the first time and every time (Mosadegh Rad, 2005). The reasons behind this barrier are the failure to create a sense of CQI, urgency among employees, and inadequate rewards and incentives (Talib et al., 2011f ).

3. AHP methodology The literature on qualitative studies has offered several well-presented methodologies that discuss ranking, identification, prioritization of factors and ways to develop relationships between them. These qualitative techniques are interpretive structural modeling, data envelopment analysis, structural equation modeling (SEM), technique for order preference by similarity to ideal solution, AHP, analytic network process (ANP), quality function deployment and many more. To accomplish the objectives of the present study, AHP has been considered for investigating and prioritizing the barriers to TQM implementation. The reasons behind selection of AHP are as follows:

• AHP is capable of handling a large number of criteria and sub-criteria competently (Law et al., 2006);

• AHP can accommodate both objective and subjective judgments and determine a priority among them (Saad, 2001);

• AHP can be applied to both tangible and intangible criteria based on the judgments of knowledgeable and expert individuals (Azizi and Azizpour, 2012);

• to solve a complex problem, researchers and academicians have made use of AHP in several different application areas, which have been published in peer-reviewed journals (Vaidya and Kumar, 2006);

• AHP is helpful for stakeholders and quality managers to enhance their business efficiency and service quality; and

• structuring of problems into criteria and sub-criteria levels leads to a systematic solution of problems (Singh et al., 2007).

Therefore, to deal with the present complex problem, the AHP approach will be best suited among the different methodologies available. Further, it was also observed from the extent literature that that no study has applied the AHP technique to identify and prioritize the barriers to TQM implementation in the service industry.

AHP is a MCDM technique developed at the Wharton School of Business by Saaty (1980) that allows decision makers to model a complex problem in a hierarchical structure showing the relationships of the objectives, categories, sub-categories and alternatives (Sarathy, 2013). Thus, a typical hierarchical structure is developed consisting of at least three levels: objectives, categories and sub-categories. The AHP methodology is extensively applied, focussing on different areas with different

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applications. Some of the key references of the AHP applications as reported in the literature are summarized in Table II.

The AHP is a method for breaking down a complex and unstructured situation into its component parts, then arranging those variables into a hierarchical order. This method is based on assigning numerical values for the subjective judgment of the relative importance of each variable, then synthesizing the judgments to determine which variables have the highest priority (Sarathy, 2013; Saaty, 1994). AHP has been a favorite decision technique for a variety of research fields (Table II), such as engineering, food, supply chain logistics, healthcare, government, mobile networks, new product development, management ISs and many others (Zopounidis and Doumpos, 2000; Garg et al., 2012; Singh, 2013).

Some of the software used, namely, Expert Choice and Super Decisions were developed to implement AHP but the present study adopted a computational approach that is simple to use and easy to understand (Singh, 2013). This approach uses the following steps to conduct the AHP study:

Step 1: define and state the objective clearly The objective of the study is to investigate and prioritize the barriers to TQM implementation experienced by service industries, in order to provide a better understanding for decision makers and managers about the barriers that are likely to hinder the implementation of an effective TQM program. This represents the first level of the hierarchy model.

Step 2: decompose the objective into lower level categories or sub-categories In this step, the objective of prioritization of the TQM barriers was decomposed into three barrier categories (second level of the hierarchy model) and 12 TQM barriers (sub-categories) also known as the third level of the hierarchy model, identified from literature to form a hierarchical structure of the multifaceted problem. The barrier categories consist of three issues. They are “people-oriented issues”; “managerial

Key references Focus area/issue

Varajão and Cruz-Cunha (2013) Selection of suitable managers for projects Singh (2013) Prioritizing the factors for coordinated supply chain Sarathy (2013) Determination of important factors that influence the TQM

practice in real estate industry Locatelli and Mancini (2012) Framework for the selection of the nuclear power plant Koilakuntlaa et al. (2012) Estimation of TQM factors rating to understand the degree of

business excellence for manufacturing and service organizations Garg et al. (2012) Prioritizing and ranking the critical success factors of customer

experience in banks Punniyamoorty et al. (2012) Development of a composite model using structural equation

modeling (SEM) and AHP for supplier selection Talib et al. (2011f) Prioritizing and ranking the TQM practices in service Industries Tsinidou et al. (2010) Evaluating and prioritizing the factors that determine quality in

higher education Chen and Chen (2009) TQM measurement model for the biotechnology industry Wong and Li (2008) Multi-criteria analysis of the selection of intelligent building systems Chan et al. (2006) Benchmarking logistics performance of the postal industry

Table II. AHP applications as reported in the literature

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issues”; and “organizational issues.” The sub-categories (TQM barriers) identified are the 12 barriers discussed in the literature review section. This decomposition of the hierarchy was performed until no further decomposition of sub-categories is possible.

Step 3: construct a hierarchy framework for analysis After the objectives related to the TQM barriers have been finalized, relevant and important categories and sub-categories of the TQM barriers were identified via Step 1 and 2. These categories and sub-categories were then structured into three levels starting from the overall objectives to the various stages and related sub-categories in a hierarchical descending order. Saaty (2000) proposed guidelines for structuring a hierarchy model for the prioritization of categories. Using these guidelines, an AHP framework was developed for facilitating the study, as depicted in Figure 1. This figure shows a three-level decision hierarchy incorporating different categories and sub-categories as discussed in Step 2.

Step 4: collection of information and data from experts After developing the AHP model, the next step was the collection of data that involved forming a team of experts and assigning pair-wise comparisons to the barriers categories and sub-categories used in the AHP method (Singh, 2013). These experts were chosen from various service industries and academia. In this study, a group of 15 experts who served as evaluators were identified and then interviewed in order to measure the categories and sub-categories (Crary et al., 2002). In this group of 15 experts, six were from academia and nine from various service industries, namely, IT (03); telecommunication (02); healthcare (02); banking (01); and hospitality (01). The figure within parenthesis indicates the number of experts chosen from each service industry. All 15 evaluators had

People- Oriented Issues

Managerial Issues

Organizational Issues

• Lack of proper training and education

• Human resource barrier

• Employee’s resistance to change

• Inadequate use of empowerment and teamwork

• Lack of top- management commitment

• Lack of coordination between department

• No benchmarking • Poor planning • Lack of

communication

• High turnover at management level

• Attitude of employees towards quality

• Lack of continuous improvement culture

Level A: Objective

Level B: Barrier Categories

Level C: TQM Barriers

Investigation and Prioritization of Barriers to TQM Implementation that Service Industries Experience

Figure 1. A hierarchy model of barriers to TQM implementation for

the AHP study

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more than ten years of experience in the field of quality management and service quality, and were responsible for managing quality improvement activities, particularly at the strategic level for their respective industries. They hold positions at the top and mid level in the industry and have a sufficient amount of knowledge on possible TQM barriers in the service industry. This implies that the group of experts represents the viewpoint and opinion of the service industry. They were able to evaluate the barrier categories and sub-categories and assign the relative importance to the categories and sub-categories in the AHP model. All the interviews involved personal visits or were conducted through video conferencing. In case of any confusion in assigning the relative importance to the categories and sub-categories, discussions were held to sort out the problems (Singh, 2013; Talib et al., 2011e).

Step 5: perform pair-wise comparison for each level of categories and sub-categories Once the experts were identified and relevant information and data were collected, the next step was to determine the relative importance among the barrier categories and sub-categories at each level. For this, the AHP approach was used to measure the strength of importance by pair-wise comparisons and the results were placed into a matrix form.

The team of experts was requested to compare carefully the categories of each hierarchy level by assigning a relative scale (nine-point scale) in a pair-wise fashion with respect to the objective of the model (Table III). The experts were asked to assess the pair-wise comparisons among three barrier categories and related 12 TQM barriers (sub-categories) using Saaty’s (1994) nine-point scale of intensity (Table III).

With the use of Table III, the pair-wise comparison matrix for the three barrier categories was calculated (Table IV). The numeric values in Table IV indicate the importance of the ith category compared to the jth category. For example, if an evaluator decided that “management issues” is very strongly or demonstrably more important than “organizational issues” then based on Table III’s scale of preferences

Scale Definition

1 Equal importance 3 Moderate importance of one over the other 5 Essential or strong importance 7 Very strong or demonstrated importance 9 Extreme or absolute importance 2, 4, 6, 8 Intermediate values between the two adjacent judgments Source: Saaty (1994)

Table III. Scale of relative preference for pair-wise comparison

Barrier categories POI MI OI

People-oriented issues (POI) 1 1/4 3 Managerial issues (MI) 4 1 7 Organizational issues (OI) 1/3 1/7 1 Sum 16/3 39/28 11

Table IV. Pair-wise comparison of the three prioritization- categories with respect to the barriers to TQM implementation

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between two categories, the number “7” was assigned. Hence, reciprocally the “organizational issues” are seven times less important than the “management issues.” In addition to this, the approach adopted in capturing the inputs and filling the remaining cells of Table IV was through consensus and discussions after obtaining number of views in terms of scale of preferences from the group of experts while doing pair-wise comparison among the three barrier categories. It was further observed that most of the evaluators have given a common preference scale value for a particular pair-wise comparison. In some cases, evaluators have marked different preference scale values. In such cases, a preference scale value given by the majority of evaluators was considered for the pair-wise combination and then placed in the matrix. This criterion was followed throughout the process of generating a rating matrix as presented in Table IV. Similarly, Tables IX, X and XI were also developed. The next step divides each entry in column “i” of Table IV by the sum of the entries in column “i.” This develops a normalized matrix as shown in Table V, in which the sum of the entries in each column is “1” (Saaty, 2000).

Finally, computing the average of the entries in row “i” of Table V, priority weights were calculated as depicted in Table VI. Priority indicates the relative importance or strength of influence of a criterion in relation to other criteria that is placed above it in the hierarchy. By reviewing Table VI, one can understand that the priority is given to “management issues” (score of 0.701437) followed by “people-oriented issues” (0.213238) and then to the “organizational issues” (0.085324).

Step 6: check for pair-wise comparison is consistent It often happens that evaluators may be inconsistent in their judgments, and thus, one of the important tasks for the AHP technique is to incorporate these inconsistencies into the model by calculating a consistency index (CI) and consistency ratio (CR). The CR is used to measure the consistency of the pair-wise comparisons (Singh, 2013) and decision making. Thus, CI and CR are obtained from the following relations:

CI ¼ lmax�n n�1 and CR ¼

CI RCI

Barrier categories POI MI OI

People-oriented issues 3/16 7/39 3/11 Managerial issues 3/4 28/39 7/11 Organizational issues 1/16 4/39 1/11

1.00 1.00 1.00 Source: Talib et al. (2011f )

Table V. Normalized matrix

Barrier categories Priority weight

People-oriented issues 0.213238 Managerial issues 0.701437 Organizational issues 0.085324 Sum 1.000000

Table VI. Priority weights

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where n is the rank of the matrix or the number of categories or sub-categories of each level, RCI is the random CI and λmax is the largest eigenvector in Table VII. The RCI value is selected from Table VIII as per the case.

To obtain the eigenvector and CR (Table VII) for different levels, the following computations were performed:

• Compute ψ (i.e. Table IV multiplied by Table VI):

1 1=4 3

4 1 7

1=3 1=7 1

2 64

3 75

0:213238

0:701437

0:085324

2 64

3 75 ¼

0:639586

2:137624

0:255155

2 64

3 75 ¼ c

• Compute eigenvector λ:

l ¼ ith entry in f ith entry in priority weight

Table VII indicates the values of λ for the three barrier categories and the largest eigenvalue (λmax) is chosen to calculate the CI. The maximum acceptable limit of the CI is 0.10 (Saaty, 1994). If the values are more than 0.10 it will highlight that the pair-wise comparisons are inconsistent and hence, discarded. In such a case, the assessment can be revised. For example, in the present case, the CR is “0.027905,” thus, the degree of consistency is considered quite satisfactory (CRo0.10).

Similarly, the pair-wise comparisons for the sub-categories (TQM barriers) in the other levels (Level-C) are performed and their degree of consistency is checked according to Steps 5 and 6. The results of the pair-wise comparisons of the sub-categories (TQM barriers) are shown in Tables IX, X and XI.

Step 7: compute the global weights of each category and sub-category After the pair-wise comparisons, the next step computes the local weights and global weights of each category and sub-category. The priority weights are divided into “local weights” and “global weights.” Local weights are the priority weights with respect to the preceding hierarchical level, while “global weights” are the priority weights with

Barrier categories ψ Eigenvector (λ)

People-oriented issues 0.639586 3.03237 Managerial issues 2.137624 3.03236 Organizational issues 0.255155 3.03051

λmax ¼ 3.03237 Notes: CI ¼ 0.016185; RI ¼ 0.580; CR ¼ 0.027905 for n ¼ 3

Table VII. Consistency ratio (CR)

Size of matrix 1 2 3 4 5 6 7 8 9 10 Random consistency index (RCI) 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.51 Source: Saaty (1994)

Table VIII. Random consistency index values

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respect to the highest hierarchical level, which is the objective. In order to conduct an overall ranking of the sub-categories, AHP combines the priority weights of the categories with the comparison ratings for sub-categories (Talib et al., 2011e). This is performed by the following equation (Drake, 1998):

Global weights ¼ ∑ (Local weight for category i � local weight for sub-category j with respect to category i )

Table XII shows the judgments for the composite priority weights of the barrier categories and sub-categories (TQM barriers).

Step 8: prioritize and rank the categories and sub-categories From the computation performed in Step 7, one can prioritize and rank the barrier categories and TQM barriers (sub-categories) to identify the barriers to TQM implementation (Table XII). Decisions makers and practitioners will be able to understand these TQM barriers and take appropriate action to minimize the presence

TQM barriers/sub-categories LPTE HRB ERC IUETW

CR ¼ 0.055911 CI ¼ 0.050319 priority weight

Lack of proper training and education (LPTE) 1 5 1/3 3 0.261514 Human resource barrier (HRB) 1/5 1 1/5 1/2 0.068372 Employee’s resistance to change (ERC) 3 5 1 7 0.573069 Inadequate use of empowerment and teamwork (IUETW) 1/3 2 1/7 1 0.097044 Note: Maximum eigenvalue λmax ¼ 4.15096 for n ¼ 4

Table IX. Pair-wise comparison

of the four sub-categories or

TQM barriers with respect to people-oriented

issues

TQM barriers/sub-categories LTMC LCBD NBM PP LCOM

CR ¼ 0.089159 CI ¼ 0.099858 priority weight

Lack of top-management commitment (LTMC) 1 3 4 3 1/4 0.234206 Lack of coordination between department (LCBD) 1/3 1 2 3 1/5 0.119701 No benchmarking (NBM) 1/4 1/2 1 3 1/3 0.098942 Poor planning (PP) 1/3 1/3 1/3 1 1/7 0.050440 Lack of communication (LCOM) 4 5 3 7 1 0.496710 Note: Maximum eigenvalue λmax ¼ 5.39943 for n ¼ 5

Table X. Pair-wise comparison

of the five sub-categories or

TQM barriers with respect to

managerial issues

TQM barriers/sub-categories HTML AETQ LCIC

CR ¼ 0.033199 CI ¼ 0.019255 priority weight

High turnover at management level (HTML) 1 1/3 1/5 0.104729 Attitude of employees toward quality (AETQ) 3 1 1/3 0.258285 Lack of continuous improvement culture (LCIC) 5 3 1 0.636986 Note: Maximum eigenvalue λmax ¼ 3.03851 for n ¼ 3

Table XI. Pair-wise comparison

of the three sub-categories or

TQM barriers with respect to

organizational issues

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prioritization of barriers

B ar ri er

ca te go ri es

L oc al /g lo ba l w ei gh

ts R an ki ng

T Q M

ba rr ie rs /s ub

-c at eg or ie s

L oc al

w ei gh

ts R an ki ng

G lo ba l w ei gh

ts R an ki ng

P eo pl e- or ie nt ed

is su es

0. 21 32 38

2 L ac k of

pr op er

tr ai ni ng

an d ed uc at io n

0. 26 15 14

2 0. 05 57 64

6 H um

an re so ur ce

ba rr ie r

0. 06 83 72

4 0. 01 45 79

11 E m pl oy ee ’s re si st an ce

to ch an ge

0. 57 30 69

1 0. 12 22 00

3 In ad eq ua te

us e of

em po w er m en t an d te am

w or k

0. 09 70 44

3 0. 02 06 93

10 M an ag er ia l is su es

0. 70 14 37

1 L ac k of

to p- m an ag em

en t co m m it m en t

0. 23 42 06

2 0. 16 42 80

2 L ac k of

co or di na ti on

be tw

ee n de pa rt m en t

0. 11 97 01

3 0. 08 39 62

4 N o be nc hm

ar ki ng

0. 09 89 42

4 0. 06 94 01

5 P oo r pl an ni ng

0. 05 04 40

5 0. 03 53 80

8 L ac k of

co m m un

ic at io n

0. 49 67 10

1 0. 34 84 10

1 O rg an iz at io na l is su es

0. 08 53 24

3 H ig h tu rn ov er

at m an ag em

en t le ve l

0. 10 47 29

3 0. 00 89 35

12 A tt it ud

e of

em pl oy ee s to w ar d qu

al it y

0. 25 82 85

2 0. 02 20 37

9 L ac k of

co nt in uo us

im pr ov em

en t cu lt ur e

0. 63 69 86

1 0. 05 43 50

7

Table XII. Composite priority weights for categories and sub-categories or TQM barriers

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TQM 27,5

of these barriers in their organizations. It is necessary to re-arrange the TQM barriers in descending order to easily recognize the barriers affecting the performance of the service industry. These TQM barriers are re-arranged through a histogram depicted in Figure 2, which also highlights the comparison levels among the global weights of different TQM barriers.

4. Results and discussion In the present study, identifying the barriers to TQM implementation in the service industry is carried out through the available literature and with the help of a team of experts, and then the AHP-based hierarchical model is proposed. The hierarchical model, shown in Figure 1, is divided into three levels: Level “A” – objective; Level “B” – three barrier categories; and Level “C” – sub-categories (12 TQM barriers). Table XII presents the local weights and global weights of the three barrier categories and 12 TQM barriers (sub-categories) that are normalized, based on the AHP analysis and the rankings of both the local and global weights are also shown. In Level “B” of the model, the evaluators considered that “managerial issues” was the most important category, followed by “people-oriented issues” and “organizational issues” based on their priority weights (managerial issues ¼ 0.701437; people-oriented issues ¼ 0.213238; and organizational issues ¼ 0.085324) as shown in column 2 and the rankings in column 3 in Table XII. As the three barrier categories form the second level of the objective, the local and global weights are the same.

4.1 Local weights of the 12 TQM barriers In Level “C” of the model, this study first reviews the TQM barriers with respect to “people-oriented issues.” The evaluators considered “employee’s resistance to change” (0.573069) as the most critical barrier, with the next most critical being “lack of proper training and education” (0.261514) followed by “inadequate use of empowerment and teamwork” (0.097044), and “human resource barrier” (0.068372).

For “managerial issues,” the five TQM barriers, in order of their critical importance, are “lack of communication” (0.496710); “lack of top-management commitment” (0.234206); “lack of coordination between department” (0.119701); “no benchmarking” (0.098942); and “poor planning” (0.050440).

For “organizational issues,” the TQM barriers are ordered as “lack of continuous improvement culture” (0.636986); “attitude of employees towards quality” (0.258285); and “high turnover at management level” (0.104729). The local weights of the TQM barriers with respect to “people-oriented issues,” “managerial issues” and “organizational issues,” and their rankings are shown in column 5 and 6 in Table XII.

4.2 Global weights of the 12 TQM barriers The global weight results indicate that “lack of communication” (0.348410) is the most critical barrier among the 12 TQM barriers and is ranked at the top. It shows that service industries are highly influenced by the lack of communication either within the various departments or between the management and employees in the organization. This is followed by “lack of top-management commitment” (0.164280) and “employee’s resistance to change” (0.122200). These two barriers are the second and third most critical TQM barriers and their weights are similar. The fourth barrier is “lack of coordination between department” (0.083962), followed by “no benchmarking” (0.069401); “lack of proper

605

Identification and

prioritization of barriers

0 .3

4 8 4 1

0 .1

6 4 2 8

0 .1

2 2 2

0 .0

8 3 9 6 2

0 .0

6 9 4 0 1

0 .0

5 5 7 6 4

0 .0

5 4 3 5

0 .0

3 5 3 8

0 .0

2 2 0 3 7

0 .0

2 0 6 9 3

0 .0

1 4 5 7 9

0 .0

0 8 9 3 5

0

0 .0

5

0 .1

0 .1

5

0 .2

0 .2

5

0 .3

0 .3

5

0 .4

Lack of communication

(LCOM)

Lack of top- management commitment

(LTMC)

Employee’s resistance to

change (ERC)

Lack of coordination

between department

(LCBD)

No benchmarking

(NBM)

Lack of proper training and education

(LPTE)

Lack of continuous

improvement culture (LCIC)

Poor planning (PP)

Attitude of employees

towards quality (AETQ)

Inadequate use of

empowerment and teamwork

(IUETW)

Human resource barrier

(HRB)

High turnover at management level (HTML)

T Q

M B

a rr

ie rs

Global Weights

Figure 2. Priority-level of barriers to TQM

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training and education” (0.055764); and “lack of continuous improvement culture” (0.054350). Others, in order of their ranking, are “poor planning” (0.035380); “attitude of employees towards quality” (0.022037); “inadequate use of empowerment and teamwork” (0.020693); and “human resource barrier” (0.014579). These barriers hinder the successful implementation of TQM programs. The lowest ranked TQM barrier, “high turnover at management level” (0.008935) is also a critical barrier and cannot be ignored. These rankings have been shown in column 8 of Table XII and in Figure 2. This graphical representation clearly portrays the priority levels of all the TQM barriers in the service industry. It will be very helpful for service managers to understand them so they can implement a successful TQM program in their organization.

This study presents a detailed framework of the TQM barriers along with their global weights that is useful for managers in the service industry. From this framework, service managers can identify and understand the top most critical barriers, the second most critical barriers, and the least critical barriers to improve TQM performance in the industry and to attain and sustain a competitive advantage. Many times due to insufficient resources, it is not possible for the managers and practitioners to deal with all the TQM barriers at the same time and this may cause difficulty in pursuing a TQM program in the organization. However, by prioritizing of the TQM barriers, the practitioners know which barriers they have to pay attention to first in order to get positive results from their TQM program. Thus, for organizations planning or yet to plan for the implementation of a TQM, these critical barriers can be very useful for them. The detailed recommendations for the service industry are given as follows:

• From the three barrier categories, “managerial issues” was given the greatest priority, with “people-oriented issues” and “organizational issues” following it. Thus, the service industry should implement “managerial issues” with the utmost priority and efforts must be given to the barriers “lack of communication”; “lack of top-management commitment”; and “lack of coordination between departments.” An organization can investigate and minimize these barriers, which deal with issues related to the managerial level. In addition, “no benchmarking” and “poor planning” are the main issues that act as barriers at the managerial level and affect the implementation of a TQM program. Therefore, due attention has to be given to these barriers in order to implement TQM effectively and successfully.

• Barriers related to “people-oriented issues” were found to be the second most critical barriers to TQM implementation. These issues are concerned with human values, recruitment, training and education, employee involvement and empowerment, and team management. The “people-oriented issues” as per the experts’, opinion is found to be significant after “managerial issues” and affects the performance of the organization to a greater extent. The barriers under this issue can be minimized by recruiting adequate and qualified workers on a continual basis, encouraging employees through rewards and incentives, involving the employees in major decisions and providing training and education in advanced quality tools and techniques. In addition, creating an environment of working together rather than as an individual can improve the performance of TQM. “People-oriented issues” should be tackled at the same level since they influence other linking issues and could greatly affect the success of a TQM program in the organization.

607

Identification and

prioritization of barriers

• Service managers and practitioners after critically appraising “people-oriented issues” and “managerial issues,” should place an emphasis on “organizational issues.” These issues are critical and responsible for helping the organization develop an atmosphere of trust, affection, a culture of quality, attitude and continuous improvement. These issues should be dealt within this specific order to sustain a TQM program in the service industry.

• For “managerial issues,” the evaluators ranked “lack of communication” at the top by giving it the highest weighting. This implies that “lack of communication” is one of the most critical barriers that cause a TQM to fail. This is also supported by the literature (Moghaddam and Moballeghi, 2008). The major reasons are a lack of transmitting information between departments/sections and communication gaps between top and middle management levels as well as at the lower level. The second ranked barrier is “lack of top-management commitment.” It was observed that without the support of top-management and a commitment toward continuous improvement in customer service and satisfaction, business performance will not improve in the organization (Talib et al., 2011e). Thus, commitment by the top-level management is a driving force for the successful implementation of TQM program in the service industry. Service managers should seriously pay attention to the reasons behind this barrier. The third ranked barrier is “lack of coordination between departments.” Experts view this as a significant barrier that plays an active role in hindering the successful implementation of TQM. A strong healthy environment with internal communication within the departments should be made to avoid a “lack of coordination between departments.” The fourth ranked barrier as per the experts rating was “no benchmarking.” This barrier affects the culture of CQI and competitiveness and hence, the effectiveness of a TQM program. The attitude to attain high productivity and adopt the best practices of other organizations will help minimize this barrier. “Poor planning” has the lowest rank under “managerial issues” which reveals that the absence of long-term planning without creative ideas leads to ineffective improvement in quality. Many organizations operate without any effective planning and are on the verge of failure. Therefore, attention has to be paid to create a strategy, develop new plans and generate adequate resources to employ an effective TQM program.

• With respect to “people-oriented issues,” the evaluators gave “employee’s resistance to change” the highest priority. This barrier frequently occurs in every organization. The employees’ attitude toward quality has to be changed, which could be done by removing any misconceptions about quality programs through training, incentives and empowerment. “Lack of proper training and education” is ranked second and a critical barrier present at all levels of an organization (Whalen and Rahim, 1994). Sometimes, it becomes a major barrier to the implementation of quality program. The reason behind this barrier is insufficient training with new and advanced quality tools and techniques and a lack of interest by the management toward providing training and education. “Inadequate use of empowerment and teamwork” was ranked third by the evaluators which implies that the non-participation of employees in major decisions and not involving them in strategic decisions creates this barrier. Beside this, lack of teamwork and insufficient efforts for bringing in team building techniques are some of the causes of the “inadequate use of empowerment and teamwork” barrier. The “human resource barrier” was ranked

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the lowest under the “people-oriented issues” category. From this study, it was found that “human resource barrier” is not an important barrier and rarely occurs in the service industry. There is a sufficient number of qualified staff present in almost all the service industries (Talib et al., 2013). Absenteeism, lack of skill, low wages and salaries has been largely reduced. Hence, the service industry is the least affected by this barrier.

• With respect to “organizational issues,” the evaluators gave the highest rank to “lack of continuous improvement culture.” Its presence in an organization leads to total failure. The foundation of TQM lies on the quality culture, people’s attitude and continuous improvement. To implement a successful TQM program, these practices have to be taken care of. “Attitude of employees towards quality” is ranked second and is another major barrier that affects the implementation of a TQM program in the organization. Educating employees about the benefits of TQM like increased productivity, profitability, incentives and ultimately customer satisfaction could remove this barrier. “High turnover at management level” ranked third. Many organizations suffer from this barrier and hence, are unable to implement a quality program successfully. The reasons are hierarchical problems, management work style, instability and ineffective employee selection practices. These types of practices should be removed and attention should be made so that they are not repeated in order to minimize “high turnover at management level.”

5. Conclusion TQM has become an integral part of the growth and development for most of the service industries. However, many of them are failing to get the maximum number of benefits from this approach due to these barriers. This study has put in efforts to identify the different TQM barriers responsible for the ineffective implementation of a TQM program. The study tries to prioritize the identified TQM barriers and proposes an AHP methodology to rank the identified barriers related to the service industry. Prioritization is helpful in deciding the relative importance of the barriers when implementing a TQM program. The strength of this study is the development of a comprehensive model for the investigation and prioritization of barriers that the service industry experiences when implementing a TQM program. In this direction, 12 TQM barriers were identified through an extensive literature review and the opinions of a team of experts. By using AHP, the relative importance of all the barriers and their impact on TQM performance were analyzed. The synthesized results have highlighted that the barrier “lack of communication” is the most significant among all the other barriers. It is followed by “lack of top-management commitment,” “employee’s resistance to change” and “lack of coordination between departments.” The least significant barrier is found to be “high turnover at management level.”

Although, the findings of this study have been thoroughly discussed in the results and discussion section, it is worth mentioning that top-management should take active initiatives to develop an atmosphere of trust and mutual understanding among employees and management within all departments. Similarly, organizations should strive for strong relationships and department integration to minimize this barrier, which acts as one of the most critical barriers to TQM implementation.

609

Identification and

prioritization of barriers

5.1 Limitations of the study The findings of this study suggest that adopting the AHP approach to prioritize the different barrier categories and sub-categories of the developed model proved to be successful, but still there are limitations of this methodology. Some of them are:

• The decision-making criteria and sub-criteria are not always independent from each other although it is a major assumption in AHP methodology, especially for service organizations (Singh, 2013).

• The scale of relative importance utilized in AHP is based on a conceptual approach used to identify which barriers take precedence (Singh, 2013).

• The procedure of pair-wise comparison is somewhat time consuming and tedious resulting in experts’ lack of interest in interview (Olson, 1988).

• Chances of evaluators’ biasness are high while making pair-wise comparisons to different categories and sub-categories. Hence, care has to be taken while rating these categories (Singh, 2013).

• AHP assumes that the system elements are uncorrelated and are unidirectionally influenced by a hierarchical relationship (Meade and Presley, 2002; Ishizaka and Labib, 2009).

• Finally, this hierarchical model has been tested only in the service sector, other sectors are not considered, hence, generalization of the study cannot be made.

5.2 Managerial implication The implications of the study are:

• With the help of this study, service managers may learn about the existence of barriers to TQM implementation and understand them.

• The barriers under “managerial issues” are crucial and should be given priority for minimizing them in the organization. After “managerial issues,” “people-oriented issues” and then “organizational issues” barrier categories should be given full attention for achieving the maximum benefits of implementing a TQM program.

• Top-management should pay special attention to the highest ranked barrier “lack of communication.” They should put all their efforts in overcoming this barrier through mutual consensus, regular meetings and involving employees in major decisions. This should be dealt with at all levels.

5.3 Scope for future research The scope of this research work provides an opportunity for researchers and academicians to develop a better and improved model by adopting the fuzzy AHP methodology after identifying additional TQM barriers through an extended literature review that were not identified in the present study. Additionally, a more precise decision-making model can be achieved using ANP where the interrelationships between different levels and within the same level can be made and more complex relationships among the categories and sub-categories can be generated. Further, validating the model using different statistical tests such as an exploratory factor analysis, confirmatory factor analysis and SEM can be made and hence, the results of

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the present study can be verified and consistent results may be obtained. Finally, the results of the study can also be verified by applying the same AHP model to various other sectors like manufacturing, small-to-medium enterprises, agriculture, etc., through which a generalized model of TQM barriers can be attained.

References

Adebanjo, D. and Kehoe, D. (1998), “An evaluation of quality culture problems in UK companies”, International Journal of Quality Science, Vol. 3 No. 3, pp. 275-286.

Alberto, P. (2000), “The logistics of industrial location decision: an application of the analytical hierarchy process methodology”, International Journal of Logistics: Research and Application, Vol. 3 No. 3, pp. 273-289.

Al-Zamany, Y., Hoddell, E.J. and Savage, B.M. (2002), “Understanding the difficulties of implementing quality management in Yemen”, The TQM Magazine, Vol. 14 No. 4, pp. 240-247.

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.

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.

Arumugam, V., Ooi, K.-B. and Fong, T.-C. (2008), “TQM practices and quality management performance – an investigation of their relationship using data from ISO 9001:2000 firms in Malaysia”, The TQM Magazine, Vol. 20 No. 6, pp. 636-650.

Azizi, M. and Azizpour, M. (2012), “A BOCR structure for privatisation effective criteria of Iran newsprint paper industry”, International Journal of Production Research, Vol. 50 No. 17, pp. 4867-4876.

Bak, C. (1992), “Lessons from veterans of TQM”, Canadian Business Review, Vol. 19 No. 4, pp. 17-19.

Beer, M. (2003), “Why total quality management programs do not persist: the role of management quality and implications for leading a TQM transformation”, Decision Sciences, Vol. 34 No. 4, pp. 623-642.

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.

Briggs, C.A. and Tolliver, D. (2012), “Managing and mitigating the upstream petroleum industry supply chain risks: leveraging analytic hierarchy process”, International Journal of Business and Economics Perspectives, Vol. 7 No. 1, pp. 1-10.

Brigham, S.E. (1993), “Lessons we can learn from industry”, Change, Vol. 25 No. 3, pp. 42-47.

Brown, M.G. (1993), “Why does total quality fail in two out of three tries?”, Journal for Quality and Participation, Vol. 16 No. 2, pp. 80-84.

Burrows, P. (1992), “TQM reality check: it works, but it’s not cheap or easy”, Electronic Business, Vol. 18 No. 1, pp. 47-54.

Chan, F.T.S., Chan, H.K., Lau, H.C.W. and Ip, R.W.L. (2006), “An AHP approach in benchmarking logistics performance of the postal industry”, Benchmarking: An International Journal, Vol. 13 No. 6, pp. 636-661.

Chang, H.H. (2006), “Development of performance systems in quality management organizations”, The Service Industries Journal, Vol. 26 No. 7, pp. 765-786.

Chen, J.-K. and Chen, I.-S. (2009), “TQM measurement model for the biotechnology industry in Taiwan”, Expert Systems with Applications, Vol. 36 No. 5, pp. 8789-8798.

611

Identification and

prioritization of barriers

Chen, S.-H. (2013), “Integrated analysis of the performance of TQM tools and techniques: a case study in the Taiwanese motor industry”, International Journal of Production Research, Vol. 51 No. 4, pp. 1072-1083.

Corbett, L. and Rastrick, K. (2000), “Quality performance and organizational culture”, International Journal of Quality and Reliability Management, Vol. 17 No. 1, pp. 14-26.

Crary, M., Nozick, L.K. and Whitaker, L.R. (2002), “Sizing the US destroyer fleet”, European Journal of Operational Research, Vol. 136 No. 3, pp. 680-695.

David, R.J. and Strang, D. (2006), “When fashion is fleeting: transitory collective beliefs and the dynamics of TQM consulting”, Academy of Management Journal, Vol. 49 No. 2, pp. 215-233.

Dowlatshahi, S. (1998), “The role of purchasing and TQM in the Maquiladora industry”, Production and Inventory Management Journal, Vol. 39, pp. 32-49.

Drake, P. (1998), “Using the analytic hierarchy process in engineering education”, International Journal of Engineering, Vol. 14 No. 3, pp. 191-196.

Ennis, K. and Harrington, D. (1999), “Quality management in Irish health care”, International Journal of Health Care Quality Assurance, Vol. 12 No. 6, pp. 232-243.

Garg, R., Rahman, Z., Qureshi, M.N. and Kumar, I. (2012), “Identifying and ranking critical success factors of customer experience in banks: an analytic hierarchy process (AHP) approach”, Journal of Modelling in Management, Vol. 7 No. 2, pp. 201-220.

Grover, S., Agrawal, V.P. and Khan, I.A. (2004), “A digraph approach to TQM evaluation of an industry”, International Journal of Production Research, Vol. 42 No. 19, pp. 4031-4053.

Gunasekaran, A. (1999), “Enablers of total quality management implementation on manufacturing: a case study”, Total Quality Management, Vol. 10 No. 7, pp. 987-996.

Helms, M.M. and Mayo, D.T. (2008), “Assessing poor quality service: perceptions of customer service representative”, Managing Service Quality, Vol. 18 No. 6, pp. 610-622.

Huq, Z. (2005), “Managing change: a barrier to TQM in implementation in service industry”, Managing Service Quality, Vol. 15 No. 5, pp. 452-469.

Huq, Z. and Martin, T.N. (2000), “Workforce cultural factors in TQM/CQI implementation in hospitals”, Healthcare Management Review, Vol. 25 No. 3, pp. 80-93.

Ishizaka, A. and Labib, A. (2009), “Analytic hierarchy process and expert choice: benefits and limitations”, OR Insight, Vol. 22 No. 4, pp. 201-220.

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.

Kanji, G.K. (1996), “Implementation and pitfalls of total quality management”, Total Quality Management, Vol. 7 No. 3, pp. 331-343.

Koilakuntlaa, M., Patyala, V.S., Modgila, S. and Ekkulurib, P. (2012), “A research stuyd on estimation of TQM ‘factors ratings’ through analytical hierarchy process”, Procedia Economics and Finance, Vol. 3, pp. 55-61.

Law, W.K., Chan, A.H.S. and Pun, K.F. (2006), “Prioritising the safety management elements: a hierarchical analysis for manufacturing enterprises”, Industrial Management and Data Systems, Vol. 106 No. 6, pp. 778-792.

Lewis, W.G., Pun, K.F. and Lalla, T.R.M. (2005), “An AHP-based study of TQM benefits in ISO9001 certified SMEs in Trinidad and Tobago”, The TQM Magazine, Vol. 17 No. 6, pp. 558-572.

Liu, C.K. (1998), “Pitfalls of total quality management in Hong Kong”, Total Quality Management, Vol. 9 No. 7, pp. 585-598.

Ljungström, M. and Klefsjö, B. (2002), “Implementation obstacles for a work-development-oriented TQM strategy”, Total Quality Management, Vol. 13 No. 5, pp. 621-634.

Locatelli, G. and Mancini, M. (2012), “A framework for the selection of the right nuclear power plant”, International Journal of Production Research, Vol. 50 No. 17, pp. 4753-4766.

612

TQM 27,5

McDermott, T. (1994), “TQM: the total quality Maquiladora”, Business Mexico, Vol. 4 No. 11, pp. 42-45.

Meade, L.M. and Presley, A. (2002), “R&D project selection using analytic hierarchy process”, IEEE Transactions on Engineering Management, Vol. 49 No. 1, pp. 59-66.

Moghaddam, G.G. and Moballeghi, M. (2008), “Total quality management in library and information sectors”, Electronic Library, Vol. 26 No. 6, pp. 912-922.

Mosadegh Rad, 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.

Newall, D. and Dale, B. (1990), “The introduction and development of a quality improvement process: a study”, International Journal of Production Research, Vol. 29 No. 9, pp. 1747-1760.

Ngai, E.W.T. and Cheng, T.C.E. (1997), “Identifying potential barriers to total quality management using principal component analysis and correspondence analysis”, International Journal of Quality and Reliability Management, Vol. 14 No. 4, pp. 391-408.

Olson, D.L. (1988), “Opportunities and limitations of analytic hierarchy process in multi-objective programming”, Mathematical and Computer Modeling, Vol. 11, pp. 206-209.

Prajogo, D.I. and Sohal, S.A. (2003), “The relationship between TQM practices, quality performance, and innovation performance: an empirical examination”, International Journal of Quality and Reliability Management, Vol. 20 No. 8, pp. 901-918.

Prajogo, D.I. and Sohal, S.A. (2006), “The integration of TQM and technology/R&D management in determining quality and innovation performance”, Omega: The International Journal of Management Science, Vol. 34 No. 3, pp. 296-312.

Punniyamoorty, M., Mathiyalagan, P. and Lakshmi, G. (2012), “A combined application of structural equation modeling (SEM) and analytic hierarchy process (AHP) in supplier selection”, Benchmarking: An International Journal, Vol. 19 No. 1, pp. 70-92.

Rajashekhar, J. (1999), “Total quality management in India-perspective and analysis”, The TQM Magazine, Vol. 11 No. 5, pp. 321-327.

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.

Saad, G.H. (2001), “Strategic performance evaluation: descriptive and prescriptive analysis”, Industrial Management and Data Systems, Vol. 101 No. 2, pp. 390-399.

Saaty, T.L. (1980), The Analytic Hierarchy Process-Planning, Priority Setting, Resource Allocation, McGraw-Hill, New York, NY.

Saaty, T.L. (1994), “How to make a decision: the analytic hierarchy process”, Interfaces, Vol. 24 No. 6, pp. 9-26.

Saaty, T.L. (2000), Fundamental of Decision Making and Priority Theory with the Analytic Hierarchy Process, RWS Publication, Pittsburgh, PA.

Salegna, G. and Fazel, F. (2000), “Obstacles to implementing TQM”, Quality Progress, Vol. 33 No. 7, pp. 53-64.

Sarathy, S.P. (2013), “TQM practice in real-estate industry using AHP”, Quality and Quantity, Vol. 47 No. 4, pp. 2049-2063.

Sebastianelli, R. and Tamimi, N. (2003), “Understanding the obstacles to TQM success”, The Quality Management Journal, Vol. 10 No. 3, pp. 45-56.

Sila, I. (2007), “Examining the effects of contextual factors on total quality management and performance through the lens of organizational theories: an empirical study”, Journal of Operations Management, Vol. 25 No. 1, pp. 83-109.

Singh, R.K. (2013), “Prioritizing the factors for coordinated supply chain using analytic hierarchy process (AHP)”, Measuring Business Excellence, Vol. 17 No. 1, pp. 80-98.

613

Identification and

prioritization of barriers

Singh, R.K., Garg, S.K., Deshmukh, S.G. and Kumar, M. (2007), “Modelling of critical success factors for implementation of AMTs”, Journal of Modelling in Management, Vol. 2 No. 3, pp. 232-250.

Soltani, E., Lai, P.-C. and Gharneh, N.S. (2005), “Breaking through barriers to TQM effectiveness: lack of commitment of upper-level management”, Total Quality Management, Vol. 16 Nos 8/9, pp. 1009-1021.

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.

Talib, F. and Rahman, Z. (2010), “Studying the impact of total quality management in service industries”, International Journal of Productivity and Quality Management, Vol. 6 No. 2, pp. 249-268.

Talib, F., Rahman, Z. and Qureshi, M.N. (2010), “The relationship between total quality management and quality performance in the service industry: a theoretical model”, International Journal of Business, Management and Social Sciences, Vol. 1 No. 1, pp. 113-128.

Talib, F., Rahman, Z. and Qureshi, M.N. (2011a), “A study of total quality management and supply chain management practices”, International Journal of Productivity and Performance Management, Vol. 60 No. 3, pp. 266-288.

Talib, F., Rahman, Z. and Qureshi, M.N. (2011b), “An empirical study of barriers to TQM implementation in Indian service industries”, Proceedings of First International Conference on Industrial Engineering (ICIE 2011), Department of Mechanical Engineering, S.V. National Institute of Technology, Surat, Association with Indian Institution of Industrial Engineering (IIIIE), NHQ-Mumbai, November 17-19, pp. 1072-1084.

Talib, F., Rahman, Z. and Qureshi, M.N. (2011c), “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.

Talib, F., Rahman, Z. and Qureshi, M.N. (2011d), “Assessing the awareness of total quality management in Indian service industries: an empirical investigation”, Asian Journal on Quality, Vol. 12 No. 3, pp. 228-243.

Talib, F., Rahman, Z. and Qureshi, M.N. (2011e), “Prioritising the practices of total quality management: an analytic hierarchy process (AHP) analysis for the service industries”, Total Quality Management and Business Excellence, Vol. 22 No. 12, pp. 1331-1351.

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

Talib, F., Rahman, Z. and Qureshi, M.N. (2012b), “Total quality management practices in indian hospitality industry: some key findings from survey”, Proceedings of National Conference on Emerging Challenges for Sustainable Business (ECSB-2012), Indian Institute of Technology Roorkee, Roorkee, June 1-2, pp. 1866-1888.

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.

Talib, F., Rahman, Z., Quershi, M.N. and Siddique, J. (2011f), “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.

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

Tatikonda, L.U. and Tatikonda, R.J. (1996), “Top ten reasons your TQM effort is failing to improve profit”, Production and Inventory Management Journal, Vol. 37 No. 3, pp. 5-9.

614

TQM 27,5

Teagarden, M.B., Butler, M.C. and Glinow, V. (1992), “Mexico’s Maquiladora industry: where strategic human resource management makes a difference”, Organizational Dynamics, Vol. 20 No. 3, pp. 34-47.

Tsinidou, M., Gerogiannis, V. and Fitsilis, P. (2010), “Evaluation of the factors that determine quality in higher education: an empirical study”, Quality Assurance in Education, Vol. 18 No. 3, pp. 227-244.

Vaidya, O.S. and Kumar, S. (2006), “Analytic hierarchy process: an overview of applications”, European Journal of Operational Research, Vol. 169 No. 1, pp. 1-29.

Van der Wiele, T. and Brown, A. (2002), “Quality management over a decade: a longitudinal study”, International Journal of Quality and Reliability Management, Vol. 19 No. 5, pp. 508-523.

Vanichchinchai, A. and Igel, B. (2011), “The impact of total quality management on supply chain management and firm’s supply performance”, International Journal of Production Research, Vol. 49 No. 11, pp. 3405-3424.

Varajão, J. and Cruz-Cunha, M.M. (2013), “Using AHP and the IPMA competence baseline in the project managers selection process”, International Journal of Production Research, Vol. 51 No. 11, pp. 3342-3354.

Venkatraman, S. (2007), “A framework for implementing TQM in higher education programs”, Quality Assurance in Education, Vol. 15 No. 1, pp. 89-112.

Whalen, M.J. and Rahim, M.A. (1994), “Common barriers to implementation and development of a TQM process”, Industrial Management, Vol. 36 No. 2, pp. 19-24.

Wong, J.K.W. and Li, H. (2008), “Application of the analytic hierarchy process (AHP) in multi-criteria analysis of the selection of intelligent building systems”, Building and Environment, Vol. 43 No. 1, pp. 108-125.

Yang, C.C. (2006), “The impact of human resource management practices on the implementation of total quality management”, The TQM Magazine, Vol. 18 No. 2, pp. 162-173.

Zopounidis, C. and Doumpos, M. (2000), “PREFDIS: a multicriteria decision support system for sorting decision problems”, Computer Operations Research, Vol. 27 No. 7, pp. 779-797.

About the authors Dr Faisal Talib is an Assistant Professor at the Mechanical Engineering Section, University Polytechnic, Faculty of Engineering and Technology, Aligarh Muslim University (AMU), Aligarh, (UP), India. He holds a PhD Degree from the Indian Institute of Technology, Roorkee and Masters in Industrial and Production Engineering from the AMU. He has 16 years of teaching experience and has more than 50 publications to his credit in national/international journals and conferences. His special interest includes quality engineering, TQM, service quality, quality concepts, industrial and production management, operations management and quality management in service industries. Dr Faisal Talib is the corresponding author and can be contacted at: [email protected]

Professor Zillur Rahman is an Associate Professor at the Department of Management Studies, Indian Institute of Technology Roorkee. He is a Recipient of the Emerald Literati Club Highly Commended Award and one of his papers was The Science Direct Top 25 Hottest Article. His work has been published and cited in various journals including Management Decision, Managing Service Quality, International Journal of Information Management, Industrial Management and Data Systems, The TQM Magazine, Business Process Management Journal, International Journal of Service Industry Management Information Systems Journal, Decision Support Systems, Journal of Business and Industrial Marketing, and International Journal of Computer Integrated Manufacturing, to name a few.

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