The current issue and full text archive of this journal is available at www.emeraldinsight.com/1463-5771.htm Using ISM Analysis of interaction among approach the barriers to total quality management implementation 563 using interpretive structural modeling approach Faisal Talib Mechanical Engineering Section, Faculty of Engineering and Technology, University Polytechnic, Aligarh Muslim University, Aligarh, India Zillur Rahman Department of Management Studies, Indian Institute of Technology, Roorkee, India, and M.N. QureshiDepartment of Mechanical Engineering, Faculty of Engineering and Technology, M S University of Baroda, Vadodara, IndiaAbstractPurpose – Previous research showed that there are some barriers which hinder the implementationof total quality management (TQM) in organizations. But no study has been undertaken to understandthe interaction among these barriers and to develop a hierarchy of TQM barriers model. There is anurgent need to analyze the behavior of these barriers so that TQM may be successfully implemented.This paper therefore, aims to understand the mutual interaction of these barriers and identify the“driving barriers” (i.e. which inﬂuence the other barriers) and the “dependent barriers” (i.e. which areinﬂuenced by others).Design/methodology/approach – In this paper, an interpretive structural modeling (ISM) basedapproach has been utilized to understand the mutual inﬂuences among the barriers of TQM.Findings – In the present research work, 12 TQM barriers are identiﬁed through the literature reviewand expert opinion. The research shows that there exist two groups of barriers, one having highdriving power and low dependency requiring maximum attention and of strategic importance(such as lack of top-management commitment, lack of coordination between departments) and theother having high dependence and low driving power and are resultant effects (such as high turnoverat management level, lack of continuous improvement culture, employees’ resistance to change).Practical implications – The adoption of such an ISM-based model on TQM barriers in serviceorganizations would help managers, decision makers, and practitioners of TQM in betterunderstanding of these barriers and to focus on major barriers while implementing TQM in theirorganizations.Originality/value – Presentation of TQM barriers in the form of an ISM-based model and thecategorization into driver and dependent clusters is a new effort in the area of TQM.Keywords Total quality management, Interpretive structural modeling, Barriers, Service organization, Benchmarking: An InternationalManagers, Modeling Journal Vol. 18 No. 4, 2011Paper type Research paper pp. 563-587 q Emerald Group Publishing Limited 1463-5771 DOI 10.1108/14635771111147641
BIJ Introduction18,4 In the era of economic liberalization and increased competition with the emergence of new products and improved services as well as fast growth in customer needs and expectations for quality service, the service organization face tremendous competition and are under immense pressure to become more responsive to customer needs and gain an upper edge. There are demands for improvement in the quality of products and564 services, transparency in policies and procedures, increased emphasis on pre and post product and service delivery procedures, and cost of quality. Service organizations must improve the quality of their services, achieve competitive advantage, and move on a path of growth and excellence. A customer centric philosophy of management needs to be all encompassing throughout the organization with an ultimate objective being customer satisfaction. In order to achieve and accomplish the above aspects of customer, service organizations are making use of well-known quality approaches like ISO 9000, total quality management (TQM), Six Sigma, 5S, quality function deployment, and continuous quality improvement (CQI) programs which have helped them in achieving their goals. One of the important quality improvement techniques, which many organizations are using to achieve excellence in business, is TQM. TQM has been widely accepted as a disciplined management process in different sector in order to cope with the changes in marketplace and focus on quality in both their products as well as services (Venkatraman, 2007). Though TQM was considered and used mainly by manufacturing industry, there has been a strong push for adopting TQM in service organizations (Kureshi et al., 2010; Kaluarachchi, 2010; Eraqi, 2006; Telford and Masson, 2005; Srikanthan and Dalrymple, 2004). Implementation of TQM has given them positive results, particularly towards achieving enhanced organization performance and customer satisfaction. It is understood that the goals of TQM are to satisfy customers, prevent poor quality rather than correcting problems, develop an attitude of continuous improvement, understand the value of measuring performance to identify opportunities and maintain improvements, and to eliminate chronic sources of inefﬁciencies and costs (Evans and Lindsay, 1996; Burr, 1993; Mosadegh Rad, 2005). These goals could be achieved if there is a total commitment by entire organization (including top-management and employees) as well as principles of TQM are fully understood by them. Moreover, TQM is the culture of an organization committed to total customer satisfaction through continuous improvement (Mosadegh Rad, 2005; Gunasekaran and McGaughey, 2003). TQM demands change in organization culture for improved performance (Kaluarachchi, 2010). TQM also demands constancy of purpose throughout the organization, and persistence in accordance with a clear and widely understood vision. It is an environment that requires and nurtures total commitment at all levels of the organization by providing potential beneﬁts such as customer satisfaction, increased productivity and proﬁt, enhanced business competitiveness, and increased market share (Gunasekaran, 1999; Mosadegh Rad, 2004). TQM has enjoyed great popularity in all sectors since its evaluation and is adopted into their regular management activities (Hansson and Eriksson, 2002; Gunasekaran, 1999). Recently, Ho (2010) has proposed an “integrated lean TQM model for global sustainability and competitiveness” to help organizations to reduce global resource wasting and improve the damages caused by the ﬁnancial tsunami. Study by Leonard (2010) suggested that quality management systems and quality award criteria are also making an impact in homebuilding industry.
Further, the application of world class manufacturing techniques like TQM, JIT, lean Using ISMmanufacturing in small and medium enterprises (SMEs) enhance the productivity andquality of these industries (Gunasekaran, 2000). approach Further, studies showed that TQM was positively associated with performanceoutcome such as ﬁnancial performance, business performance, and proﬁtability(Brah et al., 2000; Yusuf et al., 2007; Hendricks and Singhal, 1997; Salaheldin, 2009;Reed et al., 1996; Rust et al., 1999; Prajogo and McDermott, 2005; Hafeez et al., 2006; 565Bou-Llusar and Beltran-Martin, 2005) as well as with human outcome, such as employeesatisfaction, supplier relationship, and customer satisfaction (Mehra and Ranganathan,2008; Yang, 2006; Sila and Ebrahimpour, 2005; Gunasekaran and McGaughey, 2003;Arumugam et al., 2008; Salaheldin, 2009). However, in practice, these TQM beneﬁtsare not easy to achieve. There are quite a number of evidences that suggests TQMimplementation is often unsuccessful due to different focus of organizations in itsimplementation (Venkatraman, 2007; Kendrick, 1993; Eskildson, 1995; Grifﬁn, 1988; Kochand Fisher, 1998; Fuchsberg, 1993). Organizations found some barriers which hinder theimplementation of TQM. Owing to these barriers, they have not achieved the desiredbeneﬁts, which they have expected after implementation of TQM. As a result, many of theTQM initiatives have been abandoned or are in the process of being abandoned. Somestudies even have asserted that approximately two-third of organizations have failed totheir attempt to implement TQM (Hubiak and O’Donnell, 1996; Guangming et al., 2000). Furthermore, the literature review suggest that no study has been taken thatinvestigate explicitly the interactions among the barriers of TQM and proposes aninterpretive structural modeling (ISM) based model for the TQM barriers. Hence, this isperhaps the ﬁrst study in this direction. To help address this gap, the present studyattempts to identify the barriers of TQM through extent literature review and expertopinions and further develops the contextual relationships among these identiﬁedbarriers using ISM approach. It also proposes a hierarchy of TQM barriers model thatwould help the managers and practitioners of service organizations to understand andpay attention to the identiﬁed barriers for successful implementation of TQM program. For this purpose the following objectives have been designed: . to identify and rank the barriers of TQM in service organizations; . to ﬁnd out the interaction among identiﬁed barriers of TQM using ISM approach; and . to discuss the managerial implications of this research study and suggest directions for future research.The remainder of this paper has been organized as follows. The next section provides areview of the literature and discusses the identiﬁcation of TQM barriers. This isfollowed by discussion of ISM methodology and development of the relationships ´ ´ ´model using ISM. Matrice d’Impacts Croises Multiplication Appliquee a un Classement(MICMAC) analysis of developed ISM model is carried out subsequently. Finally, thediscussion and conclusion of this research study are presented, which is followed bymanagerial implications and scope for future work.Literature reviewDespite the fact that practices related to successful implementation of TQM havehelped in achieving the desired outcomes namely increased organization performance,
BIJ proﬁtability, and improved customer satisfaction, practicing and implementing TQM18,4 practices is still not free from barriers. This literature review aims to identify the barriers that need to be addressed during the implementation of TQM in service organizations, which inﬂuence organizational performance and customer satisfaction. Based on the extent literature review and discussion with the experts in the service organizations, keeping the service sector in focus, 12 barriers were identiﬁed, which566 can serve as invaluable lesson to those organizations that are planning to implement TQM or are in the process of its implementation, and are presented in Table I. The above listed barriers are often cited in the TQM literature and are found to be frequently used by different researchers in their studies which suggest that these barriers hinder the successful implementation of TQM. Beside this, some barriers like inadequate understanding of customer needs, lack of customer focus, lack of measurement, lack of awareness of quality at management level, lack of vision, lack of accounting systems, lack of access to data and result, lack of suppliers/contractors participation and other similar barriers are found to be insigniﬁcant in the present era of digital technology and mass customization. Utmost importance to such barriers are nowadays given due consideration by management by closely monitoring them through company-wide information network. Therefore, such barriers are closely controlled and monitored by management and hence, considered to be controllable with varying efforts. Moreover, the barriers like incompatible organization structure, isolated individuals and departments, inability to change organizational culture, insufﬁcient resources, short-term focus, and inappropriate rewards and recognition system which are often cited with different names and headings are covered in this study under a common barrier name like lack of coordination between departments, lack of continuous improvement culture, human resource barriers, no benchmarking, poor planning and inadequate use of empowerment and teamwork. Hence, these12 barriers are assumed to be the major TQM barriers that hinder the successful implementation of TQM. Identiﬁcation of TQM barriers Lack of top-management commitment. A TQM program will succeed only if top-management is fully committed beyond public announcements (Whalen and Rahim, 1994). Ellram (1991) emphasized top-management commitment as an enabler, while lack of top-management commitment as a barrier too. According to Brigham (1993), lack of proper leadership is a common barrier to both manufacturing and service industry in implementing TQM. Kanji (1996) identiﬁed management’s failure to lead as the primary obstacle to successful TQM. Van der Wiele and Brown (2002) found management-related factors as the core factors that affect the long-term sustainability of quality management. Lack of top-management commitment may stem from various reasons like lack of experience and training, resistance to change, and hesitation in initiating improvement programs. High turnover at management level. High turnover and absenteeism at management level have plagued many organizations and inhibited their efforts to implement TQM initiatives effectively (Dowlatshahi, 1998; McDermott, 1994). Employees and managers in most of the organization encounter difﬁculties in adopting themselves to modern work environments with new rules and organization hierarchies. Structural problems like organization culture and performance appraisal problems like lack of reward system and training program were the most often cited explanation for failing to return
Barrierno. Barriers References 1 Lack of top-management Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Jun et al. (2004), Whalen and Rahim commitment ¨ ¨ (1994), Venkatraman (2007), Ljungstrom and Klefsjo (2002), Soltani et al. (2005), Mosadegh Rad (2005), Salegna and Fazel (2000), Brigham (1993), Kanji (1996), Newall and Dale (1990) 2 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), Jun et al. (2006), Knotts and Tomlin (1994), Lawrence and Yeh (1994), Wentling and Palma-Rivas (1998), Lawrence and Lewis (1993) 3 Attitude of employees towards Amar and Zain (2002), Helms and Mayo (2008), Mosadegh Rad (2005), Salegna and Fazel (2000), Tamimi quality and Sebastianelli (1998) 4 Lack of proper training and Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Jun et al. (2004), Rajashekhar (1999), education ¨ ¨ Whalen and Rahim (1994), Huq (2005), Ljungstrom and Klefsjo (2002), Soltani et al. (2005), Mosadegh Rad (2005), Tatikonda and Tatikonda (1996), Adebanjo and Kehoe (1998), Newall and Dale (1990) 5 Lack of coordination between Amar and Zain (2002), Gunasekaran (1999), Salegna and Fazel (2000), Tamimi and Sebastianelli (1998), department Al-Zamany et al. (2002) 6 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), Ljungstrom and Klefsjo (2002), Mosadegh Rad (2005), Newall and Dale (1990) 7 No benchmarking Al-Zamany et al. (2002), Rajashekhar (1999), Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Jun et al. (2004) 8 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) 9 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)10 Inadequate use of empowerment and Tamimi and Sebastianelli (1998), Bhat and Rajashekhar (2009), Jun et al. (2004), Gunasekaran (1999), teamwork ¨ ¨ Whalen and Rahim (1994), Ljungstrom and Klefsjo (2002), Mosadegh Rad (2005), Salegna and Fazel (2000),Adebanjo and Kehoe (1998), Newall and Dale (1990)11 Lack of continuous improvement Al-Zamany et al. (2002), Amar and Zain (2002), Whalen and Rahim (1994), Huq (2005), Mosadegh Rad culture (2005)12 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) approach the TQM literature Using ISM references as reported in Barriers and their 567 Table I.
BIJ to work as scheduled and for absenteeism (Mosadegh Rad, 2005; Jun et al., 2004). High18,4 turnover and absenteeism may also stem from ineffective employee selection practice ( Jun et al., 2004). Other explanations such as cultural differences (Lawrence and Yeh, 1994), employees family issues (Teagarden et al., 1992), and switching the jobs for a minimal increase in salary (Lawrence and Lewis, 1993), have been offered to explain the high turnover at management level. Ineffective employee compensation ( Jun et al.,568 2006) and promotion (Wentling and Palma-Rivas, 1998) are also signiﬁcant factors that inﬂuence turnover and absenteeism in the organization. Appraisal schemes such as family ﬁnances, basic healthcare facilities, quality and punctuality bonuses, and on-site healthcare clinic for employees and their families could dramatically reduce turnover and absenteeism (Teagarden et al., 1992; Jun et al., 2004). Attitude of employee towards quality. Employee’s attitude towards quality is another important hindrance in effective implementation of any quality program. Difﬁculty in changing the mindset of employee with regard to quality and urgency among them are reasons which generally obstructs the movement of quality program. Studies showed that it is important for top-management to take a leadership role and show a strong commitment at the time of implementing TQM to encourage employee towards quality (Rivers and Bae, 1999; Lee and Asllani, 1997). Change of employee attitude towards quality requires training and education as well as sense of CQI culture, which can be built through committed leadership efforts. Employees have to be made to feel that quality adds improvement in productivity, services, and reduce costs and they are directly or indirectly responsible for customer satisfaction (Mosadegh Rad, 2004). Lack of proper training and education. There are evidences that lack of proper training and education exists at all levels of an organization, and that it is a large contributor to worker resistance (Whalen and Rahim, 1994). A successful TQM environment requires a committed, well-trained, and educated work force that participates fully in quality improvement activities. Insufﬁcient training on quality as well as training in problem identiﬁcation and problem solving techniques leads to failure in TQM implementation program. However, it should be noted that training programs that are effectively designed can be incorrectly implemented. For example, Tatikonda and Tatikonda (1996) analyzed such a failure where employees learned statistical process control (SPC) technique, but were not informed as to where to use it. Newall and Dale (1990) and ¨ ¨ Ljungstrom and Klefsjo (2002) have also reported in their studies that poor education and training acts as a major barrier in the development and implementation of quality program. Lack of coordination between departments. Poor coordination between departments is one of the critical barriers that an organization inhibits. Employee relations and coordination between departments inﬂuence the performance of the organizational system and consequently determine the nature and extent of TQM implementation (Sureshchandar et al., 2001). Amar and Zain (2002) found that the culture and interdepartmental relations are critical to TQM initiatives. Additionally, lack of coordination between departments is seen to be detrimental to successful TQM implementation. For example, it was observed that there are very wide differences of opinion between the quality and production departments on many organization-related matters (Amar and Zain, 2002). Weak internal communication within the departments can also cause lack of coordination between departments and thus, leads to major barrier to TQM implementation.
Human resource barrier. Human resource problem is an important barrier to Using ISMsuccessful TQM implementation. Newall and Dale (1990) found that many quality approachdepartments were overworked and understaffed leading to TQM failure. Juran (1986)reported that although the return on investment for a quality improvement project isvery high, many organizations fail to provide the adequate human resource necessaryto achieve signiﬁcant results. Some studies have predicted human resource barrierssuch as non-participation of employees, low knowledge and experience about TQM, 569lack of culture and geographic homogeneity, lack of non-monetary motivationmechanisms, the tedious aspect of writing procedures, and low wages and salaries, asmajor obstacles to successful TQM implementation (Francois et al., 2003; MosadeghRad, 2004; Huang et al., 1999). No benchmarking. Benchmarking is a continuous systematic process of measuringthe products, services, and practices against those of competitive organization leaders(Saravanan and Rao, 2006). Absence of benchmarking in the organization leads to lack ofCQI culture and competitiveness. Organization cannot achieve global standards withoutbenchmarking the critical business processes. Al-Zamany et al. (2002) examined thatregular meetings to review and improve the strategic plans will help in achieving thewell deﬁned goals and targets, and results to removal of no-benchmarking barrier inthe organization. A recent study showed that despite the beneﬁts of benchmarking,it is seldom applied within the organization due to lack of feasible tools organizationsdevelop internally which are often unstructured, to compare their business practice with ¨the practice of others (Bjorklund, 2010). Further, Presley and Meade (2010) present aframework for performance measurement and benchmarking as two tools which canassist organizations to realize the beneﬁts and sustainability in construction industry.Overall, the organization can be transformed to world class status when benchmarkingis directed at the key business processes. Poor planning. The absence of a sound strategic planning by the top-managementhas often contributed to ineffective quality improvement (Whalen and Rahim, 1994).Juran (1986) reported that some managers even gave quality planning a low priority.Though, the pre-planning stage of developing the right attitude and level of awareness isconsidered crucial in achieving success in a quality improvement program (Oakland,1989). Newall and Dale (1990) observed that a large number of organizations are eitherunable or not willing to plan effectively for quality improvement. Therefore, careful anddetailed planning is needed prior to the implementation of any quality program andorganizations should identify beforehand the stages that their processes undergo. Employees’ resistance to change. Employees’ resistance to adopt the change is acommon barrier that every organization experiences while implementing any qualityimprovement program. Employees may perceive TQM as controlling rather thanempowering. They feel that TQM ask them to work harder for fewer rewards(Mosadegh Rad, 2005). Newall and Dale (1990) found that aging workers as well asworkers, who suffer from illiteracy or language barrier, may resist the implementation ofnew ideas and new concepts. On the other hand, Blankstein (1996) reported thatprofessionals and educated employees also resist to change as they expect autonomyand academic freedom, as in case of higher education. To resolve these problems,management should clarify organization’s quality strategies and polices, motivateemployees in order to participate actively in quality planning, decision making,
BIJ processes improvement, and use of employee ideas and suggestions in quality18,4 management (Mosadegh Rad, 2005). Inadequate use of empowerment and teamwork. Employee empowerment and teamwork are critical factors in TQM. Most TQM programs place substantial emphasis on teamwork and problem-solving groups. Newall and Dale (1990) found that teams are seldom-fully used and their individual members are often contended. They suggested570 that these problems are caused by lack of feedback. Likewise, Adebanjo and Kehoe (1998), studied TQM implementation in UK manufacturing organizations, investigated the reason for inadequate use of empowerment and teamwork among the organization. They found insufﬁcient teamwork facilitators and absence of team building techniques in the organization. Oakland (1989) pointed out that it is important for the teams to focus on issues and use time as efﬁciently as possible. Lack of continuous improvement culture. Continuous improvement is increasingly becoming the life-line for a TQM organization. Absence of continuous improvement culture in the organization leads to total failure of TQM program. Deming (1986) and Schneider et al. (1996) emphasized the importance of continuous improvement culture with the goal of zero defects. Al-Zamany et al. (2002) reported that lack of continuous improvement culture in the organization may be due to the following reasons: . unhealthy habits of the managers and executives; . weak sense of responsibility of the managers; . absence of assessment activities in the organizations; . appointment of unqualiﬁed managers; and . lack of effective action to force improvement. Lack of communication. Poor communication is one of the major barriers found to hinder TQM efforts in an organization. Gunasekaran (1999) identiﬁed the enablers of TQM implementation in one of the British manufacturing company through interview of employees from different departments of the organization. He reported that among people oriented factors, communication between managers, supervisor, and staff, was the major enabler of TQM implementation, and poor communication between departments was a real barrier to implementation of TQM. Lack of communication across the organization often results to unsatisﬁed customers, unfulﬁlled customer requirements, and environment of distrust. Al-Zamany et al. (2002) argued that in most of the cases the management resists in sharing important information with the employees for several reasons. This would create the environment of distrust and conﬂict among management and employees. ISM methodology and development of the relationship model ISM methodology is an interactive learning process and helps to improve order and direction on the complex relationships among variables of a system (Sage, 1977). In this, a set of different and directly related variables affecting the system under consideration is structured into a comprehensive systemic model. The model so formed portrays the structure of a complex issue, a system of a ﬁeld of study, in a carefully designed pattern employing graphics as well as words (Singh et al., 2003; Ravi and Shankar, 2005; Faisal et al., 2006).
ISM is a powerful qualitative tool which can be applied in various ﬁelds. Saxena et al. Using ISM(1990) have identiﬁed the key variables using direct as well as indirect interrelationships approachamongst the variables and presented the results of the application of ISM methodologyto the case of energy conservation in Indian cement industry. Mandal and Deshmukh(1994) used the ISM methodology to analyze some of the important vendor selectioncriteria and have shown the interrelationships of criteria and their levels. Singh et al.(2003) have utilized this technique for the implementation of knowledge management in 571engineering industries. Bolanos et al. (2005) applied ISM methodology in improvingdecision making process among executives working in different functional areas whileQureshi et al. (2007) developed a model for the logistics outsourcing relationshipvariables to enhance shipper’s productivity and competitiveness in logistical supplychain using ISM based approach. Faisal et al. (2006) found ISM application in supplychain risk mitigation in Indian manufacturing SMEs. Hasan et al. (2007) exploredvarious barriers in adopting agile manufacturing and established a relationship amongthese barriers through the ISM methodology. Beside this, Raj et al. (2008) conducted acase a study and applied ISM approach for modeling the enablers of ﬂexiblemanufacturing system. Finally, a recent study conducted by Sahney et al. (2010)proposed a quality framework for Indian higher education system particularly foradministrative staff. The framework was developed through the application of ISM. A number of barriers exist in the implementation of TQM in serviceorganizations. An examination of the direct and indirect relationship between thesebarriers of TQM can give a clear picture of the situation than considering individualfactors alone in isolation. The ISM can be judiciously employed for getting betterinsights into the system under consideration. The process of ISM begins withthe identiﬁcation of variables that could be related to each other in a system. Direct andindirect relationships are identiﬁed between these variables, which are then convertedinto a matrix that is ﬁnally structured into a digraph model through a hierarchicalconﬁguration (Figure 1). 3 5 9 1 10 6 4 11 7 Figure 1. Digraph depicting the 8 2 relationship among 12 the TQM barriers
BIJ The ISM technique follows a systematic methodology. The various steps involved in18,4 ISM technique when applied to the 12 identiﬁed barriers (or variables) as explained in the previous section are as follows: (1) The 12 barriers are listed and numbered as barriers 1-12 (Table I). These barriers are identiﬁed through literature review and discussion with the experts of the relevant area.572 (2) Barriers identiﬁed in the ﬁrst step are arranged in rows and columns, a matrix is developed for the barriers, by relating each of the barriers with the other barrier, one by one, pair-wise, through rows and columns. A contextual relationship is thus, established among barriers in terms of “V”, “A”, “X”, and “O” which are explained in the next section. (3) On the basis of pair-wise relationship between barriers of the system as obtained from step-2, a structural self-interaction matrix (SSIM) is developed for barriers (Table II). (4) A reachability matrix is then developed from the SSIM by converting the information in each cell entry of the SSIM obtained from step-3 into binary numbers “1” and “0” and thus, an initial reachability matrix is constructed (Table III). (5) The initial matrix, obtained from step-4, is checked for transitivity and modiﬁcations (if any) are made. The transitivity of the contextual relation is a basic assumption made in ISM. It states that if a barrier (or variable) “i” is related to “j” and “j” is related to “k”, then “i” is necessarily related to “k”. Thus, a ﬁnal reachability matrix is obtained (Table IV). (6) The ﬁnal reachability matrix obtained in step-5 is partitioned into different levels on the basis of the reachability and antecedents sets for each of the barriers and through a series of iterations (Tables V-XII). (7) On the basis of the levels partitions obtained from step-6 and a ﬁnal reachability matrix (step-5), a conical matrix (lower triangular matrix) is constructed (Table XIII). A directed graph or digraph is drawn and transitive links are removed. Barrier no. Barrier 12 11 10 9 8 7 6 5 4 3 2 1 1 Lack of top-management commitment V V V V V V V V V V V – 2 High turnover at management level A A A O A A O A A A – 3 Attitude of employees towards quality V V V V V O V A X – 4 Lack of proper training and education X V V V V V O A – 5 Lack of coordination between department V V V V V V V – 6 Human resource barrier O V A V A O – 7 No benchmarking A V A O A – 8 Poor planning A V V V – 9 Employee’s resistance to change O A A – 10 Inadequate use of empowerment and A V –Table II. teamworkStructural self-interaction 11 Lack of continuous improvement culture A –matrix 12 Lack of communication –
Using ISMBarrier no. Barriers 1 2 3 4 5 6 7 8 9 10 11 12 approach 1 Lack of top-management commitment 1 1 1 1 1 1 1 1 1 1 1 1 2 High turnover at management level 0 1 0 0 0 0 0 0 0 0 0 0 3 Attitude of employees towards quality 0 1 1 1 0 1 0 1 1 1 1 1 4 Lack of proper training and education 0 1 1 1 0 0 1 1 1 1 1 1 5 Lack of coordination between department 0 1 1 1 1 1 1 1 1 1 1 1 573 6 Human resource barrier 0 0 0 0 0 1 0 0 1 0 1 0 7 No benchmarking 0 1 0 0 0 0 1 0 0 0 1 0 8 Poor planning 0 1 0 0 0 1 1 1 1 1 1 0 9 Employee’s resistance to change 0 0 0 0 0 0 0 0 1 0 0 010 Inadequate use of empowerment and teamwork 0 1 0 0 0 1 1 0 1 1 1 011 Lack of continuous improvement culture 0 1 0 0 0 0 0 0 1 0 1 0 Table III.12 Lack of communication 0 1 0 1 0 0 1 1 0 1 1 1 Initial reachability matrixBarrier Drivingno. Barriers 1 2 3 4 5 6 7 8 9 10 11 12 power Rank 1 Lack of top- management commitment 1 1 1 1 1 1 1 1 1 1 1 1 12 I 2 High turnover at management level 0 1 0 0 0 0 0 0 0 0 0 0 1 VIII 3 Attitude of employees towards quality 0 1 1 1 0 1 1† 1 1 1 1 1 10 III 4 Lack of proper training and education 0 1 1 1 0 1† 1 1 1 1 1 1 10 III 5 Lack of coordination between department 0 1 1 1 1 1 1 1 1 1 1 1 11 II 6 Human resource barrier 0 1† 0 0 0 1 0 0 1 0 1 0 4 VI 7 No benchmarking 0 1 0 0 0 0 1 0 1† 0 1 0 4 VI 8 Poor planning 0 1 0 0 0 1 1 1 1 1 1 0 7 IV 9 Employee’s resistance to change 0 0 0 0 0 0 0 0 1 0 0 0 1 VIII10 Inadequate use of V empowerment and teamwork 0 1 0 0 0 1 1 0 1 1 1 0 611 Lack of continuous improvement culture 0 1 0 0 0 0 0 0 1 0 1 0 3 VII12 Lack of communication 0 1 1† 1 0 1† 1 1 1† 1 1 1 10 III Dependence Power 1 11 5 5 2 8 8 6 11 7 10 5 Rank VIII I VI VI VII III III V I IV II VI Table IV.Note: 1† entries are included to incorporate transitivity Final reachability matrix (8) The resultant digraph obtained from step-7 is converted into an ISM, by replacing barriers nodes with statements (Figure 2). (9) Finally, the ISM model developed in step-8 is reviewed to check for conceptual inconsistency and necessary modiﬁcations are incorporated through expert opinions.
BIJ Barriers (Bi) Reachability set R(Bi) Antecedent set A (Bi) Intersection set R(Bi) > A(Bi) Level18,4 1 1,2,3,4,5,6,7,8,9,10,11,12 1 1 2 2 1,2,3,4,5,6,7,8,10,11,12 2 I 3 2,3,4,6,7,8,9,10,11,12 1,3,4,5,12 3,4,12 4 2,3,4,6,7,8,9,10,11,12 1,3,4,5,12 3,4,12574 5 2,3,4,5,6,7,8,9,10,11,12 1,5 5 6 2,6,9,11 1,3,4,5,6,8,10,12 6 7 2,7,9,11 1,3,4,5,7,8,10,12 7 8 2,6,7,8,9,10,11 1,3,4,5,8,12 8 9 9 1,3,4,5,6,7,8,9,10,11,12 9 I 10 2,6,7,9,10,11 1,3,4,5,8,10,12 10Table V. 11 2,9,11 1,3,4,5,6,7,8,10,11,12 11Barrier level iteration i 12 2,3,4,6,7,8,9,10,11,12 1,3,4,5,12 3,4,12 Barriers (Bi) Reachability set R(Bi) Antecedent set A (Bi) Intersection set R(Bi) > A(Bi) Level 1 1,3,4,5,6,7,8,10,11,12 1 1 3 3,4,6,7,8,10,11,12 1,3,4,5,12 3,4,12 4 3,4,6,7,8,10,11,12 1,3,4,5,12 3,4,12 5 3,4,5,6,7,8,10,11,12 1,5 5 6 6,11 1,3,4,5,6,8,10,12 6 7 7,11 1,3,4,5,7,8,10,12 7 8 6,7,8,10,11 1,3,4,5,8,12 8 10 6,7,10,11 1,3,4,5,8,10,12 10Table VI. 11 11 1,3,4,5,6,7,8,10,11,12 11 IIBarrier level iteration ii 12 3,4,6,7,8,10,11,12 1,3,4,5,12 3,4,12 Barriers (Bi) Reachability set R(Bi) Antecedent set A (Bi) Intersection set R(Bi) > A(Bi) Level 1 1,3,4,5,6,7,8,10,12 1 1 3 3,4,6,7,8,10,12 1,3,4,5,12 3,4,12 4 3,4,6,7,8,10,12 1,3,4,5,12 3,4,12 5 3,4,5,6,7,8,10,12 1,5 5 6 6 1,3,4,5,6,8,10,12 6 III 7 7 1,3,4,5,7,8,10,12 7 III 8 6,7,8,10 1,3,4,5,8,12 8Table VII. 10 6,7,10 1,3,4,5,8,10,12 10Barrier level iteration iii 12 3,4,6,7,8,10,12 1,3,4,5,12 3,4,12 Structural self-interaction matrix After identifying and enlisting 12 barriers through literature review and experts opinion, there analysis is carried out. A contextual relationship of “leads to” type is chosen. This means that one variable leads to another variable. Based on this principle, a contextual relationship is developed. Some experts, both from service organizations and academia, have been consulted in developing the contextual relationship among the barriers. In this study a team of 12 members participated which comprises of three core members,
two quality experts, three from service organizations, and four from academia, having vast Using ISMexperience in ﬁeld of service quality, product quality, TQM, quality implementation, and approachservice marketing. Expert group is hailed from service organizations namely: . Banks. . Hospitals. . Information and communication technology organizations. 575Barriers (Bi) Reachability set R(Bi) Antecedent set A (Bi) Intersection set R(Bi) > A(Bi) Level 1 1,3,4,5,8,10,12 1 1 3 3,4,8,10,12 1,3,4,5,12 3,4,12 4 3,4,8,10,12 1,3,4,5,12 3,4,12 5 3,4,5,8,10,12 1,5 5 8 8,10, 1,3,4,5,8,12 810 10 1,3,4,5,8,10,12 10 IV Table VIII.12 3,4,8,10,12 1,3,4,5,12 3,4,12 Barrier level iteration ivBarriers (Bi) Reachability set R(Bi) Antecedent set A (Bi) Intersection set R(Bi) > A(Bi) Level 1 1,3,4,5,8,12 1 1 3 3,4,8,12 1,3,4,5,12 3,4,12 4 3,4,8,12 1,3,4,5,12 3,4,12 5 3,4,5,8,12 1,5 5 8 8 1,3,4,5,8,12 8 V Table IX.12 3,4,8,12 1,3,4,5,12 3,4,12 Barrier level iteration vBarriers (Bi) Reachability set R(Bi) Antecedent set A (Bi) Intersection set R(Bi) > A(Bi) Level 1 1,3,4,5,12 1 1 3 3,4,12 1,3,4,5,12 3,4,12 VI 4 3,4,12 1,3,4,5,12 3,4,12 VI 5 3,4,5,12 1,5 5 Table X.12 3,4,12 1,3,4,5,12 3,4,12 VI Barrier level iteration viBarriers (Bi) Reachability set R(Bi) Antecedent set A (Bi) Intersection set R(Bi) > A(Bi) Level1 1,5 1 1 Table XI.5 5 1,5 5 VII Barrier level iteration viiBarriers (Bi) Reachability set R(Bi) Antecedent set A (Bi) Intersection set R(Bi) > A(Bi) Level Table XII.1 1 1 1 VIII Barrier level iteration viii
BIJ Barrier no. Barriers 2 9 11 6 7 10 8 3 4 12 5 118,4 2 High turnover at management level 1 0 0 0 0 0 0 0 0 0 0 0 9 Employee’s resistance to change 0 1 0 0 0 0 0 0 0 0 0 0 11 Lack of continuous improvement culture 1 1 1 0 0 0 0 0 0 0 0 0 6 Human resource barrier 1 1 1 1 0 0 0 0 0 0 0 0576 7 No benchmarking 1 1 1 0 1 0 0 0 0 0 0 0 10 Inadequate use of empowerment and teamwork 1 1 1 1 1 1 0 0 0 0 0 0 8 Poor planning 1 1 1 1 1 1 1 0 0 0 0 0 3 Attitude of employees towards quality 1 1 1 1 1 1 1 1 1 1 0 0 4 Lack of proper training and education 1 1 1 1 1 1 1 1 1 1 0 0 12 Lack of communication 1 1 1 1 1 1 1 1 1 1 0 0Table XIII. 5 Lack of coordination between department 1 1 1 1 1 1 1 1 1 1 1 0Conical matrix 1 Lack of top-management commitment 1 1 1 1 1 1 1 1 1 1 1 1 High turnover at Employee’s resistance management level (2) to change (9) Lack of continuous improvement culture (11) No benchmarking (7) Human resource barrier (6) Inadequate use of empowerment and teamwork (10) Poor planning (8) Lack of proper Attitude of Lack of training and employees towards communication (12) education (4) quality (3) Lack of coordination between departments (5)Figure 2.ISM-based model of TQMbarriers for serviceindustries Lack of top-management commitment (1)
Keeping in mind the contextual relationship for each barrier, the existence of a relation Using ISMbetween any two barriers (i and j) and the associated direction of this relation has been approachdecided as depicted in Figure 1. The following four symbols have been used to denotethe direction of the relationship between the two barriers (i and j): (1) V ¼ is used for the relation from barrier i to barrier j (i.e. if barrier i “will help achieve” or “will help alleviate” barrier j). 577 (2) A ¼ is used for the relation from barrier j to barrier i (i.e. if barrier j “will be achieved by” or “will be alleviated by barrier i). (3) X ¼ is used for both direction relations (i.e. if barriers i and j “help achieve each other”). (4) O ¼ is used for no relation between two barriers (i.e. if barriers i and j are not related).Based on the contextual relationship between barriers, the SSIM has been developed.The SSIM is discussed with the experts. Based on their responses, SSIM has beenﬁnalized and is presented in Table II. The following statements explain the use ofsymbols in SSIM: . Symbol “V” is assigned to cell (1,5) because barrier “1” (i.e. lack of top-management commitment) inﬂuences or leads to barrier “5” (i.e. lack of coordination between department). . Symbol “A” is assigned to cell (2,11) because removal of barrier 11 (i.e. “lack of continuous improvement culture”) would help alleviate Barrier 2 (i.e. high turnover at management level). . Symbol “X” is assigned to cell (3,4) because barriers 3 (i.e. “attitude of employee towards quality”) and 4 (i.e. “lack of proper training and education”) inﬂuences each other. . Symbol “O” is assigned to cell (6,7) because barriers 6 (i.e. “human resource barrier”) and 7 (i.e. “no benchmarking”) are not related.Reachability matrix (initial and ﬁnal)To develop the reachability matrix from SSIM, two sub-steps were followed. In the ﬁrstsub-step, the SSIM table is converted into the initial reachability matrix by transformingthe information of each cell of SSIM into binary digits “0s” and “1s” in the initialreachability matrix. The rules for the substitution are as follows: . If the cell (i,j) is assigned with symbol “V” in the SSIM, then this cell (i,j) entry becomes “1” and the cell ( j,i) entry becomes “0” in the initial reachability matrix. . If the cell (i,j) is assigned with symbol “A” in the SSIM, then, this cell (i,j) entry becomes “0” and the cell ( j,i) entry becomes “1” in the initial reachability matrix. . If the cell (i,j) is assigned with symbol “X” in the SSIM, then, this cell (i,j) entry becomes “1” and the cell (j,i) entry also becomes “1” in the initial reachability matrix. . If the cell (i,j) is assigned with symbol “O” in the SSIM, then, this cell (i,j) entry becomes “0” and the cell (j,i) entry also becomes “0” in the initial reachability matrix.
BIJ Following these rules, initial reachability matrix for the barriers is developed and is18,4 shown in Table III. In the second sub-step, ﬁnal reachability matrix is obtained by incorporating the transitivity as explained in step 5 of the ISM methodology. The ﬁnal reachability matrix will then consist of some entries from the pair-wise comparison and some inferred entries. After incorporating the transitivity concept as described earlier, the ﬁnal578 reachability matrix is obtained and is presented in Table IV where in transitivity is marked as 1†. In this table, the driving power and dependence of each barrier are also shown along with the ranking of the barriers is also done. The driving power of a particular barrier is the total number of barriers (including itself) which it may help achieve. The dependence is the total number of barriers which may help achieving it. These driving power and dependencies will be used in the MICMAC analysis, where the barriers will be categorized into four clusters: autonomous (cluster I), dependent (cluster II), linkage (cluster III), and independent also called driver barriers (cluster IV). Level partitions Based on the suggestions of Warﬁeld (1974) and Farris and Sage (1975), the reachability and antecedent set for each barrier is found out from ﬁnal reachability matrix. The reachability set for a particular barrier consists of the barrier itself and the other barriers, which it may help achieve. Similarly, the antecedent set consists of the barrier itself and the other barriers which may help in achieving them. After ﬁnding the reachability set and antecedent set for each barrier, the intersection for these sets is derived for all the barriers. The barriers for which the reachability and the intersection sets are the same is given the top-level barrier in the ISM hierarchy, which would not help achieve any other barrier above their own level. After the identiﬁcation of the top-level barrier, it is removed from the other remaining barriers. From Table V, it is seen that “high turnover at management level” (Barrier 2) and “employee’s resistance to change” (Barrier 9) are found at level I. Thus, it would be positioned at the top of the ISM model. This iteration is continued till the levels of each barrier are determined. The levels so determined help in building the digraph and the ﬁnal model of ISM. The barriers along with their reachability set, antecedent set, intersection set, and the different levels, are shown in Tables V-XII. Further, level identiﬁcation process of these barriers is completed in eight iterations. Developing conical matrix Conical matrix is achieved from partitioned reachability matrix by rearranging the barriers according to their level, which means all the barriers having same levels are clubbed together. Barriers 2 (high turnover at management level) and 9 (employee’s resistance to change) are found at level I, while Barrier 11 (lack of continuous improvement culture) is having level II, whereas barriers 7 (no benchmarking) and 6 (human resource barrier) are having level III. Similarly, all the barriers are clubbed as per their level partition shown in Tables V-XII. After rearranging, the conical matrix is obtained, which is depicted in Table XIII. The conical matrix helps in the generation of the digraph and later on structural model. Building the ISM-based model (Digraph) Based on the conical matrix, an initial digraph including transitivity links is obtained. This is generated by nodes and lines of edges. After removing the indirect links,
a ﬁnal digraph is developed and is than ﬁnally converted into the ISM model by Using ISMreplacing nodes of the barriers with statements as shown in Figure 2. In this approachdevelopment, the top level barriers are positioned at the top of the digraph and secondlevel barrier is placed at second position and so on, until the bottom level is placed at thelowest position in the digraph (Figure 2). The ISM model developed in this research depicts that “lack of top-managementcommitment” (Barrier 1) is very signiﬁcant barrier to TQM implementation especially in 579service organization as it comes at the base of the ISM hierarchy. “High turnover atmanagement level” (Barrier 2) and “employee’s resistance to change” (Barrier 9) are theTQM barriers on which the effectiveness of the TQM program overall depends. Thesebarriers have appeared at the top of the hierarchy (Level I). “Lack of top-management commitment” (Barrier 1) leads to “lack of coordinationbetween departments” (Barrier 5), which results in “lack of communication” (Barrier 12),“lack of proper training and education” (Barrier 4), and “attitude of employees towardsquality” (Barrier 3). A healthy relationship between department and employees should bemaintained as it inﬂuence the performance of the organization and consequentlydetermine the nature and extent of TQM implementation (Sureshchandar et al., 2001) asotherwise it may lead to “lack of communication” (Barrier 12) which would effect theimplementation of effective training and education program (Barrier 4) as both areinterrelated. Beside this “lack of communication” (Barrier 12) also propagate the “attitudeof employee’s towards quality” (Barrier 3) which will hinder the implementation of TQMprogram in the organization. Therefore, “lack of communication” (Barrier 12), “lack ofproper training and education” (Barrier 4), and “attitude of employee’s towards quality”(Barrier 3) should be addressed at the same level. “Poor planning” (Barrier 8) propagates through Barriers 12, 4 and 3, if there is ﬂow ofcommunication in the organization, proper training and education is imparted andemployee’s attitude towards quality is developed than barrier of poor planning will beremoved and a an effective planning will emerged out. Further, a good strategic planningshould be in place that could benchmark organization’s activities and practices againstthose of competitive organization leaders (Saravanan and Rao, 2006) as well as makeuse of available human resources effectively as otherwise it may lead to problems like“inadequate use of empowerment and teamwork” (Barrier 10), “no benchmarking”(Barrier 7), and “human resource barrier” (Barrier 6) which would counter to theobjective of providing quality products and services to the customers. Also, absence ofbenchmarking in the organization leads to “lack of continuous quality improvementculture” (Barrier 11). Organization cannot achieve global standards withoutbenchmarking critical business processes (Saravanan and Rao, 2006). “Human resourcebarrier” (Barrier 6) enhance the “lack of continuous improvement culture” (Barrier 11), asinsufﬁcient work force as well as incompetent and untrained employees will result in lackof continuous improvement culture. Without development of continuous improvementculture, it would be difﬁcult to improve the “high turnover at management level” (Barrier 2)and barrier of “employee’s resistance to change” (Barrier 9).MICMAC analysisThe MICMAC principle, also called as cross-impact matrix multiplication applied toclassiﬁcation, is based on multiplication properties of matrices (Sharma et al., 1995).The purpose of MICMAC analysis is to analyze the driver power and dependence power
BIJ of variables (Mandal and Deshmukh, 1994). The barriers (or variables) are categorized18,4 into four clusters (Figure 3). The ﬁrst cluster (I) contains “autonomous barriers” that have weak driver power and weak dependence. These barriers are relatively disconnected from the system, with which they have only few links, which may be strong. Second cluster (II) contains “dependent barriers” that have weak driver power but strong dependence. Third cluster (III) has the linkage barriers that have strong580 driving power and also strong dependence. These barriers are unstable in the fact that any action on these barriers will have an effect on others and also a feedback on themselves. Fourth cluster (IV) includes the independent barriers having strong driving power but weak dependence. Driving power and dependence is the summation of binary digit “1s” in their respective row and column for each barrier, respectively, in the ﬁnal reachability matrix shown in Table IV. Subsequently, the driver power-dependence diagram is constructed which is shown in Figure 3. As an illustration, it is observed from Table IV that Barrier 1 is having a driver power of “12” and a dependence of “1”. Therefore, in this ﬁgure, it is positioned at a place corresponding to a driver power of “12” and a dependence of “1”. Discussion and conclusion The main objective of this research is to analyze the interaction among the various barriers of TQM which hinder in the successful implementation of TQM and to develop a hierarchy of TQM barriers that would help in understanding these barriers in service organizations. Therefore, an ISM-based model on TQM barriers has been developed. These barriers assumes importance because they hinder the TQM implementation program and pose considerable challenges both for managers and practitioners of TQM in service organizations. Some of the major barriers have been discussed here and placed into an ISM model, to analyze the interaction between these barriers. The present Strong 12 1 11 5 10 3,4,12 4 IV III 9 8 Driving power 7 8 6 10 5 4 6,7 3 11 I II 2 Weak 1 2,9 9 0 0 1 2 3 4 5 6 7 8 9 10 11 12 Weak Dependence StrongFigure 3.Driving power and Notes: I autonomous barrier; II dependent barrier; III linkage barrier;dependence diagram IV independent (driver) barrier
research emphasize that there is need to overcome these barriers for the success of TQM Using ISMin the service organizations in order to improve organization performance and gain approachcustomer satisfaction. This study can serve an eye opener for those service organizationsthat lacks top-management commitment and coordination among departments whichare found to be major barriers of TQM implementation program in an organization. The driver power-dependence matrix diagram (Figure 3) gives some valuableinsights about the relative importance and the interdependencies among the TQM 581barriers. This can give better insights to the top-management so that they canproactively deal with these barriers. Some of the observations from the ISM model,which give important managerial implications, are discussed below: . Figure 3 shows that there are no autonomous barriers seen in the driver-dependence diagram. The absence of these barriers in the present study indicates that all the considered barriers play a signiﬁcant role in hindering the implementation of TQM program. The management therefore, should pay attention to all the considered barriers for a successful implementation of TQM program. . Barriers such as “high turn over at management level”, “employee’s resistance to change”, “lack of continuous improvement culture”, “no benchmarking”, “human resource barrier”, and “inadequate use of empowerment and teamwork” are possessing weak driving powers but strong dependency on other barriers. They are seen at the top of the ISM hierarchy (Figure 2). These barriers represent the unfavorable outcome to the managers and practitioners of service organizations. Hence, managers should take special care to handle these barriers. . No barriers are seen as a linkage barrier that has a strong driving power as well as strong dependence. Thus, it can be deduced that all the barriers of TQM identiﬁed are stable. . Finally, the driver power-dependence diagram indicates that independent barriers such as “lack of top-management commitment”, “lack of coordination between departments”, “lack of communication”, “lack of proper training and education”, “attitude of employees towards quality”, and “poor planning” are at the bottom of ISM hierarchy, having strong driving power and weak dependence. Thus, management should place a high priority in tackling these barriers which have capability of inﬂuencing other barriers. They may be treated as the “major barrier” to TQM implementation.The main contribution of this research includes the following: . In the present research paper, an attempt has been made to identify the major barriers to TQM implementation in service organizations and is brought at one platform. Though, few research papers are available on TQM barriers, but no study is taken to understand the interaction among these major barriers. Also, there is no study on the development of model on barriers of TQM which could help to develop the relationship between them so that these barriers may be omitted or minimized. The present ISM based model will help managers and practitioners of TQM to understand the relationship crux. Hence, this research assumes importance in this context.
BIJ . A key ﬁnding of this research is that “lack of top-management commitment” and18,4 “lack of coordination between departments” are signiﬁcant barriers. From the ISM model, it is observed that “lack of top-management commitment” and “lack of coordination between various departments” are at the bottom level of the hierarchy implying higher driving power. Therefore, management should focus on developing commitment and leadership within the organization and develop582 coordinal environment for healthy relationship between different departments to create quality culture and awareness about the beneﬁts of TQM program so the same can be reaped. . In this research, there are number of barriers responsible for high turnover at management level and employee’s resistance to change. These barriers of TQM are modeled in terms of their driving and dependence powers which have been carried out. Those barriers possessing higher driving power in the ISM need to be dealt with care on priority basis because they inﬂuence high turnover at management level and employee’s resistance to change. . In the present research, the proposed ISM-based model for identiﬁcation and ranking of TQM barriers can provide the decision makers and practitioners a more realistic representation of the problem in the course of implementing TQM in their organization. A major contribution of this research paper lies in the development of contextual relationship among various identiﬁed barriers of TQM through a single systemic framework. The utility of the proposed ISM methodology lies in imposing order and direction on the complexity of relationships among these barriers which would help the decision makers and practitioners of TQM to better utilize their available resources for minimizing the barriers in the service organizations. Finally, it would be useful to suggest the direction of future research in this area. The present model has not been statistically tested and validated. Thus, the model is required to be statistically tested and validated using different approaches one of them is the “Structural Equation Modeling” (SEM) approach, also referred to as linear structural relationship approach. Statistical software like Amos 16.0, Lisrel 8.8 can be used in future to build correlation matrix, conﬁrmatory factor analysis (CFA), and diagramming to validate the relationships. Comparing ISM and SEM, SEM has the capability of statistically testing an already developed theoretical model whereas ISM on the other hand has the capability to develop an initial model through managerial techniques such as brainstorming, nominal group techniques and idea engineering. In this way, ISM is a supportive analytic tool for this situation. However, it may be suggested that due to complimentary nature of both of these techniques, the future research may be directed in ﬁrst developing an initial model using ISM and then testing it using SEM. ISM also helps in classifying variable into dependent, independent, autonomous, and link categories. Management may use their resources over identiﬁed factors thus, optimization of the resources may be accomplished. Further, the systemic framework proposed in this study has wide application and can be used to improve performance, administrative abilities, and effectiveness of the organization. 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. 275-86.
Al-Zamany, Y., Hoddell, E.J. and Savage, B.M. (2002), “Understanding the difﬁculties of Using ISM implementing quality management in Yemen”, The TQM Magazine, Vol. 14 No. 4, pp. 240-7. approachAmar, K. and Zain, M.Z. (2002), “Barriers to implementing TQM in Indonesian manufacturing organizations”, The TQM Magazine, Vol. 14 No. 6, pp. 367-72.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. 206, pp. 636-50. 583Bhat, K.S. and Rajashekhar, J. (2009), “An empirical study of barriers to TQM implementation in Indian industries”, The TQM Magazine, Vol. 21 No. 3, pp. 261-72. ¨Bjorklund, M. (2010), “Benchmarking tool for improved corporate social responsibility in purchasing”, Benchmarking: An International Journal, Vol. 17 No. 3, pp. 340-62.Blankstein, A.M. (1996), “Why TQM can’t work-and a school where it did”, Education Digest, Vol. 62 No. 1, pp. 27-30.Bolanos, R., Fontela, E., Nenclares, A. and Paster, P. (2005), “Using interpretive structural modeling in strategic decision making groups”, Management Decision, Vol. 43 No. 6, pp. 877-95.Bou-Llusar, J.C. and Beltran-Martin, I. (2005), “TQM, high-commitment human resource strategy and ﬁrm performance: as empirical study”, Total Quality Management, Vol. 16 No. 1, pp. 71-86.Brah, S.A., Wong, J.L. and Rao, B.M. (2000), “TQM and business performance in the service sector: a Singapore study”, International Journal of Operations & Production Management, Vol. 20 No. 11, pp. 1293-312.Brigham, S.E. (1993), “Lessons we can learn from industry”, Change, Vol. 25 No. 3, pp. 42-7.Burr, J.T. (1993), “A new name for a not-so-new concept”, Quality Progress, pp. 87-8.Deming, W.E. (1986), Out of the Crisis, MIT, Centre for Advanced Engineering, Cambridge, MA.Dowlatshahi, S. (1998), “The role of purchasing and TQM in the Maquiladora industry”, Production & Inventory Management Journal, Vol. 39, pp. 32-49.Ellram, L. (1991), “Key success factors and barriers in international purchasing partnerships”, Management Decision, Vol. 29 No. 7, pp. 38-44.Eraqi, M.I. (2006), “Tourism services quality (TourServQual) in Egypt – the viewpoints of external and internal customers”, Benchmarking: An International Journal, Vol. 13 No. 4, pp. 469-92.Eskildson, I. (1995), “TQM’s role in corporate success: analyzing the evidence”, National Productivity Review, Vol. 14 No. 4, pp. 25-38.Evans, J.R. and Lindsay, W.M. (1996), The Management and Control of Quality, 3rd ed., West Publishing Company, St Paul, MN.Faisal, M.N., Banwet, D.K. and Shankar, R. (2006), “Supply chain risk mitigation: modeling the enablers”, Business Process Management Journal, Vol. 12 No. 4, pp. 535-52.Farris, D.R. and Sage, A.P. (1975), “On the use of interpretive structural modeling for worth assessment”, Computers and Electrical Engineering, Vol. 2 Nos 2/3, pp. 149-74.Francois, P., Peyrin, J.C., Touboul, M., Labarere, J., Reverdy, T. and Vinck, D. (2003), “Evaluating implementation of quality management systems in a teaching hospital’s clinical departments”, International Journal of Quality Health Care, Vol. 15 No. 1, pp. 47-55.Fuchsberg, G. (1993), “Total quality is termed only partial success”, The Wall Street Journal, Vol. 1, October, p. B1.Grifﬁn, R. (1988), “Consequences of quality circles in an industrial setting: a longitudinal assessment”, Academy of Management Journal, Vol. 31 No. 2, pp. 338-58.
BIJ Guangming, C., Clarke, S. and Lehaney, B. (2000), “A systemic view of organizational change and TQM”, The TQM Magazine, Vol. 12 No. 3, pp. 186-93.18,4 Gunasekaran, A. (1999), “Enablers of total quality management implementation on manufacturing: a case study”, Total Quality Management, Vol. 10 No. 7, pp. 987-96. Gunasekaran, A. (2000), “World class manufacturing in small and medium enterprises”, International Journal of Manufacturing Technology and Management, Vol. 2 Nos 1-7, pp. 777-89.584 Gunasekaran, A. and McGaughey, R.E. (2003), “TQM in supply chain management”, The TQM Magazine, Vol. 15 No. 6, pp. 361-3. Hafeez, K., Malak, N. and Abdelmeguid, H. (2006), “A framework for TQM to achieve business excellence”, Total Quality Management, Vol. 17 No. 9, pp. 1213-29. Hansson, J. and Eriksson, H. (2002), “The impact of TQM on ﬁnancial performance”, Measuring Business Excellence, Vol. 6 No. 4, pp. 44-54. Hasan, M.A., Shankar, R. and Sarkis, J. (2007), “A study of barriers to agile manufacturing”, International Journal of Agile Systems and Management, Vol. 2 No. 1, pp. 1-22. 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. 610-22. Hendricks, K.B. and Singhal, V.R. (1997), “Does implementing an effective TQM program actually improve operating performance? Empirical evidence from ﬁrms that have won quality awards”, Management Science, Vol. 43 No. 9, pp. 1258-74. Ho, S.K.M. (2010), “Integrated lean TQM model for global sustainability and competitiveness”, The TQM Journal, Vol. 22 No. 2, pp. 143-58. Huang, J., Lee, Y.W. and Wang, R.Y. (1999), Quality Information and Knowledge, Prentice-Hall, Upper Saddle River, NJ. Hubiak, W.A. and O’Donnell, S.J. (1996), “Do Americans have their minds set against TQM?”, National Productivity Review, Vol. 15, pp. 19-20. Huq, Z. (2005), “Managing change: a barrier to TQM in implementation in service industry”, Managing Service Quality, Vol. 15 No. 5, pp. 452-69. 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. Jun, M., Cai, S. and Shin, H. (2006), “Total quality management practice in Maquiladora: antecedents of employee satisfaction and loyalty”, Journal of Operations Management, Vol. 24, pp. 791-812. Juran, J.M. (1986), “The quality trilogy”, Quality Progress, August, pp. 19-24. Kaluarachchi, K.A.S.P. (2010), “Organizational culture and TQM practices: a Sri Lankan case”, The TQM Journal, Vol. 22 No. 1, pp. 41-55. Kanji, G.K. (1996), “Implementation and pitfalls of total quality management”, Total Quality Management, Vol. 7, pp. 331-43. Kendrick, J.J. (1993), “TQM: is it forging ahead or falling behind quality?”, Quality, Vol. 32 No. 5, p. 13. Knotts, R. and Tomlin, S. (1994), “A comparison of TQM practices in US and Mexico companies”, Journal of Production and Inventory Management, Vol. 35 No. 1, pp. 53-8. Koch, J.V. and Fisher, J.L. (1998), “Higher education and total quality management”, Total Quality Management, Vol. 9 No. 8, pp. 659-68. Kureshi, N., Qureshi, F. and Sajid, A. (2010), “Current health of quality management practices in service sector SME – a case study of Pakistan”, The TQM Journal, Vol. 22 No. 3, pp. 317-29.
Lawrence, J.J. and Lewis, H.S. (1993), “JIT manufacturing in Mexico: obstacles to Using ISM implementation”, Journal of Production and Inventory Management, Vol. 34 No. 3, pp. 31-5. approachLawrence, J.J. and Yeh, R. (1994), “The inﬂuence of Mexican culture on the use of Japanese manufacturing techniques in Mexico”, Management International Review, Vol. 34 No. 1, pp. 49-66.Lee, S.M. and Asllani, A. (1997), “TQM and BPR: symbiosis and a new approach for integration”, Management Decision, Vol. 35 No. 6, pp. 409-16. 585Leonard, D. (2010), “Quality management practices in the US homebuilding industry”, The TQM Journal, Vol. 22 No. 1, pp. 101-10. ¨ ¨Ljungstrom, M. and Klefsjo, B. (2002), “Implementation obstacles for a work-development-oriented TQM strategy”, Total Quality Management, Vol. 13, pp. 621-34.McDermott, T. (1994), “TQM: the total quality Maquiladora”, Business Mexico, November, pp. 42-5.Mandal, A. and Deshmukh, S.G. (1994), “Vendor selection using interpretive structural modeling (ISM)”, International Journal of Operations & Production Management, Vol. 14 No. 6, pp. 52-9.Mehra, S. and Ranganathan, S. (2008), “Implementing TQM with a focus on enhancing customer satisfaction”, International Journal of Quality & Reliability Management, Vol. 25 No. 9, pp. 913-27.Mosadegh Rad, A.M. (2004), “A step to total quality management”, Management and Development Process Quarterly, Vol. 55, pp. 32-41.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. 1747-60.Oakland, J.S. (1989), Total Quality Management, Heinemann, London.Prajogo, I. and McDermott, C.M. (2005), “The relationship between TQM practices and organizational culture”, International Journal of Operations & Production Management, Vol. 25 No. 11, pp. 1101-22.Presley, A. and Meade, L. (2010), “Benchmarking for sustainability: an application to the sustainable construction industry”, Benchmarking: An International Journal, Vol. 17 No. 3, pp. 435-51.Qureshi, M.N., Kumar, D. and Kumar, P. (2007), “Modeling the logistics outsourcing relationship variables to enhance shippers’ productivity and competitiveness in logistical supply chain”, International Journal of Productivity and Performance Management, Vol. 56 No. 8, pp. 689-714.Raj, T., Shankar, R. and Suhaib, M. (2008), “An ISM approach for modeling the enablers of ﬂexible manufacturing system: the case for India”, International Journal of Production Research, Vol. 46 No. 24, pp. 6883-912.Rajashekhar, J. (1999), “Total quality management in India-perspective and analysis”, The TQM Magazine, Vol. 11 No. 5, pp. 321-7.Ravi, V. and Shankar, R. (2005), “Analysis of interactions among the barriers of reverse logistics”, Technological Forecasting and Social Change, Vol. 72 No. 8, pp. 1011-29.Reed, R., Lemak, D.J. and Montgomery, J.C. (1996), “Beyond process: TQM content and ﬁrm performance”, Academy of Management Review, Vol. 21 No. 1, pp. 172-202.Rivers, P.A. and Bae, S. (1999), “TQM implementation in health care organizations”, Total Quality Management, Vol. 10 No. 2, pp. 281-90.
BIJ Rust, R.T., Keiningham, T.L., Clemens, S. and Zahorik, A.J. (1999), “Return on quality at Chase Manhattan Bank”, Interfaces, March-April, pp. 62-72.18,4 Sage, A.P. (1977), Interpretive Structural Modeling: Methodology for Large-scale Systems, McGraw-Hill, New York, NY, pp. 91-164. Sahney, S., Banwet, D.K. and Karunes, S. (2010), “Quality framework in education through application of interpretive structural modeling: an administrative staff perspective in the586 Indian context”, The TQM Journal, Vol. 22 No. 1, pp. 56-71. Salaheldin, S.I. (2009), “Critical success factors for TQM implementation and their impact on performance of SMEs”, International Journal of Productivity and Performance Management, Vol. 58 No. 3, pp. 215-37. Salegna, G. and Fazel, F. (2000), “Obstacles to implementing TQM”, Quality Progress, Vol. 33 No. 7, pp. 53-64. Saravanan, R. and Rao, K.S.P. (2006), “Development and validation of an instrument for measuring total quality service”, Total Quality Management, Vol. 17 No. 6, pp. 733-49. Saxena, J.P., Sushil and Vrat, P. (1990), “Impact of indirect relationships in classiﬁcation of variables – a MICMAC analysis for energy conservation system”, System Research, Vol. 7 No. 4, pp. 245-53. Schneider, B., Brief, A.P. and Guzzo, R.A. (1996), “Creating a climate and culture for sustainable organizational change”, Organizational Dynamics, Vol. 24, pp. 7-19. Sharma, H.D., Gupta, A.D. and Sushil (1995), “The objectives of waste management in India: a future inquiry”, Technological Forecasting and Social Change, Vol. 48 No. 3, pp. 285-309. Sila, I. and Ebrahimpour, M. (2005), “Critical linkages among TQM factors and business results”, International Journal of Operations & Production Management, Vol. 25 No. 11, pp. 1123-55. Singh, M.D., Shankar, R., Narain, R. and Agarwal, A. (2003), “An interpretive structural modeling of knowledge management in engineering industries”, Journal of Advances in Management Research, Vol. 1 No. 1, pp. 28-40. Soltani, E., Lai, P-C. and Gharneh, N.S. (2005), “Breaking through barrier to TQM effectiveness: lack of commitment of upper-level management”, Total Quality Management, Vol. 16 Nos 8/9, pp. 1009-21. Srikanthan, G. and Dalrymple, J. (2004), “A synthesis of a quality management model for education in universities”, The International Journal of Educational Management, Vol. 18 No. 4, pp. 266-79. Sureshchandar, G.S., Rajendran, C. and Anantharaman, R.N. (2001), “A holistic model for total quality service”, International Journal of Service Industry Management, Vol. 12, pp. 378-412. 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 & Inventory Management Journal, Vol. 37, pp. 5-9. Teagarden, M.B., Butler, M.C. and Von Glinow, M.A. (1992), “Mexico’s Maquiladora industry: where strategic human resource management makes a difference”, Organizational Dynamics, Vol. 20, pp. 34-42. Telford, R. and Masson, R. (2005), “The congruence of quality values in higher education”, Quality Assurance in Education, Vol. 13 No. 2, pp. 107-19. Van der Wiele, T. and Brown, A. (2002), “Quality management over a decade (a longitudinal study)”, International Journal of Quality & Reliability Management, Vol. 19, pp. 508-23.
Venkatraman, S. (2007), “A framework for implementing TQM in higher education programs”, Using ISM Quality Assurance in Education, Vol. 15 No. 1, pp. 89-112.Warﬁeld, J.W. (1974), “Developing interconnected matrices in structural modelling”, approach IEEE Transcript on Systems, Men and Cybernetics, Vol. 4 No. 1, pp. 81-7.Wentling, R.M. and Palma-Rivas, N. (1998), “Current status and future trends of diversity initiatives in the workplace: Diversity experts’ perspective”, Human Resource Development Quarterly, Vol. 9 No. 3, pp. 235-53. 587Whalen, 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.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. 162-73.Yusuf, Y., Gunasekaran, A. and Dan, G. (2007), “Implementation of TQM in China and organizational performance: an empirical investigation”, Total Quality Management, Vol. 18 No. 5, pp. 509-30.Further readingMosadegh Rad, A.M. (2003), The Principles of Health Care Administration, Dibagran Tehran, Tehran.About the authorsFaisal Talib is an Assistant Professor at Mechanical Engineering Section, UniversityPolytechnic, Aligarh Muslim University, Aligarh, India. He holds Masters in Industrial andProduction Engineering and is currently pursuing a PhD in Total Quality Management inService Sector from Indian Institute of Technology, Roorkee, India. He has more than 12 years ofteaching experience. He has more than 30 publications to his credit in national/internationaljournals and conferences. His special interests include quality engineering, TQM, service quality,Quality Concepts Taguchi Methods, and quality management in service industries. Faisal Talibis the corresponding author and can be contacted at: firstname.lastname@example.org Zillur Rahman is an Associate Professor at Department of Management Studies, IIT, Roorkee.He is a recipient of the Emerald Literati Club Highly Commended Award and one of his paperswas The Science Direct Top 25 Hottest Article. His work has been published and cited in variousjournals including Management Decision, Managing Service Quality, International Journal ofInformation 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 IndustrialMarketing, and International Journal of Computer Integrated Manufacturing, to name a few. M.N. Qureshi is an Associate Professor at Mechanical Engineering Department, Faculty ofEngineering and Technology, M S University of Baroda. He earned his graduation and postgraduation degrees in Mechanical Engineering from M S University of Baroda and later on aPhD from IIT Roorkee, Roorkee. He has more than 50 publications to his credit innational/international journals and in conference proceedings. His areas of interest includelogistics and supply chain management, industrial management, quality management, etc.To purchase reprints of this article please e-mail: email@example.comOr visit our web site for further details: www.emeraldinsight.com/reprints