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Page 1: An empirical investigation of relationship between total quality management practices and quality performance in Indian service companies

QUALITY PAPER

An empirical investigation ofrelationship between total quality

management practices andquality performance in Indian

service companiesFaisal Talib

Mechanical Engineering Section, Aligarh Muslim University,Aligarh, India

Zillur RahmanDepartment of Management Studies, Indian Institute of Technology Roorkee,

Roorkee, India, and

M.N. QureshiDepartment of Mechanical Engineering, MS University of Baroda,

Vadodara, India

Abstract

Purpose – The purpose of this paper is to investigate the relationship between total qualitymanagement (TQM) practices and quality performance in Indian service companies.

Design/methodology/approach – The empirical data was collected using a self-administeredinstrument that was distributed to 600 Indian service companies. Of the 600 instrument e-mailed, 172usable instrument were returned, yielding a response rate of 28.6 per cent. A stratified samplingprocedure was utilized to obtain the minimum sample size of 600 from the four chosen service industries(i.e. Healthcare, Banking, Information and Communication Technology (ICT), and Hospitality).The data was analyzed using factor, Pearson’s correlation, and multiple regression analyses.

Findings – The findings revealed that TQM practices were found to be partially correlated withquality performance of the Indian service companies. It was also found that quality culture wasperceived as the dominant TQM practice in quality performance. The other practices such as qualitysystems, training and education, teamwork, and benchmarking showed a positive relationship withquality performance.

Research limitations/implications – The research paper was limited by including only fourindustries in the selection of service companies in India, making this a possibly biased selection and itmay not be adequate to generalize the results for the entire Indian service companies.

Originality/value – The study has contributed to the TQM literature with a better understanding ofthe 17 TQM practices and their association with a company’s quality performance that will providevaluable knowledge to top-management of service companies, to refine their current TQM practicesand subsequently improve quality performance.

Keywords Total quality management, Customer relations, Quality performance, Service companies,Quality culture, India

Paper type Research paper

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0265-671X.htm

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Received 3 July 2011Revised 9 May 2012Accepted 17 July 2012

International Journal of Quality &Reliability ManagementVol. 30 No. 3, 2013pp. 280-318q Emerald Group Publishing Limited0265-671XDOI 10.1108/02656711311299845

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IntroductionIn today’s highly competitive market with escalating demands of consumers for gettingbetter products and services (Thiagaragan et al., 2001), survival of companies in theever-expanding marketplace (Zakuan et al., 2010), economic success of companies(Curkovic et al., 2000), improvement in productivity, customer satisfaction, profitability,and innovativeness (Sadikoglu and Zehir, 2010), changing organizational culture(Prajogo and McDermott, 2005), and globalization of world trade (Fotopoulos andPsomas, 2010), the emergence of quality plays a vital role and have become a top priorityfor many companies worldwide in order to achieve the above stated objectives and gaincompetitive edge. The importance of quality for company’s performance in severalterms and success in marketplace is widely accepted in business literature and practice(Kumar et al., 2009b). In an attempt to improve quality, numerous approaches tomanagement of quality and continuous improvement have been pursued, most notablyand a recommended approach is the concept of total quality management (TQM). Manycompanies claimed substantial benefits of implementing TQM in terms of financialresults, operating performance, customer satisfaction, and employee satisfaction(Brah et al., 2002; Yang, 2006; Kumar et al., 2009b; Fuentes et al., 2006; Sila, 2007). It is aholistic management approach (Hafeez et al., 2006) that seeks managing quality, itrequires development of quality strategy (Kanji and Wallace, 2000) and a framework forits implementation (Chin and Pun, 2002). It focuses on meeting customer needs andcompany’s objectives (Kumar et al., 2009a).

TQM principles and practices have been embraced by many quality managers andpractitioners from different sectors and have earned the attention of many researchersfrom diverse areas. They come out with many success stories related to TQM practices(Sila, 2007; Karia and Asaari, 2006; Lagrosen, 2003; Prajogo and McDermott, 2005;Yoo et al., 2006). While many studies have shown that almost two-third of the TQMimplementation program failed to achieve any result (David and Strang, 2006; Miller etal.,2009; Rich, 2008), and others find mixed results of TQM success (Kaynak, 2003; York andMiree, 2004; Prajogo and Sohal, 2001; Nair, 2006). These findings poses the question as towhat factors contributes to TQM success? In particular, the importance of identificationof key TQM practices and their successful implementation is frequently referred to in theliterature (Brah et al., 2002; Karia and Asaari, 2006; Prajogo and Sohal, 2006), however,many authors strongly argue that performance measurement is one of the mostimportant dimensions of TQM’s success (Brah et al., 2002; Chang, 2006; Kaynak, 2003;Taylor and Wright, 2006). An improper performance measurement can lead to TQM fadand may act as barrier to TQM implementation (Chang, 2006).

Previous empirical research investigates the relationship between TQM andperformance. Some authors find positive results (Hendricks and Singhal, 2001;Shenaway et al., 2007; Prajogo and Sohal, 2003; Arumugam et al., 2008), otherresearchers fail to find any significant link (Powell, 1995), and some studies evenidentify an inverse relationship (Kannan and Tan, 2005; Rahman and Bullock, 2005;Yang et al., 2009; Prajogo and Sohal, 2004). In the light of these results, there is need fora deeper investigation of the relationship between TQM practices and performancefrom quality perspective. Therefore, the objectives of this study are:

(1) to investigate the relationships between TQM practices and qualityperformance within Indian service companies; and

(2) to assess the extent of association of TQM practices with quality performance.

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The key TQM factors and quality performance measure were validated throughexploratory factor analysis (EFA), while the relationships between them wereexamined through bivariate correlation and multiple regression analyses.

The study investigates Indian service companies that have either implemented or arein the process of implementing TQM. Quality is crucially important for Indian servicecompanies, faced with increasing competitiveness on international market. The Indianservice sector represents about 57.3 percent of India’s gross domestic product (GDP) andtherefore, considered to be one of the vital components of its economy (InformationInfrastructure for Institutions, Centre for Monitoring Indian Economy Private Limited,India (i3, CMIE, 2010)). As world markets are becoming increasingly integrated, Indianservice companies are coming under strong pressures to ensure that their qualityperformance is up to date and matches with the leaders of quality like the USA,Australia; the UK and other competitors. Increased globalization and tough businessconditions have brought challenges and opportunities for Indian service companiesand made them to promote quality in their products and services, and has become anational imperative for Indian companies to stand and compete in the present marketcondition.

The remainder of the research follows the next structure: the second section presentsthe literature review on TQM practices and summarizes the results of previous studieson relationships between TQM practices and quality performance measure; the thirdsection describes the research framework and questions. Fourth section discusses theformulation of hypotheses. The fifth section presents the detailed research methodologyused followed by results and analysis section. Finally, the last section deals withdiscussion on the findings and summarizes the main conclusions of the study.

Literature reviewTQM practicesAn extensive literature review of the previous studies on TQM have examined whatconstitutes TQM and what are the key practices for the success of TQM (Fotopoulosand Psomas, 2010; Sadikoglu and Zehir, 2010; Al-Marri et al., 2007; Yang, 2006; Sila,2007; Sila and Ebrahimpour, 2005; Karia and Asaari, 2006; Ju et al., 2006; Prajogo andMcDermott, 2005; Antony et al., 2002; Hafeez et al., 2006; Zhang et al., 2000). Thesestudies have provided different sets of practices considered essential to the success ofTQM implementation but as such no study has identified a common set of practices forsuccessful implementation of TQM. This leads to inconsistencies in previous researchwhich made it difficult to reach a conclusion on which TQM practices to be adopted tohave desired outcomes (Ooi et al., 2008; Hoang et al., 2006). Though there are somequality award models such as Malcolm Baldrige National Quality Award, EuropeanQuality Award, The Deming Prize and Kanji Business Excellence Model, whichprovide a useful benchmark framework for industries and help in implementing TQMas well as evaluating their business performance results.

The study by Fotopoulos and Psomas (2010) identified leadership, strategic qualityplanning, employee management and involvement, supplier management, customerfocus, process management, continuous improvement, information and analysis andalso knowledge and education as a set of TQM practices to form a structural relationshipwith the organizational performance in ISO 9001:2000 certified Greek companies.Kumar et al. (2011) identified management commitment, customer satisfaction,

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continuous improvement, teamwork, employee’s empowerment, training, feedback,and effective communication as few success factors for both manufacturing and serviceindustries. While the study by Bayraktar et al. (2008) presented the following criticalsuccess factors (CSFs) of TQM: leadership, vision, measurement and evaluation, processcontrol and improvement, program design, quality system improvement, employeeinvolvement, recognition and award, education and training, student focus, and otherstake holder’s focus. Sadikoglu and Zehir (2010) after thoroughly reviewing theliterature developed a set of eight TQM practices. They are: leadership, training,employee management, information and analysis, supplier management, processmanagement, customer focus, and continuous improvement. They investigated theeffects of innovation and employee performance on the relationship between these TQMpractices in Turkish firms. Talib and Rahman (2010) identified a set of nine TQMpractices for their proposed TQM model for service industries. They are:top-management commitment, customers focus, training and education, continuousimprovement and innovation, supplier management, employee involvement, employeeencouragement, benchmarking, quality information and performance. Kanji andWallace (2000) go on to identify ten TQM practices: top-management commitment,customer focus and satisfaction, quality information and performance measurement,human resource management, employee involvement, teamwork, process management,quality assurance, zero defects, and communication. Brah et al. (2000) in their studyidentified 11 constructs of TQM: top management support, customer focus, employeeinvolvement, employee training, employee empowerment, supplier quality management(QM), process improvement, service design, quality improvement rewards,benchmarking, and cleanliness and organization. Similarly, Sila (2007) presented sixTQM practices: leadership, customer focus, information and analysis, human resourcemanagement, process management, and supplier management. Through thecomprehensive review of the TQM literature, the present study utilizes 17 TQMpractices identified by Talib et al. (2011a, b) for service industries which are frequentlyoccurring in the TQM literature. They are: top-management commitment, customerfocus, training and education, continuous improvement and innovation, suppliermanagement, employee involvement, information and analysis, process management,quality systems, benchmarking, quality culture, human resource management, strategicplanning, employee encouragement, teamwork, communication, and product andservice design.

The reasons for selecting these practices are:. Have been used frequently (highest frequency of occurrences) by different

researchers in the service industries.. Have been identified as the key practices in TQM implementation in both

manufacturing and service industries (Saraph et al., 1989; Antony et al., 2002;Zhang et al., 2000).

. Constitute practices that represent the hard and soft components of TQM.

. Significantly associated in services and in the promotion of service quality (Ueno,2008; Lakhal et al., 2006; Behara and Gundersen, 2001).

Hence, it is believed that these practices are suitable to be used in the Indian servicesector context.

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Relationship between TQM practices and quality performanceA considerable body of empirical evidence suggests that TQM implementationimproves quality performance of the company. It has been measured in various waysand found that the QM model and specific practices, which best predict performancevaries across the world (Prajogo and Sohal, 2004; Arumugam et al., 2008).

The research framework for QM proposed by Flynn et al. (1994) suggested that theinputs of this framework are the QM practices while quality performance representsoutcomes. Further, product design process, process flow management, andtop-management support have significant correlation with quality performance(Flynn et al., 1995).

Parzinger and Nath (2000) examined the link between TQM and software quality andfound that TQM implementation improves the software quality and performance, and thus,increases customer satisfaction. Hasan and Kerr (2003) studied the relationship betweenTQM practices and organization performance in service organizations and discovered thatTQM practices like top-management commitment; employee involvement; training;supplier quality; quality costs; service design; quality techniques, benchmarking; andcustomer satisfaction leads to higher productivity and quality performance.

Yang (2006) reported that TQM practices including QM, process management,employee empowerment and teamwork, customer satisfaction management, qualitygoal setting and measurement, supplier’s cooperation and quality tools training havesignificant effects on customer satisfaction and that the adoption of TQM is aneffective means by which companies can gain competitive advantage.

Prajogo and Brown (2004) conducted an empirical study within Australian organizationsto investigate the relationship between TQM practices and quality performance, and theresults indicated a strong and positive linkage. Brah and Tee (2002) examined therelationship between TQM constructs and organization performance by measuring qualityperformance of Singapore companies. They found that implementation of TQM leads toquality performance and have positive correlation. Another study based on the comparativeanalysis of TQM practices and quality performance between Australian manufacturing andservice firms, Prajogo (2005) reported that there exist no significant differences in the level ofmost of the TQM practices and quality performance between two sectors.

A study utilizing structural equation modeling (SEM) approach bySanchez-Rodriguez et al. (2006) provided the insights into the current informationtechnology (IT) and TQM theory and practice on operational and quality performance.They found TQM initiatives generate significant positive gains in operational andquality performance. In line to this, Prajogo and Sohal (2004) also employed SEMapproach to examine the multidimensionality of TQM in association with organizationperformance. Using empirical data collected form 194 Australian firms the findingsupport the proposition in pairing the mechanistic elements of TQM with qualityperformance and the organic elements with innovation performance.

Sila and Ebrahimpour (2005) explored the relationships among TQM factors such asleadership, strategic planning, customer focus, information and analysis, humanresource management, process management, supplier management and the results fromadopting such practices such as human resource results, customer results, organizationaleffectiveness and financial and market results. They identified leadership andinformation and analysis as the two factors that act as the foundations on achievingfavorable business results.

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An empirical study conducted by Arumugam et al. (2008) explored the relationshipbetween TQM practices and quality performance on ISO9001:2000 certifiedmanufacturing organizations in Malaysia. Analyzing empirical data drawn from122 Malaysian organizations through correlation and multiple regression analyses, thefinding revealed that TQM practices were found to be partially correlated with qualityperformance. They further found that customer focus and continuous improvementwere perceived as dominant TQM practices in quality performance. Summary ofdifferent studies using quality performance as a measure for evaluating companyperformance is presented in Table I.

Research framework and questionsBased on the above literature review, a conceptual framework is developed and aresearch model has been proposed to examine the relationships between TQMpractices and company’s performance by measuring the “quality performance” as aperformance indicator in the Indian service companies. The proposed TQM conceptualframework is shown in Figure 1. This research model suggests that the greater theextent to which these TQM practices are present, the quality performance of Indianservice companies will be higher. In this framework, the independent variables areTQM practices and a dependent variable is quality performance, respectively.

Author(s) Measure Performance indicator(s)

Zhang (2000) Organization performance Quality performanceSu et al. (2001) Quality performance Defect rate

Rework rateDelay rate of deliveryQuality performance

Cua et al. (2001) Organization performance Quality performanceOperational performance

Prajogo and Sohal (2003) Organization performance Quality performanceInnovation performance

Lakhal et al. (2006) Organization performance Financial performanceOperational performanceProduct quality performance

Hermann et al. (2006) Company performance Product quality performanceReduction in costsShorter R&D time

Prajogo and Sohal (2006) Organization performance Quality performanceInnovation performance

Yang (2006) Quality performance Employee satisfactionEmployee quality awarenessCustomer satisfactionCompany’s image

Saravanan and Rao (2007) Organization performance Quality performanceOperational performance

Arumugam et al. (2008) Company performance Quality performancePrajogo and Hong (2008) R&D performance Product quality performance

Product innovation performanceWong et al. (2010) Firm performance Quality performance

Table I.Quality performance

measure proposed bydifferent authors

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The two research questions of this study can be articulated as follows:

RQ1. Do the identified TQM practices have relationship with company’s qualityperformance?

RQ2. Which TQM practices are more associated with the company’s qualityperformance?

Figure 1.A conceptual frameworkof the relationshipbetween TQM practicesand quality performance

TQM PracticesH11

Top-management commitment

Customer focus

Training and education

Continuous improvementand innovation

Supplier management

Human resource management

Information and analysis

Process management

Teamwork

Quality culture

Strategic planning

Product and service design

Quality systems

Employee encouragement

Benchmarking

Communication

H12

H13

H14

H15

H16

H17

H18

H19

H110

H111

H112

H113

H114

H115

H116

H117

Employee involvement

QualityPerformance

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Hypotheses formulationThe aim this study is to establish the relationship between TQM practices and qualityperformance in Indian service companies. The literature review indicates a significantpositive relationship between TQM practices and quality performance. This leads tothe following hypothesis:

H1. There is a significant positive relationship between identified TQM practicesand quality performance of Indian service companies.

To understand the relationship of each TQM practice on quality performance in Indianservice companies, the following hypotheses will be used and tested.

Top-management commitmentPrevious research in TQM practices emphasizes the critical role of top-managementcommitment in driving overall TQM implementation in the organizations (Zakuan et al.,2010; Flynn et al., 1994; Teh et al., 2008). Teh et al. (2008) noted that senior leaders andmanagement guide the organization and assess the organizational performance. Kanji(2001) asserted that top-management commitment is the fundamental driver ofbusiness excellence. Further, studies showed that top-management commitmentsignificantly affects the quality performance (Arumugam et al., 2008; Prajogo andBrown, 2004). Accordingly, it is proposed that:

H11. Top-management commitment for TQM practices is positively associatedwith quality performance.

Customer focusOrganizations must be knowledgeable in customer requirements and responsive tocustomer demands, and measure customer satisfaction through TQM implementation(Zakuan et al., 2010; Zhang, 2000). According to the review results from Hackman andWageman (1995), obtaining information about customer is one of the most widely usedTQM implementation practices to improve quality performance of the organization.Therefore, the next hypothesis relate to customer focus and quality performance:

H12. Customer focus for TQM practices is positively correlated with qualityperformance.

Training and educationTraining and education spread the knowledge of continuous improvement andinnovation in service process to attain full benefits and business excellence. Talib andRahman (2010) reported the critical role of training and education in maintaining highquality level within the service industry. Further, the research on TQM also found apositive correlation between training and education, and organization performance(Vermeulen and Crous, 2000). Therefore, the next hypothesis attempts to find arelationship between training and education and quality performance:

H13. Training and education for TQM practices is positively correlated withquality performance.

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Continuous improvement and innovationContinuous improvement and innovation, which is the most important part of services,means searching for never-ending improvements and developing processes to find newor improved methods in the process of converting inputs into useful outputs. It helps inreducing the process variability thereby continuously improving the outputperformance (Sadikoglu and Zehir, 2010). Corbett and Rastrick (2000) asserted thatin TQM, the best way to improve organizational performance is to continuouslyimprove the performance activities. Thus, the following hypothesis is proposed:

H14. Continuous improvement and innovation for TQM practices is positivelycorrelated with quality performance.

Supplier managementAccording to Zakuan et al. (2010), effective supplier QM can be achieved by cooperationand long term relationship with the suppliers. This argument is also supported byZineldin and Fonsson (2000), who found that developing supplier partnership andlong-term relationships can increase the organization competitiveness and thus,improve performance. Therefore, a hypothesis to test this relationship is as follows:

H15. Supplier management for TQM practices is positively correlated with qualityperformance.

Employee involvementDeming claimed that involvement and participation of employees at all level is must toimprove the quality of the current and future product or service. Even non-managerialemployees can make significant contributions when they are involved in qualityimprovement processes, decision making processes, and policy making issues (Sadikogluand Zehir, 2010; Ooi et al., 2007a). Organizations should utilize all employees’ skill andabilities to gain business performance. Accordingly, the hypothesis is as follows:

H16. Employee involvement for TQM practices is positively correlated withquality performance.

Information and analysisFulfilling customer needs and expectations are considered to be baseline of any kind ofbusinesses. When customers’ needs and expectations are achieved, quality performanceis improved and thus, satisfaction is established. Prajogo (2005) revealed the importanceof information and analysis TQM practice on quality performance. Information andanalysis also helps an organization to ensure the availability of high quality, timely dataand information for all users like employees, suppliers, and customers (Teh et al., 2009).Therefore, the following hypothesis is put forward:

H17. Information and analysis for TQM practices is positively correlated withquality performance.

Process managementProcess management is a systematic approach in which all the resources of anorganization are used in most efficient and effective manner to achieve desiredperformance (Sit et al., 2009). Motwani (2001) commented that process management

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stresses the value adding to a process, increasing the productivity of every employeeand improving the quality of the organization. In many empirical studies, Prajogo andSohal (2004), Flynn et al. (1995), and Cua et al. (2001) systematically investigated therelationships between process management and quality performance. The results ofthese studies showed positive correlation between them. Hence, the followinghypothesis is proposed:

H18. Process management for TQM practices is positively correlated with qualityperformance.

Quality systemsQuality systems such as ISO 9000 standards, statistical process control (SPC) and othersupportive qualitative tools and techniques create an environment for qualityimprovement and implementing TQM in an organization (Curry and Kadasah, 2002).Lakhal et al. (2006) claimed that there is a significant relationship between use of statisticalquality techniques and organizational performance. Therefore, the next hypothesisattempts to find a relationship between quality systems and quality performance:

H19. Quality system for TQM practices is positively correlated with qualityperformance.

BenchmarkingBenchmarking is the process of comparing performance information, within theorganization as well as outside the organization. It also aims to measure organization’soperations or processes against the best-in-class performers from inside or outside itsindustry (Sit et al., 2009). The study by Yusuf et al. (2007) highlighted the usefulness ofdynamic benchmarking for improving the performance of the organization and toachieve competitive advantage. Accordingly, the next hypothesis relates tobenchmarking and quality performance:

H110.Benchmarking for TQM practices is positively correlated with qualityperformance.

Quality cultureGore (1999) emphasized that the quality culture of an organization is the strong basisfor enhancing organization’s success. Generally, the culture of an organization couldimpact individual behavior (Bose, 2004), knowledge sharing (Ooi et al., 2012), jobsatisfaction (Ooi et al., 2007b). Beside this, quality culture significantly contributes inimproving the performance of the organization as well as influencing the thought,feeling and interaction among members of the organization (Yusof and Ali, 2000).Thus, quality culture is linked to the quality performance and a hypothesis is formed:

H111.Quality culture for TQM practices is positively correlated with qualityperformance.

Human resource managementDeros et al. (2006) reported that human resource management is one of the criticalpractices for improving business and management processes. Another study bySanchez-Rodriguez et al. (2006) noted that management of people was positively

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associated with purchasing operational performance. Yang (2006) further concludedthat human resource management as TQM practice significantly correlated withcustomer satisfaction which is also supported by Sit et al. (2009). Further, Teh et al. (2008)found a positive relationship between empowerment and role conflict. Based on theabove comprehensive review of the association between human resource managementand different performance measurement indicators, the following hypothesis isproposed:

H112.Human resource management for TQM practices is positively correlated withquality performance.

Strategic planningStrategic planning incorporates the development and deployment of plans, improverelationships with customers, suppliers, and business partners and helps in achievinglong and short term goals through participative planning (Teh et al., 2009). Particularly,there is lack of empirical studies that examines the effects of strategic planning onquality performance or any other performance measure. Indeed, a significant link isfound between strategic planning and quality performance (Prajogo and Brown, 2004),knowledge management behavior (Ooi et al., 2008), role conflict (Teh et al., 2009), andcustomer satisfaction (Sit et al., 2009). Therefore, the next hypothesis attempts to find arelationship between strategic planning and quality performance:

H113.Strategic planning for TQM practices is positively correlated with qualityperformance.

Employee encouragementEmployee encouragement such as rewards and recognition motivates employees toperform which in turn influence customer satisfaction (Zhang et al., 2000; Tari, 2005). Inline with this, the findings of Yusuf et al. (2007) reported that employee encouragement ispositively related with organization performance and employee satisfaction. It has alsobeen found that employee encouragement gives the right direction to work force and isan essential practice in customer/public dealing industries. Thus, the followinghypothesis is proposed:

H114.Employee encouragement for TQM practices is positively correlated withquality performance.

TeamworkTeamwork refers to an increase in employees’ control over their work and allows themto work as a group (Ooi et al., 2007b). This practice provides an atmosphere of mutualrelationship, involvement, and participation through out the organization. Accordingto Ooi et al. (2007b), teamwork as a TQM practice is positively associated withemployees’ job satisfaction. They further found that, where teamwork was perceivedas a dominant TQM practice, improvements in job satisfaction levels were significant.Yang (2006) commented that entire organization should work for improving qualityand support for quality improvement activities by implementing teamwork practice.Formation of teams within an organization is critical to an organization’s TQMsuccess. Thus, the following hypothesis is suggested:

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H115.Teamwork for TQM practices is positively correlated with qualityperformance.

CommunicationCommunication refers to information sharing process between individual/employees ofthe organization (Ooi et al., 2007a). Managers and practitioners use effectivecommunication to enlist the support of other employees towards achievingorganization’s objectives. Several studies noted that effective communication influencethe organization to move systematically towards employees’ involvement and customersatisfaction and improves organization performance (Ooi et al., 2007a; Yusuf et al., 2007).Based on the above literature review, the following hypothesis was proposed:

H116.Communication for TQM practices is positively correlated with qualityperformance.

Product and service designProduct and service design examines an organization’s quality and service deliveryperformance in terms of timeliness, errors, costs of quality, responsiveness, andcustomer satisfaction (Brah et al., 2000). These indicators are used for measuring theproduct and service design quality. Bhatt and Emdad (2010) empirically investigatedthe relationships between IT infrastructure, product and service innovation, andbusiness advantages and found that product and service innovation is positivelyrelated with business advantages beside the two factors like IT infrastructure andcustomer responsiveness. Therefore, the next hypothesis attempts to find arelationship between product and service design and quality performance:

H117.Product and service design for TQM practices is positively correlated withquality performance.

All the above hypotheses to be tested are shown in Figure 1.

Research methodologyResearch methodology is very important as it can guide researchers on what stepsneeds to be taken in order to accomplish the objectives of the research (Tsang andAntony, 2001; Antony et al., 2002). In order to accomplish the objective of this researchstudy, a questionnaire survey methodology was adopted and was carried out in selectIndian service companies. This section discusses research design, research instrument,administration of instrument, sample, and data collection procedures used in the study.

Research designThe present research uses a descriptive cross-sectional study design. It is concerned withanalysis of phenomenon, situation, problem, opinions, and demographic information, orissue. In fact, the majority of TQM and organization performance studies in service sectorhave employed descriptive cross-sectional study design (Salaheldin, 2009; Miller et al.,2009; Salaheldin and Mukhalalati, 2009; Duggirala et al., 2008; Wardhani et al., 2009). Inaddition to this, the study also employed the survey method, which makes use of aresearch instrument. This study utilizes electronic mail (e-mail) survey method as themeans of data collection which is commonly used in similar kind of research (Kureshi et al.,2010; Zu, 2009; Sarvanan and Rao, 2007; Fotopoulos and Psomas, 2010).

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Sampling frameThe sampling frame used for this study is the list of select Indian service companiespublished by the i-cube (i3, CMIE, 2010). The list provides the names of servicecompanies, complete addresses, pin code, persons to contact which in majority of casesincludes directors, CEO, managing directors, general managers, presidents, humanresource managers or technical managers. It also mentions telephone number(s), e-mailaddresses as well as the web site of the company.

The four service industries mainly included in this study are healthcare, banking,hospitality (hotel and tourism), and information and communication technology (ICT)which includes telecommunication services, information technology enabled services(ITeS) and computer software services. The reasons for choosing these four industriesare their high GDP share in Indian economy (about 56 percent) (i3, CMIE, 2010); highlylabor intensive industries and provides substantial employment (MoL&E, GOI, 2010);and there ever increasing net annual income to the Indian service sector (i3, CMIE,2010). The list contains a total of 1,781 companies at the time of research periodcovering all the four categories. These companies are frequently up-dated andpublished by prominent and reliable source. The study was conducted betweenFebruary and May, 2011.

Sampling methodA stratified sampling method (a probability sampling technique) was used in thisstudy. This method was thought to be appropriate to collect sufficient informationfrom the total population to make statistical inferences. The major objective ofstratified sampling is to increase precision without increasing cost (Malhotra, 2007)and above all many studies on TQM have deployed stratified sampling method fordata collection (Arumugam et al., 2009; Ooi et al., 2008; Lakhal et al., 2006; Sit et al.,2009; Sila and Ebrahimpour, 2005). This study divides the target population (N) intofour strata. These four strata were: healthcare {120}, banking {200}, hospitality {350},and ICT {1111}. Each stratum contains number of companies identified from thesource (i3, CMIE, 2010) as discussed above and are indicated in the bracketscorresponding to each industry or stratum.

Sample sizeBased on the guidelines provided by Hair et al. (1998, 2006), Nunnally and Bernstein(1994), the minimum sample size (n) was calculated according to the GDP contributionof each service industry from the total contribution of GDP in the Indian service sector.Assuming that the GDP of these four service industries constitutes 100 percent ofservice industries, the minimum sample size based on GDP contribution was obtainedwhich is depicted in Table II.

The minimum sample size needed for this study comes out to be 591. This samplewas increased to 600 to reduce the probability of Type II error (Burgess et al., 2006).The sample size of 600 is above the minimum requirement and is within the acceptablerange as per the guidelines proposed by the researchers. This minimum sample sizewas stratified into four strata. The sample size drawn from each stratum, i.e. healthcare,banking, hospitality, and ICT industries based on proportionate stratified samplingtechnique were found to be 40, 67, 118, and 375, respectively. These samples weredrawn using a simple random sample approach.

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Research instrumentA self-administered structured instrument was designed in this research based on theservice as well as manufacturing and service TQM literature specifically, the works ofSalaheldin (2009), Bayraktar et al. (2008), Brah et al. (2000), Sila and Ebrahimpour (2005),Saravanan and Rao (2007), and Antony et al. (2002) were adopted and most of the itemswere taken from these studies. The instrument was modified by consulting withacademicians and quality experts, and was initially validated through a pilot surveybefore it was actually used for primary data collection. The instrument developed wasdivided into three sections. The first section comprises the demographic information ofthe respondents including profession, gender, years of experience as well as the generalbackground of the company. The second section consisting of 17 TQM practices with110 items. Third section evaluates the performance of the company, i.e. the servicecompany performance result which was measured by using a performance indicator –“quality performance” through eight items (Arumugam et al., 2008; Brah et al., 2002;Prajogo, 2005; Prajogo and Brown, 2004). The instrument comprises of anon-comparative-itemized rating scale utilizing a five-point Likert scale, with 1 – verylow, 3 – moderate, and 5 – very high, depending on the type of question. This is in linewith those suggested by Miller et al. (2009), Bayraktar et al. (2008) and Salaheldin (2009).

Pilot test of instrumentInitially, the instrument consisted of a total of 129 items representing 17 TQM practicesand nine items representing the performance indicator (quality performance) toevaluate company’s performance. This research instrument was pre-tested with agroup of 20 participants (Malhotra, 2007) consisted of ten academicians who have beeninvolved in various QM related subjects and research papers for more than ten yearsand also heads of those educational institutions like director, dean, head of department,etc. and had an overall in-charge of implementing TQM in the institution. Another tenquality experts from different service industries like three from hospitals, two frombanks and five from ICT, having over eight years experience in the field of product andservice quality as well as in quality implementation and service marketing, werechosen for this task. Each participant was asked to evaluate the instrument for thereadability, bias, understandability, ambiguous items, and appropriateness of eachitem in relevance to the Indian service company setting. The feedback resulted in themodification of several items and the layout of the instrument. All the 20 participantswere contacted personally.

Service industrycategory

Populationsize

GDPcontribution (%)

Sample size basedon GDP contribution

Stratum sample size basedon proportionate stratified

sampling technique

Healthcare 120 6.5 8 40Banking 200 23.3 47 67Hospitality 350 32.0 112 118ICT 1,111 38.2 424 375Total N ¼ 1,781 100 n*a ¼ 591 n ¼ 600

Note: n*a – minimum sample size before considering the probability of Type II error

Table II.Population and

sample size

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Instrument administration and data collection procedureThe target respondents for this study were top and middle leveladministrators/managers who have sufficient level of experience and qualificationand therefore, they will be aware of the TQM practices followed in their respectiveservice companies. Each respondent received a cover letter and a survey instrument.Addressed to the top and middle level administrators/managers of the companies, thesurvey instruments were e-mailed to 600 Indian service companies. After severalfollow-ups and personal contacts, a total of 211 companies responded which areapproximately 35.1 percent of the sample size, were selected for the study, however, only172 useable survey instruments were included for the data analysis as 39 instrumentswere unusable, yielding a response rate of 28.6 percent which is well within the range of85-300 cases as recommended by Kureshi et al. (2010) and Hair et al. (1998). The mainreasons for this are: 33 respondents (84.6 percent) did not complete the instrument orhaving the missing data and six instruments (15.4 percent) were undelivered.

To assess non-response bias in mail surveys, statistical difference tests betweenearliest and latest responses is used (Kureshi et al., 2010; Rahman and Siddiqui, 2006;Khanna, 2009). Using this method, first ten respondents and the last ten respondentswere checked and compared. This issue was validated by using t-tests with 95 percentconfidence level ( p $ 0.05) among these two groups with respect to the identificationof TQM practices, TQM variables like top-management commitment, customer focusand quality culture, and also TQM quality performance. Analysis indicated that therewere no significant differences between the early and late respondents in term of theidentification of TQM practices (t ¼ 0.264, p ¼ 0.798); top-management commitment(t ¼ 0.487, p ¼ 0.638); customer focus (t ¼ 0.362, p ¼ 0.726); quality culture(t ¼ 20.512, p ¼ 0.621) and TQM quality performance (t ¼ 20.332, p ¼ 0.747).Thus, it concludes that there was no evidence of non-response bias in the data and itmay not be a problem in this study.

Variable measurement. Independent variables: TQM practices. A total of 110 items captured the 17 TQM

practices under investigation. These items were adopted form the scalesdeveloped by Salaheldin (2009), Bayraktar et al. (2008), Brah et al. (2000), Sila andEbrahimpour (2005), Sarvanan and Rao (2007), and Antony et al. (2002). Thereasons for selecting these studies were that the scales of these studies haveshown good reliability and validity in all these studies and they are based on theservice as well as manufacturing and service industries.

. Dependent variable: quality performance. Eight measurement items dealing withproduct, process and service quality, employee service quality, employeesatisfaction, customer satisfaction, and supplier performance were adopted formprevious studies as discussed above to evaluate perceived quality performance.The quality performance items of these studies also showed good validity andreliability in assessing QM practices.

Results and analysisReliability coefficients were initially computed to check the internal consistency of themeasuring items of the independent and dependent variables. Face and content validitywere also checked followed by the validation of constructs using factor analysis (FA) for

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the study variables. Intercorrelations were computed to understand the variability andinterdependence of the subscales derived from the FA. The hypotheses were testedusing multiple regression analysis through SPSS 16.0 software (Coakes et al., 2006).

Profile of respondentsTable III depicts the profile of the respondents. The company variables consisted ofposition of respondent, years of experience, gender, department/section, and type ofcompany. The ICT companies dominate the sample size (48.8 percent). While theremaining three industries, i.e. healthcare, banking, and hospitality contributes 9.9, 21.5,and 19.8 percent, respectively, in the sample. It was also observed that many of theIndian service companies are male dominated companies (83.7 percent) in their qualitydepartment. Further, in terms of years of experience, majority of the respondents werehaving more than five years of experience (64.5 percent). This suggests that the majorityof participating companies is quite mature and has the knowledge of TQM in depth.Finally, the responses received indicate the coverage of all the departments/sections ofthe service companies by the present survey.

Frequency Percentage

Position/role of the respondentDirector/managing director/executive director/CEO/general manager 8 4.7Project manager/senior engineer manager/senior manager 32 18.6Manager/technical manager/operations manager 38 22.1Quality manager/human resource manager/quality engineer/marketmanager/executive manager 40 23.3CMO/medical superintendent/medical officer/physicians 17 9.9Others (like project architect, consultant; customer relation officer; servicemanager; assistant manager) 37 21.5Total n ¼ 172 100Years of experienceLess than five years 61 35.5More than five years 111 64.5Total n ¼ 172 100GenderMale 144 83.7Female 28 16.3Total n ¼ 172 100Department/sectionQuality 16 9.3Product and services 35 20.3Customer relation 24 14.0Marketing 34 19.8Information management services 19 11.0Others 44 25.6Total n ¼ 172 100Type of companyHealthcare 17 9.9Banking 37 21.5Hospitality (tourism and hotels) 34 19.8ICT (including ITeS and computer software services) 84 48.8Total n ¼ 172 100

Table III.Profile of respondents in

the service industry

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Reliability testThe reliability of the factors needs to be examined in order to support any measures ofvalidity that may be deployed (Nunnally and Bernstein, 1994). It is most commonlyfollowed technique to measures internal consistency among a group of items combinedto form a single scale and reflects the homogeneity of the scale. Using the SPSS 16.0reliability analysis program software, an internal consistency analysis was performedseparately for the items of each TQM practice (17 independent variables) and on onedependent variable (quality performance). The alpha values of the study variables aresummarized in Table IV. The reliability coefficients of the study variables exceeded theminimum acceptable level of 0.70, as per the suggestion made by Nunnally andBernstein (1994). Further, after performing reliability test, ten items were deleted toincrease the reliability of the scale. Hence, the total items covering 17 TQM practicesand quality performance were reduced from 118 to 108. As can be seen in Table IV,the alpha values range from 0.784 to 0.932, thus, provides strong evidence that thescales developed are judged to be reliable.

Face and content validityFace validity is the mere appearance that a variable is valid. It is the subjectivejudgment of the correspondence between the individual items and the concept throughrating by expert judges (Hair et al., 1998). While content validity of an instrument

MeasureOriginal number

of items

Originalalpha

(reliability)Items

deletedFinal number

of items

Finalalpha

(reliability)

Independent variablesTop-managementcommitment 9 0.865 2 7 0.932Customer focus 9 0.876 1 8 0.902Training and education 6 0.860 1 5 0.902Continuous improvementand innovation 7 0.793 1 6 0.882Supplier management 8 0.910 None 8 0.910Employee involvement 6 0.883 None 6 0.883Information and analysis 5 0.874 None 5 0.874Process management 6 0.775 1 5 0.833Quality systems 5 0.667 1 4 0.784Benchmarking 5 0.891 None 5 0.891Quality culture 8 0.843 1 7 0.891Human resourcemanagement 7 0.902 None 7 0.902Strategic planning 6 0.821 1 5 0.866Employee encouragement 6 0.904 None 6 0.904Teamwork 4 0.871 None 4 0.871Product and service design 8 0.874 1 7 0.902Communication 5 0.900 None 5 0.900Dependent variableQuality performance 8 0.879 None 8 0.879Total 118 10 108

Note: n ¼ 172

Table IV.Internal consistency(scale reliabilities) for17 TQM practices andquality performance

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refers to the degree to which the scale items represent the domain of the concept understudy. It is also a subjective measure of how appropriate the items seem to variousreviewers with some knowledge of the subject matter (Saraph et al., 1989). In thisresearch, it was argued that the 17 TQM practices for measuring TQM implementationpractices had face and content validity since the majority of scales/items used in thisstudy are borrowed from established scales that have already been subjected to tests offace and content validity. Moreover, the content validity of the instrument was alsoensured through an extensive review of the literature and detailed evaluation byacademicians and practitioners. Items were deleted, added, or modified based on theirreviews prior to the analysis.

Construct validityConstruct validity is the extent to which a measure is related to other measures in amanner consistent with theoretically based concepts (Bayraktar et al., 2008). In otherwords, a measure has construct validity if it measures the theoretical construct or traitthat it was designed to measure. This was generally evaluated by FA. The primarypurpose of FA is to produce a parsimonious set of new composite dimensions from alarge number of variables with a minimum loss of information (Hair et al., 1998). Giventhe nature and requirement of this study, EFA was employed to assess constructvalidity. The EFA was performed and each scale was subjected to FA separately.

Factor analysisFA is a statistical approach that can be used to analyze interrelationships among alarge number of variables and to explain these variables in terms of their commonunderlying factors (Prasad et al., 2010). It is a multivariate data reduction technique,consisting of selecting the method of extracting the components; the number ofcomponents to be extracted; and the method of rotation for interpretation of the factors.

In this research study, principal component analysis method of FA followed by thevarimax orthogonal rotation was adopted on 17 TQM practices comparing of 100 itemsby using SPSS 16.0 software. But before going for FA, one of the vital considerations inFA is the sample size of the data (Hair et al., 1998). According to Hair et al. (1998),a minimum of five subjects per variable is must for FA or a sample of 100 is acceptable toachieve good results. The sample size of this study is 172. Accordingly, this meansthat the sample size is adequate and further analysis can be done. In order to assess theconstruct validity, factor loadings are obtained for each item. The loadings reflectthe strength of the relationship between an item and a particular factor or practice.The higher the loading, the better the representation that particular item has on thefactor. In interpreting the factor, Comrey (1973) suggested that loading in excess of0.45 could be considered fair, greater than 0.55 as good, 0.63 is very good, and 0.71 asexcellent. For this study, a loading of 0.50 or greater on the factor was considered(Hair et al., 1998; Arumugam et al., 2008; Ooi et al., 2008). The results for the FA extracted17 factors solution with Eigen value greater than one, and the total variance explainedwas 72.0 percent. 20 items relating to these factors were deleted (i.e. customer focus –five items; training and education – two items; employee involvement – two items;process management – two items; quality systems – two items; strategic planning –two items; employee encouragement – one item; and product and service design – fouritems) due to low loadings. The Kaiser-Meyer-Olkin (KMO) measure of sampling

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adequacy was 0.870 which is greater than 0.60 indicate sufficient intercorrelations whilethe Barlett’s test of sphericity was significant (x 2 ¼ 17,325.27, p ¼ 0.000 , 0.01).Further, the anti-image correlation matrix also revealed that all the measures ofsampling adequacy are well above the acceptable level of 0.50. Hence, a model with17 factors or components might be adequate to represent the data. Further, it was foundthat these 17 factors accounted for more than 70.0 percent of the variance of therespective variable tests. This suggests that only a relatively small amount of the totalvariance for each group of variables is associated with causes other than the factor itself.Thus, results of the FA indicate a high level of construct validity of the measure. Finally,a total of 80 items which are unidimensional and factorially distinct loaded on theconstructs were retained for further analysis. The results of FA are summarized inTable V.

Similarly, another FA was undertaken to see the dimensionality of the dependentvariable (quality performance) representing eight items. A single factor solutionemerged with Eigen value 4.33 explaining 54.24 percent of variance in the data. TheKMO measure of sampling adequacy was 0.879 indicating sufficient intercorrelations,while the Barlett’s test of sphericity was significant (x 2 ¼ 584.00, p ¼ 0.000 , 0.01).The results of FA for quality performance are summarized in Table VI.

The reliability of the instrument was tested again on each TQM practice(independent variables) and quality performance (dependent variable). The Cronbach’sa values of the study variables are shown in Tables V and VI. The reliabilitycoefficient of the study variables exceeded the minimum acceptable level of 0.70, thus,providing strong evidence that the scales developed are judged to be reliable(Nunnally and Bernstein, 1994; Hair et al., 1998).

Criterion validityCriterion-related validity is “concerned with the extent to which a measuringinstrument is related to an independent measure of the relevant criterion” (Badri et al.,1995) and is sometimes also called as external validity or predictive validity. The17 TQM practices have high criterion-related validity if these practices are highly andpositively correlated with quality performance of the Indian service companies. Thecriterion-related validity of the combined set of 17 TQM practices was evaluated byexamining the Pearson’s correlation coefficients (r) computed for the 17 TQM practicesand quality performance as a measure of outcome as well as multiple regressionanalysis was employed to test the above hypotheses (H11-H117).

Correlation analysis: relationship between the variablesA Pearson’s correlation analysis was carried out in this part of the research study toexamine the bivariate relationships among the main variables and to check thepresence of multicollinearity problem. The correlation matrix in Table VII indicatedcorrelation coefficient between 17 independent variables and a dependent variablewhich are measured by using multiple item scales in this research study. As can beseen in Table VII, the correlation coefficients for the variables under investigation wererelatively high ranging from 0.194 to 0.816. The correlation matrix in Table VII furtherindicates that TQM practices were positively and moderately correlated with qualityperformance.

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Items Loadings Cronbach’s a

Variable 1. Top-management commitment 0.932Extent to which top-management is actively involved and supportsthe quality improvement process 0.83Commitment of the top-management to the TQM program 0.85Extent to which top-management pursues long-term qualityobjectives 0.81Importance given by the top-management for allocation ofsufficient resources and time for quality improvement initiatives 0.77Extent to which top-management discusses and reviews quality-related issues on TQM in their management meetings 0.79Inclination of the top-management on quality rather than cost 0.71Degree to which top-executives are dynamic in leading the TQMprogram 0.72Variable 2. Customer focus 0.814Extent to which company carriers out market studies to determineits customers’ needs and expectations 0.56Company has a system to collect customers’ complaints andevaluates them carefully 0.56Degree to which customer feedback is used as the basis of qualityimprovementa 0.48a

Pleasing and courteous behavior of the employees towards thecustomera 0.46a

Intensity and range of services provided by the companya 0.43a

Extent to which products and service information and details areprovided by the company 0.51Giving individual and caring attention as much as possible to thecustomers by having the customers’ best interests at hearta 0.43a

Extent to which customer participation (involvement andfeedback) is sought in matter pertaining to operations andstrategies of the companya 0.42a

Variable 3. Training and education 0.865Level of specific work-skills training (technical and vocational)given to employee throughout the company 0.57Level of quality-related continuous training given to managers,executives, and other employees 0.50Training in interactive skills (such as communication skills,leadership skills, team building, etc.) 0.50Training in problem identification and solving skills, qualityimprovement skillsa 0.41a

Management and employees are trained in advanced/special toolsand softwarea 0.44a

Variable 4. Continuous improvement and innovation 0.882Extent to which management emphasizes the continuousimprovement of quality in all work processes at various levels 0.71Extent to which the company accepts continuous improvement asa long-term strategy for quality improvement 0.80Extent to which the company believes that “continuousimprovement” results in a competitive advantage 0.68Quantification of continuous improvement strategies on the basisof factors such as cost, time, and performance 0.62

(continued )

Table V.FA results – independent

variables

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Items Loadings Cronbach’s a

Feedback provided to employees on their quality performance 0.60Level of assessment and improvement of processes, practices, andproducts/services 0.67Variable 5. Supplier management 0.910The company works in close collaboration with suppliers toimprove processes 0.72The company provides technical assistance to suppliers 0.71Extent to which suppliers are selected based on quality rather thanprice or schedule 0.77Extent to which suppliers are trained and educated to achievequality performance 0.71Extent to which the company build long-term relationships withsuppliers 0.76Clarity of specifications provided to suppliers 0.78Amount of review or checking or inspection for incoming qualityin the company 0.75Extent to which suppliers are involved in the product and servicedevelopment process 0.72Variable 6. Employee involvement 0.839Extent to which employees are encouraged for suggestions andinnovation 0.52Extent to which employees are actively involved in TQM relatedactivitiesa 0.43a

Extent to which employee involvement type programs like qualitycircles, cross-functional and quality improvement teams areimplemented for problem solving in companya 0.43a

Degree of coordination among employees of various department toachieve overall improvement in service quality 0.55Extent to which employees’ suggestions are evaluated andimplemented, if accepted 0.52Extent to which management encourage employees to participatein achieving organization’s objectives 0.50Variable 7. Information and analysis 0.874Extent to which important information is presented andtransmitted to employees 0.52Extent to which quality data (cost of quality, rejections rate, errorsrate, etc.) are used as tools to manage quality 0.60Use of charts, graphs and other statistical tools and techniques tomonitor quality 0.69Degree to which departmental meetings are conducted at regularintervals to plan, implement and monitor the effectiveness ofquality improvement programs 0.72Extent to which quality data are used by top and middlemanagement in decision making, planning and controlling 0.65Variable 8. Process management 0.809Degree to which the processes and procedures are streamlined andfoolproofa 0.46a

Degree to which technological capability (e.g. computerization,networking of operations, etc.) are enhanced to serve customersmore effectively and compete in the marketa 0.48a

(continued )Table V.

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Items Loadings Cronbach’s a

Regular tracking and maintenance of the key processes that arecritical to the company 0.75Emphasis on developing procedures for reducing the overallservice delivery times 0.61Emphasis on measuring customer complaints by involving andtaking feedback from them for service delivery improvement 0.66Variable 9. Quality systems 0.716Emphasis on continuous improvement of quality system in thecompanya 0.47a

Company has a clear quality manual and documentation procedure 0.57Company has a clear set of work instructions 0.52Extent to which implementation of strategies that focus on qualityis ensured at every stage of product and service developmenta 0.41a

Variable 10. Benchmarking 0.891Emphasis on benchmarking the services and processes with thoseof direct competitors 0.64Emphasis on benchmarking the training and developmentprograms with those of direct competitors 0.73Emphasis on benchmarking servicescapes (i.e. the cleanliness,appeal, physical facilities, physical layout, ambient condition, etc.)with those of other companies 0.78Emphasis on benchmarking the level of quality culture with thoseof direct competitors 0.67Emphasis on benchmarking the best practices and performance ofdirect competitors 0.76Variable 11. Quality culture 0.891Degree to which the management and employees accepts qualityas a strategic weapon in strengthening the company and to gaincompetitive advantage 0.66Degree to which the employees at all levels accepts the motto“service to customers” as the real purposeof their existence 0.68Extent to which the employees believe in doing things “right thefirst time and every time” 0.60Level of prevalence among employees, feeling such as “mycompany” or “my organization” and “we work together to achievecommon goals” 0.55Level of appearance of employees having a pleasant andprofessional look 0.60Degree to which physical layout of premises, facilities and otherfurnishings are comfortable for the employees to work 0.54Extent to which house keeping is kept as a priority and of thehighest order in the company 0.60Variable 12. Human resource management 0.902Degree of importance given to quality consciousness of employeesat the recruitment stage 0.56Effectiveness of the selection and recruitment process throughemploying “right man for the right job” 0.66Degree of importance given to work values and ethics foremployees selection 0.62

(continued ) Table V.

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Items Loadings Cronbach’s a

Extent to which employees are treated as long-term assets of thecompany 0.53Degree to which the employees are allowed freely to express theirviews, criticism and feedback about functioning and performanceof company 0.66Degree to which employees gets enough support andencouragement to solve problems 0.58Extent to which the company is concerned about employee wellbeing (health, security and ergonomics) 0.52Variable 13. Strategic planning 0.782Development and implementation of strategies and operationalplans focused on qualitya 0.45a

Development and implementation of strategies and operationalplans focused on customer satisfaction 0.50Extent to which management sets objectives for managers andemployees 0.50Extent to which the top-management supports long-term qualityimprovement process rather than short term gainsa 0.48a

Allocation of adequate resources for new facilities, processimprovements, and training is done considering long-termobjectives 0.54Variable 14. Employee encouragement 0.892Degree to which the management provides ample recognition,rewards and encouragement to the employees for qualityimprovement/performance 0.55Extent to which the innovative ideas and suggestions of employeesare encouraged and rewarded 0.56Effectiveness of grievance redressal of employees 0.65Extent to which non-financial incentives systems (like selection fortraining programs, selection for higher studies, preference forchoice of posting, etc.) are used to reward quality contributions andachievementsa 0.47a

Extent to which financial incentive schemes for qualityperformance are used to motivate employees 0.60Extent to which career advancement opportunities are designedand implemented 0.54Variable 15. Teamwork 0.871Extent to which the employees trust each other and work as a team 0.60Extent to which team members routinely engaged in solving theproblems of the company through conducting brainstormingsessions, decision making sessions, group meetings, etc. 0.57Extent to which team members appreciate constructive criticism 0.66Existence of communication within the team members to generategood ideas about potential changes and solutions to problems 0.67Variable 16. Communication 0.900Extent to which quality goals, strategies and plan of action areperceived in the same way by bothmanagement and employees 0.71Overall effectiveness of communication process in the company interms of quickness and completeness 0.75

(continued )Table V.

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There was a significant positive relationship between “quality culture” and “qualityperformance” (r ¼ 0.699, p , 0.01). It was followed by “top-management commitment”(r ¼ 0.637, p , 0.01); “customer focus” (r ¼ 0.657, p , 0.01); “training and education”(r ¼ 0.686, p , 0.01); “continuous improvement and innovation” (r ¼ 0.659, p , 0.01);“employee involvement” (r ¼ 0.431, p , 0.01); “information and analysis”

Items Loadings Cronbach’s a

Effective top-down, bottom-up and horizontal communication inthe company 0.78Extent to which reports on the effectiveness of QM program arecommunicated to the employees 0.74Extent to which duties and responsibilities of each employee aremade clear to him or her 0.61Variable 17. Product and service design 0.776Extent to which product and services are designed and developedbased on customer needs and expectations 0.50Clarity of product and service specifications and procedures 0.50Extent to which new products and service designs are reviewedbefore it is produced and marketeda 0.41a

Emphasis on quality of new products and services rather thanreducing costa 0.48a

Extent to which the company evaluates and improves designs anddesign processes for the improvement in service qualitya 0.45a

Extent to which products and services are made fail-safe tominimize employee errorsa 0.44a

Extent to which the company adopt inter-departmentalcoordination activities during the product and service developmentprocesses 0.52

Notes: * *p , 0.01; Sig. ¼ 0.000; n ¼ 172; KMO measure of sampling adequacy ¼ 0.870; approximatex 2 ¼ 17325.27; adeleted items due to low factor loading (,0.50); percentage of variance explained: 72.0 Table V.

Items LoadingsCronbach’s

a

Quality performance 0.879Extent to which company’s level of quality performance has increased ascompared to industry norms 0.73Extent to which number of errors has reduced 0.80Extent to which the employee turnover has decreased 0.71Extent to which absenteeism among employees has reduced 0.76Extent to which employees perform the service right the first time and are ableto leave a good impression on customers 0.74Extent to which number of customers complaints has reduced 0.73Extent to which number of repeat customers has increased 0.70Extent to which supplier performance in terms of reliability, competence,cooperation has improved 0.72

Notes: * *p , 0.01; Sig. ¼ 0.000; KMO measure of sampling adequacy ¼ 0.879; approximatex 2 ¼ 584.00; percentage of variance explained: 54.24

Table VI.FA results – dependent

variable

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*0.

194

*0.

729

**

0.62

3*

*0.

500

**

0.41

0*

*0.

224

**

0.34

4*

*0.

199

**

1.00

0S

trat

egic

pla

nn

ing

0.52

4*

*0.

397

**

0.61

5*

*0.

520

**

0.41

5*

*0.

480

**

0.55

5*

*0.

595

**

0.51

4*

*0.

456

**

0.58

6*

*0.

415

**

0.39

7*

*1.

000

Em

plo

yee

enco

ura

gem

ent

0.43

6*

*0.

312

**

0.46

2*

*0.

534

**

0.38

7*

*0.

725

**

0.63

9*

*0.

516

**

0.49

4*

*0.

331

**

0.33

7*

*0.

348

**

0.68

0*

*0.

511

**

1.00

0T

eam

wor

k0.

608

**

0.44

0*

*0.

599

**

0.58

4*

*0.

499

**

0.30

0*

*0.

485

**

0.47

9*

*0.

481

**

0.52

5*

*0.

451

**

0.59

3*

*0.

287

**

0.56

6*

*0.

501

**

1.00

0C

omm

un

icat

ion

0.53

5*

*0.

424

**

0.54

9*

*0.

481

**

0.44

8*

*0.

365

**

0.51

2*

*0.

540

**

0.46

0*

*0.

454

**

0.53

4*

*0.

480

**

0.35

0*

*0.

669

**

0.50

6*

*0.

729

**

1.00

0P

rod

uct

and

serv

ice

des

ign

0.59

8*

*0.

539

**

0.60

2*

*0.

541

**

0.53

7*

*0.

349

**

0.50

1*

*0.

569

**

0.46

6*

*0.

574

**

0.59

0*

*0.

600

**

0.35

6*

*0.

704

**

0.45

9*

*0.

700

**

0.74

6*

*1.

000

Notes:

Cor

rela

tion

issi

gn

ifica

nt

at:

* p,

0.05

and

** p

,0.

01le

vel

s(t

wo-

tail

ed);n¼

172

Table VII.Pearson’s correlationanalysis of TQMpractices and qualityperformance

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(r ¼ 0.466, p , 0.01); “process management” (r ¼ 0.491, p , 0.01); “quality systems”(r ¼ 0.658, p , 0.01); “benchmarking” (r ¼ 0.409, p , 0.01); “human resourcemanagement” (r ¼ 0.311, p , 0.01); “strategic planning” (r ¼ 0.524, p , 0.01);“employee encouragement” (r ¼ 0.436, p , 0.01); “teamwork” (r ¼ 0.608, p , 0.01);“communication” (r ¼ 0.535, p , 0.01); and “product and service design” (r ¼ 0.598,p , 0.01). The weakest correlation was for “supplier management” and “qualityperformance” (r ¼ 0.297, p , 0.01). It was found that all the TQM practices hadsignificant positive correlation (p , 0.01) with quality performance. The results alsoindicate that respondents had high levels of company’s quality performance. Out of 153correlations, all correlation coefficient are larger than 0.20. The highest coefficient ofcorrelation in this research however, is 0.816 which is below the cut-off of 0.90 for thecollinearity problem. Further, the correlation coefficient between the independentvariables and dependent variable were less than 0.90, indicating that the data was notaffected by a collinearity problem (Hair et al., 1998). Hence, collinearity andmulticollinearity do not represent data problems in this research study. The resultsfurther indicated that the most important TQM practice affecting quality performancewas quality culture (i.e. with the highest score of correlation), which goes to prove thatwhere quality culture was perceived as a dominant TQM practice, improvements inquality performance levels were significant. Similarly, training and education; customerfocus; continuous improvement and innovation; quality system; and teamwork were alsofound affecting quality performance as their scores were also high.

Multiple regression analysisMultiple regression is used to investigate the relationship between single dependentvariable (criterion) and several independent variables (predictors or explanatory) at onetime (Hair et al., 1998). It is employed to test the research hypotheses. In this analysis,a set of independent variables is weighted to form the regression variate (regressionequation or model) and that may be used to explain its relative contribution towards onedependent variable (Hair et al., 1998). This analysis was undertaken to better understandthe relationships between TQM practices and quality performance.

One of the vital considerations in multiple regression analysis is the sample size of thedata. According to Hair et al. (1998), a sample size to estimate parameter ratio of 10:1 isadequate to achieve meaningful estimates. The sample size of this study has anestimated parameter ratio of 10.2:1 for the quality performance. Accordingly, it wasfound that the sample size was adequate. Based on this method, the 17 main independentvariables (TQM practices) and dependent variables (quality performance) were enteredusing forced entry or simultaneous regression method. Scatter and Normal P-P plots ofstandardize residual that were conducted to check the normality, homoscedasticity,linearity, and outliers, if any, as shown in Figures 2 and 3 also indicate normality andconsistent variance of the error terms (homoscedasticity). It also showed that there is noclear relationship between the residual and the predicted values which is consistent withthe assumption of linearity. Further, because no univariate outliers were found,case-wise plots were not necessary. If they had been produced, then these plots wouldhave identified outlying cases with standard deviations greater than 3.

The details of the overall model summary and multiple regression output are shownin Tables VIII and IX. From Table VIII, the Durbin-Watson index is at 2.044, which lieswithin the range of 1.50-2.50, suggesting that there was no autocorrelation problem

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in the data (Durbin and Watson, 1951). Also, from Table IX, each of the variables had atolerance value of more than 0.10 and variation inflation factor (VIF) of less than 10.The finding indicated that the model had no serious multicollinearity problem (Hair et al.,1998) as also found in Pearson’s correlation analysis in the previous section. Thisindicated that there is a statistically significant relationship between TQM practicesand quality performance. From these analyses, it can be concluded that multipleregression model of this study meets all the assumptions required to ensure validity ofits significance test (Ooi et al., 2007a, b, 2012).

Change statistics

Model R R 2Adjusted

R 2SE of theestimate

R 2

changeF

change df1 df2SignificanceF change

Durbin-Watson index

1 0.804 0.646 0.607 0.40436 0.646 16.538 17 154 0.000 2.044

Notes: Significant at: p , 0.01 level (two-tailed); n ¼ 172Table VIII.Overall model summary

Figure 2.Normal P-P plot ofregression standardizedresidual

Observed Cum Prob

Dependent Variable: QP

Exp

ecte

d C

um

Pro

b

1.0

1.0

0.8

0.8

0.6

0.6

0.4

0.4

0.2

0.20.0

0.0

Figure 3.Scatter plot

Dependent Variable: QP

Regression Standardized Predicted Value

Reg

ress

ion

Sta

nd

ard

ized

Res

idu

al

–4 –2 0 2

–4

–2

0

2

4

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In order to judge the magnitude of effects in this study, Cohen’s rules for effects sizescan be used. According to Cohen (1988) as cited by Jitpaiboon and Rao (2007), R 2

between 1.0 and 5.9 percent is considered as small, between 5.9 and 13.8 percentis medium, and above 13.8 percent is large. From Table VIII, it can be observed thatcoefficient of determination (R 2) was 0.646, representing that 64.6 percent of qualityperformance can be explained by the 17 independent variables. This expresses thatTQM can significantly account for 64.6 percent in quality performance. Thus, the effectsize for this study is large and H1 was partially supported. The proposed model was

Unstandardizedcoefficients

Standardizedcoefficients

Qualityperformance

Collinearitystatistics

ModelIndependentvariable(s) B SE b t-value Sig. Tolerance VIF Results

1 (Constant) 0.724 0.202 3.592 0.000Top-managementcommitment

0.071 0.071 0.094 1.000 0.319 0.262 3.814 Reject(H11)

Customer focus 0.021 0.074 0.026 0.278 0.782 0.260 3.852 Reject(H12)

Training andeducation

0.131 0.069 0.172 1.914 0.057 * * * 0.285 3.511 Accept(H13)

Continuousimprovementand innovation

20.043 0.094 20.050 20.454 0.650 0.192 5.220 Reject(H14)

Suppliermanagement

20.042 0.069 20.052 20.611 0.542 0.315 3.177 Reject(H15)

Employeeinvolvement

0.028 0.068 0.033 0.412 0.681 0.361 2.774 Reject(H16)

Information andanalysis

0.006 0.063 0.007 0.089 0.929 0.429 2.331 Reject(H17)

Processmanagement

0.040 0.056 0.047 0.721 0.472 0.533 1.877 Reject(H18)

Quality systems 0.135 0.058 0.177 2.316 0.022 * * 0.392 2.554 Accept(H19)

Benchmarking 20.076 0.060 20.192 20.963 0.090 * * * 0.434 2.304 Accept(H110)

Quality culture 0.268 0.086 0.306 3.115 0.002 * 0.239 4.192 Accept(H111)

Human resourcemanagement

0.047 0.064 0.058 0.724 0.470 0.362 2.761 Reject(H112)

Strategicplanning

0.090 0.070 0.108 1.278 0.203 0.323 3.094 Reject(H113)

Employeeencouragement

0.007 0.068 0.009 0.103 0.918 0.312 3.203 Reject(H114)

Teamwork 0.075 0.068 0.184 1.951 0.080 * * * 0.313 3.196 Accept(H115)

Product andservice design

0.008 0.077 0.009 0.100 0.920 0.277 3.610 Reject(H116)

Communication 0.037 0.066 0.048 0.559 0.577 0.315 3.178 Reject(H117)

Notes: Significant at: *p , 0.01, * *p , 0.05 and * * *p , 0.1 levels (two-tailed); n ¼ 172

Table IX.Multiple regression

analysis of TQMpractices on quality

performance

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adequate as the F-statistics {F(17,154) ¼ 16.538} was significant at 1 percent level( p , 0.01). This indicated that the overall model was statistically significant andpositive relationship between TQM practices and quality performance (Table VIII).

The results of multiple regression analysis, include the standardized b coefficientsand t-value significant level, are tabulated and presented in Table IX. The results alsoindicated that there are five practices of TQM, namely: training and education; qualitysystems; benchmarking; quality culture; and teamwork which are positively associatedwith quality performance. The individual model variable revealed that training andeducation (b ¼ 0.172, p , 0.1); quality systems (b ¼ 0.177, p , 0.05); benchmarking(b ¼ 20.192, p , 0.1); quality culture (b ¼ 0.306, p , 0.01); and teamwork (b ¼ 0.184,p , 0.1) are all directly involved in the improvement of quality performance. Therefore,H13, H19-H111, and H115 were supported. Meanwhile, top-management commitment;customer focus; continuous improvement and innovation; supplier management;employee involvement; information and analysis; process management; human resourcemanagement; strategic process; employee encouragement; product and service design;and communication had no significant effect on quality performance. Hence, H11, H12,H14-H18, H112-H114, H116, and H117 were not supported. However, these practiceshave provided long-term (strategic), operational, and tactical (supportive) as well asinfrastructural benefits necessary for the continuous improvement over time but with anindirect relationship towards quality performance.

DiscussionThe overall objective of this section was to examine the nature of TQM practices andits relationship towards quality performance within Indian service sector. Overall, theoutcome of this study indicated that the TQM practices were found to be partiallycorrelated with quality performance of the Indian service companies.

The determinants of TQM practices in quality performance were training andeducation; quality systems; benchmarking; quality culture; and teamwork. The studyfurther revealed that where quality culture was perceived as a dominant TQM practice,there was strong association with quality performance. The result implies that TQMrecognizes and emphasizes the importance of quality culture to monitor organizationalculture and to evolve better TQM practices so that quality performance and otherquality-related outcomes are maintained at a high level. The result provide supportingevidence from the views of Yusof and Ali (2000) which states that organizationalculture is not only able to change, guide, and display behavior of the individual butalso give significant contribution by influencing the thoughts, feelings, satisfaction,interactions, and affective reactions within the company. Further, the study by Ooi et al.(2007b) also provided the supporting evidence that there is a significant relationshipbetween quality culture and employees’ job satisfaction. According to Saravanan andRao (2007), deployment of quality culture within the organization is the major factor fororganization to be successful and to achieve quality products and services.

The next dominant TQM practice found in this study which has strong and positiveassociation with quality performance is quality systems. The result indicates thatTQM recognizes and emphasizes the importance of quality systems as a processapproach in deploying, implementing, and improving the effectiveness of company’sQM system. The study further revealed that the service companies must better utilizeprocesses in their QM system. The processes may be properly aligned and measured

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against key objectives to identify opportunity for improvement. This finding was alsosupported by Zhang (2000). Schevermann et al. (1997) further reported that use ofquality systems like quality tools and techniques in service organizations are beneficialfor its business performance. However, the results are in contrast with an earlier workof Arumugam et al. (2008).

Training and education was discovered to be significant and positively related toquality performance. However, this result is inconsistent with the outcomes of Zhang(2000) and Ooi et al. (2008). Training and education is important and management shouldunderstand that there activities lead to long-term commitment, as the outcome of TQMimplementation are not realized immediately. It was also discovered that training andeducation has more positive effects on service industries workers rather thanmanufacturing industries workers (Zhang, 2000). As per Cherrington (1995), in order tominimize TQM barriers like employee absenteeism and high-turnover rate, and whenemployees are not satisfied, top-management proposes a company-wide trainingprogram. Study by Karia and Asaari (2006) also emphasized the use of training andeducation practice within an organization to increase business performance.

Teamwork was found to be significant and positively related to quality performance.The positive influence of teamwork on quality performance was concurred with priorfindings (Ooi et al., 2007b, 2008; Yang, 2006). Teamwork leads to facilitate employees’ability to work together as a team and with full participation (Karia and Asaari, 2006;Yang, 2006). It was also found that working together as a unit improves employees’attitudes (Osland, 1997). According to Anschutz (1995), participation in teamwork wasthe major factor for a successful organization to achieve collaboration betweenemployees and management.

Similarly, benchmarking was found significant and positively associated withquality performance. In order to compete in the market, benchmarking helps inimproving the performance of the company (Yusuf et al., 2007). Benchmarking discoversthe best practices, sets target, and adopt them in the company to achieve competitiveadvantages. Hence, benchmarking leads to meeting customers’ need (Yusuf et al., 2007).

Conversely, top-management commitment was found not significantly associatedwith quality performance. It showed that the level of management involvement still notintensive enough to influence quality performance. The finding supported the work ofArumugam et al. (2008) and Sit et al. (2009).

Supplier management was found not significant enough to influence qualityperformance. The finding suggested that the level of performance and relationship inproducts, processes, and service development was relatively poor. As a result, suppliermanagement as a TQM practice does not affect quality performance. This finding was inline with prior research (Zhang, 2000; Arumugam et al., 2008; Talib and Rahman, 2012).

It was also discovered that strategic planning is insignificant to qualityperformance. This implies that strategic planning in the service companies of Indiafailed to induce it, which contradicts with the previous study of Terziovski (2006).Further, the service industries must have clear mission and vision statement in order toimprove quality performance of the company. From the TQM perspective, a qualitypolicy is usually communicated via a “quality vision” statement (Sit et al., 2009).

Finally, process management was also found to be insignificant to qualityperformance. This result is consistent with the findings of Sit et al. (2009).Also, information and analysis; human resource management; and customer focus were

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also discovered to be insignificant to quality performance. The result of this study isin contrast with Sit et al. (2009) and Ott and van Dijk (2005).

Furthermore, the results of bivariate and multiple regression analyses confirmedthat the quality performance variable was significantly related to perceptions of TQMpractices and thus, implementing TQM does payoff.

ConclusionsThis research paper has accomplished the stated objectives of the study successfullyand analyzed the relationship between the TQM practices and quality performance inthe Indian service companies.

The study found 12 TQM practices (top-management commitment, customer focus,continuous improvement and innovation, supplier management, employee involvement,information and analysis, process management, human resource management, strategicplanning, employee encouragement, product and service design, and communication) tobe partially influencing the company’s quality performance. In response to RQ1, thefindings presented empirical evidence that TQM have significant and positiveassociation with quality performance. In response to RQ2, the findings indicated thatwhere quality culture was perceived as a dominant TQM practice, it has strongassociation with company’s quality performance. However, the findings also indicatedthe importance of quality systems, training and education, teamwork andbenchmarking for predicting company’s quality performance. Thus, the results of thestudy reported five practices of TQM that are more significantly associated withthe improvement in company’s quality performance and provides evidence of thepositive impact of TQM on company’s quality performance.

Furthermore, the study provided a useful framework for evaluation of TQMimplementation in Indian service companies as measured by the survey instrumentand identified 17 TQM practices for its successful implementation. These practicesrelate to perception of quality performance. All the 17 TQM practices were found tocorrelate with quality performance, regardless of the nature and type of the company.This study provided the impact of TQM on company performance in both qualitativeand quantitative terms.

Managerial implications and future researchWith regard to the managerial contributions, the findings prescribe potentialimplications for top-management to review their TQM practices and focus first oncompany’s quality culture. The importance of quality culture in the company is essentialfor the TQM to be successful. It uses teams, promotes pride in workmanship, drives outfear, allows participative management, promotes leadership in place of supervision,and promotes long-term orientation among the employees of the company. Hence, it isconcluded that the successful implementation of TQM is reliant upon the prevailingcompany culture and there is a need to change the company’s culture and attitudes of theworkforce for TQM to be effective. In addition, the usage or application of differentquality tools and techniques in the company to up date their quality systems, providetraining to employees, emphasize on working as a team with a common goal to achieve,and benchmarking the practices of other emerging companies to have a competitiveedge in the marketplace. Further, this study assumes that superior qualityperformance in the implementation of TQM practices requires company’s focus

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on customer satisfaction. Survey techniques like customer review and feedback,complaint analysis should be undertaken at regular interval to ensure the fulfillment ofcustomer needs and expectations which will enhance the level of quality performance.Also, the findings of this study serve as a valuable guideline or yardstick for bothresearchers and managers to review their TQM programs and conduct it on a prioritybasis in order to facilitate quality performance within their companies. Another lesson tobe learned is that the remaining practices of TQM which are indirectly related to thecompany’s performance, are provider of long-term (strategic), operational, and tactical(supportive) as well as infrastructural benefits necessary for the continuousimprovement over time, but with a less significant relationship with qualityperformance should not be overseen. Finally, the findings support the argument thatthe practices should be implemented holistically rather than on a piecemeal basis to getthe full potential of the identified TQM practices.

To the best of the knowledge, this is the first study undertaken within Indianservice companies to examine the relationship between TQM practices and qualityperformance. Thus, the findings of this study provide valuable knowledge in QM fromIndian service sector perspective. The findings can help academics, consultant, policymakers, quality practitioners, and companies that would like to support and promoteTQM in India.

However, a similar study may be undertaken to other emerging and newlydeveloped service industries which have not been covered in this study to understandwhether these TQM practices also influence quality performance and hence, may be abetter area for further research. Also, application of structure model analysis can beanother area to develop structural relationship between TQM practices and qualityperformance, and test the hypotheses.

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About the authorsDr Faisal Talib is an Assistant Professor in the Mechanical Engineering Section, UniversityPolytechnic, Aligarh Muslim University, Aligarh, (UP), India. He holds a PhD degree from IITRoorkee and a Master’s degree in Industrial and Production Engineering from AMU. He hasmore than 15 years of teaching experience and has 45 publications to his credit innational/international journals and conferences. His special interests include quality engineering,TQM, service quality, quality concepts, industrial management, operations management, andquality management in service industries. Faisal Talib is the corresponding author and can becontacted at: [email protected]

Dr Zillur Rahman is an Associate Professor in the Department of Management Studies, IITRoorkee. He is a recipient of the Emerald Literati Club Highly Commended Award and one of hispapers was The Science Direct Top 25 Hottest Article. His work has been published and cited invarious journals, including Management Decision, Managing Service Quality, International Journalof 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 IndustrialMarketing, and International Journal of Computer Integrated Manufacturing, to name a few.

Dr M.N. Qureshi is an Associate Professor in the Mechanical Engineering Department, TheMS University of Baroda. He earned his graduation and post graduation degrees in MechanicalEngineering from MS University of Baroda and later, his PhD degree from IIT Roorkee, Roorkee.He has more than 75 publications to his credit in national/international journals and conferenceproceedings. His areas of interest include logistics & supply chain management, industrialmanagement, quality management, etc.

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