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Critical success factors for TQMimplementation and their impact

on performance of SMEsSalaheldin Ismail Salaheldin

Department of Management and Marketing,College of Business and Economics, Qatar University, Doha, Qatar

AbstractPurpose – The purpose of this paper is to identify the critical success factors of TQM implementation,to evaluate their impact on the primary measures as expressed by the operational performance and thesecondary measures as expressed by the organizational performance, and to nd out the effect of theoperational performance on the organizational performance of small and medium-sized enterprises(SMEs) in the Qatari industrial sector using the structured equation modeling (SEM) approach.Design/methodology/approach – A questionnaire was designed and distributed to 297 SMEs in theQatari industrial sector. Of the 297 questionnaires posted, a total of 139 were returned and were used totest the theoretical model. In particular, hypotheses were developed to evaluate the impact of TQMimplementation on the operational and organizational performance of the SMEs.Findings – The empirical analysis demonstrates several key ndings: data analysis reveals thatthere is a substantial positive effect of the TQM implementation on both the operational and theorganizational performance. The ndings conrm the signicant relationship between operational andorganizational performances of the SMEs. Overall, the results showed the central role of the strategicfactors in the successful implementation of the TQM programs within the SMEs.Research limitations/implications – The research is subject to the normal limitations of surveyresearch. The study is using perceptual data provided by production managers or quality managerswhich may not provide clear measures of performance. However, this can be overcome using multiplemethods to collect data in future studies. Interestingly, the ndings here may be generalisable outsideQatar, i.e. a similar country to Qatar such as the GCC countries.Practical implications – Qatari SMEs should consider TQM as an innovative tool for improvingoperational and organizational performance in today’s dynamic manufacturing environment. Thendings suggest the notion that the TQM critical success factors (CSFs) should be implementedholistically rather than on a piecemeal basis to get the full potential of the TQM. Moreover, the studyemphasizes the need to link operational performance to organizational performance to achieve thesuccess of TQM implementation.Originality/value – The study integrates the CSFs of TQM practices, i.e. strategic, tactical andoperational factors, with operational and organizational performances as related drivers of theeffectiveness and success of TQM practices in the SMEs. Very few studies have been performed toinvestigate and understand this issue. Therefore, the research can make a useful contribution.

Keywords Total quality management, Critical success factors, Small to medium-sized enterprises,Business performance, Organizational performance, QatarPaper type Research paper

Background of the studyWith the rapid globalization of the Qatari economy, manufacturing rms are facedwith a changing competitive environment. They are competing in creating theconditions that will enable them to be competitive in the domestic and international

The current issue and full text archive of this journal is available atwww.emeraldinsight.com/1741-0401.htm

Critical successfactors for TQMimplementation

215

Received January 2008Revised March 2008

Accepted March 2008

International Journal of Productivityand Performance Management

Vol. 58 No. 3, 200pp. 215-237

q Emerald Group Publishing Limited1741-0401

DOI 10.1108/1741040091093883



markets. Accordingly, all manufacturing rms seek to adopt and implement a set of operations management practices that have been successful elsewhere and that willhelp them to identify changes in their environment and to respond proactively throughcontinuous improvement (Fassoula, 2006). One form of operations managementpractices is TQM which has received great attention in the last two decades (Jung andWang, 2006). Thus far, much have been written on TQM and its value in improving theperformance of manufacturing industries in general. Literature on TQMimplementation suggests that the TQM practices are positively associated withoperational performance (Choi and Eboch, 1998), but they marginally affectorganizational performance (Broetzmann et al., 1995).

On the other hand, research ndings concluded that the success of SMEs has adirect impact on the economic development in both the developed and developingcountries (Demirbag et al., 2006). They have the ability to generate employment withminimum cost, are pioneer in innovation realm and have high exibility which allowthem to meet the needs of the customers (Brock and Evans, 1986; Acs and Audretsch,1990).

However, a review of the current literature on TQM practices indicated that muchhave been written about TQM implementation in large manufacturing companies, butlittle attention has been paid to their implementation in the SMEs (Rahman, 2001;Petroni, 2002; Seth and Tripathi, 2005). In a similar vein, there is a dearth of literatureregarding the impact of TQM implementation on performance of SMEs, despite thepotential synergies between the two areas (Demirbag et al., 2006; Sila, 2007).Furthermore, it has been pointed out about the lack of consistency in research inQuality Measurement (QM) area due to the absence of standard and universallyacceptable measurement instrument.

More importantly, most of previous studies have been done on the impact of TQMpractices on performance of the SMEs in Europe, USA and the Far East (Rahman, 2001;

Petroni, 2002; Seth and Tripathi, 2005; Demirbag et al., 2006; Sila, 2007). In contrast,few, if any, previous writers have analyzed TQM- performance relationships of SMEsin emerging market economies (Koh et al., 2007).

In the same line, Pun and Gill (2002) reported in their study that there is a consensusregarding the versatility of TQM implementation. Thus, there is a stringent necessityto provide a model that amalgamates TQM enablers with TQM effectiveness and TQMsuccess.

Importance of the studyThere are many empirical studies which examine TQM practices-performancerelationships in large rms (Powell, 1995; Ahire and Golhar, 1996; Motwani, 2001;Montes et al., 2003; Brah and Lim, 2006; Kapuge and Smith, 2007). In contrast to mostprevious studies found in the literature, this research examined these relationships in adifferent way. Specically, this study adopted a more comprehensive approach thanprevious studies to investigate the effects of TQM practices on performance in theSMEs. In other words, this study has a wider coverage of the key TQM success factors,i.e. strategic, tactical and operational factors. It also adopted the primary measures asexpressed by the operational performance as the key mediating variables thatcomprise TQM effectiveness, all of which might have an impact on TQM CSFs – organizational performance relationships.

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More importantly, the study offers an added factor to be taken into consideration,particularly when examining the effect of the operational performance on theorganizational performance as expressed by the nancial and non-nancial measures.

This study offers a theoretical model that can be considered as a step forward indeveloping an integrated model toward investigating the relationship between TQMCSFs, TQM effectiveness as expressed by the operational performance and TQMsuccess as expressed by the organizational performance and might serve as a basis forfuture research. Most of previous research on TQM practices have been done indeveloped countries. The present study contributes by comparing TQM practices andtheir impact on the operational and organizational performances in the SMEs of developed and developing countries. Finally, this research adds to the body of knowledge by providing new data and empirical insights into the relationship betweenthe CSFs of TQM practices and operational and organizational performances of SMEsin Qatar.

Thus, based on the analysis of past reseach, the purpose of this paper is threefold:

(1) To identify the CSFs of TQM practices of the SMEs in the Qatari industrialsector;(2) To evaluate the impact of the TQM CSFs on the operational and the

organizational performances of the SMEs; and(3) To examine the effects of the operational performance (primary measures) on

the organizational performance (secondary measures).

Model and hypothesesThe conceptual model of the current study is drawn from two streams of research, i.e.operations management literature and organizational performance literature. Figure 1illustrates the conceptual model with the hypothesized relationships between theconstructs. These relationships deal with three sets of hypotheses:

Figure 1.Proposed model for the

e ffects of TQM practiceson performance


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(1) The effects of the TQM CSFs on the operational performance (primarymeasures).

(2) The relationship between the TQM CSFs and the organizational performance(secondary measures).

(3) The impact of the primary measures (as expressed by the operationalperformance) on the secondary measures (as expressed by the organizationalperformance).

The next section provides a brief denition for each construct, i.e. TQM CSFs andperformance measures followed by the development of the hypotheses.

Critical success factors of TQM practices in the SMEsGenerally speaking, the CSFs can be dened as the critical areas which organizationmust accomplish to achieve its mission by examination and categorization of theirimpacts (Oakland, 1995). Thus, in the current study they can be viewed as those thingsthat must go right in order to ensure the successful implementation of TQM.

On the other hand, the review of the literature suggested that there are numerousCSFs that can be identied as being crucial to the successful implementation of TQM(also referred to as contributing variables or critical factors or enablers in theliterature).

One of the earlier empirical studies in the quality management area that analyzedthe TQM CSFs in the SMEs was conducted by Yusof and Aspinwall (2000). This studyfound that the CSFs for TQM implementation in the SMEs are management leadership,continuous improvement system, measurement and feedback, improvement tools andtechniques, supplier quality assurance, human resource development, systems andprocesses, resources, education and training, and work environment and culture.

More importantly, Hodgetts et al. (1999) found that the CSFs of TQMimplementation in the SMEs are top management involvement, customer focus,employees “training, employees” empowerment and generating new ideas.

In this line of work, a study by Dayton (2003) used data from American industrialcompanies to determine whether the ten TQM critical factors (i.e. people and customermanagement, supplier partnerships, communications, customer satisfaction, externalinterface management, strategic quality management, teamwork structures forimprovement, operational quality planning and quality improvement systems)identied by the Black and Porter (1996) study could be considered as important TQMCSFs by USA small and large companies. From his conclusion he identied thestrategic quality management as the most important TQM critical factor.

The empirical ndings from Rahman’s (2001) study of 53 Australian SMEs foundthat the critical factors of the successful implementation of TQM are leadership,strategy and planning, employee empowerment and employee involvement, employeetraining and development, information and analysis and customer management.

Demirbag et al. (2006) carried out an empirical study to identify factors critical to thesuccess of TQM in the Turkish SMEs. They concluded that there are seven CSFs of TQM practices, i.e. quality data and reporting, role of top management, employeerelations, supplier quality management, training, quality policy and processmanagement.

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However, in contrast to the previous studies, organization culture was used as aseparate variable in the current study since an organization’s culture affects behaviorsand attitudes at all levels and it determines, to a large extent, how employees act(Robbins and DeCenzo, 2005).

In addition, the literature review undertaken revealed a lack of research with regardto some critical factors of TQM implementation (e.g. employees satisfaction, productdesign and building teams and solving problems), and this could be due to the fact thatthese factors are related to any new managerial approach such as JIT, MRPII and ERP,not necessarily to TQM only. Consequently, the current research proposes a holisticframework for TQM implementation based on an extensive review of the factors thatcontribute to the success TQM implementation.

Performance measuresGenerally speaking, performance is dened as the degree to which an operation fulllsthe performance objectives – primary measures – in order to meet the needs of thecustomers – secondary measures (Slack et al., 2001).

Performance measurement is a critical factor for the effective management. Thismay stem back from the fact that without measuring something, it is difcult toimprove it. Therefore, improving the organizational performance requires identifyingand measuring the impact of TQM practices on it (Demirbag et al., 2006; Koh et al.,2007).

Several empirical studies have been conducted to establish the link between TQMpractices and organizational performance (e.g. Sterman et al., 1997; Choi and Eboch,1998; Easton and Jarrell, 1998; Samson and Terziovski, 1999; Brah et al., 2002; Brah andLim, 2006; Demirbag et al., 2006; Feng et al., 2006). The results of these studiesindicated that there are various measures, i.e. organizational performance, corporate

performance, business performance, operational performance, nancial andnon-nancial performance, innovation performance, and quality performance.In a similar vein, Ramamurthy (1995); Beaumont et al. (2002); Brahet al. (2002); and

Koh et al. (2007) measured performance in two dimensions: operational performanceand organizational performance. Operational performance reects the performance of internal operation of the company in terms of cost and waste reduction, improving thequality of products, improving exibility, improving delivery performance; andproductivity improvement. They are considered as primary measures because theyfollow directly from the actions taken during the implementation of TQM, whileorganizational performance measured by nancial measures such as revenue growth,net prots, prot to revenue ratio and return on assets, and non-nancial measuressuch as investments in R&D, capacity to develop a competitive prole, new productsdevelopment, market development and market orientation, are secondary measuresbecause they are a consequence of TQM implementations. Accordingly, performancemeasures that have been suggested by (Ramamurthy, 1995; Beaumont et al., 2002; Brahet al., 2002; Demirbag et al., 2006; Sila, 2007) are used to measure performance in thisresearch.

In addition, the current study makes an attempt to bridge the gap left by earlierstudies regarding a lack of attention to safety and waste reduction as performancemeasures.


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Hypotheses formulationAlthough there are several CSFs related to performance measures, from review of theliterature 26 major variables are hypothesized as being signicantly related to theorganizational and operational performance measures in the Qatari SMEs.

The relationship between the TQM CSFs and operational performanceThere is a common assumption in the literature that the TQM CSFs have a positiveimpact on the operational performance (Powell, 1995; Ahire and Golhar, 1996; Brah andLim, 2006; Sila, 2007). They indicated that TQM rms out perform non-TQM rms inoperational performance such as improving delivery performance, reduction inproduction costs, increasing productivity, improving exibility, reducing scrap andimproving the quality of products.

To investigate the previous mentioned relationship, the current study makes anattempt to operationalize the CSFs, not only in terms of the importance of each factor,but also in terms of relative importance that is given to each factor. In this way, those

factors can be classied as strategic factors. They are broad in nature and impact thelong-term effectiveness of the company (Davis et al., 2003), and also they require asignicant change in the manner in which the business is conducted (Turban et al.,1999). Moreover, they are dominant factors which play a signicant role in thesuccessful implementation of TQM practices. Those factors include; top managementcommitment, organizational culture, leadership, continuous improvement, qualitygoals and policy, resources value addition process and benchmarking. So, the followinghypothesis is therefore proposed:

H1. Strategic factors have a direct and positive effect on operational performance.

The second group of factors can be classied as tactical factors. They are of lesscriticality than strategic factors of TQM implementation. However, these factors aresignicant to support the latter. More importantly, they impact the methods andactions that help accomplish the expected benets of TQM implementation. In otherwords, they affect the decision that are made by middle management (Turban et al.,1999). Those factors include employee empowerment, employee involvement,employee training, team building and problem solving, use of informationtechnology to collect and analyze quality data, supplier quality, supplierrelationships, integration with other systems and assessment of performance of suppliers. Therefore, it is hypothesized that:

H2. Tactical factors have a direct and positive effect on operational performance.

At the other end of the list, i.e. the least important or less critical factors are classied

as operational factors. They reect those factors which produce consequences that willbe visible in a short term period. Those factors include product and service design,process control, management of customer relationships, customer orientation,customer and market knowledge, realistic TQM implementation schedule, resourcesconservation and utilization, inspection and checking work and enterprise performancemetrics for TQM. Thus, the following hypothesis is offered:

H3. Operational factors have a direct and positive effect on operationalperformance.

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The effects of TQM CSFs on organizational performanceThe relationships between TQM practices and organizational performance have beenaddressed in several studies (Motwani, 2001; Montes et al., 2003; Brah and Lim, 2006;Demirbag et al., 2006; Kapuge and Smith, 2007; Sila, 2007). They indicated a positiveassociation between TQM practices and improved performance. In other words, theresults of those studies demonstrated the crucial role of TQM practices in enhancingthe organizational performance, i.e. nancial performance as measured by return oninvestment and market share growth and non-nancial performance as measured byinvestments in R&D and market orientation. Therefore, we expect:

H4. Strategic factors have a positive inuence on nancial performance.

H5. Strategic factors have a positive inuence on non- nancial performance.

H6. Tactical factors have a positive inuence on nancial performance.

H7. Tactical factors have a positive inuence on non- nancial performance.

H8. Operational factors have a positive inuence on nancial performance. H9. Operational factors have a positive inuence on non- nancial performance.

The effects of operational performance on organizational performanceThis study attempts to investigate the effects of the primary measures (as expressedby the operational performance measures) on the secondary measures (as expressed bythe organizational performance) (see Figure 1). As emphasized by Brah and Lim (2006),the operational performance has a positive correlation with overall organizationalperformance. One possible explanation could be due to the success of TQMimplementation as measured by operational measures such as producing high qualityproducts, speed of delivery, high exibility, switching costs, safety, waste reduction,resource conservation and high productivity would lead to success in the secondarymeasures, i.e. nancial and non-nancial measures (Brah et al., 2002; Brah and Lim,2006). This gives rise to the following hypotheses:

H10. Operational performance has a strong impact on nancial performance.

H11. Operational performance has a strong impact on non-nancial performance.

Hypothetical model The hypotheses presented in the previous section led us to a theoretical modeldescribed in Figure 1. The CSFs of TQM practices are factored into the three constructsof strategic, tactical and operational factors. The relationships between the CSFsconstructs to the operational and organizational performance constructs werehypothesized.

Study designSampleThe research design employed in the current study was a postal survey. The term“SMEs” covers a variety of denitions and measures. In Qatar, SMEs are dened as anindustrial undertaking in which the investment in xed assets in plant and machinery


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is less than Q.R 1.5 million ($410,959) for small rms and between Q.R 1.5 million($410,959) to Q.R 10 million ($2,739,726) for medium rms (Qatar Bank for IndustrialDevelopment, 2001). The rms included in the survey were all the SMEs in the Qatariindustrial sector. This choice was motivated by the following reasons:

. the SMEs represent the backbone of the Qatari economy; they have shown theirpresence in nearly all sectors of the economy;

. they account for 93.6 percent of the manufacturing industrial rms in the countryand provides about 70.2 percent of employment in the Qatari industrial sector(Gulf Organization for Industrial Consulting, 2005a, b); and

. some of the SMEs are producing directly for customer’ market while others areserving as suppliers to large rms.

Our target population (297 SMEs) was obtained from listings provided by the Gulf Organization for Industrial Consulting and from Industrial Bank databases. Thesewere carefully veried and cross-checked to ensure complete and up-to-dateinformation. A follow-up letter and a telephone call were also utilized to maximizethe response rate. All of the rms were contacted personally while 45 refused to beinvolved in the research quoting condentiality of data in the questionnaire as areason. A total of 139 rms thus comprised the nal sample which represents a(139/297) 46.8 percent response rate. Hair et al. (2006) pointed out that opinionsregarding sample sizes have varied. They further said that most SEM estimationprocedure (including the one used in this research) is maximum likelihood estimation(MLE) and they recommended that minimum sample sizes to ensure stable MLEsolutions are 100 to 150. Thus, the sample size of 139 is considered as appropriate forthis research.

The construction of the questionnaire and its appropriateness to the studyA personally-administered questionnaire was primarily adopted from earlier studiesspecically, the works of Saraph et al. (1989); Brah et al. (2002); Brah and Lim (2006);Demirbag et al. (2006); and Feng et al. (2006) and it was modied where necessary. Allthe items in the questionnaire were measured with a ve-point Likert scale rangingfrom very low (1) to very high (5) to ensure consistency and the ease of datacomputation (Brah and Lim, 2006). This scale was also pre-tested several times byacademics, consultants and 7 SMEs, who were well known to the researcher and it wasfound to be valid on the basis of our study.

The questionnaire distributed contained seven questions in three differentcategories as follows (see the Appendix):

(1) Questions 1-5. Data on SMEs prole(role in the enterprise, type of industry,number of employees, ownership and years of implementing TQM).(2) Question 6. Data on TQM critical success factors (24 practices).(3) Question 7. Data on performance measures (15 measures).

It was requested that the questionnaire needed to be completed by production manageror any manager in charge of quality management as in Saraph et al. (1989) andDemirbag et al. (2006).

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Reliability of the questionnaireCronbach’s alpha scores were computed for each construct (strategic factors, tacticalfactors, operational factors, operational measures, nancial measures andnon-nancial measures) to measure the internal consistency and to indicate howdifferent items can reliably measure the construct. Kline (1998) pointed out that areliability coefcient of around 0.90 can be considered “excellent”, values of around0.80 as “very good,” and values of around 0.70 as “adequate”, depending on thequestions. In this research, all scales have reliability coefcients ranging from verygood to excellent where their values were ranging from 0.84 to 0.97 (see Table I).More importantly, research conducted by Brah et al. (2002) and Brah and Lim (2006)found the internal consistency level TQM CSFs and performance measures to begreater than 0.70. Thus, the scales used in this research could be considered asreliable.

Results of the study

Prole of the respondentsTable II presents the demographic prole of the respondents. The response rate was46.8 per cent, i.e. 113 out of the 297 companies claiming to have implemented or havebeen implementing some of TQM practices. This is a healthy sign as it suggests that asubstantial number of Qatari SMEs realize the importance of TQM as a critical factorin the success and survival of manufacturing rms in the marketplace (Brah et al.,2002).

The responses indicated that a majority of the respondents completing thequestionnaire were production managers, i.e. of the 139 respondents, 113 (81 per cent)were production mangers. This result may stem from the fact that the introduction of TQM can result in, a dramatic increase in operational effectiveness (Slack et al., 2001).

The ndings in Table II indicate that the majority of SMEs implementing TQMprograms are family owned. This result can be interpreted as a major feature in theQatari economic structure with a large family business sector dominating control overthe industry.

The metal, machinery and equipment rms constituted the largest portion of therespondents with 32.4 percent of respondents. This result supports the result of Rahman (2001) study which concluded that manufacturing rms in the engineering,manufacturing (durable), and manufacturing (non-durable) elds are the majorindustries in which TQM programs have been implemented.

Constructs Number of items a

Strategic factors a 6 0.93Tactical factors a 8 0.89Operational factors a 10 0.97Operational measures 6 0.87Financial measures b 4 0.91Non-nancial measures b 5 0.84

Notes: a TQM critical success factors; b Organizational performance; a ¼ Cronbach alpha

Table I.Measures of constructs’

reliability and convergentvalidity


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Constructs of TQM CSFsIn order to examine if the items for a construct share a single underlying factor and toestablish discriminant validity of the constructs under investigation, an exploratoryfactor analysis (EFA) using varimax rotation was performed. Hair et al. (1995)indicated that factor loading with coefcients greater than 0.50 are very signicant.Accordingly, this research used 0.50 as the cutoff score for factor loadings.

In order to determine the number of factors needed to represent the data, the 26items (variables) measuring the TQM CSFs in the research model were subjected toprincipal component factor analysis. Table III indicates that three factors out of 26critical success variables were extracted with an eigenvalue greater than 1 for each,and explaining 75.71 percent of the total variance. Based on the items loading on eachfactor, these factors were labelled as “strategic factors” (factor 1), “tactical factors”(factor 2) and “operational factors” (factor 3). None of the items (variables) weredropped in the analysis because all factor loadings exceeded 0.50 on its own factors, i.e.all items loaded onto the expected factors as they were originally designed. Thisanalysis shows that the average variances extracted (AVE) of the individual constructsare higher than the shared variances between the constructs, thus conrmingdiscriminant validity.

Number of respondents Percentage of respondents

Years of implementing TQM Less than 3 years 87 62.6More than 3 years 52 37.4

Role in the enterpriseProduction manager 113 81.0General manager 17 12.0Marketing manager 7 5.0Other 3 2.0

OwnershipCreated as a new business 23 16.6Franchised 4 2.9Purchased 18 12.9Family business 94 67.6Other 0 0.0

Capital Less than QR 1.5 millions 78 56.1QR 1.5 millions-QR 10 millions 61 43.9More than QR 10 millions 0 0.0

Type of industryFood and beverage 23 16.6Textile, garments and leather 18 12.9Wood and furniture 14 10.1Chemical and petrochemical 32 23.0Mining 6 4.3Metal, machinery and equipment 45 32.4Other 1 0.07

Table II.Demographics of respondents of the survey

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Testing the measurement modelsA conrmatory factor analysis (CFA) using AMOS version 6.0 package was used totest the measurement model. To evaluate the t of CFAs, several goodness-of-tindicators were used to assess the model’s goodness of t including the ratio of x

2 todegrees-of-freedom (df), goodness-of-t index (GFI), adjusted goodness-of-t index(AGFI), non-normalized t index (NNFI), comparative t index (CFI) and standardizedroot mean square residual (SRMSR) (see Table IV). The results indicated that allindividual measurement model indices exceed their respective common acceptancelevels recommended by previous researchers (Jo reskog and So rbom, 1982; Bentler,1990; Browne and Cudeck, 1993; MacCallumet al., 1996; Hu and Bentler, 1995), thus

suggesting that all the constructs were unidimensional and demonstrating that themeasurement model posited a good t with the data collected.

Path model The structural equation modeling was considered as a more comprehensive and exibleapproach to research design and data analysis than any other statistical model (Hafeezet al., 2006). Therefore, this study develops a structural equation modeling (SEM) model,where the combined effects of CSFs of TQM on the primary measures as expressed by

ComponentFactor 1 Factor 2 Factor 3

TQM critical success factors Strategic factors Tactical factors Operational factors

Leadership 0.882Organisational culture 0.923Top management support 0.801Continuous improvement 0.603Benchmarking 0.731Quality goals and policy 0.861Team building and problem solving 0.835Employee empowerment 0.741Employee involvement 0.598Employee training 0.901Use of information technology 0.743Supplier quality 0.710Supplier relationships 0.911

Assessment of performance of suppliers 0.730Product and service design 0.914Enterprise performance metrics for TQM 0.667Process control 0.823Customer orientation 0.634Management of customer relationships 0.612Resources value addition process 0.881Realistic TQM implementation schedule 0.752Customer and market knowledge 0.651Resources conservation and utilization 0.683Inspection and checking work 0.923Eigenvalues 3.652 2.973 2.483Percent of variance explained 28.32 25.16 22.23Cumulative percent 28.32 53.48 75.71

Table III.Results of factor analysis

for CSFs


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M e a s u r e m e n t m o d e l

F i t i n d i c e s

S u g g e s t e d

v a l u e

S F *

T F *

O F *

O P *

F M *

N o n - F

M *

S t r u c t u r a l m o d e l

x 2 / d f

, 3 . 0 0

1 . 4 6

1 . 0 9

0 . 6 8

0 . 4 1

0 1 . 0

0 . 0 7

1 . 1 5

[ P_ v

a l u e

]

[ 0 . 1 9 ]

[ 0 . 1 8 ]

[ 0 . 3 4 ]

[ 0 . 5 9 ]

[ 0 . 8 8 ]

[ 0 . 6 7 ]

[ 0 . 3 4 ]

G o o d n e s s - o f - t i n d e x ( G F I )

. 0 . 9 0

1 . 0 0

1 . 0 0

1 . 0 0

1 . 0 0

1 . 0 0

1 . 0 0

0 . 9 3

A d j u s t e d g o o d n e s s - o f - t

i n d e x ( A G F I )

. 0 . 8 0

0 . 9 4

0 . 9 6

0 . 9 5

0 . 9 8

0 . 9 9

0 . 9 8

0 . 8 9

N o n - n o r m a l i z e d

t i n d e x ( N N F I )

. 0 . 9 0

1 . 0 0

1 . 0 0

1 . 0 0

1 . 0 0

1 . 0 0

1 . 0 0

0 . 9 3

C o m p a r a t i v e

t i n d e x ( C F I )

. 0 . 9 0

1 . 0 0

1 . 0 0

1 . 0 0

1 . 0 0

1 . 0 0

1 . 0 0

1 . 0 0

S t a n d a r d i z e d r o o t m e a n s q u a r e r e s i d u a l

( S R M S R )

, 0 . 1 0

0 . 0 0 8 3

0 . 0 0 4 1

0 . 0 0 6 6

0 . 0 0 5 3

0 . 0 0 3 7

0 . 0 0 1 7

0 . 0 5 2 1

N o t e s :

* S F

¼ S t r a t e g i c

f a c t o r s ; T F

¼ T a c t i c a l

f a c t o r s ; O F

¼ O p e r a t i o n a l

f a c t o r s ; O P

¼ O p e r a t

i o n a l p e r f o r m a n c e ;

F M

¼ F i n a n c i a l p e r f o r m a n c e ;

N o n - F

M ¼

N o n - n a n c i a l p e r f o r m a n c e

Table IV.Goodness of t indices forindividual measurementand structural models

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the operational performance, as well as the effects of these measures on the secondarymeasures as expressed by the organizational measures, are tested using survey data asshown in Figure 2. A similar set of indices was used to examine the structural model (seeTable IV). The model’s key statistics are good since the x

2=df ¼ 1:15, GFI ¼ 0:93,AGFI ¼ 0:89, NNFI ¼ 0:93, CFI ¼ 1:00, and SRMR ¼ 0:0521. We can thus safelyconclude that the model is accepted to t the data and we can continue to analyze theoutcome of the hypothesized effects.

Hypotheses test resultsOne of the purposes of this study is to test the hypothesized causal relationshipsamong the constructs of the model, using the structural equation-modeling package of AMOS. The model parameters were estimated using the maximum likelihoodestimates (MLE) method. The average of item scores for each factor in TQM constructwas used as measures in the path model as in Demirbag et al. (2006); and Sila (2007).

Carroll and Ruppert (1998); Chatterjee and Price (1991); and Hutcheson (1997)indicated that using the standard regression techniques such as the MLE techniquerequire us to test the normality for all the constructs. Therefore, for all the constructs,tests of normality specically Skewness, and Cook’s distance were computed. Theyindicated no departure from normality. Thus, we proceeded in using the MLEtechnique to estimate the model. Figure 2 presents the estimated standardizedparameters for the causal paths and their level of signicance. It also illustrates thestrength of the relationships among the constructs. Following Cohen’s (1988)recommendations, standardized path coefcient with absolute values of less than 0.10may indicate “small” effect; values of around 0.30 a “medium” effect; and “large” effectsmay be suggested by coefcients with absolute value of 0.50 or more. As aconsequence, the results of the squared multiple correlations posit that the t of themodel to the data is strong (0.55, 0.58, and 0.51 respectively).

Figure 2.Results of path analysis


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Moreover, Table V summarizes the measurement models for TQM practices and showsthe hypothesized relationships, the standardized regression weight for each variable,the results of hypotheses testing and the square multiple correlations for eachconstruct. Once again, we computed the chi-square statistic of the model (for doubleaccuracy). It was very small ( x 2 ¼ 11:731) and insignicant ( p ¼ 0:096), thusdemonstrating that the measurement model posited a good t with the data collected.

The ndings in Table V support our conceptual model. The results place support toall the hypotheses.

Hypotheses 1, 4 and 5 . The relationship between strategic factors and operationalperformance, nancial performance and non-nancial performance.

Inspection of these coefcients indicates that, as expected, strategic factors have astrong signicant positive effect on operational performance, nancial performanceand non-nancial performance, thus, conrming H1 , H4 and H5 . ( H1: b ¼ 0:68, p , 0.01; H4: b ¼ 0:56, p , 0.01; H5: b ¼ 0:61, p , 0.01;). This result is not surprisingconsidering that strategic factors such as leadership, organizational culture, topmanagement support, continuous improvement and quality goals and policy have amajor impact on what the organization does and how it does it (Stevenson, 2007).Therefore, without those factors it is hard for TQM to be implemented effectively andsuccessfully. These positive effects support previous studies that investigated therelationship (see Demirbag et al., 2006; Sila, 2007).

Hypotheses 2, 6 and 7 . The relationship between tactical factors and operationalperformance, nancial performance and non-nancial performance.

The ndings indicated that there is a strong signicant positive effect of the tacticalfactors on the operational performance ( H2 : b ¼ 0:73, p , 0.01), but there is a weakeffect of the tactical factors on the nancial performance and non-nancialperformance of the SMEs ( H6 : b ¼ 0:18, p , 0.05 ; and H7 : b ¼ 0:17, p , 0.05).

This is again expected, as employee empowerment, employee training, employeeinvolvement, team building, supplier quality and supplier relationships are therequired pillars to be strongly built in the organizations’ operations structure tomaximize the effects of TQM on the operational performance. This is a good signreecting that SMEs in Qatar are aware of how to specify the methods and actionsnecessary to achieve SME’ objectives i.e. operational objectives and organizationalobjectives of TQM implementation. These ndings are consistent with previousstudies that investigated the relationship (see Tata et al., 2000; Ahmad and Schroeder,2002; Huang and Lin, 2002; Sila, 2007).

Hypotheses 3, 8 and 9 . The relationship between operational factors and operationalperformance, nancial performance and non-nancial performance.

The standardized regression weight for the direct relationships between operationalfactors and operational and nancial performances were found to be positive andsignicant ( H3: b ¼ 0:81, p , 0.01; H8 : b ¼ 0:89, p , 0.01) indicating a strong supportfor H3 and H8 that operational factors had a positive and strong direct effects onoperational performance and also on nancial performance measures as shown in Table V.

In line with the above mentioned result, the standardized regression weights for therelationship between operational factors and non-nancial performance were found tobe positive and signicant ( H9: b ¼ 0:15, p , 0.05), thus conrming H9 .

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P r e d i c t o r v a r i a b l e s

C r i t e r i o n v a r i a b l e s

H y p o t h e s i z e d

r e l a t i o n s h i p

S t a n d a r d i z e d

c o e f c i e n t

H y p o t h e s i s

r e s u l t

R 2

S u g g e s t e d

O b t a i n e d

S t r a t e g i c f a c t o r s

O p e r a t i o n a l p e r f o r m a n c e

H 1

0 . 6 8 * *

S u p p o r t e d

0 . 5 5

T a c t i c a l f a c t o r s


H 2

0 . 7 3 * *

S u p p o r t e d

O p e r a t i o n a l

f a c t o r s


H 3

0 . 8 1 * *

S u p p o r t e d


F i n a n c i a l p e r f o r m a n c e

H 4

0 . 5 6 * *

S u p p o r t e d

0 . 5 8



H 6

0 . 1 8 *

S u p p o r t e d


f a c t o r s


H 8

0 . 8 9 * *

S u p p o r t e d



H 1 0

0 . 6 7 * *

S u p p o r t e d


N o n - n a n c i a l

p e r f o r m a n c e

H 5

0 . 6 1 * *

S u p p o r t e d

0 . 5 1




H 7

0 . 1 7 *

S u p p o r t e d


f a c t o r s



H 9

0 . 1 5 *

S u p p o r t e d




H 1 1

0 . 1 9 *

S u p p o r t e d

S t a t i s t i c

C h i - s q u a r e s i g n i c a n c e

$ 0 . 0 5

0 . 0 7 2

C h i - s q u a r e / d e g r e e o f

f r e e d o m

# 5 . 0 0

3 . 6 4 5

N o t e s :

* p ,

0 . 0 5 ; * * p

,

0 . 0 1

Table V.Standardized regression

weights


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To a large extent this result is similar to Handeld et al. (1998); Anderson and Sohal(1999); Demirbaget al. (2006); and Sila (2007) where they found that there is a signicantassociation between TQM practices and operational and organizational performances.

Hypotheses 10 and 11 . The relationship between operational performance andnancial performance and non-nancial performance.

Operational performance has a strong effect on nancial performance ( H10:b ¼ 0:67, p , 0.01) while there is a weak effect of the operational performance onnon-nancial performance ( H11 : b ¼ 0:19, p , 0.05). However, H10 and H11 areconrmed. Thus, this nding conrmed a previous study that investigated therelationship (see Brah et al., 2002; Brah and Lim, 2006).

This nding shows the nature of the relat ionship between TQMeffectiveness-operational performance- and the success of TQM – organizationalperformance. In other words, operational performance measures should be broughtinto the proactive measurement loop. They should be the starting point of themeasurement cycle, particularly if TQM managers are really interested in reaping thefull benets of TQM implementation.

Conclusion, theoretical and managerial implicationsThe purpose of the current paper is to identify the critical success factors of TQMimplementation and to evaluate their impact on the primary measures as expressed bythe operational performance and the secondary measures as expressed by theorganizational performance in SMEs in the Qatari industrial sector. But, the novelty of it lies in investigating the effects of the operational performance on the organizationalperformance i.e. nancial and non-nancial performances of SMEs.

Unlike the previous studies, the current study presents a roadmap for the successfulimplementation of TQM in SMEs. A roadmap proposed by the current study has beentaken from a model proposed in the study. The model contained 24 CSFs which areexpected to enhance the practices of TQM implementation in SMEs. The model dividesthose factors into three levels, namely strategic, tactical, and operational factors.

However, our ndings are consistent with the ndings of previous studies where theCSFs of TQM implementation in SMEs in Qatar are similar to their peers in developedcountries including USA, Japan and the Far East.

Our model implicitly acknowledges the potency of strategic factors as crucialfactors in the successful implementation of TQM in SMEs in Qatar. Overall, it can beconcluded that there is a causality between strategic factors of TQM practices andoperational and organizational performances ( H1, H4 and H5 are signicant). Hence, itcan be said that CSFs and operational and organizational performances are largelyrelated and feed-off from each other.

Interestingly, we found that tactical factors ( H2 ) have a strong impact onoperational performance. Moreover, the higher the degree of employees empowerment,employees training, quality suppliers, employees involvement displayed by the SMEs,the greater their inuences on operational performance and consequently, the higherthe likelihood of the success of TQM implementation. Thus, this explains why tacticalfactors ( H6 and H7 ) and operational performance ( H10 and H11 ) have an effect onnancial and non-nancial performances, respectively.

The ndings of this study also support prior research that operational factors have astrong impact on performance. All operational factors have effects on operational

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performance ( H3 ), nancial performance ( H8 ), and non-nancial performance ( H9 ). Thisindicates that operational factors are not only concerned about the effectiveness of TQMas expressed by operational performance but also are drivers of the success of TQM asexpressed by organizational performance, i.e. nancial and non-nancial performances.

More importantly, this research contributes to the body of knowledge by proposingand testing a conceptual model that considers operational performance as anantecedent to organizational performance. Thus, we can now conrm that operationalperformance is an important factor for both nancial and non-nancial performance i.e.organizational performance.

From the managerial perspective, this study offers a number of managerialimplications for SMEs managers and policy makers. First, the instrument developedand used in this research will be very useful to policy makers in SMEs as a tool forevaluating the effectiveness of their current TQM practices.

Second, the SMEs managers should be aware of the intermediating impact of operational performance that TQM-related nancial and non-nancial performancecould only be enhanced by improving operational performance in the rst place.

Third, in order to get the full potential of TQM it is necessary train all people at alllevels in order to create TQM awareness, interest, desire and action. Thus, topmanagement attention might be fruitfully focused on the development of appropriatetraining programs on TQM implementation.

Fourth, SMEs managers should consider suppliers as business partners. They haveto be involved in product development, process improvement and making the qualitypolicy. This may lead to better quality and then better customer satisfaction.

Fifth, SMEs leaders should be aware that the imminent competitive pressuresaffecting the domestic market can be appeased through improving both operationalperformance and organizational performance and this depends on the successfulimplementation of TQM.

Further, the ndings of this study could offer a useful potential orientation of theimportance of the CSFs for TQM implementation and their impact on performance of SMEs to both researchers and decision makers who are concerned with the issue underinvestigation.

Finally, the ndings presented in this paper support the argument that SMEsmanagers need to realize that the TQM CSFs should be implemented holistically ratherthan on a piecemeal basis to get the full potential of the TQM practices.

Limitations of the study and future researchSince this study is considered as the rst attempt to investigate the state of the art of TQM implementation in SMEs in Qatar, directions for further research are suggested. Adetailed study (i.e. an independent investigation) of the CSFs inuencing the operationalperformance is warranted. This should be exploited in-depth to understand and highlightwhat are the hindrances and stumbling blocks that are disturbing the effectiveness of TQM implementation. Another useful avenue for future research is to carry out acomparative study with SMEs in the service sector to provide good insights on theeffectiveness of TQM implementation. One important limitation of this study is usingperceptual data provided by production managers or quality mangers which may notprovide clear measures of performance. However, this can be overcome using multiplemethods to collect data in future studies. Finally, the model used in this study can be


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tested by conducting cross-country studies. This will help produce a useful benchmark forcomparing how the model behaves in the same SMEs but in different countries.

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Appendix

Figure A1.Questionnaire


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Figure A1.

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About the authorSalaheldin Ismail Salaheldin is the Chair of Department of Management &Marketing at Collegeof Business and Economics at the Qatar University. He has an MSc degree in Commerce from theCollege of Commerce and Business Administration at Helwan University, Cairo, Egypt. DrSalaheldin earned a PhD in Operations Management from the Glasgow Business School atGlasgow University, UK. Prior to that, he served as Lecturer, Assistant Professor and AssociateProfessor of Operations Management in the College of Commerce and Business Administrationat the Helwan University, Cairo. His publications have appeared in highly respected journals, i.e. International Journal of Operations & Production Management , Industrial Management & DataSystems , International Journal of Management & Decision Making , International Journal of Learning & Intellectual Capital , Journal of Manufacturing Technology Management , and TheTQM Journal. Salaheldin Ismail Salaheldin can be contacted at: [email protected] [email protected]

Figure A1.


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