International Journal of Quality & Reliability ManagementThe impact of “soft” and “hard” TQM elements on quality management resultsChristos B. Fotopoulos Evangelos L. Psomas

Article information:To cite this document:Christos B. Fotopoulos Evangelos L. Psomas, (2009),"The impact of “soft” and “hard” TQM elements onquality management results", International Journal of Quality & Reliability Management, Vol. 26 Iss 2 pp.150 - 163Permanent link to this document:http://dx.doi.org/10.1108/02656710910928798

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The impact of “soft” and “hard”TQM elements on quality

management resultsChristos B. Fotopoulos and Evangelos L. Psomas

University of Ioannina, Agrinio, Greece

Abstract

Purpose – The purpose of this paper is to explore the relationships between “soft” and “hard” TQMelements and quality management results.

Design/methodology/approach – Empirical data were drawn from 370 Greek companies using thequestionnaire method. Confirmatory Factor Analysis was used to examine constructs’ reliability andvalidity, while the relationships between them were examined through Structural Equation Modelling.

Findings – The study proved that quality improvement and the consolidation of the company’smarket position are influenced mainly by adopting “soft” TQM elements and secondarily “hard” TQMelements.

Research limitations/implications – The fact that the study was based on quality managers’perceptions and the participation of companies from all sectors creates limitations, but also futureresearch orientations.

Practical implications – To achieve benefits and obtain a competitive advantage, which is of majorimportance for the sustainability of a company, quality design, control and improvement tools are notenough and the adoption of a TQM culture is primarily required.

Originality/value – The study describes in a reliable and valid way a model which consists of “soft”and “hard” TQM elements and quality management results.

Keywords Total quality management, Quality management, Greece

Paper type Research paper

IntroductionSystems for improving and managing quality have rapidly evolved in recent years.During the last decades simple inspection activities have been replaced orsupplemented by quality control and quality assurance standards. The fourth levelof quality management is that of Total Quality Management (van der Wiele et al.,1997). When Deming introduced TQM in the 1950s, the Japanese adopted thisphilosophy while the USA rejected its principles. Thus, the Japanese made a significantprogress in the field of quality (Talha, 2004), resulting in the penetration of USAmarkets by Japanese products (Martinez-Lorente et al., 1998). Therefore, in the early1980s, the USA utilized TQM concepts as tools to compete with Japan (Davig et al.,2003; Sun et al., 2004). European organizations also recognized the need for a keenerfocus on quality and in the 1990s, TQM concepts spread to Europe (Sun et al., 2004).

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

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The research Project is co-funded by the European Union – European Social Fund (ESF)& National Sources, in the framework of the program “HRAKLEITOS” of the “OperationalProgram for Education and Initial Vocational Training” of the Third Community SupportFramework of the Hellenic Ministry of Education.

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Received April 2008Revised September 2008Accepted September 2008

International Journal of Quality &Reliability ManagementVol. 26 No. 2, 2009pp. 150-163q Emerald Group Publishing Limited0265-671XDOI 10.1108/02656710910928798

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However, making the step towards TQM was much more difficult as there waswidespread confusion about the components of TQM and how they could beimplemented. This was because TQM was a rather abstract philosophy and did nothave clear guidelines on its implementation (Sun et al., 2004). Coleman and Douglas(2003) stated that TQM is too abstract with many definitions and a lack of “hard”requirements. According to Zairi (1994), there is nothing wrong with TQM terminologyand as a philosophy it is fine, provided that we understand its workings and itsbenefits, which are long-term. The problem became easier to solve as TQMcomponents were more clearly understood through the development and theworldwide acceptance of quality awards models (Sun et al., 2004). Excellence modelsare helpful in defining TQM in a way in which management can more easilyunderstand. They also help organizations to develop and manage their continuousimprovement activities in a number of ways (van der Wiele et al., 2000).

In almost all TQM definitions a reference is made to its “soft” and “hard” side(Vouzas and Psyhogios, 2007). The “soft” side is associated with management conceptsand principles such as leadership, employee empowerment and culture, while the“hard” side refers to quality improvement tools and techniques (Vouzas and Psyhogios,2007; Thiagaragan et al., 2001). The “soft” TQM elements are long-term issues andtherefore must be emphasized and addressed accordingly in an organization’s TQMimplementation plan. The effective manipulation of the “soft” elements must besupported by the “hard” elements of TQM (Zairi and Thiagarajan, 1997).

Despite the numerous studies in TQM literature, authors such as Idris and Zairi(2006), Singh and Smith (2006), Gotzamani et al. (2006), Karuppusami andGandhinathan (2006), Sila and Ebrahimpour (2005), Prajogo (2005), Vouzas andGotzamani (2005), Sun et al. (2004), Rahman (2004), Coleman and Douglas (2003) andDale (2002), recommend that further efforts should be made aiming at the diachronicevaluation of TQM elements, the results of their adoption and mainly the type andextent of their relationships. As Dale (2002) noted, improvement is a process, which,once started, should never end and the same can be said of the research into TQM.

The purpose of this paper is to examine the impact of “soft” and “hard” TQMelements on quality management results. The model reliability and validity wasexamined through Confirmatory Factor Analysis, while the relationships between“soft” and “hard” TQM elements and quality management results were examinedthrough Structural Equation Modelling.

The rest of the paper is organized as follows: the first part reviews the existingTQM literature. The second part describes the methodology of a research carried out inGreek companies. The third part presents the analysis and the respective results.Finally, the results of research are discussed and final conclusions are presented.

Theoretical backgroundDeming’s 14 points and cycle (plan, do, check, act), Juran’s quality trilogy (planning,control and improvement), Crosby’s absolutes of quality management (conformance torequirements, prevention, zero defects and cost of quality), Garvin’s qualitydimensions, Ishikawa’s cause and effect diagram, Feigenbaum’s three steps toquality (quality leadership, modern quality technology and organizationalcommitment) and Taguchi’s advice to companies to turn to Statistical ProcessControl and Design of Experiments, that is “On-line” and “Off-line” quality control

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respectively, constitute the most important aspects of the TQM framework that qualitygurus have recommended.

There is no unique model for a good TQM programme and TQM is a network ofinterdependent elements, namely critical factors, practices, techniques and tools (Tari,2005). However, TQM without certain elements is likely to yield little in the way of realbenefits (Curry and Kadasah, 2002). Despite the divergence of views on whatconstitutes TQM there are a number of common elements running through the variousdefinitions (Martinez-Lorente et al., 1998). “Soft” TQM elements as they have beendetected in recent studies are the following (Table I): leadership, strategic qualityplanning, employee management and involvement, supplier management, customerfocus, process management, continuous improvement, information and analysis,knowledge and education. A number of quality management tools and techniques were

Articles

“Soft” TQMLeadership Yang (2006), Hoang et al. (2006), Singh and Smith (2006), Gotzamani

et al. (2006), Hafeez et al. (2006), Armstrong-Stassen et al. (2005),Prajogo and McDermott (2005), Sila and Ebrahimpour (2005), Prajogo(2005), Miyagawa and Yoshida (2005), Lagrosen and Lagrosen (2005),Tari (2005)

Strategic quality planning Drew and Healy (2006), Yang (2006), Hoang et al. (2006), Gotzamaniet al. (2006), Prajogo and McDermott (2005), Sila and Ebrahimpour(2005), Prajogo (2005), Miyagawa and Yoshida (2005), Tari (2005),Bou-Llusar et al. (2005)

Employee management andinvolvement

Drew and Healy (2006), Yang (2006), Hoang et al. (2006), Singh andSmith (2006), Gotzamani et al. (2006), Hafeez et al. (2006),Armstrong-Stassen et al. (2005), Prajogo and McDermott (2005), Silaand Ebrahimpour (2005), Prajogo (2005)

Supplier management Drew and Healy (2006), Yang (2006), Singh and Smith (2006),Gotzamani et al. (2006), Sila and Ebrahimpour (2005), Miyagawa andYoshida (2005), Tari (2005)

Customer focus Yang (2006), Hoang et al. (2006), Singh and Smith (2006), Gotzamaniet al. (2006), Drew and Healy (2006), Prajogo and McDermott (2005),Sila and Ebrahimpour (2005), Prajogo (2005), Tari (2005)

Process management Yang (2006), Hoang et al. (2006), Singh and Smith (2006), Gotzamaniet al. (2006), Prajogo and McDermott (2005), Sila and Ebrahimpour(2005), Prajogo (2005), Lagrosen and Lagrosen (2005), Tari (2005)

Continuous improvement Yang (2006), Hafeez et al. (2006), Armstrong-Stassen et al. (2005),Lagrosen and Lagrosen (2005), Tari (2005)

Information and analysis Hoang et al. (2006), Singh and Smith (2006), Gotzamani et al. (2006),Armstrong-Stassen et al. (2005), Prajogo and McDermott (2005), Silaand Ebrahimpour (2005), Prajogo (2005), Lagrosen and Lagrosen(2005), Miyagawa and Yoshida (2005)

Knowledge and education Drew and Healy (2006), Yang (2006), Hoang et al. (2006), Hafeez et al.(2006), Armstrong-Stassen et al. (2005), Miyagawa and Yoshida (2005),Tari (2005)

“Hard” TQMQuality tools and techniques Drew and Healy (2006), Tari (2005), Lagrosen and Lagrosen (2005),

Bayazit (2003), Ahmed and Hassan (2003)

Table I.“Soft” and “hard” TQMelements used in recentstudies

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introduced as a means of increasing awareness of TQM concepts and the importance ofcontinuous and company-wide improvement (Bunney and Dale, 1997). “Hard” TQMelements include quality management tools and techniques such as flow charts,relations diagram, scatter diagram, control charts, Pareto analysis, quality functiondeployment, design of experiments and so on.

A significant number of companies have adopted some form of TQM in theirbusiness and have derived demonstrable benefits (Rahman and Sohal, 2002).Furthermore, there is a trend towards stronger demand for improved measures of theperformance of companies and TQM has a role to play in relation to this (Williams et al.,2004). Exploring the TQM literature the following quality management results arereferred (Table II): customer satisfaction, employee satisfaction, impact on society andinternal and external business results.

Lagrosen and Lagrosen (2005) studied the effects generated by “soft” TQM elements,quality management models and tools. They showed that there is a correlation betweenhow well quality management works and to what extent the company adopts “soft” TQMelements. However, the most important “soft” TQM elements were continuousimprovement, management by facts and participation of everybody. Furthermore, theyfound that the use of quality management models is related to well functioning qualitymanagement and models such as ISO 9000, Swedish Quality Award and European QualityAward were found to be the most important. Finally they showed that there is a correlationbetween the use of quality management tools and well functioning quality management.

Tari (2005) indicated that the weaknesses in ISO 9000 certified firms were humanaspects such as work teams, suggestions schemes, recognition models and the use ofquality techniques and tools. He concluded that companies wishing to go beyond ISO9000 must improve all these aspects in order to improve their competitiveness throughimproved business results.

Ahmed et al. (2005) concluded that the success of any quality management systemdepends greatly on the strong commitment of top management and how customers arevalued. They also mentioned that in order to determine the effectiveness of qualitymanagement systems, quantifying quality improvement is essential. Different tools areavailable for measuring quality improvement such as benchmarking, statisticalprocess control and defect cost analysis. Finally, they mentioned that suchmeasurements constitute only the first step towards the never-ending cycles ofcontinual process improvement and that the objective is to use the results obtained

TQM results Articles

Customer satisfaction Yang (2006), Singh and Smith (2006), Hafeez et al. (2006), Miyagawa andYoshida (2005), Tari (2005), Bou-Llusar et al. (2005), Sila and Ebrahimpour(2005)

Employee satisfaction Yang (2006), Tari (2005), Bou-Llusar et al. (2005), Sila and Ebrahimpour(2005)

Impact on society Singh and Smith (2006), Miyagawa and Yoshida (2005), Tari (2005),Bou-Llusar et al. (2005)

Business results Drew and Healy (2006), Singh and Smith (2006), Hafeez et al. (2006), Sila andEbrahimpour (2005), Miyagawa and Yoshida (2005), Tari (2005),Bou-Llusar et al. (2005)

Table II.TQM results according to

recent studies

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from such measurements to decision making, in order to achieve continualimprovement and therefore satisfy the customers’ ever ending needs and requirements.

Ally and Schloss (2003) shed light on quality management issues regarding themaquiladora industry in Mexico. Their study provided evidence of a decent qualitysystem in the maquiladoras based on TQM and SPC principles, utilizing the teamworkapproach to problem solving, providing training to employees, working with suppliersand striving for quality certifications. In other words, by establishing quality systems,implementing quality principles and techniques and training managers and employeesin quality issues, the maquiladoras are playing a significant role in creating a qualityculture in Mexico’s industry. As these authors noted, this quality culture could beinstrumental in transforming industry into a global power recognized for itsworld-class manufacturing and excellence in quality.

Bayazit (2003) found that the TQM implementation status for the large companiesin Turkey was fairly mature. Top management support, employee involvement andcommitment, customer focus, quality education and training, teamwork and qualitytools and techniques were the main factors that contributed to the success of TQMefforts. The most important achievements after implementing TQM were an increasein customer satisfaction, quality improvement, a decrease in prices, on time delivery,an increase in profitability and market share, an increase in work satisfaction,workforce quality, work harmony and a decrease in defects.

Ahmed and Hassan (2003), argue that quality management cannot be ensuredwithout the application of appropriate tools either management or statistical. Firms withgreater implementation of these quality tools can improve their business results. Thesetools are required in any firm irrespective of its size. Finally, they suggest that firmsshould accept the quality practices as part of their life, in order for them to be benefited.

As Idris and Zairi (2006) noted, until this millennium TQM had survived the test oftime as a corporate philosophy. However, will it sustain as a dominant logic of businesscorporate strategy in the future? As they noted, this question, among academics andpractitioners, remains not fully answered by the past literature. Although there hasbeen empirical evidence that supports TQM as a universal business strategy; theintensity of effective implementation of its success factors brings operationalexcellence, but the changing business orientation poses a challenge to TQM as asustainable strategy for competitiveness.

Based on the previous and having in mind the future research proposals mentionedby authors, it is interesting to examine the simultaneous impact of “soft” and “hard”TQM elements on quality management results. The research hypothesis examinedthrough this study is the following: “soft” and “hard” TQM elements affect the resultsof adopting a quality management system.

MethodologyQuestionnaireA research was carried out in Greek companies through questionnaires. Based on theabove mentioned “soft” and “hard” TQM elements and the results from their adoption, aquestionnaire was designed that was reviewed by quality management academics andprofessionals and tested through a pilot study on 23 ISO 9001:2000 certified companies.The final questionnaire consisted of four parts. The first part contained questions aboutthe companies’ profile and the second part questions about “soft” TQM elements. Thequestions of the third part concerned the results related to customers, employees, society

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and the company itself (internal and external). Finally, the fourth part containedquestions using respective quality management tools and techniques. The answers weregiven on a seven-point Likert scale. Confirmatory Factor Analysis was applied to assessmeasurement model reliability and validity. The relationships between latent constructswere examined through Structural Equation Modeling. The SPSS 15 and AMOS sixstatistical packages were used for data processing.

SampleGiven that the ISO 9001:2000 standard is much more in line with TQM than other qualitystandards, the criterion for selecting the companies that would participate in the studywas their certification to this standard. The only available and formal source informingdata about the ISO 9000 certified Greek companies was ICAP, the largest businessinformation and consulting firm in Greece. According to its database, the ISO 9001:2000certified companies in Greece during the research period were 1720. The questionnairewas sent to all these companies and was addressed to the quality manager.

In total, 370 questionnaires were returned fully completed. Comparing the 370companies that participated in the research with the 1350 companies that did not, interms of the number of employees, head office location and their sector (manufacturing,commercial, service industry), no statistically significant differences were detected(Mann Whittney Test). From this it is concluded that the responded companies werenot different from the remaining ISO 9001:2000 certified companies (non-responded)with respect to their profile.

Testing the assumptions of multivariate analysisAccording to Hair et al. (2005), before multivariate data analysis, we should checkthe assumptions regarding sample size, the scale of variables, their multicollinearity,their multivariate normal distribution and outliers. As far as sample size isconcerned, it exceeds 300 cases and is regarded satisfactory for analyses throughStructural Equation Modeling (SEM) according to Kline (2005) and Hair et al. (2005).According to Garson (2007) and Byrne (2001), we can use Likert scale data andapply the Maximum Likelihood Estimation method in SEM, given that we have alarge sample, a seven-point Likert scale and the skewness and kurtosis of variablesis within acceptable limits, a fact that suggests distribution symmetry. Themulticollinearity among independent variables was excluded after controls wereheld, according to Kline (2005) and Hair et al. (2005), on their correlations (r , 0:85)and the multiple regression analysis of every independent variable with all theothers (R 2 , 0:9, Tolerance ¼ 1 2 R 2 . 0:1, Variance Inflation Factor¼ 1=½1 2 R 2� , 10, Condition Index , 30). According to Hair et al. (2005), theoutliers were identified from a univariate and multivariate perspective (MahalanobisD2/independent variables , 3) and were excluded from the analysis. As far asmultivariate normal distribution is concerned and according to Hair et al. (2005),there are no serious indications that it is violated (histograms, p-p and q-q plots,skewness and kurtosis , ^1, standardized residuals , ^2:5). Therefore, it can besuggested that these basic assumptions are not violated.

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ResultsCompanies profileThe majority of the companies that participated in the research were small-mediumenterprises (, 250 employees), two or three of them were manufacturing having yearsof experience in quality assurance, since most of them were certified to the standards ofthe ISO 9000:1994 series. The selection of the certification body and the externalquality consultant, on whose support 75 per cent of the companies relied to becomecertified, was made using their reputation in the market as the primary criterion andnot so much on financial grounds. Finally, a rate of 62 per cent of the companiesexpressed the wish to implement a quality management system in accordance withTQM principles in the future.

Confirmatory factor analysis (the measurement model)The measured (observed) values for the questions, obtained from the respondents,constitute the measured variables of the model, which are used as the indicators of therespective latent constructs (factors). However, the Confirmatory Factor Analysisrevealed some measured variables regarding quality tools and quality managementresults with a low squared multiple correlation (, 0:5) that were removed from themodel. Thus, the final model consists of 18 measured variables that constitute two latentconstructs (“soft” TQM – “hard” TQM) and 12 measured variables that constitute threelatent constructs (TQM results: customer satisfaction, quality improvement-internalbusiness result and market benefits-external business result), (Table III). The goodnessof model fit to the observed data (318 cases) is shown in Table IV.

According to Table III and Hair et al. (2005), Standardized Regression Weights areabove 0.7 (or at least . 0.5) and the respective Squared Multiple Correlations are above0.5. This means that factor loadings are satisfactorily large and that a high amount ofmeasured variable’s variance is explained by a latent construct.

The reliability of the above latent constructs was checked according to Hair et al.(2005), by calculating the Cronbach’s alpha coefficients that were higher than 0.7(Table V). Construct validity was confirmed according to Hair et al. (2005), throughConfirmatory Factor Analysis by evaluating convergent validity (factor loadings .

Goodness of fit measures CFA model Structural model

Chi-square 503.958 517.622Degrees of freedom 381 384Chi-square/degrees of freedom (x2=df) 1.323 1.348Probability level 0.00 * 0.00 *

Root Mean Square of Approximation (RMSEA) 0.032 0.033Root Mean Square Residual (RMR) 0.069 0.073Goodness of Fit Index (GFI) 0.906 0.904Normed Fit Index (NFI) 0.932 0.931Relative Fit Index (RFI) 0.923 0.921Incremental Fit Index (IFI) 0.983 0.981Tucker-Lewis coefficient (TLI) 0.980 0.978Comparative Fit Index (CFI) 0.982 0.981

Notes: *According to Hair et al. (2005) when n . 250, observed variables m $ 30, RMR , 0.08,RMSEA , 0.07, CFI . 0.90

Table III.Goodness of fit measures– measurement modeland structural model

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Latent constructs Observed variablesStandardized

regression weightsSquared multiple

correlations

“Soft” TQMelements (X1)

Top management commitment 0.781 0.610Strategic quality planning 0.810 0.656Employee involvement 0.671 0.451Supplier management 0.559 0.313Customer focus 0.674 0.454Process orientation 0.740 0.548Continuous improvement 0.793 0.629Facts-based decision making 0.746 0.557Human resource development 0.747 0.557

“Hard” TQMelements (X2)

Cause and effect diagram 0.730 0.532Scatter diagram 0.791 0.626Affinity diagram 0.859 0.738Relations diagram 0.852 0.726Force-field analysis 0.903 0.816Run chart 0.841 0.707Control charts 0.794 0.631Quality function deployment 0.812 0.660Failure mode and effect analysis 0.743 0.552

Qualityimprovement (X3)

End product defects are reduced 0.862 0.744Obsolete products are reduced 0.898 0.806Non-conformances are reduced 0.877 0.769Reprocessing is reduced 0.852 0.726Warranty compensations arereduced

0.699 0.489

Market benefits(X4)

Profit has increased 0.698 0.487Competitive position has improved 0.870 0.756Performance has improved 0.895 0.801Sales have increased 0.789 0.623

Customersatisfaction (X5)

The number of customercomplaints has decreased

0.808 0.653

Customer satisfaction hasdiachronically improved

0.896 0.803

Customers are retained and areloyal to the company

0.593 0.352Table IV.

Confirmatory factoranalysis

Latent constructsCronbach’s

alphaAverage variance

extracted *

Constructreliability * * (Corr)2 * * *

X1 0.902 0.531 0.910 0.389X2 0.947 0.655 0.947 0.108X3 0.923 0.707 0.923 0.486X4 0.895 0.667 0.888 0.403X5 0.792 0.603 0.816 0.486

Notes: *AVE ¼ Sli 2=n (i ¼ 1. . .n; l ¼ standardized factor loadings, i ¼ observed variables);* *CR ¼ ðSliÞ2=½ðSliÞ2 þ ðSdiÞ�, (li ¼ standardized factor loading, i ¼ observed variables, di ¼ errorvariance); * * *: the highest squared correlation between factor of interest and remaining factors

Table V.Model reliability and

validity

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0.7-0.5, Average Variance Extracted . 0.5, Construct Reliability . 0.7), discriminantvalidity (Average Variance Extracted . Corr2), (Table V), face-content validity(literature review, questionnaire review by academics and quality professionals) andnomological validity (significant correlations among latent constructs and between themand an independent variable, which they predict satisfactorily, R-square ¼ 0.644).Cross-validation was used to make a second confirmation of the measurement model.So we randomly split the initial data sample (n ¼ 318) into two groups (n1 ¼ 159 andn2 ¼ 159) and examined the goodness of model fit to the two groups. According to Hairet al. (2005), we applied a series of progressively more rigorous tests across samples(Table VI), which confirmed the measurement’s model validity.

The structural modelHaving examined the measurement model reliability and validity, we determined therelationships between the latent constructs, as it is presented in Figure 1 and then we

Figure 1.The structural model

Model description X2 df p RMSEA CFI Dx2 Ddf p

Group 1 480.7 381 0 0.041 0.97 *

Group 2 560.2 381 0 0.055 0.95 *

Factor structure equivalence 1040.9 762 0 0.034 0.96 *

Factor loading equivalence 1076.3 787 0 0.034 0.96 35.3 25 . 0.001 * *

Interfactor covariance equivalence 1081.5 797 0 0.034 0.96 5.1 10 . 0.001 * *

Error variance equivalence 1129.7 827 0 0.034 0.95 48.2 30 . 0.001 * *

Notes: *Good fit; * *InsignificantTable VI.Cross-validation

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examined the goodness of model fit to the observed data. According to Hair et al.(2005), we initially compared the structural model with the CFA model in terms ofStandardized Regression Weights (nontrivial, differences , 0.05, non-statisticallysignificant – Wilcoxon Singed Ranks Test). In Table IV it is observed that thestructural model provides a good overall fit, while as far as goodness of fit indices areconcerned, we conclude that there are no significant differences with the respectiveindices of the CFA model. Figure 1 presents the statistically significant relationshipsand the variance explained for the endogenous constructs.

From this figure it is obvious that “soft” and “hard” TQM elements have both adirect and indirect impact on the quality management results. More specifically,“quality improvement” is influenced mainly by “soft” TQM elements and secondarilyby “hard” TQM elements. Customer satisfaction is influenced mainly by “qualityimprovement” and secondarily by “soft” TQM elements. “Market benefits” areinfluenced mainly by “customer satisfaction” and secondarily by “hard” TQMelements. From the above mentioned it is concluded that quality management resultsare significantly influenced mainly by “soft” TQM elements and secondarily by “hard”TQM elements. In other words, the research hypothesis, that is “soft” and “hard” TQMelements affect the results of adopting a quality management system, is not rejected.

DiscussionTaking the profiles of the companies participating in the study into account, we canconclude that they are characterized by a desire to pursue quality, given that most of themstarted their journey towards quality before the revision of the ISO 9000 standard in theyear 2000. Thus, by implementing the ISO 9000:1994 and mostly the revised ISO 9001:2000standards, the foundations are laid for the future implementation of other qualitystandards, such as Health and Safety (OHSAS 18001) and Environmental (ISO 14001).Furthermore, if we take into account the willingness of most companies to incorporate theTQM principles into their quality system, we cannot but talk about a hopeful future forquality management. On the contrary, in the study of Coleman and Douglas (2003), themajority of the organizations viewed ISO 9000 as the end of their quality journey.

However, we should stress that the quality management attempts made bycompanies individually are not sufficient. To satisfy the end customer – consumer,quality should be ensured outside companies as well, that is throughout thedistribution network. Therefore, after quality is firmly founded inside companies, weshould turn our attention to the way quality is managed amongcompanies-wholesalers-retailers. The authors believe that TQM can guaranteequality within the companies, but also throughout the supply chain.

Results showed that both aspects of TQM – the “soft” and the “hard” side – play asignificant role in gaining benefits from the quality management system, both insideand outside the business environment. However, it becomes evident that “soft” TQMelements play a major role, while the role of quality management tools is inferior, yetnot insignificant. The consolidation of the company’s market position seemed to besignificantly determined by the degree of customer satisfaction, while it is also directlyaffected by quality tools to a lesser degree. But customer satisfaction requires thecompany’s quality improvement and the adoption of TQM principles, such as customerfocus and the measurement of customer satisfaction. Based on the results of this study,the adoption of “soft” and “hard” TQM elements can lay the foundations for improvingthe way a company operates and hence its quality.

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The result of the present study regarding the more significant role of “soft” TQMelements compared to “hard” TQM elements, is consistent with that of Lagrosen andLagrosen (2005), who indicated that the functioning of a company’s quality managementsystem depends, to a significant degree, on the use of quality management models such asISO, EFQM, MBNQA and the level of adoption of three quality management principles(continuous improvement, management by facts and participation of everybody).Moreover, in the study conducted by Ahmed et al. (2005), a small rate of companiesconsidered quality tools as the most important element in a TQM system, contrary to topmanagement commitment and customer orientation. Ahmed and Hassan (2003), giventhat their study revealed a limited use of quality tools and mainly the Statistical ProcessControl, recommend that companies widely accept quality practices that are incorporatedinto everyday practice and realize the advantages coming from quality toolsimplementation so that they can achieve business performance improvement.

Tari (2005) indicated that, in order to progress towards TQM, ISO 9000 certifiedfirms must improve their people orientation and use quality improvement tools andtechniques to a higher extent, even if, in contrast to our study, the factors related to thehard part were more implemented.

The significant effect of implementing a quality system according to “soft” TQMelements on customer satisfaction and the company’s position in the market, as itbecame evident in the present study, is consistent with the results coming from thestudy of Agus et al. (2000). They found that implementing “soft” TQM elementscontributes to improved customer satisfaction, which in turn results in financialperformance improvement. Prajogo and Sohal (2003) found that the effects of the TQMsystem on product and process quality and innovation are important.

The significant effect of “soft” TQM elements on quality improvement, which wasproved in the present research, is consistent with the result of Prajogo’s study (2005),which showed that TQM principles adoption by services and manufacturing companies,significantly promotes product quality improvement in terms of reliability, performance,duration and conformance to requirements. Finally, the meta-analysis results ofJitpaiboon and Rao (2007) revealed that “soft” TQM elements are significantly associatedwith the results in the internal and external business environment.

ConclusionsObtaining a competitive advantage that ensures the company’s sustainability anddominance in the market, by means of satisfying its customers and substantiallyimproving its quality, is significantly affected by “soft” TQM elements and theimplementation of quality management tools and techniques. However, tools are onlythe “vehicle” to quality improvement. Quality tools usage alone can not lead a companyto continuous process improvement, customer satisfaction and consolidation of itsmarket position, without the proper guidance by top management and employee andsupplier support.

However, in the present study there are limitations. Data constitute subjectivebusiness evidence that came from quality managers, a fact that entails the risk ofreceiving biased answers. It is also a research conducted on companies from all sectorsand the proposed model has not been checked for its validity in separate sectors, due tothe limited number of companies per sector. However, this can be the subject of a futureresearch. We would also suggest conducting a future research on companies with thepurpose of collecting primary data on TQM that will be subjective and will be based on

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the opinions of more than one person per company including employees, as well asobjective data that would be based on the company’s financial indicators.

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About the authorsChristos Fotopoulos is full time Professor of Marketing Management and Head of theDepartment of Business Administration of Food and Agricultural Enterprises of the Universityof Ioannina. His scientific contribution includes the completion of 27 research projects, in the 13of which, he was the project leader. His scientific work includes over 35 papers more than 22 ofwhich published in international peer reviewed journals, over 13 books – monographs, over 30papers published in peer reviewed conferences and a lot of research project reports published inGreek and in English. His current research interests include, but are not limited in, Management,Agribusiness, Food Marketing (especially organic products), Total Quality Management, SupplyChain Management and finally Promotion and Marketing of PDO products and aspects ofcontemporary marketing of agricultural businesses. Christos Fotopoulos is the correspondingauthor and can be contacted at: chfotopu@cc.uoi.gr

Dr Evangelos Psomas is a Research Assistant in the Department of Business Administrationof Food and Agricultural Enterprises of the University of Ioannina. He has dealt widely withissues of Management and Marketing and has worked as a research and teaching assistant inUniversity of Ioannina and Technological Educational Institute of Epirus. His current researchinterests include: Management, Total Quality Management, Quality Assurance, HumanResource Management, Supply Chain Management, Agribusiness and Food Marketing.

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39. Ahmad M. Herzallah, Leopoldo Gutiérrez-Gutiérrez, Juan Francisco Munoz Rosas. 2014. Total qualitymanagement practices, competitive strategies and financial performance: the case of the Palestinianindustrial SMEs. Total Quality Management & Business Excellence 25:5-6, 635-649. [CrossRef]

40. José Álvarez García, Mercedes Vila Alonso, José Antonio Fraiz Brea, María de la Cruz del Río Rama.2014. Relación entre herramientas y factores críticos de la calidad. Revista Europea de Dirección y Economíade la Empresa 23:2, 82-97. [CrossRef]

41. Sanjay Bahl Indian Institute of Foreign Trade, New Delhi, India O.P. Wali Indian Institute of ForeignTrade, New Delhi, India . 2014. Perceived significance of information security governance to predict theinformation security service quality in software service industry. Information Management & ComputerSecurity 22:1, 2-23. [Abstract] [Full Text] [PDF]

42. Mehdi Narimani Human Resources Research Center, Institute for International Energy Studies, Tehran,Iran and Faculty of Management, University of Tehran, Tehran, Iran Elham Tabaeian Faculty ofManagement and Accounting, Allameh Tabatabai University, Tehran, Iran Maral Khanjani Faculty ofManagement, University of Tehran, Tehran, Iran Farzaneh Soltani Faculty of Management, Universityof Isfahan, Isfahan, Iran . 2013. The impact of organizational citizenship behavior on enterprise resourceplanning success. International Journal of Quality & Reliability Management 31:1, 53-65. [Abstract] [FullText] [PDF]

43. M. Natarajan Department of Mechanical Engineering, Adithya Institute of Technology, Coimbatore,India V. Senthil Department of Mechanical Engineering, Adithya Institute of Technology, Coimbatore,India S.R. Devadasan Department of Production Engineering, PSG College of Technology, Coimbatore,India N. Vijay Mohan Research and Development Department, Lakshmi Machine Works Limited,Coimbatore, India N.M. Sivaram Department of Production Engineering, PSG College of Technology,Coimbatore, India . 2013. Quality and reliability in new product development. Journal of ManufacturingTechnology Management 24:8, 1143-1162. [Abstract] [Full Text] [PDF]

44. Mehran Ebrahimi, Mehran Sadeghi. 2013. Quality management and performance: An annotated review.International Journal of Production Research 51:18, 5625-5643. [CrossRef]

45. Lai-Ying Leong, Keng-Boon Ooi, Alain Yee-Loong Chong, Binshan Lin. 2013. Modeling the stimulatorsof the behavioral intention to use mobile entertainment: Does gender really matter?. Computers in HumanBehavior 29:5, 2109-2121. [CrossRef]

46. Manal YunisCollege of Business Administrations, University of Texas‐Pan American, Edinburg, Texas,USA Joo JungCollege of Business Administrations, University of Texas‐Pan American, Edinburg, Texas,USA Shouming ChenSchool of Economics and Management, Tongji University, Shanghai, China. 2013.

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TQM, strategy, and performance: a firm‐level analysis. International Journal of Quality & ReliabilityManagement 30:6, 690-714. [Abstract] [Full Text] [PDF]

47. Juan Antonio Gimenez-Espin, Daniel Jiménez-Jiménez, Micaela Martínez-Costa. 2013. Organizationalculture for total quality management. Total Quality Management & Business Excellence 24:5-6, 678-692.[CrossRef]

48. Faisal Talib, Zillur Rahman, Asif Akhtar. 2013. An instrument for measuring the key practices of totalquality management in ICT industry: an empirical study in India. Service Business 7:2, 275-306. [CrossRef]

49. Professor T.C. Melewar and Dr Sharifah AlwiS.J. GoraneDepartment of Mechanical Engineering,Sardar Vallabhbhai National Institute of Technology, Surat, India Ravi KantDepartment of MechanicalEngineering, Sardar Vallabhbhai National Institute of Technology, Surat, India. 2013. Modelling theSCM enablers: an integrated ISM‐fuzzy MICMAC approach. Asia Pacific Journal of Marketing and Logistics25:2, 263-286. [Abstract] [Full Text] [PDF]

50. Keng-Boon Ooi, Voon-Hsien Lee, Alain Yee-Loong Chong, Binshan Lin. 2013. Does TQM improveemployees’ quality of work life? Empirical evidence from Malaysia's manufacturing firms. ProductionPlanning & Control 24:1, 72-89. [CrossRef]

51. Voon-Hsien Lee, Keng-Boon Ooi, Amrik S. Sohal, Alain Yee-Loong Chong. 2012. Structuralrelationship between TQM practices and learning organisation in Malaysia's manufacturing industry.Production Planning & Control 23:10-11, 885-902. [CrossRef]

52. Saman YapaDepartment of Decision Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka.2012. Total quality management in Sri Lankan service organizations. The TQM Journal 24:6, 505-517.[Abstract] [Full Text] [PDF]

53. Salina DaudDo knowledge management processes mediate the relationship between TQM factors andorganizational business results? 1-6. [CrossRef]

54. Siew‐Yong LamUniversiti Tunku Abdul Rahman, Kampar, Malaysia Voon‐Hsien LeeUniversiti TunkuAbdul Rahman, Kampar, Malaysia Keng‐Boon OoiUniversiti Tunku Abdul Rahman, Kampar, MalaysiaKongkiti PhusavatKasetsart University, Bangkok, Thailand. 2012. A structural equation model of TQM,market orientation and service quality. Managing Service Quality: An International Journal 22:3, 281-309.[Abstract] [Full Text] [PDF]

55. Ana Belén Escrig-Tena, Juan Carlos Bou-Llusar, Vicente Roca-Puig, Inmaculada Beltrán-Martín. 2012.Does quality management drive labour flexibility?. Total Quality Management & Business Excellence 23:2,159-176. [CrossRef]

56. Paul ChapmanSaïd Business School, University of Oxford, Oxford, UK Michael BernonCranfield Schoolof Management, Cranfield University, Cranfield, UK Paul HaggettOTIF Consultants, Brampton, UK.2011. Applying selected quality management techniques to diagnose delivery time variability. InternationalJournal of Quality & Reliability Management 28:9, 1019-1040. [Abstract] [Full Text] [PDF]

57. Peter Nielsen and Palle RasmussenAalborg University, DenmarkChee‐Yang FongFaculty of Business andFinance, Universiti Tunku Abdul Rahman, Malaysia Keng‐Boon OoiFaculty of Business and Finance,Universiti Tunku Abdul Rahman, Malaysia Boon‐In TanFaculty of Business and Finance, UniversitiTunku Abdul Rahman, Malaysia Voon‐Hsien LeeFaculty of Business and Finance, Universiti TunkuAbdul Rahman, Malaysia Alain Yee‐Loong ChongDepartment of Industrial and Systems Engineering,The Hong Kong Polytechnic University, Hong Kong, Republic of China. 2011. HRM practices andknowledge sharing: an empirical study. International Journal of Manpower 32:5/6, 704-723. [Abstract][Full Text] [PDF]

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58. Rajesh Kr SinghIndian Institute of Foreign Trade, New Delhi, India. 2011. Analyzing the interaction offactors for success of total quality management in SMEs. Asian Journal on Quality 12:1, 6-19. [Abstract][Full Text] [PDF]

59. Evangelos L. PsomasDepartment of Business Administration of Food and Agricultural Enterprises,University of Ioannina, Agrinio, Greece Christos V. FotopoulosDepartment of Business Administrationof Food and Agricultural Enterprises, University of Ioannina, Agrinio, Greece Dimitrios P.KafetzopoulosDepartment of Business Administration of Food and Agricultural Enterprises, Universityof Ioannina, Agrinio, Greece. 2011. Core process management practices, quality tools and qualityimprovement in ISO 9001 certified manufacturing companies. Business Process Management Journal 17:3,437-460. [Abstract] [Full Text] [PDF]

60. Keng-Boon Ooi, Jia-Jia Sim, King-Tak Yew, Binshan Lin. 2011. Exploring factors influencing consumers’behavioral intention to adopt broadband in Malaysia. Computers in Human Behavior 27:3, 1168-1178.[CrossRef]

61. Faisal TalibMechanical Engineering Section, Faculty of Engineering and Technology, UniversityPolytechnic, Aligarh Muslim University, Aligarh, India Zillur RahmanDepartment of ManagementStudies, Indian Institute of Technology Roorkee, Roorkee, India M.N. QureshiMechanical EngineeringDepartment, Faculty of Technology and Engineering, M.S. University of Baroda, Vadodara, India. 2011.A study of total quality management and supply chain management practices. International Journal ofProductivity and Performance Management 60:3, 268-288. [Abstract] [Full Text] [PDF]

62. Iñaki Heras, Frederic Marimon, Martí Casadesús. 2009. Impacto competitivo de las herramientas para lagestión de la calidad. Cuadernos de Economía y Dirección de la Empresa 12:41, 7-35. [CrossRef]

63. Daniel Jiménez‐JiménezDepartment of Management and Finance, University of Murcia, Murcia, SpainMicaela Martínez‐CostaDepartment of Management and Finance, University of Murcia, Murcia, Spain.2009. The performance effect of HRM and TQM: a study in Spanish organizations. International Journalof Operations & Production Management 29:12, 1266-1289. [Abstract] [Full Text] [PDF]

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