Leadership styles in technologyacceptance: do followers practice

what leaders preach?Jeroen Schepers and Martin Wetzels

Department of Technology Management, OrganizationScience and Marketing, Eindhoven University of Technology,

Eindhoven, The Netherlands, and

Ko de RuyterDepartment of Marketing and Market Research,

Faculty of Economics and Business Administration,Maastricht University, Maastricht, The Netherlands

Abstract

Purpose – Service firms recognize the need to introduce new technologies to stay in the market, or toretain their competitive advantage compared to their rivals. Introducing new technologies in anorganization is by no means easy and poses many challenges like the acceptance and adoption of newtechnologies by employees. The technology acceptance model (TAM) has often been applied to explainindividual technology use. In previous studies, the model has been extended with many differentconstructs, including personal and technology related factors. Also management support and traininghave been shown to positively influence technology acceptance. However, the influence of leadershipstyle in this context has not been studied before. This study models and tests two leadership styles(transactional and transformational) as antecedents to perceived usefulness and perceived ease of useof new technologies.

Design/methodology/approach – This is an empirical study in a service setting.

Findings – In the surveyed company transformational leadership positively influences perceivedusefulness of the technology. This was fully accounted for by the sub-dimension of intellectualstimulation. Transactional leadership did not display any significant effects.

Research limitations/implications – Since data analysis was conducted in a single company,future research is needed to generalize the current findings. Furthermore, a longitudinal design wouldallow for statements regarding the stability and durability of the observed effects.

Practical implications – Besides technology support and training, leader behavior can influence anindividual’s perception of a technology, ultimately resulting in usage.

Originality/value – Insight has been given to which extent a leadership style can influencetechnology acceptance and through which mechanisms.

Keywords Management styles, Leadership, Service industries, Communication technologies

Paper type Research paper

IntroductionWith the ever changing business landscape of more and innovative competitors, mostservice firms recognize the need to introduce innovations and new technologies withintheir organizational processes to stay in the market, or to retain their competitiveadvantage compared to their rivals. Introducing new technologies in an organization isby no means an easy job and poses many challenges like their acceptance and adoption

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Managing Service QualityVol. 15 No. 6, 2005pp. 496-508q Emerald Group Publishing Limited0960-4529DOI 10.1108/09604520510633998

by employees. One of the most often used models explaining technology acceptance isthe technology acceptance model (TAM) by Davis et al. (1989). It was the first model tostate that psychological factors, perceived usefulness and perceived ease of use of thenew technology, are central in influencing its use. Since the model allows for theaddition of external variables, numerous extensions have been made. These relate totechnology-based factors like perceived enjoyment and perceived attractiveness (Vander Heijden, 2003, 2004), personal factors like personal innovativeness (Agarwal andPrasad, 1998, 1999), or interpersonal factors like trust (Gefen et al., 2003). Also concretemanagement actions like offering training and education, and organizational technicalsupport have been shown to play a role in influencing individual usage of innovations(Schillewaert et al., 2005). Less attention, however, has been given to the influence ofthe overall leadership style in an organization. We, therefore, extend TAM with twostyles: transactional leadership and transformational leadership. These concepts weredeveloped by Burns (1978) on the basis of observing political leadership, and extendedby Bass (1985). Despite the fact that the styles cannot be seen as opposite ends of acontinuum (Avolio and Bass, 1991), they are different in nature. We expect them toplay similar roles in the context of technology acceptance, but via differentmechanisms. Unlike many other papers based on TAM we tested our conceptual modelin a service setting, paying attention to the use of software for planning andcoordinating service activities on a laptop by service employees.

The paper is structured as follows. First, a short literature overview is given on theconcept of leadership styles. Secondly, a conceptual framework is built by formulatinghypotheses on the effects of leadership styles on TAM-related variables. Thereafter theempirical study is described and its results will be presented. The paper concludes witha discussion on the theoretical and managerial implications of this study, directions forfurther research are given as well.

LeadershipThere are different approaches to studying leadership. Yukl (1994) considers the traitapproach and the charismatic/transformational leadership approach as two majorresearch avenues to the concept of leadership. The first, focusing on personal attributesof successful leaders, has mainly been used in psychology. In organizational studies,the second approach is used more often. Originally the theory of charismatic leadershipwas coined by House (1977), stating that a charismatic leader is generously acceptedand obeyed by followers by having a strong need for power and a high self-confidence.Parallel to this conception of charismatic leadership, the concepts of transformationaland transactional leadership were developed by Burns (1978) on the basis of observingpolitical leadership. Bass (1985) further extended these notions and applied them in anorganizational setting. In his theory transformational and transactional leadership arenot defined to be on a single continuum, but as two separate concepts. A leader couldpossess elements of both styles. The transformational style of leadership ischaracterized by charisma, individual consideration, intellectual stimulation, andinspirational motivation. Charisma can be defined as the degree to which the leaderbehaves in admirable ways that cause followers to identify with the leader (Judge andPiccolo, 2004) or the amount of faith, respect, and inspiration he instills (Bass, 1985;Bycio et al., 1995). Individual consideration refers to the ability of a leader to considersubordinates individually, by delegating projects to stimulate people, creating learning

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experiences, and paying attention to the personal needs of these followers. Intellectualstimulation is the act of encouraging new ways of thinking, reasoning before acting,and enabling subordinates to analyze problems from many different viewpoints(Avolio and Bass, 1988). Finally inspirational motivation is inspiring and empoweringfollowers to enthusiastically accept and pursue challenging goals and a mission (Bass,1985). Transactional leadership on the other hand is characterized by contingentreward and management-by-exception. The former refers to whether a leader rewardshis followers when they act in accordance with contracts, rules, norms, agreed-uponobjectives, or expend the necessary effort on a certain task (Howell and Avolio, 1993).The latter applies when a leader does not give any directions if the current ways ofdoing a job still apply, or are still effective. Only if mistakes are made, something hasgone wrong, or performance standards are not met any more, the leader takes action.Next we will build our conceptual model based on the leadership styles describedabove.

Conceptual model and hypothesesOver the years, strong empirical support has been established in favor of TAM (Adamset al., 1992; Davis, 1989; Igbaria, 1993; Venkatesh and Davis, 2000), making it a robusttheory since it holds across persons, settings, and times (Cook and Campbell, 1979).Two central hypotheses in TAM state that perceived usefulness and perceived ease ofuse positively influence an individual’s attitude towards using a new technology,which in turn influences his behavioral intention to use it. Finally, intention ispositively related to actual use. The mediating role of attitude has been doubtful fromthe start and was, therefore, not considered in later assessments of the model.Analogous to Schillewaert et al. (2005) we focus on current usage of technology,measured by perceived actual use, meaning that there is no need to examine intentionsto use. Hence, we hypothesize:

H1. The perceived usefulness of the new technology positively influencestechnology usage.

H2. The perceived ease of use of the new technology positively influencestechnology usage.

Another TAM hypothesis indicates that perceived ease of use influences perceivedusefulness. Intuitively this makes sense, a technology will be more useful for somebodyif it is easier to use in general, or as Davis et al. (1989, p. 987) put it, “effort saved due toimproved ease of use may be redeployed, enabling a person to accomplish more workfor the same effort”. Therefore,

H3. The perceived ease of use of the technology positively influences theperceived usefulness of the new technology.

The goal of our study is to examine whether leadership styles have an effect onindividual acceptance of information technologies within service organizations. SinceTAM assumes that factors influencing behavior only do so indirectly by influencingperceived usefulness, perceived ease of use, or their relative weights (Davis, 1989),transactional and transformational leadership can influence both factors to beconsistent with the theory. Regarding perceived usefulness, if a leader clearly states the

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benefits of a technology, for example, by indicating that using the system is the onlyway to reach specified targets, employees might find it more useful to work with. Thistransactional leadership style has a cost effectiveness focus which could alsopotentially reveal the usefulness of a technology given that technologies are oftenintroduced out of cost reduction considerations. Transformational leadership styleapplies another mechanism by challenging people to be more creative and exploratory.With this attitude it is likely that people will more easily grasp the usefulness of atechnology. Hence, we hypothesize:

H4. Transactional leadership positively influences the perceived usefulness of thenew technology.

H5. Transformational leadership positively influences the perceived usefulness ofthe new technology.

Regarding perceived ease of use, if a leader is stressing in-role behavior and costefficiency (transactional leadership), employees use the technology in a very rigid wayto increase the quantity and quality of their output. They do not have the freedom toexperiment with the technology and explore difficult features, as they will only use thesystem in a clearly predefined way. This reduces the potential complexity of atechnology for an individual. Analogous to the case of perceived usefulness,transformational leadership is another mechanism influencing perceived ease of use. Ifa leader encourages creativity and open-mindedness, employees will be more used toexperimenting with new technologies and procedures, and more quickly learn thefeatures. Since previous learning experiences build up some latent innovativeness, thenewly introduced technology appears easier to use. We, therefore, hypothesize:

H6. Transactional leadership positively influences the perceived ease of use of thenew technology.

H7. Transformational leadership positively influences the perceived ease of use ofthe new technology.

While leadership styles are abstract and broad in nature, organizational facilitators canbe regarded as more concrete actions taken by a leader and/or implemented in anorganization. Conditions and events that create a positive environment for technologyadoption such as training and education and organizational technical support can beseen as elements of organizational facilitators (Frambach and Schillewaert, 2002;Schillewaert et al., 2005). Training, education and technical support can affect the wayan individual applies a technology in a useful way and/or finds it easy to use(Venkatesh, 1999). Giving hands-on sessions and feedback can illustrate functions andfeatures of a technology, thus influencing perceived usefulness. Besides, in general, ifsomebody demonstrates a technology it is perceived easier to use then if an individualhas to learn it by himself. Hence, it is hypothesized:

H8. Organizational facilitators positively influence the perceived usefulness of thenew technology.

H9. Organizational facilitators positively influence the perceived ease of use of thenew technology.

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Together the above hypotheses constitute the conceptual framework depicted inFigure 1.

Empirical studySetting and samplingThe research was conducted using the after-sales service department of a Dutch,high-technology company, which operates globally. For the study, 327 questionnaireswere handed out personally to boundary spanning service employees in TheNetherlands. A total of 236 questionnaires were returned yielding a response rate of 72percent. Of the returned questionnaires, ten were not filled out for the greater part andthese were excluded from data analysis resulting in 226 completed questionnaires to beexamined. The median age of the respondents is between 31 and 40 years (30.1percent), and the median level of education is secondary education with an applicationcourse (60.2 percent). The median tenure with the company is more than 20 years (32.6percent) and the median working time in a similar function to the current one is morethan 15 years (35.6 percent).

MeasuresMulti-item scales were employed based on previously published scales and translatedin Dutch by means of a translation – back translation procedure (Brislin, 1986).Transformational and transactional leadership were measured using the multifactorleadership questionnaire (MLQ), version 5X developed by Avolio and Bass (1988). Ithas oftentimes been shown to be a reliable scale (Lowe et al., 1996) and since it is alsomore parsimonious in comparison with alternative versions of the scale (e.g.MLQ-Form 10 in Howell and Avolio (1993)), we apply MLQ5X in our research. In theinstrument charisma is measured by eight items. Individualized consideration,intellectual stimulation, and inspirational motivation are assessed by four items each.The contingent reward component measuring transactional leadership wasoperationalized by a four-item scale while management-by-exception was

Figure 1.Conceptual model

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conceptualized as an eight-item scale. All items were answered on a seven-point Likertscale, where respondents had to indicate whether described situations happenedsporadically (1), sometimes (4), up to often (7).

Technology usage, perceived usefulness, and perceived ease of use were measuredby an instrument developed by Davis (1989) and Venkatesh and Davis (1996).Technology usage was measured by three items while perceived usefulness andperceived ease of use both had four items. Organizational facilitators were measured ona six-item scale based on Schillewaert et al. (2000, 2005). All these items were measuredon a seven-point Likert scale, where respondents had to indicate the extent to whichthey agreed with a given statement, ranging from totally disagree (1) to totally agree(7). Descriptive statistics on the constructs are given in Table I.

Methodology and resultsWe used partial least squares (PLS) analysis as implemented in SmartPLS to estimateboth the measurement model and the structural model (Hansmann and Ringle, 2004).This technique is considered adequate in the current research since the distribution ofthe data deviates from normality and PLS makes no distributional assumptions(Fornell and Cha, 1994). The evaluation of the model fit was conducted in two stages(Chin, 1998; Hulland, 1999). First, the measurement model is assessed, in whichconstruct validity and reliability of the measures are key. Secondly, the structuralmodel with hypotheses is tested.

Validity and reliabilityWe first assessed construct validity and reliability of the measurement instruments.Convergent validity can be evaluated by inspecting all item loadings on theirrespective constructs (Hulland, 1999; Tenenhaus et al., 2005). Observing the itemloadings in Table II we removed the italicized items from our analysis (SL , 0.5).

The next step was to assess discriminant validity. According to Fornell and Larcker(1981), the square root of the average variance extracted (AVE) of each constructshould exceed the correlation shared between the construct and other constructs in themodel. Table III shows the details of this analysis. The square root of the AVE oftransformational leadership is slightly too low, but is still deemed high enough for avalid analysis. A second test for discriminant validity assessed the cross-factorloadings of the measures (Hulland, 1999). The measures should not exhibit anyloadings substantial in magnitude on constructs for which we have not hypothesizedso. Moreover, the correlations of residual terms (Q) across blocks should not exceed0.20 in absolute terms (Fornell and Bookstein, 1982). These criteria were satisfied forour study.

Measure Mean SD a Composite reliability

Technology usage 5.93 1.07 0.878 0.931PU 5.44 1.23 0.904 0.935PEOU 5.72 1.13 0.865 0.912Organizational facilitators 4.63 1.19 0.892 0.908Transformational leadership 4.64 0.92 0.912 0.914Transactional leadership 4.01 0.87 0.653 0.535

Table I.Descriptive statistics of

measures

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Perceived usefulnessPU 1 0.8785PU 2 0.8867PU 3 0.9301PU 4 0.8428Perceived ease of usePEOU 1 0.7166PEOU 2 0.7381PEOU 3 0.7898PEOU 4 0.7990Organizational facilitatorsOF 1 0.8580OF 2 0.8982OF 3 0.8611OF 4 0.6241OF 5 0.7259OF 6 0.7139UsageU 1 0.8931U 2 0.9283U 3 0.8920Transformational leadershipTFL – Charisma – 1 0.4355TFL – Charisma – 2 0.2387TFL – Charisma – 3 0.7250TFL – Charisma – 4 0.5940TFL – Charisma – 5 0.6302TFL – Charisma – 6 0.6297TFL – Charisma – 7 0.6877TFL – Charisma – 8 0.7032TFL – Individual consideration – 1 0.6986TFL – Individual consideration – 2 0.3782TFL – Individual consideration – 3 0.6801TFL – Individual consideration – 4 0.7560TFL – Intellectual stimulation – 1 0.5142TFL – Intellectual stimulation – 2 0.5750TFL – Intellectual stimulation – 3 0.6846TFL – Intellectual stimulation – 4 0.5970TFL – Inspirational motivation – 1 0.4891TFL – Inspirational motivation – 2 0.6629TFL – Inspirational motivation – 3 0.5826TFL – Inspirational motivation – 4 0.6417Transactional leadershipTAL – Contingent reward – 1 0.5771TAL – Contingent reward – 2 0.5544TAL – Contingent reward – 3 0.4359TAL – Contingent reward – 4 0.3903TAL – Management-by-exception – 1 0.3632TAL – Management-by-exception – 2 0.0678TAL – Management-by-exception – 3 0.4201TAL – Management-by-exception – 4 0.4061TAL – Management-by-exception – 5 0.5018TAL – Management-by-exception – 6 0.5719TAL – Management-by-exception – 7 0.5199TAL – Management-by-exception – 8 0.5896

Table II.Item loadings

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A reliability analysis of the measures using Cronbach’s a and composite reliability wasconducted. The internal consistency reliability estimates (a’s) are all above thecommonly used threshold value for acceptable reliability of 0.70 (Nunnally andBernstein, 1994), except for the construct transactional leadership which had an overallreliability coefficient of 0.65. Given the small difference compared to the cutoff value,we still render this construct sufficiently reliable. For composite reliability, a value ofcut-off value of 0.70 is suggested as well (Nunnally and Bernstein, 1994). Again, allvalues were well above this threshold except for transactional leadership (0.535)indicating that the reliability of this construct is not optimal and proving a slightlimitation. Cronbach’s a and composite reliability scores are given in Table I.

Hypotheses testingThe results for testing the hypotheses are summarized in Table IV. The t-value of eachcoefficient was obtained by applying a bootstrap procedure of 250 resamples (Efronand Tibshirani, 1993). Our results supported the original TAM, with perceivedusefulness (b ¼ 0.417; t ¼ 5.114) and perceived ease of use (b ¼ 0.378; t ¼ 4.956)positively influencing technology usage thus supporting H1 and H2. Also consistentwith most TAM literature, perceived usefulness has a slightly stronger positive effecton technology acceptance than has perceived ease of use (Agarwal and Prasad, 1997;Straub et al., 1997; Szajna, 1996). The positive relationship between perceived ease ofuse and perceived usefulness (b ¼ 0.482; t ¼ 7.256) supports H3 and is supported in

PU PEOU OF U TAL TFL

PU 0.885PEOU 0.257 0.762OF 0.305 0.423 0.786U 0.653 0.161 0.192 0.904TAL 0.124 0.348 0.227 0.014 0.688TFL 0.071 0.300 0.176 0.087 0.582 0.565

Notes: PU ¼ perceived usefulness; PEOU ¼ perceived ease of use; OF ¼ organizational facilitators;U ¼ usage; TAL ¼ transactional leadership; TFL ¼ transformational leadership

Table III.Construct correlations

(square root of AVE ondiagonal)

Relationship Coefficient t-value p-value Conclusion

Perceived usefulness ! usage 0.417 5.114 0.0000 Fail to reject H1Perceivede ease of use ! usage 0.378 4.956 0.0000 Fail to reject H2Perceived ease of use ! perceived usefulness 0.482 7.256 0.0000 Fail to reject H3Transactional leadership ! perceived usefulness 0.010 0.099 0.9212 Reject H4Transformational leadership ! perceivedusefulness 0.137 2.049 0.0416 Fail to reject H5Transactional leadership ! perceived ease of use 0.111 0.806 0.4211 Reject H6Transformational leadership ! perceived ease ofuse 20.032 0.241 0.8098 Reject H7Organizational facilitators ! perceived usefulness 0.091 1.494 0.1366 Reject H8Organizational facilitators ! perceived ease of use 0.359 4.628 0.0000 Fail to reject H9

Table IV.Results of hypotheses

testing

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the majority of studies involving TAM. Analyzing the influence of leadership styles,only one of the four hypothesized paths turned out to be significant. Transformationalleadership positively related to perceived usefulness (b ¼ 0.137; t ¼ 2.049), thusyielding support for H5. The same leadership style did not have a significant effect onperceived ease of use, rejecting H7. Transactional leadership style did not display anysignificant relationship to either of the two technology perceptions, rejecting H4 andH6. Concerning organizational facilitators, these displayed a strong significant effecton the perceived ease of use of the system (b ¼ 0.359; t ¼ 4.628), supportingH9. Perceived usefulness was however not affected by organizational facilitators,rejecting H8.

To allow for more detailed statements on the influence of transformationalleadership style on perceived usefulness, we tested a second model where we related allsub-dimensions of the two leadership styles directly to perceived usefulness andperceived ease of use. We obtained t-values by applying a bootstrap procedureconsisting of 250 re-samples. Our results showed that contingent reward andmanagement-by-exception, being sub-dimensions of the transactional leadership style,did not display any significant relationships to either perceived usefulness or perceivedease of use (0.339 , t , 1.440). Focusing on the significant relationship betweentransformational leadership and perceived usefulness, our additional analysis showsthis effect is fully accounted for by the sub-dimension of intellectual stimulation(b ¼ 0.094; t ¼ 1.900). The other sub-dimensions remained non-significant.

Model fitPLS has no proper single goodness-of-fit measures, although the R 2 values of theendogenous constructs indicate whether a particular PLS model accomplishes theobjective of maximizing the variance explained (Hulland, 1999). The current modeldisplays R 2 values of 0.341 for perceived usefulness, 0.134 for perceived ease of use,and 0.507 for usage. In accordance with the categorization of R 2 effect sizes by Cohen(1988) (small: 0.02; medium: 0.13; large: 0.26) we can conclude these effect sizes to bemedium (perceived ease of use) to large (perceived usefulness and usage). Recently,Tenenhaus et al. (2005) developed a global fit measure for PLS based on R 2 values. Bytaking the square root of the product of the average communality of all constructs andthe average R 2 value of the endogenous constructs a fit measure between 0 and 1 iscalculated. Based the categorization by Cohen (1988), and using 0.5 as a cut-off valuefor commonality (Fornell and Larcker, 1981), GoF criteria for small, medium, and largeeffect sizes would be 0.1, 0.25 and 0.36. For the current model this fit is 0.405, indicatinga good fit of the model to the data.

The model of the additional analysis performed slightly better in terms of model fit.However, with decomposed leadership styles this was expected. R 2 values of perceivedusefulness, perceived ease of use, and usage were 0.394, 0.176, and 0.506, respectively.Based on the Tenenhaus et al. (2005) statistic, this leads to a GoF value of 0.436.

Conclusion and discussionWhile numerous studies have already verified TAM (Legris et al., 2003), to ourknowledge no attention was paid to leadership styles before. The objective of thisstudy was to determine the impact of two leadership styles, transactional leadershipand transformational leadership, on TAM factors. We hypothesized both styles to

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positively relate to perceived usefulness and perceived ease of use, albeit usingdifferent mechanisms. Our findings show that only the relationship betweentransformational leadership and perceived usefulness was significant. Additionalanalysis illustrates that this effect is fully accounted for by the sub-dimension ofintellectual stimulation. This indicates that encouraging new ways of thinking andenabling subordinates to analyze problems from many different viewpoints willindirectly yield a better individual technology acceptance level within the organization(mediated by perceived usefulness). Charismatic leadership, individual considerationand inspirational motivation might be less effective with this goal in mind. Togetherwith perceived ease of use transformational leadership explained more than 34 percentof the variance in perceived usefulness. The hypotheses concerning transactionalleadership style did not display significance. So, pointing out the usefulness of atechnology by means of setting targets and objectives that require the use of atechnology might not be very effective in stimulating the use of a technology. Thenon-significance could be due to the fact that the reliability of the construct measuredby Cronbach’s a was slightly below the commonly accepted cut-off value of 0.7(Nunnally and Bernstein, 1994).

Concerning organizational facilitators, these displayed a strong influence on anindividual’s perceived ease of use of the technology. Consistent with previous research(Amoako-Gyampah and Salam, 2004; Venkatesh et al., 2002), we state that training andmore general end-user support are of importance in enhancing individual technologyacceptance as well. Implementing a help desk, or on-site support are possibilities tocommunicate organizational commitment to employees. Management should alsothink about the less tangible aspects, however, a positive word-of-mouth in an internalmarketing campaign can serve a useful purpose too. These actions only influenceindividual technology usage via perceived ease of use, however, as there was nosignificant relationship between organizational facilitators and perceived usefulness ofthe technology.

With regards to the limitations of our research a couple of points can be mentioned.First, perceived actual use was used as opposed to objective measures. Using the lattermight lead to superior analysis. Secondly, the results are based on findings in onecompany only, which limits the generalizability of the results. Further research indifferent countries and industries is needed to be able to make stronger statements.The observation by Igbaria et al. (1997) that results with respect to relationshipsbetween internal support and internal training on the one hand and PU and PEOU onthe other hand might differ between small and large firms only adds to this statement.Furthermore the use of cross-sectional data instead of a longitudinal research designinhibits to make statements on causal relationships. As a last limitation, the lowreliability of transactional leadership could have caused non-significance in some of thehypothesized relations. It could be explored whether this might be due to a potentialformative nature of the relationship of the indicators with the construct. With regard tofuture research a couple of opportunities arise, ranging from replicating this type ofresearch in small companies to making cross-cultural comparisons. A longitudinalstudy could be beneficial as well, as it would allow making statements on the stabilityand durability of the observed effects. To get a more fine-grained analysis of theimpact of leadership on technology acceptance, authors could also link other leadershiptheories and constructs (e.g. leader characteristics) to TAM.

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(Jeroen Schepers MSc is a PhD candidate in Organization Science and Marketing at EindhovenUniversity of Technology in The Netherlands. Before becoming a PhD candidate he studiedInformation Management at Tilburg University. His research interests include technologyadoption and organizational innovation management.

Martin G.M. Wetzels currently is a Full Professor of Marketing with the Faculty ofTechnology Management, Eindhoven University of Technology, The Netherlands. His mainresearch interests are: new product development, electronic marketing, quality management,(online) marketing research, service marketing and management, relationship marketing andinnovation and technology management. His work has resulted in more than 40 articles ininternational journals including Management Science, Marketing Letters, International Journal ofResearch in Marketing, Journal of Business Research, Journal of Interactive Marketing, Journal ofEconomic Psychology, Industrial Marketing Management, European Journal of Marketing,Journal of Management Studies and Total Quality Management. Finally, he has contributed morethan sixty papers to conference proceedings.

Ko de Ruyter is Professor of Marketing and Head of the Department of Marketing atMaastricht University, The. He has published six books and numerous scholarly articles inamong others the Journal of Marketing, Management Science, Journal of Retailing International,Journal of Research in Marketing, Decision Sciences, Marketing Letters, Journal of ManagementStudies, Journal of Business Research, Journal of Economic Psychology, Journal of ServiceResearch, International Journal of Service Industry Management, Journal of Business Research,Information andManagement, European Journal of Marketing and Accounting and Organisationand Society. He serves on the editorial boards of various international academic journals, amongwhich, the Journal of Service Research and International Journal of Service IndustryManagement. His research interests concern international service management, e-commerceand customer satisfaction and dissatisfaction.)

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