Service quality in the Australian advertising industry: a methodological study Pascale G. Quester and Simon Romaniuk

Transcription

1 An executive summary for managers and executives can be found at the end of this article Service quality in the Australian advertising industry: a methodological study Pascale G. Quester and Simon Romaniuk Deregulation and recession Defining and measuring service quality Background There is ample evidence that the Australian advertising industry is under considerable stress after advertising budgets were cut or frozen during the last economic recession. Indeed, more than 100 Australian advertising agencies have closed or merged since A survey by the Advertising Federation of Australia (Shoebridge, 1993) found that if agencies billings grew by 4.7 percent during 1992, revenues increased by just 1.1 percent. For the same year, agencies average profit after tax, expressed as a percentage of billings, plummeted to 1.4 percent (Fox, 1994). The advertising industry is not unique in this respect, and many service businesses face the increasing competition brought about by deregulation and a declining profitability induced by recession (Bitner, 1990). The most successful service companies aim to differentiate themselves on the basis of high service quality (Berry and Parasuraman, 1993). Additional benefits of this strategy, apart from competitive differentiation, include enduring customer relationships, favorable customer word-of-mouth, higher employee morale and greater productivity (Berry and Parasuraman, 1993). Termination of established agency-client relationships is the expected outcome of inadequate service quality for advertising agencies. An advertising agency image study conducted in 1993 revealed that a total of 68 percent of marketers (as clients) had changed agencies in the last two-to-three years or had seriously considered it, compared to 62 percent in 1991 (AMR: Quantum, 1993). This suggests that there is an opportunity for agencies to improve relationships with clients, and thus profitability, by focussing on service quality. Service quality is a construct that is difficult to define and measure (Brown and Swartz, 1989; Carman, 1990; Parasuraman, Zeithaml, and Berry, 1985, 1988; Rathmell, 1966). Services have unique features, such as intangibility, heterogeneity, and inseparability of production and consumption, which makes the measurement of quality a complex issue (Parasuraman et al., 1985). In the absence of objective measures of service quality, a more subjective approach, measuring consumers perceptions and expectations of quality, is appropriate (Parasuraman et al., 1988). The specification and measurement of service quality have received a lot of attention in recent marketing literature. The debate has centered on the SERVQUAL measure of service quality, which was developed by Parasuraman et al. (1985, 1988). However, the basis of their model, which measures the difference between consumers perceptions and expectations of a particular service, has been disputed. Cronin and Taylor (1992) question the relevance of the expectations-perceptions gap as a basis for measuring service quality (see also Carman, 1990) and suggest a simple performance-based measure of service quality, named SERVPERF, as more appropriate. Their measure is based essentially on consumers perceptions of actual performance. 180 THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO , pp MCB UNIVERSITY PRESS

2 SERVQUAL or SERVPERF? Expectations The ultimate objective of this study is to ascertain which measurement scale (SERVQUAL or SERVPERF) advertising agencies should use as the better measurement of service quality as perceived by their clients. In addition, the relationships between advertising agency service quality and advertiser satisfaction will be examined. While the practical applications of this study to the advertising industry are obvious, its results will also build on the limited empirical evidence that currently exists in the literature. Until recently, only one published study had directly compared the SERVQUAL and SERVPERF scales and none had analyzed Australian data. Furthermore, while services in general have been the focus of much research, professional services, such as those offered by lawyers, accountants or consultants, have benefitted from little attention, and no previously published service quality study has analyzed empirical evidence from professional service providers such as advertising agencies. Indeed, an extensive search through databases such as ABI/Inform failed to uncover any advertising industry-related service measurement study. A preliminary study in which the present authors were involved, however, exposed the potential for different scales, based on SERVQUAL and SERVPERF, to be used in this context (Quester, Wilkinson and Romaniuk, 1995). This article will present the data and methodology of a survey of major advertisers, the results of which are used to compare Cronin and Taylor s (1992) SERVPERF measurement scale with the original SERVQUAL measure. The article will conclude by providing some of the implications of the study for advertising agencies and directions for future research. Perceived service quality The most popular and consistent definition of perceived service likens the concept to an attitude. For example, Parasuraman et al. (1988) define perceived service quality as a global judgement, or attitude, relating to the superiority of the service and Castleberry and McIntyre (1993) define perceived service quality as a belief (or attitude) about the degree of excellence of a service Parasuraman et al. (1988) emphasize that the term expectations is used differently in the service quality literature, where it represents what customers feel the service provider should offer, from its use in the consumer satisfaction literature, where it represents customers beliefs about what the service provider would offer (Oliver, 1980; Teas, 1993). Recently, a number of researchers examining service quality issues have adopted the former conceptualization of expectations (Brown and Swartz 1989; Carman 1990) despite some arguments opposing this usage (Cronin and Taylor, 1992). In the case of advertising agencies, service quality as perceived by advertisers may be defined as an attitude of advertisers relating to the superiority of agencies services, or the discrepancy between advertisers perceptions and expectations of agencies services. Oliver (1981) defines satisfaction as: a summary psychological state resulting when the emotion surrounding disconfirmed expectations is coupled with the consumers prior feelings about consumption experience. THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

3 Attitude and satisfaction Underlying model is flawed? He goes on to summarize the nature of satisfaction, and differentiates it from attitude, as follows: attitude is the consumer s relatively enduring affective orientation for a product, store, or process while satisfaction is the emotional reaction following a disconfirmation experience which acts on the base attitude level and is transaction-specific. Since perceived service quality is defined as an attitude, the distinction between attitude and satisfaction is argued to be the same as the distinction between perceived service quality and satisfaction (Parasuraman et al., 1988). Bitner (1990) sums up this conceptualization of satisfaction and quality as follows: [customer satisfaction with] individual [service] encounters are nested within broader customer perceptions of service quality. In relation to advertising agencies services, perceived service quality and advertisers satisfaction can be conceptualized by the following: perceived advertising agency service quality is the advertisers relatively enduring affective orientation for agency services, while satisfaction is the emotional reaction following a disconfirmation experience which acts on perceived service quality and is transaction-specific. Carman (1990) was the first to criticize the perceptions-minus-expectations operationalization of SERVQUAL. His criticisms were based on theoretical considerations rather than empirical evidence, which supported the SERVQUAL measure. He attempted to answer these criticisms from within the framework of the original service quality model with important extensions to the SERVQUAL measure. Cronin and Taylor (1992) also criticized the perceptions-minus-expectations operationalization of SERVQUAL. They argued that the theoretical considerations evidence suggests that the underlying service quality model developed by Parasuraman et al. (1985) is flawed. Therefore, using their own service quality model, they developed an alternative measurement scale based on service performance (or perceptions) rather than perceptions minus expectations. They tested this alternative scale empirically, along with the SERVQUAL scale, in four previously untested service settings and argued that the results proved the superiority of their performance-based measures of service quality. Specifically, Cronin and Taylor (1992) tested the ability of their performance-only measurement scale, SERVPERF (1) compared to SERVQUAL (2). Service quality = (perceptions) (1) Service quality = (perceptions expectations (P E)) (2) Further criticism stemmed from Teas s work (1993) in which it is argued that if perceived quality can be conceptualized as an attitude, the ideal standard of expectations could be interpreted to be similar to the ideal point specified in classic ideal point attitudinal models. However, the P E measurement specification suggests that perceived service quality increases as perceptions exceed expectations. In contrast, ideal point attitudinal models suggest that perceived quality might decrease as perceptions exceed the ideal point. Clearly then, the SERVQUAL P E measurement specification is not compatible with the classic ideal point interpretation (Teas, 1993). 182 THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

4 Ideal circumstances Theoretical and definitional problems A second interpretation of the SERVQUAL ideal standard of expectations, however, is that it represents a feasible level of performance under ideal circumstances, i.e. the best level of performance by the highest quality provider under perfect circumstances. Under this interpretation, then, it could be argued that the service provider s performance might exceed this standard and that perceived quality would increase accordingly. However, depending on whether the attributes are vector attributes or finite ideal point attributes, this feasible ideal point interpretation may not be justified. Teas (1993) argues also that empirical research has identified important problems concerning the operationalization of the service expectation concept: (1) The word should in expectation survey items may cause respondents to assign unrealistically high ratings to the expectation response scales. (2) On the basis of empirical results, Carman (1990) questions the validity of the expectations measure when consumers do not have well-formed expectations. (3) Exploratory research by Teas (1993) suggests that a considerable portion of the variance in responses to the SERVQUAL expectations scale stems from the variance in respondents interpretations of the question rather than from any variance in respondents attitudes. In summary, there are a number of complex theoretical and definitional problems associated with the SERVQUAL perceptions-minus-expectations model. Removing the problematic expectations measure from the equation and measuring merely perceptions of performance (as SERVPERF does) may be more valid in measuring service quality. An opportunity exists, therefore, to re-test these models in the context of a previously untested service setting, such as advertising services. In such a test the limiting assumption of unidimensionality can be lifted and meaningful conclusions can be drawn with regard to the two measurement scales. The study Despite the above criticism, it is reasonable to consider SERVQUAL to be superior to SERVPERF as a measure of perceived service quality because the SERVQUAL measurement scale follows a more scientific approach to scale development and also because it is arguably more firmly based on the literature than is the SERVPERF scale. Therefore, it could be argued, SERVQUAL is potentially a superior measure of perceived service quality from an empirical standpoint also. And this, from a practitioner s perspective, would make it a more suitable tool for the purpose of performance evaluation and monitoring which, it was noted, becomes crucial in an increasingly competitive environment in order to avoid costly client relationship terminations. The hypothesis to be tested in this research project, therefore, can be stated as follows: H1: The SERVQUAL measurement scale is the better predictor of the generally perceived service quality of Australian advertising agencies than is the alternative, SERVPERF as measured by the adjusted goodness of fit (R 2 ). THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

5 Sampling frame High response rate To evaluate H1, the study examined 182 responses from a sample of major Australian advertisers. A further 49 responses were received, but could not be used. Of these, 29 were refusals or incorrectly filled responses and 20 were replies from companies not presently using the services of an advertising agency. The total number of surveys posted was 350; therefore, after adjusting the sample size for advertisers not using agencies, the response rate was 55 percent. This sample size compares well with the studies conducted by Cronin and Taylor (1992) and by Parasuraman et al. (1988), where the sizes of the samples analyzed were 183 and 200, respectively. The sampling frame was selected from the B & T Advertising Marketing and Media Year Book 1993 (Thomson Business Publishing). This publication profiles major advertisers in Australia and includes information on the marketing and management personnel of each company. This information was used to target directly and personally those people most likely to be in direct contact with an advertising agency. This was thought potentially to improve the response rate which a nonpersonal mail survey might otherwise receive. A mail survey, including a prepaid return envelope, was used. The personal interview method of data collection has been predominantly used in previous studies because the sampling frame has been in a localized area. In the case of a national survey in a country as vast as Australia, this was not practical. While there is a concentration of businesses in the eastern states of the continent, their geographical dispersion is such that a mail survey proved to be the only cost-effective method to collect the necessary data. Moreover, the time flexibility afforded by the self-administration of the questionnaire made this methodology much more suitable for the types of respondent targetted by this study. The survey was conducted over the period of July-August 1993, the busy winter season in the southern hemisphere when the least holiday-related absenteeism could be expected from members of our sample. This may have contributed to our relatively high response rate, even though no comparison can be drawn with previous studies in the area, due to the undisclosed response rates achieved in the personal interviews reported. Cronin and Taylor s (1992) questionnaire proforma was used to enable direct comparison with that study. Minor adjustments to wording were necessary to customize the survey for the new service setting of advertising (Carman, 1990). The data collected for the study included expectations of service quality and perceptions of performance. These were used to construct the alternative measures of service quality. A measure of consumer satisfaction, a direct measure of service quality, and a measure of future purchase intention also were collected. The first 22 expectation and performance items were derived directly from the SERVQUAL scale (Parasuraman et al., 1988). The addition of items 23 and 24 (see Table I) was made to customize the survey further, in line with recommendations by Parasuraman et al. (1988) and by Carman (1990). The direct measure of service quality was based on responses to a 7-point semantic differential question. Self-reported measures of consumer satisfaction and purchase intention were constructed similarly (Cronin and Taylor, 1990). The analysis of the data was conducted in two stages. The first stage determined the dimensionality of the two service quality models tested, and followed the procedure outlined by Parasuraman et al. (1988). The second 184 THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

6 SERVQUAL SERVPERF Dimensions Items Loadings Dimensions Items Loading Tangibility Q Tangibility Q Q Q Q Q Output Q Output Q Q Q Reliability Q Reliability Q Q Q Q Q Assurance Q Assurance Q Q Q Empathy Q Empathy/responsiveness Q Q Q Q Percentage total variance explained Table I. Dimensionality of alternative measurement scales Two-stage analysis Factor-loading matrices stage involved regressing the two structural models against the overall service quality variable to determine which scale is the better predictor of perceived service quality in the case of advertising services. Following the analysis procedure detailed by Parasuraman et al. (1988), each scale was factor analyzed using the principal axis factoring procedure (Harmon, 1976). The analysis was constrained a priori to ten factors and each scale was rotated orthogonally (using the VARIMAX procedure in FASTAT). The number of factors retained were those with eigenvalues greater than one. Factors below this number could not be interpreted (Carman, 1990). In contrast to the Parasuraman et al. (1988) study, the orthogonal rotations yielded factor-loading matrices that could be interpreted. Parasuraman et al. (1988) found it difficult to interpret their orthogonally rotated factor patterns, so they proceeded with an oblique rotation procedure to allow for intercorrelations among the dimensions and easier interpretation. The ease of interpretation of the orthogonal rotations in this study suggests that intercorrelations among remaining dimensions, in each of the two scales, are negligible in the context of advertising services. Several items in the factor-loading matrices had high loadings on more than one factor. When such items were removed from the factor-loading matrices, several factors themselves became meaningless because they had near-zero correlations with the remaining items, thereby suggesting a reduction in the assumed dimensionality of the service quality domain (Parasuraman et al., 1988). The resultant deletion of certain items necessitated the recomputation of the factor structures of the reduced item pools. This iterative sequence of analysis was repeated a few times on each of the scales examined and resulted in a final pool of items representing distinct dimensions (Parasuraman et al., 1988). Each scale produced differing factor-loading matrices and therefore each has its own dimension and item construction. THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

7 In an approach similar to that of Cronin and Taylor (1992), structural models representing the two measurement scales were correlated with the variables overall service quality, satisfaction and future purchase intention in order to assess the convergent and discriminant validity of each construct. On determining their dimensionality and validity, each measurement scale was evaluated by following the procedure employed by Cronin and Taylor (1992). That is, the ability of each scale to explain the variation in service quality was assessed by regressing the individual items comprising the alternative scales against a measure of advertisers perceptions of the overall service quality of their agency and comparing the adjusted goodness of fit. Service quality dimensions Validation for the method used Empirical results Dimensionality The service quality dimensions, as presented originally in Parasuraman et al. (1988), are tangibility, reliability, responsiveness, assurance (including communication, credibility, security, competence, and courtesy) and empathy (including understanding and access). Carman (1990) found that when dimensions of service quality are particularly important to customers, they are likely to break that dimension into subdimensions. In the study reported here, this occurred across both measurement scales. The items included for customization purposes (Q23 and Q24) loaded on to a unique factor in each case. These two items relate to agency production or output and so the dimension is henceforth named output. In the case of SERVQUAL, four iterations resulted in five final dimensions (tangibility, output, reliability, assurance and empathy) explaining some percent of the total variance. Four iterations were also necessary in the case of SERVPERF, with a final five dimensions (tangibility, output, reliability, assurance and empathy/responsiveness) explaining some percent of the total variance. Results of the final iteration for each scale are provided in Table I. These results provide strong validation for the empirical method used in the analysis. However, both scales were also quite high compared to previous studies (Carman, 1990). Overall, the differences between the scales can be described at best as trivial and the results do not justify a preference for either scale over the other in terms of ability to explain service quality variations. Validity Validity was assessed by generating a correlation matrix (see Table II) of the two service quality scales, the overall service quality, satisfaction and future purchase intention. While always subject to interpretation, the relatively high correlation between SERVQUAL and overall service quality, as well as Purchase Overall service SERVQUAL SERVPERF Satisfaction intentions Overall service quality SERVPERF SERVQUAL Satisfaction Purchase intentions Table II. Pearson correlation matrix 186 THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

8 Is SERVQUAL better? Lower adjusted R 2 between SERVPERF and overall service quality, suggests each has a degree of convergent validity (Cronin and Taylor, 1992). Discriminant validity involves the extent to which a measure is novel and does not simply reflect some other variable. Churchill (1979) suggested assessing discriminant validity by determining whether the correlation of a measurement construct is higher with another variable than with the one it was intended to measure. Discriminant validity can be assessed by comparing the correlations of each of the measurement scales to both overall service quality and satisfaction. It can be concluded, according to Churchill (1979), that if a service quality scale correlates more with satisfaction than with service quality it therefore lacks discriminant validity. Using this rule, the results of this study found both SERVPERF and SERVQUAL to have discriminant validity (see Table II). The literature suggests that the SERVQUAL measurement scale should be the better predictor of overall service quality. To test this hypothesis the structural models of the two measurement scales, determined in the first section of this article, were regressed with the dependent variable overall service quality and the adjusted R 2 s compared. The use of the adjusted R 2 measure to determine which scale better predicts overall perceived service quality is accepted in the literature (see Cronin and Taylor, 1992; Parasuraman et al., 1994). By definition, R 2 measures the proportion of the variation in the dependent variable (overall perceived service quality) accounted for by the explanatory variables the service quality model, SERVQUAL and SERVPERF (Gujarati, 1988). An important property of R 2 is that it is a nondecreasing function of the number of explanatory variables present in the model. That is, as the number of regressors increases, R 2 almost invariably increases and never decreases. To compare the R 2 s, the number of explanatory variables in each model must be taken into account. The adjusted R 2 measure is adjusted for the number of degrees of freedom and parameters associated with each model. It is good practice to use adjusted R 2 rather than R 2 because R 2 tends to give an overly optimistic picture of the fit of the regression (Theil, 1978). In this study, the adjusted R 2 for each model was: SERVQUAL: 0.49 SERVPERF: This result does not support H1, that SERVQUAL is the better predictor of overall service quality, because the SERVPERF scale has the higher adjusted R 2. In this study, the SERVQUAL measurement scale has a lower adjusted R 2 and is therefore not as good a predictor of overall service quality. However, differences between the scales could be characterized as trivial and therefore not indicative that one scale is better suited than the other for measuring service quality. An analysis of variance also was undertaken on each regression model to assess their relative significance. The F-test showed that both the regression models were significant at a confidence level superior to 99 percent, a result expected as factor analysis was used to boost the explanatory power of each model. Table III summarizes the analysis of variance procedure undertaken. Managerial implications The empirical research conducted in this study found that the performancebased SERVPERF measure outperforms the SERVQUAL measurement THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

9 Degrees of freedom F-ratio Regression Residual F-value SERVQUAL SERVPERF Table III. Analysis of variance of the regression models Two ways to resolve the quandary Demonstrating value of service scale. This suggests that there may be problems in the perceptions-minusexpectations operationalization of SERVQUAL. This presents a quandary: expectations are important in determining service quality; yet it may be operationally unwise to follow the SERVQUAL procedure. Carman (1990) offered two suggestions for resolving this quandary which the advertising industry could well use in order to make service quality easier to measure in their particular context: (1) The first is to collect the data in terms of the perception-expectation difference directly rather than by asking questions about each separately. This technique is likely to be most useful in the advertising context where norms for expectations are likely to be well-formulated in the respondent s mind on the basis of past experience. Each item in the perceptions battery could be answered on a 5-point scale as a comparison to expectations (Carman, 1990). For example, one question would read: The visual appeal of the agency s physical facilities are (much better, better, about the same, worse, much worse) than I expected. (2) The second suggestion concerns how much experience the client should have with the agency before answering the expectations battery (Carman, 1990). It is reasonable to assume that the important decision makers of major advertisers would have developed realistic expectations of advertising service quality from years of experience. Also, because advertising services are delivered within an enduring agency-client relationship the opportunity exists to establish realistic expectations upfront and review them as infrequently as once-yearly. Within this framework, perceptions could be surveyed regularly and factor analysis conducted on perceptions adjusted for the constant expectations. While some may argue that measurement scales such as SERVQUAL or SERVPERF are unlikely to contribute significantly to the operational management of advertising agencies, it is important to note that advertising practitioners are under increasing pressure to demonstrate the value of their services. It is not unreasonable, therefore, to assume that they would welcome instruments which may contribute to the relationship-building process by providing benchmarks and demonstrating, graphically if need be, any improvement in service delivery and client satisfaction over time. By undertaking such measurement activities routinely, an agency might be able even to identify early warnings of any deterioration in a client s service quality perception, thus enabling remedial actions to be taken before the relationship is terminated by the client. In Australia, where a court appeal is soon to decide the fate of the accreditation process itself, such initiatives may be all that remains for agencies in order to retain credibility and professional standing in an industry where profits are likely to be further eroded by the ending of the commission-based remuneration system which was enshrined in the accreditation process. In other countries, where this may not be the case, a 188 THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

10 No personal contacts Identical performance Explore the links considerable competitive advantage may be gained still from the ability to demonstrate service quality improvements over time. The results of this study must, of course, be considered in light of a number of limitations. Because of the great size of Australia, the survey was mailed and so did not allow for the invaluable personal contacts which previous studies had gained through direct interviewing for the completion of the questionnaire. Furthermore, the self-administered nature of the survey made it likely that a bias would exist in favor of the more involved and interested respondents, leaving the thoughts of many less opinionated respondents uncovered. The process of filling out the questionnaire itself may have led the respondents along a set cognitive path, perhaps even predetermining their ultimate overall assessment of service quality. Furthermore, it has been argued that expectations would be difficult to ascertain following the actual service performance, but should instead be measured prior to the service delivery. However, while this may be possible in the case of oneoff or episodic services, such as garbage collection or haircuts, there would be very little opportunity to do so in the case of a more continuous service relationship such as that experienced by an advertiser and his or her agency. That both scales examined in this study are equal in their ability to capture the concept of service quality should certainly not be perceived by advertising professionals as a shortcoming of either scale. Rather, it may provide additional support for the notion that either of the two instruments may be of use to them, as they both contribute substantially to explaining the observed variation in clients perceptions of service quality. Conclusions and directions for future research The somewhat unexpected finding of this study is that, in the case of the Australian advertising industry, SERVQUAL, despite a seemingly more rigorous process of scale development, performs no better than does SERVPERF, its often-cited alternative. Both perform almost identically in explaining about half of the observed variations in advertisers perceptions of their advertising agencies service quality. If, indeed, the characteristics of the advertising industry are such as to make such generic instruments as SERVQUAL or SERVPERF less effective, future research may be aimed at refining both, or either of them, in an attempt to provide the industry with a better means of predicting clients perceptions in relation to service quality. An alternative or complementary stream of research may aim to develop a better instrument from the ground up, using the type of systematic scale development process advocated by Churchill (1979). Perhaps more immediately needed are studies exploring the link between perceived service quality and client loyalty. If, for instance, it was found that an advertiser s decision to continue a relationship despite less-than-ideal service quality perceptions, can be influenced by other such factors as confidentiality concerns or switching costs, then refining a service quality measurement scale may not be so urgent a task for advertising practitioners or academic researchers in this area. THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

11 Finally, this study shows also that professional services present some context singularities that make them worthy of more focussed investigation. Future research therefore should include such services as those performed by consultants, lawyers or architects. References Advertising Agency Image Survey General Report (1993), AMR Quantum, Sydney, September. Berry, L.L and Parasuraman, A. (1993), Prescriptions for a service quality revolution in America, Organizational Dynamics, Vol. 37 No. 4, pp Bitner, M.J. (1990), Evaluating service encounters: the effects of physical surroundings and employee responses, Journal of Marketing, Vol. 54, pp Brown, S.W. and Swartz, T.A. (1989), A gap analysis of professional service quality, Journal of Marketing, Vol. 53, April, pp Carman, J.M. (1990), Consumer perceptions of service quality: an assessment of the SERVQUAL dimensions, Journal of Retailing, Vol. 66 No. 1, pp Castleberry, S.B. and. McIntyre, F.S (1993), Consumers quality evaluation process, Journal of Applied Business Research, Vol. 8 No. 3, pp Churchill, G.A. Jr ( 1979), A paradigm for developing better measures of marketing constructs, Journal of Marketing Research, Vol. 16, pp Cronin J.J. and Taylor, S.A. (1992), Measuring service quality: a re-examination and extension, Journal of Marketing, Vol. 56, July, pp Fox, C. (1994), Pressure grows as new clients dry up, The Australian Financial Review, Tuesday April 26, p. 45. Gujarati, D.N. (1988), Basic Econometrics, 2nd ed., McGraw-Hill Book Company, New York, NY. Harmon, H.H. (1976), Modern Factor Analysis, 3rd ed., The University of Chicago Press, Chicago, IL. Oliver, R.L. (1980), A cognitive model of the antecedents and consequences of satisfaction decisions, Journal of Marketing Research, Vol. 27, November, pp Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1985), A conceptual model of service quality and its implications for future research, Journal of Marketing, Vol. 49, Fall, pp Parasuraman, A., Zeithaml, V.A. and. Berry, L.L. (1988), SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality, Journal of Retailing, Vol. 64 No. 1, pp Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1994), Reassessment of expectations as a comparison standard in measuring service quality: implications for further research, Journal of Marketing, Vol. 58, January, pp Quester, P., Wilkinson, J. and Romaniuk, S. (1995), Measuring service quality: the case of the Australian advertising industry, Proceedings of the 7th Bi-Annual World Congress in Marketing, Melbourne, July. Rathmell, J.M. (1966), What is meant by services?, Journal of Marketing, Vol. 30, pp Shoebridge, N. (1993), The writing is on the billboard for ad agencies, Business Review Weekly, November 19, pp Teas, R.K. (1993), Expectations, performance evaluation, and consumers perceptions of quality, Journal of Marketing, Vol. 57, October, pp Theil,H. (1978), Introduction to Econometrics, Prentice-Hall, Edgewood Cliffs, NJ. Pascale Quester is a senior lecturer in the Department of Commerce at the University of Adelaide, South Australia and Simon Romaniuk is an honours student who graduated in 1994 and currently works as Product Manager for Unilever, Australia. Copies of the questionnaire used for this study are available on request from the Editor of JSM or the first-named author. 190 THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

12 This summary has been provided to allow managers and executives a rapid appreciation of the content of this article. Those with a particular interest in the topic covered may then read the article in toto to take advantage of the more comprehensive description of the research undertaken and its results to get the full benefit of the material present Executive summary and implications for the managers and executives How to measure a good advertising service It s pretty simple really, isn t it! To find out whether your ad agency is doing its job look at the results. Well, not exactly. After all, the agency is working to your brief, promoting your product at a price you set. And you control the distribution and manage the sales channels. In many cases today another agency even plans and buys the media. Looking at your sales chart might be a starting-point but alone it s rather unfair to the agency to base a judgment on this measure alone. Most clients don t base their assessment of the agency on sales performance alone. They use other means. Are the contact reports right and promptly produced? What s the billing process like? How often do the agency visit? How well do they present? Do they respond to challenges (crises?) well or do they panic? And lest we forget, how good is the hospitality on offer? As any agency account manager will tell you (when they stop tearing their hair out) some clients are more of a problem than others. There are clients who insist on seeing every last little element in the campaign; who constantly nit-pick; who change their minds at the last moment; who agree an estimate and then quibble about the bill. And there are the dream clients who don t demand constant attention; don t expect lunch at a posh restaurant every time they visit; and thank you for all the efforts you ve put in to an ultimately successful campaign. In the environment, measuring service quality is never objective. When you only have 20 or so customers the difference in their attitudes exaggerates the variations in quality. When asked, one client will describe the service in glowing terms. Another often served by the same account team thinks the agency is an incompetent shower unfit for the account. You don t know who is right. All you can try to do is improve the service to the grumbling client and keep up with the good client. The danger is that you over-service the troublesome client to no real benefit and upset the nice client by spending less time on the account. Quester and Romaniuk compare two measures of service quality SERVQUAL and SERVPERF finding that the latter (and less well known) performs best; all well and good. Let s get out there and measure. But can one view from one individual at a firm define the service relationship? If you ask the marketing director (whose day-to-day involvement amounts to a bimonthly lunch with the agency s client services director) you ll get one view. If you speak to the ordinary marketing executives struggling to produce the advertising from a confusing and contradictory brief you ll get a second, and perhaps, very different opinion. While standardized means of measuring quality are welcome they need putting into context. It s good to have further confirmation that the SERVQUAL measure doesn t quite fulfill its original promise. And we can welcome the assessment of SERVPERF alongside SERVQUAL. But in the end we have to be sure that applying either method to one agency and one set of clients provides us with information on which we can act. If not we are better relying on less scientific approaches to measuring our quality. On the face of it SERVQUAL seems entirely logical. You find out what people expected and then establish the gap (positive and negative) between expectations and the actual service received. Most managers can buy that THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO

13 concept and see how it can be applied. Yet academic researchers persist in suggesting the system doesn t explain quality differences. For the ad agency, manager perceptions and outcomes are only part of the story. We know that clients expect a certain minimum level of service. They expect the contact report from a meeting by return of post. They want the ad produced on time (even when they muck about with the schedule). And they want the agency to keep in touch as the campaign develops. Using some wondrous model developed by academics is great if we ve the time and money. But most of the time the agency manager is chasing his tail trying to keep clients happy. It may prove that approaches like SERVQUAL or SERVPERF make sense when applied to whole industries. If such a study shows (as I suspect it would) that clients think ad agencies give pretty lousy service then that provides a benchmark on which agencies can improve. What I doubt is whether, given the individual and idiosyncratic nature of agency-client relationships, there is any standardized system that can do justice to the problem of agency service quality. Those who propose standard measures should take care not to over-promote them. They have their value and Quester and Romaniuk confirm this but must work with measures of specific operations performed. Knowing on which broad area to focus is good, but not as easy to make use of as knowing that improving how the phone is answered or providing more detailed invoices will improve client perceptions of our service quality. (A précis of the article Service quality in the Australian advertising industry: a methodological study. Supplied by Marketing Consultants for MCB University Press) 192 THE JOURNAL OF SERVICES MARKETING, VOL. 11 NO