An examination of the effect of product performance on brand reputation, satisfaction and loyalty
Selnes, FredEuropean Journal of Marketing; 1993; 27, 9; ABI/INFORM Research pg. 19
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An Examination of the
Effect of Product Performance
on Brand Reputation,
Satisfaction and Loyalty
Fred Selnes
Norwegian Institute for Research in Marketing, Norwegian School of Management, Oslo
Introduction
Many companies have recently developed defence strategies for retaining customer accounts through quality products and services, both in business and consumer markets[l ]. Many large companies have also developed measurement programmes where customers evaluate quality of products and services. Customer satisfaction has become one of the pillars in the work on total quality management[2]. In parallel with the development in quality, researchers and managers have become interested in strong brand names which has driven companies to reconsider the importance of established brands[3]. The motivation for the increased emphasis on brand names and quality is that they both have a strong effect on customer loyalty[4].
A brand has been defined as a distinguishing name or symbol intended to identify both goods and services[3, p. 7]. SAS, Citibank, McKinsey and others, are several examples of strong brands in typical service companies. There is also a growing number of companies such as IBM, Toyota and ABB, which sell combinations of physical products and services. Even though brand names are important for service companies, the empirical published studies of brand names[5] appear to have focused on consumer products only and neglected services. Similarly, most research on quality of services has focused on customer satisfaction and paid little attention to brand replitation[6-13]. If then, as argued in this article, loyalty is also driven by strong brand names, remedies other than quality improvements may also be appropriate. Brand reputation can, for example, be managed to adjust expectations in line with the disconfirmation of expectation paradigm (i.e. [14,15]).
The objective of this research is to explore the relationship between satisfaction, brand reputation and loyalty. It is suggested that both customer satisfaction and brand reputation are important antecedents of intended loyalty. Although both brand reputation and satisfaction have been found to affect loyalty separately, very little is known about the interaction effect. Under what conditions should the company be particularly concerned about their brand's reputation? It is the ambition of this article to provide theoretical insight and practical advice as to how loyalty may be improved through working on ''internal''
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Received January 1993 Revised May 1993European Journal of Marketing, Vol. 'l:I No. 9. 1993, pp. 19-35. © MCB University Press. 0309-0566
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---quality improvements on the one hand, and the more traditional ''external'' marketing-mix variables on the other hand.
After presenting the theory and hypotheses, research methods and results are described. Findings are then discussed and their implications for management and future research are explored.
Theory and Hypotheses
Brand Repu,taJion
It has been debated whether brand reputation and customer satisfaction are the same constructs[16]. The more dominant view in the literature appears to be that attitude towards the brand (i.e. reputation) or service provider, is a more long-run and overall evaluation than the satisfaction construct[6,7,17} Brand reputation has been defined as a perception of quality associated with the name[18]. A key function of a brand is that it facilitates choice when intrinsic cues or attributes are difficult or impossible to employ[19,20]. Intrinsic cues involve the physical or technical composition of a product. Brand name has been defined as an extrinsic cue, that is, as an attribute related to the product but not part of the physical product itself. A brand will thus have a perception of overall quality not necessarily based on knowledge of detailed (intrinsic) specifications associated with it[3, p. 19].
Zeithaml[21] and Shapiro[22] suggest that the perceived quality of a product or service is related to the reputation associated with the brand name. In some situations, customers will only associate one product or one service with the brand (i.e. Pepsi, Avis, Federal Express, McKinsey, etc.), and thus the brand reputation is only measurable at the product level. In other situations, customers identify a bundle of products and services with a brand name (i.e. Philips, IBM, Citibank, etc.). The major point is that brand reputation is not necessarily limited to a focal product or service. In services and business-to-business industries, the brand appears to be more often connected to the reputation of the company rather than individual products or services.
Product Performance
Products and services are, for several reasons, often acquired based on an evaluation of extrinsic cues only (i.e. brand name, price, package)[21 ]. One reason suggested, is that intrinsic cues are not available at the time of purchase. A second reason may be that evaluation of intrinsic cues requires more effort and time than is perceived as worthwhile. And, finally, intrinsic cues may not be used because quality is difficult to evaluate. The first opportunity to judge the intrinsic qualities of the service, is often at the point where the product is consumed. In some cases, for example, in insurance, the intrinsic qualities are only revealed when a "damage" occurs. Although the consumption experience gives the customer an opportunity to inspect intrinsic qualities of the product or service, this does not mean that all elements will, or may be, evaluated. The consumption experience will, however, usually reveal several qualities of the product or service which were not salient at the moment of purchase or acquisition.
In order to evaluate performance of a product or service, customers need some kind of norm for what is good or acceptable. The brand name may create certain expectations in that direction[lS]. There is, however, very little theoretical reason to believe that customers use focal brand expectations to judge performance after purchase. Customers are, therefore, very likely to use other kinds bf performance standards in the post-purchase evaluation[23]. Cronin and
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fit of the theoretical model than using expectation measures. Customers may -thus employ other standards of comparison in forming disconfirmation and
satisfaction feelings. Cadotte et al. [11] suggest two different norms customers may use as the "ideal" for comparison. First, the norm might be the typical performance of a particular brand such as the most preferred, the last purchased, the most popular, or other. A second possibility is that the norm might be an average performance which a customer believes is typical for a group of similar brands within a product category, thus a product-norm. Experience with and knowledge of the product class or related products may, therefore, be an important determinant of how customers judge product or service performance.
Customer Satisfaction
Customer satisfaction has been defined in various ways, but the conceptualization which appears to have achieved the widest acceptance, is that satisfaction is a post-choice evaluative judgement of a specific transaction[ 6,17]. Fomell[l] suggests that satisfaction can be assessed directly as an overall feeling. In addition, he suggests that customers have an idea about how the product or service compares with an ''ideal'' norm. Thus a person may be satisfied with the focal product or service and at the same time evaluate the performance as mediocre, compared with what it should or could have been.
Customer Loyalty
Customer loyalty expresses an intended behaviour related to the product or service. This includes the likelihood of future purchases or renewal of service contracts or, conversely, how likely it is that the customer will switch to another brand or service provider[3]. Customers may be loyal owing to high switching barriers related to technical, economical or psychological factors, which make it costly or difficult for the customer to change supplier. Customers may also be loyal because they are satisfied with the supplier or product brand, and thus want to continue the relationship. As most barriers appear to be of limited durability, companies tend to approach satisfaction as the only viable strategy in the long run [1].
Another important element of loyalty is the intended support of the product expressed in communicating one's experiences, that is positive of-mouth[24]. One of the most powerful sources in persuasion is personal word-of-mouth. When a company's customers recommend the product to others, this reflects a high degree of loyalty.
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---Performance and Satisfaction
The expected positive relationship between performance quality and customer satisfaction is in line with the Rational Expectation Theory (i.e. [16]) and well documented in several studies such as Fomell[l] and Cronin and Taylor[6]. Fomell[l] found, in a survey of Swedish customers, a correlation between perceived quality (performance) and satisfaction, in the range between 0.43 (gas companies) to 0.79 (property insurance). Cronin and Taylor[6] found strong and positive casual paths between overall service quality and satisfaction, in a study of four industries (banks, pest control, dry cleaning and fast food). These results suggest the following relationship:
HJ: Performance quality will have a positive effect on satisfaction.
Performance and Brand Reputation
Brand reputation was defined earlier as a perception of quality associated with the brand[18]. Attitude research has found that attitudes increase in predictive value as they become more accessible in memory[25,26]. Direct experience has a strong impact on brand reputation because the attitude is more accessible. The accessibility is a function of frequency of interaction or use with a product or service. Thus consumption will make attitudes more accessible and, hence, make the brand reputation more directive for future behaviour.
An attitude is generally defined as an overall evaluation of an object based on a sum of belief expectations on a set of attributes[27]. As experienced performance gives the person more information on this set of attributes, attitude should by definition, be affected. In addition, the experience of consuming may reveal new attributes which were not salient or important earlier. Oliver[l5] suggested that attitude towards a product is a function of initial attitude at the time of purchase, and satisfaction with the transaction. It is, therefore, important to distinguish brand reputation at the point of purchase and attitudes at later stages in the post-purchase process.
Performance quality is thus, in addition to the effect on satisfaction (HJ),
expected to affect a global and more general evaluation of the brand. The perception of quality associated with the brand is either reinforced or strengthened when the customer experiences high quality performance, or disconfirmed when the customer experiences poor quality[4]. Products or services perceived as inferior, will thus have a negative effect on the perceived global quality of the brand.
H2: Performance quality will have a positive effect on brand reputation.
Satisfaction Brand Reputation and Loyalty
It has been earlier argued that satisfaction (an attitude towards the transaction), and brand reputation are related but different constructs. They both, however, are expected to affect future behaviour or customer loyalty[15]. The relationship between satisfaction and loyalty has been observed in several studies. Fomell[l] examined 27 different businesses and found strong correlations between satisfaction and loyalty in the range of 0.17 (department stores) to 0.66 (television
Ill
broadcasting). Cronin and Taylor[6] examined four businesses and found strong correlations between satisfaction and loyalty in the range from 0.36 (fast food) to 0.837 (dry cleaning).
However, the relationship between satisfaction and loyalty is expected to be dependent on the characteristics of the focal products or services. The studies reported above did not control for brand reputation (or a similar global evaluation
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of the brand). Thus, the observed effect between satisfaction and loyalty may
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be due to a third variable (brand reputation). The ambiguity in the intrinsic -quality of the product or service is expected to work as a moderator on theeffect between satisfaction and loyalty[19,20].
When consumers have access to unambiguous product information, judgements are to a large extent determined by objective physical evidence. Only when the evidence is ambiguous is brand found to have a dramatic effect on perceptions of quality[20]. Thus the ambiguity in the quality of the core product may affect the importance of building a strong brand reputation. When, however, customers are able to have the opportunity to evaluate the quality of the delivered service or product, satisfaction is expected to have an effect on loyalties. Customers have better information on the intrinsic cues and are thus better able to judge the quality of the products or services. A telephone subscriber will, for example, easily observe when the service is not functioning as it should. In situations where the customers, for various reasons, lack this opportunity, satisfaction with product performance will have less, if any, effect on loyalty because the customer is unable to appreciate the value of the core product or service. In these situations the reputation of the brand is expected to operate as an indicator of core product's quality, and thus loyalty is expected to be driven by brand reputation.
H3: Ambiguity in the intrinsic cues of the experienced performance will
moderate the effect of satisfaction on loyalty.
Oliver[15] suggested a casual path from satisfaction to post-experience attitude (i.e. reputation). Oliver's argument is that the post-experience attitude is a result of a cognitive comparison conducted between the anticipated satisfaction (represented by a pre-experience attitude) and the received satisfaction. This is in effect a disconfirmation at the more abstract effect level, rather than the more objective attribute level. Oliver[15] found a significant path from satisfaction to post-experience attitude towards the product. A limitation of this study is that the measure of attitude is related to the specific product (sum of beliefs on attributes) and not to the brand. The focal product was a federal influenza shot programme and thus not a commercial company with a brand name. With respect to a branded product (or service) the following relationship is expected:
H4: Satisfaction will have a positive effect on brand reputation.
Attitudes are of specific interest to social scientists because they often are important determinants of future behaviour[27]. Researchers in marketing have long debated the definition of brand loyalty, but there is consensus regarding the strong effect of brand reputation on loyalty[5]. Thus, brand reputation is expected to be an important determinant of loyalty.
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Figure 1. A Theoretical Model for the Relationship between Quality, Customer Satisfaction, Brand Reputation and Intended LoyaltyH5: Brand reputation will have a positive effect on loyalty.
On the basis of the preceding discussion, Figure 1 represents a general model of the constructs and their relationship to be tested.
Method
Overview
Data were collected from four different companies. The objective was to collect a set of companies from businesses expected to be different with respect to the ambiguity of the intrinsic cues in the product of service. Life insurance is a business where customers are expected to lack the ability to evaluate the quality of the core product. First, customers' knowledge of insurance products are generally low[28]. Second, the quality of an insurance product is often first evidenced when the conditions in the agreement come into operation (age, injury, death, etc.). Contrary to life insurance, the quality of telephone services is expected to be more easily observable. The third business included is a business college where we expect the quality of the teaching within the school to be quite unambiguous to the students. Students have numerous experiences with the performance of the college and are probably well capable of judging the quality of the delivered product. The fourth business included was a salmon feed supplier. The customers of the salmon feed supplier have limited opportunity to evaluate the effect of a premium food product. The health and growth of farmed salmon is, to a large extent, determined by other factors than the feed, such as water temperature and viruses. In order to isolate the effect of different feed products the farmers would need to conduct controlled experiments. Such experiments are carried out by the competing suppliers, and thus the farmers must trust the results presented to them.
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The selection of businesses also balance business customers and private customers. The salmon feed supplier and the telephone services serve business customers; and the insurance company and the business college private customers.
It was sought, also, to balance the companies' distance to their customers. The salmon feed supplier operates in a market with relatively few customers, whereas the telephone company operates within a mass market and thus with a more distant interaction with its customers. A similar type of difference exists between the business college and the insurance company, where the former has a high degree of personal interaction with its customers. A description of the samples is provided in Table I.
Measures
The measures employed in the four studies are shown in Table II. The measures needed for the study were perception of performance quality, brand reputation, satisfaction and loyalty. Performance quality was assessed with three indicators reflecting various aspects of the service. In order to secure a subjective norm[29], respondents were asked to express their degree of satisfaction on a set of performance issues. One could argue that the word ''satisfaction'' may cause the performance construct to be confounded with the satisfaction construct. Because the satisfaction measures address the overall and global satisfaction with the transaction, and the performance measures address elements of the transaction, they are expected to tap different constructs. The three indicators of performance quality were chosen from a larger set based on their high loadings on the first factor in a principal component analysis.
Customer satisfaction was measured with three indicators. Overall satisfaction was measured before and after the performance evaluations. Thus, the first measure is a kind of "unaided" recall, and the second is a form of "aided"
Life insurance Telephone company College sample3 Salmon feed supplier Sample Random sample of consumer customers with life insurance Random sample of business customers from major city Random sample of college students in one-year full-time programme Population of business customers Length
Method (minutes) Responses
Telephone with 20 187 two call-backs Telephone with 30 395 two call-backs Mail questionnaire 30 325 Telephone with 15 125 four call-backs
a The customers (students) were measured at the end of a one-year full-time programme in business administration. Students had the option to continue studies at the same college in a two-year programme, as the college provides a 1+2 year programme.
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Table I. Description of Sampling Procedure. An Additional Number of Questions of Interest to the Companies was Addressed in Each SurveyEuropean
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Table II. The Measures Employed in the Four Samples Performance qualityPQl: How satisfied are you with ... (element l)? PQ2: How satisfied are you with ... (element 2)? PQ3: How satisfied are you with ... (element 3)?
Each item in the scales contained questions with six intervals anchored "Very little satisfied" to "Very satisfied"
Loyalty
LI: How likely is it that you will buy products/services from XYZ in the future? In the business college setting, we asked: If you were to continue studies in business administration, how likely is it that you would continue the studies at XYZ?
L2: If another person asked your advice, how likely is it that you would recommend XYZ? The six-point scale went from 0 to 100 per cent with 20 per cent intervals, thus, the interval points were labelled 0 per cent, 20 per cent, 40 per cent, 60 per cent, 80 per cent and 100 per cent.
Customer satisfaction
Cl and C2: What is your overall satisfaction with company XYZ?
Cl and C2 were measured on a ten-point scale anchored with "Very little satisfied" and "Very much satisfied", and each interval point were labelled 1 through 6 C3: On a scale from 1 to 10, how close do you think XYZ is delivering product/services of an optimal company? (1 = XYZ is far from the perfect; 10 = XYZ is perfect)
Brand reputation
Bl: What reputation has XX among your collegues/friends and family? B2: How do you rate XX's reputation compared to their competitors?
Bl and B2 were anchored "Very negative" to "Very positive" on a six-point scale Bl was related to colleagues in business samples and family and friends in consumer samples
recall after the respondent has thought through his or her relationship with the company. The third indicator is an evaluation of the company's distance from an ideal product or service provider[!]. Behavioural intention or loyalty was measured with two indicators. The first indicator was the likelihood that the customer will continue the relationship with the vendor[l]. The second item addressed the degree to which respondents would recommend their supplier to others, creating positive word-of-mouth[24].
Brand reputation was assessed with two indicators reflecting the company's overall reputation[21,22]. The first item assessed the absolute level of reputation (positive-negative). The second item addressed the relative reputation as compared with competitors.
The mean, standard deviation, skewness and kurtosis for the ten measures in each of the four samples are shown in Appendix 1. It is observed that a large proportion of the measures are negatively skewed, thus the distribution is more dense at the higher values. The kurtosis measures indicate that most of the measures have distributions, with fatter tails than normal. Overall, these measures are fairly close to normal distributions, and the small deviations should not affect the consistency of the estimators[30, p. 418].
The four correlation matrixes are reported in Appendix 2. In order to assess construct validity a maximum likelihood LISREL VII was used[31 ]. The approach suggested by Anderson and Gerbing[32] was employed in order to assess
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convergent and discriminant validity. Convergent validity is expected when each indicator's estimated pattern coefficient on its posited underlying construct factor is significant. Table III reports the standardized coefficients for the ten indicators, and t-values for the free estimators. As can be seen they are all high and significant.
Discriminant validity can be assessed for two estimated constructs by constraining the estimated correlation parameter (phi) between them to 1.0 and then performing a
x
2 difference test on the values obtained for theconstrained and unconstrained models. A significantly lower
x
2 value for the model in which the trait correlations are not constrained to unity, would indicate that the traits are not perfectly correlated and that discriminant validity is achieved. Anderson and Gerbing[32] recommend that the test should be performed for one pair of factors at a time. Thex
2 values for each pair offactors is reported in Table IV. All
x
2 differences are significant at the 0.001 level except for brand reputation with satisfaction and brand reputation with loyalty in the insurance sample. The difference in the latter is significant at 10 per cent and 15 per cent. The indicators of satisfaction, loyalty and brand reputation in the insurance data could thus tap the same construct. In order to rule out this possibility the x2 difference was estimated between a one anda three factor solution to the seven items. The
x
2 dropped 15.57 (from 44.82to 29.25) with three degrees of freedom. This difference is clearly significant
<.p = 0.002), and thus, three factors give a better fit to the data than one factor. Thus the tests performed indicate that both convergent and discriminant validity was achieved.
Salmon Telephone College Insurance
bl 0.82 0.77 0.72 0.60 b2 0.86 0.76 0.74 0.71 (t= 9.43) (t= 13.99) (!=8.15) (t= 7.59) cl 0.30 0.63 0.75 0.61 c2 0.74 0.85 0.62 0.87 (t=2.88) (t= 12.83) (t= 10.44) (t=8.70) c3 0.76 0.81 0.82 0.79 (t=2.88) (t= 12.51) (t= 13.35) (t= 8.27) 11 0.87 0.80 0.73 0.52 12 0.69 0.73 0.84 0.91 (t=5.08) (t= 11.41) (t=ll.54) (t= 6.29) ql 0.76 0.51 0.76 0.73 q2 0.64 0.61 0.70 0.83 (t=6.52) (t=8.14) (t=ll.22) (t= 10.80) q3 0.75 0.63 0.52 0.88 (t= 7.53) (t= 8.25) (t= 8.43) (t= 11.30)
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Table III. Estimated Standardized Loadings of Each Indicator on Respective Factor. T -Values are Provided for the Free ElementsEuropean
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Table IV. Estimated X2 Values in Test of Discriminant ValiditySalmon Telephone College Insurance
Quality and satisfaction
One factor 35.41 36.35 25.15 94.63
Two factor 12.45 21.57 11.3 42.14
Difference 22.96 14.78 13.85 52.49
Quality and brand reputation
One factor 22.06 8.29 67.53 9.42
Two factor 2.13 3.09 10.48 1.15
Difference 19.93 5.2 57.05 8.27
Satisfaction and brand reputation
One factor 34.43 32.18 66.94 10.36
Two factor 7.3 1.87 1.69 7.75
Difference 27.13 30.31 65.25 2.61
Loyalty and satisfaction
One factor 44.3 68.6 44.3 12.00
Two factor 9.03 4.7 0.44 4.9
Difference 35.27 63.9 43.86 7.1
Loyalty and brand reputation
One factor 34.4 56.8 54.2 6.4
Two factor 0.1 0.1 0.1 4.7
Difference 34.3 56.7 54.1 1. 7
Loyalty and quality
One factor 38.5 42. 69. 41.1
Two factor 2.2 4.9 4.8 23.2
Difference 36.3 37.1 64.2 17.9
Differences above 10.8 are significant at the 0.001 level. Differences larger than 2. 7 are significant at 0.10 with 1 d.f. The corresponding critical values for 5 per cent and 1 per cent are 3.84 and 6.63 respectively (d.f. = 1)
Results
Maximum likelihood LISREL VII[31] was used to examine the overall adequacy of the theoretical model and to test the hypothesized relationships of interest
(Hl-H5). The operationalized model is shown in Figure 2.
The four estimated models are shown in Table V. The measurement model was standardsized by fixing the values of Cl, Ll, Bland PQl to 1.0[31]. The results from the test of the model were encouraging. The
x
2 test with 30 degrees of freedom for overall model fit were all non-significant, except for the insurance sample. In the latter case thex2
value was quite high, and a substantial proportion of this can probably be attributed to the poor fit of the satisfaction, brand reputation and loyalty measures (see above). In the insurance model, adjusted goodness of fit was 0.831 and the root mean square error was 0.048, which both indicate a moderately good fit.11
Key:
q 1-q3: Performance quality measures b1 -b2: Brand reputation measures c1 -c3: Customer satisfaction measures I 1 -I 2 : Loyalty measures
GA (1, 1 ): Effect of performance quality on brand reputation Salmon Q->B 0.67 GA(l,l) ... (t=4.21) Q->S 0.68 GA(2,1) ... (t=2.71) S->B 0.18 BE(l,2) ... (t= 1.13) B->L 0.50 BE(3,l) ... (t= 3.36) S->L 0.11 BE(3,2) ... (t=0.70) x?- (30) 40.37 P-value 0.098 AGF 0.897 RMSE 0.045 R2 eta 1 0.65 R2 eta 2 0.46 R2 eta 3 0.34
GA (2, 1 ): Effect of performance quality on customer satisfaction BA (1,2): Effect of customer satisfaction on
brand reputation
BA (3, 1 ): Effect of brand reputation on loyalty BA (3,2): Effect of customer satisfaction on loyalty
Telephone College Insurance
0.71 0.44 0.17 (t= 3. 72) (t=2.06) (t= 1.38) 0.83 0.86 0.78 (t= 7.26) (t= 10.10) (!=6.86) 0.24 0.17 0.77 (t= 1.49) (t=0.83) (!=4.58) 0.34 0.27 1.161 (t=2.43) (!=3.23) (t= 1. 78) 0.43 0.61 -0.30 (t=3.12) (t=6.98) (t= -0.50) 36.22 23.29 106.01 0.201 0.803 0.000 0.967 0.974 0.831 0.027 0.021 0.048 0.85 0.35 0.83 0.69 0.74 0.61 0.54 0.61 0.82
T-values above 2.57 are significant at the 0.001 level. Critical value at the 10 per cent level is 1.645 (given the large sample sizes)
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Figure 2. The Operationalized Model for the Relationship between Quality Performance, Customer Satisfaction, Brand Reputation and Intended LoyaltyTable V.
Estimated Parameters (Standardized) in the Four Models
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Performance quality had significant effects on customer satisfaction in all four models, and thus HJ was supported. Performance quality also affected brand reputations in three of the four models. In the insurance sample the coefficient was positive, but not significant. Thus H2 was partly supported.
The expected effect of satisfaction on loyalty, when the effect of brand reputation was controlled (H3), was, as expected, significant only in the two models with the least ambiguity in intrinsic cues of the product, that is the telephone and college models. Support in the salmon feed supplier and the - - - insurance models was not found. Thus H3 was supported.
The anticipated effect from satisfaction on brand reputation (H4) was only significant in the insurance model. The effect of quality on brand reputation appears to work through satisfaction for the insurance sample, whereas the effect from satisfaction to brand reputation is non-significant in the other samples. A possible explanation may be found in the difference in the variety of products associated with the brand. For the salmon feed supplier, the telephone company and the business college customers most likely associate only one line of products or services, whereas the insurance company is associated with a series of financial services, like damage insurances, pension insurances and so forth. Admittedly, this explanation is speculative and
post-hoe,
and the research design chosen can properly test this proposition.Perhaps most important, the casual path from brand reputation on loyalty was significant in all four models and thus H5 was supported. Loyalty is clearly driven by brand reputation in the companies examined.
Discussion
The major objective of this research was to investigate the effect of product quality on brand reputation, satisfaction and loyalty. Brand reputation was found to have a consistent and strong effect on loyalty in all four models tested. The effect of customer satisfaction on loyalty appears to be contingent on the context, and it is suggested that satisfaction will only have a direct effect on loyalty when customers are able to evaluate product quality through their experience with the product or service.
The strong empirical correlation between perceived quality and satisfaction, and in turn loyalty, found in several studies, could be biased, as these studies have not controlled for the effect of the brand. Perceived quality and reputation of the brand are theoretically different constructs and should, therefore, not be mixed together. The formation of a brand reputation is a different process than the creation of perceived quality, and the two constructs behave differently with respect to other variables. As they are correlated and are both expected to affect loyalty (however, by different mechanisms), they should both be included when factors driving satisfaction and loyalty are analysed.
Similarly, the strong positive relationship between brand reputation and loyalty, could be overestimated, as these have not been controlled for the effect of experienced quality and satisfaction. It follows, from the presented hypotheses, that the effect of quality on satisfaction will be substantially less when controlling for brand, and also that the effect between satisfaction and loyalty will be less when controlling for the effect of the brand reputation on loyalty.
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Managerial Implications
The presented study has several implications for management. The strategic role of brand name in creating loyalty is important not only for physical products, but also for services and combined product-service industries. One implication is that loyalty is not only driven by internal quality-improvements, but also by the more traditional external activities familiar to marketing managers (i.e. advertising, public relations, packaging, and so on).
Where customers have limited ability to evaluate product quality, brand reputation and not customer satisfaction, should be emphasized. In some industries, market segments could be defined on the basis of the customer's ability to evaluate quality or product-expertise. Thus in some segments loyalty may be driven through brand reputation, whereas in other segments loyalty may also be driven by customer satisfaction.
Another important managerial implication is related to what measures companies should monitor in their loyalty programmes. This study indicates that in addition to performance and satisfaction, companies should monitor brand reputation. The presented models varied in their ability to explain variations in loyalty from 34.6 per cent for the salmon feed supplier, to 81.5 per cent for the insurance company. Thus tracking experienced quality, brand-attitude and customer satisfaction should provide most companies with a substantial amount of diagnostic information.
Limitations and Future Research
Although the ambition of this article was to minimize limitations, a major limitation of the presented study is internal validity[33]. All data was collected from a cross-sectional study and thus other explanations could explain the relationship between the tested constructs. In the future, researchers should try to test models employing longitudinal data or experiments. Another limitation is that the data was collected from only four companies. The model should be tested out in more industries and on multiple companies within the same industry.
As the managerial implications of the findings in this study is quite substantial, future research is clearly warranted.
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Salmon feed Telephone Business
supplier services college Life insurance
Means bl 5.06 4.56 4.66 4.64 b2 5.15 4.26 4.22 4.65 cl 8.41 7.59 6.99 6.56 c2 8.42 7.24 5.35 6.88 c3 8.22 6.99 6.50 6.52 11 5.43 4.58 4.49 4.64 12 5.41 4.79 4.31 4.65 ql 4.99 4.97 4.28 4.64 q2 4.85 4.26 3.97 4.65 q3 5.15 3.88 4.19 4.17 Standard deviation bl 0.81 0.87 0.86 0.83 b2 0.76 1.04 1.05 0.92 cl 1.42 1.59 1.58 1.83 c2 1.08 1.38 1.94 1.57 c3 1.45 1.51 1.48 1.65 11 0.83 1.63 1.42 0.83 12 0.80 1.18 1.21 0.92 ql 0.66 0.77 0.71 0.82 q2 0.85 0.99 0.71 0.86 q3 0.80 0.87 0.85 0.87 Skewness bl -1.04 -0.40 -0.41 -0.44 b2 -0.96 -0.51 -0.32 -0.60 cl -1.32 -0.66 -0. 75 -0.30 c2 -0.21 -0.58 -0.25 -0.81 c3 -0.76 -0.59 -0.73 -0.62 11 -1.41 -0.67 -0.89 -0.44 12 -1.28 -1.03 -0.62 -0.59 ql -1.42 -0.97 -0.35 -0.46 q2 -1.44 -0.33 -0.46 -0.62 q3 -0.96 -0.31 -0.30 -0.64 (Continued)
The Effect of
Product
Performance
33
Appendix 1. Means, Standard Deviations, Skewness and Kurtosis for Indicators in the Four Data SetsEuropean
Salmon feed Telephone Business
Journal
of Marketing
supplier services college Life insurance27,9
Kurtosis bl 1.55 0.32 0.20 -0.09 b2 1.83 0.20 -0.12 0.6334
cl 3.56 1.03 0.67 0.30 c2 0.45 1.18 -0.19 1.12 c3 0.59 1.01 0.73 0.80 11 1.24 0.08 -0.18 -0.09 12 0.97 0.74 0.01 0.64 ql 3.13 1.77 0.21 0.08 q2 3.28 -0.15 0.75 0.24 Appendix 1. q3 0.67 0.30 -0.01 0.48 Continued bl b2 cl c2 c3 11 12 ql q2 q3 Salmon bl 1.00 b2 0.71 1.00 cl 0.18 0.22 1.00 c2 0.28 0.42 0.25 1.00 c3 0.43 0.44 0.16 0.58 1.00 11 0.52 0.34 0.16 0.32 0.26 1.00 12 0.40 0.28 0.12 0.21 0.17 0.60 1.00 ql 0.48 0.58 0.19 0.32 0.39 0.31 0.33 1.00 q2 0.39 0.42 0.21 0.27 0.33 0.29 0.29 0.50 1.00 q3 0.43 0.54 0.24 0.45 0.40 0.29 0.23 0.56 0.49 1.00 Telephone bl 1.00 b2 0.59 1.00 cl 0.39 0.39 1.00 c2 0.56 0.52 0.55 1.00 c3 0.52 0.52 0.49 0.68 1.00 11 0.42 0.41 0.35 0.46 0.50 1.00 12 0.39 0.39 0.31 0.41 0.43 0.58 1.00 ql 0.33 0.34 0.41 0.40 0.35 0.27 0.24 1.00 q2 0.42 0.44 0.33 0.39 0.39 0.31 0.32 0.32 1.00 Appendix 2. q3 0.45 0.43 0.31 0.44 0.41 0.38 0.32 0.26 0.42 1.00 Estimated CorrelationMatrixes for the Four
(Continued)
