Customer Satisfaction Research Paper

1. Two Views Of Satisfaction

Customer satisfaction research has developed around two different types of evaluations: transaction-specific satisfaction and cumulative satisfaction. Transaction-specific satisfaction is a customer’s evaluation of their experience with and reactions to a particular product transaction, episode, or service encounter. Early transaction-specific satisfaction research explored the cognitive-psychological antecedents of satisfaction, while more recent research has focused on the effects of positive and negative emotions on satisfaction (Oliver 1997).

Since the early 1990s, satisfaction research has grown to include an emphasis on cumulative satisfaction, defined as a customer’s overall experience with a product or service provider to date. This definition is more consistent with those in economic psychology and welfare economics, where customer satisfaction is synonymous with the concept of consumption utility. It is cumulative satisfaction upon which the prominent national satisfaction, indices, such as the American Customer Satisfaction Index (ACSI; Fornell et al. 1996), are built.

These two streams of satisfaction research are complementary rather than competing. Transaction-specific research focuses on satisfaction with a product or service on a given occasion or transaction, or over a limited period of time. In cumulative satisfaction studies, the period of evaluation is left open. In the ACSI survey, for example, customers consider all of their experiences to date when evaluating their satisfaction with a product or service. The distinction is important as it affects how one views and models the evaluations. Whereas transaction-specific models pro-vide a rich understanding of the dynamics of product and service encounters or episodes, cumulative satisfaction provides a stable basis for determining the drivers of satisfaction and its consequences (customer retention and subsequent economic performance).

1.1 Transaction-Specific Customer Satisfaction

Oliver’s extensive contributions to satisfaction re-search over the past 20-plus years illustrate how transaction-specific research has evolved over time (see Oliver 1997). Oliver posited that customers form preconsumption expectations, observe product performance, compare this performance with expectations, and then combine this information with expectation levels to judge satisfaction. When performance exceeds expectations (positive disconfirmation), satisfaction increases. When performance falls below expectations (negative disconfirmation), satisfaction decreases. The disconfirmation of expectations model has dominated the literature for years; a simple version of it is presented in Fig. 1. The direct effect of expectations on satisfaction is the result of a framing or assimilation effect; the expectations establish a baseline or anchor that directly influences the resulting satisfaction judgments. Thus attribute performance, expectations of performance, and dis-confirmation of expectations may all have direct effects on evaluations of satisfaction.

The disconfirmation model has been augmented over the years to include the effects of equity, attribution, and emotions on satisfaction evaluations. The concept of reciprocity, and more specifically customer perceptions of equity and fairness, lies at the heart of marketing as an exchange process. Thus customers should be more satisfied when they are treated more fairly or equitably in a transaction, especially when there is a prospect for future trans-actions with the same party. Oliver and Swan (1989) posited and showed that equity is an important driver of satisfaction. Attribution theory has also been used to explain transaction-specific satisfaction from a cognitive perspective. The attribution of favorable outcomes to oneself and unfavorable outcomes to others systematically affects perceptions of performance and satisfaction (Folkes 1990).

However, Westbrook, Oliver, and others have recognized that these more cognitive perspectives on transaction-specific satisfaction do not completely capture the more affective basis of satisfaction (Oliver 1997, Westbrook and Oliver 1991). Customers form both positive and negative affective states that systematically influence satisfaction. For example, on the positive side there is joy and interest, and on the negative side is anger, disgust, and contempt, which affect satisfaction as expected.

1.2 Cumulative Customer Satisfaction

Cumulative satisfaction gained momentum with the advent of national customer satisfaction indices. Johnson and Fornell (1991) speak specifically to the problem of constructing broad-based satisfaction measures. They argue that cumulative satisfaction, as an overall evaluation of the consumption experience, should be viewed as a theoretical or latent variable (similar to an attitude). As a latent variable, satisfaction can be empirically measured and meaning-fully compared as a weighted-average or index of satisfaction indicators.

The ACSI model exemplifies the measurement and modeling of cumulative customer satisfaction. The model is presented in Fig. 2 (see Fornell et al. 1996). There are three main drivers of satisfaction in the model: quality, value, and customer expectations. Satisfaction, in turn, should reduce the incidence of complaints and increase customer loyalty. Most of the survey questions are rated on 1 to 10-point scales and the measurement variables are specified as reflective indicators of the latent or abstract constructs (circles) in the model.

Of particular interest is the overall satisfaction index, which is a weighted average of three survey ratings: (a) an overall rating of satisfaction, (b) the degree to which performance falls short of or exceeds expectations, and (c) a rating of overall performance relative to the customer’s ideal good or service in the category. The three measures provide a highly reliable and stable index of satisfaction. Notice that factors that may be conceptually and empirically distinct drivers of satisfaction in a transaction-specific satisfaction model become multiple measures of a more overall evaluation in a cumulative satisfaction model. Consider the differential role that disconfirmation plays in transaction-specific vs. cumulative satisfaction research. From transaction to transaction or episode to episode, one would expect some variation between performance and expectations. Service providers have a particularly difficult job of conforming to specifications on any given occasion. When these trans-actions or episodes are accumulated and evaluated over time, they become easier to predict. Thus significant disconfirmation, when it occurs, is more likely when studying a particular transaction or episode than when studying consumption experience to date. Be-cause cumulative satisfaction is a more overall or molar-level evaluation, disconfirmation of expectations is one of several valuable proxies by which customers evaluate their overall experience.

Cumulative satisfaction is systematically related to various financial and business performance measures. Research using the national indices demonstrates the positive impact that cumulative satisfaction has on both market value and accounting returns (Fornell et al. 1996). It is no wonder that customer satisfaction has become an important part of companies’ overall accounting, stakeholder management, and business performance measures. Cumulative satisfaction re-search has also explored the nature of customer expectations and how satisfaction varies across industries. For example, whereas price expectations tend to be more rational, performance expectations are more adaptive; they do not adjust as quickly to changes in performance. Fornell et al. (1996) report that satisfaction is highest among goods industries, lower among services, and lower still among public and government agencies.

2. Methodological Issues

In customer satisfaction modeling, satisfaction plays a key role in linking customer perceptions of a product’s price and quality with customers’ behavioral intentions and subsequent behaviors. Companies use two essential outputs of a satisfaction model to set priorities for improvement. First, how well do pro-ducts and services perform on their attributes, the benefits they provide, and the customer satisfaction and loyalty that results? Second, what impacts do the attributes and benefits have on satisfaction and sub-sequent loyalty? That is, how important are the attributes and benefits to customers? This performance and importance information is combined to set priorities for improvement. From a cost–benefit stand-point, the essential benefits to improve are those where importance or impact is relatively high and performance is relatively low.

As latent variables, performance levels on abstract benefits (such as the ‘cleanliness’ or ‘convenience’ of a retail store) and overall satisfaction can be constructed using weighted averages or indices of more concrete attributes or proxies. There is a debate, however, as to how to determine attribute and benefit importance measures. Many satisfaction measurement systems rely heavily on customers’ direct ratings of importance. The primary advantage of direct importance ratings is that they are easy to collect and analyze. Yet direct measures assume that customers understand what is meant by ‘important,’ just what attributes are important to them and that they are willing to tell you. As a result, direct importance measures often result in socially acceptable or status quo answers and poor discrimination. More objective estimates of importance or impact can be obtained using statistical estimation. This statistical estimation must accommodate the fact that a satisfaction model is a network of cause and effect relationships (which predicts a pattern of relationships) that contains latent (abstract) variables. Partial least squares (PLS) and principal-components regression (PCR) are particularly well suited to estimating a satisfaction model and deriving importance measures (see Johnson and Gustafsson 2000).

3. Future Research

Transaction-specific satisfaction research recognizes that customers may have very complex psychological reactions to a product’s performance on a given occasion or over a given time period. Cumulative satisfaction recognizes that, when forming intentions or making decisions regarding their behavior, customers rely on their entire experience to date with a product or service provider. Yet there has been little in the way of an integration of these two perspectives. Going forward, it will be important to better under-stand just how satisfaction-related constructs and their relationships change when customers move from transaction to cumulative-based evaluations. There is also a need to better understand the psychological and behavioral consequences of satisfaction, specifically customer loyalty (an intention) and retention (a behavior).

Company or brand image (reputation) and relation-ship commitment (involvement or strength), when combined with overall satisfaction, should explain much greater variation in loyalty and retention than does satisfaction alone. Finally, research in the quality improvement and product development areas must strive to ‘bridge the gap’ between internal (organizational) quality measures and processes and external (customer) perceptions of quality and satisfaction. It is not sufficient to simply understand what attributes and benefits drive satisfaction. Companies must understand how to break customer satisfaction down into its means of accomplishment within an organization.

Bibliography:

1. Folkes V S 1990 Conflict in the marketplace: Explaining why products fail. In: Graham S, Folkes V S (eds.) Attribution Theory: Applications to Achievement, Mental Health, and Interpersonal Conflict. Erlbaum, Hillsdale, NJ, pp. 143–60
2. Fornell C, Johnson M D, Anderson E W, Cha J, Bryant B E 1996 The American Customer Satisfaction Index: Nature, purpose and findings. Journal of Marketing 60: 7–18
3. Johnson M D, Fornell C 1991 A framework for comparing customer satisfaction across individuals and product categories. Journal of Economic Psychology 12: 267–86
4. Johnson M D, Gustafsson A 2000 Improving Customer Satisfaction, Loyalty and Profit: An Integrated Measurement and Management System. Jossey-Bass, San Francisco
5. Olander F 1977 Can consumer dissatisfaction and complaints guide public consumer policy? Journal of Consumer Policy 1: 124–37
6. Oliver R L 1997 Satisfaction: A Behavioral Perspective on the Consumer. McGraw-Hill, New York
7. Oliver R L, Swan J E 1989 Equity and disconfirmation perceptions as influences on merchant and product satisfaction. Journal of Consumer Research 16: 372–83
8. Westbrook R A, Oliver R L 1991 The dimensionality of consumption emotion patterns and consumer satisfaction. Journal of Consumer Research 18: 84–91
9. Yi Y 1991 A critical review of customer satisfaction. In: Zeithaml V (ed.) Review of Marketing 1990. American Marketing Association, Chicago, pp. 68–123