TITLE

What You Don't Know About Customer-Perceived Quality: The Role of Customer Expectation Distribution

AUTHOR(S)
Rust, Roland T.; Inman, J. Jeffrey; Jia, Jianmin; Zahorik, Anthony
PUB. DATE
March 1999
SOURCE
Marketing Science;1999, Vol. 18 Issue 1, p77
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Abstract We show that some of the most common beliefs about customer-perceived quality are wrong. For example, 1) it is not necessary to exceed Customer expectations to increase preference, 2) receiving an expected level of bad service does not reduce preference, 3) rational customers may rationally choose an option with lower expected quality, even if all non-quality attributes are equal, and 4) paying more attention to loyal, experienced customers can sometimes be counterproductive. These surprising findings make sense in retrospect, once customer expectations are viewed as distributions, rather than simple point expectations. That is, each customer has a probability density function that describes the relative likelihood that a particular quality outcome will be experienced. Customers form these expectation distributions based on their cumulative experience with the good or service. A customer's cumulative expectation distribution may be conceptualized as being a predictive density for the next transaction.When combined with a diminishing returns (i.e., concave) utility function, this Bayesian theoretical framework results in predictions of: (a) how consumers will behave over time, and (b) how their perceptions and evaluations will change. In managerial terms, we conclude that customers consider not only expected quality, but also risk. This may help explain why current measures of customer satisfaction (which is highly related to expected quality) only partially predict future behavior. We find that most of the predictions of our theoretical model are borne out by empirical evidence from two experiments. Thus, we conclude that our approach provides a useful simplification of reality that successfully predicts many aspects of the dynamics of consumer response to quality.These findings are relevant to both academics and managers. Academics in the area of customer satisfaction and service quality need to be aware that it may be insufficient to measure only the ...
ACCESSION #
1987096

 

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