If service quality relates to retention of customers at the aggregate level, as other research has indicated, then evidence of its impact on customers’ behavioral responses should be detectable. Th...

The behavioral consequences of service quality

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

Considerable progress has been made in identifying market-driven businesses, understanding what they do, and measuring the bottom-line consequences of their orientation to their markets. The next c...

/pdf/the-capabilities-of-market-driven-organizations-152hbwt1bs.pdf

The capabilities of market-driven organizations

Are there economic benefits to improving customer satisfaction? Many firms that are frustrated in their efforts to improve quality and customer satisfaction are beginning to question the link betwe...

Customer satisfaction, market share, and profitability: Findings from Sweden.

Customer switching behavior damages market share and profitability of service firms yet has remained virtually unexplored in the marketing literature. The author reports results of a critical incid...

https://www.jstor.org/stable/pdfplus/1252074.pdf

Customer switching behavior in service industries: An exploratory study

Customer satisfaction, customer retention, and market share

Many companies have been disappointed by a lack of results from their quality efforts. The financial benefits of quality, which had been assumed as a matter of faith in the “religion of quality,” are now being seriously questioned by cost-cutting executives, who cite the highly publicized financial failures of some companies prominent in the quality movement. In this increasingly results-oriented environment, managers must now justify their quality improvement efforts financially. The authors present the “return on quality” approach, which is based on the assumptions that (1) quality is an investment, (2) quality efforts must be financially accountable, (3) it is possible to spend too much on quality, and (4) not all quality expenditures are equally valid. The authors then provide a managerial framework that can be used to guide quality improvement efforts. This framework has several attractive features, including ensured managerial relevance and financial accountability.

Return on quality (ROQ): Making service quality financially accountable

Return on quality (ROQ) : making service quality financially accountable : technical wooking paper

We show that some of the most common beliefs about customer-perceived quality are wrong For example, 1) it isnot 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 nonquality attributes are equal, and 4) paying more attention to loyal, experienced customers can sometimes be counter-productive 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 maybe conceptualized as being a predictive density for the next transaction When combined with a diminishing returns (ie, 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 point expectation, as has always been the standard practice Instead it may be necessary to measure the uncertainty that the customer has with respect to the level of service that will be received Due to questionnaire length constraints, it may not be practical for managers to include uncertainty questions on customer satisfaction surveys Nevertheless it is possible to build a proxy for uncertainty by measuring the extent of experience with the service/good, and this proxy can be used to partially control for uncertainty effects The findings of the study were obtained using 1) an analytical model of customer expectation updating, based on aset of assumptions that are well-supported in the academic literature, and 2) two behavioral experiments using human subjects: a cross-sectional experiment, and a longitudinal experiment Both the analytical model and the behavioral experiments were designed to investigate the effects that distributions of expectations might have, and especially the effects that might deviate from the predictions that would arise from a traditional point expectation model The behavioral experiments largely confirmed the predictions of the analytical model As it turned out, the analytical model correctly (in most cases) predicted behavioral effects that contradict some of the best-accepted "truisms" of customer satisfaction It is now clear that a more sophisticated view of customer expectations is required-one that considers not only the point expectation but also the likelihood across the entire distribution of possible outcomes This distinction is not "just academic," because it results in predictable behavior that deviates significantly from that which was traditionally expected based on simpler models

http://bear.warrington.ufl.edu/centers/mks/articles/WhatYouDont.pdf

What You Don'T Know About Customer-Perceived Quality: the Role of Customer Expectation Distributions

Too often, quality programs fail to improve quality because they concentrate on internal processes which do not affect the customer. This is at least partially due to the alienation of marketing from the quality movement, a situation for which both sides are partially at fault. Ideally, marketing should serve as the eyes and ears of the organization, linking the external customer to managerial processes. One way to do this is to organize the collection of customer satisfaction measures around the managerial processes themselves. This forms a natural bridge from the customer to management and allows management to track the impact of quality improvements all the way from internal process measures to overall customer satisfaction and market share.

Anthony J. Zahorik

Papers

Customer satisfaction, customer retention, and market share

Return on quality (ROQ): Making service quality financially accountable

Return on quality (ROQ) : making service quality financially accountable : technical wooking paper

What You Don'T Know About Customer-Perceived Quality: the Role of Customer Expectation Distributions

Why Improving Quality Doesn't Improve Quality (or Whatever Happened to Marketing?):