Discrimination in Service

Kalinda Ukanwa and Roland T. Rust, 2018, 18-121-07

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Litigation concerning firm-against-consumer discrimination has a long history in the U.S. In the past two decades alone, prominent corporations have paid more than half a billion dollars in settlements and fines for consumer discrimination cases - an amount that does not include additional sales losses due to bad publicity, damaging boycotts, or impaired reputation and brand.

Here, Kalinda Ukanwa and Roland Rust seek to (1) uncover the mechanism by which service discrimination can emerge from seemingly rational service policy; (2) investigate how service discrimination interacts with competition and consumer word-of-mouth to affect profits; (3) help firms avoid losing profits due to discrimination.

They develop a theoretical model that illuminates the critical roles that variation in consumer quality (i.e., their profitability to the firm) and measurement error in detecting consumer quality play in the emergence and magnitude of discrimination in service. Empirical evidence in two studies supports their theory that large variation in consumer quality reduces service discrimination while large measurement error increases service discrimination.

Further, agent-based modeling demonstrates that service providers using a “group-blind” service policy that ignores group membership information about consumers have greater total profits over time than those with a “group-aware” service policy that uses group membership information in addition to individual attributes in service decision-making.

Managerial implications

Firms should consider the long-term benefits of switching to a service policy that does not use group membership information.  Although discriminatory (i.e., “group aware”) practices may seem profitable in the short term, they can damage service demand and profits in the long run. Because of strong word-of-mouth effects, consumers can learn from each other which firms are unlikely to provide favorable service conditions to them, and can switch their preferences to competitive alternatives.

Firms that persist in using group identity information should invest in methods of measurement error reduction such as developing advanced methods of measuring consumer quality or more sophisticated predictive models that improve accuracy in predicting quality based on available measures. These firms could also increase exposure to consumer populations, which could improve information on the mean and variance of group quality.

These findings apply to any service scenario where the service provider can segment consumers into groups based on some observable attribute; and where the service provider uses group membership as well as individual information to make a decision about the provision of service to the consumer.

Kalinda Ukanwa is a doctoral candidate in the Department of Marketing and Roland T. Rust is Distinguished University Professor and David Bruce Smith Chair in Marketing, and Executive Director of the Center for Excellence in Service, both at the Robert H. Smith School of Business, University of Maryland.

This research is supported by grants from the Marketing Science Institute and the Robert H. Smith School of Business, University of Maryland. The authors thank the attendees of the Frontiers in Service Conference and the PhD Project MDSA Conference for helpful comments.


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