Optimal Design of Social Comparison Effects: Setting Reference Groups and Reference Points

43 Pages Posted: 8 Apr 2013  

Guillaume Roels

University of California, Los Angeles (UCLA) - Decisions, Operations, and Technology Management (DOTM) Area

Xuanming Su

University of Pennsylvania - Operations & Information Management Department

Date Written: March 1, 2013

Abstract

In this paper, we study how social planners should exploit social comparisons to pursue their objectives. We consider two modes of social comparison, referred to as behind-averse and ahead-seeking behaviors, depending on whether individuals experience a utility loss from under-performing or a utility gain from over-performing relative to their peers. Modeling social comparison as a game between players, we find that ahead-seeking behavior leads to output polarization whereas behind-averse behavior leads to output clustering. A social planner can mitigate these effects in two ways, (i) by providing the full reference distribution of outputs instead of an aggregate reference point based on the average output, and (ii) by assigning players into uniform rather than diverse reference groups. Social planners may thus need to tailor the reference structure to the predominant mode of social comparison and their objective. A performance-focused social planner may set the reference structure so as to maximize the output of either the top or the bottom player depending on whether she puts greater marginal weight to larger or smaller outputs. When the social planner also cares about utility, she faces a dilemma because performance-optimization may not be aligned with utility-maximization. Inevitably, the social planner will have to confront equity issues because better performance may not reflect greater effort or greater ability.

Keywords: social comparisons, reference points, behavioral operations, non-cooperative game theory

Suggested Citation

Roels, Guillaume and Su, Xuanming, Optimal Design of Social Comparison Effects: Setting Reference Groups and Reference Points (March 1, 2013). Available at SSRN: https://ssrn.com/abstract=2246838 or http://dx.doi.org/10.2139/ssrn.2246838

Guillaume Roels

University of California, Los Angeles (UCLA) - Decisions, Operations, and Technology Management (DOTM) Area ( email )

110 Westwood Plaza
Los Angeles, CA 90095-1481
United States

Xuanming Su (Contact Author)

University of Pennsylvania - Operations & Information Management Department ( email )

Philadelphia, PA 19104
United States

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