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When do group incentives for retail store managers work?

Authors
Lee, Hyun Seok (Huck)Kesavan, SaravananKuhnen, Camelia
Issue Date
8월-2022
Publisher
WILEY
Keywords
empirical; geographical proximity; incentive; retail operations
Citation
PRODUCTION AND OPERATIONS MANAGEMENT, v.31, no.8, pp.3077 - 3095
Indexed
SCIE
SCOPUS
Journal Title
PRODUCTION AND OPERATIONS MANAGEMENT
Volume
31
Number
8
Start Page
3077
End Page
3095
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/143268
DOI
10.1111/poms.13740
ISSN
1059-1478
Abstract
Retail stores are geographically dispersed as a part of a multiunit organization. In such a setting, store managers play an important role in driving store performance. To motivate them to exert effort, retailers have provided group incentives for store managers. Using data from 75 stores of a U.S.-based retail chain that changed its incentive plan for store managers from being purely dependent on store performance to being dependent upon both store and corporate performance, we investigate the effect of this change on store performance. We also examine the moderating role of geographical proximity among stores and past performance of the focal store. To establish a causality, we identify a control group from a matched store of another retail chain in the same industry and perform a difference-in-differences analysis. We find that making managers' bonus dependent on corporate goals has resulted in overall worsening of store performance. However, such an effect is contingent upon both geographical proximity among stores and past performance of the focal store. The impact of the incentive change on store performance is positively moderated by the increase in stores within close geographical proximity, while it is negatively moderated by the past performance of the focal store. This paper broadens our understanding of how incentives work in practice, and more importantly, documents how firms can design more effective incentive schemes for managers by considering relevant conditions, such as stores' geographical networks and their past performance.
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