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Measuring and Improving Stakeholder Welfare Is Easier Said than Done

Published online by Cambridge University Press:  19 December 2022

Umit G. Gurun ,
Jordan Nickerson  and
David H. Solomon
Umit G. Gurun
Affiliation:
University of Texas at Dallas Department of Finance umit.gurun@utdallas.edu
Jordan Nickerson
Affiliation:
University of Washington Department of Finance jnick@uw.edu
David H. Solomon*
Affiliation:
Boston College Department of Finance
*
david.solomon@bc.edu (corresponding author)
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Abstract

While corporate social responsibility by firms aims at improving welfare for different social groups, whether it achieves this is often difficult to measure. After Apr. 2018 protests, Starbucks enacted policies that anybody could sit in their stores and use the bathroom without making a purchase. Using anonymized cellphone location data, we estimate this led to a 7.0% decline in attendance relative to other nearby coffee shops. The effect is 84% larger near homeless shelters and larger for Starbucks’ wealthier customers. The average time spent per visit declined by 4.1%. Public urination citations decreased near Starbucks locations, but other minor crimes were unchanged.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 58 , Issue 4 , June 2023 , pp. 1473 - 1507
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the Michael G. Foster School of Business, University of Washington

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Footnotes

An earlier draft of this article was titled “The Perils of Private Provision of Public Goods.” We are grateful to Auren Hoffman, Lauren Spiegel, and Noah Yonack for their help with providing and understanding the SafeGraph’s anonymized GPS data. We also thank Sam Hartzmark, Eugene Soltes, and seminar participants at Chapman University, the University of St. Gallen, the 2021 Western Finance Association Meetings, and the 2021 European Finance Association Meetings for helpful comments. Some of the results in this article are based on researchers’ own analyses calculated (or derived) based in part on data from The Nielsen Company (US), LLC and marketing databases provided through the Nielsen data sets at the Kilts Center for Marketing Data Center at The University of Chicago Booth School of Business. The conclusions drawn from the Nielsen data are those of the researchers and do not reflect the views of Nielsen. Nielsen is not responsible for, had no role in, and was not involved in analyzing and preparing the results reported herein. All remaining errors are our own.

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