Persuading Customers to Buy Early: The Value of Personalized Information Provisioning

Kimon Drakopoulos (), Shobhit Jain () and Ramandeep Randhawa ()
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Kimon Drakopoulos: Data Sciences and Operations, Marshall School of Business, University of Southern California, Los Angeles, California 90089
Shobhit Jain: Data Sciences and Operations, Marshall School of Business, University of Southern California, Los Angeles, California 90089
Ramandeep Randhawa: Data Sciences and Operations, Marshall School of Business, University of Southern California, Los Angeles, California 90089

Management Science, 2021, vol. 67, issue 2, 828-853

Abstract: We study a pricing and information provisioning game between a better-informed seller (such as a retailer) and its customers. The seller is (ex post) better informed about product availability and can choose how to communicate this information to the customers. The customers are heterogeneous in their valuation for the product. The firm optimizes on publicly posted prices (which are the same for all customers) and its information provisioning (which can be personalized). Using a Bayesian persuasion framework, we find that public information provisioning, in which the firm sends the same information to all customers, has limited value. However, personalized information provisioning, in which the firm can share different information with different customers, has significant value and has attributes very similar to personalized pricing. This paper was accepted by Gabriel Weintraub, revenue management and market analytics.

Keywords: revenue management; information; pricing; Bayesian persuasion; information operations (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:67:y:2021:i:2:p:828-853

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