Platform Refund Insurance or Being Cast Out: Quantifying the Signaling Effect of Refund Options in the Online Service Marketplace

Jinyang Zheng (), Youwei Wang () and Yong Tan ()
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Jinyang Zheng: Krannert School of Management, Purdue University, West Lafayette, Indiana 47906
Youwei Wang: Department of Information Management and Business Intelligence, School of Management, Fudan University, Shanghai 200433, China
Yong Tan: Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195

Information Systems Research, 2023, vol. 34, issue 3, 910-934

Abstract: This study examines whether and how an online service marketplace can leverage refund options endorsed by different parties (i.e., the platform or sellers) to address the “lemons” problem that is caused by the intangibility, variability, and unreturnable nature of the services sought. Through developing a signaling mechanism and a corresponding demand estimation model, we show that both platform refund insurance and a seller-guaranteed refund increase service demand, with platform refund insurance as the more effective option and hence having a more effective signaling mechanism. A reduced-form analysis suggests that sellers with a better reputation or less popularity might benefit less from refund options. An investigation on further use of the more effective refund option, a “having platform refund insurance or being cast out” policy (i.e., retaining platform refund-insured sellers but expelling uninsured ones), using counterfactual simulations and supply-side single interrupted time series designs, reveals the effectiveness of this policy in filtering out low-quality sellers, shown as an improved quality of sellers on the platform due to the change in sellers (i.e., new sellers’ replacing those who were expelled) both immediately after the policy and in the (near) equilibrium, yet a cost (i.e., a loss in demand and consumer welfare) for the platform in the (near) equilibrium due to the changes in characteristics (e.g., price) of sellers. This cost, however, is lower than the benefit from the improved quality of the sellers, so that the platform’s overall performance improves. The study also quantifies the consumer welfare of the online service marketplace and provides practical insight for consumers, sellers, and online service marketplace operators.

Keywords: demand estimation; online marketplace; platform refund insurance; signaling theory; consumer surplus (search for similar items in EconPapers)
Date: 2023
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