Information Design for Congested Social Services: Optimal Need-Based Persuasion

Jerry Anunrojwong (), Krishnamurthy Iyer and Vahideh Manshadi ()
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Jerry Anunrojwong: Columbia Business School, Columbia University, New York, New York 10027
Vahideh Manshadi: Yale School of Management, Yale University, New Haven, Connecticut 06511

Management Science, 2023, vol. 69, issue 7, 3778-3796

Abstract: We study the effectiveness of information design in reducing congestion in social services catering to users with varied levels of need. In the absence of price discrimination and centralized admission, the provider relies on sharing information about wait times to improve welfare. We consider a stylized model with heterogeneous users who differ in their private outside options: low-need users have an acceptable outside option to the social service, whereas high-need users have no viable outside option. Upon arrival, a user decides to wait for the service by joining an unobservable first-come-first-serve queue, or leave and seek her outside option. To reduce congestion and improve social outcomes, the service provider seeks to persuade more low-need users to avail their outside option, and thus better serve high-need users. We characterize the Pareto-efficient signaling mechanisms and compare their welfare outcomes against several benchmarks. We show that if either type is the overwhelming majority of the population, then information design does not provide improvement over sharing full information or no information. On the other hand, when the population is sufficiently heterogeneous, information design not only Pareto-dominates full-information and no-information mechanisms, in some regimes it also achieves the same welfare as the “first-best,” that is, the Pareto-efficient centralized admission policy with knowledge of users’ types.

Keywords: information design; social services; Pareto improvement; congestion (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Working Paper: Information Design for Congested Social Services: Optimal Need-Based Persuasion (2022)
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