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

Author

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  • Jerry Anunrojwong

    (Columbia Business School, Columbia University, New York, New York 10027)

  • Krishnamurthy Iyer

    (Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota 55455)

  • Vahideh Manshadi

    (Yale School of Management, Yale University, New Haven, Connecticut 06511)

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.

Suggested Citation

  • Jerry Anunrojwong & Krishnamurthy Iyer & Vahideh Manshadi, 2023. "Information Design for Congested Social Services: Optimal Need-Based Persuasion," Management Science, INFORMS, vol. 69(7), pages 3778-3796, July.
  • Handle: RePEc:inm:ormnsc:v:69:y:2023:i:7:p:3778-3796
    DOI: 10.1287/mnsc.2022.4548
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    1. Baccara, Mariagiovanna & Lee, SangMok & Yariv, Leeat, 2020. "Optimal dynamic matching," Theoretical Economics, Econometric Society, vol. 15(3), July.
    2. Nick Arnosti & Peng Shi, 2020. "Design of Lotteries and Wait-Lists for Affordable Housing Allocation," Management Science, INFORMS, vol. 66(6), pages 2291-2307, June.
    3. David Lingenbrink & Krishnamurthy Iyer, 2019. "Optimal Signaling Mechanisms in Unobservable Queues," Operations Research, INFORMS, vol. 67(5), pages 1397-1416, September.
    4. Emir Kamenica & Matthew Gentzkow, 2011. "Bayesian Persuasion," American Economic Review, American Economic Association, vol. 101(6), pages 2590-2615, October.
    5. Gad Allon & Achal Bassamboo & Itai Gurvich, 2011. "“We Will Be Right with You”: Managing Customer Expectations with Vague Promises and Cheap Talk," Operations Research, INFORMS, vol. 59(6), pages 1382-1394, December.
    6. Santiago R. Balseiro & Huseyin Gurkan & Peng Sun, 2019. "Multiagent Mechanism Design Without Money," Operations Research, INFORMS, vol. 67(5), pages 1417-1436, September.
    7. Itai Feigenbaum & Yash Kanoria & Irene Lo & Jay Sethuraman, 2020. "Dynamic Matching in School Choice: Efficient Seat Reassignment After Late Cancellations," Management Science, INFORMS, vol. 66(11), pages 5341-5361, November.
    8. Ilan Kremer & Yishay Mansour & Motty Perry, 2014. "Implementing the "Wisdom of the Crowd"," Journal of Political Economy, University of Chicago Press, vol. 122(5), pages 988-1012.
    9. Yiangos Papanastasiou & Kostas Bimpikis & Nicos Savva, 2018. "Crowdsourcing Exploration," Management Science, INFORMS, vol. 64(4), pages 1727-1746, April.
    10. Hassin, Refael, 1986. "Consumer Information in Markets with Random Product Quality: The Case of Queues and Balking," Econometrica, Econometric Society, vol. 54(5), pages 1185-1195, September.
    11. Kanoria, Yash & Saban, Daniela, 2017. "Facilitating the Search for Partners on Matching Platforms: Restricting Agents' Actions," Research Papers 3572, Stanford University, Graduate School of Business.
    12. Jerry Anunrojwong & Krishnamurthy Iyer & David Lingenbrink, 2024. "Persuading Risk-Conscious Agents: A Geometric Approach," Operations Research, INFORMS, vol. 72(1), pages 151-166, January.
    13. Bergemann, Dirk & Morris, Stephen, 2016. "Bayes correlated equilibrium and the comparison of information structures in games," Theoretical Economics, Econometric Society, vol. 11(2), May.
    14. Erjie Ang & Sara Kwasnick & Mohsen Bayati & Erica L. Plambeck & Michael Aratow, 2016. "Accurate Emergency Department Wait Time Prediction," Manufacturing & Service Operations Management, INFORMS, vol. 18(1), pages 141-156, February.
    15. Canice Prendergast, 2017. "How Food Banks Use Markets to Feed the Poor," Journal of Economic Perspectives, American Economic Association, vol. 31(4), pages 145-162, Fall.
    16. Naor, P, 1969. "The Regulation of Queue Size by Levying Tolls," Econometrica, Econometric Society, vol. 37(1), pages 15-24, January.
    17. Itai Ashlagi & Maximilien Burq & Patrick Jaillet & Vahideh Manshadi, 2019. "On Matching and Thickness in Heterogeneous Dynamic Markets," Operations Research, INFORMS, vol. 67(4), pages 927-949, July.
    18. Nikhil Agarwal & Itai Ashlagi & Michael A. Rees & Paulo J. Somaini & Daniel C. Waldinger, 2019. "Equilibrium Allocations under Alternative Waitlist Designs: Evidence from Deceased Donor Kidneys," NBER Working Papers 25607, National Bureau of Economic Research, Inc.
    19. Agarwal, Nikhil & Ashlagi, Itai & Rees, Michael & Somaini, Paulo & Waldinger, Daniel, 2019. "An Empirical Framework for Sequential Assignment: The Allocation of Deceased Donor Kidneys," Research Papers 3724, Stanford University, Graduate School of Business.
    20. Rouba Ibrahim, 2018. "Sharing delay information in service systems: a literature survey," Queueing Systems: Theory and Applications, Springer, vol. 89(1), pages 49-79, June.
    21. Kostas Bimpikis & Shayan Ehsani & Mohamed Mostagir, 2019. "Designing Dynamic Contests," Operations Research, INFORMS, vol. 67(2), pages 339-356, March.
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    Cited by:

    1. Krishnamurthy Iyer & Haifeng Xu & You Zu, 2023. "Markov Persuasion Processes with Endogenous Agent Beliefs," Papers 2307.03181, arXiv.org, revised Jul 2023.
    2. Charlson, G., 2022. "In platforms we trust: misinformation on social networks in the presence of social mistrust," Janeway Institute Working Papers 2202, Faculty of Economics, University of Cambridge.
    3. Modibo Camara & Jason Hartline & Aleck Johnsen, 2020. "Mechanisms for a No-Regret Agent: Beyond the Common Prior," Papers 2009.05518, arXiv.org.
    4. Charlson, G., 2022. "In platforms we trust: misinformation on social networks in the presence of social mistrust," Cambridge Working Papers in Economics 2204, Faculty of Economics, University of Cambridge.

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