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Manufacturing and Service Operations Management 2026

Delay Information Sharing in Two-Sided On-Demand Platforms

Siddharth Prakash Singh1; Mohammad Delasay2; Mehmet Berat Aydemir3; Mustafa Akan4

1 University College London, School of Management, London, WC1E 6BT, United Kingdom of Great Britain and Northern Ireland · 2 Stony Brook University, College of Business, Stony Brook, New York, 11794, United States · 3 Walmart Global Tech, Walmart Global Tech, United States · 4 Carnegie Mellon University Tepper School of Business, Tepper School of Business, Pittsburgh, Pennsylvania, United States

Abstract

Problem Definition: We study delay information disclosure policies for on-demand platforms serving two user classes (customers and providers) who seek matches using the platform. The platform's objective is to maximize the match rate by choosing the level of information—no information, binary information (indicating whether the wait is zero or non-zero), or occupancy information (indicating the expected delay based on the number of users currently in the system)—to disclose to each user class. Users of each class are strategic and decide whether to join or balk based on the delay information disclosed to them. Methodology/results: We consider two user types in each user class: patient users who are willing to wait for a match and impatient users who are not. We use continuous-time Markov chains to model the system as two-sided queues and employ equilibrium analysis to characterize users' joining behavior and the platform's match rate under each information disclosure policy. We show that the two-sided system decouples and disclosure decisions can be analyzed as two one-sided systems only if some level of information (binary or occupancy) is disclosed to both user classes. We find that disclosing binary information dominates disclosing no information or occupancy information to a user class when its patient users are sufficiently patient, while disclosing occupancy information dominates disclosing binary information to a user class when there are enough patient users. Numerical experiments show that disclosing occupancy information to both user classes, while often suboptimal, is typically not suboptimal by much. Finally, we find that compared to the platform's optimal disclosure choice, a user class may prefer more or less granular information for themselves or the other class. Furthermore, this utility analysis does not lend itself to decoupling. Managerial implications: Our findings hold crucial implications for platform managers: carefully evaluating the chosen information-sharing strategy is imperative, and guidelines from the one-sided literature are generally inadequate for making disclosure decisions

DOI
10.1287/msom.2025.0482
Language
en
Sources
crossref openalex

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