Information Design for On-Demand Service Platforms : A Queueing-Theoretic Approach
Information design in on-demand service platforms matters in applications such as taxi services, ride-hailing platforms, and freight exchanges. Displayed service delay information significantly affects platform revenues, leading users to balk or renege. Information design is crucial for platforms with dynamic supply and demand; however, the effects of various information policies on user behavior are unclear. User arrival rates are not only influenced by the platform's information policy, but also by the perceived long-term matching probability in a model with multiple platforms. We use queueing theory to examine information disclosure policies for maximizing platform revenue in a marketplace featuring single- and double-sided queueing service systems. In a single-sided model, forming the queue on the side with the higher arrival rate generates higher expected revenue. The preferred information policy depends on the arrival rate and system load. In a double-sided model, hiding the queue-length information is preferred for the side with a lower arrival rate, whereas displaying it on both sides proves advantageous when both sides have high arrival rates. Considering the long-term influence of matching probability on user arrival rates, the recommendations for selecting the information policy remain qualitatively the same, but the revenue difference between information policies increases
Year of publication: |
[2023]
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Authors: | Zhu, Donghao ; Minner, Stefan ; Bichler, Martin |
Publisher: |
[S.l.] : SSRN |
Saved in:
freely available
Extent: | 1 Online-Ressource (55 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments June 15, 2023 erstellt |
Other identifiers: | 10.2139/ssrn.4480537 [DOI] |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014344281
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