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Pricing policy selection for a platform providing vertically differentiated services with self-scheduling capacity

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  • Xiaogang Lin
  • Yong-Wu Zhou

Abstract

In this article, we study three pricing policies for a monopoly platform, such as Uber or Gett, who offers vertically differentiated services to customers via multiple types of self-scheduling providers. Ideally, the platform can employ a “dynamic pricing” policy, which pays providers wages and charges customers prices for the transactions of different services that both adjust based on prevailing demand conditions, to maximize its profit. However, since it is challenging for the platform to implement and for providers to understand this policy, the other two pricing policies are commonly adopted in practice, that is, “surge pricing” policy (adopted by Uber) which pays providers a fixed commission of its dynamic prices, and “static pricing” policy (applied by Gett) which pays providers a fixed commission of its fixed prices. By observing these phenomena, we propose to study and discuss the platform’s profit performance of these three pricing strategies. We show that the surge pricing policy does not always perform well, which can explain why some on-demand platforms would implement the static pricing policy in practice. Also, although the dynamic pricing policy will significantly improve the platform’s profit, we find that the profitability of the static (surge) pricing policy would approach that of the dynamic pricing policy if the platform can balance the number of different types of providers and/or reduce the commission rate.

Suggested Citation

  • Xiaogang Lin & Yong-Wu Zhou, 2019. "Pricing policy selection for a platform providing vertically differentiated services with self-scheduling capacity," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(7), pages 1203-1218, July.
  • Handle: RePEc:taf:tjorxx:v:70:y:2019:i:7:p:1203-1218
    DOI: 10.1080/01605682.2018.1487822
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    Cited by:

    1. Zhong, Yuanguang & Lin, Zhaozhan & Zhou, Yong-Wu & Cheng, T.C.E. & Lin, Xiaogang, 2019. "Matching supply and demand on ride-sharing platforms with permanent agents and competition," International Journal of Production Economics, Elsevier, vol. 218(C), pages 363-374.
    2. Rojanakit, Patcharapar & Torres de Oliveira, Rui & Dulleck, Uwe, 2022. "The sharing economy: A critical review and research agenda," Journal of Business Research, Elsevier, vol. 139(C), pages 1317-1334.
    3. Qingyang Xiao & Jee Eun Kang, 2023. "Pricing in emerging mobility services: a comprehensive review," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(6), pages 482-500, December.
    4. Jena, Sarat Kumar & Meena, Purushottam, 2022. "Shopping in the omnichannel supply chain under price competition and product return," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    5. Xu, Xiaoping & Zhang, Mian & He, Ping, 2020. "Coordination of a supply chain with online platform considering delivery time decision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    6. Zhong, Yuanguang & Yang, Tong & Cao, Bin & Cheng, T.C.E., 2022. "On-demand ride-hailing platforms in competition with the taxi industry: Pricing strategies and government supervision," International Journal of Production Economics, Elsevier, vol. 243(C).
    7. Zhong, Yuanguang & Lan, Yibo & Chen, Zhi & Yang, Jiazi, 2023. "On-demand ride-hailing platforms with heterogeneous quality-sensitive customers: Dedicated system or pooling system?," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 247-266.
    8. Chen, Mingyang & Zhao, Daozhi & Gong, Yeming & Rekik, Yacine, 2022. "An on-demand service platform with self-scheduling capacity: Uniform versus multiplier-based pricing," International Journal of Production Economics, Elsevier, vol. 243(C).

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