On-demand ride-hailing platforms with heterogeneous quality-sensitive customers: Dedicated system or pooling system?

被引:6
作者
Zhong, Yuanguang [1 ]
Lan, Yibo [1 ]
Chen, Zhi [2 ]
Yang, Jiazi [1 ]
机构
[1] South China Univ Technol, Sch Business Adm, Guangzhou, Peoples R China
[2] City Univ Hong Kong, Coll Business, Dept Management Sci, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
On-demand ride-hailing platform; Differentiated services; Sensitivity to service quality; Dedicated system; Pooling system; SELECTION; WORKERS; POLICY; TIME; UBER;
D O I
10.1016/j.trb.2023.04.003
中图分类号
F [经济];
学科分类号
02 ;
摘要
We examine how an on-demand ride-hailing platform chooses between the dedicated system and the pooling system when facing heterogeneous customers and drivers. In the dedicated system, there are two independent queues where quality-sensitive and quality-insensitive customers can be matched with drivers of low-or high-quality service, respectively; while in the pooling system, both types of customers are randomly matched with all drivers without distinguishing the service quality. We characterize the heterogeneity of customers and drivers, and we analyze the platform's optimal pricing and wage decisions in the two systems, respectively. Comparing the two systems, we find that when the driver's basic opportunity cost is not quite large and the difference in opportunity cost between two types of drivers is relatively small, the pooling system can achieve a win-win-win outcome for all participants (i.e., customers, drivers, and the platform). Furthermore, a high level of customers' sensitivity to service quality can increase the platform profit in the dedicated system but has no impact on the pooling system. However, when the level of customers' sensitivity to service quality is within a certain range (which is relatively small), quality-sensitive customers may pay a higher price to join the pooling system compared with the case in the dedicated system.
引用
收藏
页码:247 / 266
页数:20
相关论文
共 50 条
  • [1] Pricing and Prioritizing Time-Sensitive Customers with Heterogeneous Demand Rates
    Afeche, Philipp
    Baron, Opher
    Milner, Joseph
    Roet-Green, Ricky
    [J]. OPERATIONS RESEARCH, 2019, 67 (04) : 1184 - 1208
  • [2] Bai J., 2018, INT J PROD ECON, V250
  • [3] Coordinating Supply and Demand on an On-Demand Service Platform with Impatient Customers
    Bai, Jiaru
    So, Kut C.
    Tang, Christopher S.
    Chen, Xiqun
    Wang, Hai
    [J]. M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT, 2019, 21 (03) : 556 - 570
  • [4] Banerjee S., 2015, Pricing in ride-share platforms: A queueing-theoretic approach, DOI DOI 10.2139/SSRN.2568258
  • [5] A Learning-Based Optimization Approach for Autonomous Ridesharing Platforms with Service-Level Contracts and On-Demand Hiring of Idle Vehicles
    Beirigo, Breno A.
    Schulte, Frederik
    Negenborn, Rudy R.
    [J]. TRANSPORTATION SCIENCE, 2022, 56 (03) : 677 - 703
  • [6] Labor Welfare in On-Demand Service Platforms
    Benjaafar, Saif
    Ding, Jian-Ya
    Kong, Guangwen
    Taylor, Terry
    [J]. M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT, 2022, 24 (01) : 110 - 124
  • [7] Surge Pricing and Its Spatial Supply Response
    Besbes, Omar
    Castro, Francisco
    Lobel, Ilan
    [J]. MANAGEMENT SCIENCE, 2021, 67 (03) : 1350 - 1367
  • [8] Spatial Pricing in Ride-Sharing Networks
    Bimpikis, Kostas
    Candogan, Ozan
    Saban, Daniela
    [J]. OPERATIONS RESEARCH, 2019, 67 (03) : 744 - 769
  • [9] Surge Pricing Solves the Wild Goose Chase
    Castillo, Juan Camilo
    Knoepfle, Dan
    Weyl, Glen
    [J]. EC'17: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON ECONOMICS AND COMPUTATION, 2017, : 241 - 242
  • [10] Chen Li., 2020, BONUS COMPETITION GI