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大数据管理与优化系列论坛:Yunke Mai 助理教授

报告题目:Courteous or Crude? Managing User Conduct to Improve On-demand Service Platform Performance

报 告 人:Yunke Mai

报告时间: 2020年10月31日(周六)09:30-11:30

意甲平台报告地点:腾讯会议 (会议ID: 588 407 489)

主办单位:管理科学与工程学院大数据管理与优化研究中心

【报告人简介】

Yunke Mai is an Assistant Professor of Supply Chain at the Gatton College of Business and Economics, University of Kentucky. Prior to joining Gatton, Yunke received his Ph.D. in Business Administration from the Fuqua School of Business, Duke University. He also holds a B.S. degree in Mathematics from the Pennsylvania State University.

Yunke's research mainly focuses on supply chain management, innovative marketplace, and operations-marketing interface. His research has been published in Production and Operations Management and recognized with the 2018 INFORMS's IBM Best Student Paper Award.

【报告摘要】

In this paper, we build an evolutionary game theory model to investigate how riders' and drivers' behavior evolves in response to a ride-hailing platform's operational decisions, and study how it impacts the platform's performance and the social welfare. We identify two sustainable asymptotically stable equilibria of the dynamic system of the platform, one resembling a traditional taxi service while the other resembling a successful ride-hailing platform. Using this characterization, we then show how the platform could leverage operational tools at its disposal to optimize its performance. Finally, we establish that a platform can generally improve social welfare and may achieve the socially optimal state by prioritizing high-rating riders in matching under supply shortage. Our analysis highlights the importance for ride-hailing platforms to implement and strategically leverage rider ratings, and can potentially provide guidelines for improving platform performance not just with standard instruments such as price and wage adjustments, but also by making rider rating-driven adjustments into the matching procedure.


意甲平台

撰稿:田甜 审核:唐加福 单位:管理科学与工程学院

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