TRIPS体系结构
计算机科学
弹性(材料科学)
供求关系
运输工程
业务
经济
工程类
微观经济学
物理
热力学
作者
Yingjie Zhang,Beibei Li,Sean Qian
出处
期刊:Information Systems Research
[Institute for Operations Research and the Management Sciences]
日期:2023-04-04
卷期号:34 (4): 1775-1790
被引量:6
标识
DOI:10.1287/isre.2023.1212
摘要
This article investigates how and why the traditional on-demand service (i.e., taxies) and ridesharing platforms (e.g., Uber) perform in contexts of urban uncertainty. We consider different types of unexpected urban anomalies and collect large-scale trip data on taxi and ridesharing services. Empirically, we employ a difference-in-differences econometric model to compare the platform-level performances (measured by the number of fulfilled trips) of a traditional taxi system and a ridesharing platform after urban anomaly shocks. We observe that the ridesharing platform significantly outperforms the traditional taxi platform in coping with the uncertainties brought about by unexpected anomalies. We conclude, conservatively, that the technological effect and technology-enabled supply elasticity, are the main factors determining the differences between the platforms during an urban anomaly. This work offers important insights into the design of platform strategies, especially for stimulation of the labor supply and incentivization of the adoption and use of technology in urban transportation systems in response to anomalous urban upheavals.
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