The role of data-based intelligence and experience on time efficiency of taxi drivers: An empirical investigation using large-scale sensor data

• 成果类型: Article
• 署名作者: Lu, Yingda; Wang, Youwei; Chen, Yuxin; Xiong, Yun
• 署名单位: University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Fudan University; New York University; NYU Shanghai; Fudan University; Fudan University
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.14056
• 发表日期: 2023
• 页码: 3665-3682
• 关键词: big data; efficiency improvement; experience; technology adoption

摘要

In this paper, we employ large-scale sensor data to examine the impact of data-based intelligence and work-related experience on the time efficiency of individual taxi drivers, measured by their propensity of choosing the fastest routes. The identification strategy is built on (1) a unique exogenous policy shock-banning taxi-hailing app with an embedded GPS system, and (2) a measure of nonrecurring congestion avoidance, enabled by the real-time sensor data, which serves as a proxy for GPS usage. Our empirical model provides evidence that data-based intelligence improves taxi drivers' routing decisions by close to 3% as measured by trip speed. Our results further demonstrate that inexperienced drivers have a higher chance of choosing the fastest route, as they are more likely to rely on the real-time traffic information from GPS technology than experienced drivers. The general implications of our findings on the adoption and utilization of data-based performance-enhancing technology are discussed in closing.