{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:27:42Z","timestamp":1767338862496,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,2,16]],"date-time":"2021-02-16T00:00:00Z","timestamp":1613433600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41771484"],"award-info":[{"award-number":["41771484"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>In China, the traditional taxi industry is conforming to the trend of the times, with taxi drivers working with e-hailing applications. This reform is of great significance, not only for the taxi industry, but also for the transportation industry, cities, and society as a whole. Our goal was to analyze the changes in driving behavior since taxi drivers joined e-hailing platforms. Therefore, this paper mined taxi trajectory data from Shanghai and compared the data of May 2015 with those of May 2017 to represent the before-app stage and the full-use stage, respectively. By extracting two-trip events (i.e., vacant trip and occupied trip) and two-spot events (i.e., pick-up spot and drop-off spot), taxi driving behavior changes were analyzed temporally, spatially, and efficiently. The results reveal that e-hailing applications mine more long-distance rides and new pick-up locations for drivers. Moreover, driver initiative have increased at night since using e-hailing applications. Furthermore, mobile payment facilities save time that would otherwise be taken sorting out change. Although e-hailing apps can help citizens get taxis faster, from the driver\u2019s perspective, the apps do not reduce their cruising time. In general, e-hailing software reduces the unoccupied ratio of taxis and improves the operating ratio. Ultimately, new driving behaviors can increase the driver\u2019s revenue. This work is meaningful for the formulation of reasonable traffic laws and for urban traffic decision-making.<\/jats:p>","DOI":"10.3390\/ijgi10020077","type":"journal-article","created":{"date-parts":[[2021,2,16]],"date-time":"2021-02-16T04:23:10Z","timestamp":1613449390000},"page":"77","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Exploring the Influence of E-Hailing Applications on the Taxi Industry\u2014From the Perspective of the Drivers"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9437-4403","authenticated-orcid":false,"given":"Yitong","family":"Gan","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongchao","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, 7491 Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Jiao","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6387-3122","authenticated-orcid":false,"given":"Mengqi","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,16]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Correa, D., Xie, K., and Ozbay, K. 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