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Open AccessArticle

Uncovering Spatial Inequality in Taxi Services in the Context of a Subsidy War among E-Hailing Apps

State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Luoyu Road 129, Wuhan 430079, China
Collaborative Innovation Center of Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China
School of Urban Construction, Wuhan University of Science and Technology, Wuhan 430065, China
Shenzhen Transportation Operation Command Center, 8003 Shennan Avenue, Shenzhen 518040, China
Authors to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(6), 230;
Received: 13 May 2018 / Revised: 4 June 2018 / Accepted: 18 June 2018 / Published: 20 June 2018
PDF [3283 KB, uploaded 20 June 2018]


Spatial inequalities in urban public transportation are a major concern in many countries but little of this research has focused specifically on taxi services. The taxi situation has grown more complex, as traditional ride-for-hire services face growing competition from e-hailing apps like Uber in the U.S., or Didi and Kuaidi in China. In 2014, Didi and Kuaidi triggered a nationwide subsidy war, with possible effects on the spatial inequality of taxi services. Taxi trajectory data from Shenzhen collected during the subsidy war shows that this competition reduced spatial inequality in the inner city but aggravated it in the outer city. In this study, a measure of service rate to depict the quantity of taxi services is proposed to calculate a Gini coefficient for evaluating change in the spatial inequality of taxi services. The Theil index and its decomposition were used to distinguish the contribution of Traffic Analysis Zones (TAZs) in the inner and the outer city and compare them to the overall spatial inequality of taxi services in Shenzhen, TAZs in the outer city had greater inequality in taxi services than the inner city. Furthermore, the primary contributor to overall inequality in taxi services was inequality within, rather than between, the inner and outer city. Moreover, the mean values for the changed service rates in the inner city were always larger than the outer city, and the inner city had a more equitable changed service rate than the outer city. These results could serve as a foundation for improving taxi services citywide. View Full-Text
Keywords: subsidy war; e-hailing service; spatial inequality; Gini coefficient; Theil index subsidy war; e-hailing service; spatial inequality; Gini coefficient; Theil index

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Su, R.; Fang, Z.; Xu, H.; Huang, L. Uncovering Spatial Inequality in Taxi Services in the Context of a Subsidy War among E-Hailing Apps. ISPRS Int. J. Geo-Inf. 2018, 7, 230.

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