An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.

Using data provided by a ride-hailing platform, this paper examines the factors that affect taxi driver response behavior to ride-hailing requests. The empirical investigation from a driver's perspective is of great importance for ride-hailing service providers, given that approximately 40% of...

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Main Authors: Ke Xu, Luping Sun, Jingchen Liu, Hansheng Wang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5993247?pdf=render
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spelling doaj-0ef87bb4ba724522805f8167ba5bdefd2020-11-25T02:47:07ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01136e019860510.1371/journal.pone.0198605An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.Ke XuLuping SunJingchen LiuHansheng WangUsing data provided by a ride-hailing platform, this paper examines the factors that affect taxi driver response behavior to ride-hailing requests. The empirical investigation from a driver's perspective is of great importance for ride-hailing service providers, given that approximately 40% of the hailing requests receive no response from any driver. To comprehensively understand taxi driver response behavior, we use a rich dataset to generate variables related to the spatio-temporal supply-demand intensities, the economic incentives, the requests' and the drivers' characteristics. The results show that drivers are more likely to respond to requests with economic incentives (especially a firm subsidy), and those with a lower spatio-temporal demand intensity or a higher spatio-temporal supply intensity. In addition, drivers are more likely to respond to requests involving rides covering a greater geographical distance and to those with a smaller number of repeated submissions. The drivers' characteristics, namely, the number of requests received and the number of requests responded, however, have relatively little impacts on their response probability to the current request. Our findings contribute to the related literature and provide managerial implications for ride-hailing service providers.http://europepmc.org/articles/PMC5993247?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Ke Xu
Luping Sun
Jingchen Liu
Hansheng Wang
spellingShingle Ke Xu
Luping Sun
Jingchen Liu
Hansheng Wang
An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.
PLoS ONE
author_facet Ke Xu
Luping Sun
Jingchen Liu
Hansheng Wang
author_sort Ke Xu
title An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.
title_short An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.
title_full An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.
title_fullStr An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.
title_full_unstemmed An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective.
title_sort empirical investigation of taxi driver response behavior to ride-hailing requests: a spatio-temporal perspective.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2018-01-01
description Using data provided by a ride-hailing platform, this paper examines the factors that affect taxi driver response behavior to ride-hailing requests. The empirical investigation from a driver's perspective is of great importance for ride-hailing service providers, given that approximately 40% of the hailing requests receive no response from any driver. To comprehensively understand taxi driver response behavior, we use a rich dataset to generate variables related to the spatio-temporal supply-demand intensities, the economic incentives, the requests' and the drivers' characteristics. The results show that drivers are more likely to respond to requests with economic incentives (especially a firm subsidy), and those with a lower spatio-temporal demand intensity or a higher spatio-temporal supply intensity. In addition, drivers are more likely to respond to requests involving rides covering a greater geographical distance and to those with a smaller number of repeated submissions. The drivers' characteristics, namely, the number of requests received and the number of requests responded, however, have relatively little impacts on their response probability to the current request. Our findings contribute to the related literature and provide managerial implications for ride-hailing service providers.
url http://europepmc.org/articles/PMC5993247?pdf=render
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