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Article: Is ridesourcing more efficient than taxis?

TitleIs ridesourcing more efficient than taxis?
Authors
KeywordsService efficiency
Taxis
DiDi
Vehicle occupancy rate
Ridesourcing
Issue Date2020
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/apgeog
Citation
Applied Geography, 2020, v. 125, article no. 102301 How to Cite?
AbstractRidesourcing services such as Uber, Lyft, and DiDi are purported to be more efficient than traditional taxis because they can match passengers with drivers more effectively. Previous studies have compared the efficiency of ridesourcing and taxis in several cities. However, gaps still exist regarding the measurement and comparison between the two modes, and the reasons for the higher efficiency of ridesourcing have not been empirically examined. This paper aims to measure, compare, and explain the efficiency and variation of DiDi and taxis. The case study is conducted in Chengdu, China. We use vehicle occupancy rate (VOR) as the efficiency measure - the percentage of time that a vehicle is occupied by a fare-paying passenger. We measure the VORs of DiDi and taxis and their spatial and temporal variations using the trip origin-destination data for DiDi and the trajectory data for taxis. The VOR patterns between DiDi and taxis are compared and contrasted, and the underlying factors that affect the difference are examined: more efficient driver-rider matching algorithm, larger scale of ridesourcing services, and the number of taxi trips per capita. Results show that the overall VOR of DiDi is six percentage points higher than taxis on the weekday and 12 percentage points higher on the weekend. However, the VOR of taxis is slightly higher than DiDi during the weekday morning peak hours and in downtown areas. Regression models reveal that the more efficient matching and the greater scale of DiDi drivers enlarge the VOR gap between DiDi and taxis, while the number of taxi trips per capita reduce the gap. The findings have implications for both business operation and transportation policies in terms of service design, service coordination, and location-specific regulations.
Persistent Identifierhttp://hdl.handle.net/10722/300134
ISSN
2023 Impact Factor: 4.0
2023 SCImago Journal Rankings: 1.204
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorKong, Hui-
dc.contributor.authorZhang, Xiaohu-
dc.contributor.authorZhao, Jinhua-
dc.date.accessioned2021-06-04T05:49:07Z-
dc.date.available2021-06-04T05:49:07Z-
dc.date.issued2020-
dc.identifier.citationApplied Geography, 2020, v. 125, article no. 102301-
dc.identifier.issn0143-6228-
dc.identifier.urihttp://hdl.handle.net/10722/300134-
dc.description.abstractRidesourcing services such as Uber, Lyft, and DiDi are purported to be more efficient than traditional taxis because they can match passengers with drivers more effectively. Previous studies have compared the efficiency of ridesourcing and taxis in several cities. However, gaps still exist regarding the measurement and comparison between the two modes, and the reasons for the higher efficiency of ridesourcing have not been empirically examined. This paper aims to measure, compare, and explain the efficiency and variation of DiDi and taxis. The case study is conducted in Chengdu, China. We use vehicle occupancy rate (VOR) as the efficiency measure - the percentage of time that a vehicle is occupied by a fare-paying passenger. We measure the VORs of DiDi and taxis and their spatial and temporal variations using the trip origin-destination data for DiDi and the trajectory data for taxis. The VOR patterns between DiDi and taxis are compared and contrasted, and the underlying factors that affect the difference are examined: more efficient driver-rider matching algorithm, larger scale of ridesourcing services, and the number of taxi trips per capita. Results show that the overall VOR of DiDi is six percentage points higher than taxis on the weekday and 12 percentage points higher on the weekend. However, the VOR of taxis is slightly higher than DiDi during the weekday morning peak hours and in downtown areas. Regression models reveal that the more efficient matching and the greater scale of DiDi drivers enlarge the VOR gap between DiDi and taxis, while the number of taxi trips per capita reduce the gap. The findings have implications for both business operation and transportation policies in terms of service design, service coordination, and location-specific regulations.-
dc.languageeng-
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/apgeog-
dc.relation.ispartofApplied Geography-
dc.subjectService efficiency-
dc.subjectTaxis-
dc.subjectDiDi-
dc.subjectVehicle occupancy rate-
dc.subjectRidesourcing-
dc.titleIs ridesourcing more efficient than taxis?-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.apgeog.2020.102301-
dc.identifier.scopuseid_2-s2.0-85089803681-
dc.identifier.hkuros330723-
dc.identifier.volume125-
dc.identifier.spagearticle no. 102301-
dc.identifier.epagearticle no. 102301-
dc.identifier.isiWOS:000602320100006-
dc.publisher.placeUnited Kingdom-

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