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Revealing Influences on Carsharing Users' Trip Distance in Small Urban Areas

Title data

Baumgarte, Felix ; Keller, Robert ; Röhrich, Felix ; Valett, Lynne ; Zinsbacher, Daniela:
Revealing Influences on Carsharing Users' Trip Distance in Small Urban Areas.
In: Transportation Research Part D: Transport and Environment. Vol. 105 (April 2022) . - No. 103252.
ISSN 1361-9209
DOI: https://doi.org/10.1016/j.trd.2022.103252

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
Projektgruppe WI Nachhaltiges Energiemanagement & MobilitätNo information

Abstract in another language

Carsharing is an essential part of the transformation towards sustainable mobility in smaller urban areas. To expand their services and the positive social and environmental benefits, carsharing operators must understand their users' travel behavior. To accelerate this understanding, we analyze usage data of a station-based carsharing service from a small city in Germany with machine learning and explainable artificial intelligence to reveal influencing factors on the trip distance. The resulting four overarching groups are personal characteristics, time-related, car-related, and environmental features. We further analyze the driving distance of several subgroups split by personal and time-related features. Our findings highlight the importance of time-related features for the trip distance of carsharing users in all subgroups. We also discuss the influence of non-time-related features on the user groups. With these results, we derive valuable insights for research and carsharing operators by understanding patterns in individual user behavior in smaller urban areas.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Carsharing; User behavior; Trip distance; Machine learning; Explainable artificial intelligence; Feature importance
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Professor Information Systems and Digital Energy Management
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Professor Information Systems and Digital Energy Management > Professor Information Systems and Digital Energy Management - Univ.-Prof. Dr. Jens Strüker
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 23 Mar 2022 10:47
Last Modified: 23 Mar 2022 13:13
URI: https://eref.uni-bayreuth.de/id/eprint/68991