Home Business & Economics Traveler’s Willingness to Accept and Provide Carpooling Services: A Case Study in Beijing
Article
Licensed
Unlicensed Requires Authentication

Traveler’s Willingness to Accept and Provide Carpooling Services: A Case Study in Beijing

  • Lingling Xiao EMAIL logo and Zhitian Zhou
Published/Copyright: September 3, 2020
Become an author with De Gruyter Brill

Abstract

Carpooling as a transportation demand management (TDM) tool is currently being prevalent in major Chinese cities and producing much diminishment in the frequency of solo-driving trips. Meanwhile, much disputes relating to carpooling is arising. To better understand the acceptance and the influence factors of carpooling, this paper investigates travelers’ willingness to provide and accept carpooling services. Firstly, a questionnaire survey was conducted. Secondly, we proposed a theoretical model, both car-owners and non-car-owners were sampled as respondents, and a multi-variable regression method was employed to analyze the survey data. Finally, we found that the higher acceptance, the more positive reactions to carpooling. The results indicate that it is necessary to improve the public’s acceptance of carpooling, because lower acceptance will lead to more negative reactions towards the carpooling, which may weaken its effectiveness.


Supported by the Beijing Social Science Foundation (16GLC054)


References

[1] Gheorghiu A, Delhomme P. For which types of trips do French drivers carpool? Motivations underlying carpooling for different types of trips. Transportation Research Part A, 2018, 113: 460–475.10.1016/j.tra.2018.05.002Search in Google Scholar

[2] Eriksson L, Garvill J, Nordlund A M. Acceptability of travel demand management measures: The importance of problem awareness, personal norm, freedom, and fairness. Journal of Environmental Psychology, 2006, 26: 15–26.10.1016/j.jenvp.2006.05.003Search in Google Scholar

[3] Xia J, Curtin K M, Huan J. A carpool matching model with both social and route networks. Computers, Environment and Urban Systems, 2019, 75: 90–102.10.1016/j.compenvurbsys.2019.01.008Search in Google Scholar

[4] Filcek G, Hojda M, Zak J. A heuristic algorithm for solving a multiple criteria carpooling optimization (MCCO) problem. Transportation Research Procedia, 2017, 27: 656–663.10.1016/j.trpro.2017.12.108Search in Google Scholar

[5] Shaheen S A, Chan N D, Gaynor T. Casual carpooling in the San Francisco Bay Area: Understanding usercharacteristics, behaviors, and motivations. Transport Policy, 2016, 51: 165–173.10.1016/j.tranpol.2016.01.003Search in Google Scholar

[6] Li R, Liu Z, Zhang R. Studying the benefits of carpooling in an urban area using automatic vehicle identification data. Transportation Research Part C, 2018, 93: 367–380.10.1016/j.trc.2018.06.012Search in Google Scholar

[7] Bachmann F, Hanimann A, Artho J, et al. What drives people to carpool? Explaining carpooling intention from the perspectives of carpooling passengers and drivers. Transportation Research Part F, 2018, 59: 260–268.10.1016/j.trf.2018.08.022Search in Google Scholar

[8] Jia N, Zhang Y, He Z, et al. Commuters’ acceptance of and behavior reactions to license plate restriction policy: A case study of Tianjin, China. Transportation Research Part D, 2017, 52: 428–440.10.1016/j.trd.2016.10.035Search in Google Scholar

Received: 2019-10-23
Accepted: 2020-05-29
Published Online: 2020-09-03
Published in Print: 2020-08-26

© 2020 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 28.1.2026 from https://www.degruyterbrill.com/document/doi/10.21078/JSSI-2020-356-11/html
Scroll to top button