A multinomial probit analysis of shanghai commute mode choice

Commute trips account for a large portion of travel demand in peak hours and significantly influence the operation of urban transportation systems. In this paper, we apply a fully flexible multinomial probit (MNP) model for the analysis of commute mode choice behavior, and compare this MNP model with more traditional discrete choice models, including the multinomial logit (MNL), the cross-nested logit (CNL), the heteroscedastic independent MNP (HI-MNP), and the homoscedastic non-independent MNP (HONI-MNP). The two-variate bivariate screening (TVBS) approach, a recently developed analytical evaluation for the multivariate normal cumulative distribution (MVNCD) function, is employed. The sample for analysis is drawn from a web-based travel survey conducted in Shanghai. Overall, from a data fit perspective at, both the disaggregate and aggregate levels, the MNP clearly outperforms all the other four models, underscoring the importance of considering both heteroscedasticity as well as correlated error terms when estimating mode choice models. Policy implications are also examined and discussed.

• Record URL:
  • https://doi.org/10.1007/s11116-022-10284-x
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00494488
• Supplemental Notes:
  • © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
• Authors:
  • Wang, Ke
  • Bhat, Chandra R
  • 0000-0002-0715-8121
  • Ye, Xin
  • 0000-0001-9697-6953
• Publication Date: 2023-8

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 1471-1495
• Serial:
  • Transportation
  • Volume: 50
  • Issue Number: 4
  • Publisher: Springer
  • ISSN: 0049-4488
  • EISSN: 1572-9435
  • Serial URL: http://link.springer.com/journal/11116

Subject/Index Terms

• TRT Terms: Choice models; Commuters; Mode choice; Travel behavior; Travel demand; Urban transportation
• Geographic Terms: Shanghai (China)
• Subject Areas: Data and Information Technology; Highways; Passenger Transportation; Pedestrians and Bicyclists; Public Transportation; Safety and Human Factors;

Filing Info

• Accession Number: 01888867
• Record Type: Publication
• Files: TRIS
• Created Date: Jul 26 2023 3:59PM