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A Copula-Based Joint Model Of Commute Mode Choice And Number Of Non-Work Stops During The Commute

Author

Listed:
  • Alessandro Portoghese
  • Erika Spissu
  • Chandra Bhat
  • Naveen Eluru
  • Italo Meloni

Abstract

In this paper, in the spirit of a tour-based frame of analysis, we examine the commute mode choice and the number of non-work stops during the commute. Understanding the mode and activity stop dimensions of weekday commute travel is important since the highest level of weekday traffic congestion in urban areas occurs during the commute periods. The paper employs a copulabased joint multinomial logit – ordered modeling framework in which commute mode choice is modeled using a multinomial logit formulation and the number of commute stops is modeled using an ordered response formulation. The data used in this study are drawn from the “Time use” multipurpose survey conducted between 2002 and 2003 by the Turin Town Council and the Italian National Institute of Statistics (ISTAT) in the Greater Turin metropolitan area of Italy. The results highlight the importance of accommodating the inter-relationship between commute mode choice and commute stops behavior. The results also point to the stronger effect of household responsibilities and demographic characteristics in the Italian context compared to the US context.

Suggested Citation

  • Alessandro Portoghese & Erika Spissu & Chandra Bhat & Naveen Eluru & Italo Meloni, 2011. "A Copula-Based Joint Model Of Commute Mode Choice And Number Of Non-Work Stops During The Commute," Articles, International Journal of Transport Economics, vol. 38(3).
    • Handle: RePEc:jte:journl:2011:3:38:5
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    Citations

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    Cited by:

    1. João De Abreu e Silva, 2018. "The Effects of Land-Use Patterns on Home-Based Tour Complexity and Total Distances Traveled: A Path Analysis," Sustainability, MDPI, vol. 10(3), pages 1-16, March.
    2. Jesus Gonzalez-Feliu & Joelle Morana & Josep-Maria Salanova Grau & Tai-Yu Ma, 2013. "Design And Scenario Assessment For Collaborative Logistics And Freight Transport Systems," Articles, International Journal of Transport Economics, vol. 40(2).
    3. Irannezhad, Elnaz & Prato, Carlo & Hickman, Mark, 2019. "A joint hybrid model of the choices of container terminals and of dwell time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 119-133.
    4. Piras, Francesco & Sottile, Eleonora & Tuveri, Giovanni & Meloni, Italo, 2021. "Could there be spillover effects between recreational and utilitarian cycling? A multivariate model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 297-311.
    5. Chen, Xiaohong & Guo, Yingjie & Yang, Chao & Ding, Fangyi & Yuan, Quan, 2021. "Exploring essential travel during COVID-19 quarantine: Evidence from China," Transport Policy, Elsevier, vol. 111(C), pages 90-97.
    6. Keya, Nowreen & Anowar, Sabreena & Eluru, Naveen, 2019. "Joint model of freight mode choice and shipment size: A copula-based random regret minimization framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 97-115.
    7. Zidan Mao & Dick Ettema & Martin Dijst, 2018. "Analysis of travel time and mode choice shift for non-work stops in commuting: case study of Beijing, China," Transportation, Springer, vol. 45(3), pages 751-766, May.
    8. Xin Guan & Xin Ye & Cheng Shi & Yajie Zou, 2019. "A Multivariate Modeling Analysis of Commuters’ Non-Work Activity Allocations in Xiaoshan District of Hangzhou, China," Sustainability, MDPI, vol. 11(20), pages 1-19, October.

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