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Structural equation approach to investigate trip-chaining and mode choice relationships in the context of developing countries

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  • Md Hadiuzzaman
  • Nahid Parvez Farazi
  • Sanjana Hossain
  • Saurav Barua
  • Farzana Rahman

Abstract

This paper investigates empirical relationships between trip chain type and mode class choice for developing countries. To formulate these two sets of decisions, four empirical models are developed using structural equation modeling (SEM). Those models are calibrated using one-month travel diary data collected in Dhaka city. SEM correlates the observed variables and identifies their relationship with trip-chaining type utility and mode class choice utility. The fitted models are selected based on statistical results and similarity with the real-life situation. Direct relationships between trip-chaining and mode choice utilities are found insignificant. However, several socio-demographic factors influence both simultaneously. Consequently, it is essential to consider mode class choice concurrently for modeling trip chains. This study also investigates the influencing factors for work-based and non-work-based trip chains separately and effects of road users’ heterogeneity. The research results can be utilized to perceive trip chain-mode choice patterns for developing countries.

Suggested Citation

  • Md Hadiuzzaman & Nahid Parvez Farazi & Sanjana Hossain & Saurav Barua & Farzana Rahman, 2019. "Structural equation approach to investigate trip-chaining and mode choice relationships in the context of developing countries," Transportation Planning and Technology, Taylor & Francis Journals, vol. 42(4), pages 391-415, May.
    • Handle: RePEc:taf:transp:v:42:y:2019:i:4:p:391-415
    DOI: 10.1080/03081060.2019.1600244
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    Cited by:

    1. Elias, Wafa & Zatmeh-Kanj, Sunbola, 2021. "Extent to which COVID-19 will affect future use of the train in Israel," Transport Policy, Elsevier, vol. 110(C), pages 215-224.
    2. Huang, Yuqiao & Gao, Linjie & Ni, Anning & Liu, Xiaoning, 2021. "Analysis of travel mode choice and trip chain pattern relationships based on multi-day GPS data: A case study in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 93(C).
    3. Yuan Yuan & Chunfu Shao & Zhichao Cao & Chaoying Yin, 2023. "The Effect of Travel-Chain Complexity on Public Transport Travel Intention: A Mixed-Selection Model," IJERPH, MDPI, vol. 20(5), pages 1-29, March.
    4. Zhang, Yiyuan & Luo, Xia & Qiu, Yuansen & Fu, Yuxue, 2022. "Understanding the generation mechanism of BEV drivers' charging demand: An exploration of the relationship between charging choice and complexity of trip chaining patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 158(C), pages 110-126.
    5. Cong Qi & Zhenjun Zhu & Xiucheng Guo & Ruiying Lu & Junlan Chen, 2020. "Examining Interrelationships between Tourist Travel Mode and Trip Chain Choices Using the Nested Logit Model," Sustainability, MDPI, vol. 12(18), pages 1-15, September.
    6. Rafiq, Rezwana & McNally, Michael G., 2022. "A structural analysis of the work tour behavior of transit commuters," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 61-79.

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