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A Tour-Based Mode Choice Model for Commuters in Indonesia

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  • Faza Fawzan Bastarianto

    (Department of Civil and Environmental Engineering Universitas Gadjah Mada, Jln. Grafika No.2 Bulaksumur, 55281 Yogyakarta, Indonesia
    Institute for Transport Studies University of Leeds, 34-40 University Road, Leeds LS2 9JT, UK)

  • Muhammad Zudhy Irawan

    (Department of Civil and Environmental Engineering Universitas Gadjah Mada, Jln. Grafika No.2 Bulaksumur, 55281 Yogyakarta, Indonesia)

  • Charisma Choudhury

    (Institute for Transport Studies University of Leeds, 34-40 University Road, Leeds LS2 9JT, UK)

  • David Palma

    (Institute for Transport Studies University of Leeds, 34-40 University Road, Leeds LS2 9JT, UK)

  • Imam Muthohar

    (Department of Civil and Environmental Engineering Universitas Gadjah Mada, Jln. Grafika No.2 Bulaksumur, 55281 Yogyakarta, Indonesia)

Abstract

With the advent of activity-based modelling, transport planners’ focus has shifted from isolated trips to tours. Tours are series of interconnected trips that start and finish at home. There are different types of tours; we focus on two: hwh (start at home; go to work; and then go back home) and hw+wh (where + represents a non-work activity). Tour types introduce a new dimension to the traditional problem of travel mode choice, as the mode choice might be influenced by the type of tour. This study attempts to measure and compare the relationship between tour type and mode choice using three different modelling approaches: Multinomial Logit (MNL); Nested Logit (NL) and Cross-Nested Logit (CNL). We compare each approach using secondary data from a larger survey: 24-h daily activity patterns of 420 commuters between Bekasi and Jakarta; one of the busiest commuting routes in Indonesia. Among other results, we found that gender and income significantly influence commuter’s choice of mode and that reducing travel time and cost can increase the ridership of public transport. Furthermore, the NL and CNL models showed significant improvement over the simpler MNL when grouping the alternatives based on tour types. This points to a significant influence of the tour type on the mode choice. Policy recommendations to increase traveler’s wellbeing are also formulated.

Suggested Citation

  • Faza Fawzan Bastarianto & Muhammad Zudhy Irawan & Charisma Choudhury & David Palma & Imam Muthohar, 2019. "A Tour-Based Mode Choice Model for Commuters in Indonesia," Sustainability, MDPI, vol. 11(3), pages 1-20, February.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:3:p:788-:d:203094
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    References listed on IDEAS

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    1. Dharmowijoyo, Dimas B.E. & Susilo, Yusak O. & Karlström, Anders, 2017. "Analysing the complexity of day-to-day individual activity-travel patterns using a multidimensional sequence alignment model: A case study in the Bandung Metropolitan Area, Indonesia," Journal of Transport Geography, Elsevier, vol. 64(C), pages 1-12.
    2. Wen, Chieh-Hua & Koppelman, Frank S., 2001. "The generalized nested logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 627-641, August.
    3. Lars Lundqvist & Lars-Göran Mattsson (ed.), 2002. "National Transport Models," Advances in Spatial Science, Springer, number 978-3-662-04853-5.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    5. Olszewski, Piotr & Xie, Litian, 2005. "Modelling the effects of road pricing on traffic in Singapore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 755-772.
    6. Soltani, Ali, 2017. "Social and urban form determinants of vehicle ownership; evidence from a developing country," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 90-100.
    7. Chinh Ho & Corinne Mulley, 2013. "Tour-based mode choice of joint household travel patterns on weekend and weekday," Transportation, Springer, vol. 40(4), pages 789-811, July.
    8. Levinson, David & Zhao, Zhirong Jerry, 2012. "Introduction to the special issue on value capture for transportation finance," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 5(1), pages 1-3.
    9. Dimas B. E. Dharmowijoyo & Yusak O. Susilo & Anders Karlström, 2016. "Day-to-day variability in travellers’ activity-travel patterns in the Jakarta metropolitan area," Transportation, Springer, vol. 43(4), pages 601-621, July.
    10. Stephane Hess & Mark Fowler & Thomas Adler & Aniss Bahreinian, 2012. "A joint model for vehicle type and fuel type choice: evidence from a cross-nested logit study," Transportation, Springer, vol. 39(3), pages 593-625, May.
    11. Djoen San Santoso & Koji Tsunokawa, 2005. "Spatial Transferability and Updating Analysis of Mode Choice Models in Developing Countries," Transportation Planning and Technology, Taylor & Francis Journals, vol. 28(5), pages 341-358, July.
    12. Dissanayake, Dilum & Morikawa, Takayuki, 2010. "Investigating household vehicle ownership, mode choice and trip sharing decisions using a combined revealed preference/stated preference Nested Logit model: case study in Bangkok Metropolitan Region," Journal of Transport Geography, Elsevier, vol. 18(3), pages 402-410.
    13. Eric Miller & Matthew Roorda & Juan Carrasco, 2005. "A tour-based model of travel mode choice," Transportation, Springer, vol. 32(4), pages 399-422, July.
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    Cited by:

    1. Irawan, Muhammad Zudhy & Simanjuntak, Nurvita I.M. & Bastarianto, Faza Fawzan & Dwitasari, Reslyana & Herawati,, 2020. "Predicting the impact of Trans Java Toll Roads on demand for intercity air travel in Indonesia," Journal of Air Transport Management, Elsevier, vol. 87(C).
    2. Fariha Riska Yumita & Muhammad Zudhy Irawan & Siti Malkhamah & Muhammad Iqbal Habibi Kamal, 2021. "School Commuting: Barriers, Abilities and Strategies toward Sustainable Public Transport Systems in Yogyakarta, Indonesia," Sustainability, MDPI, vol. 13(16), pages 1-18, August.
    3. Muhammad Zudhy Irawan & Prawira Fajarindra Belgiawan & Tri Basuki Joewono & Nurvita I. M. Simanjuntak, 2020. "Do motorcycle-based ride-hailing apps threaten bus ridership? A hybrid choice modeling approach with latent variables," Public Transport, Springer, vol. 12(1), pages 207-231, March.
    4. Hamad, Khaled & Obaid, Lubna, 2022. "Tour-based travel demand forecasting model for a university campus," Transport Policy, Elsevier, vol. 117(C), pages 118-137.

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