IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i10p6367-d822185.html
   My bibliography  Save this article

Modeling and Structuring of Activity Scheduling Choices with Consideration of Intrazonal Tours: A Case Study of Motorcycle-Based Cities

Author

Listed:
  • Thuy Linh Hoang

    (UHasselt—Hasselt University, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium
    Faculty of Civil Engineering, University of Transport and Communications, No. 3 Cau Giay Street, Lang Thuong Ward, Dong Da District, Hanoi 100000, Vietnam)

  • Muhammad Adnan

    (UHasselt—Hasselt University, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium)

  • Anh Tuan Vu

    (Vietnamese–German Transport Research Centre, Vietnamese–German University, Le Lai Street, Hoa Phu Ward, Thu Dau Mot City 820000, Binh Duong Province, Vietnam)

  • Nguyen Hoang-Tung

    (Faculty of Construction Management, University of Transport and Communications, No. 3 Cau Giay Street, Lang Thuong Ward, Dong Da District, Hanoi 100000, Vietnam)

  • Bruno Kochan

    (UHasselt—Hasselt University, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium)

  • Tom Bellemans

    (UHasselt—Hasselt University, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium)

Abstract

The travel demand prediction of an activity-based travel demand model (ABM) is based on a hierarchical structure of multiple choices related to an individual’s activity scheduling. This structure has, however, not been investigated for motorcycle-based cities. The coarseness of the traffic analysis zoning system combined with mixed land use results in a large proportion of intrazonal trips, which demands model enhancement in ABMs for these cities. Using large-scale household travel survey data from Ho Chi Minh City, a major motorcycle-based city in Vietnam, this study investigated the hierarchical structure for non-work activity scheduling, with consideration of three dimensions: (1) activity starting time, (2) travel mode, and (3) destination choices at the tour level with attention given to the impacts of intrazonal tours. Multinomial logit and nested logit models were adopted for model development. Results showed that work durations in the schedule strongly affected the scheduling of non-work activities. The estimated logsum parameters showed empirical evidence that hierarchy could be different for different activity types. Our findings also suggested a significant impact of intrazonal tours on the structuring and modeling of activity scheduling choices. The validation result indicated that our proposed models’ predictive capability is acceptable.

Suggested Citation

  • Thuy Linh Hoang & Muhammad Adnan & Anh Tuan Vu & Nguyen Hoang-Tung & Bruno Kochan & Tom Bellemans, 2022. "Modeling and Structuring of Activity Scheduling Choices with Consideration of Intrazonal Tours: A Case Study of Motorcycle-Based Cities," Sustainability, MDPI, vol. 14(10), pages 1-23, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6367-:d:822185
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/10/6367/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/10/6367/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sanjana Hossain & Md. Sami Hasnine & Khandker Nurul Habib, 2021. "A latent class joint mode and departure time choice model for the Greater Toronto and Hamilton Area," Transportation, Springer, vol. 48(3), pages 1217-1239, June.
    2. T. Abrahamsson & L. Lundqvist, 1999. "Formulation and Estimation of Combined Network Equilibrium Models with Applications to Stockholm," Transportation Science, INFORMS, vol. 33(1), pages 80-100, February.
    3. Ouassim Manout & Patrick Bonnel, 2019. "The impact of ignoring intrazonal trips in assignment models: a stochastic approach," Transportation, Springer, vol. 46(6), pages 2397-2417, December.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    5. Susan Handy & Kelly Clifton, 2001. "Local shopping as a strategy for reducing automobile travel," Transportation, Springer, vol. 28(4), pages 317-346, November.
    6. 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.
    7. Jeffrey Newman & Vincent Bernardin, 2010. "Hierarchical ordering of nests in a joint mode and destination choice model," Transportation, Springer, vol. 37(4), pages 677-688, July.
    8. Soora Rasouli & Harry Timmermans, 2014. "Activity-based models of travel demand: promises, progress and prospects," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 18(1), pages 31-60, March.
    9. Keunhyun Park & Sadegh Sabouri & Torrey Lyons & Guang Tian & Reid Ewing, 2020. "Intrazonal or interzonal? Improving intrazonal travel forecast in a four-step travel demand model," Transportation, Springer, vol. 47(5), pages 2087-2108, October.
    10. Ho, Chinh Q. & Hensher, David A. & Wang, Shangbo, 2020. "Joint estimation of mode and time of day choice accounting for arrival time flexibility, travel time reliability and crowding on public transport," Journal of Transport Geography, Elsevier, vol. 87(C).
    11. Auld, Joshua & Mohammadian, Abolfazl(Kouros), 2012. "Activity planning processes in the Agent-based Dynamic Activity Planning and Travel Scheduling (ADAPTS) model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1386-1403.
    12. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304.
    13. Bhat, Chandra R., 1998. "Analysis of travel mode and departure time choice for urban shopping trips," Transportation Research Part B: Methodological, Elsevier, vol. 32(6), pages 361-371, August.
    14. Daly, Andrew, 1982. "Estimating choice models containing attraction variables," Transportation Research Part B: Methodological, Elsevier, vol. 16(1), pages 5-15, February.
    15. Cervero, Robert B., 2013. "Linking urban transport and land use in developing countries," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 6(1), pages 7-24.
    16. Bhatta, Bharat P. & Larsen, Odd I., 2011. "Are intrazonal trips ignorable?," Transport Policy, Elsevier, vol. 18(1), pages 13-22, January.
    17. Sean Doherty & Abolfazl Mohammadian, 2011. "The validity of using activity type to structure tour-based scheduling models," Transportation, Springer, vol. 38(1), pages 45-63, January.
    18. Martin Dijst & Velibor Vidakovic, 2000. "Travel time ratio: the key factor of spatial reach," Transportation, Springer, vol. 27(2), pages 179-199, May.
    19. Malayath, Manoj & Verma, Ashish, 2013. "Activity based travel demand models as a tool for evaluating sustainable transportation policies," Research in Transportation Economics, Elsevier, vol. 38(1), pages 45-66.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ozonder, Gozde & Miller, Eric J., 2021. "Longitudinal investigation of skeletal activity episode timing decisions – A copula approach," Journal of choice modelling, Elsevier, vol. 40(C).
    2. Siliang Luan & Qingfang Yang & Zhongtai Jiang & Huxing Zhou & Fanyun Meng, 2022. "Analyzing Commute Mode Choice Using the LCNL Model in the Post-COVID-19 Era: Evidence from China," IJERPH, MDPI, vol. 19(9), pages 1-26, April.
    3. Saleh, Wafaa & Farrell, Séona, 2005. "Implications of congestion charging for departure time choice: Work and non-work schedule flexibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 773-791.
    4. Zhifeng Gao & Ted C. Schroeder, 2009. "Consumer responses to new food quality information: are some consumers more sensitive than others?," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 339-346, May.
    5. Ortega, David L. & Wang, H. Holly & Wu, Laping & Hong, Soo Jeong, 2015. "Retail channel and consumer demand for food quality in China," China Economic Review, Elsevier, vol. 36(C), pages 359-366.
    6. Yamada, Katsunori & Sato, Masayuki, 2013. "Another avenue for anatomy of income comparisons: Evidence from hypothetical choice experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 89(C), pages 35-57.
    7. Potoglou, Dimitris & Palacios, Juan & Feijoo, Claudio & Gómez Barroso, Jose-Luis, 2015. "The supply of personal information: A study on the determinants of information provision in e-commerce scenarios," 26th European Regional ITS Conference, Madrid 2015 127174, International Telecommunications Society (ITS).
    8. Sant'Anna, Ana Claudia & Bergtold, Jason & Shanoyan, Aleksan & Caldas, Marcellus & Granco, Gabriel, 2021. "Deal or No Deal? Analysis of Bioenergy Feedstock Contract Choice with Multiple Opt-out Options and Contract Attribute Substitutability," 2021 Conference, August 17-31, 2021, Virtual 315289, International Association of Agricultural Economists.
    9. Choi, Andy S., 2013. "Nonmarket values of major resources in the Korean DMZ areas: A test of distance decay," Ecological Economics, Elsevier, vol. 88(C), pages 97-107.
    10. Doherty, Edel & Campbell, Danny, 2011. "Demand for improved food safety and quality: a cross-regional comparison," 85th Annual Conference, April 18-20, 2011, Warwick University, Coventry, UK 108791, Agricultural Economics Society.
    11. Kesternich, Iris & Heiss, Florian & McFadden, Daniel & Winter, Joachim, 2013. "Suit the action to the word, the word to the action: Hypothetical choices and real decisions in Medicare Part D," Journal of Health Economics, Elsevier, vol. 32(6), pages 1313-1324.
    12. David Hensher & John Rose & Zheng Li, 2012. "Does the choice model method and/or the data matter?," Transportation, Springer, vol. 39(2), pages 351-385, March.
    13. Qin, Pin & Carlsson, Fredrik & Xu, Jintao, 2009. "Forestland Reform in China: What do the Farmers Want? A Choice Experiment on Farmers’ Property Rights Preferences," Working Papers in Economics 370, University of Gothenburg, Department of Economics.
    14. Clark, Andrew E. & Senik, Claudia & Yamada, Katsunori, 2017. "When experienced and decision utility concur: The case of income comparisons," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 70(C), pages 1-9.
    15. Ping Qin & Fredrik Carlsson & Jintao Xu, 2011. "Forest Tenure Reform in China: A Choice Experiment on Farmers’ Property Rights Preferences," Land Economics, University of Wisconsin Press, vol. 87(3), pages 473-487.
    16. Joachim Marti, 2012. "Assessing preferences for improved smoking cessation medications: a discrete choice experiment," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(5), pages 533-548, October.
    17. Lorenzo Masiero & Juan L. Nicolau, 2012. "Price Sensitivity to Tourism Activities: Looking for Determinant Factors," Tourism Economics, , vol. 18(4), pages 675-689, August.
    18. Dugstad, Anders & Grimsrud, Kristine & Kipperberg, Gorm & Lindhjem, Henrik & Navrud, Ståle, 2020. "Acceptance of wind power development and exposure – Not-in-anybody's-backyard," Energy Policy, Elsevier, vol. 147(C).
    19. Mohammed H. Alemu & Søren Bøye Olsen & Suzanne E. Vedel & John Kinyuru & Kennedy O. Pambo, 2016. "Integrating sensory evaluations in incentivized discrete choice experiments to assess consumer demand for cricket flour buns in Kenya," IFRO Working Paper 2016/02, University of Copenhagen, Department of Food and Resource Economics.
    20. Ida, Takanori & Goto, Rei & Takahashi, Yuko & Nishimura, Shuzo, 2011. "Can economic-psychological parameters predict successful smoking cessation?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(3), pages 285-295, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6367-:d:822185. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.