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Understanding activity engagement across weekdays and weekend days: A multivariate multiple discrete-continuous modeling approach

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  • Astroza, Sebastian
  • Bhat, Prerna C.
  • Bhat, Chandra R.
  • Pendyala, Ram M.
  • Garikapati, Venu M.

Abstract

This paper is motivated by the increasing recognition that modeling activity-travel demand for a single day of the week, as is done in virtually all travel forecasting models, may be inadequate in capturing underlying processes that govern activity-travel scheduling behavior. The considerable variability in daily travel suggests that there are important complementary relationships and competing tradeoffs involved in scheduling and allocating time to various activities across days of the week. Both limited survey data availability and methodological challenges in modeling week-long activity-travel schedules have precluded the development of multi-day activity-travel demand models. With passive and technology-based data collection methods increasingly in vogue, the collection of multi-day travel data may become increasingly commonplace in the years ahead. This paper addresses the methodological challenge associated with modeling multi-day activity-travel demand by formulating a multivariate multiple discrete-continuous probit (MDCP) model system. The comprehensive framework ties together two MDCP model components, one corresponding to weekday time allocation and the other to weekend activity-time allocation. By tying the two MDCP components together, the model system also captures relationships in activity-time allocation between weekdays on the one hand and weekend days on the other. Model estimation on a week-long travel diary data set from the United Kingdom shows that there are significant inter-relationships between weekdays and weekend days in activity-travel scheduling behavior. The model system presented in this paper may serve as a higher-level multi-day activity scheduler in conjunction with existing daily activity-based travel models.

Suggested Citation

  • Astroza, Sebastian & Bhat, Prerna C. & Bhat, Chandra R. & Pendyala, Ram M. & Garikapati, Venu M., 2018. "Understanding activity engagement across weekdays and weekend days: A multivariate multiple discrete-continuous modeling approach," Journal of choice modelling, Elsevier, vol. 28(C), pages 56-70.
    • Handle: RePEc:eee:eejocm:v:28:y:2018:i:c:p:56-70
    DOI: 10.1016/j.jocm.2018.05.004
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    Cited by:

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    2. Pellegrini, Andrea & Pinjari, Abdul Rawoof & Maggi, Rico, 2021. "A multiple discrete continuous model of time use that accommodates non-additively separable utility functions along with time and monetary budget constraints," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 37-53.
    3. Saxena, Shobhit & Pinjari, Abdul Rawoof & Paleti, Rajesh, 2022. "A multiple discrete-continuous extreme value model with ordered preferences (MDCEV-OP): Modelling framework for episode-level activity participation and time-use analysis," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 259-283.
    4. Rodrigo J. Tapia & Gerard Jong & Ana M. Larranaga & Helena B. Bettella Cybis, 2021. "Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina," Networks and Spatial Economics, Springer, vol. 21(3), pages 581-608, September.
    5. Dubey, Subodh & Cats, Oded & Hoogendoorn, Serge & Bansal, Prateek, 2022. "A multinomial probit model with Choquet integral and attribute cut-offs," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 140-163.
    6. Sarangi, Punyabeet & Manoj, M., 2022. "Task-allocation among adult household members by activity purpose and accompanying person," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 246-266.
    7. Deschaintres, Elodie & Morency, Catherine & Trépanier, Martin, 2022. "Cross-analysis of the variability of travel behaviors using one-day trip diaries and longitudinal data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 228-246.

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