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Timing utility of daily activities and its impact on travel

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  • Wang, James Jixian

Abstract

As an activity-based approach, this study focuses on the methodology of estimating the timing utility of people's daily activities and examines how such utility interacts with travel time. This study argues that the utility of time for undertaking a specific activity may vary over the course of day. That is, each activity has its ideal time to be undertaken. The utility of "saved" travel time thus depends on not only the value of travel time, but also "where" the "saved" time slot is "located" and the increasing utility due to rescheduling other activities to make use of this time slot. The estimation of such utility therefore needs a methodology to estimate people's timing choices and timing utility over all major daily activities. To achieve this goal, a two-stage simulation model is established. The hazard-rate duration is used to estimate the revealed preferences of Canadians on their major daily activities. The estimates are then applied to a scheduling program to examine how trip makers determine the optimal objective to maximize their total timing utility. With the results of this simulation, the tradeoff between travel time and the scheduling choices is examined and a commuter equilibrium is established on a basis of activity timing utility, work start-time, and travel time.

Suggested Citation

  • Wang, James Jixian, 1996. "Timing utility of daily activities and its impact on travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(3), pages 189-206, May.
    • Handle: RePEc:eee:transa:v:30:y:1996:i:3:p:189-206
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    References listed on IDEAS

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    1. Henderson, J. Vernon, 1981. "The economics of staggered work hours," Journal of Urban Economics, Elsevier, vol. 9(3), pages 349-364, May.
    2. Paul W. Wilson, 1989. "Scheduling Costs and the Value of Travel Time," Urban Studies, Urban Studies Journal Limited, vol. 26(3), pages 356-366, June.
    3. Harvey, A.S., 1992. "Changing Temporal Perspectives and the Canadian Metropolis," Papers 92-65, Saint Mary's - Department of Economics.
    4. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
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    Cited by:

    1. Stephane Hess & John Polak & Andrew Daly & Geoffrey Hyman, 2007. "Flexible substitution patterns in models of mode and time of day choice: new evidence from the UK and the Netherlands," Transportation, Springer, vol. 34(2), pages 213-238, March.
    2. Li, Zhi-Chun & Lam, William H.K. & Wong, S.C., 2014. "Bottleneck model revisited: An activity-based perspective," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 262-287.
    3. Iragaël Joly & Karl Littlejohn & Vincent Kaufmann, 2006. "La croissance des budgets-temps de transport en question : nouvelles approches," Post-Print halshs-00174992, HAL.
    4. Jason D. Lemp & Kara M. Kockelman & Paul Damien, 2012. "A Bivariate Multinomial Probit Model for Trip Scheduling: Bayesian Analysis of the Work Tour," Transportation Science, INFORMS, vol. 46(3), pages 405-424, August.
    5. Ram Pendyala & Chandra Bhat, 2004. "An Exploration of the Relationship between Timing and Duration of Maintenance Activities," Transportation, Springer, vol. 31(4), pages 429-456, November.
    6. Jindo Jeong & Jiwon Lee & Tae‐Hyoung Tommy Gim, 2022. "Travel mode choice as a representation of travel utility: A multilevel approach reflecting the hierarchical structure of trip, individual, and neighborhood characteristics," Papers in Regional Science, Wiley Blackwell, vol. 101(3), pages 745-765, June.
    7. Lemp, Jason D. & Kockelman, Kara M. & Damien, Paul, 2010. "The continuous cross-nested logit model: Formulation and application for departure time choice," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 646-661, June.
    8. Zhang, Xiaoning & Yang, Hai & Huang, Hai-Jun & Zhang, H. Michael, 2005. "Integrated scheduling of daily work activities and morning-evening commutes with bottleneck congestion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(1), pages 41-60, January.
    9. Lizana, Pedro & Ortúzar, Juan de Dios & Arellana, Julián & Rizzi, Luis I., 2021. "Forecasting with a joint mode/time-of-day choice model based on combined RP and SC data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 302-316.
    10. Dick Ettema & Olu Ashiru & John Polak & Fabian Bastin, 2005. "Taste Heterogeneity and Substitution Patterns in Models of the Simultaneous Choice of Activity Timing and Duration," ERSA conference papers ersa05p439, European Regional Science Association.
    11. Eva Gutiérrez-i-Puigarnau & Jos N. Van Ommeren, 2012. "Start Time and Worker Compensation Implications for Staggered-Hours Programmes," Journal of Transport Economics and Policy, University of Bath, vol. 46(2), pages 205-220, May.
    12. Andrew Daly & Stephane Hess & Geoff Hyman & John Polak & Charlene Rohr, 2005. "Modelling departure time and mode choice," ERSA conference papers ersa05p688, European Regional Science Association.
    13. Fosgerau, Mogens & Engelson, Leonid, 2011. "The value of travel time variance," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 1-8, January.
    14. Robin Lindsey, 2004. "Existence, Uniqueness, and Trip Cost Function Properties of User Equilibrium in the Bottleneck Model with Multiple User Classes," Transportation Science, INFORMS, vol. 38(3), pages 293-314, August.
    15. Yamamoto, Toshiyuki & Madre, Jean-Loup & Kitamura, Ryuichi, 2004. "An analysis of the effects of French vehicle inspection program and grant for scrappage on household vehicle transaction," Transportation Research Part B: Methodological, Elsevier, vol. 38(10), pages 905-926, December.

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