IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v35y2001i1p61-79.html
   My bibliography  Save this article

Modeling the Commute Activity-Travel Pattern of Workers: Formulation and Empirical Analysis

Author

Listed:
  • Chandra Bhat

    (Department of Civil Engineering, ECJ 6.810, University of Texas at Austin, Austin, Texas 78712)

Abstract

This paper proposes a methodological framework to analyze the activity and travel pattern of workers during the evening commute. The framework uses a discrete-continuous econometric system to model jointly the decision to participate in an activity during the evening commute and the following attributes of the participation: activity type, activity duration, and travel time deviation to the activity location relative to the direct travel time from work to home. The model parameters are estimated using a sample of workers from the 1991 Boston Household Activity Survey. The paper also presents mathematical expressions to evaluate the effect of changes in sociodemographic variables and policy-relevant exogenous variables on the temporal pattern of trips and cold starts attributable to commute stops. The application of the model indicates that failure to accommodate the joint nature of the activity decisions during the evening commute can lead to misdirected policy actions for traffic congestion alleviation and for mobile-source emissions reduction.

Suggested Citation

  • Chandra Bhat, 2001. "Modeling the Commute Activity-Travel Pattern of Workers: Formulation and Empirical Analysis," Transportation Science, INFORMS, vol. 35(1), pages 61-79, February.
    • Handle: RePEc:inm:ortrsc:v:35:y:2001:i:1:p:61-79
    DOI: 10.1287/trsc.35.1.61.10142
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.35.1.61.10142
    Download Restriction: no
    File URL: https://libkey.io/10.1287/trsc.35.1.61.10142?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Mohammad M. Hamed & Fred L. Mannering, 1993. "Modeling Travelers' Postwork Activity Involvement: Toward a New Methodology," Transportation Science, INFORMS, vol. 27(4), pages 381-394, November.
    2. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
    3. Bhat, Chandra R., 1996. "A hazard-based duration model of shopping activity with nonparametric baseline specification and nonparametric control for unobserved heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 30(3), pages 189-207, June.
    4. Bhat, Chandra R. & Singh, Sujit K., 2000. "A comprehensive daily activity-travel generation model system for workers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(1), pages 1-22, January.
    5. Kondo, Katsunao & Kitamura, Ryuichi, 1987. "Time-space constraints and the formation of trip chains," Regional Science and Urban Economics, Elsevier, vol. 17(1), pages 49-65, February.
    6. Bhat, Chandra R., 1998. "A model of post home-arrival activity participation behavior," Transportation Research Part B: Methodological, Elsevier, vol. 32(6), pages 387-400, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Usman Ahmed & Ana Tsui Moreno & Rolf Moeckel, 2021. "Microscopic activity sequence generation: a multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes," Transportation, Springer, vol. 48(3), pages 1481-1502, June.
    2. Jianchuan Xianyu & Soora Rasouli & Harry Timmermans, 2017. "Analysis of variability in multi-day GPS imputed activity-travel diaries using multi-dimensional sequence alignment and panel effects regression models," Transportation, Springer, vol. 44(3), pages 533-553, May.
    3. Rongrong Hong & Wenming Rao & Dong Zhou & Chengchuan An & Zhenbo Lu & Jingxin Xia, 2020. "Commuting Pattern Recognition Using a Systematic Cluster Framework," Sustainability, MDPI, vol. 12(5), pages 1-20, February.
    4. Bautista-Hernández, Dorian Antonio, 2022. "Individual, household, and urban form determinants of trip chaining of non-work travel in México City," Journal of Transport Geography, Elsevier, vol. 98(C).
    5. Usman Ahmed & Ana Tsui Moreno & Rolf Moeckel, 0. "Microscopic activity sequence generation: a multiple correspondence analysis to explain travel behavior based on socio-demographic person attributes," Transportation, Springer, vol. 0, pages 1-22.
    6. Jingni Song & Feng Chen & Qunqi Wu & Weiyu Liu & Feiyang Xue & Kai Du, 2019. "Optimization of Passenger Transportation Corridor Mode Supply Structure in Regional Comprehensive Transport Considering Economic Equilibrium," Sustainability, MDPI, vol. 11(4), pages 1-18, February.
    7. Stephan Brunow & Manuela Gründer, 2013. "The impact of activity chaining on the duration of daily activities," Transportation, Springer, vol. 40(5), pages 981-1001, September.
    8. Irene Casas & Mei‐Po Kwan, 2007. "The Impact of Real‐Time Information on Choices During the Commute Trip: Evidence from a Travel Simulator," Growth and Change, Wiley Blackwell, vol. 38(4), pages 523-543, December.
    9. Ta, Na & Zhao, Ying & Chai, Yanwei, 2016. "Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data," Journal of Transport Geography, Elsevier, vol. 57(C), pages 161-170.
    10. Calastri, Chiara & Hess, Stephane & Daly, Andrew & Carrasco, Juan Antonio, 2017. "Does the social context help with understanding and predicting the choice of activity type and duration? An application of the Multiple Discrete-Continuous Nested Extreme Value model to activity diary," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 1-20.

    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. 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.
    2. Bhat, Chandra R. & Steed, Jennifer L., 2002. "A continuous-time model of departure time choice for urban shopping trips," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 207-224, March.
    3. Bhat, Chandra R., 1996. "A generalized multiple durations proportional hazard model with an application to activity behavior during the evening work-to-home commute," Transportation Research Part B: Methodological, Elsevier, vol. 30(6), pages 465-480, December.
    4. Wang, Rui, 2015. "The stops made by commuters: evidence from the 2009 US National Household Travel Survey," Journal of Transport Geography, Elsevier, vol. 47(C), pages 109-118.
    5. Bhat, Chandra R. & Mondal, Aupal, 2022. "A New Flexible Generalized Heterogeneous Data Model (GHDM) with an Application to Examine the Effect of High Density Neighborhood Living on Bicycling Frequency," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 244-266.
    6. Bhat, Chandra R. & Singh, Sujit K., 2000. "A comprehensive daily activity-travel generation model system for workers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(1), pages 1-22, January.
    7. Bowman, J. L. & Ben-Akiva, M. E., 2001. "Activity-based disaggregate travel demand model system with activity schedules," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(1), pages 1-28, January.
    8. Hemant Gehlot & Arif M. Sadri & Satish V. Ukkusuri, 2019. "Joint modeling of evacuation departure and travel times in hurricanes," Transportation, Springer, vol. 46(6), pages 2419-2440, December.
    9. Marcela Munizaga & Sergio Jara-Díaz & Paulina Greeven & Chandra Bhat, 2008. "Econometric Calibration of the Joint Time Assignment--Mode Choice Model," Transportation Science, INFORMS, vol. 42(2), pages 208-219, May.
    10. Bhat, Chandra R., 1997. "Work travel mode choice and number of non-work commute stops," Transportation Research Part B: Methodological, Elsevier, vol. 31(1), pages 41-54, February.
    11. Zidan Mao & Dick Ettema & Martin Dijst, 2018. "Analysis of travel time and mode choice shift for non-work stops in commuting: case study of Beijing, China," Transportation, Springer, vol. 45(3), pages 751-766, May.
    12. Italo Meloni & Erika Spissu & Massimiliano Bez, 2007. "A Model of the Dynamic Process of Time Allocation to Discretionary Activities," Transportation Science, INFORMS, vol. 41(1), pages 15-28, February.
    13. Nam, Doohee & Mannering, Fred, 2000. "An exploratory hazard-based analysis of highway incident duration," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(2), pages 85-102, February.
    14. Bhat, Chandra, 1999. "An analysis of evening commute stop-making behavior using repeated choice observations from a multi-day survey," Transportation Research Part B: Methodological, Elsevier, vol. 33(7), pages 495-510, September.
    15. Joshua Wang & Eric J Miller, 2014. "A Prism-Based and Gap-Based Approach to Shopping Location Choice," Environment and Planning B, , vol. 41(6), pages 977-1005, December.
    16. Chandra Bhat & Frank Koppelman, 1999. "A retrospective and prospective survey of time-use research," Transportation, Springer, vol. 26(2), pages 119-139, May.
    17. Rezwana Rafiq & Michael G. McNally, 2021. "A study of tour formation: pre-, during, and post-recession analysis," Transportation, Springer, vol. 48(5), pages 2187-2233, October.
    18. Reinhard Hössinger & Florian Aschauer & Sergio Jara-Díaz & Simona Jokubauskaite & Basil Schmid & Stefanie Peer & Kay W. Axhausen & Regine Gerike, 2020. "A joint time-assignment and expenditure-allocation model: value of leisure and value of time assigned to travel for specific population segments," Transportation, Springer, vol. 47(3), pages 1439-1475, June.
    19. Bhat, Chandra R. & Srinivasan, Sivaramakrishnan, 2005. "A multidimensional mixed ordered-response model for analyzing weekend activity participation," Transportation Research Part B: Methodological, Elsevier, vol. 39(3), pages 255-278, March.
    20. Bhat, Chandra R. & Gossen, Rachel, 2004. "A mixed multinomial logit model analysis of weekend recreational episode type choice," Transportation Research Part B: Methodological, Elsevier, vol. 38(9), pages 767-787, November.

    More about this item

    Statistics

    Access and download statistics

    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:inm:ortrsc:v:35:y:2001:i:1:p:61-79. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.