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An analysis of multiple interepisode durations using a unifying multivariate hazard model

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  • Bhat, Chandra R.
  • Srinivasan, Sivaramakrishnan
  • Axhausen, Kay W.

Abstract

This paper jointly examines the length between successive participations in several activity purposes using a 1999 multi-week travel survey conducted in the German cities of Halle and Karlsruhe. A multivariate hazard model that accommodates a flexible duration dynamics structure, recognizes the effects of covariates, incorporates the variation in interepisode duration due to unobserved individual-specific factors and variation in interepisode duration within spells of the same individual, and considers the joint nature of participation in the various activities is proposed and applied. The variables considered in the analysis include demographics, access to the internet, location characteristics, and day of week variables. The results indicate a very distinct weekly rhythm in individuals' participation in social, recreation, and personal business activities. While there is a similar rhythm even for participation in shopping activities, it is not as pronounced as for the non-shopping activity purposes. Also, individuals and spouse attributes, household characteristics, residential location and trip-making variables, and day of week effects have a strong influence on interepisode durations.

Suggested Citation

  • Bhat, Chandra R. & Srinivasan, Sivaramakrishnan & Axhausen, Kay W., 2005. "An analysis of multiple interepisode durations using a unifying multivariate hazard model," Transportation Research Part B: Methodological, Elsevier, vol. 39(9), pages 797-823, November.
  • Handle: RePEc:eee:transb:v:39:y:2005:i:9:p:797-823
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    References listed on IDEAS

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    Cited by:

    1. Darren M. Scott & Kenneth Bruce Newbold & Jamie E.L. Spinney & Ruben Mercado & Antonio Páez & Pavlos S. Kanaroglou, 2009. "New Insights into Senior Travel Behavior: The Canadian Experience," Growth and Change, Wiley Blackwell, vol. 40(1), pages 140-168, March.
    2. Lin, Tao & Wang, Donggen & Zhou, Meng, 2018. "Residential relocation and changes in travel behavior: what is the role of social context change?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 360-374.
    3. Lee, Backjin & Timmermans, Harry J.P., 2007. "A latent class accelerated hazard model of activity episode durations," Transportation Research Part B: Methodological, Elsevier, vol. 41(4), pages 426-447, May.
    4. Elisabetta Cherchi & Cinzia Cirillo, 2014. "Understanding variability, habit and the effect of long period activity plan in modal choices: a day to day, week to week analysis on panel data," Transportation, Springer, vol. 41(6), pages 1245-1262, November.
    5. Arentze, Theo A. & Ettema, Dick & Timmermans, Harry J.P., 2011. "Estimating a model of dynamic activity generation based on one-day observations: Method and results," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 447-460, February.
    6. Elias, Wafa & Benjamin, Julian & Shiftan, Yoram, 2015. "Gender differences in activity and travel behavior in the Arab world," Transport Policy, Elsevier, vol. 44(C), pages 19-27.
    7. Abdul Rawoof Pinjari & Chandra R. Bhat, 2011. "Activity-based Travel Demand Analysis," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 10, Edward Elgar Publishing.
    8. Tai-Yu Ma & Charles Raux & Eric Cornelis & Iragaël Joly, 2009. "multi-state non-homogeneous semi-markov model of daily activity type, timing and duration sequence," Post-Print halshs-00310900, HAL.
    9. Eisenmann, Christine & Buehler, Ralph, 2018. "Are cars used differently in Germany than in California? Findings from annual car-use profiles," Journal of Transport Geography, Elsevier, vol. 69(C), pages 171-180.
    10. Jara-Díaz, Sergio & Rosales-Salas, Jorge, 2015. "Understanding time use: Daily or weekly data?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 38-57.
    11. Dick Ettema & Tanja Lippe, 2009. "Weekly rhythms in task and time allocation of households," Transportation, Springer, vol. 36(2), pages 113-129, March.
    12. Kang, Hejun & Scott, Darren M., 2010. "Exploring day-to-day variability in time use for household members," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(8), pages 609-619, October.
    13. Bhat, Chandra R. & Guo, Jessica Y., 2007. "A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels," Transportation Research Part B: Methodological, Elsevier, vol. 41(5), pages 506-526, June.
    14. Christina Milioti & Konstantinos Kepaptsoglou & Alexandros Deloukas & Gerasimos Prodromitis & Christina Iliopoulou, 2019. "Modeling traveler recovery time following man-made incidents: the case of the Athens metro," Journal of Transportation Security, Springer, vol. 12(3), pages 103-117, December.
    15. Esra Suel & Nicolò Daina & John W. Polak, 2018. "A hazard-based approach to modelling the effects of online shopping on intershopping duration," Transportation, Springer, vol. 45(2), pages 415-428, March.

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