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Examining the effects of out-of-home and in-home constraints on leisure activity participation in different seasons of the year

Author

Listed:
  • Nursitihazlin Ahmad Termida

    (KTH Royal Institute of Technology)

  • Yusak O. Susilo

    (KTH Royal Institute of Technology)

  • Joel P. Franklin

    (KTH Royal Institute of Technology)

Abstract

Using multi-day, multi-period travel diaries data of 56 days (four waves of two-week diaries) for 67 individuals in Stockholm, this study aims to examine the effects of out-of-home and in-home constraints (e.g. teleworking, studying at home, doing the laundry, cleaning and taking care of other household member[s]) on individuals’ day-to-day leisure activity participation decisions in four different seasons. This study also aims to explore the effects of various types of working schedules (fixed, shift, partial- and full-flexible) on individuals’ decisions to participate in day-to-day leisure activities. A pooled model (56 days) and wave-specific models (14 days in each wave) are estimated by using dynamic ordered Probit models. The effects of various types of working schedules are estimated by using 28 days of two waves’ data. The results show that an individual’s leisure activity participation decision is significantly influenced by out-of-home work durations but not influenced by in-home constraints, regardless of any seasons. Individuals with shift working hours engage less in day-to-day leisure activities than other workers’ types in both spring and summer seasons. The thermal indicator significantly affects individuals’ leisure activity participation decisions during the autumn season. Individuals exhibit routine behaviour characterized by repeated decisions in participating in day-to-day leisure activities that can last up to 14 days, regardless of any seasons.

Suggested Citation

  • Nursitihazlin Ahmad Termida & Yusak O. Susilo & Joel P. Franklin, 2016. "Examining the effects of out-of-home and in-home constraints on leisure activity participation in different seasons of the year," Transportation, Springer, vol. 43(6), pages 997-1021, November.
    • Handle: RePEc:kap:transp:v:43:y:2016:i:6:d:10.1007_s11116-016-9717-3
    DOI: 10.1007/s11116-016-9717-3
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    as
    1. Kitamura, Ryuichi & Yamamoto, Toshiyuki & Susilo, Yusak O. & Axhausen, Kay W., 2006. "How routine is a routine? An analysis of the day-to-day variability in prism vertex location," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(3), pages 259-279, March.
    2. Bernardo, Christina & Paleti, Rajesh & Hoklas, Megan & Bhat, Chandra, 2015. "An empirical investigation into the time-use and activity patterns of dual-earner couples with and without young children," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 71-91.
    3. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    4. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    6. Meurs, Henk & Van Wissen, Leo & Visser, Jacqueline, 1989. "Measurement Biases in Panel Data," University of California Transportation Center, Working Papers qt00q1x266, University of California Transportation Center.
    7. Kay Axhausen & Andrea Zimmermann & Stefan Schönfelder & Guido Rindsfüser & Thomas Haupt, 2002. "Observing the rhythms of daily life: A six-week travel diary," Transportation, Springer, vol. 29(2), pages 95-124, May.
    8. 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.
    9. Patricia L. Mokhtarian & Michael N. Bagley & Ilan Salomon, 1998. "The impact of gender, occupation, and presence of children on telecommuting motivations and constraints," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(12), pages 1115-1134.
    10. 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.
    11. Stanley, John K. & Hensher, David A. & Stanley, Janet R. & Vella-Brodrick, Dianne, 2011. "Mobility, social exclusion and well-being: Exploring the links," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(8), pages 789-801, October.
    12. Mokhtarian, Patricia L., 1990. "A Typology of Relationships Between Telecommunications And Transportation," University of California Transportation Center, Working Papers qt4rx589m0, University of California Transportation Center.
    13. Ahmad Termida, Nursitihazlin & Susilo, Yusak O. & Franklin, Joel P., 2016. "Observing dynamic behavioural responses due to the extension of a tram line by using panel survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 78-95.
    14. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D., 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, September.
    15. 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.
    16. Spinney, Jamie E.L. & Scott, Darren M. & Newbold, K. Bruce, 2009. "Transport mobility benefits and quality of life: A time-use perspective of elderly Canadians," Transport Policy, Elsevier, vol. 16(1), pages 1-11, January.
    17. Kitamura, Ryuichi, 1990. "Panel Analysis in Transportation Planning: An Overview," University of California Transportation Center, Working Papers qt86v0f7zh, University of California Transportation Center.
    18. Aguiléra, Anne & Guillot, Caroline & Rallet, Alain, 2012. "Mobile ICTs and physical mobility: Review and research agenda," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 664-672.
    19. Meurs, Henk & Van Wissen, Leo & Visser, Jacqueline, 1989. "Measurement Biases in Panel Data," University of California Transportation Center, Working Papers qt4095q216, University of California Transportation Center.
    20. 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.
    21. Erika Spissu & Abdul Pinjari & Chandra Bhat & Ram Pendyala & Kay Axhausen, 2009. "An analysis of weekly out-of-home discretionary activity participation and time-use behavior," Transportation, Springer, vol. 36(5), pages 483-510, September.
    22. 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.
    23. Liu, Chengxi & Susilo, Yusak O. & Karlström, Anders, 2014. "Examining the impact of weather variability on non-commuters’ daily activity–travel patterns in different regions of Sweden," Journal of Transport Geography, Elsevier, vol. 39(C), pages 36-48.
    24. 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.
    25. Patricia Mokhtarian & Ilan Salomon & Susan Handy, 2006. "The Impacts of Ict on leisure Activities and Travel: A Conceptual Exploration," Transportation, Springer, vol. 33(3), pages 263-289, May.
    26. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    27. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
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