[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/eejocm/v40y2021ics1755534521000397.html
   My bibliography  Save this article

Longitudinal investigation of skeletal activity episode timing decisions – A copula approach

Author

Listed:
  • Ozonder, Gozde
  • Miller, Eric J.
Abstract
This study proposes a joint modelling approach to simulate episode timing decisions of skeletal activities -- activities that typically take precedence in the scheduling process -- using copulas. The analyses focus on examining the correlation between activity start time and duration while exploring the timing behaviour over a 20-year period between 1996 and 2016 in the Greater Toronto and Hamilton Area. For three types of agent classes (“Worker”, “Student”, “Both”), timing decisions associated with three skeletal activities are investigated: “Work”, “Work Business” and “School”. To obtain mutually exclusive homogeneous subsamples, further segmentation of agents is undertaken considering employment and/or student status, and occupation of the individuals. Parametric models are fitted independently to marginal start time and duration distributions using finite mixture models before estimating copula models for their joint distributions. In the “Worker” class, considerable stability is observed in “Work” activity timing models in all occupation sectors for full-time out-of-home employees, except for the “retail sales/service” sector. “Student” class agents’ “School” timing behaviour is also found to be stable in general for full-time students. More noise is observed in the timing behaviour of “Both” class agents. Given the correlation levels observed, it is concluded that start time and duration variables should be modelled jointly, not independently, within an agent-based, activity-based travel demand modelling framework. This paper demonstrates that it is possible to capture complex behaviour in timing decisions through parsimonious models that only utilize a small number of parameters and recommends exploiting behavioural information accrued over time while developing models.

Suggested Citation

  • Ozonder, Gozde & Miller, Eric J., 2021. "Longitudinal investigation of skeletal activity episode timing decisions – A copula approach," Journal of choice modelling, Elsevier, vol. 40(C).
    • Handle: RePEc:eee:eejocm:v:40:y:2021:i:c:s1755534521000397
    DOI: 10.1016/j.jocm.2021.100306
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1755534521000397
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jocm.2021.100306?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Arentze, Theo A. & Timmermans, Harry J. P., 2004. "A learning-based transportation oriented simulation system," Transportation Research Part B: Methodological, Elsevier, vol. 38(7), pages 613-633, August.
    2. Pawlak, Jacek & Polak, John W. & Sivakumar, Aruna, 2017. "A framework for joint modelling of activity choice, duration, and productivity while travelling," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 153-172.
    3. Jara-Díaz, Sergio & Rosales-Salas, Jorge, 2017. "Beyond transport time: A review of time use modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 209-230.
    4. Joe, H., 1993. "Parametric Families of Multivariate Distributions with Given Margins," Journal of Multivariate Analysis, Elsevier, vol. 46(2), pages 262-282, August.
    5. Pinjari, Abdul Rawoof & Bhat, Chandra, 2010. "A multiple discrete-continuous nested extreme value (MDCNEV) model: Formulation and application to non-worker activity time-use and timing behavior on weekdays," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 562-583, May.
    6. Eric Miller & Matthew Roorda & Juan Carrasco, 2005. "A tour-based model of travel mode choice," Transportation, Springer, vol. 32(4), pages 399-422, July.
    7. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    8. Ettema, Dick & Bastin, Fabian & Polak, John & Ashiru, Olu, 2007. "Modelling the joint choice of activity timing and duration," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(9), pages 827-841, November.
    9. Jeffrey Newman & Vincent Bernardin, 2010. "Hierarchical ordering of nests in a joint mode and destination choice model," Transportation, Springer, vol. 37(4), pages 677-688, July.
    10. Yan, Jun, 2007. "Enjoy the Joy of Copulas: With a Package copula," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 21(i04).
    11. Bhat, Chandra R. & Eluru, Naveen, 2009. "A copula-based approach to accommodate residential self-selection effects in travel behavior modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 749-765, August.
    12. Bhat, Chandra R., 2018. "A new flexible multiple discrete–continuous extreme value (MDCEV) choice model," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 261-279.
    13. Benaglia, Tatiana & Chauveau, Didier & Hunter, David R. & Young, Derek S., 2009. "mixtools: An R Package for Analyzing Mixture Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i06).
    14. Auld, Joshua & Mohammadian, Abolfazl(Kouros), 2012. "Activity planning processes in the Agent-based Dynamic Activity Planning and Travel Scheduling (ADAPTS) model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1386-1403.
    15. 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.
    16. Cooke, R.M. & Kurowicka, D. & Wilson, K., 2015. "Sampling, conditionalizing, counting, merging, searching regular vines," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 4-18.
    17. Erika Spissu & Abdul Pinjari & Ram Pendyala & Chandra Bhat, 2009. "A copula-based joint multinomial discrete–continuous model of vehicle type choice and miles of travel," Transportation, Springer, vol. 36(4), pages 403-422, July.
    18. Bhat, Chandra R., 1998. "Analysis of travel mode and departure time choice for urban shopping trips," Transportation Research Part B: Methodological, Elsevier, vol. 32(6), pages 361-371, August.
    19. Xiao Fu & William H. K. Lam, 2018. "Modelling joint activity-travel pattern scheduling problem in multi-modal transit networks," Transportation, Springer, vol. 45(1), pages 23-49, January.
    20. 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.
    21. 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.
    22. 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.
    23. Peter E. Rossi, 2014. "Bayesian Non- and Semi-parametric Methods and Applications," Economics Books, Princeton University Press, edition 1, number 10259.
    Full references (including those not matched with items on IDEAS)

    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. Khan, Mubassira & Machemehl, Randy, 2017. "Commercial vehicles time of day choice behavior in urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 68-83.
    2. Pudāne, Baiba & van Cranenburgh, Sander & Chorus, Caspar G., 2021. "A day in the life with an automated vehicle: Empirical analysis of data from an interactive stated activity-travel survey," Journal of choice modelling, Elsevier, vol. 39(C).
    3. 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.
    4. Shasha Liu & Toshiyuki Yamamoto & Enjian Yao, 2023. "Joint modeling of mode choice and travel distance with intra-household interactions," Transportation, Springer, vol. 50(5), pages 1527-1552, October.
    5. 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.
    6. Calastri, Chiara & Giergiczny, Marek & Zedrosser, Andreas & Hess, Stephane, 2023. "Modelling activity patterns of wild animals - An application of the multiple discrete-continuous extreme value (MDCEV) model," Journal of choice modelling, Elsevier, vol. 47(C).
    7. Bhat, Chandra R. & Mondal, Aupal & Asmussen, Katherine E. & Bhat, Aarti C., 2020. "A multiple discrete extreme value choice model with grouped consumption data and unobserved budgets," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 196-222.
    8. Vo, Khoa D. & Lam, William H.K. & Chen, Anthony & Shao, Hu, 2020. "A household optimum utility approach for modeling joint activity-travel choices in congested road networks," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 93-125.
    9. Ipek Sener & Chandra Bhat, 2012. "Modeling the spatial and temporal dimensions of recreational activity participation with a focus on physical activities," Transportation, Springer, vol. 39(3), pages 627-656, May.
    10. Annesha Enam & Karthik C. Konduri & Naveen Eluru & Srinath Ravulaparthy, 2018. "Relationship between well-being and daily time use of elderly: evidence from the disabilities and use of time survey," Transportation, Springer, vol. 45(6), pages 1783-1810, November.
    11. Pinjari, Abdul Rawoof & Bhat, Chandra, 2010. "A multiple discrete-continuous nested extreme value (MDCNEV) model: Formulation and application to non-worker activity time-use and timing behavior on weekdays," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 562-583, May.
    12. Enam, Annesha & Konduri, Karthik C. & Pinjari, Abdul R. & Eluru, Naveen, 2018. "An integrated choice and latent variable model for multiple discrete continuous choice kernels: Application exploring the association between day level moods and discretionary activity engagement choi," Journal of choice modelling, Elsevier, vol. 26(C), pages 80-100.
    13. Sobhani, Anae & Eluru, Naveen & Faghih-Imani, Ahmadreza, 2013. "A latent segmentation based multiple discrete continuous extreme value model," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 154-169.
    14. 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.
    15. Nurul Habib, Khandker M. & Day, Nicholas & Miller, Eric J., 2009. "An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(7), pages 639-653, August.
    16. Sabreena Anowar & Naveen Eluru & Luis F. Miranda-Moreno, 2014. "Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review," Transport Reviews, Taylor & Francis Journals, vol. 34(4), pages 441-473, July.
    17. Jokubauskaitė, Simona & Hössinger, Reinhard & Aschauer, Florian & Gerike, Regine & Jara-Díaz, Sergio & Peer, Stefanie & Schmid, Basil & Axhausen, Kay W. & Leisch, Friedrich, 2019. "Advanced continuous-discrete model for joint time-use expenditure and mode choice estimation," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 397-421.
    18. Bhat, Chandra R. & Sener, Ipek N. & Eluru, Naveen, 2010. "A flexible spatially dependent discrete choice model: Formulation and application to teenagers' weekday recreational activity participation," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 903-921, September.
    19. Rajesh Paleti & Rachel Copperman & Chandra Bhat, 2011. "An empirical analysis of children’s after school out-of-home activity-location engagement patterns and time allocation," Transportation, Springer, vol. 38(2), pages 273-303, March.
    20. Xuemei Fu & Zhicai Juan, 2017. "An integrated framework to jointly model decisions of activity time allocation and work-related travel," Transportation Planning and Technology, Taylor & Francis Journals, vol. 40(6), pages 689-705, August.

    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:eee:eejocm:v:40:y:2021:i:c:s1755534521000397. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/journal-of-choice-modelling .

    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.