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Analysis of variability in multi-day GPS imputed activity-travel diaries using multi-dimensional sequence alignment and panel effects regression models

Author

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  • Jianchuan Xianyu

    (Shanghai Dian Ji University)

  • Soora Rasouli

    (Eindhoven University of Technology)

  • Harry Timmermans

    (Eindhoven University of Technology)

Abstract

The use of GPS devices and smartphones has made feasible the collection of multi-day activity-travel diaries. In turn, the availability of multi-day travel diary data opens up new avenues for analyzing dynamics of individual travel behavior. This paper addresses the issue of day-to-day variability in activity-travel behavior. The study, which is the first of its kind in China, applies a unique combination of methods to analyze the degree of dissimilarity between travel days using multi-day GPS data. First, multi-dimensional sequence alignment is applied to measure the degree of dissimilarity in individual daily activity-travel sequences between pairs of travel days. Next, a series of panel effects regression models is used to estimate the effects of socio-demographics and days of the week. The models are estimated using multi-day activity-travel patterns imputed from GPS-enabled smartphone data collected in Shanghai, China. Results indicate that (1) days of the week have significant effects on day-to-day variability in activity-travel behavior with weekday activity-travel sequences being more similar and thereby different from weekend sequences; (2) the degree of dissimilarity in activity-travel sequences is strongly influenced by respondent socio-demographic profiles; (3) individuals having more control over and flexibility in their work schedule show greater intra-personal variability. Day-to-day variability in activity-travel behavior of this sample is similar to patterns observed in developed countries in some aspects but different in others. Strict international comparison study based on comparative data collection is required to further distinguish the sources of travel behavior differences between developing countries and developed countries. The paper ends with a discussion of the limitations of this study and the implications of the research findings for future research.

Suggested Citation

  • 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.
    • Handle: RePEc:kap:transp:v:44:y:2017:i:3:d:10.1007_s11116-015-9666-2
    DOI: 10.1007/s11116-015-9666-2
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    References listed on IDEAS

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    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. 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.
    3. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-793, May.
    4. MacKinnon, James G. & White, Halbert & Davidson, Russell, 1983. "Tests for model specification in the presence of alternative hypotheses : Some further results," Journal of Econometrics, Elsevier, vol. 21(1), pages 53-70, January.
    5. Clarke Wilson, 2008. "Activity patterns in space and time: calculating representative Hagerstrand trajectories," Transportation, Springer, vol. 35(4), pages 485-499, July.
    6. Lee, Yuhwa & Hickman, Mark & Washington, Simon, 2007. "Household type and structure, time-use pattern, and trip-chaining behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1004-1020, December.
    7. Hensher, David A. & Rose, John M., 2007. "Development of commuter and non-commuter mode choice models for the assessment of new public transport infrastructure projects: A case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 428-443, June.
    8. W C Wilson, 1998. "Activity Pattern Analysis by Means of Sequence-Alignment Methods," Environment and Planning A, , vol. 30(6), pages 1017-1038, June.
    9. Saarloos, Dick & Joh, Chang-Hyeon & Zhang, Junyi & Fujiwara, Akimasa, 2010. "A segmentation study of pedestrian weekend activity patterns in a central business district," Journal of Retailing and Consumer Services, Elsevier, vol. 17(2), pages 119-129.
    10. Mark Bradley & Peter Vovsha, 2005. "A model for joint choice of daily activity pattern types of household members," Transportation, Springer, vol. 32(5), pages 545-571, September.
    11. Paul Kelly & Patricia Krenn & Sylvia Titze & Peter Stopher & Charlie Foster, 2013. "Quantifying the Difference Between Self-Reported and Global Positioning Systems-Measured Journey Durations: A Systematic Review," Transport Reviews, Taylor & Francis Journals, vol. 33(4), pages 443-459, July.
    12. 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.
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    Cited by:

    1. Allahviranloo, Mahdieh & Aissaoui, Leila, 2019. "A comparison of time-use behavior in metropolitan areas using pattern recognition techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 271-287.
    2. Ho, Hillbun & Tien, Keng-Ming (Terence) & Wu, Anne & Singh, Sonika, 2021. "A sequence analysis approach to segmenting credit card customers," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    3. Shi, Hui & Su, Rongxiang & Xiao, Jingyi & Goulias, Konstadinos G., 2022. "Spatiotemporal analysis of activity-travel fragmentation based on spatial clustering and sequence analysis," Journal of Transport Geography, Elsevier, vol. 102(C).
    4. Kim, Seheon & Rasouli, Soora & Timmermans, Harry & Yang, Dujuan, 2018. "Estimating panel effects in probabilistic representations of dynamic decision trees using bayesian generalized linear mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 168-184.
    5. Nan Ye & Linjie Gao & Zhicai Juan & Anning Ni, 2018. "Are People from Households with Children More Likely to Travel by Car? An Empirical Investigation of Individual Travel Mode Choices in Shanghai, China," Sustainability, MDPI, vol. 10(12), pages 1-14, December.
    6. Huang, Yuqiao & Gao, Linjie & Ni, Anning & Liu, Xiaoning, 2021. "Analysis of travel mode choice and trip chain pattern relationships based on multi-day GPS data: A case study in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 93(C).
    7. Everhart, Avery R. & Ferguson, Laura & Wilson, John P., 2022. "Construction and validation of a spatial database of providers of transgender hormone therapy in the US," Social Science & Medicine, Elsevier, vol. 303(C).
    8. Lingjuan Chen & Yijing Zhao & Zupeng Liu & Xinran Yang, 2022. "Construction of Commuters’ Multi-Mode Choice Model Based on Public Transport Operation Data," Sustainability, MDPI, vol. 14(22), pages 1-20, November.

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