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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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    Cited by:

    1. 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.
    2. 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).
    3. 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.
    4. 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).
    5. 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).
    6. 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.
    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. 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.

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