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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

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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.

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Acknowledgments

This research is supported by the China Postdoctoral Science Foundation (2012M520904; 2013T60452) and Innovation Program of Shanghai Municipal Education Commission (15ZS078). Three anonymous reviewers provided valuable comments for improvement of an earlier version of this paper. The contents of the paper reflect the views of the writers who are responsible for the facts and accuracy of the information presented. The contents do not necessarily reflect the official views of the Business School of Shanghai Dian Ji University.

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  1. Business School, Shanghai Dian Ji University, 1350 Ganlan Rd., Shanghai, 201306, People’s Republic of China

    Jianchuan Xianyu

  2. Urban Planning Group, Department of Urban Science and Systems, Eindhoven University of Technology, PO Box 513, 5600MB, Eindhoven, The Netherlands

    Soora Rasouli & Harry Timmermans

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  1. Jianchuan Xianyu
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Correspondence to Jianchuan Xianyu.

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Xianyu, J., Rasouli, S. & Timmermans, H. Analysis of variability in multi-day GPS imputed activity-travel diaries using multi-dimensional sequence alignment and panel effects regression models. Transportation 44, 533–553 (2017). https://doi.org/10.1007/s11116-015-9666-2

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