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Article

Interpersonal and Intrapersonal Variabilities in Daily Activity-Travel Patterns: A Networked Spatiotemporal Analysis

1
School of Urban Planning & Design, Peking University Shenzhen Graduate School, Shenzhen 518055, China
2
Faculty of Science, Division of Geography & Tourism, Katholieke Universiteit Leuven, 3000 Leuven, Belgium
3
College of Urban & Environmental Science, Peking University, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Academic Editors: Wolfgang Kainz and Giuseppe Borruso
ISPRS Int. J. Geo-Inf. 2021, 10(3), 148; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10030148
Received: 31 December 2020 / Revised: 25 February 2021 / Accepted: 1 March 2021 / Published: 8 March 2021
(This article belongs to the Special Issue Geospatial Methods in Social and Behavioral Sciences)
Interpersonal and intrapersonal variabilities are two important perspectives to understand daily travel behaviors, while only a small number of studies incorporate them for understanding human dynamics. This paper employed a network analysis approach to detecting daily activity-travel patterns of 680 Beijing’s residents within a week and then used a multilevel multinomial logit model to analyze the intrapersonal variability in patterns and the socioeconomic linkages behind them. Results suggest that most activity-travel patterns have significant day-to-day intrapersonal and interpersonal variabilities. This suggests that the application of a typical day of activity-travel behaviors to measure and represent a week’s or even longer-term behaviors may be biased, due to the existence of day-to-day intrapersonal variability. This study also provides a hint for the selection of days of a week to conduct a diary survey for activity pattern mining or travel demand modeling. View Full-Text
Keywords: activity-travel pattern mining; interpersonal and intrapersonal variability; network analysis; multilevel logit model; multiple-day trajectory data activity-travel pattern mining; interpersonal and intrapersonal variability; network analysis; multilevel logit model; multiple-day trajectory data
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MDPI and ACS Style

Zhang, W.; Ji, C.; Yu, H.; Zhao, Y.; Chai, Y. Interpersonal and Intrapersonal Variabilities in Daily Activity-Travel Patterns: A Networked Spatiotemporal Analysis. ISPRS Int. J. Geo-Inf. 2021, 10, 148. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10030148

AMA Style

Zhang W, Ji C, Yu H, Zhao Y, Chai Y. Interpersonal and Intrapersonal Variabilities in Daily Activity-Travel Patterns: A Networked Spatiotemporal Analysis. ISPRS International Journal of Geo-Information. 2021; 10(3):148. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10030148

Chicago/Turabian Style

Zhang, Wenjia, Chunhan Ji, Hao Yu, Yi Zhao, and Yanwei Chai. 2021. "Interpersonal and Intrapersonal Variabilities in Daily Activity-Travel Patterns: A Networked Spatiotemporal Analysis" ISPRS International Journal of Geo-Information 10, no. 3: 148. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10030148

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