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  • 标题:Interpersonal and Intrapersonal Variabilities in Daily Activity-Travel Patterns: A Networked Spatiotemporal Analysis
  • 本地全文:下载
  • 作者:Wenjia Zhang ; Chunhan Ji ; Hao Yu
  • 期刊名称:ISPRS International Journal of Geo-Information
  • 电子版ISSN:2220-9964
  • 出版年度:2021
  • 卷号:10
  • 期号:3
  • 页码:148
  • DOI:10.3390/ijgi10030148
  • 语种:English
  • 出版社:MDPI AG
  • 摘要: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.
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