TY - JOUR
T1 - Variability in individual home-work activity patterns
AU - Zhou, Yang
AU - Thill, Jean Claude
AU - Xu, Yang
AU - Fang, Zhixiang
N1 - Funding Information:
The authors wish to thank the journal editor and anonymous reviewers who critically commented on the research reported herein and were instrumental in enhancing the quality of the manuscript. This work was supported by the National Natural Science Foundation of China (No. 42001399 ), the Fundamental Research Funds for the Central Universities ( CCNU20ZT020 , CCNU19TD001 , CCNU19TD002 ), and the Open Fund of Key Laboratory of Geospatial Big Data Mining and Application, Hunan Province (No. 2019-01 ).
Publisher Copyright:
© 2020 Elsevier Ltd
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2021/1
Y1 - 2021/1
N2 - The way people allocate time across home and work activities determines their commuting patterns and frames much of the activities they undertake in the urban space. While inter-personal and intra-personal variability and repetitiveness in these activities have been documented, they remain largely underexplored. This study highlights the variations in and between individual home-work activity patterns by using information from metro smart card data as a proxy. To this end, the concept of individual space time usage matrix (STUM) is proposed and an analytical framework is developed in support of its use to depict how each rider allocates time in the vicinity of metro stations spatially and temporally. With this framework, we can classify space-time activity patterns that can be traced back to behavioral variability. By using Wuhan, China as a case study, variability in the number of home/work locations in personal activity patterns, and flexibility of work timeframes are investigated inter- and intra-personally. Our results show that about 25% of the population has a sophisticated home-work activity pattern that does not confirm to the ordinary 1-home 1-workplace pattern. Furthermore, even for this latter group, we find quite differentiated home and work timeframe patterns. The STUM is proved to be an effective and efficient concept to create a personal profile in analyzing the activity variability with big geo-spatial data.
AB - The way people allocate time across home and work activities determines their commuting patterns and frames much of the activities they undertake in the urban space. While inter-personal and intra-personal variability and repetitiveness in these activities have been documented, they remain largely underexplored. This study highlights the variations in and between individual home-work activity patterns by using information from metro smart card data as a proxy. To this end, the concept of individual space time usage matrix (STUM) is proposed and an analytical framework is developed in support of its use to depict how each rider allocates time in the vicinity of metro stations spatially and temporally. With this framework, we can classify space-time activity patterns that can be traced back to behavioral variability. By using Wuhan, China as a case study, variability in the number of home/work locations in personal activity patterns, and flexibility of work timeframes are investigated inter- and intra-personally. Our results show that about 25% of the population has a sophisticated home-work activity pattern that does not confirm to the ordinary 1-home 1-workplace pattern. Furthermore, even for this latter group, we find quite differentiated home and work timeframe patterns. The STUM is proved to be an effective and efficient concept to create a personal profile in analyzing the activity variability with big geo-spatial data.
KW - Activity variability
KW - Commuting flexibility
KW - Home-work patterns
KW - Smart card data
UR - http://www.scopus.com/inward/record.url?scp=85096232720&partnerID=8YFLogxK
U2 - 10.1016/j.jtrangeo.2020.102901
DO - 10.1016/j.jtrangeo.2020.102901
M3 - Journal article
AN - SCOPUS:85096232720
VL - 90
JO - Journal of Transport Geography
JF - Journal of Transport Geography
SN - 0966-6923
M1 - 102901
ER -