IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v90y2021ics0966692320309789.html
   My bibliography  Save this article

Variability in individual home-work activity patterns

Author

Listed:
  • Zhou, Yang
  • Thill, Jean-Claude
  • Xu, Yang
  • Fang, Zhixiang

Abstract

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.

Suggested Citation

  • Zhou, Yang & Thill, Jean-Claude & Xu, Yang & Fang, Zhixiang, 2021. "Variability in individual home-work activity patterns," Journal of Transport Geography, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:jotrge:v:90:y:2021:i:c:s0966692320309789
    DOI: 10.1016/j.jtrangeo.2020.102901
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692320309789
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2020.102901?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kuhn, Max, 2008. "Building Predictive Models in R Using the caret Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i05).
    2. Camille Roth & Soong Moon Kang & Michael Batty & Marc Barthélemy, 2011. "Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-8, January.
    3. Ron Buliung & Matthew Roorda & Tarmo Remmel, 2008. "Exploring spatial variety in patterns of activity-travel behaviour: initial results from the Toronto Travel-Activity Panel Survey (TTAPS)," Transportation, Springer, vol. 35(6), pages 697-722, November.
    4. Jie Huang & David Levinson & Jiaoe Wang & Zi-jia Wang, 2018. "Tracking job and housing dynamics with smartcard data," Working Papers 2018-01, University of Minnesota: Nexus Research Group.
    5. Zhou, Jiangping & Murphy, Enda & Long, Ying, 2014. "Commuting efficiency in the Beijing metropolitan area: an exploration combining smartcard and travel survey data," Journal of Transport Geography, Elsevier, vol. 41(C), pages 175-183.
    6. Ma, Xiaolei & Liu, Congcong & Wen, Huimin & Wang, Yunpeng & Wu, Yao-Jan, 2017. "Understanding commuting patterns using transit smart card data," Journal of Transport Geography, Elsevier, vol. 58(C), pages 135-145.
    7. Kitamura, Ryuichi & Yamamoto, Toshiyuki & Susilo, Yusak O. & Axhausen, Kay W., 2006. "How routine is a routine? An analysis of the day-to-day variability in prism vertex location," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(3), pages 259-279, March.
    8. Cats, Oded & Wang, Qian & Zhao, Yu, 2015. "Identification and classification of public transport activity centres in Stockholm using passenger flows data," Journal of Transport Geography, Elsevier, vol. 48(C), pages 10-22.
    9. repec:nas:journl:v:115:y:2018:p:12710-12715 is not listed on IDEAS
    10. Wang, Yihong & Correia, Gonçalo Homem de Almeida & de Romph, Erik & Timmermans, H.J.P., 2017. "Using metro smart card data to model location choice of after-work activities: An application to Shanghai," Journal of Transport Geography, Elsevier, vol. 63(C), pages 40-47.
    11. Tu, Wei & Cao, Rui & Yue, Yang & Zhou, Baoding & Li, Qiuping & Li, Qingquan, 2018. "Spatial variations in urban public ridership derived from GPS trajectories and smart card data," Journal of Transport Geography, Elsevier, vol. 69(C), pages 45-57.
    12. Chen Zhong & Michael Batty & Ed Manley & Jiaqiu Wang & Zijia Wang & Feng Chen & Gerhard Schmitt, 2016. "Variability in Regularity: Mining Temporal Mobility Patterns in London, Singapore and Beijing Using Smart-Card Data," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-17, February.
    13. Yang Xu & Shih-Lung Shaw & Ziliang Zhao & Ling Yin & Feng Lu & Jie Chen & Zhixiang Fang & Qingquan Li, 2016. "Another Tale of Two Cities: Understanding Human Activity Space Using Actively Tracked Cellphone Location Data," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 106(2), pages 489-502, March.
    14. Shen, Yue & Kwan, Mei-Po & Chai, Yanwei, 2013. "Investigating commuting flexibility with GPS data and 3D geovisualization: a case study of Beijing, China," Journal of Transport Geography, Elsevier, vol. 32(C), pages 1-11.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Moncayo-Unda, Milton Giovanny & Van Droogenbroeck, Marc & Saadi, Ismaïl & Cools, Mario, 2023. "A longitudinal analysis of the COVID-19 effects on the variability in human activity spaces in Quito, Ecuador," Journal of Transport Geography, Elsevier, vol. 113(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Shanqi & Yang, Yu & Zhen, Feng & Lobsang, Tashi & Li, Zhixuan, 2021. "Understanding the travel behaviors and activity patterns of the vulnerable population using smart card data: An activity space-based approach," Journal of Transport Geography, Elsevier, vol. 90(C).
    2. Pengfei Lin & Jiancheng Weng & Dimitrios Alivanistos & Siyong Ma & Baocai Yin, 2020. "Identifying and Segmenting Commuting Behavior Patterns Based on Smart Card Data and Travel Survey Data," Sustainability, MDPI, vol. 12(12), pages 1-18, June.
    3. Yang, Xiping & Fang, Zhixiang & Xu, Yang & Yin, Ling & Li, Junyi & Lu, Shiwei, 2019. "Spatial heterogeneity in spatial interaction of human movements—Insights from large-scale mobile positioning data," Journal of Transport Geography, Elsevier, vol. 78(C), pages 29-40.
    4. Wang, Jing & Wan, Feng & Dong, Chunjiao & Yin, Chaoying & Chen, Xiaoyu, 2023. "Spatiotemporal effects of built environment factors on varying rail transit station ridership patterns," Journal of Transport Geography, Elsevier, vol. 109(C).
    5. Fangye Du & Jiaoe Wang & Yu Liu & Zihao Zhou & Haitao Jin, 2022. "Equity in Health-Seeking Behavior of Groups Using Different Transportations," IJERPH, MDPI, vol. 19(5), pages 1-16, February.
    6. Jinjun Tang & Xiaolu Wang & Fang Zong & Zheng Hu, 2020. "Uncovering Spatio-temporal Travel Patterns Using a Tensor-based Model from Metro Smart Card Data in Shenzhen, China," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    7. Zhang, Yuerong & Marshall, Stephen & Manley, Ed, 2021. "Understanding the roles of rail stations: Insights from network approaches in the London metropolitan area," Journal of Transport Geography, Elsevier, vol. 94(C).
    8. F. Crawford & D. P. Watling & R. D. Connors, 2023. "Analysing Spatial Intrapersonal Variability of Road Users Using Point-to-Point Sensor Data," Networks and Spatial Economics, Springer, vol. 23(2), pages 373-406, June.
    9. Mu Lin & Zhengdong Huang & Tianhong Zhao & Ying Zhang & Heyi Wei, 2022. "Spatiotemporal Evolution of Travel Pattern Using Smart Card Data," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
    10. Duan, Zhengyu & Zhao, Haoran & Li, Zhenming, 2023. "Non-linear effects of built environment and socio-demographics on activity space," Journal of Transport Geography, Elsevier, vol. 111(C).
    11. Ta, Na & Zhao, Ying & Chai, Yanwei, 2016. "Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data," Journal of Transport Geography, Elsevier, vol. 57(C), pages 161-170.
    12. Chen, Wendong & Cheng, Long & Chen, Xuewu & Chen, Jingxu & Cao, Mengqiu, 2021. "Measuring accessibility to health care services for older bus passengers: A finer spatial resolution," Journal of Transport Geography, Elsevier, vol. 93(C).
    13. Fangye Du & Jiaoe Wang & Liang Mao & Jian Kang, 2024. "Daily rhythm of urban space usage: insights from the nexus of urban functions and human mobility," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    14. Zhang, Shen & Liu, Xin & Tang, Jinjun & Cheng, Shaowu & Qi, Yong & Wang, Yinhai, 2018. "Spatio-temporal modeling of destination choice behavior through the Bayesian hierarchical approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 537-551.
    15. Gao, Fan & Yang, Linchuan & Han, Chunyang & Tang, Jinjun & Li, Zhitao, 2022. "A network-distance-based geographically weighted regression model to examine spatiotemporal effects of station-level built environments on metro ridership," Journal of Transport Geography, Elsevier, vol. 105(C).
    16. Jie Huang & David Levinson & Jiaoe Wang & Haitao Jin, 2019. "Job-worker spatial dynamics in Beijing: Insights from Smart Card Data," Working Papers 2019-01, University of Minnesota: Nexus Research Group.
    17. Yang, Xiong & Zhuge, Chengxiang & Shao, Chunfu & Huang, Yuantan & Hayse Chiwing G. Tang, Justin & Sun, Mingdong & Wang, Pinxi & Wang, Shiqi, 2022. "Characterizing mobility patterns of private electric vehicle users with trajectory data," Applied Energy, Elsevier, vol. 321(C).
    18. Qi-Li Gao & Qing-Quan Li & Yan Zhuang & Yang Yue & Zhen-Zhen Liu & Shui-Quan Li & Daniel Sui, 2019. "Urban commuting dynamics in response to public transit upgrades: A big data approach," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-18, October.
    19. Honghu Sun & Feng Zhen & Yupei Jiang, 2020. "Study on the Characteristics of Urban Residents’ Commuting Behavior and Influencing Factors from the Perspective of Resilience Theory: Theoretical Construction and Empirical Analysis from Nanjing, Chi," IJERPH, MDPI, vol. 17(5), pages 1-17, February.
    20. Zhou, Jiangping & Sipe, Neil & Ma, Zhenliang & Mateo-Babiano, Derlie & Darchen, Sébastien, 2019. "Monitoring transit-served areas with smartcard data: A Brisbane case study," Journal of Transport Geography, Elsevier, vol. 76(C), pages 265-275.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jotrge:v:90:y:2021:i:c:s0966692320309789. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.