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What construct one’s familiar area? A quantitative and longitudinal study

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  • Wen Zhang
  • Nursitihazlin Ahmad Termida
  • Yusak O Susilo

Abstract

There is a lack of understanding of how certain characteristics of the urban environment influence an individual’s spatial cognition and familiarity with surrounding areas, and, subsequently, their travel behaviours and how these change over time. This paper aims to address this research gap in exploring the dynamics of individuals’ spatial cognitions by observing the changes of respondents’ familiar areas over time, and investigating the possible determinants that constitute respondents’ familiar areas. Panel data, containing two-week travel diaries and maps of familiar areas, were collected in four different waves over a seven-month period for 55 individuals in Stockholm, Sweden. The reported familiar areas for each individual were digitised into quantifiable variable form and further analysed by applying dynamic binary probit and linear regression models. The results show that, while familiar area is largely influenced by one’s previous knowledge of the area, it is also continuously corrected by events in between. Different land use characteristics have different impacts on different social groups’ travel patterns, thus contributing to the variability in the size of one’s familiar areas.

Suggested Citation

  • Wen Zhang & Nursitihazlin Ahmad Termida & Yusak O Susilo, 2019. "What construct one’s familiar area? A quantitative and longitudinal study," Environment and Planning B, , vol. 46(2), pages 322-340, February.
    • Handle: RePEc:sae:envirb:v:46:y:2019:i:2:p:322-340
    DOI: 10.1177/2399808317714798
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    1. Jeffrey M. Wooldridge, 2005. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 39-54, January.
    2. Dellaert, Benedict G.C. & Arentze, Theo A. & Timmermans, Harry J.P., 2008. "Shopping context and consumers’ mental representation of complex shopping trip decision problems," Journal of Retailing, Elsevier, vol. 84(2), pages 219-232.
    3. Sabina Buczkowska & Nicolas Coulombel & Matthieu de Lapparent, 2015. "Euclidean distance versus travel time in business location: A probabilistic mixture of hurdle-Poisson models," ERSA conference papers ersa15p1060, European Regional Science Association.
    4. T. Arentze & H. Timmermans, 2005. "Representing mental maps and cognitive learning in micro-simulation models of activity-travel choice dynamics," Transportation, Springer, vol. 32(4), pages 321-340, July.
    5. Golledge, Reginald G. & Garling, Tommy, 2002. "Cognitive Maps and Urban Travel," University of California Transportation Center, Working Papers qt5wb4524r, University of California Transportation Center.
    6. Ahmad Termida, Nursitihazlin & Susilo, Yusak O. & Franklin, Joel P., 2016. "Observing dynamic behavioural responses due to the extension of a tram line by using panel survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 78-95.
    7. Robert Schlich & Kay Axhausen, 2003. "Habitual travel behaviour: Evidence from a six-week travel diary," Transportation, Springer, vol. 30(1), pages 13-36, February.
    8. Dellaert, Benedict G.C. & Arentze, Theo & Horeni, Oliver & Timmermans, Harry J.P., 2017. "Deriving attribute utilities from mental representations of complex decisions," Journal of choice modelling, Elsevier, vol. 22(C), pages 24-38.
    9. Kitamura, Ryuichi & Fujii, Satoshi & Pas, Eric I., 1997. "Time-use data, analysis and modeling: toward the next generation of transportation planning methodologies," Transport Policy, Elsevier, vol. 4(4), pages 225-235, October.
    10. Zhang, Wen & Susilo, Yusak O. & Ahmad Termida, Nursitihazlin, 2016. "Investigating the interactions between travellers' familiar areas and their multi-day activity locations," Journal of Transport Geography, Elsevier, vol. 53(C), pages 61-73.
    11. Minaei, Negin, 2014. "Do modes of transportation and GPS affect cognitive maps of Londoners?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 162-180.
    12. Susilo, Yusak O. & Williams, Katie & Lindsay, Morag & Dair, Carol, 2012. "The influence of individuals’ environmental attitudes and urban design features on their travel patterns in sustainable neighborhoods in the UK," Working papers in Transport Economics 2012:1, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    13. Kitamura, Ryuichi, 1990. "Panel Analysis in Transportation Planning: An Overview," University of California Transportation Center, Working Papers qt86v0f7zh, University of California Transportation Center.
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