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Social influences on household location, mobility and activity choice in integrated micro-simulation models

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  • Ettema, Dick
  • Arentze, Theo
  • Timmermans, Harry

Abstract

Agent-based approaches to simulating long-term location and mobility decisions and short-term activity and travel decisions of households and individuals are receiving increasing attention in land-use and transportation interaction (LUTI) models to predict land-use changes and travel behaviour in mutual interaction. Social interactions between households and between individuals potentially have an influence on a wide range of the long-term and short-term choices involved in these systems. In this paper we identify the areas in which social interactions play a role and address the question how these influences can be modelled in the context of agent-based LUTI models. We distinguish impacts on activity participation (joint activity participation, support-and-help activities) and impacts on decision making (information exchange, social adaptation of preferences and aspirations) as the two main areas of social influence. A prototype of a LUTI model is proposed that accounts for impacts of the social network on longer-term mobility decision making through information exchange and social adaptation of preferences and aspirations. The model is demonstrated in a numerical simulation.

Suggested Citation

  • Ettema, Dick & Arentze, Theo & Timmermans, Harry, 2011. "Social influences on household location, mobility and activity choice in integrated micro-simulation models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 283-295, May.
    • Handle: RePEc:eee:transa:v:45:y:2011:i:4:p:283-295
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    Cited by:

    1. Guidon, Sergio & Wicki, Michael & Bernauer, Thomas & Axhausen, Kay, 2019. "The social aspect of residential location choice: on the trade-off between proximity to social contacts and commuting," Journal of Transport Geography, Elsevier, vol. 74(C), pages 333-340.
    2. Kim, Jinhee & Rasouli, Soora & Timmermans, Harry, 2014. "Expanding scope of hybrid choice models allowing for mixture of social influences and latent attitudes: Application to intended purchase of electric cars," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 71-85.
    3. Kii, Masanobu & Nakanishi, Hitomi & Nakamura, Kazuki & Doi, Kenji, 2016. "Transportation and spatial development: An overview and a future direction," Transport Policy, Elsevier, vol. 49(C), pages 148-158.
    4. Wei, Fangfang & Jia, Ning & Ma, Shoufeng, 2016. "Day-to-day traffic dynamics considering social interaction: From individual route choice behavior to a network flow model," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 335-354.
    5. Givoni, Moshe, 2017. "Assessing core-periphery relation through travel patterns - The case of Israel," Research in Transportation Economics, Elsevier, vol. 63(C), pages 73-85.
    6. Zhang, Guijie & Wei, Fangfang & Jia, Ning & Ma, Shoufeng & Wu, Yi, 2019. "Information adoption in commuters’ route choice in the context of social interactions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 300-316.
    7. Kowald, Matthias & van den Berg, Pauline & Frei, Andreas & Carrasco, Juan-Antonio & Arentze, Theo & Axhausen, Kay & Mok, Diana & Timmermans, Harry & Wellman, Barry, 2013. "Distance patterns of personal networks in four countries: a comparative study," Journal of Transport Geography, Elsevier, vol. 31(C), pages 236-248.
    8. Lisa Döring & Maarten Kroesen & Christian Holz-Rau, 2019. "The role of parents’ mobility behavior for dynamics in car availability and commute mode use," Transportation, Springer, vol. 46(3), pages 957-994, June.
    9. Xiao, Yu & Lo, Hong K., 2016. "Day-to-day departure time modeling under social network influence," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 54-72.

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