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A model for integrated analysis of household location and travel choices

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  • Eliasson, Jonas
  • Mattsson, Lars-Göran

Abstract

We develop a model for integrated analysis of household location and travel choices and investigate it from a theoretical point of view. Each household makes a joint choice of location (zone and house type) and a travel pattern that maximizes utility subject to budget and time constraints. Prices for housing are calculated so that demand equals supply in each submarket. The travel pattern consists of a set of expected trip frequencies to different destinations with different modes. The joint time and budget constraints ensure that time and cost sensitivities are consistent throughout the model. Choosing the entire travel pattern at once, as opposed to treating travel decisions as a series of isolated choices, allows the marginal utilities of trips to depend on which other trips are made. When choosing trip frequencies to destinations, households are assumed to prefer variation to an extent varying with the purpose of the trip. The travel pattern will tend to be more evenly distributed across trip ends the less similar destinations and individual preferences are. These heterogeneities of destinations and individual preferences, respectively, are expressed in terms of a set of parameters to be estimated.

Suggested Citation

  • Eliasson, Jonas & Mattsson, Lars-Göran, 2000. "A model for integrated analysis of household location and travel choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(5), pages 375-394, June.
  • Handle: RePEc:eee:transa:v:34:y:2000:i:5:p:375-394
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    Cited by:

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    2. Metin Senbil & Ryuichi Kitamura & Jamilah Mohamad, 2009. "Residential location, vehicle ownership and travel in Asia: a comparative analysis of Kei-Han-Shin and Kuala Lumpur metropolitan areas," Transportation, Springer, vol. 36(3), pages 325-350, May.
    3. Jonas Eliasson & Fredrik Kopsch & Svante Mandell & Mats Wilhelmsson, 2020. "Transport Mode and the Value of Accessibility–A Potential Input for Sustainable Investment Analysis," Sustainability, MDPI, vol. 12(5), pages 1-14, March.
    4. Schwanen, Tim & Mokhtarian, Patricia L., 1998. "Does Dissonance Between Desired and Current Residential Neighbourhood Type Affect Individual Travel Behaviour? An Empirical Assessment From the San Francisco Bay Area," University of California Transportation Center, Working Papers qt26k8w6xf, University of California Transportation Center.
    5. Ibeas, Ángel & Cordera, Ruben & dell’Olio, Luigi & Coppola, Pierluigi, 2013. "Modelling the spatial interactions between workplace and residential location," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 110-122.
    6. Ng, Ka Fai & Lo, Hong K., 2017. "On joint railway and housing development: Housing-led versus railway-led schemes," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 464-488.
    7. Pinjari, Abdul Rawoof & Bhat, Chandra R. & Hensher, David A., 2009. "Residential self-selection effects in an activity time-use behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 729-748, August.
    8. Brian Lee & Paul Waddell, 2010. "Residential mobility and location choice: a nested logit model with sampling of alternatives," Transportation, Springer, vol. 37(4), pages 587-601, July.
    9. Abdul Pinjari & Ram Pendyala & Chandra Bhat & Paul Waddell, 2011. "Modeling the choice continuum: an integrated model of residential location, auto ownership, bicycle ownership, and commute tour mode choice decisions," Transportation, Springer, vol. 38(6), pages 933-958, November.
    10. Ignacio A. Inoa & Nathalie Picard & André de Palma, 2013. "Commuting Time and Accessibility in a Joint Residential Location, Workplace, and Job Type Choice Model," Working Papers hal-00776945, HAL.
    11. Ignacio A. Inoa & Nathalie Picard & Andr� de Palma, 2015. "Effect of an Accessibility Measure in a Model for Choice of Residential Location, Workplace, and Type of Employment," Mathematical Population Studies, Taylor & Francis Journals, vol. 22(1), pages 4-36, March.
    12. Le Vine, Scott & Lee-Gosselin, Martin & Sivakumar, Aruna & Polak, John, 2013. "A new concept of accessibility to personal activities: development of theory and application to an empirical study of mobility resource holdings," Journal of Transport Geography, Elsevier, vol. 31(C), pages 1-10.
    13. Ng, Ka Fai & Lo, Hong K., 2015. "Optimal housing supply in a bid-rent equilibrium framework," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 62-78.
    14. Biying, Yu & Zhang, Junyi & Fujiwara, Akimasa, 2012. "Analysis of the residential location choice and household energy consumption behavior by incorporating multiple self-selection effects," Energy Policy, Elsevier, vol. 46(C), pages 319-334.
    15. Peng, Ya-Ting & Li, Zhi-Chun & Choi, Keechoo, 2017. "Transit-oriented development in an urban rail transportation corridor," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 269-290.
    16. Zhang, Junyi & Yu, Biying & Chikaraishi, Makoto, 2014. "Interdependences between household residential and car ownership behavior: a life history analysis," Journal of Transport Geography, Elsevier, vol. 34(C), pages 165-174.

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