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A methodological framework for the study of residential location and travel-to-work mode choice under central and suburban employment destination patterns

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  • Vega, Amaya
  • Reynolds-Feighan, Aisling

Abstract

The aim of this paper is to contribute to the methodological questions that arise from the study of the simultaneous choice of residential location and travel-to-work mode under central and non-central or suburban employment patterns. Geographic information system (GIS) visualisations and network analysis are used to generate a choice set based on the definition of spatially aggregated alternatives. Discrete choice models specified as cross-nested logit (CNL) are estimated for each of the two different types of employment patterns and direct and cross elasticities are presented. The analysis is carried out for the Greater Dublin Area, a metropolitan region that is a recent example of rapid employment suburbanisation and residential sprawl in a European context. A simulation exercise, tracing the extent of mode switching and location switching behaviour is undertaken using the framework developed.

Suggested Citation

  • Vega, Amaya & Reynolds-Feighan, Aisling, 2009. "A methodological framework for the study of residential location and travel-to-work mode choice under central and suburban employment destination patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 401-419, May.
    • Handle: RePEc:eee:transa:v:43:y:2009:i:4:p:401-419
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    References listed on IDEAS

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    Cited by:

    1. Yang, Liya & Shen, Qing & Li, Zhibin, 2016. "Comparing travel mode and trip chain choices between holidays and weekdays," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 273-285.
    2. Driscoll, Áine & Lyons, Sean & Morgenroth, Edgar & Nolan, Anne, 2013. "Comparing the Determinants of Mode Choice across Travel Purposes," MPRA Paper 46034, University Library of Munich, Germany.
    3. Lois, David & López-Sáez, Mercedes, 2009. "The relationship between instrumental, symbolic and affective factors as predictors of car use: A structural equation modeling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(9-10), pages 790-799, November.
    4. 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.
    5. Namazi-Rad, Mohammad-Reza & Mokhtarian, Payam & Shukla, Nagesh & Munoz, Albert, 2016. "A data-driven predictive model for residential mobility in Australia – A generalised linear mixed model for repeated measured binary data," Journal of choice modelling, Elsevier, vol. 20(C), pages 49-60.
    6. repec:eee:transa:v:105:y:2017:i:c:p:123-137 is not listed on IDEAS
    7. De Witte, Astrid & Hollevoet, Joachim & Dobruszkes, Frédéric & Hubert, Michel & Macharis, Cathy, 2013. "Linking modal choice to motility: A comprehensive review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 329-341.
    8. repec:eee:transa:v:104:y:2017:i:c:p:238-254 is not listed on IDEAS
    9. Shi An & Ze Wang & Jianxun Cui, 2015. "Integrating Regret Psychology to Travel Mode Choice for a Transit-Oriented Evacuation Strategy," Sustainability, MDPI, Open Access Journal, vol. 7(7), pages 1-16, June.
    10. Israel, Emil & Cohen-Blankshtain, Galit, 2010. "Testing the decentralization effects of rail systems: Empirical findings from Israel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(7), pages 523-536, August.

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