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The Intention to Move and Residential Location Choice Behaviour

School of Social Science, University of Ulsan, PO Box 18, Ulsan, South Korea, jhkim{at}ulsan.ac.kr

Francesca Pagliara

Department of Transport Engineering, University of Naples Federico . Via Claudio 21. 80125 Navies. Italy, fpagliar{at}unina.it

John Preston

Transport Studies Unit, School of Geography, University of Oxford, 11 Bevington Road, Oxford, OX2 6NB, UK, john.preston @tsu.ox.ac.uk

This paper aims to quantify the extent to which transport and other factors impact on residential decisions using Oxfordshire, UK, as a case study. It investigates the impacts of the current dwelling, household characteristics and alternative properties on the probability of moving. It also highlights the trade-off between access, space and other attributes in residential location choice. Particular emphasis is placed on assessing the impact of transport and location-embedded amenities. A nested logit model is applied to estimate the indirect random utility functions of the intention to move and residential location choice based on stated preference data. The estimation results of the intentions to move model illustrate the impact of housing and household characteristics on the probability of moving. The estimation results of the residential location choice model quantify the trade-offs between transport, amenities and other factors.

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