Household Residential Location Choice Equilibrium Model Based on Reference-Dependent Theory
Publication: Journal of Urban Planning and Development
Volume 146, Issue 1
Abstract
We focus on the location choice behavior of new residents in the urban system using the reference-dependent theory approach. Reference-dependent theory offers an alternative analytical framework for the study of residential location choice behavior. This problem is formulated as bilevel programming in which the upper-level programming model is of household residential choice behavior with a combination of the reference-dependent theory and a discrete choice model, whereas the lower-level is a multiclass stochastic user equilibrium model. Here, the heterogeneity of households/travelers and the stochastic character of traffic networks are carefully taken into account. The multiclass stochastic user equilibrium condition is formulated into an equivalent variational inequality problem. Furthermore, an iterative algorithm combined method of successive averages has been adopted to solve this bilevel model. In numerical experiments, we illustrate the effect of different highway toll strategies and different reference points on the urban spatial structure. Finally, some interesting conclusions are obtained.
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Acknowledgments
Dr. Li was supported by the China Postdoctoral Science Foundation funded project (BX20190022, 2019M650412) and the National Natural Science Foundation of China (71901007). Prof. Sun was supported by the National Natural Science Foundation of China (91846202, 71771018, and 71621001). Prof. Wu was supported by the China National Funds for Distinguished Young Scientists (71525002) and the National Natural Science Foundation of China (71890972/71890970).
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Published In
Journal of Urban Planning and Development
Volume 146 • Issue 1 • March 2020
Copyright
©2019 American Society of Civil Engineers.
History
Received: Apr 30, 2018
Accepted: Apr 16, 2019
Published online: Dec 2, 2019
Published in print: Mar 1, 2020
Discussion open until: May 2, 2020
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