Modeling Destination Choice Behavior Incorporating Spatial Factors, Individual Sociodemographics, and Travel Mode
Publication: Journal of Transportation Engineering
Volume 136, Issue 9
Abstract
Destination choice studies have been primarily carried out in developed countries. However in China, a typical developing country, few studies about destination choice exist. In this paper, we propose nonlinear-in-parameters multinomial logit models to investigate the influences of spatial factors on both work and intermediate stop destination choices. We use individual sociodemographics, travel-activity attributes, and land-use characteristics as exogeneous variables. Individual’s destination choice behaviors with different sociodemographics and travel modes are examined as well. The models are applied to data collected in the city of Shangyu, China. Compared with previous studies, this research further distinguishes the size variables influencing destination choices for work and intermediate stop in the type and the extent to which each type of size variables exerts influence. Besides, the preferences to destination choices are more clearly illustrated, resulting from the typical occupation characteristics and commuting modes of China.
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Acknowledgments
This research is supported by National Natural Science Foundation (Grant Nos. NNSFC50738001 and NNSFC50908052) and National Basic Research Program (Grant No. UNSPECIFIED2006CB705501) of China. The writers thank Mr. Tao Wan for his partial work on the processing of the data. Finally, the writer also appreciates the anonymous reviewers and the editors of journal of ASCE, for they offered many valuable revision suggestions.
References
Ben-Akiva, M., and Lerman, S. R. (1985). Discrete choice analysis: Theory and application to travel demand, MIT Press, Cambridge, Mass., 253–275.
Bhat, C. R., Govindarajan, A., and Pulugurta, V. (1998). “Disaggregate attraction-end choice modeling: Formulation and empirical analysis.” Proc., 77th Annual Meeting of the Transportation Research Board, Transportation Research Board, Washington, D.C.
Bierlaire, M. (2008). “An introduction to BIOGEME version 1.4.” ⟨http://www.biogeme.epfl.ch⟩ (March 2, 2008).
Bowman, J. L., and Ben-Akiva, M. (2001). “Activity-based disaggregate travel demand model system with activity schedules.” Transp. Res., Part A: Policy Pract., 35, 1–28.
Chow, L. -F., Zhao, F., and Li, M. -T. (2005). “Development and evaluation of aggregate destination choice models for trip distribution in Florida.” Proc., 83th Annual Meeting of the Transportation Research Board, Transportation Research Board, Washington, D.C.
Daly, A. (1982). “Estimating choice models containing attraction variables.” Transp. Res., Part B: Methodol., 16, 5–15.
Guan, H. Z. (2004). Discrete choice model-tool for travel behavior analysis, China Communication Press, Beijing, 26–60.
Kitamura, R., Chen, C., and Narayanan, R. (1998). “The effects of time of day, activity duration and home location on travelers’ destination choice behavior.” Proc., 77th Annual Meeting of the Transportation Research Board, Transportation Research Board, Washington, D.C.
Li, M. -T., Chow, L. -F., and Zhao, F. (2005). “Application of geographically stratified importance sampling in the calibration of aggregated destination choice models for trip distribution.” Proc., 83th Annual Meeting of the Transportation Research Board, Transportation Research Board, Washington, D.C.
McFadden, D. (1978). “Modeling the choice of residential location.” Transportation Research Record 673, Transportation Research Board, Washington, D.C., 531–552.
Pozsgay, M. A., and Bhat, C. R. (2001). “Destination choice modeling for home-based recreational trips; analysis and implication for land-use, transportation, and air quality planning.” Proc., 80th Annual Meeting of the Transportation Research Board, Transportation Research Board, Washington, D.C.
Southworth, F. (1981). “Calibration of multinomial logit models of mode and destination choice.” Transp. Res., Part A, 15, 315–325.
Yang, M., et al. (2005). “Trip generation forecasting model of new district based on urban population and land use.” Journal of Southeast University, 35(5), 815–819.
Yang M., et al. (2007). “Empirical analysis of commute trip chaining: Case study of Shangyu, China.” Transportation Research Record 2038, Transportation Research Board, Washington, D.C., 139–147.
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© 2010 ASCE.
History
Received: Nov 1, 2008
Accepted: Dec 1, 2009
Published online: Dec 28, 2009
Published in print: Sep 2010
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