Temporal Variation in Consumer Spatial Behavior in Shopping Streets
Publication: Journal of Urban Planning and Development
Volume 132, Issue 3
Abstract
Modeling consumer behavior in shopping streets to support urban planning decisions has a long tradition in a variety of disciplines. Surprisingly, temporal variation in such a shopping process has received only scant attention in these models. This paper therefore proposes a multinomial logit model, in which real time is part of the utility function, implying that temporal variation in consumer preference structures can be analyzed. A grid-based estimation procedure is developed to estimate the unknown temporal variability from consumer choice data. The goodness-of-fit of the estimated model is very satisfactory and most parameters are statistically significant and in anticipated directions. Time-varying effects on consumer behavior are shown to be fairly strong. Some factors are weakened over time while others are strengthened. This finding suggests the existence of systematic variations in consumer behavior, which could enable retailers, urban planners, and real estate developers to evaluate their plans or to make decisions in more specific spatio-temporal contexts.
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Acknowledgments
The writers thank Professor Yanwei Chai, Guilan Weng, Yanran Shang, Changxia Li, and Tao Lin of the Peking University for their warm cooperation during the survey.
References
Arentze, T. A., and Timmermans, H. J. P. (2001). “Deriving performance indicators from models of multipurpose shopping behavior.” J. Retailing Consumer Services, 8(6), 325–334.
Borgers, A., and Timmermans, H. J. P. (1985). “City centre entry points, store location patterns and pedestrian route choice behavior: A microlevel simulation model.” Socio-Econ. Plan. Sci., 20(1), 25–31.
Borgers, A., and Timmermans, H. J. P. (1986) “A model of pedestrian route choice and demand for retail facilities within inner-city shopping areas.” Geogr. Anal., 18(2), 115–128.
Fortheringham, A. S., and Trew, R. (1993). “Chain image and store-choice modeling: The effects of income and race.” Envir. Plan. A, 25(2), 179–196.
Hagishima, S., Mitsuyoshi, K., and Kurose, S. (1987). “Estimation of pedestrian shopping trips in a neighborhood by using a spatial interaction model.” Envir. Plan. A, 19(9), 1139–1152.
Haklay, M., and O’Sullivan, D. (2001). “‘So go downtown’: Simulating pedestrian movement in town centers.” Environ. Plan. B: Plan. Des., 28(3), 343–359.
Jacoby, J., Szybillo, G. J., and Berning, C. K. (1976). “Time and consumer behavior: An interdisciplinary overview.” J. Consum. Res., 2(4), 320–339.
Kerridge, J., Hine, J., and Wigan, M. (2001). “Agent-based modeling of pedestrian movements: The questions that need to be asked and answered.” Environ. Plan. B: Plan. Des., 28(3), 327–341.
O’Kelly, M. E. (1981). “A model of the demand for retail facilities incorporation multistop, multipurpose trips.” Geogr. Anal., 13(2), 134–148.
Oppewal, H., and Timmermans, H. J. P. (1997). “Modeling the effects of shopping centre size and store variety on consumer choice behavior.” Envir. Plan. A, 29(6), 1073–1090.
Saito, S., and Ishibashi, K. (1992). “A Markov chain model with covariates to forecast consumer’s shopping trip chain within a central commercial district.” Proc., 4th at Fourth World Congress of Regional Science Association International, RSAI, Leeds, United Kingdom.
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© 2006 ASCE.
History
Received: Mar 29, 2005
Accepted: Aug 31, 2005
Published online: Sep 1, 2006
Published in print: Sep 2006
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