Modeling enterprise location choice decision behavior


  • Nguyen Cao Y University of Communications and Transport



This study presents a location choice model that incorporates urban spatial effects for enterprises. A modeling framework is developed to analyze decisions regarding location choice for enterprises using a series of discrete choice models including multinomial logit without any urban spatial effects, multinomial logit incorporating urban spatial effects, and mixed logit incorporating urban spatial effects. In this framework, urban spatial effects, such as the urban spatial correlation among enterprises in deterministic terms and the urban spatial correlation among zones in the error term, are captured by mixed logit models in particular and discrete choice models in general.

The results indicate that the urban spatial effects and the land prices in a given zone strongly affect the decision-making process of all the enterprises in the Tokyo metropolitan area. Moreover, the important role of urban spatial effects in the proposed model will be clarification through comparing the three above models. This comparison will be implemented on the basis of three types of indicators such as the log likelihood ratio, Akaike information indicator, and hit ratio of each model.


Ben-Akiva, M., Bolduc, D., & Walker, J. (2001). Specification, identifications, and estimation of the logit kernel (or continuous mixed logit) model (PDF draft). Berkeley, CA: University of California Berkeley.

Bhat, C. R., & Guo, J. A. (2004). Mixed spatially correlated logit model: Formulation and application to residential choice modeling, Transportation Research Part B, 38, 147–168.

Boots, B. N., & Kanaroglou, P. S. (1988). Incorporating the effect of spatial structure in discrete choices models of migration. Journal of Regional Science, 28, 495–507.

de Bok, M., & Sanders, F. (2005). Firm location and the accessibility of locations: Empirical results from the Netherlands. Transportation Research Record: Journal fo the Transportation Research Board, 1902(1), 35–43.

de Bok, M. D., & van Oort, F. (2011). Agglomeration economies, accessibility, and the spatial choice behavior of relocating firms. Journal of Transport and Land Use, 4, 5–24.

Dubin, R. A. (1995). Estimating logit models with spatial dependence. In L. Anselin & R. Florax (Eds), New directions in spatial econometrics (pp. 229–242). Heidelberg: Springer-Verlag.

Fotheringham, A. S. (1983). A new set of spatial-interaction models: The theory of competing destinations. Environment and Planning A, 15(1), 15–36. https//: doi.10.1068/a150015

Griffith, D. A. (1996). Some guidelines for specifying the geographic weights matrix contained in spatial statistical models (Chapter 4). In A. L. Arlinghaus, D. A. Griffith, W. C. Arlinghaus, W. D. Drake, & J. D. Nystuen (Eds.), Practical handbook of spatial statistics. Boca Raton, FL: CRC Press.

Löchl, M., & Axhausen, K. W. (2010). Modelling hedonic residential rents for land use and transport simulation while considering spatial effects. Journal of Transport and Land Use, 3(2), 39–63.

Maoh, H., & Kanaroglou, P. (2007). Business establishment mobility behavior in urban areas: A microanalytical model for the city of Hamilton in Ontario, Canada. Journal of Geographic Systems, 9, 229–252.

McMillen, D. P. (1992). Probit with spatial autocorrelation. Journal of Regional Science, 32(3), 335–348.

McQuaid, R. W., Greig, M., Smyth, A., & Cooper, J. (2004). The importance of transport in business' location decisions. (Reference no. UG494 ). Report to Department for Transport, Napier University, Edinburg, UK.

Miaou, S., & Sui, D. (2004). Implications of changing demographic and socioeconomic structures on highway safety: A Texas initiative. Final report. Austin: Texas Transportation Institute.

Miyamoto, K., Vichiensan, V., Shimomura, N., & Paez, A. (2004). Discrete choice model with structuralized spatial effects for location analysis. Transportation Research Record: Journal of the Transportation Research Board, 1898, 183–190. Washington, DC: Transportation Research Board of the National Academies.

Mohammadian, A., & Kanaroglou, P. S. (2003). Application of spatial multinomial logit model to transportation planning. Paper presented at the 10th International Conference on Travel Behavior Research, Lucerne.

Mohammadian, A., Haider, M., & Kanaroglou, P.S. (2005) Incorporating spatial dependencies in random parameter discrete choice models. Proceedings of the 84th Annual Transportation Research Board (CD-ROM). Washington, DC: Transportation Research Board.

Nilsen, O. L., Tørset, T., Gutiérrez, M. D., Cherchi, E., & Andersen, S. N. (2020). Where and why do firms choose to move? Empirical evidence from Norway. Journal of Transport and Land Use, 13(1), 207–225.

Ozmen-Ertekin, D., Ozbay, K., & Holguín-Veras, J. (2007) Role of transportation accessibility in attracting businesses to New Jersey. Journal of Urban Planning and Development, 133(2), 138–149.

Paez, A., & Suzuki, J. (2001). Transportation impacts on land use changes: An assessment considering neighborhood effect. Journal of Eastern Asia Society for Transportation Studies, 4, 47–59.

Pellegrini, P. A., & Fotheringham, A. S. (2002). Modelling spatial choice: A review and synthesis in a migration context. Progress in Human Geography, 26(4), 487–510.

Pellenbarg, P. H., van Wissen, L. J. G, & Van Dijk, J. (2002). Firm migration. In P. McCann (Ed.), Industrial location economics (pp. 110–148). Cheltenham: Edward Elgar Publishing.

Schirmer, P. M., van Eggermond, M. A., & Axhausen, K. W. (2014). The role of location in residential location choice models: A review of literature. Journal of Transport and Land Use, 7(2), 3–21.

Train, K. E. (2003). Discrete choice methods with simulation. New York: Cambridge University Press.

Van Dijk, J., & Pellenbarg, P. H. (2017). Firm migration. In International encyclopedia of geography: People, the earth, environment and technology. Hoboken, NJ: John Wiley & Sons.

Wisetjindawat, W., Sano, K., & Matsumoto, S. (2006). Commodity distribution model incorporating spatial interactions for urban freight movement. Transportation Research Record: Journal of the Transportation Research Board, 1966, 41–50.




How to Cite

Y, N. C. (2021). Modeling enterprise location choice decision behavior. Journal of Transport and Land Use, 14(1), 669–691.