Retail Location Choice with Complementary Goods: An Agent-Based Model
This paper models the emergence of retail clusters on a supply chain network comprised of suppliers, retailers, and consumers. Firstly, an agent-based model is proposed to investigate retail location distribution in a market of two complementary goods. The methodology controls for supplier locales and unit sales prices of retailers and suppliers, and a consumer’s willingness to patronize a retailer depends on the total travel distance of buying both goods. On a circle comprised of discrete locations, retailers play a non-cooperative game of location choice to maximize individual profits. Our findings suggest that the probability distribution of the number of clusters in equilibrium follows power law and that hierarchical distribution patterns are much more likely to occur than the spread-out ones. In addition, retailers of complementary goods tend to co-locate at supplier locales. Sensitivity tests on the number of retailers are also performed. Secondly, based on the County Business Patterns (CBP) data of Minneapolis-St. Paul from US Census 2000 database, we find that the number of clothing stores and the distribution of food stores at the zip code level follows power-law distribution.
Keywordsclustering agent-based model location choice distribution pattern
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- 3.Baldwin, R., Forslid, R., Martin, P., Ottaviano, G., Robert-Nicoud, F.: Economic Geography and Public Policy. Princeton University Press, Princeton (2003)Google Scholar
- 5.Weber, A.: Theory of the Location of Industries. University of Chicago Press (1957)Google Scholar
- 6.Christaller, W.: Central Places in Southern Germany (Translated by C.W. Baskin). Prentice-Hall, NY (1966)Google Scholar
- 7.Krugman, P.: Urban concentration: The Role of Increasing Returns and Transport Costs. International Regional Science Review 19, 5–30 (1996)Google Scholar
- 9.Levinson, D., Krizek, K.: Planning for Place and Plexus: Metropolitan Land Use and Transport. Routledge, New York (2008)Google Scholar
- 10.Huang, A., Levinson, D.: An Agent-based Retail Location Model on a Supply Chain Network. University of Minnesota. Working paper (2008)Google Scholar
- 11.Simon, H.A., Bonini, C.P.: The Size distribution of business firms. American Economic Review 48(4), 607–617 (1958)Google Scholar
- 12.Clauset, A., Shalizi, C., Newman, M.E.J.: Power-law Distributions in Empirical Data. SFI Working Paper (2007)Google Scholar
- 15.Zipf, G.: Human Behavior and the Principle of Least Effort: An Introduction to Human Ecology. Addison-Wesley, Reading (1949)Google Scholar
- 20.Fujiwara, Y., Di Guilmi, C., Aoyama, H., Gallegati, M., Souma, W.: Do Pareto-Zipf and Gibrat laws Hold True? An analysis with European rms. Physica A: Statistical Mechanics and its Applications 335, 197–216 (2004)Google Scholar