Retail location choice with complementary goods: An agent-based model

Arthur Huang, David Levinson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationComplex Sciences - First International Conference, Complex 2009, Revised Papers
Pages175-187
Number of pages13
EditionPART 1
DOIs
StatePublished - Dec 1 2009
Event1st International Conference on Complex Sciences: Theory and Applications, Complex 2009 - Shanghai, China
Duration: Feb 23 2009Feb 25 2009

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
NumberPART 1
Volume4 LNICST
ISSN (Print)1867-8211

Other

Other1st International Conference on Complex Sciences: Theory and Applications, Complex 2009
CountryChina
CityShanghai
Period2/23/092/25/09

Keywords

  • Agent-based model
  • Clustering
  • Distribution pattern
  • Location choice

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