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Simulating Spatial Dynamics and Processes in a Retail Gasoline Market: An Agent‐Based Modeling Approach
Author(s) -
Heppenstall Alison J.,
Harland Kirk,
Ross Andrew N.,
Olner Dan
Publication year - 2013
Publication title -
transactions in gis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 63
eISSN - 1467-9671
pISSN - 1361-1682
DOI - 10.1111/tgis.12027
Subject(s) - agent based model , competition (biology) , gasoline , closure (psychology) , space (punctuation) , scale (ratio) , spatial ecology , dynamics (music) , computer science , industrial organization , business , economics , artificial intelligence , geography , engineering , cartography , physics , acoustics , ecology , market economy , biology , waste management , operating system
Simulating the dynamics and processes within a spatially influenced retail market, such as the retail gasoline market, is a highly challenging research area. Current approaches are limited through their inability to model the impact of supplier or consumer behavior over both time and space. Agent‐based models ( ABMs ) provide an alternative approach that overcomes these problems. We demonstrate how knowledge of retail pricing is extended by using a ‘hybrid’ model approach: an agent model for retailers and a spatial interaction model for consumers. This allows the issue of spatial competition between individual retailers to be examined in a way only accessible to agent‐based models, allowing each model retailer autonomous control over optimizing their price. The hybrid model is shown to be successful at recreating spatial pricing dynamics at a national scale, simulating the effects of a rise in crude oil prices as well as accurately predicting which retailers were most susceptible to closure over a 10‐year period.