Is competition sufficient to drive observed retail location and revenue patterns? An agent-based case study.

Abstract

Agent-based models (ABMs) have been widely used to represent and investigate complex systems and are a contemporary modelling approach used in the study of land-use and land-cover change. While many ABMs have been constructed to address research questions associated with residential land development and human choices, agricultural land transition and farmer decision-making, and transportation networks and planning, less attention has been given to improving our understanding about the drivers and agent behaviours associated with commercial and retail competition, which subsequently affects land-use change. Among existing ABMs that represent the retail system, the focus has been on understanding consumer behaviours, but the inclusion of the store competition is lacking, and most retail competition models still use a top-down modelling framework. The thesis herein provides a new contribution to retail competition literature through the development and use of a retail-competition agent-based model (RC-ABM). Utilizing previous empirical research on consumer expenditures and retail location site selection, competition for home-improvement expenditures is simulated within the home-improvement retail system in the Region of Waterloo, Ontario, Canada. Results exhibit a high level of alignment between the RC-ABM and a traditional Location-Allocation Model (LAM) in estimating a market capture and store revenue acquisition. In addition, while modelled competition itself cannot reproduce the observed spatial pattern of home-improvement stores in our study area, results from the model can be used to identify path dependencies associated with retail success generated by competition and factors affecting retail store survival. Lastly, the presented RC-ABM provides the potential to enrich future land-use and land-cover change models by better representing commercial development.