Citing this article

A standard form of citation of this article is:

Heppenstall, Alison, Evans, Andrew and Birkin, Mark (2006). 'Using Hybrid Agent-Based Systems to Model Spatially-Influenced Retail Markets'. Journal of Artificial Societies and Social Simulation 9(3)2 <http://jasss.soc.surrey.ac.uk/9/3/2.html>.

The following can be copied and pasted into a Bibtex bibliography file, for use with the LaTeX text processor:

@article{heppenstall2006,
title = {Using Hybrid Agent-Based Systems to Model Spatially-Influenced Retail Markets},
author = {Heppenstall, Alison and Evans, Andrew and Birkin, Mark},
journal = {Journal of Artificial Societies and Social Simulation},
ISSN = {1460-7425},
volume = {9},
number = {3},
pages = {2},
year = {2006},
URL = {http://jasss.soc.surrey.ac.uk/9/3/2.html},
keywords = {Agents, Spatial Interaction Model, Retail Markets, Networks},
abstract = {One emerging area of agent-based modelling is retail markets; however, there are problems with modelling such systems. The vast size of such markets makes individual-level modelling, for example of customers, difficult and this is particularly true where the markets are spatially complex. There is an emerging recognition that the power of agent-based systems is enhanced when integrated with other AI-based and conventional approaches. The resulting hybrid models are powerful tools that combine the flexibility of the agent-based methodology with the strengths of more traditional modelling. Such combinations allow us to consider agent-based modelling of such large-scale and complex retail markets. In particular, this paper examines the application of a hybrid agent-based model to a retail petrol market. An agent model was constructed and experiments were conducted to determine whether the trends and patterns of the retail petrol market could be replicated. Consumer behaviour was incorporated by the inclusion of a spatial interaction (SI) model and a network component. The model is shown to reproduce the spatial patterns seen in the real market, as well as well known behaviours of the market such as the "rocket and feathers" effect. In addition the model was successful at predicting the long term profitability of individual retailers. The results show that agent-based modelling has the ability to improve on existing approaches to modelling retail markets.},
}

The following can be copied and pasted into a text file, which can then be imported into a reference database that supports imports using the RIS format, such as Reference Manager and EndNote.


TY - JOUR
TI - Using Hybrid Agent-Based Systems to Model Spatially-Influenced Retail Markets
AU - Heppenstall, Alison
AU - Evans, Andrew
AU - Birkin, Mark
Y1 - 2006/06/30
JO - Journal of Artificial Societies and Social Simulation
SN - 1460-7425
VL - 9
IS - 3
SP - 2
UR - http://jasss.soc.surrey.ac.uk/9/3/2.html
KW - Agents
KW - Spatial Interaction Model
KW - Retail Markets
KW - Networks
N2 - One emerging area of agent-based modelling is retail markets; however, there are problems with modelling such systems. The vast size of such markets makes individual-level modelling, for example of customers, difficult and this is particularly true where the markets are spatially complex. There is an emerging recognition that the power of agent-based systems is enhanced when integrated with other AI-based and conventional approaches. The resulting hybrid models are powerful tools that combine the flexibility of the agent-based methodology with the strengths of more traditional modelling. Such combinations allow us to consider agent-based modelling of such large-scale and complex retail markets. In particular, this paper examines the application of a hybrid agent-based model to a retail petrol market. An agent model was constructed and experiments were conducted to determine whether the trends and patterns of the retail petrol market could be replicated. Consumer behaviour was incorporated by the inclusion of a spatial interaction (SI) model and a network component. The model is shown to reproduce the spatial patterns seen in the real market, as well as well known behaviours of the market such as the "rocket and feathers" effect. In addition the model was successful at predicting the long term profitability of individual retailers. The results show that agent-based modelling has the ability to improve on existing approaches to modelling retail markets.
ER -