Abstract

For many years, effective model-based representations of the dynamics and evolution of urban spatial structure have proved elusive. While some progress has been made through the deployment of spatial interaction models, these approaches have been limited by the difficulty of representing behavioural mechanisms and processes. In this paper, it is demonstrated that evolutionary models grounded in the principles of spatial interaction are compatible with the more novel approaches of agent-based modelling. The incorporation of agents provides a much more flexible means for the representation of behavioural mechanisms. The paper illustrates the way in which three more complicated situations can be handled through the fusion of spatial interaction and agent modelling perspectives. These situations comprise discontinuous evolution (in which structural adjustment takes place in discrete steps, and not as a continuously smooth process); nonequilibrium dynamics (in which the underlying system parameters continue to evolve through time); the incorporation of new decision variables (which we illustrate through the addition of land rents into the model). The conclusion of the paper is that the combination of spatial interaction and agent-based modelling methods provides encouraging prospects for the social simulation of real urban systems.

Highlights

  • In this paper, we set out to explore the relationship between two styles of modelling which have developed independently and have hitherto not been regarded as compatible

  • We set out to explore the relationship between two styles of modelling which have developed independently and have hitherto not been regarded as compatible. One of these is a well-established approach to simulating the dynamics and evolution of urban spatial structure

  • There is a long tradition of representing the spatial relationships between retailers and their customers using spatial interaction models

Read more

Summary

Introduction

We set out to explore the relationship between two styles of modelling which have developed independently and have hitherto not been regarded as compatible. Applications to geographical systems are less widespread local models of crowd behaviour in public spaces or at specialised events, such as football matches or rock concerts, have been popular for some time [22] and there are the beginnings of some applications at the metropolitan scale [23] Another interesting attempt to model dynamic retail markets with an agent-based framework is found in the work of Heppenstall et al [24,25,26], in which the behaviour of petrol station managers was simulated as a population of interacting agents. The equilibrium-seeking mechanism of the Harris-Wilson model and related applications and the local dynamic interactions of the agent-based simulations appear to be complementary in a number of ways While the former is largely focused on long-term, “slow” dynamics, the latter is much more oriented to short-term “fast” dynamics.

An Equilibrium-Seeking Model of Retail Dynamics
An Agent-Based Model of Retail Dynamics
Agent-Based Model
Extended Applications of a Dynamic Retail Model
Findings
Introduction of New Decision Variables
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call