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School of Geography FACULTY OF ENVIRONMENT. Extending spatial interaction models with agents for understanding relationships in a dynamic retail market. Alison Heppenstall & Mark Birkin University of Leeds Presenter: Andrew Evans. Overview. An agent-based retail model – review

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Presentation Transcript
slide1

School of Geography

FACULTY OF ENVIRONMENT

Extending spatial interaction models with agents for understanding relationships in a dynamic retail market

Alison Heppenstall & Mark Birkin

University of Leeds

Presenter: Andrew Evans

overview
Overview
  • An agent-based retail model – review
  • An agent-based retail model – extension
  • Experiments with an extended ABRM
  • Future plans and reflections
complex geographical systems
Complex Geographical Systems
  • Characteristics of a geographical system:
    • Dynamic, nonlinear relationships among a multitude of components
    • Complex, recursive or highly iterative interactions among components
    • Evolve dynamically over time and space
    • Exhibit chaotic and potentially self-organising behaviour

Retail Petrol Market

  • Highly competitive and sensitive market.
  • Complex system:
    • Internal, external factors. Effects of locality.
    • Petrol brands operate unique rule sets?
    • Networks of information geographically constrained?
agent based retail model
Agent-based retail model

About 1000 people

agent based retail model1
Agent-based retail model

Weighting for price and distance

Portion of total fuel sold in this ward

The greater the distance and price, the closer the weighting to zero

agent based retail model version 2
Agent-based retail model: Version 2
  • New agent rules
    • Attraction = floorspace, not price
      • Standard retail model as prices unknown – floorspace proxy for competitiveness.
    • Adjustment mechanism based on provision (‘floorspace’) rather than price
      • If operation is profitable then expand, otherwise contract.
      • This has the advantage that unprofitable stations will close naturally.
    • Retail agents not dispersed but homogeneous
abrm version 2
ABRM: Version 2

Set

floorspace

Evaluate profit

Spatial

Interaction

Model

Profit

>0?

Increase

floorspace

Reduce

floorspace

agent based retail model3
Agent-based retail model

Attractiveness

Price effect

Accessibility

Set the effect of price to neutral.

Introduce a new weighting associated with floorspace Wjα : Wj is adjusted in line with profits.

abrm version 21
ABRM: Version 2
  • Experiment 1 –
    • Rectangular lattice of 27 x 27 zones
    • Even distribution of population and accessibility
    • Explore variations in provision (at equilibrium) for alternative configurations of accessibility (beta) and attractiveness (alpha)
    • Adjustment mechanism:
      • Wj = Profits / constant
      • Means stations with negative profits shrink to nothing and gain no consumers.
slide14

Distance harder to travel

Distance harder to travel

Agent-based model

Attractiveness more important

Attractiveness more important

Competition increases with ease of travel and attractiveness

slide15

Distance harder to travel

Spatial Interaction Model

Attractiveness more important

abrm version 22
ABRM: Version 2
  • Significance of this result:
    • Exactly parallels the simulations of Wilson & Clarke (1983), following Harris and Wilson (1978)
    • Further applications to
      • Residential location (Clarke & Wilson, 1984)
      • Industrial location (Birkin & Wilson, 1986a,b)
      • Agricultural location (Wilson & Birkin, 1987)
abrmv2 further experiments
ABRMV2: Further Experiments
  • A) Move to real geography

Distribution of petrol stations comes from the Catalist data

  • B) Add demographics

Distance travelled comes from a paper by Haining and Plummer

  • C) Calibrate model
slide18

Distance harder to travel

Agent-based model

Attractiveness more important

slide20

What happens if we mess with the real world?

EPS = sensitivity to profit

Higher EPS = faster reaction to market

= more instability

=less survival

models
Models
  • started with a model in which changes in both the interactions and petrol station profits were dictated by changing prices; but stations never closed.
  • then we created a classical model in which the dynamics are determined by changes in retail floorspace. Stations could shrink.
  • Now we want to look at a third model in which prices and floorspace (i.e. Location) are both changing simultaneously.
slide22

Eps1 (price sensitivity) =0.1

Eps2 (floorspace sensitivity) =0.1

slide23

Price constraint low,

Floorspace important

Price constraint medium,

Floorspace neutral

Price constraint high

Floorspace unimportant

future directions
Future directions
  • Variable patterns of price and location adjustment
  • Discrete changes in strategy or provision
  • Reactive behaviour and agent interactions
summary and conclusions
Summary and conclusions
  • Agent-based modelling breathes new life into classical approaches
  • Spatial interaction model emphasises the potential for practical deployment of simulation methods
  • Extension of this work to agent-based models of consumer behaviour is the obvious next step