Alison Heppenstall & Mark Birkin University of Leeds Presenter: Andrew Evans - PowerPoint PPT Presentation

minh
slide1 n.
Skip this Video
Loading SlideShow in 5 Seconds..
Alison Heppenstall & Mark Birkin University of Leeds Presenter: Andrew Evans PowerPoint Presentation
Download Presentation
Alison Heppenstall & Mark Birkin University of Leeds Presenter: Andrew Evans

play fullscreen
1 / 25
Download Presentation
Alison Heppenstall & Mark Birkin University of Leeds Presenter: Andrew Evans
83 Views
Download Presentation

Alison Heppenstall & Mark Birkin University of Leeds Presenter: Andrew Evans

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. 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

  2. Overview • An agent-based retail model – review • An agent-based retail model – extension • Experiments with an extended ABRM • Future plans and reflections

  3. 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?

  4. Spatial Diffusion: Price Drop

  5. Agent-based retail model About 1000 people

  6. 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

  7. Agent-based retail model

  8. ‘What if?’ analysis: aggressive drop t3 t1 t2 t4

  9. 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

  10. ABRM: Version 2 Set floorspace Evaluate profit Spatial Interaction Model Profit >0? Increase floorspace Reduce floorspace

  11. 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.

  12. 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.

  13. 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

  14. Distance harder to travel Spatial Interaction Model Attractiveness more important

  15. 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)

  16. 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

  17. Distance harder to travel Agent-based model Attractiveness more important

  18. Where is the real world in this solution space?

  19. What happens if we mess with the real world? EPS = sensitivity to profit Higher EPS = faster reaction to market = more instability =less survival

  20. 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.

  21. Eps1 (price sensitivity) =0.1 Eps2 (floorspace sensitivity) =0.1

  22. Price constraint low, Floorspace important Price constraint medium, Floorspace neutral Price constraint high Floorspace unimportant

  23. Future directions • Variable patterns of price and location adjustment • Discrete changes in strategy or provision • Reactive behaviour and agent interactions

  24. 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