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On Modelling Internet Transactions as a Time-Dependent Random Walk: An Application of the Retail Aggregate Space-Time Trip (RASTT) Model

  • Robert G. V. Baker
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Part of the The GeoJournal Library book series (GEJL, volume 70)

Abstract

The mathematical description of the Internet is a new challenge facing applied modellers. There are now new spatial and temporal accessibilities to consider and new concepts emerging, such as, ‘e-tailing’, where commercial transactions can take place globally and almost instantaneously. This freedom of access into the Internet for consumers means issues of physical location, travel time or market area may be less relevant and the research frontier has to deal with such things as ‘virtual distance’ and unrestricted shopping opportunities between countries. There even appears to be some sort of time substitution for spatial interaction (particularly from time-poor affluent households). A key theoretical question is whether cyberspace is a product of what Marx described as ‘time annihilating space’.

Keywords

Shopping Centre Internet Traffic Shopping Trip Geographical System Gravity Coefficient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. Albert, R., J. Hawoong and A. Barabasi (2000), ‘Error and attack tolerance of complex networks.’ Nature, 406, 378–382.CrossRefGoogle Scholar
  2. Baker, R.G.V. (1994), ‘An assessment of the space-time differential model for aggregate trip behaviour to planned suburban shopping centres.’ Geographical Analysis, 26, 341–362.CrossRefGoogle Scholar
  3. Baker, R.G.V. (1996), ‘Multi-purpose shopping behaviour at planned suburban shopping centres: a space-time analysis.’ Environment and Planning A, 28, 611–630.CrossRefGoogle Scholar
  4. Baker, R.G.V. (2000), ‘Towards a dynamic aggregate shopping model and its application to retail trading hour and market area analysis.’ Papers in Regional Science, 79, 413–434.CrossRefGoogle Scholar
  5. Barabasi, A. (2001), ‘The physics of the Web.’ Physics World, 14 (7).Google Scholar
  6. Barabasi, A. and R. Albert (1999), ‘Emerging of scaling in ransom networks.’ Science, 286, 509–512.CrossRefGoogle Scholar
  7. Blaut, J.M. (1961), ‘Space and process.’ The Professional Geographer, 13, 1–7.CrossRefGoogle Scholar
  8. Boulding, K.E. (1985), ‘Regions of time.’ Papers of the Regional Science Association, 57, 19–32.CrossRefGoogle Scholar
  9. Cheswick, B. (1999), Internet Mapping Project, http://www.cs.bell-labs.com.Google Scholar
  10. Cohen, R. K. Erez, D. Be-Avraham and S. Havlin (2000), ‘Resilience of the Internet to random breakdown.’ Physical Review Letters,85 4626–4628.Google Scholar
  11. Erdos, P. and A. Renyi (1960), ‘On the evolution of random graphs.’ Publications of Mathematical Institute of Hungarian Academy of Sciences, 5, 17–60.Google Scholar
  12. Faloutsos, M., P. Faloutsos and C. Faloutsos (1999), ‘On power law relationships of the Internet topology.’ Proceedings ACM SIGCOMM, http//www.can.org/sigcomm99/papers. Google Scholar
  13. Forer, P. (1978), `Time-space and area in the city of the plains.’ In T. Carlstein, D. Parkes andGoogle Scholar
  14. N. Thrift (eds.), Timing Space and Spacing Time,Vol. 1. Edward Arnold, London. Gatrell, A. (1983), Distance and Space. Clarendon Press, Oxford.Google Scholar
  15. Ghez, R. (1988), A Primer of Diffusion Problems. John Wiley, New York.CrossRefGoogle Scholar
  16. Internet Weather Report (2001), http://www.mids.org/weather. Google Scholar
  17. Interent Traffic Report (2001), http://internettrafficreport.com/. Google Scholar
  18. Janelle, D.G. (1968), ‘Central place development in a time-space framework.’ The Professional Geographer, 20, 5–10.CrossRefGoogle Scholar
  19. Janelle, D.G. (1969), ‘Spatial reorganisation: model and concept.’ Annals of the Association of American Geographers, 59, 348–364.CrossRefGoogle Scholar
  20. Jiang, B. and F. Ormeling (2000), ‘Mapping Cyberspace: visualising, analysing and exploring virtual worlds.’ The Cartographic Journal, 37, 117–122.CrossRefGoogle Scholar
  21. Montroll, E.W and B.J. West (1979), ‘Stochastic processes.’ In E.W. Montroll and J.L. Lebowitz (eds.), Studies in Statistical Mechanics, VII, Fluctuation Phenomena. Elsevier, New York.Google Scholar
  22. Padmanabhan, V.N. and L. Subramanian (2001), `An investigation of geographic mapping tech-niques for Internet hosts.’ Proceedings of ACM SIGCOMM, San Diego, USA.Google Scholar
  23. Roy, J.R. and P.F. Less (1981), ‘On appropriate microstate descriptions of entropy modelling.’ Transportation Research B, 15, 85–96.CrossRefGoogle Scholar
  24. Watts, D.J. and S.H. Strogatz (1998), ‘Collective dynamics of “small world” networks.’ Nature, 393, 440–442.CrossRefGoogle Scholar
  25. Wilson, A.G. (1967), ‘A statistical theory of spatial distribution models.’ Transportation Research, 1, 253–269.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2003

Authors and Affiliations

  • Robert G. V. Baker
    • 1
  1. 1.Division of Geography and Planning, School of Human and Environmental StudiesUniversity of New EnglandArmidaleAustralia

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