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Complex landscapes of spatial interaction

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  • David F. Batten

    (The Temaplan Group P.O. Box 3026, Dendy Brighton 3186, Australia)

Abstract

How complex is the spatial economy? Some apostles of complexity argue that complex behaviour can arise in any system consisting of a largish number of intelligent, adaptive agents interacting on the basis of local information only. This paper examines several features of such dynamic systems, including path-dependence, emergence and self-organization. It goes on to explore their importance for the spatial sciences. Because space scales can change abruptly from local to global, strongly-interactive spatial economies sometimes exhibit astonishing collective properties, emergent features which are lawful in their own right. Segregation, self-similarity and the rank-size rule are familiar examples. To understand how collective order arises from seemingly random fluctuations, we must note how agents choose to interact with other agents and with their environment. We must synthesize rather than analyse. In the paper, self-organization is explored in a variety of contexts, including Schelling's model of neighborhood segregation and some work with cellular automata that has sharpened our insights into the collective synthesis of agents' interactions. Power laws are widely observed. A new way of doing social science - agent-based simulation - offers powerful new insights. It seems likely to revolutionize our field, along with the whole of the social sciences. Some of the current research underway in this area is discussed. "Truth is much too complicated to allow anything but approximations." John von Neumann

Suggested Citation

  • David F. Batten, 2001. "Complex landscapes of spatial interaction," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 35(1), pages 81-111.
    • Handle: RePEc:spr:anresc:v:35:y:2001:i:1:p:81-111
    Note: Received: February 1999/Accepted: January 2000
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    Citations

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    Cited by:

    1. Bertazzi, Ilaria, 2014. "Transitivity matters. Norms Enforcement and diffusion using different neighborhoods in CAs," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201429, University of Turin.
    2. Boschma, Ron & Frenken, Koen, 2002. "Why is economic geography an evolutionary science?," ERSA conference papers ersa02p320, European Regional Science Association.
    3. Ron Martin & Peter Sunley, 2010. "Complexity Thinking and Evolutionary Economic Geography," Chapters, in: Ron Boschma & Ron Martin (ed.), The Handbook of Evolutionary Economic Geography, chapter 4, Edward Elgar Publishing.
    4. Wolfram Elsner, 2010. "The process and a simple logic of ‘meso’. Emergence and the co-evolution of institutions and group size," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 445-477, June.
    5. Tieju Ma, 2010. "Coping with Uncertainties in Technological Learning," Management Science, INFORMS, vol. 56(1), pages 192-201, January.
    6. Sadasivuni, R. & Cooke, W.H. & Bhushan, S., 2013. "Wildfire risk prediction in Southeastern Mississippi using population interaction," Ecological Modelling, Elsevier, vol. 251(C), pages 297-306.
    7. Ahjond S. Garmestani & Craig R. Allen & K. Michael Bessey, 2005. "Time-series Analysis of Clusters in City Size Distributions," Urban Studies, Urban Studies Journal Limited, vol. 42(9), pages 1507-1515, August.
    8. Juan Miguel Benito & Penélope Hernández, 2007. "Modelling Segregation Through Cellular Automata: A Theoretical Answer," Working Papers. Serie AD 2007-16, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    9. Bernardo Alves Furtado & Ricardo Machado Ruiz, 2006. "Metrópole Fractal: Um Modelo Com Autômatos Celulares Para Análise Do Espaço Urbano," Anais do XXXIV Encontro Nacional de Economia [Proceedings of the 34th Brazilian Economics Meeting] 73, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    10. Gabriele Ruoff & Gerald Schneider, 2006. "Segregation in the Classroom," Rationality and Society, , vol. 18(1), pages 95-117, February.
    11. Ricardo Ruiz & Bernardo Alves Furtado, 2007. "An Agent Based Model for Urban Structure: the case of Belo Horizonte - Brazil," EcoMod2007 23900079, EcoMod.
    12. He, Zheng & Rayman-Bacchus, Lez & Wu, Yiming, 2011. "Self-organization of industrial clustering in a transition economy: A proposed framework and case study evidence from China," Research Policy, Elsevier, vol. 40(9), pages 1280-1294.
    13. Elsner, Wolfram & Heinrich, Torsten, 2009. "A simple theory of 'meso'. On the co-evolution of institutions and platform size--With an application to varieties of capitalism and 'medium-sized' countries," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(5), pages 843-858, October.
    14. Rianne Duinen & Tatiana Filatova & Wander Jager & Anne Veen, 2016. "Going beyond perfect rationality: drought risk, economic choices and the influence of social networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(2), pages 335-369, November.

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