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Methodological Implications of Complex Systems Approaches to Sociality: Simulation As a Foundation for Knowledge

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  • Chris Goldspink

Abstract

There is growing advocacy for the adoption of computational methods as a substitute for, or complement to, traditional research methods, particularly for examining social phenomena derivative of organised complexity. This paper examines some of the reasons for this advocacy and the specific advantages of the method for studying such phenomena. It considers also the limitations and problems that need to be addressed if the method is to gain wider acceptance. In joining in the advocacy of these techniques, a framework is proposed which can assist with the incorporation of computational techniques in a broader methodological mix. Such a mix has the potential to harness the strengths of the method while offsetting some of its weaknesses.

Suggested Citation

  • Chris Goldspink, 2002. "Methodological Implications of Complex Systems Approaches to Sociality: Simulation As a Foundation for Knowledge," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(1), pages 1-3.
    • Handle: RePEc:jas:jasssj:2001-22-2
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    Citations

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    Cited by:

    1. Matteo Richiardi, 2003. "The Promises and Perils of Agent-Based Computational Economics," LABORatorio R. Revelli Working Papers Series 29, LABORatorio R. Revelli, Centre for Employment Studies.
    2. Francesc S. Beltran & Salvador Herrando & Doris Ferreres & Marc-Antoni Adell & Violant Estreder & Marcos Ruiz-Soler, 2009. "Forecasting a Language Shift Based on Cellular Automata," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(3), pages 1-5.
    3. Stuart Rossiter & Jason Noble & Keith R.W. Bell, 2010. "Social Simulations: Improving Interdisciplinary Understanding of Scientific Positioning and Validity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-10.
    4. Albino, Vito & Carbonara, Nunzia & Giannoccaro, Ilaria, 2007. "Supply chain cooperation in industrial districts: A simulation analysis," European Journal of Operational Research, Elsevier, vol. 177(1), pages 261-280, February.
    5. Nuno David & Jaime Simão Sichman & Helder Coelho, 2005. "The Logic of the Method of Agent-Based Simulation in the Social Sciences: Empirical and Intentional Adequacy of Computer Programs," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-2.
    6. Xiaoguang Gong & Renbin Xiao, 2007. "Research on Multi-Agent Simulation of Epidemic News Spread Characteristics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 1-1.

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