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A Landscape Theory of Aggregation

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  • Axelrod, Robert
  • Bennett, D. Scott

Abstract

Aggregation means the organization of elements of a system into patterns that tend to put highly compatible elements together and less compatible elements apart. Landscape theory Predicts how aggregation will lead to alignments among actors (such as nations), whose leaders are myopic in their assessments and incremental in their actions. The predicted configurations are based upon the attempts of actors to minimize their frustration based upon their pairwise Propensities to align with some actors and oppose others. These attempts lead to a local minimum in the energy landscape of the entire system. The theory is supported by the results of two cases: the alignment of seventeen European nations in the Second World War and membership in competing alliances of nine computer companies to set standards for Unix computer operating systems. The theory has potential for application to coalitions of political Parties in parliaments, social networks, social cleavages in democracies and organizational structures.

Suggested Citation

  • Axelrod, Robert & Bennett, D. Scott, 1993. "A Landscape Theory of Aggregation," British Journal of Political Science, Cambridge University Press, vol. 23(2), pages 211-233, April.
  • Handle: RePEc:cup:bjposi:v:23:y:1993:i:02:p:211-233_00
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    Cited by:

    1. Claudio Altafini, 2012. "Dynamics of Opinion Forming in Structurally Balanced Social Networks," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-9, June.
    2. Galam, Serge, 1996. "Fragmentation versus stability in bimodal coalitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 230(1), pages 174-188.
    3. Desmet, Klaus & Le Breton, Michel & Ortuno-Ortin, Ignacio, 2006. "Nation Formation and Genetic Diversity," IDEI Working Papers 133, Institut d'Économie Industrielle (IDEI), Toulouse.
    4. Le Breton, Michel & Weber, Shlomo, 2009. "Existence of Pure Strategies Nash Equilibria in Social Interaction Games with Dyadic Externalities," CEPR Discussion Papers 7279, C.E.P.R. Discussion Papers.
    5. Klaus Desmet & Michel Breton & Ignacio Ortuño-Ortín & Shlomo Weber, 2011. "The stability and breakup of nations: a quantitative analysis," Journal of Economic Growth, Springer, vol. 16(3), pages 183-213, September.
    6. Keith Hartley & Todd Sandler, 2001. "Economics of Alliances: The Lessons for Collective Action," Journal of Economic Literature, American Economic Association, vol. 39(3), pages 869-896, September.
    7. Vinogradova, Galina & Galam, Serge, 2013. "Rational instability in the natural coalition forming," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 6025-6040.
    8. Galam, Serge, 2004. "Sociophysics: a personal testimony," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 49-55.
    9. Ball, Philip, 2002. "The physical modelling of society: a historical perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 1-14.
    10. Pierpaolo Andriani & Bill McKelvey, 2006. "Beyond Gaussian Averages: Redirecting Management Research Toward Extreme Events and Power Laws," Working Papers 2006_03, Durham University Business School.
    11. Le Breton, Michel & Weber, Shlomo, 2011. "Games of social interactions with local and global externalities," Economics Letters, Elsevier, vol. 111(1), pages 88-90, April.
    12. Xiaolong Zheng & Daniel Zeng & Fei-Yue Wang, 2015. "Social balance in signed networks," Information Systems Frontiers, Springer, vol. 17(5), pages 1077-1095, October.
    13. Le Breton, Michel & Shapoval, Alexander & Weber, Shlomo, 2020. "A Game-Theoretical Model of the Landscape Theory," CEPR Discussion Papers 14993, C.E.P.R. Discussion Papers.
    14. Bärbel M. R. Stadler, 1998. "Abstention Causes Bifurcations in Two-Party Voting Dynamics," Working Papers 98-08-072, Santa Fe Institute.
    15. Joshua M. Epstein, 2007. "Agent-Based Computational Models and Generative Social Science," Introductory Chapters, in: Generative Social Science Studies in Agent-Based Computational Modeling, Princeton University Press.
    16. Jan W. Rivkin & Nicolaj Siggelkow, 2007. "Patterned Interactions in Complex Systems: Implications for Exploration," Management Science, INFORMS, vol. 53(7), pages 1068-1085, July.
    17. Bill McKelvey & Benyamin B. Lichtenstein & Pierpaolo Andriani, 2012. "When organisations and ecosystems interact: toward a law of requisite fractality in firms," International Journal of Complexity in Leadership and Management, Inderscience Enterprises Ltd, vol. 2(1/2), pages 104-136.
    18. Musatov, Daniil & Savvateev, Alexei & Weber, Shlomo, 2015. "Gale-Nikaido-Debreu and Milgrom-Shannon: Market Interactions with Endogenous Community Structures," CEPR Discussion Papers 10641, C.E.P.R. Discussion Papers.
    19. Thomas Bury, 2014. "Collective behaviours in the stock market -- A maximum entropy approach," Papers 1403.5179, arXiv.org, revised Mar 2014.
    20. Hedayatifar, L. & Hassanibesheli, F. & Shirazi, A.H. & Vasheghani Farahani, S. & Jafari, G.R., 2017. "Pseudo paths towards minimum energy states in network dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 109-116.
    21. Musatov, Daniil & Savvateev, Alexei & Weber, Shlomo, 2016. "Gale–Nikaido–Debreu and Milgrom–Shannon: Communal interactions with endogenous community structures," Journal of Economic Theory, Elsevier, vol. 166(C), pages 282-303.
    22. Klaus Desmet & Michel Le Breton & Ignacio Ortuno-Ortin & Shlomo Weber, 2008. "Stability of Nations and Genetic Diversity," Working Papers 003-08, International School of Economics at TSU, Tbilisi, Republic of Georgia.
    23. Luis R. Izquierdo & Segismundo S. Izquierdo & José Manuel Galán & José Ignacio Santos, 2009. "Techniques to Understand Computer Simulations: Markov Chain Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-6.

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