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A fuzzy approach to a municipality grouping model towards creation of synergies

Author

Listed:
  • Víctor G. Alfaro-García

    (Universitat de Barcelona)

  • Anna M. Gil-Lafuente

    (Universitat de Barcelona)

  • Gerardo G. Alfaro Calderón

    (Universidad Michoacana de San Nicolás de Hidalgo)

Abstract

In recent years, a trend for accelerating the economic, social and environmental development of cities through associations, organization and creation of synergies has been identified. Our investigation applies a grouping model in order to identify municipalities that could create optimal synergies towards the construction of competitive advantages. In order to achieve this task, we use tools of Fuzzy Logic to evaluate subjective and qualitative characteristic elements of different municipalities under Galois’ group theory. Results conclude on 32 different groups ordered in 7 different levels, relating 12 municipalities of a specific region according to 8 competitive variables. This work seeks to shed light in the conformation of groups under uncertain conditions and the deep examination of the characteristic competitive elements in a specific region for further policy and decision-making processes.

Suggested Citation

  • Víctor G. Alfaro-García & Anna M. Gil-Lafuente & Gerardo G. Alfaro Calderón, 2017. "A fuzzy approach to a municipality grouping model towards creation of synergies," Computational and Mathematical Organization Theory, Springer, vol. 23(3), pages 391-408, September.
    • Handle: RePEc:spr:comaot:v:23:y:2017:i:3:d:10.1007_s10588-016-9233-1
    DOI: 10.1007/s10588-016-9233-1
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    References listed on IDEAS

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    Cited by:

    1. Artemisa Zaragoza-Ibarra & Gerardo G. Alfaro-Calderón & Víctor G. Alfaro-García & Fernando Ornelas-Tellez & Rodrigo Gómez-Monge, 2021. "A machine learning model of national competitiveness with regional statistics of public expenditure," Computational and Mathematical Organization Theory, Springer, vol. 27(4), pages 451-468, December.

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