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

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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.

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Fig. 1

Source: Retrieved from Keropyan and Gil-Lafuente (2013)

Fig. 2

Source: Self-elaborated

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Acknowledgments

The first author expresses his gratitude to the Mexican Council of Science and Technology (CONACYT) for the financial support given to this research project with the scholarship no. 381436 to graduate studies.

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Authors and Affiliations

  1. Faculty of Economics and Business, Universitat de Barcelona, Av. Diagonal 690, 08034, Barcelona, Spain

    Víctor G. Alfaro-García & Anna M. Gil-Lafuente

  2. Faculty of Accountancy and Managerial Sciences, Universidad Michoacana de San Nicolás de Hidalgo, Francisco J. Mújica SN, Felicitas del Río, 58030, Morelia, Mich, Mexico

    Gerardo G. Alfaro Calderón

Authors
  1. Víctor G. Alfaro-García
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  2. Anna M. Gil-Lafuente
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  3. Gerardo G. Alfaro Calderón
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Correspondence to Víctor G. Alfaro-García.

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Alfaro-García, V.G., Gil-Lafuente, A.M. & Alfaro Calderón, G.G. A fuzzy approach to a municipality grouping model towards creation of synergies. Comput Math Organ Theory 23, 391–408 (2017). https://doi.org/10.1007/s10588-016-9233-1

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