Abstract
Our investigation applies a fuzzy grouping model in order to identify potential enterprise clusters based on their characteristic manufacturing activities in a specific city. The aim is to create clusters towards the construction of competitive advantages, cost reduction and economies of scale. We utilize tools of Fuzzy Sets Theory, evaluating productive capacities of local enterprises under Moore Families. Results conclude in 16 different clusters formed by 2, 3, 4 and 5 firms located in 6 different zones of a specific city. This work seeks to shed light in the conformation of groups under uncertain conditions, and the deep examination of the manufacturing activities in a specific territory for decision and policy making.
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Alfaro-Garcia, V.G., Gil-Lafuente, A.M., Klimova, A. (2015). A Fuzzy Approach to Competitive Clusters Using Moore Families. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9119. Springer, Cham. https://doi.org/10.1007/978-3-319-19324-3_13
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DOI: https://doi.org/10.1007/978-3-319-19324-3_13
Publisher Name: Springer, Cham
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