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.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Ketels, C.I.: Recent research on competitiveness and clusters: what are the implications for regional policy? Cambridge Journal of Regions, Economy and Society 6(2), 269–284 (2013)
Porter, M.: What is strategy? Harvard Business Review 74(6), 61–78 (1996)
Porter, M.E.: The Competitive Advantage of Nations. Harvard Business Review 68, 73–93 (1990)
Jacobs, D., De Man, A.: Clusters Industrial policy and firm strategy. Analys & Strategic Mangement (1996)
Porter, M.: Clusters and the New Economics of Competition. Harvard Business (2000)
OCDE.: Primer Foro sobre Clusters Locales. International Conference on Territorial Development. Organizacin para la Cooperación y el Desarrollo Económico (2001)
Florida, R.: Who’s Your City? Basic Books, USA (2008)
INEGI.: Directorio Estadístico Nacional de Unidades Económicas, http://www.inegi.org.mx
Gil Lafuente, J.: Marketing para el nuevo milenio: nuevas técnicas para la gestión comercial en la incertidumbre, p. 476. Ediciones Pirámide, Barcelona (1997)
Gil Lafuente, A.M.: Nuevas estrategias para el análisis financiero en la empresa, p. 480. Ariel, Barcelona (2001)
Gil Aluja, J.: Elements for a theory of decision in uncertainty, p. 347. Kluwer Academic Publishers, Dordrecht (1999)
Gil Aluja, J.: Towards a new paradigm of investment selection in uncertainty. Fuzzy Sets and Systems 84(2), 187–197 (1996)
INEGI. North American Industry Classification System, Mexico. Methodological synthesis. SCIAN 2013 (2013), http://www3.inegi.org.mx (retrieved 2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-19324-3_13
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19323-6
Online ISBN: 978-3-319-19324-3
eBook Packages: Computer ScienceComputer Science (R0)