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Methodology Focused on Identifying Variables Necessary to Develop Logistics Clusters

Cristiano Farias Almeida, Yaeko Yamashita, Mario Cools, Jean Marchal, Bernard Piette
Journal of Sustainable Development , Volume 14; doi:10.5539/jsd.v14n3p147

Abstract: Several scholars have addressed the locational factors necessary for the best installation of industries or services; among them, one finds the costs with transportation of products and raw materials, labor-related costs, benefits deriving from the agglomeration of companies, as well as place-environment associations. Some agglomeration types stand out in this context, each one of them has its specific features, although they share the same goal. The agglomeration of companies is an increasingly frequent trend observed in production centers. Companies belonging to the same production chain remain close to each other in order to reduce costs with product transportation, storage and distribution processes. Consequently, they get to optimize their processes and increase their profits. The proximity between companies belonging to the same branch increases competitiveness between them. In addition, there is significant presence of skilled labor in these regions, a fact that favors logistics operations such as the transportation of inputs needed to enable companies’ production, and cost reduction. Thus, the aim of the present research is to create a methodology capable of identifying the variables necessary to develop a logistics cluster based on concepts such as productive economic agglomerations, by taking into consideration aspects addressed in a survey conducted with key cluster policy-development actors. Moreover, Interpretive Structural Modelling (ISM) was used to create an ontology to help better understanding the association among all variables necessary to structure logistics clusters.
Keywords: survey / agglomeration / optimize / belonging / identifying the variables necessary / Variables Necessary to Develop / Necessary to Develop Logistics / Develop Logistics Clusters

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