A network based approach towards industry clustering

dc.contributor.affiliationUniversidad EAFIT. Escuela de Economía y Finanzas. Research in Spatial Economics (RiSE), Carrera 49 7 Sur-50, Medellín, Colombia.spa
dc.contributor.authorDuque, Juan C.spa
dc.contributor.authorRey, S. J.spa
dc.contributor.departmentEscuela de Economía y Finanzasspa
dc.contributor.eafitauthorDuque, Juan C. (jduquec1@eafit.edu.co)spa
dc.contributor.programResearch in Spatial Economics (RiSE)eng
dc.creator.emailDuque, Juan C. (jduquec1@eafit.edu.co)
dc.creator.emailRey, S. J. (rey@asu.edu)
dc.date2008
dc.date.accessioned2015-05-15T21:18:26Z
dc.date.available2015-05-15T21:18:26Z
dc.date.issued2008
dc.descriptionIndustry cluster identification has become an important research topic in regional science, partly as a response to the growing demand by policymakers for analytical tools that provide a better understanding of a regional economy. The main objective of this paper is to provide a detailed description of a new approach to identify industry clusters and interindustry networks, based on input-output tables. The goal is to outline and efficient algorithm using readily available data so that the method can be replicated in any region, thereby allowing for comparative studies of industrial clusters over space and time. This new method draws on concepts from network analysis theory. It can be divided into two main block: data reduction and network partitioning. Data reduction begins by representing industries and products/services flows as a directed graph, where the links are represented as arrows indicating the direction of the flows. Based on several assumptions about how industries are related into a supply chain, the initial graph is then concerted into an undirected graph by transforming products/services flows into relative weights. The second reduction is formulated as a minimization problem, resulting in a minimum spanning tree (MST) for a subset of the initial graph edges. The final clusters are obtained by selectively deleting edges in the MST, such that each cluster contains a core industry.eng
dc.identifier.isbn9781847205155
dc.identifier.urihttp://hdl.handle.net/10784/5338
dc.language.isoengeng
dc.publisherEdward Elgar Publishing Ltdeng
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.sourceinstname:Universidad EAFITspa
dc.sourcereponame:Repositorio Institucional Universidad EAFITspa
dc.subject.keywordindustry clusterseng
dc.subject.keywordgraph theoryeng
dc.subject.keywordinputoutputeng
dc.subject.keywordimpact analysiseng
dc.titleA network based approach towards industry clustering
dc.typebookParteng
dc.typeinfo:eu-repo/semantics/bookParteng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.type.hasVersionObra publicadaspa
dc.type.localCapítulo o parte de un libro

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