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dc.creatorChain, Caio Peixoto-
dc.creatorSantos, Antônio Carlos dos-
dc.creatorCastro Júnior, Luiz Gonzaga de-
dc.creatorPrado, José Willer do-
dc.date.accessioned2019-04-09T13:49:35Z-
dc.date.available2019-04-09T13:49:35Z-
dc.date.issued2019-02-
dc.identifier.citationCHAIN, C. P. et al. Bibliometric analysis of the quantitative methods applied to the measurement of industrial clusters. Journal of Economic Surveys, [S.l.], v. 33, n. 1, p. 60-84, Feb. 2019.pt_BR
dc.identifier.urihttps://onlinelibrary.wiley.com/doi/full/10.1111/joes.12267pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/33461-
dc.description.abstractLiterature on methods for analysing interindustry interdependence and geographical concentration of firms began to multiply since the 1990s. The aim of this paper was to systematize the literature on methods and measures applied to the analysis of industrial clusters, as well as to identify trends in this knowledge field. The method used was bibliometrics, which consisted of a frequency evaluation of the publications and the relationship network between them. It was verified an exponential increase in the number of papers that composed this area, based mainly on the theories of New Economic Geography. Recently, the literature has focused on the geographic location in relation to interindustry linkages, and the frontier of knowledge has shifted from traditional methods of regional science to areas such as spatial statistics, econophysics and artificial intelligence. There are still relevant questions being explored, as Modifiable Area Unit Problem (aggregation bias), nevertheless, spatial anisotropy (directional bias) is still neglected and indicates a new research path.pt_BR
dc.languageen_USpt_BR
dc.publisherWileypt_BR
dc.rightsrestrictAccesspt_BR
dc.sourceJournal of Economic Surveyspt_BR
dc.subjectBibliometricspt_BR
dc.subjectInput–output methodspt_BR
dc.subjectSpatial statisticspt_BR
dc.subjectTheory of agglomerationspt_BR
dc.titleBibliometric analysis of the quantitative methods applied to the measurement of industrial clusterspt_BR
dc.typeArtigopt_BR
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