Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/33461
metadata.artigo.dc.title: Bibliometric analysis of the quantitative methods applied to the measurement of industrial clusters
metadata.artigo.dc.creator: Chain, Caio Peixoto
Santos, Antônio Carlos dos
Castro Júnior, Luiz Gonzaga de
Prado, José Willer do
metadata.artigo.dc.subject: Bibliometrics
Input–output methods
Spatial statistics
Theory of agglomerations
metadata.artigo.dc.publisher: Wiley
metadata.artigo.dc.date.issued: Feb-2019
metadata.artigo.dc.identifier.citation: CHAIN, 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.
metadata.artigo.dc.description.abstract: Literature 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.
metadata.artigo.dc.identifier.uri: https://onlinelibrary.wiley.com/doi/full/10.1111/joes.12267
http://repositorio.ufla.br/jspui/handle/1/33461
metadata.artigo.dc.language: en_US
Appears in Collections:DGA - Artigos publicados em periódicos

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