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Revista Lasallista de Investigación
versión impresa ISSN 1794-4449
Resumen
RODRIGUEZ-ROJAS, Yuber Liliana; LUQUE CLAVIJO, Ana María y CASTRO ROJAS, Martha Lucía. Methodologies for the strengthening of research lines in academic or business research groups. Rev. Lasallista Investig. [online]. 2019, vol.16, n.2, pp.142-159. ISSN 1794-4449. https://doi.org/10.22507/rli.v16n2a12.
Introduction:
The availability of large volumes of data has made the decision making process, both for academics and businesses, a complex issue, so it is necessary to simplify these procedures in order to decide effectively.
Objective:
This article presents the results of a study that sought to identify the methodologies used to define or strengthen research lines in academic or business groups.
Materials and methods:
A systematic exploratory review in Scopus, Ebsco, Science Direct and Scielo retrieved 146 items, of which 35 were incorporated into the analysis.
Results:
Three different trends were found: 1) the quantitative approach shows methodologies related to the use of bibliometrics, scientometrics and text mining, 2) the qualitative approach identified documentary, knowledge or perceptions analyses regarding the management of innovation and development, seen from academia and from the real sector, and 3) the mixed approach identified profile studies of human capital, Hilbert formal system for classical propositional logic, qualitative-sociological simulation, intermediate review (metric and peers), interviews and surveys to businesses and Delphi technique.
Conclusion:
The findings show that the use of quantitative, qualitative or mixed approaches is relevant according to the area of interest of the center or research group; in addition, for developed countries this issue is apparently overcome, given that no recent evidence about academic production was found, whilst for developing countries, there is current interest, in particular that which is related to aspects of investment and its return.
Palabras clave : technological innovation management; industrial policy; sectoral planning methods; data collection and estimation methodology.