Open Journal of Business and Management

Volume 8, Issue 4 (July 2020)

ISSN Print: 2329-3284   ISSN Online: 2329-3292

Google-based Impact Factor: 1.02  Citations  

Organizational Guidelines for Embrapa Advanced Quantitative Methods and Scientific Computing Area

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DOI: 10.4236/ojbm.2020.84111    96 Downloads   257 Views  

ABSTRACT

This study aimed to define organizational guidelines on advanced quantitative methods and scientific computing (QMSC) for the Brazilian Agricultural Research Corporation (Embrapa), a public institution under the Brazilian Ministry of Agriculture, Livestock and Food Supply (MAPA). The study was based on a strategic and systemic perspective to support the strengthening of governance of the area of research, development and innovation (RD&I) at Embrapa. This exploratory qualitative study was conducted in two phases. In the first phase, a benchmarking study of organizational model restructuring, especially in areas of QMSC, was carried out in Brazilian and international RD&I institutions. The second phase included an analytical and critical study on the general panorama of QMSC research. Both phases supported the generation of the final result of this study, which was the formulation of a proposal for organizational guidelines for the QMSC area at Embrapa. The study presented the following main results: 1) there is no similarity between the institutions surveyed in the benchmarking and Embrapa, either in terms of the scope of institutional performance, or in relation to the interests focused on organizational innovation in the QMSC area; 2) quantitative methods and scientific computing as areas of expertise and knowledge are widely spread in Brazil, especially at Embrapa, however we did not find equivalence and/or similarity with organizational structure of international institutions. The study highlights the need to expand the scope of the QMSC area at Embrapa, due to the emergence of new fields of activity and new lines of research, for example Data Science. The study recommends Embrapa to prioritize Data Science as a strategic line of research to achieve its results, through research data use and reuse engineering, in order to generate new information and knowledge for decision-making and/or public policy formulation and management.

Cite this paper

Souza, M. , Torres, T. , Júnior, M. , Carvalho, J. , Ternes, S. , Souza, K. and Souza, G. (2020) Organizational Guidelines for Embrapa Advanced Quantitative Methods and Scientific Computing Area. Open Journal of Business and Management, 8, 1816-1830. doi: 10.4236/ojbm.2020.84111.

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