Caracterização das competências do gerente de projetos no setor público
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Data
2016-06-13
Autores
Oliveira, Bruno Silva
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Universidade Federal do Espírito Santo
Resumo
This research aimed to identify the competencies that characterize the project manager in the public sector. To achieve this goal, it was analyzed the influence of the competencies in the probability of project success. To help in the definition of the competencies, it was used the work of Durand (2006) for the decomposition on observable dimensions – knowledge, skills and atitudes – that relates the contribution of the competencies in organizational development. It was applied a online questionaire with 77 project managers working on brazilian public organizations with a minimum maturity level in project management (Prado; Archibald, 2014), between October/2015 and January/2015. Through factor analysis, 49 variables was grouped into three significative factors, and through logistic regression analysis, it was verified the relation of these factors with probability of project success, in the dimensions of time, cost and quality. Qualitative analysis has strengthened results obtained in quantitative analysis and identified negative and positive points in conducting project management in the context of the respondents. Results point that the competencies that characterize project managers in public sector are: knowledge in projects; communication habilities; and trust atitudes, motivation and emotional intelligence. Experience as project manager was also identified as positive to project success, but time of work in the same organization had negative contribution in analyzed sample. Results of this research can serve as a basis for definition of project managers selection criteria in public sector, decreasing the influence of nomination by political reasons and increasing chances of project success, in triple constraint dimensions
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Competencies , Project manager , Public sector , Factor analysis , Logistic regression , Competências , Gerente de projetos , Análise fatorial , Regressão logística