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Mapeamento dos fluxos de informa??o e conhecimento: a governan?a de TI sob a ótica das redes sociais

DOI: 10.1590/S0104-530X2012000200011

Keywords: creation and diffusion of knowledge, social network analysis, information technology, itil.

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Abstract:

business competitiveness requires the company's ability to define and implement competitive strategies that will allow its survival and development in the long term - in other words, its sustainability. among these strategies, technological innovation associated with the development of the technical-scientific capacity of the company, and therefore, of the individuals who work in its various processes, has acquired a position of growing importance in corporate planning and actions. accordingly, interpersonal relations are a critical factor for innovation processes, which must be continuously improved. the main objective of this study is to contribute to the understanding of the dynamics associated with these processes from the case study conducted focusing on procedures and information flows generated by the capacity management of a large telecommunications company in brazil. the research was carried out based on qualitative and quantitative approaches. on the one hand, from the philosophical perspective of interpretation and based on the qualitative research, it was possible to study the social phenomenon related to the diffusion of knowledge among members of a team responsible for the actions and technical proposals in the capacity management of the telecom company being studied. on the other hand, the quantitative approach allowed the use of mathematical models in order to measure properties (e.g. cohesion, centrality, prestige and connectivity) of the networks studied and to provide their topological characterization. the present study was developed based on the model proposed by nonaka and takeuchi (1977) in order to analyze and describe the processes of creation and dissemination of knowledge in the organization, associated with the methods of social network analysis (sna). the results suggest that the networks studied exhibit scale-free topology, which makes the flow of information and knowledge resistant to random "attacks" (e.g. spontaneous resignation of a

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