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Introduction: this article supports the bases of a knowledge management infrastructure that improves the capacity for innovation in a company in the Colombian energy sector. Materials and methods: four methodological phases were carried out: a bibliometric review was carried out, the model that contemplates as variables was defined: intellectual capital and organizational learning, human resources management, information, and communication technologies (ICT) and innovation, this was used for the diagnosis and, finally, for the practical proposal. Results: it was validated a direct, positive, and significant relationship between knowledge management and innovation and a direct, positive, and significant mediation of human resource management and ICT between knowledge management and innovation. Conclusions: we concluded that intellectual capital and organizational learning integrate knowledge management, and in turn, that there are mediating conditions for human resource management and ICT for knowledge management in innovation in an organization. [ABSTRACT FROM AUTHOR]

Introduction: Knowledge management as an innovative and key process for smart organizations allowed its application in higher education research centers, based on intellectual capital (IC), as a fundamental axis in the creation of intangible assets, using the Intellectus model, which emphasizes as components of the IC: Human Capital (HC), Structural Capital (SC) and Relational Capital(RC). Objective: The work seeks to develop a measurement methodology for HC and SC for research centers. Materials and methods: Using the fuzzy logic technique 2 and the Matlab® toolbox, algorithms were generated to obtain an intelligent tool. The model validation was applied to the Administrative Sciences research group of the Metropolitan Technological Institute of Medellin. Through the Delphi technique, six experts determined that the decisive variables to be evaluated, according to the model, were from the HC: values and aptitudes, attitudes, and knowledge; from organizational SC: organizational learning; and from technological SC: R&D. The information was obtained from the application of a questionnaire with 54 questions to 16 researchers, measured with a Likert scale. Results: With fuzzy logic 2, a base of rules was achieved that, together with the Karnik-Mendel type of reduction, allowed decision making on the variables through the control surface. Conclusion: The combination of capabilities and effort and R&D brings greater value. The relationship between attitudes and organizational learning is significant, although not a priority in the generation of value; and the generation of value, between the values and skills variables, with organizational learning, is not significant.e [ABSTRACT FROM AUTHOR]