Model of intellectual capital measurement in accredited careers of Industrial Engineering from Peru

Descripción del Articulo

In this globalization scenario, where the knowledge is the new basis for competitiveness, organizations face challenges that require imminently, the identification and measurement of intangible that represent of Intellectual Capital so they can be managed effectively and achieve the levels of compet...

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Detalles Bibliográficos
Autor: Pastrana Díaz, Nérida del Carmen
Formato: artículo
Fecha de Publicación:2016
Institución:Universidad Nacional Mayor de San Marcos
Repositorio:Revistas - Universidad Nacional Mayor de San Marcos
Lenguaje:español
OAI Identifier:oai:ojs.csi.unmsm:article/12546
Enlace del recurso:https://revistasinvestigacion.unmsm.edu.pe/index.php/idata/article/view/12546
Nivel de acceso:acceso abierto
Materia:intellectual capital
human capital
structural capital
relational capital
social capital
capital intelectual
capital humano
capital estructural
capital relacional
capital social.
Descripción
Sumario:In this globalization scenario, where the knowledge is the new basis for competitiveness, organizations face challenges that require imminently, the identification and measurement of intangible that represent of Intellectual Capital so they can be managed effectively and achieve the levels of competitiveness today’s world demands. In the article the design of Model of Intellectual Capital Measurement in Accredited Careers of Industrial Engineering: CII-FII is proposed, based on a case study. This model is empirically validated through a sample of 100 teachers obtained from four (04) Accredited Careers of Industrial Engineering from Peru, the results show that the Intellectual Capital is a distinctive competitive advantage, having reached a valuation of 63.54%, where the Human Capital has the highest valuation in respect of Structural Capital with 24.02%, followed by Structural Capital with 16.5%, the Relational Capital with 13.98% and finally the Social Capital with 9.05% and using Bayesian Networks twelve factors that have significant influence on the Intellectual Capital and the impacts that they generate are determined. An application software for the measurement and management of Intellectual Capital is proposed.
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