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

Authors

  • Nérida del Carmen Pastrana Díaz Universidad Nacional Hermilio Valdizán de Huánuco

DOI:

https://doi.org/10.15381/idata.v19i1.12546

Keywords:

intellectual capital, human capital, structural capital, relational capital, social capital

Abstract

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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Author Biography

  • Nérida del Carmen Pastrana Díaz, Universidad Nacional Hermilio Valdizán de Huánuco
    Magíster en Gestión de Desarrollo Social, investigadora del Departamento Académico de Ingeniería Industrial y de Sistemas de la Universidad Nacional Hermilio Valdizán de Huánuco.

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Published

2016-10-03

Issue

Section

Sistemas e Informática

How to Cite

Model of intellectual capital measurement in accredited careers of Industrial Engineering from Peru. (2016). Industrial Data, 19(1), 131-138. https://doi.org/10.15381/idata.v19i1.12546