A fuzzy approach to the strategic development of human capital in the electric sector. (November 2020)
- Record Type:
- Journal Article
- Title:
- A fuzzy approach to the strategic development of human capital in the electric sector. (November 2020)
- Main Title:
- A fuzzy approach to the strategic development of human capital in the electric sector
- Authors:
- da Silva, Cleriston Fritsch Damasio
de Albuquerque, André Philippi Gonzaga
de Melo, Fagner José Coutinho
Calábria, Felipe Alves
de Medeiros, Denise Dumke - Abstract:
- Highlights: The Fuzzy Set Theory in data processing to reduce respondent subjectivity. Employee training using a literature model to assess human capital development. The model used was adequate to evaluate the strategic development of human capital. The model was applied in two companies in the electric sector. The paper presents the factors that influence the paradigm of formation change. Abstract: Each day employees are becoming essential for organizations to stand out from their competitors in the globalized and disputed world. From this, companies began to invest in training and developing the skills of their employees. Therefore, this research aims to analyze human capital as one of the main factors of competitive differentiation between companies. For this, the research utilizes a tool in the treatment of data that do not fit in the common theories in which the limits between the distinct elements of a set are very clear: Fuzzy Sets Theory. In addition, this paper addresses the issue of training, applying a specific model to assess the development of human capital. The research presented the analysis of data collected in two companies in the electricity sector, one in the energy distribution sector and the other in the energy generation sector. Within the context, the model used was adequate in assessing the development of human capital, bringing a detailed approach to the factors that influence the training paradigm shift, presenting indicators to evaluate theseHighlights: The Fuzzy Set Theory in data processing to reduce respondent subjectivity. Employee training using a literature model to assess human capital development. The model used was adequate to evaluate the strategic development of human capital. The model was applied in two companies in the electric sector. The paper presents the factors that influence the paradigm of formation change. Abstract: Each day employees are becoming essential for organizations to stand out from their competitors in the globalized and disputed world. From this, companies began to invest in training and developing the skills of their employees. Therefore, this research aims to analyze human capital as one of the main factors of competitive differentiation between companies. For this, the research utilizes a tool in the treatment of data that do not fit in the common theories in which the limits between the distinct elements of a set are very clear: Fuzzy Sets Theory. In addition, this paper addresses the issue of training, applying a specific model to assess the development of human capital. The research presented the analysis of data collected in two companies in the electricity sector, one in the energy distribution sector and the other in the energy generation sector. Within the context, the model used was adequate in assessing the development of human capital, bringing a detailed approach to the factors that influence the training paradigm shift, presenting indicators to evaluate these factors, and how to evaluate them within an organization. … (more)
- Is Part Of:
- Computers & industrial engineering. Volume 149(2020)
- Journal:
- Computers & industrial engineering
- Issue:
- Volume 149(2020)
- Issue Display:
- Volume 149, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 149
- Issue:
- 2020
- Issue Sort Value:
- 2020-0149-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-11
- Subjects:
- Human capital -- Fuzzy sets theory -- Strategic development -- Electric sector -- Training
Engineering -- Data processing -- Periodicals
Industrial engineering -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03608352 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cie.2020.106787 ↗
- Languages:
- English
- ISSNs:
- 0360-8352
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.713000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14735.xml