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An Early Warning Risk and Control Model for Manpower Capital Investment Using Data Warehousing and Computational Intelligence.
Liu, Yang; Wang, Zongyu.
Affiliation
  • Liu Y; School of Economics and Management, Harbin University of Science and Technology, Harbin, Heilongjiang 150080, China.
  • Wang Z; School of Electronics and Information Engineering, Heilongjiang University of Science and Technology, Harbin, Heilongjiang 150022, China.
Comput Intell Neurosci ; 2022: 7624135, 2022.
Article in En | MEDLINE | ID: mdl-35371241
Human capital plays an important role in the development of enterprises. Investing in human capital is the main focus of enterprises to improve personnel quality and enhance their core competitiveness. With the development of market economy, the function of human resource market allocation has been improved and the mobility of enterprise human resources has been enhanced leading to the increase in investment risk of enterprise human capital. Enterprise human capital investment risk has a negative impact on enterprises, reduces the income of enterprises' human capital investment, and affects their growth. Hence, enterprises need to avoid the risk of human capital investment or minimize the negative impact of risk. Using the data warehouse and computational intelligence, this paper constructs the early warning and control model for human capital investment risk and analyzes the existing approaches during the recruitment process and training, investment, and production, among enterprises. Finally, this paper proposes the corresponding control method according to the model inspiration.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Data Warehousing / Investments Type of study: Etiology_studies / Risk_factors_studies Limits: Humans Language: En Journal: Comput Intell Neurosci Journal subject: INFORMATICA MEDICA / NEUROLOGIA Year: 2022 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Data Warehousing / Investments Type of study: Etiology_studies / Risk_factors_studies Limits: Humans Language: En Journal: Comput Intell Neurosci Journal subject: INFORMATICA MEDICA / NEUROLOGIA Year: 2022 Document type: Article Affiliation country: Country of publication: