An Analysis of the Optimal Allocation of Core Human Resources in Family Enterprises Based on the Markov Model. (17th January 2022)

• Record Type: Journal Article
• Authors: Cao, Jinyang
• Other Names: Chen Miaochao Academic Editor.
• Is Part Of: Journal of mathematics. Volume 2022(2022)
• Publication Date: 2022-01-17
• Subjects: Mathematics -- Periodicals; Mathematics; Periodicals; 510
• DOI: 10.1155/2022/7619293
• Languages: English
• ISSNs: 2314-4629

Abstract

Abstract : As an important component of family business management, human resource allocation greatly affects all aspects of the company's strategic direction and organizational structure. Therefore, the optimal allocation of core human resources in family businesses has become a topic of great practical significance. Based on the Markov model, this article is based on the B/S architecture, designed the three-tier architecture of the presentation layer, business logic layer, and data layer adopted by the system, forming the basis of quality management, job management, performance management, and salary management-oriented human resources optimization configuration system. Taking family business A as an example, the Markov chain is used to predict the flow of personnel in the company in the next three years. The results show that with the development of normalization and the improvement of the management level, the demand for personnel in the family business will decrease year by year. Competency analysis of human resources positions found that grassroots employees have higher requirements for competency, but at the same time, lower performance requirements, while company seniors need relatively low requirements for competence indicators and higher requirements for performance. In addition, through data calculation and prediction, it is found that the prediction accuracy of the model algorithm is 81.37% on average. Compared with other model algorithms, the Markov model algorithm has the highest accuracy in predicting the state, and the accurate prediction results make the recruitment work predictable. The system makes up for the shortcomings of traditional human resource management data, such as insufficient data, low accuracy, and inability to achieve homogeneity. It uses a centralized database to comprehensively and organically link human resource management-related information to provide a basis for future family business human resource optimization.