Artificial intelligence-based organizational human resource management and operation system

被引:4
作者
Yang, Yang [1 ]
机构
[1] North China Univ Water Resources & Elect Power, Sch Management & Econ, Zhengzhou, Peoples R China
关键词
human resources; artificial intelligence; operational systems; management operations; data mining; DEEP;
D O I
10.3389/fpsyg.2022.962291
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
The trend of globalization, marketization, and informatization continues to strengthen, in today's development environment, how to seize the opportunity and obtain a competitive advantage in human resources is an important issue that needs to be explored. Human resource management refers to the effective use of relevant human resources inside and outside the organization through management forms under the guidance of economics and humanistic thinking. It is a general term for a series of activities that ensure the achievement of organizational goals and the maximization of member development. With the rapid development of society and economy, the competition between enterprises has intensified. If an enterprise wants to adapt to social development, it is necessary to strengthen the internal management of the organization. The internal management also needs to rely on human resource management. The purpose of this paper is to study an organization's human resource management and operation system based on artificial intelligence. It expects to use artificial intelligence technology to design the human resource management system and to improve the quality of employees to make the enterprise develop toward a more scientific and reasonable method. It uses artificial intelligence technology to mine the relevant data of enterprises, understand the situation of enterprises in a timely manner, and adjust unreasonable rules. This paper establishes a dynamic capability evaluation model and an early warning model for human resource management and further studies the improvement approach based on human resource management. This paper analyzes the application, feasibility, and practical significance of data mining technology in human resource management systems. It focuses on the commonly used algorithms in the field of data mining and proposes specific algorithm application scenarios and implementation ideas combined with the needs of human resource management practices. The experimental results of this paper show that the average working life of incumbent employees is 3.5 years, the average length of employees who leave the company is 5 years, and some employees are 5-6 years old. From this data, it can be seen that the average number of years of on-the-job employees is short, and the work experience has yet to be accumulated.
引用
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页数:11
相关论文
共 20 条
[1]  
Agrawal A, 2017, MIT SLOAN MANAGE REV, V58, P23
[2]   Modes of integration of human resource management practices in multinationals [J].
Belizon, Maria Jesus ;
Morley, Michael J. ;
Gunnigle, Patrick .
PERSONNEL REVIEW, 2016, 45 (03) :539-556
[3]   Ethical Considerations in Artificial Intelligence Courses [J].
Burton, Emanuelle ;
Goldsmith, Judy ;
Koenig, Sven ;
Kuipers, Benjamin ;
Mattei, Nicholas ;
Walsh, Toby .
AI MAGAZINE, 2017, 38 (02) :22-34
[4]   Concepts, contexts, and mindsets: Putting human resource management research in perspectives [J].
Cooke, Fang Lee .
HUMAN RESOURCE MANAGEMENT JOURNAL, 2018, 28 (01) :1-13
[5]  
Crowley F, 2017, INT J INNOV MANAG, V21, DOI 10.1142/S1363919617500037
[6]   Human capital and human resource management to achieve ambidextrous learning: A structural perspective [J].
Diaz-Fernandez, Mirta ;
Pasamar-Reyes, Susana ;
Valle-Cabrera, Ramon .
BRQ-BUSINESS RESEARCH QUARTERLY, 2017, 20 (01) :63-77
[7]  
Ghoson T., 2021, AM J BUSINESS OPERAT, V5, P61, DOI [10.54216/AJBOR.050201, DOI 10.54216/AJBOR.050201]
[8]  
Grover S., 2020, FUSION PRACTICE APPL, V2, P64, DOI [10.54216/FPA.020204, DOI 10.54216/FPA.020204]
[9]   Using a multi-agent system and artificial intelligence for monitoring and improving the cloud performance and security [J].
Grzonka, Daniel ;
Jakobik, Agnieszka ;
Kolodziej, Joanna ;
Pllana, Sabri .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 86 :1106-1117
[10]   Human resource management and employee well-being: towards a new analytic framework [J].
Guest, David E. .
HUMAN RESOURCE MANAGEMENT JOURNAL, 2017, 27 (01) :22-38