Empirical Research on Employee Satisfaction in K Enterprise
In today' s highly homogenized competitive market environment, the construction efficiency of organizational human resource management has become an important variable determining the sustainable development capability of enterprises. Employees are the most valuable resources of enterprises, and their work performance is directly related to the survival and development of enterprises. However, as an important indicator to measure employees' work attitude and happiness, employee satisfaction is often ignored by enterprises. The purpose of this paper is to explore the empirical research and influence of employee satisfaction. Through the empirical research method, this paper analyzes the influence of different employee satisfaction results on the work performance of enterprises, so as to provide theoretical basis and practical guidance for enterprises to formulate effective incentive policies. In real enterprises, employees with high job satisfaction are less likely to be lost than those with low job satisfaction, and are more responsible, creative and enthusiastic. Therefore, improving employee satisfaction, maintaining the stability of the employee team, reducing the turnover rate of the enterprise, strengthening the sense of belonging of employees to the enterprise, and strengthening the centripetal force and cohesion of the enterprise will be extremely important for the stability and future development of the enterprise. The results show that reasonable incentive policies can significantly improve the job satisfaction of employees, and then increase the efficiency of enterprises and enhance the overall competitiveness of enterprises.
Authors
- Jiufeng Sun (ORCID: https://orcid.org/0000-0003-1047-929X)
- H Chen (ORCID: https://orcid.org/0009-0001-5187-8644)
- Yanping Chen (ORCID: https://orcid.org/0000-0002-7765-8201)
- Zhanming Liang (ORCID: https://orcid.org/0000-0002-8022-4017)
Publication Details
- Journal
- Bulletin of Chinese Psychological Sciences
- Published
- 2025-03-28
- DOI
- https://doi.org/10.48014/pcms.20250208001
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00