Research and Simulation of Enterprise Management Performance Evaluation Model Based on Grey Management Theory
- 10.2991/amcce-15.2015.224How to use a DOI?
- enterprise performance evaluation; human resource management; grey correlation evaluation
The system design of enterprise performance evaluation is researched, traditionally, there is no effective business enterprise performance management mathematical model, the quantitative venture evaluation of enterprise performance is difficult, and the science and quantitative analysis of enterprise performance management is absent. For this problem, an improved enterprise management performance evaluation model is proposed based on grey management theory, the multiple linear regression mathematical model of performance management tendency degree is established, the overall design of the system is established based on questionnaire survey and case risk data analysis, the performance management the risk evaluation and the prediction algorithm is designed, the mathematical modeling of enterprise performance management model is obtained based on performance management tendency degree computing, the grey correlation evaluation prediction algorithm is proposed, the model factor is evaluated and estimated, the practical applications is taken as the background, and the simulation is completed, the test and simulation results show that the model can improve the performance of enterprise management level, promote the company related reform and rectification, it has good application value in field of enterprise human resources management.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Ming Li AU - JianYun Li PY - 2015/04 DA - 2015/04 TI - Research and Simulation of Enterprise Management Performance Evaluation Model Based on Grey Management Theory BT - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/amcce-15.2015.224 DO - 10.2991/amcce-15.2015.224 ID - Li2015/04 ER -