节点文献
中国林业上市公司绩效评价与优化——基于灰色关联度指标筛选与数据包络分析
Performance Evaluation and Optimization of Chinese Forestry Listed Companies——Based on GRA Index Screening and DEA Analysis
【摘要】 选取14家林业上市公司,搜集2017年相关数据,先用灰色关联度(GRA)挑选投入产出指标,再利用数据包络法(DEA)对林业上市公司绩效进行评价与优化。相比于只用DEA模型分析数据,经过GRA指标筛选的绩效评价结果更加准确。研究结果显示:14家公司综合效率平均值为93%,存在7%的资源浪费。总共有6家林业上市公司达到DEA有效。根据各指标优化量并结合公司实际情况,从资产管理、成本控制、规模发展、技术提升等方面为DEA完全无效的5家林业公司提供绩效优化对策。
【Abstract】 Selecting fourteen listed forestry companies, collecting relevant data in 2017, this paper first used Grey Relation Analysis(GRA)to select input-output indicators, and then applied Data Envelopment Analysis(DEA)to evaluate and optimize the performance evaluation of listed forestry companies. Compared with using DEA model only to analyze data, the results of performance evaluation screened by GRA indicators were more accurate. The results showed that: the average comprehensive efficiency of 14 companies is 93%, and there is 7% waste of resources.Six listed forestry companies have achieved DEA effectiveness. According to the optimization quantity of each index and the actual situation of the company, five forestry companies which is totally non-DEA effective are provided with performance optimization countermeasures from the aspects of asset management, cost control, scale development, technology upgrading and so on.
【Key words】 forestry listed company; performance evaluation; optimization; GRA; DEA;
- 【文献出处】 林业经济 ,Forestry Economics , 编辑部邮箱 ,2019年09期
- 【分类号】F326.25;F832.51;F302.6
- 【被引频次】21
- 【下载频次】606