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环保理念下化工行业财务绩效评价指标体系构建 被引量:2

Construction of financial performance evaluation index system of chemical industry under the concept of environmental protection
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摘要 在目前提倡经济与环境协调发展的背景下,化工行业在进行财务绩效评价时仍盲目追求传统的财务绩效,忽略环境保护行为与财务绩效之间的平衡。选取沪深两市2015—2017年化工行业25家上市公司作为研究样本,利用多元线性回归分析法论证化工行业环境指标与财务绩效之间具有显著相关性,再通过主成分分析法筛选出部分传统的财务绩效指标,与相关性强的环境指标共同组成化工行业基本财务绩效评价指标,最后利用熵权法确定指标权重,设计出一套基于环保理念的化工行业财务绩效评价指标体系。该体系旨在既能准确对化工行业进行财务绩效评价又可以约束化工行业片面追求财务绩效而忽视环保问题的行为。 Under the current background of promoting the coordinated development of economy and environment,the chemical industry still blindly pursues the traditional financial performance in the financial performance evaluation,ignoring the balance between environmental protection behavior and financial performance.Therefore,this paper selects 25 listed companies in the chemical industry in Shanghai and Shenzhen stock markets from 2015 to 2017 as research samples,demonstrates the significant correlation between the environmental indicators and financial performance of the chemical industry by the multiple linear regression analysis method,and then selects some traditional financial performance indicators by the principal component analysis method,which together constitute the basic financial performance of the chemical industry.Finally,the entropy weight method is used to determine the index weight,and a set of financial performance evaluation index system of chemical industry based on the concept of environmental protection is designed.The purpose of this system is not only to evaluate the financial performance of the chemical industry accurately,but also to restrain the chemical industry's unilateral pursuit of financial performance and neglect of environmental protection.
作者 刘萍 于建鑫 LIU Ping;YU Jian-xin(School of Economics and Management,Harbin University of Science and Technology,Harbin 150000,China)
出处 《科技与管理》 2020年第1期58-64,共7页 Science-Technology and Management
关键词 环境指标 财务指标 主成分分析 多元线性回归 熵权法 environmental performance financial indicators principal component analysis multiple linear regression entropy weight method
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