摘要
本研究以国际标准化组织的ISO26000、全球报告倡议组织的G4标准等权威机构报告及相关文献为基础,结合企业社会责任内涵,依据权威机构典型指标高频率原则,通过方差膨胀因子剔除反映信息重复的指标,通过主成分分析遴选出对企业社会责任评价结果影响显著的指标,构建了包括环境、人权等5个准则层,循环再造物料的使用、烟粉尘排放及减排等45个指标的企业社会责任海选评价指标体系。通过云模型构建交通运输行业企业社会责任评价模型。本文的创新与特色:一是通过云模型构建交通运输行业企业社会责任评价模型,不仅考虑了企业社会责任概念的不确定性,也体现了交通运输行业的随机性与企业社会责任的模糊性之间的联系,在定性与定量之间形成相互映射的关系,测度了交通运输行业企业社会责任的履行情况。二是通过建立某准则层内一个指标与其他所有指标的线性回归方程,求解反映指标相关性的指标方差膨胀因子VIF,剔除指标方差膨胀因子VIF大于阈值的指标并保留剩余指标,避免了指标反映信息重复。实证结果表明,42家交通运输企业得分均值为40.16分,只有20家企业超过平均得分,不同企业的社会责任履行差异较大,社会责任总体处于中下等水平。
Based on the IS026000 of the International Organization for Standardization, the G4 standard of the Global Reporting Initiative, and other relevant authoritative reports and related literature, this paper combines with the connotation of CSR and the principle of typical indicators of high frequency in the authority agency to eliminate the indicators. [t reflects the repetition of in- formation through the variance expansion factor and selects the indexes of significant impact on the CSR evaluation through the principal component analysis. Hence five criterion layers （including the environment, human rights, etc. ） and 45 indicators （ including the use of recycled materials, smoke and dust emission and reduction, etc. ） are constructed. The model is used to construct the CSR evaluation model of transportation industry. The innovation and characteristics of this paper ： First, it is to con- struct a model of the performance evaluation for the CSR of the transportation industry based on the cloud model, it not only con- siders the uncertainty of the concept of the CSR, but also reflects the connection between the randomness of the transportation in- dustry the vagueness of the CSR, it forms a mutual mapping relationship between qualitative and quantitative, and weights the e- valuation index of the CSR through the cloud model, finally it measures the implementation of the CSR of the transportation indus- try. Second, by establishing a linear regression equation of one index and all other indicators, the index variance expansion factor VIF is used to solve the correlation index, and then remove the variance expansion factor which VIF is larger than the threshold and keep the remaining indicators to avoid the indicators reflecting the information repetition. The empirical results show that the average score of 42 transportation companies is 40.16, and only 20 companies have exceeded the average level. Different compa- nies have large differences in social responsibility performance, and the overall developme
作者
孟斌
钮尔轩
匡海波
骆嘉琪
Meng Bin;Niu Erxuan;Kuang Haibo;Luo Jiaqi(Collaborative Innovation Center for Transport Studies, Dalian Maritime University, Dalian 116026, Liaoning, China)
出处
《科研管理》
CSSCI
CSCD
北大核心
2018年第7期139-150,共12页
Science Research Management
基金
国家自然科学基金项目(71731003
71672016
71503199
71431002
71301017)
长江学者和创新团队发展计划(IRT_17R13
IRT13048)
国家社会科学基金项目(16BTJ017)
辽宁省高等教育内涵发展专项资金资助项目(20110117201)
大连市社科联重点课题(2016dlskzd042
2017dlskzd034)
