基于PCA-DEA-Tobit模型的物流企业绩效评价  

Performance Evaluation of Logistic Companies Based on PCA-DEA-Tobit Model

作　　者：郭瑛[1] GUO Ying(School of Economics and Management,Wuhu Institute of Technology,Wuhu 241003,China)

机构地区：[1]芜湖职业技术学院经济管理学院,安徽芜湖241003

出　　处：《安徽建筑大学学报》2023年第6期64-69,85,共7页Journal of Anhui Jianzhu University

基　　金：安徽高校人文社会科学研究重点项目(SK2021A0925)。

摘　　要：提出了基于PCA-DEA-Tobit的物流企业绩效评价的新方法并实证验证了其有效性和可行性。首先将物流企业绩效的指标区分为内部因子指标和外部因子指标,并将每个一层内部因子指标进一步区分为与物流企业各个运营环节契合的二层内部因子指标。为了满足DEA的使用条件,应用主成分分析法(PCA)消除原二层指标之间的相关性,并按照至少85%的累计贡献率提取出新的二层指标并进行正数化处理,进而应用交叉效率DEA对各一层内部因子指标进行评价,结合由熵权法得到的客观权重得到各决策单元的整体绩效值及相应排序,最后以Tobit回归模型分析外部因子指标与物流企业整体绩效的关联程度及其影响。A new evaluation method of logistics enterprise performance based on PCA-DEA-Tobit was proposed and its effectiveness and feasibility was verified by empirical study.The indicators of logistics enterprise performance were divided into internal and external factor indicators,and each first-level indicator was subdivided into second-level indicators that fit with the logistics operations.To meet the use conditions of DEA,the principal component analysis(PCA)method was applied to eliminate the correlation between the original second-level indicators,and the new second-level indicators were extracted considering the cumulative contribution rate of at least 85%and further processed into positive numbers.Then,the cross-efficiency DEA was used to evaluate the first-level internal factor indicators,combined with the objective weights calculated by the entropy weight method,to yield the overall performance and the ranking of decision-making unit.Finally,the Tobit regression model was used to analyze the correlation degree as well as the impact between external factor indicators and the overall performance of logistics enterprises.

关 键 词：绩效评价 PCA-DEA-Tobit 物流企业 

分 类 号：F259.23[经济管理—国民经济]