基于改进超效率DEA的企业竞争情报分析

Analysis on Competitive Intelligence Work in Enterprises Based on a Modified Super-efficiency DEA Model

DEA是一种有效的企业竞争情报分析方法,但基本DEA方法在应用过程中会出现多个决策单元同时相对有效的局面,不能继续区分它们之间有效的差异程度。笔者提出了分段规模报酬改进超效率DEA方法,并以20家钢铁上市企业为例,阐述了其在企业竞争情报分析中的具体应用。结果表明,经改进后的超效率DEA方法能有效区分各决策单元效率值。

Data Envelopment Analysis （ DEA ） is an effective approach for competitive intelligence work analysis to provide the visual and authoritative foundation for competition decision-making in enterprises. However, the basic DEA model is confined to a situation, in which multiple decision-making units appear relative effectiveness simultaneously, and it＇s hard to distinguish the difference degree of ef- fectiveness among them. Considering the premise, this paper aims to build up a modified Super-efficiency DEA model based on piecewise returns to scale, and argue the specific applications in analysis of competitive intelligence work, using 20 listed steel companies as a sam- pie. The research outcome indicated that, the modified Supper-efficiency DEA model can effectively distinguish the efficiency value of each decision unit.