基于Pareto分布的决策单元DEA效率评价

针对网络数据包络分析(DEA)应用时缺少内部数据的瓶颈,提出将决策单元内部的生产活动按照价值动因分为核心和非核心生产单元,并根据经验Pareto分布估计核心单元的输入数据,据此构建DEA效率评价模型.新模型利用输入输出数据和基于管理者经验信息获得的更多信息,据此估计生产潜力并给出相应的估计的概率,为决策单元的管理者分配资源和设定目标提供理论支持.最后利用模拟数据演示所提出的模型,并与BCC模型的结论相比较,结果显示新模型能够发现更高的生产潜力的信息,可以为决策者制订目标提供依据.

Evaluation of the DEA efficiency of decision making units based on Pareto distribution

Aiming at the bottleneck for the application of network DEA(data envelopment analysis),namely, lacking internal operational data,this paper proposes firstly to classify the production activities in light of value analysis to form core production unit and non-core production unit.Secondly,the input data of core production unit are estimated based on Pareto distribution,and then used by extended DEA model for evaluation purpose. The proposed model can uncover much more useful information through better exploration of observational data and manager’s experience.It estimates the production potential and provides the accompanying probability, which serves as theoretical support for decision makers to allocate resource and set targets.Finally, simulated data are used to demonstrate the proposed model and the results are compared with those from BCC model.It is shown that the proposed model can discover production information to support for higher targets.