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Multi-evaluation method for group data envelopment analysis

Akio Naito, Shingo Aoki, Hiroshi Tsuji

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Abstract

DEA (Data Envelopment Analysis) is a method for evaluating management efficiency of DMU (Decision Making Unit). Focusing on the DMUs which have group relationship, this study proposes MF-DEA (Multi-Frontier based DEA) model which treats it. The characteristic of the proposed model is that large number of groups can be treated at once by setting frontier of each group. Though the traditional methods have restriction about the number of groups they can treat, MF-DEA is able to deal with group relationship extensively. As a result, the proposed model solves problems which the traditional methods have. The advantages and power of the proposed method are shown by numerical experiments.

About this research paper

What this paper is about

DEA (Data Envelopment Analysis) is a method for evaluating management efficiency of DMU (Decision Making Unit). Focusing on the DMUs which have group relationship, this study proposes MF-DEA (Multi-Frontier based DEA) model which treats it. The characteristic of the proposed model is that large number of groups can be treated at once by setting frontier of each group. Though the traditional methods have restriction about the number of groups they can treat, MF-DEA is able to deal with group relationship extensively. As a result, the proposed model solves problems which the traditional methods have. The advantages and power of the proposed method are shown by numerical experiments.

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Available abstract

DEA (Data Envelopment Analysis) is a method for evaluating management efficiency of DMU (Decision Making Unit). Focusing on the DMUs which have group relationship, this study proposes MF-DEA (Multi-Frontier based DEA) model which treats it. The characteristic of the proposed model is that large number of groups can be treated at once by setting frontier of each group. Though the traditional methods have restriction about the number of groups they can treat, MF-DEA is able to deal with group relationship extensively. As a result, the proposed model solves problems which the traditional methods have. The advantages and power of the proposed method are shown by numerical experiments.

Key concepts: Data envelopment analysis, Efficient frontier, Group (periodic table), Computer science, Econometrics, Mathematical optimization, Operations research, Mathematics

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