2016 Fiscal Year Final Research Report
A DEA theoretical foundation coping with both precise improvement target and quality assurance of efficiency measurement
| Project/Area Number |
26350421
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | Shizuoka University |
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Principal Investigator |
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Keywords | 経営効率性分析 / 最適化問題 / 公理的アプローチ / 列挙アルゴリズム |
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| Outline of Final Research Achievements |
Data Envelopment Analysis (DEA) is a marginal approach to evaluate performance/efficiency of various organizations. The DEA is one of very popular OR (Operations Research) schemes and it has a theoretical background of micro economics. The DEA provides not only the efficiency score but also improvement target. The conventional DEA models find the farthest target from the evaluated organization. The farthest target is difficult to be practically attained because there is significant difference between the target and the organization. This study explores the minimum distance inefficiency measure for the DEA model. A critical issue is that this measure does not satisfy monotonicity, i.e., the measure may provide a better evaluation score to an inferior decision making unit (DMU) than to a superior one. To overcome this, we focus several special classes of the DEA model, and show that for these models, the minimum distance inefficiency measure satisfies the monotonicity property.
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| Free Research Field |
オペレーションズリサーチ
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