表題番号：2021E-018
日付：2022/04/05
研究課題非効率的な事業体に最適な改善経路を提供する動的なDEA手法の開発
| 研究者所属（当時） | 資格 | 氏名 | |
|---|---|---|---|
| （代表者） | 理工学術院 創造理工学部 | 助手 | 王 緒 |
- 研究成果概要
- Data envelopment analysis(DEA) has been widely applied to evaluate relative efficiency and provide benchmarking information(efficient target) for decision making units(DMUs). Recently, the least-distance DEA has been extensively researched, and various corresponding models are proposed because of the practicability of the least-distance benchmarking information(closest efficient target). We have formulated the least-distance range adjusted measure (LRAM), which satisfies a set of desirable properties, as a new practical DEA model for efficiency evaluation and benchmarking. Based on more numerical experiments and deeper analysis, we found (1) that efficient targets provided by the LRAM match the evaluated DMUs more closely than those provided by the convention range adjusted measure(RAM) for most of the inputs and outputs, (2) although LRAM may suggest modifying a greater number of inputs and outputs than that suggested by the RAM, it optimizes the input-output modification to significantly reduce the total percentages of modifications required for each of the inefficient banks to achieve efficiency. Thus, the LRAM suggests the required modifications to achieve efficiency in a more equitable and balanced manner.