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| 초효율 자료포락분석× | 네트워크 자료포괄분석 (Network DEA)× | |
|---|---|---|
| 분야 | 효율성 분석 | 효율성 분석 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1993 | 2000 |
| 창시자≠ | Andersen & Petersen | Färe & Grosskopf |
| 유형≠ | Nonparametric linear programming model | Multi-stage nonparametric efficiency model |
| 원전≠ | Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261–1264. DOI ↗ | Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49. DOI ↗ |
| 별칭 | Andersen-Petersen Model, Super-Radial DEA, Ranking DEA, Süper Etkinlik VZA | Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi |
| 관련 | 2 | 2 |
| 요약≠ | Super-Efficiency DEA is a nonparametric linear programming extension of classical Data Envelopment Analysis (DEA) introduced by Andersen and Petersen (1993). While standard DEA assigns a maximum efficiency score of 1.0 to all units on the efficient frontier, Super-Efficiency DEA allows efficient units to receive scores greater than 1.0 by temporarily removing the evaluated unit from the reference set. This modification enables full ranking of all decision-making units (DMUs), including those previously indistinguishable at the frontier. | Network Data Envelopment Analysis (Network DEA) is a nonparametric efficiency measurement framework introduced by Färe and Grosskopf (2000) that extends classical DEA to multi-stage or multi-division production processes. Rather than treating a decision-making unit as a black box, it explicitly models the internal structure — the divisions and the intermediate products that flow between them — enabling stage-level and overall efficiency scores to be estimated simultaneously within a single coherent model. |
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