Methoden vergleichen

	Netzwerk Data Envelopment Analysis (Network DEA)	Bootstrap DEA: Bias-Korrektur und Konfidenzintervalle für Effizienzwerte
Fachgebiet	Effizienzanalyse	Effizienzanalyse
Familie	Regression model	Regression model
Entstehungsjahr	2000	1998
Urheber	Färe & Grosskopf	Simar & Wilson
Typ	Multi-stage nonparametric efficiency model	Nonparametric efficiency estimation with bootstrap inference
Wegweisende Quelle	Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49.	Simar, L., & Wilson, P. W. (1998). Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Management Science, 44(1), 49–61.
Aliasnamen	Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi	Bootstrapped DEA, DEA Bootstrap Inference, Simar-Wilson Bootstrap, Bootstrap Sınır Analizi
Verwandt	2	2
Zusammenfassung	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.	Bootstrap Data Envelopment Analysis (Bootstrap DEA) is a resampling-based extension of standard DEA that provides statistically valid inference for efficiency scores. Introduced by Simar and Wilson in 1998, it addresses the core weakness of classical DEA — its inability to quantify uncertainty in estimated scores — by constructing bootstrap confidence intervals and bias-corrected efficiency estimates from repeatedly resampled pseudo-frontiers.