विधियों की तुलना करें

	नेटवर्क डेटा एनवेलपमेंट एनालिसिस (नेटवर्क डीईए)	बूस्टस्ट्रैप डीईए: दक्षता स्कोर के लिए पूर्वाग्रह सुधार और विश्वास अंतराल
क्षेत्र	दक्षता विश्लेषण	दक्षता विश्लेषण
परिवार	Regression model	Regression model
उद्भव वर्ष	2000	1998
प्रवर्तक	Färe & Grosskopf	Simar & Wilson
प्रकार	Multi-stage nonparametric efficiency model	Nonparametric efficiency estimation with bootstrap inference
मौलिक स्रोत	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.
उपनाम	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
संबंधित	2	2
सारांश	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.