So sánh phương pháp

	Bootstrap DEA: Hiệu chỉnh độ chệch và khoảng tin cậy cho điểm hiệu quả	Phân tích bao dữ liệu mạng (Network DEA)
Lĩnh vực	Phân tích hiệu quả	Phân tích hiệu quả
Họ	Regression model	Regression model
Năm ra đời	1998	2000
Người khởi xướng	Simar & Wilson	Färe & Grosskopf
Loại	Nonparametric efficiency estimation with bootstrap inference	Multi-stage nonparametric efficiency model
Công trình gốc	Simar, L., & Wilson, P. W. (1998). Sensitivity analysis of efficiency scores: How to bootstrap in nonparametric frontier models. Management Science, 44(1), 49–61.	Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49.
Tên gọi khác	Bootstrapped DEA, DEA Bootstrap Inference, Simar-Wilson Bootstrap, Bootstrap Sınır Analizi	Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi
Liên quan	2	2
Tóm tắt	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.	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.