Comparer des méthodes

	L'analyse enveloppante de données de réseau (Network DEA)	Indice de productivité de Malmquist
Domaine	Analyse d'efficience	Analyse d'efficience
Famille	Regression model	Regression model
Année d'origine	2000	1994
Auteur d'origine	Färe & Grosskopf	Färe, Grosskopf, Norris & Zhang
Type	Multi-stage nonparametric efficiency model	Non-parametric productivity index
Source fondatrice	Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49.	Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. American Economic Review, 84(1), 66–83.
Alias	Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi	MPI, Malmquist Index, Malmquist DEA Productivity Index, Malmquist Verimlilik Endeksi
Apparentées	2	1
Résumé	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.	The Malmquist Productivity Index (MPI) is a non-parametric measure of total factor productivity (TFP) change over time. Formally grounded in distance functions by Caves, Christensen, and Diewert (1982) and operationalized using Data Envelopment Analysis by Färe, Grosskopf, Norris, and Zhang (1994), MPI decomposes productivity growth into two components: efficiency change (catching-up to the frontier) and technical change (shift of the frontier itself).