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मालमक्विस्ट उत्पादकता सूचकांक×नेटवर्क डेटा एनवेलपमेंट एनालिसिस (नेटवर्क डीईए)×
क्षेत्रदक्षता विश्लेषणदक्षता विश्लेषण
परिवारRegression modelRegression model
उद्भव वर्ष19942000
प्रवर्तकFäre, Grosskopf, Norris & ZhangFäre & Grosskopf
प्रकारNon-parametric productivity indexMulti-stage nonparametric efficiency model
मौलिक स्रोतFäre, 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. link ↗Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49. DOI ↗
उपनामMPI, Malmquist Index, Malmquist DEA Productivity Index, Malmquist Verimlilik EndeksiNetwork Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi
संबंधित12
सारांशThe 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).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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