পদ্ধতির তুলনা করুন

	উইন্ডো ডেটা এনভেলপমেন্ট অ্যানালাইসিস	নেটওয়ার্ক ডেটা এনভেলপমেন্ট অ্যানালাইসিস (নেটওয়ার্ক ডিইএ)
ক্ষেত্র	দক্ষতা বিশ্লেষণ	দক্ষতা বিশ্লেষণ
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1984	2000
প্রবর্তক	Charnes, Clark, Cooper & Golany	Färe & Grosskopf
ধরন	Non-parametric panel efficiency model	Multi-stage nonparametric efficiency model
মৌলিক উৎস	Charnes, A., Clark, C. T., Cooper, W. W., & Golany, B. (1984). A developmental study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. Air Forces. Annals of Operations Research, 2(1), 95–112.	Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-Economic Planning Sciences, 34(1), 35–49.
অপর নাম	Sliding-Window DEA, Temporal DEA, Rolling-Period DEA, Pencere VZA	Network Data Envelopment Analysis, Network Efficiency Analysis, Multi-Stage DEA, Ağ Veri Zarflama Analizi
সম্পর্কিত	2	2
সারসংক্ষেপ	Window Data Envelopment Analysis (Window DEA) is a non-parametric panel efficiency method that evaluates decision-making units (DMUs) over time by embedding each DMU's observations across a rolling temporal window into a single cross-sectional DEA problem. Introduced by Charnes, Clark, Cooper, and Golany in 1984, it enables longitudinal efficiency tracking without requiring a full panel, increasing discriminatory power by pooling observations across consecutive periods.	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.