Fuzzy interpretation of efficiency in data envelopment analysis and its application in a non-discretionary model

Non-discretionary Factors in Data Envelopment Analysis: Review and Extension

A data envelopment analysis model with discretionary and non-discretionary factors in fuzzy environments

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision-making units (DMUs) that use multiple inputs to produce multiple outputs. The standard DEA models assume that all inputs and outputs are crisp and can be changed at the discretion of management. While crisp input and output data are fundamentally indispensable in the standard DEA evalua...

Data Envelopment Analysis Models In The Presence Of Ratio Data and Non-Discretionary Factors

Non-discretionary imprecise data in efficiency Measurement

This paper introduces discretionary imprecise data in Data Envelopment Analysis (DEA) and discusses the efficiency evaluation of Decision Making Units (DMUs) with non-discretionary imprecise data. Then, suggests a method for evaluation the efficiency of DMUs with non-discretionary imprecise data. When some inputs and outputs are imprecise and non-discretionary, the DEA model becomes non-linear ...

Measuring Economic Efficiency of Kidney Bean Production using Non-Discretionary Data Envelopment Analysis

Efficient use of assets in agriculture is a goal for policy-makers and farmers. Agricultural input resources are scarce therefore optimum use of inputs in different agricultural operations is important. Mathematical programming technique such as data envelopment analysis (DEA) is a well-known approach for estimation efficiency of agricultural DMUs. In this study, efficiency of kidney bean produ...