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

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

A method to consider Non-Discretionary factors in Data Envelopment Analysis

The technique for efficiency measurement known as Data Envelopment Analysis (DEA) has been extended to allow on-discretionary inputs that affect production. Several methods exist for measuring efficiency to control these factors in production. This paper review these approaches, providing a discussion of strengths and weaknesses and highlighting potential limitations. In addition, a new approac...

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...

Supplier selection using chance- constrained data envelopment analysis with non-discretionary factors and stochastic data

The changing economic conditions have challenged many organizations to search for more efficient and effective ways to manage their supply chain. During recent years supplier selection decisions have received considerable attention in the supply chain management (SCM) literature. There are four major decisions that are related to the supplier selection process: what product or services to order...

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...

An Extension to Imprecise Data Envelopment Analysis

The standard data envelopment analysis (DEA) method assumes that the values for inputs and outputs are exact. While DEA assumes exact data, the existing imprecise DEA (IDEA) assumes that the values for some inputs and outputs are only known to lie within bounded intervals, and other data are known only up to an order. In many real applications of DEA, there are cases in which some of the input ...