Abstract Data Envelopment Analysis (DEA) can be regarded as a useful management tool to the assessment evaluation of decision making units (DMUs) using multiple inputs to produce multiple outputs. In some cases, to evaluate the efficiency having imprecise inputs and outputs such as fuzzy or interval data the efficiency of DMUs won’t be exact as well. Most researches have been conducted were bas...

BACKGROUND Analysis of data collected from pig farms may be useful to understand factors affecting pig health and productive performance. However, obtaining these data and drawing conclusions from them can be done at different levels and presents several challenges. In the present study, information from 688 batches of growing-finishing (GF) pigs (average initial and final body weight of 19.1 a...

It is a general precondition of Data Envelopment Analysis (DEA) that all Decision Making Units (DMUs) to be evaluated are homogeneous. However, it is hard to find a method in the literature to judge whether DMUs are homogeneous or not. This paper firstly analyzes the impacts of DMUs’ non-homogeneity caused by technology difference on the efficiency estimates. It is showed that the DMU under eva...

In the performance evaluation process, using the classic data envelopment analysis (DEA) models, decision making units (DMUs) are considered as black boxes. While in many cases and different applications such as investment funds, banks, insurance companies, etc., DMUs have a network structure. In addition, in many network structures, some of the indicators used to calculate the efficiency...

Abstract Nowadays among many evaluation methods, data envelopment analysis has widely used to evaluate the relative performance of a set of Decision Making Units (DMUs). Data Envelopment Analysis (DEA(is a mathematical tool for evaluating the relative efficiency of a set Decision Making Units (DMUs), with multiple inputs and outputs. Traditional DEA models treat with each DMU as a “black box" t...