Discretionary models of data envelopment analysis (DEA) assume that all inputs and outputs are discretionary, i.e., controlled by the management of each decision making unit (DMU) and varied at its discretion. In any realistic situation, however, there may exist exogenously fixed or non-discretionary inputs or outputs that are beyond the control of a DMU\u27s management. There are some models that incorporate non-discretionary inputs into DEA models. This paper reviews these approaches, providing a discussion of strengths and weaknesses and highlighting potential limitations. Moreover, a new method is developed that overcomes existing weaknesses
Data Envelopment Analysis (DEA) is a non-parametric approach to operations research for assessing th...
DEA is a mathematical quantitative approach for measuring the performance of a set of homogeneous De...
Data envelopment analysis (DEA) is a method for assessing the comparative efficiencies of decision m...
This paper develops a method based on data envelopment analysis (DEA) for efficiency assessments ta...
As the title suggests, this paper constitutes a modification and improvement of the paper by Gholam ...
Data Envelopment Analysis (DEA) is a popular non-parametric technique for the assessment of efficien...
Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of...
In this paper, we discuss three-stage models that control for exogenous, non-discretionary inputs in...
Analyzing the efficiency of actions, productions, or organizational units is a fundamental problem o...
Data envelopment analysis (DEA) is a data based mathematical approach, which handles large numbers o...
The dependent relationship among the decision making units (DMU) is usually assumed to be non-existe...
This paper attempts to provide a systematic approach to the DEA model building. To this end, we try ...
Data envelopment analysis (DEA) as a method of measuring the efficiency of decision-making units (DM...
In models of data envelopment analysis (DEA), an optimal set of input and output weights is generall...
Classical Data Envelopment Analysis (DEA) models consider each Decision Making Unit (DMU), whose rel...
Data Envelopment Analysis (DEA) is a non-parametric approach to operations research for assessing th...
DEA is a mathematical quantitative approach for measuring the performance of a set of homogeneous De...
Data envelopment analysis (DEA) is a method for assessing the comparative efficiencies of decision m...
This paper develops a method based on data envelopment analysis (DEA) for efficiency assessments ta...
As the title suggests, this paper constitutes a modification and improvement of the paper by Gholam ...
Data Envelopment Analysis (DEA) is a popular non-parametric technique for the assessment of efficien...
Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of...
In this paper, we discuss three-stage models that control for exogenous, non-discretionary inputs in...
Analyzing the efficiency of actions, productions, or organizational units is a fundamental problem o...
Data envelopment analysis (DEA) is a data based mathematical approach, which handles large numbers o...
The dependent relationship among the decision making units (DMU) is usually assumed to be non-existe...
This paper attempts to provide a systematic approach to the DEA model building. To this end, we try ...
Data envelopment analysis (DEA) as a method of measuring the efficiency of decision-making units (DM...
In models of data envelopment analysis (DEA), an optimal set of input and output weights is generall...
Classical Data Envelopment Analysis (DEA) models consider each Decision Making Unit (DMU), whose rel...
Data Envelopment Analysis (DEA) is a non-parametric approach to operations research for assessing th...
DEA is a mathematical quantitative approach for measuring the performance of a set of homogeneous De...
Data envelopment analysis (DEA) is a method for assessing the comparative efficiencies of decision m...