insurance industry is one of the most influential economic institutions and is considered to support other economic institutions and families. insurance industry has been facing changes that lead it to becoming a competitive industry. therefore, we can say insurance companies that are active in iran insurance industry must constantly monitor performance of their branches and agencies. ongoing p...

Discretionary models of data envelopment analysis (DEA) assume that all inputs and outputs can be varied at the discretion of management or other users. In any realistic situation, however, there may exist ”exogenously fixed” or non-discretionary factors that are beyond the control of a DMU’s management, which also need to be considered. Also DEA requires that the data for all discretionary inp...

Few inverse data envelopment analysis (DEA) models have incorporated non-discretionary measures based on radial efficiency values. However, the may be miscounted in approaches when some non-zero slacks appear. Furthermore, there is scant research DEA to estimate performance restaurant industry. Accordingly, this proposes non-radial analyze and output changes of Iranian restaurants while also pr...

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 ...

abstract. data envelopment analysis (dea) is now widely utilized as a method for assessing relative efficiency of a set of decision making units (dmus). along as evaluating relative efficiency dea models are capable of to be improved for finding benchmark for inefficient units which can help managers for better making decision. thus it is important to obtain accurate results from dea models. in...

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 ...

data envelopment analysis (dea) measures the relative efficiency of a homogenous set of decision-making units (dmus) when multiple inputs and outputs are present. the deabased malmquist productivity index measuring the productivity change of dmus over time has proven itself to be a valid tool to compare group performance. however, in the previous models developed for this purpose, it was suppos...

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...