In this paper, we discuss three-stage models that control for exogenous, non-discretionary inputs in data envelopment analysis. In a recent article in this journal, Monte Carlo analysis was employed to compare and contrast alternative DEA models that measure efficiency in the presence of exogenous variables. The methodology for comparison was flawed, calling into question the results presented....

This research presents a new application of Data Envelopment Analysis (DEA) to empirically determine prices of multiple products. The DEA technique is now widely applied to performance analysis and efficiency measurement in economics, business and other areas in social science. This study does not explore such conventional DEA uses, rather directing towards a new DEA application to the determin...

Supplier selection has a strategic importance for every company. Hybrid integer data is one of the models in data envelopment analysis (DEA). In many real world applications, data are often stochastic. A successful approach to address uncertainty in data is to replace deterministic data via random variables, leading to chance-constrained DEA. In this paper, a chance-constrained hybrid integer d...

Microfinance has been developed as alternative solution for global poverty alleviation effort in the last 30 years. Microfinance institution (MFI) has unique characteristic wherein they face double bottom line objectives of outreach to the poor and financial sustainability. This study proposes a two-stage analysis to measure Islamic Microfinance institutions (IMFIs) performance by comparing the...

the ahp/dea methodology is an integration of analytical hierarchical process (ahp) and data envelopment analysis. this method uses the capabilities of both ahp and dea. however, it has some problems: it illogically compares two decision-making units in a data envelopment analysis (dea) model, it is not compatible with dea ranking in the case of multiple inputs/multiple outputs, and it leads to ...

Understanding the effects of operational conditions and practices on productive efficiency can provide valuable economic and managerial insights. The conventional approach is to use a twostage method where the efficiency estimates are regressed on contextual variables representing the operational conditions. The main problem of the two-stage approach is that it ignores the correlations between ...

‎the purpose of this paper is to offer the equitable method for ranking decision making units(dmus) based on the dynamic data envelopment analysis (ddea) concept, where quasi-fixed inputs or intermediate products are the source of inter-temporal dependence between consecutive periods. in fact, this paper originally makes the use of an approach extending the ranking of dmus in dea by khodabakhsh...

Data envelopment analysis (DEA) is a method used for measuring the efficiency of decision-making units‎. Unlike the standard models‎, ‎which assume decision-making units to be a black box‎, ‎network data envelopment analysis focuses on the internal structure of these units‎. ‎Some researchers have developed a two-stage method where all the inputs are entirely used in the first stage‎, ‎producin...

Data envelopment analysis technique which is developed based on the mathematical programming, evaluates the relative efficiency of a set of homogeneous decision making units. This paper shows the method of Discriminant Analysis (DA), on Imprecise Data by Data Envelopment 724 F. Hosseinzadeh Lotfi et al Analysis (DEA). DEA-Discriminant Analysis (DEA-DA) is designed to identify the existence or n...