Two-stage data envelopment analysis (2-DEA) is commonly used in productive efficiency analysis to estimate the effects of operational conditions and practices on performance. In this method the DEA efficiency estimates are regressed on contextual variables representing the operational conditions. We reexamine the statistical properties of the 2-DEA estimator, and find that it is statistically c...

A DEA-based stochastic estimation framework is presented to evaluate contextual variables affecting productivity. Conditions are identified under which a two-stage procedure consisting of DEA followed by regression analysis yields consistent estimators of the impact of contextual variables. Conditions are also identified under which DEA in the first stage followed by maximum likelihood estimati...

Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). Recently DEA has been extended to examine the efficiency of two-stage processes, where all the outputs from the first stage are intermediate measures that make up the inputs to the second stage. The resulting two-stage DEA model provides not only an overall efficiency score for the ent...

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still l...

Proposed in this study is a hybrid model for supporting the performance of a department within Amir Kabir University in Iran. The proposal is a two-stage model designed to fully rank the organizational departments where each faculty has multiple inputs and outputs. First, the Data Envelopment Analysis (DEA) separately formulates each pair of units. In the second stage, the pair-wise evaluation ...

As a non-parametric technique, Data Envelopment Analysis (DEA) evaluates the relative efficiency of peer decision making units (DMUs) that have multiple inputs and outputs. In many situations, DMUs have a two-stage structure, where * Corresponding author. E-mail address: [email protected] (A. Ashrafi) 1436 A. Ashrafi, A. B. Jaafar, L. S. Lee and M. R. Abu Bakar the first stage uses inputs to ...

Supplier selection is a multi-Criteria problem. This study proposes a hybrid model for supporting the suppliers’ selection and ranking. This research is a two-stage model designed to fully rank the suppliers where each supplier has multiple Inputs and Outputs. First, the supplier evaluation problem is formulated by Data Envelopment Analysis (DEA), since the regarded decision deals with uncertai...

In this paper we propose a new technique for incorporating environmental effects and statistical noise into a producer performance evaluation based on data envelopment analysis (DEA). The technique involves a three-stage analysis. In the first stage, DEA is applied to outputs and inputs only, to obtain initial measures of producer performance. In the second stage, stochastic frontier analysis (...

This study analyses the technical efficiency of Saudi banks using a two-stage DEA-data envelopment analysis approach. In the first stage, we use a bootstrapped DEA–VRS model to identify the efficiency scores, and in the second stage, we use a bootstrapped truncated regression model to identify the covariates that explain technical efficiency. Policy implications are derived. 2010 Elsevier Ltd. ...

This paper examines the wide-spread practice where data envelopment analysis (DEA) efficiency estimates are regressed on some environmental variables in a secondstage analysis. In the literature, only two statistical models have been proposed in which second-stage regressions are well-defined and meaningful. In the model considered by Simar and Wilson (2007), truncated regression provides consi...