Data envelopment analysis (DEA) has been a wildly used powerful method to measure efficiencies of decision making units (DMUs). However, DEA efficiency scores are influenced by uncontrollable factors for respective DMUs. Previous studies attempted separating such factors from DEA scores. Fried et al. [4] proposed a multi-stage data adjustment approach using DEA and a regression model, and sever...

A measure of company efficiency is also commonly used in banking. The DEA (Data Envelopment Analysis) method, which compares the input and output, a mathematical program optimization method. This study investigates level Islamic banks Indonesia from 2018 to 2021. It examines role capital liquidity their impact on banking efficiency. quantitative methods were nonparametric (DEA) parametric using...

This study consists of three types of vendor selection models in supply chains and presents a decision making scheme for choosing appropriate method for supplier selection under certainty, uncertainty and probabilistic conditions. These models are, Data Envelopment Analysis (DEA), Fuzzy Data Envelopment Analysis (FDEA), and Chance Constraint Data Envelopment Analysis (CCDEA). In FDEA model we u...

By employing the non-stochastic data envelopment analysis (DEA) method, the present paper provides empirical evidence on the efficiency of the Malaysian banking sector around the Asian financial crisis. The empirical findings suggest that the foreign banks (FB) have exhibited higher technical efficiency (TE) compared to their domestic bank counterparts. However, the results suggest that the FB ...

‎Data envelopment analysis (DEA) is an objective method for priority determination of decision making units (DMUs) with the same multiple inputs and outputs. DEA is an efficiency estimation technique, but it can be used for solving many problems of management such as rankig of DMUs. Many researchers have found similarity between DEA and MCDM techniques. One of the earliest techniques in MCDM is...

It is well known that Data Envelopment Analysis (DEA) is a relative efficiency measurement tool, which uses optimization techniques to automatically calculate the weights assigned to the crisp deterministic multiple inputs and outputs of a set of the Decision Making Units (DMUs) being assessed. However, crisp deterministic data requirement delimits an application to the real world problems wher...

data envelopment analysis (dea) is a non-parametric technique for evaluation of relative efficiency of decision making units described by multiple inputs and outputs. it is based on solving linear programming problems. since 1978 when basic dea model was introduced many its modifications were formulated. among them are two or multi-stage models with serial or parallel structure often called net...

data envelopment analysis (dea) is a method to evaluate the relative efficiency of decision making units (dmus). in this method, the issue has always been to determine a set of weights for each dmu which often caused many problems. since the dea models also have the multi-objective linear programming (molp) problems nature, a rational relationship can be established between molp and dea problem...

We propose alternative regression models to assess the effects of covariates in output oriented DEA scores. We use probability choice models combined with specifications related to the gamma and to the truncated normal families of distributions. These specifications imply different two stage regression models and alternative quasi maximum likelihood estimators. We apply these methods to assess ...