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...

Today, one of the most fundamental issues within the field of industrial and nonindustrial activities is evaluate the costs performance of the units which are associated with industrial and nonindustrial activities. Data envelopment analysis (DEA) is a nonparametric method for evaluating performance. Fuzzy sets theory is a powerful tool for mentioning ambiguous situations. Traditional DEA model...

Data envelopment analysis (DEA) is widely used as a benchmarking tool for improving productive performance of decision making units (DMUs). The benchmarks produced by DEA are obtained as a sideproduct of computing efficiency scores. As a result, the benchmark units may differ from the evaluated DMU in terms of their input–output profiles and the scale size. Moreover, the DEA benchmarks may oper...

Abstract In the last decades, there has been a growing interest in measuring efficiency of hospitals using different methodological approaches, mainly represented by data envelopment analysis (DEA) and stochastic frontier (SFA). this study, we estimate measures performance for sample Panamanian public over an 11‐year period (2005–2015) both traditional methods (DEA SFA) compare them with effici...

The stochastic data envelopment analysis (SDEA) was developed considering the value ofinputs and outputs as random variables. Therefore, statistical distributions play an importantrole in this regard. The skew-normal (SN) distribution is a family of probability densityfunctions that is frequently used in practical situations. In this paper, we assume that the inputand output variables are skew-...

Recent research has shown that combination approaches, such as taking the maximum or mean over different methods of estimating efficiency scores, have practical merits and offer a useful alternative to adopting only one technique. This recent shows minimizes risk underestimation, improves precision estimation. In this paper, we propose implement formal criterion weighting based on maximizing pr...

Data Envelopment Analysis (DEA) is a powerful quantitative tool that provides a means to obtain useful information about efficiency and performance of firms, organizations, and all sorts of functionally similar, relatively autonomous operating units, known as Decision Making Units (DMU). Usually the investigated DMUs are characterized by a vector of multiple inputs and multiple outputs. Unfortu...

We present a nonparametric approach for the equity and e¢ ciency evaluation of (private and public) primary schools in Flanders. First, we use a nonparametric (Data Envelopment Analysis) model that is specially tailored to assess educational e¢ ciency at the pupil level. The model accounts for the fact that minimal prior structure is typically available for the behavior (objectives and feasibil...