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...

Data envelopment analysis (DEA) is one of the widely used methods to measure efficiency scores decision making units (DMUs). Conventional DEA unable consider both uncertainty in data and makers’ (DMs) judgments evaluations. This study, address shortcomings conventional DEA, proposes a new best worst method (BWM)- robust credibility (BWM-RCDEA) model estimate DMUs considering DMs’ preferences un...

This paper explores the link between the presence of unions in the workplace, the adoption of decentralized labor agreements and technical efficiency, using a large sample of Italian manufacturing firms. We apply the Data Envelopment Analysis, and its robust version based on bootstrap theory, to get reliable estimates of technical efficiency at the firm level in a standard first stage. We devot...

This research evaluates the connection between corruption, economic development, and insecurity in several Colombian departments. This chapter explores the dynamics of these variables using two empirical techniques: the Data Envelopment Analysis (DEA) and the Dynamic Panel Data Model (DPDM). DEA is performed to evaluate social performance in terms of corruption, economic development, and insecu...

In the data envelopment analysis (DEA) literature, linear fractional non-cooperative network DEA models for two-stage network structures are often transformed into parametric linear models. The transformed parametric linear models are then solved by computing a series of linear models when the parameter is varied. For example, Wu, Zhu, Ji, Chu and Liang (2016) provide a linear fractional non-co...

having a comprehensive evaluation model with reliable data is useful to improve performance of supply chain. in this paper, according to the nature of supply chain, a model is presented that able to evaluate the performance of the supply chain by a network data envelopment analysis model and by using the financial, intellectual capital (knowledge base), collaboration and responsiveness factors ...

In this paper we propose a data envelopment analysis (DEA) based method for assessing the comparative efficiencies of units operating production processes where input–output levels are inter-temporally dependent. One cause of inter-temporal dependence between input and output levels is capital stock which influences output levels over many production periods. Such units cannot be assessed by tr...