Data envelopment analysis (DEA) is known as a useful tool that produces many efficient decision-making units (DMUs). Traditional DEA provides relative efficient scores and reference sets, but does not influence and rank the efficient DMUs. This paper suggests a method that pro‐ vides influence and ranking information by using Pag‐ eRank as a centrality of Social Network analysis (SNA) based on ...

there are several methods to ranking dmus in data envelopment analysis (dea) and candidates in voting system. this paper proposes a new two phases method based on dea’s concepts. the first phase presents an aspiration rank for each candidate and second phase propose final ranking.

This paper established a comprehensive model of Delphi-AHP-DEA-FCE to evaluate competitiveness of sports tourism destinations. Research shows that, this model effectively constructed an indicator system for the competitiveness of sports tourism destination, and weights for all indicators were obtained by analysis. Second, the comprehensive model translated fuzzy evaluation into numerical values...

This paper aims to provide a new methodological and empirical contribution to the rising literature on the relative performance and benchmarking of large cities in a competitive world. On the basis of a recent detailed database on many achievement criteria of 35 major cities in the world, it seeks to arrive at a relative performance ranking of these cities by using Data Envelopment Analysis (DE...

This paper uses integrated Data Envelopment Analysis (DEA) models to rank all extreme and non-extreme efficient Decision Making Units (DMUs) and then applies integrated DEA ranking method as a criterion to modify Genetic Algorithm (GA) for finding Pareto optimal solutions of a Multi Objective Programming (MOP) problem. The researchers have used ranking method as a shortcut way to modify GA to d...

Data envelopment analysis (DEA) with considering the best condition for each decision making unit (DMU) assesses the relative efficiency for it and divides a homogenous group of DMUs in to two categories: efficient and inefficient, but traditional DEA models can not rank efficient DMUs. Although some models were introduced for ranking efficient DMUs, Franklin Lio & Hsuan peng (2008), proposed a...

in many real applications, the data of production processes can't be precisely measured.we develop some fuzzy versions of the classical dea models (in particular, the ccrmodel) by using some ranking methods based on the comparison of cuts. our approachescan be seen as an extension of the dea methodology. the provides users and practitionerswith models which represent some real life processes mo...

in many real applications, the data of production processes can't be precisely measured.we develop some fuzzy versions of the classical dea models (in particular, the ccrmodel) by using some ranking methods based on the comparison of cuts. our approachescan be seen as an extension of the dea methodology. the provides users and practitionerswith models which represent some real life process...

Ranked voting data arise when voters select and rank more than one candidate with an order of preference. Cook et al.[1] introduced data envelopment analysis (DEA) to analyze ranked voting data. Obata et al.[2] proposed a new method that did not use information obtained from inefficient candidates to discriminate efficient candidates. Liu et al.[3] ranked efficient DMUs on the DEA frontier with...

This article elaborates on the applicability of basic and extended data envelopment analysis (DEA) models for various information system (IS) decision use-cases including illustrative examples from an enterprise resource planning (ERP) software investment appraisal. The usage of data envelopment analysis models and their extensions for IS decisions remains limited. This omission seems critical ...