a r t i c l e i n f o In the fast changing financial circumstances of nowadays, in avoiding the crisis of closing down, financial institutions are concerned about the efficiency and risk strictly in the meantime. Therefore, efficiency and risk management are goals for a financial institution administrator. Data Envelopment Analysis (DEA) is a non-parameter approach to evaluate the performance o...

Data envelopment analysis (DEA) has been widely applied in evaluating multicriteria decision making problems, which have multi-input and multi-output. However, the traditional DEA method does neither take the decision maker’s subjective preferences to the individual criteria into consideration nor rank the selected options or decision making units (DMUs). On the other hand, Satty’s analytical h...

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...

The study combines fuzzy logic calculation method and bootstrap-DEA to explore the efficiency of National Quality Online Courses (NQOOCs) during new coronavirus epidemic. We choose Project 985 universities in China as our sample considering their academic influence. results show that value NQOOCs calculated by differs from measured traditional DEA. difference universities` ranking is more prono...

Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. ‎‎Standard DEA models are ‎‎quite limited models‎, ‎in the sense that they do not consider a DMU ‎‎at different times‎. ‎To resolve this problem‎, ‎DEA models with dynamic ‎‎structures have been proposed‎.‎In a recent pape...

Abstract: Classical cost efficiency (CE) measurement models require exact and accurate knowledge of the input and output values for each decision making unit (DMU). However, the observed values of the input and output data in real-world problems are often imprecise or vague. In recent years, fuzzy data envelopment analysis (DEA) has been successfully used to deal with imprecise or vague data in...

Seaport network efficiency is very crucial for global maritime economic trades and growth. In this work, data of three years (2018–2020) with input variables (time in port, age vessels, size cargo carrying capacity vessels) output (Liner Shipping Connectivity Index (LSCI) Gross Domestic Product (GDP)) are collected. Few screening tests performed to ensure the fit further analyses. Since none ex...

DEA (Data Envelopment Analysis) is a technique for evaluating the relative effectiveness of decision-making units (DMU) with multiple inputs and outputs data based on non-parametric modeling using mathematical programming (including linear programming, multi-parameter programming, stochastic programming, etc.). The classical DEA methods are developed to handle the information in the form of cri...

Comparing the performance of a set of activities or organizations under uncertainty environment has been performed by means of Fuzzy Data Envelopment Analysis (FDEA) since the traditional DEA models require accurate and precise performance data. As regards a method for dealing with uncertainty environment, many researchers have introduced DEA models in fuzzy environment. Some of these models ar...

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...