Fuzzy Data Envelopment Analysis Research Articles

A Novel Pythagorean Approach Based Sine-Shaped Fuzzy Data Envelopment Analysis Model: An Assessment of Indian Public Sector Banks

A Novel Pythagorean Approach Based Sine-Shaped Fuzzy Data Envelopment Analysis Model: An Assessment of Indian Public Sector Banks

Employing fuzzy DEA for Green-resilient supplier selection in an electronic industry of household appliances: a case study (Snowa)

Employing fuzzy DEA for Green-resilient supplier selection in an electronic industry of household appliances: a case study (Snowa)

Hierarchical fuzzy DEA model with double frontiers combined with TOPSIS technique: application on mobile money agents locations

Hierarchical fuzzy DEA model with double frontiers combined with TOPSIS technique: application on mobile money agents locations

Measuring the eco-efficiency of municipal solid waste service: A fuzzy DEA model for handling missing data

In the last decades, evaluating the performance of municipal solid waste (MSW) service has attracted the interest of scholars and policymakers worldwide. This study adopts a generalized directional distance function (GDDF) data envelopment analysis (DEA) model to measure the eco-efficiency of 94 Apulian municipalities providing MSW service over 2019–2021. The model uses the α-cut method to handle missing data in a fuzzy DEA environment. During the period covered by the research, on average, the MSW eco-efficiency was between 0.825 and 0.879. The MSW separate collection rate is the only factor significantly affecting the MSW eco-efficiency.

Measuring power consumption efficiency of an electromechanical system within a long-term period by fuzzy DEA and TOPSIS for sustainability

Measuring power consumption efficiency of an electromechanical system within a long-term period by fuzzy DEA and TOPSIS for sustainability

External R&D Supplier Evaluation and Selection: A Three-Stage Integrated Funnel Model

Rapidly changing market demand has seen more and more companies pay attention to external R&D, to make full use of external resources, improve competitiveness, and promote innovation. The suitability of external R&D suppliers directly impacts the success of R&D. However, existing research in this topic has limitations. First, few existing studies have examined the evaluation and selection of external R&D suppliers, quantitatively. Second, there are few studies on the evaluation of effectiveness of R&D suppliers from the perspective of customer demand. Third, the evaluation of prototypes involves heterogeneous data for different technical criteria. As yet, there is no specific suitable model. To bridge abovementioned gaps, this article proposes a comprehensive three-stage integrated funnel model for external R&D supplier evaluation and selection. Specifically, it evaluates the effectiveness of suppliers from the perspective of customer demand and improves the nonradial superefficiency Pythagorean fuzzy DEA methodology. In addition, it proposes a novel fuzzy MA-VIKOR submodel based on heterogeneous data, which can evaluate suppliers from two perspectives: group utility and individual regret, while avoiding the potential problem of equal ranking. Finally, the effectiveness of the proposed model is illustrated by an external R&D supplier selection case of Company J, an international communication equipment company.

Assessing the Relative Impact of Colombian Higher Education Institutions Using Fuzzy Data Envelopment Analysis (Fuzzy-DEA) in State Evaluations

This research aims to design a helpful methodology for estimating universities' relative impact on students as a sustainability factor in higher education. To this end, the research methodology implemented a two-stage approach. The first stage involves the relative efficiency analysis of the study units using Fuzzy Data Envelopment Analysis. The second stage consists of a predictive evaluation of the efficiency of the study units. Consequently, among the most relevant results of the research, it is observed that the methodology identifies the institutions that need to strengthen the academic competencies of the industrial engineering program. Additionally, we developed a benchmark analysis called Efficient Route to help inefficient units achieve efficiency, associating efficiency, and sustainability as pillars of higher education processes.

The ‘Healthcare Access and Quality Index’ revisited: A fuzzy data envelopment analysis approach

Nowadays, health systems comprise a series of resources structured to provide healthcare services to meet our health needs. However, premature deaths still occur. To quantify and understand personal healthcare conditions affecting such amenable mortality, the Healthcare Access and Quality Index (HAQI) was put forward, evaluating 195 countries and territories since 1990. Nevertheless, the literature acknowledges a series of limitations of this framework, such as the drawbacks of using principal component analysis to aggregate individual indicators, the absence of control for financing and environmental conditions, and the presence of a substantial degree of data uncertainty. Accordingly, we propose a methodological alternative to the computation of the HAQI using a novel fuzzy Data Envelopment Analysis model to handle the aforementioned shortcomings. We also propose its extension towards the quantification of efficiency (E-HAQI) – in the sense of value for money – by incorporating financial aspects as modelling inputs. This way, we contribute with innovative modelling approaches that can also deal with the high degree of data uncertainty. Furthermore, in a second-stage analysis, the impact of key exogenous factors on healthcare access and quality is assessed via non-parametric hypothesis testing. Our results show positive and significant correlations of both the revisited HAQI and E-HAQI with the original HAQI 2016 dataset. They also reveal a better use of resources by European and Oceanian countries and territories than by Sub-Saharan African ones. Concerning contextual determinants, socio-demographic development, human development, and the type of health system were found to be statistically significant drivers of healthcare access and quality efficiency.

A novel technique for solving intuitionistic fuzzy DEA model: an application in Indian agriculture sector

Fuzzy DEA is a performance measurement tool that is used to assess the performance of DMUs in highly uncertain environments. In this article, the Intuitionistic fuzzy DEA (IFDEA) model is proposed based on the triangular intuitionistic fuzzy numbers (TIFNs). The weighted Possibility mean for TIFN is used to compare and rank the TIFN. The weighted possibility mean approach is proposed to solve the IFDEA model, and the IFDEA model is converted into its equivalent crisp DEA model to assess the relative efficiencies of the DMUs. One advantage of the proposed approach is that the attitude of the decision-maker is considered while measuring the efficiency of the DMUs. The weight or risk factor delta in [0,1] indicates whether the decision-maker is a risk-taker, neutral, or adverse. The crisp DEA model is a LP problem that is solved by using an existing LP method with different risk factors to determine the efficiency score of the DMUs. The DMUs are ranked based on the overall efficiency score of the DMUs, which is the arithmetic mean of the efficiency scores of the DMUs with different risk factors. Two numerical examples are given here to demonstrate the validity and applicability of the proposed technique and to compare the performance of the DMUs in the proposed approach with the exciting ranking approach and the expected value approach. A case study on the agriculture sector has been conducted in order to evaluate the agricultural performance of Indian states using the IFDEA model. According to the results of the IFDEA model, 15 (53.57%) out of the 28 Indian states were found to be efficient.

Fully fuzzy DEA: a novel additive slacks-based measure model

AbstractThe subject of assessing the relative efficiency of Decision-Making Units (DMUs) has been explored extensively in the literature on Data Envelopment Analysis (DEA). While typical DEA models require exact and conclusive data, the observed values of the inputs and outputs in real-world problems may be inaccurate or ambiguous. This paper presents a novel fully fuzzy DEA (FFDEA) model based on the additive slacks-based measure (ASBM). FFDEA models imply that all inputs, outputs, and variables, are fuzzy. It is demonstrated how fuzzy ranking and fuzzy arithmetic approaches can be used to handle the trapezoidal fuzzy number assumptions. To solve the fuzzy ASBM model under variable returns-to-scale assumptions, we proposed two different methods, first method use of lexicographic method for solving multi-objective linear programming (MOLP) approach, which provides an efficiency measure and a fuzzy goal operating point for each DMU under assessment. In alternative method, we convert the fuzzy linear fractional programming problems to an equivalent MOLP problem. A case study is provided to illustrate the applicability of the proposed approach for selecting sustainable suppliers, we compare the results with other fuzzy DEA approaches, while shedding light on future research venues.

Heterogeneous multi-attribute group decision making based on a fuzzy data envelopment analysis cross-efficiency model

Heterogeneous multi-attribute group decision making (HMAGDM) is a kind of complex decision making problem, which exists widely in reality. The purpose of this paper is to extend data envelopment analysis (DEA) for solving the HMAGDM problems whose attribute values include real numbers, intervals, intuitionistic fuzzy numbers, triangular fuzzy numbers, trapezoidal fuzzy numbers and linguistic variables. For this purpose, a method to HMAGDM based on a fuzzy DEA cross-efficiency model is proposed. In the proposed method, heterogeneous information is uniformly transformed into intervals, which are expressed as variables with unknown parameters. On this basis, a fuzzy DEA cross-efficiency model is established to calculate the individual cross-efficiency intervals of decision making units (DMUs). The model takes into consideration all possible attribute values of each DMU in the intervals, and obtains stable evaluation results through peer evaluation mode and iteration. Then, a maximizing group consensus model is established to calculate the weights of decision makers (DMs). Given the weights of DMs, the individual cross-efficiency intervals can be aggregated into the collective cross-efficiency interval, and DMU can be ranked based on this. An example of supplier selection is presented to illustrate the practicability and effectiveness of the proposed method.

Performance appraisement of supplier selection in construction company with fuzzy AHP, Fuzzy TOPSIS, and DEA: A case study based approach

In the present marketing environment, choosing the right suppliers is very difficult for any construction company. Current supplier selection models in the construction industry often suffer from limitations such as incomplete criteria coverage, inadequate handling of uncertainties, and oversimplification of decision-making, leading to sub-optimal supplier choices and project risks. This paper aims in selecting the best suppliers among the different M-Sand environment suppliers. In this study 13 qualitative criterions are selected by the expert team. For handling the attributes, uncertainties, vagueness associated with supplier selection problems the Fuzzy Delphi, Fuzzy Analytical hierarchal Process (AHP) and Fuzzy Technique for order preference by similarity to ideal solution (TOPSIS) methods were chosen. In the first phase of this study, Fuzzy Delphi Method is employed to select the 5 significant criterions. These criterions can be used to help the construction company in the direction to choose the right suppliers at the end. During the second phase, one of the significant Multi-criteria Decision Making Method called AHP is employed with extended support of fuzzy logic to evaluate the weightage of each criterion. Further ranking of various alternative suppliers are done by Fuzzy TOPSIS model. The ranking results indicate that A2 is the best supplier followed by A1 and A2. The third phase of this study deals with analyzing both the qualitative and quantitative criteria, hence Data Envelopment Analysis (DEA) is adopted to correlate the criteria. This is done to select efficient suppliers. The develop model is demonstrated in the construction industry.

Does green innovation promote environmental efficiency from a global perspective? A hybrid approach (fuzzy DEA-SEM-ANN).

Green innovation is crucial for reducing carbon dioxide (CO2) emissions and promoting environmental efficiency worldwide. However, there is a lack of scholarly research investigating the relationship between environmentally friendly innovations and improved environmental performance. To fill this knowledge gap, a comprehensive study was conducted using data from 64 countries spanning 2010 to 2018. The study employed a hybrid approach, combining fuzzy DEA, structural equation modeling (SEM), and artificial neural networks (ANN) to analyze the nexus between green innovation and environmental efficiency. The SEM analysis revealed that green innovation, green trade, green employment, and green investment significantly impact environmental efficiency. The ANN model achieves a perfect prediction rate for environmental efficiency and green growth, emphasizing the importance of incorporating various sources of green innovation to achieve long-term environmental goals. The study's findings have significant implications for policymakers and governments, highlighting the value of environmentally friendly technologies and the need to allocate resources toward their development. Regional collaboration and integrating green innovation throughout the development process are essential for achieving environmental efficiency. By embracing green innovation, nations can capitalize on its potential benefits while mitigating pollution and promoting sustainable development. Overall, this research serves as a cornerstone for decision-makers, providing insights into the importance of green innovation and guiding efforts to foster environmentally conscious technologies globally.

Fuzzy cost, revenue efficiency assessment and target setting in fuzzy DEA: a fuzzy directional distance function approach

PurposeThis study aims to present the cost and revenue efficiency evaluation models in data envelopment analysis in the presence of fuzzy inputs, outputs and their prices that the prices are also fuzzy. This study applies the proposed approach in the energy sector of the oil industry.Design/methodology/approachThis study proposes a value-based technology according to fuzzy input-cost and revenue-output data, and based on this technology, the authors propose an approach to calculate fuzzy cost and revenue efficiency based on a directional distance function approach. These papers incorporated a decision-maker’s (DM) a priori knowledge into the fuzzy cost (revenue) efficiency analysis.FindingsThis study shows that the proposed approach obtains the components of fuzzy numbers corresponding to fuzzy cost efficiency scores in the interval [0, 1] corresponding to each of the decision-making units (DMUs). The models presented in this paper satisfies the most important properties: translation invariance, translation invariance, handle with negative data. The proposed approach obtains the fuzzy efficient targets corresponding to each DMU.Originality/valueIn the proposed approach, by selecting the appropriate direction vector in the model, we can incorporate preference information of the DM in the process of evaluating fuzzy cost or revenue efficiency and this shows the efficiency of the method and the advantages of the proposed model in a fully fuzzy environment.

Classification and forecasting of sustainable-resilience suppliers via developing a novel fuzzy MIP model and DEA in the presence of zero data

Classification and forecasting of sustainable-resilience suppliers via developing a novel fuzzy MIP model and DEA in the presence of zero data

Measuring returns to scale based on the triangular fuzzy DEA approach with different views of experts: Case study of Iranian insurance companies

Measuring returns to scale based on the triangular fuzzy DEA approach with different views of experts: Case study of Iranian insurance companies

Three-way decision based on ITARA and public weights DEA under picture fuzzy environment and its application in new energy vehicles selection

Petroleum is the main power of automobiles, yet the environmental pollution it brings has caused globally. The promotion of new energy vehicles (NEVs) is effective. Even though the governments have introduced various supports for the popularization of NEVs, many enterprises and individuals continue to drive gas vehicles as they are poorly informed about them and cannot choose the right products. This paper proposes a categorization and ranking model of NEVs over three-way decisions (TWD) to tackle the problem. Picture fuzzy sets serve as a valid tool to describe uncertainty and fuzziness information. At first, the attribute weights are ascertained with the indifference threshold-based attribute ratio analysis (ITARA) method improved by the picture fuzzy distance. Then, the public weight picture fuzzy data envelopment analysis (DEA) which is enhanced by the picture fuzzy aggregation operator is employed for the conditional probability of decision units. Third, updated picture fuzzy TWD is utilized for the categorization and ranking. Fourth, the enterprise NEVs selection case is tested for the model. Later, comparative analysis with the classical methods illustrates that the proposed method yields accurate and reliable decisions. Finally, the robustness of the model is demonstrated by sensitivity analysis.

On the environmental performance analysis: A combined fuzzy data envelopment analysis and artificial intelligence algorithms

On the environmental performance analysis: A combined fuzzy data envelopment analysis and artificial intelligence algorithms

Supplier selection using Fuzzy DEA credibility constrained and relative closeness index: A case of Indonesian manufacturing industry

Supplier selection using Fuzzy DEA credibility constrained and relative closeness index: A case of Indonesian manufacturing industry

A new fuzzy DEA network based on possibility and necessity measures for agile supply chain performance evaluation: A case study

With respect to the necessity (Nec) measure, suggesting by Dubois and Prade, there is a dearth of any procedure or formula to deal with equality chance constraints. Therefore, this study attempted to introduce (Nec) and possibility (Pos) equality constraints in a real-case network non-oriented slack based model problem via agile supply chain (ASC) theory. The efficiency of different levels of agility of a dairy supply chain (SC), using a new fuzzy network Date Envelopment Analysis slack based model (FNDEA-SBM) on the basis of (Pos)/(Nec) measures, has been measured in this paper. The measurement took place in a multi-stage process. Since the agility features were rather qualitative in nature, the measures were likely to be delineated subjectively using linguistic expressions and fuzzy data. The application of (Pos)/(Nec) measures and different confidence levels made decision makers capable of getting information of all efficiency and sub efficiency scores through optimistic-pessimistic lenses and taking appropriate decisions on the basis of different optimistic-pessimistic points of view and confidence levels. The validity of the suggested approach was demonstrated through a real-life case study related to Iranian top twenty dairy firms. The results indicated the success of the suggested approach and computations were straightforward.