Vlse Kriterijumska Optimizacija Kompromisno Resenje Research Articles

Spherical fuzzy sets based integrated DEMATEL, ANP, VIKOR approach and its application for renewable energy selection in Turkey

Renewable energy continues occupying the global agenda for the low-carbon transition. Identifying suitable sources for renewable energy involves different criteria and alternatives, which can be defined as a Multi-Criteria Decision-Making (MCDM) problem. MCDM methods can be enriched with Group Decision Making (GDM) to merge individual judgments into group opinions, as well as with fuzzy sets to better simulate human opinions. To handle uncertainties of DMs’ preferences, a recently developed fuzzy set extension, the Spherical Fuzzy Sets (SFSs), is combined in this study with different MCDM tools to establish a decision support tool for the energy source selection problem. This article proposes a novel MCDM approach that integrates SF-DEMATEL (Spherical Fuzzy Decision-Making Trial and Evaluation Laboratory), SF-ANP (Spherical Fuzzy Analytic Network Process), and SF-VIKOR (Spherical Fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje) algorithms in a GDM environment and presents its application in a case study for selecting renewable energy sources in Turkey. Comparing wind, geothermal, solar, hydropower, and biogas, the proposed method highlighted both wind and solar energy as a compromise solution as the most suitable options for Turkey. It has been found that compared to similar fuzzy sets, SFS can better reflect the hesitation degree to address the lack of knowledge and errors in the membership function definitions. The robustness and plausibility of these findings are demonstrated with sensitivity and comparative analyses, suggesting this MCDM method can also be applied to similar problems in other settings.

A new exponential knowledge and similarity measure with application in multi-criteria decision-making

The knowledge measure of fuzzy sets (FSs) has drawn greater attention and is still unresolved since it is the complementary idea to fuzzy entropy. The amount of knowledge is important in evaluating fuzzy information. This study proposes an exponential entropy-based knowledge measure for fuzzy sets to quantify the knowledge amount conveyed by fuzzy sets. Intuitive analysis of the characteristics of the knowledge amount in fuzzy sets is introduced, and its value and validity are demonstrated with numerical examples. In addition, a new measures is proposed from the exponential knowledge measure (i.e., exponential similarity measure). These measure are examined for validity, and their characteristics and put forward. Last, a modified Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) strategy based on the suggested similarity measure is suggested to handle a multi-criteria decision-making problem in a fuzzy environment. The effectiveness of the proposed approach is shown By utilizing a numerical example. A comparative analysis is also provided to evaluate the viability of the proposed approach.

Attaining Sustainable Development Goals through embedding circular economy principles: Evidence from food processing small‐ and medium‐sized enterprises in India

AbstractVarious industries are gradually sifting away from the linear economy and toward the circular economy (CE), but its advancement is crawling far behind the environmental contamination by the food processing industry in developing countries. Hardly any research analyzes the CE performance of food processing small‐ and medium‐sized enterprises (FPSMEs) in an emerging economy context. Hence, developing a CE performance evaluation framework is imperative to facilitate this transition. This research proposes a comprehensive framework for evaluating CE performance based on three real‐world cases of Indian FPSMEs. Initially, 15 essential criteria are shortlisted from the literature and refined by the experts. Afterward, data are collected through questionnaires administered to experts and structured interviews. Next, this research employs a multi‐criteria decision‐making (MCDM)–based approach, in which the Criteria Importance Through Inter‐criteria Correlation (CRITIC) method is used to compute the objective weights of criteria and the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method is used to determine the performances of FPSMEs and rank them accordingly. The results reveal that “investment in Corporate Social Responsibility (CSR),” “use of renewable energy,” “increase in scrap recycling rate,” “total emission,” and “total water consumption” are the top five criteria for CE performance. Investment in CSR emerges as the most influential criterion for strategic corporate transformation, which blends the notions of CE and CSR as a feasible solution for designing circular business processes.

Prioritizing the attributes of sustainable banking performance

PurposeGrowing concern over sustainability adoption has presented an array of challenges to businesses. While vital to an economy's success, banking is not immune to societal, environmental and economic consequences of business practices. The study has examined the sustainable performance of banking institutions on the suggested multidimensional framework comprising economic, environmental, social, governance and financial dimensions and 52 sustainability indicators. The study benchmarks the significant performance indicators of leading banks indispensable to sustainable banking performance. The findings attempt to address research questions concerning the extent of sustainable banking performance, ranking the sustainability dimensions and indicators and standardizing sustainability adoption metrics.Design/methodology/approachTo determine the responsiveness of the banking industry to sustainability dimensions, content analysis was conducted using NVivo software for the year 2021–2022. Furthermore, a hybrid multicriteria decision-making (MCDM) approach is used by integrating entropy, the technique for order preference by similarity to ideal solution (TOPSIS) and VlseKriterijumska Optimizacija KOmpromisno Resenje (VIKOR) to provide relative weights to performance indicators and prioritize banks based on their sustainable performance. Sensitivity analysis is used to ensure the robustness of results.FindingsIn the context of the Indian banking industry, the pattern of sustainability reporting is inconsistent and concentrated on addressing environmental and social concerns. The results of the entropy methodology prioritized “Environmental” sustainability over other selected dimensions while “Financial” dimension has been assigned the least priority in the ranking order. The significant sustainable performance indicators delineated in this study should be used as standards to ensure the accountability and credibility of the sustainable banking industry. Additionally, the research findings will provide valuable inputs to policymakers and regulators to assure better contribution of the banking sector in meeting sustainability goals.Originality/valueConsidering the paucity of studies on sustainable banking performance, this study makes two significant contributions to the literature. First, the suggested multidimensional disclosure model integrating financial and nonfinancial indicators would facilitate banking institutions in addressing the five aspects of sustainability. As one of the first studies in the context of the Indian banking industry, the findings would pave the way for better diffusion of sustainability practices. Second, the inclusion of MCDM techniques prioritizes the significance of sustainability indicators and benchmarks the performance of leading banks to achieve better profits and more substantial growth.

Evaluation and adoption of artificial intelligence in the retail industry

PurposeThe introduction of artificial intelligence (AI) technology has had a substantial influence on the retail industry. However, AI adoption entails considerable responsibilities and risks for senior managers. In this study, the authors developed an evaluation and selection mechanism for successful AI technology adoption in the retail industry. The multifaceted measurement and identification of critical factors (CFs) can enable retailers to adopt AI technology effectively and maintain a sustainable competitive advantage.Design/methodology/approachThe evaluation and adoption of organisational AI technology involve multifaceted decision-making for management. Therefore, the authors used the analytic network process to develop an AI evaluation framework for calculating the weight and importance of each consideration. An expert questionnaire survey was distributed to senior retail managers and 17 valid responses were obtained. Finally, the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method was used to identify CFs for AI adoption.FindingsThe results revealed five CFs for AI adoption in the retail industry. The findings indicated that after AI adoption, top retail management is most concerned with factors pertaining to business performance and minor concerned about the internal system's functional efficiency. Retailers pay more attention to technology and organisation context, which are matters under the retailers' control, than to external uncontrollable environmental factors.Originality/valueThe authors developed an evaluation framework and identified CFs for AI technology adoption in the retail industry. In terms of practical application, the results of this study can help AI service providers understand the CFs of retailers when adopting AI. Moreover, retailers can use the proposed multifaceted evaluation framework to guide their adoption of AI technology.

The Progress of the Development of a Climate-smart Agriculture in Europe: Is there Cohesion in the European Union?

The development of climate-smart agriculture (CSA) is crucial in ensuring the creation of a low-carbon society and mitigation of climate change. These tasks require concerted actions from multiple stakeholders since the very concept of CSA is rather complex and requires multi-dimensional consideration. This study defines and applies various indicators to evaluate the development of CSA in the European Union (EU). To do this, three different multi-criteria decision-making methods, namely Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR; multi-criteria optimization and compromise solution), were employed for the construction of a composite indicator. A combination of both objective (entropy) and subjective (Analytic Hierarchy Process) weighting techniques was utilized to derive the weights of the indicators. The leaders in the EU in terms of CSA are Austria, Denmark and the Netherlands, whereas the countries with the lowest levels of CSA development are Cyprus, Greece and Portugal. This study also revealed divergence in the development of these practices in the EU-24 for the period 2004-2019. Thus, a more inclusive approach is needed to ensure the spread of climate-smart ideas in European agriculture sectors.

A Novel Safety Risk Assessment Based on Fuzzy Set Theory and Decision Methods in High-Rise Buildings

The high-rise construction industry has particular features, such as prolonged construction periods and constant change in the workplace. These features may have turned it into the most dangerous industry, given its significant mortality rate. This research aims to identify effective criteria for high-rise buildings’ safety issues and rank the most critical risks to level up the safety of these projects. This research is divided into two phases: In Phase I, the effective criteria in the literature on the occurrence of accidents are divided into three main classes, and their weights are determined using the best–worst method. In Phase II, the existing risks are ranked using the fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje (FUZZY VIKOR) method. The results indicate that safety training and monitoring, which account for approximately 35% of the total weight, are the most influential criteria for risk occurrence. The risk of falling from heights has been ranked first as the most critical safety risk according to the eight criteria, including safety training and monitoring. The total weight of criteria in which falling from height attains the first rank equals 0.688. Damages caused by working with manual tools and equipment have the highest priority in four criteria, and the total weight of 0.1591 attains the second rank. The results of this research comply with the current situation of the construction industry and pave the way for future research on high-rise construction projects.

New MCDM Algorithms with Linear Diophantine Fuzzy Soft TOPSIS, VIKOR and Aggregation Operators

In this paper, we focus on several ideas associated with linear Diophantine fuzzy soft sets (LDFSSs) along with its algebraic structure. We provide operations on LDFSSs and their specific features, elaborating them with real-world examples and statistical depictions to construct an inflow of linguistic variables based on linear Diophantine fuzzy soft (LDFSS) information. We offer a study of LDFSSs to the multi-criteria decision-making (MCDM) process of university determination, together with new algorithms and flowcharts. We construct LDFSS-TOPSIS, LDFSS-VIKOR and the LDFSS-AO techniques as robust extensions of TOPSIS (a technique for order preferences through the ideal solution), VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) and AO (aggregation operator). We use the LDFSS-TOPSIS, LDFSS-VIKOR and LDFSS-AO techniques to solve a real-world agricultural problem. Moreover, we present a small-sized robotic agri-farming to support the proposed technique. A comparison analysis is also performed to examine the symmetry of optimal decision and to analyze the efficiency of the suggested algorithms.

Critical Factors Considered by Companies to Introduce Business Intelligence Systems

The advent of intelligent technology has spurred most large companies to introduce business intelligence systems (BIS), but those with low information maturity still have a wait-and-see attitude towards BIS. In order to accelerate the introduction of BIS, this study found and analyzed the critical factors (CFs) considered by companies when introducing BIS. First, the literature on factors considered by companies to introduce BIS was reviewed. The three stages before, during, and after introduction in marketing that organizations undergo during the procurement process were developed into a three-layer hierarchy factor table. An expert questionnaire with pairwise factors was then designed and sent to senior executives in companies that had introduced BIS, and the weights of all factors were calculated by the fuzzy analytic hierarchy process (FAHP) based on the collected questionnaire data. After this, four critical factors—system function integrity, approaching corporate strategy, licensing fee, and information technology maturity—were determined objectively by using the conditions for the acceptable advantage of Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) and further explored in order to help companies input fewer resources, introduce BIS efficiently, and thus increase their decision-making power.

VIKOR method for MCDM based on bipolar fuzzy soft β-covering based bipolar fuzzy rough set model and its application to site selection of solar power plant

Bipolarity indicates the positive and negative aspects of a particular problem. The concept behind the bipolarity is that a huge range of human decision analysis is involved in bipolar subjective thoughts. The VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) which means multicriteria optimization and compromise solution, has already become a quite popular multi-criteria decision making tool for its computational simplicity and solution accuracy. In this article, we propose a hybrid model for multi-criteria decision-making (MCDM) based on bipolar fuzzy soft β-covering based bipolar fuzzy rough sets using VIKOR technique. It consists of a suitable redesign of the VIKOR approach so that it can use information with bipolar configurations. This method focuses on selecting and ranking from a set of feasible alternatives, and determines compromise solution for a problem with conflicting criteria to help the decision maker in reaching a final course of action. It determines the compromise ranking list based on the particular measure of closeness to the ideal solution. For illustration, the proposed technique is applied to a decision-making problems, namely, the selection of site for renewable energy project (solar power plant). A comparison of this method with another aggregation operator method and with the existing decision making algorithm Fuzzy VIKOR is also presented.

Optimal selection of an AA8011 reinforced nano Si3N4 composite using multi criteria decision-making method

Materials selection is a multiple criteria decision-making (MCDM) problem. There are numerous decision-making approaches that can be applied to material selection, and they can provide significant differences in material selection results. However, it is unclear which decision-making method is best. In this paper, an objective weighting criteria method (standard deviation) combined with various MCDM methods is presented. These methods determine the optimal alternative from all the accessible options and provide a ranking of the available options. The present paper examines the application of a few decision-making paradigms for selecting the most suitable alternatives. Five different composites reinforced with varying percentages of silicon nitride (Si3N4) are analysed with four different multi-criteria decision-making models, viz. Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR), COmplex PRoportional ASsessment (COPRAS), and Preference Ranking Organization Method for Enrichment Evaluations-II (PROMETHEE II) methods are used to predict the best alternative for automobile applications. The different composite materials were compared in order to present a list of all materials, ranging from the best to the worst. It has been observed that in all cases, the best classified alternative material is M4 (AA8011-15 %Si3N4).

Ranking Energy Storage Technologies with VIKOR

Various energy storage technologies are currently available to address the problem of renewable energy intermittency. Due to wide selection of energy storage technologies with contrasting characteristics, strengths, and weaknesses, selection of the most appropriate technology for a specific type of application is a daunting task. In this study, the multiple attribute decision-making method VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) is used as a systematic approach for ranking available energy storage technologies. The competing technologies are evaluated based on energy density, power rating, discharge time, cycle efficiency, lifetime, and specific cost. Data for these various criteria are based on reports in the literature and are processed using the VIKOR algorithm. This study demonstrates that the lithium-ion battery is the best technology for energy storage of renewable energy with assessment index, Q = 0.16; it is followed closely by the sodium-sulfur battery, with Q = 0.17. The result of this study shows that VIKOR can be used to select the best energy storage technology for power generation and guide decision-makers on the most suitable technology for enabling the transition to a zero-carbon energy systems.

Hybrid Multi-Criteria Decision Making approach for the evaluation of sustainable photovoltaic farms locations

As a result of the increased demand for energy combined with the limitations of traditional energy sources, it is necessary to turn to renewable energy sources such as solar energy, which is one of the most promising technologies to assist the transition towards sustainable development. With the increasing interest in renewable energies in general and solar energy in particular, attempts have been made to ensure that solar energy technologies provide an amount of energy equal to or close to the amount of energy currently consumed. Solar photovoltaic farm applications have become so widespread that they are now relied upon to produce massive amounts of energy for use in factories and homes. In this regard, identifying and prioritizing convenient areas for the construction of expensive solar photovoltaic farms is an important issue. Additionally, determining the suitable geographical locations for photovoltaic farms is not only related to the amount of solar radiation received, but many dimensions must be taken into accounts such as technical, economic, environmental, socio-political dimensions, risks, and their sub-indicators. To overcome the problem of prioritizing and selecting the best location for solar photovoltaic farms to achieve sustainability factors resulting from the presence of many different indicators, this paper applies a hybrid multi-criteria decision-making approach under a neutrosophic environment. Initially, the Delphi method is employed to capture preference and to determine the dimensions and their indicators in addition to provide preference among sub-indicators and available alternatives. The proportional importance of the designated dimensions and their sub-indicators was evaluated by the Decision-Making Trial and Evaluation Laboratory. Then, Vlse Kriterijumska Optimizacija Kompromisno Resenje is adopted to rank seven solar photovoltaic farm locations in Egypt. The Benban solar photovoltaic farm is shown to be the most sustainable alternative among the solar photovoltaic farm locations followed by Darb Al Arbaeen solar photovoltaic farm and so has priority for increased installation investments in solar energy production. To validate the proposed approach, results comparisons were implemented to indicate the advantages of the hybrid multi-criteria decision-making methods. Sensitivity analysis reveals that changing criteria weightings does not affect the ranking order.

Critical factors affecting the introduction of mobile payment tools by microretailers

Mobile payment (MP) is a key tool for establishing a cashless society. To comprehensively examine the critical factors (CFs) that influence the introduction of MP tools by microretailers (MRs) in Taiwan, this study employed the technology–organization–environment model as a theoretical basis. Two multicriteria decision-making tools (i.e., the analytic network process and Vlse Kriterijumska Optimizacija Kompromisno Resenje concept of acceptable advantage) were combined to objectively identify the CFs influencing MRs’ introduction of MP tools. The results indicate that technology is more essential than organization and environment, and the eight identified CFs are security/trust, compatibility, usability, stability, complexity, organizational scale, government support, and information maturity. These CFs and the hybrid method form the basis for the findings and academic contributions of this study. The results serve as incisive and practical guidelines that can help MRs to introduce MP tools, encourage MP use by consumers, and promote the establishment of a cashless society.

A New Extended VIKOR Approach Using q-Rung Orthopair Fuzzy Sets for Sustainable Enterprise Risk Management Assessment in Manufacturing Small and Medium-Sized Enterprises

In recent years, the important role of sustainable development is highlighted in the literature; therefore, a company to make a sustainable business success needs to be well focused on social, environmental, economic, and technological characteristics of the business to address risks and capture value properly. The process of Sustainability Enterprise Risk Management (SERM) is typically implemented to integrate all social, economic, environmental, and technological aspects in a systematic way to properly manage emerging risks and other non-quantifiable risks for company survival. Therefore, in this study, an attempt has been carried out to develop a comprehensive framework to implement the ERM framework under the sustainability platform by considering 29 sub-criteria based on four main aspects, including social, environmental, technological, and economic. In addition, a new fuzzy decision-making approach using the VIKOR (VlseKriterijumska Optimizacija Kompromisno Resenje) approach under q-rung orthopair fuzzy set (q-ROFSs) called VIKOR-q-ROFSs approach is introduced to identify, rank, and evaluate the main criteria of SERM in the universal appeal for all industries such as Chinese manufacturing Small And Mid-Size Enterprises (SMEs) based on expert opinions and literature review. To determine the weights of SERM criteria by the decision experts, this study has introduced q-ROFNs. Moreover, to facilitate the q-ROFNs, a novel q-rung orthopair fuzzy weighted averaging operator (q-ROFWAO) is proposed. Furthermore, VIKOR is applied to rank and evaluate the manufacturing SMEs as the alternatives for this study. The results of this paper showed that technological suitability was the important risk factor followed by technological advance, occupational safety and health, product and services responsibility, (benefit) anti-corruption labor practices, and technological practicability. In addition, the findings of the analysis show that the proposed method was efficient and effective in evaluating risk assessment of SERM in the SMEs.

Ranking of occupational health and safety risks by a multi-criteria perspective: Inclusion of human factors and application of VIKOR

Nowadays, the Occupational Health and Safety (OHS) is more and more recognized as a crucial process to be properly managed and continuously improved by every organization. Primarily addressed to prevent workers’ injuries and diseases, it positively impacts on productivity, competitiveness and reputation as well as it contributes to cost savings in general. OHS management is grounded upon the risk assessment results, on the basis of which defining corrective measures to be taken to reduce risks to acceptable values. In this regard, the paper proposes a Multi-Criteria Decision Making (MCDM) based methodology addressed to the occupational risks prioritization. In order to overcome the shortcomings of the traditional risk matrix, the new methodology considers three evaluation criteria differently weighted by the Analytic Hierarchy Process (AHP) method. Among criteria, one specifically refers to the contribution of human factors to the occurrence of accidents, and a combination of Human Error Assessment and Reduction Technique (HEART) and Standardized Plant Analysis Risk-Human (SPAR-H) techniques is used to this aim. Afterwards, the Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method is applied to rank risks. The proposed approach is implemented in a Sicilian manufacturing company that produces and commercializes wooden products, together with the sale of outdoor furniture. The comparison of the obtained results with the ones arising from previous risk analyses performed by the company highlights the higher ability of the proposed methodology to differentiate risks.

An integrated multi-criteria decision-making approach for identifying the risk level of musculoskeletal disorders among handheld device users.

In work-from-home (WFH) situation due to coronavirus (COVID-19) pandemic, the handheld device (HHD) users work in awkward postures for longer hours because of unavailability of ergonomically designed workstations. This problem results in different type of musculoskeletal disorders (MSDs) among the HHD users. An integrated multi-criteria decision-making approach was offered for identifying the risk level of MSDs among HHD users. A case example implemented the proposed approach in which, firstly, the best–worst method (BWM) technique was used to prioritize and determine the relative importance (weightage) of the risk factors. The weightages of the risk factors further used to rank the seven alternatives (HHD users) using Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) technique. The outcomes of the BWM investigation showed that the three most significant risk factors responsible for MSDs are duration of working, poor working posture and un-ergonomic design. The outcome of the VIKOR technique exhibited that computer professionals were at the highest risk among all users. The risk factor priority must be used for designing a working strategy for the WFH situation which will help to mitigate the risks of MSDs.

Hybrid IT2 fuzzy modelling with alpha cuts for hydrogen energy investments

The framework of this study is to weight 8 selected determinants and rank energy alternatives for hydrogen investments. For this purpose, different criteria that are based on two dimensions are identified with supported literature and interval type-2 (IT2) fuzzy decision-making trial and evaluation laboratory (DEMATEL) with alpha cuts is considered to measure the significant criteria. Additionally, renewable and non-renewable energy alternatives are ranked regarding the appropriateness for hydrogen energy investments with the help of IT2 fuzzy technique for order preference by similarity to ideal solution (TOPSIS) and IT2 fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) with alpha cuts. It is concluded that the weights of the criteria are quite similar for different alpha cuts. Also, ranking results of different energy alternatives are almost the same for both IT2 fuzzy TOPSIS and IT2 fuzzy VIKOR. Thus, it can be concluded that the analysis results are reliable and coherent. The principal results indicate that cost-efficiency and reserve adequacy play a key role in hydrogen investments since they have the highest weight (0.129). Moreover, it is also found that technological capacity also plays a critical role in this regard with the weight of 0.127. However, legal regulation has the lowest importance weight (0.121) in comparison with other factors. Additionally, the weights of personnel competency (criterion 3) and storage (criterion 4) are also low (0.122). The major conclusion show that renewable energy alternatives are more suitable to generate hydrogen energy in comparison with non-renewable ones. Within this context, it is identified that solar and geothermal energies are more appropriate alternatives for hydrogen production whereas coal and nuclear are on the last rank. Hence, the main strategy should be lowering the costs by following up-to-date technological developments. Another important issue is that it becomes more logical to produce hydrogen in renewable energy sources that will not be consumed forever so that sustainable production of the hydrogen can be provided.

Efficient MCDM Model for Evaluating the Performance of Commercial Banks: A Case Study

Evaluation of commercial banks (CBs) performance has been a significant issue in the financial world and deemed as a multi-criteria decision making (MCDM) model. Numerous research assesses CB performance according to different metrics and standers. As a result of uncertainty in decision-making problems and large economic variations in Egypt, this research proposes a plithogenic based model to evaluate Egyptian commercial banks’ performance based on a set of criteria. The proposed model evaluates the top ten Egyptian commercial banks based on three main metrics including financial, customer satisfaction, and qualitative evaluation, and 19 sub-criteria. The proportional importance of the selected criteria is evaluated by the Analytic Hierarchy Process (AHP). Furthermore, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Vlse Kriterijumska Optimizacija Kompro-misno Resenje (VIKOR), and COmplex PRoportional ASsessment (COPRAS) are adopted to rank the top ten Egyptian banks based on their performance, comparatively. The main role of this research is to apply the proposed integrated MCDM framework under the plithogenic environment to measure the performance of the CBs under uncertainty. All results show that CIB has the best performance while Faisal Islamic Bank and Bank Audi have the least performance among the top 10 CBs in Egypt.

A Neutrosophic VIKOR Method-Based Decision-Making with an Improved Distance Measure and Score Function: Case Study of Selection for Renewable Energy Alternatives

In this study, a new score and distance function which provides more accurate results than the studies in the literature and considers the decision maker’s cognition has been proposed. In order to show the effects of the new score function coefficients on neutrosophic numbers, a new representation named “4D Plot” has been proposed. VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje which means multicriteria optimization and compromise solution in Serbian) method, which is based on the creation of a conciliatory solution within the framework of alternatives and evaluation criteria, provides highly effective results in multiple criteria decision-making problems. Neutrosophic numbers play an active role in facilitating the decision-making process in many studies. In this context, extension of the classical VIKOR method is introduced in detail in this study. The framework of the extended neutrosophic VIKOR method has been established. The proposed method has been applied to the renewable energy alternative selection problem in Turkey and compared with different methods and different scenarios. It has been shown that the proposed method gives more effective and accurate results. Furthermore, the sensitivity and accuracy of the study are enhanced by a sensitivity analysis. We have extended the classical VIKOR method for SVN numbers with a newly generalized score function and a distance measure. As a novel and newly presentation named “The 4D Plot” has been developed and applied in this paper to SVN numbers for presenting the effect of the new score function. The renewable energy alternative selection was made in Turkey with the proposed method by the opinions of the experts and the ranking of the alternatives was obtained. A sensitivity analysis has been made to show the accuracy and validity of the study. With the proposed distance measure and score function, it is shown that more accurate results can be found in multiple criteria decision-making problems. The model will provide solutions for many soft computing problems such as engineering and economy by finding more effective and accurate results in the neutrosophic number space according to the preference of decision makers. As a future work, the presented functions and framework can be adapted to different MCDM problems.