Expert Decision Research Articles

Selection of a Green Contractor for the Implementation of a Solar Power Plant Project

This study is focused on the problem of contractor selection for the implementation of a solar power plant project to produce electricity from sustainable sources for the needs of the company Voćar. The goal of this research is to select a construction contractor to install a solar power plant using sustainability criteria. With this power plant, the company Voćar can reduce its electricity costs and contribute to the production of sustainable energy. A total of three main sustainability criteria were used, in which six auxiliary criteria were symmetrically distributed. With these criteria, six suppliers were analyzed, and expert decision making was carried out with the application of the fuzzy–rough approach. To define the weights of the criteria, the SWARA method was utilized in this study. Based on the findings of this method, the most important criteria are the ecological criteria. Using the CRADIS method, the contractors were ranked, and the results show that contractor C6 has the best results and is the first choice for implementing this project. Choosing the best supplier increases the sustainability of project implementation and the realization of the expected effects.

Sarcoidosis-Associated Pulmonary Hypertension.

Sarcoidosis-associated pulmonary hypertension (SAPH) is a very severe complication of the disease, largely impacting its morbidity and being one of its strongest predictors of mortality. With the recent modifications of the hemodynamic definition of pulmonary hypertension (mean arterial pulmonary pressure >20 instead of <25 mmHg,) its prevalence is presently not precisely known, but it affects from 3 to 20% of sarcoid patients; mostly, although not exclusively, those with an advanced, fibrotic pulmonary disease. Its gold-standard diagnostic tool remains right heart catheterization (RHC). The decision to perform it relies on an expert decision after a non-invasive work-up, in which echocardiography remains the screening tool of choice. The mechanisms underlying SAPH, very often entangled, are crucial to define, as appropriate and personalized therapeutic strategies will aim at targeting the most significant ones. There are no recommendations so far as to the indications and modalities of the medical treatment of SAPH, which is based upon the opinion of a multidisciplinary team of sarcoidosis, pulmonary hypertension and sometimes lung transplant experts.

Fuzzy causal model of enterprise flexibility dimensions using Fermatean Fuzzy DEMATEL: a case study of Indian pharmaceutical industry

PurposeTo develop a fuzzy causal model of enterprise flexibility dimensions in a case study of Indian pharmaceutical industry.Design/methodology/approachThe eight dimensions of enterprise flexibility were identified based on literature review. Fermatean fuzzy decision-making trail and evaluation laboratory (FF-DEMATEL) technique is applied to develop the cause-and-effect interrelationship model among various enterprise flexibility dimensions.FindingsThe information technology flexibility, supply chain flexibility, technical flexibility and marketing flexibility are found to be causing/influencing other flexibilities and contributing to overall enterprise flexibilities. Therefore, more attention needs to be paid to develop and sustain them for competitive advantage.Research limitations/implicationsFermatean fuzzy sets offer more flexibility and more accurate handling complex uncertain group decision making. FF-DEMATEL is a more accurate method to develop inter-dependencies and causal model than ISM, TISM. Ratings from the limited number of decision experts (DEs) from few pharmaceutical firms were done. Future study should take bigger sample of firms and more number of DEs to generalize the findings.Practical implicationsThe model will help managers in pharmaceutical industry to prioritize the dimensions of enterprise flexibility to achieve agility, responsiveness, resilience and competitive advantage.Originality/valueTo the best knowledge of the authors, causal modeling enterprise flexibility dimensions using FF-DEMATEL has been studied for the first time in a developing economy context.

Earthquake Risk Assessment Using GIS-Based Analytical Hierarchy Process (AHP): The Case of Bitlis Province (Türkiye)

The risk level of natural disasters such as earthquakes depends on many factors. Some of these are direct hazards, while others are vulnerability factors that increase the risk. In this regard, risk assessment should be performed by evaluating the hazard and vulnerability factors together. The Analytical Hierarchy Process (AHP) is a powerful tool for co-evaluating such multiple decision criteria. The spatial visualization of the results facilitates the direct assessment of risks as well. In the present study, the seismic risk assessment of the Bitlis province in Eastern Anatolia, which has a high seismic risk, was performed by using the GIS-based AHP method. Among many criteria, six effective criteria on earthquake risk such as seismicity, demographic and topographic criteria were taken into consideration based on expert decision makers. It is concluded that the results obtained from the study were quite successful in terms of determining the seismic risks of the study area. Accordingly, while the risks are high in densely populated settlements with high peak ground acceleration (PGA), the risk decreases according to soil and land use.

The Role of Actuaries in Sustainable Development Goals

Purpose: The general purpose of this study was to investigate the role of actuaries in Sustainable Development Goals.&#x0D; Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.&#x0D; Findings: The findings reveal that there exists a contextual and methodological gap relating to the role of actuaries in Sustainable Development Goals. The study underscored the indispensable role of actuaries in advancing sustainable development goals (SDGs) across multiple sectors. Actuaries contribute significantly to promoting environmental sustainability by assessing and managing risks associated with climate change, while also fostering social equity and inclusivity through the design of insurance and pension schemes. Moreover, they facilitate long-term investment and infrastructure development aligned with SDGs 8 and 9, and support health and well-being initiatives, particularly in healthcare financing and risk assessment. Overall, through their expertise in risk assessment, financial management, and strategic decision-making, actuaries play a critical role in driving transformative change towards a more sustainable, inclusive, and resilient future.&#x0D; Unique Contribution to Theory, Practice and Policy: The Stakeholder theory, Institutional theory and Systems theory may be used to anchor future studies on the role of actuaries in Sustainable Development Goals. The study provided recommendations aimed at enhancing the contributions of actuaries to sustainable development agendas. It advocated for increased awareness among actuaries about their role in supporting SDGs, fostering collaboration between stakeholders, integrating sustainability considerations into actuarial practices, and promoting transparency and accountability within the profession. These recommendations emphasized the importance of aligning actuarial efforts with sustainability goals, leveraging collective expertise, and ensuring ethical and responsible decision-making. By implementing these recommendations, actuaries could play a more proactive and impactful role in advancing sustainable development goals and addressing societal challenges.&#x0D; Keywords: Actuaries, Sustainable Development Goals, Contributions, Recommendations, Awareness, Collaboration, Sustainability Considerations, Transparency

Information Source Attributes and Terrorism Risk Preparedness among the Residents of Nairobi City County

Purpose: The main purpose of the study was to establish the association of source attributes and terrorism risk preparedness among the residents of Nairobi City County.&#x0D; Materials and Methods: This study followed a mixed-methods design comprising mainly of a questionnaire survey complemented by observation, key informant interviews and document analysis, The design employed the Concurrent Convergent (Triangulation) Parallel strategy. According to the Kenya National Bureau of Statistics, Nairobi City County has a resident population of 4,397,073. A further estimated 2.5 million non-residents visit the city-county daily for business, work, or as tourists and travelers in transit to other counties. Therefore, the target population for this study was approximately 6.5 million. The study population was drawn using stratified purposive random sampling technique where the list of all the sampling locations was categorized into four strata. The sample size was 640 respondents who were proportionately randomly drawn from four different strata. &#x0D; Findings: Regression of coefficients showed that source attributes and terrorism risk preparedness were positively and significantly related (β=0.379, p=0.000). Specifically, 53.6% of the respondents agreed with the statement that receiving information from credible sources on terrorism attacks provides motivation for preparedness in case of a terrorist attack. Similarly, 64.8% agreed with the statement that consistency in terrorism risks communications provides motivation to preparedness behaviour adoption 62.6% of the respondents were in concurrence that competence among that communication terrorism risk preparedness was a motivating factor for preparedness. Further, only 43.1% of the respondents indicated that their organisations were using experts in terrorism risk communication and preparedness. 64.6% were of the opinion that involving non experts in decisions related to terrorism risk communications and preparedness can result in preparedness action taking laxity.&#x0D; Implications to Theory, Practice and Policy: The study recommends that professionals charged with emergency risk communication for terrorism preparedness should particularly: demonstrate expertise and competence in the subject matter to instill confidence in their audiences that the information is reliable and useful. This can be achieved by involving qualified professionals, experts, or organizations with relevant experience in emergency risk preparedness and build trust by being transparent, honest, and reliable in communication. Trust can also be enhanced by providing accurate information, acknowledging uncertainties when applicable, and addressing any concerns or doubts promptly.

Validation of the ACC Expert Consensus Decision Pathway for Patients With Chest Pain

BackgroundThe American College of Cardiology (ACC) recently published an Expert Consensus Decision Pathway for chest pain. ObjectivesThe purpose of this study was to validate the ACC Pathway in a multisite U.S. cohort. MethodsAn observational cohort study of adults with possible acute coronary syndrome was conducted. Patients were accrued from 5 U.S. Emergency Departments (November 1, 2020, to July 31, 2022). ECGs and 0- and 2-hour high-sensitivity troponin (Beckman Coulter) measures were used to stratify patients according to the ACC Pathway. The primary safety outcome was 30-day all-cause death or myocardial infarction (MI). Efficacy was defined as the proportion stratified to the rule-out zone. Negative predictive value for 30-day death or MI was assessed among the whole cohort and in a subgroup of patients with coronary artery disease (CAD) (prior MI, revascularization, or ≥70% coronary stenosis). ResultsACC Pathway assessments were complete in 14,395 patients, of whom 51.7% (7,437 of 14,395) were women with a median age of 56 years (Q1-Q3: 44-68 years). Known CAD was present in 23.5% (3,386 of 14,395) and 30-day death or MI occurred in 8.1% (1,168 of 14,395). The ACC Pathway had an efficacy of 48.1% (95% CI: 47.3%-49.0%). Among patients in the rule-out zone, 0.3% (22 of 6,930) had death or MI at 30 days, yielding a negative predictive value of 99.7% (95% CI: 99.5%-99.8%). In patients with known CAD, 20.0% (676 of 3,386) were classified to the rule-out zone, of whom 1.5% (10 of 676) had death or MI. ConclusionsThe ACC expert consensus decision pathway was safe and efficacious. However, it may not be safe for use among patients with known CAD.

New q-rung orthopair fuzzy Aczel–Alsina weighted geometric operators under group-based generalized parameters in multi-criteria decision-making problems

The concept of q-rung orthopair fuzzy set (q-ROF) defined as generalization of intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PyFS) has more flexible structure according to several clusters. Therefore, it is a benefit tool to obtain various results for different values of q. The basic benefit of generalized concepts is to rate level of truth and falsity and reduce to error margin. Thus, while the final decision is decided by experts, the most accuracy finding is to present. Aczel–Alsina t-norm (AA-TN) and t-conorm (AA-TCN) structures were defined by Aczel and Alsina in 1982. The both concepts include parameters changing according to prefer, decision, and request of experts. In this paper, q-rung orthopair fuzzy Aczel–Alsina weighted geometric operator (q-ROFAAWG) is produced and also ordered and hybrid concepts (q-ROFAAOWG, q-ROFAAHWG) are obtained using Aczel–Alsina operators (AAOs). Hence, this operator is expanded to generalized q-rung orthopair fuzzy Aczel–Alsina weighted geometric operator (Gq-ROFAAWG), ordered and hybrid concepts (Gq-ROFAAOWG, Gq-ROFAAHWG) using single parameter. Finally, group-based generalized q-rung orthopair fuzzy Aczel–Alsina weighted geometric operator (GGq-ROFAAWG), ordered and hybrid concepts (GGq-ROFAAOWG, GGq-ROFAAHWG) are proposed and their properties are worked. Moreover, an algorithm-based multi-criteria decision-making is given and applied over a numerical example to illustrate the effective of the proposed method. The results are evaluated for different values of parameters. In addition to, comparative analysis is developed to show the superiority of proposed approach than existing methods.

A novel LqROPF-Entropy-WASPAS group model based on Frank aggregation operators and improved score function in linguistic q-rung orthopair fuzzy framework

Decision analysis plays a crucial role in our everyday actions. Efficient decision-making models rely heavily on accurately representing human cognitive knowledge. The linguistic q-rung orthopair fuzzy sets (LqROPFSs) offer a versatile means of representing qualitative cognitive information by adapting the parameter q to different scenarios. This study presents a novel scoring function to rank linguistic q-rung orthopair fuzzy numbers (LqROPFNs) with greater precision compared to the current score function. Next, we present novel arithmetic/geometric aggregation operators (AOs) that utilize new Frank operational rules to combine a finite collection of LqROPFNs. The work also examines the several desirable characteristics and special cases of the provided AOs. Furthermore, a novel decision-making model called the LqROPF-Entropy-WASPAS model has been introduced to address the challenges of multiple attribute group decision-making (MAGDM) problems in a linguistic q-rung orthopair fuzzy environment. The model incorporates proposed AOs and a scoring function. The suggested methodology is exemplified by considering a practical decision to select an online teaching platform. The validity of the results is confirmed through an extensive sensitivity analysis and comparative investigation employing various existing MAGDM approaches within the linguistic q-rung orthopair fuzzy framework. The proposed approach offers enhanced flexibility to decision experts, empowering them to analyze decision outcomes across diverse scenarios. This flexibility is achieved by allowing the manipulation of values associated with various parameters, enabling decision-makers to tailor the analysis according to their specific attitudes and requirements. This adaptability ensures a more advanced and personalized analysis of decision outcomes, accommodating decision experts’ distinct viewpoints and preferences in varying situations.

Edge computing-oriented smart agricultural supply chain mechanism with auction and fuzzy neural networks

Powered by data-driven technologies, precision agriculture offers immense productivity and sustainability benefits. However, fragmentation across farmlands necessitates distributed transparent automation. We developed an edge computing framework complemented by auction mechanisms and fuzzy optimizers that connect various supply chain stages. Specifically, edge computing offers powerful capabilities that enable real-time monitoring and data-driven decision-making in smart agriculture. We propose an edge computing framework tailored to agricultural needs to ensure sustainability through a renewable solar energy supply. Although the edge computing framework manages real-time crop monitoring and data collection, market-based mechanisms, such as auctions and fuzzy optimization models, support decision-making for smooth agricultural supply chain operations. We formulated invisible auction mechanisms that hide actual bid values and regulate information flows, combined with machine learning techniques for robust predictive analytics. While rule-based fuzzy systems encode domain expertise in agricultural decision-making, adaptable training algorithms help optimize model parameters from the data. A two-phase hybrid learning approach is formulated. Fuzzy optimization models were formulated using domain expertise for three key supply chain decision problems. Auction markets discover optimal crop demand–supply balancing and pricing signals. Fuzzy systems incorporate domain knowledge into interpretable crop-advisory models. An integrated evaluation of 50 farms over five crop cycles demonstrated the high performance of the proposed edge computing-oriented auction-based fuzzy neural network model compared with benchmarks.

Integration perspectives for improving regional policy in rural areas of Bulgaria

Purpose. The purpose of the research is to determine the degree of implementation of specific regional policies in rural areas in the context of Bulgaria’s integration into the European Union through the prospects of the changing economic situation and new trends in the implementation of regional policy. Methodology / approach. The focus of the research is the need for a working regional policy that gives importance to the development of rural areas and influences the demographic and socio-economic processes in Bulgaria. The study is defined by comparative analysis, reference to expert assessment, use of statistical data, and analysis of strategic documents and programs related to regional development. Results. This research has shown that the applied regional development policies within the European Union have partial success. At the same time, the problems and emerging deficits are successfully defined, but it is more difficult to find optimal solutions that can be applied in more than one municipality. In this direction, regional policy has its achievements in its development, but new solutions are still being sought for several spatial and territorial problems in connection with integration into a common European market. This means a comprehensive process of functional impacts in the socio-economic development of nearly 281 regions. In Bulgaria, the situation is even more complicated, because it is necessary to have a dual approach in regional politics. On the one hand, the development of the most urbanised regions, and on the other hand, the development of the rural areas, which are decisive for the development of the greater part of the territory of Bulgaria. Originality / scientific novelty. The regional development policy carried out in the years after 2007 has a static and spontaneous character, the new approach of the measures and programs after 2023 are based on new concepts and elements in line with information technologies, development of intelligent systems, economic connectivity to overcome the backward development of rural areas. New approaches and moments are proposed in the construction of a regional policy, which has a new framework and provisions for the development of the European economic space. In this direction, the need for expert decisions related to the management of regional development comes to the fore. Practical value / implications. It is necessary to make regional development a national priority. In addition, governments should facilitate access to young people and medium-sized businesses for the use of inputs and the promotion of projects. Access to financing, strategic, and planning activities, which have their characteristics at different levels, must be further developed.

Some Topological Approaches of Rough Sets through Minimal Neighborhoods and Decision Making

Rough set has an important role to deal with uncertainty objects. The aim of this article is to introduce some kinds of generalization for rough sets through minimal neighborhoods using special kinds of binary relations. Moreover, four different types of dual approximation operators will be constructed in terms of minimal neighborhoods. The comparison between these types of approximation operators is discussed. Some new kinds of topological structures induced by minimal neighborhoods are established and some of their properties are studied. Finally, we give a comparison between these topologies that help for determining the major components of COVID-19 infections. In this application, the components of infections help the expert in decision making in medicine.

Integrating Multi-Criteria Decision Models in Smart Urban Planning: A Case Study of Architectural and Urban Design Competitions

The focus of this study is to integrate the DEX (Decision EXpert) decision-modeling method in architectural and urban design (A &amp; UD) competitions. This study aims to assess the effectiveness of integrating the DEX (Decision EXpert) decision-modeling method into the evaluation process of A &amp; UD competitions to enhance decision-making transparency, objectivity, and efficiency. By using symbolic values in decision models, the approach offers a more user-friendly alternative to the conventional jury decision-making process. The practical application of the DEX method is demonstrated in the Rhinoceros 3D environment to show its effectiveness in evaluating A &amp; UD competition project solutions related to the development of the smart city. The results indicate that the DEX method, with its hierarchical and symbolic values, significantly improves the simplicity of the evaluation process in A &amp; UD competitions, aligning it with the objectives of the smart cities. This method provides an efficient, accessible, and viable alternative to other multi-criteria decision-making approaches. This study importantly contributes to the field of architectural decision making by merging qualitative multi-criteria decision models into the CAD environment, thus supporting more informed, objective, and transparent decision-making processes in the planning and development of smart cities.

The study on the appearance of deformation defects in the yacht lamination process using an AI algorithm and expert knowledge.

This article describes the application of the A-priori algorithm for defining the rule-based relationships between individual defects caused during the lamination process, affecting the deformation defect of the yacht shell. The data from 542 yachts were collected and evaluated. For the proper development of the algorithm, a technological process of the yacht lamination supported by expert decisions was described. The laminating technology is a complex process of a sequential application of individual laminates according to a special strategy. The A-priori algorithm allowed for obtaining the set of association rules defining the relationships between the defects resulting from the lamination process and influencing the deformation defect of the yacht shell, which is one of the most common errors in yacht production. The obtained aggregated rules were compared with the expert knowledge of the employees of the production, quality control, mould regeneration, and technology departments of the yacht yard. The use of the proposed A-priori algorithm allowed for the generation of relationship rules consistent with the general opinion of experts. Associative rules additionally took into account detailed causes of a specific error, which were not always noticed by employees of specific departments. The assessment of the lamination process using an artificial intelligence algorithm turned out to be more objective, which made it possible to gradually reduce the total number of errors occurring in the yacht shell lamination process, and thus shorten the time needed to repair errors and the total time of producing the yacht.

A guide to measuring expert performance in forensic pattern matching

Decisions in forensic science are often binary. A firearms expert must decide whether a bullet was fired from a particular gun or not. A face comparison expert must decide whether a photograph matches a suspect or not. A fingerprint examiner must decide whether a crime scene fingerprint belongs to a suspect or not. Researchers who study these decisions have therefore quantified expert performance using measurement models derived largely from signal detection theory. Here we demonstrate that the design and measurement choices researchers make can have a dramatic effect on the conclusions drawn about the performance of forensic examiners. We introduce several performance models – proportion correct, diagnosticity ratio, and parametric and non-parametric signal detection measures – and apply them to forensic decisions. We use data from expert and novice fingerprint comparison decisions along with a resampling method to demonstrate how experimental results can change as a function of the task, case materials, and measurement model chosen. We also graphically show how response bias, prevalence, inconclusive responses, floor and ceiling effects, case sampling, and number of trials might affect one’s interpretation of expert performance in forensics. Finally, we discuss several considerations for experimental and diagnostic accuracy studies: (1) include an equal number of same-source and different-source trials; (2) record inconclusive responses separately from forced choices; (3) include a control comparison group; (4) counterbalance or randomly sample trials for each participant; and (5) present as many trials to participants as is practical.

Decision-Making Conflict Measurement of Old Neighborhoods Renovation Based on Mixed Integer Programming DEA-Discriminant Analysis (MIP DEA–DA) Models

Renovating old neighborhoods for the benefit of people has become increasingly important in urban renewal. Nevertheless, old neighborhood renovations are currently considered a group decision-making issue under public participation, involving diverse decision-making subjects. Conflicts within a group are a common problem during group decision-making. In this paper, conflict is examined in the decision-making process for renovating old neighborhoods and novel ideas are provided for quantifying conflict. Public participation in old neighborhood renovations is assessed using conflict degree calculations in group decision-making. Based on the preferences of decision-making experts, a MIP DEA–DA (Mixed Integer Programming Data Envelopment Analysis–Discriminant Analysis) based partial binary tree cyclic clustering model is constructed for clustering experts, and an aggregated group conflict indicator and an aggregated conflict vector are computed, allowing for the quantification of conflict during the renovation process of the old neighborhood based on actual situations. Results indicate that there is primarily a conflict between the benefits of decision-making subject interests and the professionalism of decision-making renovations. This paper contributes to improving public participation, promoting the application of group decision-making theory in old neighborhood renovation, reducing conflict between decision-makers, and speeding up urban renewal.

Bridging the Fact/Value Divide in Wisdom Research: The Development of Expertise in Wise Decision-Making

Bridging the Fact/Value Divide in Wisdom Research: The Development of Expertise in Wise Decision-Making

A new approach for configuring modular floating cities: assessing modular floating platforms by means of analytic hierarchy process

Floating cities have emerged as an efficient long-term solution over unsustainable practiced solutions to combat the rising seas problem; nevertheless, the world lacks an international, official, and comprehensive framework regarding floating cities. Although previous research approached modular floating city design; however, resulted in configurations with various critical design restrictions mainly regarding interlocking capabilities and space utilization. The purpose of this paper is to offer a new systematic strategy for configuring modular and expandable floating cities without such restrictions. This paper explores Euclidean tilings as a strategy to offer numerous configurations based on regular, semi-regular, and demi-regular tilings. Selecting the ideal configuration is complicated; therefore, both quantitative and qualitative data methods were implemented to attain the objectives. Via an extensive literature review, this research derives key factors for configuring floating cities, then sets a brainstorming session with experts for group decision making before providing findings upon calculations via analytic hierarchy process, one of the most used quantitative data methods of multiple-criteria decision analysis. Through comprehensive literature review: seakeeping, modularity, zoning and circulation, and feasibility have been identified as the most significant criteria in floating city research. It explores the qualities and limitations of triangular, squared, hexagonal, octagonal, and dodecagonal platforms. Regarding criteria, seakeeping was the most significant criterion for platform selection by 53.6%. Regarding platforms, the hexagonal platform scored the highest with 25.31%. Relying on this method and the design considerations presented, numerous dynamic configurations can be offered and assessed through specific contexts without any of the past restrictions.

Determination of best renewable energy sources in India using SWARA-ARAS in confidence level based interval-valued Fermatean fuzzy environment

The requirement for renewable energy sources arises from the depletion of fossil fuels and the increasing energy demand. A case study in India has been conducted in this context to identify the most promising renewable energy sources. A novel multi-attribute group decision-making (MAGDM) method integrating stepwise weight assessment ratio analysis (SWARA) and additive ratio assessment (ARAS) has been proposed for this purpose. We have used interval-valued Fermatean fuzzy numbers for data representation due to their ability to accommodate a broad range of fuzzy information. By introducing confidence level-based aggregation operators in an interval-valued Fermatean fuzzy environment, we avoid erroneous assessments by decision experts. We have employed objective and subjective weight determination approaches to determine decision experts’ weights. The SWARA method has been used for attribute weight evaluation due to its simplicity and efficiency, and the ARAS method is employed for alternative ranking and optimal choice selection using the utility degree. The findings show the potential to expand solar and wind power, whereas geothermal energy is not yet suitable for widespread deployment because of its early stage of development. We find the technical and environmental aspects to be especially significant during the decision-making process. To demonstrate the proposed method’s applicability, we have compared the results with existing MAGDM methods. To establish its stability, we conducted a sensitivity analysis. The presented MAGDM method can help make informed decisions regarding implementing solar energy as a primary source of energy supply in India, thereby aiding decision-making for policymakers, regulators, energy planners, and stakeholders.

Evaluation of optimal waste lithium-ion battery recycling technology driven by multiple factors

As energy and environmental issues become increasingly prominent, the process of global carbon emission reduction is now underway. In the transportation sector, the application of electric vehicles is an effective way to achieve energy saving and emission reduction. Lithium-ion battery, an important component of electric vehicles, has received widespread attention for its advantages including small size, high energy density and smooth discharge voltage. However, their potential safety and pollution issues are becoming prominent and must be properly handled. Moreover, the technical route and future direction of LIB recycling are still unclear at this stage. Herein, this paper evaluates different waste lithium-ion battery recycling technologies in a multi-criteria decision framework to determine the best technology. A criteria system driven by multiple factors is established, including environmental impact (C1), technical risk (C2), comprehensive resource utilization (C3), resource consumption (C4) and economic performance (C5). Subsequently, since the optimal technology is novel and difficult to select, the hesitant fuzzy linguistic term sets are used to express the degree of hesitation in expert decision making. Finally, from the aspects of the choice of sorting method, the Tomada de decisao interativa multicriterio method based on the expectation effect is used to evaluate the optimal waste lithium-ion battery recycling technology, and the validity of the framework is illustrated by data analysis.