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This study aims to analyze the factors that influence electricity prices. For this purpose, a hybrid multi-criteria decision-making (MCDM) model based on interval-valued intuitionistic hesitant fuzzy (IVIHF) sets is proposed. Firstly, a large literature review is carried out and 10 different factors that can affect electricity prices are determined. After that, IVIHF decision making trial and evaluation laboratory (DEMATEL) methodology is considered to find which factors are more significant in electricity prices. The finding shows that inflation rate and technological improvement are the most important criteria that affect electricity prices. Thus, the countries should consider expected future inflation rates to take necessary precautions to minimize volatility in electricity prices. Moreover, countries should follow current technologies regularly and make effective research and development to provide electricity with lower prices. In the second stage of the analysis, emerging 7 (E7) economies are ranked with respect to the performance related to the management of electricity price volatility. In this context, IVIHF VIšeKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) approach is considered. It is concluded that Russia and China are the most successful countries in keeping electricity prices away from volatility whereas India and Turkey get the latest order. Furthermore, a comparative evaluation is also implemented by considering IVIHF technique for order preference by similarity to ideal solution (TOPSIS) methodology to check the consistency of the analysis results. The results of both approaches are quite similar which gives information about the consistency of the ranking results. On the other hand, a sensitivity analysis is performed to ten different cases consecutively. It is determined that the ranking results are coherent by considering the changes in the criteria weights.

The purpose of the study is to identify the ways to improve the public acceptance for nuclear energy investment in energy importing countries. In this framework, 4 different factors are identified that have an influence on this situation. After that, consensus model is applied for obtaining the fuzzy preference relations at the most consistency level. Next, the criteria are weighted by using DEMATEL (Decision Making Trial and Evaluation Laboratory) methodology based on the Spherical fuzzy sets. Additionally, another evaluation has also been made by considering the Pythagorean fuzzy sets to check the consistency and coherency of the analysis results. It is identified that the results of both Spherical and Pythagorean fuzzy sets are almost the same. This situation gives information about the consistency of the analysis results. Also, sensitivity analysis is also applied by using the different values of $\delta $ with 4 cases. It is determined that there is significant coherency in the consensus-based group decision-making process. The findings indicate that security conditions play the most crucial role to improve the public acceptance for nuclear energy investments in energy importing countries. In addition, it is also identified that economic benefit and environmental issues also have importance influence on this situation. It is recommended that countries should be able to convince their citizens that nuclear energy is safe. Within this context, necessary measures should be taken for security in nuclear power plants and this situation should be clearly explained to citizens. It is obvious that priority should be mainly given to the security issues to improve public perception of nuclear energy investments in energy importing countries. One of the issues most worried by the public is the possibility of an explosion of the nuclear reactor. Hence, for this purpose, the nuclear power plant should be open to international inspection.

La industria de la aviación daña el medio ambiente principalmente a través de la creación de emisiones de carbono. Por lo tanto, es necesario tomar medidas para garantizar la sostenibilidad ambiental de la industria de la aviación, como el reciclaje de productos de desecho, la gestión eficaz de los residuos y la introducción de medidas de eficiencia energética. Sin embargo, al mismo tiempo, la implementación de mejoras para remediar tales problemas conduce a la creación de costos adicionales para las compañías de aviación. Por lo tanto, las empresas deben realizar análisis prioritarios exhaustivos sobre la estrategia óptima para la sostenibilidad de la industria de la aviación. Sin embargo, hay un número muy limitado de estudios en la literatura que se centraron en qué enfoque debe priorizarse. En consecuencia, este estudio tuvo como objetivo la evaluación de la viabilidad de invertir en las llamadas medidas de vuelo verde en la industria de la aviación, para lo cual se creó un modelo de toma de decisiones completamente original. En primer lugar, se ponderaron las diversas prioridades estratégicas y se ilustraron las direcciones de relación de impacto entre ellas con el objetivo de identificar posibles influencias por medio de una metodología de análisis de relación de evaluación de peso multipaso (M-SWARA) que incorpora conjuntos difusos de ortopares de escalón q bipolares (q-ROFS) y corte dorado. En segundo lugar, se clasifican las diversas actividades de vuelo y se determinan los impactos potenciales de estas actividades en términos de las prioridades estratégicas de una industria de aviación sostenible que emplea q-ROF como técnica de eliminación y elección de realidad traslacional (ELECTRE). Todos los cálculos también se calcularon con conjuntos difusos intuicionistas (IFS) y conjuntos difusos pitagóricos (PFS) destinados a verificar la validez de los hallazgos. El análisis concluyó que, si bien la eficiencia energética comprende el factor más importante en términos de inversión estratégica prioritaria para la industria de la aviación basada en la economía circular, la respuesta a emergencias constituye la actividad más crucial de la industria. Se debe priorizar la eficiencia operativa para disminuir la cantidad de combustible consumido, en relación con qué rutas de vuelo se deben planificar de acuerdo con las condiciones climáticas actuales, lo que serviría para acortar los tiempos de vuelo y, por lo tanto, ayudar a aumentar la eficiencia energética. Tal enfoque contribuiría positivamente a minimizar las emisiones de carbono destinadas a garantizar la sostenibilidad de la industria de la aviación. L'industrie aéronautique nuit à l'environnement principalement par la création d'émissions de carbone. Par conséquent, des mesures doivent être prises pour assurer la durabilité environnementale de l'industrie aéronautique, telles que le recyclage des déchets, la gestion efficace des déchets et l'introduction de mesures d'efficacité énergétique. Cependant, dans le même temps, la mise en œuvre d'améliorations pour remédier à ces problèmes entraîne la création de coûts supplémentaires pour les compagnies aériennes. Les entreprises doivent donc mener des analyses prioritaires complètes concernant la stratégie optimale pour la durabilité de l'industrie de l'aviation. Cependant, il existe un nombre très limité d'études dans la littérature qui se sont concentrées sur l'approche à privilégier. En conséquence, cette étude visait à évaluer la viabilité d'investir dans des mesures dites de vol vert dans l'industrie de l'aviation, pour lesquelles un modèle de prise de décision tout à fait original a été créé. Tout d'abord, les différentes priorités stratégiques ont été pondérées et les directions de relation d'impact entre elles illustrées visaient à identifier les influences potentielles au moyen d'une méthodologie d'analyse du rapport d'évaluation du poids par étapes multiples (M-SWARA) qui intègre des ensembles flous d'orthopaires bipolaires q-rung (q-ROFS) et une coupe dorée. Deuxièmement, les différentes activités de vol sont classées et les impacts potentiels de ces activités sont déterminés en fonction des priorités stratégiques d'une industrie aéronautique durable utilisant q-ROF comme technique d'élimination et de traduction des choix (ELECTRE). Tous les calculs ont également été calculés avec des ensembles flous intuitionnistes (IFS) et des ensembles flous pythagoriciens (PFS) visant à vérifier la validité des résultats. L'analyse a conclu que si l'efficacité énergétique constitue le facteur le plus important en termes d'investissement stratégique prioritaire pour l'industrie de l'aviation basée sur l'économie circulaire, l'intervention d'urgence constitue l'activité la plus cruciale de l'industrie. L'efficacité opérationnelle doit être priorisée pour réduire la quantité de carburant consommée, en relation avec laquelle les itinéraires de vol doivent être planifiés en fonction des conditions météorologiques actuelles, ce qui permettrait de raccourcir les temps de vol et, ainsi, d'augmenter l'efficacité énergétique. Une telle approche contribuerait positivement à minimiser les émissions de carbone afin d'assurer la durabilité de l'industrie de l'aviation. The aviation industry harms the environment mainly via the creation of carbon emissions. Hence, action needs to be taken to ensure the environmental sustainability of the aviation industry such as the recycling of waste products, effective waste management and the introduction of energy efficiency measures. However, at the same time, the implementation of improvements to remediate such problems leads to the creation of additional costs for aviation companies. Companies thus need to conduct comprehensive priority analyses regarding the optimum strategy for the sustainability of the aviation industry. However, there is a very limited number of studies in the literature that focused on which approach should be prioritized. Accordingly, this study aimed at the assessment of the viability of investing in so-called green flight measures in the aviation industry, for which a completely original decision-making model was created. Firstly, the various strategic priorities were weighted and the impact-relation directions between them illustrated aimed at the identification of potential influences by means of a multi stepwise weight assessment ratio analysis (M-SWARA) methodology that incorporates bipolar q-rung orthopair fuzzy sets (q-ROFSs) and golden cut. Secondly, the various flight activities are ranked, and the potential impacts of these activities determined in terms of the strategic priorities of a sustainable aviation industry employing q-ROF as the elimination and choice translating reality (ELECTRE) technique. All the calculations were also computed with intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs) aimed at verifying the validity of the findings. The analysis concluded that while energy efficiency comprises the most important factor in terms of strategic priority investment for the circular economy-based aviation industry, emergency response makes up the most crucial activity in the industry. Operational efficiency must be prioritized to decrease the amount of fuel consumed, in connection with which flight routes should be planned according to current weather conditions, which would serve to shorten flight times and, thus, help to increase energy efficiency. Such an approach would make a positive contribution to minimizing carbon emissions aimed at ensuring the sustainability of the aviation industry. تضر صناعة الطيران بالبيئة بشكل رئيسي من خلال خلق انبعاثات الكربون. وبالتالي، يجب اتخاذ إجراءات لضمان الاستدامة البيئية لصناعة الطيران مثل إعادة تدوير منتجات النفايات والإدارة الفعالة للنفايات وإدخال تدابير كفاءة الطاقة. ومع ذلك، في الوقت نفسه، يؤدي تنفيذ التحسينات لمعالجة مثل هذه المشاكل إلى خلق تكاليف إضافية لشركات الطيران. وبالتالي تحتاج الشركات إلى إجراء تحليلات شاملة للأولويات فيما يتعلق بالاستراتيجية المثلى لاستدامة صناعة الطيران. ومع ذلك، هناك عدد محدود للغاية من الدراسات في الأدبيات التي ركزت على النهج الذي ينبغي إعطاء الأولوية له. وبناءً على ذلك، هدفت هذه الدراسة إلى تقييم جدوى الاستثمار في ما يسمى بتدابير الطيران الأخضر في صناعة الطيران، والتي تم من أجلها إنشاء نموذج أصلي تمامًا لصنع القرار. أولاً، تم ترجيح الأولويات الاستراتيجية المختلفة وتم توضيح اتجاهات علاقة التأثير بينها بهدف تحديد التأثيرات المحتملة عن طريق منهجية تقييم نسبة الوزن متعدد الخطوات (M - SWARA) التي تتضمن مجموعات ضبابية لتقويم العظام ثنائية الأقطاب (q - ROFSs) والقطع الذهبي. ثانيًا، يتم تصنيف أنشطة الطيران المختلفة، ويتم تحديد الآثار المحتملة لهذه الأنشطة من حيث الأولويات الاستراتيجية لصناعة الطيران المستدامة التي تستخدم q - ROF كأسلوب للتخلص من الواقع وترجمته (ELECTRE). تم حساب جميع الحسابات أيضًا باستخدام مجموعات غامضة بديهية (IFSs) ومجموعات غامضة فيثاغورية (PFSs) تهدف إلى التحقق من صحة النتائج. وخلص التحليل إلى أنه في حين أن كفاءة الطاقة تشكل العامل الأكثر أهمية من حيث الاستثمار ذي الأولوية الاستراتيجية لصناعة الطيران القائمة على الاقتصاد الدائري، فإن الاستجابة للطوارئ تشكل النشاط الأكثر أهمية في هذه الصناعة. يجب إعطاء الأولوية للكفاءة التشغيلية لتقليل كمية الوقود المستهلكة، فيما يتعلق بتخطيط مسارات الطيران وفقًا للظروف الجوية الحالية، مما سيعمل على تقصير أوقات الطيران، وبالتالي المساعدة في زيادة كفاءة الطاقة. ومن شأن هذا النهج أن يسهم إسهاما إيجابيا في التقليل إلى أدنى حد من انبعاثات الكربون التي تهدف إلى ضمان استدامة صناعة الطيران.

Energy costs are the key factors regarding the selection of appropriate renewable energy (RWG) alternatives. All costs of a power plant, such as investment, operation, maintenance, and repair are considered in the scope of levelized costs. Therefore, for the effective determination of the selling price of the energy, levelized cost has a guiding role. Because the levelized costs of RWG alternatives develop the sustainable production and energy consumption for the long term, the leading indicators of these costs should be analyzed significantly. Accordingly, in this study, it is aimed to investigate the levelized cost of RWG alternatives by using bipolar q-rung orthopair fuzzy (q-ROF) hybrid decision-making approach. The novelty of this study is to recommend an integrated decision-making model based on bipolar and q-ROFSs with golden cut. At the first stage, bipolar q-ROF multi stepwise weight assessment ratio analysis (M-SWARA) is employed for weighting the selected criteria of levelized costs of RWG alternatives. At the following stage, bipolar q-ROF technique for order preference by similarity to ideal solution (TOPSIS) is considered to rank the alternatives in terms of the levelized cost performance. On the other side, vise kriterijumska optimizacija i kompromisno resenje (VIKOR) model is also considered to rank the alternatives. In addition to this issue, the sensitivity analysis is also performed with four cases comparatively. Hence, consistency, reliability and coherency of the proposed model can be measured. It is identified that capacity loss has the greatest importance regarding the levelized cost of RWG projects. Solar is found as the best clean energy type with respect to the levelized cost management performance. In this context, it would be appropriate for investors to design projects close to the center. This will contribute to increasing the efficiency and productivity of these projects.

The aim of this study is to generate appropriate strategies to improve renewable energy investments. Within this framework, a novel model has also been proposed which includes three different stages. Firstly, incomplete preferences of the relation matrixes are calculated. For this purpose, 4 different decision makers evaluate the balanced scorecard-based criteria. In this stage, missing values are estimated by incomplete preferences to complete the relation matrixes. Additionally, the second stage includes the computing the fuzzy preferences by considering the consensus-based group decision-making (CGDM). The final stage is related to the calculation of the weights of the criteria by considering Pythagorean fuzzy decision-making trial and evaluation laboratory (DEMATEL) methodology. Hence, the main motivation of this study is to identify innovative strategies for the renewable energy investments with a novel multi-criteria decision-making (MCDM) model based on incomplete preferences, CGDM and Pythagorean fuzzy sets. The findings indicate that learning and growth is the most important balanced scorecard-based perspective to improve the performance of renewable energy investments. Additionally, the perspective of internal process is identified as another significant factor for this situation. The biggest problem in renewable energy projects is their high initial costs. Hence, technological developments reduce the production costs of renewable energy sources. Additionally, it is also possible to increase the amount of electricity from renewable energy sources owing to the innovative technologies. Thus, renewable energy investors should follow up-to-date technological developments so that it will be possible to reduce the cost of renewable energy investments.

This study examines the fintech innovation life cycle of green energy investments with a new model by using integer patterns, geometrical recognition methodology, Pythagorean fuzzy decision-making trial and evaluation laboratory (DEMATEL) and technique for order preference by similarity to ideal solution (TOPSIS). It is concluded that aging and declining are the most significant phases for the innovation life cycle process for the fintech-financing alternatives in clean energy investments. Furthermore, the finding funds from the shareholders is the most appropriate fintech-based financing alternatives for green energy investment projects. Thus, it is recommended that green energy investors must make a strategic decision in the last stages of the life cycle of innovation. In this framework, either this investment should be terminated, or new technological developments should be adapted to the investments. Moreover, it is also identified that they should mainly prefer equity financing.

Green energy projects contribute to sustainable economic development of countries with the employment of environmentally friendly energy production strategies. However, environmental priorities should be examined for this situation. Therefore, priority analysis should be executed for the environmental issues while implementing green investment projects. Accordingly, this study aims at proposing a unique decision-making model based on orthopair fuzzy sets and the golden cut degrees for the environmental priorities of green project investments. The main novelty of the study stems from its proposed integrated model by equipping the Multi-SWARA, and TOPSIS based on the q-ROFSs technique with the golden cut. A set of criteria is identified for measuring the green projects’ environmental priorities while several project alternatives are also determined with the supporting literature. Appropriately, the extensions of Multi-SWARA and TOPSIS methods have been applied for weighting and ranking the factors, respectively, in the integrated approach. Additionally, a comparative evaluation is performed with the help of VIKOR method to rank the alternatives. Besides, the sensitivity analysis is applied to illustrate the coherency of the weighting results in the decision-making approach. Accordingly, 5 cases are considered to measure the effects of changing weight results. It is defined that this model is coherent and could be extended for further studies. It is concluded that the reduction of emissions is the most essential item for the environmental priorities of green project investments. Pollution control, waste management and eco-friendly transportation activities are the most critical alternatives. Therefore, this study recommends that investors of green projects should prioritize the strategies of minimizing carbon emissions problem. In this context, investing in renewable energy technologies will help green project investors solve this problem.

This study aims to identify the factors that affect youth unemployment in emerging countries. For this purpose, 3 dimensions and 12 criteria are selected as a result of literature review. The analysis process has 3 different steps. Firstly, interval-valued intuitionistic fuzzy sets are created with the help of 2-tuple linguistic data. Additionally, relation matrix is generated by considering these fuzzy sets. In the second process, defuzzification process is occurred. Finally, the dimensions and criteria are weighted with Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach by using defuzzified data sets. The findings indicate that economic and social inequalities play the most significant role for youth unemployment in emerging countries. On the other side, it is also identified that economic crisis and insufficient education conditions are also important issues which lead to youth unemployment in these countries. Hence, it is recommended that governments should implement fair tax management practices in these countries to minimize economic and social inequalities. Furthermore, education conditions should be improved in the countries. In this framework, an effective education plan can be designed by cooperating with companies in the industry. Thus, labor needs in industry can be identified and education system can be designed according to the needs in the market. With the help of these implementations, it can be much easier for young people to find a job.