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The purpose of this study is to assess technical and financial challenges for renewable energy project alternatives with a novel model. Firstly, a set of technical and financial challenges is created by considering the results of the literature evaluation. After that, the weights of these values are computed by Sine Trigonometric Pythagorean Fuzzy (ST-PFN) DEMATEL. The next step includes the ranking of six renewable energy alternatives with interval valued Spherical fuzzy multicriteria analysis with ratio and categorical data (SF MAIRCA) approach. Entropy and ARAS methodology are also considered to make comparative evaluation. Similarly, sensitivity analysis is also conducted for 10 different cases. It is concluded that the analysis results of all methods are the same. Therefore, it is identified that the findings of the proposed model are reliable and coherent. Identification of the most crucial technical and financial challenges of the renewable energy projects is the most important contribution of this manuscript. Furthermore, preferring the sine trigonometric structure in the proposed model will provide superiority to this model in many respects. It is concluded that difficulty in accessing finance for local projects is the most significant challenge for renewable energy investments. Moreover, competitive pricing of renewable sources is another critical issue in this regard. Additionally, it is identified that solar is the most successful renewable energy alternative to overcome technical and financial challenges.

The purpose of this study is to evaluate the environmental impacts of material production investments. The factors of Higg Materials Sustainability Index are defined as the parameters. These factors are weighted by considering T-SF TOPSIS-DEMATEL. Moreover, the items of the life cycle process are defined as alternative set for measuring the environmental effects of each process in the sustainable production investments. These alternatives are ranked with interval valued SF MAIRCA. The calculations are also made for different t, u and d values with the aim of making comparative evaluations. The main contribution of this study is that a priority analysis has been made so that the most significant indicators are defined for the companies to increase sustainability in material production investment process. Another important novelty of this paper is that a new model is created by the name of TOPSIS-DEMATEL. This situation has a positive influence on both increasing methodological originality and overcoming criticized issues of DEMATEL. The results are quite similar for all conditions, so it is understood that the proposed model provides consistent and coherent findings. It is concluded that chemistry is the most critical factor for environmental impact for material production investments. Moreover, recycle is determined as the most optimal alternative.

It is essential to supply the necessary electricity for both the increase in the quality of life of the citizens and the stable growth of the country’s economy. For countries to have energy independence, they need to increase their electricity generation capacity. However, all alternatives required to increase electrical capacity have both advantages and disadvantages. Within this scope, it is not easy for countries to make the right investment decisions. Therefore, a comprehensive analysis is needed to determine the right investment policy. The purpose of this study is to evaluate the electricity production capacities of emerging markets. A new fuzzy decision-making model has been constructed to find a solution for this situation. The groups for the electricity production capacities are examined by the extension of DEMATEL with Quantum Spherical fuzzy sets and golden ratio. In the following stage, emerging seven economies are ranked by using QSF TOPSIS technique. This situation helps to understand which of these countries are more successful in generating electricity capacity effectively. The main novelty is to define the most significant electricity generation alternatives by a novel model that integrates DEMATEL and TOPSIS with QSFSs and golden ratio. The results demonstrate that solar photovoltaic is the most optimal way to increase electricity capacity of the countries. Additionally, China is the most successful emerging country to generate electricity in an efficient way. Countries should take some actions to increase their solar energy investments. First, it would be appropriate to provide tax exemptions to solar energy investors so that the costs of these projects can be decreased. Additionally, investments in solar energy technologies need to be further increased.

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.

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.

Strategic planning is an effective tool for long-term planning and utilized by organizations and industries to achieve competitive advantage. Addressing difficulties that the European banking sector struggled during and after the global financial crisis (GFC), the purpose of this paper is to raise important questions about the sustainability of the sector and offers competitive strategy formulations for European policy makers. Empirical findings are accomplished by applying a three phase analysis of SWOT, an integrated model of DEMATEL-ANP (DANP), and fuzzy TOPSIS. Empirical findings from the SWOT analysis suggest a total of twelve factors, which are then incorporated to formulate four strategies. The DANP results illustrate that opportunities dimension has the highest impact and strengths has the lowest among others. The fuzzy TOPSIS results demonstrate that “the European Banking Union (EBU) is expected to remove divergence in the Euro area banking sector” is the most important strategy, whilst “the non-risk based leverage ratio (LR) requirement by Basel III” has the weakest importance among the strategy preferences.

This study evaluates the synergy of coalition for hybrid renewable energy (RWB) system alternatives. In this context, the alternative sources of hybrid RWB system are examined to illustrate the impact-relation directions among them with multi SWARA based on q-ROFs and golden cut. Next, the performances of renewable alternatives are measured in terms of the synergy of coalition with game theory and Shapley value. It is concluded that solar energy is the most suitable RWB alternative for synergy to increase efficiency in investments. However, biomass does not have a significant influence on providing synergy in energy investments. Therefore, solar energy should be prioritized for hybrid energy investments. Especially with the effect of technological developments, the efficiency of solar energy investments increases significantly. Thus, solar energy investments have become quite suitable for increasing the synergy in hybrid energy projects. Furthermore, necessary research should be conducted to make biomass energy more efficient.

The most essential criteria should be determined in the selection of the suitable energy transition technologies due to budget deficit problem. Therefore, it is necessary to identify the most important criteria in energy transition technology selection. Therefore, a new study is needed to determine the most prominent issues in the correct selection of energy transition technologies. The purpose of this study is to identify the most appropriate energy transition technology alternative. Within this framework, a novel artificial intelligence (AI)-based fuzzy decision-making model has been presented. In the first part, the experts are prioritized by the help of AI methodology. In the next section, missing evaluations of energy transition technology investments are estimated via expert recommender system. Thirdly, the weights of the criteria for energy transition technology selection are computed by quantum picture fuzzy rough sets (QPFR) M-Stepwise Weight Assessment Ratio Analysis (SWARA). At the final stage, selected energy transition technology alternatives are ranked via QPFR-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). The main contribution of this study is the integration of AI technique to the proposed model. Similar to this issue, using M-SWARA methodology in the process of criteria weighting increases the quality of the findings. This methodology helps to consider the impact relation map of the criteria. The findings demonstrate that the most important factor is cost-effectiveness of energy transition. Similarly, it is also found that the local ecosystem is the second most significant issue. On the other side, the ranking results denote that compact renewable systems for small scale production is the most optimal solution of energy transition technology alternatives.

The purpose of this study is to examine optimal solar module investments. Firstly, key determinants of the performance of solar energy investments are evaluated by DEMATEL method with the 2-tuple IVIF sets. Moreover, the cell material alternatives for solar module investments are also ranked. For this purpose, an evaluation has been made by 2-tuple IVIF TOPSIS. The contributions of the paper are performing a priority analysis to understand the most significant factors to increase solar energy projects and creating an original model by the integration of DEMATEL and TOPSIS with the 2-tuple IVIF sets. The findings denote that crystalline silicon is the optimal solar panel module to increase the performance of these projects. In the short term, government subsidies can provide cost advantages to solar energy investors. It is not a very continuous practice to try to increase these projects only with government supports. The costs of solar energy projects should be reduced to solve this problem permanently. Owing to new technological developments, high cost problem of solar energy investments can be handled more successfully.

Abstract Companies must be able to identify their suppliers appropriately and effectively in order to survive in the competitive market conditions. In order to fulfill and surpass the expectations of the consumers and clients, companies need to interact with the relevant suppliers. It is a tough manner for companies to select the best supplier from a large number of relevant alternatives. The selection process of the appropriate supplier involves multiple interacting and competing factors. Generally, the selection process and its results cause a waste of time and money. For this purpose, MCDM methodologies are utilized to manage this complex process efficiently. MCDMs allows for consistent and accurate decision-making as well as the selection of the most appropriate supplier. MCDM is one the most preferred tool to select the best alternative under the conflicting and competitive criteria when the evaluations are made in crisp numbers. Therefore, MCDM methods are preferred in various applications in academia and real life. However, the evaluations could not be always possible with crisp numbers, especially in vague environments or evaluations needs qualitative data. This study is one of the first to combine the AHP and COPRAS supplier selection methods with interval-valued Pythagorean fuzzy (IPF) logic. The effectiveness of these IPF-AHP and IPF-COPRAS evaluations for the supplier selection problem is compared and examined. The experimental results of case scenarios show that IPF is an effective way to apply in decision-making applications. In addition, sensitivity analysis is conducted to evaluate the proposed methodologies. According to sensitivity analysis, the IPF-AHP and IPF-COPRAS be able to illustrate the effects of small changings in criteria weights. Therefore, companies can use the IPF-AHP and IPF-COPRAS to assist their decision-makers in identifying and selecting the best suppliers.

The purpose of this study is to analyze the investment success of renewable energy generation projects design. A novel model has been constructed for this purpose. At the first stage, collaborative filtering methodology is taken into consideration to complete missing evaluations. After that, M-SWARA based on QUSFSs with golden cut is used to compute the weights of these factors. Finally, the components of the service design are ranked by TOPSIS approach. The main contribution of the paper is that a new methodology (M-SWARA) has been created in this study by making improvements to SWARA. With the help of this new model, causal directions between the indicators can also be examined. Similarly, collaborative filtering methodology is taken into consideration to complete missing evaluations. In this process, the decision makers are allowed to leave the questions they wanted blank. This situation is considered as the superiority of the proposed model compared to many previous models in the literature. The findings indicate that cost is the most significant factor for the success of renewable energy investments because it gets the highest weight (.261). The ranking results also demonstrate that product is the most essential component of the service design of renewable energy investments. Therefore, solving the high-cost problem is of vital importance to increase these investments. First, renewable energy companies can reduce costs with more effective financial management. To carry out this process effectively, a finance department consisting of qualified personnel is needed. Thanks to this team, current situations in the financial markets will be better followed and this will play an important role in reducing costs.

The purpose of this research is to examine the interaction between financial stress and conflict risk having impacts on fi nancial instruments in capital markets within an interdisciplinary frame. The Fuzzy TOPSIS method is applied in order to analyse effects of conflict hazard on capital markets and fi nancial instruments in the E7 economies and to demonstrate the best possible ranks of the E7 economies based on performance evaluation criteria. In order to obtain the dynamics of data as to develop a suffi cient reference bases for expert opinions, conflict hazard index and fi nancial stress index have been structured. The empirical results confirm that there is strong relation between fi nancial stress index and confl ict hazard index for the E7 economies. The fundamental conclusion demonstrates the effects of the financial and conflict risks for the stock selection in the E7 economies by the criteria derived from the Financial Stress Index and Confl ict Risk Index.