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Abstract The current study evaluates the financial innovation life cycle for renewable energy investments. A novel model is proposed that has two stages. First, the financial innovation life cycle is weighted by the two-generation technology S-curve (TTSC) for renewable energy investments. Second, the TTSC is ranked with integer patterns for renewable energy investments. For this purpose, the decision-making trial and evaluation laboratory (DEMATEL) is considered with q-rung orthopair fuzzy sets (q-ROFSs). A comparative examination is then performed using intuitionistic and Pythagorean fuzzy sets, and we find similar results for all fuzzy sets. Hence, the suggested model is reliable and coherent. Maturity phase 1 is the most significant phase of the financial innovation life cycle for these projects. Aging is the most important period for financial innovation in renewable energy investment projects—renewable energy companies should make strategic decisions after that point. In this situation, decisions should relate to either radical or incremental innovation. If companies do not make decisions during these phases, innovative financial products cannot be improved. As a result, renewable energy companies will not prefer financing products.

Abstract The purpose of this study is to determine the essential indicators to improve insurtech systems and select the most critical alternative to increase insurtech-based investments in European countries. A novel fuzzy decision-making model is generated by integrating entropy and additive ratio assessment (ARAS) techniques with spherical fuzzy sets. First, the indicators are weighted using spherical fuzzy entropy. Then, the alternatives are ranked using spherical fuzzy ARAS. The alternatives are also ranked with the spherical fuzzy technique for order of preference by similarity to the ideal solution methodology. The main contribution of this study is that it would help investors to take the right actions to increase the performance of insurtech investments without incurring high costs. Another important novelty is that a new fuzzy decision-making model is proposed to solve this problem. The results of the two models are quite similar, proving the validity and coherency of the findings. It is found that pricing is the most critical factor that affects the performance of insurtech investments. Insurtech companies are required to make accurate pricing by conducting risk analyses to increase their profits and minimize their risks. Additionally, according to the ranking results, big data are the most appropriate way to improve the performance of insurtech investments in Europe. Big data analytics helps companies learn more about the behavior of their customers. By analyzing data about their customers’ past transactions, companies can provide more convenient services to them. This would increase customer satisfaction and enable companies to achieve long-term customer loyalty.

Abstract Crypto assets have become increasingly popular in recent years due to their many advantages, such as low transaction costs and investment opportunities. The performance of crypto exchanges is an essential factor in developing crypto assets. Therefore, it is necessary to take adequate measures regarding the reliability, speed, user-friendliness, regulation, and supervision of crypto exchanges. However, each measure to be taken creates extra costs for businesses. Studies are needed to determine the factors that most affect the performance of crypto exchanges. This study develops an integrated framework, i.e., fuzzy best–worst method with the Heronian function—the fuzzy measurement of alternatives and ranking according to compromise solution with the Heronian function (FBWM’H–FMARCOS’H), to evaluate cryptocurrency exchanges. In this framework, the fuzzy best–worst method (FBWM) is used to decide the criteria’s importance, fuzzy measurement of alternatives and ranking according to compromise solution (FMARCOS) is used to prioritize the alternatives, and the Heronian function is used to aggregate the results. Integrating a modified FBWM and FMARCOS with Heronian functions is particularly appealing for group decision-making under vagueness. Through case studies, some well-known cryptocurrency exchanges operating in Türkiye are assessed based on seven critical factors in the cryptocurrency exchange evaluation process. The main contribution of this study is generating new priority strategies to increase the performance of crypto exchanges with a novel decision-making methodology. “Perception of security,” “reputation,” and “commission rate” are found as the foremost factors in choosing an appropriate cryptocurrency exchange for investment. Further, the best score is achieved by Coinbase, followed by Binance. The solidity and flexibility of the methodology are also supported by sensitivity and comparative analyses. The findings may pave the way for investors to take appropriate actions without incurring high costs.

Abstract The risk profiles of investors play an important role in the success of derivative products investments. It is also necessary to determine the appropriate investor profile according to the conditions of a country. This protects investors from major losses. Therefore, there is a strong need for a new study that analyzes the risk profiles of derivative products in emerging economies. This study aims to identify the most appropriate investor risk profile for derivative instruments in emerging economies. It constructs a novel decision-making model. In this model, the facial action coding system, quantum theory, spherical fuzzy sets, and multi-stepwise weight assessment ratio analysis (M-SWARA) methodology are integrated to minimize uncertainty in this process. First, three main participants of derivatives for financial technology investors are evaluated using the quantum spherical fuzzy M-SWARA technique. After that, seven emerging economies are ranked based on this performance using quantum spherical fuzzy technique for order of preference by similarity to ideal solution. The main contribution is that an appropriate investor profile is identified for financial derivative investments in emerging economies. One of the important originalities of this study is the development of a new technique called M-SWARA by making some improvements to the classical stepwise weight assessment ratio analysis method. It is concluded that hedging is the most appropriate purpose for making investments in derivative products in emerging economies. It is also identified that China has the greatest performance among the seven emerging economies regarding the appropriate purpose for making derivative investments. For the effective management of this problem in these countries, it is recommended to prevent the speculative use of derivative products with legal regulations.

Abstract This research paper analyzes revenue trends in e-commerce, a sector with an annual sales volume of more than 340 billion dollars. The article evaluates, despite a scarcity of data, the effects on e-commerce development of the ubiquitous lockdowns and restriction measures introduced by most countries during the pandemic period. The analysis covers monthly data from January 1996 to February 2021. The research paper analyzes relative changes in the original time series through the autocorrelation function. The objects of this analysis are Amazon and Alibaba, as they are benchmarks in the e-commerce industry. This paper tests the shock effect on the e-commerce companies Alibaba in China and Amazon in the USA, concluding that it is weaker for companies with small market capitalizations. As a result, the effect on estimated e-trade volume in the USA was approximately 35% in 2020. Another evaluation considers fuzzy decision-making methodology. For this purpose, balanced scorecard-based open financial innovation models for the e-commerce industry are weighted with multistepwise weight assessment ratio analysis based on q-rung orthopair fuzzy sets and the golden cut. Within this framework, a detailed analysis of competitors should be made. The paper proves that this situation positively affects the development of successful financial innovation models for the e-commerce industry. Therefore, it may be possible to attract greater attention from e-commerce companies for these financial innovation products.

Abstract This study aimed to evaluate the components of a fintech ecosystem for distributed energy investments. A new decision-making model was created using multiple stepwise weight assessment ratio analysis and elimination and choice translating reality techniques based on quantum spherical fuzzy sets. First, in this model, the criteria for distributed energy investment necessities were weighted. Second, we ranked the components of the fintech ecosystem for distributed energy investments. The main contribution of this study is that appropriate strategies can be presented to design effective fintech ecosystems to increase distributed energy investments, by considering an original fuzzy decision-making model. Capacity is the most critical issue with respect to distributed energy investment necessities because it has the greatest weight (0.261). Pricing is another significant factor for this condition, with a weight of 0.254. Results of the ranking of the components of the fintech ecosystem indicate that end users are of the greatest importance for the effectiveness of this system. It is necessary to develop new techniques for the energy storage process, especially with technological developments, to prevent disruptions in energy production capacity. In addition, customers’ expectations should be considered for the development of effective and user-friendly financial products that are preferred by a wider audience. This would have a positive effect on fintech ecosystem performance.

Abstract In the last decade, the risk evaluation and the investment decision are among the most prominent issues of efficient project management. Especially, the innovative financial sources could have some specific risk appetite due to the increasing return of investment. Hence, it is important to uncover the risk factors of fintech investments and investigate the possible impacts with an integrated approach to the strategic priorities of fintech lending. Accordingly, this study aims to analyze a unique risk set and the strategic priorities of fintech lending for clean energy projects. The most important contributions to the literature can be listed as to construct an impact-direction map of risk-based strategic priorities for fintech lending in clean energy projects and to measure the possible influences by using a hybrid decision making system with golden cut and bipolar q-rung orthopair fuzzy sets. The extension of multi stepwise weight assessment ratio analysis (M-SWARA) is applied for weighting the risk factors of fintech lending. The extension of elimination and choice translating reality (ELECTRE) is employed for constructing and ranking the risk-based strategic priorities for clean energy projects. In this process, data is obtained with the evaluation of three different decision makers. The main superiority of the proposed model by comparing with the previous models in the literature is that significant improvements are made to the classical SWARA method so that a new technique is created with the name of M-SWARA. Hence, the causality analysis between the criteria can also be performed in this proposed model. The findings demonstrate that security is the most critical risk factor for fintech lending system. Moreover, volume is found as the most critical risk-based strategy for fintech lending. In this context, fintech companies need to take some precautions to effectively manage the security risk. For this purpose, the main risks to information technologies need to be clearly identified. Next, control steps should be put for these risks to be managed properly. Furthermore, it has been determined that the most appropriate strategy to increase the success of the fintech lending system is to increase the number of financiers integrated into the system. Within this framework, the platform should be secure and profitable to persuade financiers.

Abstract The purpose of the paper is to identify the factors of financial development that have the greatest impact on open innovation in 7 emerging countries. The analysis was performed featuring the MF-X-DMA method, as well as its further verification for autocorrelation and heteroscedasticity. The time period covers years from 2002 to 2020. The article states that the main indicators to improve financial development should enhance the process of bank lending and equity market development. An important area is the development of competition by providing equal access to information to all market participants in a continuously refining technical infrastructure. Regression analysis with the MF-X-DMA method confirms the statistical significance of this influence. The article fills the knowledge gap into the link between open innovations and the relatively low capitalization of the modern emerging countries’ financial market, low liquidity in small cap stocks at the financial market and concentration of the banking sector, as well as risks arising in the process of globalization. Another analysis has also been conducted by generating a novel fuzzy decision-making model. In the first stage, the determinants of open innovation-based fintech potential are weighted for the emerging economies. For this purpose, M-SWARA methodology is taken into consideration based on bipolar q-ROFSs and golden cut. The second stage of the analysis includes evaluating the emerging economies with the determinants of open innovation-based fintech potential. In this context, emerging seven countries are examined with ELECTRE methodology. It found the most significant factor is the open innovation-based fintech potential.

Abstract This study evaluates financial innovation priorities for renewable energy investors by generating a novel hybrid fuzzy decision-making model. First, SERVQUAL-based customer needs for financial innovation are weighted with decision-making trial and evaluation laboratory based on picture fuzzy sets. Second, the financial innovation priorities are ranked by technique for order preference by similarity to ideal solutions based on picture fuzzy rough sets. In this process, Theory of the solution of inventive problems-based technical characteristics for financial services, the process for innovative services, and competencies for financial innovation are considered using quality function deployment phases. In addition, the Vise Kriterijumska Optimizacija I Kompromisno Resenje method is also considered for an alternative ranking. Similarly, sensitivity analysis is also performed by considering five different cases. It is determined that the ranking priorities based on the proposed model are almost identical, demonstrating the proposed model’s validity and reliability. Assurance is the most crucial factor for the customer needs regarding the financial innovation priorities for renewable energy investors. Concerning the financial innovation priorities, the product is the essential priority for financial innovation; hence, it is recommended that companies engage qualified employees to effectively design the financial innovation for renewable energy investors. Additionally, necessary training should be given to the employees who currently work in the company, which can increase the renewable energy investors’ trust in the innovative financial products. Companies should mainly focus on the product to provide better financial innovation to attract renewable energy investors. An effectively designed financial innovation product can help solve the financing problem of renewable energy investors.

Abstract Effective crowdfunding platforms positively contribute toward improving microgrid energy management systems. Therefore, a comprehensive analysis is required to understand the key factors responsible for success in crowdfunding systems by considering various criteria. This study evaluates crowdfunding platforms for microgrid project investments. In this context, a novel fuzzy decision-making model that includes two different stages is proposed. First, the selected criteria for the crowdfunding platforms for microgrid project investments are evaluated. Second, alternatives, regarding the microgrid project investments, are ranked. In this process, a multi-stepwise weight assessment ratio analysis (M-SWARA) approach based on q-rung orthopair fuzzy sets (q-ROFSs) is considered. Intuitionistic and Pythagorean fuzzy sets are also used in the calculation process to make a comparative evaluation. Similarly, a sensitivity analysis of the ranking alternatives is also conducted with 12 different q values. All the results are rather similar; thus, the findings are reliable. Another model is also created for this purpose with the help of the decision-making trial and evaluation laboratory (DEMATEL) and the technique for order preference by similarity to ideal solution methodologies to check the performance of the proposed model. It is defined that by considering the q-ROF DEMATEL weights, the ranking results vary for different cases. The proposed model with a M-SWARA is more reliable than the model created via the DEMATEL method. This situation provides information regarding the superiority of the model proposed in this study. It is concluded that security is the most important factor in crowdfunding platforms for smart-grid project investors. Additionally, solar panels and energy storage systems/batteries are the most significant alternatives for microgrid project investors. Necessary measures should be taken to forestall the risk of fraud that may occur on this platform. Therefore, the website to be established must be secure against possible hacking attacks. Another important conclusion of this study is that solar panels should be preliminarily developed to increase the effectiveness of microgrid systems.

Abstract The purpose of this study is to provide a hybrid group decision-making approach to evaluate fintech-based financial alternatives for green energy investment projects. First, the multidimensional factors of due diligence for fintech-based financing alternatives of green energy investment projects are identified. In this regard, the balanced scorecard perspectives are considered. Next, consensus-based group decision-making analysis is performed. Second, impact-relation directions for fintech-based financing alternatives of green energy investment projects are defined. For this purpose, the spherical fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology is applied. The novelty of this study is its proposal of a new outlook to due diligence of fintech-project financing for renewable energy investments by using the group and integrated decision-making approaches with spherical fuzzy DEMATEL. The findings indicate that customer expectations are the most essential factor for the revenue sharing and rewarding models. Additionally, this study identified that organizational competency plays the most important role with respect to the peer-to-business debt model. In contrast, the conclusion was reached that financial returns have the greatest importance for the equity sharing model.

Abstract This study aims to evaluate the crowdfunding alternatives regarding new service development process pathways of clean energy investment projects. In this framework, a new model has been generated by considering the consensus-based group decision-making with incomplete preferences, Pythagorean fuzzy decision-making trial and evaluation laboratory (DEMATEL) and technique for order preference by similarity to ideal solution (TOPSIS). Moreover, a comparative evaluation has been performed with Vise Kriterijumska Optimizacija I. Kompromisno Resenje methodology and sensitivity analysis has been made by considering 4 different cases. The main contribution is to identify appropriate crowdfunding-based funding alternatives for the improvement of the clean energy investments with a novel MCDM model. By considering the iteration technique and consensus-based analysis, the missing parts in the evaluations can be completed and opposite opinion problems can be reduced. Furthermore, with the help of hybrid MCDM model by combining DEMATEL and TOPSIS, more objective results can be reached. It is concluded that the analysis results are coherent and reliable. The findings indicate that the full launch is the most significant criterion for equity and debt-based crowdfunding alternatives. On the other side, the analysis has the highest weight for reward and donation-based alternatives whereas design is the most essential item regarding the royalty-based alternative. Additionally, it is also defined that equity-based crowdfunding alternative is the most significant for the service development process of clean energy investment projects. In this way, it will be possible to provide a continuous resource for clean energy investment projects. On the other hand, by providing financing with equity, there will be no fixed financing cost for clean energy investors. If these investors make a profit, they distribute dividends with the decision of their authorized bodies.

Abstract Financial technology (Fintech) makes a significant contribution to the financial system by reducing costs, providing higher quality services and increasing customer satisfaction. Hence, new studies play an essential role to improve Fintech investments. This study evaluates Fintech-based investments of European banking services with an application of an original methodology that considers interval type-2 (IT2) fuzzy decision-making trial and evaluation laboratory and IT2 fuzzy TOPSIS models. Empirical findings are controlled for consistency by applying the VIKOR method. Moreover, we conduct a sensitivity analysis by considering six distinct cases. This study contributes to the existing literature by identifying the most important Fintech-based investment alternatives to improve the financial performance of European banks. Our empirical findings illustrate that results are coherent, reliable, and identify “competitive advantage” as the most important factor among Fintech-based determinants. Moreover, “payment and money transferring systems” are the most important Fintech-based investment alternatives. It is recommended that, among Fintech-based investments, European banks should mainly focus on payment and money transferring alternatives to attract the attention of customers and satisfy their expectations. This is also believed to have a positive impact on the ease of bank’ receivable collection. Another important point is that Fintech-based investments in money transferring systems could help to decrease costs.