Pattern recognition of fnancial innovation life cycle for renewable energy investments with integer code series and multiple technology S-curves based on Q-ROF DEMATEL

The current study evaluates the fnancial innovation life cycle for renewable energy investments. A novel model is proposed that has two stages. First, the fnancial 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 fnd similar results for all fuzzy sets. Hence, the suggested model is reliable and coherent. Maturity phase 1 is the most signifcant phase of the fnancial innovation life cycle for these projects. Aging is the most important period for fnancial 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 fnancial products cannot be improved. As a result, renewable energy companies will not prefer fnancing products.