Pattern recognition of green energy innovation investments using a modified decision support system

Abstract

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.