Understanding the market potential of crypto mining with quantum mechanics and golden cut-based picture fuzzy rough sets

Abstract

Significant improvements should be made to increase the market potential of crypto mining. However, it is not financially feasible to make too many improvements because all actions lead to cost increases. In this context, it is necessary to determine the factors that most affect this process. Accordingly, the purpose of this study is to understand the main indicators to improve the market potential of crypto mining activities. Therefore, the main research question of this study is to identify which factors should be prioritized while generating appropriate strategies to increase these activities. In this context, a new model has been constructed to answer this question. First, significant indicators are identified based on the literature evaluation. After that, these factors are weighted via quantum picture fuzzy rough set-based M-SWARA. The main contribution of this study is the generation of a new decision-making model to understand the key issues related to the market potential of the crypto mining activities. The M-SWARA model is taken into consideration for criteria weighting. Owing to this issue, the causal relationships between the items can be identified. The findings demonstrate that reducing energy costs emerges as the most important factor for improving the market potential of the crypto mining industry. Furthermore, technological developments also play an important role in this regard.