Optimizing cloud resource utilization in the digital economy: An integrated Pythagorean fuzzy-based decision-making approach

Abstract

The digital economy has experienced an unheard-of surge in the twenty-first century, revolutionizing how businesses run, societies function, and people interact. The utilization of cutting-edge technologies to optimize resources and streamline operations has become crucial with the changing digital landscape. Cloud computing has become a potential enabler in this transformative era, providing a flexible and scalable solution that meets the needs of the rapidly growing digital ecosystem. This study aims a novel PF-DNMA-SWARA method that amalgamates Stepwise Weight Assessment Ratio Analysis (SWARA) and double normalization-based multiple aggregation (DNMA) constructed on Pythagorean Fuzzy Sets (PFSs) to identify potential barriers to efficient cloud resource utilization for large-scale implementation in the digital economy. The results of this study uncovered a compelling narrative that emphasized the developed approach’s unique advantages in terms of its capacity to function naturally within the context of PFSs. The method offered a more complex and finely tuned evaluation framework by utilizing the inherent flexibility and interpretability of PFSs. This factor is of utmost importance, especially in complex situations where there are many uncertainties and imprecisions, making it impossible for conventional methods to accurately capture the nuances of real-world resource utilization dynamics.