Fermatean fuzzy-based PCA CoCoSo framework to assess digital technologies in Health 4.0

During the COVID-19 pandemic, digital technologies (DTs) emerged as crucial tools to uphold healthcare services while abiding by safety protocols. However, adopting such technologies is very relevant even today, but it faces substantial challenges that demand a sophisticated selection framework. This study proposes a Fermatean fuzzy-based PCA ("principal component analysis") and CoCoSo ("combined compromise solution") framework to assess these challenges/barriers systematically. The data consisting of 4 alternatives evaluated against 24 criteria, were converted to FFS ("Fermatean fuzzy sets") in this framework, providing a mechanism for interpreting preference and non-preference degrees and enhancing decision-making. From an initial list of 24 criteria affecting the adoption of DTs, this study successfully distills them into a set of 16 criteria using PCA. These were then evaluated using the CoCoSo method, allowing a thorough, balanced analysis and providing a viable solution by striking a compromise among the conflicting criteria. This study outlines the framework's detailed execution, the ensuing vital challenges, and the methodical ordering of DTs. This novel method provides a mechanism for rationally ordering DTs based on the reduced criteria, set thereby reducing computational overhead, and comparison is performed to realize the advantages and disadvantages of the framework.