A Fuzzy Multi-Criteria Framework for AI-Driven Sustainable Technology Adoption and Economic Resilience in Pharmaceutical Cold Chains

The resilience of Pharmaceutical Cold Chains (PCCs) is vital for maintaining the quality and efficacy of temperature-sensitive medications and vaccines. Considering the field of sustainable technology entrepreneurship, the strategic implementation of AI-based innovations within the logistics sector of the pharmaceutical industry is a significant economic choice with clear consequences for organizational sustainability. This study proposes a structured decision-making framework to evaluate and prioritize Artificial Intelligence (AI)-driven technologies through a comprehensive, multi-dimensional approach that enhances PCC resilience across technical, business, environmental, and social dimensions. The framework integrates advanced fuzzy Multi-Criteria Decision-Making (MCDM) methods to systematically assess technologies under uncertainty. This research develops a novel framework for decision-making that makes two main contributions. First, from a methodological perspective, it proposes a p,q -Quasirung Orthopair Fuzzy ( p,q -QOF) extension to the existing Ranking Alternatives with Weights of Criteria (RAWEC) method that incorporates a p,q -QOF Delphi-Lawshe’s Content Validity Ratio (CVR) to address high-order expert uncertainty and hesitancy. Secondly, from a substantive perspective, it presents a strategic approach to the prioritization of AI-driven technological solutions that identify predictive analytics and ML models as the most impactful solutions for enhancing the resilience of PCCs. This research thus closes the gap between fuzzy modeling theory and resource allocation for high-stakes medical logistics applications. It reveals that while technical robustness is the primary concern for technical systems, sustainability in the multi-dimensional approach to business agility and human capital development is a critical factor for resilience. The findings offer actionable economic guidance for pharmaceutical organizations navigating technology investment decisions under regulatory and operational uncertainty.