Challenges to GenAI Adoption in E-Waste Management

The transition in electronic supply chains is critical to mitigating the environmental impacts of rapidly growing e-waste. Generative artificial intelligence (GenAI) technologies offer promising capabilities to enable e-waste management practices through intelligent data integration, stakeholder coordination, and real-time decision-making. However, the adoption of these technologies faces several challenges. This study identifies and examines ten key challenges to GenAI adoption in e-waste management using expert inputs and a literature review. To analyze the complex interdependencies among these challenges, we employ an advanced Interval-Valued Fermatean Fuzzy Set (IVFFS) Decision Making Trial and Evaluation Laboratory (DEMATEL) model, enhanced by Dombi t-norm and t-conorm operations. The results reveal five causal challenges-led by fragmented product lifecycle data and poor data quality-that significantly influence the remaining…