This research advances supply chain management scholarship by exploring the individual-level cognitive drivers influencing blockchain adoption among upstream and downstream supply chain actors. Leveraging the Three Arenas Model and integrating Institutional Isomorphism with the mental model theory, we conducted 34 in-depth, semi-structured interviews complemented by Fuzzy Cognitive Mapping (FCM) to capture detailed perceptual frameworks. Using thematic analysis via Atlas.ti, our findings indicate clear motivational distinctions: upstream actors (e.g., producers) predominantly seek enhanced transparency and traceability to optimize operational efficiency, while downstream actors (e.g., end users) emphasize trust and reputational capital to strengthen market confidence. Our study highlights that these contrasting cognitive schemas require differentiated strategic approaches for successful blockchain integration. By linking micro-level cognitive processes with institutional pressures, this research enriches theoretical perspectives on technology adoption within supply chain contexts and provides actionable insights for practitioners and policymakers to customize adoption strategies, regulatory frameworks, and stakeholder engagement practices for maximum effectiveness.

This study investigates the motivations behind blockchain adoption in supply chains, revealing through interviews and Fuzzy Cognitive Mapping that producers prioritize transparency and traceability for efficiency and compliance, while end-users value trust and reputation to enhance brand credibility. By identifying these drivers, the research enables businesses to develop targeted strategies and policymakers to craft supportive regulations, fostering more transparent and ethical supply chains in industries like food and fashion. Key takeaways include the need for tailored blockchain strategies to address distinct stakeholder priorities and industry-specific regulations to facilitate adoption.