Qualitative comparative analysis reveals factors influencing adoption of blockchain traceability in food enterprises, indicating pathways for effective implementation.
Amid growing public concerns over food safety, blockchain-based traceability systems have emerged as a transformative solution. However, their widespread implementation critically depends on organizational adoption willingness. This study bridges a significant research gap by investigating the multidimensional drivers of adoption behavior through an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model, incorporating enterprise-specific variables—informational motivation, perceived risk, perceived cost, and system compatibility. Employing qualitative comparative analysis (QCA) on rigorously validated survey data from 603 food enterprises, we identify five distinct high-adoption pathways. Our findings demonstrate that adoption decisions result from synergistic interactions of multiple factors rather than isolated conditions, revealing three dominant adoption logics: (1) external pressure-driven, (2) internal value-driven, and (3) contradiction-balancing. The study makes dual contributions: theoretically, it advances technology adoption literature by developing a context-specific framework; practically, it offers actionable insights for promoting blockchain implementation—including multifactor synergy optimization, targeted intervention strategies for heterogeneous enterprises, risk-cost expectation management, and compatibility enhancement to reduce adoption barriers.
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Zhang et al. (2025) studied this question.
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