Consumer adoption of food blockchain traceability: insights from integrating TAM and TR models

The primary application of blockchain technology in the food supply chain is the development of a food traceability system that enhances transparency and accountability. The adoption of food blockchain traceability systems depends on consumer engagement and support at retail endpoints. This study integrates the Technology Acceptance Model (TAM) and Technology Readiness (TR) to explore consumer adoption behavior. A survey was conducted with 322 supermarket consumers in Shenzhen, and data were analyzed using Structural Equation Modeling (SEM) and hierarchical multiple regression analysis. The findings suggest that the extended TAM framework effectively predicts consumer adoption attitudes and intentions towards blockchain traceability systems. Perceived ease of use and perceived usefulness are significant factors influencing adoption attitude, which in turn strongly predicts adoption intention. Furthermore, positive dimensions of TR, such as optimism and innovativeness, significantly moderate the TAM model, whereas negative dimensions, such as discomfort and insecurity, show no significant moderating effects. These insights provide valuable recommendations for food and retail enterprises to facilitate blockchain adoption and expand its application within the food industry.