A study on customers' purchase intentions and influencing factors regarding blockchain food supply chains based on meta-analysis

This study explores the impact of blockchain technology on consumers' food purchasing intentions and the factors influencing it. This study followed a meta-analysis protocol registered with PROSPERO. From 1715 screened literature records, 10 eligible studies were included (13,768 participants, 46 outcomes). The study constructed a "Signal Triggering -Cognitive Processing -Trust Transfer-Behavioral Decision" framework and used the Joanna Briggs Institute cross-sectional study appraisal tool to assess study quality. The results revealed a high degree of heterogeneity in studies on the relationship between blockchain technology and food purchase intention. The statistical methodology results regarding the correlation between blockchain technology and consumers' purchase intentions are as follows (r = 0.577, p < .001) and the results of the random-effects model (r = 0.566, 95% CI [0.520, 0.603], p < .001). Trust transfer emerged as the core mechanism driving purchase intention, with blockchain having a stronger impact on high-risk foods. Female consumers demonstrated a higher willingness to pay for blockchain-traced foods. Region and food type explained 23% and 11% of the effect size heterogeneity, respectively. Subgroup analyses and meta-regression were used to explain the reasons for the very high heterogeneity. These findings clarify the influence of blockchain on purchase intention and provide strategies for food enterprises, particularly in implementing blockchain for high-risk foods. The results offer guidance for policymakers to promote blockchain technology and establish traceability standards in regions with underdeveloped food safety systems. This study suggests that scholars explore the contextual and conditional roles of blockchain.