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

Bibliographic Data

ID21284049
AuthorsYue Zhao (0000-0003-0636-7092, Emilio Aguinaldo College, corresponding author), Lijuan Gao (0000-0003-3657-3698, Wuqing District People's Hospital), Gang Wang (0000-0002-2288-3807, Emilio Aguinaldo College), Wenfa Zhang (Emilio Aguinaldo College), Hao Teng (0000-0001-6468-7073, Shandong Management University), Mei Sun (0000-0003-0276-0612, Liaoning Technical University)
Year2026
Volume265
Pages106642
Publication date2026-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueActa Psychologica (JOURNAL)
Journal identifiersISSN: 0001-6918 • E-ISSN: 1873-6297
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.actpsy.2026.106642
PMID41850082
OpenAlexW7138037647
LanguageEN
References cited45

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. • There is a high degree of heterogeneity in studies of blockchain technology - food purchase intention studies. • Future research should focus on contexts where blockchain affects consumers' purchase intentions. • Consumer trust, transparency, and gender significantly moderate the blockchain-purchase intent link. • High-quality/unfamiliar foods gain more from blockchain; consumer knowledge boosts its perceived value. • Female consumers exhibit a stronger willingness to pay for blockchain-certified foods

Blockchain · Core (optical fiber) · Food products · Food safety · Purchasing · Supply chain · Traceability · Blockchain Technology Applications and Security · Food Supply Chain Traceability · Technology Adoption and User Behaviour

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