The role of information heterogeneity in blockchain-based traceability systems: evidence from fresh fruits buyers in China
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Blockchain technology is now being piloted to agri-food traceability systems to restore consumers’ confidence for food quality and safety. It is important for the industry to understand what information to be recorded and tracked in blockchain-based fresh produce traceability systems to meet consumers’ preferences for information. Yet little research has focused specifically on consumers’ preferences concerning information attributes traced by this new blockchain technology. This study conducts a best-worst scaling experiment with fresh fruit buyers in China to investigate consumers’ preference and perceived value regarding sixteen information attributes about blockchain-based fresh fruit traceability systems. The results from the analysis of a random parameter logit model reveal that consumers consistently rank testing information as the first-most valuable attribute, followed by production inputs (pesticides and fertilizers), quality certification and grades information attributes, while supplier and logistics information are considered to be the least valuable traceability one. Furthermore, there exist significant heterogeneity in relative value placed on traceable information attributes. The findings identify four different consumer segments by using a latent class modelling approach: (1) sensitivity for authoritative information, (2) preferences for comprehensive information, (3) information preferences equally, and (4) preferences for production inputs information. Preference heterogeneity is mainly explained by risk attitude, risk perception, information concern, traceability cognition, gender and other factors. The findings from this study can provide stakeholders and policymakers with certain insights as well as strategies on information provision and disclosure for fresh produce blockchain-based traceability.
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The role of information heterogeneity in blockchain-based traceability systems: evidence from fresh fruits buyers in China
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Blockchain technology is now being piloted to agri-food traceability systems to restore consumers’ confidence for food quality and safety. It is important for the industry to understand what information to be recorded and tracked in blockchain-based fresh produce traceability systems to meet consumers’ preferences for information. Yet little research has focused specifically on consumers’ preferences concerning information attributes traced by this new blockchain technology. This study conducts a best-worst scaling experiment with fresh fruit buyers in China to investigate consumers’ preference and perceived value regarding sixteen information attributes about blockchain-based fresh fruit traceability systems. The results from the analysis of a random parameter logit model reveal that consumers consistently rank testing information as the first-most valuable attribute, followed by production inputs (pesticides and fertilizers), quality certification and grades information attributes, while supplier and logistics information are considered to be the least valuable traceability one. Furthermore, there exist significant heterogeneity in relative value placed on traceable information attributes. The findings identify four different consumer segments by using a latent class modelling approach: (1) sensitivity for authoritative information, (2) preferences for comprehensive information, (3) information preferences equally, and (4) preferences for production inputs information. Preference heterogeneity is mainly explained by risk attitude, risk perception, information concern, traceability cognition, gender and other factors. The findings from this study can provide stakeholders and policymakers with certain insights as well as strategies on information provision and disclosure for fresh produce blockchain-based traceability.
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