Using Blockchain and AI to Track Organic Products: Challenges, Opportunities, and Consumer Willingness to Pay in South Tamil Nadu

Abstract

The nature of organic products is susceptible to the fraud and verification failure as one cannot directly observe the credence attributes of the product. A fragmented value chain and a lack of digitalisation in the emerging market environments compound the supply chain tracing sights, posing a risk to price premiums and brand loyalty. This paper explores whether traceability and AI-supported quality assurance supported by blockchain can fetch quantifiable price premises in South Tamil Nadu. The discrete choice experiment with mixed logit, latent class, and integrated choice and latent variable (ICLV) modelling is utilized on a stratified consumer sample (n = 562). The findings indicate that third-party audit and public ledger disclosure are the most priced (18.5%), then blockchain traceability (14.8%), and AI-based quality prediction (11.2%). The hybrid model indicates that transparency has positive impact on trust (g = 0.61, p < 0.001), and trust has a positive impact on utility (b = 0.29, p < 0.001), which means that willingness to pay is 26 percent (high trust) as compared to 9 percent (low trust). The paper has a value addition in that the trust is directly implemented in a valuation system, signalling theory is furthered by using verifiable digital processes, and district-level evidence is given on how digital traceability is governed in organic supply chains.