Consumer Preference for AI and Blockchain Verified Organic Products in South Tamil Nadu

DOI: https://doie.org/10.10399/ES.2026984350

Mr. S. Rakesh Kumar, Dr. R. Thangasundari

Keywords:

Blockchain traceability; Artificial intelligence; Willingness to pay; Hybrid choice model; Organic supply chains

Abstract:

Because one cannot immediately examine the product's credibility qualities, organic items are vulnerable to fraud and verification failures. Price premiums and brand loyalty are at danger due to a fragmented value chain and a lack of digitisation in developing market situations. This study investigates if blockchain-enabled AI-supported quality assurance and traceability may provide quantifiable pricing premises in South Tamil Nadu. A stratified consumer sample (n = 562) is used in the discrete choice experiment using mixed logit, latent class, and integrated choice and latent variable (ICLV) models. The results show that public ledger disclosure and third-party audit are the most expensive (18.5%), followed by blockchain traceability (14.8%) and AI-based quality prediction (11.2%). Transparency has a positive effect on trust (g = 0.61, p < 0.001) and trust has a positive effect on utility (b = 0.29, p < 0.001), according to the hybrid model. This suggests that willingness to pay is 26 percent for high trust and 9 percent for low trust. The study adds value by directly implementing the trust in a valuation system, utilising verifiable digital procedures to advance signalling theory, and providing district-level data on how digital traceability is managed in organic supply chains.

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