Decoding Food Labels in the Digital Era: Nutrition Label Literacy, AI Applications, and Sustainable Food Purchase Decisions

Abstract

Purpose: This study examines the influence of Nutrition Label Literacy (NLL) on Sustainable Food Purchase Decisions (SFPD) by investigating the mediating role of AI-Based Nutrition Applications (AINA) and the moderating role of Digital Health Literacy (DHL).

Methodology: A cross-sectional quantitative research design was employed using survey data collected from 280 Indian consumers. The proposed conceptual framework, grounded in Information Processing Theory (IPT), the Technology Acceptance Model (TAM), and the Theory of Planned Behavior (TPB), was analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM).

Findings: The results reveal that Nutrition Label Literacy significantly influences Sustainable Food Purchase Decisions (β = 0.291, p < 0.001) and positively affects the adoption of AI-Based Nutrition Applications (β = 0.657, p < 0.001). AI-Based Nutrition Applications significantly enhance Sustainable Food Purchase Decisions (β = 0.462, p < 0.001) and partially mediate the relationship between Nutrition Label Literacy and Sustainable Food Purchase Decisions. Furthermore, Digital Health Literacy significantly strengthens the effect of AI-Based Nutrition Applications on Sustainable Food Purchase Decisions (β = 0.174, p < 0.001). The proposed model explains 68.4% of the variance in Sustainable Food Purchase Decisions, indicating substantial predictive capability.

Originality: This study extends the literature by integrating nutrition label literacy, artificial intelligence, and digital health literacy into a unified framework explaining sustainable food purchasing behaviour. The findings provide theoretical insights and practical implications for policymakers, food manufacturers, retailers, and AI developers seeking to promote healthier and more sustainable food consumption.