Bridging the Eco-Label Awareness-Behavior Gap: A Meta-Analysis of Consumer Rights to Redress in Animal-Product Supply Chains
Keywords:
Animal Environment; Consumer Rights Awareness; Meta-Analysis; Eco-Labeling; Behavioral Inertia; Choice Architecture; Zootechnical Transparency.Abstract
The contemporary livestock production sector is increasingly shaped by the “sentient consumer,” whose purchasing choices reflect perceived ethical treatment of animals and the environmental footprints of production facilities. Nevertheless, a substantial contradiction remains: although global consumer surveys show strong structural recognition of animal welfare rights, the market share of certified high-welfare animal products continues to be limited. This study provides a thorough meta-analysis of the “Eco-Label Awareness-Behavior Gap.” In line with the PRISMA-MA protocol, we compiled empirical evidence across 248 independent effect sizes from peer-reviewed studies (2015–2026) to estimate the pooled global correlation between consumer awareness of rights and active ethical purchasing or efforts to seek redress. Using a random-effects model, the baseline global correlation was found to be moderate (r = 0.28, p < 0.001), thereby mathematically confirming a statistically meaningful behavioral gap. Moderator analyses by category indicated that explicitly stated, third-party audited labels are associated with a significantly higher correlation (r = 0.46) than ambiguous corporate marketing assertions such as “farm-fresh” or “natural” (r = 0.12). At the regional level, the European Union’s centralized “Farm to Fork” regulatory framework produced the strongest translation into behavior (r = 0.41) relative to more fragmented or voluntary arrangements. Overall, the results indicate that conventional disclosure-based public policy is not sufficient to overcome consumer inertia toward seeking redress. To close this gap, consumer rights frameworks need to move beyond passive information disclosure toward technologically enabled, real-time algorithmic traceability—for example, IoT-enabled blockchain networks that record ammonia thresholds, stocking densities, and access to outdoor areas at the point of sale.