Work

Why artificial intelligence–based emotion monitoring in livestock matters: effects on meat quality perceptions and consumer purchase intentions

Year: 2025

Type: article

Abstract: Livestock production is under growing scrutiny for its environmental impact and concerns about animal welfare, prompting the exploration of new technologies that can boost productivity while maintaining high welfare standards. Using data from a representative U.S. sample, the paper develops and empirically tests a conceptual model in which perceived AI effectiveness in monitoring animal emotions with the aim of reducing their stress levels positively relates to consumers' purchase intentions—both directly and indirectly through perceived meat quality. We further introduce two moderating variables: perceived AI effectiveness in promoting sustainability within the livestock sector and individual concern for animal welfare. Our findings reveal that the indirect relationship between perceived AI effectiveness in monitoring animal emotions and purchase intentions through perceived meat quality is amplified among consumers who perceive AI as a valuable tool for enhancing sustainability, as well as among those with heightened concern for animal welfare. These results underscore the complex interplay between technology, ethics, and sustainability in shaping consumer behavior. From a managerial standpoint, the results emphasize the importance of transparent communication about AI-driven animal welfare and environmental improvements. Likewise, policymakers can use these insights to create frameworks that align technological innovations with consumers' ethical and sustainability expectations for meat production. • AI's perceived efficacy in monitoring animal emotions increases purchase intention for AI-monitored meat. • Perceived meat quality mediates the link between AI's perceived efficacy in monitoring animal emotions and purchase intention. • AI's perceived efficacy in enhancing livestock sustainability, and consumers' concern for animal welfare, positively moderate the observed indirect effect. • Results guide managers to use AI to boost meat quality perception and purchase intention.

Source: Food Quality and Preference

DOI: 10.1016/j.foodqual.2025.105841

Authors: Vanessa Apaolaza, Mario R. Paredes, Patrick Hartmann, Ainhize Eletxigerra

Institution: University of the Basque Country

Language: English

Topic: Meat and Animal Product Quality

Subfield: Animal Science and Zoology

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDGs: Zero hunger, Responsible consumption and production

Open Access status: hybrid

Estimated APC paid: $4,420