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Orientador(es)
Resumo(s)
This study explores the role of artificial intelligence (AI)-based recommendations in shaping consumer responses within the context of sustainable consumption. Specifically, it examines how sustainability-oriented versus traditional chatbot recommendations influence consumer trust, purchase intention, and subjective wellbeing. Drawing on a quantitative experimental design, data were collected from 111 participants who were randomly assigned to one of two recommendation scenarios. The findings reveal that the type of recommendation does not exert a statistically significant effect on either purchase intention or subjective well-being, suggesting that sustainability framing alone may be insufficient to drive meaningful changes in consumer behavior. In contrast, trust in AI recommendations emerges as a critical determinant, significantly influencing both behavioral and emotional outcomes. Consumers who perceive AI systems as reliable and credible are more likely to report higher purchase intention and enhanced well-being. Furthermore, environmental awareness plays a significant role, positively affecting both trust and consumer responses, highlighting the importance of individual predispositions in shaping reactions to AI-driven interventions. These results contribute to the literature by challenging assumptions regarding the effectiveness of sustainabilityoriented recommendations and by reinforcing the central role of trust in human–AI interactions. From a managerial perspective, the study underscores the importance of designing transparent, reliable, and user-centered AI systems, rather than relying solely on sustainability cues to influence consumer decision-making
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Digital Marketing and Analytics
Palavras-chave
Artificial Intelligence Sustainable Consumption Consumer Trust Purchase Intention Subjective Well-Being AI Recommendations Consumer Behavior
