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Orientador(es)
Resumo(s)
This study investigates the impact of AI-based recommendation systems on consumer
behavior in B2B retail environments, with a specific focus on satisfaction and purchase
intention. As artificial intelligence becomes increasingly integrated into business decisionmaking, understanding its perceived value compared to traditional sales approaches is
essential. The study was conducted through a survey of 155 respondents from a local food
retail chain in Portugal, including franchisees and central structure employees. Using a
conceptual framework supported by established theories of trust, personalization and
technology adoption, the study tested the direct influence of AI-based recommendations on
satisfaction and purchase intention, as well as the mediating roles of perceived
trustworthiness, competence and personalization. A moderation analysis was also conducted
to assess the impact of buyer experience on these relationships. The results indicate that AIbased recommendations significantly increase satisfaction and purchase intention, with
strong mediating effects of the identified trust-related variables. However, buyer experience
did not significantly moderate these effects. These findings contribute to the theoretical
understanding of AI in B2B marketing and provide practical insights for companies considering
hybrid human-AI strategies. The study highlights the growing role of AI as a reliability,
competent and personalized advisor in retail decision-making and paves the way for future
research on ethical considerations and industry-specific applications of AI.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing Intelligence
Palavras-chave
B2B Retail Consumer Behavior Artificial Intelligence Recommendation Systems Satisfaction Purchase Intention SDG 8 - Decent work and economic growth SDG 17 - Partnerships for the goals
