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Autores
Orientador(es)
Resumo(s)
The widespread adoption of Artificial Intelligence (AI) has transformed the social media environment
dramatically. Advertising a cornerstone of this ecosystem, has been notably influenced by AI's capacity
to personalise content, target people with pinpoint accuracy, and optimise user engagement. The aim
of this study is to investigate the impact of personalized recommendations, specifically the exploitation
of the Fear of Missing Out (FOMO) cognitive bias, on consumer purchasing behavior. I intend to study
how Amazon utilizes AI-powered algorithms to trigger FOMO and drive impulsive buying. This research
will contribute to a deeper understanding of digital addiction and the role of cognitive biases in
consumer behavior. For these analyses, a study (1 PLS-SEM) was conducted with 230 participants,
demonstrating how different consumer segments perceive and respond to personalized ads, leading
individuals to ocasional impulse purchases driven by the fear of missing out, consequently causing
regret. The present research provides an empirical contribution by increasing our knowledge of how
cognitive biases like FOMO interact with AI-driven personalized advertising to influence consumer
decision-making. Practically, the findings provide useful insights for marketers and digital platform
designers by emphasising the ethical consequences of exploiting such biases, especially when they lead
to impulsive purchases and consumer regret. These insights may guide the development of more
responsible recommendation systems and advertising strategies.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing Intelligence
Palavras-chave
Personalized Recommendations Artificial Intelligence FOMO Impulsive Buying Consumer Behavior SDG 9 - Industry, innovation and infrastructure SDG 10 - Reduced inequalities SDG 12 - Responsible production and consumption
