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Impact of AI Recommendations’ transparency in E-Commerce: Understanding the impact of covert and overt personalization
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| 1.29 MB | Adobe PDF |
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Orientador(es)
Resumo(s)
With the increasing usage of Artificial Intelligence in marketing and e-commerce, techniques
such as product recommendations have been enhanced through usage of consumers’
behavior and preferences to optimize their efficiency. While this has many benefits, it also
raises concerns over data privacy and usage. This study addresses a gap in the current
literature by examining how the transparency of AI recommendations - defined as overt and
covert - affects perceived benefits and privacy concerns, and how these effects may vary
depending on the customer journey stage that the recommendation is made. The research
was based on a 2x2 between-subjects experimental design with transparency (overt vs covert)
and customer journey stage (pre-purchase vs post-purchase) as the two manipulated factors.
The results indicate that transparency alone does not have a significant impact on perceived
benefits or privacy concerns, refuting some assumptions in previous research. However,
higher perceived benefits were associated with lower privacy concerns. Additionally, the
impact of transparency on perceived benefits was significant in the pre-purchase phase, but
not in the post-purchase phase. These findings offer a new look that connects transparency
and timing in the context of recommendations in e-commerce, while expanding the existing
literature to the realm of AI-generated recommendations.
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
Personalization Recommendation Artificial Intelligence Privacy Concerns Perceived Benefits SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure