This dissertation examines the impact of trust and transparency on purchase intent in the context of artificial intelligence (AI) and human recommendations, focusing on the online fashion industry. To do so, three primary research questions were addressed: (1) How do AI recommendations affect the willingness to buy of customers? (2) How does trust differ between humans and AI, and how does this affect purchase intent? (3) How does recommendation transparency affect trust and willingness to buy? To address these questions, a quantitative experimental study with a 2x2 design was conducted, manipulating the recommendation source and transparency levels. The results revealed no significant differences in participant9s trust or purchase intent between AI and human recommenders. However, when perceived transparency was considered, AI recommenders were trusted less than human ones. In both cases, higher levels of trust were linked to a higher willingness to buy. While actual transparency was not found to moderate trust, perceived transparency did have significant effects here. In addition, the results of the study showed that the more familiar participants were with AI, the greater their trust and willingness to buy. This dissertation has practical importance since it provides valuable insights into recommendations and AI in the online fashion industry.
Date of Award | 15 Oct 2024 |
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Original language | English |
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Awarding Institution | - Universidade Católica Portuguesa
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Supervisor | Filipa de Almeida (Supervisor) |
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- Artificial intelligence
- AI recommendations
- AI transparency
- Decision-making processes
- Online fashion industry
- Trust
- Mestrado em Gestão e Administração de Empresas
Artificial intelligence vs. human recommendations: how trust and transparency affect purchase intent in the online fashion industry
Tilly, F. A. (Student). 15 Oct 2024
Student thesis: Master's Thesis