Publicação
The Impact of Recommendations Agents in consumers’ purchasing decisions and satisfaction
| Resumo: | This work explores the impact of recommendation agents on consumer purchasing decisions and satisfaction. With the rise of Artificial Intelligence (AI), recommendation agents have become a significant part of consumers' daily lives, offering product suggestions based on analysis of customers' online behaviors. These agents simplify decision-making by reducing information overload and personalizing the shopping experience. The research tries to understand how RA helps consumers deal with choice overload and how it conditions the purchase decision and satisfaction of online consumers. The main results of the research show that, although we did not obtain significant results between the RA and the purchase intention and satisfaction variables, we were able to verify that the participants who had AI assistance had a lower choice overload, and a higher purchase intention and satisfaction compared to the participants who did not have AI assistance. Furthermore, the research considers the differences between maximizers and satisficers to try to understand how each group reacts to personalized recommendations and a control variable, privacy concerns, to understand if users with AI are more subject to online attacks than those without AI. The results of this study contribute to the understanding of the strategic implications of RA in online retail and offer insights for future research on this topic and on how companies can optimize their recommendation strategies to better meet consumers' needs. To obtain this insight, this thesis was developed through quantitative analytic research via an online questionnaire with 130 responses. |
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| Autores principais: | Diniz, Vasco Azevedo Mendes Fernandes |
| Assunto: | Artificial Intelligence Recommendation Agents Consumer Behavior Online Shopping Purchase Intention Satisfaction SDG 4 - Quality education |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | This work explores the impact of recommendation agents on consumer purchasing decisions and satisfaction. With the rise of Artificial Intelligence (AI), recommendation agents have become a significant part of consumers' daily lives, offering product suggestions based on analysis of customers' online behaviors. These agents simplify decision-making by reducing information overload and personalizing the shopping experience. The research tries to understand how RA helps consumers deal with choice overload and how it conditions the purchase decision and satisfaction of online consumers. The main results of the research show that, although we did not obtain significant results between the RA and the purchase intention and satisfaction variables, we were able to verify that the participants who had AI assistance had a lower choice overload, and a higher purchase intention and satisfaction compared to the participants who did not have AI assistance. Furthermore, the research considers the differences between maximizers and satisficers to try to understand how each group reacts to personalized recommendations and a control variable, privacy concerns, to understand if users with AI are more subject to online attacks than those without AI. The results of this study contribute to the understanding of the strategic implications of RA in online retail and offer insights for future research on this topic and on how companies can optimize their recommendation strategies to better meet consumers' needs. To obtain this insight, this thesis was developed through quantitative analytic research via an online questionnaire with 130 responses. |
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