Publicação
AI vs Non-AI Tools in the Skincare Market: A Study on Consumer Trust, Enjoyment and Loyalty
| Resumo: | This thesis examines the impact of AI-driven personalization on consumer satisfaction and brand loyalty within the skincare industry. Employing a quantitative experimental design, participants were randomly assigned to interact with either an AI-assisted or a human-assisted recommendation scenario. The study investigated the mediating roles of trust, enjoyment, and perceived personalization in the relationship between the recommendation approach and key consumer outcomes, as well as the moderating effect of familiarity with AI. Results indicate that while AI-driven tools significantly reduced perceptions of trust, enjoyment, and personalization, only enjoyment emerged as a consistent mediator influencing both satisfaction and brand loyalty. In contrast, trust and perceived personalization did not reliably mediate these relationships, suggesting that the presence of AI alone does not guarantee improved consumer outcomes. Furthermore, the direct effects of the recommendation approach on satisfaction and brand loyalty were significant, yet the overall total effects were undermined by competing indirect influences. These findings highlight that merely implementing AI is insufficient; the design and presentation of AI interfaces must be tailored to evoke positive affective responses and ensure clarity in personalization. From a managerial perspective, these insights call for strategic enhancements in AI-driven customer experiences through increased interactivity and emotional engagement. The study contributes to the academic discourse by challenging prevailing assumptions regarding AI’s automatic benefits and by underscoring the necessity of aligning technological innovations with consumer expectations in the highly personalized context of skincare. |
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| Autores principais: | Silva, Mafalda |
| Assunto: | Artificial Intelligence Personalization Consumer Behavior Brand Loyalty Skin Care SDG 3 - Good health and well-being SDG 9 - Industry, innovation and infrastructure SDG 12 - Responsible production and consumption |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso embargado |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | This thesis examines the impact of AI-driven personalization on consumer satisfaction and brand loyalty within the skincare industry. Employing a quantitative experimental design, participants were randomly assigned to interact with either an AI-assisted or a human-assisted recommendation scenario. The study investigated the mediating roles of trust, enjoyment, and perceived personalization in the relationship between the recommendation approach and key consumer outcomes, as well as the moderating effect of familiarity with AI. Results indicate that while AI-driven tools significantly reduced perceptions of trust, enjoyment, and personalization, only enjoyment emerged as a consistent mediator influencing both satisfaction and brand loyalty. In contrast, trust and perceived personalization did not reliably mediate these relationships, suggesting that the presence of AI alone does not guarantee improved consumer outcomes. Furthermore, the direct effects of the recommendation approach on satisfaction and brand loyalty were significant, yet the overall total effects were undermined by competing indirect influences. These findings highlight that merely implementing AI is insufficient; the design and presentation of AI interfaces must be tailored to evoke positive affective responses and ensure clarity in personalization. From a managerial perspective, these insights call for strategic enhancements in AI-driven customer experiences through increased interactivity and emotional engagement. The study contributes to the academic discourse by challenging prevailing assumptions regarding AI’s automatic benefits and by underscoring the necessity of aligning technological innovations with consumer expectations in the highly personalized context of skincare. |
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