Publicação
AI-induced privacy concerns
| Resumo: | Purpose This study explores the factors influencing customers’ willingness to disclose personal information (WDPI) in electronic banking (e-banking), with a focus on how fear of artificial intelligence (AI) moderates these relationships. Grounded in privacy calculus theory, the research model incorporates personalization, financial literacy, satisfaction and loyalty as key predictors of WDPI. Design/methodology/approach A survey was administered to 408 e-banking users in Portugal, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). Findings Results show that personalization and loyalty have a positive impact on WDPI, while financial literacy negatively affects it. Satisfaction indirectly influences WDPI through loyalty. Fear of AI moderates two key pathways: it diminishes the positive effect of personalization and amplifies the negative impact of financial literacy on WDPI. The model accounts for 36% of the variance in WDPI. Originality/value This study advances the understanding of information disclosure in digital banking by integrating cognitive (e.g. financial literacy and personalization) and emotional (e.g. fear of AI) dimensions. It highlights how psychological responses to AI shape customer behavior, offering novel insights for e-banking service personalization strategies and privacy management. |
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| Autores principais: | de Matos, Celso Augusto |
| Outros Autores: | Rohden, Simoni F.; Lourenço Azevedo, Ana Barbara |
| Assunto: | Fear of AI Financial literacy Personalization Willingness to disclose personal information Marketing SDG 1 - No Poverty SDG 12 - Responsible Consumption and Production |
| Ano: | 2026 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| Resumo: | Purpose This study explores the factors influencing customers’ willingness to disclose personal information (WDPI) in electronic banking (e-banking), with a focus on how fear of artificial intelligence (AI) moderates these relationships. Grounded in privacy calculus theory, the research model incorporates personalization, financial literacy, satisfaction and loyalty as key predictors of WDPI. Design/methodology/approach A survey was administered to 408 e-banking users in Portugal, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). Findings Results show that personalization and loyalty have a positive impact on WDPI, while financial literacy negatively affects it. Satisfaction indirectly influences WDPI through loyalty. Fear of AI moderates two key pathways: it diminishes the positive effect of personalization and amplifies the negative impact of financial literacy on WDPI. The model accounts for 36% of the variance in WDPI. Originality/value This study advances the understanding of information disclosure in digital banking by integrating cognitive (e.g. financial literacy and personalization) and emotional (e.g. fear of AI) dimensions. It highlights how psychological responses to AI shape customer behavior, offering novel insights for e-banking service personalization strategies and privacy management. |
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