This study aims to investigate the relationship between artificial intelligence (AI)-enabled perceived brand transparency and self-brand connections, examining the mediating role of social media brand trust and the moderating effects of AI-assisted digital remedy and digital learning paradox.
The study adopted a mixed-method approach combining qualitative interviews, experimental manipulation, and quantitative surveys. Study 1 conducted semi-structured interviews with 24 retail consumers, Study 2 employed a between-subjects experiment with controlled transparency manipulation, and Study 3 collected survey data from 688 retail consumers analyzed through structural equation modeling to assess the hypothesized relationships.
The results reveal that AI-enabled perceived brand transparency directly enhances self-brand connections and indirectly through social media brand trust. AI-assisted digital remedy positively moderates both the direct transparency-connection relationship and the mediated pathway through trust. Conversely, digital learning paradox negatively moderates the trust-mediated relationship, weakening the positive effects of transparency on self-brand connections.
This study extends social identity theory by positioning AI-enabled brand transparency as a critical signaling mechanism for identity construction and relationship building in resource-constrained emerging market environments. The integration of signaling theory and trust theory provides a comprehensive framework for understanding transparency-driven consumer-brand relationships in developing countries. The findings offer actionable insights for retail managers seeking to enhance consumer engagement through strategic AI-enabled transparency initiatives in emerging markets.
