Mapping AI-Driven Consumer Privacy Research Through TCCM
DOI:
https://doi.org/10.5281/zenodo.20776892Keywords:
Conspicuous consumption, digitalization, social mediaAbstract
The use of artificial intelligence in processing personal data has transformed data privacy from a technical concern into an ethical, legal, and socio-technical issue. This study systematically reviews 53 peer-reviewed articles published between 2019 and 2025 and analyzes the relationship between AI and Consumer Data Privacy using the TCCM framework. Findings show that while research spans disciplines such as psychology, information systems, law, and business, interdisciplinary synthesis remains limited. Studies address diverse contexts healthcare, finance, telecom, marketing, and culture but mainly in isolation. Dependent variables such as user trust, security, and ease of data sharing are standard, though contextual and structural factors are underexplored. Methodologically, quantitative rigor dominates, with fewer mixed or qualitative approaches. This review maps theoretical, contextual, and methodological patterns in AI–privacy research and proposes a multi-level, interdisciplinary, and context-rich agenda for future studies, contributing to both academic and practical understanding of ethical data sharing.
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