Pathways toward responsible AI adoption through AI literacy and acceptance using PLS SEM fsQCA and explainable machine learning
Discover Computing, cilt.29, sa.1, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 29 Sayı: 1
- Basım Tarihi: 2026
- Doi Numarası: 10.1007/s10791-026-10313-8
- Dergi Adı: Discover Computing
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Anahtar Kelimeler: Acceptance, AI literacy, Artificial intelligence, Behavioral intentions
- Çanakkale Onsekiz Mart Üniversitesi Adresli: Evet
Özet
Artificial intelligence (AI) technologies are increasingly integrated into educational and professional environments, raising questions about how individuals responsibly engage with these systems. Although AI literacy is widely recognized as an important competence for interacting with AI, limited research has examined how its cognitive and affective dimensions relate to individuals’ intentions to adopt AI in responsible ways. This study examines the associations between affective and cognitive dimensions of AI literacy, AI acceptance, and responsible AI adoption intentions. Drawing on the Technology Acceptance Model and AI Literacy frameworks, the study considers affective AI literacy (motivation, self-efficacy, and concerns), cognitive AI literacy (knowledge and critical thinking), and AI acceptance (perceived usefulness, perceived ease of use, and ethical dimension) in relation to adoption intentions. Survey data were collected from 221 postgraduate students and analyzed using a triangulated analytical approach combining Partial Least Squares Structural Equation Modeling (PLS-SEM), fuzzy-set Qualitative Comparative Analysis (fsQCA), and Random Forest analysis. The results indicate that AI acceptance shows a positive association with behavioral intentions, while affective and cognitive dimensions are also positively related. Overall, the findings indicate that responsible AI adoption intentions are associated with configurations of affective (e.g., concerns), cognitive (e.g., critical thinking), and AI acceptance (e.g., ethical dimension) factors, with multiple pathways leading to behavioral intentions toward AI use.