Enhancing the self-efficacy-value-adoption model through smart factory adoption and digital trust

Purpose – Smart factory (SF) adoption has become a critical strategy for achieving energy efficiency and sustainable operations. While prior studies emphasize technological drivers, non-technological perspectives remain underexplored, particularly regarding adoption timing and barriers. This study aims to examine the self-efficacy value adoption model (SVAM) by incorporating digital trust (DT) as a determinant of intention to adopt a SF. Design/methodology/approach – This explanatory research applies technology adoption and self-efficacy (SE) theories, using a quantitative approach. Data were collected through a structured questionnaire distributed via Google Forms to managers and employees in technology provider companies actively engaged in SF adoption. A total of 189 valid responses were analyzed with structural equation modeling using SmartPLS 3.2.4. Findings – Results indicate that SE does not directly affect adoption intention but becomes significant when mediated by perceived value (PV). The role of Internet of Things (IoT) in influencing PV is limited, as respondents who are already technologically adept consider IoT a basic necessity rather than a differentiating factor. Moreover, gender does not moderate the relationship between DT and SE. Originality/value – This study contributes by positioning DT as a critical determinant within the SVAM, highlighting its role in shaping adoption decisions. The findings emphasize the importance of aligning managerial support and frontline employee engagement in realizing SF integration, offering both theoretical enrichment and practical guidance for industry stakeholders.