Behavioral Drivers of Digital Innovation in Vietnamese Import-Export Enterprises
Abstract
Background: Digital transformation is reshaping global business ecosystems; however, Vietnamese import-export enterprises often struggle to align technological adoption with behavioral and organizational enablers such as culture and leadership. Objective: Grounded in the organizational learning theory and the behavioral agency theory, this study examines how digital transformation translates into business model innovation through behavioral mechanisms. By linking technology, culture, and leadership, the research addresses the gap in understanding internal drivers of innovation within emerging market contexts. Design and Methodology: A mixed-method design was employed. Qualitative interviews with five experts refined the behavioral constructs, followed by a survey of 148 import–export enterprises. PLS-SEM was used to test the hypothesized relationships, while multigroup analysis explored firm-level differences. Results: Digital transformation positively affects business model innovation (β = .29, p < .001) and digital culture (β = .69, p < .001). Digital culture strongly mediates the relationship (β = .32, p < .001), while digital leadership moderates it (β = .17, p = .01). The model explains 62% of the variance in business model innovation (R² = .62). No significant differences were found in the structural relationships among constructs based on various enterprise characteristics. Conclusion and Implications: Findings highlight that digital transformation outcomes depend on behavioral change processes rather than technology alone. Managers should cultivate organizational learning, foster shared cognitive frames, and strengthen leadership signaling to align human decision-making with strategic digital initiatives.
Fields of Study & Subjects
Digital Innovation in Industries
Corporate Management and Leadership
Innovation and Knowledge Management
Publication details
- Journal / source
- The Journal of Behavioral Science
- Volume
- 21
- Issue
- 1
- Pages
- 88–104
- Publication date
- 31 January 2026
- Language
- EN