Digital Leadership and Employee Innovative Behavior: The Mediating Role of Digital Work Competence - Mukhlis (Global Research Collaboration, 2026)
Digital transformation creates a practical problem that technology investment alone cannot resolve: employees must interpret leadership direction and possess sufficient perceived competence to convert digital tools into innovative work practices. This cross-sectional study examined whether perceived digital work competence was statistically associated with the relationship between perceived digital leadership and self-reported innovative work behavior. The analysis used 250 complete questionnaires obtained through purposive mixed-mode recruitment from employees who reported routine use of workplace digital applications, at least one year of organizational tenure, and an identifiable immediate supervisor. Organization-, industry-, geographic-, invitation-denominator-, leader-, and response-mode identifiers were not retained in the available study records; the findings are therefore interpreted as associational and limited to the analyzed respondents. Partial least squares structural equation modeling in SmartPLS 3 indicated acceptable indicator loadings, internal consistency, convergent validity, and HTMT point estimates. Perceived digital leadership was positively associated with perceived digital work competence (β = .661, p < .001) and self-reported innovative work behavior (β = .429, p < .001); perceived competence was also associated with innovative behavior (β = .414, p < .001). The specific indirect association was β = .274, 95% CI [.203, .340], while the direct association remained positive. In-sample R² values were .437 for competence and .590 for innovative behavior. The results identify perceived competence as a plausible explanatory variable, not a demonstrated temporal mechanism. Tentative managerial implications favor coordinated leadership development and role-specific digital competence support, while longitudinal, multisource, and contextually identified research is required for causal and generalizable conclusions.