Digital Leadership and Business Performance in SMES: A Moderated Mediation Model Through Digital Capability and Top Management Support

Recent studies reveal inconsistent digital leadership-performance relationships in SMEs, challenging traditional direct-effect models that ‎inadequately explain transformation mechanisms in resource-constrained contexts. This study resolves theoretical inconsistencies by testing ‎a capability-mediated framework where digital capability fully mediates digital leadership-business performance relationships, with top ‎management support as a moderator. Grounded in dynamic capabilities theory, we propose that leadership operates exclusively through capability-building mechanisms contingent upon organizational support conditions. Data from 210 Indonesian food and beverage SMEs were ‎analyzed using partial least squares structural equation modeling with bootstrap procedures. The measurement model demonstrated excellent ‎psychometric properties, while the common method bias assessment confirmed the validity. Findings reveal complete mediation, with digital ‎leadership influencing performance exclusively through capability development, explaining substantial variance in organizational outcomes. ‎Large effect sizes confirm digital capability as the primary performance driver and leadership as the key capability antecedent. Top ‎management support significantly moderates the capability-performance relationship, where supportive contexts amplify returns from digital ‎investments. Results advance digital transformation theory by establishing capability-mediated pathways as primary mechanisms, moving ‎beyond traditional direct-effect models that showed inconsistent results across studies. For practitioners, SMEs should prioritize sequential ‎capability-building strategies over simultaneous technology adoption, with leadership development preceding technology acquisition to ‎maximize transformation effectiveness. This approach offers substantially higher performance returns compared to technology-first ‎strategies. Cross-sectional design limitations necessitate longitudinal replication across industries and cultural contexts to strengthen causal ‎inference‎.