TRANSFORMATIONAL LEADERSHIP AS A CATALYST FOR BIG DATA ANALYTICS LEARNING INTENTION IN MALAYSIAN SMES: EXTENDING UTAUT WITH A MODERATION LENS

Abstract

Big Data Analytics (BDA) capability has become increasingly critical for Malaysian Small and Medium Enterprises (SMEs), yet many firms continue to face a persistent skills bottleneck where employees are hesitant or insufficiently motivated to learn analytics-related competencies. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), this study examines the determinants of BDA learning intention and investigates transformational leadership as a moderating mechanism that shapes how technology-related beliefs translate into employees’ learning motivation. Data were collected from 351 SME employees across major Malaysian regions and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) following the two-step approach. The findings indicate that UTAUT constructs significantly explain BDA learning intention, while transformational leadership strengthens key expectancy-based relationships. The results extend UTAUT by embedding leadership as a socially grounded mechanism in analytics learning contexts and offer practical insights for SME leaders seeking to accelerate data-driven capability development through leadership-enabled learning environments