This study investigates the determinants of tax management effectiveness in Vietnam’s information technology (IT) enterprises. Drawing on a multi-theoretical framework, a research model was developed incorporating seven factors: cost of tax compliance, firm size and transparency, legal risk awareness, clarity of tax laws, professional competence of tax officers, digitalization of tax administration, and audit transparency and fairness. Data collected from 402 finance and tax professionals in Hanoi-based IT firms were analyzed using a hybrid structural equation modeling (SEM) and artificial neural network (ANN) approach. The SEM results confirmed that all seven factors have a significant positive impact on tax management effectiveness, with clarity of tax laws and audit transparency and fairness exhibiting the strongest path coefficients. The ANN analysis further validated these findings and provided a robust ranking of predictor importance, identifying audit transparency and fairness as the most critical determinants, followed by the cost of tax compliance and clarity of tax laws. This study underscores the paramount importance of a transparent, fair, and clear regulatory environment, complemented by digital transformation and firm-level capabilities, for enhancing tax governance. This research fills a gap in the literature by being among the first to apply a hybrid SEM-ANN methodology to this context, offering a more nuanced understanding of non-linear interactions among determinants. The findings contrast with prior studies that emphasized firm-level factors by highlighting the primacy of institutional and regulatory factors — particularly audit transparency and legal clarity — in driving sustainable tax management practices. The hybrid SEM-ANN methodology demonstrates superior capability in capturing the complex, non-linear relationships influencing tax management, offering valuable theoretical and practical implications for policymakers, tax authorities, and business leaders in Vietnam’s digital economy.