Driven by Indonesia’s low tax ratio and limited enforcement resources, this study integrates fragmented academic research to address the need for evidence-based selective law enforcement policies. Unlike conventional enforcement, selective strategies are critical because they efficiently prioritize cases that maximize state revenue and compliance deterrents. The research aims to map thematic clusters and research gaps while conceptually synthesizing the effectiveness of enforcement in optimizing state revenue. Utilizing a Systematic Literature Review (SLR) guided by the PRISMA approach and bibliometric analysis of 2010–2025 publications, this study offers a novel integration of bibliometrics with evidence-based policy evaluation. Findings show a significant increase in research over the last decade, primarily focused on tax compliance, risk-based audits, and international tax avoidance. However, bibliometric mapping highlights a critical scarcity of empirical studies on selective law enforcement, Preliminary Evidence Investigations, and voluntary disclosure behavior. The synthesis demonstrates that enforcement effectiveness relies heavily on procedural design, legal certainty, taxpayers’ economic capacity, and risk-based strategies. Consequently, this study recommends developing risk-based, selective-enforcement models and expanding empirical research on taxpayer behavioral compliance in Indonesia.