Drone Enabled Tax Monitoring, Trust in Authorities, and Voluntary Tax Compliance Intentions - Jordev Gazza Ibrahim; Daryono (Inovasi Analisis Data, 2025)
Purpose – This study presents a research model focussing on the influence of drone-enabled tax monitoring on voluntary tax compliance by integrating the enforcement power, institutional trust, and governance perceptions. Design/methodology/approach – Base on a survey-based PLS-SEM technique, the study conceptualizes how drone monitoring, transparency, regulation and privacy tenets together predict trust and compliance intentions while advancing behavioral governance arguments. Findings – The results show that the use of drone technology to monitor has a significant effect on voluntary tax compliance, and this relationship is mediated by trust in tax authorities. Factors related to governance, particularly procedural transparency and regulatory clarity, impact trust and thus indirectly compliance intentions in one direction, while privacy concerns reduce trust and cooperative intentions. Perceived risk of detection increases compliance through a direct effect but not trust, reflecting constraints on deterrence in technologized enforcement environments. Originality/value – It continues to be one of the early works that introduce drone-based surveillance into tax compliance theory empirically. It builds upon the Slippery Slope Framework; showing how new surveillance technologies, in conjunction with perceived trust, legitimacy and privacy operating conditions will condition compliance behavior. Research Implications – These findings contribute to behavioral tax research by demonstrating that technological enforcement must be institutionally embedded to maintain compliance. They stress trust as a central mediating mechanism through which digital innovation is connected to cooperative taxpayer actions, providing the groundwork for purposeful digital tax governance.