Impact of Tax System Automation on Revenue Generation in Federal Inland Revenue Service (FIRS), Nigeria

This quantitative study rigorously investigates the impact of tax system automation on revenue mobilization, taxpayer compliance behavior, and organizational transparency within the Federal Inland Revenue Service (FIRS) of Nigeria’s Southwest zone. Drawing upon survey data from 97 randomly selected FIRS administrators, the research employs descriptive statistics and inferential techniques—simple linear regression and chi-square analysis—to test three hypotheses derived from the Technology Acceptance Model. Results reveal that increased utilization of e-filing, e-payment, ITAS, and TaxProMax platforms significantly predicts revenue generation (β = 0.243, p = 0.016) and compliance rates (β = 0.280, p = 0.005), while higher automation adoption is moderately associated with perceptions of enhanced transparency (χ²(1) = 9.112, p = 0.003; Cramer’s V = 0.306). These findings underscore that digital transformation in tax administration contributes to measurable performance gains, albeit with modest effect sizes that point to supplementary determinants such as technological infrastructure quality, user training adequacy, and regulatory support. Practical recommendations include targeted legislative amendments, infrastructure investments, capacity-building initiatives, and stakeholder-specific implementation protocols to optimize system uptime, security, and user engagement. This study extends empirical literature on e-governance and public sector innovation by providing localized evidence and a robust methodological template for future longitudinal and comparative analyses. .