Digital Innovation in Revenue Administration Reform and Environmental Sustainability: Evidence from a Systematic Review and Meta-Analysis

Background: Many countries' government revenue systems rely on manual processes and fragmented registries, fostering tax evasion and corruption. In developing nations, the tax-to-GDP ratio averages 15 to 18 percent, significantly below the 25 to 35 percent needed for Sustainable Development Goals. While digital innovation is a primary policy response, a quantitative synthesis of its impact on revenue generation and environmental benefits is lacking. Objectives: This study aims to (i) quantify the digital innovation-revenue performance relationship across various national contexts; (ii) identify which types of innovations, income levels, and implementation conditions yield the most significant gains; and (iii) assess whether digital revenue platforms produce measurable environmental sustainability co-benefits. Method: A systematic search was conducted across eight academic databases and five institutional repositories from January 2024 to March 2026, utilizing keywords related to digital tax administration and revenue reform. Inclusion criteria adhered to the PICOS framework, emphasizing government revenue systems, technological innovations, and pre-reform baselines, covering studies from 2000 to 2026. Quality was evaluated using the Mixed Methods Appraisal Tool, and effect sizes were calculated using a random-effects model in Stata 17.0, with five moderators analyzed through mixed-effects meta-regression. Findings: Of 478 records, 56 studies from 38 countries met the criteria (N approximately 2.4 million observations). The pooled effect was r = 0.414, with data-analytics-based enforcement showing the highest effect size (r = 0.492). Upper-middle-income countries exhibited the strongest effects, challenging assumptions about digitalization's efficacy in poorer nations. Additionally, 32 percent of studies documented environmental co-benefits, particularly in VAT digitalization (r = 0.435). Significance: This meta-analysis establishes a foundational benchmark (r = 0.414) for understanding the revenue performance and environmental impacts of digital innovation in tax administration.