This study empirically examines how information technology (IT) governance and digital financial transformation interact to influence economic sustainability performance. The research instrument used in the current study is a questionnaire survey. The data were collected from different government authorities in Oman. The study used convenience and snowball sampling to collect the data. Online questionnaire platforms, such as Google Forms, were used to collect data for the current study. The data collected for the current study were from 104 respondents. The results indicate that IT governance has a significant positive effect on digital financial transformation. Further, digital financial transformation has effectively and significantly enhanced the level of economic sustainability performance. However, IT governance does not have a direct effect on economic sustainability performance; rather, it has an indirect effect on economic sustainability performance through the mediating effect of digital financial transformation. These findings provide actionable implications for policymakers and practitioners to enhance awareness and integration of governance across different aspects in the context of digital financial transformation. The present study contributes to the literature and offers a unique perspective to the existing body of knowledge by highlighting the importance of IT governance as a key driver for digital financial transformation and economic sustainability performance.

Environmental, social, and governance (ESG) disclosure quality remains constrained by fragmented data, limited verifiability, and inconsistent reporting practices. This study examines whether artificial intelligence and blockchain are associated with perceived ESG disclosure quality and whether financial regulation conditions the artificial intelligence relationship while stakeholder engagement conditions the blockchain relationship. A cross-sectional survey produced 250 usable responses from professionals involved in finance, sustainability reporting, compliance, and corporate governance. Partial least squares structural equation modeling was conducted using SmartPLS 3. Artificial intelligence (β = 0.297, p < 0.001), blockchain (β = 0.142, p = 0.001), financial regulation (β = 0.190, p = 0.008), and stakeholder engagement (β = 0.340, p < 0.001) showed positive direct associations with ESG disclosure quality. Financial regulation positively moderated the relationship between artificial intelligence and ESG disclosure quality (β = 0.069, p = 0.020). The blockchain–stakeholder engagement interaction was not supported because its bias-corrected confidence interval included zero. The model explained 86.6% of the variance in ESG disclosure quality (R² = 0.866), while blindfolding indicated positive predictive relevance (Q² = 0.613). However, elevated construct-level collinearity and HTMT values require caution in interpreting the structural effects.