The growing digitalisation of public administration and the increasing number of countries affected by armed conflicts raise important questions about the role of e-government in sustaining government revenue mobilisation under institutional stress. This study examines how the development of digital government influences different sources of public revenue and whether armed conflict moderates this relationship across countries. The analysis uses cross-country panel data for 2003–2024, combining indicators of e-government development from the UN EGDI database, fiscal indicators from the World Bank Open Data, and conflict information from the UCDP/PRIO Armed Conflict Dataset, estimated using two-way fixed effects models with robust clustered standard errors. The results show that economic development is the strongest determinant of revenue mobilisation, with GDP per capita coefficients ranging from 0.95 to 1.22 across models. The overall EGDI does not demonstrate a statistically significant direct effect on tax revenue or revenue excluding grants, although weak interaction effects suggest that armed conflict may reduce the fiscal effectiveness of digital governance (−0.238; p ≈ 0.10). A significant negative relationship is observed for the telecommunications infrastructure component with tax revenue (−0.362; p = 0.005) and revenue excluding grants (−0.349; p = 0.011). For customs duties and social contributions, the results indicate no systematic relationship between e-government development and revenue performance, highlighting the dominant role of macroeconomic conditions in shaping fiscal capacity.

Digital transformation of the public sector is increasingly relevant because it can reshape the costs firms face in finance, logistics, and cross-border service provision. This study investigates how e-government development and its human-capital, online-service, and telecommunication components influence interest rate spread distortions, logistics performance, and services trade restrictiveness across countries, and whether these effects are linear or non-linear. The analysis uses three unbalanced country panels covering 1,299 observations for 130 countries, 906 observations for 163 countries, and 306 observations for 51 countries, estimated with two-way fixed-effects models and Driscoll–Kraay standard errors, with robustness checks and quadratic specifications implemented in R. The results show that a 0.1-point increase in EGDI is associated with an approximately 0.45-point reduction in the absolute interest rate spread, while the robustness coefficient remains negative at-0.677. Human capital and telecommunication infrastructure are especially important in this dimension, with baseline coefficients of-3.921 and-1.910, respectively. In the logistics specification, aggregate EGDI is insignificant, but HCI is positive and significant (β = 0.372), and a 0.1-point increase in HCI raises the Logistics Performance Index by about 0.037 points. In the services-trade specification, EGDI reduces STRI by-0.095. At the same time, HCI shows a U-shaped effect with a turning point at 0.975, indicating that digital human capital lowers restrictiveness up to very high levels before the relationship turns upward.

GovTech has become a key driver of societal transformation, yet its impact on human well-being and social progress remains complex and potentially non-linear. This study aims to examine how GovTech development, as a “Technological – Institutional – Human” system, shapes social progress by identifying its mechanisms, non-linear dynamics, and structural conditions. The analysis is based on a panel dataset of 1,964 observations for 2003–2024, employing two-way fixed-effects models with Driscoll–Kraay standard errors and non-linear specifications. The results show that the aggregate EGDI has a positive and significant effect on social progress, even after controlling for time effects (β = 3.37, p = 0.036). A non-linear relationship is identified, with a turning point at approximately 0.61, indicating diminishing returns at higher levels of digital development. Component-level analysis reveals that telecommunications infrastructure has the strongest impact (β = 14.09, p < 0.001), followed by online services (β = 4.16, p = 0.002), while human capital exhibits a threshold effect (turning point ≈ 0.26). Additionally, social progress increased steadily until 2020 (β ≈ 6.10) but declined in 2022 (β = 3.04), reflecting global shocks.