Nexus of E-government, cybersecurity and corruption on public service (PSS) sustainability in Asian economies using fixed-effect and random forest algorithm

E-government development (EGD) is vital in enhancing the institutional quality and sustainable public service (SPS) delivery by eradicating corruption and cybersecurity crimes.

The present study applied econometric fixed-effect (FE) regression analysis and random forest (RF) algorithm through machine learning for comprehensive estimations in achieving SPS. This study gauges the nexus between the EGD as an independent variable and public service sustainability (PSS) as a proxy of public health services as a dependent variable in the presence of two moderators, corruption and cybersecurity indices from 47 Asian countries economies from 2015 to 2019.

The computational estimation and econometric findings show that EGD quality has improved with time in Asia and substantially promoted PSS. It further explores that exercising corruption control measures and introducing sound cybersecurity initiatives enhance PSS's quality and support the EDG effect much better.

The study concludes that E-Government has positively impacted PSS (healthcare) in Asia while controlling cybersecurity and institutional malfunctioning made an E-Government system healthier and SPS development in Asia.

This study added a novel contribution to existing E-Government and public services literature by comprehensively applied FE regression and RF algorithm analysis. Moreover, E-Government and cybersecurity improvement also has taken under consideration for PSS in Asian economies.