From human touch to aI-based self-service: antecedents of business users’ switching intention in government-to-business services

Governments are increasingly deploying AI-based self-service technologies (AI-based SSTs) to improve government-to-business (G2B) services, yet little is known about why business users switch from human-assisted G2B services to AI-based SSTs. Drawing on the push–pull–mooring (PPM) framework, this study examines how negative incumbent service experiences, perceived benefits of AI-based SSTs, and status quo biases jointly shape switching intention. Using survey data from 461 business users in Chinese government service agencies and PLS-SEM, we find that perceived intelligence, shaped by responsiveness, personalization, and autonomy, together with physical attractiveness, procedural fairness, and structural assurance, generates pull effects toward AI-based SSTs. Switching costs, habit, and desire for human interaction strengthen inertia, which directly reduces switching intention and weakens the effects of both push and pull factors. The study extends the PPM framework to digital government service delivery and offers guidance for reducing inertia and promoting migration to AI-enabled self-service channels.