Resolving the Effectiveness–Efficiency Paradox in AI-Enabled Public Services: Insights From the Resource-Based View and Public Value Theory

Abstract

The integration of AI in public services creates a paradox where efficiency can undermine effectiveness, affecting service quality, citizen trust, and stakeholder satisfaction. This study addresses the dual outcomes of citizen and employee satisfaction, highlighting the moderating role of Human-AI collaboration in balancing these dimensions. Drawing on the Resource-Based View (RBV) and Perceived Value Theory (PVT), the research examines AI's impact on citizen satisfaction (effectiveness) and employee satisfaction (efficiency). Data were collected from 805 government employees and 699 citizens across multiple Indonesian public agencies over a 6-month period in 2024 and analyzed through Structural Equation Modeling (SEM). Results show that service accuracy, transparency, and trust enhance citizen satisfaction, while processing time, accessibility, and resource utilization improve employee satisfaction. Human-AI collaboration moderates the relationship between efficiency and service quality, aligning effectiveness and efficiency to achieve dual satisfaction. By addressing theoretical gaps in public administration and AI adoption, the study underscores Human-AI collaboration as a critical mechanism for integrating technological solutions with human oversight.