Unveiling civil servants' preferences: Human-machine matching vs. regulating algorithms in algorithmic decision-making——Insights from a survey experiment

Abstract

While research has explored trust in algorithmic decision-making, the factors shaping civil servants' trust perceptions remain underexamined. Using public value theory and technology adoption frameworks, this study employs a survey experiment to analyze the effects of human-machine matching and algorithm regulation on civil servants' trust and adoption inclination. The findings indicate that both factors independently influence adoption inclination, with trust perceptions mediating this relationship, but no interaction effect is observed. Addressing gaps in technology acceptance and ethical frameworks, this study highlights the importance of algorithm regulation and human-machine matching in advancing algorithmic governance and achieving public value through procedural and performance dimensions, offering practical implications for policy and governance.