Will Embedding Algorithms into Performance Appraisals Influence the Configuration of Organizational Authority? Experimental Evidence from the Public Sector

Existing research has not examined how embedding algorithms into public sector performance evaluation systems influences street-level bureaucrats’perceptions of algorithmic authority and compliance tendency. Drawing on technology enactment theory, this study uses an experimental design to examine the effects of algorithm embedding degree and algorithm transparency on algorithm compliance in public performance assessment, while semi-structured interviews provide triangulation, mechanism illustration, and contextual explanation for the experimental findings. The results show that higher embedding and greater transparency significantly strengthen bureaucrats’algorithmic compliance tendency. Under high embedding and low transparency, algorithms are viewed as the core evaluative mechanism, yet unclear rules lead bureaucrats to rely on superior judgment, producing compliance with both algorithmic and leadership authority. Under low embedding and low transparency, weak algorithm dominance causes compliance to revert to leadership authority. Perceived predictability of evaluation outcomes partially mediates the relationship between algorithm embedding and compliance tendency. Overall, the study reveals how algorithm embedding influences authority-related compliance orientations and provides empirical evidence for understanding authority-related changes in public performance appraisal.