When More Is Not Better: Bounded Policy Mixes and Digital Government Service Performance in Chinese Cities

Improving digital service performance in the public sector has become central to modernizing national governance and to advancing the United Nations’ Sustainable Development Goal (SDG) 16—effective, accountable institutions. Empirical research on digital government services remains limited, particularly on how different policy instruments shape service performance. Drawing on policy mix theory, this study introduces the concept of a bounded policy mix (BPM), referring to a policy configuration in which data governance, process re-engineering, and standardization operate within defined boundaries. It examines the effect of this three-dimensional configuration on digital government service performance (DGSP). Using panel data from 296 prefecture-level cities in China from 2018 to 2024, this study employs a city–year two-way fixed-effects model. The findings reveal that the bounded policy mix is significantly and positively associated with DGSP under both original performance measures and resource-adjusted measures. Mechanism analysis suggests that process re-engineering helps connect data governance with standardization and translate these instruments into service performance. The findings are consistent with a degree of functional complementarity among the three policy instruments. Adding platform construction to the core combination does not significantly strengthen the positive effect. These findings provide empirical evidence for understanding the performance effects of digital government policy mixes.