Administrative burden reducing in China: The digital administration reform and government–business interaction
Chun Zhang & Liao Fu
Abstract
The digital reform is a special government reform being undertaken in China, and digital administration is a key part. Administrative burden theory has largely been applied to citizen–state interactions in welfare regimes, yet its implications for firms in transitional economies remain underexplored. This paper extends the theory by distinguishing between a subjective administrative burden and an objective administrative burden. Using survey data from Chinese private enterprise, the authors employ matching and multiple variables ordinary least squares regression. The authors find that digital administration significantly reduces burden. To address endogeneity and reverse causality, the analysis employs propensity score matching. Robust results across matching estimators confirm the estimation. The digital administration reform extends beyond China's domestic reform landscape, offering valuable insights into the broader discourse on government enterprise interaction. This paper provides a framework for reconciling disparate findings and guiding future research across diverse policy domains. Points for practitioners The expanded adoption of digital administrative tools delivers clear and immediate reductions in the administrative burden. Evidence from this study indicates that online service portals, electronic approval systems and process visualization mechanisms substantially diminish uncertainty, information search costs and time spent navigating administrative procedures, thereby strengthening confidence in regulatory interactions. Building on these foundations, the integration of artificial intelligence (AI) technologies further amplifies the burden-reducing effects of digital governance. Through generative AI, intelligent query systems, automated document processing and predictive workflow assistance, governments can provide more timely, precise and tailored policy guidance, effectively mitigating the informational pressures generated by regulatory complexity. Such AI-enabled digital government services not only enhance the experiential quality of administrative interactions but also generate data-driven feedback for continuous process improvement, fostering more efficient and responsive state–business relations.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.