Digital government platforms are increasingly used to integrate dispersed public services and improve coordination among public organizations. However, existing research offers limited understanding of how governments govern these platforms during their formation, especially how boundary resources develop and how they work with coordination practices to support public service innovation. To address these gaps, we integrate boundary resources and coordination research to build a theoretical lens and examine a case of a county-level digital health platform in China. Based on the data analysis, we develop a three-stage governance model to explain how governments configure boundary resources over time to govern digital government platforms. We also identify three patterns of coupling between boundary resources and coordination activities to explain how evolving boundary resources are enacted to enable different forms of public service innovation. This study contributes a temporal explanation of boundary resource evolution and clarifies the process through which governance arrangements influence public service innovation. It also offers practical insights for governments seeking to steer platform development and scale digital public services.
Research has increasingly focused on identifying and analyzing the key components of accountability in the use of artificial intelligence (AI) in the public sector. However, much of the existing literature takes a government-centric approach, emphasizing how public organizations implement accountability measures while paying limited attention to citizens' perspectives. This study addresses this gap by empirically examining whom citizens believe should be held accountable and what information about AI-based decisions should be communicated to the public. Using data from a nationally representative sample of U.S. citizens, our analysis reveals several overall trends in public perceptions of accountability for AI-based systems, as well as demographic differences. These findings provide valuable empirical insights to advance research and practice on the use of AI in government.
Lengthy public procurement processes can slow the delivery of essential public services. While most research on procurement duration has focused on infrastructure and public works, digital solutions now play a central role in how public services are delivered. This study uses survival analysis to examine the time required to award contracts, execute them, and report project delivery, drawing on 40,991 digitalization projects carried out by 7838 Italian municipalities under the Next Generation EU program. We proxy experience in procuring digital solutions with historical procurement expenditure and show that its relationship with project duration varies by solution type. Higher prior activity is associated with faster timelines for standardized connections to centrally managed platforms, but with slower timelines for cloud migration and citizen experience projects, where implementation requires more local configuration. Results for interoperability projects are inconclusive. At the median, interquartile increases in prior activity span about 118 days between citizen experience and digital notice projects, or about 22% of median completion duration. These findings challenge the common assumption that procurement experience necessarily speeds up project delivery. Prior activity may reflect both reusable organizational routines and the installed base created by earlier projects, although our data do not directly measure either mechanism. Historical procurement expenditure on digital solutions should therefore not be treated as a general indicator of readiness. Program managers should consider solution category when assessing readiness and setting or monitoring timelines.
