Smart information and communication technologies are finding their way into public administration. Today, there are numerous initiatives in the public sector, promising a new model for the public services: smart government. In this article, we seek to identify success factors for smart government initiatives. We provide a selected review of the current literature on the motivations, goals, and processes behind smart government so as to provide a conceptual and analytical basis for the analysis. Based on desk research, interviews, and workshops, our qualitative analysis reveals institutional (political commitment, clear governance, legal agility, digital awareness, and IT infrastructure), organizational (structure and processes, capabilities, values, and human resources), and leadership/strategy success factors that must be considered when implementing smart government initiatives. We discuss our findings and conclude by emphasizing the limitations as well as implications for praxis and future research.

Public sector innovation has become a ubiquitous theme in legislature plans and political debates. Subsequently, academia has become increasingly interested in the topic, and research on public sector innovation has grown in recent decades. Yet, research lacks a clearly conceptualised definition of public sector innovation, and a measurement framework that allows for more representative research and a comparison of results both within the public sector and with other sectors. Based on semi-structured interviews and workshops with public sector practitioners complemented by existing literature on public sector innovation, we have refined the Oslo Manual’s measurement framework that originally addresses innovation in the business sector to capture public-sector-specific requirements. The refined measurement framework gives a comprehensive and comparable set of data that researchers might collect and analyse to understand public sector innovation, and to develop and test theories. Thus, it provides a common base for future representative research.