Search

Digital technologies and connectivity offer unprecedented opportunities for businesses to adapt and reinvent themselves to gain and sustain competitive advantage. Digital transformation and business model innovation have generated a large body of research in recent years due to their great practical importance. This study critically evaluates this extensive literature and aims to capture different understandings of digital business models (DBMs), identify knowledge gaps and highlight perspectives for further research. To achieve this, the literature review deductively filters out the most relevant 626 studies. For this purpose, the literature is clustered into the areas of "definition and terminology", "classification and taxonomy", "technology", "configuration, structures and processes", "drivers and determinants" and "results and impacts". The most important scientific results and approaches are discussed and corresponding implications are derived from previous research in order to summarise the most important findings and perspectives for science and practice. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) extends the limits of current performance in data processing and analysis many times over. Since this states a great improvement in managing public data, this conceptual study discusses the use of AI in public management structures in connection with their risks and side effects. The exercise of state power and public influence through intelligent machines make ethical and political guidelines essential for their operation, constituting the cornerstones of the AI framework model developed here. The organizational structure and technical specification are additional aspects of the AI that determine design and functionality of the framework model in practical application. [ABSTRACT FROM AUTHOR]