The aim of our research is to investigate practice-relevant questions on business information systems in a theory-based, methodologically sound manner and in close cooperation with partners in practice to develop internationally visible research results. The following main research areas are focused on:

In addition to traditional issues of IT architecture management, such as IT integration and mastering the complexity of IT landscapes, we also examine the design and management of the architecture of digital platforms. Our focus is on technical properties such as modularity, compatibility, complexity, and the resulting economic tensions.

In this research area, we are also investigating how blockchain technologies affect the design of organizations. Blockchain-based decentralized autonomous organizations (DAOs), such as Uniswap and MakerDAO, are often seen as an alternative to centrally coordinated digital platforms because in DAOs the users are often also owners and jointly shape the organization. This new type of blockchain-based organization raises numerous research questions at the interface of information technology and management. Examples include new forms of decentralized governance and IT architecture management, the use of smart contracts as a tool for IT management, or the effect of tokens to incentivize users.

Companies in numerous industries complement their offerings with digital services to benefit from economic properties, such as positive network effects, re-combinability, and the characteristic cost structure. We develop in close cooperation with practice partners recommendations for action for providers of digital services. Our focus is on developing innovative digital services, IT security management, and the design of digital innovation platforms.

The use of free internet-based services (such as Google or Facebook) is widespread. However, many of these services are only "free" at first glance - users pay with private data, which the provider companies then monetize. Therefore, from the provider's perspective, it is essential to weigh up additional revenues through (more intensive) use of the data and the potential deterrent effect of such monetization strategies on users. In this research area, we investigate the technical and organizational design of the data disclosure process. For example, we are investigating how artificial intelligence (AI) can facilitate data disclosure processes. The goal of this research focus is to develop profitable and privacy-friendly data-based business models.

The Research Training Group "Digital Platform Ecosystems" will be the University’s pivotal hub for leading-edge, international, and interdisciplinary research and advanced academic qualifications around a central phenomenon of the digital economy.

Digital platform ecosystems are both the basis for fundamentally novel data- and knowledge-intensive business models and a key phenomenon of the digital economy: AirBnB, Amazon, Uber, Google and Microsoft are well-known examples of platforms that form such digital ecosystems. The Research Training Group "Digital Platform Ecosystems (DPE) – Digital Platform-Based Value Creation and its Implications for Data Exchange, Organisation and Socio-Economic Development" seeks to address the research question of "What are the idiosyncratic characteristics of digital platform ecosystems and what are their implications for the transformation and design of economic value-creation architectures as well as for overarching socio-economic and regulatory developments?"