Information Systems

Research area
The IS group operates within the general area of business information systems. Its research focuses on the design, optimization and computer-aided support of operational processes within and between organizations through business process engineering. The group studies implications for information systems, information system design, governance and decision support. The research focus includes design methods, analysis tools, information system architectures, data mining and intelligent systems development using advanced prototypes. The approach is modelcentric and engineering-oriented, integrating basic and applied research with contemporary realworld cases.

The IS group distinguishes two research lines:

  1. Business Process Management (leader: Grefen). This research line is devoted to the investigation and development of new concepts, models, techniques and application scenarios for the management of and information exchange in operational business processes. The research line covers the entire spectrum from process-oriented business model conception to business process execution in advanced information system infrastructures. Developing theory-based connections between elements in this spectrum is a major focus, such as engineering business models into business processes, mapping business processes onto system architectures, designing information models into decision structures and providing integration with elements in the business process intelligence research line. A close connection with industry cases in logistics, mobility services, hightech manufacturing and healthcare is a key factor in this line of research in order to maintain a solid balance between theory advancement (scientific rigor) and practical application (industrial relevance), founded on design science research methodology.
  2. Business Process Intelligence (leader: Kaymak). This research line is aimed at the development of methods, techniques and tools for advanced analysis of business processes and optimal decision making in their execution. Data mining, process mining, machine learning and computational intelligence methods are applied for building consistent models that make use of different modalities of data from multiple sources. These approaches can be used to design information system architecture for developing intelligent decision support with which organizations can fulfil their goals of operational excellence and improved decision making. Special focus is on computational intelligence methods for decision models in which qualitative, linguistic information can be combined with quantitative, numerical information from data. The practical relevance of the resulting context-aware, adaptive decision support systems are studied in industry cases from e-commerce, logistics and healthcare.

The IS group’s research is structured in an open, topic-oriented, dynamic cluster. This group is part of a strong international research and industry network, in which it participates in multiple European projects and organizes international conferences and workshops. The group also participates in TU/e’s Data Science Centre and flagship project programs.

Contribution to the School
Information systems are vital for the design and control of successful operational processes.

The IS group contributes to the School IE through its research in this key area. There is project collaboration with other groups within the School on topics at the interface of multiple expertise areas. The group’s research fits naturally with the Department IE&IS “value of big data” research theme. The interplay between information systems and logistics is explored within the “logistics with its interfaces” research theme together with the OPAC group. The IS group also collaborateof innovation and transitions by conducting theoretical as well as qualitative and quantitative research. We do so by building our research on a combination of theoretical perspectives, including evolutionary economics and STS, and by looking at the historical, institutional, legal and user perspectives. In the past six years, the TIS group has made significant contributions to theory development and refinement (notable strategic niche management and multi-level perspective), as well as qualitative and quantitative research in the area of innovation and transitions. The involvement of societal groups and end users has been key in many of our studies, and has also resulted in new research methodologies and approaches. We have also contributed to policy development, for instance through Transition Management. For the coming years, our aim is to further build the link with technology (smart energy systems, mobility, etc.) and to apply our theoretical foundations to address sustainability challenges and creating appropriate governance / policy.

More information about the Information Systems Group can be found at their website.