In our field, programming education for non-computer science students (e.g., Business Informatics, Business Administration), we can observe high diversity among our students, for example, with respect to gender differences, cultural differences, differences with respect to age, educational background, or work experience. Introductory programming courses traditionally face high drop-out rates and poor performance and students often perceive learning to program as difficult. Current research on diversity in programming education has primarily focused on gender differences, thus neglecting the influence of other diversity dimensions on students’ performance. The proposed project aims to fill this gap by first identifying how heterogeneous groups of students can be best supported. Based on our findings we will develop a didactic concept with accompanying teaching and learning material to actively support different diversity dimensions in programming education. The concept will include competence models for measuring competences and as a result support individual learning paths. Support for distance learning and flipped classroom methods will be a fundamental part of our concept. To further support a flat learning curve in university programming courses in the future, we will closely work with schools and educational centers for teachers to integrate algorithmic thinking into school curricula. We will empirically evaluate our concept using a mixed method approach, combining both qualitative and quantitative methods for data collection and analysis. In particular, we will explore the effects of our concept in our programming course and will investigate the value of these effects as perceived by lecturers and students.

Production companies still struggle transforming their shopfloor operations into digitalized, decentralized networks of cyber-physical production systems (CPPS). This is due to the high complexity of these systems, making their effective and efficient design a difficult task leading to high risk and uncertainty. A number of recent studies have identified the lack of a suitable methodology for CPPS design as a major obstacle. Recommended extensions of current systems engineering methods include:

• the integration of agile methods
• the integration of methods for stakeholder collaboration, and
• rapid and virtual prototyping

These issues have been declared in a 2018 Industry 4.0 study as “primary research needs” to be addressed by 2025, and establish the principal targets of the research proposed in DESTINY. The project follows an interdisciplinary approach that amalgamates methods from two separate disciplines: design thinking, including its foundations in the scientific study of design, and (cyber-physical) production systems. Such an approach is required as common design thinking techniques – such as collaborating and empathizing with customers/users, working in interdisciplinary teams, and rapidly producing tangible prototypes – cannot be easily mapped onto CPPS design due to its highly constrained technical environment and the different mindsets of systems engineers and design thinkers. DESTINY applies a rigorous scientific methodology to develop a framework and methods for CPPS design thinking, and to theoretically and empirically validate the results. The research will thus produce a theory and toolset for effectively and efficiently develop CPPS, helping to accelerate the digital transformation of the production industry.

The spread of COVID-19 seems to have hit Europe out of the blue. Scholars as well as practitioners are particularly interested in how health care organizations can cope with uncertainty and how they can become more resilient. Organizational resilience is the firm’s ability to anticipate trends and threats, to cope with unexpected events effectively, and to learn from those events in order to produce a dynamic capability that is directed towards facilitating organizational change (Duckek, 2014). Responding to current calls in the literature, we aim to investigate the relationship between leaders’ and organizational resilience. Such a multilevel study involves multiple relationships that are examined as part of this project. By examining health care organizations’ resilience from a multi-level perspective, we address one of “the grand challenges that confront our species” (Tourish, 2019: 21), especially since this crisis will probably not be the last global pandemic. We will also develop implications for health care practice.

Additional information can be found here.

See the German short report on the German website here., opens a file

Many problems in business decision making can be modeled as mathematical optimization problems, like mixed-integer programming problems; or satisfiability problems. Using (commercial) software packages for solving these problems, companies such as AirFrance, Amazon, Microsoft, Uber or HP apply these techniques to diverse areas like assigning flights to aircrafts, facility location, project scheduling, project portfolio optimization, network design, vehicle routing, security testing, formal verification of hardware and many others. These software packages now allow solution of problem-instances with up to millions of decision variables in reasonable time. However, the solvability often depends on the structure of the encoded problem, and from a theoretical computer science perspective, both mixed-integer programming problems and satisfiability problems belong to a family of hard problems. Moreover, with the advent of big data, the instances, which are needed to be solved are becoming lager and larger. Thus, to tackle the issues imposed by theoretical hardness and ever-increasing problem-sizes, further improvements in the solution algorithms are needed.

In the research carried out within this “seed”-project, we want to improve solution algorithms for mathematical optimization problems and satisfiability  problems, by i) hybridizing the solution algorithms and ii) transferring ideas between the different scientific domains. The researchers involved in this proposal already successfully published their first joint paper on such research, and the “seed”-project would be a great opportunity to allow to explore this promising research area further.

In this project, we aim to develop a closer understanding of the influence of religious (Christian or Muslim) and secular values on family firms (FFs) and their managerial decisions. Managerial decisions of family firms are shaped by their unique emphasis on socio-emotional wealth, i.e. distinct non-financial aspects or goals that meet the owner family’s affective needs. We focus on selected influential managerial decisions including corporate social responsibility engagements, mergers & acquisitions activities, crisis management and management control choices. Religious and secular values can be expected to either attenuate or reinforce the impact of socioemotional wealth on these managerial decisions. This project can therefore shed light on how religious and secular values shift families’ reference points and thus influence decision-making. To do so, we want to draw on interviews with members of owner families from the DACH region (Germany, Austria and Switzerland) due to its homogenous cultural background. We envisage that this project not only allows for novel insights into the under-researched question of how religion shapes managerial decisions of family firms, but also for the identification of configurations of such values and managerial choices that promise a more effective management of FFs.