Research projects
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Initial situation
Dynamic growth is a challenge, especially for young companies. Especially when company structures change quickly and flexibly due to rapid growth, it is important to enable employees to participate in the change. [more]
The project "HUB Shaping data-oriented value creation sustainably - DaWeNa-HUB" is taking up the challenge of actively and sustainably shaping the digital transformation of the economy. In view of the rapidly evolving information economy, which is characterized by increasing digitalization and the need for sustainable development strategies, the project aims to rethink value creation. With a specific focus on innovative technologies such as generative AI, large-scale language models and low-code/no-code platforms, the project aims to redefine and implement value creation, in particular through the increased use of data and digital services.
Initial situation
The economy is at a turning point where technical and organizational modernization and an ecological turnaround are increasingly coming to the fore. Digitalization is creating new structural patterns and paradigms that are bringing about radical, structural changes in the way companies and administrations operate. This transformation, often described as the transition to an information economy, is challenging existing business models while opening up new opportunities for data-driven services and products. Platform-based business models and ecosystems based on extensive data analysis and digital services are becoming increasingly important.
Project goals
DaWeNa-HUB aims to create an innovation ecosystem that enables SMEs and the public sector to successfully master the digital transformation while integrating sustainable practices. By pooling the expertise from various research projects, the aim is to develop a broad spectrum of digital solutions (e.g. generative AI or low-code/no-code) and business models based on the sustainable use of data. The project aims to strengthen value chains, promote organizational resilience and support companies in redesigning their business models and adapting them to the challenges of the new economy.
Approach:
The DaWeNa-HUB will be implemented in several phases. First, a comprehensive analysis of current business processes and existing data infrastructures will be carried out. Based on these findings, the project team, consisting of scientists, industry experts and practitioners, will develop new methods and tools that will be summarized in a digital toolbox. This toolbox should enable the participating companies and public institutions to make data-driven decisions more effectively and develop new business models.
In practice, these tools are tested in the form of pilot projects with industry partners. These real-life use cases serve to test and continuously improve the practicability and efficiency of the solutions developed. Throughout the project, regular workshops and training sessions will be offered to deepen stakeholders' knowledge and skills in using the new tools.
Results and application potential
The results of the DaWeNa-HUB include not only the development of sustainable, data-based business models, but also the creation of a lasting innovation network that will endure beyond the duration of the project. The methods and tools developed will help companies to increase their efficiency, improve their competitiveness and at the same time operate in a more environmentally sustainable way. The promotion of an agile learning culture and the establishment of a participatory community will also ensure that the project results are widely applied and contribute to the general strengthening of data-oriented economic performance.
Funding
The HISS project is funded by the Federal Ministry of Education and Research (BmBF) under the project management of PTKA (Project Management Agency Karlsruhe at the Karlsruhe Institute of Technology/KIT).
Funding reference number: 02K23A001
Contact person
HISS -Hybrid Intelligence Service Support
Initial Situation
In the era of continuously increasing numbers of digital products, processes and services, the demands on high-quality IT-Support are constantly rising. This applies to small businesses as well as to large companies. Therefore,... [mehr]
AI junior research group "Hybridization of human and artificial intelligence in knowledge work (HyMeKI)
Initial Situation
Advances in the field of artificial intelligence, (especially machine learning and speech recognition), offer new design options for reorganizing knowledge work at the interface between humans and AI. AI systems not only provide potential in... [more]
The KoDaKIS project "Conception of Data-Driven AI Services", initiated in cooperation between the Chair of Information Systems at the University of Kassel under the direction of Prof. Dr. Leimeister and the Landeswohlfahrtsverband Hessen (LWV), is a groundbreaking initiative to transform the social sector through digitalization. Given the complex challenges facing the LWV - large amounts of data and complicated administrative processes - this project aims to reshape the digital landscape in the social sector to ensure efficient and people-centered services.
The importance of the project can be understood not only through the optimization of internal processes, but above all through the social added value it generates. By developing AI-based solutions that are specifically tailored to the needs and individual circumstances of service recipients, we are specifically addressing the need to simplify access to social services and increase their quality. These digital services are designed to significantly reduce processing and waiting times, which has a direct, positive impact on the quality of life of those affected.
Project goals
The KoDaKIS project aims to use artificial intelligence (AI) to develop data-driven services that make input processes more effective and thus create added value for stakeholders. Under the scientific direction of Prof. Dr. Leimeister of the University of Kassel, innovative prototypes are to be developed that optimize the data processing processes in the MASS system of the LWV. A scientifically sound concept of use cases and a feasibility study will be developed to lay the foundation for further implementations.
Approach
The project's approach is as dynamic as it is targeted. First, basic workshops are offered to introduce the potential of generative AI, combined with a careful analysis of existing processes and systems. This in-depth insight allows us to identify the specific requirements and pain points that need to be addressed. In this explorative phase, we gather valuable insights that form the basis for the subsequent development work.
Prototypes are developed in iterative loops, starting with low-fidelity versions that are gradually developed into high-fidelity prototypes. This methodical approach makes it possible to obtain continuous user feedback and adapt the prototypes accordingly. The aim is to create a product that is not only technically mature, but also keeps an eye on and optimizes the user experience.
Parallel to the technical development, a comprehensive service concept is being developed that shows how these new technologies can be integrated into the existing structures of LWV Hessen. This includes the development of a business model that not only ensures the cost-effectiveness of the solutions, but also their sustainability and scalability.
The final phase of the project is dedicated to documenting and presenting the results achieved. The research results are recorded in a detailed final report and presented to a wider audience in a concluding presentation. This documentation not only serves as proof of our achievements, but also as an important reference for future projects and as a source of inspiration for further research and development in the field of data-driven AI services.
Results and application potential
With KoDaKIS, Prof. Dr. Leimeister's chair is positioning itself at the forefront of digital transformation in the social sector by delivering innovative solutions that are both scientifically sound and practice-oriented. This project underlines the University of Kassel's commitment and ability to bring about significant change and strengthen the welfare state in a sustainable way by combining theory and practice. By developing intelligent solutions specifically tailored to the needs of the social sector, KoDaKIS demonstrates not only the feasibility of AI technologies in this area, but also their essential value for the future of the welfare state. This pioneering project thus serves as a key reference and source of inspiration for further innovations and underlines the crucial role of digitalization in promoting social justice and efficient social care.
Funding
The project is funded and supported by ANLEI Service GmbH - a subsidiary of the Landeswohlfahrtsverband Hessen (LWV).
https://www.anlei-service-gmbh.de/
Contact person
Co-creation concepts for the development of interactive learning content and videos (InLeVi)
Initial situation
Even before the pandemic, the use of videos and other learning content to support learning processes increased strongly. Due to the closure of many educational institutions, such as universities, the use of learning videos as a learning method has increased even more. In addition, the University of Kassel is pursuing...[more]
KI-BA
KI-BA – KI-basierte Business Automation für wiederkehrende Geschäftsmodelle
Initial Situation
In today’s time subscription-based business models gain significant relevance and develop across all industries, including IT, production, e-commerce and future-oriented industries like digital media, automotive... [more]
Our goal is to use AI to support learners individually in building important generic competencies in parallel with the consolidation of subject-specific content - the focus is on empathy and digital media skills [learn more].
Initial situation
Students in the Master's program of the Faculty of Business and Economics learn to solve business-relevant problems conceptually through problem-oriented modeling. However, there is often a lack of implementation skills to test these as software. For this purpose, low code development platforms are offered, which are also established in practice in companies, in order to enable laymen to develop software independently. [more]
Workload optimization for SMEs and freelancers through Predictive Matching
The volatility in the project market triggered by the Corona virus is a major challenge for SMEs: For example, many companies have to find new projects for numerous employees at the same time. The long duration of viewing, application and selection processes leads here to existence-threatening ...[more]
Small and medium-sized enterprises (SMEs) are increasingly making use of crowdsourcing. In this process, SMEs outsource certain tasks to a set of potential Internet users (crowd) by means of an open call via the Internet. The crowd takes over the processing of the tasks and submits contributions to solve them....[more]
Initial situation
The ZUKIPRO Future Center creates a practice-oriented format for consulting, qualification, testing and diffusion of digital technologies. The aim is to enable small and medium-sized enterprises to make better use of the potential of digital technologies in work and business processes through participatory work and technology design. ZuKIPro is intended to be a contact and transfer point for ...[more]
You can find the completed research projects here.