In order to ensure the long-term competitiveness of the German economy, start-ups are becoming increasingly important as drivers of innovation, especially in the face of socio-ecological challenges. The potential, which exists in particular in the technology and knowledge-intensive sector, and through outstanding universities and research institutions, has not yet been exhausted. Therefore, it is essential to create and improve start-up-promoting framework conditions. However, the effectiveness of these improvement measures cannot always be clearly predicted due to a lack of data and the complexity and interrelationships of various determinants.
- Start-ups gain importance as innovation drivers
- Start-up potential not yet fully utilized, especially by universities
- Creating and improving framework conditions conducive to start-ups essential
- Effectiveness of measures not always clearly predictable (lack of data, complexity, interrelationships)
Practical concepts for decision-makers in the state will be obtained from a systematically research-based monitoring of start-up funding measures in the state. A monitoring system will be developed that provides continuous science-based feedback on the effectiveness of measures.
- Systematic science-based monitoring of start-up support measures of the state
- Development of practice-relevant concepts for decision-makers in the country
- Development of a monitoring system
- Continuous scientifically based feedback on the effectiveness of policies
To design this monitoring system, the first objective is to analyze the current state of the country’s entrepreneurship transformation. Following this, an evaluation model is to be developed which makes measures and their effectiveness empirically assessable in order to use available resources in a more targeted manner in the future. In this way, recommendations for action can be made to accelerate the entrepreneurship transformation of the country more effectively.
- Analysis of the current state of the country’s entrepreneurship transformation
- Make measures and their effectiveness empirically assessable with the help of the evaluation model
- Make more targeted use of available resources in the future
- Recommendations for action to accelerate entrepreneurship transformation based on research findings.