This thesis aims to fill this gap by developing a decision support system for universities of applied sciences incubators. It utilizes identified critical success factors to augment its operational effectiveness and bolster its role in fostering economic growth.

Employing Design Science Research, this study combines logical reasoning with a pragmatic approach in a multi-method qualitative analysis. A semi-systematic literature review was conducted to establish a foundational knowledge base. Primary data was then gathered through expert interviews, culminating in the evaluation phase, where the generated radar chart for performance evaluation was applied and critically assessed against pre-defined success metrics.

The utility evaluation of this radar chart affirms its practical contribution to the challenge of assessing and enhancing incubator performance, exemplifying successful utility evaluation within this context. The resulting decision support system offers comprehensive support to universities of applied sciences incubators, facilitating strategic planning, enhancing decision-making processes, and providing a robust framework for data processing. Conclusively, this research advances decision-making within university incubators and presents an effective tool for visually representing performance, thereby supporting startups more effectively and enhancing their growth potential.