Abstract: It is of key importance to identify innovative business ideas in an early stage, so that funding resources can be adequately allocated according to their economic potential. Traditional indicators do not reliably discriminate business ideas with high degree of innovativeness and high incorporation chances from those with low degree of innovativeness and low incorporation prospects. Therefore, this paper examines the content of business idea descriptions to improve the estimations of the incorporation probability. The paper aims to answer two questions: 1) Are there differences in topic prevalence in innovative and non-innovative business ideas?, and 2) How does the composition of topics related to a business idea influence its incorporation probability? Structural topic modeling and classification tree analysis are applied on business idea descriptions from a competition in Bremen, Germany, from 2003 until 2019. The results show that business idea descriptions are a rich source of information to identify both innovative ideas and those with higher incorporation prospects.
