Deep tech innovations and emerging competitors are putting increasing pressure on established companies to defend their competitive position in globalized markets. With the aim of efficiently generating deep tech innovations through access to deep technologies and thus ensuring growth, corporates are increasingly entering into collaborations with deep tech startups. For their part, deep tech startups are seeking access to complementary competencies in collaborations with corporates. However, due to their differences in practice both partners often lack an understanding of transferable competencies and resources, e.g., deep technologies, competencies and resources. In the context of this work, a model to characterize and identify the potentials for complementary transfer of competencies from corporates and startups within a collaboration is elaborated. Based on an organization-theoretical delimitation of the collaboration partners, a morphology is developed that characterizes suitable groups and dimensions for the identification of competencies and resources. For this purpose, existing approaches for the exchange of competencies in collaborations are analysed and the deficits in relation to deep tech startups are discussed. Based on this, superordinate groups are derived that consider the specific characteristics of corporates and startups. The morphology enables the description of the competencies and resources within a collaboration between corporates and deep tech startups.