Knowledge network formation for innovative study programmes in higher education
In recent years, higher education institutions (HEIs) have increasingly developed new and innovative study formats such as work-based learning, short-cycle programmes, e-learning, blended learning and massive open online courses. While studies on other research sectors have shown how network structures emerge between companies and research institutions for the purpose of generating product and process innovations (see for example Broekel and Hartog 2011, Ponds et al. 2007, Scherngell and Barber 2009), there is a lack of evidence whether such organisational innovation networks also exist for the purpose of developing new study programmes, how they are structured and what determines collaboration within these networks. In this article, we analyse a network of HEIs in the field of new study programmes and explore what determines collaboration and closeness within this network. The network we analyse consists of 52 German universities and universities of applied sciences that receive public funding for the development, evaluation and implementation of innovative study programmes of academic continuing education. Drawing on the literature on different dimensions of proximity that are known to be able to enhance interactive learning and innovation between actors and organisations in innovation networks (Boschma 2005), we analyse determinants of collaboration with discrete choice models and determinants of closeness within the network with ordered logit models. Our initial results indicate that the usually dominating influence of geographic proximity in innovation networks is very limited. On the contrary, thematic and institutional proximity appear to be important determinants of collaboration.