Clustering based on Preferences with K-modes using Categorical Variables

In a globalized market environment with continuously changing conditions and customer requirements, international and cross-border co-operations gain an increasing importance for different actors in order to establish adequate networks. This can highly contribute to the sustainable, more effective operation of market actors in the long-run that can even become more resilient in case of turbulent events. 51 actors of the Central European region with different organisational types were selected and their preferences were asked in a survey about their interests regarding up-to-date technologies in which they would like to work together with other partners and they were ready to broaden the limits of their present knowledge. In this paper, based on the received answers a clustering of the members is performed with the K-modes algorithm and a well-interpretable profiling of the resulted groups is provided, which may serve as a tool to assist more beneficial network formations within the Central European region.