02/26/15

Publication on co-evolution of proximities


My paper „The co-evolution of proximities – a network level study“ has been published in Regional Studies. It can be downloaded here.

Abstract:

Theco-evolution of proximities – a network level study, Regional Studies. Little isknownabouthownetwork structures and proximity relations between linked actors evolve over time. This paper argues that a number of networks’ internal proximity structures are interrelated, which may give rise to specific types of co-evolution dynamics. An empirical investigation tests these arguments using information on the evolution of 280 networks of subsidized research and development (R&D) collaboration in Germany. The empirical findings clearly confirm the existence of systematic and dynamic interrelatedness between proximities. In this way, the paper underlines the need to consider such relations when investigating the evolution of knowledge networks.

12/18/14

New working paper on regional innovation systems and networks

Schnappschuss (2014-12-18 21.38.15)A new working paper is out! The title is „Network Structures in Regional Innovation Systems“ and it is co-authored by Jêromé Stuck and Javier Revilla Diez. It can be downloaded here.

Abstract: While interactive learning and inter-organisational relations are fundamental building blocks in RIS theory, the framework is rarely related to investigations of regional knowledge network structures, because in RIS literature relational structures and interaction networks are discussed in a rather fuzzy and generic manner with the ‘network term’ often being used rather metaphorically.

This paper contributes to the literature by discussing theoretical arguments about interactions and knowledge exchange relations in the RIS literature from the perspective of social network analysis. More precise, it links network theoretical concepts and insights to the well-known classification of RIS types by Cooke (2004). We thereby exemplarily show how the RIS literature and the literature on regional knowledge networks can benefit from considering insights of the respective other.