Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/190491 
Erscheinungsjahr: 
2017
Schriftenreihe/Nr.: 
IEHAS Discussion Papers No. MT-DP - 2017/30
Verlag: 
Hungarian Academy of Sciences, Institute of Economics, Budapest
Zusammenfassung: 
Knowledge networks are important to understand learning in industry clusters but surprisingly little is known about what drives the formation, persistence and dissolution of ties. Applying stochastic actor-oriented models on longitudinal relational data from a mature cluster in a medium-tech industry, we show that triadic closure and geographical proximity increase the probability of tie creation but does not influence tie persistence. Cognitive proximity is positively correlated to tie persistence but firms create ties to cognitively proximate firms only if they are loosely connected through common third partners. We propose a micro perspective to understand how endogenous network effects, cognitive proximity of actors and their interplay influence the evolutionary process of network formation in clusters.
Schlagwörter: 
knowledge networks
cluster evolution
network dynamics
stochastic actor-oriented models
JEL: 
D85
L14
R11
O31
ISBN: 
978-615-5457-20-3
Dokumentart: 
Working Paper

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