| dc.description.abstract |
"In the face of apparent failures to govern complex environmental problems by the central
state, new modes of governance have been proposed in recent years. Network governance is an emerging
concept that has not yet been consolidated. In network governance, processes of (collective) learning
become an essential feature. The key issue approached here is the mutual relations between network structure
and learning, with the aim of improving environmental management. Up to now, there have been few
attempts to apply social network analysis (SNA) to learning and governance issues. Moreover, little research
exists that draws on structural characteristics of networks as a whole, as opposed to actor-related network
measures. Given the ambiguities of the concepts at stake, we begin by explicating our understanding of
both networks and learning. In doing so, we identify the pertinent challenge of individual as opposed to
collective actors that make up a governance network. We introduce three learning-related functions that
networks can perform to different degrees: information transmission, deliberation, and resilience. We
address two main research questions: (1) What are the characteristics of networks that foster collective
learning in each of the three dimensions? To this end, we consider SNA-based network measures such as
network size, density, cohesion, centralization, or the occurrence of weak as opposed to strong ties. (2)
How does collective learning alter network structures? We conclude by outlining a number of open issues
for further research." |
en_US |