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.
Highlights
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
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 social network analysis (SNA)-based network measures such as network size, density, cohesion, centralization, or the occurrence of weak as opposed to strong ties
As learning concepts in the literature are quite diverse, we have specified learning in networks by introducing three different learning-related functions of a network, namely information transmission, deliberation, and resilience
Summary
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. One main reason for the proliferation of network approaches in environmental management is their potential to integrate and make available different sources of knowledge and competences and to foster individual and collective learning (Liebeskind et al 1996, Wenger 2000, Haas 2004, Dedeurwaerdere 2007). The literature on complex social– ecological systems (Gunderson and Holling 2002, Berkes et al 2003) has pointed out that closely coupled systems components, feedback, nonlinearity, and self-organization typically lead to emergent dynamics and unpredictable systems behavior Against this background, learning becomes a central category in governance approaches (Knoepfel and Kissling-Näf 1998, Siebenhüner and Suplie 2005). We can generalize the above hypothesis as follows: The structural properties of a governance network (such as size, composition, density, and so forth) have an impact on individual and collective learning in the context of environmental management.
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