Pelling, Mark; High, Chris; Dearing, John and Smith, Denis
PDF (Not Set)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
|DOI (Digital Object Identifier) Link:||http://doi.org/10.1068/a39148|
|Google Scholar:||Look up in Google Scholar|
Recent UK government policy on climate change, and wider policy movement within the United Nations Framework Convention on Climate Change, emphasise the building of adaptive capacity. But what are the institutional constraints that shape capacity to build adaptive organisations? The authors synthesise theory from social learning and institutional aspects of multilevel environmental governance to help unpack the patterns of individual and collective action within organisations that can enhance or restrict organisational adaptive capacity in the face of abrupt climate change. Theoretical synthesis is grounded by empirical work with a local dairy farmers group and two supporting public sector bodies that are both local actors in their own rights and which also shape the operating environment for other local actors (the Environment Agency and the Welsh Assembly and Assembly-sponsored public bodies). Providing space within and between local organisations for individuals to develop private as well as officially sanctioned social relationships is supported as a pathway to enable social learning. It is also a resource for adaptation that requires little financial investment but does call for a rethinking of the personal skills and working routines that are incentivised within organisations.
|Item Type:||Journal Article|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Interdisciplinary Research Centre:||Innovation, Knowledge & Development research centre (IKD)|
|Depositing User:||Pat Shah|
|Date Deposited:||09 Jul 2007|
|Last Modified:||04 Oct 2016 14:06|
|Share this page:|
Download history for this item
These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.