Learnings from Local Collaborative Transformations: Setting a Basis for a Sustainability Framework
The complexity of the sustainability challenge demands for collaboration between different actors, be they governments, businesses, or grassroots movements, at all levels. Nevertheless, and according to previous research, many tensions and obstacles to partnership still exist and results are far fro...
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Veröffentlicht in: | Sustainability 2020-02, Vol.12 (3), p.795, Article 795 |
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Sprache: | eng |
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Zusammenfassung: | The complexity of the sustainability challenge demands for collaboration between different actors, be they governments, businesses, or grassroots movements, at all levels. Nevertheless, and according to previous research, many tensions and obstacles to partnership still exist and results are far from meaningful. By investigating potential synergies, our purpose is to define a sustainability framework to promote better collaboration between community-based initiatives and local governments, in the context of transformation. Specifically, the research aim presented in this paper is to harvest learnings from existing collaborative experiments at the municipal level. As a starting point and using exploratory literature review concerning areas like policy (e.g., public administration) or business and management research, we propose a 'Compass for Collaborative Transformation'. This heuristic device can support the study of these sustainability experiments. We also introduce a method to map the governance imprint of these collaborations and to provide a 'proxy' of transformative efforts. We then present and discuss results from 71 surveyed cases happening in 16 countries in America and Europe, comparing distinctive frameworks involved. Finally, we consider the preconditions of a framework to improve these local collaborations-namely the capacity to support joint navigation through transformative efforts, facing high levels of uncertainty and complexity-and present ongoing efforts to codesign a new sustainability framework. |
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ISSN: | 2071-1050 2071-1050 |
DOI: | 10.3390/su12030795 |