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Difference between revisions of "Publication - Understanding Multi-Level Drivers of Behaviour Change - A Cross-Impact Balance Analysis of What Influences the Adoption of Improved Cookstoves in Kenya"
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{{Pub Database | {{Pub Database | ||
|Pub Title=Understanding Multi-Level Drivers of Behaviour Change - A Cross-Impact Balance Analysis of What Influences the Adoption of Improved Cookstoves in Kenya | |Pub Title=Understanding Multi-Level Drivers of Behaviour Change - A Cross-Impact Balance Analysis of What Influences the Adoption of Improved Cookstoves in Kenya | ||
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|Pub Abstract=The research described in this paper is part of the Behaviour and Choice Initiative, a multi-year research initiative by the Stockholm Environment Institute, funded by the Swedish International Development Cooperation Agency (Sida). The initiative explores the factors that influence household choice and decision-making, with a specific focus on the uptake of technologies, services or changes of practice that lead to sustainable outcomes. It does so using case studies of drivers of behaviour and a range of analytical approaches. This paper relies on empirical data on the drivers of adoption of improved cookstoves in Kenya. | |Pub Abstract=The research described in this paper is part of the Behaviour and Choice Initiative, a multi-year research initiative by the Stockholm Environment Institute, funded by the Swedish International Development Cooperation Agency (Sida). The initiative explores the factors that influence household choice and decision-making, with a specific focus on the uptake of technologies, services or changes of practice that lead to sustainable outcomes. It does so using case studies of drivers of behaviour and a range of analytical approaches. This paper relies on empirical data on the drivers of adoption of improved cookstoves in Kenya. | ||
| − | The paper outlines an approach for synthesizing empirical data from different analytical levels using the Cross-impact Balance (CIB) method in a way that is epistemologically consistent and documents its application. In so doing, | + | The paper outlines an approach for synthesizing empirical data from different analytical levels using the Cross-impact Balance (CIB) method in a way that is epistemologically consistent and documents its application. In so doing, the authors contribute a systemic view of how behaviour change with regard to the adoption of an improved cooking technology may – or may not – come about. |
| − | Furthermore, in order to explore consistent stories of behaviour change, the authors combine CIB with Scenario Diversity Analysis (SDA) as suggested by Kemp-Benedict (2012). Combining CIB with SDA allows | + | Furthermore, in order to explore consistent stories of behaviour change, the authors combine CIB with Scenario Diversity Analysis (SDA) as suggested by Kemp-Benedict (2012). Combining CIB with SDA allows the authors to reduce what might potentially be half a million combinations of scenarios – what referred to in the paper as scenario kernels – to just four scenarios, which represents quite an efficient reduction. |
|Pub Topics=Cooking, Impacts, Other | |Pub Topics=Cooking, Impacts, Other | ||
|Pub Download=https://www.sei.org/wp-content/uploads/2018/12/181221a-gill-lambe-kenya-cookstove-analysis-1811h.pdf | |Pub Download=https://www.sei.org/wp-content/uploads/2018/12/181221a-gill-lambe-kenya-cookstove-analysis-1811h.pdf | ||
|Pub Newsletter=No | |Pub Newsletter=No | ||
}} | }} | ||
| − | |||
[[Category:Cooking]] | [[Category:Cooking]] | ||
[[Category:Improved_Cooking]] | [[Category:Improved_Cooking]] | ||
[[Category:Impacts]] | [[Category:Impacts]] | ||
Latest revision as of 12:00, 8 January 2019
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The paper outlines an approach for synthesizing empirical data from different analytical levels using the Cross-impact Balance (CIB) method in a way that is epistemologically consistent and documents its application. In so doing, the authors contribute a systemic view of how behaviour change with regard to the adoption of an improved cooking technology may – or may not – come about.
Furthermore, in order to explore consistent stories of behaviour change, the authors combine CIB with Scenario Diversity Analysis (SDA) as suggested by Kemp-Benedict (2012). Combining CIB with SDA allows the authors to reduce what might potentially be half a million combinations of scenarios – what referred to in the paper as scenario kernels – to just four scenarios, which represents quite an efficient reduction.
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