Behavioural Change MOT Demonstrator Project

Descriptions

**Please note this is an Award Notice not a call for competition** This contract has been awarded via Energy and Climate Change Behavioural Science Framework Agreement. Reference: CR20116. Background Meeting the UK's target for net-zero by 2050 requires societal change. Almost all government policies in the energy and climate change space, require behaviour change at the level of individuals and businesses to reduce carbon emissions as intended. Currently, there is an evidence gap whereby it is unclear the extent to which BEIS policies have behaviour change mechanisms built in and in turn, promote real behaviour change. The research questions that Behaviour Change MOTs would seek to address are as follows: •To what extent do BEIS energy and climate change policies currently utilise behavioural science to effectively encourage the behaviour change needed to achieve their policy goals and reduce carbon emissions? •What potential is there for behavioural science to be applied further to policies to help achieve their intended behaviour changes? Rationale This is a clear behavioural insights project, as Behaviour Change MOTs would seek to explore the extent to which BEIS policies are developed to best promote changes in people's and businesses' behaviours. BEIS currently lacks the capacity to develop and deliver a programme of Behaviour Change MOTs, so would like to draw on expertise from the BI framework to develop the structure/framework that all future behavioural MOTs will follow, and to use this to deliver an exemplar version. The aim is that BEIS will then be able to use the standardised behavioural MOT structure to complete MOTs for the remaining policies in the future (although we hope to also commission the supplier to undertake some as well). The expertise of framework suppliers will also be invaluable for helping to develop a prioritisation methodology to determine which policies should take priority when delivering Behaviour Change MOTs in the future. This could account for factors such as how much behaviour change has already happened; how much potential there is for behaviour change in future; GHG mitigation potential etc. A similar example could be The Impact-Likelihood Matrix (Kneebone at al., 2017). However, the proposed methodology should be practical and simple enough to implement in BEIS within the constraints of what data we can readily collect/access. This project will inform future policy development by allowing policy makers to reflect upon areas that are identified in their MOT as having potential for greater consideration of behavioural science.