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School of Geography

Modelling middle actors in the building energy retrofit system

Supervisors: Professor Alison Heppenstall, Professor of Geocomputation, School of Geography ;
Dr Alice Owen, Associate Professor, Sustainability Research Institute  

Background
Transforming the UK’s existing buildings to a zero carbon building stock by 2050, in order to meet statutory targets, remains an enormous challenge and a major business opportunity.  The technology, equipment and products exist to meet the challenge and realise the opportunity.  But the obstacles lie in consumer behaviour and in the behaviour of the construction trades and construction DIY practitioners.  Consumer behaviour is well researched, but the behaviour of tradespeople as professionals has only recently started to be evaluated qualitatively.  This qualitative understanding of how small building firms and DIY practitioners choose and use products and processes to achieve low carbon outcomes is revealing the importance of focussing on decision making in supply chains, local networks and interpersonal communications and trust.

Agent based modelling is an approach which may allow these small scale, qualitative insights to be combined with forms of “big data”.  Specifically, spatially defined agent based models might help to assess which interventions are most effective in delviering the desired outcomes – warm, low cost, energy efficient homes.

At the very core of ABM is the individual.  Through ABM, individuals are ‘created’ and assigned unique behaviour and relationships. This ‘bottom-up’ representation allows new knowledge and behaviours to emerge from interactions between the agents (see Crooks and Heppenstall, 2012 for a detailed introduction).  An attractive aspect of ABM is its ability to represent individuals and their relationships across different spatial scales, giving them the ability to learn, evolve, and make decisions adaptively in both space and time. 

PhD Research aim

This studentship will develop and test some aspect of spatial agent based modelling to simulate the trasnformaton of existing homes into low carbon homes, through changing the behaviours of small constuction firms and heating system installers.

Relevant areas of expertise or interest:
Methods
• ABM
• Network analysus
• Data
Themes
• SME behaviours
• Construction industry supply chain
• Domestic energy retrofit

This project is suitable for ESRC White Rose DTP Advanced Quantitative Methods funding. The White Rose DTP is offering up to 4 AQM studentships through an open competition from October 2018 and strong applicants will be encouraged to apply . If you are interested in the project, please submit a PhD application to the School of Geography by 30th November.  If your PhD application is successful, you will be advised how to apply for ESRC funding .  The deadline for funding application is 24th January 2018 (17:00)