Synergies and conflicts on the landscape of domestic energy consumption: beyond metaphor

David Shipworth, The University of Reading, Whiteknights

Keywords

socio-technical systems, complex systems, Bayesian belief networks, barriers, energy policy, research design, transdisciplinary

Abstract

A transdisciplinary research and modelling process is presented. This goes beyond the metaphor of a 'landscape' of influences on domestic energy consumption, to construct a Bayesian Belief Network model of such a landscape.

Bayesian Belief Networks are of both academic and practical interest. They are applied in many areas governed by complex sets of socio-technical drivers including management of water catchments, ecosystems and fisheries. Such models allow better understanding of the range of social, economic and environmental impacts of a given management strategy and how benefits in one part of the system may be offset in another. These interactions between influences generate the 'landscape' of the system.

The research design for development of a Bayesian Belief Network model of the socio-technical influences on home energy use is presented. A realist synthesis of the literature identifies factors influencing domestic energy use, their strength, and the direction of their interrelationships. These are represented as a network diagram. This initial network is presented to experts for elaboration and verification. Data is used to estimate probabilistic relationships between the factors. Primary qualitative social research methods identify new, and contextualise known factors for the UK. Data from primary or secondary quantitative analysis is integrated to refine estimates of the influence of key factors. This process is iterated to build and refine the model.

This research design will be presented, and the policy implications of this modelling approach explored. This research forms part of the UK's recently launched 'Carbon Vision' programme on carbon reductions in buildings.