An evaluation of local authority social network interventions for the promotion of energy efficiency measures in the domestic sector

Local governments at city and regional level have a key role in promoting the uptake of energy-efficiency measures by households through schemes such as the UK’s Green Deal financing mechanism. However, there is little understanding of the role that social network interactions between householders play in ensuring the successful diffusion of energy-efficiency measures. In this paper we explore the role of local authorities in using interventions designed to use interactions on social networks to promote uptake of energy-efficiency measures in the domestic sector. Both the individual preferences of households and the influences that they experience from peer groups and the wider population (through social norms) are important factors in the adoption of energy innovations, and local authorities have the means to harness these influences to their advantage in encouraging increased adoption. The role of social networks in the spread of information on energy-efficient technologies and behaviours is a relatively new area for research, but one which draws on evidence of success in other areas, such as health. To investigate this, we use results from modelling work recently conducted by the authors, and examples of methods used in practice by local authorities in the UK and elsewhere to promote uptake of energy-efficiency initiatives. This enables us to appraise the potential utility of different types of social network interventions for promoting uptake, including interventions aimed at individuals, groups, and the network structure itself. In conclusion, we present the resulting insights into the use of network interventions by local authorities for promoting uptake of energy-efficiency measures in the domestic sector, and examine current UK and EU policy to see to what extent it supports implementation

Strategic Energy Planning within Local Authorities in the UK: a Study of the City of Leeds

This paper considers the development of a strategic energy body in a local authority in the UK and looks at the perceived need for, and possible roles of, such a body. Historically, energy provision and management has not usually been a strategic priority for UK local authorities. Yet energy considerations are implicit in key local authority responsibilities such as transport, waste management, planning, and the provision of housing services. In addition, recent UK central government policies support the move to localism and provide incentives for low-carbon energy generation. A study was undertaken to assess the potential (including both the perceived benefits and actual capacity to deliver) for Leeds City Council to develop a strategic body to execute delivery of city-level energy decision-making. We examine the perceived benefits to a range of main stakeholders, using data drawn from interviews with managers responsible for low-carbon and renewable energy projects across the city. Through participant observation we explore the capacity of a local authority to deliver a strategic energy body, and we briefly examine the possible forms of delivery. We conclude with recommendations for national policy that would enable the development of strategic energy bodies across local governments in the UK

Modeling diffusion of energy innovations on a heterogeneous social network and approaches to integration of real-world data

A model has been developed to simulate the diffusion of energy innovations on a heterogeneous social network. Nodes on a network represent households, whose adoption of an energy innovation is based on a combination of personal and social benefit; social benefit includes the positive influence from an individual's personal social network and feedback from the wider population. This article describes the development of the model to incorporate heterogeneous parameters and, thus, become more like a real social system. The sensitivity of the model is investigated and it is shown that heterogeneity matters. This has important implications for the inclusion of real-world data into this type of model