Investigation of the key drivers influencing the uptake of energy-efficient durables
Joel Guilbaud, UCL
My research investigates the key reasons that influence the uptake of energy-efficient measures by using macro data from the HEED database and Census data. It focuses on determining what are the key factors correlated with a low/high uptake.
The UK government has committed in legislation to reduce carbon emissions by 80% from their 1990 level by 2050. Given the large part of energy consumed by existing buildings, it has become increasingly clear that both significant reductions on the energy demand of the building stock as well as efficiency improvements will be needed. The framing of the issue of energy demand and carbon emissions is critical to its ultimate success. The way in which technical interventions in the building stock, such as insulation or lighting standards, improved heating efficiencies or the implementation of renewable technologies is relatively well understood. Yet, we still need to better understand the key drivers that motivate and influence household to take up energy efficient durables in their homes. This element of understanding is vital in order to develop well-targeted energy policies and ultimately improve energy interventions.
There is already a large body of work on the factors influencing consumer take-up of energy efficient durables. For example, a past study showed that the households which adopted energy efficiency measure typically came from a two-person middle class household living in a detached or semi-detached house with three or four bedrooms. Another study found that the main motivations for installing such measures were environmental concern and saving money, while the main barriers were capital cost and lack of reliable information. However, all these studies were based on small-scale survey including no more than 400 respondents, and were therefore limited to certain types of households.
The increased availability of data on buildings provides a strong opportunity to review the past findings based on larger datasets which include data points for several millions households. Recently, an improved source of energy and buildings data has been developed for the domestic stock of Britain including data on more than 19 million households; this dataset is referred as the HEED (Homes Energy Efficiency Database). This is a unique set of data on energy efficiency refurbishment and housing characteristics at the individual property level. Using this set of data, it becomes possible to determine the key factors influencing the adoption of energy-efficient measures for all types of household including social, economic and building factors.
Scope & Objectives
The scope of this study is to develop and assess a research method in order to understand the key drivers for technology adoption with regard to the HEED dataset. The primary aim is to offer an introduction into the type of results that HEED is capable to deliver for a specific energy intervention. Our results will provide methodological support for researching about technology adoption in relation to large empirical data. Also, we will evaluate the opportunities that this dataset can offer for further research on energy interventions beyond the scope of this project.
Example of analysis
An improved source of energy and buildings data has been developed recently for the domestic stock of Britain including data on more than 11 million households. Based on this new dataset, we have investigated the potential influencing factors to the uptake of energy-efficient glazing at a macro scale. The results of this review were framed against the utility-based theory and the human ecosystem theory model. Variables identified in the study that were highly correlated with uptake levels were net present value, tenure type, building type, age and gender, and profession type. These findings support the underlying premise of the human ecosystem theory: Variables from the natural, the social, and the designed environments and human organism variables seem to interact with the uptake levels of energy-efficient glazing.