Consumer Data Research Centre

Housing & Energy Research

People move home for all kinds of reasons: to take up a new job, to up-size when they have a child or down-size when they retire.  Understanding these patterns of household mobility is extremely important for resource allocation and policy decisions.  In addition the nature of household energy consumption is receiving increasing attention amongst academics and industry stakeholders. Smart meter technology is making it possible to monitor geotemporal patterns of energy consumption and gauge the sensitivity of energy consumption to price and other probable household and environmental circumstances.

 

 

To demonstrate the value of our data holdings,  researchers at our host universities are currently undertaking Big Data exemplar research projects in each of our key research themes.

 

Identifying the Fuel Poor from Consumption Behaviour: Towards an Integrated Interpretative Framework of Domestic Energy Consumption in the UK

In collaboration with a major UK Domestic Energy Provider, this research proposes an approach for identifying vulnerable customers through the utilisation of Big Data analytics. It presents spatio-temporal analyses of consumption trends and identifies unique behavioural groups using clustering techniques.

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The Centre delivers a national service to the social science research community by providing access to a large volume of consumer data for research. Users can access our datasets either directly from the datastore or by application.

 

Investigating Domestic Energy Efficiency Data (InDEED), Leeds Beckett University

Improving the energy efficiency of homes reduces energy bills and carbon emission. Energy Performance Certificates (EPCs) were introduced in the UK to measure the current efficiency of homes and encourage these improvements. Evidence from national EPC datasets show that the energy efficiency of homes is steadily improving over time. In these databases, many homes have multiple EPCs which indicate they have had some form of retrofit. However, it appears that the majority of houses with multiple EPCs do not, in fact, show much improvement in their score. This project aims to determine if national datasets around household and community income, property-value or other geographic measures can explain why people improve their homes.

This project was funded as part of the CDRC Innovation Fund.

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Impact of investments in local public goods and planning decisions on house prices, rents and equilibrium sorting, University of Essex

This project combines microdata on local infrastructure and planning decisions with the CDRC’s Whenfresh/Zoopla data sets on house values and rents.  The project team are using these data to measure the social value of public goods and to predict the impacts of investments and planning decisions on urban mobility, house prices and rents, tax revenue, and social welfare.

This project was funded as part of the CDRC Innovation Fund.

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Data on housing returns for the UK, with an application to quantifying the value of local healthcare and schools quality, National Institute of Economic and Social Research

This project uses CDRC data on UK housing sale prices, rental prices and mortgage lending to construct measures of the returns, to owner occupied housing for local areas in the UK, and uses them to value local amenities such as school and healthcare quality.

This project was funded as part of the CDRC Innovation Fund.

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CDRC’s Masters Research Dissertation Programme instigates several masters led research projects which seek to tackle topical problems put forward by industry. We have included a number of example projects below, you can also view the full selection of extended abstracts which summarise the research undertaken by students who participated in previous years of the programme.

 

Identifying Socio-Spatial Inequalities in Student Housing in London – Knight Frank

This project, in collaboration with Knight Frank, aimed to analyse existing spatial patterns in student accommodation and, based on student’s preferences, suggest the most suitable areas for students in London.

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Exploring submarket trends in London: a constrained spatial interaction modelling analysis – Cluttons

This study investigates the characteristics of the London housing market and the effects of variables such as house price and accessibility on commuter distance through spatial interaction modelling.

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Can smart meters save consumers and British Gas money and carbon by pinpointing which consumers are most likely and best placed to install insulation in their homes? – British Gas

British Gas, as with other energy providers, have certain energy-savings targets to fulfil as part of the Government’s ECO (Energy Company Obligation) policy. These include providing wall cavity and loft insulation to customers’ homes. With no existing dataset regarding how energy-efficient consumers’ homes are, this has to be inferred from other sources, such as smart meter data. In this project the aim was to focus on customers that are homeowners and living in homes with cavity walls.

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Identifying fuel and poverty characteristics through e.on consumer records and geo-demographic segmentation data – e.on

Fuel poverty is known to be a distinct social problem, which can occur across a wide array of household demographics.  The occurrence of fuel poverty and its consequential impacts has been identified by many different studies, using a range of data sets. This dissertation presents a unique identification process, combining household resolution data with commercial grade geo-demographic customer segmentation classifications (CAMEO), not previously used in the identification of fuel poverty.

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Social Energy Responsibility: Identifying vulnerable energy customers through a K-Means clustering approach – e.on

This project aimed to identify areas that contain a high proportion of vulnerable households and should be targeted as part of the government implemented Energy Company Obligation (ECO), by taking into account demographic and property characteristics alongside average annual energy consumption data.

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Electric vehicle charge point placement optimisation – e.on

There is increasing demand for plug-in and hybrid vehicles in the UK as they are becoming more affordable due to decreased battery costs and lower manufacturing costs. As part of its sustainability programme, coupled with the increasing need to focus on the environment, E.ON is looking to assess the market for new public charging points across E.ON sites and the feasibility of incentivising its business customers to operate public charging stations.

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Harnessing the power of social media to determine moving house flows and customers’ energy needs – e.on

The aim of this project was to determine if there is a correlation between Twitter data and E.ON data on the subject of moving house, to encourage the development of using Twitter as a data source.

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