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Bourikas, L, Costanza, E, Gauthier, S, James, P A B, Kittley-Davies, J, Ornaghi, C, Rogers, A, Saadatian, E and Huang, Y (2018) Camera-based window-opening estimation in a naturally ventilated office. Building Research & Information, 46(02), 148–63.

Conradie, D, van Reenen, T and Bole, S (2018) Degree-day building energy reference map for South Africa. Building Research & Information, 46(02), 191–206.

Ortlepp, R, Gruhler, K and Schiller, G (2018) Materials in Germany’s domestic building stock: calculation model and uncertainties. Building Research & Information, 46(02), 164–78.

Prieto, A J, Silva, A, de Brito, J and Macias-Bernal, J M (2018) Serviceability of facade claddings. Building Research & Information, 46(02), 179–90.

Sanderford, A R, McCoy, A P and Keefe, M J (2018) Adoption of Energy Star certifications: theory and evidence compared. Building Research & Information, 46(02), 207–19.

  • Type: Journal Article
  • Keywords: diffusion; eco-labels; energy efficiency; energy labels; Energy Star; housing; new product adoption; United States;
  • ISBN/ISSN: 0961-3218
  • URL: https://doi.org/10.1080/09613218.2016.1252618
  • Abstract:
    Energy Star, the largest voluntary housing eco-labelling programme in the US, conveys important signals to housing market actors about the energy efficiency of homes. With energy demand from housing being a significant energy consumer and contributor to climate change, gaining insight into the diffusion patterns of these certifications is an important analytical step. Informed by theories of new product adoption, research is used to identify the factors associated with the diffusion patterns of Energy Star certifications into US single-family housing from 2002 to 2013. The findings are generally congruent with recent studies of energy-efficiency adoption patterns in commercial property (real estate) and residential building construction. The key significant predictors of variation in the proportion of Energy Star-certified homes across US core-based statistical areas (CBSAs) are found to be public policy, climate, market attributes, industry characteristics and energy prices.

Sole, T and Wagner, C (2018) Understanding domestic fuel use practices in an urban township. Building Research & Information, 46(02), 220–30.