Sanderford, A R; McCoy, A P and Keefe, M J (2018) Adoption of energy star certifications: Theory and evidence compared. Building Research & Information, 46(2), pp. 207-13. ISSN 0961-3218
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.;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.;
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | eco-labels; diffusion; energy labels; United States; Energy Star; housing; energy efficiency; new product adoption; Energy consumption; Construction; Environmental policy; Residential buildings; Markets; Labelling; Public policy; Certification; Climate change; Energy; Mathematical analysis; Pricing; Energy demand; Product development; Power efficiency; Commercial buildings; Real estate; Residential energy; Adoption; Environmental labelling |
| Index terms: | residential energy, single-family housing, programme, United States, certification, environmental labelling, environmental policy, public policy, product development, climate change, housing, mathematical analysis, new product adoption, commercial building, variation, commercial property, evidence, energy star, residential building, energy efficiency, efficiency, energy star certification, energy demand, pricing, markets, eco-label, energy consumption, energy labels, real estate, power efficiency |
| Subjects: | data analysis and analytics, energy systems, economic analysis, public policy, real estate economics, sustainability and energy, climate science, innovation studies, evaluation and assessment methods, construction type, administrative processes, project controls, Geography, contractual condition, sustainability assessment, performance management |
| Topics: | Quality Management, Urban Studies, Time Control, Contract Administration, Research Practice, Geographical Context, Business Strategy, Sustainability, Governance, Construction Technology |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here