Beyond Curtailment and Efficiency: Identifying Household Energy- and Water-Saving Measure Classes
Date Published |
08/2020
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Publication Type | Conference Paper
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DOI |
10.20357/B70K63
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Abstract |
A key component of behavior-based energy conservation programs is the identification of target behaviors. A common approach is to target behaviors with the greatest energy-saving potential. The concept of behavioral spillover introduces further considerations, namely that adoption of one energy-saving behavior may increase (or decrease) the likelihood of other energy-saving behaviors. Thus, the total impact of correlated measure classes could be an important consideration when selecting target behaviors. Understanding the unique drivers and barriers for different measure classes can also support more efficient and effective interventions. However, current understanding of measure classes is limited. This research aimed to identify household energy- and water-saving measure classes, within which positive spillover is likely to occur (e.g., adoption of energy-efficient appliances may correlate with adoption of water-efficient appliances). Nearly 1,000 households in a California city were surveyed and asked to report whether they had adopted 75 different energy- and/or water-saving measures. Cluster analysis based on correlations between adoption of these diverse measures revealed eight water-energy-saving measure classes: Water Conservation; Energy Conservation; Maintenance and Management; Efficient Appliance; Edge of Efficiency; Efficient Irrigation; Green Gardening; and Green Landscaping. Understanding these measure classes can help guide behavior-based energy program developers in selecting target behaviors and designing interventions. For example, a series of energy reports could focus on one measure class at a time, each report promoting multiple measures within a given class and particularly highlighting high-leverage, “gateway” measures, i.e., those most correlated with others in the class.
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Conference Name |
ACEEE Summer Study
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Year of Publication |
2020
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Refereed Designation |
Refereed
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Organizations | |
Research Areas | |
File(s) | |
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