Publication Detail
Two (or More) for One: Identifying Classes of Household Energy- and Water-Saving Measures to Understand the Potential for Positive Spillover
UCD-ITS-RP-22-38 Journal Article Energy and Efficiency Institute Available online at: https://doi.org/10.1371/journal.pone.0268879 |
Suggested Citation:
Sanguinetti, Angela, Claire McIlvennie, Marco Pritoni, Susan Schneider (2022) Two (or More) for One: Identifying Classes of Household Energy- and Water-Saving Measures to Understand the Potential for Positive Spillover. PLoS ONE 17
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. This research aimed to identify and describe 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), and explore demographic and psychographic predictors of each. 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. Principal Component Analysis and Network Analysis based on correlations between adoption of these diverse measures revealed and characterized eight water-energy-saving measure classes: Water Conservation, Energy Conservation, Maintenance and Management, Efficient Appliance, Advanced 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.
Key words: behavior, conservation of energy, surveys, computer software, principal component analysis, network analysis, housing, surface water
Key words: behavior, conservation of energy, surveys, computer software, principal component analysis, network analysis, housing, surface water