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Classifying Residents who use Landscape Irrigation: Implications for Encouraging Water Conservation Behavior. | LitMetric

Large amounts of water applied as urban irrigation can often be reduced substantially without compromising esthetics. Thus, encouraging the adoption of water-saving technologies and practices is critical to preserving water resources, yet difficult to achieve. The research problem addressed in this study is the lack of characterization of residents who use urban irrigation, which hinders the design of effective behavior change programs. This study examined audience segmentation as an approach to encouraging change using current residential landscape practices. K-means cluster analysis identified three meaningful subgroups among residential landscape irrigation users (N = 1,063): the water considerate majority (n = 479, 45 %), water savvy conservationists (n = 378, 36 %), and unconcerned water users (n = 201, 19 %). An important finding was that normative beliefs, attitudes, and perceived behavioral control characteristics of the subgroups were significantly different with large and medium practical effect sizes. Future water conservation behaviors and perceived importance of water resources were also significantly different among subgroups. The water considerate majority demonstrated capacity to conserve, placed high value on water, and were likely to engage in behavior changes. This article contributes to the literature on individuals who use residential landscape irrigation, an important target audience with potential to conserve water through sustainable irrigation practices and technologies. Findings confirm applicability of the capacity to conserve water to audience segmentation and extend this concept by incorporating perceived value of water resources and likelihood of conservation. The results suggest practical application to promoting residential landscape water conservation behaviors based on important audience characteristics.

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http://dx.doi.org/10.1007/s00267-016-0706-2DOI Listing

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