title: Householders' Mental Models of Domestic Energy Consumption: Using a Sort-And-Cluster Method to Identify Shared Concepts of Appliance Similarity.
abstract: If in-home displays and other interventions are to successfully influence people's energy consumption, they need to communicate about energy in terms that make sense to users. Here we explore householders' perceptions of energy consumption, using a novel combination of card-sorting and clustering to reveal shared patterns in the way people think about domestic energy consumption. The data suggest that, when participants were asked to group appliances which they felt naturally 'went together', there are relatively few shared ideas about which appliances are conceptually related. To the extent participants agreed on which appliances belonged together, these groupings were based on activities (e.g., entertainment) and location within the home (e.g., kitchen); energy consumption was not an important factor in people's categorisations. This suggests messages about behaviour change aimed at reducing energy consumption might better be tied to social practices than to consumption itself.
authors.affiliation: Plymouth University Peninsular School of Medicine and Dentistry, Plymouth University, Drake Circus, Plymouth, PL4 8AA, United Kingdom.
authors.forename: Elizabeth
authors.identifier: http://orcid.org/0000-0003-3249-1011
authors.initials: E
authors.lastname: Gabe-Thomas
authors.affiliation: Department of Psychology, University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom.
authors.forename: Ian
authors.initials: I
authors.lastname: Walker
authors.affiliation: Department of Psychology, University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom.
authors.forename: Bas
authors.initials: B
authors.lastname: Verplanken
authors.affiliation: Department of Mathematical Sciences, University of Bath, Claverton Down, Bath, BA2, 7AY, United Kingdom.
authors.forename: Gavin
authors.initials: G
authors.lastname: Shaddick
mesh_terms: D000328:Adult; D000368:Aged; D016000:Cluster Analysis; D004560:Electricity; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008960:Models, Psychological