Publication | Closed Access
Effective User Interface Designs to Increase Energy-efficient Behavior in a Rasch-based Energy Recommender System
55
Citations
32
References
2017
Year
Unknown Venue
EngineeringBehavioral Decision MakingEnergy EfficiencyEnergy ConservationTailored AdvicePersuasive TechnologyConsumer ResearchSocial SciencesData SciencePreference LearningDecision TheoryConservation AdvicePreference ModelingEnergy ConsumptionBehavioral SciencesHealth PolicyDesignComputer EngineeringUser ExperienceComputer ScienceEnergyCold-start ProblemBehavioral EconomicsEnergy ManagementSustainable EnergyEnergy PolicyOrdinal Rasch ScaleHuman-computer InteractionBehavioral InsightPreference ElicitationEnergy-efficient BehaviorDecision ScienceCollaborative Filtering
People often struggle to find appropriate energy-saving measures to take in the household. Although recommender studies show that tailoring a system's interaction method to the domain knowledge of the user can increase energy savings, they did not actually tailor the conservation advice itself. We present two large user studies in which we support users to make an energy-efficient behavioral change by presenting tailored energy-saving advice. Both systems use a one-dimensional, ordinal Rasch scale, which orders 79 energy-saving measures on their behavioral difficulty and link this to a user's energy-saving ability for tailored advice. We established that recommending Rasch-based advice can reduce a user's effort, increase system support and, in turn, increase choice satisfaction and lead to the adoption of more energy-saving measures. Moreover, follow-up surveys administered four weeks later point out that tailoring advice on its feasibility can support behavioral change.
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