Effective user interface designs to increase energy-efficient behavior in a Rasch-based energy recommender system

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Abstract

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.
Original languageEnglish
Title of host publicationRecSys '17 Proceedings of the Eleventh ACM Conference on Recommender Systems, 27-31 August 2017, Como, Italy
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages65-73
Number of pages9
ISBN (Electronic)9781450346528
ISBN (Print)978-1-4503-4652-8
DOIs
Publication statusPublished - Aug 2017
Event11th ACM Conference on Recommender Systems, RecSys 2017 - Como, Italy
Duration: 27 Aug 201731 Aug 2017
Conference number: 11

Conference

Conference11th ACM Conference on Recommender Systems, RecSys 2017
Abbreviated titleRecSys 2017
Country/TerritoryItaly
CityComo
Period27/08/1731/08/17

Keywords

  • Behavioral change
  • Energy conservation
  • Rasch model
  • Recommender systems
  • User experience

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