 Behavioral study of personalized automated demand response in the workplaceTakanori Ida, Naoya Motegi and Yoshiaki Ushifusa Energy Policy, 2019, vol. 132, issue C, 1009-1016 Abstract: This paper presents a quasi-randomized controlled trial in a workplace with personalized lighting control and investigates the impact of automated demand response (DR) on employees. It also clarifies what type of conditions will make employees participate in DR. To meet this objective, we set up four treatment groups: opt-in performance incentive, opt-in fixed incentive, opt-out performance incentive, and opt-out fixed incentive. In the experiment, the group with the highest participation rate is the opt-out fixed incentive. Subsequently, we estimate two average treatment effects (intent-to-treat and treatment-on-treated) for DR. The results reveal a significant reduction in electricity consumption during peak hours for all four treatment groups. We find that although the DR participation rate is high for the opt-out group, its average energy-saving effect is not significantly different than that for the opt-in group, and the average energy-saving amount of opt-in consumers is larger than that of opt-out consumers. We also show a similar trade-off between the participation rate and the power-saving effect for employees participating in DR. Keywords: Automated demand response; Default effect; Field experiment; Incentive (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:enepol:v:132:y:2019:i:c:p:1009-1016 DOI: 10.1016/j.enpol.2019.06.029 Access Statistics for this article Energy Policy is currently edited by N. France More articles in Energy Policy from Elsevier |
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