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Extended TAM Analysis of a Residential DR Pilot Program  

Jung, Euna (서울대학교 융합과학기술대학원 융합과학부)
Lee, Kyungeun (서울대학교 융합과학기술대학원 융합과학부)
Kim, Hwayoung (서울대학교 융합과학기술대학원 융합과학부)
Jeong, Sora (서울대학교 융합과학기술대학원 융합과학부)
Lee, Hyoseop (서울대학교 융합과학기술대학원 융합과학부)
Suh, Bongwon (서울대학교 융합과학기술대학원 융합과학부)
Rhee, Wonjong (서울대학교 융합과학기술대학원 융합과학부)
Publication Information
Journal of the HCI Society of Korea / v.12, no.4, 2017 , pp. 65-73 More about this Journal
Abstract
While electricity demand is generally increasing, stably controlling supply is becoming a serious challenge because renewable energies are becoming popular and often their productions are dependent on the weather. The 'demand response' programs can be used to complement the problems of renewable energies, and therefore their role is becoming increasingly important. This study provides an analysis of a demand response pilot that was conducted in Korea. The study first focused on questionnaire surveys and in-depth interviews, and the data was used to perform a Technology Acceptance Model (TAM) analysis. The goal of the pilot was to have the residential users reduce their power consumptions when an energy reduction mission is issued during peak load hours. The experimental subjects consisted of two groups with different characteristics. Subjects in group A obtained smart meters as an optional function of IoT platform service provided by a mobile service company, and received a charge deduction as their compensation. Subjects in group B either voluntarily purchased smart meters as individuals or received them by participating in an energy self-sufficient village program that was run by a local government, and were entitled to a donation as their compensation. With the analysis, group A was found to fit the extended technology acceptance model that includes perceived playfulness in addition to perceived ease of use and perceived usefulness. On the contrary, group B failed to fit the model well, but perceived usefulness was found to be relatively more important compared to group A. The results indicate that the residential energy groups' behavior changes are dependent on each group's characteristics, and group-specific DR design should be considered to improve the effectiveness of DR.
Keywords
Extended Technology Acceptance Model (TAM); Residential Demand Response (DR); Peak Reduction;
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Times Cited By KSCI : 1  (Citation Analysis)
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