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Effects of feedback on residential electricity demand: Findings from a field trial in Austria

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  • Schleich, Joachim
  • Klobasa, Marian
  • Götz, Sebastian
  • Brunner, Marc

Abstract

This paper analyzes the effects of providing feedback on electricity consumption in a field trial involving more than 1,500 households in Linz, Austria. About half of these households received feedback together with information about electricity-saving measures (pilot group), while the remaining households served as a control group. Participation in the pilot group was random, but households were able to choose between two types of feedback: access to a web portal or written feedback by post. Results from cross section OLS regression suggest that feedback provided to the pilot group corresponds with electricity savings of around 4.5 % for the average household. Our results from quantile regressions imply that for house-holds in the 30th to the 70th percentile, feedback on electricity consumption is statistically significant and effects are highest in absolute terms and as a share of electricity consumption. For percentiles below or above this range, feedback ap-pears to have no effect. Finally, controlling for a potential endogeneity bias induced by non random participation in the feedback type groups, we find no difference in the effects of feedback provided via the web portal and by post.

Suggested Citation

  • Schleich, Joachim & Klobasa, Marian & Götz, Sebastian & Brunner, Marc, 2012. "Effects of feedback on residential electricity demand: Findings from a field trial in Austria," Working Papers "Sustainability and Innovation" S8/2012, Fraunhofer Institute for Systems and Innovation Research (ISI).
  • Handle: RePEc:zbw:fisisi:s82012
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    1. repec:eee:energy:v:125:y:2017:i:c:p:382-392 is not listed on IDEAS
    2. Schleich, Joachim & Gassmann, Xavier & Faure, Corinne & Meissner, Thomas, 2016. "Making the implicit explicit: A look inside the implicit discount rate," Energy Policy, Elsevier, vol. 97(C), pages 321-331.
    3. Degen, Kathrin & Fleisch, Elgar & Götte, Lorenz & Lalive, Rafael & Staake, Thorsten & Tasic, Vojkan & Tiefenbeck, Verena, 2016. "Overcoming Salience Bias: How Real-Time Feedback Fosters Resource Conservation," CEPR Discussion Papers 11480, C.E.P.R. Discussion Papers.
    4. repec:eee:enepol:v:107:y:2017:i:c:p:225-233 is not listed on IDEAS
    5. repec:eee:rensus:v:77:y:2017:i:c:p:1146-1168 is not listed on IDEAS
    6. Ramos, A. & Gago, A. & Labandeira, X. & Linares, P., 2015. "The role of information for energy efficiency in the residential sector," Energy Economics, Elsevier, vol. 52(S1), pages 17-29.
    7. Hege Westskog & Tanja Winther & Hanne Sæle, 2015. "The Effects of In-Home Displays—Revisiting the Context," Sustainability, MDPI, Open Access Journal, vol. 7(5), pages 1-21, May.
    8. Khanna, Nina Zheng & Guo, Jin & Zheng, Xinye, 2016. "Effects of demand side management on Chinese household electricity consumption: Empirical findings from Chinese household survey," Energy Policy, Elsevier, vol. 95(C), pages 113-125.
    9. Adnane Kendel & Nathalie Lazaric & Kevin Maréchal, 2017. "What Do People 'Learn By Looking' at Direct Feedback on their Energy Consumption? Results of a Field Study in Southern France," GREDEG Working Papers 2017-19, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), University of Nice Sophia Antipolis.
    10. repec:eee:enepol:v:108:y:2017:i:c:p:593-605 is not listed on IDEAS
    11. Gils, Hans Christian, 2014. "Assessment of the theoretical demand response potential in Europe," Energy, Elsevier, vol. 67(C), pages 1-18.
    12. repec:eee:eneeco:v:66:y:2017:i:c:p:85-98 is not listed on IDEAS
    13. Fumo, Nelson & Rafe Biswas, M.A., 2015. "Regression analysis for prediction of residential energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 332-343.
    14. repec:eee:appene:v:205:y:2017:i:c:p:1560-1570 is not listed on IDEAS
    15. Gils, Hans Christian, 2016. "Economic potential for future demand response in Germany – Modeling approach and case study," Applied Energy, Elsevier, vol. 162(C), pages 401-415.

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    Keywords

    smart metering; feedback; household electricity consumption;

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