IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v35y2010i4p1598-1608.html
   My bibliography  Save this article

The impact of informational feedback on energy consumption—A survey of the experimental evidence

Author

Listed:
  • Faruqui, Ahmad
  • Sergici, Sanem
  • Sharif, Ahmed

Abstract

In theory, In-Home Displays (IHDs) can revolutionize the way utilities communicate information to customers because they can induce changes in customer behavior even when they are not accompanied by a change in electric prices or rebates for purchasing efficient equipment. IHDs provide consumers with direct feedback—real-time information on energy consumption and costs—and turn a once opaque and static electric bill into a transparent, dynamic, and controllable process. However, to what extent do consumers actually respond to the direct feedback provided by IHDs?

Suggested Citation

  • Faruqui, Ahmad & Sergici, Sanem & Sharif, Ahmed, 2010. "The impact of informational feedback on energy consumption—A survey of the experimental evidence," Energy, Elsevier, vol. 35(4), pages 1598-1608.
    • Handle: RePEc:eee:energy:v:35:y:2010:i:4:p:1598-1608
    DOI: 10.1016/j.energy.2009.07.042
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544209003387
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2009.07.042?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Isamu Matsukawa, 2004. "The Effects of Information on Residential Demand for Electricity," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 1-18.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gans, Will & Alberini, Anna & Longo, Alberto, 2013. "Smart meter devices and the effect of feedback on residential electricity consumption: Evidence from a natural experiment in Northern Ireland," Energy Economics, Elsevier, vol. 36(C), pages 729-743.
    2. Schleich, Joachim & Klobasa, Marian & Brunner, Marc & Gölz, Sebastian & Götz, Konrad, 2011. "Smart metering in Germany and Austria: Results of providing feedback information in a field trial," Working Papers "Sustainability and Innovation" S6/2011, Fraunhofer Institute for Systems and Innovation Research (ISI).
    3. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs," HSC Research Reports HSC/13/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    4. Manuel Frondel and Gerhard Kussel, 2019. "Switching on Electricity Demand Response: Evidence for German Households," The Energy Journal, International Association for Energy Economics, vol. 0(Number 5).
    5. repec:wvu:wpaper:06-01 is not listed on IDEAS
    6. Gilbert E. Metcalf, 2006. "Energy Conservation in the United States: Understanding its Role in Climate Policy," Discussion Papers Series, Department of Economics, Tufts University 0609, Department of Economics, Tufts University.
    7. Strong Aaron & Goemans Chris, 2014. "Quantity Uncertainty and Demand: The Case of Water Smart Reader Ownership," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 14(3), pages 1-26, July.
    8. Carsten Lynge Jensen, Lars Garn Hansen, Troels Fjordbak, and Erik Gudbjerg, 2012. "Providing Free Autopoweroff Plugs: Measuring the Effect on Households' Electricity Consumption through a Field Experiment," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    9. Dorothee Charlier and Berangere Legendre, 2019. "A Multidimensional Approach to Measuring Fuel Poverty," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    10. Lynham, John & Nitta, Kohei & Saijo, Tatsuyoshi & Tarui, Nori, 2016. "Why does real-time information reduce energy consumption?," Energy Economics, Elsevier, vol. 54(C), pages 173-181.
    11. Giraudet, Louis-Gaëtan, 2020. "Energy efficiency as a credence good: A review of informational barriers to energy savings in the building sector," Energy Economics, Elsevier, vol. 87(C).
    12. Iztok Podbregar & Sanja Filipović & Mirjana Radovanović & Olga Mirković Isaeva & Polona Šprajc, 2021. "Electricity Prices and Consumer Behavior, Case Study Serbia—Randomized Control Trials Method," Energies, MDPI, vol. 14(3), pages 1-12, January.
    13. Buyung Romadhoni & Akhmad Akhmad, 2020. "Household Electricity Demand in South Sulawesi, Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 229-233.
    14. S. Gaudin, 2006. "Effect of price information on residential water demand," Applied Economics, Taylor & Francis Journals, vol. 38(4), pages 383-393.
    15. Mizobuchi, Kenichi & Takeuchi, Kenji, 2013. "The influences of financial and non-financial factors on energy-saving behaviour: A field experiment in Japan," Energy Policy, Elsevier, vol. 63(C), pages 775-787.
    16. Kazutoshi Tsuda & Michinori Uwasu & Keishiro Hara & Yukari Fuchigami, 2017. "Approaches to induce behavioral changes with respect to electricity consumption," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 7(1), pages 30-38, March.
    17. Quinn Keefer & Galib Rustamov, 2018. "Limited attention in residential energy markets: a regression discontinuity approach," Empirical Economics, Springer, vol. 55(3), pages 993-1017, November.
    18. Sovacool, Benjamin K., 2009. "The importance of comprehensiveness in renewable electricity and energy-efficiency policy," Energy Policy, Elsevier, vol. 37(4), pages 1529-1541, April.
    19. Akito Ozawa & Ryota Furusato & Yoshikuni Yoshida, 2017. "Tailor-Made Feedback to Reduce Residential Electricity Consumption: The Effect of Information on Household Lifestyle in Japan," Sustainability, MDPI, vol. 9(4), pages 1-23, March.
    20. Shirley Pon, 2017. "The Effect of Information on TOU Electricity Use: an Irish residential study," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).
    21. Andersen, Frits Møller & Baldini, Mattia & Hansen, Lars Gårn & Jensen, Carsten Lynge, 2017. "Households’ hourly electricity consumption and peak demand in Denmark," Applied Energy, Elsevier, vol. 208(C), pages 607-619.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:35:y:2010:i:4:p:1598-1608. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.