IDEAS home Printed from https://ideas.repec.org/p/ris/fcnwpa/2015_008.html
   My bibliography  Save this paper

Effectiveness of Real Time Information Provision with Time of Use Pricing

Author

Listed:
  • Pon, Shirley

    (Department of Agricultural and Resource Economics - University of Maryland)

Abstract

Real time information feedback combined with various pricing schemes has been found to reduce residential energy consumption more than information and pricing policies alone. I examine the effect of information provision with bi-monthly, monthly, and real time pricing with in-home displays with a time-of-use pricing scheme on consumption over each month of the Irish Consumer Behavior Trial. I find that time-of-use pricing with real time pricing information reduce electricity usage up to 8.7 percent during peak times at the start of the trial but the effect decays over the first three months and after three months the trial group is indistinguishable from the control group. I do not find statistically significant improvements in energy savings when comparing monthly and bi-monthly billing treatments. These findings suggest that increasing billing reports to the monthly level or a web application providing real time information may be more cost effective than providing in-home displays.

Suggested Citation

  • Pon, Shirley, 2015. "Effectiveness of Real Time Information Provision with Time of Use Pricing," FCN Working Papers 8/2015, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised Oct 2015.
    • Handle: RePEc:ris:fcnwpa:2015_008
    as

    Download full text from publisher

    File URL: http://www.fcn.eonerc.rwth-aachen.de/global/show_document.asp?id=aaaaaaaaaaoymed
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Newsham, Guy R. & Bowker, Brent G., 2010. "The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review," Energy Policy, Elsevier, vol. 38(7), pages 3289-3296, July.
    2. Victor Stango & Jonathan Zinman, 2014. "Limited and Varying Consumer Attention: Evidence from Shocks to the Salience of Bank Overdraft Fees," Review of Financial Studies, Society for Financial Studies, vol. 27(4), pages 990-1030.
    3. Joachain, Hélène & Klopfert, Frédéric, 2014. "Smarter than metering? Coupling smart meters and complementary currencies to reinforce the motivation of households for energy savings," Ecological Economics, Elsevier, vol. 105(C), pages 89-96.
    4. Iacus, Stefano & King, Gary & Porro, Giuseppe, 2009. "cem: Software for Coarsened Exact Matching," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 30(i09).
    5. Torriti, Jacopo, 2012. "Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy," Energy, Elsevier, vol. 44(1), pages 576-583.
    6. Sexton, Richard J & Johnson, Nancy Brown & Konakayama, Akira, 1987. "Consumer Response to Continuous-Display Electricity-Use Monitors in a Time-of-Use Pricing Experiment," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(1), pages 55-62, June.
    7. Katrina Jessoe & David Rapson, 2014. "Knowledge Is (Less) Power: Experimental Evidence from Residential Energy Use," American Economic Review, American Economic Association, vol. 104(4), pages 1417-1438, April.
    8. Hargreaves, Tom & Nye, Michael & Burgess, Jacquelin, 2013. "Keeping energy visible? Exploring how householders interact with feedback from smart energy monitors in the longer term," Energy Policy, Elsevier, vol. 52(C), pages 126-134.
    9. Matthew Blackwell & Stefano Iacus & Gary King & Giuseppe Porro, 2009. "cem: Coarsened exact matching in Stata," Stata Journal, StataCorp LP, vol. 9(4), pages 524-546, December.
    10. Ivanov, Chris & Getachew, Lullit & Fenrick, Steve A. & Vittetoe, Bethany, 2013. "Enabling technologies and energy savings: The case of EnergyWise Smart Meter Pilot of Connexus Energy," Utilities Policy, Elsevier, vol. 26(C), pages 76-84.
    11. Eugenio J. Miravete, 2003. "Choosing the Wrong Calling Plan? Ignorance and Learning," American Economic Review, American Economic Association, vol. 93(1), pages 297-310, March.
    12. Sridhar Narayanan & Pradeep Chintagunta & Eugenio Miravete, 2007. "The role of self selection, usage uncertainty and learning in the demand for local telephone service," Quantitative Marketing and Economics (QME), Springer, vol. 5(1), pages 1-34, March.
    13. Sebastien Houde, Annika Todd, Anant Sudarshan, June A. Flora , and K. Carrie Armel, 2013. "Real-time Feedback and Electricity Consumption: A Field Experiment Assessing the Potential for Savings and Persistence," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    14. Richins, Marsha L. & Bloch, Peter H., 1991. "Post-purchase product satisfaction: Incorporating the effects of involvement and time," Journal of Business Research, Elsevier, vol. 23(2), pages 145-158, September.
    15. Richins, Marsha L & Bloch, Peter H, 1986. "After the New Wears Off: The Temporal Context of Product Involvement," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(2), pages 280-285, September.
    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. 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).
    2. Batalla-Bejerano, Joan & Trujillo-Baute, Elisa & Villa-Arrieta, Manuel, 2020. "Smart meters and consumer behaviour: Insights from the empirical literature," Energy Policy, Elsevier, vol. 144(C).
    3. Strong, Derek Ryan, 2017. "The Early Diffusion of Smart Meters in the US Electric Power Industry," Thesis Commons 7zprk, Center for Open Science.
    4. Kendel, Adnane & Lazaric, Nathalie & Maréchal, Kevin, 2017. "What do people ‘learn by looking’ at direct feedback on their energy consumption? Results of a field study in Southern France," Energy Policy, Elsevier, vol. 108(C), pages 593-605.
    5. Jing Liang & Yueming Qiu & Bo Xing, 2021. "Social Versus Private Benefits of Energy Efficiency Under Time-of-Use and Increasing Block Pricing," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 78(1), pages 43-75, January.
    6. Buckley, Penelope, 2020. "Prices, information and nudges for residential electricity conservation: A meta-analysis," Ecological Economics, Elsevier, vol. 172(C).
    7. Khosrowpour, Ardalan & Jain, Rishee K. & Taylor, John E. & Peschiera, Gabriel & Chen, Jiayu & Gulbinas, Rimas, 2018. "A review of occupant energy feedback research: Opportunities for methodological fusion at the intersection of experimentation, analytics, surveys and simulation," Applied Energy, Elsevier, vol. 218(C), pages 304-316.
    8. Agarwal, Sumit & Sing, Tien Foo & Sultana, Mahanaaz, 2022. "Public media campaign and energy conservation: A natural experiment in Singapore," Energy Economics, Elsevier, vol. 114(C).
    9. Ross C. Beppler & Daniel C. Matisoff & Matthew E. Oliver, 2023. "Electricity consumption changes following solar adoption: Testing for a solar rebound," Economic Inquiry, Western Economic Association International, vol. 61(1), pages 58-81, January.
    10. Liddle, Brantley & Loi, Tian Sheng Allan & Owen, Anthony D. & Tao, Jacqueline, 2020. "Evaluating consumption and cost savings from new air-conditioner purchases: The case of Singapore," Energy Policy, Elsevier, vol. 145(C).
    11. Kenta Tanaka & Clevo Wilson & Shunsuke Managi, 2022. "Impact of feed-in tariffs on electricity consumption," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 24(1), pages 49-72, January.
    12. Lucas A. Mariani & Jose Renato Haas Ornelas & Bernardo Ricca, 2023. "Banks’ Physical Footprint and Financial Technology Adoption," Working Papers Series 576, Central Bank of Brazil, Research Department.
    13. Sergio Afcha & Jose García-Quevedo, 2016. "The impact of R&D subsidies on R&D employment composition," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 25(6), pages 955-975.
    14. Jin, Haofeng, 2022. "The effect of overspending on tariff choices and customer churn: Evidence from mobile plan choices," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    15. Merino, José & Borja, Victor Hugo & Lopez, Oliva & Ochoa, José Alfredo & Clark, Eduardo & Petersen, Lila & Caballero, Saul, 2021. "Ivermectin and the odds of hospitalization due to COVID-19: evidence from a quasi-experimental analysis based on a public intervention in Mexico City," SocArXiv r93g4, Center for Open Science.
    16. Jing Wang & Gen Li & Kai-Lung Hui, 2022. "Monetary Incentives and Knowledge Spillover: Evidence from a Natural Experiment," Management Science, INFORMS, vol. 68(5), pages 3549-3572, May.
    17. Wheeler, P. Barrett, 2019. "Loan loss accounting and procyclical bank lending: The role of direct regulatory actions," Journal of Accounting and Economics, Elsevier, vol. 67(2), pages 463-495.
    18. Leduc, Elisabeth & Tojerow, Ilan, 2020. "Subsidizing Domestic Services as a Tool to Fight Unemployment: Effectiveness and Hidden Costs," IZA Discussion Papers 13544, Institute of Labor Economics (IZA).
    19. Patricio Aroca & Juan Gabriel Brida & Juan Sebastián Pereyra & Serena Volo, 2014. "Tourism statistics: correcting data inadequacy using coarsened exact matching," BEMPS - Bozen Economics & Management Paper Series BEMPS22, Faculty of Economics and Management at the Free University of Bozen.
    20. Guignet, Dennis & Jenkins, Robin R. & Belke, James & Mason, Henry, 2023. "The property value impacts of industrial chemical accidents," Journal of Environmental Economics and Management, Elsevier, vol. 120(C).

    More about this item

    Keywords

    time-of-use pricing; information provision; feedback; energy efficiency behavior;
    All these keywords.

    JEL classification:

    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ris:fcnwpa:2015_008. 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: Hendrik Schmitz (email available below). General contact details of provider: https://edirc.repec.org/data/fceonde.html .

    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.