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Money doesn’t matter! Householders’ intentions to reduce standby power are unaffected by personalised pecuniary feedback

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  • Kathryn Buchanan
  • Riccardo Russo

Abstract

Many researchers have examined whether giving people feedback about their energy use can lead them to decrease it. However, to date no consensus has been reached about which type of eco-feedback is the most effective. We aim to test the efficacy of different feedback techniques by providing participants with personalised information about the annual monetary costs of their home’s standby power usage (i.e., appliances that consume electricity despite not being actively used). Using a sample of 708 participants we tested the following feedback strategies: advice, disaggregation, loss vs gain framing, social norms, and collective information. We measured the impact of each of these feedback conditions on knowledge and intention to change behaviour, and compared them to a control condition. Using both frequentist and Bayesian analyses, we found that relative to the control condition all the feedback strategies led participants to report significant gains in knowledge. Yet, neither the additional knowledge gains, nor the feedback approach used significantly affected behavioural intentions. Consequently, the results suggest that while a wide range of feedback strategies emphasizing the financial impact of standby power consumption can effectively improve knowledge, this approach alone is insufficient in inciting intentions to change energy consumption behaviours.

Suggested Citation

  • Kathryn Buchanan & Riccardo Russo, 2019. "Money doesn’t matter! Householders’ intentions to reduce standby power are unaffected by personalised pecuniary feedback," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-16, October.
  • Handle: RePEc:plo:pone00:0223727
    DOI: 10.1371/journal.pone.0223727
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    References listed on IDEAS

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    1. Buchanan, Kathryn & Russo, Riccardo & Anderson, Ben, 2014. "Feeding back about eco-feedback: How do consumers use and respond to energy monitors?," Energy Policy, Elsevier, vol. 73(C), pages 138-146.
    2. Amos Tversky & Daniel Kahneman, 1991. "Loss Aversion in Riskless Choice: A Reference-Dependent Model," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 1039-1061.
    3. Frederiks, Elisha R. & Stenner, Karen & Hobman, Elizabeth V., 2015. "Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1385-1394.
    4. Schultz, P. Wesley & Estrada, Mica & Schmitt, Joseph & Sokoloski, Rebecca & Silva-Send, Nilmini, 2015. "Using in-home displays to provide smart meter feedback about household electricity consumption: A randomized control trial comparing kilowatts, cost, and social norms," Energy, Elsevier, vol. 90(P1), pages 351-358.
    5. Rink Hoekstra & Rei Monden & Don van Ravenzwaaij & Eric-Jan Wagenmakers, 2018. "Bayesian reanalysis of null results reported in medicine: Strong yet variable evidence for the absence of treatment effects," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-9, April.
    6. Sorrell, Steve, 2015. "Reducing energy demand: A review of issues, challenges and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 74-82.
    7. Buchanan, Kathryn & Russo, Riccardo & Anderson, Ben, 2015. "The question of energy reduction: The problem(s) with feedback," Energy Policy, Elsevier, vol. 77(C), pages 89-96.
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