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Correcting consumer misperception

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  • Omar Isaac Asensio

    (Georgia Institute of Technology)

Abstract

For the well informed, taking actions to curb energy consumption from household appliances is uncomplicated. Now, research shows that simple information provision interventions can correct consumer misperceptions of the energy consumed by common appliances, offering hope to the rest of us.

Suggested Citation

  • Omar Isaac Asensio, 2019. "Correcting consumer misperception," Nature Energy, Nature, vol. 4(10), pages 823-824, October.
    • Handle: RePEc:nat:natene:v:4:y:2019:i:10:d:10.1038_s41560-019-0472-5
    DOI: 10.1038/s41560-019-0472-5
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    Citations

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    Cited by:

    1. Chen, Si-Yuan & Xue, Meng-Tian & Wang, Zhao-Hua & Tian, Xin & Zhang, Bin, 2022. "Exploring pathways of phasing out clean heating subsidies for rural residential buildings in China," Energy Economics, Elsevier, vol. 116(C).
    2. Ana Salomé García-Muñiz & María Rosalía Vicente, 2021. "The Effects of Informational Feedback on the Energy Consumption of Online Services: Some Evidence for the European Union," Energies, MDPI, vol. 14(10), pages 1-14, May.
    3. Giovanna d’Adda & Yu Gao & Massimo Tavoni, 2022. "A randomized trial of energy cost information provision alongside energy-efficiency classes for refrigerator purchases," Nature Energy, Nature, vol. 7(4), pages 360-368, April.
    4. Verma, Pramit & Kumari, Tanu & Raghubanshi, Akhilesh Singh, 2021. "Energy emissions, consumption and impact of urban households: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    5. Gong, Yuanchao & Cai, Bo-feng & Sun, Yan, 2020. "Perceived fiscal subsidy predicts rural residential acceptance of clean heating: Evidence from an indoor-survey in a pilot city in China," Energy Policy, Elsevier, vol. 144(C).
    6. Omar Isaac Asensio & Camila Z. Apablaza & M. Cade Lawson & Sarah Elizabeth Walsh, 2022. "A field experiment on workplace norms and electric vehicle charging etiquette," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 183-196, February.
    7. Ahmadian, Amirhossein & Ghodrati, Vahid & Gadh, Rajit, 2023. "Artificial deep neural network enables one-size-fits-all electric vehicle user behavior prediction framework," Applied Energy, Elsevier, vol. 352(C).

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