IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v318y2022ics0306261922006067.html
   My bibliography  Save this article

The deterring effect of monetary costs on smart meter adoption

Author

Listed:
  • Tsvetanov, Tsvetan

Abstract

This paper utilizes an experiment embedded within a hypothetical survey to a nationally representative sample of US households to quantify the extent to which monetary installation costs (in the form of a monthly electric bill surcharge) can present a barrier to the residential adoption of smart meters. The results suggest that a $2.50/month surcharge would decrease the average probability of smart meter adoption by 18 percentage points. This estimate is robust to a variety of alternative empirical specifications and sample restrictions. There is considerable heterogeneity in the estimated effect based on household electricity consumption, familiarity with smart meter technology, and perceived accuracy of traditional meters. These findings have important implications for electricity providers and policymakers, as they suggest that eliminating installation charges would be justified from a benefit-cost perspective and point to potential gains from redesigning smart meter policy to account for household heterogeneity.

Suggested Citation

  • Tsvetanov, Tsvetan, 2022. "The deterring effect of monetary costs on smart meter adoption," Applied Energy, Elsevier, vol. 318(C).
    • Handle: RePEc:eee:appene:v:318:y:2022:i:c:s0306261922006067
    DOI: 10.1016/j.apenergy.2022.119247
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922006067
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.119247?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. John Micklewright & Sylke V. Schnepf, 2010. "How reliable are income data collected with a single question?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 409-429, April.
    2. Chou, Jui-Sheng & Gusti Ayu Novi Yutami, I, 2014. "Smart meter adoption and deployment strategy for residential buildings in Indonesia," Applied Energy, Elsevier, vol. 128(C), pages 336-349.
    3. David M. A. Murphy & Vesall Nourani & David R. Lee, 2022. "Chatting at Church: Information Diffusion through Religious Networks," The Review of Economics and Statistics, MIT Press, vol. 104(3), pages 449-464, May.
    4. Buchanan, Kathryn & Banks, Nick & Preston, Ian & Russo, Riccardo, 2016. "The British public’s perception of the UK smart metering initiative: Threats and opportunities," Energy Policy, Elsevier, vol. 91(C), pages 87-97.
    5. Gerpott, Torsten J. & Paukert, Mathias, 2013. "Determinants of willingness to pay for smart meters: An empirical analysis of household customers in Germany," Energy Policy, Elsevier, vol. 61(C), pages 483-495.
    6. Balta-Ozkan, Nazmiye & Davidson, Rosemary & Bicket, Martha & Whitmarsh, Lorraine, 2013. "Social barriers to the adoption of smart homes," Energy Policy, Elsevier, vol. 63(C), pages 363-374.
    7. Isaac Koomson & Renato A. Villano & David Hadley, 2020. "Intensifying financial inclusion through the provision of financial literacy training: a gendered perspective," Applied Economics, Taylor & Francis Journals, vol. 52(4), pages 375-387, January.
    8. Mah, Daphne Ngar-yin & van der Vleuten, Johannes Marinus & Hills, Peter & Tao, Julia, 2012. "Consumer perceptions of smart grid development: Results of a Hong Kong survey and policy implications," Energy Policy, Elsevier, vol. 49(C), pages 204-216.
    9. Krishnamurti, Tamar & Schwartz, Daniel & Davis, Alexander & Fischhoff, Baruch & de Bruin, Wändi Bruine & Lave, Lester & Wang, Jack, 2012. "Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters," Energy Policy, Elsevier, vol. 41(C), pages 790-797.
    10. Park, Chan-Kook & Kim, Hyun-Jae & Kim, Yang-Soo, 2014. "A study of factors enhancing smart grid consumer engagement," Energy Policy, Elsevier, vol. 72(C), pages 211-218.
    11. Pepermans, Guido, 2014. "Valuing smart meters," Energy Economics, Elsevier, vol. 45(C), pages 280-294.
    12. McKenna, Eoghan & Richardson, Ian & Thomson, Murray, 2012. "Smart meter data: Balancing consumer privacy concerns with legitimate applications," Energy Policy, Elsevier, vol. 41(C), pages 807-814.
    13. Peter A. Groothuis & Tanga McDaniel Mohr, 2014. "Do Consumers Want Smart Meters? Incentives or Inertia: Evidence from North Carolina and Lessons for Policy," Economics of Energy & Environmental Policy, International Association for Energy Economics, vol. 0(Number 1).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shubhra Chaudhry & Arne Surmann & Matthias Kühnbach & Frank Pierie, 2022. "Renewable Energy Communities as Modes of Collective Prosumership: A Multi-Disciplinary Assessment, Part I—Methodology," Energies, MDPI, vol. 15(23), pages 1-16, November.

    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. Christine Milchram & Geerten Van de Kaa & Neelke Doorn & Rolf Künneke, 2018. "Moral Values as Factors for Social Acceptance of Smart Grid Technologies," Sustainability, MDPI, vol. 10(8), pages 1-23, August.
    2. Strong, Derek Ryan, 2017. "The Early Diffusion of Smart Meters in the US Electric Power Industry," Thesis Commons 7zprk, Center for Open Science.
    3. Chou, Jui-Sheng & Kim, Changwan & Ung, Thanh-Khiet & Yutami, I Gusti Ayu Novi & Lin, Guo-Tai & Son, Hyojoo, 2015. "Cross-country review of smart grid adoption in residential buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 192-213.
    4. Chamaret, Cécile & Steyer, Véronique & Mayer, Julie C., 2020. "“Hands off my meter!” when municipalities resist smart meters: Linking arguments and degrees of resistance," Energy Policy, Elsevier, vol. 144(C).
    5. Lopes, Marta A.R. & Henggeler Antunes, Carlos & Janda, Kathryn B. & Peixoto, Paulo & Martins, Nelson, 2016. "The potential of energy behaviours in a smart(er) grid: Policy implications from a Portuguese exploratory study," Energy Policy, Elsevier, vol. 90(C), pages 233-245.
    6. Chou, Jui-Sheng & Gusti Ayu Novi Yutami, I, 2014. "Smart meter adoption and deployment strategy for residential buildings in Indonesia," Applied Energy, Elsevier, vol. 128(C), pages 336-349.
    7. Tu, Gengyang & Faure, Corinne & Schleich, Joachim & Guetlein, Marie-Charlotte, 2021. "The heat is off! The role of technology attributes and individual attitudes in the diffusion of Smart thermostats – findings from a multi-country survey," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    8. Milchram, Christine & Hillerbrand, Rafaela & van de Kaa, Geerten & Doorn, Neelke & Künneke, Rolf, 2018. "Energy Justice and Smart Grid Systems: Evidence from the Netherlands and the United Kingdom," Applied Energy, Elsevier, vol. 229(C), pages 1244-1259.
    9. Julien Lancelot Michellod & Declan Kuch & Christian Winzer & Martin K. Patel & Selin Yilmaz, 2022. "Building Social License for Automated Demand-Side Management—Case Study Research in the Swiss Residential Sector," Energies, MDPI, vol. 15(20), pages 1-25, October.
    10. Yash Chawla & Anna Kowalska-Pyzalska & Widayat Widayat, 2019. "Consumer Willingness and Acceptance of Smart Meters in Indonesia," Resources, MDPI, vol. 8(4), pages 1-23, November.
    11. Yash Chawla & Anna Kowalska-Pyzalska, 2019. "Public Awareness and Consumer Acceptance of Smart Meters among Polish Social Media Users," Energies, MDPI, vol. 12(14), pages 1-27, July.
    12. Jacqueline Nicole Adams & Zsófia Deme Bélafi & Miklós Horváth & János Balázs Kocsis & Tamás Csoknyai, 2021. "How Smart Meter Data Analysis Can Support Understanding the Impact of Occupant Behavior on Building Energy Performance: A Comprehensive Review," Energies, MDPI, vol. 14(9), pages 1-23, April.
    13. Yash Chawla & Anna Kowalska-Pyzalska & Burcu Oralhan, 2020. "Attitudes and Opinions of Social Media Users Towards Smart Meters’ Rollout in Turkey," Energies, MDPI, vol. 13(3), pages 1-27, February.
    14. Kowalska-Pyzalska, Anna, 2018. "What makes consumers adopt to innovative energy services in the energy market? A review of incentives and barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3570-3581.
    15. Eunice Espe & Vidyasagar Potdar & Elizabeth Chang, 2018. "Prosumer Communities and Relationships in Smart Grids: A Literature Review, Evolution and Future Directions," Energies, MDPI, vol. 11(10), pages 1-24, September.
    16. Anna Kowalska-Pyzalska & Katarzyna Byrka, 2019. "Determinants of the Willingness to Energy Monitoring by Residential Consumers: A Case Study in the City of Wroclaw in Poland," Energies, MDPI, vol. 12(5), pages 1-20, March.
    17. Le Ray, G. & Pinson, P., 2020. "The ethical smart grid: Enabling a fruitful and long-lasting relationship between utilities and customers," Energy Policy, Elsevier, vol. 140(C).
    18. Abolhosseini, Shahrouz & Heshmati, Almas & Altmann, Jörn, 2014. "A Review of Renewable Energy Supply and Energy Efficiency Technologies," IZA Discussion Papers 8145, Institute of Labor Economics (IZA).
    19. Xu, Xiaojing & Chen, Chien-fei & Zhu, Xiaojuan & Hu, Qinran, 2018. "Promoting acceptance of direct load control programs in the United States: Financial incentive versus control option," Energy, Elsevier, vol. 147(C), pages 1278-1287.
    20. Hafize Nurgul Durmus Senyapar & Ramazan Bayindir, 2023. "The Research Agenda on Smart Grids: Foresights for Social Acceptance," Energies, MDPI, vol. 16(18), pages 1-31, September.

    More about this item

    Keywords

    Smart meters; Adoption barriers; Costs; Experiment;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • 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

    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:eee:appene:v:318:y:2022:i:c:s0306261922006067. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.