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Which dynamic pricing rule is most preferred by consumers?—Application of choice experiment

Author

Listed:
  • Yumi Yoshida

    (Fukui University of Technology)

  • Kenta Tanaka

    (Musashi University)

  • Shunsuke Managi

    (Kyushu University
    Queensland University of Technology)

Abstract

This study investigates consumers’ preference for dynamic pricing rules using a choice experiment. Among alternative electricity pricing rules, time of use (TOU) is most preferred by consumers, and our estimation results show that TOU has the highest value of WTP among pricing rules. Furthermore, consumers’ characteristics affect their choice of a pricing rule. Our results show that risk preference in particular affects the choice probability of each pricing rule.

Suggested Citation

  • Yumi Yoshida & Kenta Tanaka & Shunsuke Managi, 2017. "Which dynamic pricing rule is most preferred by consumers?—Application of choice experiment," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 6(1), pages 1-11, December.
    • Handle: RePEc:spr:jecstr:v:6:y:2017:i:1:d:10.1186_s40008-017-0064-0
    DOI: 10.1186/s40008-017-0064-0
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    References listed on IDEAS

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    1. Severin Borenstein, 2007. "Customer Risk from Real-Time Retail Electricity Pricing: Bill Volatility and Hedgability," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 111-130.
    2. S. Borenstein, 2013. "Effective and Equitable Adoption of Opt-In Residential Dynamic Electricity Pricing," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 42(2), pages 127-160, March.
    3. Paul L. Joskow & Catherine D. Wolfram, 2012. "Dynamic Pricing of Electricity," American Economic Review, American Economic Association, vol. 102(3), pages 381-385, May.
    4. Faruqui, Ahmad & George, Stephen, 2005. "Quantifying Customer Response to Dynamic Pricing," The Electricity Journal, Elsevier, vol. 18(4), pages 53-63, May.
    5. Allcott, Hunt, 2011. "Rethinking real-time electricity pricing," Resource and Energy Economics, Elsevier, vol. 33(4), pages 820-842.
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    7. Herter, Karen, 2007. "Residential implementation of critical-peak pricing of electricity," Energy Policy, Elsevier, vol. 35(4), pages 2121-2130, April.
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    Citations

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    Cited by:

    1. Nakai, Miwa & von Loessl, Victor & Wetzel, Heike, 2024. "Preferences for dynamic electricity tariffs: A comparison of households in Germany and Japan," Ecological Economics, Elsevier, vol. 223(C).
    2. von Loessl, Victor, 2023. "Smart meter-related data privacy concerns and dynamic electricity tariffs: Evidence from a stated choice experiment," Energy Policy, Elsevier, vol. 180(C).
    3. Darshana Rajapaksa & Robert Gifford & Benno Torgler & María A. García-Valiñas & Wasantha Athukorala & Shunsuke Managi & Clevo Wilson, 2019. "Do monetary and non-monetary incentives influence environmental attitudes and behavior? Evidence from an experimental analysis," Post-Print hal-03191523, HAL.
    4. Minseok Jang & Hyun-Cheol Jeong & Taegon Kim & Sung-Kwan Joo, 2021. "Load Profile-Based Residential Customer Segmentation for Analyzing Customer Preferred Time-of-Use (TOU) Tariffs," Energies, MDPI, vol. 14(19), pages 1-12, September.
    5. Lim, Keumju & Lee, Jongsu & Lee, Hyunjoo, 2021. "Implementing automated residential demand response in South Korea: Consumer preferences and market potential," Utilities Policy, Elsevier, vol. 70(C).
    6. Bernadeta Gołębiowska, 2020. "Preferences for demand side management—a review of choice experiment studies," Working Papers 2020-05, Faculty of Economic Sciences, University of Warsaw.

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