Energy Efficiency

, Volume 9, Issue 4, pp 911–924 | Cite as

Evaluating a behavioral demand response trial in Japan: evidence from the summer of 2013

  • Toshihiro MukaiEmail author
  • Ken-ichiro Nishio
  • Hidenori Komatsu
  • Teppei Uchida
  • Kyoko Ishida
Original Article


This paper presents results from a behavioral demand response trial targeted to both grid and residential peak hours, in which weekly feedback via paper-based reports, real-time feedback via an in-home display, 30-minute tiered rate, and email prompts are adopted to almost 230 residential customers of a condominium in Funabashi, a city located in Greater Tokyo. Through a randomized experiment, we find that the peak saving impact during grid peak hours (1–4 pm, weekdays only) was 11.6 %, given that all the four interventions provided all at once. In addition, the results show that the variation in peak saving effects by household characteristics exists, and the variation differs among packages of peak saving interventions. Furthermore, we analyzed how much informational elements in weekly reports are considered as useful by residential customers. These results suggest that feedback-based approaches for peak saving can promote households’ energy conservation behavior.


Behavioral intervention Peak saving Energy conservation Impact evaluation 


  1. Abrahamse, W., Steg, L., Vlek, C., & Rothengatter, T. (2005). A review of intervention studies aimed at household energy conservation. Journal of Environmental Psychology, 25(3), 273–291.CrossRefGoogle Scholar
  2. Accenture. (2012). Actionable insights for the new energy consumer. Google Scholar
  3. Allcott, H. (2011). Rethinking real-time electricity pricing. Resource and Energy Economics, 33(4), 820–842.CrossRefGoogle Scholar
  4. Darby, S. (2006). The effectiveness of feedback on energy consumption: a review for DEFRA of the literature on metering, billing and direct displays. University of Oxford Environmental Change Institute.Google Scholar
  5. Ehrhardt-Martinez, K., Donnelly K., Laitner J. (2010). Advanced metering initiatives and residential feedback programs: a meta-review for household electricity saving opportunities. Report Number E105, American Council for an Energy Efficient Economy.Google Scholar
  6. EPRI. (2009). Residential electricity use feedback: a research synthesis and economic framework.Google Scholar
  7. Faruqui, A., & Sergici, S. (2010). Household response to dynamic pricing of electricity: a survey of 15 experiments. Journal of Regulatory Economics, 38(2), 193–225.CrossRefGoogle Scholar
  8. Faruqui, A., Sergici, S., & Sharif, A. (2010). The impact of informational feedback on energy consumption—a survey of the experimental evidence. Energy, 35, 1598–1608.CrossRefGoogle Scholar
  9. Fischer, C. (2008). Feedback on household electricity consumption: a tool for saving energy? Energy Efficiency, 1(1), 79–104.CrossRefGoogle Scholar
  10. Iyengar, S. S., & Lepper, M. R. (2000). When choice is demotivating: can one desire too much of a good thing? Journal of Personality and Social Psychology, 79(6), 995–1006.CrossRefGoogle Scholar
  11. Jessoe, K., & Rapson, D. (2014). Knowledge is (less) power: experimental evidence from residential energy use. The American Economic Review, 104(4), 1417–1438.CrossRefGoogle Scholar
  12. Karlin, B., Zinger, J. F. & Ford, R. (2015). The Effects of feedback on energy conservation: a meta-analysis. Psychological Bulletin, 141(6), 1205–1227.Google Scholar
  13. METI (2014). With respect to the state and efforts of energy efficiency. A document distributed at the Energy Efficiency Subcommittee’s 2nd meeting (June 24th), Ministry of Economy, Trade and Industry. (In Japanese: 省エネルギーに関する情勢及び取組の状況について.省エネルギー小委員会(第2回)配布資料)Google Scholar
  14. Mori, I. (2011). Empowering households: research on presenting energy consumption benchmarks on energy bills. UK: Department of Energy and Climate Change.Google Scholar
  15. Nolan, J. M., Schultz, P. W., Cialdini, R. B., Goldstein, N. J., & Griskevicius, V. (2008). Normative social influence is underdetected. Personality and Social Psychology Bulletin, 34(7), 913–923.CrossRefGoogle Scholar
  16. Novemsky, N., & Kahneman, D. (2005). The boundaries of loss aversion. Journal of Marketing Research, 42(2), 119–128.CrossRefGoogle Scholar
  17. Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J., & Griskevicius, V. (2007). The constructive, destructive, and reconstructive power of social norms. Psychological Science, 18(5), 429–434.CrossRefGoogle Scholar
  18. Seligman, C., Darley, J. M., & Becker, L. J. (1978). Behavioral approaches to residential energy conservation. Energy and Buildings, 1(3), 325–337.CrossRefGoogle Scholar
  19. Sernhed, K., Pyrko J., Abaravicius J. (2003). Bill me this way! Customer preferences regarding electricity bills in Sweden. ECEEE 2003 Summer Study:1147–1150.Google Scholar
  20. Smith, G. E., Venkatraman, M. P., & Dholakia, R. R. (1999). Diagnosing the search cost effect: waiting time and the moderating impact of prior category knowledge. Journal of Economic Psychology, 20(3), 285–314.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Toshihiro Mukai
    • 1
    Email author
  • Ken-ichiro Nishio
    • 1
  • Hidenori Komatsu
    • 1
  • Teppei Uchida
    • 2
  • Kyoko Ishida
    • 3
  1. 1.Central Research Institute of Electric Power IndustryTokyoJapan
  2. 2.Familynet Japan CorporationTokyoJapan
  3. 3.Nomura Real Estate Development Co., Ltd.TokyoJapan

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