Skip to main content
SpringerLink
Log in

Behavioral Study of Demand Response: Web-Based Survey, Field Experiment, and Laboratory Experiment

  • Chapter
  • First Online:
Economically Enabled Energy Management

Abstract

This chapter analyzes customers’ electricity conservation behavior when demand response is called for. Behavioral economics provides very useful insights to account for human behavioral anomalies such as status quo bias, loss aversion, overconfidence, moral cost, and default bias. The chapter is composed of five sections. The second section investigates a Web-based survey of residential electricity plan choice. The third section investigates a field experiment on residential electricity plan choice. The fourth section investigates a laboratory experiment on residential energy conservation. The fifth section investigates a field experiment on building electricity conservation.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    According to the results of [33], the average marginal WTPs for a 1% dependency on renewable and nuclear sources were $0.28 (31 JPY if $1=110 JPY) and −$0.65 (−72 JPY if $1=110 JPY), respectively.

  2. 2.

    In estimating the selection probability, the attribute value of “Monthly electricity charges” is replaced with 1 if it is “the same as the present”, 0.9 if it is “10% decrease”, and 0.8 if it is “20% decrease”.

References

  1. Abildtrup J, Garcia S, Olsen SB, Stenger A (2013) Spatial preference heterogeneity in forest recreation. Ecol Econ 92:67–77

    Article  Google Scholar 

  2. Allcott H (2011) Social norms and energy conservation. J Publ Econ 95:1082–1095

    Article  Google Scholar 

  3. Barber BM, Odean T (2001) Boys will be boys: gender, overconfidence, and common stock investment. Q J Econ 116:261–292

    Article  Google Scholar 

  4. Bertrand M, Morse A (2011) RECAP disclosure, cognitive biases, and payday borrowing. J Finance 66:1865–1893

    Article  Google Scholar 

  5. Birol E, Karousakis K, Koundouri P (2006) Using a choice experiment to account for preference heterogeneity in wetland attributes: the case of Cheimaditida wetland in Greece. Ecol Econ 60:145–156

    Article  Google Scholar 

  6. Clark J, Friesen L (2009) Overconfidence in forecasts of own performance: an experimental study. Econ J 119(534):229–251

    Article  Google Scholar 

  7. Costa DL, Kahn ME (2013) Energy conservation “nudges” and environmentalist ideology: evidence from a randomized residential electricity field experiment. J Eur Econ Assoc 11:680–702

    Article  Google Scholar 

  8. Eil D, Rao JM (2011) The good news-bad news effect: asymmetric processing of objective information about yourself. Am Econ J Microecon 3:114–138

    Article  Google Scholar 

  9. Einav L, Finkelstein A, Ryan S, Schrimpf P, Cullen MR (2013) Selection on moral hazard in health insurance. Am Econ Rev 103(1):178

    Article  Google Scholar 

  10. Ertac S (2011) Does self-relevance affect information processing? Experimental evidence on the response to performance and non-performance feedback. J Econ Behav Organ 80:532–545

    Article  Google Scholar 

  11. Fischbacher U (2007) z-Tree: Zurich toolbox for ready-made economic experiments. Exp Econ 10:171–178

    Article  Google Scholar 

  12. Fowlie M, Wolfram C, Spurlock CA, Todd A, Baylis P, Cappers P (2017) Default effects and follow-on behavior: evidence from an electricity pricing program. Energy Institute at Haas, Working Papers WP-280

    Google Scholar 

  13. Giné X, Mazer RK (2016) Financial (Dis-)RECAP: evidence from a multi-country audit study. Policy research working papers

    Google Scholar 

  14. Griesinger DW, Livingston JW (1973) Toward a model of interpersonal motivation in experimental games. Behav Sci 18:173–188

    Article  Google Scholar 

  15. Handel BR (2013) Adverse selection and inertia in health insurance markets: when nudging hurts. Am Econ Rev 103(7):2643–2682

    Article  Google Scholar 

  16. Handel BR, Kolstad JT (2015) Health insurance for “Humans”: information frictions, plan choice, and consumer welfare. Am Econ Rev 105(8):2449–2500

    Article  Google Scholar 

  17. Herter K (2007) Residential implementation of critical-peak pricing of electricity. Energy Policy 35(4):2121–2130

    Article  Google Scholar 

  18. Hartman RS, Doane MJ, Woo C-K (1991) Consumer rationality and the status quo. Quart J Econ 106:141–162

    Article  Google Scholar 

  19. Hortaçsu A, Madanizadeh SA, Puller SL (2017) Power to choose? An analysis of consumer inertia in the residential electricity market. Am Econ J Econ Policy 9:192–226

    Article  Google Scholar 

  20. Ida T, Wang W (2015) A field experiment on dynamic electricity pricing in Los Alamos: Opt-in versus opt-out. Kyoto University, Discussion Paper No. E-14-010

    Google Scholar 

  21. Ida T, Motegi N, Ushifusa Y (2019) Behavioral study of personalized automated demand response in the workplace. Energy Policy 132:1009–1016

    Article  Google Scholar 

  22. Ishihara T, Ida T (2019) Effects of information provision on stated preferences and revealed preferences: field experiment of electricity plan choice before and after deregulation. Kyoto University, Discussion Paper No. E-19

    Google Scholar 

  23. Jain RK, Taylor JE, Peschiera G (2012) Assessing eco-feedback interface usage and design to drive energy efficiency in buildings. Energy Build 48:8–17

    Article  Google Scholar 

  24. Jimenez LR, Potter JM, George SS (2013) Smart pricing option interim evaluation. Sacramento Municipal Utility District

    Google Scholar 

  25. Kamenica E, Mullainathan S, Thaler R (2011) Helping consumers know themselves. Am Econ Rev 101:417–422

    Article  Google Scholar 

  26. Kling JR, Mullainathan S, Shafir E, Vermeulen LC, Wrobel MV (2012) Comparison friction: Experimental evidence from medicare drug plans. Quart J Econ 127:199–235

    Article  Google Scholar 

  27. Krioukov A, Dawson-Haggerty S, Lee L, Rehmane O, Culler D (2011) A living laboratory study in personalized automated lighting controls. 3rd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, Seattle, WA

    Google Scholar 

  28. Levitt SD, List JA (2007) What do laboratory experiments measuring social preferences reveal about the real world? J Econ Perspect 21:153–174

    Article  Google Scholar 

  29. Liebrand WBG (1984) The effect of social motives, communications and group sizes on behavior in an n-person multi-stage mixed motive game. Eur J Soc Psychol 14:239–264

    Article  Google Scholar 

  30. McFadden D, Train KE (2000) Mixed MNL models of discrete choice models of discrete response. J Appl Econom 15:447–470

    Article  Google Scholar 

  31. METI (Japan’s Ministry of Economy, Trade and Industry) (2018) Electricity system and market in Japan, presented from Tatsuya Shinkawa in Electricity and Gas Market Surveillance Commission

    Google Scholar 

  32. Miravete EJ (2003) Choosing the wrong calling plan? Ignorance and learning. Am Econ Rev 93(1):297–310

    Article  Google Scholar 

  33. Murakami K, Ida T, Tanaka M, Friedman L (2015) Consumers’ willingness to pay for renewable and nuclear energy: a comparative analysis between the US and Japan. Energy Econ 50:178–189

    Article  Google Scholar 

  34. Murakami K, Ida T (2019) Deregulation and status quo bias: evidence from stated and revealed switching behaviors in the electricity market in Japan. Graduate School of Economics, Kyoto University, Discussion Paper E-19-01

    Google Scholar 

  35. Offerman T, Sonnemans J, Arthur A (1996) Value orientation, expectations and voluntary contributions in public goods. Econ J 106:817–845

    Article  Google Scholar 

  36. Park E (2000) Warm-glow versus cold-prickle: a further experimental study of framing effects on free-riding. J Econ Behav Organ 43:405–421

    Article  Google Scholar 

  37. Piette MA, Schetrit O, Killacotte S, Cheung I, Li BZ (2015) Costs to automate demand response—taxonomy and results from field studies and programs. Lawrence Berkeley National Laboratory Report, LBNL Report Number 1003924

    Google Scholar 

  38. Sacramento Municipal Utility District (2014) Smart pricing options final evaluation: the final report on pilot design, implementation, and evaluation of the Sacramento Municipal Utility District’s Consumer Behavior Study

    Google Scholar 

  39. Siero FW, Bakker AB, Dekker GB, Van Den Burg MTC (1996) Changing organizational energy consumption behavior through comparative feedback. J Environ Psych 16:235–246

    Article  Google Scholar 

  40. SMUD (2014) Smart pricing options final evaluation: the final report on pilot design, implementation, and evaluation of the Sacramento Municipal Utility District’s Consumer Behavior Study

    Google Scholar 

  41. Tanaka K, Kurakawa H, Ishihara T, Ida T, Akao K (2020) Moral utility or moral tax? Experimental study of electricity conservation by social comparison. Kyoto University, Discussion Paper No. E-19-011

    Google Scholar 

  42. Thaler RH, Sunstein CR (2009) Nudge: improving decisions about health, wealth, and happiness. Penguin Books, London

    Google Scholar 

  43. Train KE (2009) Discrete choice methods with simulation, 2nd edn. Cambridge University Press, New York

    MATH  Google Scholar 

  44. Vanthournout K, Dupont B, Foubert W, Stuckens C, Claessens S (2015) An automated residential demand response pilot experiment, based on day-ahead dynamic pricing. Appl Energy 155:195–203

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graduate School of Economics, Kyoto University, Kyoto, 606-8501, Japan

    Takanori Ida & Takunori Ishihara

  2. Faculty of Economics and Business Administration, The University of Kitakyushu, Fukuoka, 802-8577, Japan

    Yoshiaki Ushifusa

  3. Faculty of Economics, Musashi University, Tokyo, 176-0011, Japan

    Kenta Tanaka

  4. Graduate School of Agriculture, Kyoto University, Kyoto, 606-8502, Japan

    Kayo Murakami

Authors
  1. Takanori Ida
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yoshiaki Ushifusa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kenta Tanaka
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kayo Murakami
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Takunori Ishihara
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Takanori Ida .

Editor information

Editors and Affiliations

  1. School of Engineering, Tokyo Institute of Technology, Meguro-ku, Tokyo, Japan

    Takeshi Hatanaka

  2. School of Advanced Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan

    Yasuaki Wasa

  3. Research Institute of Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan

    Kenko Uchida

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ida, T., Ushifusa, Y., Tanaka, K., Murakami, K., Ishihara, T. (2020). Behavioral Study of Demand Response: Web-Based Survey, Field Experiment, and Laboratory Experiment. In: Hatanaka, T., Wasa, Y., Uchida, K. (eds) Economically Enabled Energy Management. Springer, Singapore. https://doi.org/10.1007/978-981-15-3576-5_6

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-3576-5_6

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3575-8

  • Online ISBN: 978-981-15-3576-5

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics

Search

Navigation