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Real-time feedback promotes energy conservation in the absence of volunteer selection bias and monetary incentives

A Publisher Correction to this article was published on 20 September 2019

A Publisher Correction to this article was published on 08 March 2019

This article has been updated


Feedback interventions have proved to be effective at promoting energy conservation behaviour, and digital technologies have the potential to make interventions more powerful and scalable. In particular, real-time feedback on a specific, energy-intensive activity may induce considerable behaviour change and savings. Yet the majority of feedback studies that report large effects are conducted with opt-in samples of individuals who volunteer to participate. Here we show that real-time feedback on resource consumption during showering induces substantial energy conservation in an uninformed sample of guests at 6 hotels (265 rooms, N = 19,596 observations). The treatment effects are large (11.4% reduction in energy use), indicating that the real-time feedback induced substantial energy conservation among participants who did not opt in, and in a context where participants were not financially responsible for energy costs. We thus provide empirical evidence for real-time feedback as a scalable and cost-efficient policy instrument for fostering resource conservation among the broader public.

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Fig. 1: Smart shower meter.

Amphiro AG (b,c)

Fig. 2: Effect of consumption feedback.

Data availability

The data that support the findings of this study are available at

Change history

  • 20 September 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

  • 08 March 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.


  1. Sovacool, B. K. Diversity: energy studies need social science. Nature 511, 529–530 (2014).

    Article  Google Scholar 

  2. Allcott, H. & Greenstone, M. Is there an energy efficiency gap? J. Econ. Perspect. 26, 3–28 (2012).

    Article  Google Scholar 

  3. Allcott, H. & Mullainathan, S. Behavior and energy policy. Science 327, 1204–1205 (2010).

    Article  Google Scholar 

  4. Tiefenbeck, V. Bring behaviour into the digital transformation. Nat. Energy 2, 17085 (2017).

    Article  Google Scholar 

  5. Darby, S. The Effectiveness of Feedback on Energy Consumption - A Review for DEFRA of the Literature on Metering Billing and Direct Display s (Environmental Change Institute, University of Oxford, Oxford, 2006).

  6. Ehrhardt-Martinez, K. et al. Advanced Metering Initiatives and Residential Feedback Programs: A Meta-Review for Household Electricity-Saving Opportunities (Washington, DC, American Council for an Energy-Efficient Economy, 2010).

  7. Davis, A. L., Krishnamurti, T., Fischhoff, B. & Bruine de Bruin, W. Setting a standard for electricity pilot studies. Energy Policy 62, 401–409 (2013).

    Article  Google Scholar 

  8. McKerracher, C. & Torriti, J. Energy consumption feedback in perspective: integrating Australian data to meta-analyses on in-home displays. Energy Effic. 6, 387–405 (2013).

    Article  Google Scholar 

  9. Kelly, J. & Knottenbelt, W. Does disaggregated electricity feedback reduce domestic electricity consumption? A systematic review of the literature. 1605, 00962v2 (2016).

  10. Allcott, H. & Mullainathan, S. External Validity and Partner Selection Bias Working Paper No. 18373 (NBER, 2012).

  11. Schleich, J., Klobasa, M., Götz, S. & Brunner, M. Effects of feedback on residential electricity demand: findings from a field trial in Austria. Energy Policy 61, 1097–1106 (2013).

    Article  Google Scholar 

  12. Buchanan, K., Russo, R. & Anderson, B. The question of energy reduction: The problem(s) with feedback. Energy Policy 77, 89–96 (2015).

    Article  Google Scholar 

  13. Delmas, M. A., Fischlein, M. & Asensio, O. I. Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012. Energy Policy 61, 729–739 (2013).

    Article  Google Scholar 

  14. Abrahamse, W., Steg, L., Vlek, C. & Rothengatter, T. A review of intervention studies aimed at household energy conservation. J. Environ. Psychol. 25, 273–291 (2005).

    Article  Google Scholar 

  15. Haynes, L., Service, O., Goldacre, B. & Torgerson, D. Test, Learn, Adapt: Developing Public Policy with Randomised Controlled Trials (London Cabinet Office Behavioural Insights Team, 2012).

  16. Vine, E., Sullivan, M., Lutzenhiser, L., Blumstein, C. & Miller, B. Experimentation and the evaluation of energy efficiency programs. Energy Effic. 7, 627–640 (2014).

    Article  Google Scholar 

  17. Campbell, D. T. Reform as experiments. Am. Psychol. 24, 409–429 (1969).

    Article  Google Scholar 

  18. Clark, C. F., Kotchen, M. J. & Moore, M. R. Internal and external influences on pro-environmental behavior: Participation in a green electricity program. J. Environ. Psychol. 23, 237–246 (2003).

    Article  Google Scholar 

  19. Sulyma, I., Tiedemann, K., Pedersen, M., Rebman, M. & Yu, M. Experimental evidence: a residential time of use pilot. In Proc. ACEEE Summer Study Energy Effic. Build. 292–304 (ACEEE, 2008).

  20. Baladi, S. M., Herriges, J. A. & Sweeney, T. J. Residential response to voluntary time-of-use electricity rates. Resour. Energy Econ. 20, 225–244 (1998).

    Article  Google Scholar 

  21. Herter, K., Wood, V. & Blozis, S. The effects of combining dynamic pricing, AC load control, and real-time energy feedback: SMUD’S 2011 Residential Summer Solutions Study. Energy Effic. 6, 641–653 (2013).

    Article  Google Scholar 

  22. Schleich, J., Klobasa, M., Gölz, S. & Brunner, M. Effects of feedback on residential electricity demand-findings from a field trial in Austria. Energy Policy 61, 1097–1106 (2013).

    Article  Google Scholar 

  23. Lossin, F., Kozlovskiy, I., Sodenkamp, M., & Staake, T. Incentives to go green: an empirical investigation of monetary and symbolic rewards to motivate energy savings. In Proc. Eur. Conf. Inf. Syst. 1–16 (2016).

  24. A Framework for Pro-Environmental Behaviours (Department for Environment Food and Rural Affairs, 2008).

  25. Tiefenbeck, V. et al. Overcoming salience bias: how real-time feedback fosters resource conservation. Manag. Sci. 64, 983–1476 (2016).

    Google Scholar 

  26. Frederiks, E. R., Stenner, K., Hobman, E. V. & Fischle, M. Evaluating energy behavior change programs using randomized controlled trials: Best practice guidelines for policymakers. Energy Res. Soc. Sci. 22, 147–164 (2016).

    Article  Google Scholar 

  27. Faruqui, A., Sergici, S. & Sharif, A. The impact of informational feedback on energy consumption-A survey of the experimental evidence. Energy 35, 1598–1608 (2010).

    Article  Google Scholar 

  28. Schwartz, D., Bruine de Bruin, W., Fischhoff, B. & Lave, L. Advertising energy saving programs: The potential environmental cost of emphasizing monetary savings. J. Exp. Psychol. Appl. 21, 158–166 (2015).

    Article  Google Scholar 

  29. Allcott, H. & Sweeney, R. L. The role of sales agents in information disclosure: evidence from a field experiment. Manage. Sci. 63, 21–39 (2017).

    Article  Google Scholar 

  30. Energy Efficiency Campaign: ‘Deutschland Macht’s Effizient’ (German Federal Ministry for Economic Affairs and Energy, 2016);

  31. Customer Incentives for Energy Efficiency Through Program Offerings (US Environmental Protection Agency, 2010).

  32. Landry, C. E., Lange, A., List, J. A., Price, M. K. & Rupp, N. G. Toward an understanding of the economics of charity: evidence from a field experiment. Q. J. Econ. 121, 747–782 (2006).

    Article  Google Scholar 

  33. Karlan, D. & List, J. A. Does price matter in charitable giving? Evidence from a large-scale natural field experiment. Am. Econ. Rev. 97, 1774–1793 (2007).

    Article  Google Scholar 

  34. Goette, L., Stutzer, A. & Frey, B. M. Prosocial motivation and blood donations: a survey of the empirical literature. Transfus. Med. Hemotherapy 37, 149–154 (2010).

    Article  Google Scholar 

  35. Olmstead, S. M. & Stavins, R. N. Comparing price and nonprice approaches to urban water conservation. Water Resour. Res. 45, 1–10 (2009).

    Article  Google Scholar 

  36. Borenstein, S. The long-run efficiency of real time electricity pricing. Energy J. 26, 93–116 (2005).

    Article  Google Scholar 

  37. Maki, A., Burns, R. J., Ha, L. & Rothman, A. J. Paying people to protect the environment: a meta-analysis of financial incentive interventions to promote proenvironmental behaviors. J. Environ. Psychol. 47, 242–255 (2016).

    Article  Google Scholar 

  38. Bamberg, S. Is a residential relocation a good opportunity to change people’s travel behavior?: Results from a theory-driven intervention study. Environ. Behav. 38, 820–840 (2006).

    Article  Google Scholar 

  39. Frey, B. S. & Oberholzer-Gee, F. The cost of price incentives: an empirical analysis of motivation crowding-out. Am. Econ. Rev. 87, 746–755 (1997).

    Google Scholar 

  40. Sandel, M. J. What Money Can’t Buy: The Moral Limits of Markets (Macmillan, London, 2012).

  41. Gneezy, U. & Rustichini, A. A fine is a price. J. Legal Stud. 29, 1–17 (2000).

    Article  Google Scholar 

  42. Thøgersen, J. Monetary incentives and environmental concern. Effects of a differentiated garbage fee. J. Consum. Policy 17, 407–442 (1994).

    Article  Google Scholar 

  43. Karlin, B., Zinger, J. F. & Ford, R. The effects of feedback on energy conservation: a meta-analysis. Psychol. Bull. 141, 1205–1227 (2015).

    Article  Google Scholar 

  44. Schopfer, S., Tiefenbeck, V. & Staake, T. Economic assessment of photovoltaic battery systems based on household load profiles. Appl. Energy 223, 229–248 (2018).

    Article  Google Scholar 

  45. Tiefenbeck, V., Tasic, V., Schöb, S. & Staake, T. Long-lasting effects or short-term spark? On the persistence of behaviour change induced by real-time feedback on resource consumption. In Proc. Eur. Conf. Inf. Syst. 1–17 (2016).

  46. I’m Not Surprised. Nat. Energy 2, 17101 (2017).

  47. Baca-Motes, K., Brown, A., Gneezy, A., Keenan, E. A. & Nelson, L. D. Commitment and behavior change: evidence from the field. J. Consum. Res. 39, 1070–1084 (2013).

    Article  Google Scholar 

  48. Goldstein, N. J., Cialdini, R. B. & Griskevicius, V. A room with a viewpoint: using social norms to motivate environmental conservation in hotels. J. Consum. Res. 35, 472–482 (2008).

    Article  Google Scholar 

  49. Schultz, P. W., Khazian, A. M. & Zaleski, A. C. Using normative social influence to promote conservation among hotel guests. Soc. Influ. 3, 4–23 (2008).

    Article  Google Scholar 

  50. Schwartz, D. et al. The Hawthorne effect and energy awareness. Proc. Natl Acad. Sci. USA 110, 15242–15246 (2013).

    Article  Google Scholar 

  51. Tiefenbeck, V. On the magnitude and persistence of the Hawthorne effect - evidence from four field studies. In Proc. European Conference on Behaviour and Energy Efficiency 1–6 (2016).

  52. Ableitner, L., Schöb, S., Tiefenbeck, V. & Fridgen, G. Real-world impact of information systems: the effect of seemingly small design choices. In Proc. Work. Inf. Technol. Syst. 1–16 (2017).

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We thank S. Häcki and T. Bachmann from Swiss Mobiliar insurance for their great efforts in reaching out to hotels and managing the on-site study implementation and data collection. We would also like to express our gratitude to the management of the six Swiss hotels for the opportunity to run the study. Funding for this work was provided by the MTEC foundation of ETH Zurich (data analysis) as well as by Swiss Mobiliar insurance (hardware, deployment).

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Authors and Affiliations



V.T. and T.S. designed the study. S.S. wrote the software of the study devices and enabled the technical side of the data collection. V.T. oversaw the study implementation. A.W. and V.T. analysed the data. V.T. and A.W. drafted the manuscript; T.S. and E.F. edited the manuscript. V.T., T.S. and E.F. secured funding for the study.

Corresponding author

Correspondence to Verena Tiefenbeck.

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Competing interests

V.T., A.W. and E.F. declare no competing financial interests. T.S. and S.S. are co-founders of and hold shares in Amphiro AG, the SME that manufactures the smart shower meters. T.S. and S.S. were not involved in the data analysis, hotel selection or room assignment.

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Tiefenbeck, V., Wörner, A., Schöb, S. et al. Real-time feedback promotes energy conservation in the absence of volunteer selection bias and monetary incentives. Nat Energy 4, 35–41 (2019).

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