Abstract
The extent to which adopting energy-efficient technologies results in energy savings depends on how such technologies are used, and how monetary savings from energy efficiency are spent. Energy rebound occurs when potential energy savings are diminished due to post-adoption behaviour. Here we review empirical studies on how six behavioural regularities affect three energy-relevant decisions and ultimately rebound: adoption of energy-saving products or practices, their intensity of use and spending of associated monetary savings. The findings suggest that behaviours that reflect limited rationality and willpower may increase rebound, while the effects of behaviours driven by bounded self-interest are less clear. We then describe how interventions associated with each of the behavioural regularities can influence rebound and thus serve to achieve higher energy savings. Future research ought to study energy-relevant decisions in a more integrated manner, with a particular focus on re-spending as this presents the greatest challenge for research and policy.
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Change history
04 August 2022
A Correction to this paper has been published: https://doi.org/10.1038/s41560-022-01111-9
References
Berkhout, P. H. G., Muskens, J. C. & W. Velthuijsen, J. Defining the rebound effect. Energy Policy 28, 425–432 (2000).
Brookes, L. The greenhouse effect: the fallacies in the energy efficiency solution. Energy Policy 18, 199–201 (1990).
Gillingham, K., Kotchen, M. J., Rapson, D. S. & Wagner, G. Energy policy: the rebound effect is overplayed. Nature 493, 475–476 (2013).
Azevedo, I. M. L. Consumer end-use energy efficiency and rebound effects. Annu. Rev. Environ. Resour. 39, 393–418 (2014). A Review Article on the various definitions of rebound, the research gaps in the literature and the importance of scope in estimating rebound.
Sorrell, S., Dimitropoulos, J. & Sommerville, M. Empirical estimates of the direct rebound effect: a review. Energy Policy 37, 1356–1371 (2009).
Brockway, P. E., Sorrell, S., Semieniuk, G., Heun, M. K. & Court, V. Energy efficiency and economy-wide rebound effects: a review of the evidence and its implications. Renew. Sustain. Energy Rev. 141, 110781 (2021).
Peters, A. & Dütschke, E. in Rethinking Climate and Energy Policies (eds Santarius, T., Walnum, H. J. & Aall, C.) 89–105 (Springer, 2016); https://doi.org/10.1007/978-3-319-38807-6_6
Girod, B. & De Haan, P. Mental Rebound (ETH Zurich, 2009); https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/152329/eth-2118-01.pdf
Dütschke, E., Frondel, M., Schleich, J. & Vance, C. Moral licensing—another source of rebound? Front. Energy Res. 6, 38 (2018). This review suggests that consumers may feel morally licensed to consume more energy after adopting a more energy-efficient technology or making an energy-conservation decision.
Santarius, T. & Soland, M. How technological efficiency improvements change consumer preferences: towards a psychological theory of rebound effects. Ecol. Econ. 146, 414–424 (2018). This study integrates rational-choice and psychological behavioural theories for the study of rebound and identifies multiple channels through which rebound can arise.
Seebauer, S. The psychology of rebound effects: explaining energy efficiency rebound behaviours with electric vehicles and building insulation in Austria. Energy Res. Soc. Sci. 46, 311–320 (2018).
Font Vivanco, D., McDowall, W., Freire-González, J., Kemp, R. & van der Voet, E. The foundations of the environmental rebound effect and its contribution towards a general framework. Ecol. Econ. 125, 60–69 (2016).
Jolls, C., Sunstein, C. R. & Thaler, R. A behavioral approach to law and economics. Stanf. Law Rev. 50, 1471 (1998).
Turrentine, T. S. & Kurani, K. S. Car buyers and fuel economy? Energy Policy 35, 1213–1223 (2007).
Allcott, H. Consumers’ perceptions and misperceptions of energy costs. Am. Econ. Rev. 101, 98–104 (2011).
Wang, S., Fan, J., Zhao, D., Yang, S. & Fu, Y. Predicting consumers’ intention to adopt hybrid electric vehicles: using an extended version of the theory of planned behavior model. Transportation 43, 123–143 (2016).
Gerarden, T. D., Newell, R. G. & Stavins, R. N. Assessing the energy-efficiency gap. J. Econ. Lit. 55, 1486–1525 (2017).
Cohen, F., Glachant, M. & Söderberg, M. Consumer myopia, imperfect competition and the energy efficiency gap: evidence from the UK refrigerator market. Eur. Econ. Rev. 93, 1–23 (2017).
Halvorsen, B., Larsen, B. M., Wilhite, H. & Winther, T. Revisiting household energy rebound: perspectives from a multidisciplinary study. Indoor Built Environ. 25, 1114–1123 (2016).
Waechter, S., Sütterlin, B. & Siegrist, M. The misleading effect of energy efficiency information on perceived energy friendliness of electric goods. J. Clean. Prod. 93, 193–202 (2015).
Keefer, Q. & Rustamov, G. Limited attention in residential energy markets: a regression discontinuity approach. Empir. Econ. 55, 993–1017 (2018).
Attari, S. Z., DeKay, M. L., Davidson, C. I. & De Bruin, W. B. Public perceptions of energy consumption and savings. Proc. Natl Acad. Sci. USA 107, 16054–16059 (2010).
Camilleri, A. R., Larrick, R. P., Hossain, S. & Patino-Echeverri, D. Consumers underestimate the emissions associated with food but are aided by labels. Nat. Clim. Change 9, 53–58 (2019).
Thaler, R. H. Mental accounting matters. J. Behav. Decis. Mak. 12, 183–206 (1999).
Antonides, G., Manon de Groot, I. & Fred van Raaij, W. Mental budgeting and the management of household finance. J. Econ. Psychol. 32, 546–555 (2011).
Kahneman, D. & Tversky, A. Prospect theory: an analysis of decision under risk. Econometrica 47, 263–292 (1979).
Epley, N., Mak, D. & Idson, L. C. Bonus of rebate?: the impact of income framing on spending and saving. J. Behav. Decis. Mak. 19, 213–227 (2006).
Hahnel, U. J. J., Chatelain, G., Conte, B., Piana, V. & Brosch, T. Mental accounting mechanisms in energy decision-making and behaviour. Nat. Energy 5, 952–958 (2020). This Perspective examines the ways mental accounting can affect energy-related behaviour, from which implications for rebound are drawn.
Schleich, J., Gassmann, X., Meissner, T. & Faure, C. A large-scale test of the effects of time discounting, risk aversion, loss aversion, and present bias on household adoption of energy-efficient technologies. Energy Econ. 80, 377–393 (2019).
Heutel, G. Prospect theory and energy efficiency. J. Environ. Econ. Manag. 96, 236–254 (2019).
Energy Supply Probe–Initial Findings Report (Ofgem, 2008); https://www.ofgem.gov.uk/publications/energy-supply-probe-initial-findings-report
Antonides, G. & Ranyard, R. Mental accounting and economic behaviour. Econ. Psychol. 1, 123–138 (2017).
Beatty, T. K. M., Blow, L., Crossley, T. F. & O’Dea, C. Cash by any other name? Evidence on labeling from the UK Winter Fuel Payment. J. Public Econ. 118, 86–96 (2014).
Andor, M. A., Gerster, A., Gillingham, K. T. & Horvath, M. Running a car costs much more than people think—stalling the uptake of green travel. Nature 580, 453–455 (2020). This empirical study shows that a majority of car drivers do not consider initial purchase costs of a new car as part of—that is, in the same mental account as—total car costs.
de Haan, P., Mueller, M. G. & Peters, A. Does the hybrid Toyota Prius lead to rebound effects? Analysis of size and number of cars previously owned by Swiss Prius buyers. Ecol. Econ. 58, 592–605 (2006).
Cunha, M. Jr & Caldieraro, F. Sunk-cost effects on purely behavioral investments. Cogn. Sci. 33, 105–113 (2009).
Henderson, P. W. & Peterson, R. A. Mental accounting and categorization. Organ. Behav. Hum. Decis. Process. 51, 92–117 (1992).
Milkman, K. L. & Beshears, J. Mental accounting and small windfalls: evidence from an online grocer. J. Econ. Behav. Organ. 71, 384–394 (2009).
Chitnis, M., Sorrell, S., Druckman, A., Firth, S. K. & Jackson, T. Who rebounds most? Estimating direct and indirect rebound effects for different UK socioeconomic groups. Ecol. Econ. 106, 12–32 (2014).
Kahneman, D., Knetsch, J. L. & Thaler, R. H. The endowment effect, loss aversion, and status quo bias. J. Econ. Perspect. 5, 193–206 (1991).
Sunstein, C. R. & Reisch, L. A. Greener by default. Trinity Coll. Law Rev. 21, 31–66 (2018).
Verplanken, B. & Aarts, H. Habit, attitude, and planned behaviour: is habit an empty construct or an interesting case of goal-directed automaticity? Eur. Rev. Soc. Psychol. 10, 101–134 (1999).
Huebner, G. M., Cooper, J. & Jones, K. Domestic energy consumption—what role do comfort, habit, and knowledge about the heating system play? Energy Build. 66, 626–636 (2013).
Pichert, D. & Katsikopoulos, K. V. Green defaults: information presentation and pro-environmental behaviour. J. Environ. Psychol. 28, 63–73 (2008).
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).
Dinner, I., Johnson, E. J., Goldstein, D. G. & Liu, K. Partitioning default effects: why people choose not to choose. J. Exp. Psychol. Appl. 17, 332–341 (2011).
Janssen, M. A. & Jager, W. Stimulating diffusion of green products—co-evolution between firms and consumers. J. Evol. Econ. 12, 283–306 (2002).
Laibson, D. Golden eggs and hyperbolic discounting. Q. J. Econ. 112, 443–478 (1997).
Baumeister, R. & Vohs, K. in Time and Decision: Economic and Psychological Perspectives on Intertemporal Choice (eds Loewenstein, G. et al.) 201–216 (Russell Sage Foundation, 2003).
Bradford, D., Courtemanche, C., Heutel, G., McAlvanah, P. & Ruhm, C. Time preferences and consumer behavior. J. Risk Uncertain. 55, 119–145 (2017).
Fuerst, F. & Singh, R. How present bias forestalls energy efficiency upgrades: a study of household appliance purchases in India. J. Clean. Prod. 186, 558–569 (2018).
Tsvetanov, T. & Segerson, K. Re-evaluating the role of energy efficiency standards: a behavioral economics approach. J. Environ. Econ. Manag. 66, 347–363 (2013).
Allcott, H. & Taubinsky, D. Evaluating behaviorally motivated policy: experimental evidence from the lightbulb market. Am. Econ. Rev. 105, 2501–2538 (2015).
Allcott, H. & Wozny, N. Gasoline prices, fuel economy, and the energy paradox. Rev. Econ. Stat. 96, 779–795 (2014).
Harding, M. & Hsiaw, A. Goal setting and energy conservation. J. Econ. Behav. Organ. 107, 209–227 (2014).
Lillemo, S. C. Measuring the effect of procrastination and environmental awareness on households’ energy-saving behaviours: an empirical approach. Energy Policy 66, 249–256 (2014).
Wesley Schultz, P. The structure of environmental concern: concern for self, other people, and the biosphere. J. Environ. Psychol. 21, 327–339 (2001).
Mohana, R., Turaga, R., Howarth, R. B., Borsuk, M. E. & Rosenwald, J. Pro-environmental behavior: rational choice meets moral motivation. Ann. N. Y. Acad. Sci. 1185, 211–224 (2010).
Black, J. S., Stern, P. C. & Elworth, J. T. Personal and contextual influences on household energy adaptations. J. Appl. Psychol. 70, 3–21 (1985).
Wolske, K. S. & Stern, P. C. in Psychology and Climate Change: Human Perceptions, Impacts, and Responses (eds Clayton, S. & Manning, C.) 127–160 (Elsevier, 2018); https://doi.org/10.1016/B978-0-12-813130-5.00007-2
Kollmuss, A. & Agyeman, J. Mind the gap: why do people act environmentally and what are the barriers to pro-environmental behavior? Environ. Educ. Res. 8, 239–260 (2002).
Monin, B. & Jordan, A. in Personality, Identity, and Character: Explorations in Moral Psychology (eds Narvaez, D. & Lapsley, D.) Ch. 15 (Cambridge Univ. Press, 2009).
Hope, A. L. B., Jones, C. R., Webb, T. L., Watson, M. T. & Kaklamanou, D. The role of compensatory beliefs in rationalizing environmentally detrimental behaviors. Environ. Behav. 50, 401–425 (2018).
Truelove, H. B., Carrico, A. R., Weber, E. U., Raimi, K. T. & Vandenbergh, M. P. Positive and negative spillover of pro-environmental behavior: an integrative review and theoretical framework. Glob. Environ. Change 29, 127–138 (2014).
Wagner, G. & Zizzamia, D. Green moral hazards. Ethics Policy Environ. https://doi.org/10.1080/21550085.2021.1940449 (2021).
Fischbacher, U., Schudy, S. & Teyssier, S. Heterogeneous preferences and investments in energy saving measures. Resour. Energy Econ. 63, 101202 (2021).
Di Maria, C., Ferreira, S. & Lazarova, E. Shedding light on the light bulb puzzle: the role of attitudes and perceptions in the adoption of energy efficient light bulbs. Scott. J. Polit. Econ. 57, 48–67 (2010).
Harding, M. & Rapson, D. Does absolution promote sin? A conservationist’s dilemma. Environ. Resour. Econ. 73, 923–955 (2019).
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).
Andersson, D., Linscott, R. & Nässén, J. Estimating car use rebound effects from Swedish microdata. Energy Effic. 12, 2215–2225 (2019). This empirical study shows that when drivers switch to more efficient cars that are green-labelled, direct rebound is null.
Matiaske, W., Menges, R. & Spiess, M. Modifying the rebound: It depends! Explaining mobility behavior on the basis of the German socio-economic panel. Energy Policy 41, 29–35 (2012).
Klöckner, C. A., Nayum, A. & Mehmetoglu, M. Positive and negative spillover effects from electric car purchase to car use. Transp. Res. Part D 21, 32–38 (2013).
Gatersleben, B., Steg, L. & Vlek, C. Measurement and determinants of environmentally significant consumer behavior. Environ. Behav. 34, 335–362 (2002).
Vita, G. et al. Happier with less? Members of European environmental grassroots initiatives reconcile lower carbon footprints with higher life satisfaction and income increases. Energy Res. Soc. Sci. 60, 101329 (2020).
Laroche, M., Bergeron, J. & Barbaro-Forleo, G. Targeting consumers who are willing to pay more for environmentally friendly products. J. Consum. Mark. 18, 503–520 (2001).
Wolske, K. S., Gillingham, K. T. & Schultz, P. W. Peer influence on household energy behaviours. Nat. Energy 5, 202–2012 (2020).
Brick, C., Sherman, D. K. & Kim, H. S. “Green to be seen” and “brown to keep down”: visibility moderates the effect of identity on pro-environmental behavior. J. Environ. Psychol. 51, 226–238 (2017).
Uren, H. V., Roberts, L. D., Dzidic, P. L. & Leviston, Z. High-status pro-environmental behaviors: costly, effortful, and visible. Environ. Behav. 53, 455–484 (2021).
Griskevicius, V., Tybur, J. M. & Van den Bergh, B. Going green to be seen: status, reputation, and conspicuous conservation. J. Pers. Soc. Psychol. 98, 392–404 (2010).
Sexton, S. & Sexton, A. The Prius halo and willingness to pay for environmental bona fides. J. Environ. Econ. Manag. 67, 303–317 (2014).
Bollinger, B. & Gillingham, K. Peer effects in the diffusion of solar photovoltaic panels. Mark. Sci. 31, 900–912 (2012).
Farrow, K., Grolleau, G. & Ibanez, L. Social norms and pro-environmental behavior: a review of the evidence. Ecol. Econ. 140, 1–13 (2017).
Allcott, H. & Rogers, T. The short-run and long-run effects of behavioral interventions: experimental evidence from energy conservation. Am. Econ. Rev. 104, 3003–3037 (2014).
Demarque, C., Charalambides, L., Hilton, D. J. & Waroquier, L. Nudging sustainable consumption: the use of descriptive norms to promote a minority behavior in a realistic online shopping environment. J. Environ. Psychol. 43, 166–174 (2015).
Peattie, K. Green consumption: behavior and norms. Annu. Rev. Environ. Resour. 35, 195–228 (2010).
Jackson, T. Motivating Sustainable Consumption: A Review of Evidence on Consumer Behaviour and Behavioural Change. A Report to the Sustainable Development Research Network 30–40 (University of Surrey, 2005).
Biswas, A., Mukherjee, A. & Roy, M. Leveraging factors for consumers’ car purchase decisions—a study in an emerging economy. J. Manag. Policies Pract. 2, 99–111 (2014).
Nisa, C. F., Bélanger, J. J., Schumpe, B. M. & Faller, D. G. Meta-analysis of randomised controlled trials testing behavioural interventions to promote household action on climate change. Nat. Commun. 10, 4545 (2019). This recent meta-analysis finds that the size of emissions reduction of various behavioural interventions is not as big as previously thought.
Abrahamse, W. & Steg, L. Social influence approaches to encourage resource conservation: a meta-analysis. Glob. Environ. Change 23, 1773–1785 (2013).
Karlin, B., Zinger, J. F. & Ford, R. The effects of feedback on energy conservation: a meta-analysis. Psychol. Bull. 141, 1205–1227 (2015).
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).
Andor, M. A. & Fels, K. M. Behavioral economics and energy conservation—a systematic review of non-price interventions and their causal effects. Ecol. Econ. 148, 178–210 (2018). A systematic review of social comparison, commitment devices, goal setting and labelling as behavioural interventions aimed at achieving reductions in household energy use.
Iweka, O., Liu, S., Shukla, A. & Yan, D. Energy and behaviour at home: a review of intervention methods and practices. Energy Res. Soc. Sci. 57, 101238 (2019).
Camilleri, A. R. & Larrick, R. P. Metric and scale design as choice architecture tools. J. Public Policy Mark. 33, 108–125 (2014).
Sintov, N. D. & Schultz, P. W. Unlocking the potential of smart grid technologies with behavioral science. Front. Psychol. 6, 410 (2015).
Darby, S. The Effectiveness of Feedback on Energy Consumption: A Review for DEFRA of the Literature on Metering, Billing and Direct Displays (Environmental Change Institute, Univ. of Oxford, 2006).
Mogles, N. et al. How smart do smart meters need to be? Build. Environ. 125, 439–450 (2017). This study shows that to increase their effectiveness, smart energy meters should provide context to the feedback they provide and help to improve the energy literacy of households.
Thaler, R.H. & Sunstein. C. R. Nudge: Improving Decisions about Health, Wealth, and Happiness (Yale Univ. Press, 2008).
Tiefenbeck, V. et al. Overcoming salience bias: how real-time feedback fosters resource conservation. Manag. Sci. 64, 1458–1476 (2018).
Ropret Homar, A. & Knežević Cvelbar, L. The effects of framing on environmental decisions: a systematic literature review. Ecol. Econ. 183, 106950 (2021). A systematic review regarding the effects of framing on environmental decisions, which describe the conditions under which loss versus gain frames are more effective in promoting behavioural change.
Hermsen, S., Frost, J., Renes, R. J. & Kerkhof, P. Using feedback through digital technology to disrupt and change habitual behavior: a critical review of current literature. Comput. Hum. Behav. 57, 61–74 (2016).
Fujii, S., Gärling, T. & Kitamura, R. Changes in drivers’ perceptions and use of public transport during a freeway closure. Environ. Behav. 33, 796–808 (2001).
Fujii, S. & Gärling, T. Development of script-based travel mode choice after forced change. Transp. Res. Part F 6, 117–124 (2003).
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).
Thomas, G. O., Poortinga, W. & Sautkina, E. Habit discontinuity, self-activation, and the diminishing influence of context change: evidence from the UK understanding society survey. PLoS ONE 11, e0153490 (2016).
Brown, Z., Johnstone, N., Haščič, I., Vong, L. & Barascud, F. Testing the effect of defaults on the thermostat settings of OECD employees. Energy Econ. 39, 128–134 (2013).
McCalley, L. T. From motivation and cognition theories to everyday applications and back again: the case of product-integrated information and feedback. Energy Policy 34, 129–137 (2006).
Johnson, E. J. et al. Beyond nudges: tools of a choice architecture. Mark. Lett. 23, 487–504 (2012).
Allcott, H. & Knittel, C. Are consumers poorly informed about fuel economy? Evidence from two experiments. Am. Econ. J. Econ. Policy 11, 1–37 (2019).
Osbaldiston, R. & Paul Schott, J. Environmental sustainability and behavioral science: Meta-analysis of proenvironmental behavior experiments. Environ. Behav. 44, 257–299 (2012).
Locke, E. A. & Latham, G. P. Building a practically useful theory of goal setting and task motivation: a 35-year odyssey. Am. Psychol. 57, 705–717 (2002).
Deconinck, G. et al. An approach towards socially acceptable energy saving policies via monetary instruments on the smart meter infrastructure. In 3rd International Conference on Next Generation Infrastructure Systems for Eco-Cities (IEEE, 2010); https://doi.org/10.1109/INFRA.2010.5679226
Asensio, O. I. & Delmas, M. A. Nonprice incentives and energy conservation. Proc. Natl Acad. Sci. USA 112, E510–E515 (2015).
Bougherara, D., Grolleau, G. & Thiébaut, L. Can labelling policies do more harm than good? An analysis applied to environmental labelling schemes. Eur. J. Law Econ. 19, 5–16 (2005).
Gneezy, U., Imas, A. & Madarász, K. Conscience accounting: emotion dynamics and social behavior. Manag. Sci. 60, 2645–2658 (2014).
Thøgersen, J. & Crompton, T. Simple and painless? The limitations of spillover in environmental campaigning. J. Consum. Policy 32, 141–163 (2009).
Nilsson, A., Bergquist, M. & Schultz, W. P. Spillover effects in environmental behaviors, across time and context: a review and research agenda. Environ. Educ. Res. 23, 573–589 (2017).
Nash, N. et al. Climate-relevant behavioral spillover and the potential contribution of social practice theory. Wiley Interdiscip. Rev. Clim. Change 8, e481 (2017).
Maki, A. et al. Meta-analysis of pro-environmental behaviour spillover. Nat. Sustain. 2, 307–315 (2019).
Bollinger, B., Gillingham, K., Kirkpatrick, A. J. & Sexton, S. Visibility and peer influence in durable good adoption. SSRN https://doi.org/10.2139/ssrn.3409420 (2019).
Sunter, D. A., Castellanos, S. & Kammen, D. M. Disparities in rooftop photovoltaics deployment in the United States by race and ethnicity. Nat. Sustain. 2, 71–76 (2019).
Font Vivanco, D., Kemp, R. & van der Voet, E. How to deal with the rebound effect? A policy-oriented approach. Energy Policy 94, 114–125 (2016). This Review Article analyses strategies for curbing rebound, suggesting that economic instruments might be the most effective.
Hanimann, R. Consumer Behaviour in Renewable Electricity: Can Identity Signaling Increase Demand for Renewable Electricity? (Uppsala Univ., 2013).
Allcott, H. Social norms and energy conservation. J. Public Econ. 95, 1082–1095 (2011).
Bardsley, N. et al. Domestic thermal upgrades, community action and energy saving: a three-year experimental study of prosperous households. Energy Policy 127, 475–485 (2019).
Freire-González, J. Energy taxation policies can counteract the rebound effect: analysis within a general equilibrium framework. Energy Effic. 13, 69–78 (2020).
van den Bergh, J. C. J. M. Energy conservation more effective with rebound policy. Environ. Resour. Econ. 48, 43–58 (2011).
Drews, S., Exadaktylos, F. & van den Bergh, J. C. J. M. Assessing synergy of incentives and nudges in the energy policy mix. Energy Policy 144, 111605 (2020).
Becker, G. The Economic Approach to Human Behavior (Univ. Chicago Press, 1976).
Simon, H. A. A behavioral model of rational choice. Q. J. Econ. 69, 99 (1955).
Kahneman, D. & Tversky, A. Choices, Values, and Frames (Cambridge Univ. Press, 2000).
White, M. D. in Economics and the Mind (ed. Barbara Montero, M. D. W.) 143–158 (Routledge, 2007).
Sen, A. Rational fools: a critique of the behavioral foundations of economic theory. Phil. Public Aff. 6, 317–344 (1977).
Henrich, J. et al. ‘Economic man’ in cross-cultural perspective: behavioral experiments in 15 small-scale societies. Behav. Brain Sci. 28, 795–855 (2005).
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This study has received funding through an ERC Advanced Grant from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 741087).
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Exadaktylos, F., van den Bergh, J. Energy-related behaviour and rebound when rationality, self-interest and willpower are limited. Nat Energy 6, 1104–1113 (2021). https://doi.org/10.1038/s41560-021-00889-4
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DOI: https://doi.org/10.1038/s41560-021-00889-4
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