Advertisement

Journal of Consumer Policy

, Volume 40, Issue 4, pp 485–508 | Cite as

The Energy Paradox Revisited: Analyzing the Role of Individual Differences and Framing Effects in Information Perception

  • Samdruk Dharshing
  • Stefanie Lena Hille
Original Paper

Abstract

In the ongoing debate about the “energy paradox”, a recent stream of literature highlights the importance of behavioural anomalies such as bounded rationality and self-control problems. However, the role of individual-level factors in explaining the energy paradox is still not fully understood. Combining literature on behavioural anomalies and consumer heterogeneity, the current paper analyses how individual differences influence the perception of energy-related information and susceptibility to choice-framing effects. A choice-based conjoint experiment about energy-saving home improvements was conducted with 363 homeowners in Switzerland. Results show that numeracy and energy literacy have no influence on how much attention individuals pay to energy cost savings. However, impulsivity and risk aversion are found to significantly impact homeowners’ weighting of future energy cost savings. Further, it is found that impulsive homeowners are significantly more susceptible to energy cost-framing effects. A key implication for consumer policy is that general educational programs targeted at enhancing citizens’ knowledge and cognitive abilities are unlikely to increase energy conservation investments. The findings further suggest that consumer policies and business models aimed at reducing impulsiveness and influencing risk perception might foster the uptake of energy-saving measures in the residential housing sector.

Keywords

Household behaviour Energy conservation Numeracy Energy literacy Time preferences Cost framing Consumer policy 

Notes

Acknowledgements

We thank two anonymous reviewers for their constructive feedback on an earlier version of this paper.

Funding Information

The authors thank the Swiss Federal Office of Energy for funding the survey described in this research article. The research is part of the activities of SCCER CREST (Swiss Competence Center for Energy Research), which is financially supported by the Swiss Commission for Technology and Innovation (CTI) under Grant No. 466 KTI.2014.0114.

References

  1. Abrahamse, W., & Steg, L. (2009). How do socio-demographic and psychological factors relate to households’ direct and indirect energy use and savings? Journal of Economic Psychology, 30(5), 711–720.CrossRefGoogle Scholar
  2. 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
  3. Alberini, A., Banfi, S., & Ramseier, C. (2013). Energy efficiency investments in the home: Swiss homeowners and expectations about future energy prices. Energy Journal, 34(1), 49–86.CrossRefGoogle Scholar
  4. Allcott, H. (2011). Consumers’ perceptions and misperceptions of energy costs. The American Economic Review, 101(3), 98–104.CrossRefGoogle Scholar
  5. Allcott, H., & Greenstone, M. (2012). Is there an energy efficiency gap? The Journal of Economic Perspectives, 26(1), 3–28.CrossRefGoogle Scholar
  6. Allenby, G. M., & Rossi, P. E. (2003). Perspectives based on 10 years of HB in marketing research. Paper presented at the Sawtooth Software Conference Proceedings.Google Scholar
  7. Amstalden, R. W., Kost, M., Nathani, C., & Imboden, D. M. (2007). Economic potential of energy-efficient retrofitting in the Swiss residential building sector: the effects of policy instruments and energy price expectations. Energy Policy, 35(3), 1819–1829.CrossRefGoogle Scholar
  8. Andor, M., Gerster, A., & Sommer, S. (2016). Consumer inattention, heuristic thinking and the role of energy labels. Retrieved from https://EconPapers.repec.org/. Accessed 06 Dec 2016.
  9. Bamberg, S. (2003). How does environmental concern influence specific environmentally related behaviors? A new answer to an old question. Journal of Environmental Psychology, 23(1), 21–32.CrossRefGoogle Scholar
  10. Barr, S., Gilg, A. W., & Ford, N. (2005). The household energy gap: Examining the divide between habitual-and purchase-related conservation behaviours. Energy Policy, 33(11), 1425–1444.CrossRefGoogle Scholar
  11. Bento, A. M., Li, S., & Roth, K. (2012). Is there an energy paradox in fuel economy? A note on the role of consumer heterogeneity and sorting bias. Economics Letters, 115(1), 44–48.CrossRefGoogle Scholar
  12. Benzion, U., Rapoport, A., & Yagil, J. (1989). Discount rates inferred from decisions: An experimental study. Management Science, 35(3), 270–284.CrossRefGoogle Scholar
  13. Bergkvist, L., & Rossiter, J. R. (2007). The predictive validity of multiple-item versus single-item measures of the same constructs. Journal of Marketing Research, 44(2), 175–184.CrossRefGoogle Scholar
  14. Bioregional. (2011). Helping to inform the green deal green shoots from pay as you save, August 2011. London: Bioregional.Google Scholar
  15. Bissing-Olson, M. J., Iyer, A., Fielding, K. S., & Zacher, H. (2013). Relationships between daily affect and pro-environmental behavior at work: The moderating role of pro-environmental attitude. Journal of Organizational Behavior, 34(2), 156–175.CrossRefGoogle Scholar
  16. Blasch, J., Filippini, M., & Kumar, N. (2016). Boundedly rational consumers, energy and investment literacy, and the display of information on household appliances. CER-ETH-Center of Economic Research at ETH Zurich, Working Paper, 16, 24.Google Scholar
  17. Brounen, D., Kok, N., & Quigley, J. M. (2013). Energy literacy, awareness, and conservation behavior of residential households. Energy Economics, 38, 42–50.CrossRefGoogle Scholar
  18. Brown, M. A. (2001). Market failures and barriers as a basis for clean energy policies. Energy Policy, 29(14), 1197–1207.CrossRefGoogle Scholar
  19. Bull, J. (2012). Loads of green washing—Can behavioural economics increase willingness-to-pay for efficient washing machines in the UK? Energy Policy, 50, 242–252.CrossRefGoogle Scholar
  20. Chapman, G. B., & Winquist, J. R. (1998). The magnitude effect: Temporal discount rates and restaurant tips. Psychonomic Bulletin & Review, 5(1), 119–123.CrossRefGoogle Scholar
  21. Chrzan, K., & Orme, B. (2000). An overview and comparison of design strategies for choice-based conjoint analysis. Sawtooth software research paper series.Google Scholar
  22. Conlisk, J. (1996). Why bounded rationality? Journal of Economic Literature, 34(2), 669–700.Google Scholar
  23. Deutsch, M. (2010). Life cycle cost disclosure, consumer behavior, and business implications. Journal of Industrial Ecology, 14(1), 103–120.CrossRefGoogle Scholar
  24. DeWaters, J. E., & Powers, S. E. (2011). Energy literacy of secondary students in New York State (USA): A measure of knowledge, affect, and behavior. Energy Policy, 39(3), 1699–1710.CrossRefGoogle Scholar
  25. Diamond, P., & Köszegi, B. (2003). Quasi-hyperbolic discounting and retirement. Journal of Public Economics, 87(9), 1839–1872.CrossRefGoogle Scholar
  26. Dickert, S., Kleber, J., Peters, E., & Slovic, P. (2011). Numeracy as a precursor to pro-social behavior: The impact of numeracy and presentation format on the cognitive mechanisms underlying donation decisions. Judgment and Decision making, 6(7), 638.Google Scholar
  27. Dunlap, R. E., Van Liere, K. D., Mertig, A. G., & Jones, R. E. (2000). New trends in measuring environmental attitudes: Measuring endorsement of the new ecological paradigm: a revised NEP scale. Journal of Social Issues, 56(3), 425–442.CrossRefGoogle Scholar
  28. Erdem, C., Şentürk, İ., & Şimşek, T. (2010). Identifying the factors affecting the willingness to pay for fuel-efficient vehicles in Turkey: A case of hybrids. Energy Policy, 38(6), 3038–3043.CrossRefGoogle Scholar
  29. Farsi, M. (2010). Risk aversion and willingness to pay for energy efficient systems in rental apartments. Energy Policy, 38(6), 3078–3088.CrossRefGoogle Scholar
  30. Fellner, G., & Maciejovsky, B. (2007). Risk attitude and market behavior: Evidence from experimental asset markets. Journal of Economic Psychology, 28(3), 338–350.CrossRefGoogle Scholar
  31. Frederiks, E. R., Stenner, K., & Hobman, E. V. (2015). The socio-demographic and psychological predictors of residential energy consumption: A comprehensive review. Energies, 8(1), 573–609.CrossRefGoogle Scholar
  32. Gabaix, X., & Laibson, D. (2005). Bounded rationality and directed cognition. Harvard University. Retrieved from https://scholar.harvard.edu/xgabaix/publications/bounded-rationality-and-directed-cognition-working-paper. Accessed 10 Dec 2016.
  33. Gadenne, D., Sharma, B., Kerr, D., & Smith, T. (2011). The influence of consumers’ environmental beliefs and attitudes on energy saving behaviours. Energy Policy, 39(12), 7684–7694.CrossRefGoogle Scholar
  34. Gardner, G. T., & Stern, P. C. (1996). Environmental problems and human behavior. Boston: Allyn & Bacon.Google Scholar
  35. Gatersleben, B., Steg, L., & Vlek, C. (2002). Measurement and determinants of environmentally significant consumer behavior. Environment and Behavior, 34(3), 335–362.CrossRefGoogle Scholar
  36. Geller, H., Harrington, P., Rosenfeld, A. H., Tanishima, S., & Unander, F. (2006). Polices for increasing energy efficiency: Thirty years of experience in OECD countries. Energy Policy, 34(5), 556–573.CrossRefGoogle Scholar
  37. Gelman, A., & Park, D. K. (2012). Splitting a predictor at the upper quarter or third and the lower quarter or third. The American Statistician.Google Scholar
  38. Gillingham, K., Newell, R. G., & Palmer, K. (2009). Energy efficiency economics and policy. Annual Review of Resource Economics, 1(1), 597–620.CrossRefGoogle Scholar
  39. Gillingham, K., & Palmer, K. (2014). Bridging the energy efficiency gap: policy insights from economic theory and empirical evidence. Review of Environmental Economics and Policy, 8(1), 18–38.CrossRefGoogle Scholar
  40. Gourville, J. T. (2003). The effects of monetary magnitude and level of aggregation on the temporal framing of price. Marketing Letters, 14(2), 125–135.CrossRefGoogle Scholar
  41. Green, L., Myerson, J., & McFadden, E. (1997). Rate of temporal discounting decreases with amount of reward. Memory & Cognition, 25(5), 715–723.CrossRefGoogle Scholar
  42. Green, L., Myerson, J., & Schneider, R. (2003). Is there a magnitude effect in tipping? Psychonomic Bulletin & Review, 10(2), 381–386.CrossRefGoogle Scholar
  43. Green, P. E., & Srinivasan, V. (1990). Conjoint analysis in marketing: new developments with implications for research and practice. The Journal of Marketing, 3–19.Google Scholar
  44. Greene, D. L. (2011). Uncertainty, loss aversion, and markets for energy efficiency. Energy Economics, 33(4), 608–616.CrossRefGoogle Scholar
  45. Gul, F., & Pesendorfer, W. (2001). Temptation and self-control. Econometrica, 69(6), 1403–1435.CrossRefGoogle Scholar
  46. Hardisty, D. J., Appelt, K. C., & Weber, E. U. (2013). Good or bad, we want it now: Fixed-cost present bias for gains and losses explains magnitude asymmetries in intertemporal choice. Journal of Behavioral Decision Making, 26(4), 348–361.CrossRefGoogle Scholar
  47. Harrison, M. (2010). Valuing the future: The social discount rate in cost-benefit analysis. Available at SSRN: https://ssrn.com/abstract=1599963. Accessed 2 April 2016.
  48. Hassett, K. A., & Metcalf, G. E. (1993). Energy conservation investment: Do consumers discount the future correctly? Energy Policy, 21(6), 710–716.CrossRefGoogle Scholar
  49. Hausman, J. A. (1979). Individual discount rates and the purchase and utilization of energy-using durables. The Bell Journal of Economics, 10, 33–54.Google Scholar
  50. Heinzle, S. L. (2012). Disclosure of energy operating cost information: A silver bullet for overcoming the energy-efficiency gap? Journal of Consumer Policy, 35(1), 43–64.CrossRefGoogle Scholar
  51. Heinzle, S. L., & Wüstenhagen, R. (2012). Dynamic adjustment of eco-labeling schemes and consumer choice—The revision of the EU energy label as a missed opportunity? Business Strategy and the Environment, 21(1), 60–70.CrossRefGoogle Scholar
  52. Hernández, A., Drasgow, F., & González-Romá, V. (2004). Investigating the functioning of a middle category by means of a mixed-measurement model. Journal of Applied Psychology, 89(4), 687.CrossRefGoogle Scholar
  53. Hoch, S. J., & Loewenstein, G. F. (1991). Time-inconsistent preferences and consumer self-control. Journal of Consumer Research, 492–507.Google Scholar
  54. Howarth, R. B., & Sanstad, A. H. (1995). Discount rates and energy efficiency. Contemporary Economic Policy, 13(3), 101–109.CrossRefGoogle Scholar
  55. INFE. (2011). Measuring financial literacy: questionnaire and guidance notes for conducting an internationally comparable survey of financial literacy. Periodical measuring financial literacy: questionnaire and guidance notes for conducting an internationally comparable survey of financial literacy.Google Scholar
  56. Jaccard, M., & Dennis, M. (2006). Estimating home energy decision parameters for a hybrid energy—Economy policy model. Environmental Modeling & Assessment, 11(2), 91–100.CrossRefGoogle Scholar
  57. Jaffe, A. B., Newell, R. G., & Stavins, R. N. (2004). Economics of energy efficiency. Encyclopedia of Energy, 2, 79–90.CrossRefGoogle Scholar
  58. Jaffe, A. B., & Stavins, R. N. (1994). The energy-efficiency gap: What does it mean? Energy Policy, 22(10), 804–810.CrossRefGoogle Scholar
  59. Jakob, M. (2006). Marginal costs and co-benefits of energy efficiency investments: The case of the Swiss residential sector. Energy Policy, 34(2), 172–187.CrossRefGoogle Scholar
  60. Kaenzig, J., & Wüstenhagen, R. (2010). The effect of life cycle cost information on consumer investment decisions regarding eco-innovation. Journal of Industrial Ecology, 14(1), 121–136.CrossRefGoogle Scholar
  61. Kallbekken, S., Sælen, H., & Hermansen, E. A. (2013). Bridging the energy efficiency gap: A field experiment on lifetime energy costs and household appliances. Journal of Consumer Policy, 36(1), 1–16.CrossRefGoogle Scholar
  62. Kollmuss, A., & Agyeman, J. (2002). Mind the gap: why do people act environmentally and what are the barriers to pro-environmental behavior? Environmental education research, 8(3), 239–260.Google Scholar
  63. Koomey, J. G., & Sanstad, A. H. (1994). Technical evidence for assessing the performance of markets affecting energy efficiency. Energy Policy, 22(10), 826–832.CrossRefGoogle Scholar
  64. Kühberger, A. (1998). The influence of framing on risky decisions: A meta-analysis. Organizational Behavior and Human Decision Processes, 75(1), 23–55.CrossRefGoogle Scholar
  65. Kuosmanen, T. (2005). Measurement and analysis of eco-efficiency: An economist’s perspective. Journal of Industrial Ecology, 9(4), 15–18.CrossRefGoogle Scholar
  66. Laibson, D. (1997). Golden eggs and hyperbolic discounting. The Quarterly Journal of Economics, 112(2), 443–477.Google Scholar
  67. Lauriola, M., & Levin, I. P. (2001). Personality traits and risky decision-making in a controlled experimental task: An exploratory study. Personality and Individual Differences, 31(2), 215–226.CrossRefGoogle Scholar
  68. Lauriola, M., Russo, P. M., Lucidi, F., Violani, C., & Levin, I. P. (2005). The role of personality in positively and negatively framed risky health decisions. Personality and Individual Differences, 38(1), 45–59.CrossRefGoogle Scholar
  69. Lee, L.-S., Lee, Y.-F., Altschuld, J. W., & Pan, Y.-J. (2015). Energy literacy: Evaluating knowledge, affect, and behavior of students in Taiwan. Energy Policy, 76, 98–106.CrossRefGoogle Scholar
  70. Levin, I. P., Schneider, S. L., & Gaeth, G. J. (1998). All frames are not created equal: A typology and critical analysis of framing effects. Organizational Behavior and Human Decision Processes, 76(2), 149–188.CrossRefGoogle Scholar
  71. Levine, M. D., Koomey, J. G., McMahon, J. E., Sanstad, A. H., & Hirst, E. (1995). Energy efficiency policy and market failures. Annual Review of Energy and the Environment, 20(1), 535–555.CrossRefGoogle Scholar
  72. Lillemo, S. C. (2014). Measuring the effect of procrastination and environmental awareness on households’ energy-saving behaviours: An empirical approach. Energy Policy, 66, 249–256.CrossRefGoogle Scholar
  73. Linares, P., & Labandeira, X. (2010). Energy efficiency: Economics and policy. Journal of Economic Surveys, 24(3), 573–592.Google Scholar
  74. Loewenstein, G., & Prelec, D. (1992). Anomalies in intertemporal choice: Evidence and an interpretation. The Quarterly Journal of Economics, 107, 573–597.Google Scholar
  75. Lusardi, A., & Mitchell, O. S. (2011). Financial literacy around the world: An overview. Journal of Pension Economics and Finance, 10(04), 497–508.CrossRefGoogle Scholar
  76. Lusardi, A., Mitchell, O. S., & Curto, V. (2010). Financial literacy among the young. Journal of Consumer Affairs, 44(2), 358–380.CrossRefGoogle Scholar
  77. Lusardi, A., & Mitchelli, O. (2007). Financial literacy and retirement preparedness: Evidence and implications for financial education. Business Economics, 42(1), 35–44.CrossRefGoogle Scholar
  78. Marino, A., Bertoldi, P., Rezessy, S., & Boza-Kiss, B. (2011). A snapshot of the European energy service market in 2010 and policy recommendations to foster a further market development. Energy Policy, 39(10), 6190–6198.CrossRefGoogle Scholar
  79. Markowitz, H. (1952). The utility of wealth. The Journal of Political Economy, 151–158.Google Scholar
  80. Martinsson, J., Lundqvist, L. J., & Sundström, A. (2011). Energy saving in Swedish households. The (relative) importance of environmental attitudes. Energy Policy, 39(9), 5182–5191.CrossRefGoogle Scholar
  81. Metcalf, G. E., & Hassett, K. A. (1999). Measuring the energy savings from home improvement investments: Evidence from monthly billing data. Review of Economics and Statistics, 81(3), 516–528.CrossRefGoogle Scholar
  82. Min, J., Azevedo, I. L., Michalek, J., & de Bruin, W. B. (2014). Labeling energy cost on light bulbs lowers implicit discount rates. Ecological Economics, 97, 42–50.CrossRefGoogle Scholar
  83. Moeller, F. G., Barratt, E. S., Dougherty, D. M., Schmitz, J. M., & Swann, A. C. (2001). Psychiatric aspects of impulsivity. American Journal of Psychiatry, 158(11), 1783–1793.CrossRefGoogle Scholar
  84. Moore, W. L., Louviere, J. J., & Verma, R. (1999). Using conjoint analysis to help design product platforms. Journal of Product Innovation Management, 16(1), 27–39.CrossRefGoogle Scholar
  85. Mullainathan, S., & Thaler, R. H. (2000). Behavioral economics (NBER Working Papers: 7948). Retrieved from http://www.nber.org/
  86. Neumann, L. J., & Morgenstern, O. (1947). Theory of games and economic behavior (vol. 60). Princeton: Princeton University Press.Google Scholar
  87. Ölander, F., & Thøgersen, J. (2014). Informing versus nudging in environmental policy. Journal of Consumer Policy, 37(3), 341–356.CrossRefGoogle Scholar
  88. Osbaldiston, R., & Schott, J. P. (2012). Environmental sustainability and behavioral science: Meta-analysis of proenvironmental behavior experiments. Environment and Behavior, 44(2), 257–299.Google Scholar
  89. Parker, A. M., & Fischhoff, B. (2005). Decision-making competence: External validation through an individual-differences approach. Journal of Behavioral Decision Making, 18(1), 1–27.CrossRefGoogle Scholar
  90. Patton, J. H., & Stanford, M. S. (1995). Factor structure of the Barratt impulsiveness scale. Journal of Clinical Psychology, 51(6), 768–774.CrossRefGoogle Scholar
  91. Peters, E., & Levin, I. P. (2008). Dissecting the risky-choice framing effect: Numeracy as an individual-difference factor in weighting risky and riskless options. Judgment and Decision Making, 3(6), 435.Google Scholar
  92. Peters, E., Västfjäll, D., Slovic, P., Mertz, C., Mazzocco, K., & Dickert, S. (2006). Numeracy and decision making. Psychological Science, 17(5), 407–413.CrossRefGoogle Scholar
  93. Peters, J., & Büchel, C. (2010). Episodic future thinking reduces reward delay discounting through an enhancement of prefrontal-mediotemporal interactions. Neuron, 66(1), 138–148.CrossRefGoogle Scholar
  94. Pettifor, H., Wilson, C., & Chryssochoidis, G. (2015). The appeal of the green deal: empirical evidence for the influence of energy efficiency policy on renovating homeowners. Energy Policy, 79, 161–176.CrossRefGoogle Scholar
  95. Pingle, M. (2006). Deliberation cost as a foundation for behavioral economics. In M. Altman (Ed.), Handbook of contemporary behavioral economics: Foundations and developments (pp. 340–355). New York: Routledge.Google Scholar
  96. Poortinga, W., Steg, L., & Vlek, C. (2004). Values, environmental concern, and environmental behavior a study into household energy use. Environment and Behavior, 36(1), 70–93.CrossRefGoogle Scholar
  97. Qiu, Y., Colson, G., & Grebitus, C. (2014). Risk preferences and purchase of energy-efficient technologies in the residential sector. Ecological Economics, 107, 216–229.CrossRefGoogle Scholar
  98. Rabin, M., & Thaler, R. H. (2001). Anomalies: Risk aversion. The Journal of Economic Perspectives, 15(1), 219–232.Google Scholar
  99. Ramos, A., Gago, A., Labandeira, X., & Linares, P. (2015). The role of information for energy efficiency in the residential sector. Energy Economics, 52, S17–S29.CrossRefGoogle Scholar
  100. Revelt, D., & Train, K. (1998). Mixed logit with repeated choices: Households’ choices of appliance efficiency level. Review of Economics and Statistics, 80(4), 647–657.CrossRefGoogle Scholar
  101. Reyna, V. F., Nelson, W. L., Han, P. K., & Dieckmann, N. F. (2009). How numeracy influences risk comprehension and medical decision making. Psychological Bulletin, 135(6), 943.CrossRefGoogle Scholar
  102. Rossi, P. E., & Allenby, G. M. (2003). Bayesian statistics and marketing. Marketing Science, 22(3), 304–328.CrossRefGoogle Scholar
  103. Sallee, J. M. (2014). Rational inattention and energy efficiency. The Journal of Law and Economics, 57(3), 781–820.CrossRefGoogle Scholar
  104. Sanstad, A. H., Blumstein, C., & Stoft, S. E. (1995). How high are option values in energy-efficiency investments? Energy Policy, 23(9), 739–743.CrossRefGoogle Scholar
  105. Sapci, O., & Considine, T. (2014). The link between environmental attitudes and energy consumption behavior. Journal of Behavioral and Experimental Economics, 52, 29–34.CrossRefGoogle Scholar
  106. Shapira, Z. (1995). Risk taking: A managerial perspective. New York: Russell Sage Foundation.Google Scholar
  107. Shiloh, S., Salton, E., & Sharabi, D. (2002). Individual differences in rational and intuitive thinking styles as predictors of heuristic responses and framing effects. Personality and Individual Differences, 32(3), 415–429.CrossRefGoogle Scholar
  108. Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99–118.CrossRefGoogle Scholar
  109. Stanovich, K. E., & West, R. F. (1998). Individual differences in rational thought. Journal of Experimental Psychology: General, 127(2), 161.CrossRefGoogle Scholar
  110. Strotz, R. H. (1955). Myopia and inconsistency in dynamic utility maximization. The Review of Economic Studies, 165–180.Google Scholar
  111. Sütterlin, B., Brunner, T. A., & Siegrist, M. (2011). Who puts the most energy into energy conservation? A segmentation of energy consumers based on energy-related behavioral characteristics. Energy Policy, 39(12), 8137–8152.CrossRefGoogle Scholar
  112. Tabi, A., Hille, S. L., & Wüstenhagen, R. (2014). What makes people seal the green power deal?—Customer segmentation based on choice experiment in Germany. Ecological Economics, 107, 206–215.CrossRefGoogle Scholar
  113. Train, K. (1985). Discount rates in consumers’ energy-related decisions: A review of the literature. Energy, 10(12), 1243–1253.CrossRefGoogle Scholar
  114. Tsvetanov, T., & Segerson, K. (2013). Re-evaluating the role of energy efficiency standards: A behavioral economics approach. Journal of Environmental Economics and Management, 66(2), 347–363.CrossRefGoogle Scholar
  115. Turrentine, T. S., & Kurani, K. S. (2007). Car buyers and fuel economy? Energy Policy, 35(2), 1213–1223.CrossRefGoogle Scholar
  116. U.S. Energy Information Administration. (2015). World energy consumption by end-use sector (quadrillion Btu) and shares of total energy use, 2011. Available at www.eia.gov
  117. US Department of Energy. (2012). Essential principles and fundamental concepts for energy education. Retrieved from Washington: US Department of Energy.Google Scholar
  118. Van Rooij, M. C., Lusardi, A., & Alessie, R. J. (2011). Financial literacy and retirement planning in the Netherlands. Journal of Economic Psychology, 32(4), 593–608.CrossRefGoogle Scholar
  119. Vine, E. (2005). An international survey of the energy service company (ESCO) industry. Energy Policy, 33(5), 691–704.CrossRefGoogle Scholar
  120. Weber, E. U., Blais, A. R., & Betz, N. E. (2002). A domain-specific risk-attitude scale: Measuring risk perceptions and risk behaviors. Journal of Behavioral Decision Making, 15(4), 263–290.CrossRefGoogle Scholar
  121. Weber, M., Weber, E. U., & Nosić, A. (2013). Who takes risks when and why: Determinants of changes in investor risk taking*. Review of Finance, 17(3), 847–883.CrossRefGoogle Scholar
  122. Weitzman, M. L. (1998). Why the far-distant future should be discounted at its lowest possible rate. Journal of Environmental Economics and Management, 36(3), 201–208.CrossRefGoogle Scholar
  123. Wulfert, E., Block, J. A., Santa Ana, E., Rodriguez, M. L., & Colsman, M. (2002). Delay of gratification: Impulsive choices and problem behaviors in early and late adolescence. Journal of Personality, 70(4), 533–552.CrossRefGoogle Scholar
  124. Zografakis, N., Menegaki, A. N., & Tsagarakis, K. P. (2008). Effective education for energy efficiency. Energy Policy, 36(8), 3226–3232.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.University of St. Gallen, IWO-HSGSt. GallenSwitzerland

Personalised recommendations