Minds and Machines

, Volume 26, Issue 1–2, pp 149–183 | Cite as

Nudge Versus Boost: How Coherent are Policy and Theory?

  • Till Grüne-YanoffEmail author
  • Ralph Hertwig


If citizens’ behavior threatens to harm others or seems not to be in their own interest (e.g., risking severe head injuries by riding a motorcycle without a helmet), it is not uncommon for governments to attempt to change that behavior. Governmental policy makers can apply established tools from the governmental toolbox to this end (e.g., laws, regulations, incentives, and disincentives). Alternatively, they can employ new tools that capitalize on the wealth of knowledge about human behavior and behavior change that has been accumulated in the behavioral sciences (e.g., psychology and economics). Two contrasting approaches to behavior change are nudge policies and boost policies. These policies rest on fundamentally different research programs on bounded rationality, namely, the heuristics and biases program and the simple heuristics program, respectively. This article examines the policy–theory coherence of each approach. To this end, it identifies the necessary assumptions underlying each policy and analyzes to what extent these assumptions are implied by the theoretical commitments of the respective research program. Two key results of this analysis are that the two policy approaches rest on diverging assumptions and that both suffer from disconnects with the respective theoretical program, but to different degrees: Nudging appears to be more adversely affected than boosting does. The article concludes with a discussion of the limits of the chosen evaluative dimension, policy–theory coherence, and reviews some other benchmarks on which policy programs can be assessed.


Bounded rationality Nudging Heuristics-and-biases program Simple heuristics program Ecological rationality Defaults 


  1. Akl, E. A., Oxman, A. D., Herrin, J., Vist, G. E., Terrenato, J., Sperati, F., Costiniuk C, Blank D., & Schünemann H. (2011). Using alternative statistical formats for presenting risks and risk reductions. Cochrane Database of Systematic Reviews, 3, CD006776.Google Scholar
  2. Anderson, B. L., Gigerenzer, G., Parker, S., & Schulkin, J. (2012). Statistical literacy in obstetricians and gynecologists. Journal for Healthcare Quality, 36(1), 5–17.CrossRefGoogle Scholar
  3. Arkes, H. R., Gigerenzer, G., & Hertwig, R. (2014). Coherence cannot be a universal criterion for rational behavior: An ecological perspective. Manuscript submitted for publication.Google Scholar
  4. Bargh, J. A. (1994). The four horsemen of automaticity: Awareness, intention, efficiency, and control in social cognition. In R. S. Wyer Jr & T. K. Srull (Eds.), Handbook of social cognition (pp. 1–40). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
  5. Beglinger, B., Rohacek, M., Ackermann, S., Hertwig, R., Karakoumis-Ilsemann, J., Boutellier, S., Geigy, N., Nickel, C., & Bingisser, R. (2015). The physician’s first clinical impression of emergency department patients with non-specific complaints is associated with morbidity and mortality. Medicine, 94(7), e374. doi: 10.1097/MD.0000000000000374
  6. Berwick, D. M., Fineberg, H. V., & Weinstein, M. C. (1981). When doctors meet numbers. American Journal of Medicine, 71, 991–998.CrossRefGoogle Scholar
  7. Beshears, J., Choi, J. J., Laibson, D., & Madrian, B. C. (2009). The importance of default options for retirement saving outcomes: Evidence from the United States. In J. R. Brown, J. B. Liebman, & D. A. Wise (Eds.), Social security policy in a changing environment (pp. 167–195). Chicago, IL: University of Chicago Press.CrossRefGoogle Scholar
  8. Bond, M. (2009). Risk school. Nature, 461, 1189–1192.CrossRefGoogle Scholar
  9. Bornstein, B. H., & Emler, A. C. (2001). Rationality in medical decision making: A review of the literature on doctors’ decision-making biases. Journal of Evaluation in Clinical Practice, 7, 97–107.CrossRefGoogle Scholar
  10. Börsch-Supan, A. (2004). Mind the gap: The effectiveness of incentives to boost retirement saving in Europe. OECD Economic Studies, 39, 111–144.Google Scholar
  11. Bovens, L. (2008). The ethics of nudge. In T. Grüne-Yanoff & S. O. Hansson (Eds.), Preference change: Approaches from philosophy, economics and psychology (pp. 207–219). Berlin: Springer.Google Scholar
  12. Brunswik, E. (1956). Perception and the representative design of psychological experiments. Berkeley, CA: University of California Press.Google Scholar
  13. Camerer, C., Issacharoff, S., Loewenstein, G., O’Donoghue, T., & Rabin, M. (2003). Regulation for conservatives: Behavioral economics and the case for “asymmetric paternalism”. University of Pennsylvania Law Review, 151(3), 1211–1254.CrossRefGoogle Scholar
  14. Cialdini, R. B. (2001). Influence: Science and practice (4th ed.). Boston: Allyn & Bacon.Google Scholar
  15. Covey, J. (2007). A meta-analysis of the effects of presenting treatment benefits in different formats. Medical Decision Making, 27, 638–654.CrossRefGoogle Scholar
  16. European Commission. (2011). Attitudes of European citizens towards the environment. (Special Eurobarometer 365). Retrieved from
  17. Fateh-Moghadam, B., & Gutmann, T. (2013). Governing [through] autonomy: The moral and legal limits of “soft paternalism”. Ethical Theory and Moral Practice, 17, 383–397.CrossRefGoogle Scholar
  18. Fischer, J. E., Steiner, F., Zucol, F., Berger, C., Martignon, L., Bossart, W., et al. (2002). Use of simple heuristics to target macrolide prescription in children with community-acquired pneumonia. Archives of Pediatrics and Adolescent Medicine, 156, 1005–1008.CrossRefGoogle Scholar
  19. Fodor, J. A. (1983). The modularity of mind. Cambridge, MA: MIT Press.Google Scholar
  20. Fox, C. R., Rogers, B. A., & Tversky, A. (1996). Options traders exhibit subadditive decision weights. Journal of Risk and Uncertainty, 13, 5–17.zbMATHCrossRefGoogle Scholar
  21. Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economic perspectives, 19(4), 25–42.CrossRefGoogle Scholar
  22. Freeman, A. M, I. I. I. (1993). The measurement of environmental and resource values. Washington, DC: Resources for the Future.Google Scholar
  23. Frey, R., Hertwig, R., & Herzog, S. M. (2014). Surrogate decision making: Do we have to trade off accuracy and procedural satisfaction? Medical Decision Making, 34, 258–269.CrossRefGoogle Scholar
  24. García-Retamero, R., Galesic, M., & Gigerenzer, G. (2010). Do icon arrays help reduce denominator neglect? Medical Decision Making, 30, 672–684.CrossRefGoogle Scholar
  25. Gerend, M. A., & Cullen, M. (2008). Effects of message framing and temporal context on college student drinking behavior. Journal of Experimental Social Psychology, 44(4), 1167–1173.CrossRefGoogle Scholar
  26. Gigerenzer, G. (1996). On narrow norms and vague heuristics: A reply to Kahneman and Tversky (1996). Psychological Review, 103, 592–596.CrossRefGoogle Scholar
  27. Gigerenzer, G. (2005). I think, therefore I err. Social Research: An International Quarterly, 72(1), 1–24.Google Scholar
  28. Gigerenzer, G. (2010). Collective statistical illiteracy. Archives of Internal Medicine, 170, 468–469.CrossRefGoogle Scholar
  29. Gigerenzer, G. (2014). Breast cancer screening pamphlets mislead women: All women and women’s organisations should tear up the pink ribbons and campaign for honest information. British Medical Journal, 348, g2636.CrossRefGoogle Scholar
  30. Gigerenzer, G., & Brighton, H. (2009). Homo heuristicus: Why biased minds make better inferences. Topics in Cognitive Science, 1(1), 107–143.CrossRefGoogle Scholar
  31. Gigerenzer, G., & Edwards, A. (2003). Simple tools for understanding risks: From innumeracy to insight. British Medical Journal, 327, 741–744.CrossRefGoogle Scholar
  32. Gigerenzer, G., Gaissmaier, W., Kurz-Milcke, E., Schwartz, L. M., & Woloshin, S. (2007). Helping doctors and patients make sense of health statistics. Psychological Science in the Public Interest, 8(2), 53–96.Google Scholar
  33. Gigerenzer, G., Hertwig, R., & Pachur, T. (Eds.). (2011). Heuristics: The foundations of adaptive behavior. Oxford, UK: Oxford University Press.Google Scholar
  34. Gigerenzer, G., & Hoffrage, U. (1995). How to improve Bayesian reasoning without instruction: Frequency formats. Psychological Review, 102(4), 684–704.CrossRefGoogle Scholar
  35. Gigerenzer, G., & Muir Gray, J. A. (Eds.). (2011). Better doctors, better patients, better decisions: Envisioning health care 2020. Cambridge, MA: MIT Press.Google Scholar
  36. Gigerenzer, G., Todd, P. M., & the ABC Research Group. (1999). Simple heuristics that make us smart. New York, NY: Oxford University Press.Google Scholar
  37. Gilovich, T., Griffin, D., & Kahneman, D. (Eds.). (2002). Heuristics and biases: The psychology of intuitive judgment. Cambridge, UK: Cambridge University Press.Google Scholar
  38. Glaeser, E. L. (2006). Paternalism and psychology. University of Chicago Law Review, 73, 133–156.Google Scholar
  39. Goldstein, D. G., & Gigerenzer, G. (2002). Models of ecolological rationality: The recognition heuristic. Psychological Review, 109, 75–90.CrossRefGoogle Scholar
  40. Grüne-Yanoff, T. (2012). Old wine in new casks: Libertarian paternalism still violates liberal principles. Social Choice and Welfare, 38(4), 635–645.MathSciNetzbMATHCrossRefGoogle Scholar
  41. Hausman, D. M., & Welch, B. (2010). Debate: To nudge or not to nudge. Journal of Political Philosophy, 18(1), 123–136.CrossRefGoogle Scholar
  42. Hautz, W. E., Kämmer, J. E., Schauber, S. K., Spies, C. D., & Gaissmaier, W. (2015). Diagnostic performance by medical students working individually or in teams. JAMA, 313, 303–304.CrossRefGoogle Scholar
  43. Heath, C., Larrick, R. P., & Klayman, J. (1998). Cognitive repairs: How organizational practices can compensate for individual shortcomings. Research in Organizational Behavior, 20, 1–37.Google Scholar
  44. Hertwig, R. (2012). Tapping into the wisdom of the crowd: With confidence. Science, 336(6079), 303–304.CrossRefGoogle Scholar
  45. Hertwig, R., Buchan, H., Davis, D. A., Gaissmaier, W., Härter, M., Kolpatzik, K., Légaré, F., Schmacke, N., & Wormer, H. (2011). How will health care professionals and patients work together in 2020? A manifesto for change. In G. Gigerenzer & J. A. Muir Gray (Eds.), Better doctors, better patients, better decisions: Envisioning health care 2020 (pp. 317–337). Cambridge, MA: MIT Press.Google Scholar
  46. Hertwig, R., & Erev, I. (2009). The description–experience gap in risky choice. Trends in Cognitive Sciences, 13, 517–523.CrossRefGoogle Scholar
  47. Hertwig, R., & Gigerenzer, G. (1999). The “conjunction fallacy” revisited: How intelligent inferences look like reasoning errors. Journal of Behavioral Decision Making, 12, 275–305.CrossRefGoogle Scholar
  48. Hertwig, R., Hoffrage, U., & the ABC Research Group. (2013). Simple heuristics in a social world. New York, NY: Oxford University Press.Google Scholar
  49. Herzog, S. M., & Hertwig, R. (2009). The wisdom of many in one mind: Improving individual judgments with dialectical bootstrapping. Psychological Science, 20, 231–237.CrossRefGoogle Scholar
  50. Herzog, S. M., & Hertwig, R. (2013). The crowd-within and the benefits of dialectical bootstrapping: A reply to White and Antonakis (2013). Psychological Science, 24, 117–119.CrossRefGoogle Scholar
  51. Herzog, S. M., & Hertwig, R. (2014). Think twice and then: Combining or choosing in dialectical bootstrapping? Journal of Experimental Psychology: Learning, Memory, and Cognition, 40, 218–232.Google Scholar
  52. Hoffrage, U., Lindsey, S., Hertwig, R., & Gigerenzer, G. (2000). Communicating statistical information. Science, 290, 2261–2262.CrossRefGoogle Scholar
  53. House of Lords Science and Technology Select Committee. (2011). Behaviour change (2nd report of session 2010–12, HL paper 179). London, UK: The stationary office. Retrieved from
  54. Jenny, M. A., Pachur, T., Williams, S. L., Becker, E., & Margraf, J. (2013). Simple rules for detecting depression. Journal of Applied Research in Memory and Cognition, 2, 149–157.CrossRefGoogle Scholar
  55. Johnson, E. J., Bellman, S., & Lohse, G. L. (2002). Defaults, framing and privacy: Why opting in-opting out. Marketing Letters, 13(1), 5–15.CrossRefGoogle Scholar
  56. Johnson, E., & Goldstein, D. (2003). Do defaults save lives? Science, 302, 1338–1339.CrossRefGoogle Scholar
  57. Kahneman, D. (2003). Maps of bounded rationality: Psychology for behavioral economics. The American Economic Review, 93, 1449–1475.CrossRefGoogle Scholar
  58. Kahneman, D. (2011). Thinking, fast and slow. New York, NY: Farrar, Straus & Giroux.Google Scholar
  59. Kahneman, D., Diener, E., & Schwarz, N. (Eds.). (1999). Well-being: The foundations of hedonic psychology. New York, NY: Russell Sage Foundation.Google Scholar
  60. Kahneman, D., & Krueger, A. B. (2006). Developments in the measurement of subjective well-being. Journal of Economic Perspectives, 20, 3–24.CrossRefGoogle Scholar
  61. Kahneman, D., & Renshon, J. (2007). Why hawks win. Foreign Policy, 158, 34–38.Google Scholar
  62. Kahneman, D., Slovic, P., & Tversky, A. (Eds.). (1982). Judgment under uncertainty: Heuristics and biases. New York, NY: Cambridge University Press.Google Scholar
  63. Kahneman, D., & Tversky, A. (1972). Subjective probability: A judgment of representativeness. Cognitive Psychology, 3, 430–454.CrossRefGoogle Scholar
  64. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47, 263–291.zbMATHCrossRefGoogle Scholar
  65. Kahneman, D., & Tversky, A. (1996). On the reality of cognitive illusions: A reply to Gigerenzer’s critique. Psychological Review, 103, 582–591.CrossRefGoogle Scholar
  66. Katsikopoulos, K. (2014). Bounded rationality: The two cultures. Journal of Economic Methodology,. doi: 10.1080/1350178X.2014.965908.Google Scholar
  67. Klein, J. G. (2005). Five pitfalls in decisions about diagnosis and prescribing. British Medical Journal, 330, 781–783.CrossRefGoogle Scholar
  68. Koehler, J. J. (1996). The base rate fallacy reconsidered: Descriptive, normative and methodological challenges. Behavioral and Brain Sciences, 19, 1–53.CrossRefGoogle Scholar
  69. Kruglanski, A. W., & Gigerenzer, G. (2011). Intuitive and deliberate judgments are based on common principles. Psychological Review, 118, 97–109.CrossRefGoogle Scholar
  70. Kunreuther, H., & Michel-Kerjan, E. (2011). People get ready: Disaster preparedness. Issues in Science and Technology, 28, 1–7.Google Scholar
  71. Kurz-Milcke, E., Gigerenzer, G., & Martignon, L. (2008). Transparency in risk communication: Graphical and analog tools. Annals of the New York Academy of Sciences, 1128, 18–28.CrossRefGoogle Scholar
  72. Kurz-Milcke, E., Gigerenzer, G., & Martignon, L. (2011). Risiken durchschauen: Grafische und analoge Werkzeuge [Understanding risk: Graphical and analog tools]. Stochastik in der Schule, 31, 8–16.Google Scholar
  73. Latten, S., Martignon, L., Monti, M., & Multmeier, J. (2011). Die Förderung erster Kompetenzen für den Umgang mit Risiken bereits in der Grundschule: ein Projekt von RIKO-STAT und dem Harding Center [Teaching risk literacy in elementary school: A project of RIKO-STAT and the Harding Center]. Stochastik in der Schule, 31, 17–25.Google Scholar
  74. Levin, I. P., & Gaeth, G. J. (1988). How consumers are affected by the framing of attribute information before and after consuming the product. Journal of Consumer Research, 15, 374–378.CrossRefGoogle Scholar
  75. Lindsey, S., Hertwig, R., & Gigerenzer, G. (2003). Communicating statistical DNA evidence. Jurimetrics: The Journal of Law, Science, and Technology, 43, 147–163.Google Scholar
  76. Loewenstein, G., & Prelec, D. (1992). Anomalies in intertemporal choice: Evidence and an interpretation. Quarterly Journal of Economics, 107, 573–597.CrossRefGoogle Scholar
  77. Lopes, L. L. (1991). The rhetoric of irrationality. Theory & Psychology, 1, 65–82.CrossRefGoogle Scholar
  78. Luan, S., Schooler, L. J., & Gigerenzer, G. (2011). A signal detection analysis of fast-and-frugal trees. Psychological Review, 118, 316–338.CrossRefGoogle Scholar
  79. Malmendier, U., & Tate, G. (2005). CEO overconfidence and corporate investment. Journal of Finance, 60, 2661–2700.Google Scholar
  80. Marewski, J. N., & Schooler, L. J. (2011). Cognitive niches: An ecological model of strategy selection. Psychological Review, 118, 393–437.CrossRefGoogle Scholar
  81. Martignon, L., Katsikopoulos, K. V., & Woike, J. K. (2008). Categorization with limited resources: A family of simple heuristics. Journal of Mathematical Psychology, 52, 352–361.MathSciNetzbMATHCrossRefGoogle Scholar
  82. Martignon, L., Vitouch, O., Takezawa, M., & Forster, M. (2003). Naïve and yet enlightened: From natural frequencies to fast and frugal decision trees. In D. Hardman & L. Macchi (Eds.), Thinking: Psychological perspectives on reasoning, judgment, and decision making (pp. 189–211). Chichester, UK: Wiley.Google Scholar
  83. Mata, J., Frank, R., & Gigerenzer, G. (2014). Symptom recognition of heart attack and stroke in nine European countries: A representative study. Health Expectations, 17, 376–387.CrossRefGoogle Scholar
  84. McKenzie, C. R. M., Liersch, M. J., & Finkelstein, S. R. (2006). Recommendations implicit in policy defaults. Psychological Science, 17, 414–420.CrossRefGoogle Scholar
  85. McLeod, P., & Dienes, Z. (1996). Do fielders know where to go to catch the ball, or only how to get there? Journal of Experimental Psychology: Human Perception and Performance, 22, 531–543.Google Scholar
  86. Meyvis, T., Ratner, R. K., & Levav, J. M. (2010). Why don’t we learn to accurately forecast feelings? How misremembering our predictions blinds us to forecasting errors. Journal of Experimental Psychology: General, 139, 579–589.CrossRefGoogle Scholar
  87. Mitchell, G. (2005). Libertarian paternalism is an oxymoron. Northwestern University Law Review, 99(3), 1245–1277.Google Scholar
  88. Nelson, W., Reyna, V. F., Fagerlin, A., Lipkus, I., & Peters, E. (2008). Clinical implications of numeracy: Theory and practice. Annals of Behavioral Medicine, 35(3), 261–274.CrossRefGoogle Scholar
  89. Pachur, T., & Hertwig, R. (2006). On the psychology of the recognition heuristic: Retrieval primacy as a key determinant of its use. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32, 983–1002.Google Scholar
  90. Park, C. W., Jun, S. Y., & MacInnis, D. J. (2000). Choosing what I want versus eliminating what I don’t want: The effects of additive versus subtractive product option framing on consumer decision making. Journal of Marketing Research, 37(2), 187–202.CrossRefGoogle Scholar
  91. Payne, J. W., Bettman, J. R., & Johnson, E. J. (1993). The adaptive decision maker. Cambridge, UK: Cambridge University.CrossRefGoogle Scholar
  92. Payne, J. W., Bettman, J. R., & Schade, D. A. (1999). Measuring constructed preferences: Towards a building code. Journal of Risk and Uncertainty, 19, 243–270.zbMATHCrossRefGoogle Scholar
  93. Pichert, D., & Katsikopoulos, K. V. (2008). Green defaults: Information presentation and pro-environmental behavior. Journal of Environmental Psychology, 28, 63–73.CrossRefGoogle Scholar
  94. Posner, R. A. (1979). Some uses and abuses of economics in law. The University of Chicago Law Review, 46(2), 281–306.CrossRefGoogle Scholar
  95. Rebonato, R. (2012). Taking liberties: A critical examination of libertarian paternalism. New York, NY: Palgrave Macmillan.Google Scholar
  96. 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), 943–973.CrossRefGoogle Scholar
  97. Rieskamp, J., & Otto, P. E. (2006). SSL: A theory of how people learn to select strategies. Journal of Experimental Psychology: General, 135, 207–236.CrossRefGoogle Scholar
  98. Rothman, A. J., Bartels, R. D., Wlaschin, J., & Salovey, P. (2006). The strategic use of gain-and loss-framed messages to promote healthy behavior: How theory can inform practice. Journal of Communication, 56(s1), S202–S220.CrossRefGoogle Scholar
  99. Rottenstreich, Y., & Tversky, A. (1997). Unpacking, repacking, and anchoring: Advances in support theory. Psychological Review, 104, 406–415.CrossRefGoogle Scholar
  100. Saghai, Y. (2014). Salvaging the concept of nudge. Journal of Medical Ethics, 38, 487–493.Google Scholar
  101. Sarfati, D., Howden-Chapman, P., Woodward, A., & Salmond, C. (1998). Does the frame affect the picture? A study into how attitudes to screening for cancer are affected by the way benefits are expressed. Journal of Medical Screening, 5, 137–140.CrossRefGoogle Scholar
  102. Sedlmeier, P., & Gigerenzer, G. (2001). Teaching Bayesian reasoning in less than two hours. Journal of Experimental Psychology: General, 130, 380–400.CrossRefGoogle Scholar
  103. Sedrakyan, A., & Shih, C. (2007). Improving depiction of benefits and harms: Analyses of studies of well-known therapeutics and review of high-impact medical journals. Medical Care, 45, 523–528.CrossRefGoogle Scholar
  104. Simon, H. A. (1956). Rational choice and the structure of the environment. Psychological Review, 63, 129–138.CrossRefGoogle Scholar
  105. Simon, H. A. (1978). Rationality as process and as product of thought. American Economic Review, 68, 1–16.Google Scholar
  106. Simon, H. A. (1990). Invariants of human behavior. Annual Review of Psychology, 41, 1–19.CrossRefGoogle Scholar
  107. Skinner, B. F. (1971). Beyond freedom and dignity. New York, NY: Knopf.Google Scholar
  108. Skinner, B. F. (1975). Walden two. Indianapolis, IN: Hackett.Google Scholar
  109. Smith, N. C., Goldstein, D. G., & Johnson, E. J. (2013). Choice without awareness: Ethical and policy implications of defaults. Journal of Public Policy & Marketing, 32, 159–172.CrossRefGoogle Scholar
  110. Staddon, J. (1995) On responsibility and punishment. The Atlantic Monthly, 275(2), 88–94.Google Scholar
  111. Sunstein, C. R. (2014). Why nudge? The politics of libertarian paternalism. New Haven, CN: Yale University Press.Google Scholar
  112. Thaler, R. H. (1991). Quasi rational economics. New York, NY: Sage.Google Scholar
  113. Thaler, R., & Benartzi, S. (2004). Save more tomorrow: Using behavioral economics to increase employee savings. Journal of Political Economy, 112, 164–187.CrossRefGoogle Scholar
  114. Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven, CT: Yale University Press.Google Scholar
  115. Todd, P. M., Gigerenzer, G., & the ABC Research Group. (2012). Ecological rationality: Intelligence in the world. New York, NY: Oxford University Press.CrossRefGoogle Scholar
  116. Tversky, A. (1996). Contrasting rational and psychological principles in choice. In R. J. Zeckhauser, R. L. Keeny, & J. K. Sebenius (Eds.), Wise choices: Decisions, games and negotiations (pp. 5–21). Boston, MA: Harvard Business School Press.Google Scholar
  117. Tversky, A., & Kahneman, D. (1971). Belief in the law of small numbers. Psychological Bulletin, 76(2), 105.CrossRefGoogle Scholar
  118. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.CrossRefGoogle Scholar
  119. Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5, 297–323.zbMATHCrossRefGoogle Scholar
  120. Veetil, V. P. (2011). Libertarian paternalism is an oxymoron: An essay in defence of liberty. European Journal of Law and Economics, 31(3), 321–334.CrossRefGoogle Scholar
  121. Volz, K. G., Schooler, L. J., Schubotz, R. I., Raab, M., Gigerenzer, G., & von Cramon, D. Y. (2006). Why you think Milan is larger than Modena: Neural correlates of the recognition heuristic. Journal of Cognitive Neuroscience, 18(11), 1924–1936.CrossRefGoogle Scholar
  122. Wegwarth, O., & Gigerenzer, G. (2013). Trust-your-doctor: A simple heuristic in need of a proper social environment. In R. Hertwig, U. Hoffrage, & the ABC Research Group (Eds.), Simple heuristics in a social world (pp. 67–102). New York, NY: Oxford University Press.Google Scholar
  123. White, M. (2013). The manipulation of choice. Ethics and libertarian paternalism. New York, NY: Palgrave MacMillan.CrossRefGoogle Scholar
  124. Wilkinson, T. M. (2013). Nudging and manipulation. Political Studies, 61(2), 341–355.CrossRefGoogle Scholar
  125. World Health Organization. (2013). Obesity and overweight. Factsheet N°311. Geneva, Switzerland: Author. Retrieved from

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Department of Philosophy and History of TechnologyRoyal Institute of Technology (KTH)StockholmSweden
  2. 2.Max Planck Institute for Human DevelopmentBerlinGermany

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