Author Note
An earlier version of ideas contained in this
article was presented by Fox at the August
2016 Academy of Management Conference
in Anaheim, California. We thank Alain Cohn,
Hengchen Dai, Jana Gallus, Jon Jachimowicz,
Dean Karlan, Alicea Lieberman, and Stephen
Spiller for helpful comments on earlier drafts of
this article.
endnotes
A. This number was corroborated by a personal
communication from the Dutch agency registering
organ donation consent (Agentschap
CIBG—Donorregister), received June 1, 2017.
B. It is worth noting that Beshears et al. (in the study
provided in reference 24) tested their explanation
in a laboratory setting, which may have exacerbated
the social concerns of participants relative
to the field experiment.
C. This is not apparent from the published version of
the article cited in reference 57, which provides
smoothed data, but it can be seen from the raw
data, which are available from the authors of that
article upon request.
D. This pattern is called a Hawthorne effect because
it was first noted in studies from the 1920s and
1930s at the Hawthorne Works (a Western Electric
factory) outside Chicago. The studies reported
that experimentally manipulated changes in
working conditions (for example, the brightness
of lighting) led to increases in worker productivity,
regardless of the nature of those changes, but
these improvements diminished after the study
ended and workers were no longer reminded that
they were being observed. The original data from
the interventions at the Hawthorne plant were
analyzed in a 2011 article (see reference 59), and
the authors concluded that “ironically, there is little
evidence of the type of Hawthorne effect widely
attributed to these data when one subjects them
to careful analysis.”
E. For a related discussion on the effects that different
forms of transparency may have, see “Putting
the Public Back in Behavioral Public Policy,” by
P. De Jonge, M. Zeelenberg, and P. W. J. Verlegh,
Behavioural Public Policy, in press.
F. We hasten to point out that the backlash in the
Netherlands was temporary. In the months after
the bill was passed, the rate of new nondonors
slowly returned to the rate at which it had been
before. Although it is quite likely that in the long
run the introduction of an opt-out system will
have a positive effect on the number of people
who consent to organ donation, it still would have
been better if the Dutch legislature had been able
to prevent the backlash altogether.
Author Affiliation
Krijnen: University of California, Los Angeles.
Tannenbaum: University of Utah. Fox: University
of California, Los Angeles. Corresponding
author’s e-mail: [email protected].
References
1. Thaler, R. H., & Sunstein, C. R. (2008).
Nudge: Improving decisions about
health, wealth, and happiness. New
Haven, CT: Yale University Press.
2. Johnson, E. J., Shu, S., Dellaert, B., Fox,
C., Goldstein, D., Häubl, G., & Weber,
E. (2012). Beyond nudges: Tools of a
choice architecture. Marketing Letters,
23, 487–504.
3. Madrian, B. C., & Shea, D. F. (2001). The
power of suggestion: Inertia in 401(k)
participation and savings behavior.
Quarterly Journal of Economics, 116,
1149–1187.
4. Malhotra, S., Cheriff, A. D., Gossey, J.
T., Cole, C. L., Kaushal, R., & Ancker, J.
S. (2016). Effects of an e-prescribing
interface redesign on rates of generic
drug prescribing: Exploiting default
options. Journal of the American
Medical Informatics Association, 23,
891–898.
5. Ebeling, F., & Lotz, S. (2015). Domestic
uptake of green energy promoted by
opt-out tariffs. Nature Climate Change,
5, 868–871.
6. Pichert, D., & Katsikopoulos, K. V.
(2008). Green defaults: Information
presentation and pro-environmental
behaviour. Journal of Environmental
Psychology, 28, 63–73.
7. Johnson, E. J., & Goldstein, D. (2003,
November 21). Do defaults save lives?
Science, 302, 1338–1339.
8. Centraal Bureau voor de Statistiek.
(2017, July 26). Ontwikkelingen
donorregistraties 2016 [Developments
donor registrations 2016].
Retrieved from https://www.
cbs.nl/nl-nl/nieuws/2017/30/
ontwikkeling-donorregistraties-2016
9. August, J. G. (2013). Modern models of
organ donation: Challenging increases
of federal power to save lives. Hastings
Constitutional Law Quarterly, 40,
339–422.
10. Siminoff, L. A., & Mercer, M. B. (2001).
Public policy, public opinion, and
consent for organ donation. Cambridge
Quarterly of Healthcare Ethics, 10,
377–386.
11. Maitlis, S. (2005). The social processes
of organizational sensemaking.
Academy of Management Journal, 48,
21–49.
12. Maitlis, S., & Christianson, M. (2014).
Sensemaking in organizations: Taking
stock and moving forward. Academy of
Management Annals, 8, 57–125.
13. Weick, K. (1995). Sensemaking in
organizations. London, United Kingdom:
Sage.
14. Weick, K. E., Sutcliffe, K. M., & Obstfeld,
D. (2005). Organizing and the process of
sensemaking. Organization Science, 16,
409–421.
15. Grice, H. P. (1975). Logic and
conversation. In P. Cole & N. L. Morgan
(Eds.), Syntax and semantics: Speech
acts (Vol. 3, pp. 41–58). New York, NY:
Academic Press.
16. Orne, M. T. (1962). On the social
psychology of the psychological
experiment: With particular reference
to demand characteristics and their
implications. American Psychologist, 17,
776–783.
17. Schwarz, N. (1994). Judgment in a social
context: Biases, shortcomings, and
the logic of conversation. Advances in
Experimental Social Psychology, 26,
123–162.
18. Kamenica, E. (2008). Contextual
inference in markets: On the
informational content of product
lines. American Economic Review, 98,
2127–2149.
19. Prelec, D., Wernerfelt, B., & Zettelmeyer,
F. (1997). The role of inference in
context effects: Inferring what you
want from what is available. Journal of
Consumer Research, 24, 118–125.
20. Wernerfelt, B. (1995). A rational
reconstruction of the compromise
effect: Using market data to infer
utilities. Journal of Consumer Research,
21, 627–633.
21. Choi, J. J., Laibson, D., & Madrian, B.
C. (2011). $100 bills on the sidewalk:
Suboptimal investment in 401(k) plans.
Review of Economics and Statistics, 93,
748–763.
22. Rhee, N. (2013). The retirement
savings crisis: Is it worse than we think?
Washington, DC: National Institute on
Retirement Security.
23. Thaler, R. H., & Benartzi, S. (2004). Save
More Tomorrow™: Using behavioral
economics to increase employee
saving. Journal of Political Economy,
112, 164–187.
24. Beshears, J., Dai, H., Milkman, K. L., &
Benartzi, S. (2017). Framing the future:
The risks of pre-commitment nudges
and potential of fresh start messaging.
Working paper.
25. McKenzie, C. R., & Nelson, J. D.
(2003). What a speaker’s choice of
frame reveals: Reference points,
frame selection, and framing effects.
Psychonomic Bulletin & Review, 10,
596–602.
26. Sher, S., & McKenzie, C. R. (2006).
Information leakage from logically
equivalent frames. Cognition, 101,
467–494.
27. Jachimowicz, J. M., Duncan, S., &
Weber, E. U. (2017). When and why
defaults influence decisions: A metaanalysis
of default effects. Working
paper.
28. McKenzie, C. R., Liersch, M.
J., & Finkelstein, S. R. (2006).
Recommendations implicit in policy
defaults. Psychological Science, 17,
414–420.
29. Tannenbaum, D., & Ditto, P. H. (2011).
Information asymmetries in default
options. Working paper.
30. 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. Brown, J. B. Liebman, & D.
A. Wise (Eds.), Social Security policy in
a changing environment (pp. 167–195).
Chicago, IL: University of Chicago Press.
31. Brown, J. R., Farrell, A. M., &
Weisbenner, S. J. (2012). The downside
of defaults. Retrieved from http://www.
nber.org/aging/rrc/papers/orrc12-05.
pdf
32. Liersch, M. J., & McKenzie, C. R. M.
(2009). In defaults we trust. Unpublished
manuscript.
33. Agnew, J. R., & Szykman, L. R. (2005).
Asset allocation and information
overload: The influence of information
display, asset choice, and investor
experience. Journal of Behavioral
Finance, 6, 57–70.
34. Brown, C. L., & Krishna, A. (2004). The
skeptical shopper: A metacognitive
account for the effects of default
options on choice. Journal of
Consumer Research, 31, 529–539.
35. Northcraft, G. B., & Neale, M. A. (1987).
Experts, amateurs, and real estate: An
anchoring-and-adjustment perspective
on property pricing decisions.
Organizational Behavior and Human
Decision Processes, 39, 84–97.
36. Keys, B. J., & Wang, J. (2014). Perverse
nudges: Minimum payments and
debt paydown in consumer credit
cards [Working paper]. Retrieved from
meetpapers/2014/paper_323.pdf
37. Navarro-Martinez, D., Salisbury, L. C.,
Lemon, K. N., Stewart, N., Matthews,
W. J., & Harris, A. J. (2011). Minimum
16 behavioral science & policy | volume 3 issue 2 2017
required payment and supplemental
information disclosure effects on
consumer debt repayment decisions.
Journal of Marketing Research, 48,
S60–S77.
38. Stewart, N. (2009). The cost of
anchoring on credit-card minimum
repayments. Psychological Science, 20,
39–41.
39. Loschelder, D. D., Friese, M., Schaerer,
M., & Galinsky, A. D. (2016). The
too-much-precision effect: When and
why precise anchors backfire with
experts. Psychological Science, 27,
1573–1587.
40. Goswami, I., & Urminsky, O. (2016).
When should the ask be a nudge? The
effect of default amounts on charitable
donations. Journal of Marketing
Research, 53, 829–846.
41. Choi, J. J., Laibson, D., Madrian, B.
C., & Metrick, A. (2004). For better or
for worse: Default effects and 401(k)
savings behavior. In D. A. Wise (Ed.),
Perspectives on the economics of aging
(pp. 81–126). Chicago, IL: University of
Chicago Press.
42. Fox, C. R., Ratner, R. K., & Lieb, D.
S. (2005). How subjective grouping
of options influences choice and
allocation: Diversification bias and the
phenomenon of partition dependence.
Journal of Experimental Psychology:
General, 134, 538–551.
43. Tannenbaum, D., Doctor, J. N., Persell,
S. D., Friedberg, M. W., Meeker, D.,
Friesema, E. M., . . . Fox, C. R. (2015).
Nudging physician prescription
decisions by partitioning the order
set: Results of a vignette-based study.
Journal of General Internal Medicine,
30, 298–304.
44. Tannenbaum, D., Fox, C. R., &
Goldstein, N. J. (2017). Partitioning
menu items to nudge single-item
choice [Working paper]. Retrieved from
https://davetannenbaum.github.io/
documents/pdepend.pdf
45. Cialdini, R. B., Kallgren, C. A., & Reno,
R. R. (1991). A focus theory of normative
conduct: A theoretical refinement
and reevaluation of the role of norms
in human behavior. Advances in
Experimental Social Psychology, 24,
201–234.
46. Fox, C. R., & Clemen, R. T. (2005).
Subjective probability assessment in
decision analysis: Partition dependence
and bias toward the ignorance prior.
Management Science, 51, 1417–1432.
47. Sonnemann, U., Camerer, C. F.,
Fox, C. R., & Langer, T. (2013). How
psychological framing affects economic
market prices in the lab and field.
Proceedings of the National Academy of
Sciences, USA, 110, 11779–11784.
48. Mulder, L. B. (2008). The difference
between punishments and rewards
in fostering moral concerns in
social decision making. Journal of
Experimental Social Psychology, 44,
1436–1443.
49. Tannenbaum, D., Valasek, C. J.,
Knowles, E. D., & Ditto, P. H. (2013).
Incentivizing wellness in the workplace:
Sticks (not carrots) send stigmatizing
signals. Psychological Science, 24,
1512–1522.
50. Homonoff, T. A. (2015). Can small
incentives have large effects? The
impact of taxes versus bonuses on
disposable bag use. Working paper.
51. Lieberman, A. J., Duke, K., & Amir, O.
(2017). How incentive framing can
harness the power of social norms.
Working paper.
52. Bénabou, R., & Tirole, J. (2003). Intrinsic
and extrinsic motivation. Review of
Economic Studies, 70, 489–520.
53. Bowles, S. (2008, June 20). Policies
designed for self-interested citizens
may undermine “the moral sentiments”:
Evidence from economic experiments.
Science, 320, 1605–1609.
54. Frey, B. S., & Oberholzer-Gee, F.
(1997). The cost of price incentives:
An empirical analysis of motivation
crowding-out. American Economic
Review, 87, 746–755.
55. Exec. Order No. 13676, 3 C.F.R.
56931 (2014). Combating antibioticresistant
bacteria. Retrieved from
https://www.whitehouse.gov/
the-press-office/2014/09/18/
executive-order-combating-antibioticresistant-
bacteria
56. Review on Antimicrobial Resistance.
(2016). Tackling drug-resistant
infections globally: Final report and
recommendations. Retrieved from
https://amr-review.org/sites/default/
files/160518_Final%20paper_with%20
cover.pdf
57. Meeker, D., Linder, J. A., Fox, C.
R., Friedberg, M. W., Persell, S. D.,
Goldstein, N. J., . . . Doctor, J. N. (2016).
Effect of behavioral interventions on
inappropriate antibiotic prescribing
among primary care practices: A
randomized clinical trial. JAMA, 315,
562–570.
58. Barnett, M. L., & Linder, J. A. (2014).
Antibiotic prescribing for adults with
acute bronchitis in the United States,
1996–2010. JAMA, 311, 2020–2022.
59. Levitt, S. D., & List, J. A. (2011). Was
there really a Hawthorne effect at
the Hawthorne plant? An analysis of
the original illumination experiments.
American Economic Journal: Applied
Economics, 3, 224–238.
60. Gosnell, G. K., List, J. A., & Metcalfe,
R. (2016). A new approach to an
age-old problem: Solving externalities
by incenting workers directly (NBER
Working Paper No. 22316). Cambridge,
MA: National Bureau of Economic
Research.
61. Schwartz, D., Fischhoff, B., Krishnamurti,
T., & Sowell, F. (2013). The Hawthorne
effect and energy awareness.
Proceedings of the National Academy of
Sciences, USA, 110, 15242–15246.
62. Zizzo, D. J. (2010). Experimenter
demand effects in economic
experiments. Experimental Economics,
13, 75–98.
63. Gerber, A. S., Green, D. P., & Larimer,
C. W. (2008). Social pressure and voter
turnout: Evidence from a large-scale
field experiment. American Political
Science Review, 102, 33–48.
64. Lerner, J. S., & Tetlock, P. E. (1999).
Accounting for the effects of
accountability. Psychological Bulletin,
125, 255–275.
65. Friestad, M., & Wright, P. (1994). The
persuasion knowledge model: How
people cope with persuasion attempts.
Journal of Consumer Research, 21,
1–31.
66. Brehm, J. W. (1966). A theory of
psychological reactance. Oxford, United
Kingdom: Academic Press.
67. Clee, M. A., & Wicklund, R. A. (1980).
Consumer behavior and psychological
reactance. Journal of Consumer
Research, 6, 389–405.
68. Wicklund, R. A. (1974). Freedom and
reactance. Oxford, United Kingdom:
Erlbaum.
69. Jung, J. Y., & Mellers, B. A. (2016).
American attitudes toward nudges.
Judgment and Decision Making, 11,
62–74.
70. Agnew, J. R., Szykman, L. R., Utkus,
S. P., & Young, J. A. (2012). Trust, plan
knowledge and 401(k) savings behavior.
Journal of Pension Economics &
Finance, 11, 1–20.
71. Davidai, S., Gilovich, T., & Ross, L. D.
(2012). The meaning of default options
for potential organ donors. Proceedings
a publication of the behavioral science & policy association 17
of the National Academy of Sciences,
USA, 109, 15201–15205.
72. Young, S. D., Monin, B., & Owens, D.
(2009). Opt-out testing for stigmatized
diseases: A social psychological
approach to understanding the potential
effect of recommendations for routine
HIV testing. Health Psychology, 28,
675–681.
73. Bénabou, R., & Tirole, J. (2006).
Incentives and prosocial behavior.
American Economic Review, 96,
1652–1678.
74. Kamenica, E. (2012). Behavioral
economics and psychology of
incentives. Annual Review of
Economics, 4, 427–452.
75. Gneezy, U., Meier, S., & Rey-Biel, P.
(2011). When and why incentives (don’t)
work to modify behavior. Journal of
Economic Perspectives, 25, 191–209.
76. Gneezy, U., & Rustichini, A. (2000). A
fine is a price. Journal of Legal Studies,
29, 1–18.
77. Mellström, C., & Johannesson, M.
(2008). Crowding out in blood donation:
Was Titmuss right? Journal of the
European Economic Association, 6,
845–863.
78. Thaler, R. H., Sunstein, C. R., & Balz, J. P.
(2012). Choice architecture. In E. Shafir
(Ed.), The behavioral foundations of
public policy (pp. 428–439). Princeton,
NJ: Princeton University Press.
79. Brockington, D. (2003). A low
information theory of ballot position
effect. Political Behavior, 25, 1–27.
80. Hadar, L., Sood, S., & Fox, C. R. (2013).
Subjective knowledge in consumer
financial decisions. Journal of Marketing
Research, 50, 303–316.
81. Hadar, L., Tannenbaum, T., & Fox,
C. R. (2017). Subjective knowledge
attenuates default effects. Working
paper, Interdisciplinary Center Herzliya,
Herzliya, Israel.
82. Tannenbaum, D., Fox, C. R., & Rogers,
T. (2017). On the misplaced politics
of behavioral policy interventions.
Nature Human Behaviour, 1, Article
0130. https://doi.org/10.1038/
s41562-017-0130
83. Forehand, M. R., & Grier, S. (2003).
When is honesty the best policy?
The effect of stated company intent
on consumer skepticism. Journal of
Consumer Psychology, 13, 349–356.
84. Costa, D. L., & Kahn, M. E. (2013).
Energy conservation “nudges” and
environmentalist ideology: Evidence
from a randomized residential electricity
field experiment. Journal of the
European Economic Association, 11,
680–702.
85. Reisch, L. A., & Sunstein, C. R. (2016).
Do Europeans like nudges? Judgment
and Decision Making, 11, 310–325.
86. De Haan, T., & Linde, J. (2017). “Good
nudge lullaby”: Choice architecture
and default bias reinforcement. The
Economic Journal. Advance online
publication. https://doi.org/10.1111/
ecoj.12440
87. Goldstein, D. G., Johnson, E. J.,
Herrmann, A., & Heitmann, M. (2008).
Nudge your customers toward better
choices. Harvard Business Review, 86,
99–105.
88. Jones, E. E., & Davis, K. E. (1965). From
acts to dispositions: The attribution
process in person perception. In
L. Berkowitz (Ed.), Advances in
experimental social psychology (Vol.
2, pp. 219–266). Durham, NC: Duke
University Press.
89. Chaiken, S., & Eagly, A. H. (1989).
Heuristic and systematic information
processing within and beyond the
persuasion context. In J. S. Uleman & J.
A. Bargh (Eds.), Unintended thought (pp.
212–252). New York, NY: Guilford Press.
90. Petty, R. E., & Cacioppo, J. T. (1986).
The elaboration likelihood model
of persuasion. In R. E. Petty (Ed.),
Communication and persuasion (pp.
1–24). New York, NY: Springer.
91. Folkes, V. S. (1988). Recent attribution
research in consumer behavior: A
review and new directions. Journal of
Consumer Research, 14, 548–565.
92. Pyszczynski, T. A., & Greenberg,
J. (1981). Role of disconfirmed
expectancies in the instigation of
attributional processing. Journal of
Personality and Social Psychology, 40,
31–38.
93. Weiner, B. (1985). An attributional
theory of achievement motivation and
emotion. Psychological Review, 92,
548–573.
94. Kahneman, D., & Miller, D. T. (1986).
Norm theory: Comparing reality to its
alternatives. Psychological Review, 93,
136–153.
95. Wood, W., & Quinn, J. M. (2003).
Forewarned and forearmed? Two metaanalysis
syntheses of forewarnings
of influence appeals. Psychological
Bulletin, 129, 119–138.
96. Campbell, M. C., Mohr, G., & Verlegh,
P. W. J. (2012). Can disclosures lead
consumers to resist covert persuasion?
The important roles of disclosure
timing and type of response. Journal of
Consumer Psychology, 23, 483–495.
97. Bang, H. M., Shu, S. B., & Weber,
E. U. (2018). The role of perceived
effectiveness on the acceptability of
choice architecture. Behavioural Public
Policy. Advance online publication.
https://doi.org/10.1017/bpp.2018.1
98. Felsen, G., Castelo, N., & Reiner, P. B.
(2013). Decisional enhancement and
autonomy: Public attitudes towards
overt and covert nudges. Judgment and
Decision Making, 8, 202–213.
99. Science and Technology Select
Committee. (2011). Behaviour change
(Second report of Session 2010–12, HL
Paper 179). London, United Kingdom:
House of Lords.
100. Steffel, M., Williams, E. F., & Pogacar,
R. (2016). Ethically deployed defaults:
Transparency and consumer protection
through disclosure and preference
articulation. Journal of Marketing
Research, 53, 865–880.
101. Bruns, H., Kantorowicz-Reznichenko,
E., Klement, K., Jonsson, M. L., & Rahali,
B. (2018). Can nudges be transparent
and yet effective? Journal of Economic
Psychology, 65, 41–59. https://doi.
org/10.1016/j.joep.2018.02.002
102. Kroese, F. M., Marchiori, D. R., & de
Ridder, D. T. (2015). Nudging healthy
food choices: A field experiment at the
train station. Journal of Public Health,
38, e133–e137.
103. Loewenstein, G., Bryce, C., Hagmann,
& Rajpal, S. (2015). Warning: You are
about to be nudged. Behavioral Science
& Policy, 1(1), 35–42.
104. Haynes, L., Service, O., Goldacre,
B., & Torgerson, D. (2012). Test, learn,
adapt: Developing public policy with
randomized controlled trials. London,
United Kingdom: Cabinet Office
Behavioural Insights Team.
105. Giessen, P. (2018, February 4). Waarom
dat getwijfel over de donorwet?
Elders in Europa gaat orgaandonatie
simpeler [Why the hesitation about
the donor law? Elsewhere in Europe
organ donation is done simpler].
Volkskrant. Retrieved from https://
www.volkskrant.nl/wetenschap/
waarom-dat-getwijfel-over-dedonorwet-
elders-in-europa-gaatorgaandonatie-
simpeler~a4566096/
106. Nieuwe donorwet of niet, deze jonge
mensen staan geen organen af [New
donor law or not, these young people
will not donate organs]. (2018, February
13). NOS. Retrieved from https://nos.nl/
18 behavioral science & policy | volume 3 issue 2 2017
op3/artikel/2216962-nieuwe-donorwetof-
niet-deze-jonge-mensen-staangeen-
organen-af.html
107. Rosdorf, M. (2018, February 14).
Vreugde en onrust op social media over
donorwet [Joy and unrest on social
media about donor law]. EenVandaag.
Retrieved from https://eenvandaag.
avrotros.nl/item/vreugde-en-onrustop-
social-media-over-donorwet/