Choice architecture

Last updated

Choice architecture is the design of different ways in which choices can be presented to decision makers, and the impact of that presentation on decision-making. For example, each of the following:

Contents

can influence consumer choice. As a result, advocates of libertarian paternalism and asymmetric paternalism have endorsed the deliberate design of choice architecture to nudge consumers toward personally and socially desirable behaviors like saving for retirement, choosing healthier foods, or registering as an organ donor. These interventions are often justified by advocates of libertarian paternalism in that well-designed choice architectures can compensate for irrational decision-making biases to improve consumer welfare. [5] These techniques have consequently become popular among policymakers, leading to the formation of the UK's Behavioural Insights Team and the White House "Nudge Unit" for example. [6] While many behavioral scientists stress that there is no neutral choice-architecture and that consumers maintain autonomy and freedom of choice despite manipulations of choice architecture, [7] critics of libertarian paternalism often argue that choice architectures designed to overcome irrational decision biases may impose costs on rational agents, for example by limiting choice [8] or undermining respect for individual human agency and moral autonomy. [9] Moreover, it can result in dark patterns because of the Principal–agent problem.

Background

The term "choice architecture" was coined by Richard Thaler and Cass Sunstein in their 2008 book Nudge: Improving Decisions about Health, Wealth, and Happiness . [10] Thaler and Sunstein have endorsed thoughtful design of choice architecture as a means to improve consumer decision-making by minimizing biases and errors that arise as the result of bounded rationality. This approach is an example of "libertarian paternalism", a philosophy endorsed by Thaler and Sunstein that aims to "nudge" individuals toward choices that are in their best interest without forbidding options or significantly changing their economic incentives. [11] They go further to say that completely restricting options is no longer a nudge, but simply making something more obvious amongst a group of choices is.

Libertarian paternalism may also be described as soft paternalism.

Behavioral scientists have grouped the elements of choice architecture in different ways. For example, Thaler, Sunstein, and John P. Balz have focused on the following "tools" of choice architecture: defaults, expecting error, understanding mappings (which involves exploring the different ways that information presentation affects option comparisons), giving feedback, structuring complex choices, and creating incentives. [5] Another group of leading behavioral scientists has created a typology of choice architecture elements dividing them into those that structure the choice set and those that describe the choice. Examples of choice set structuring include: the number of alternatives, decision aids, defaults, and choice over time. Describing choice options include: partitioning options and attributes, and designing attributes. [7] The most prominent element amongst those listed above is said the be the use of defaults as it preselects the option that is in the best interest of the consumer, firm, or potentially both.

Elements

Research from the field of behavioral economics has shown that individuals tend to be subject to predictable biases that may lead to decision errors. The following sections describe these biases and describe the ways that they can be minimized by changing decision context through choice architecture.

Reducing choice overload

Classical economics predicts that providing more options will generally improve consumer utility, or at least leave it unchanged. However, each additional choice demands additional time and consideration to evaluate, potentially outweighing the benefits of greater choice. Behavioral economists have shown that in some instances presenting consumers with many choices can lead to reduced motivation to make a choice and decreased satisfaction with choices once they are made. [7] This phenomenon is often referred to as choice overload, [12] Overchoice or the tyranny of choice. [13] However, the importance of this effect appears to vary significantly across situations. [7] Choice architects can reduce choice overload by either limiting alternatives or providing decision support tools.

Choice architects may choose to limit choice options; however, limits to choice may lead to reductions of consumer welfare. This is because, the greater the number of choices, the greater the likelihood that the choice set will include the optimal choice for any given consumer. As a result, the ideal number of alternatives will depend upon the cognitive effort required to evaluate each option and the heterogeneity of needs and preferences across consumers. [7] There are examples of consumers faring worse with many options rather than fewer in social-security investments [4] and Medicare drug plans [14]

As consumption decisions increasingly move online, consumers are relying upon search engines and product recommendation systems to find and evaluate products and services. These types of search and decision aids both reduce the time and effort associated with information search, but also have the power to subtly shape decisions dependent upon what products are presented, the context of the presentation, and the way that they are ranked and ordered. For example, research on consumer goods like wine has shown that the expansion of online retailing has made it simpler for consumers to gather information on products and compare alternatives, making them more responsive to price and quality information. [15]

Defaults

A large body of research has shown that, all things being equal, consumers are more likely to choose default options. [16] A default is defined as a choice frame in which one selection is pre-selected so that individuals must take active steps to select another option. [17] Defaults can take many forms ranging from the automatic enrollment of college students in university health insurance plans to forms which default to a specific option unless changed.

Several mechanisms have been proposed to explain the influence of defaults. For example, individuals may interpret defaults as policymaker recommendations, cognitive biases related to loss aversion like the status quo bias or endowment effect might be at work, or consumers may fail to opt-out of the default due to associated effort. [16] It is important to note that these mechanisms are not mutually exclusive and their relative influence will likely differ across decision contexts.

Types of default include simple defaults where one choice is automatically selected for all consumers, forced-choice in which a product or service is denied until the consumer makes a proactive selection, and sensory defaults in which the choice is pre-selected based upon other information that was gathered about specific consumers. Choices that are made repeatedly may also be affected by defaults, for instance, persistent defaults may be continually reset regardless of past decisions, whereas reoccurring defaults "remember" past decisions for use as the default, and predictive defaults use algorithms to set defaults based upon other related behavior. [7]

One of the most commonly cited studies on the power of defaults is the example of organ donation. One study found that donor registration rates were twice as high when potential donors had to opt out versus opt into donor registration. [3] However, the influence of defaults has been demonstrated across a range of domains including investment [4] [18] and insurance [19]

Choice over time

Choices with outcomes that manifest in the future will be influenced by several biases. For example, individuals tend to be myopic, preferring positive outcomes in the present often at the expense of future outcomes. This may lead to behaviors like overeating or overspending in the short-term at the expense of longer-term health and financial security outcomes. In addition, individual projections about the future tend to be inaccurate. When the future is uncertain they may overestimate the likelihood of salient or desirable outcomes, [20] [21] and are generally overly optimistic about the future, for example assuming that they will have more time and money in the future than they will in actuality. [22] [23]

However research indicates that there are several ways to structure choice architecture to compensate for or reduce these biases. For example, researchers demonstrated improved decision-making by drawing attention to the future outcomes of decisions [24] or by emphasizing second best options. [21] In addition, limited time offers can be successful in reducing procrastination. [7]

Partitioning options and attributes

The ways in which options and attributes are grouped influence the choices that are made. Examples of such partitioning of options include the division of a household budget into categories (e.g. rent, food, utilities, transportation etc.), or categories of investments within a portfolio (e.g. real estate, stocks, bonds, etc.), while examples of partitioning attributes include the manner in which attributes are grouped together for example a label may group several related attributes together (e.g. convenient) or list them individually (e.g. short running time, little cleanup, low maintenance). The number and type of these categories is important because individuals have a tendency to allocate scarce resources equally across them. People tend to divide investments over the options listed in 401K plans [25] they favor equal allocation of resources and costs across individuals (all else being equal), [26] and are biased to assign equal probabilities to all events that could occur. [27] [28] As a result, aggregate consumption can be changed by the number and types of categorizations. For instance, car buyers can be nudged toward more responsible purchases by itemizing practical attributes (gas mileage, safety, warranty etc.) and aggregating less practical attributes (i.e. speed, radio, and design are grouped together as "stylishness"). [29]

Avoiding attribute overload

Consumers would optimally consider all of a product's attributes when deciding between options. However, due to cognitive constraints, consumers may face similar challenges in weighing many attributes to those of evaluating many choices. As a result, choice architects may choose to limit the number of attributes, weighing the cognitive effort required to consider multiple attributes [30] against the value of improved information. This may present challenges if consumers care about different attributes, but online forms that allow consumers to sort by different attributes should minimize the cognitive effort to evaluate many options without losing choice.

Translating attributes

The presentation of information about attributes can also reduce the cognitive effort associated with processing and reduce errors. This can generally be accomplished by increasing evaluability and comparability of attributes. [7] One example is to convert commonly used metrics into those that consumers can be assumed to care about. For example, choice architects might translate non-linear metrics (including monthly credit payments or miles per gallon) into relevant linear metrics (in this case the payback period associated with a credit payment or the gallons per 100 miles). [2] Choice architects can also influence decisions by adding evaluative labels (e.g. good versus bad or high versus low) to numerical metrics, [31] explicitly calculating consequences (for instance translating energy consumption into greenhouse gas emissions), or by changing the scale of a metric (for instance listing monthly cost versus yearly cost). [32]

Examples

The concept of choice architecture exists in a number of fields. See for example the work of B. J. Fogg on computers as persuasive technologies; the concept of permission marketing as described by Seth Godin. Choice Architecture is also similar to the concept of "heuristics," or manipulation that changes outcomes without changing people's underlying preferences, described by political scientist William H. Riker. Choice architecture has been implemented in several public and private policy domains. Variants of the Save More Tomorrow Plan (conceived by Richard Thaler and Shlomo Benartzi), which has individuals commit in advance to allocate a portion of future salary increases to savings, have been adopted by companies to increase employee retirement savings. [33]

Lev Virine and Michael Trumper applied choice architecture concept to project management. [34] They proposed Choice Engineering as a choice architecture-related framework for improving project decisions. Project managers make predictable, repeated mental mistakes which could lead to project failures. Choice Engineering is a creating of processes or environment in which project managers would be steered towards making better choices rather than mandating these choices. The examples of such processes would be using checklists and templates, introducing project audit rather than direct control, providing full disclosure of information for project team members, improving project management education, and other processes. Virine and Trumper argued that in many cases, especially for smaller projects, it would be more beneficial to use Choice Engineering rather than strict and complex project management processes.

Criticisms

Choice architecture interventions may fail to produce their desired result for several reasons. First, individual differences may lead consumers to respond differently to information. For example, liberals and conservatives have been shown to respond differently to information about the environmental consequences of energy-related behaviors, [35] while individual numeracy has also been linked to different responses to choice architectures. [7]

A second major challenge is assessing whether choice architectures are, in fact, improving decision-making and making people better off as Sunstein and Thaler propose. Questions arise in regards to what constitutes someone as better off and where this standard might come from. Heath recommendations (for example, 60 minutes of physical activity each day) that promote physical wellness can be assessed and the consequences of not meeting these recommendations are well researched and observable. Thus, the use of choice architectures to promote healthy decisions can be easily justified. Though typically choice architecture is implemented with the intention of nudging consumers to socially and personally desirable choices, they can sometimes increase firm profits while decreasing consumer welfare. [36] One way of assessing how a consumer is impacted in this case, is to evaluate consumer experiences after the choice has been made both in the short and long-term. [7]

Terminology

See also

Related Research Articles

<span class="mw-page-title-main">Cognitive bias</span> Systematic pattern of deviation from norm or rationality in judgment

A cognitive bias is a systematic pattern of deviation from norm or rationality in judgment. Individuals create their own "subjective reality" from their perception of the input. An individual's construction of reality, not the objective input, may dictate their behavior in the world. Thus, cognitive biases may sometimes lead to perceptual distortion, inaccurate judgment, illogical interpretation, and irrationality.

Bounded rationality is the idea that rationality is limited when individuals make decisions, and under these limitations, rational individuals will select a decision that is satisfactory rather than optimal.

Behavioral economics is the study of the psychological, cognitive, emotional, cultural and social factors involved in the decisions of individuals or institutions, and how these decisions deviate from those implied by classical economic theory.

<span class="mw-page-title-main">Loss aversion</span> Overall description of loss aversion theory

Loss aversion is a psychological and economic concept, which refers to how outcomes are interpreted as gains and losses where losses are subject to more sensitivity in people's responses compared to equivalent gains acquired. Kahneman and Tversky (1992) suggested that losses can be twice as powerful psychologically as gains.

The anchoring effect is a psychological phenomenon in which an individual's judgements or decisions are influenced by a reference point or "anchor" which can be completely irrelevant. Both numeric and non-numeric anchoring have been reported in research. In numeric anchoring, once the value of the anchor is set, subsequent arguments, estimates, etc. made by an individual may change from what they would have otherwise been without the anchor. For example, an individual may be more likely to purchase a car if it is placed alongside a more expensive model. Prices discussed in negotiations that are lower than the anchor may seem reasonable, perhaps even cheap to the buyer, even if said prices are still relatively higher than the actual market value of the car. Another example may be when estimating the orbit of Mars, one might start with the Earth's orbit and then adjust upward until they reach a value that seems reasonable.

Status quo bias is an emotional bias; a preference for the maintenance of one's current or previous state of affairs, or a preference to not undertake any action to change this current or previous state. The current baseline is taken as a reference point, and any change from that baseline is perceived as a loss or gain. Corresponding to different alternatives, this current baseline or default option is perceived and evaluated by individuals as a positive.

In psychology and behavioral economics, the endowment effect is the finding that people are more likely to retain an object they own than acquire that same object when they do not own it. The endowment theory can be defined as "an application of prospect theory positing that loss aversion associated with ownership explains observed exchange asymmetries."

<span class="mw-page-title-main">Cass Sunstein</span> American legal scholar, writer, blogger (born 1954)

Cass Robert Sunstein is an American legal scholar known for his work in constitutional law, administrative law, environmental law, and behavioral economics. He is also The New York Times best-selling author of The World According to Star Wars (2016) and Nudge (2008). He was the administrator of the White House Office of Information and Regulatory Affairs in the Obama administration from 2009 to 2012.

<span class="mw-page-title-main">Richard Thaler</span> American economist

Richard H. Thaler is an American economist and the Charles R. Walgreen Distinguished Service Professor of Behavioral Science and Economics at the University of Chicago Booth School of Business. In 2015, Thaler was president of the American Economic Association.

<span class="mw-page-title-main">Mental accounting</span>

Mental accounting is a model of consumer behaviour developed by Richard Thaler that attempts to describe the process whereby people code, categorize and evaluate economic outcomes. Mental accounting incorporates the economic concepts of prospect theory and transactional utility theory to evaluate how people create distinctions between their financial resources in the form of mental accounts, which in turn impacts the buyer decision process and reaction to economic outcomes. People are presumed to make mental accounts as a self control strategy to manage and keep track of their spending and resources. People budget money into mental accounts for savings or expense categories. People also are assumed to make mental accounts to facilitate savings for larger purposes. Mental accounting can result in people demonstrating greater loss aversion for certain mental accounts, resulting in cognitive bias that incentivizes systematic departures from consumer rationality. Through increased understanding of mental accounting differences in decision making based on different resources, and different reactions based on similar outcomes can be greater understood.

Choice-supportive bias or post-purchase rationalization is the tendency to retroactively ascribe positive attributes to an option one has selected and/or to demote the forgone options. It is part of cognitive science, and is a distinct cognitive bias that occurs once a decision is made. For example, if a person chooses option A instead of option B, they are likely to ignore or downplay the faults of option A while amplifying or ascribing new negative faults to option B. Conversely, they are also likely to notice and amplify the advantages of option A and not notice or de-emphasize those of option B.

Libertarian paternalism is the idea that it is both possible and legitimate for private and public institutions to affect behavior while also respecting freedom of choice, as well as the implementation of that idea. The term was coined by behavioral economist Richard Thaler and legal scholar Cass Sunstein in a 2003 article in the American Economic Review. The authors further elaborated upon their ideas in a more in-depth article published in the University of Chicago Law Review that same year. They propose that libertarian paternalism is paternalism in the sense that "it tries to influence choices in a way that will make choosers better off, as judged by themselves" ; note and consider, the concept paternalism specifically requires a restriction of choice. It is libertarian in the sense that it aims to ensure that "people should be free to opt out of specified arrangements if they choose to do so". The possibility to opt out is said to "preserve freedom of choice". Thaler and Sunstein published Nudge, a book-length defense of this political doctrine, in 2008.

The framing effect is a cognitive bias in which people decide between options based on whether the options are presented with positive or negative connotations. Individuals have a tendency to make risk-avoidant choices when options are positively framed, while selecting more loss-avoidant options when presented with a negative frame. In studies of the bias, options are presented in terms of the probability of either losses or gains. While differently expressed, the options described are in effect identical. Gain and loss are defined in the scenario as descriptions of outcomes, for example, lives lost or saved, patients treated or not treated, monetary gains or losses.

Attribute substitution is a psychological process thought to underlie a number of cognitive biases and perceptual illusions. It occurs when an individual has to make a judgment that is computationally complex, and instead substitutes a more easily calculated heuristic attribute. This substitution is thought of as taking place in the automatic intuitive judgment system, rather than the more self-aware reflective system. Hence, when someone tries to answer a difficult question, they may actually answer a related but different question, without realizing that a substitution has taken place. This explains why individuals can be unaware of their own biases, and why biases persist even when the subject is made aware of them. It also explains why human judgments often fail to show regression toward the mean.

<i>Nudge</i> (book) 2008 book by Richard H. Thaler and Cass R. Sunstein

Nudge: Improving Decisions about Health, Wealth, and Happiness is a book written by University of Chicago economist and Nobel Laureate Richard H. Thaler and Harvard Law School Professor Cass R. Sunstein, first published in 2008. In 2021, a revised edition was released, subtitled The Final Edition.

Heuristics is the process by which humans use mental shortcuts to arrive at decisions. Heuristics are simple strategies that humans, animals, organizations, and even machines use to quickly form judgments, make decisions, and find solutions to complex problems. Often this involves focusing on the most relevant aspects of a problem or situation to formulate a solution. While heuristic processes are used to find the answers and solutions that are most likely to work or be correct, they are not always right or the most accurate. Judgments and decisions based on heuristics are simply good enough to satisfy a pressing need in situations of uncertainty, where information is incomplete. In that sense they can differ from answers given by logic and probability.

Nudge theory is a concept in behavioral economics, decision making, behavioral policy, social psychology, consumer behavior, and related behavioral sciences that proposes adaptive designs of the decision environment as ways to influence the behavior and decision-making of groups or individuals. Nudging contrasts with other ways to achieve compliance, such as education, legislation or enforcement.

The default effect, a concept within the study of nudge theory, explains the tendency for an agent to generally accept the default option in a strategic interaction. The default option is the course of action that the agent, or chooser, will obtain if he or she does not specify a particular course of action. The default effect has broad applications for firms attempting to 'nudge' their customers in the direction of the firm's optimal outcome. Experiments and observational studies show that making an option a default increases the likelihood that such an option is chosen. There are two broad classes of defaults: mass defaults and personalised defaults. Setting or changing defaults has been proposed and applied by firms as an effective way of influencing behaviour—for example, with respect to setting air-conditioner temperature settings, giving consent to receive e-mail marketing, or automatic subscription renewals.

Debiasing is the reduction of bias, particularly with respect to judgment and decision making. Biased judgment and decision making is that which systematically deviates from the prescriptions of objective standards such as facts, logic, and rational behavior or prescriptive norms. Biased judgment and decision making exists in consequential domains such as medicine, law, policy, and business, as well as in everyday life. Investors, for example, tend to hold onto falling stocks too long and sell rising stocks too quickly. Employers exhibit considerable discrimination in hiring and employment practices, and some parents continue to believe that vaccinations cause autism despite knowing that this link is based on falsified evidence. At an individual level, people who exhibit less decision bias have more intact social environments, reduced risk of alcohol and drug use, lower childhood delinquency rates, and superior planning and problem solving abilities.

References

  1. Scheibehenne, Benjamin; Greifeneder, Rainer; Todd, Peter (2010). "Can there ever be too many options? A meta-analytic review of choice overload" (PDF). Journal of Consumer Research. 37 (3): 409–25. doi:10.1086/651235. JSTOR   10.1086/651235. S2CID   5802575.
  2. 1 2 Larrick, R.P.; Soll, J.B (2008). "The MPG Illusion". Science. 320 (5883): 1593–4. doi:10.1126/science.1154983. PMID   18566271. S2CID   206511466.
  3. 1 2 Johnson, E.J.; Goldstein, D.G. (2003). "Do Defaults Save Lives?" (PDF). Science. 302 (5649): 1338–1339. doi:10.1126/science.1091721. PMID   14631022. S2CID   166476782. Archived from the original (PDF) on 2020-01-10.
  4. 1 2 3 Cronqvist, H; Thaler, R (2004). "Design choices in privatized social security systems: Learning from the Swedish experience". American Economic Review. 94 (2): 424–8. doi:10.1257/0002828041301632. S2CID   14415952.
  5. 1 2 Thaler, Richard H.; Sunstein, Cass R.; Balz, John P. (2013). Shafir, Eldar (ed.). The Behavioral Foundations of Public Policy. Princeton, New Jersey: Princeton University Press. pp. 428–39.
  6. Nesterak, Evan. "Head of White House "Nudge Unit" Maya Shankar Speaks about Newly Formed Social and Behavioral Sciences Team". thepsychreport. Archived from the original on 16 November 2018. Retrieved 13 December 2014.
  7. 1 2 3 4 5 6 7 8 9 10 Johnson, Eric J.; Shu, S.B.; Dellaert, B.G.C.; Fox, C.; Goldstein, D.G.; Haeubl, G.; Larrick, R.P.; Payne, J.W.; Schkade, D.; Wansink, B.; Weber, E.U. (2012). "Beyond Nudges: Tools of a choice architecture". Marketing Letters. 23 (2): 487–504. doi:10.1007/s11002-012-9186-1. S2CID   839902.
  8. Mitchell, Gregory (2005). "Libertarian Paternalism is an Oxymoron". Northwestern University Law Review. 99.
  9. Goodwin, Morag (2016). Kemmerer, Alexandra; et al. (eds.). Choice Architecture in Democracies: Exploring the Legitimacy of Nudging. Baden-Baden / Oxford: Nomos / Hart Publishing. pp. 285–307.{{cite book}}: |work= ignored (help)
  10. "Designing better choices". Los Angeles Times. 2 April 2008.
  11. Thaler, Richard; Sunstein, Cass (2008). Nudge: improving decisions about health, wealth, and happiness. Yale University Press. ISBN   978-0-300-12223-7.
  12. Iyengar, S.S.; Lepper, M.R. (2000). "When choice is demotivating: can one desire too much of a good thing?". Journal of Personality and Social Psychology. 79 (6): 995–1006. CiteSeerX   10.1.1.594.9159 . doi:10.1037/0022-3514.79.6.995. PMID   11138768.
  13. Schwartz, B. (2004). The paradox of choice: why more is less. New York: Harper.
  14. Kling, J.; et al. (2012). "Comparison Friction: Experimental Evidence from Medicare Drug Plans". Quarterly Journal of Economics. 127 (1): 199–235. doi:10.1093/qje/qjr055. PMC   3314343 . PMID   22454838.
  15. Lynch, John G.; Ariely, Dan (2000). "Wine Online: Search Costs Affect Competition on Price, Quality, and Distribution". Marketing Science. 19: 83–103. doi:10.1287/mksc.19.1.83.15183. S2CID   260505667.
  16. 1 2 Smith, N.C; Goldstein, D.; Johnson, E. (2013). "Choice without awareness: Ethical and policy implications of defaults". Journal of Public Policy.
  17. 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 (3): 529–39. doi:10.1086/425087. S2CID   145408470.
  18. Madrian, B.C.; Shea, D.F. (2001). "The power of suggestion: inertia in 401(k) participation and savings behavior" (PDF). Quarterly Journal of Economics. 116 (4): 1149–1187. doi:10.1162/003355301753265543.
  19. Johnson, E.J.; et al. (1993). "Framing, probability distortions, and insurance decisions". Journal of Risk and Uncertainty. 7: 35–51. doi:10.1007/BF01065313. S2CID   154911666.
  20. Koehler, D.J. (1991). "Explanation, imagination, and confidence in judgement". Psychological Bulletin. 110 (3): 499–519. doi:10.1037/0033-2909.110.3.499. PMID   1758920.
  21. 1 2 Shu, S.B. (2008). "Future-biased search: the quest for the ideal". Journal of Behavioral Decision Making. 21 (4): 352–377. doi:10.1002/bdm.593. S2CID   691398.
  22. Kahneman, D.; Lovallo, D. (1993). "Timid choices and bold forecasts: a cognitive perspective on risk taking". Management Science. 39: 17–31. doi:10.1287/mnsc.39.1.17. S2CID   53685999.
  23. Zauberman, G.; Lynch, J.G. (2005). "Resource slack and propensity to discount delayed investments of time versus money". Journal of Experimental Psychology. 134 (1): 23–37. doi:10.1037/0096-3445.134.1.23. PMID   15702961.
  24. Weber, E.U.; et al. (2007). "Asymmetric discounting in intertemporal choice: a query theory account". Psychological Science. 18 (6): 516–523. doi:10.1111/j.1467-9280.2007.01932.x. PMID   17576265. S2CID   7327020.
  25. Benartzi, S.; Thaler, R. (2001). "Naive Diversification Strategies in Defined Contribution Saving Plans". American Economic Review. 91: 79–98. doi:10.1257/aer.91.1.79. S2CID   14955737.
  26. Messick, D.M. (1993). "Equality as a decision heuristic". In Psychological Perspectives on Justice: 11–31. doi:10.1017/CBO9780511552069.003. ISBN   9780521431996.
  27. Fox, C.R.; Clemen, R.T. (2005). "Subjective probability assessment in decision analysis: partition dependence and bias toward the ignorance prior". Management Science. 51 (9): 1417–1432. doi:10.1287/mnsc.1050.0409. S2CID   14760347.
  28. Fox, C.R.; Rottenstreich, Y. (2003). "Partition priming in judgement in judgement under uncertainty". Psychological Science. 14 (3): 195–200. doi:10.1111/1467-9280.02431. PMID   12741740. S2CID   12590325.
  29. Martin, J.M.; Norton, M.I. (2009). "Shaping online consumer choice by partitioning the web". Psychology and Marketing. 26 (10): 908–926. doi:10.1002/mar.20305.
  30. Peters, E.; et al. (2007). "Numeracy skill and the communication, comprehension, and use of risk and benefit information" (PDF). Health Affairs. 26 (3): 741–748. doi:10.1377/hlthaff.26.3.741. PMID   17485752. S2CID   5938616.
  31. Peters, E.; et al. (2009). "Bringing meaning to numbers: the impact of evaluative categories on decisions" (PDF). Journal of Experimental Psychology. 15 (3): 213–227. doi:10.1037/a0016978. PMID   19751072. S2CID   11035873.
  32. Burson, K.A.; Larrick, R.P.; Lynch, J.G. (2009). "Six of one, half dozen of the other: expanding and contracting numerical dimensions produces preference reversals". Psychological Science. 20 (9): 1074–1078. doi:10.1111/j.1467-9280.2009.02394.x. PMID   19572972. S2CID   5646829.
  33. "Behavioral economics can help you save money - Jul. 24, 2008".
  34. Virine, Lev; Trumper, Michael (2013). ProjectThink: Why Good Managers Make Poor Project Choices. Gower Pub.Co.
  35. Gromet, D.; Kunreuther, H.; Larrick, R. (2013). "Political Ideology Affects Energy-Efficiency Attitudes and Choices". Proceedings of the National Academy of Sciences. 110 (23): 9314–9. Bibcode:2013PNAS..110.9314G. doi: 10.1073/pnas.1218453110 . PMC   3677426 . PMID   23630266.
  36. Mrkva, Kellen; Posner, Nathaniel A.; Reeck, Crystal; Johnson, Eric J. (July 2021). "Do Nudges Reduce Disparities? Choice Architecture Compensates for Low Consumer Knowledge". Journal of Marketing. 85 (4): 67–84. doi:10.1177/0022242921993186. ISSN   0022-2429.
  37. Sunstein, Cass R.; Thaler, Richard H. (9 May 2003). "Libertarian Paternalism Is Not An Oxymoron". ssrn.com. doi:10.2139/ssrn.405940. S2CID   14916962. SSRN   405940.