* This introduction was originally published in the Behavioral Economics Guide 2014. To learn more about the subject and the latest ideas, please download our free annual Behavioral Economics Guides.
Introduction
Think about the last time you purchased a customizable product. Perhaps it was a laptop computer. You may have decided to simplify your decision making by opting for a popular brand or the one you already owned in the past. You may then have visited the manufacturer’s website to place your order. But the decision making process did not stop there, as you now had to customize your model by choosing from different product attributes (processing speed, hard drive capacity, screen size, etc.) and you were still uncertain which features you really needed. At this stage, most technology manufacturers will show a base model with options that can be changed according to the buyer’s preferences. The way in which these product choices are presented to buyers will influence the final purchases made and illustrates a number of concepts from behavioral economic (BE) theories.
First, the base model shown in the customization engine represents a default choice. The more uncertain customers are about their decision, the more likely it is that they will go with the default, especially if it is explicitly presented as a recommended configuration. Second, the manufacturer can frame options differently by employing either an ‘add’ or ‘delete’ customization mode (or something in between). In an add mode, customers start with a base model and then add more or better options. In a delete frame, the opposite process occurs, whereby customers have to deselect options or downgrade from a fully-loaded model. Past research suggests that consumers end up choosing a greater number of features when they are in a delete rather than an add frame (Biswas, 2009). Finally, the option framing strategy will be associated with different price anchors prior to customization, which may influence the perceived value of the product. If the final configured product ends up with a £1500 price tag, its cost is likely to be perceived as more attractive if the initial default configuration was £2000 (fully loaded) rather than £1000 (base). Sellers will engage in a process of careful experimentation to find a sweet spot—an option framing strategy that maximizes sales, but set at a default price that deters a minimum of potential buyers from considering a purchase in the first place.
Rational Choice
In an ideal world, defaults, frames, and price anchors would not have any bearing on consumer choices. Our decisions would be the result of a careful weighing of costs and benefits and informed by existing preferences. We would always make optimal decisions. In the 1976 book The Economic Approach to Human Behavior, the economist Gary S. Becker famously outlined a number of ideas known as the pillars of so-called ‘rational choice’ theory. The theory assumes that human actors have stable preferences and engage in maximizing behavior. Becker, who applied rational choice theory to domains ranging from crime to marriage, believed that academic disciplines such as sociology could learn from the ‘rational man’ assumption advocated by neoclassical economists since the late 19th century. The decade of the 1970s, however, also witnessed the beginnings of the opposite flow of thinking, as discussed in the next section.
Prospect Theory
While economic rationality influenced other fields in the social sciences from the inside out, through Becker and the Chicago School, psychologists offered an outside-in reality check to prevailing economic thinking. Most notably, Amos Tversky and Daniel Kahneman published a number of papers that appeared to undermine ideas about human nature held by mainstream economics. They are perhaps best known for the development of prospect theory (Kahneman & Tversky, 1979), which shows that decisions are not always optimal. Our willingness to take risks is influenced by the way in which choices are framed, i.e. it is context-dependent. Have a look at the following classic decision problem:
Which of the following would you prefer:
- A) A certain win of $250, versus
B) A 25% chance to win $1000 and a 75% chance to win nothing? - How about:
C) A certain loss of $750, versus
D) A 75% chance to lose $1000 and a 25% chance to lose nothing?
Tversky and Kahneman’s work shows that responses are different if choices are framed as a gain (1) or a loss (2). When faced with the first type of decision, a greater proportion of people will opt for the riskless alternative A), while for the second problem people are more likely to choose the riskier D). This happens because we dislike losses more than we like an equivalent gain: Giving something up is more painful than the pleasure we derive from receiving it.
Bounded Rationality
Long before Tversky and Kahneman’s work, 18th– and 19th-century thinkers were already interested in the psychological underpinnings of economic life. Scholars during the neoclassical revolution at the turn of the 20th century, however, increasingly tried to emulate the natural sciences, as they wanted to differentiate themselves from the then “unscientific” field of psychology (see summary in Camerer, Loewenstein and Rabin, 2011). The importance of psychologically informed economics was later reflected in the concept of ‘bounded rationality’, a term associated with Herbert Simon’s work of the 1950s. According to this view, our minds must be understood relative to the environment in which they evolved. Decisions are not always optimal. There are restrictions to human information processing, due to limits in knowledge (or information) and computational capacities (Simon, 1982; Kahneman, 2003).
Gerd Gigerenzer’s work on “fast and frugal” heuristics later built on Simon’s ideas and proposed that the rationality of a decision depends on structures found in the environment. People are “ecologically rational” when they make the best possible use of limited information-processing abilities, by applying simple and intelligent algorithms that can lead to near-optimal inferences (Gigerenzer & Goldstein, 1996).
While the idea of human limits to rationality was not a radically new thought in economics, Tversky and Kahneman’s ‘heuristics and biases’ research program made important methodological contributions, in that they advocated a rigorous experimental approach to understanding economic decisions based on measuring actual choices made under different conditions. About 30 years later, their thinking entered the mainstream, resulting in a growing appreciation in scholarly, public, and commercial spheres.
Mental Accounting
The economist Richard Thaler, a keen observer of human behavior and founder of behavioral economics, was inspired by Kahneman & Tversky’s work (see Thaler, 2015, for a summary). Thaler coined the concept of mental accounting. According to Thaler, people think of value in relative rather than absolute terms. They derive pleasure not just from an object’s value, but also the quality of the deal – its transaction utility (Thaler, 1985). In addition, humans often fail to fully consider opportunity costs (tradeoffs) and are susceptible to the sunk cost fallacy.
Why are people willing to spend more when they pay with a credit card than cash (Prelec & Simester, 2001)? Why would more individuals spend $10 on a theater ticket if they had just lost a $10 bill than if they had to replace a lost ticket worth $10 (Kahneman & Tversky, 1984)? Why are people more likely to spend a small inheritance and invest a large one (Thaler, 1985)?
According to the theory of mental accounting, people treat money differently, depending on factors such as the money’s origin and intended use, rather than thinking of it in terms of the “bottom line” as in formal accounting (Thaler, 1999). An important term underlying the theory is fungibility, the fact that all money is interchangable and has no labels. In mental accounting, people treat assets as less fungible than they really are. Even seasoned investors are susceptible to this bias when they view recent gains as disposable “house money” (Thaler & Johnson, 1990) that can be used in high-risk investments. In doing so, they make decisions on each mental account separately, losing out the big picture of the portfolio.
Consumers’ tendency to work with mental accounts is reflected in various domains of applied behavioral science, especially in the financial services industry. Examples include banks offering multiple accounts with savings goal labels, which make mental accounting more explicit, as well as third-party services that provide consumers with aggregate financial information across different financial institutions (Zhang & Sussman, 2018).
Another concept related to mental accounting captures the fact that people don’t like to spend money. We experience pain of paying (Zellermayer, 1996), because we are loss averse. The pain of paying plays an important role in consumer self-regulation to keep spending in check (Prelec & Loewenstein, 1998). This pain is thought to be reduced in credit card purchases, because plastic is less tangible than cash, the depletion of resources (money) is less visible and payment is deferred. Different types of people experience different levels of pain of paying, which can affect spending decisions. Tightwads, for instance, experience more of this pain than spendthrifts. As a result, tightwads are particularly sensitive to marketing contexts that make spending less painful (Rick, 2018).
Too Much Information: Choice Overload
Humans’ bounded rationality is particularly well illustrated by the concept of choice overload. Also referred to as ‘overchoice’, this phenomenon occurs as a result of too many choices being available to consumers. Overchoice has been associated with unhappiness (Schwartz, 2004), decision fatigue, going with the default option, as well as choice deferral—avoiding making a decision altogether, such as not buying a product (Iyengar & Lepper, 2000). Many different factors may contribute to perceived choice overload, including the number of options and attributes, time constraints, decision accountability, alignability and complementarity of options, consumers’ preference uncertainty, among other factors (Chernev et al., 2015).
Choice overload can be counteracted by simplifying choice attributes or the number of available options (Johnson et al., 2012).
Limited Information: The Importance of Feedback
Bounded rationality’s principle of limited knowledge or information is one of the topics discussed in the 2008 book Nudge. In the book, Thaler and Sunstein point to experience, good information, and prompt feedback as key factors that enable people to make good decisions. Consider climate change, for example, which has been cited as a particularly challenging problem in relation to experience and feedback. Climate change is invisible, diffuse, and a long-term process. Pro-environmental behavior by an individual, such as reducing carbon emissions, does not lead to a noticeable change. The same is true in the domain of health. Feedback in this area is often poor, and we are more likely to get feedback on previously chosen options than rejected ones.
The impact of smoking, for example, is at best noticeable over the course of years, while its effect on cells and internal organs is usually not evident to the individual. Traditionally, generic feedback aimed at inducing behavioral change has been limited to information ranging from the economic costs of the unhealthy behavior to its potential health consequences (Diclemente et al., 2001). More recent behavior change programs, such as those employing smartphone apps to stop smoking, now usually provide positive and personalized behavioral feedback, which may include the number of cigarettes not smoked and money saved, along with information about health improvement and disease avoidance.
Information Avoidance
Behavioral economics assumes that people are boundedly rational actors with a limited ability to process information. While a great deal of research has been devoted to exploring how available information affects the quality and outcomes of decisions, a newer strand of research has also explored situations where people avoid information altogether.
Information avoidance in behavioral economics (Golman et al., 2017) refers to situations in which people choose not to obtain knowledge that is freely available. Active information avoidance includes physical avoidance, inattention, the biased interpretation of information (see also confirmation bias) and even some forms of forgetting. In behavioral finance, for example, research has shown that investors are less likely to check their portfolio online when the stock market is down than when it is up, which has been termed the ostrich effect (Karlsson et al., 2009). More serious cases of avoidance happen when people fail to return to clinics to get medical test results, for instance (Sullivan et al., 2004).
While information avoidance is sometimes strategic, it can have immediate hedonic benefits for people if it prevents the negative (usually psychological) consequences of knowing the information. It usually carries negative utility in the long term, because it deprives people of potentially useful information for decision making and feedback for future behavior. Furthermore, information avoidance can contribute to a polarization of political opinions and media bias.
“Irrational” Decision Making: The Example of the Psychology of Price
Boundedly rational choices, made due to limits in our thinking processes, especially those we make as consumers, are illustrated well in Dan Ariely’s popular science book Predictably Irrational. A good portion of the research he discusses involves prices and value perception. One study asked participants whether they would buy a product (e.g. a cordless keyboard) for a dollar amount that was equal to the last two digits of their US social security number. They were then asked about the maximum they would be willing to pay. In the case of cordless keyboards, people in the top 20% of social security numbers were willing to pay three times as much compared to those in the bottom 20%. The experiment demonstrates anchoring, a process whereby a numeric value provides a non-conscious reference point that influences subsequent value perceptions (Ariely, Loewenstein, & Prelec, 2003).
Ariely also introduces the concept of the zero price effect, namely when a product is advertised as ‘Free’, consumers perceive it as intrinsically more valuable. A free chocolate is disproportionately more attractive relative to a $0.14 chocolate than a $0.01 chocolate is compared to one priced at $0.15. To a ‘rational’ economic decision maker, a price difference of 14 cents should always provide the same magnitude of change in incentive to choose the product (Shampanier, Mazar, & Ariely, 2007). Finally, price is often taken as an indicator of quality, and it can even serve as a cue with physical consequences, just like a placebo in medical studies. One experiment, for instance, gave participants a drink that purportedly helped mental acuity. When people received a discounted drink their performance in solving puzzles was significantly lower compared to regular-priced and control conditions (Shiv, Carmon, & Ariely, 2005).
Price can also be an ingredient for a decoy effect. Choices often occur relative to what is on offer rather than based on absolute preferences. The decoy effect is technically known as an ‘asymmetrically dominated choice’ and occurs when people’s preference for one option over another changes as a result of adding a third (similar but less attractive) option. Ariely (2008) illustrates this with subscription options advertised by The Economist newspaper. Subscription options included web-only content for $59, print-only for $125, or print and web combined, also for $125. Ariely asked his students. As you would expect, 0% chose the print-only subscription. 84% chose the print-online combination, and 16% the web-only subscription. When repeated the poll without the print-only option, 32% opted for print-only, while 68% preferred to go web-only. The presence of the inferior option (print-only for $125) made the web and print subscription seem like a better deal.
Predictably Irrational and Nudge alerted the public to a new breed of economists influenced by the study of behavioral decision making that was pioneered by Kahneman and Tversky’s work (sometimes referred to as ‘choice under uncertainty’). The psychology of homo economicus—a rational and selfish individual with relatively stable preferences—has been challenged, and the traditional view that behavior change should be achieved by informing, convincing, incentivizing or penalizing people has been questioned (Thaler & Sunstein, 2008). The field associated with this stream of research and theory is behavioral economics (BE), which suggests that human decisions are strongly influenced by context, including the way in which choices are presented to us. Behavior varies across time and space, and it is subject to cognitive biases, emotions, and social influences. Decisions are the result of less deliberative, linear, and controlled processes than we would like to believe.
[Continued…]
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