Decoy effect

Last updated

In marketing, the decoy effect (or attraction effect or asymmetric dominance effect) is the phenomenon whereby consumers will tend to have a specific change in preference between two options when also presented with a third option that is asymmetrically dominated. [1] An option is asymmetrically dominated when it is inferior in all respects to one option; but, in comparison to the other option, it is inferior in some respects and superior in others. In other words, in terms of specific attributes determining preferences, it is completely dominated by (i.e., inferior to) one option and only partially dominated by the other. When the asymmetrically dominated option is present, a higher percentage of consumers will prefer the dominating option than when the asymmetrically dominated option is absent. The asymmetrically dominated option is therefore a decoy serving to increase preference for the dominating option. The decoy effect is also an example of the violation of the independence of irrelevant alternatives axiom of decision theory. More simply, when deciding between two options, an unattractive third option can change the perceived preference between the other two. [2]

Contents

The decoy effect is considered particularly important in choice theory because it is a violation of the assumption of "regularity" present in all axiomatic choice models, for example in a Luce model of choice. [3] Regularity means that it should not be possible for the market share of any alternative to increase when another alternative is added to the choice set. The new alternative should reduce, or at best leave unchanged, the choice share of existing alternatives. Regularity is violated in the example shown below where a new alternative C not only changes the relative shares of A and B but actually increases the share of A in absolute terms. Similarly, the introduction of a new alternative D increases the share of B in absolute terms.

Examples

Suppose there is a consideration set (options to choose from in a menu) that involves smartphones. Consumers will generally see higher storage capacity (number of GB) and lower price as positive attributes; while some consumers may want a device that can store more photos, music, etc., other consumers will want a device that costs less. In Consideration Set 1, two devices are available:

Consideration Set 1
AB
price$400$300
storage300GB200GB

In this case, some consumers will prefer A for its greater storage capacity, while others will prefer B for its lower price.

Now suppose that a new player, C, the "decoy", is added to the market; it is more expensive than both A, the "target", and B, the "competitor", and has more storage than B but less than A:

Consideration Set 2
A (target)B (competitor)C (decoy)
price$400$300$450
storage300GB200GB250GB

The addition of decoy C — which consumers would presumably avoid, given that a lower price can be paid for a model with more storage—causes A, the dominating option, to be chosen more often than if only the two choices in Consideration Set 1 existed; C affects consumer preferences by acting as a basis of comparison for A and B. Because A is better than C in both respects, while B is only partially better than C, more consumers will prefer A now than did before. C is therefore a decoy whose sole purpose is to increase sales of A.

Conversely, suppose that instead of C, a player D is introduced that has less storage than both A and B, and that is more expensive than B but not as expensive as A:

Consideration Set 3
A (competitor)B (target)D (decoy)
price$400$300$350
storage300GB200GB150GB

The result here is similar: consumers will not prefer D, because it is not as good as B in any respect. However, whereas C increased preference for A, D has the opposite effect, increasing preference for B.

Another example shown in Dan Ariely's book Predictably Irrational was a true case used by The Economist magazine. [4] The subscription screen presented three options:

  1. Economist.com subscription - US $59.00. One-year subscription to Economist.com. Includes online access to all articles from The Economist since 1997
  2. Print subscription - US $125.00. One-year subscription to the print edition of The Economist
  3. Print & web subscription - US $125.00. One-year subscription to the print edition of The Economist and online access to all articles from The Economist since 1997

Given these choices, 16% of the students in the experiment conducted by Ariely chose the first option, 0% chose the middle option, and 84% chose the third option. Even though nobody picked the second option, when he removed that option the result was the inverse: 68% of the students picked the online-only option, and 32% chose the print and web option. [ citation needed ]

Measurement

The decoy effect is usually measured by comparing the frequency of choice of the target, A in the absence of the decoy, C, compared with when the decoy is present in the consideration set. The decoy effect can also be measured as how much more a consumer is ready to pay to choose the target rather than the competitor. [5]

Debate

Some research suggests that the attraction effect does not appear in realistic purchasing scenarios, for example when options are presented graphically, or when the target and the competitor are not exactly of the same value. [6] [7] [5]

The original authors had to underline again that the attraction effect occurs only if the consumer is close to indifference between the target and the competitor, if both dimensions of the products (in our example, price and storage capacity) are about as important as each other to the consumer, if the decoy is not too undesirable, and if the dominance relation is easy to identify. [8] A recent study has indeed confirmed that the attraction effect persists when options are presented graphically, i.e., as scatter plots. [9]

See also

Related Research Articles

As a topic of economics, utility is used to model worth or value. Its usage has evolved significantly over time. The term was introduced initially as a measure of pleasure or happiness as part of the theory of utilitarianism by moral philosophers such as Jeremy Bentham and John Stuart Mill. The term has been adapted and reapplied within neoclassical economics, which dominates modern economic theory, as a utility function that represents a consumer's ordinal preferences over a choice set, but is not necessarily comparable across consumers or possessing a cardinal interpretation. This concept of utility is personal and based on choice rather than on pleasure received, and so requires fewer behavioral assumptions than the original concept.

Arrow's impossibility theorem, the general possibility theorem or Arrow's paradox is an impossibility theorem in social choice theory that states that when voters have three or more distinct alternatives (options), no ranked voting electoral system can convert the ranked preferences of individuals into a community-wide ranking while also meeting the specified set of criteria: unrestricted domain, non-dictatorship, Pareto efficiency, and independence of irrelevant alternatives. The theorem is often cited in discussions of voting theory as it is further interpreted by the Gibbard–Satterthwaite theorem. The theorem is named after economist and Nobel laureate Kenneth Arrow, who demonstrated the theorem in his doctoral thesis and popularized it in his 1951 book Social Choice and Individual Values. The original paper was titled "A Difficulty in the Concept of Social Welfare".

The theory of consumer choice is the branch of microeconomics that relates preferences to consumption expenditures and to consumer demand curves. It analyzes how consumers maximize the desirability of their consumption, by maximizing utility subject to a consumer budget constraint. Factors influencing consumers' evaluation of the utility of goods include: income level, cultural factors, product information and physio-psychological factors.

The independence of irrelevant alternatives (IIA), also known as binary independence or the independence axiom, is an axiom of decision theory and various social sciences. The term is used in different connotation in several contexts. Although it always attempts to provide an account of rational individual behavior or aggregation of individual preferences, the exact formulation differs widely in both language and exact content.

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

Loss aversion is a psychological concept that has been increasingly applied in the field of economic analysis. Finance and insurance are the economics fields with the most active applications. Loss aversion 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) have suggested that losses can be twice as powerful, psychologically, as gains. When defined in terms of the utility function shape as in the Cumulative Prospect Theory (CPT), losses have a steeper utility than gains, thus being more "painful" than the satisfaction from a comparable gain as shown in Figure 1. Loss aversion was first proposed by Amos Tversky and Daniel Kahneman as an important framework for Prospect Theory - an analysis of decision under risk.

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.

Utility maximization was first developed by utilitarian philosophers Jeremy Bentham and John Stuart Mill. In microeconomics, the utility maximization problem is the problem consumers face: "How should I spend my money in order to maximize my utility?" It is a type of optimal decision problem. It consists of choosing how much of each available good or service to consume, taking into account a constraint on total spending (income), the prices of the goods and their preferences.

Revealed preference theory, pioneered by economist Paul Anthony Samuelson in 1938, is a method of analyzing choices made by individuals, mostly used for comparing the influence of policies on consumer behavior. Revealed preference models assume that the preferences of consumers can be revealed by their purchasing habits.

Freedom of choice describes an individual's opportunity and autonomy to perform an action selected from at least two available options, unconstrained by external parties.

<span class="mw-page-title-main">George Loewenstein</span> American educator and economist

George Loewenstein is an American educator and economist. He is the Herbert A. Simon Professor of Economics and Psychology in the Social and Decision Sciences Department at Carnegie Mellon University and director of the Center for Behavioral Decision Research. He is a leader in the fields of behavioral economics, neuroeconomics, Judgment and Decision Making.

Decision field theory (DFT) is a dynamic-cognitive approach to human decision making. It is a cognitive model that describes how people actually make decisions rather than a rational or normative theory that prescribes what people should or ought to do. It is also a dynamic model of decision making rather than a static model, because it describes how a person's preferences evolve across time until a decision is reached rather than assuming a fixed state of preference. The preference evolution process is mathematically represented as a stochastic process called a diffusion process. It is used to predict how humans make decisions under uncertainty, how decisions change under time pressure, and how choice context changes preferences. This model can be used to predict not only the choices that are made but also decision or response times.

<i>Predictably Irrational</i> 2008 book by Dan Ariely

Predictably Irrational: The Hidden Forces That Shape Our Decisions is a 2008 book by Dan Ariely, in which he challenges readers' assumptions about making decisions based on rational thought. Ariely explains, "My goal, by the end of this book, is to help you fundamentally rethink what makes you and the people around you tick. I hope to lead you there by presenting a wide range of scientific experiments, findings, and anecdotes that are in many cases quite amusing. Once you see how systematic certain mistakes are—how we repeat them again and again—I think you will begin to learn how to avoid some of them". The book has been republished in a "revised & expanded edition".

In social choice theory, a dictatorship mechanism is a rule by which, among all possible alternatives, the results of voting mirror a single pre-determined person's preferences, without consideration of the other voters. Dictatorship by itself is not considered a good mechanism in practice, but it is theoretically important: by Arrow's impossibility theorem, when there are at least three alternatives, dictatorship is the only ranked voting electoral system that satisfies unrestricted domain, Pareto efficiency, and independence of irrelevant alternatives. Similarly, by Gibbard's theorem, when there are at least three alternatives, dictatorship is the only strategyproof rule.

Overchoice or choice overload is the paradoxical phenomenon that choosing between a large variety of options can be detrimental to decision making processes. The term was first introduced by Alvin Toffler in his 1970 book, Future Shock.

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:

Itamar Simonson is a professor of marketing, holding the Sebastian S. Kresge Chair of Marketing in the Graduate School of Business, Stanford University. He is known for his work on the factors that determine the choices that buyers make. His academic career started at the University of California at Berkeley, where he taught for six years, before he moved to Stanford. Many of his former PhD students hold senior positions at some of the best universities in the world.

In economics and other social sciences, preference refers to the order in which an agent ranks alternatives based on their relative utility. The process results in an "optimal choice". Preferences are evaluations and concern matter of value, typically in relation to practical reasoning. An individual's preferences are determined purely by a person's tastes as opposed to the good's prices, personal income, and the availability of goods. However, people are still expected to act in their best (rational) interest. In this context, rationality would dictate that an individual will select the option that maximizes self-interest when given a choice. Moreover, in every set of alternatives, preferences arise.

In psychology, economics and philosophy, preference is a technical term usually used in relation to choosing between alternatives. For example, someone prefers A over B if they would rather choose A than B. Preferences are central to decision theory because of this relation to behavior. Some methods such as Ordinal Priority Approach use preference relation for decision-making. As connative states, they are closely related to desires. The difference between the two is that desires are directed at one object while preferences concern a comparison between two alternatives, of which one is preferred to the other.

A context effect is an aspect of cognitive psychology that describes the influence of environmental factors on one's perception of a stimulus. The impact of context effects is considered to be part of top-down design. The concept is supported by the theoretical approach to perception known as constructive perception. Context effects can impact our daily lives in many ways such as word recognition, learning abilities, memory, and object recognition. It can have an extensive effect on marketing and consumer decisions. For example, research has shown that the comfort level of the floor that shoppers are standing on while reviewing products can affect their assessments of product's quality, leading to higher assessments if the floor is comfortable and lower ratings if it is uncomfortable. Because of effects such as this, context effects are currently studied predominantly in marketing.

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.

References

  1. ↑ Huber, Joel; Payne, John W.; Puto, Christopher (1982). "Adding Asymmetrically Dominated Alternatives: Violations of Regularity and the Similarity Hypothesis". Journal of Consumer Research. 9 (1): 90–98. doi:10.1086/208899. S2CID   120998684.
  2. ↑ Robson, David (1 August 2019). "The trick that makes you overspend". www.bbc.com. Retrieved 1 August 2019.
  3. ↑ Luce, R. Duncan. "The choice axiom after twenty years."(1977), Journal of mathematical psychology 15 (3) 215-233.
  4. ↑ Ariely, Dan (2009). Predictably Irrational: The Hidden Forces that Shape Our Decisions. HarperCollins. Chapter 1. ISBN   9780007319923.
  5. 1 2 Crosetto, Paolo; Gaudeul, Alexia (2016). "A monetary measure of the strength and robustness of the attraction effect". Economics Letters. 149: 38–43. doi:10.1016/j.econlet.2016.09.031. ISSN   0165-1765. S2CID   157481325. Archived from the original on July 27, 2020.
  6. ↑ Yang, Sybil; Lynn, Michael (2014). "More Evidence Challenging the Robustness and Usefulness of the Attraction Effect". Journal of Marketing Research. 51 (4): 508–513. CiteSeerX   10.1.1.686.9374 . doi:10.1509/jmr.14.0020. ISSN   0022-2437. S2CID   42112659.
  7. ↑ Frederick, Shane; Lee, Leonard; Baskin, Ernest (2014). "The Limits of Attraction". Journal of Marketing Research. 51 (4): 487–507. doi:10.1509/jmr.12.0061. ISSN   0022-2437. S2CID   144931982.
  8. ↑ Huber, Joel; Payne, John W.; Puto, Christopher P. (2014). "Let's Be Honest About the Attraction Effect". Journal of Marketing Research. 51 (4): 520–525. doi:10.1509/jmr.14.0208. ISSN   0022-2437. S2CID   143974563.
  9. ↑ Dimara, Evanthia; Bezerianos, Anastasia; Dragicevic, Pierre (2017). "The attraction effect in information visualization" (PDF). IEEE Transactions on Visualization and Computer Graphics. 23 (1): 471–480. doi:10.1109/TVCG.2016.2598594. ISSN   1077-2626. PMID   27875163. S2CID   8447747.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.