A literature review of the anchoring effect
Research highlights
▶ Anchoring bias is a process whereby people are influenced by specific information given before a judgement. ▶ This paper reviews 40 years research on this very robust finding which occurs with many different judgements. ▶ Different processes have been proposed. ▶ Ability, personality, processing styles and mood have a small impact on anchoring judgements. ▶ The applications to the area are substantial.
Introduction
Behavioural economics is based on the science of judgemental heuristics (or mental shortcuts; rules of thumb) that most people rely on reflexively (Belsky and Golivich, 1999). Heuristics are characterised as an ‘intuitive, rapid, and automatic system’ (Shiloh et al., 2002, p. 417), which ‘reduce the complex tasks of assessing probabilities and predicting values to simpler judgmental operations’ (Tversky and Kahneman, 1974, p. 1124). Although the use of rules of thumb reduces cognitive and time constraints, sometimes they lead to severe and systematic errors such as biases and fallacies in decision making (Tversky and Kahneman, 1974).
The idea of heuristics was originally raised by Simon (1955), who proposed a behavioural model of rational choice, which argues for a “limited” rationality, where decisions are derived through the processes of dynamic adjustment on both external (environmental) and internal (human characteristics) factors. The “limited” rationality models are also known as models of heuristic cognition. This has lead to many studies of bounded rationality and how heuristics can make accurate decisions in appropriate environments (Goldstein and Gigerenzer, 2008, Todd and Gigerenzer, 2003).
The main focus in this review article is the robust influence of the anchoring heuristic, which is a ubiquitous phenomenon in human judgement. The earliest mention of the anchoring bias can be traced back to the research on psychophysics, where judgments of others’ weights were influenced by one extreme weight (Brown, 1953, as cited in Chapman and Johnson, 1999). The notion of anchoring in decision making was first introduced by Slovic (1967), who studied descriptions of preference reversals (as cited in Chapman and Johnson, 1999). However, the anchoring-and-adjustment heuristics, first introduced by Tversky and Kahneman (1974) in their pioneering work on judgment under uncertainty, will be the main anchoring effect referred to in the current study. The heuristic maintains that anchoring bias is caused by insufficient adjustment because final judgements are assimilated toward the starting point of a judge's deliberations.
According to Tversky and Kahneman (1974), the anchoring effect is the disproportionate influence on decision makers to make judgments that are biased toward an initially presented value. In a classic study by Tversky and Kahneman (1974), participants were required to provide an estimation for the percentage of African countries in the United Nations with reference to a range of randomly generated numbers by spinning a wheel of fortune between 0 and 100. Participants were asked to consider whether the actual answer was higher or lower than the reference value presented (comparative judgment) before the absolute judgment was made.
Following Tversky and Kahneman's study, many studies (see Table 1) have illustrated the prevalence of anchoring effect in human decision making processes. These have demonstrated the anchoring effect in a variety of domains including general knowledge (Epley and Gilovich, 2001, McElroy and Dowd, 2007, Mussweiler and Englich, 2005, Mussweiler and Strack, 1999, Mussweiler and Strack, 2001a, Mussweiler and Strack, 2001b, Strack and Mussweiler, 1997) and probability estimates (Chapman and Johnson, 1999, Plous, 1989). In general knowledge, for example, researchers have investigated the anchoring effect by asking participants questions such as the freezing point of vodka (Epley and Gilovich, 2001), the length of the Mississippi river (McElroy and Dowd, 2007) and the annual mean temperature of Germany (Mussweiler and Englich, 2005). Most of these studies were conducted with university students in laboratory settings and utilised questions that the students may not have naturally used for decision making, therefore, their generalizability and validity can be questioned. However “real-world” judgement and decision making tasks such as in legal judgments (Englich and Mussweiler, 2001, Englich et al., 2005, Englich et al., 2006, Englich and Soder, 2009), valuations and purchasing decisions (Ariely et al., 2003, Mussweiler et al., 2000, Wansink et al., 1998), forecasting (Critcher and Gilovich, 2008), negotiation (e.g. Galinsky and Mussweiler, 2001) and self-efficacy (Cervone and Peake, 1986) have shown the effect to be very robust.
Research findings from several domains illustrate the robust influence of anchoring. For instance Thorsteinson et al. (2008) used both field and laboratory studies to show how anchoring works on performance judgements. Similarly in four experimental studies Oppenheimer et al. (2008) should that the boundary conditions of anchoring effects are very loose with anchors operating across modalities and dimensions to bias judgement. What is most impressive is the number of studies that have demonstrated the robustness of the anchoring effects with very different judgements, for instance, time estimation (Thomas and Handley, 2008). There have even been electrophysiological studies on the anchoring effect noting how people respond differently when making decisions (Qu et al., 2008).
The literature does indicate that, in decision making, the higher the ambiguity, the lower the familiarity, relevance or personal involvement with the problem, a more trustworthy source or plausible bid/estimate the stronger the anchoring effects (Van Exel et al., 2006).
On the other hand, there are various studies demonstrating that this influence can be mitigated (Galinsky and Mussweiler, 2001, LeBoeuf and Shafir, 2009, Mussweiler et al., 2000). However, mixed results have been found, which suggests the question: “what factors affect the susceptibility to the influence of the anchoring effect?”
Section snippets
Underlying mechanisms to the anchoring effect
In order to understand the question above, first the psychological processes that contribute to the anchoring effect need to be outlined (see Table 2). Early explanations of the anchoring-and-adjustment heuristic were provided by Tversky and Kahneman (1974). They suggested that people make insufficient adjustments to yield a final estimation based on an initially presented value or parameter. In other words, people who are exposed to a higher anchor make insufficient adjustments downward and
Types of anchors
It is, however, premature to claim that the confirmatory hypothesis testing model accounts for all of the underlying psychological processes of anchoring. Different mechanisms appear to account for the anchoring effect under different contexts. Epley and Gilovich, 2001, Epley and Gilovich, 2005 argued that the anchoring effect is generated by multiple mechanisms. Their findings demonstrate that the adjustment process comes into play when the anchor values are self-generated; where participants
Mood of participants
After considering the possible factors related to anchor values, researchers in the field have turned to potential human components, which may contribute to the susceptibility to the anchoring effect (Table 3). Drawing from the perspective of attitude change, anchors serve multiple “roles”. They can be a simple cue directly influencing decisions, engage in effortful processing, be similar to selective accessibility mechanism or to the bias judgment (Blankenship et al., 2008, Wegener et al., 2010
Knowledge of participants
The effect of mood on magnitude of anchoring, however, does not influence all individuals at the same level. Research by Englich and Soder (2009) demonstrated that emotions only have an effect on the magnitude of anchoring with non-experts. They found that experts are vulnerable to the anchoring effect regardless of their moods. One could argue that judges with high expertise should have greater knowledge, more experience and less uncertainty in making relevant decisions, thus less is
Rewards for accuracy/motivation
Following the attitude change perspective proposed by Wegener et al., 2001, Wegener et al., 2010, the elaboration-based approach has been widely adopted to explain the robust and pervasive influence of anchoring. Low-elaboration anchoring results from non-thoughtful processes, where the motivation and the ability to make the correct judgment is lacking, and therefore, the anchors are treated as a “hint” to a reasonable answer (Schwarz, 1994, as cited in Wegener et al., 2010) without considering
Individual differences
Individual differences are the different responses generated by an individual toward specific events or circumstances in a way that is different from other people on a regular basis (Brandstätter, 1993). Personality is one of the individual difference variables that affects one's performance and more specifically, the cognitive processing in judgmental decisions. There is limited research on the relationship between personality and the anchoring effect. Previous research has focused on groups
Information processing styles
The attitudes and persuasion perspective on anchoring proposed by Wegener et al. (2001) have suggested that both effortful and non-effortful information processing can lead to the assimilation of answers toward anchor cues. This proposes that the influence of the anchoring effect could be due to the thinking styles adopted by judges in decision making. Low-elaboration anchoring results especially during non-thoughtful processes, where the motivation and the ability to make the correct judgment
Applications
Research in the field demonstrates that anchoring is a pervasive and robust effect in human decisions regardless of factors such as types of anchors, relevance of anchor cues, expertise, motivation and cognitive load. Therefore, can anchoring effects be reduced or prevented? Based on the selective accessibility model, Mussweiler et al. (2000) argued that consider-the-opposite strategy could mitigate the magnitude of the anchoring effect. The consider-the-opposite strategy requires judges to
Conclusion
There is now nearly 40 years worth of research on the anchoring effect which has proved to be extremely robust. It can be demonstrated over a wide array of decisional tasks, with different groups and in different settings. It is unusual in experimental settings not to be able to demonstrate it. There exist different, but not contradictory models, to account for the process. Anyone working in the area become aware of the fact that there exist considerable individual differences in the extent to
References (54)
- et al.
Anchoring and cognitive ability
Economics Letters
(2010) - et al.
Reference pricing studies in marketing: a synthesis of research results
Journal of Business Research
(1993) - et al.
Elaboration and consequences of anchored estimates: an attitudinal perspective on numerical anchoring
Journal of Experimental Social Psychology
(2008) Should economic psychology care about personality structure?
Journal of Economic Psychology
(1993)- et al.
Biases in judgmental adjustments of statistical forecasts: the role of individual differences
International Journal of Forecasting
(2010) - et al.
The recognition heuristic and the less-is-more effect
Handbook of Experimental Economics Results
(2008) - et al.
Subliminal anchoring: judgmental consequences and underlying mechanisms
Organizational Behavior and Human Decision Processes
(2005) - et al.
Hypothesis-consistent testing and semantic priming in the anchoring paradigm: a selective accessibility model
Journal of Experimental Social Psychology
(1999) - et al.
The semantics of anchoring
Organizational Behavior and Human Decision Processes
(2001) - et al.
Experts, amateurs, and real estate: an anchoring-and-adjustment perspective on property pricing decisions
Organizational Behavior and Human Decision Processes
(1987)
Cognitive abilities and behavioural biases
Journal of Economic Behavior and Organization
Anchors aweigh: a demonstration of cross-modality anchoring and magnitude priming
Cognition
Electrophysiological correlates of adjustment process in anchoring effects
Neuroscience Letters
Individual differences in rational and intuitive thinking styles as predictors of heuristic responses and framing effects
Personality and Individual Differences
Anchoring effects on performance judgements
Organizational Behavior and Human Decision Processes
Bounded rationality to the world
Journal of Economic Psychology
Anchoring in time estimation
Acta Psychologia
With a little help from an anchor. Discussion and evidence of anchoring effects in contingent valuation
Journal of Socio-Economics
Elaboration and numerical anchoring: implications of attitude theories for consumer judgment and decision making
Journal of Consumer Psychology
Implications of attitude change theories for numerical anchoring: anchor plausibility and the limits of anchor effectiveness
Journal of Experimental Social Psychology
The effects of reference prices on bidding behavior in interactive pricing mechanisms
Journal of Interactive Marketing
“Coherent Arbitrariness”: stable demand curves without stable preferences
The Quarterly Journal of Economics
Why Smart People Make Big Money Mistakes – and How to Correct Them. Lessons from the New Science of Behavioural Economics
Sadness and susceptibility to judgmental bias: the case of anchoring
Psychological Science
Anchoring, efficacy, and action: the influence of judgmental heuristics on self-efficacy judgments and behavior
Journal of Personality and Social Psychology
The limits of anchoring
Journal of Behavioral Decision Making
Anchoring, activation, and the construction of values
Organizational Behavior and Human Decision Processes
Cited by (681)
Unraveling the anchoring effect of crisis communication in cyberattack spillover crises
2024, Public Relations ReviewCognitive Biases in Fact-Checking and Their Countermeasures: A Review
2024, Information Processing and ManagementDoes more information mean better choices? A study on calorie display and consumer behavior in restaurants
2024, Food Quality and PreferenceThe effects of modular process models on gaze patterns - A follow-up investigation about modularization in process model literacy
2024, Expert Systems with ApplicationsETF MAX and MIN effects
2024, Finance Research Letters