GENERATION MECHANISM OF ANCHORING EFFECT IN MANAGEMENT JUDGMENT: AN ANALYSIS BASED ON THE NEUROSCIENCE OF DECISION-MAKING

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Revista Argentina de Clínica Psicológica 2020, Vol. XXIX, N°2, 314-321

DOI: 10.24205/03276716.2020.242 314

G

ENERATION

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ECHANISM OF

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NCHORING

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FFECT IN

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ANAGEMENT

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UDGMENT

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A

N

A

NALYSIS

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ASED ON THE

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EUROSCIENCE OF

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ECISION

-M

AKING

Liwei Gu*, Yulian Zhu, Guolin Li

Abstract

The anchoring effect is a major cause of judgment deviation. In management judgment, the irrelevant anchors will distract the decision-making from the target issue. This paper explores the generation mechanism of anchoring effect in management judgment through an analysis based on the neuroscience of decision-making. Specifically, the author analyzed the influence of value judgment, common sense judgment and Big Five Personality traits on the generation mechanism of anchoring effect, and proved the semantic priming mechanism of anchoring effect in management judgment. The mechanism of the anchoring effect in value judgment was verified by electroencephalogram (EEG) experiment and the that in common sense judgment was studied through the magnetic resonance imaging (MRI) experiment. The results show that different anchor values activate different semantic information; the mean EEG power spectrum under high anchor values is significantly higher than that under low anchor values; for common sense judgment, the reaction time of feasible anchor, infeasible anchor and no anchor decreases in turn in the comparison stage, with a significant difference in reaction time between feasible anchor and no anchor, and enhances in turn in the answer stage; there are a significant difference in the partial correlation coefficient between each trait of the Big Five Personality and the intensity of anchoring effect, and a linear relationship between the pleasantness of the Big Five Personality and the intensity of anchoring effect.

Key words: Anchoring Effect, Neuroscience of Decision-Making, Value Judgment, Common Sense Judgment.

Received: 18-02-19 | Accepted: 20-08-19

INTRODUCTION

In the field of management, decision-making is an important basic activity in the survival and development of human beings, and a correct judgment is the key to good decision-making (Frydman & Camerer, 2016). In reality, before making various management decisions, the accurate judgment of the management decision-maker will greatly improve the efficiency and execution degree of the decision-making. However, it is often influenced by various

College of Education, Hebei Normal University of Science & Technology, Qinhuangdao 066004, China.

E-Mail: 47154041@qq.com

internal or external factors before making the decision-making, so it is difficult to make correct judgment (Yoon, Vo, & Venkatraman, 2017; Gorb, Yasnolob, & Protsiuk, 2016). Since managers are people with limited rationality, it is difficult to completely abandon the heuristic thinking and thus difficult to overcome the bias in judgment (Wouters, 2006). Therefore, in order to raise the accuracy of economic management judgment, improve the decision-making and then better the management level, it is worth exploring to study the management judgment deviation and put forward the suggestions of overcoming the deviation and improving judgment and decision-making (Ramanathan & Velayudhan, 2015; Aguirre-Rodriguez, Bóveda-Lambie, & Montoya, 2014).

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In the development of multi-perspective and multi-method economic management

decision-making research, the decision-making

neuroscience of integrating psychology,

cognitive science and neuroscience has matured gradually (Hanslin & Rindell, 2014). Anchoring effect is a classical judgment deviation. After

many years’ research, scientists have given

several mechanisms of anchoring effect, including selective access model, attitude change model, scale distortion model and so on (Bossaerts & Murawski, 2015). The reasons for the generation of anchoring effect develop slowly, the attributes of anchor information itself, the mood, individual difference and other factors of the judges are all important factors affecting the anchoring effect (Schoech, 2010; Servant, White, Montagnini et al., 2016). Judgment and decision-making are the core of functions of management science. The source of management variation is the anchoring effect, which has special characteristics of neural activities (Gergaud, Plantinga, & Ringeval-Deluze, 2016; Tanskanen, Ahola, Aminoff et al.,

2017). In this paper, decision-making

neuroscience is applied to the neural activities of the judges, and the generation mechanism of the anchoring effect in management judgment and the regulation of personality traits are deeply studied. The mechanism of the anchoring effect in the empirical value judgment is verified by EEG experiment and the mechanism of the anchoring effect in fact judgment are studied through the magnetic resonance experiment.

RESEARCH ON ANCHORING EFFECT AND NEUROSCIENCE

Regulating factors of anchoring effect In order to discuss the mechanism of anchoring effect from many angles, many researchers discuss the cause of anchoring effect respectively from the the perspectives of initiation, attitude, judgment and adjustment (Pontes,Palmeira, & Jevons, 2017). From the the perspectives of initiation, the access model and the inadequate adjustment theory are the most extensive theories in the process of exploring the mechanism of anchoring effect, but the universality of the two theories is different. In addition to the above two theories, numerical and magnitude initiation, attitude change theory and scale distortion theory all discuss the generation mechanism of anchoring effect from

different perspectives, but with greater

limitations, there are many doubts about the research results.

Figure 1 shows the relationship between the extremity and strength of the anchor. The study divided the relationship into three types: linear

relationship, weakening relationship and

contrast relationship. The linear relationship increases with the increase of the extreme of anchor and the strength of anchor effect does

not change; the weakening relationship

increases with the increase of the extreme of anchor and the strength of anchor effect decreases; the contrast relationship increases with increase of extreme of the anchor, and the judgment caused by the very high anchor is lower than the judgment caused by the high anchor. In view of the feasibility of anchor as regulating factor, it is not possible to reach a unified conclusion, and mechanisms for different anchoring effects are different.

Figure 1

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The relationship between the

extremeness of an anchor and the strength

of the anchor

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

-0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4

Contrast

Weakened Linear

Re

ac

tion

Anchor value

Research on neuroscience related to anchoring effect

The vigorous development of

decision-making neuroscience has expanded the

application fields of management, economics, psychology, etc., but the researches in the field of anchoring effects are rare (Fudali-Czyå, Ratomska, Cudo et al., 2016; Punyatoya, 2013). The precision of anchor value has a great influence on the experiment. In the experiment, the source of anchor is self-generated anchor and external anchor. However, it is found that the precision of anchor value has no effect on

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GENERATION MECHANISM OF ANCHORING EFFECT IN MANAGEMENT JUDGMENT: AN ANALYSIS BASED ON THE NEUROSCIENCE OF DECISION-MAKING 316

external anchor. The higher the accuracy of anchor value is, the stronger the assimilation of anchoring effect is and the greater the amplitude of positive component in EEG experiment is. In the external anchor experiment, although the accuracy of the anchor value does not play a role in regulation, its anchoring effect is significant.

From the perspective of neuroscience, the individual's neurological function and neural structure have a strong regulatory effect on the anchoring effect. The subjects with both sides and hands interact more quickly between left and right brain, and the subjects in EEG experiment are easier to change their judgment and decision and to be anchored in the anchoring category. The subjects with bilateral hands interact more quickly between the left and right brain, which makes it easier for the subjects to change their judgment and decision-making and to be anchored in the anchoring category. The use of magnetic resonance imaging can provide neurological evidence of visual anchoring effect, the advantage of which is that the subjects will use their own characteristics as an anchor according to their preferences or characteristics. However, the subjects' preference differences are linearly related to the degree of activation of the medial prefrontal cortex in the brain, so the MRI study could provide the degree of activation of the brain closely related to the anchoring effect.

MECHANISM OF ANCHORING EFFECT

Mechanism of anchoring effect in value judgment

In value judgment, the existence of anchor information can easily cause the deviation of judgment (Amorim, Moraes, Fazanaro et al., 2017). In this experiment, noise evaluation is used as a value judgment task. First, the subjects are given several segments of bad noises at an interval of 1 minute. The subjects can accept the lowest price compensation of these noises once given again, and an integer is randomly introduced as the anchor information. Then the subjects' compensation amount is compared with the integer for final evaluation. According to the theory of decision-making neuroscience, it is found that environmental factors influence the coding of value by the brain, and then influence the judgment of value. The level of anchor value is related to the pain degree for noise. The pain degree caused by noise is

reflected in EEG experiment through nerve activity, so that the relationship between anchor value and EEG experiment is established.

Figure 2

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EEG data recording method

EEG digital conversion computer

Filters and Amplifiers EEG

Stimulus presentation computer

Markup / code of digital form

Figure 3

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Waveform of frontal area, central

area, and occipital area when a random

number anchor appears

-200 0 200 400 600 800

3 2 1 0 -1 -2 -3

Amplitude/μV

Time/ms High anchor Low anchor

(a) Frontal area

-200 0 200 400 600 800

3 2 1 0 -1 -2 -3

Amplitude/μV

Time/ms High anchor Low anchor

(b) Central area

-200 0 200 400 600 800

3 2 1 0 -1 -2 -3

Amplitude/μV

Time/ms High anchor Low anchor

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A total of 240 subjects are recruited (without history of mental illness, and stimulant drink cited before the experiment), and 80 segments of the 5s noise is played in the experiment. The EEG experiment is divided into 90 trials, including 40 trials for high anchor, 10 trials for medium anchor and 40 trials for low anchor. As shown in Figure 2 for the record mode of EEG data, the noise stimulation is presented to the subject, whose brain stimulation is transmitted to the digital conversion computer of EEG signals through a filter and an amplifier, and finally the EEG data is analyze by a series of measures such as filtering and off-eye electric baseline correction.

Figure 3 shows the brain wave patterns of the frontal, central, and parietal areas in the presence of random number anchors. It can be seen that the main effects of the anchor value are significant, and the wave amplitudes at high

anchors are significantly higher than those at low anchors (the mean amplitude under high anchor is 1.731 μV, and the mean amplitude under high anchor is 0.291 μV). Figure 4 shows the difference of EEG power spectra (EPS) of frontal, central, occipital and hemispheric areas under high and low anchors in noise playing. It can be seen from three graphs that the anchor value has significant main effect on EEG power spectra (EPS) of three areas in noise experiment. Compared with baseline, the mean value of EEG power spectrum under high anchor condition is significantly higher than that under low anchor condition. Therefore, there are great differences in the semantic information activated by different anchor values, and the different information is integrated into the formation process of judgment because of the different degree of reaction of the brain activated by neural activity.

Figure 4

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Theta ERS differences in different positions and hemispheres at high and low anchor

conditions

10 15 20 25 30 35 40

Right Middle

Left

ERS/

%

Hemisphere

High anchor Low anchor

10 15 20 25 30 35

Right Middle

Left

ERS/

%

Hemisphere

High anchor Low anchor

(a) Frontal area (b) Central area

10 15 20 25

Right Middle

Left

ERS/

%

Hemisphere

High anchor Low anchor

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GENERATION MECHANISM OF ANCHORING EFFECT IN MANAGEMENT JUDGMENT: AN ANALYSIS BASED ON THE NEUROSCIENCE OF DECISION-MAKING 318

Mechanism of anchoring effect in common sense judgment

What’s the most stable in anchoring effect is

the anchoring effect produced by the fact judgment, under which all kinds of irrelevant information as comparison criteria will play the role of assimilation to the judgment value (Herz, Bogacz, & Brown, 2016). When the anchor's semantics is activated, the anchor's feasibility influences the attitude of judges to the anchor's information processing. The anchoring response function of the infeasible anchor is weakened or compared, and the anchoring response function of the feasible anchor is linear. In comparison with the infeasible anchor, the feasible anchor will result in greater anchoring effect. There is a difference between feasible anchor and infeasible anchor at comparison stage and return stage in reaction time. Under feasible anchor condition, the reaction time of answer stage is shorter but the comparison stage is longer.

In this study, the traditional two-stage anchoring paradigm is used to investigate the mechanism of anchoring effect in factual judgment and the adjustment of anchor feasibility to anchoring effect. The test content is 120 items that the subjects are unfamiliar

with, and three anchor values are used to manipulate variables: feasible anchor, infeasible anchor and no anchor. Figure 5 shows an experimental paradigm for anchoring effects judged by common sense, which lasts for six steps, and each step has a strict time limit.

Table 1 shows the mean reaction time and standard error at different anchor levels in different stages of reaction. It can be seen that the reaction time in the comparison stage is successively reducing under feasible anchor, infeasible anchor and no anchor. Table 2 shows the information of brain zone activated by feasible anchor condition minus no anchor condition in the comparison stage, and the maximum t values of the right putamen, the left putamen and the right inferior frontal gyrus decrease in turn. Table 3 shows the information of brain zone activated by feasible anchor condition minus no anchor condition. Compared with no anchor condition, the zones of the maximum t value of left superior temporal gyrus and left middle temporal gyrus are the same, and the maximum t values are larger than that of left superior lobular gyrus in thinking and judging the answer under the condition of feasible anchor.

Figure 5

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Common sense to determine the experimental paradigm of anchoring effect

Focus attention

Topic

31

Think about

answer Oral

answer Blank

space &#%&

1s 2s

Up to 4s until the

button

Up to 5s until the

button 3s

1

2

3

4

5

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Advance button duration Digital Anchor Condition: comparison size

String condition: Press to continue

Think the answer but do not answer it. Think of the answer immediately press

the button

Oral answer, the answer through the fiber optic microphone transmission

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Table 1.

Mean and standard error of response at different stages of different anchor value

Anchor value

Compare phase reaction time Response time of the reaction

95% confidence interval

95% confidence interval Mean

value

Standard error

Lower limit

Upper limit

Mean value

Standard error

Lower limit

Upper limit Feasible

anchor 1.734 0.072 1.563 2.005 1.720 0.144 1.400 2.038 Infeasible

anchor 1.528 0.081 1.340 1.716 1.729 0.155 1.387 2.070 No anchor 1.138 0.070 1.073 1.304 1.760 0.146 1.437 2.084

Table 2.

The comparison stage feasible anchor condition minus the non-anchor condition

activates the brain area

Brain area Body prime number Maximum t value Maximum t value MNI coordinate position

Right putamen 20 5.1247 [20,5,-8]

Left putamen 14 4.8558 [-17,2,-4.5]

Right inferior frontal gyrus 21 4.18 [53,11,18]

Table 3.

Answering stage feasible anchor conditions minus no anchor activation of the brain area

Brain area Body prime number Maximum t value Maximum t value MNI coordinate position

Left temporal gyrus 22 7.2345 [-59,-59,18]

Left middle temporal gyrus 16 7.2345 [-59,-59,18]

Left superior lobule 25 5.2212 [-29,-62,53]

ADJUSTMENT OF BIG FIVE PERSONALITY TRAITS FOR MANAGING AND JUDGING THE ANCHORING EFFECT

Regulation of Big Five Personality Traits on anchoring effect

In the management judgment, the anchor irrelevant to the problem will play certain anchoring effect on people's judgment. Besides

the value judgment and common-sense

judgment, the personality traits also play a quite important regulating role in the anchoring effect. The Big Five Personality Traits (openness, strictness, extroversion, pleasantness and

neuroticism) influence the management

judgment and decision-making of people, that’s

say, the degree of the anchoring effect of the judge is influenced by the Big Five Personality Traits. In the experiment of adjusting the anchoring effect by the Big Five Personality Traits, questionnaire method is adopted with more than 900 questionnaires collected. Table 4 shows the confidence analysis results of Big Five Personality Scale, and Cronbach's α coefficient

of all dimension variables are greater than 0.7. The items of various dimensions of Big Five Personality Scale used in the questionnaire are consistent internally. Table 5 shows the mean score and standard deviation of each Big Five

Personality Trait of the subjects. The

pleasantness accounts for the highest mean, followed by strictness, openness, extroversion, and neuroticism successively.

Table 6 shows the partial correlation coefficient between each of Big Five Personality Traits and the strength of anchoring effect. The greater partial correlation coefficient is the pleasantness. According to the p-value analysis, there is a linear relationship between the pleasantness and the strength of anchoring effect in Big Five Personality Traits, and other traits are of non-linear relationship. In the questionnaire, it can be concluded that the higher score the pleasantness accounts for, the lower the degree of the subject approaching the anchor is, and the lower the anchoring effect, and the less the subject is anchored.

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GENERATION MECHANISM OF ANCHORING EFFECT IN MANAGEMENT JUDGMENT: AN ANALYSIS BASED ON THE NEUROSCIENCE OF DECISION-MAKING 320

Table 4.

Confidence Analysis of Big Five Personality Scale

Dimension Nervous Rigorism Pleasant Openness Extraversion

Cronbach’s α coefficient 0.835 0.848 0.822 0.828 0.815

Table 5.

Big Five Personality Traits of the mean and standard deviation

Personality Traits Nervous Rigorism Pleasant Openness Extraversion

Mean value 3.3515 4.2008 4.4122 4.1588 3.7220

Standard deviation 0.82033 0.72685 0.70503 0.72225 0.80123

Table 6.

Partial correlation coefficient among strengths and anchoring effects of Big Five

Personality

Personality Traits Nervous Rigorism Pleasant Openness Extraversion

Partial correlation coefficient -0.051 -0.018 0.145 -0.051 0.075

p value 0.364 0.684 0.025 0.448 0.210

Semantic priming mechanism of anchoring effect in management judgment

In recent years, a lot of researchers have

found that it’s easy to generate anchoring effect,

but it’s hard to explain the generation of

anchoring effectd. The introduction of decision-making neuroscience analyses the generation of anchoring effect in the process of judgment with the help of EEG and MRI experiments. According to the characteristics of neural activities revealed by the EEG data and magnetic resonance data, and the behavior data of the judge, it can be concluded that the semantic information of the anchor plays an initiating role and thus causes the shift of the judgment value toward the anchor value. This research also shows that the process of semantic priming is also influenced by the attitude of the judge in the beginning of the process, and the difference of attitude due to the difference of anchor feasibility and other factors will determine the

specific activation pattern of semantic

information.

CONCLUSIONS

Based on decision-making neuroscience, this study focuses on the generation mechanism of anchoring effect in management judgment, and analyzes the effects of value judgment, common sense judgment and Big Five Personality Traits on the generation mechanism of anchoring effect. The concrete conclusions are as follows:

(1) The responses of the brain activated by neural activity are different, and the different

information is integrated into the process of the formation of judgment, so the semantic information activated by different anchor values is different.

(2) In the common sense judgment, when the anchor's semantics is initiated, the anchor's feasibility influences the attitude of the judge to process anchor information. The anchor response function of the infeasible anchor presents a weakening or contrast form, while the anchor response function of the feasible anchor presents a linear relation.

(3) There is a great difference in the partial correlation coefficient between each of Big Five Personality Traits and the strength of the anchoring effect. There is a linear relationship between the pleasantness of Big Five Personality Traits and the strength of the anchoring effect, and there is a non-linear relationship among other traits.

Acknowledgements

The project supported by the Social Science Foundation of Hebei Province, named “Research on the Supply System of ‘Internet +’ Elementary Education from the Perspective of Accurate

Education”, (Grant No. HB18JY036).

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