Monetary Intelligence Theory (MIT):Personal Financial Motive and Prospect of Dishonesty

• Thomas Li-Ping Tang, Ph.D.• Middle Tennessee State

University, USA

– Fellow, Economic Psychology,– International Association of

Applied Psychology (IAAP)

Prospect Theory

• Decision Under Risk and Uncertainty

• Dishonesty Prospect

Prof. Daniel Kahneman

Nobel Prize Winner in

Economic Sciences,

2002

Daniel Kahneman and Vernon L. Smith at the Prize Award Ceremony, Concert Hall, Stockholm,

Sweden 2002

Prof. Daniel Kahneman

Senior Scholar; Eugene Higgins

Professor of Psychology, Emeritus; and Professor of Psychology and Public Affairs, Emeritus, Princeton University

Prof. Daniel Kahneman

BS: Psychology, Mathematics, Hebrew University of Jerusalem, 1954 PhD: Psychology, University of California, Berkeley, 1958

 

Most Cited Papers• PROSPECT THEORY - ANALYSIS OF DECISI

ON UNDER RISK

KAHNEMAN, D; TVERSKY, A

ECONOMETRICA, 47(2): 263-291(1979)

Cited: 10,425 Times• JUDGMENT UNDER UNCERTAINTY - HEURIS

TICS AND BIASES

TVERSKY, A; KAHNEMAN, D

SCIENCE, 185(4157): 1124-1131 (1974)• Cited: 7,710 Times (10/31/2014)

Citations

• Articles = 160• Total Citation = 56,954

• Articles in Science = 7• Total Citation = 13,184• 4.375% of Articles = 23.15% Citations

Prospect Theory

Provides a value function that is concave for gains, convex for losses, and steeper for losses than for gains,

Tversky & Kahneman (1981) Science

Prospect Theory

Provides a nonlinear transformation of the probability scale, which overweights small probabilities and underweights moderate andhigh probabilities

Prospect Theory • Provides a distinctive fourfold

pattern of risk attitudes: • (1) Risk aversion for gains and• (2) Risk seeking for losses of high

probability; • (3) Risk seeking for gains and • (4) Risk aversion for losses of low

probability

Prospect Theory

• Risk Aversion vs. Risk Seeking

• Gains vs. Losses

• High vs. Low Probability

Risk: Aversion vs. Risk Seeking

• Risk Aversion: Prefer the certain prospect to any risky prospect with expected value.

Risk Seeking: the opposite of risk aversion

Context:

• Gains vs. Losses Domains• High vs. Low Probability

Decision A

Choose between• (a) a sure gain of $240• (b) a 25% chance to gain $1,000 and a

75% chance to gain nothing

• Tversky & Kahneman (1981) Science

7-27

Decision B

Choose between• (c) a sure loss of $750• (d) a 75% chance to lose $1,000 and a

25% chance to lose nothing

7-28

Decision C

Choose between• (e) a 25% chance to win $240 and a 75%

chance to lose $760• (f) a 25% chance of win $250 and a 75%

change to lose $750.

7-29

Analysis of Decision C

• Combine (a) and (d) = (e)• Combine (b) and (c) = (f)

7-30

Analysis of Decision C

• (a) + (d) = (e)

(100%)($240) + [(75%)(-$1,000) + (25%) ($0)] =

(25%)($240) + (75%) (-$760)

• (b) + (c) = (f)

[(25%)($1,000) + (75%)($0)] + (100%)(-$750) =

(25%)($250) + (75%)(-$750)

7-31

Decision: ABC

• Decision A Decision B– 84% chose (a) 87% chose (d)– 16% chose (b) 13% chose (c)

– Decision C– 86% chose (f)*– 14% chose (e)

*The sum of the undesirable choices dominates the sum of the desirable choices.

Reversal of Preferences 7-32

Monetary Intelligence Theory (MIT)

• A form of social intelligence, • Individuals monitor their own

monetary motive, behavior, and cognition; evaluate risk and uncertainty; and strategically select various prospects to capitalize their financial goals and ultimate success—peace, love, and joy.

The Present Study

• Study 1: Survey• Study 2: Experiment• We Frame:

Personal Financial Motive Dishonesty

in the context of • Gains vs. Losses Domains• High vs. Low Probability

Personal Financial Motive(Love of Money)

• Those who want to be rich are falling into temptation and into a trap and into many foolish and harmful desires, which plunge them into ruin and destruction. For the love of money is the root of all evils (1 Timothy 6: 9-10).

• Evil Dishonesty, Corruption, Cheating

Dishonesty

• Has several synonyms: Corruption, Cheating, Deception, Fraud, and Misconduct.

• Involving large corporations and individuals around the world is a real cross-level world phenomenon which has indirectly caused a loss of $3.7 trillion a year globally.

Dishonesty

• Understanding the motivations of individuals’ dishonesty across the global economic pyramid is a central question in political economy and behavioral ethics.

• The dearth of empirical research on applying Prospect Theory to include individual-difference variables and behavioral ethics.

Dishonesty

• It is a cost-benefit analysis of self-interest, balancing the financial rewards of dishonesty against the consequences of getting caught and punished.

Dishonesty

• Reflects a choice of simple gamble with

• “monetary outcomes” and • various “probabilities”.

We “FRAME”Personal Financial Motive (LOM)

Dishonesty in the Context

• Satisfaction vs. Dissatisfaction (PSQ) Gains vs. Losses Domain

• Clean vs. Corrupt Cultural Norms (CPI)

High vs. Low Probability of Risk for Dishonesty

CPI = Corruption Perceptions Index

We Theorize Pay

• Pay causes dissatisfaction and satisfaction, with almost identical frequency,

• but the duration of the former is three times longer than the latter (Herzberg, 1969)

• Pay “dissatisfaction” excites people to steal in the name of justice (Greenberg, 1993)

Pay

• Dissatisfaction provokes impulsive, automatic, and angry “emotions” or intuition (System 1 thinking) and excite some to engage in risk seeking for losses.

• Satisfaction promotes logical, conscious, and effortful “reflective” reasoning, or rationality (System 2 thinking) and cause people to become risk averse for gains.

Brain/Neuroscience

• “Emotions” (System 1 thinking) and “reflections” (System 2 thinking) activate different areas of the brain.

• Greene et al., Science, 293, 2105 (2001).

Frame: Pay

• Pay Satisfaction Gains

• Pay Dissatisfaction Losses

Cultural Norms

• Corruption Perceptions Index (CPI)• High CPI entities: legal, political, and

social infrastructures and strict enforcement of laws

• Perceived probability of getting caught for dishonesty is much higher in “clean” cultures with high CPI than in “corrupt” ones with low CPI, relatively speaking

Cultural Norms

• High CPI High Probability of Risk for Dishonesty

• Low CPI Low Probability of Risk for Dishonesty

In Clean Cultures

• Pay satisfaction (gains) “frame” dishonesty in the context of “risk aversion for gains of high probability”

• Maintain their Honest Self-Concept • Pay dissatisfaction (losses) “frame”

dishonesty in the milieu of “risk seeking for losses of high probability”

• Fuel the LOM Dishonesty Fire

In Corrupt Cultures

• Pay satisfaction adopt the “risk seeking for gains of low probability” framework

• The rich develop a license-to-corrupt-mentality

• Pay dissatisfaction select “risk aversion for losses of low probability”.

• The poor avoid risks of competing against the king of the hill (rule-by-the-thief/ kleptocracy)

Matthew Effect

• To anyone who has, more will be given, he will grow rich;

• From anyone who has not, even what he has, will be taken away (Matthew 13: 12)

Study 1

• Sample: 6,382 managers in 31 countries• Measures:

Micro-level:• 1. Personal financial motive (12-item LOM—

Factors Rich, Motivator, Power, and Importance • 2. 18-item Pay Satisfaction Questionnaire (PSQ), • 3. and 7-item Dishonesty (corruption, cheating, and

theft intentions)

Macro-level

4. CPI

Analysis

• Income of the sample = Population

$12,189.48 ~ $12,736.23 World Bank’s GDP

• Measurement invariance across 3 CPI groups

• No Concern for Common Method Variance• SPSS, Amos, Mplus

High CPI

• CPI > 5.0, n = 2,761, • 13 entities—Australia, Belgium, France,

Hong Kong, Malta, Malaysia, Oman, Portugal, Singapore, Slovenia, Spain, Taiwan, and the USA

Medium CPI

• 5.0 = CPI > 3.5, n = 1,269, • 8 entities—Brazil, Bulgaria, Hungary,

Mexico, South Africa, South Korean, Thailand, and Turkey

Low CPI

• CPI < 3.4, n = 2,352, • 10 entities—Croatia, China, Democratic

Republic of Congo, Egypt, Macedonia, Nigeria, Peru, the Philippines, Romania, and Russia

Results

• 2 Main Effects: LOM, CPI (PSQ not significant)

• 3 2-way Interaction• 1 3-way Interaction

Study 1: Anonymous Survey

•  • Gains Losses

Satisfaction Dissatisfaction• Magnitude Intensity• ----------------------------------------------------------------• High—High CPI Risk Aversion Risk Seeking • Low—Low CPI Risk Seeking Risk Aversion

Study 2

• Phase 1:• Open Seminar Room High

Prob. • Opaque Private Cubicles Low Prob.• Part A: Match Task• Part B: Matrix Task• Paid ¥15 (USD$2.42)

金钱偏好和欺骗行为的关系：环境和薪酬满意度的影响

陈景秋 汤立平上海交通大学安泰经济与管理学院美国中田纳西州立大学瓊斯商学院

第 17 届全国心理学大会决策心理学专业委员会报告专场

• 经过北京人民几个小时的不停呼吸，空气质量终于稍有改善。 新北京人精神由此诞生：

• ＂厚德载雾，自强不吸，霾头苦干，再创灰黄！＂ 事实再次证明：雾以吸为贵啊！

• 悟空问：师傅，前面烟雾缭绕是不是到大雷音寺了？

• 师傅说：你这泼猴，出家人不说诳语，那是北京，那里的人生活在仙境里，据说幸福指数全国第一，要不你留下吧。

• 悟空说：不，我不留下，我想去西天。• 师傅说：你这泼猴，留在北京是去西

天最快的方式了。

Matching Task

Matrix Task

Part A

Part B

Study 2

• Phase 2:• Open Seminar Room High Prob. • Opaque Private Cubicles Low Prob.• Part A: Match Task• Part B: Matrix Task

Pay for Part A• Pay (¥9) High Satisfaction Gains • Pay (¥3) High Dissatisfaction Losses

Pay for Part B: Pay-for-Performance = ¥1/item

Study 2

Experimenter provided the answer sheet, Student wrote answers on Pay-for-Performance Form, shred Matrix sheet. Experimenter gave them opportunity to cheat, left the room for 3 min..

Experiment asked them to complete questionnaire (LOM, manipulation checks, and demographic variables) and paid them Pay-for-Performance = ¥1/item.

8.5

9

9.5

10

10.5

11

11.5

12

12.5

8.83

9.489.35

9.679.53

11.9512.05

11.86

Actual Performance vs. Self-Reported Performance

Open RoomsPrivate Cubicles

Axis Title

Per

form

an

ce

Low Love of Money High Love of Money

8

9

10

11

12

13

14

9.87

8.88

12.22

11.91

10.57

9.00

10.18

13.55

(1) High Pay Satisfaction, Open Rooms

(2) High Pay Satisfaction, Private Cubicles

(3) High Pay Disatisfac-tion, Open Rooms

(4) High Pay Disatisfac-tion, Private Cubicles

Personal Financial Motive

Sel

f-R

epor

ted

Per

form

ance

Tempted with Money

In private cubicles: high intensity (risk seeking for losses) and low intensity but high magnitude (risk aversion for gains), partially replicating managers’ dishonesty in clean cultures (Study 1). In open seminar rooms, all illustrate low dishonesty (risk aversion).

Conclusion

We expand Prospect Theory and show the “dark” side of Monetary Intelligence Theory (MIT)—dishonesty.

Thank You! 谢谢 !!!Danke Спасиб

Dankeshen ありがとうGrazie 너를 감사하십시요

Merci 謝謝 谢谢

Muchas Gracias

Obrigado

Takk Deg Thomas.Tang@mtsu.edu