Antecedents and Consequences of Unethical Behavior:

Does Economic Development Make a Difference?

International Congress of PsychologyBerlin, Germany, July 20-28, 2008

Presented by

Thomas Li-Ping Tang, Ph.D.Middle Tennessee State University, the USA

TOTO SUTARSO, Middle Tennessee State University, USA,ADEBOWALE AKANDE, International Institute of Research, South Africa,MICHAEL W. ALLEN, Griffith University, Australia,ABDULGAWI SALIM ALZUBAIDI, Sultan Qaboos University, Oman,MAHFOOZ A. ANSARI, University of Lethbridge, Canada, FERNANDO ARIAS-GALICIA, National University of Mexico, Mexico,MARK G. BORG, University of Malta, Malta,LUIGINA CANOVA, University of Padua, Italy,BRIGITTE CHARLES-PAUVERS, University of Nantes, France,BOR-SHIUAN CHENG, National Taiwan University, Taiwan,RANDY K. CHIU, Hong Kong Baptist University, Hong Kong, IOANA CODOBAN, Babes-Bolyai University, Romania,LINZHI DU, Nanjing University, China,ILIA GARBER, Saratov State Social-Economic University, Russia,CONSUELO GARCIA DE LA TORRE, Technological Institute of

Monterrey, Mexico,ROSARIO CORREIA HIGGS, Polytechnic Institute of Lisbon – Portugal,

Portugal, CHIN-KANG JEN, National Sun-Yat-Sen University, Taiwan,ALI MAHDI KAZEM, Sultan Qaboos University, Oman,KILSUN KIM, Sogang University, South Korea,

VIVIEN KIM GEOK LIM, National University of Singapore, Singapore,ROBERTO LUNA-AROCAS, University of Valencia, Spain,EVA MALOVICS, University of Szeged, Hungary, ANNA MARIA MANGANELLI, University of Padua, Italy,ALICE S. MOREIRA, Federal University of Pará, Brazil, ANTHONY UGOCHUKWU O. NNEDUM, Nnamdi Azikiwe University, Nigeria, JOHNSTO E. OSAGIE, Florida A & M University, USA,FRANCISCO COSTA PEREIRA, Polytechnic Institute of Lisbon – Portugal, Portugal,RUJA PHOLSWARD, University of the Thai Chamber of Commerce, Thailand, HORIA D. PITARIU, Babes-Bolyai University, Romania, MARKO POLIC, University of Ljubljana, Slovenia,ELISAVETA SARDZOSKA, University St. Cyril and Methodius, Macedonia, PETAR SKOBIC, Middle Tennessee State University, Croatia,ALLEN F. STEMBRIDGE, Southwestern Adventist University, USA,THERESA LI-NA TANG, Affinion Group, Brentwood, TN, USA, THOMPSON SIAN HIN TEO, National University of Singapore, Singapore,MARCO TOMBOLANI, University of Padua, Italy,MARTINA TRONTELJ, University of Ljubljana, Slovenia, CAROLINE URBAIN, University of Nantes, France,PETER VLERICK, Ghent University, Belgium

Scandals and Corruptions1. It is not lack of brains (intelligence), but

lack of wisdom (Feiner, 2004: 85) or virtue (Giacalone, 2004: 417)

2. Pressure & Opportunity: The bottom-line-mentality” (Sims, 1992: 508) or “Maximizing shareholder value” (Kochan, 2002: 139).

3. Power tends to corrupt, and absolute power corrupts absolutely. (Lord Acton, Letter to Bishop Mandell Creighton, 1887)

Management Spirituality and Religion

“People who want to get rich fall into temptation and a trap and into many foolish and harmful desires that plunge men into ruin and destruction. For the love of money is a root of all kinds of evil”

(http://www.biblegateway.com, 1 Timothy, 6: 9-10, New International Version).

Corporate Ethical Values *Enhance firm performance (Hunt, Wood, & Chonko, 1989; O’Reilly &

Chatman, 1996; Victor & Cullen, 1987)

*People do look to the social context: ethically right and wrong

*Social Learning Theory: (Bandura, 1977)

*Obey authority figures (Milgram, 1974),

*Reinforcement Theory: People do what is rewarded (Skinner, 1972)

*The Interactionist model of Ethical Behavior (Trevino, 1986).

*The Sarbanes-Oxley Act (July 30, 2002): Public companies to adopt a code of ethics (Anand, Ashforth, & Joshi, 2004).

Corruption Around the World

Countries with high GDP per Capita tend to have low CPI Corruption Perceptions Index (http://www.transparency.org/documents/cpi/2001/cpi2001.html)

Bribery is illegal in the USA (Foreign Corruption Practices Act), but widely practiced in other countries (Sims, 1992).

In cross-cultural research:

64% has covered only 2 countries, 23% > 2 countries (Sin, Cheung, & Lee, 1999)

72.43%: did not report Measurement Invariance (He, Merz, & Alden, 2008)

Theory of Reasoned Action

Behavior is determined by intention, which is a function of attitude towards the behavior and subjective norms (Ajzen & Fishbein, 1980; Ajzen, 1991; Armitage & Conner, 2001).

1. Attitude: the love of money (Cognitive moral development, economic, political, and religious value, ego strength, ethical philosophy, locus of control, Machiavellisnism, nationality, sex role orientation)

2. Subjective Norms: corporate ethical values (competition, economic conditions, organizational philosophy and policy, quality of the work experience, referent others, reinforcement contingencies, relationships among actors, responsibility for consequences, scarcity of resources , stakeholders).

3. Behavioral Intention: the propensity to engage in unethical behavior (workplace deviance, counterproductive behavior, corruption, organizational misbehavior, unethical behavior)

Attitude: Love of Money

Rich (A): “People who want to get rich fall into temptation and a trap and into many foolish and harmful desires that plunge men into ruin and destruction.” (Bible: 1 Timothy, 6: 9-10; Tang & Chiu, 2003).

Factor Rich has highest factor loading (Tang & Chen, 2006; Tang & Chiu, 2003).

Motivator (B): “No other incentive or motivational technique comes even close to money” (Locke, Feren, McCaleb, Shaw, & Denny, 1980: 381). Money is a motivator (Stajkovic & Luthans, 2001).

Important (C): The most consistent thread of the money attitude literature is the “emphasis on its importance” (Mitchell & Mickel, AMR, 1999: 569).

Power (C): The adage “Power corrupts and absolute power corrupts absolutely” once again has proven true (Kochan, 2002: 139).

The Love of Money ScaleFactor 1: Rich (Affective)

1. I want to be rich.2. It would be nice to be rich.3. Having a lot of money (being rich) is good.

Factor 2: Motivator (Behavioral)4. I am motivated to work hard for money.5. Money reinforces me to work harder.6. I am highly motivated by money.

Factor 3: Important (Cognitive)7. Money is good.8. Money is important.9. Money is valuable.

Factor 4: Power (Cognitive) 10. Money is power. 11. Money gives one considerable power. 12. Money can buy the best products and services.

Response scale (1) strongly disagree, (3) neutral, and (5) strongly agree.

Social Norms: Corporate Ethical Values

Organizational ethical values are

negatively related to organizational misbehavior (Vardi, 2001), unethical behavior, counterproductive behavior (Wimbush & Shepard, 1994),

workplace deviant behavior (Peterson, 2002), role conflict, and role ambiguity,

but positively related to ethical behavioral intentions (Shih & Chen, 2006) and ethical decision making (Jose & Thibodeaux, 1999).

Corporate Ethical Values Scale (CEV)

1. Top management in my company has let it be known in no uncertain terms that unethical behaviors will not be tolerated.

2. If a manager in my company is discovered to have engaged in unethical behaviors that result primarily in personal gain (rather than corporate gain), he or she will be promptly reprimanded.

3. If a manager in my company is discovered to have engaged in unethical behaviors that result primarily in corporate gain (rather than personal gain), he or she will be

promptly reprimanded (Hunt, Wood, & Chonko, 1989).

Unethical Behavior Intention: PUB

Resource Abuse: abuse office supplies (e.g., pencil, paper) (Ivancevich et al., 2005; Perotin, 2002) cyberloafing (Lim, 2002)

Not Whistle Blowing: Some managers implicitly condone employee theft by “looking the other way” (Near & Miceli, 1995; Tang & Chiu, 2003).

Theft: Shoplifting: $196/incident, $10.23 billion/yearTheft: $1,446/incident; $15.2 billion/year (Greenberg, 1993; Perotin, 2002; Wells, 2001).

Corruption: Misuse of position or authority for personal or organizational gain and may include acts that are committed against the organization or on behalf of the organization (Anand et al., 2004).

Propensity to Engage in Unethical Behavior (PUB)

Factor Resource Abuse 1. Use office supplies (paper, pen), Xerox machine, and stamps for personal purposes 2. Make personal long-distance (mobile phone) calls at work 3. Waste company time surfing on the Internet, playing computer games, and socializing

Factor Not Whistle Blowing4. Take no action against shoplifting by customers 5. Take no action against employees who steal cash/merchandise

Factor Theft 6. Abuse the company expense accounts and falsify accounting records.7. Take merchandise and/or cash home. 8. Borrow $20 from a cash register overnight without asking.

Factor Corruption9. Accept money, gift, and kickback from others. 10. Reveal company secrets when a person offers several million dollars.11. Sabotage the company to get even due to unfair treatment.12. Lay off 500 employees to save the company money and increase one’s personal bonus. (Chen & Tang, 2006, Journal of Business Ethics)

The Income Pyramid: Moderator

1. High: > $20,000,

2. Medium: $20,000-- $2,000, and3. Low: < $2,000 (Prahalad & Hammond, 2002, HBR)

Three Levels of Economic Development

1. High: GDP > $20,000, the rule of the law

2. Medium: $5,000 - $20,000, the rule of the man

3. Low: GDP < $5,000, no rule (law or order)

Stewardship Theory

Davis, Schoorman, & Donaldson, 1997

We included two consequences of ethical behavioral intention:

1. Job Stress

2. Life Satisfaction

Job Stress

When you think about yourself and your job nowadays, how do you feel?

Irritation

1. I get angry.

2. I get aggravated.

3. I get irritated or annoyed.(Caplan, Cobb, French, Van Harrison, & Pinneau, 1975).

Life Satisfaction

1. My work/family/personal life in general

2. My life as a whole these days

3. My overall life satisfaction

Similar to those in the United States’ General Social Survey (GSS) Conducted by the National Opinion Research Center since 1972 (Easterlin, 2001).

Theoretical Model: Variables

Theory of Reasoned Action Stewardship Theory (Ajzen & Fishbein, 1980; Trevino, 1986) (Davis, Schoorman, & Donaldson, 1997)

The LoveOf Money

EthicalValues

UnethicalBehavior

JobStress

LifeSatisfaction

The Love of Money

M40,

e4

M50,

e51

M60,

e61

M70,

e71

M80,

e8

M90,

e9

M10,

e1

M20,

e2

1

1

1

1

1

0

Motivator

1

0

Important

0

Rich

1

M30,

e31

1

0,

The Loveof Money

0,

e22

0,

e23

0,

e21

1

1

1

M100,

e10

M110,

e11

M120,

e12

0

Power

0,

e241

1

1

11

1

S40,

e34

S50,

e35

S60,

e36

1

1

1

S70,

e37

S80,

e38

S90,

e39

1

1

1

S100,

e40

S110,

e41

1

1

S10,

e31

S20,

e32

S30,

e33

1

1

1

0

AbuseResources

0

Not WhistleBlowing

0

Theft

0,

e51

0,

e52

0,

e53

1

0

Corruption

0,

e54

1

1

1

1

1

1

1

0,

Evil

S120,

e421

1

M40,

e4

M50,

e51

M60,

e61

M70,

e71

M80,

e8

M90,

e9

M10,

e1

M20,

e2

1

1

1

1

10

Motivator

1

0

Important

0

Rich

1

M30,

e31

1

0,

The Loveof Money

0,

e22

0,

e23

0,

e21

1

1

1

E4

0,

e54

E5

0,

e55

E60,

e56

1

1

E70,

e57

E80,

e58

E90,

e59

11 1

E100,

e60

E110,

e61

11

E1

0,

e51

E2

0,

e52

E3

0,

e531 11

0

ResourceAbuse

0

Not WhistleBlowing

0

Theft

0,

e81

0,

e82

0,

e83

1

0

Corruption

0,

e8411

11

1

0UnethicalBehaviorM10

0,

e10

M110,

e11

M120,

e12

0

Power

0,

e241

1

1

1 1

E120,

e62

1

V10,

e14

V20,

e15

0,

EthicalValues

1

1

1

V30,

e161

S10,

e63

S20,

e64

S30,

e65

0

Stress

1

1

L10,

e66

L20,

e67

L30,

e68

0

LifeSatisfaction

1 1

0,

e85

0,

e860,

e88

1

1

1

1

1

1

1 1

1

1

1

1

Measurement Invariance: CriteriaConfigural:

Chi-square/df < 5.00

TLI > .90 Tucker-Lewis Index,

CFI > .90 Comparative Fit Index,

IFI > .90 Incremental Fit Index,

SRMSR < .10 Standardized Root Mean Square Residual

RMSEA < .10 Root Mean Square Error of Approximation

Metric: Rule of thumb

If ΔCFI < .01: Differences between models do not exist(Cheung & Rensvold, 2002; Vandenberg & Lance, 2000).

29 Countries/Entities, N = 6081, (1) High GDP Group (> $20,000, n = 1,756):

the USA, Belgium, Australia, France, Spain, Singapore (2), and Hong Kong (PRC); 7 entities;

(2) Medium GDP Group ($5,000 - $20,000, n = 2,371): Portugal, Slovenia, South Korea, Taiwan, Malta, Oman, Hungary, Croatia, Mexico, Russia, South Africa, and Malaysia; 12 entities; and

(3) Low GDP Group (< $5,000, n = 1,954): Romania, Brazil, Bulgaria, Peru, Macedonia, Thailand, People’s Republic of China, Egypt, the Philippines, and Nigeria; 10 entities

  GDP CPI Income LOM PUB CEV Irritation Life Bad Apple Sample N M M SD M SD M SD M SD M SD % 1. USA 274 42,000 7.6 35,357 3.80 .61 1.55 .53 3.57 .93 2.62 1.12 3.87 .73 22.3 2. Belgium 201 35,712 7.4 20,269 3.49 .56 1.51 .45 3.54 .83 1.95 1.05 3.80 .71 19.9 3. Australia 262 34,740 8.8 - 3.63 .62 1.72 .48 3.60 .76 2.42 1.06 3.77 .91 34.7 4. France 87 33,918 7.5 16,735 3.48 .53 1.56 .34 3.44 .88 2.22 1.06 3.72 .90 17.2 5. Spain 183 27,226 7.0 - 3.50 .63 1.55 .47 3.15 .82 2.33 .91 3.82 .69 24.0 6. Singapore 1 202 26,836 9.4 31,746 3.76 .63 1.50 .49 3.64 .78 2.64 1.05 3.70 .78 15.3 7. Singapore 2 336 26,836 9.4 29,277 3.76 .57 1.29 .45 3.67 .91 2.30 1.07 3.74 .72 8.6 8. HK 211 25,493 8.3 47,509 3.78 .58 1.63 .54 3.33 .69 2.69 .91 3.40 .67 26.5 ------------------------------------------------------------------------------------------------------------------------------------------------------ 9. Portugal 200 17,456 6.5 3,386 3.44 .58 1.49 .50 3.52 .84 2.11 .97 3.70 .77 18.5 10. Slovenia 200 16,986 6.1 7,025 3.48 .51 1.56 .43 3.04 .83 2.19 .90 3.87 .59 22.0 11. S. Korea 203 16,308 5.0 45,647 3.97 .59 2.16 .72 3.82 .70 2.76 .94 3.35 .75 62.1 12. Taiwan 201 15,203 5.9 22,567 3.86 .56 1.71 .54 3.62 .91 2.43 .97 3.57 .78 29.9 13. Malta 200 13,803 6.6 14,922 3.85 .57 1.62 .50 3.62 .83 2.47 .95 3.87 .79 30.0 14. Oman 204 12,664 6.3 5,816 3.56 .59 1.50 .45 3.57 1.08 2.40 .99 3.82 .86 12.3 15. Hungary 100 10,814 5.0 2,700 3.84 .63 1.71 .52 3.34 .90 2.06 .88 3.92 .75 34.0 16. Croatia 165 8,675 3.4 14,336 3.60 .52 1.82 .52 3.14 .85 2.32 .91 3.72 .80 43.6 17. Mexico 295 7,298 3.5 7,416 3.57 .66 1.59 .49 3.40 .92 2.36 .98 4.03 .73 25.4 18. Russia 200 5,349 2.4 2,901 3.76 .58 2.25 .71 3.17 .72 2.63 .92 3.44 .82 66.0 19. S. Africa 203 5,106 4.5 5,247 3.67 .41 2.38 .41 2.78 .60 2.82 .62 3.56 .65 87.7 20. Malaysia 200 5,042 5.1 10,180 3.85 .53 1.63 .63 3.28 .84 2.54 .98 3.71 .72 29.0 ------------------------------------------------------------------------------------------------------------------------------------------------------ 21. Romania 200 4,539 3.0 1,723 3.77 .57 1.29 .36 3.69 .83 2.13 1.00 3.68 .85 11.0 22. Brazil 201 4,320 3.7 5,006 3.54 .61 1.68 .56 3.76 .86 2.04 .84 3.71 .73 30.3 23. Bulgaria 162 3,459 4.0 2,148 3.84 .55 1.92 .51 3.33 .70 2.19 .62 3.46 .72 19.9 24. Peru 183 2,841 3.5 13,060 3.58 .59 1.83 .86 3.55 .79 2.42 1.02 3.91 .78 33.9 25. Macedonia 204 2,810 2.7 2,176 3.91 .55 1.54 .47 3.33 .88 2.60 1.02 3.59 .82 24.5 26. Thailand 200 2,659 3.8 10,985 3.65 .60 2.04 .79 3.31 .66 2.37 .78 3.56 .59 47.5 27. China 204 1,709 3.2 2,553 3.46 .64 1.44 .54 3.24 .93 2.18 .86 3.28 .77 15.7 28. Egypt 200 1,265 3.4 7,181 3.51 .65 1.44 .69 3.94 1.06 2.29 1.11 3.98 .83 14.5 29. Philippines 200 1,168 2.5 2,027 3.69 .62 1.57 .64 3.65 .94 1.85 .90 3.91 .71 26.0 30. Nigeria 200 678 1.9 1,909 4.20 .43 1.29 .44 2.68 .63 1.53 .76 4.36 .74 20.5 ____________________________________________________________________________________________________ 1. High 1,756 31,595 7.9 30,148 3.68 .61 1.53 .50 3.55 .77 2.41 1.06 3.73 .77 20.9 2. Medium 2,371 11,225 5.0 11,845 3.70 .58 1.78 .62 3.40 .78 2.44 .95 3.72 .78 38.0 3. Low 1,954 2,544 3.2 4,880 3.71 .62 1.60 .65 3.51 .73 2.16 .95 3.75 .81 26.6 Whole 6,081 13,862 5.2 13,384 3.70 .60 1.65 .61 3.44 .88 2.34 .99 3.73 .79 29.4 ____________________________________________________________________________________________________

Variable M SD 1 2 3 4 5 6 7 8 9 1. Age 34.68 9.63 .85 .69 .88 .90 .86 (Cronbach’s alpha) 2. Sex .51 .50 .12** 3. Education 15.42 2.56 .03* .04* 4. Income (Z) .00 .97 .28** .15** .18** 5. LOM 3.70 .60 -.02 .10** .03* -.03* 6. CEV 3.48 .76 .03* -.02 .03** .06** -.01 7. PUB 1.65 .61 -.06** .08** .04** -.04** .10** -.19** 8. Irritation 2.34 .99 -.02 -.02 -.07** -.10** .06** -.22** .27** 9. Life 3.73 .79 .02 -.01 -.00 .08** -.00 -.13** -.14** -.28** High GDP 1. Age 33.14 10.25 .86 .73 .83 .93 .89 2. Sex .50 .50 .22** 3. Education 14.71 2.46 .11** .13** 4. Income (Z) .00 .98 .38** .21** .23** 5. LOM 3.68 .61 -.09** .15** .01 -.03 6. CEV 3.55 .77 .08** .00 .01 .12** -.01 7. PUB 1.53 .50 -.17** .07** -.00 -.04 .13** -.20** 8. Irritation 2.41 1.06 -.09** -.08** -.01 -.12** .10** -.30** .23** 9. Life 3.73 .77 .03 .01 -.02 .11** -.07 .16** -.13** -.26** Medium GDP 1. Age 35.37 9.53 .84 .71 .86 .86 .82

2. Sex .52 .50 .08** 3. Education 15.45 2.67 .01 - .03 4. Income (Z) .00 .98 .24** .17** .17** 5. LOM 3.70 .58 -.01 .11** .08* -.03 6. CEV 3.40 .78 -.04 -.01 .05* .04 -.03 7. PUB 1.78 .62 -.03 .09** .07** -.06** .15** -.18** 8. Irritation 2.44 .95 .01 -.01 -.02 -.08** .11** -.20** .28** 9. Life 3.72 .78 -.03 -.01 -.03 .07** -.06** -.12** -.16** -.28** Low GDP 1. Age 35.22 8.99 .85 .63 .92 .91 .87

2. Sex .51 .50 .09** 3. Education 16.01 2.36 -.09** -.04 4. Income (Z) .00 .95 .22** .06** .17** 5. LOM 3.71 .62 -.02 .03 - .02 -.02 6. CEV 3.51 .73 .10** -.06** .07** .03 -.06* 7. PUB 1.60 .65 -.14** .07** -.02 -.02 .03 -.15** 8. Irritation 2.16 .95 .03 .04 -.13** -.11** -.04 -.14** .30** 9. Life 3.75 .81 -.06** -.03 .04 .08** .11** .11** -.13** -.31**

Regression and SEM Results  ____________________________________________________________________________________________________________________________________ Variable R R2 R2 Change F Change df p ____________________________________________________________________________________________________________________________________ Step 1: Multiple Regression Analyses (Unethical Behavior Intention) 1. The Love of Money (LOM) .099 .010 .010 60.63 1, 6079 .000 2. GDP .134 .018 .008 49.75 1, 6208 .000 3. LOM x GDP .137 .019 .001 5.05 1, 6207 .025* 1. Corporate Ethical Values (CEV) .092 .008 .008 51.92 1, 6079 .000 2. GDP .125 .016 .007 44.92 1, 6078 .000 3. CEV x GDP .126 .016 .000 .30 1, 6077 .582 ____________________________________________________________________________________________________________________________________ Model χ2 df p χ2/df IFI TLI CFI SRMSR RMSEA Models ΔCFI Step 2: Compare Proposed Model with Alternative Models (Whole Sample) 1. Proposed Model 4172.89 483 .0000 8.6395 .9579 .9540 .9579 .0400 .0345 2. Alternative 1 4201.46 483 .0000 8.6987 .9576 .9536 .9576 .0414 .0356 3. Alternative 2 4648.81 483 .0000 9.6249 .9525 .9481 .9525 .0510 .0377 Step 3: Measurement model: Configural Invariance (Each Group) 4. High GDP 1593.53 477 .0000 3.3407 .9566 .9519 .9565 .0400 .0365 5. Medium GDP 2403.08 477 .0000 5.0379 .9382 .9315 .9381 .0430 .0413 6. Low GDP 2371.66 477 .0000 4.9720 .9449 .9389 .9448 .0604 .0451 Step 4: Measurement model: Metric Invariance (3 GDP Groups) 7. Unconstrained 6368.25 1431 .0000 4.4502 .9459 .9400 .9458 .0604 .0238 8. Constrained 7049.91 1475 .0000 4.7796 .9389 .9343 .9388 .0644 .0249 8 vs. 7 .0070 Step 5: Measurement Model Without and With Latent Common Method Variance (CMV) Factor (3 GDP Groups): 9. Model 6368.25 1431 .0000 4.4502 .9459 .9400 .9458 .0604 .0238 10. Model 9 + CMV 5106.63 1332 .0000 3.8338 .9587 .9507 .9586 .0334 .0216 10 vs. 9 .0128 Step 6: Main SEM Model (3 GDP Groups) 11. Model 6468.77 1443 .0000 4.4829 .9449 .9395 .9448 .0639 .0239 12. Model 11 + LOM 6799.17 1465 .0000 4.6411 .9415 .9367 .9415 .0670 .0245 12 vs. 11 .0033 13. Model 12 + CEV 6995.43 1469 .0000 4.7620 .9394 .9346 .9393 .0682 .0249 13 vs. 12 .0022 14. Model 13 + PUB 7355.83 1491 .0000 4.9335 .9357 .9316 .9355 .0684 .0254 14 vs. 13 .0038 15. Model 14 + Irritation 7365.64 1495 .0000 4.9269 .9356 .9317 .9356 .0684 .0254 15 vs. 14 .0001 16. Model 15 + Life 7369.98 1499 .0000 4.9166 .9356 .9319 .9356 .0684 .0254 16 vs. 15 .0000 Step 7: Set All Paths to be Equal (Model 17) 17. Model 16 + Paths 7560.46 1511 .0000 5.0036 .9337 .9304 .9336 .0749 .0257 14 vs. 13 .0020 _______________________________________________________________________________________________________________________________________

High GDP Group

The LoveOf Money

EthicalValues

UnethicalBehavior

StressLife

Satisfaction.15***

-.16***

.09**

-.20***

.21*** -.27***

Medium GDP Group

The LoveOf Money

EthicalValues

UnethicalBehavior

StressLife

Satisfaction.25***

-.12***

.07**

-.12***

.31*** -.32***

Low GDP Group

The LoveOf Money

EthicalValues

UnethicalBehavior

StressLife

Satisfaction.00

.01

-.07**

.09***

.31*** -.33***

Across All 3 GDP Groups: Unstandardized Estimates

The LoveOf Money

EthicalValues

UnethicalBehavior

StressLife

Satisfaction.11***

-.10***

.03

-.10***

.46*** -.23***

4 Culture-Specific (emic) Paths

The Love of Money has a negative “double-whammy” effect: increasing unethical behavior intention and stress/irritation

Corporate ethical values have a positive “double-whammy” effect: reducing unethical behavior intention and stress/irritation

For managers in High and Medium GDP groups only

Economic Development is a Moderator.

2 Culture-Free (etic) Paths

Unethical Behavior Job Stress Life Satisfaction

Job Stress is a Mediator of the relationship between Unethical Behavior and Life Satisfaction

Good vs. Bad Apples: Cluster

Bad apples (29.4%) Good apples (70.6%).

Among Bad Apples:

20.5% in the High GDP

50.4% in the Medium GDP

29.0% in the Low GDP

Bad Apples

High GDP group: 20.9% ,

Medium GDP group: 38.0%,

Low GDP group: 26.6%

Across 3 GDP Groups

The High GDP group: The LOWEST Unethical Behavior

The Medium GDP group:

The Lowest corporate ethical vales

The Highest unethical behavior

The highest job stress

The highest percentage of bad apples = 38.0%

Limitations

1. Extraneous or nuisance variables (size or org. economy of the region, unemployment rate, religion, etc.)

2. Non-random samples from each of the three levels of economic development and from each of the geopolitical entities.

3. Min. number of constructs and items in our model

A New Cross-Cultural Study

100 Data Sets (Groups) for Each Country

1 Manager

3 Subordinates: A, B, C

Manager – Subordinate A

Manager – Subordinate B

Manager – Subordinate C

Bor-Shiuan Chen: Paternalistic LeadershipJuly 21, 2008, Invited Address: 10:15-11:15

21 Countries/Geopolitical EntitiesBelgium Japan Taiwan

China Mexico Thailand

France Nigeria The USA

Greece Poland

Hong Kong Portugal

Hungry Russia

India Singapore

Indonesia South Korea

Italy South Africa

Contact

ttang@mtsu.edu

Thank YouDanke

Dankeshen

Grazie

Merci

Muchas Gracias

謝謝