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Antecedents and Consequences of Unethical Behavior: Does Economic Development Make a Difference?

Antecedents and Consequences of Unethical Behavior: Does Economic Development Make a Difference?. International Congress of Psychology Berlin, Germany, July 20-28, 2008 Presented by Thomas Li-Ping Tang, Ph.D. Middle Tennessee State University, the USA.

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Antecedents and Consequences of Unethical Behavior: Does Economic Development Make a Difference?

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  1. Antecedents and Consequences of Unethical Behavior: Does Economic Development Make a Difference? International Congress of Psychology Berlin, Germany, July 20-28, 2008 Presented by Thomas Li-Ping Tang, Ph.D. Middle Tennessee State University, the USA

  2. 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,

  3. 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

  4. Scandals and Corruptions • 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)

  5. 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).

  6. 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).

  7. Corruption Around the World Countries with high GDP per Capita tend to have lowCPI 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)

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

  9. 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).

  10. The Love of Money Scale Factor 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.

  11. 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).

  12. 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).

  13. 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/year Theft: $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).

  14. 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 Blowing 4. 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 Corruption 9. 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)

  15. The Income Pyramid: Moderator 1. High: > $20,000, 2. Medium: $20,000-- $2,000, and 3. Low: < $2,000 (Prahalad & Hammond, 2002, HBR) Three Levels of Economic Development • High: GDP > $20,000, the rule of the law • Medium: $5,000 - $20,000, the rule of the man 3. Low: GDP < $5,000, no rule (law or order)

  16. Stewardship Theory Davis, Schoorman, & Donaldson, 1997 We included two consequences of ethical behavioral intention: • Job Stress 2. Life Satisfaction

  17. 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).

  18. Life Satisfaction • My work/family/personal life in general 2. My life as a whole these days • 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).

  19. Theoretical Model: Variables Theory of Reasoned Action Stewardship Theory (Ajzen & Fishbein, 1980; Trevino, 1986) (Davis, Schoorman, & Donaldson, 1997) The Love Of Money Unethical Behavior Job Stress Life Satisfaction Ethical Values

  20. Measurement Invariance: Criteria Configural: 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).

  21. 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

  22. 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 .9134.7 • 4. France87 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 • ____________________________________________________________________________________________________

  23. 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**

  24. Regression and SEM Results •  ____________________________________________________________________________________________________________________________________ • Variable RR2R2Change 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 • _______________________________________________________________________________________________________________________________________

  25. High GDP Group The Love Of Money .09** -.27*** .21*** .15*** Unethical Behavior Stress Life Satisfaction -.16*** Ethical Values -.20***

  26. Medium GDP Group The Love Of Money .07** -.32*** .31*** .25*** Unethical Behavior Stress Life Satisfaction -.12*** Ethical Values -.12***

  27. Low GDP Group The Love Of Money -.07** -.33*** .31*** .00 Unethical Behavior Stress Life Satisfaction .01 Ethical Values .09***

  28. Across All 3 GDP Groups: Unstandardized Estimates The Love Of Money .03 -.23*** .46*** .11*** Unethical Behavior Stress Life Satisfaction -.10*** Ethical Values -.10***

  29. 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.

  30. 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

  31. 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

  32. Bad Apples High GDP group: 20.9% , Medium GDP group: 38.0%, Low GDP group: 26.6%

  33. 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%

  34. Limitations • Extraneous or nuisance variables (size or org. economy of the region, unemployment rate, religion, etc.) • Non-random samples from each of the three levels of economic development and from each of the geopolitical entities. • Min. number of constructs and items in our model

  35. 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 Leadership July 21, 2008, Invited Address: 10:15-11:15

  36. 21 Countries/Geopolitical Entities Belgium Japan Taiwan China Mexico Thailand France Nigeria The USA Greece Poland Hong Kong Portugal Hungry Russia India Singapore Indonesia South Korea Italy South Africa

  37. Contact ttang@mtsu.edu

  38. Thank You Danke Dankeshen Grazie Merci Muchas Gracias 謝謝

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