450 likes | 625 Views
Antecedents and Consequences of Unethical Behavior: Does CPI Make a Difference?. Academy of Management Anaheim, CA , August 8-13, 2008 Presented by Thomas Li-Ping Tang, Ph.D. Middle Tennessee State University, the USA. TOTO SUTARSO, Middle Tennessee State University, USA,
E N D
Antecedents and Consequences of Unethical Behavior: Does CPI Make a Difference? Academy of Management Anaheim, CA, August 8-13, 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 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)
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 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)
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)
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 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.
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/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).
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)
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)
CPI Is a composite index that draws on 14 expert opinion surveys Provides data for 180 countries and territories on a scale from zero to ten, 10 = low levels of perceived corruption 0 = high levels of perceived corruption < 5 = "serious" perceived levels of corruption, < 3 = "rampant" corruption
Stewardship Theory Davis, Schoorman, & Donaldson, 1997 We included two consequences of ethical behavioral intention: • 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 • 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).
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).
29 Countries/Entities, N = 6081, (1) High CPI Group (> 7, n = 1,756): Singapore (2), Australia, Hong Kong, the USA, France, Belgium, and Spain; 7 entities; (2) Medium CPI Group (5 < CPI < 7, n = 1,771): Malta, Portugal, Oman, Slovenia, Taiwan, Malaysia South Korea, Hungary, and South Africa*, 9 entities; (3)Low CPI Group (< 5, n = 2,614): Bulgaria, Thailand, Brazil, Mexico, Peru, Egypt, Croatia, China, Romania,, Macedonia, the Philippines, Russia, and Nigeria; 13 entities
Table 1. Major Variables across 30 Samples (29 Geopolitical Entities) Arranged Based on CPI GDP CPI Income LOM PUB CEV Stress Life • Sample N M M SD M SD M SD M SD M SD _________________________________________________________________________________________________ • 1. Singapore 1 (H) 202 26,836 9.4 31,746 3.76 .63 1.50 .49 3.64 .78 2.64 1.05 3.70 .78 • 2. 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 • 3. Australia 262 34,740 8.8 - 3.63 .62 1.72 .48 3.60 .76 2.42 1.06 3.77 .91 • 4. HK 211 25,493 8.3 47,509 3.78 .58 1.63 .54 3.33 .69 2.69 .91 3.40 .67 • 5. The USA 274 42,000 7.6 35,357 3.80 .61 1.55 .53 3.57 .93 2.62 1.12 3.87 .73 • 6. France87 33,918 7.5 16,735 3.48 .53 1.56 .34 3.44 .88 2.22 1.06 3.72 .90 • 7. Belgium 201 35,712 7.4 20,269 3.49 .56 1.51 .45 3.54 .83 1.95 1.05 3.80 .71 • 8. Spain 183 27,226 7.0 - 3.50 .63 1.55 .47 3.15 .82 2.33 .91 3.82 .69 • ---------------------------------------------------------------------------------------------------------------------------------------------------- • 9. Malta (M) 200 13,803 6.6 14,922 3.85 .57 1.62 .50 3.62 .83 2.47 .95 3.87 .79 • 10. Portugal 200 17,456 6.5 3,386 3.44 .58 1.49 .50 3.52 .84 2.11 .97 3.70 .77 • 11. 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. Slovenia 200 16,986 6.1 7,025 3.48 .51 1.56 .43 3.04 .83 2.19 .90 3.87 .59 • 13. Taiwan 201 15,203 5.9 22,567 3.86 .56 1.71 .54 3.62 .91 2.43 .97 3.57 .78 • 14. Malaysia 200 5,042 5.1 10,180 3.85 .53 1.63 .63 3.28 .84 2.54 .98 3.71 .72 • 15. S. Korea 203 16,308 5.0 45,647 3.97 .59 2.16 .72 3.82 .70 2.76 .94 3.35 .75 • 16. Hungary 100 10,814 5.0 2,700 3.84 .63 1.71 .52 3.34 .90 2.06 .88 3.92 .75 • 17. S. Africa 203 5,106 4.5 5,247 3.67 .41 2.38 .41 2.78 .60 2.82 .62 3.56 .65
GDP CPI Income LOM PUB CEV Stress Life • Sample N M M SD M SD M SD M SD M SD • -------------------------------------------------------------------------------------------------------------------------------------------------- • 18. Bulgaria (L) 162 3,459 4.0 2,148 3.84 .55 1.92 .51 3.33 .70 2.19 .62 3.46 .72 • 19. Thailand 200 2,659 3.8 10,985 3.65 .60 2.04 .79 3.31 .66 2.37 .78 3.56 .59 • 20. Brazil 201 4,320 3.7 5,006 3.54 .61 1.68 .56 3.76 .86 2.04 .84 3.71 .73 • 21. Mexico 295 7,298 3.5 7,416 3.57 .66 1.59 .49 3.40 .92 2.36 .98 4.03 .73 • 22. Peru 183 2,841 3.5 13,060 3.58 .59 1.83 .86 3.55 .79 2.42 1.02 3.91 .78 • 23. 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 • 24. Croatia 165 8,675 3.4 14,336 3.60 .52 1.82 .52 3.14 .85 2.32 .91 3.72 .80 • 25. China 204 1,709 3.2 2,553 3.46 .64 1.44 .54 3.24 .93 2.18 .86 3.28 .77 • 26. Romania 200 4,539 3.0 1,723 3.77 .57 1.29 .36 3.69 .83 2.13 1.00 3.68 .85 • 27. Macedonia 204 2,810 2.7 2,176 3.91 .55 1.54 .47 3.33 .88 2.60 1.02 3.59 .82 • 28. The Philippines 200 1,168 2.5 2,027 3.69 .62 1.57 .64 3.65 .94 1.85 .90 3.91 .71 • 29. Russia 200 5,349 2.4 2,901 3.76 .58 2.25 .71 3.17 .72 2.63 .92 3.44 .82 • 30. Nigeria 200 678 1.9 1,909 4.20 .43 1.29 .44 2.68 .63 1.53 .76 4.36 .74 • _________________________________________________________________________________________________ • 1. High CPI 1,756 31,595 8.2 30,148 3.68 .61 1.53 .50 3.55 .77 2.41 1.06 3.73 .77 • 2. Medium CPI 1,711 12,588 5.7 13.054 3.70 .57 1.75 .61 3.46 .79 2.44 .95 3.69 .76 • 3. Low CPI 2,614 3,597 3.2 5,648 3.69 .62 1.66 .66 3.45 .74 2.23 .96 3.75 .81 • Whole Sample 6,081 13,862 5.2 13,279 3.70 .60 1.65 .61 3.44 .88 2.34 .99 3.73 .79 • _________________________________________________________________________________________________
Table 3. Main Results of the three CPI Groups • __________________________________________________________________________________________________ • Model χ2 df p χ2/df IFI TLI CFI SRMSR RMSEA Models ΔCFI • __________________________________________________________________________________________________ • Step 1: Measurement model • Configural Invariance: • 1. High CPI 1955.47 487 .0000 4.0157 .9429 .9380 .9428 .0746 .0415 • 2. Medium CPI 3068.73 487 .0000 6.3013 .8897 .8802 .8895 .0929 .0557 • 3. Low CPI 2948.02 487 .0000 6.0534 .9408 .9358 .9408 .0788 .0440 • Metric Invariance (3 CPI Groups): • 4. Unconstrained 7972.50 1461 .0000 5.4569 .9282 .9221 .9281 .0746 .0271 • 5. Constrained 8537.83 1505 .0000 5.6730 .9224 .9183 .9224 .0754 .0277 5 vs. 4 .0057 • Step 2: Measurement Model Without and With Latent Common Method Variance (CMV) Factor (3 CPI Groups): • 6. Model 7972.50 1461 .0000 5.4569 .9282 .9221 .9281 .0740 .0271 • 7. Model 12 + CMV 5759.12 1262 .0000 4.2284 .9516 .9436 .9515 .0391 .0230 7 vs. 6 .0234 • Step 3: Main SEM Model (3 CPI Groups) • 8. Model 6704.72 1437 .0000 4.6658 .9419 .9359 .9419 .0409 .0246 • 9. Model 8 + LOM 7004.02 1459 .0000 4.8006 .9389 .9336 .9388 .0417 .0250 9 vs. 8 .0031 • 10. Model 9 + CEV 7112.55 1463 .0000 4.8616 .9377 .9325 .9376 .0423 .0252 10 vs. 9 .0012 • 11. Model 10 + PUB 7440.22 1485 .0000 5.0102 .9343 .9299 .9343 .0468 .0257 11 vs. 10 .0033 • 12. Model 11 + Stress 7450.26 1489 .0000 5.0035 .9343 .9340 .9342 .0468 .0257 12 vs. 11 .0001 • 13. Model 12 + Life 7460.83 1493 .0000 4.9972 .9342 .9301 .9341 .0468 .0256 13 vs. 12 .0001 • Step 4: Set All Paths to be Equal • 14. Model 13 + Paths 7638.49 1509 .0000 5.0620 .9324 .9290 .9323 .0519 .0259 14 vs. 13 .0018 • ___________________________________________________________________________________________________
Table 4 Direct Effect, Indirect Effect, Total Effect, Squared Multiple Correlation, and Factor Loading (CPI) • _______________________________________________________________________________________________ • Step 3, Model 13 Step 4, Model 14 • Path High Medium Low Across Three CPI Groups • _______________________________________________________________________________________________ • Part 1: Direct Effect Standardized Comparison Unstandardized • 1. LOM PUB .16*** .29*** .03 M > H > L .11*** • 2. CEV PUB -.16*** -.10*** -.03 H < L -.10*** • 3. LOM Stress .08** .03 -.03 H > L .02 • 4. PUB Stress .21*** .36*** .32*** .46*** • 5. CEV Stress -.20*** -.11*** .04 H < M < L -.12*** • 6. LOM Life -.07** -.04 .09*** HM < L .01 • 7. Stress Life -.24*** -.35*** -.30*** ML < H -.23*** • 8. CEV Life .08** .04 .02 .05*
6 Culture-Specific (etic) Paths The Love of Money has one significant effect: increasing unethical behavior intention Corporate ethical values have a positive “triple-whammy” effect: reducing unethical behavior intention, irritation, and increasing life satisfaction Unethical Intention High Irritation Low Life Satisfaction
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
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
21 Countries/Geopolitical Entities Belgium Japan Taiwan China Mexico Thailand France Nigeria The USA Greece Poland Hong Kong Portugal Please contact Hungry Russia ttang@mtsu.edu India Singapore Indonesia South Korea Italy South Africa
ttang@mtsu.edu Please Provide: Country, Name, E-Mail Address
Thank You Danke Dankeshen Grazie Merci Muchas Gracias 謝謝