Journal of Business Ethics

, Volume 148, Issue 4, pp 919–937 | Cite as

Monetary Intelligence and Behavioral Economics: The Enron Effect—Love of Money, Corporate Ethical Values, Corruption Perceptions Index (CPI), and Dishonesty Across 31 Geopolitical Entities

  • Thomas Li-Ping Tang
  • Toto Sutarso
  • Mahfooz A. Ansari
  • Vivien K. G. Lim
  • Thompson S. H. Teo
  • Fernando Arias-Galicia
  • Ilya E. Garber
  • Randy Ki-Kwan Chiu
  • Brigitte Charles-Pauvers
  • Roberto Luna-Arocas
  • Peter Vlerick
  • Adebowale Akande
  • Michael W. Allen
  • Abdulgawi Salim Al-Zubaidi
  • Mark G. Borg
  • Bor-Shiuan Cheng
  • Rosario Correia
  • Linzhi Du
  • Consuelo Garcia de la Torre
  • Abdul Hamid Safwat Ibrahim
  • Chin-Kang Jen
  • Ali Mahdi Kazem
  • Kilsun Kim
  • Jian Liang
  • Eva Malovics
  • Alice S. Moreira
  • Richard T. Mpoyi
  • Anthony Ugochukwu Obiajulu Nnedum
  • Johnsto E. Osagie
  • AAhad M. Osman-Gani
  • Mehmet Ferhat Özbek
  • Francisco José Costa Pereira
  • Ruja Pholsward
  • Horia D. Pitariu
  • Marko Polic
  • Elisaveta Gjorgji Sardžoska
  • Petar Skobic
  • Allen F. Stembridge
  • Theresa Li-Na Tang
  • Caroline Urbain
  • Martina Trontelj
  • Luigina Canova
  • Anna Maria Manganelli
  • Jingqiu Chen
  • Ningyu Tang
  • Bolanle E. Adetoun
  • Modupe F. Adewuyi


Monetary intelligence theory asserts that individuals apply their money attitude to frame critical concerns in the context and strategically select certain options to achieve financial goals and ultimate happiness. This study explores the dark side of monetary Intelligence and behavioral economics—dishonesty (corruption). Dishonesty, a risky prospect, involves cost–benefit analysis of self-interest. We frame good or bad barrels in the environmental context as a proxy of high or low probability of getting caught for dishonesty, respectively. We theorize: The magnitude and intensity of the relationship between love of money and dishonest prospect (dishonesty) may reveal how individuals frame dishonesty in the context of two levels of subjective norm—perceived corporate ethical values at the micro-level (CEV, Level 1) and Corruption Perceptions Index at the macro-level (CPI, Level 2), collected from multiple sources. Based on 6382 managers in 31 geopolitical entities across six continents, our cross-level three-way interaction effect illustrates: As expected, managers in good barrels (high CEV/high CPI), mixed barrels (low CEV/high CPI or high CEV/low CPI), and bad barrels (low CEV/low CPI) display low, medium, and high magnitude of dishonesty, respectively. With high CEV, the intensity is the same across cultures. With low CEV, the intensity of dishonesty is the highest in high CPI entities (risk seeking of high probability)—the Enron Effect, but the lowest in low CPI entities (risk aversion of low probability). CPI has a strong impact on the magnitude of dishonesty, whereas CEV has a strong impact on the intensity of dishonesty. We demonstrate dishonesty in light of monetary values and two frames of social norm, revealing critical implications to the field of behavioral economics and business ethics.


Theory of planned behavior Prospect theory Love of money Behavioral intention/Behavioral ethics Good/bad apples Barrels Risk aversion Risk seeking Cross-cultural Multilevel CPI GDP FDI   Global economic pyramid Corruption Human resource management 



The senior author would like to thank Faculty Research and Creative Activity Committee of Middle Tennessee State University and all co-authors’ respective institutions for financial support, late Fr. Wiatt Funk, late Prof. Kuan Ying Tang, and Fang Chen Tang for their inspiration, and pay special tribute to Prof. Horia D. Pitariu who passed away on March 25, 2010.


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Thomas Li-Ping Tang
    • 1
  • Toto Sutarso
    • 2
  • Mahfooz A. Ansari
    • 3
  • Vivien K. G. Lim
    • 4
  • Thompson S. H. Teo
    • 4
  • Fernando Arias-Galicia
    • 5
  • Ilya E. Garber
    • 6
  • Randy Ki-Kwan Chiu
    • 7
  • Brigitte Charles-Pauvers
    • 8
  • Roberto Luna-Arocas
    • 9
  • Peter Vlerick
    • 10
  • Adebowale Akande
    • 11
  • Michael W. Allen
    • 12
  • Abdulgawi Salim Al-Zubaidi
    • 13
  • Mark G. Borg
    • 14
  • Bor-Shiuan Cheng
    • 15
  • Rosario Correia
    • 16
  • Linzhi Du
    • 17
  • Consuelo Garcia de la Torre
    • 18
  • Abdul Hamid Safwat Ibrahim
    • 19
  • Chin-Kang Jen
    • 20
  • Ali Mahdi Kazem
    • 13
  • Kilsun Kim
    • 21
  • Jian Liang
    • 22
  • Eva Malovics
    • 23
  • Alice S. Moreira
    • 24
  • Richard T. Mpoyi
    • 2
  • Anthony Ugochukwu Obiajulu Nnedum
    • 25
  • Johnsto E. Osagie
    • 26
  • AAhad M. Osman-Gani
    • 27
  • Mehmet Ferhat Özbek
    • 28
  • Francisco José Costa Pereira
    • 29
  • Ruja Pholsward
    • 30
  • Horia D. Pitariu
    • 31
  • Marko Polic
    • 32
  • Elisaveta Gjorgji Sardžoska
    • 33
  • Petar Skobic
    • 34
  • Allen F. Stembridge
    • 35
  • Theresa Li-Na Tang
    • 36
  • Caroline Urbain
    • 8
  • Martina Trontelj
    • 32
  • Luigina Canova
    • 37
  • Anna Maria Manganelli
    • 37
  • Jingqiu Chen
    • 22
  • Ningyu Tang
    • 22
  • Bolanle E. Adetoun
    • 38
  • Modupe F. Adewuyi
    • 39
  1. 1.Department of Management, Jennings A. Jones College of BusinessMiddle Tennessee State UniversityMurfreesboroUSA
  2. 2.Middle Tennessee State UniversityMurfreesboroUSA
  3. 3.University of LethbridgeLethbridgeCanada
  4. 4.National University of SingaporeSingaporeSingapore
  5. 5.Universidad Autónoma del Estado de MorelosMexicoMexico
  6. 6.Saratov State UniversitySaratovRussia
  7. 7.Hong Kong Baptist UniversityHong KongHong Kong
  8. 8.University of NantesNantesFrance
  9. 9.University of ValenciaValenciaSpain
  10. 10.Ghent UniversityGhentBelgium
  11. 11.Independent Research CollaborationPretoriaSouth Africa
  12. 12.İpek UniversityOranTurkey
  13. 13.Sultan Qaboos UniversityMuscatOman
  14. 14.University of MaltaMsidaMalta
  15. 15.National Taiwan UniversityTaipeiTaiwan
  16. 16.Polytechnic Institute of Lisbon – PortugalLisbonPortugal
  17. 17.Lanzhou UniversityLanzhouChina
  18. 18.Technological Institute of MonterreyMonterreyMexico
  19. 19.Suez Canal UniversityIsmaileyaEgypt
  20. 20.National Sun-Yat-Sen UniversityKaohsiungTaiwan
  21. 21.Sogang UniversitySeoulSouth Korea
  22. 22.Shanghai Jiao Tong UniversityShanghaiChina
  23. 23.University of SzegedSzegedHungary
  24. 24.Federal University of ParáCastanhalBrazil
  25. 25.Nnamdi Azikiwe UniversityAwkaNigeria
  26. 26.FAMUTallahasseeUSA
  27. 27.International Islamic University of MalaysiaKuala LumpurMalaysia
  28. 28.Gümüşhane UniversityGümüşhaneTurkey
  29. 29.Lusófona UniversityLisbonPortugal
  30. 30.Rangsit UniversityPathum ThaniThailand
  31. 31.Babes-Bolyai UniversityCluj-NapocaRomania
  32. 32.University of LjubljanaLjubljanaSlovenia
  33. 33.University St. Cyril and MethodiusSkopjeMacedonia
  34. 34.ALDI, Inc.MurfreesboroUSA
  35. 35.Andrews UniversityBerrien SpringsUSA
  36. 36.Tang Global Consulting GroupFranklinUSA
  37. 37.University of PaduaPaduaItaly
  38. 38.Economic Commission of West AfricaAbujaNigeria
  39. 39.Mercer UniversityAtlantaUSA

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