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The Love of Money and Pay Level Satisfaction

The Love of Money and Pay Level Satisfaction. 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, U.S.A.,

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The Love of Money and Pay Level Satisfaction

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  1. The Love of Money and Pay Level Satisfaction Academy of Management Anaheim, CA, August 8-13, 2008 Presented by Thomas Li-Ping Tang, Ph.D. Middle Tennessee State University, the USA

  2. Toto Sutarso, Middle Tennessee State University, U.S.A., AdebowaleAkande, International Institute of Research,South Africa, Michael W. Allen, University of Sydney, Australia, AbdulgawiSalimAlzubaidi, Sultan Qaboos University, Oman, Mahfooz A. Ansari, University of Lethbridge,Canada, Fernando Arias-Galicia, Universidad Autónoma del Estado de Morelos, 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, Linzhi Du, Nankai University, China, Ilya Garber, Saratov State Socio-Economic University,Russia, Consuelo Garcia De La Torre, Technological Institute of Monterrey, Mexico, Rosario Correia Higgs, Polytechnic Institute of Lisbon – Portugal, Portugal, Abdul HamidSafwat Ibrahim, Iman University, Saudi Arabia, Chin-Kang Jen, National Sun-Yat-Sen University,Taiwan, Ali MahdiKazem, 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,

  3. Anna Maria Manganelli, University of Padua, Italy, Alice S. Moreira, Federal University of Pará, Brazil, Richard T. Mpoyi, Middle Tennessee State University, the U.S.A., Anthony Ugochukwu Obiajulu Nnedum, Nnamdi Azikiwe University,Nigeria, Johnsto E. Osagie, Florida A & M University, U.S.A., AAhad M. Osman-Gani, Nanyang Technological University, Singapore, Francisco Costa Pereira, Polytechnic Institute of Lisbon – Portugal, Portugal, Ruja Pholsward, RangsitUniversity, 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, U.S.A. Allen F. Stembridge, Andrews University, U.S.A., Theresa Li-Na Tang, AffinionGroup, Brentwood, TN, U.S.A., 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. Money • The instrument of commerce and the measure of value(Smith, 1776/1937). • Attract, retain, and motivate employees and achieve organizational goals(Chiu, Luk, & Tang, 2002; Milkovich & Newman, 2005; Tang, Kim, & Tang, 2000). • Objective

  5. The Meaning of Money is “in the eye of the beholder”(McClelland, 1967, p. 10) and can be used as the “frame of reference”(Tang, 1992)in which people examine their everyday lives(Tang & Chiu, 2003; Tang, Luna-Arocas, & Sutarso, 2005). Subjective

  6. The Importance of Money *10 Job Preferences, Pay was ranked: (Jurgensen, 1978) No. 5 by Men No. 7 by Women *11 work goals, Pay was ranked: (Harpaz, 1990). No. 1 in Germany No. 2 in Belgium, UK, and the US

  7. The Love of Money • Those who want to get rich fall into temptation and a trap and into many foolish and harmful desires that plunge people into ruin and destruction. For the love of money is a root of all kinds of evil. (1 Timothy 6: 9-10)

  8. The ABCs of Money Attitudes Affective: Do you “love or hate” money? Behavioral: What do you “do” with your money? Cognitive: What does money “mean” to you?

  9. 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 (Behavior) 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: Importance (Cognitive) 7. Money is good. 8. Money is important. 9. Money is valuable.

  10. Pay Satisfaction Job satisfaction: A pleasurable or positive emotional state resulting from the appraisal of one’s job or job experiences (Locke, 1976: 300). Pay Satisfaction: Pay Level-Pay Satisfaction relationship is the most robust finding (Heneman & Judge, 2000: 71).

  11. Pay Satisfaction Questionnaire 1. Pay Level 2. Pay Raise 3. Benefit 4. Pay Administration (Heneman & Schwab, 1985) Time 1-Time 2 (Judge & Welbourne, 1994) Majority of studies included only Pay Level Satisfaction of PSQ (Williams, McDaniel, & Nguyen, 2006)

  12. Pay Level Satisfaction • My take home pay • My current salary • My overall level of pay • Size of my current salary

  13. The Love of Money-Pay Satisfaction Adam (1963): Equity model Lawler (1971): Discrepancy model Easterlin (2001): Relative theory Veenhoven (1984): Absolute theory Brickman & Campbell (1971): Adaptation theory Michalos (1985): Aspiration theory

  14. The Love of Money-Pay Satisfaction Poverty consists, not in the decrease of one’s possessions, but in the increase of one’s greed. Plato (427-347 BC) Whoever loves money never has money enough; whoever loves wealth is never satisfied with his income. (Ecclesiastes 5:10)

  15. Cross-Cultural Study 64%: only 2 countries 23%: > 2 countries (Sin, Cheung, & Lee, 1999). 72.43%: did not report Measurement Invariance (He, Merz, & Alden, 2008) Configural Invariance: Factor structure Metric Invariance: Factor Loading

  16. The Income Pyramid Prahalad & Hammond, 2002, HBR 1. > 20,000 2. 2,000 – 20,000 3. < 2,000

  17. Level of Economic Development 1. GDP > 20,000 2. GDP 5,000 – 20,000 3. GDP < 5,000 We treat GDP as a “Moderator”

  18. Method N = 6,285 • High GDP Group (n = 1,960): the USA, Belgium, Australia, France, Italy, Spain, Singapore, Hong Kong; 8 entities; (2) Medium GDP Group (n = 2,371): Portugal, Slovenia, South Korea, Taiwan, Malta, Oman, Hungary, Croatia, Mexico, Russia, South Africa, Malaysia; 12 entities; (3) Low GDP Group (n = 1,954): Romania, Brazil, Bulgaria, Peru, Macedonia, Thailand, China, Egypt, the Philippines, and Nigeria; 10 entities

  19. TABLE 1 Descriptive Statistics of All Variables and SEM Path of the Relationship between the Love of Money to Pay Level Satisfaction across 31 Samples (30 Geopolitical Entities) • High GDP Group • GDP Age Sex Education Income LOM PLS Path • Sample N M % M MM SD M SD LOM  PLS • 1. The USA (H) 274 42,000 35.03 45 15.08 35,357 3.85 .65 2.83 1.00 -.11 • 2. Belgium 201 35,712 38.85 57 14.83 20,269 3.37 .61 3.30 .85 -.04 • 3. Australia 262 34,740 26.50 29 12.74 - 3.58 .66 3.14 .94 -.17* • 4. France87 33,918 36.63 63 15.74 16,735 3.39 .64 2.86 1.04 -.11 • 5. Italy 204 30,200 37.65 40 14.14 15,303 3.22 .72 3.04 .88 -.27*** • 6. Spain 183 27,226 33.82 58 14.20 - 3.40 .72 3.12 .86 -.12 • 7. Singapore 1 202 26,836 33.70 53 15.12 31,746 3.80 .66 3.18 .88 -.22** • 8. Singapore 2 336 26,836 33.22 57 15.01 29,277 3.85 .58 3.26 .82 -.08 • 9. HK 211 25,493 30.79 49 15.66 47,509 3.82 .58 3.00 .83 -.34***

  20. Medium GDP Group • GDP Age Sex Education Income LOM PLS Path • Sample N M % M M M SD M SD LOM  PLS • 10. Portugal (M) 200 17,456 35.16 39 15.44 3,386 3.36 .61 2.70 .90 -.24** • 11. Slovenia 200 16,986 38.68 44 13.68 7,025 3.34 .57 2.93 1.00 -.32** • 12. S. Korea 203 16,308 37.15 73 15.91 45,647 3.97 .52 3.02 .82 -.10 • 13. Taiwan 201 15,203 34.94 51 16.50 22,567 4.02 .56 3.03 .86 -.11 • 14. Malta 200 13,803 36.91 51 16.47 14,922 3.81 .66 2.56 1.02 -.39*** • 15. Oman 204 12,664 29.91 64 14.68 5,816 3.59 .61 3.56 .94 -.30*** • 16. Hungary 100 10,814 34.06 55 15.96 2,700 3.79 .67 3.05 1.08 -.11 • 17. Croatia 165 8,675 37.48 42 14.73 14,336 3.47 .59 2.93 .86 -.05 • 18. Mexico 295 7,298 30.95 55 14.32 7,416 3.49 .71 2.97 .93 -.03 • 19. Russia 200 5,349 35.92 42 17.58 2,901 3.73 .61 2.76 .92 -.25** • 20. S. Africa 203 5,106 43.32 50 15.61 5,247 3.69 .44 2.28 .56 -.15 • 21. Malaysia 200 5,042 31.80 53 15.23 10,180 3.93 .54 3.12 .89 .01

  21. Low GDP Group • GDP Age Sex Education Income LOM PLS Path • Sample N M % M M M SD M SD LOM  PLS • 22. Romania (L) 200 4,539 38.02 27 16.69 1,723 3.75 .63 2.56 .94 -.05 • 23. Brazil 201 4,320 37.50 45 16.87 5,006 3.45 .63 2.68 .95 .20*** • 24. Bulgaria 162 3,459 27.48 43 16.76 2,148 3.78 .61 2.64 .84 .30** • 25. Peru 183 2,841 31.98 68 16.93 13,060 3.57 .65 3.07 .87 .08 • 26. Macedonia 204 2,810 41.60 44 13.31 2,176 3.86 .61 2.87 .97 .02 • 27. Thailand 200 2,659 33.32 55 16.84 10,985 3.68 .65 3.19 .63 -.19* • 28. China 204 1,709 31.86 60 15.38 2,553 3.59 .66 2.72 .81 -.05 • 29. Egypt 200 1,265 40.41 50 14.88 7,181 3.57 .70 3.37 1.08 -.07 • 30. The Philippines 200 1,168 33.45 60 16.96 2,027 3.71 .65 3.44 .74 .09 • 31. Nigeria 200 678 34.80 60 15.74 1,909 4.09 .42 3.45 .84 1.00***† • ______________________________________________________________________________________________________ • 1. High GDP 1,960 31,595 33.61 49 14.65 27,314 3.63 .68 3.10 .90 -.16*** • 2. Medium GDP 2,371 11,225 35.37 52 14.45 11,995 3.68 .64 2.91 .95 -.14*** • 3. Low GDP 1,954 2,544 35.22 51 16.01 7,764 3.71 .65 3.01 .93 .08** (-.02) † • Whole Sample 6,285 13,862 34.77 51 15.37 15,434 3.67 .66 3.00 .93 -.10***(-.11***)† ______________________________________________________________________________________________________

  22. Multiple Regression Results • ________________________________________________________________________________________________________________ • Variable RR2R2Change F Change df p • ________________________________________________________________________________________________________________ • Step 1 • Sex, Age, Education .051 .003 .003 5.41 3, 6211 .001 • Z Income .219 .048 .045 296.19 1, 6210 .001 • The Love of Money (LOM) .232 .054 .006 37.59 1, 6209 .001 • GDP .233 .054 .000 3.05 1, 6208 .081 • LOM x GDP .238 .057 .002 15.98 1, 6207 .001 • _________________________________________________________________________________________________________________ • Note. Sample size: N = 6,285. Due to large income differences, we calculated standardized Z income for each entity.

  23. Model χ2 df p χ2/df IFI TLI CFI SRMSR RMSEA Models ΔCFI • ____________________________________________________________________________________________________ •  Step 2: Measurement model • Configural Invariance: • 1. High GDP 271.04 62 .0000 4.3716 .9864 .9829 .9864 .0548 .0415 • 2. Medium GDP 374.65 62 .0000 6.0428 .9802 .9750 .9802 .0498 .0461 • 3. Low GDP 711.68 62 .0000 11.4705 .9471 .9334 .9471 .0563 .0732 • Metric Invariance (3 GDP Groups): • 4. Unconstrained 1,356.87 186 .0000 7.2950 .9731 .9661 .9730 .0548 .0317 • 5. Constrained 1,631.70 204 .0000 7.9859 .9671 .9623 .9671 .0564 .0334 5 vs. 4 .0059 • Step 3: Measurement Model Without and With Latent Common Method Variance (CMV) Factor (3 GDP Groups): • 6. Model 1,356.87 186 .0000 7.2950 .9731 .9661 .9730 .0548 .0317 • 7. Model 6 + CMV 1,460.75 159 .0000 9.1871 .9701 .9559 .9700 .0422 .0361 7 vs. 6 .0030 • Step 4: Main SEM Model (3 GDP Groups) • 8. Model 1,280.22 183 .0000 6.9957 .9748 .9677 .9747 .0262 .0309 • 9. Model 8 + LOM 1,521.09 199 .0000 7.6437 .9696 .9642 .9695 .0324 .0325 9 vs. 8 .0052 • 10. Model 9 + PLS 1,579.68 205 .0000 7.7058 .9684 .9639 .9683 .0324 .0327 10 vs. 9 .0012 • 11. Model 10 – Nigeria 847.40 205 .0000 4.1337 .9848 .9826 .9848 .0308 .0277 11 vs. 9 -.0153 • Step 5: Set the Path to be Equal • 12. Model 11 + Path 861.83 207 .0000 4.1635 .9845 .9824 .9845 .0312 .0228 12 vs. 11 .0003 • 13. Model 10 + Path 1,624.84 207 .0000 7.8495 .9674 .9631 .9673 .0361 .0330 13 vs. 10 .0010

  24. Step 4, Model 10/11 Step 5, Model 12/13 • Path High Medium Low Across Three GDP Groups • ____________________________________________________________________________________________________ • Part 1: Direct Effect Standardized Comparison Unstandardized • Model 10 LOM  PLS -.16*** -.14*** .08** HM < L Model 13-.10*** • Model 11 LOM  PLS -.16*** -.14*** -.02 W/O HM < L Model 12-.11*** • Part 2: Squared Multiple Correlation (SMC) • Model 10 PLS .026 .020 .006 • Model 11 PLS .025 .020 .000 • Part 3: Factor Loading • Model 10 The Love of Money (LOM) • 1. Rich .92 .88 .84 • 2. Motivator .66 .65 .61 • 3. Important .69 .71 .64 • Model 11 The Love of Money (LOM) • 1. Rich .92 .87 .84 • 2. Motivator .68 .66 .66 • 3. Important .68 .70 .63 • _______________________________________________________________________________________________________

  25. Main Findings Love of Money  Pay Level Satisfaction • High GDP Group: -.16*** • Medium GDP Group: -.14*** • Low GDP Group: -.02 The Whole Sample: -.11*** (functional equivalence) High GDP + Low LOM  The Highest Pay Level Satisfaction Medium GDP + High LOM  The Lowest Pay Level Satisfaction Low GDP + High LOM  High Pay Level Satisfaction (Corruption)

  26. Implications Love of Money  Pay Level Satisfaction Varies Across GDP Groups Bribery = 20 % of the total wage compensation in the Public sector, 0.9-1.2 % of Ukraine’s GDP in 2003 (Gorodnichenko & Peter, 2007). Low salaries force Public servants to supplement their incomes illicitly.

  27. Limitations Convenience samples from H, M, L GDP Groups from each entity, from 1 Source, at 1Time Extraneous/Nuisance variables: the size of the organization, organizational culture, economy of the nation/region, unemployment rate, etc. Any arbitrary categorization of a continuous variable (GDP) is problematic.

  28. 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

  29. 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

  30. Contact ttang@mtsu.edu

  31. Thank You Danke Dankeshen Grazie Merci Muchas Gracias 謝謝

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