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.,Adebowale Akande, International Institute of Research, South Africa,Michael W. Allen, University of Sydney, Australia,Abdulgawi Salim Alzubaidi, 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 Hamid Safwat Ibrahim, Iman University, Saudi Arabia, 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, 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, Rangsit University, 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, Affinion Group, 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, FrancePeter Vlerick, Ghent University, Belgium

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

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

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 GermanyNo. 2 in Belgium, UK, and the US

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)

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?

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.

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).

Pay Satisfaction Questionnaire

1. Pay Level 2. Pay Raise3. Benefit4. 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)

Pay Level Satisfaction

1. My take home pay2. My current salary3. My overall level of pay4. Size of my current salary

The Love of Money-Pay Satisfaction

Adam (1963): Equity modelLawler (1971): Discrepancy modelEasterlin (2001): Relative theoryVeenhoven (1984): Absolute theoryBrickman & Campbell (1971):

Adaptation theoryMichalos (1985): Aspiration theory

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)

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 structureMetric Invariance: Factor Loading

The Income PyramidPrahalad & Hammond, 2002, HBR

1. > 20,0002. 2,000 – 20,0003. < 2,000

Level of Economic Development

1. GDP > 20,0002. GDP 5,000 – 20,0003. GDP < 5,000

We treat GDP as a “Moderator”

Method N = 6,285(1) 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

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 M M 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. France 87 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***

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

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***)†

______________________________________________________________________________________________________

Multiple Regression Results   ________________________________________________________________________________________________________________   Variable R R2 R2 Change 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.    

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

 

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 _______________________________________________________________________________________________________

Main Findings Love of Money Pay Level Satisfaction

1. High GDP Group: -.16***2. Medium GDP Group: -.14***3. 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)

Implications

Love of Money Pay Level Satisfaction

Varies Across GDP GroupsBribery = 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.

LimitationsConvenience samples from H, M, L GDP Groups

from each entity, from 1 Source, at 1TimeExtraneous/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.

A New Cross-Cultural Study

100 Data Sets (Groups) for Each Country1 Manager3 Subordinates: A, B, C

Manager – Subordinate AManager – Subordinate BManager – Subordinate C

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

21 Countries/Geopolitical Entities

Belgium Japan TaiwanChina Mexico ThailandFrance Nigeria The USAGreece PolandHong Kong PortugalHungry RussiaIndia SingaporeIndonesia South KoreaItaly South Africa

Contact

ttang@mtsu.edu

Thank YouDanke Dankeshen Grazie Merci Muchas Gracias

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