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The Love of Money Research around the World: Implications for HRD

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The Love of Money Research around the World: Implications for HRD Thomas Li-Ping Tang Middle Tennessee State University, the USA AAhad M. Osman-Gani, Presenting Author – PowerPoint PPT presentation

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Title: The Love of Money Research around the World: Implications for HRD


1
The Love of Money Research around the World
Implications for HRD
  • Thomas Li-Ping Tang
  • Middle Tennessee State University, the USA
  • AAhad M. Osman-Gani, Presenting Author
  • Nanyang Technological University, Singapore
  • 4th Asian Conference of the AHRD, Taipei, Taiwan,
  • December 4-6, 2005

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 Science Malaysia,
    Malaysia,
  • 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,
  • ALLEN F. STEMBRIDGE, Southwestern Adventist
    University, USA,
  • THERESA LI-NA TANG, Cendant Marketing 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
Outline
  • The Meaning of Money
  • The Love of Money
  • The Love of Money Scale
  • Method
  • Results
  • Discussion, Implications, Limitations

5
Money
  • Money is the instrument of commerce and the
    measure of value (Smith, 1776/1937).
  • Money has been used to attract, retain, and
    motivate their employees and achieve
    organizational goals around the world (Milkovich
    Newman, 2005).
  • Money represents culture, history, values,
    location, political systems, and people.

6
The Meaning of Money
  • The meaning of money is in the eye of the
    beholder (McClelland, 1967, p. 10).
  • The meaning of money can be used as the frame of
    reference (Tang, 1992) in which people examine
    their everyday lives, such as pay satisfaction
    (Tang Chiu, 2003 Tang, Luna-Arocas, Sutarso,
    2005).

7
The Meaning of Money
  • In the compensation literature, one construct
    that should not be overlooked is the meaning of
    money (Barber Bretz, 2000 45)

8
The Importance of Money
  • Research shows that 49.9 of freshman in 1971
    said that the important reason in deciding to go
    on to college is to make more money.
  • That number increased to 75.1 in 1993
  • (The American Freshman, 1994).

9
The Importance of Money
  • Among 10 Job Preferences (Jurgensen, 1978).
  • Men ranked Pay the 5th
  • Women ranked Pay the 7th
  • Among 11 work goals, Pay was ranked
  • The 1st in Germany
  • The 2nd in Belgium, the UK, and the US and
  • (Harpaz, 1990).

10
The Importance of Money
  • In Hong Kong and China, most Chinese prefer cash
    among 35 components of compensation,
  • The cash mentality (Chiu, Luk, Tang, 2001).

11
The Importance of Money
  • The lack of money has become the number one cause
    of dissatisfaction among university students on
    campus for the past seven years (1997-2003), up
    from the third and the second place of two
    earlier periods (1990-1996, 1981-1987,
    respectively) (Bryan, 2004).

12
The Importance of Money
  • Pay Dissatisfaction has numerous undesirable
    consequences (Heneman Judge, 2000 77)
  • Turnover (Hom Griffeth, 1995 Tang, Kim,
    Tang, 2000),
  • Low Commitment,
  • Counterproductive Behavior (Cohen-Charash,
    Spector, 2001 Luna-Arocas Tang, 2004), and
  • Unethical Behavior (e.g., Chen Tang, 2006
    Tang Chen, 2005 Tang Chiu, 2003).

13
The Love of Money
  • The Love of Money has been used in everyday
    expression and popular literature.
  • There is very little empirical research on this
    construct.

14
The Love of Money
  • Many scholars consider the love of money
  • as a taboo,
  • a religious or controversial issue,
  • not a scientific/academic issue, and
  • to be excessively value-laden.
  • Thereby, they may have great reluctance to study
    these issues.

15
The Oldest Reference
  • 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 (Bible 1 Timothy, 6 9-10
    Tang Chiu, 2003).

16
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?

17
The Love of Money Construct
  1. Factor Rich (Affective)
  2. Factor Motivator (Behavioral)
  3. Factor Important (Cognitive)

18
I Want to be Rich
  • The affective components of an attitude examine
    ones love and/or hate orientations, feelings, or
    emotions.
  • I want to be Rich.
  • Being rich is good. Rich is better than poor.
    Very few want to be poor.

19
Money Is a Motivator
  • 4 Methods Improvement in Productivity
  • Participation 0
  • Job design 9
  • Goal setting 16
  • Contingent Pay 30
  • 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).
  • Money is NOT a motivator (Herzberg, 1987).

20
Money Is Important
  • Lucrative rewards of Wall Street and the high
    compensation attract the most talented people to
    the business field. Bok (1993), formal president
    of Harvard University
  • Management professors (Gomez-Mejia Balkin,
    1992) Mental health workers change jobs (Tang,
    Kim, Tang, 2000).
  • Money literature emphasis on its importance
    (Mitchell Mickel, 1999 569).

21
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 2 Importance (Cognitive)
  • 7. Money is good.
  • 8. Money is important.
  • 9. Money is valuable.

22
The Love of Money Is
  • (1) ones wants, desires, and values of money,
  • (2) ones attitudes toward money,
  • (3) ones meaning of money,
  • (4) not ones needs, greed, nor materialism
    (Belk, 1985),
  • (5) a multi-dimensional individual difference
    variable, and
  • (6) the combined notion of several constructs or
    factors (Du Tang, 2005 Luna-Arocas Tang,
    2004 Tang Chiu, 2003 Tang, Luna-Arocas,
    Sutarso, 2005)

23
Operational definition of the Love of Money
  • This study does adopt a 9-item-3-factor Love of
    Money Scale, based on previous research (e.g.,
    Tang Chiu, 2003).
  • The love of money is a higher-order (latent)
    construct with three sub-constructs (latent
    factors) Factors Rich, Motivator, and Important.

24
Measurement Invariance
  • It does little good to test a theoretical and
    conceptual relationship across cultures unless
    there is confidence that the measures
    operationalizing the constructs of that
    relationship exhibit both conceptual and
    measurement equivalence across the comparison
    groups (Riordan Vandenberg, 1994, p. 645).

25
Measurement Invariance 9 Steps
  1. an omnibus test of equality of covariance
    matrices across groups,
  2. a test of configural invariance,
  3. a test of metric invariance,
  4. a test of scalar invariance,
  5. a test of the null hypothesis that like items
    unique variances are invariant across groups,
  6. a test of the null hypothesis that factor
    variances were invariant across groups,
  7. a test of the null hypothesis that factor
    covariances were invariant across groups,
  8. a test of the null hypothesis of invariant factor
    means across groups, and
  9. other more specific test.

26
Measurement Invariance
  • Vandenberg and Lance (2000) concluded that tests
    for configural and metric invariance were most
    often reported (p. 35).
  • Configural invariancefactor structures
  • Metric invariancefactor loadings

27
Method
The senior author recruited researchers in
approximately 50 geopolitical entities through
personal friends, contacts, or networking at
professional conferences Collaborators were
asked to collect data from 200 full-time
white-collar employees and managers in large
organizations.
28
31 Samples, N 6,498
  • (1) Australia (n 262), (2) Belgium (201), (3)
    Brazil (201), (4) Bulgaria (162), (5) China-1
    (319 university students), (6) China-2 (204
    employees), (7) Egypt (200), (8) France (135),
    (9) Hong Kong (211), (10) Hungary (100), (11)
    Italy (204), (12) Macedonia (204), (13) Malaysia
    (200), (14) Malta (200), (15) Mexico (295), (16)
    Nigeria (200), (17) Oman (204), (18) Peru (192),
    (19) Philippines (200), (20) Portugal (200), (21)
    Romania (200), (22) Russia (200), (23)
    Singapore-1 (203), (24) Singapore-2 (336), (25)
    Slovenia (200), (26) South Africa (211), (27)
    South Korea (203), (28) Spain (183), (29) Taiwan
    (200), (30) Thailand (202), and (31) the USA
    (274).

29
Measure
  • 58-item Money Ethic Scale (cf. Tang Tang, 2003)
    5-point Likert-type Scale
  • strongly disagree (1),
  • neutral (3) and
  • strongly agree (5) as anchors.
  • Participants completed the survey voluntarily and
    anonymously.

30
Evaluation criteria
  • Cronbachs alpha alpha gt .70
  • Measurement Invariance
  • (1) configural invariance ?2/df lt 3.0, TLI gt
    .90, CFI gt .90, RMSEA lt .08 and
  • (2) metric invariance (a) chi-square change
    (??2/?df) and (b) practical fit index change

31
(No Transcript)
32
Note. First, we eliminated 14 samples (printed in
bold) based on our rigorous criteria (?2/df lt
3.0, TLI gt .90, CFI gt .90, RMSEA lt .08) and
dropped 2 samples (bold and underlined) based on
low Cronbachs alpha (.70). Second, we eliminated
only 5 samples (bold) out of 31 Bulgaria,
Hungary, Malaysia, Malta, and Nigeria based on
less rigorous but acceptable criteria (?2/df lt 5,
TLI gt .90, CFI gt .90, RMSEA lt .10).
33
Configural Invariance
  • First, we eliminated 14 samples (printed in bold)
    based on our rigorous criteria (?2/df lt 3.0, TLI
    gt .90, CFI gt .90, RMSEA lt .08) and dropped 2
    samples (bold and underlined) based on low
    Cronbachs alpha (.70). Second, we retained a
    sample if it satisfied ¾ of the following four
    reasonably rigorous and acceptable criteria for
    evaluating configural invariance (?2/df lt 5, TLI
    gt .90, CFI gt .90, RMSEA lt .10). We eliminated
    only 2 samples (bold) out of 31 Malta and
    Nigeria.

34
Metric Invariance
  • The differences between unconstrained MGCFA (?2
    529.23, df 360, p .00, TLI 1.00, CFI
    1.00, RMSEA .01) and constrained MGCFA (?2
    867.43, df 444, p .00, TLI .99, CFI 1.00,
    RMSEA .02) was significant based on chi-square
    change (??2 338.20, ?df 84, p lt .05), but not
    significant based on fit index change (?CFI
    .00, n.s.).
  • We have achieved metric (factor loadings)
    invariance.

35
Discussion, Implications, Limitations
  • There was a good fit between our 9-item-3-factor
    Love of Money Scale (LOMS) and our whole sample
    involving 31 geopolitical entities.
  • We achieved configural invariance in 15 samples
    using the most rigorous criteria
  • We achieved configural invariance in 29 samples
    (our of 31) using less rigorous but acceptable
    criteria
  • We achieved metric invariance in 15 samples using
    15 samples.

36
Implications--1
  • Researchers should not take the measurement
    invariance for granted.
  • Researchers need to systematically examine the
    assumption of stable and transferable measurement
    continua (Riordan Vandenberg, 1994 666).
  • This study is an initial step in the
    cross-cultural validation of the Love of Money
    Scale.

37
Implications--2
  • This study examines the love of money across
    samples and money is the focus of our
    attention.
  • Researchers have to examine the wording or
    phrasing of items carefully when they design
    future measurement instruments (Riordan
    Vandenberg, 1994 667).

38
Implications--3
  • Cronbachs alpha examines inter-item reliability
  • Measurement invariance identifies equivalence
    across populations factor structure and factor
    loading.
  • Both contribute to our understanding of the
    measurement instrument.

39
Implications--4
  • One of the possible reasons of non-invariance is
    the composition of the samples.
  • Malaysia and Singapore-2 samples have Chinese,
    Malay, Indian, and Caucasian.
  • Singapore-1 sample has Chinese.
  • The Nigeria sample has Igbo, Yoruba, Housa, and
    other ethnic groups.

40
Other Research
  • The love of money is indirectly related to
    unethical behavior through Machiavellianism for
    Business students, male students, and male
    Business students, but not for Psychology
    students, female students, and female Psychology
    student.
  • Tang and Chens results offer some hope regarding
    the efficacy of teaching business ethics in
    business school because Business students reduce
    significantly the propensity to engage in Theft
    from Time 1 to Time 2.

41
Implications
  • Researchers and managers may have the potential
    to use the Love of Money Scale and the Propensity
    to Engage in Unethical Behavior Scale (Evil) as a
    personnel selection or an at-hire tool for
    money sensitive positions in organizations.
  • Future research may also examine the impact of
    possible training (HRD) on the love of money and
    other constructs that, in turn, may enhance
    employees ethical behaviors in organizations.
    More research is needed in this direction.

42
Limitations
  • First, there is no guarantee that the original
    meaning of these items is perfectly translated to
    the other languages.
  • Second, we have collected data from full-time
    employees in these geopolitical entities.
    However, we do not have perfect control of many
    nuisance variables
  • Third, our whole sample is reasonably large, but
    the sample from each geopolitical entity is quite
    small and does not represent a random sample or
    the average citizen of the geopolitical entity.
    We cannot generalize the findings to the whole
    population with full confidence.

43
Final Thoughts and Conclusions
  • This study offers researchers some confidence and
    insights in using the Love of Money Scale.
  • When researchers and practitioners apply the same
    tools consistently across organizations and
    geopolitical entities overtime, the cumulative
    results will enhance our abilities to understand,
    predict, and control the role of the love of
    money in organizations.

44
Thank You
  • Danke
  • Dankeshen
  • Grazie
  • Merci
  • Muchas Gracias
  • ??
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