2005_management research: from income to pay satisfaction

Management Research 2005, 3(1), 7-26. The Love of Money and Pay Satisfaction 1

FROM INCOME TO PAY SATISFACTION: THE LOVE OF MONEY AND PAY EQUITY COMPARISON AS MEDIATORS AND

CULTURE (THE US AND SPAIN) AND GENDER AS MODERATORS

Thomas Li-Ping Tang

Roberto Luna-Arocas

Toto Sutarso

The final version of this paper was published in:

Tang, T. L. P., Luna-Arocas, R. & Sutarso, T. (2005) From income to pay satisfaction: The

love of money and pay equity comparison as mediators and culture (The US and Spain)

and Gender as Moderators. Management Research, 3(1), 7-26.

ABSTRACT

This study examined a mediating model of income and pay satisfaction with a direct path

(income → pay satisfaction) and an indirect path with two mediators (income → the love of

money → pay equity comparison → pay satisfaction). Results of the whole sample showed that

the indirect path was significant and the direct path was insignificant. When the indirect path was

eliminated, income contributed positively to pay satisfaction. We then tested the model across

two moderators: culture (the United States versus Spain) and gender. This study provides the

following theoretical and empirical contributions: the direct relationship between income and

pay satisfaction depends on the indirect path and the extent to which (1) income enhances the

love of money and (2) the love of money is applied to evaluate pay equity comparison

satisfaction. If both conditions exist, income leads to pay dissatisfaction. If the second condition

does not exist, income does not lead to pay dissatisfaction. Pay satisfaction depends on (1) one’s

love of money and (2) how one compares. The role of the love of money in pay satisfaction is

“not” universal across cultures and gender.

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Keywords: Administration, Benefits, Comparison, Direct indirect path, Equity, External, Faculty,

Gender, Income, Internal, Love of Money, Mediator and Moderator variables, Motivator, Pay

Satisfaction, Raises, Spain, Structural Equation Model (SEM), Success, USA


FROM INCOME TO PAY SATISFACTION: THE LOVE OF MONEY AND

PAY EQUITY COMPARISON AS MEDIATORS AND CULTURE

(THE US AND SPAIN) AND GENDER AS MODERATORS

Money is the instrument of commerce and the measure of value. Managers around the

world use money to attract, retain, and motivate employees in organizations (Milkovich &

Newman, 2005). The meaning of money, however, is in the eye of the beholder. There is a

spirited debate regarding money as a motivator (e.g., Gupta & Shaw, 1998; Locke, Feren,

McCaleb, Shaw, & Denny, 1980) or as a hygiene factor (Herzberg, Mausner, & Snyderman,

1959; Kohn, 1998; Pfeffer, 1998)1. Organizations in the world market are increasingly interested

in reducing labor costs and increasing worker productivity and profits. Managers and researchers

are interested in employee pay satisfaction because pay dissatisfaction has “numerous

undesirable consequences” (Heneman & Judge, 2000: 77) such as turnover, low commitment,

and unethical behavior (e.g., Hom & Griffeth, 1995; Tang & Chiu, 2003).

The two most widely known models of pay satisfaction are the equity model (Adams,

1963) and the discrepancy model (Lawler, 1971). The equity model suggests that pay satisfaction

depends on the comparison of the person’s outcome-input ratio to the outcome-input ratio of a

comparison other. A greater similarity of the ratios will lead to higher pay satisfaction. The

discrepancy model examines the difference between individuals’ perceptions of the amounts of

pay that they should receive and what individuals do receive. A smaller (or larger) discrepancy

will lead to higher pay satisfaction (or pay dissatisfaction).

In the pay satisfaction literature, “one construct that should not be overlooked is the

meaning of money” (Barber & Bretz, 2000: 45). The meaning of money can be perceived as the

frame of reference in which people examine their everyday lives (Tang, 1992). For example,

high Love-of-Money employees have high voluntary turnover regardless of their intrinsic job

satisfaction. That study reveals the importance of including the love of money in turnover

research in that researchers can use the love of money to predict voluntary turnover (Tang, Kim,

& Tang, 2000). More recently, Tang, Luna-Arocas, Sutarso, and Tang (2004) have found that the

love of money is a moderator and also a mediator of the income-pay satisfaction relationship.

Following this rationale, we assert that the objective money (self-reported income), subjective

values related to money (i.e., the love of money), and pay equity comparison will play an

important role in studying pay satisfaction or dissatisfaction. The topic is ripe for reexamination.

This study examines not only the income and pay satisfaction relationship but also the

role of two mediators, the love of money and pay equity comparison, in the income-pay

satisfaction relationship using a sample of university professors in the US and Spain. Our

research questions are listed below: In general, is income related to pay satisfaction? When does

income lead to pay satisfaction or dissatisfaction? Why is income not related to pay satisfaction

in some situations? Does the love of money enhance our understanding of the income-pay

satisfaction (dissatisfaction) relationship? What roles do the two mediators (the love of money

and pay equity comparison) play in the income-pay satisfaction relationship? Does the inclusion

of the love of money improve beyond the equity comparison? Are there cross culture (the US vs.

Spain) and gender (male vs. female) differences in the income-pay satisfaction relationship?

THEORY AND HYPOTHESES

The major purpose of this study is to propose a model of income and pay satisfaction (or

dissatisfaction) based on existing literature that involves two mediators: the love of money (e.g.,


Barber & Bretz, 2000; Tang & Chiu, 2003; Tang et al., 2004) and pay equity comparison

(Adams, 1963). More specifically, we will examine a direct path (Income Pay Satisfaction)

and an indirect path with two mediators (Income the Love of Money Pay Equity

Comparison Pay Satisfaction) simultaneously using structural equation modeling (SEM)

(Figure 1). We will compare our model with the equity model (Income Pay Equity

Comparison Pay Satisfaction). We, then, test the model across two moderators: culture (the

US vs. Spain) and gender (male vs. female). We trust that our model offers contributions beyond

existing theories and recent studies in the literature (e.g., Tang & Chiu, 2003; Tang et al., 2004)

and provides a much deeper understanding of the income-pay satisfaction relationship.

Let us introduce the model first. The direct path (Income Pay Satisfaction, Figure 1,

Path 1) has been examined in many studies and is not new. Income can be defined as one’s

annual salary. Pay satisfaction is multidimensional and can be defined by Pay Level, Raises,

Benefits, and Pay Administration (Heneman & Judge, 2000). Pay level refers to the average of

the array of rates paid by an employer. Raises typically reflect additional pay offered to

employees above and beyond the employees’ previous pay level. Raises may represent the cost

of living adjustment, employee characteristics (e.g., age, performance rating, position in salary

grade), and supervisor’s own salary increase. Benefits are that part of the total compensation

package, other than pay for time worked, provided to employees (e.g., life insurance, pension,

workers’ compensation, vacation). Pay administration deals with consistency, communication,

and administration of pay policies in an organization. The literature suggests that there is a strong

pay level-pay satisfaction relationship (Heneman & Judge, 2000). In this study, we assert that

this direct path depends on the indirect path examined in Figure 1.

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Insert Figure 1 about here

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Theoretical and empirical contributions. Our first value-added theoretical and empirical

contribution is that we examine the direct path (Path 1) (Heneman & Judge, 2000) and the

indirect path (Paths 2, 3, and 4) simultaneously using structural equation modeling (SEM). This

allows researchers to examine both paths and also the impact of the indirect path on the direct

path and vice versa. Researchers can identify what, how, why, and when income causes pay

satisfaction (or dissatisfaction) directly or indirectly.

Second, the indirect path has four variables (Income the Love of Money Pay Equity

Comparison Pay Satisfaction), i.e., two mediators (the Love of Money and Pay Equity

Comparison) and three separate paths. Each variable will be defined later. More specifically, the

Income to the Love of Money path (Path 2) reflects one’s subjective perception of one’s

objective income. The Love of Money to Pay Equity Comparison path (Path 3) deals with the

extent to which one’s love of money (i.e., internal and subjective standard) will be used to judge

and evaluate Pay Equity Comparison using internal and external referents (cf. Tversky &

Kahneman, 1981). Pay Equity Comparison, in turn, will be related to Pay Satisfaction (Path 4).

Recently, Tang et al. (2004) have examined the love of money as a mediator of the

income-pay satisfaction relationship using the multiple regression approach. They have not

examined the love of money as a mediator (i.e., Income the Love of Money Pay

Satisfaction) using the structural equation modeling (SEM). Our present study differs from Tang

et al.’s (2004) study by adding a new variable, the Pay Equity Comparison, to the model as the

second mediator of the income-pay satisfaction relationship. Due to the inclusion of this variable,


we can compare our model with the equity model (Paths 5, 4, and 1, without the Love of

Money). Tang et al. (2004) performed neither these procedures nor the SEM techniques.

Third, we investigate the model across cultures (the US vs. Spain) and gender (males vs.

females) simultaneously in two separate Multi-Group Confirmatory Factor Analyses (MGCFAs)

and treat culture and gender as two moderators. These additional analyses help researchers

identify the boundaries of the model: who (male vs. female), where (the US vs. Spain), and when

(i.e., the significance of the indirect path will have an impact on the significance of the direct

path in different situations). That is, our model enables us to identify what, how, and why as well

as who, where, and when people do (or do not) experience pay satisfaction. The use of SEM does

allow us accomplishing all these goals, but multiple regression method (cf. Tang et al., 2004)

does not. We assert that the love of money is a deeply-rooted value that will play an important

and critical role in forming and judging other work-related attitudes and behaviors. We will

introduce the Love of Money first.

The Love of Money

Definition. The first question a scientific investigator must ask is not “How can I

measure it?” but rather, “What is it” (Locke, 1969: 334)? Research (e.g., Luna-Arocas & Tang,

2004; Tang & Chiu, 2003; Tang et al., 2004) suggests that the love of money can be defined (1)

as a measure of one’s values, wants (Locke, 1969), or desires of money (Sloan, 2002) and (2) as

the meaning of money (Barber & Bretz, 2000), the importance of money (Mitchell & Mickel,

1999), and one’s own personal attitudes toward money, i.e., an individual difference variable.

We examine the love of money in the context of the income-pay satisfaction relationship.

Why is it relevant? First, the love of money (an unobservable construct) has been used in

everyday lay expressions and in popular literature. The love of money is the root of evil. Those

who want to be “rich” are falling into temptation (Tang & Chiu, 2003). Very little empirical

research has examined this construct.

Second, the adaptation of Euro on January 1, 2002 in 12 European Union (EU) countries

(305 million people), the expansion of the EU from 15 to 25 countries in 2004 that creates an

economic superpower (415 million people and a 9 trillion dollar economy), the provisions of the

North American Free Trade Agreement (NAFTA), China’s accession to WTO, and other

economic developments have integrated the world economy into a single, huge free market

economy. These changes enhance the flow of money, human resources, technology, and products

and services across borders that, in turn, significantly increase the importance of money in the US

and around the world. For example, in 1978, Jurgensen found that men ranked pay the fifth and

women ranked pay the seventh in importance, among 10 items. Pay was the most important factor

for others. In 1990, among 11 work goals, pay has been ranked the second in importance in the

US and Britain and the first in Germany (Harpaz, 1990). Money, in the context of global market,

has become more important than ever in attracting, retaining, and motivating employees. We will

select the US (North America) and Spain (EU) and examine the cross-cultural differences in the

role of money (income) and the love of money in pay satisfaction.

What does it mean theoretically and empirically? Tang and Chiu (2003) examine the

Love of Money using Factors Rich, Motivator, Important, and Success. Factor Rich (the

affective component) reflects that most people want to be rich and have a lot of money. In one

study, rich people were seen, in the US at the time, as relatively healthy, happy, and well

adjusted, while the poor were seen as maladjusted and unhappy. Rich is better than poor. Factor

Motivator (the behavioral component) taps on the notion that money is a motivator (Gupta &


Shaw, 1998; Kohn, 1993). Regarding improving performance in organizations, “no other

incentive or motivational technique comes even close to money” (Locke et al., 1980: 381).

Factor Important (a cognitive component) stresses that money is important (Mitchell & Mickel,

1999). As mentioned, pay has been ranked the second in importance in the US and the UK and

the first in Germany (Harpaz, 1990). Factor Success is based on the notion that “in America,

money is how we keep score” and “income is used to judge success” (Rubenstein, 1981: 34).

Some people have “an obsession with money as a sign of success” (Furnham & Argyle, 1998:

148). Tang and Chiu (2003) found that the love of money is significantly and positively related

to unethical behaviors in organizations (i.e., Evil), whereas income (money) is not. Thus, “the

love of money is the root of evil”, but money is not. Tang and his associates (2003) tested a

three-factor Love of Money Scale (LOMS) (Rich, Motivator, and Important) and established

measurement invariance across 22 out of 26 geopolitical entities in five continents (N = 5,341)

with different languages, cultures, and religions.

In this study, we will employ Factors Success, Motivator (Tang & Chiu, 2003), and

Equity (Luna-Arocas & Tang, 2004). Factor Equity is important to pay satisfaction because the

value of a given reward is not absolute but is relative to other rewards with which it is compared

(Adams, 1963). What is fair or just is open to interpretation. Factor Equity involves individual

equity and internal equity (Milkovich & Newman, 2005).

Individual equity refers to the notion that given the same job duties and responsibilities,

individuals with higher quality and quantity of performance should be paid more than those

without. Not everyone is equally interested in individual equity. Research suggests that “males,

white-collar employees, high performers, achievement-oriented employees, and those who

already work under a merit plan” prefer merit pay (Heneman, 1992: 98) because they have the

opportunity to make more money in the system.

Internal equity deals with the pay dispersion at different levels of the organization’s

hierarchy. Men with high Love of Money tend to favor “equity” (pay based on merit) and have a

larger top/bottom pay differential in an organizational hierarchy than men with low Love of

Money (Tang, Furnham, & Davis, 2000). Women favor “equality” (equal pay) and have a small

pay differential, i.e., a small amount of pay dispersion between managers and employees. The

love of money may help us understand, predict, and control pay satisfaction.

Pay Equity Comparison

Our second mediator assesses the adequacy of their reward through a process of social

comparison, i.e., external competitiveness (Milkovich & Newman, 2005). In order to attract,

retain, and motivate employees and stay competitive, managers pay their employees more than

or equal to their competitors in the labor market. Pay referents (e.g., Bordia & Blau, 1998;

Summers & DeNisi, 1990) are defined as someone inside or outside the focal organization. This

study examines internal and external referents to evaluate pay fairness. Internal referents are

defined as other people within the department and the university. External referents are defined

as other people in comparable universities and in the labor market. In the labor market,

accounting (management) professors, for example, may use certified public accountant, CPA

(human resources manager) in business and industry as external referents.

In the US, university presidents and faculty in Research Universities have higher income

than those in Doctoral Granting I Institutions and Liberal Arts Colleges (Tang & Tang, 2003).

The pay structures are not exactly the same across public institutions and are based on

institutional characteristics and market-related variables. The popular press provides many


anecdotal examples of external referents (e.g., Tang, Luk, & Chiu, 2000). The anecdotal

examples of Michael Eisner, Bill Gates, and Michael Dell are more salient to some Americans,

while the case of Amancio Ortega, Inditex Group, however, will be more salient to some Spanish

people. People with low concern for money are less likely to compare themselves with external

referents, rich people, in particular. We assert that high Love-of-Money individuals and male

employees will be interested in external competitiveness (Heneman, 1992).

A Model of Pay Satisfaction

Income to Pay Satisfaction. “The consistency of the pay level-pay satisfaction

relationship is probably the most robust (though hardly surprising) finding regarding the causes

of pay satisfaction” (Heneman & Judge, 2000: 71). Actual pay level (income) is consistently and

positively related to pay satisfaction. The magnitude of the relationship varies from study to

study, with correlations ranging from .13 to .46. It makes intuitive sense that the higher the pay

level (income), the higher the pay satisfaction. It is easy to understand the relationships of pay

level and pay satisfaction because both are dealing with the same domain, i.e., pay. This is not

new. Following these suggestions, we will test this robust finding in Hypothesis 1a (Path 1,

Income Pay Satisfaction), when the indirect path is not considered in our model.

Hypothesis 1a: Income will be positively related to Pay Satisfaction (Path 1 only).

In this study, we assert that this direct path depends on the indirect path (see Figure 1).

We will defy the widely known facts and examine both the direct path and the indirect path using

structural equation modeling (SEM). One of the major advantages of using SEM is that we can

examine the direct and the indirect paths simultaneously. The indirect path may alter the strength

of the direct path that may create the complete mediation model (the direct path does not exist)

or the partial mediation model (both the direct and indirect paths exist).

Our theoretical and empirical contributions of this study are related to this mediating

effect. Tang and Chiu (2003) have found a significant and negative path between the Love of

Money and Pay Satisfaction (-.27) for Hong Kong professionals. That provides some clues for

our study. Pay satisfaction depends on (1) one’s love of money and (2) how one compares. We

assert that the Income to Pay Satisfaction path (the direct path) may be influenced by the indirect

path (Income the Love of Money Pay Equity Comparison Pay Satisfaction). If one

considers the Love of Money very important and uses the Love of Money as a frame of reference

when comparing their pay with the referents, then, the Income to Pay Satisfaction path may be

negative. Without comparison, one does not know whether one should be happy or sad.

Unfavorable comparisons will make one upset about one’s pay. A significant (the Love of

Money Pay Equity Comparison) path will lead to a negative direct path (Income Pay

Satisfaction). If one does not use the Love of Money as a frame of reference to compare, then,

one feels neutral or positive about one’s pay. This is the key element of our model. On the basis

of the above discussion, the income to pay satisfaction path is quite complex and may depend on

the indirect path (discussed below) in our model. Please also see our additional discussion

regarding culture and gender. Therefore, we will present our Hypothesis 1b tentatively here.

Hypothesis 1b: The Income to Pay Satisfaction relationship (Path 1) depends on the

indirect path. Income will not be positively related to Pay Satisfaction, when Paths 2, 3,

and 4 are examined simultaneously in the model.


Income to the Love of Money. This path reflects one’s “subjective” evaluation of one’s

“objective” income. Some say: Rich or poor is a state of mind and can be perceived from financial

and psychological perspectives. Professors do not have the highest value toward money and are

financially poor, compared to investment bankers. This may vary from one person to the next.

According to needs theories, unsatisfied needs are motivators, but satisfied needs are not

(Maslow, 1970). Higher income is related to lower marginal utility of money (Brandstatter &

Brandstatter, 1996). The rising tide lifts all boats. Money changes almost everything. As income

increases, some people may adjust their standard of living, expectations, tastes/preferences,

consumption, and the “frame of reference” up to a point (Tang 1992; Tversky & Kahneman,

1981). Then, money may decrease its value or utility: Money assumes decreasing importance as a

person advanced in the organizational hierarchy (Harpaz, 1990). From a global perspective, as

nations get richer, increases in wealth are associated with diminishing increases in well-being

(Ahuvia & Friedman, 1998). Within nations, increased income is associated with well-being

primarily for the poor; once the poverty threshold is crossed, increased income matters little for

happiness (Diener & Oishi, 2000). At the individual level, there is a strong negative path between

Income and the Love of Money (-.27) among highly paid Hong Kong professionals whose income

(US$47,502) was higher than the GDP per Capita ($25,100) (Tang & Chiu, 2003). They may be

rich both financially and psychologically. Satisfied needs (high income) may lead to low love of

money (a negative path between the two variables).

On the other hand, people who have experienced financial hardship tend to be obsessed

with money (Lim & Teo, 1997): The more money they have, the more they want, up to a point.

(Laboratory rats and squirrels hoard foods after experiencing hunger because they do not want to

be hungry again. Poor children overestimate the size of coins (money). After being poor, they

need more money to feel secure.) In a sample of full-time regular employees (not professors) in

the US, the Income to the Love of Money path was significant and positive for African-

Americans (.34) and females (.40) but insignificant for Caucasians (.02) and males (-.15) (Tang

& Tang, 2002). African-Americans ($32,073.15) and women ($32,400.58) tended to have lower

income than Caucasians ($37,180.73) and men ($38,287.97), respectively, in that sample. These

employees change their jobs 2.65 times in their 14.24-year career. Leavers usually receive pay at

the market value on their new jobs and about 20 percent pay increases. It pays to quit. The

significant and positive path for African-Americans and females may reveal their significant

desire to have more money (due to low income compared to others). They may feel poor

financially and psychologically. This creates a positive path. Caucasians and males (financially

adequate and psychologically adequate or rich) have an insignificant path in this sample of non-

teaching full-time employees.

We assert that the sign (positive, neutral (insignificant), or negative) of the path (Income

the Love of Money) depends on the specific sample under study, the objective measure of

money (self-reported income), and the subjective interpretation (the love of money) of the

objective measure (income), and other related demographic variables (e.g., sex and race). It varies

from one sample to the next. In this study, we will examine university professors. Professors, in

general, are “notoriously underpaid” in our society compared to other comparable jobs in business

and industry (Bok, 1993). Many professors do not change jobs after receiving tenure (i.e., risk

averse) that may lead to pay compression (pay lower than the market). If they are underpaid,

obsessed with money, and seek job mobility and more money (i.e., poor both financially and

psychologically), a positive path may exist. This is similar to African-Americans and females,


examined by Tang and Tang (2002). We assert that Americans and male professors may fall into

this category.

However, if they are relatively satisfied with the teaching profession even if they are

underpaid and do not want to change jobs and seek more money (i.e., financially poor but

psychologically adequate or rich), then, there is no relationship between the two (cf. Caucasians

and males). This argument may be applicable to females and Spanish professors in this study. For

specific groups of people in this study, see additional discussion on culture, institutional

characteristics, and gender differences. We will offer a general prediction for professors below:

Hypothesis 2: Income will be positively related to the Love of Money for professors.

The Love of Money to Pay Equity Comparison. Equity theory suggests that satisfaction

depends on the comparison of one’s output/input ratio with that of others, where the discrepancy

model focuses on the difference in pay between expectation and reality (Rice, Phillips, &

McFarlin, 1990). We argue that people may use the love of money as their “frame of reference”

in comparing their income with that of others, i.e., the framing effect (Tversky & Kahneman,

1981). On the one hand, if money is not important to them, they will pay very little attention to

it. An insignificant path is expected. On the other hand, if money is important to them, they may

pay more attention to and are constantly aware of others’ pay in the society (Pfeffer & Langton,

1993). In general, a positive path is expected.

Hypothesis 3: The Love of Money will be positively related to Pay Equity Comparison.

Pay Equity Comparison to Pay Satisfaction. Satisfaction with internal and external

referents and satisfaction with pay level, raises, benefits, and administration reflect the similar

domains of pay satisfaction. Research suggests that pay equity comparison satisfaction predicts

pay satisfaction consistently (Tang & Tang, 2002; Tang, Sutarso, Tang, & Luna-Arocas, 2001).

A positive association between the two is expected.

Hypothesis 4: Pay Equity Comparison will be positively related to Pay Satisfaction.

Equity model (without the Love of Money). So far, we have examined our proposed

model with a direct path (Income Pay Satisfaction) and an indirect path (Income Love of

Money Pay Equity Comparison Pay Satisfaction) that has two mediators. When we remove

the Love of Money from the model, it will be the traditional equity model with a direct path

(Income Pay Satisfaction) and an indirect path (Income Pay Equity Comparison Pay

Satisfaction) that has only one mediator. We assert that our proposed model with the Love of

Money will be better than the equity model. We will test the overall model below.

Hypothesis 5: Our model involving two mediators will be better than the equity model.

We will examine two moderators using the model: culture and gender. We will discuss

culture first.

MODERATORS

Culture (The US vs. Spain)

One of the most valuable frameworks regarding national cultures was develop by Geert

Hofstede. We assert that two dimensions are related to the Love of Money: (1) Individualism-

Collectivism and (2) Masculinity-Femininity. First, for the Individualism-Collectivism

dimension, the US ranked the highest (rank = 1, score = 91) on individualism and Spain ranked


15 (score = 62) (Hofstede & Bond, 1988). Individualistic societies emphasize individual

freedom. Collectivistic cultures pay attention to interactions with their fellow humans and

membership within groups or communities, consider group welfare over their own individual

welfare. Second, for the Masculinity-Femininity dimension, the US again ranked higher on

masculinity (15, score = 62) than Spain (37-38, score = 42). Masculinity can be defined by the

notions of materialism, possession, success, assertiveness, performance, advancement, and

quantity of life, whereas femininity emphasizes a concern for others, relationships, service, and

quality of life (Hofstede, 1993). Materialism is a devotion to material needs, desires, and the

importance a consumer attaches to worldly possessions (Belk, 1985). Low and high materialists

are also likely to differ in the meaning money holds for them and in money-related attitudes. Pay

level was extremely important to materialists. In this study, we do not measure and examine

Individualism and Masculinity directly. Our literature review leads us to expect that some

Americans (males in particular, discussed below), in an individualistic and materialistic society,

are more obsessed with money (i.e., have higher love of money), may judge everything from the

perspectives of money and materialistic values, and have a strong belief regarding individual

equity, internal equity, and external competitiveness (i.e., use the love of money as a frame of

reference) than their Spanish counterparts.

Institutional Characteristics

The American system. American professors in a state university have lower pay

compared to those in private universities and the market. The Association to Advance Collegiate

Schools of Business (AACSB) International provides Salary Survey Inquiry Service Report. It

showed the following pay rates for business faculty based on 30 peer institutions with

comparable size and mission of the target university in this study: full professors ($73,700),

associate professors ($60,700), and assistant professors ($56,700). The average of all AACSB

ranks (full, associate, and assistant) was $63,700. In the US, the best predictor of management

professors’ pay is the number of job changes (Gomez-Mejia & Balkin, 1992). However,

university professors are less likely to change jobs like these professionals. In industry, for

example, the post MBA median salary at Harvard was $160,000 (Merritt, 2000: 79). Compared

to $160,000, university faculty’s pay (available in the library, open to the public) is lower than

the market. With few job changes, they experience pay compression. Professors in professional

schools (e.g., business school) have higher pay than those in other colleges (e.g., Liberal Arts).

The average professor may feel that they are poor financially and psychologically (a positive

path for Income the Love of Money). People may have a stronger motivation to compare (a

positive path for the Love of Money Pay Equity Comparison) when their pay rates are not the

same. This may lead to a negative overall direct path (Income Pay Satisfaction).

The Spanish system. In Spain, there are several types of professors. Their titles in

Spanish (English), the percentage of faculty in this group, and total annual income (in 2004) are

listed below: (1) catedratico (tenured full professor with the highest rank, civil servant), 11

percent of the faculty population, €37,830.22 ($47,666.08, 1€ = $1.26), (2) profesor titular de

Universidad (tenured full professor normal rank, civil servant), 45 percent, €30,062.06

($37,878.20), (3) profesor titular de escuela universitaria (full professor normal rank, in three-

year career, mostly without Ph.D., civil servant), 12 percent, €26,461.54 ($33,341.54), (4)

professor ayudante de Universidad (full-time assistant professor, not tenured in the 8-year

promotion process, not civil servant, contract renewed every two years), 12 percent, €19,493.48

($24,561.78), and (5) professor asociado (associate professor, part-time professor from business


and industry, contract renewed every year), 20 percent, pay depends on the number of hours

taught.

The Ministry of Education has established common pay structures for professors in all

public universities in Spain. Professors’ pay will be almost the same if they have the same rank

and merit. The only differences come from civil servants’ extra courses taught in the university

or in postgraduate programs (e.g., MBA). Although they do not have a pay record that is open to

the public, faculty can obtain personal salary information via Internet through the human

resource department using personal codes. Relatively speaking, Spanish people are less likely to

change jobs than their American counterparts. Professors are rewarded according to their ranks

and additional merits and are probably “not” rewarded by changing their jobs. Very likely,

compared to American professors, Spanish professors are financially adequate (poor compared to

the market but adequate compared to other faculty) and psychologically adequate or rich (also

well respected in the society) (an insignificant path for Income the Love of Money). People

may have very little motivation to compare when their pay rates are almost the same. Researcher

argues that external competitiveness is not relevant for professors in Spanish universities.2 This

may lead to two insignificant paths (the Love of Money Pay Equity Comparison, Income

Pay Satisfaction).

We predict that American faculty will support Hypotheses 1b, 2, 3, and 4. Due to limited

research data available for Spanish faculty, we will examine these issues on an exploratory basis

and tentatively propose the following: Hypothesis 4 will be supported because Pay Equity

Comparison and Pay Satisfaction are measuring the same domain—pay satisfaction. Hypotheses

1b, 2, and 3 will not be supported due to Spanish people’s low concerns over Individualism,

Masculinity (Hofstede, 1993), and faculty’s pay stability and security.

Gender Differences (Men vs. Women) Women tend to rate social needs as more important than do men, while men tend to

consider pay more important than do women (Heneman, 1992). Men ranked pay the fifth and

women ranked pay the seventh in importance, among 10 items (Jurgensen, 1978). Women are

subjectively satisfied with their pay in spite of objective underpayment, the paradox of the

contented female worker (Crosby, 1982). That is, for some of them, they are financially poor but

psychologically adequate or rich. Women have lower pay expectations than men; have a

tendency to be equally as satisfied as men with lower pay or more satisfied than men with

equivalent pay (Sauser & York, 1978). Females have significantly lower career-entry and career

peak pay expectations than males (Major & Konar, 1984). Recent research suggests that men are

more concerned about equity (merit), whereas women are more concerned about equality (Tang,

Furnham, & Davis, 2000). Graham and Welbourne (1999) have found that women reported

higher levels of both pay level and pay structure/administration satisfaction than men, in the

traditional pay sample. This is true for women at lower salary levels. The paradox does not exist

among women and men after gainsharing is introduced. It is plausible that men have higher pay

satisfaction because men are more interested in money, equity, merit, and making extra money

(e.g., merit pay, Heneman, 1992) in the gainsharing program than women. In summary, most

female professors (financially poor but psychologically adequate or rich) are content with their

income, are not obsessed with money (an insignificant path for Income the Love of Money),

do not compare their pay with others (an insignificant path for the Love of Money Pay Equity

Comparison), and are less likely to reveal pay dissatisfaction (a non-negative path for Income

Pay Satisfaction). These paths will be significantly different for males. It appears that gender


differences are similar in the US and in Spain. We predict that Hypotheses 1b, 2, 3, and 4 will be

supported by male faculty. For female faculty, similar to Spanish faculty, Hypothesis 4 will be

supported.

METHODS

Participants

The American sample. A questionnaire was mailed to all full-time faculty members of

one public (state) Doctoral Granting I Institution in the southeastern US. Middle Tennessee State

University was founded in 1911 and had about 18,500 students and 715 full-time professors (full,

associate, assistant professors, tenured or on tenure track) at the time of our data collection. The

response rate was 28.95 percent (n = 207). Professors of the state university in the US have lower

pay compared to those in private universities and the market. For this present study, average

salary figures for both the population of the business faculty ($57,213.37) and our current

business sample ($60,392.42) were lower than the average of the AACSB data ($63,700). For the

whole sample, the average salary was $48,614.21 (Table 1). These professors have changed jobs

1.24 times in their 21.32-year career. These American professors may have suffered from pay

compression (indeed financially poor). Further, male American professors had higher income

($55,460.24) than their female counterparts ($39,348.53) (F (1, 202) = 28.32, p < .001).

The Spanish sample. We translated the questionnaire into Spanish using a multi-stage

translation-back-translation procedure. University of Valencia in Spain was founded in 1245 and

became a recognized public university “Estudi General” in 1499, comparable to other ancient

universities (e.g., Roma, Bolonia, Salamanca, and Lerida). It is the third largest public university

in Spain with about 47,000 students and 3,000 professors in three campuses (Technology,

Humanities, and Social Sciences). We surveyed a sample of professors in the Social Sciences

campus (19,132 students and 1,000 professors). The response rate was 32.5 percent (n = 104

professors) that is similar to the American sample (28.95%).

The average annual salary of our Spanish sample (collected in 1997-1998) was

$23,173.55. That average was $28,500.58 in 2004, if we aged the data by adding 3 percent for

seven years. Spanish professors’ annual salary in our sample was very similar to the average of

these four types of professors’ annual salary, €28,461.83 (or $35,861.91 in 2004). Spanish

professors have changed their jobs .82 times in their 10.41-year career. American professors

have changed jobs more often than their Spanish counterparts (F (1, 243) = 4.13, p < .05). These

Spanish professors may be paid below the market, compared to professionals in business and

industry, but not significantly underpaid (i.e., financially adequate) compared to faculty in other

universities in Spain. Male Spanish professors had higher income ($28,780.56) than their female

counterparts ($18,368.42) (F (1, 99) = 17.81, p < .001).

These two universities are similar (in terms of student and faculty on campus) but not

perfectly matched. We do not claim that these two small samples represent the population of

professors or the general public of the nation. There is no reason to believe that these two

samples are atypical. American professors may experience pay compression (financial hardship),

whereas Spanish professors may have similar but weaker experience of pay compression. Results

of this study may reflect both the culture (the US vs. Spain) and the institutional characteristics.


Measures

Professors’ age, sex, current work experience, career experience (in years), and self-

reported total annual income (in US$) were obtained. We measure the Love of Money using

three factors (Factors Equity, 3 items; Success, 2 items; and Motivator, 2 items) (Luna-Arocas &

Tang, 2004) and a five-point Likert scale with disagree strongly (1), neutral (3), and agree

strongly (5) as anchors. Pay equity Comparison was measured using a 5-point Likert scale with

very dissatisfied (1), neutral (3), and very satisfied (5) as anchors: Internal Referents were

measured using (1) colleagues in my department and (2) colleagues in my organization, while

External Referents had the following two items: (1) others at comparable organizations and (2)

others in the labor market). For pay satisfaction, we adopted the 18-item Pay Satisfaction

Questionnaire (PSQ) (Heneman & Schwab, 1985) with very dissatisfied (1), neutral (3), and very

satisfied (5) as anchors. Table 1 presents means, standard deviations, and correlations of

variables for the US and Spanish samples.

Data Analysis “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: 645). It is of supreme importance that we examined configural (factor

structures) and metric (factor loadings) invariance for all measures across cultures first.

Vandenberg and Lance (2000) have provided criteria for using Comparative Fit Index (CFI),

Tucker-Lewis Index (TLI) (.90 = the lower bound of a good fit, .95 or higher = excellent fit),

Root Mean Square Error of Approximation (RMSEA) (.08 = the upper limit of a good fit, .06 or

less = excellent fit), chi-square change (Δχ2), and fit indexes change (i.e., Δ = .01 or less:

differences between models do not exist). The path from any construct to its measured variable

equals the square root of the reliability (Cronbach’s α) of the measured variable, while the

amount of random error variable is the quantity one minus the reliability for each model.

Configural and metric measurement invariance across cultures. For the Love of Money

Scale (LOMS), we have achieved configural (factor structures, conceptual) invariance (The US,

χ2 = 12.56, df = 11, p = .32, TLI = 1.00, CFI = 1.00, RMSEA = .03, and Spain, χ

2 = 16.66, df =

11, p = .12, TLI = .99, CFI = 1.00, RMSEA = .07) and metric (factor loadings, measurement)

invariance using Multi-Group Confirmatory Factor Analysis (MGCFA) based on both the

Likelihood Ratio (LR) test or the chi-square change (Δχ2 = 5.61, Δdf = 4, p > .05) and fit indexes

change (ΔCFI, ΔTLI, and ΔRMSEA = 0) between unconstrained (χ2 = 29.26, df = 22, p = .14,

TLI = 1.00, CFI = 1.00, RMSEA = .03) and constrained model (χ2 = 34.87, df = 26, p = .11, TLI

= 1.00, CFI = 1.00, RMSEA = .03) (Table 2) (Vandenberg & Lance, 2000). We will not repeat

similar results for Pay Equity Comparison and Pay Satisfaction Questionnaire (see Table 2).

American professors had stronger factor loadings for External Referents (.95 and .93) than

Internal Referents (.74 and .82), whereas Spanish professors had stronger factor loadings for

Internal Referents (.84 and .84) than External Referents (.79 and .75).

Harman’s one factor test. Researchers suggest that common method variance is a

potential problem in behavioral research (Podsakoff, MacKenzie, Lee, & Podsakoff, 2003: 879).

Our data were collected from a single source at one point in time. In order to examine the

possible common method variance biases, we conducted Harman’s one factor test (e.g.,

Podsakoff et al., 2003) and examined the unrotated factor solution involving all variables of


interest (29 items) in an exploratory factor analysis (EFA) to determine the number of factors

that are necessary to account for the variance in the variables. Our exploratory factor analysis

(EFA) results showed seven factors. The amount of variance explained for the seven individual

factors (36.11%, 8.50%, 7.18%, 5.43%, 4.76%, 4.01%, and 3.57%, respectively) suggested that

no single factor accounted for the majority of the covariance in the independent and criterion

variables. We assert that since all three measures are well developed instruments with proven

psychometric properties, they are likely resistant to common method variance (e.g., Spector,

1987). Therefore, common method variance was not solely responsible for our findings.

RESULTS

Multivariate analysis of variance (MANOVA) results (F (3,307) = 16.48, p < .001) showed

that American professors had higher interests in Factors Equity (3.66) and Success (2.93) than

their Spanish counterparts (3.05, 2.57, respectively). Men scored higher on Factors Equity (3.60)

and Success (2.99) than women (3.29, 2.63, respectively) (F (3, 301) = 5.80, p < .001),

supporting research findings in the literature. Income was significantly correlated with Pay Level

satisfaction for both American (.34) and Spanish (.26) professors, supporting the literature

(Heneman & Judge, 2000). Professors had higher satisfaction with two Internal Referents than

External Referents in the US (2.94 vs. 2.54) and in Spain (3.04 vs. 2.72, respectively) (p < .001).

Step One: The Whole Sample (Our Model vs. The Equity Model)

Model 1 (Figure 1) examined all four major variable and all six paths among variables

(i.e., the default model). Results of Model 1 showed the following data: χ2 = 165.49, df = 36, p <

.01, TLI = .98, CFI = .98, RMSEA = .11. We, then, evaluated the relative contributions of Paths

1, 2, 3, and 4 of the model. In Model 2, we set Paths 1, 2, 3, and 4 to zero. When several paths

are removed from the model (i.e., set the paths to zero), the new model (Model 2) will have less

power to explain the relationships among the variables. If the chi-square value increases

significantly relative to the degree of freedom after removing several paths, then, the new model

(Model 2) becomes significantly worse than original model (Model 1). We compared Model 2

(χ2 = 386.53, df = 40, p < .01, TLI = .94, CFI = .96, RMSEA = .17) with Model 1 and found that

Model 2 was significantly worse than Model 1 (the default model) (Δχ2 = 221.04, Δdf = 4, p <

.01), suggesting that Paths 1, 2, 3, and 4 contributed significantly to the model. Next, in order to

identify our theoretical model (Model 3), we estimated Paths 1, 2, 3, and 4 and set Paths 5 and 6

to zero. Results suggested that there was a good fit between our Model 3 and our data (χ2 =

171.62, df = 38, p < .01, TLI = .98, CFI = .98, RMSEA = .11). Further, Model 3 was more

parsimonious than Model 1.

We now examined the equity model. In Model 4, we set Paths 1, 5, and 4 to zero (χ2 =

216.32, df = 39, p < .01, TLI = .97, CFI = .98, RMSEA = .11). Model 4 was significantly worse

than Model 1 (Δχ2 = 50.83, Δdf = 3, p < .00). Thus, Paths 1, 5, and 4 made significant

contributions to the model. We then, estimated the paths of the equity model (Model 5) that

involved only Paths 1, 5, and 4 (set Paths 2, 3, and 6 to zero). The equity model, Model 5,

showed: χ2 = 186.44, df = 39, p < .01, TLI = .98, CFI = .98, RMSEA = .11.

Next, we compared our theoretical model with the equity model. Our theoretical model

(Model 3) was significantly better than the equity model (Model 5) (Δχ2 = 186.44 – 171.62 =

14.82, Δdf = 1, p < .01) and more parsimonious than Model 1. Thus, we adopted Model 3.

Hypothesis 5 was supported.


A mediating model. A path is significant (p < .05, .01, .001) when the critical ratio, C.R.,

is greater than or equal to 1.96, 2.58, 3.50, respectively. Figure 2 shows that the indirect path was

significant (Income the Love of Money, path = .41, critical ratio = 4.95, p < .001; the Love of

Money Pay Equity Comparison, .29, C.R. = 3.04, p < .01; and Pay Equity Comparison Pay

Satisfaction path, .86, C.R. = 14.75, p < .001), whereas the direct path was not significant

(Income Pay Satisfaction, .02, C.R. = .41, n.s.). Our results support the complete mediation

model (Hypotheses 2, 3, and 4). The direct path (Hypothesis 1b) was not significant due to the

combination of two samples and our indirect path. Income explained 16 percent of the Love of

Money (i.e., path = .405, .4052 = .16). The Love of Money explained 8 percent of Pay Equity

Comparison. Income and Pay Equity Comparison explained 75 percent of pay satisfaction. Both

the indirect path (.41 x .29 x .86 = .10) and the direct path (.02) contributed positively to Pay

Satisfaction (.10 + .02 = .12).

Income to Pay Satisfaction (Path1). We examined specifically the Income to Pay

Satisfaction path using the model and the full sample by setting all other paths to zero in a

separate analysis. Results suggested that the Income to Pay Satisfaction path was positive and

significant (.19, C.R. = 3.06, p < .01) (χ2 = 395.62, df = 41, p < .01, TLI = .94, CFI = .94,

RMSEA = .17). Hypothesis 1a was supported. Our direct path alone, of course, supported the

commonly held belief in the literature (Heneman & Judge, 2000). With that said, our model

provides additional information beyond the robust pay level-pay satisfaction relationship.

Theoretical and empirical contributions. Our model offers the following contributions.

First, when we examine only the direct path (Income Pay Satisfaction), income is positively

related to pay satisfaction. As suggested in the literature, higher income leads to higher pay

satisfaction. Second, when we examine both the direct path and the indirect path simultaneously,

then, the direct path is insignificant and the indirect path is significant. In other words, higher

income does not lead to higher pay satisfaction directly. Instead, higher income is indirectly

related to pay satisfaction through the love of money and pay equity comparison. These results

provide the elements and factors (i.e., the “what” issue) that may cause pay satisfaction or

dissatisfaction. If organizations pay employees more money, employees should have higher pay

satisfaction. This is not always the case, however. Researchers and managers have long been

aware of the fact that pay is a hygiene factor for some (Herzberg et al., 1959). Herzberg pointed

out that pay satisfaction goes back to zero and the zero point escalates.

We cannot look at the direct income-pay satisfaction relationship alone. When we add the

love of money and pay equity comparison to the indirect path of the model, the direct path

becomes insignificant. This explains the issue of “when” income will (or will not) lead to pay

satisfaction. Further, the indirect path shows that (1) income enhances the love of money and (2)

the love of money is applied to evaluate pay equity comparison satisfaction. If both conditions

exist, income does not lead to pay satisfaction, for the whole sample. The income-pay

satisfaction relationship depends on (1) one’s love of money and (2) how one compares. This is

the step-by step process of “how” and “why” income does not lead to pay satisfaction. This

shows the importance of focusing on employee’s love of money and their equity comparison

when we examine the income-pay satisfaction relationship.

Step Two: Culture (the US vs. Spain) as a Moderator

We analyzed the same model across culture using American and Spanish data

simultaneously in a Multi-Group Confirmatory Factor Analysis (MGCFA) (χ2 = 223.35, df = 76,

p < .01, TLI = .98, CFI = .98, RMSEA = .08) and found that RMSEA had improved from .11


(the whole sample in Step 1) to .08 (Step 2, the upper limit of a good fit). We will present the

American and Spanish results below (see Figures 3 and 4).

The American professors. Income explained 23 percent of the Love of Money (Figure

3). The Love of Money explained 24 percent of Pay Equity Comparison. Pay Equity Comparison

and Income explained 88 percent of Pay Satisfaction. All the paths in our model were significant:

Income to the Love of Money (.48, p < .001), the Love of Money to Pay Equity Comparison

(.49, p < .001), Pay Equity Comparison to Pay Satisfaction (.96, p < .001), Income to Pay

Satisfaction (-.18, p < .001).

Income led to high pay dissatisfaction. This finding is different from the general

perceptions in the literature (Heneman & Judge, 2000). Structural equation modeling technique

(SEM) allows researchers to examine the relationships among all the constructs specified in the

structural equation model, i.e., the indirect path and the direct path and the correlations among

variables, simultaneously. Money is the instrument of commerce and the measure of value.

Value is that which a person “actually seeks to gain and/or keep or considers beneficial” (Locke,

1969: 318). Moreover, values rather than expectations determine satisfaction (Locke, 1969). The

love of money reflects one’s deeply-rooted values toward money. When we examine the whole

model, income leads to pay dissatisfaction that can be explained by the indirect path: American

professors’ income significantly enhances the importance for the love of money. The more

(income) they have, the more they want (the love of money). Professors with the love of money

orientation are concerned about money and pay equity comparison. They refer the love of money

as a frame of reference to judge pay equity comparison. Pay equity comparison is directly related

to pay satisfaction. In short, the love of money (i.e., value) determines (causes) pay

dissatisfaction.

Results support the indirect path and the direct path (Hypotheses 1b, 2, 3, and 4). Factors

Equity (.36), Success (.37), and Motivator (.39) represented the latent construct of the Love of

Money. External Referents (.86) and Internal Referents (.82) revealed the construct of Pay

Equity Comparison. Satisfactions with Pay Administration (.85), Raises (.78), Pay Level (.75),

and Benefits (.74) expressed the construct of Pay Satisfaction. Thus, American people pay less

attention to Benefits in organizations.

--------------------------------------------------------------------------------

Insert Tables 1 and 2 and Figures 2, 3, and 4 about here

--------------------------------------------------------------------------------

Income to Pay Satisfaction. We performed one additional analysis by examining only

the income to pay satisfaction path across countries (and set all other paths to zero) (χ2 = 469.03,

df = 82, p < .01, TLI = .94, CFI = .94, RMSEA = .12). Results suggested that Path 1 (Income

Pay Satisfaction) for American professors was in the predicted direction of Hypothesis 1a but not

significant (.13, C.R. = 1.78). There was no relationship between income and pay satisfaction.

Hypothesis 1a was not supported.

Spanish professors. Income explained only 3 percent of the Love of Money that, in turn,

explained 2 percent of Pay Equity Comparison (Figure 4). Pay Equity Comparison and Income

explained 57 percent of Pay Satisfaction. Results showed: Income to the Love of Money (.18,

n.s.), the Love of Money to Pay Equity Comparison (.13, n.s.), and Pay Equity Comparison to

Pay Satisfaction (.74, p < .001). Income to Pay Satisfaction path was positive but not significant

(.14, n.s.): Income led to mild (insignificant) pay satisfaction. Please recall that income led to

significant pay dissatisfaction for American professors. Our cultural differences reflect the


“where” and “who” issues of our theoretical model. These results may help us understand the

insignificant Path 1 for the whole sample (the US and Spain combined).

Factors Motivator (.61), Success (.49), and Equity (.39) represented the latent construct

of the Love of Money. External Referents (.65) and Internal Referents (.62) revealed the

construct of Pay Equity Comparison. Benefits (.81), Pay Administration (.76), Raises (.73), and

Pay Level (.70) expressed the construct of Pay Satisfaction. Results supported Hypothesis 4, as

expected. It appears that Factor Motivator is the most important element of the Love of Money

Scale for both American and Spanish professors. Regarding Pay Satisfaction, American

professors focus on Pay Administration and Raises, whereas Spanish professors are concerned

about Benefits and Pay Administration.

Income to Pay Satisfaction. Again, the direct relationship between income and pay

satisfaction for Spanish professors was in the predicted direction, but not significant (.17, C.R. =

1.57, n.s.) when all other paths were set to zero. Thus, without the indirect path, there was no

relationship between income and pay satisfaction for Spanish and American professors.

Hypothesis 1a was not supported.

Step Three: Gender (Male vs. Female) as a Moderator

We analyzed male and female professors simultaneously in a MGCFA (χ2= 216.37, df =

76, p < .01, TLI = .98, CFI = .98, RMSEA = .08). We will present results regarding male

professors first and then female professors in this section.

Male professors. Income explained 31 percent of the Love of Money that, in turn,

explained 21 percent of Pay Equity Comparison. Pay Equity Comparison and Income explained

78 percent of Pay Satisfaction. All indirect paths were significant (Income the Love of

Money, .56, p < .001; the Love of Money Pay Equity Comparison, .46, p < .01; and Pay

Equity Comparison Pay Satisfaction, .89, p < .001). The Income to Pay Satisfaction path was

not significant (-.03, n.s.). Results supported the indirect path (Hypotheses 2, 3, and 4).

Female professors. Income explained 3 percent of the Love of Money that, in turn,

explained 7 percent of Pay Equity Comparison. Pay Equity Comparison and Income explained

79 percent of the Pay Satisfaction. Income to the Love of Money path (.18, n.s.), the Love of

Money to Pay Equity Comparison path (.26, n.s.), and Income to Pay Satisfaction path (.13, n.s.)

all failed to reach significance. The only significant path was the Pay Equity Comparison to Pay

Satisfaction path (.87, p < .001). Results supported Hypothesis 4. These gender differences

reflect the “who” aspect of our theoretical model.

Step Four: Gender Differences Within the US and Spanish Cultures

We analyzed male and female professors simultaneously within each culture in two

separate analyses. We will present the US results first.

Male vs. female in the US. For male professors in the US (χ2= 180.66, df = 76, p < .01,

TLI = .97, CFI = .98, RMSEA = .08), Income explained 34 percent of their Love of Money that,

in turn, explained 50 percent of Pay Equity Comparison. Pay Equity Comparison and Income

explained 88 percent of Pay Satisfaction. The indirect path and the direct path were all

significant (Hypotheses 1b, 2, 3, and 4). For female professors in the US, Income explained 8

percent of their Love of Money that, in turn, explained 12 percent of Pay Equity Comparison.

Pay Equity Comparison and Income explained 93 percent of Pay Satisfaction. Only one path was

significant: Pay Equity Comparison to Pay Satisfaction (.97, p < .01) (Hypothesis 4).


Male vs. female in Spain. Spanish data suggested (χ2= 123.07, df = 76, p < .01, TLI =

.98, CFI = .98, RMSEA = .08) that for male Spanish professors, Income explained 36 percent of

their Love of Money that, in turn, explained 1 percent of Pay Equity Comparison. Pay Equity

Comparison and Income explained 58 percent of Pay Satisfaction. The only two significant paths

were Income to the Love of Money (Hypothesis 2) and Pay Equity Comparison to Pay

Satisfaction (Hypothesis 4). For female professors in Spain, Income explained 4 percent of their

Love of Money that, in turn, explained 7 percent of Pay Equity Comparison. Pay Equity

Comparison and Income explained 41 percent of Pay Satisfaction. Again, only one path was

significant: Pay Equity Comparison to Pay Satisfaction (.63, p < .01). Hypothesis 4 was

supported. Our cultural and gender differences reflect the “where” and “who” issues of our

theoretical model.

Summary. The Income to the Love of Money path is significant for faculty in the US,

male faculty in the US, and male faculty in Spain. Income increases men’s love of money but not

women’s, a gender-specific (emic) path. The Love of Money to Pay Equity Comparison path is

significant for the US sample, male faculty, and male American professors. This result comes

from one source: Male American professors use the Love of Money as a “frame of reference” in

evaluating Pay Equity Comparison, a culture-specific and gender-specific (emic) path. There is

one cultural-free and gender-free (etic) path (Pay Equity Comparison Pay Satisfaction). These

cross culture (the US vs. Spain) and gender (male vs. female) results provide information

regarding the “where” and “who” aspects of our model. Income leads to pay dissatisfaction

among American professors and male American professors. The two significant paths (Income

the Love of Money and the Love of Money Pay Equity Comparison) are the prerequisites

for, or harbingers of, pay dissatisfaction. Further, the Love of Money to Pay Equity Comparison

path is the most critical one to pay dissatisfaction. When the Love of Money is a mediator of this

indirect path, Income leads to Pay Dissatisfaction. For female professors and professors in Spain,

Income has no impact on the Love of Money that, in turn, does not influence Pay Equity

Comparison. In this case, the Love of Money is not a “frame of reference” in evaluating pay

satisfaction and, thus, is not a mediator. This findings offer clear explanations regarding “what”,

“how”, “why, and the “who”, “where”, and “when” issues of pay satisfaction or dissatisfaction.

DISCUSSION

In this study, we propose a model of pay satisfaction and test the model using a direct

path and an indirect path. Our model with the two mediators (the Love of Money and Pay Equity

Comparison) is better than the equity model (with only one mediator, without the Love of

Money). When we examine both the direct and the indirect path for the whole sample, the

indirect path (Income the Love of Money Pay Equity Comparison Pay Satisfaction) is

significant and the direct path is insignificant. When we consider the direct path alone, income is

positively related to pay satisfaction. Then, we test the model across two moderators: cultures

and gender.

The Income to the Love of Money path is significant for Americans but not significant

for Spanish counterparts. We speculate that American professors in this sample may have the

feeling that they are poor financially and psychologically, whereas Spanish professors are

financially and psychologically adequate. Future research needs to test this hypothesis directly.

Based on gender within cultures, income does explain men’s love of money (the US: 34%;

Spain: 36%) more than that of women’s (the US: 8%; Spain: 7%). The impact of income on the

love of money is very similar for American professors (men: 34%; women: 8%) and for Spanish


professors (men: 36%; women: 7%). It appears that this is a culture-free (etic) path for the

present samples in these two cultures. Regarding gender differences (the US and Spain

combined), our research supports the notion that females in general have lower love of money

(8%) than their male counterparts (31%). Moreover, regarding culture differences, Americans

have higher love of money (23%) than their Spanish counterparts (3%). For the whole sample, it

makes sense that the impact of income on the love of money is 16 percent due to the different

sample size in the US (N = 207) and Spain (N = 104). Future research may test this hypothesis in

other professions, organizations, and cultures.

The Love of Money to Pay Equity Comparison path is not significant for Spanish

professors, but is significant for American professors. Further, this path is significant for only

male Americans but not for female Americans. Moreover, the Income to Pay Satisfaction path is

not significant for Spanish professors and is negative and significant for American professors,

male American professors, in particular. Spanish professors are significantly younger and have

lower level of experience (on their jobs and in their careers) and less job changes than their

American counterparts. Spanish professors have high job stability and security as civil servants

that may have some impacts on their perceptions of their job, their remuneration, and in their pay

satisfaction. It is plausible that since faculty pay has been very well established by the Ministry

of Education, the Love of Money does not play a role and serve as a frame of reference to

evaluate their Pay Equity Comparison in our model (see our discussion on institutional

characteristics). It is easy for Spanish professors to know the salary of others in the same

category. The Love of Money to Pay Equity Comparison path is not significant for Spanish

faculty. Thus, their income does not lead to pay dissatisfaction. For American professors, they do

have significant results in both paths.

Herzberg claimed that salary has potency as a job dissatisfier (Herzberg et al., 1959). Our

results suggest that his claim does apply to American professors, male American professors, in

particular, but not to the Spanish sample. Spanish professors may have similar salary

“information” as their American counterparts. Spanish professors do not compare, whereas

Americans do. Our model suggests: When the Love of Money to Pay Equity Comparison path is

not significant, then, the Income to Pay Satisfaction path is not significant, supporting previous

findings (Tang & Tang, 2002).

Conclusion A good theory will examine what, how, why, and who, where, and when. What are the

causes of pay satisfaction (or dissatisfaction)? How, why, and when (under what condition) do

these variables cause pay satisfaction (or dissatisfaction)? Does the model provide the same or

different information across culture (where) and gender (who) and conditions (when)? Our

model provides the following theoretical and empirical contributions: When we examine only the

direct path (Income Pay Satisfaction) for the whole sample, then, income leads significantly

to pay satisfaction, supporting the extent literature. We examine both the direct path and the

indirect path simultaneously, and test the model across culture, gender, and gender within

culture. We find that the direct path depends on the indirect path (Income the Love of Money

Pay Equity Comparison Pay Satisfaction) and the extent to which (1) income enhances the

love of money and (2) the love of money is applied to evaluate pay equity comparison

satisfaction. If both conditions exist, income leads to pay dissatisfaction (a significant and

negative path). If the second condition does not exist, income does not lead to pay

dissatisfaction. The role of the Love of Money in pay satisfaction is “not” universal across


cultures and gender. Pay satisfaction depends on (1) one’s love of money and (2) how one

compares. Our model examines not only what causes pay satisfaction or dissatisfaction but also

how and why as well as who, where, and when people do (or do not) experience pay satisfaction,

beyond motivator-hygiene theory, equity theory, and discrepancy theory. This paper contributes

significantly beyond several recent research papers in the literature (e.g., Luna-Arocas & Tang,

2004; Tang & Chiu, 2003; Tang et al., 2004).

Implications

In the US, universities (private universities, in particular) set their own tuition (Tang,

Tang, & Tang, 2004) and pay their university presidents and professors based on the type of

institutions (e.g., Research, Doctorate-Granting Institutions, Liberal-Arts Institutions), size, the

supply and demand in the market, reputation rankings in the country, and other factors (Tang &

Tang, 2003). The best predictor of American management professors’ pay is the number of job

changes (Gomez-Mejia & Balkin, 1992). Further, the highest correlate of job moves is top-tier

publications. Thus, research productivity leads to labor mobility and high income. As we

mentioned, no other incentive or motivational technique comes even close to money (Locke et

al., 1980). When there is a difference in pay, then, money (or income) will become one of the

most salient factors in people’s perceptions.

Administrators, faculty, and researchers are increasingly interested in improving

scholarship, research productivity, and efficiency in delivering services to university students.

When the reward systems (remuneration policies) are related to academic reputation and faculty

productivity, it creates different impacts on people: High performers will have the opportunity to

make more money and are happier with frequent job changes than low performers. One

important implication for prestigious private (or public) universities is that they may use

significant amounts of pay to attract top faculty members with top-tier publications and to

increase the reputation of the university. External competitiveness allows administrators to

attract, retain, and motivate top talents in higher education. It is plausible that those with high

Love-of-Money, talents, and research productivity will work hard and identify the opportunities

of their next move in their careers.

In Spain, since December of 2002, there has been a new "Law for the Organization of

Universities" (Ly Organica de Universidades, LOU). That law changes the procedures of

obtaining professorship in the promotion process. One of the major purposes of this change is to

offer opportunities for candidates of professors in the promotion process to move around among

different universities and to solve the past problems. Many professors get promoted to the top

rank within the same university without having much or any experience in teaching and research

in other universities. These professors may have stayed in the ivory tower for life and lost the

contact with the real world of work and professors in other universities. That complacency may

kill professors’ innovation, creativity, and research productivity.

The system of higher education in Spain has been fairly consistent and stable for all

professors. There has been very little motivation to improve research productivity and compare

their pay because the pay is the same in the system. Therefore, external competitiveness for

professors in Spanish universities is not relevant in the past. Due to these perceptions,

institutional supports to the universities are getting even lower, compared to other countries. For

example, recent data reveal that the percentage of GDP per Capita devoted to “education” in the

European Union (EU) in 2000 was 5.4 percent. In Spain, it was lower (4.3%) than the EU figure.


It is plausible that the new law, LOU, may create some changes for Spanish professors in

the future. One of the important implications is that researchers and administrators need to

investigate the impacts of these changes on professors’ pay satisfaction, perceptions of the new

university systems, and research productivity. Indeed, many universities have problems to retain

good students to stay in the systems of higher education and to become professors in Spain

because salaries in the market are higher than that in the university. In a recent study, Luna-

Arocas (1999) compares a sample from the general public with a simple from university faculty.

Indeed, results of cluster analysis (segmentation) suggest that there are three clusters of

professors: (1) Intrinsic Teachers (motivated mainly by intrinsic motivation, 33%), (2) Power

and Money Worshipers (30%), and (3) Money Worshipers (37%). In fact, 67 percent of these

Spanish professors (Clusters 2 and 3 combined) are really concerned about money and interested

in money while doing their work. Spanish professors have the perception that their efforts and

talents are not being recognized in the past. Thus, administrators cannot afford to overlook the

importance of money attitudes, the Love of Money, and external competition, in particular, in the

future.

Money does attract top talents to move across borders in the global market of higher

education. For the last decade, anecdotal evidences suggest that many English-speaking

professors have offered their services in Hong Kong and Singapore, for example. After Hong

Kong returned back to China in 1997, some came back to the US recently due to slow economy,

faculty salary freeze, and the lack of funding and support in Hong Kong. In Great Britain,

historically, funding for most of the universities has come from the states. The lack of funding,

however, leads to a decline of quality in higher education. Currently, British universities are 80

million dollars in the red. Tony Blair’s Labor Government will impose tuition on public higher

education. Under the plan, British students are required to pay the tuition (about $8/week for

about 10-15 years, interest free) when they start to earn an income equal to the national average.

Under the current crisis of brain drain, many top Cambridge professors quit their jobs and teach

in American universities. Some called it the Americanization of the British educational system

(NPR news, 2003, December 10). The switch will be easier for British professors than for

Spanish professors, due to the common English language. These changes will be an emerging

trend around the world. Thus, people do pay attention to external competitiveness, pay equity

comparison, and compare their pay with that of others in the market. The love of money is the

major cause of voluntary turnover (Tang et al., 2000). It pays to quit. More research is needed in

this direction.

Limitations Cross-sectional data collected at one time may reflect the artifacts of the common method

variance (Podsakoff et al., 2003). We employ the following techniques for controlling common

method biases: (1) adopt well developed instruments with proven psychometric properties that

are likely to resist the common method biases (e.g., Spector, 1987), (2) protect anonymity (do

not write one’s name on a survey), and (3) select appropriate scale items. We, further, apply the

following statistical remedies in our data analysis regarding the common method biases: (4)

Harman’s single-factor test (exploratory factor analysis, EFA), (5) confirmatory factor analysis

(CFA) for all measures, and (6) configural and metric invariance across cultures. Our results

suggest that the method effects were insignificant.

We have selected only one public university in each country. These two institutions are

not perfectly matched. Our results may reflect not only cultural and economic differences of the


US and Spain but also the characteristics of these two institutions. Our samples (professors) are

potentially restricted to individuals who do not have the highest value toward money. Caution is

warranted when we examine the gender differences within the cultures due to the small sample

size. Factors Equity, Success, and Motivator cover only a small part of the equity concern and

the Love of Money and money attitudes.

Money may become an escalating moving target. Higher “labor rates” may lead to lower

“labor costs” due to employees’ high productivity (Pfeffer, 1998). Individual incentive pay

undermines performance—of both the individual and the organization (Pfeffer, 1998).

Compensation managers need to pay employees as much as they can so that employees can take

their mind off money (Kohn, 1998), balance the intrinsic motivation (the labor-of-love, Amabile,

1998) and extrinsic reward, and create a positive culture in organizations. Pay has substantive

and symbolic components. The love of money is dynamic. This study reveals a “robust”

phenomenon regarding the role of the Love of Money in our understanding of pay satisfaction,

culture, and gender differences. Future research may want to incorporate additional variables,

use longitudinal data, examine people in other professions (e.g., medical doctors, lawyers,

professional athletes, CEOs, and investment bankers), and examine the culture-free (etic) and

culture-specific (emic) constructs around the world.

Footnote: 1According to the motivator-hygiene theory (Herzberg et al., 1959), pay is a hygiene

factor. Pay may cause long-term (lasted for years) job dissatisfaction, but only short-term (less

than two weeks) job satisfaction. It is the context in which one does one’s work. Managers need

to pay employees monthly in order to sustain their lives (i.e., personal hygiene, like food, water,

air, etc.) and get their minds off pay (Kohn, 1998). The satisfaction of pay goes back to zero at

the end of the month. The zero point escalates: one always wants more money. Pay is not a valid

contributor to psychological growth (a motivator). People do not work “primarily for money”

(Pfeffer, 1998: 111); they also seek the meaning in life. 2We would like to thank Reviewers for providing constructive comments regarding this point.


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Money and Pay Satisfaction 26

TABLE 1

Means, Standard Deviations, and Correlations of Major Variables

____________________________________________________________________________________________________________________________

US Spain

Variable M SD M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14

____________________________________________________________________________________________________________________________

1. Age 47.19 9.69 33.56 9.11 31* 83** 95** 74** -13 19 -11 -07 -01 12 01 –12 -08

2. Sex .57 .50 .48 .50 31** 15 33** 39** 20** 14 –02 –14 –10 –17 –11 –17 –09

3. Experience 11.62 9.97 6.85 7.20 68** 26** 81** 65** -06 08 –12 05 –01 24* 05 –13 06

4. Career 21.32 10.41 10.41 8.95 88** 24** 66** 77** -06 23* -12 –11 –04 12 –01 –19 -04

5. Income 48,614.21 23,293.76 23,173.55 13,653.76 49** 35** 34** 46** 04 21* 03 04 02 26* 16 –05 15

6. Equity 3.66 .79 3.05 .80 04 14* -02 05 27** -04 20* 01 05 –10 –01 –02 15

7. Success 2.93 1.04 2.57 1.05 07 17* -02 12 17* 17* 40** -05 14 07 05 15 21*

8. Motivator 3.55 .86 3.57 .78 -04 08 -10 -06 -02 14 32** -03 –06 07 22* 19 27**

9. Internal 2.93 1.04 3.05 .93 19** 05 -00 17* 34** 12 16* 13 41** 43** 23* 32* 35**

10. External 2.54 1.07 2.74 .84 14 04 05 17* 29** 07 13 09 71** 33** 32** 36** 50**

11. Pay 3.06 1.09 3.12 .94 19** 04 10 21** 34* 19** 05 -03 72** 72** 71** 51** 47**

12. Benefits 3.47 .90 2.90 .69 -05 -08 -05 -00 04 21** 02 09 46** 54** 58** 64** 56**

13. Raise 2.78 .87 2.67 .63 -05 -10 -07 -02 -01 01 -03 00 54** 58** 68** 53** 54**

14. Administration 2.66 .76 2.56 .72 02 -07 01 06 08 13 09 11 62** 63** 64** 57** 67**

_______________________________________________________________________________________________________________________

Note. N varied between 184 and 209 for the US sample and between 86 and 101 for the Spanish sample. All decimal points

for correlations were omitted. Correlations for the US sample were presented at the lower left corner and the Spanish

sample at the upper right corner. Sex was a nominal variable, Female = 0, Male = 1. Experience = Years of experience in

current organization. Career = Experience in whole career.


TABLE 2

Results of Configural and Metric Measurement Invariance

__________________________________________________________________________________

Lambdas*

Item US Spain

__________________________________________________________________________________

The Love of Money Scale

Factor 1: Equity

1. People on the same job should be paid equally (equality). .35 .33

2. People on the same job should be paid based on merit (equity). .93 .87

3. Lower-level job with little responsibility should be paid less. .23 .21

Factor 2: Success

4. Money is a symbol of success. .77 .77

5. Money represents one’s achievement. .84 .90

Factor 3: Motivator

6. Money is a motivator. .48 .59

7. I am motivated to work hard for money. .92 .95

Note. Item 1 was reverse scored.

Phase 1. Configural invariance (factor structures across cultures) was achieved: The US (χ2

=

12.56, df = 11, p = .32, TLI = 1.00, CFI = 1.00, RMSEA = .03), Spain (χ2

= 16.66, df = 11, p =

.12, TLI = .99, CFI = 1.00, RMSEA = .07). Phase 2. Metric invariance (factor loadings) was

achieved (Δχ2 = 5.61, df = 4, p > .05; ΔCFI = .00) between unconstrained (χ

2 = 29.26, df = 22, p

= .14, TLI = 1.00, CFI = 1.00, RMSEA = .03) and constrained MGCFA (χ2= 34.87, df = 26, p =

.11, TLI = 1.00, CFI = 1.00, RMSEA = .03). *Lambdas were based on constrained MGCFA.

__________________________________________________________________________________

Pay Equity Comparison

Factor 1: Internal Referents

1. Compared with colleagues in my department .74 .84

2. Compared with other colleagues in my organization .82 .84

Factor 2: External Referents

3. Compared with others at other comparable organizations .95 .79

4. Compared with other colleagues at the labor market .93 .75


=

3.19, df = 1, p = .07, TLI = .99, CFI = 1.00, RMSEA = .10), Spain (χ2

= 1.53, df = 1, p = .22, TLI

= .99, CFI = 1.00, RMSEA = .07). Phase 2. Metric invariance (factor loadings) was not achieved

based on Δχ2 = 16.65, df = 2, p < .05, but achieved based on ΔCFI = .01, between unconstrained

(χ2 = 4.72, df = 2, p = .09, TLI = .99, CFI = 1.00, RMSEA = .07) and constrained MGCFA (χ

2=

21.61, df = 4, p = .00, TLI = .97, CFI = .99, RMSEA = .12).

__________________________________________________________________________________

TABLE 2


Results of Configural and Metric Measurement Invariance (Continued)

__________________________________________________________________________________

Lambdas

Item US Spain

__________________________________________________________________________________

Pay Satisfaction Questionnaire

Factor 1: Pay Level

1. My take–home pay .89 .85

2. My current salary .95 .93

3. My overall level of pay .96 .94

4. Size of my current salary .97 .92

Factor 2: Benefits

5. My benefit package .86 .61

6. Amount the organization pays toward my benefits .85 .79

7. The value of my benefits .93 .88

8. The number of benefits I receive .91 .72

Factor 3: Raises

9. My most recent raise .67 .47

10. The raises I have typically received in the past .74 .60

11. Influence my supervisor has on my pay .57 .46

12. How my raises are determined .61 .46

Factor 4: Pay Administration

13. The organization’s pay structure .79 .82

14. Information the organization gives about pay issues .71 .72

15. Pay of other jobs in the organization .54 .50

16. Consistency of the organization’s pay policies .72 .77

17. Differences in pay among jobs in the organization .78 .78

18. How the organization administers pay .63 .82


=

303.85, df = 130, p = .00, TLI = .98, CFI = .98, RMSEA = .08), Spain (χ2

= 278.83, df = 130, p =

.00, TLI = .96, CFI = .97, RMSEA = .11). Phase 2. Metric invariance (factor loadings) was

achieved (Δχ2 = 16.44, df = 14, p > .05; ΔCFI = .01) between unconstrained (χ

2 = 583.12, df =

260, p = .00, TLI = .97, CFI = .98, RMSEA = .06) and constrained MGCFA (χ2= 599.56, df =

274, p = .00, TLI = .98, CFI = .98, RMSEA = .06).

______________________________________________________________________________

FIGURE 1: A Theoretical Model of Pay Satisfaction


FIGURE 2: Results of Our Theoretical Model (The Whole Sample)

Hypothesized Model

The Love ofMoney

Equity Success Motivator

PaySatisfaction

PSQAdministration

PSQRaises

PSQBenefits

PSQPay

Income

Pay EquityComparison

Path 3

Internal External

Path 1

Path 4Path 2

Path 5

Path 6


Hypothesized Model

.16

The Love ofMoney

.17

MESEquity

e21

.41

.91.20

MESSuccess

e22

.45

.89.24

MESMotivator

e23

.49

.87

.75Total Pay

Satisfaction

.68

PSQAdministration

e44

.82

.57

.58

PSQRaises

e43

.76

.65

.53

PSQBenefits

e42

.73

.69

.53

PSQPay

e41

.73

e1 e2

e3Income

e11

1.00

ReportedIncome

1.00

.08Pay Equity

Comparison.29

.69

Chi-Square = 171.62df = 38p = .00

NFI= .98RFI = .97IFI = .98

TLI = .98CFI = .98

RMSEA = .11e31

.59

Internal

.64

e32

.66

External

.58

.77 .82

The Whole Sample

.41

.02

.86


FIGURE 3: Results of the American Sample

FIGURE 4: Results of the Spanish Sample

Hypothesized Model

.23

The Love ofMoney

.13

MESEquity

e21

.36

.93.14

MESSuccess

e22

.37

.93.15

MESMotivator

e23

.39

.92

.88Pay

Satisfaction

.72

PSQAdministration

e44

.85

.53

.60

PSQRaises

e43

.78

.63

.55

PSQBenefits

e42

.74

.67

.56

PSQPay

e41

.75

e1 e2

e3Income

e11

1.00

ReportedIncome

1.00

.24Pay Equity

Comparison.49

.66

Chi-Square = 223.35df = 76p = .00

NFI= .97RFI = .96IFI = .98

TLI = .98CFI = .98

RMSEA = .08e31

.68

Internal

.57

e32

.74

External

.51

.82 .86

The American Faculty

.48

-.18

.96


Hypothesized Model

.03

The Love ofMoney

.15

MESEquity

e21

.39

.92.24

MESSuccess

e22

.49

.87.37

MESMotivator

e23

.61

.80

.57Pay

Satisfaction

.57

PSQAdministration

e44

.76

.65

.53

PSQRaises

e43

.73

.69

.66

PSQBenefits

e42

.81

.58

.50

PSQPay

e41

.70

e1 e2

e3Income

e11

1.00

ReportedIncome

1.00

.02Pay Equity

Comparison.13

.71

Chi-Square = 223.35df = 76p = .00

NFI= .97RFI = .96IFI = .98

TLI = .98CFI = .98

RMSEA = .08e31

.38

Internal

.78

e32

.42

External

.76

.62 .65

The Spanish Faculty

.18

.14

.74