A Global Study of Pay Preferences and Employee Characteristics

Abstract

Companies are managing more diverse work forces, and pay systems must be designed to attract, retain and motivate employees who may have very different pay preferences from employees of even a decade ago. This study examines how employee characteristics (i.e., gender, age, education, work experience, annual pay and number of dependents) are related to pay preferences. We found that older respondents with more education and more dependents had a stronger preference for variable pay than did respondents who were younger, less educated and had fewer dependents. Older respondents and those with higher pay preferred less pay transparency than did younger and lower paid respondents. Pay differences based on capability were preferred by better educated employees. When controlling for the other demographic characteristic, we found significant differences among nationalities for all four measures of pay preferences, that is, pay differences, pay variability, bonus plans and pay transparency.

Keywords

pay preferences pay transparency variable pay incentive pay and comparative pay

Alignment of compensation policies and programs with a company’s business strategy is often suggested as a means of enhancing organizational competitiveness and improving both organizational and individual effectiveness.^1-4 However, strategic alignment is only one element of an effective pay system. An equally important element is the ability of the pay system to attract, retain and enhance employee motivation—all of which is driven, in large part, by employee pay preferences.^5-7 Unfortunately, little evidence exists as to the importance of the relationship between compensation pay preferences and attraction, retention and motivation.^8,9

Understanding existing and prospective employee pay preferences has become more important in recent years for a number of reasons. First, as the world economy emerges from one of the worst recessions in decades, competition for scarce talent, especially among new entrants into professional labor markets, is becoming intense.^10,11 Among economically developed nations, competition for talent is heightened by the retirement of the Baby Boomer generation (those born shortly after World War II), slower population growth, increasing specialization and technical demands of jobs and increased global competition for talent.^12,13

Second, there has been a major shift in labor force demographics across most industrial countries,¹⁴ and these demographic variables have been associated with pay preferences, for example, gender, age, income levels, work experience and nationality.^15-29 Today’s labor force is becoming older and more racially and ethnically varied, with a larger proportion of women. These trends will make the global workforce even more diverse in the future.³⁰

Finally, a diverse society brings a diversified workforce, mostly as a result of immigration and increasing corporate globalization. For example, approximately 25% of Australia’s labor force was born overseas.³¹ Once companies achieve multinational status, they move professionals and managers across the globe to fill employment needs and to integrate company cultures and operations. Customers empathize with corporations that understand their culture, their needs and that expand their labor pools to include talented employees from that culture. Conversely, ignoring diversity can increase costs through losses in market share.³²

For these reasons, companies are managing more diverse work forces, and pay systems must be designed to attract, retain and motivate these employees who may have very different pay preferences from employees of even a decade ago. Unfortunately, many studies examining these relationships are outdated, stretching back into the 1960s, with few examining the differences across countries.^33-38

Consequently, we conducted a global study across eight countries, examining how employee characteristics (i.e., gender, age, education, work experience, annual pay and number of dependents) are related to pay preferences. Understanding how these pay preferences differ will help human resource (HR) and compensation professionals better design and more effectively market their competitive pay policies and programs to an increasingly diverse labor force.

Data Collection Methods and Analysis

Professors in seven countries administered the pay preference survey to their full and part-time graduate students in Australia, Britain, Canada, Germany, Poland, Spain, and the United States. Since there was a substantial number of Chinese studying at these universities, we were able to include them as one of the nationalities examined.³⁹ Many of the part-time students held full-time jobs and were only returning to school after having gained substantial professional experience, as shown in Table 1. The surveys were administered in English, except where they were translated for students in Germany, Poland and Spain. These are the languages in which the classes were taught.

Table 1.

Demographic Profile of Survey Respondents by Country.

Characteristics	Australia (n = 38)	Britain (n = 94)	Canada (n = 163)	China (n = 87)	Germany (n = 171)	Poland (n = 183)	Spain (n = 238)	United States (n = 103)	Total sample (N = 1,282)
Gender
Male	37%	22%	49%	36%	74%	38%	51%	56%	48%
Female	63%	78%	51%	64%	26%	62%	49%	44%	52%
Age (years)
18-25	35%	30%	65%	84%	48%	27%	31%	39%	43%
26-35	46%	57%	33%	16%	31%	33%	29%	46%	36%
36-45	16%	10%	2%	0%	12%	31%	30%	16%	16%
46-60	3%	3%	0%	0%	9%	9%	11%	0%	6%
Education
High school	5%	5%	0%	0	8%	3%	0%	1%	2%
Trade	5%	6%	0%	0	2%	1%	11%	0%	3%
Undergraduate	71%	68%	78%	49%	58%	33%	56%	77%	59%
Master’s	18%	20%	22%	51%	28%	57%	28%	19%	32%
Doctorate	0	0%	0%	0	4%	6%	6%	3%	3%
Work experience
<1 Year	6%	1%	0%	37%	20%	3%	43%	4%	15%
1-5 Years	36%	38%	68%	55%	40%	27%	22%	38%	40%
6-10 Years	25%	36%	23%	7%	19%	24%	18%	35%	23%
11-15 Years	19%	11%	7%	1%	7%	18%	8%	12%	10%
16-20 Years	6%	10%	1%	0%	7%	16%	4%	6%	6%
>20 Years	8%	4%	0%	0%	7%	12%	5%	5%	6%
Annual pay
<$30,000	14%	6%	2%	69%	63%	44%	41%	25%	37%
$30,000 to $50,000	16%	47%	80%	27%	6%	35%	31%	20%	34%
Over $50,000 to $100,000	46%	39%	14%	3%	10%	19%	26%	41%	22%
>$100,000	24%	8%	3%	0%	21%	2%	1%	14%	7%
Number of dependents
0	70%	83%	93%	63%	38%	6%	60%	85%	59%
1	14%	9%	4%	9%	41%	14%	4%	7%	12%
2	3%	7%	2%	25%	8%	17%	27%	4%	13%
3 to 4	11%	1%	1%	3%	8%	53%	9%	4%	13%
5 or more	3%	0%	0%	0%	4%	11%	0%	0%	3%

A total of 1,282 surveys were returned, representing an 80% response rate. The data analysis was limited to the 1,077 respondents from the eight nationalities listed above. Students of other nationalities were taken out of the sample because there were so few from the countries that they represented. Although the surveys were administered to students in graduate classes, there was wide dispersion in the age, educational level completed, work experience, annual pay, number of dependents and gender among respondents. Our sample was made up of almost equal numbers of men (48%) and women (52%). Respondent age ranged from 18 to 60 years, and work experience from less than a year to over 20 years. Education levels varied from the completion of high school to doctorate degrees. For those working, 37% earned less than $30,000; 34% earned $30,000 to $50,000; 22% earned over $50,000 to $100,000; and 7% earned over $100,000 in U.S. dollars. Specific demographic information about the respondents used in this study is provided in Table 1.

Data were analyzed using descriptive statistics, t tests, bivariate correlations, and ANCOVA.

Pay Preferences

Pay preferences are assumed to be driven or shaped by a variety of human needs,^40,41 culture,^42,43 national legislation and pay tradition.⁴⁴ Pay preference research offers insight into the most efficient ways to reward employees and maximize the organization’s ability to attract, retain and motivate employees.

Over the past 50 years, pay preference research has focused on a variety of compensation and benefit comparisons. Nealey and Goodale⁴⁵ asked workers their preferences regarding more time off, early retirement and increased pay. More recent studies have examined reward preferences for increased pay, job security, coworker respect, promotions, variable pay, specific benefits, employee dispositions/personality, job flexibility, status and prestige, meaningful public service and a host of other factors.^46-51 Specific to compensation systems, Clugston and colleagues⁵² found job seekers were differentiated based on their preferences for different types of compensation systems, that is, merit pay, skill-based pay, and broad-banding.

In this study, we focused on four preferences associated with base (salary or wage) and incentive pay. Specifically, we asked respondents to complete the following: “I prefer to be employed by an organization where . . .”

Pay differences are based on individual capabilities to do the job as indicated by unique skills or competencies, above average performance and being recognized as high talent (three-item scale with a coefficient alpha of .72).

Pay variability allows an individual to make more or less, based on individual performance, how much his/her team or organization produces (eight items with a coefficient alpha of .76).

Opportunity to receive bonuses is based on individual, team or organizational performance (four items with a coefficient alpha of .69).

Pay transparency exists—the organization shares pay ranges for all positions and may actually share the amount individual employees are paid (five items with a coefficient alpha of .71). This scale is adapted from Day.⁵³

Five-point Likert-type scales (strongly agree to strongly disagree) were developed specifically for this study. The actual items used to construct these measures are available on request.

Previous Research, Findings and Discussion

The proposed relationships, empirical evidence and our findings regarding the relationships between employee characteristics and pay preferences are presented in detail. Table 1 shows the demographic breakdown of six employee characteristics (gender, age, annual pay, education, number of dependents and work experience) by nationality. Table 2 shows the relationship between the continuous variable age, any pay, education, number of dependents and work experience. Note that many of these variables are related. One would expect that age, number of dependents, annual pay and even education would be related to age. One would also expect that income and education would be related.

Table 2.

Correlation Matrix.

Variable	Mean	SD	1	2	3	4	5	6	7	8	9
1. Age	29.71	8.15	—
2. Annual Pay	1.98	0.94	.31**	—
3. Education	3.00	0.68	.32**	.08**	—
4. Number of Dependents	0.96	1.42	.49**	0.03	.21**	—
5. Work Experience	6.78	7.14	.78**	.36**	.20**	.41**	—
6. Bonus Plans	3.57	0.74	.05	−.01	−.01	−.03	.01	(.69)
7. Pay Differences	3.84	0.71	.05	.05	.11**	.02	.04	.24**	(.72)
8. Pay Transparency	2.96	0.80	−.11**	−.08*	−.02	.02	.00	−.18**	−.02	(.71)
9. Pay Variability	3.12	0.67	.06*	−.05	.08**	.09**	.03	.43**	.39**	−.02	(.76)

Note. Cronbach’s alpha for scales are listed in parenthesis on the diagonal.

p < .05. **p < .01. ***p < .001.

Because gender and nationality were categorical, they were analyzed using a t test (gender) and ANCOVA for nationality.

Age

How age affects pay preferences may be difficult to discern due to the number of workplaces and personal differences among age groups. According to Pudelko,⁵⁴ there is a discernible difference in attitude of younger employees compared with their older colleagues, mainly because younger people do not expect to remain in the same company for their entire professional careers. Younger workers differ from older workers in that they are typically paid less, are less likely to have family responsibilities, are typically in good health and retirement is on the distant horizon. Furthermore, younger workers have less experience with performance pay and may believe that they are good performers and so will do well under a pay-for-performance program. Older workers who have had more experience may realize that pay-for-performance programs do not always reward high performers or they may have more realistic perceptions of their own performance and, as such, prefer less subjective systems of pay determination and base pay. Middle-aged employees often have responsibilities for children and possibly spouses who do not work outside the home, unlike younger or older employees. Of course, retirement is on the immediate horizon for older workers, and they are more likely to suffer chronic and age-related illnesses. Finally, it may be difficult to categorize employees by age, since it is often uncertain when employees will marry, start raising families, have health-related problems or even retire.

Research has found that older workers want more of their compensation in benefits than do younger workers.^55,56 Specifically, older workers prefer retirement packages⁵⁷ and company job security,⁵⁸ whereas younger workers prefer time off, work/life balance and career development.^59,60 Lee and colleagues⁶¹ found that employees who have been with the company for less than 10 years and were under the age of 35 showed a stronger preference for pay variability or pay-for-performance. In contrast, other research has found that older workers had a stronger preference for financial rewards than did younger workers.^62-65

Consistent with Chonko and colleagues,⁶⁶ we found that older workers preferred variable pay more than did younger workers. It was also interesting that younger workers preferred more pay transparency than did older workers, which seems consistent with the willingness of younger people to share information on social media.

Annual Pay

No research was found connecting level of pay with pay preferences. One might hypothesize that respondents who were paid more would have the financial capacity to take more risk and thus prefer variable pay or a bonus; however, the only significant relationship with pay preferences was a negative one between pay transparency and annual pay, indicating that transparency is preferred by those who make less money.

Education

Education levels can vary considerably across an organization’s work force. Although theory provides little insight as to why education levels should affect pay preferences, limited research indicates that they do. One possibility is that higher income resulting from additional education shapes work values. Andrews and Henry⁶⁷ found that more formally educated managers preferred merit over seniority, were willing to give up company-provided security for an increase in pay and preferred pay increases over increased benefits, as compared to their less educated colleagues.

Mamman and colleagues⁶⁸ found that additional education did shape pay preferences but more so for some cultures than for others. What could be inferred from these findings is that the more educated workers may feel more secure in their jobs, and their higher income may allow them to take more risks with their pay, reinforcing perceptions that they are more capable of obtaining merit increases.

In our study, educational level was positively correlated with annual pay, as shown in Table 2. While the more educated respondents preferred both pay differences based on capability and variable pay when compared with less educated respondents, they were not found to prefer pay transparency or bonuses more than the less educated employees.

Number of Dependents

Although research directly examining the relationship between the number of dependents and pay preference was not found, one might infer that the more dependents one had, the less willing one might be to take pay-associated risks. Thus, individuals with fewer dependents would have stronger preferences for bonus pay and variable pay than would individuals with more dependents.

A stronger preference for variable pay was found for respondents who had more dependents. However, no relationship was found between the number of dependents and preference for pay differences based on capability, preference for a bonus or pay transparency.

Work Experience

Milanowski⁶⁹ found that students prefer pay programs that reward work experience or knowledge rather than personality traits or work values. Davis and colleagues⁷⁰ found college students with previous work experience had a significantly higher preference for cost of living increases, company stock and vacations, when compared to students with no work experience. This may be because along with work experience comes the realization that meaningful merit increases and bonuses are only given to a few employees. Therefore, with experience comes a preference for rewards that are not attached to the individual’s performance.

We did not find a relationship between work experience and any of the pay preferences we measured, which was consistent with Clugston and colleagues.⁷¹

Gender

Given the difference in societal roles of men and women, including child rearing and job opportunities, and the pay gap between men and women, researchers have shown considerable interest in how gender may affect pay preference.^72-74 Researchers have found that men placed more importance on extrinsic rewards, such as pay and promotions, than did women.^75-82 Women were found to prefer jobs with good coworker relationships, interesting work, work–life balance and development opportunities.^83-88

Men were found to prefer variable pay based on performance more than did women.^89,90 Women preferred skill and seniority-based pay systems.

Consistent with Dohmen and Falk⁹¹ and Chiang and Birtch,⁹² t test found support that men preferred variable pay over women, mean = 3.16 and mean = 3.01, respectively. No significant differences were found between men and women for the other three forms of pay preferences: pay differences, bonuses or transparency.

Nationality

Researchers have traditionally studied cultural values using Hofstede’s⁹³ framework, as it is particularly useful for understanding how employees from different cultures or nationalities may react to different work environments and payment systems. Existing cross-cultural literature proposes a relation between value systems (i.e., cultures) and pay preferences.^94-96 Nevertheless, and in spite of existing cross-country studies of compensation, no clear linkages between national culture and pay preferences were apparent.⁹⁷

Although dimensions provided by this framework provide insight into why employee pay perceptions might differ, the research is problematic, since countries and even companies most often hold a mix of employees with different cultural values. Furthermore, pay policies and practices differ substantially among nations, both by tradition and by employment laws within a nation, which can also significantly affect employee pay preferences. In fact, Chiang,⁹⁸ Chiang and Birtch⁹⁹ and others have found that the above may affect work values, especially in terms of how employees are rewarded. Chiang and Birtch’s research suggests that nationality is more important than culture in determining pay preferences. As such, we do not attempt to group countries with similar cultures, but simply report the differences in pay preferences that exist among the eight countries examined.

As one can see in Table 2, there are substantial demographic differences among respondents from the countries where data were collected. As a result, in our analyses we controlled for the characteristics of age, gender, annual pay, education, number of dependents and work experience. Table 3 reports the nationality mean scores for each of the pay preferences, as well as the accompanying F statistic. Significant F statistics (p < .001) indicate there are differences across nationalities for pay differences, pay variability, bonuses and pay transparency. A preference for pay transparency represented the widest difference among countries, with respondents from Spain, Britain and the United States having the least preference for transparency and Germany having the most. Preference for pay difference based on capabilities had the least variation among countries, with Germany and Britain having the lowest preference for pay differences and China, Spain and Australia having the most. Germany and Britain had the least preference for pay variability and China and the United States the most. Finally, Australia and China had the strongest preference for bonus plans, with Germany and Poland the least.

Table 3.

Nationality Averages and ANCOVA Results for Pay Preferences Controlling for Age, Gender, Annual Pay, Education, Number of Dependents and Work Experience.

Countries	Pay differences	Pay variability	Bonus plans	Transparency
Australia	3.91	3.14	3.96	3.20
Britain	3.70	2.90	3.75	2.89
Canada	3.87	3.23	3.61	3.26
China	4.05	3.39	3.97	3.30
Germany	3.58	2.76	3.11	3.80
Poland	3.86	3.09	3.32	3.16
Spain	3.96	3.18	3.66	2.20
United States	3.84	3.29	3.80	2.89
F	5.32*	11.50*	16.81*	30.47*

p < .001.

The extent to which there are significant differences among specific nationalities that responded to the survey is reported in Table 4 (ANCOVA analysis controlling respondent characteristics). Table 4 shows, on average, how a country compared to the other seven countries on each pay preference. For example, respondents from Australia have significantly higher preferences for bonuses than do those from Germany and Poland. Australian respondents have a higher level of preference for pay transparency than do those from Spain and a lower preference for transparency than those from Germany. The significant differences are marked with an asterisk (*) for each subsequent country.

Table 4.

Comparing Country Average Differences: Statistically Significant Differences (ANCOVA) Controlling for Age, Gender, Annual Pay, Education, Number of Dependents, and Work Experience.

Country (A)	Comparison group (B)	Pay differences (A − B)	Pay variability (A − B)	Bonus plans (A − B)	Transparency (A − B)
Australia	Britain	0.21	0.24	0.21	0.30
	Canada	0.04	−0.10	0.35	−0.06
	China	−0.14	−0.25	−0.02	−0.11
	Germany	0.33	0.38	0.85*	−0.60*
	Poland	0.05	0.05	0.64*	0.03
	Spain	−0.06	−0.04	0.30	1.00*
	United States	0.07	−0.15	0.16	0.30
Britain	Australia	−0.21	−0.24	−0.21	−0.30
	Canada	−0.17	−0.34*	0.14	−0.37
	China	−0.35	−0.49*	−0.23	−0.41
	Germany	0.12	0.14	0.64*	−0.91*
	Poland	−0.17	−0.19	0.43*	−0.27
	Spain	−0.27	−0.28	0.09	0.69*
	United States	−0.14	−0.39*	−0.06	0.00
Canada	Australia	−0.04	0.10	−0.35	0.06
	Britain	0.17	0.34*	−0.14	0.37
	China	−0.18	−0.15	−0.37*	−0.05
	Germany	0.29*	0.48*	0.50*	−0.54*
	Poland	0.01	0.14	0.29	0.10
	Spain	−0.09	0.06	−0.05	1.06*
	United States	0.03	−0.06	−0.20	0.37
China	Australia	0.14	0.25	0.02	0.11
	Britain	0.35	0.49*	0.23	0.41
	Canada	0.18	0.15	0.37*	0.05
	Germany	0.47*	0.63*	0.86*	−0.49*
	Poland	0.18	0.30	0.65*	0.14
	Spain	0.08	0.21	0.32	1.11*
	United States	0.21	0.10	0.17	0.41
Germany	Australia	−0.33	−0.38	−0.85*	0.60*
	Britain	−0.12	−0.14	−0.64*	0.91*
	Canada	−0.29*	−0.48*	−0.50*	0.54*
	China	−0.47*	−0.63*	−0.86*	0.49*
	Poland	−0.29*	−0.33*	−0.21	0.63*
	Spain	−0.39*	−0.42*	−0.55*	1.60*
	United States	−0.26	−0.53*	−0.7*	0.90*
Poland	Australia	−0.05	−0.05	−0.64*	−0.03
	Britain	0.17	0.19	−0.43*	0.27
	Canada	−0.01	−0.14	−0.29	−0.10
	China	−0.18	−0.30	−0.65*	−0.14
	Germany	0.29*	0.33*	0.21	−0.63*
	Spain	−0.10	−0.09	−0.34*	0.96*
	United States	0.02	−0.20	−0.49*	0.27
Spain	Australia	0.06	0.04	−0.30	−1.00*
	Britain	0.27	0.28	−0.09	−0.69*
	Canada	0.09	−0.06	0.05	−1.06*
	China	−0.08	−0.21	−0.32	−1.11*
	Germany	0.39*	0.42*	0.55*	−1.60*
	Poland	0.10	0.09	0.34*	−0.96*
	United States	0.12	−0.12	−0.15	−0.69*
United States	Australia	−0.07	0.15	−0.16	−0.30
	Britain	0.14	0.39*	0.06	0.00
	Canada	−0.03	0.06	0.20	−0.37
	China	−0.21	−0.10	−0.17	−0.41
	Germany	0.26	0.53*	0.70*	−0.90*
	Poland	0.02	0.20	0.49*	−0.27
	Spain	−0.12	0.12	0.15	0.69*

Note. Pairwise comparisons could only test one level of significance at a time.

p < .05.

Conclusions and Recommendations

Although the correlations were relatively small, this study found that pay preferences varied across individual characteristics for a global sample of graduate students. Older respondents with more education and more dependents had a stronger preference for variable pay than did respondents who were younger, less educated and had fewer dependents. Older respondents and those with higher pay preferred less pay transparency than did younger and lower paid respondents. Pay differences based on capability were preferred by better educated employees. No relationship among these variables was found for bonus plan preferences.

Respondent nationality, when controlling for other characteristics, provided more interesting results. When controlling for the other demographic characteristic, there were significant differences among nationalities for all four measures of pay preferences, that is, pay differences, pay variability, bonus plans and pay transparency. Germany consistently had a lower preference for pay difference based on capability, pay variability and bonus plans than did virtually all other countries, with the exception of Australia and Britain. Furthermore, Germany had a stronger preference for pay transparency than did all other countries.

Compared to all other countries, with the exception of Germany, Polish respondents were least likely to prefer bonus plans. However, Polish respondents did not have as much of an aversion to variable pay. The Spanish respondents were the least likely of all the countries to prefer pay transparency and only differed consistently from Germany in terms of their stronger preferences for pay differences, pay variability and bonus plans. This is interesting as it contrasts the availability of variable pay schemes in Spain and Germany.

A recent European Company Survey¹⁰⁰ shows that the prevalence of variable pay schemes in Spanish companies is below the average of other European countries, while German and U.K. companies fall in the average, and Polish companies are above the average. Finally, for the most part, Australia, Britain, Canada, China and the United States did not have many pay preferences that were statistically different from other countries, except Germany. The mean scores for each of the pay preferences were statistically different. Respondents, on average, more strongly preferred pay differences based on capability (mean = 3.84) and bonus plans (mean = 3.57) than pay variability (mean = 3.12). Preference for pay transparency scored the lowest (mean = 3.06). The higher preference for pay differences based on capability and bonuses rather than pay variability might indicate that respondents prefer the chance to earn more compared to the risk of earning less with variable pay. The strong preference for pay differences based on capability might reflect the particular interest of our sample of graduate students to get a safe return on their educational investment. Their comparatively low preference for pay transparency might indicate their fear of conflict or envy resulting from social comparisons and their expectations of being paid above average in the future, based on their above average qualifications.

Interpreting the differences found in this study may require substantial knowledge of culture, labor laws and employment history. For example, tradition may be related to the Polish respondents’ greater willingness for transparency of compensation. Increased need for a fair wage and transparency may be associated with unfair practices and abuse in compensation that took place in the past. Negative experience in this context is connected with a “persons-based reward system,” which differentiates rewards mostly in terms of personal and political considerations rather than competencies and efficiency.^101-103

Based on our findings, managers would be well served to consider the following when developing compensation programs:

There are considerable differences across employees and potential employees in terms of their pay preferences, especially in terms of pay transparency.

Nationality is an important factor in pay preferences, with Germany having substantially different views from respondents from other countries. Also, Polish respondents are particularly negative toward bonus plans.

Preferences for pay differences, pay variability and bonus plans are related.

A strong preference for pay differences based on demonstrated capabilities exists across all nationalities.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

Author Biographies

Dow Scott, PhD, is a professor of human resources in the Quinlan School of Business, Loyola University Chicago, and President of Performance Development International, a management consulting firm. His practical approaches to teaching, research and consulting focus on helping business leaders create high-performance organizations. He has published in more than 125 journals, books, and conference proceedings and has received national recognition for team/productivity improvement, compensation and incentive pay, attendance control, pay-for-performance and human resources research. His most recent work focuses on how reward programs impact innovation and incentive pay programs.

Michelle Brown (PhD, University of Wisconsin, Madison) is an associate professor in the Department of Management and Marketing, Faculty of Business and Economics, University of Melbourne, Australia. She undertakes research into the intended and unintended consequences of performance management and performance pay systems. She also undertakes research into employee willingness to become involved in organizational decision-making processes. Her work has been published in journals in Australia (Journal of Industrial Relations, Asia Pacific Journal of Human Resources), the United States (Industrial and Labor Relations Review, Human Resource Management, Group and Organization Management) and the United Kingdom (British Journal of Industrial Relations, Human Relations and Human Resource Management Journal). She makes presentations to professional human resource associations and local organizations and unions on her research.

John Shields, PhD, is deputy dean (education) and professor of human resource management and organizational studies in The University of Sydney Business School, Sydney, Australia. His main areas of research, publication and teaching include performance management, reward management, executive remuneration, director human and social capital, corporate governance and organizational leadership. In the field of human resource management, his coauthored publications include Managing Employee Performance and Reward (Cambridge University Press, 2007) and Human Resource Management: Strategy and Practice (2013).

Richard J. Long, PhD, is a professor of human resources and Hanlon Scholar in International Business in the Edwards School of Business at the University of Saskatchewan. He holds BCom and MBA degrees from the University of Alberta, a PhD from Cornell University, and is a certified human resources professional. He has been teaching, conducting research and consulting in human resources management for more than 40 years and has produced more than 100 publications based on his research and experience. He is the author of several books, including Strategic Compensation in Canada, the fifth edition of which was published in Toronto by Nelson Education in 2014. He was named a “Master Teacher” at the Fall Convocation of the University of Saskatchewan in 2014, an honor accorded to only two University of Saskatchewan faculty members each year. He is currently on the editorial boards of the International Journal of Human Resource Management and Relations Industrielles/Industrial Relations.

Conny H. Antoni, PhD, is a professor of work and organization psychology at the University of Trier and Vice-President of the German Association of Psychology (DGPs). He holds a BA from Kalamazoo College, a diploma of psychology and a doctoral degree from the University of Mannheim, Germany. He has been teaching, conducting research and consulting in work and organizational psychology, particularly in the areas reward management, teamwork, leadership and organizational development for more than 30 years, and he has produced more than 130 publications based on his research and experience. He is the author and editor of several books and special issues, including Reward Management (2012), Pay and Reward Systems—Theoretical Approaches and Empirical Outcomes (2011), Shaping Pay in Europe: A Stakeholder Approach (2007). He is currently on the editorial boards of the Zeitschrift für Arbeits- und Organisationspsychologie (coeditor), European Journal of Work and Organizational Psychology (consulting editor) and Team Performance Management (editorial advisory board).

Ewa J. Beck-Krala, PhD, (email: ebeck@zarz.agh.edu.pl) is an assistant professor of human resources at the Faculty of Management, AGH University of Science and Technology, Krakow. She has been teaching, conducting research and consulting in human resources management for more than 15 years in Poland and has produced more than 50 publications based on her research and experience. She is a member of the Polish Association of Human Resources and has been awarded with the Fulbright Scholarship at the Institute of Human Resources and Industrial Relations at the Business School at the Loyola University in the United States as well as the Tempus Scholarship at the Business School at the University of Teesside in the United Kingdom.

Ana Maria Lucia-Casademunt, PhD, is a professor of business organization at the Business Administration Department, Loyola Andalucia University (Seville-Cordoba, Spain). She holds master’s degree in financial economics and master’s degree in organization and human resource psychology from the University of Seville (Spain). She received her PhD in social sciences from the University of Córdoba in July 2013, and her research interests cover different aspects of human resource management in profit and nonprofit organizations, the configuration of workplace environment, job well-being, job involvement and female managers. She has published her work in international and Spanish journals: Academia Revista Latinoamericana de Administración, Revista Venezolana de Gerencia, Universia Business Review, Journal of Society for Development of Teaching and Business Processes in New Net Environment in B&H, International Human Resource Management, Proelium, Procedia Economics and Finance and Scientific Journal Intangible Capital. She has presented several reports in conferences and scientific meetings of her specialty. She had also edited the book ICT Management in Non-Profit Organizations (IGI Global Publishing) and currently is editing the book titled Strategic Labor Relations Management in Modern Organizations.

Stephen J. Perkins, DPhil (Oxon), is the professor of corporate governance and leadership and dean, Guildhall Faculty of Business and Law, London Metropolitan University, UK.