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To the Graduate Council:
I am submitting herewith a dissertation written by Mary Lynn Berry entitled “Predicting
Turnover Intent: Examining the Effects of Employee Engagement, Compensation
Fairness, Job Satisfaction, and Age.” I have examined the final paper copy of this
dissertation for form and content and recommend that it be accepted in partial fulfillment
of the requirements for the degree of Doctor of Philosophy, with a major in Business
Administration.
Michael Lane Morris
_______________________________
Major Professor
We have read this dissertation
and recommend its acceptance:
Robert T. Ladd
________________________________
Donde Plowman
________________________________
T. Russell Crook
________________________________
Alan Chesney
________________________________
Accepted for the Council:
_________________________________
Carolyn R. Hodges, Vice Provost and Dean
of the Graduate School
Original signatures are on file with official student records.
i
Predicting Turnover Intent: Examining the Effects of Employee Engagement,
Compensation Fairness, Job Satisfaction, and Age.
A Dissertation Presented for
The Doctor of Philosophy
Degree
The University of Tennessee, Knoxville
Mary Lynn Berry
May 2010
ii
Copyright © 2010 by Mary Lynn Berry
All rights reserved.
iii
DEDICATION
To Lauren, Jacob, and Caroline.
And Jeff.
iv
ACKNOWLEDGEMENTS
I would like to extend my deepest appreciation to my graduate committee for their
support and encouragement--Dr. Lane Morris, Dr. Tom Ladd, Dr. Donde Plowman, Dr.
Russell Crook, and Dr. Alan Chesney. In addition, a special thank you to Dr. Sharon
Jeffcoat Bartley, Dr. Virginia Kupritz, and Dr. Vicky Johnson Stout for your
encouragement over the years. Next, a thank you is extended to Angie White, Anita Van
De Vate, and Callie Blount for proofreading. A special thank you is also extended to Jim
Atchley, fellow teacher, for his continued encouragement and support. Finally, a special
thank you to Drs. Hazel and Bob Spitze and Lynn and Marilyn Slayton.
v
ABSTRACT
The current study assessed the moderating effects of Age and the mediating effects of Job
Satisfaction on the relationship between antecedents Employee Engagement and
Compensation Fairness and the outcome variable Turnover Intent. The theory of reasoned
action and a theoretical framework for examining age-effects on employee attitudes were
used as the theoretical underpinnings for the study. The study utilized a secondary data
set with surveyed population including faculty (n = 1,229) from a land-grant institution
holding the doctoral/research-extensive classification from the Carnegie Classification
and serving about 42,000 students each year with graduates totaling more than 9,000 per
year. Findings confirmed that 11 of the 12 items of the Gallup Workplace Audit loaded
on the Employee Engagement factor. Findings also confirmed a 3-item solution for the
Compensation Fairness factor. Both Employee Engagement and Compensation Fairness
demonstrated an inverse relationship with Turnover Intent as expected. Job Satisfaction
was found not to mediate the relationship between both Employee Engagement and
Compensation Fairness with the outcome variable Turnover Intent. Finally, Age was not
found to moderate the relationship between antecedent variables and Turnover Intent.
Recommendations for research and practice were made.
vi
TABLE OF CONTENTS
CHAPTER ..................................................................................................................PAGE
CHAPTER 1 ....................................................................................................................... 1
Introduction......................................................................................................................... 1
Significance of the Study................................................................................................ 8
Statement of the Problem................................................................................................ 8
Purpose of the Study ....................................................................................................... 9
Objectives of the Study................................................................................................. 10
Research Questions....................................................................................................... 10
Hypotheses.................................................................................................................... 11
Nominal Definitions...................................................................................................... 12
Employee Engagement ............................................................................................. 12
Compensation Fairness ............................................................................................. 12
Compensation ........................................................................................................... 12
Employee Benefits.................................................................................................... 12
Job Satisfaction ......................................................................................................... 13
Employee Retention.................................................................................................. 13
Employee Turnover .................................................................................................. 13
Turnover Intent ......................................................................................................... 13
Cohort ....................................................................................................................... 13
vii
Tenure ....................................................................................................................... 13
Faculty....................................................................................................................... 14
Theoretical Framework................................................................................................. 14
Theory of Reasoned Action ...................................................................................... 14
General Theoretical Framework: Age Effects, Cohort Effects................................. 19
Higher Education .......................................................................................................... 29
Assumptions of the Study ............................................................................................. 31
Summary....................................................................................................................... 32
Review of the Literature ................................................................................................... 33
Employee Engagement ................................................................................................. 33
Defining Employee Engagement .............................................................................. 34
Employee Engagement, Employee Disengagement, and Burnout ........................... 36
Prevalence of Employee Engagement ...................................................................... 37
Employee Engagement as a Multidimensional Concept .......................................... 38
Employee Engagement vs. Organizational Commitment......................................... 40
Personal Engagement................................................................................................ 41
Promotion of Employee Engagement ....................................................................... 43
Compensation Fairness ................................................................................................. 53
Compensation ........................................................................................................... 54
Employee Benefits.................................................................................................... 56
Turnover Intent ............................................................................................................. 60
viii
Turnover.................................................................................................................... 60
Turnover Intent ......................................................................................................... 62
Employee Engagement with Turnover Intent............................................................... 64
Expectations with Turnover Intent............................................................................ 66
Materials with Turnover Intent ................................................................................. 67
Opportunity with Turnover Intent............................................................................. 67
Recognition with Turnover Intent............................................................................. 68
Care with Turnover Intent......................................................................................... 69
Encouragement with Turnover Intent ....................................................................... 70
Opinions Count with Turnover Intent....................................................................... 71
Mission with Turnover Intent ................................................................................... 71
Quality Work with Turnover Intent .......................................................................... 72
Best Friend with Turnover Intent.............................................................................. 73
Progress/Appraisal with Turnover Intent.................................................................. 74
Learn and Grow with Turnover Intent...................................................................... 74
Compensation Fairness with Turnover Intent............................................................... 75
Job Satisfaction ............................................................................................................. 78
Employee Engagement, Job Satisfaction, and Turnover Intent.................................... 80
Compensation Fairness, Job Satisfaction, and Turnover Intent.................................... 83
Age................................................................................................................................ 84
Profile of the Mature Worker.................................................................................... 85
ix
Profile of the Midcareer Worker............................................................................... 86
Profile of the Late Midcareer Worker....................................................................... 87
Profile of the Early Midcareer Worker ..................................................................... 88
Profile of the Young Worker .................................................................................... 88
Moderating Effects of Age............................................................................................ 90
Expectations, Turnover Intent, and Age ................................................................... 92
Materials, Turnover Intent, and Age......................................................................... 93
Opportunity, Turnover Intent, and Age .................................................................... 94
Recognition, Turnover Intent, and Age .................................................................... 95
Care, Turnover Intent, and Age ................................................................................ 96
Encouragement, Turnover Intent, and Age............................................................... 97
Opinions Count, Turnover Intent, and Age .............................................................. 98
Mission, Turnover Intent, and Age........................................................................... 99
Quality Work, Turnover Intent, and Age.................................................................. 99
Best Friend, Turnover Intent, and Age ................................................................... 100
Progress/Appraisal, Turnover Intent, and Age ....................................................... 101
Learn and Grow, Turnover Intent, and Age............................................................ 102
Summary..................................................................................................................... 104
CHAPTER III ................................................................................................................. 106
Methodology................................................................................................................... 106
Methods....................................................................................................................... 106
x
Selection of the Population ......................................................................................... 108
Sample......................................................................................................................... 109
Instrumentation ........................................................................................................... 109
Employee Engagement ........................................................................................... 110
Compensation Fairness ........................................................................................... 111
Job Satisfaction ....................................................................................................... 112
Turnover Intent ....................................................................................................... 112
Demographics ......................................................................................................... 112
Procedures................................................................................................................... 113
Data Collection ........................................................................................................... 114
Data Analysis.............................................................................................................. 114
Ethical Considerations ................................................................................................ 118
Summary..................................................................................................................... 119
CHAPTER IV ................................................................................................................. 120
Data Analysis.................................................................................................................. 120
Descriptive Statistics................................................................................................... 120
Measurement Model ................................................................................................... 121
Structural Model ......................................................................................................... 123
Prediction of Turnover Intent.................................................................................. 123
Mediating Effects of Job Satisfaction in the Structural Model............................... 124
Moderating Effects of Age in the Structural Model ............................................... 126
xi
Summary................................................................................................................. 127
CHAPTER V .................................................................................................................. 128
Conclusion and Recommendations................................................................................. 128
Conclusion .................................................................................................................. 128
Findings................................................................................................................... 129
Significance of the Study........................................................................................ 135
Objectives of the Study Satisfied............................................................................ 135
Improvements Made to Employee Engagement Literature .................................... 136
Recommendations....................................................................................................... 138
Recommendations for Future Research.................................................................. 138
Recommendations for Practice ............................................................................... 141
Summary..................................................................................................................... 151
REFERENCES ............................................................................................................... 153
APPENDICES ................................................................................................................ 197
Employee Satisfaction Survey ........................................................................................ 199
VITA............................................................................................................................... 236
xii
LIST OF FIGURES
FIGURE PAGE
Figure 1. Turnover Model Based on Mobley (1977), Mobley et al. (1978),
Mobley et al. (1979), and Muchinsky and Morrow. (1980). 203
Figure 2. Current Model: Mediating Effects of Job Satisfaction and Moderating
Effects of Age on the Relationship between Antecedents Employee Engagement
and Compensation Fairness (Evaluation of Current Job) and Outcome Variable
Turnover Intent (Thoughts of Quitting). 204
Figure 3. Measurement Model for Employee Engagement. 205
Figure 4. Measurement Model for Compensation Fairness. 206
Figure 5. Model showing Prediction of Turnover Intent by Employee
Engagement and Compensation Fairness with Mediating Effects of Job
Satisfaction and Moderating Effect of Age. 207
Figure 6. Accepted Measurement Model for Employee Engagement,
Compensation Fairness. 208
Figure 7. Accepted Model for Employee Engagement, Compensation Fairness,
Job Satisfaction, and Turnover Intent. 209
xiii
LIST OF TABLES
TABLE PAGE
Table 1. Employee Engagement Items (Gallup Workplace Audit),
Variable Names of Predictor Variables, and The Four Camps of the Gallup
Workplace Audit (Buckingham and Coffman, 1999). 211
Table 2. Gallup Workplace Audit Items, Parallel Items in the Literature,
Name of Measure, Source, Relationship with Turnover Intent and/or Age. 212
Table 3. Employee Engagement by Career Stage. 227
Table 4. Descriptive Statistics for Faculty for Employee Engagement Scale,
Compensation Fairness Factor, Job Satisfaction, and Turnover Intent. 229
Table 5. Standardized Regression Weights for A Priori Two-Factor
Measurement Weights Model. 230
Table 6. Standardized Regression Weights for Revised Two-Factor
Measurement Weights Model. 231
Table 7. Summary Table of Measurement Models. 232
Table 8. Summary Table of Structural Models. 233
Table 9. Summary Table of Hypotheses. 234
Table 10. Post Hoc ANOVA for Age Differences in Study Variables 235
1
CHAPTER 1
Introduction
“The challenge today is not just retaining talented people, but fully engaging them,
capturing their minds and hearts at each stage of their work lives”
(Lockwood, 2007, p. 1).
The American workforce is changing. Demographers have proposed that the workforce
of tomorrow will be quite different from that of yesterday. One may attribute these
coming changes to the great exodus of the baby boomers from the work place, or,
perhaps, the longevity boom caused by the increase in life expectancy from about 47
years around 1900 to 77 years today, or even to the birth dearth in the U.S. and abroad
where birth rates are falling, some below replacement rates (Dychtwald, Erickson, &
Morison, 2006). Compound these “problems” by the fact that the ethnic make-up of
workers is more diverse (Dychtwald et al., 2006), the family life cycle has changed
(Dychtwald et al., 2006), and the generation entering the workforce is less educated than
its predecessors with 21-23% of these workers functionally illiterate (Jamrog, 2004), and,
as a result, American businesses and organizations have the elements for a “Workforce
Crisis” (Dychtwald et al., 2006) or “Perfect Storm” (Jamrog, 2004). What’s in the
forecast for American businesses and organizations? While current economic conditions
have employees striving to maintain positions, it is anticipated that as baby boomers exit
the workplace both profit and non-profit organizations will be confronted with a shortage
2
of skilled laborers, a shortage further exacerbated by the voluntarily turnover by many
workers in an effort to secure better jobs (Jamrog, 2004). To encourage readiness for such
a crisis, Jamrog (2004) suggested that Human Resource Development professionals focus
on building a culture of both retention and engagement in the workplace: “Employer
strategies to build a culture that retains and engages the best and brightest will rely less
heavily on traditional pay and benefits and more on the creation of a work environment
that allows people to grow and develop” (p. 29). In sum, a prepared organization will be
able to weather the storm, and many (Lockwood, 2007; Dychtwald et al., 2006; Jamrog,
2004) have suggested that the best strategies to weather the coming crisis are those that
deal with retention, job satisfaction, engagement, turnover intent, and compensation
fairness.
Similarly, within the context of higher education, the shortage of faculty has been
forecasted by several researchers (Bland, Center, Finstad, Risbey, & Staples, 2006;
Harrison & Hargrove, 2006) with as many as half of the nation’s faculty retiring by 2015.
Harrison and Hargrove (2006) explained that finding replacements for aging faculty is a
major concern for institutions in higher education, a problem exacerbated by rising costs
of health care and the unattractiveness of faculty positions to doctoral students as
compared to salaries and benefits they may earn in other industries. Also, according to
Harrison and Hargrove, a decline in faculty positions may decrease the quality of
instruction via a reduction in the effectiveness of available faculty to manage normal
tasks. Moreover, results of a decreased quality in education can damage the reputation of
3
an institution, threaten faculty morale, and impact student-faculty interactions (Harrison
& Hargrove, 2006; Dee, 2004). In addition to concerns with the retirement of the baby
boomers, concerns with the attraction of and retention in staff are extended also to
diverse faculty members as women and people of color are underrepresented as compared
to a diversifying student body (Van Ummersen, 2005). Efforts to better understand
retention, job satisfaction, engagement, and compensation fairness may be useful in
ameliorating the crisis in higher education and retain valuable employees that may choose
to proceed with retirement or even seek jobs elsewhere if the opportunity arises.
While healthy turnover in an organization can be positive, refreshing, and helpful
in introducing new ideas and techniques that can move the organization to greater levels
of success, turnover among highly-productive, key employees is costly (Hellman, 1997).
For example, typical turnover costs include exit costs (e.g., exit interviews, administrative
time, and pay for leave not taken), temporary replacement costs (e.g., agency fees and
training), recruitment and selection costs (e.g., advertising costs, agency fees, lost time,
screening, applicant testing assessment, background checks, interviews, travel and
relocation), missed and lost sales opportunities, decreased morale and productivity among
retained workers, loss of future key talent (i.e., intellectual capital including knowledge,
skills, and experience), and sharing of organizational processes, technology, and
relationships (International Survey Research, n.d.; Frank, Finnegan, & Taylor, 2004).
Since, the long-term retention of a highly productive workforce is coveted, and a goal of
human resources is to attract and maintain highly productive employees, it is imperative
4
for human resources to better understand how to maximize the retention of productive
employees through the analysis of the antecedents of organizational withdrawal
decisions. This is a popular research topic among investigators and theorists in the fields
of business and human resource management as well as economics, organizational
science, psychology, and political science (Hulin, Roznowski, & Hachiya, 1985).
Although retention of highly productive key employees is certainly an important
task for human resources, so is the creation and development of a workplace that not only
encourages retention, but also high levels of productivity among all employees. Many
researchers (Buckingham & Coffman, 1999; Seijts & Crim, 2006; Harter, Schmidt, &
Hayes, 2002) have used the term engagement to refer to employees who are involved in,
enthusiastic about, and satisfied with his or her work. The 2003 Towers Perrin Talent
Report found that approximately 81% of employees surveyed were engaged, but as many
as 19% of employees surveyed were disengaged. BlessingWhite (2008) also reported the
same percentage of disengaged employees in North America. Disengaged employees are
more likely to perform poorly, actively look for another job, and make negative
comments about management or the organization for which they work (Gubman, 2004).
Such counterproductive work behavior also has a documented relationship with a lack of
organizational citizenship (Dalal, 2005). Moreover, Sanford (2003) reported that
disengaged employees cost their organizations financially via decreased profits,
decreased sales, lower customer satisfaction, and lower productivity. Furthermore,
Sanford (2003) reported that the Gallup Organization estimated that actively disengaged
5
employees may cost the American economy up to $350 billion per year in lost
productivity. The encouragement of engagement among employees through the creation
and development of a stronger workplace culture has enormous return on investment
(ROI) potential for organizations. BlessingWhite (2008) cited a number of instances
where high employee engagement is linked to superior business performance including
BestBuy which reported that stores increasing employee engagement by a tenth of a point
(using a 5-point scale) see an increase in sales for the year totaling $100,000. According
to Lockwood (2007), “[T]o gain a competitive edge, organizations are turning to HR
[Human Resources] to set the agenda for employee engagement and commitment” (p. 2).
Employee engagement includes those characteristics of a workplace environment
that “attract and retain the most productive employees” (Buckingham and Coffman,
1999, p. 30). Employee engagement has been measured by the Gallup Workplace Audit
(GWA) that consists of 12 items measuring concepts ranging from understanding work
expectations to having a best friend at work to having opportunities at work to learn and
grow. (See Table 1 in Appendix C). The GWA will be discussed in more depth in
Chapter II.
Employee engagement is an important part of the Employee Value Proposition
(EVP) described by Ledford and Lucy (2002). In the EVP, rewards of work drive
employee outcomes that in turn drive organizational outcomes (Ledford & Lucy, 2002,
part 1). The monetary and non-monetary rewards of work include many of the facets
related to employee engagement and may be divided into 5 areas:
6
• Compensation,
• Benefits (including recognition),
• Career (including advancement, training, and employment security),
• Work Content (including meaningfulness, feedback, and variety), and
• Affiliation (including work environment, trust, and organizational
commitment) (Ledford & Lucy, 2002, The Segal Group, Inc., 2006d).
All five types of rewards have an impact on employee outcomes including retention,
engagement, and performance (The Segal Group, Inc., 2006a); although employees may
prefer one reward to another and accept substitutions (Ledford & Lucy, 2002).
Organizational outcomes include productivity, customer satisfaction, growth, and
profitability (The Segal Group, Inc., 2006a). Work should be rewarding and engaging.
Work is an important component contributing to the well- being of both the individual
and the community, affecting the quality of the life and mental health of the individual as
well as the productivity of a community (Harter, Schmidt, & Keyes, 2002). Of particular
concern to employers is the degree to which employees accept the rewards of work,
monetary or otherwise, but simultaneously experience decreased satisfaction and
engagement without an increased intention to leave and, in essence, they are “quitting on
the job” (The Segal Group, Inc., 2006a, p.4).
Despite the fact that organizational performance has been measured using hard
numbers (i.e., numbers associated with productivity, profitability, and other revenues),
recent research has shown that “soft” numbers may be useful in action planning
7
(Coffman & Harter, 1999). “Soft” numbers are sometimes difficult to quantify directly,
difficult to convert to monetary values, subjectively based, and attitude or behaviorally
oriented (Phillips, 1997). “Soft” numbers may be very useful for human resources
looking to decrease employee turnover and increase employee engagement through the
development of a stronger workplace environment or as a prediction of occupational
well-being (or unwell-being) (Bakker, Schaufeli, Demerouti, & Euwema, 2007) These
soft numbers may include employee attitudes regarding a number of organizational topics
including employee engagement—which mirror many of the rewards in the EVP such as
recognition, meaningfulness and feedback (Ledford and Lucy, 2002)--and employees’
expressed turnover intent. The use of “soft” data may be an important component to an
organization’s attainment of competitive advantage over competition (Luthans &
Peterson, 2002). Hence, Harrison, Newman, and Roth (2006) called soft data “one of the
most useful pieces of information an organization can have about its employees” (p. 320-
321).
As we continue into the new millennium, not only are we faced with the baby
boomers exiting the workplace, but we are also confronted with the task of attracting,
training, and retaining a younger workforce entering the workplace who may differ
significantly from previous generations (Smola & Sutton, 2002). While a number of
researchers have focused on the relationship between age and Turnover Intent (Waters,
Roach & Waters, 1976; Gupta & Beehr, 1979; Martin, 1979; Jamal, 1981; Arnold &
Feldman, 1982; Schulz, Bigoness, & Gagnon, 1987; Weisberg & Kirschenbaum, 1991),
8
previous research has not addressed the age-related issues present in employees’ attitudes
concerning the employee value proposition, specifically as it relates to compensation
fairness and to employee engagement.
Significance of the Study
This study extended previous conceptualizations of Turnover Intent (e.g., Mobley, 1977;
Mobley, Griffeth, Hand, & Meglino, 1979; see Figures 1 and 2 in Appendix B) by
incorporating new work environment variables (i.e., Employee Engagement) that a small
but growing number of studies have shown to have a significant effect on Turnover and
Turnover Intent. Moreover, this study conceptually linked Employee Engagement (as
measured by the 12 items of the Gallup Workplace Audit and recently popularized in the
consulting literature) with similar items in the research literature (see Table 2 in
Appendix C). Finally, this study tested both the mediating effects of Job Satisfaction and
the moderating effects of Age on the relationship between antecedents—Employee
Engagement and Compensation Fairness—and the outcome variable Turnover Intent
among faculty utilizing secondary data obtained from an institution of higher education.
Statement of the Problem
While Macey and Schneider (2008) have suggested that employee engagement is not a
new concept but simply an “old wine in new bottles” (p. 6) and “ composed of a
potpourri of items” (p. 6) representing previously researched concepts such as Job
satisfaction, empowerment, job involvement, and organizational commitment, the term
employee engagement has appeared fairly recently in the research literature (See Kahn,
9
1990; Maslach, Schaufeli, & Leiter, 2001; Harter, Schmidt, & Hayes, 2002; Harter,
Schmidt, & Keyes, 2003; May, Gilson, & Harter, 2004; and Schaufeli, Bakker, &
Salanova, 2005) but is much more commonly found in consulting works (Buckingham &
Coffman, 1999; Towers-Perrin, 2003). Because of its relative infancy, there has been a
lack of sufficient information about employee engagement, specifically conditions in the
work environment that are said to promote employee engagement (Macey & Schneider,
2008), its measurement, and the relationship between employee engagement and turnover
intent. Furthermore, there also has existed a lack of information about the moderating
effects of age on the relationships between the antecedents employee engagement and
compensation fairness and the outcome variable turnover intent as well as the mediating
effects of job satisfaction on the same. Because of this lack of information, there has been
missed opportunities for growth and development that could essentially affect the
organizational performance and staffing in organizations, especially academia and
particularly in light of the forecasted shortages in higher education (Bland et al., 2006).
Purpose of the Study
The purpose of the study was to ascertain the influence of Job Satisfaction as a mediator
and Age as a moderator on the antecedents Employee Engagement and Compensation
Fairness on the outcome variable Turnover Intent in order that improvements can be
made in the work environment as well as for the studied organization’s performance.
Additionally, the researcher of the current study purposed to bridge consulting works
10
popularizing the concept employee engagement with the research literature via a study
assessing faculty in higher education who have been infrequently studied.
Objectives of the Study
Using a sample of faculty in higher education, the objectives for this predictive study
included the following:
1. Test the measurement models for both Employee Engagement and
Compensation Fairness. (See Figures 3 and 4 in Appendix B).
2. Test the prediction of the outcome variable Turnover Intent by antecedents
Employee Engagement and Compensation Fairness. (See Figure 5 in
Appendix B).
3. Test the mediating effects of Job Satisfaction on the relationship between
antecedents Employee Engagement and Compensation Fairness and the
outcome variable Turnover Intent. (See Figure 5 in Appendix B).
4. Test the moderating effect of Age on the relationship between antecedents
Employee Engagement and Compensation Fairness and the outcome variable
Turnover Intent. (See Figure 5 in Appendix B).
Research Questions
Using a sample of faculty in higher education, the research questions for this study
included the following:
1. Can employee engagement and compensation fairness be measured?
11
2. Can employee engagement and compensation fairness be used to predict
turnover intent? Furthermore, which variable—Employee Engagement or
Compensation Fairness—best predicts Turnover Intent?
3. Does Job Satisfaction mediate the relationship between the antecedents—
Employee Engagement and Compensation Fairness—and the outcome
variable Turnover Intent?
4. Does Age moderate the relationship between the antecedents—Employee
Engagement and Compensation Fairness—and the outcome variable Turnover
Intent?
Hypotheses
The hypotheses for the study included the following:
Hypothesis 1a: Employee Engagement is inversely related to Turnover Intent.
Hypothesis 1b: Compensation Fairness is inversely related to Turnover Intent.
Hypothesis 2a: Job Satisfaction mediates the relationship between the antecedent
Employee Engagement and outcome variable Turnover Intent.
Hypothesis 2b: Job Satisfaction mediates the relationship between the antecedent
Compensation Fairness and outcome variable Turnover Intent.
Hypothesis 3a: Age moderates the relationship between antecedent Employee
Engagement and outcome variable Turnover Intent.
Hypothesis 3b: Age moderates the relationship between antecedent Compensation
Fairness and outcome variable Turnover Intent.
12
Nominal Definitions
Employee Engagement
Employee engagement is the act of an employee being involved in, enthusiastic
about, and satisfied with his or her work (Seijts et al., 2006; Harter, Schmidt, & Hayes,
2002; Harrison, 2007; Gubman, 2004). It includes the characteristics of a workplace
environment that “attract and retain the most productive employees” (Buckingham and
Coffman, 1999, p. 30).
Compensation Fairness
Compensation fairness refers the perceptions that employees have regarding
equity in company practices concerning internal compensation, external compensation,
and benefits.
Compensation
According to Milkovich and Newman (2005), compensation refers to “all forms
of financial returns and tangible services and benefits employees receive as part of an
employment relationship” (p. 602).
Employee Benefits
An employee benefit is “any type of plan sponsored or initiated unilaterally or
jointly by employers and employees in providing benefits that stem from the employment
relationship that are not underwritten or paid directly by government” (Yohalem, 1977, p.
19).
13
Job Satisfaction
Job satisfaction refers to the contentment an individual has with her or her job.
Employee Retention
Employee retention (versus employee turnover) refers to the continued
employment of employees. Optimally, high-quality, productive employees are retained.
Employee Turnover
Employee turnover (versus employee retention) refers to the process of an
employee leaving a position and a new employee hired to take his or her place. Employee
turnover can be voluntary and involuntary as well as internal and external. Of particular
concern to the current study is employee turnover that is both voluntary and external in
nature.
Turnover Intent
Turnover intent refers to the voluntary intention of an employee to leave an
organization.
Cohort
Cohort refers to subgroups of workers sorted according to age: mature workers
are workers aged 55 and above, midcareer workers are workers aged 36 to 54, and young
workers are workers aged 35 and under (Dychtwald et al., 2006).
Tenure
Tenure is a “covariant of age” (Hellman, 1997, p. 679) and refers to longevity, not
a faculty rank or status.
14
Faculty
Faculty refers to whether the employee is non-tenure track, tenure track, or
tenured. Faculty may be exempt (i.e., not compensated for overtime) or non-exempt (i.e.,
compensated for overtime) (Igalens & Rousel, 1999).
Theoretical Framework
While there has been extensive research on the topic of turnover intent as well as age-
related effects across a variety of variables, Fishbein and Ajzen’s (1975) theory of
reasoned action and a general theoretical framework for explaining age-related effects
(Rhodes, 1983) served as the theoretical framework for the current study. See Figures 1
and 2 in Appendix B. The theory of reasoned action is useful in explaining the
relationship between employee engagement, compensation fairness, job satisfaction, and
turnover intent (and, subsequently, turnover). A general theoretical framework for
explaining age-related effects in employee attitudes is useful in explaining both age-
effects and cohort-effects in employee attitudes. Within this framework suggested by
Rhodes (1983), Super’s Life-Span Life-Space Theory is useful in explaining age-effects
in career stages and Generational Cohort Theory is useful in explaining cohort-effects
across social cohorts. These theories are discussed more in depth below.
Theory of Reasoned Action
Fishbein and Ajzen’s (1975) theory of reasoned action is useful in explaining the
relationship between attitude, intention, and behavior. The theory of reasoned action
purports that intentions—based on reason--mediate the relationship between attitude and
15
behavior (Sheppard, Harwick, & Warshaw, 1988; Prestholdt, Lane, & Mathews, 1987).
The theory of reasoned action posits that:
(a) the most proximal cause of behavior is a person’s intention to engage in it; (b)
intention is a function of attitude toward the behavior and subjective norms: (c)
attitude toward the behavior is a function of beliefs that the behavior leads to
salient outcomes; and (d) subjective norms are a function of the person’s
perceptions of significant others’ preferences about whether he or she should or
should not engaged in the behavior and the person’s motivation to comply with
these referent expectations (Brief, 1998, p. 64).
According to Brief (1998), Fishbein and Ajzen’s (1975) theory of reasoned action
“dominates the attitude-behavior literature in social psychology” (p. 64), and, therefore,
has been used in a variety of studies including tax evasion behavior (Hessing, Elffers, &
Weigel, 1988), members’ participation in union activities (Kelloway & Barling, 1993),
AIDS-preventive behavior (Fisher, Fisher, & Rye, 1995), physicians’ delivery of
preventive services (Millstein, 1996), attitudes towards affirmative action programs (Bell,
Harrison, & McLaughlin, 2000), supervisor referrals to work-family programs (Casper,
Fox, Sitzmann, & Landy, 2004), and smoking behavior among teens (Hersey,
Niederdeppe, Evans, Nonnemaker, Blahut, Holden, Messeri, & Haviland, 2005).
The theory of reasoned action has served as the impetus for additional theory (i.e., the
theory of planned behavior) as well as several models used to explain turnover (and, thus,
16
turnover intent) (i.e., Mobley, 1977; Mobley, Horner, Hollingsworth, 1978; Mobley,
Griffeth, Hand, and Meglino, 1979; Muchinsky & Morrow, 1980).
The basic concept of the theory of reasoned action (e.g., intention precedes
behavior) has been incorporated into a number of models explaining employee turnover
and its antecedent job satisfaction. The variable job satisfaction has traditionally been an
important variable assessed in job turnover studies (Hulin, 1968; Hulin, 1966a; Hulin,
1966b; Porter & Steers, 1973; Mobley, 1977; Price, 1977; Koch & Steers, 1978; Dittrich
& Carrell, 1979; Mobley et al., 1979; Muchinsky & Tuttle, 1979; Shikiar & Freudenberg,
1982; Carsten & Spector, 1987; Tett & Meyer, 1993; Hellman, 1997; Dormann & Zapf,
2001; Lambert, Hogan, & Barton, 2001; Karsh, Booske, & Sainfort, 2005). Over time,
the study of the job satisfaction-employee turnover relationship matured yielding a
number of models and incorporating a number of variables (albeit limited, according to
Maertz & Campion, 2004, who classified the models as process models of turnover even
though the limited attitudinal variables explained “why”). Several models (i.e., Mobley,
1977; Mobley et al., 1978; Mobley et al., 1979; Muchinsky and Morrow, 1980) appear
repeatedly in the literature, are based on the concept that intention to turnover precedes
turnover behavior, and test the basic premise that attitude influences satisfaction which in
turn influences intent. One model—Mitchell and Lee (2001)—differs significantly from
the traditional models listed previously yet has been modified to be incorporated into
traditional models. Each of these five models are discussed below.
17
First, Mobley (1977) proposed intermediate linkages in the process model
describing the job satisfaction-employee turnover relationship. Mobley suggested that
beginning with the evaluation of the existing job; an employee experiences job
satisfaction or dissatisfaction; thinks of quitting; evaluates the usefulness of job search as
well as cost of quitting; intends to, searches for, and evaluates alternatives compared to
present job; intentions to quit or stay; and quits or stays. Hom and Griffeth (1991) found
support for Mobley’s (1977) theory and suggested that job dissatisfaction may stimulate a
behavioral predisposition to withdraw. Additional researchers (Hom, Griffeth, & Sellaro,
1984) have also tested the model.
Second, the Mobley et al. (1978) model drew on Mobley (1977) and explained the
withdrawal decision process as flowing from job satisfaction to thoughts of quitting then
to search intention, quit intention, and turnover. According to Hom, Caranikas-Walker,
Prussia, Griffeth (1992), the Mobley et al. (1978) model has attracted “more research
attention than any other turnover theory” (p. 890) (See Miller, Katerberg, & Hulin, 1979;
Peters, Jackofsky, & Salter, 1981; Bannister & Griffeth, 1986; Dalessio, Sliverman, &
Schuck, 1986; Lee, 1988; Laker, 1991). Hom et al.’s (1992) use of Structural Equations
Modeling (SEM) corroborated the model better than previous studies.
Third, the Mobley et al. (1979) model is characterized by individual-level
turnover behavior; treatment of the evaluation of alternative jobs; recognition of
individual values, interests, and beliefs’ the proposition of possible joint contributions of
job satisfaction, job attraction, and attraction of attainable alternatives on turnover; and
18
the consideration of intention to quit as the immediate precursor of turnover. Michaels
and Spector (1982) found support for the model.
Fourth, the Muchinsky and Morrow (1980) model predicted that the relationship
between job satisfaction and turnover is based on the economy. This model conjectured
that the job satisfaction-turnover relationship is strongest during periods of low
unemployment and weakest during periods of high unemployment. Their model
recognized that the variable turnover intent served as the immediate precursor of
turnover. Several researchers have tested the Muchinsky and Morrow model. A meta-
analysis by Carsten and Spector (1987) replicated the meta-analysis conducted by Shikiar
and Freudenberg (1982) in an effort to correct methodological problems. Carsten and
Spector (1987) found support for the Muchinsky and Morrow model.
Fifth, Crossley, Bennett, Jex, and Burnfield (2007) found support for Mitchell and
Lee’s (2001) unfolding model of voluntary turnover during their examination of how the
concept of job embeddedness integrates into a traditional model of turnover. Job
embeddedness, loosely defined as a combination of forces that keep an employee from
leaving his or her job, includes forces such as marital status, community involvement,
and tenure. Job embeddedness includes two sub-factors—on-the-job embeddedness and
off-the-job embeddedness—and is represented by three facets: links (i.e., connections
between a person and institutions, locations, and people), fit (i.e., the fit between the
employee and both work and nonwork environments), and sacrifice (i.e., both material
and psychological benefits that may be forfeited by giving up one’s job or community).
19
These facets of job embeddedness mirror the rewards found in the Employee Value
Proposition (Ledford & Lucy, 2002).
The model tested in the current study utilized the basic concept of attitude
affecting intention leading to behavior as conveyed by Fishbein and Ajzen’s (1975)
theory of reasoned action and employed by the before-mentioned models of turnover
intent. (See Figures 1 and 2 in Appendix B for a graphic representing the withdrawal
process based on these models of turnover intent.) For the current study, employee
engagement, compensation fairness, and job satisfaction served as attitudes affecting
turnover intent considered to be the immediate precursor of actual turnover as suggested
by Fishbein and Ajzen (1975). (See Figure 5 in Appendix B for a graphic representing the
model connecting employee engagement, compensation fairness, and job satisfaction to
turnover intent.)
General Theoretical Framework: Age Effects, Cohort Effects
Because age-related differences in employee attitudes may be caused by a number
of factors, Rhodes (1983) suggested using a general framework that addresses period
effect (e.g., change in the work or nonwork environment), cohort effects (e.g., past
experiences, structure and size of cohort), age effects (e.g., psychosocial and biological
aging), and systematic error. An integrative theoretical orientation allows a more
comprehensive understanding of age-related differences in employee attitudes including
those regarding employee engagement, compensation fairness, job satisfaction, and
turnover intent. Since the current study utilized secondary data describing faculty from an
20
institution of higher education that was cross-sectional in nature and since cross-sectional
data includes both age and cohort effects, theoretical models such as Super’s Life-Span
Life-Space Theory and Generational Cohort Theory are useful in understanding both age
and cohort effects on variables impacting turnover intent and will be discussed more in
depth below.
Super’s Life-Span, Life-Space Theory
Systematically related to time and, therefore, developmental in nature, age-effects
in worker attitudes are related to both biological aging as well as psychosocial aging.
While biological aging refers to the physiological changes that occur as an individual
ages chronologically (e.g., changes in vision, balance, reaction time, strength, etc.),
psychosocial aging includes systematic changes in behavior, expectations, and needs as
well as and individual’s progression through a series of prescribed social roles along with
corresponding experiences (Rhodes, 1983). Super’s Life-Span, Life-Space Theory
addresses psychosocial aging associated with career development.
Super’s Life-Span, Life-Space Theory is one of several career stage theories
which parallel the stages of the family life cycle in that they both presume that discrete
stages build on each other and that there are appropriate developmental tasks appointed
for each stage (Wrobel, Raskin, Marazano, Frankel, & Beacom, 2003). Super’s Life-
Span, Life-Space Theory (also termed Theory of Career Development) is rooted in
differential psychology, self-concept theory, and developmental psychology (Osipow &
Fitzgerald, 1996). Super proposed that people endeavor to put their self-concept (i.e.,
21
beliefs about self) into practice by making choices to enter the vocation that allows self-
expression consistent with their self-concept (Osipow & Fitzgerald, 1996). Vocational
behaviors that are useful in the implementation of the self-concept, which matures with
age, are a function of the stage of life development for the individual. Vocational
decisions made during one stage of development are different from those made in other
stages of development, and, according to Super, this is due to the demands of the life
cycle on the individual’s attempt to implement the self-concept. “The career pattern
concept suggests that the life cycle imposes different vocational tasks on people at
various times of their lives” (Osipow& Fitzgerald, 1996, p. 112).
Super’s Life-Span, Life-Space Theory maintains that maturity and career
development are related, an individual’s career-related development is influenced by the
demands’ of the life cycle, there are specific tasks to be achieved at each life stage, and
the life stage is useful in describing what a person of a particular age is like and can do.
(Pietrofesa & Splete, 1975). Super defined 5 separate life stages (Pietrofesa & Splete,
1975):
• Growth Stage, occurring from birth to age 14 is characterized by role playing
and exploration of interests.
• Exploration Stage, occurring from age 15 to age 24, is characterized by role-
tryouts. Values and opportunities are considered.
• Establishment Stage, occurring from age 25 to age 44, is characterized by the
individual attempting to make a permanent place in an appropriate field.
22
• Maintenance Stage, occurring from age 45 to age 64 is characterized by very
little change, instead a continuation of filling roles previously chosen.
• Decline Stage, occurring from age 65 and above, is characterized by a decline
in physical and mental powers. Employees may become selective participants
or observers. Career deceleration and retirement occur.
Wrobel et al. (2003) reported that ages in Super’s career stages are not fixed, but
tasks at each stage are preparatory for tasks at the next stage. Individuals may recycle
back to earlier stages to crystallize their career objectives and then move forward.
Additionally, Super theorized that the following attitudes and behaviors are important to
vocational tasks: Crystallization (i.e., formation of ideas of appropriate work for self, 14-
18), Specification (i.e., narrow vocational choices to a general direction, 18-21),
Implementation (i.e., completion of training, 21-24), Stabilization (i.e., settling down,
changing position if necessary, 25-35), and Consolidation (i.e., establishes himself in his
position, 35 plus) (Osipow, 1968). The model tested in the current study utilized Super’s
Life-Span, Life-Space Theory to explain age effects that were expected in the employee
engagement-turnover intent relationship. See Figure 5 in Appendix B for a graphic
representing the relationship between employee engagement and turnover intent.
Super’s Life-Span, Life, Space Theory has many of the same weaknesses as each
of the career stage theories (see Miller & Form, 1951; Hall & Nougaim, 1968; Erikson,
1968; Sheehy, 1976; Levinson, Darrow, Klein, Levinson, & McKee, 1978; Schein, 1978;
Greenhaus, 1987; and Super, 1994). One criticism of career stage theory is that it has
23
traditionally been applied only to men (Wrobel et al., 2003) although Levinson and
Levinson (1997) tried to rectify this in their book “Season’s of a Woman’s Life.” A
second criticism is that career stage theory lacks validation through longitudinal research
(Wrobel et al., 2003). Third, stage demarcation differs according to theorist, some using
age, tasks, or other markers (Wrobel, et al, 2003). Similarly, according to Kacmar and
Ferris (1989), career stage theories are criticized for utilizing broad and contradictory age
ranges (and labels) to define phases of development. For example, Erikson used the terms
young adult (i.e., age 18 to 35), middle aged adult (age 35 to 55 or 65), and older or late
adult (i.e., age 55 or 65 to death) (Erikson, 1968; Learning Theories Knowledgebase,
2008). And, Levinson et al. (1978) uses the terms early adulthood (i.e., age 28 to 50),
middle adulthood (i.e., age 50 to 70), late adulthood (i.e., age 70 to 80), and late late
adulthood (i.e., age 80 and over) with transitional periods occurring between each stage.
Despite this criticism, career stage theories are helpful in linking phases of career
development to age ranges (Kacmar & Ferris, 1989).
Super’s Life-Span, Life-Space Theory also has many of the same strengths and
weaknesses as each of the career stage theories (see Miller & Form, 1951; Hall &
Nougaim, 1968; Erikson, 1968; Levinson et al., 1978; Schein, 1978; Greenhaus, 1987;
and Super, 1994). One strength is that they each have a common theme:
The main theme guiding any career stage theory is the assumption that people’s
careers follow a basic sequence. This sequence includes a young, middle, and old
adult phase, with different challenges facing individuals in each phase. Generally,
24
workers in the young adult phase try to fit into the adult working world, workers
in the middle phase are highly productive, and workers in the old adult phase
attempt to disengage from work (Kacmar & Ferris, 1989, p. 202).
Another strength is that these theories show recognition of the influence of the
employee’s entire life on career development tasks as well as the influence of the career
development tasks on the employee’s life outside of work (Kacmar & Ferris, 1989).
Finally, a particular strength for this study is its applicability to the understanding of the
impact of antecedents employee engagement, compensation fairness, and job satisfaction
on turnover intent among faculty in higher education. Bland and Bergquest (1997)
suggested that career development models (e.g., Super’s Life-Span, Life-Space Theory)
may be most appropriate to describe the periods of stability, stress, and transition that
aging faculty undergo as these types of models emphasize multiple stages and careers and
may be more encouraging of faculty to enable them to continue developing and using
skills.
Generational Cohort Theory
Cohort effects also influence age-related effects. Social cohorts include those
people who are born at the same time and then also age together (Rhodes, 1983).
Generational theories can be useful in describing the social cohorts (e.g., Traditionalists,
Baby Boomers, Generation X, and Millenials) that impose age-related effects on the
cross-sectional secondary data used in the current study. These social cohorts have been
described by birth years, size, structure, significant social events (i.e., war vs. peace,
25
economic climate, etc.), influential leaders, inventions, struggles, accomplishments, and
expression of values (Lancaster & Stillman, 2002; Zemke, Raines, & Filipczak, 2000;
Deal, 2007). Researchers, consultants, and other professionals have made use of what is
known about these social cohorts for practical applications in a variety of areas including
education and training, marketing choices, and work related issues including resolving
generational conflict in the workplace (Deal, 2007). The researcher has compiled
descriptors of these social cohorts to orient the reader to the general differences found is
these four social cohorts.
Traditionalists (also termed Veterans by Zemke et al., 2000), born 1900 to 1945,
number about 75,000,000, were influenced by Dr. Spock, Alfred Hitchcock, John Wayne,
Betty Crocker, and Franklin Delano Roosevelt (Lancaster & Stillman, 2002). Between
World War I, World War II, and the Great Depression, this generation had opportunity to
learn frugality (Lancaster & Stillman, 2002). Loyalty and patriotism are descriptive of
this group that spans two generations (Lancaster & Stillman, 2002). Core values include
dedication, hard work, respect for authority, patience, delayed reward, and honor (Zemke
et al., 2000). On the job, their assets include stability and attention to detail while
liabilities include difficulties with ambiguity and change (Zemke et al., 2000). Younger
Traditionalists (also called Schwarzkopfers) seek satisfying work that makes a
contribution to the organization and reflects their level of skill and expertise (Martin &
Tulgan, 2006).
26
Baby Boomers were born 1946 to 1964, number 80,000,000 strong, and were
influenced by personalities such as Martin Luther King Jr., Richard Nixon, Beaver
Cleaver, Barbra Streisand, Captain Kangaroo, and the Beatles (Lancaster & Stillman,
2002). Television was the greatest invention of their youth. Optimism is descriptive of
this group who grew up in a relatively affluent world (Zemke et al., 2000; Lancaster &
Stillman, 2002). Competitive is another descriptor for the boomers (Lancaster &
Stillman, 2002), who, due to the sheer number of competitors (at school, in the
community, and in the workplace), will have to spend more time in the same jobs
awaiting advancement while facing additional competition from Generation X who will
be demanding higher wages due to labor shortages among that generation (Light, 1988).
Core values of the baby boomers include personal gratification, personal growth, work
and involvement (Zemke et al., 2000). On the job, baby boomers are driven and want to
please but are somewhat sensitive to feedback, judgmental of those who look at things
differently, and somewhat reluctant to go against their peers (Zemke et al., 2000). Martin
& Tulgan (2006) suggested to honor the opinions, skills, and contributions of Boomers as
they (particularly the older Boomers) have a strong commitment to the mission of the
organization (Martin & Tulgan, 2006).
Generation Xers were born between 1965 and 1980 and number 46,000,000
(Lancaster & Stillman, 2002). Leading people during their formative years included Bill
Clinton, Monica Lewinsky, Beavis and Butt-head, O. J. Simpson, and Madonna
(Lancaster & Stillman, 2002). Gen Xers are described as skepticists having grown up
27
during a time when major corporations were called into question and the divorce rate
tripled (Lancaster & Stillman, 2002). And, even though the inventions of cable tv, video
games, microwaves, cell phones, and the personal computer were invented to simplify
life, the xers were plagued with the complications of AIDS, drugs, child molestation, and
drunk driving (Lancaster & Stillman, 2002). Generation X grew up in the time of a
wavering economy putting them into the highest child-poverty rates, and later, in the
lowest wage and homeownership rates. Then, they were told they would be the first
generation of Americans that would not be as financially well off as their parents (Martin
& Tulgan, 2006). Core values include diversity, balance, informality, and self-reliance
(Zemke et al., 2000). On the job, Gen Xers are technoliterate, creative, and unintimidated
by authority, while liabilities include impatience, inexperience, poor “people” skills, and
cynicism (Zemke et al, 2000). Martin & Tulgan (2006) suggested offering Generation X
career development opportunities as they seek increased authority, prestige, status, and
reward.
The Millennial Generation (or Nexters, according to Zemke et al., 2000, and
Generation Y, according to Martin & Tulgan, 2006) was born between 1981 and 1999
and number 76,000,000 (Lancaster & Stillman, 2002). This Echo Boom generation has
been influenced by Prince William, Barney, Buffy, Marilyn Manson, and Mark McGwire
(Lancaster & Stillman, 2002). This generation grew up with all previous technology plus
the information highway (Lancaster & Stillman, 2002). Gangs, the availability of drugs,
and violent school outbreaks such as Columbine may to blame for Millenials naming
28
“personal safety” (p. 29) as their most serious workplace issue (Lancaster & Stillman,
2002). Millennials can be described as realistic (Lancaster & Stillman, 2002). Core
values, according to Zemke et al. (2000), include optimism, confidence, sociability, and
diversity. On the job, Millennials have tenacity, capabilities to multi-task, and
technological savvy, while liabilities include the need for structure and supervision.
Millenials enjoy challenging work, creative expression, freedom, and flexibility (Martin
& Tulgan, 2006). They seek employers who care about them and who create meaningful
products or services but also where they can make meaningful contributions (Martin &
Tulgan, 2006). Millenials demand immediate feedback and have “an obsession with
training and development” (Martin & Tulgan, 2006, p. 17). Martin and Tulgan (2006)
suggested best management practices for Millenial include establishing coaching
relationships.
Concerning both Generation X and the Millenials, Twenge (2006) communicated
the uniqueness of these generations in the book “Generation Me: Why Today’s Young
American’s Are More Confident, Assertive, Entitled—and More Miserable Than Ever
Before.” Twenge described these generations as having a feeling of entitlement that
extends to salary and duties in the workplace. Furthermore, salary is very important to
them, especially at a time when the housing market has far-outpaced inflation. They do
not take criticism well but do work hard when praised and recognized. They learn best
through hands-on activities and not lectures.
29
Higher Education
For the current study, the mediating effects of job satisfaction along with the moderating
effects of age on selected proposed antecedents of Turnover Intent were assessed among
faculty at an institution of higher education. This relationship may be increasing in
importance as several researchers (Bland et al., 2006; Harrison & Hargrove, 2006) have
forecasted the shortage of faculty in higher education. Low exit rates coupled with slower
growth in the number of new faculty positions has produced an aging faculty (Clark &
d’Ambrosio, 2005). With as many as half of the nation’s faculty retiring by 2015, the
world of academia will likely undergo major changes to compensate for the shortages.
Even though there are benefits to faculty turnover (e.g., the capacity to hire
younger faculty members, the opportunity to reallocate monies across different program
areas, and the chance to diversify faculty with regards to gender, race, and ethnicity)
(Nagowski, 2006), finding replacements for the aging faculty is a major concern
(Harrison & Hargrove, 2006). The faculty search process is reasonably similar to filling
other positions, with the exception that the students suffer when the process is not
completed in a timely manner. According to Glandon and Glandon (2001), faculty search
committees screen applicants for the consideration of qualified candidates who are
interviewed, perhaps multiple times until a candidate is selected. The process is complete
when the candidate accepts the employment offer. If the candidate does not accept the
offer, the committee will continue to invite applicants in order to fill the position. This
process, especially when repeated for multiple positions, consumes time on behalf of the
30
committee that could be better used for student appointments, research, and course
preparation (Glandon & Glandon, 2001).
Doyle (2008) wrote that the average age of faculty increased from 46 in 1988 to
50 in 2004. This is due in part to the fact that higher education not only has a no
mandatory retirement age but also guaranteed employment to the tenured. While colleges
are waiting for the baby boomers to begin to retire, they have begun to become more
dependent on faculty members who are part-time or adjunct. According to Doyle (2008)
when current professors do retire, colleges are likely to see the percentage of faculty that
are employed on a contingent basis escalate.
There are few studies of faculty turnover in higher education (Glandon &
Glandon, 2001). This may be due in part to the lower exit rates (Clark & d’Ambrosio,
2005). Several research studies are highlighted here based on their relevance to the
current study. Several researchers have noted a relationship between intent to leave
among faculty based on the work environment/climate. Ruhland (2001) cited that one of
the most common reasons faculty gave for leaving technical colleges in Minnesota was
institutional climate. Still others (Bright, 2002) have found differences in attitudes
towards recognition given at work between African-Americans and Caucasian-American
full-time, contractual, non-tenured track faculty members at a community college
employed between 1 and 5 years. The Segal Group’s (2007) Rewards of Work Study
resulted in some interesting findings related to intent to leave among faculty. Most of the
respondents in higher education reported being satisfied with 4 of the 5 elements of the
31
Employee Value Proposition: 90% were satisfied with work content, 67% were satisfied
with affiliation (e.g., feelings of belonging to an organization with shared values), 60%
were satisfied with career (e.g., development opportunities), 59% were satisfied with
benefits, but only 30% were satisfied with compensation. Compared to other respondents,
those in higher education were more satisfied with work content (90% vs. 75%),
affiliation (67% vs. 61%), and career (60% vs. 53%), but less so with benefits (58% vs.
69%) and compensation (30% vs. 70%). When considering the importance of the EVP
elements for retention, compared to respondents from other organizations, those
respondents in higher education were more likely to cite work content (85% vs. 81%),
affiliation (61% vs. 56%), and benefits (69% vs. 64%) but less likely to cite career (64%
vs. 65%) and compensation (66% vs. 79%). Bland and Bergquist (1997) suggested that
when employees are meaningfully engaged and ensured competence, senior faculty can
maintain vitality, avoid burnout, and continue to lead their institutions. Finally,
BlessingWhite (2008) reported finding that employees in academia and higher education
have the lowest engagement rate of surveyed industries.
Assumptions of the Study
Assumptions of the study included the following:
1. Subjects had time, could access, and were able to read and complete the
survey.
2. Subjects honestly responded to questions in spite of potential concerns they
had regarding the security of their jobs.
32
3. The study produced results generalizeable only to the organizations or work
sites serving as data collection points.
Summary
High turnover among key, productive employees and low productivity due to the lack of
engagement among employees are both costly for organizations. Because employee
engagement is a fairly new concept in the literature, there is a lack of information
connecting employee engagement with other “soft” data such as turnover intent.
Furthermore, there is a lack of information regarding these same variables at institutions
of higher learning. Utilizing secondary data describing employees from an institution in
higher education, the current study tested the mediating effects of Job Satisfaction on the
relationship between antecedents Employee Engagement and Compensation Fairness on
the outcome variable Turnover intent. The study utilized the Theory of Reasoned Action
and a theoretical framework for examining age-related effects on employee attitudes as
theoretical underpinnings for the study.
33
CHAPTER II
Review of the Literature
“It does not seem to be true that work necessarily needs to be unpleasant. It may always
have to be hard, or at least harder than doing nothing at all. But there is ample evidence
that work can be enjoyable, and that indeed, it is often the most enjoyable part of life.”
(Csikszentmihalyi, 1990, p. 145).
Utilizing secondary data describing faculty from an institution of higher education, the
current study tested the mediating effects of Job Satisfaction and the moderating effects
of Age on the relationship between the antecedents Employee Engagement and
Compensation Fairness on the outcome variable, Turnover Intent. (See Figure 5 in
Appendix B for a model representing the proposed relationships.) The review of the
literature will be presented in the following manner: (a) employee engagement, (b)
compensation fairness, (c) turnover intent, (d) employee engagement with turnover intent
(e) compensation fairness with turnover intent, (f) job satisfaction, (g) employee
engagement, job satisfaction, and turnover intent, (h) compensation fairness, job
satisfaction, and turnover intent, (i) age, (j) moderating effects of age, and (k) summary.
Employee Engagement
The review of the literature focused on employee engagement will be presented in the
following manner: (a) defining employee engagement, (b) employee engagement,
employee disengagement, and burnout; (c) prevalence of employee engagement; (d)
34
employee engagement as a multidimensional concept; (e) employee engagement vs.
organizational commitment; (f) personal engagement; and (g) promotion of employee
engagement.
Defining Employee Engagement
For the current study, employee engagement as a characteristic of the workplace
environment was the focus. However, employee engagement has also been defined as the
act of an employee being involved in, enthusiastic about, and satisfied with his or her
work (Seijts et al., 2006; Harter, Schmidt, & Hayes, 2002; Gubman, 2004; Harrison,
2007). However, it is important to note that different organizations may define employee
engagement differently (Lockwood, 2007) and that the definitions used are frequently
ambiguous (Macey & Schneider, 2008). For example, Lockwood (2007) defined
employee engagement as “the extent to which employees commit to something or
someone in their organization, how hard they work and how long they stay as a result of
that commitment” (p. 2). And, Harter, Schmidt, and Hayes (2002) defined employee
engagement as “the individual’s involvement and satisfaction with as well as enthusiasm
for work” (p. 269). Schaufeli and Bakker’s (2004) definition of engagement differed
somewhat, for according to them, engagement is “a positive, fulfilling, work-related state
of mind that is characterized by vigor, dedication, and absorption” (p. 295). Schaufeli and
Bakker further defined vigor, dedication, and absorption:
“Vigor is characterized by high levels of energy and mental resilience while
working, the willingness to invest effort in one’s work, and persistence also in the
35
face of difficulties. Dedication is characterized by a sense of significance,
enthusiasm, inspiration, pride, and challenge . . .absorption is characterized by
being fully concentrated and happily engrossed in one’s work, whereby time
passes quickly and one has difficulties with detaching oneself from work” (p.
295).
Csikszentmihalyi’s (1990) “flow” is similar to the absorption component of engagement.
Demerouti (2006) also described flow as absorption and further expanded the idea by
suggesting that flow (and absorption and engagement) is an enjoyment of work, and
intrinsic work motivation, directly related to motivating job characteristics. There are
observable components of employee engagement: Gubman (2004) stated that engaged
employees “perform well, want to stay with their employers, and say good things about
them” (p. 43). Moreover, engaged employees are easily motivated and frequently put
forth extra effort (Harrison, 2007).
The Segal Group, Inc. (2006d) defined engagement as “knowing what to do and
wanting to do the work (p. 3). The Segal Group, Inc. (2006d) explained that knowing
what to do includes a desire to do the work, understanding the organization’s vision, as
well as an understanding of job expectations. Furthermore, wanting to do the work
includes getting satisfaction from the job and being inspired to perform the work. By
combining scores from their two-factor model of engagement in a 2 X 2 engagement
characteristics matrix (i.e., “knowing what to do at work” vs. “wanting to do the work”),
The Segal Group, Inc. (2006d) was able to contrast engaged employees (Quadrant 1)
36
with renegades (Quadrant 2) who know what to do but do not want to do it, disengaged
employees (Quadrant 3) who do not know what to do nor do they want to do it, and
enthusiasts (Quadrant 4) who do not know what to do but want to do it. If engaged
workers are those who know what to do and want to do it (The Segal Group, Inc., 2006d),
then no wonder Towers Perrin (2003) described engaged employees as “the ultimate
prize for employers” (p. 2).
Employee Engagement, Employee Disengagement, and Burnout
Several researchers (Demerouti, Bakker, Nachreiner, & Schaufeli, 2001; Bakker,
Demerouti, Taris, Schaufeli, & Schreurs, 2003; Schaufeli & Bakker, 2004; Hakanen,
Bakker, & Demerouti, 2005; and Hakenen, Bakker, & Schaufeli, 2006) have noted
relationships between burnout and engagement and job demands and job resources.
Demerouti et al. (2001) found support for the job demands-resources model that proposes
two categories of working conditions: job demands and job resources. In addition,
Demerouti et al. (2001) reported that job demands are related to the exhaustion
component of burnout while job resources (or lack thereof) are related to disengagement.
Baker et al. (2003) reported support for the job demands-resources model explaining that
burnout develops when job demands are high and job resources are limited leading to
energy depletion and decreased motivation. Schaufeli & Bakker (2004) called
engagement a positive antipode of burnout and suggested that since burnout and
engagement differ on possible causes and consequences, they likely also differ on
intervention strategies that will be successful if burnout is to be reduced or engagement is
37
to be enhanced. More recent research has demonstrated that job resources are helpful for
coping with high demands and staying engaged in work among dentists (Hakanen et al.,
2005). Finally, Hakenen et al. (2006) found support for the energetical process (i.e.,
burnout mediates the relationship between job demands and ill health) as well as the
motivational process (i.e., engagement mediates the relationship between job resources
and organizational commitment). Burnout has been measured using the Oldenburg
Burnout Inventory (Halbesleben, 2003) as well as the Maslach Burnout Inventory
(Jackson, Tothman, & Van de Vijver, 2006). Jackson et al. (2006) reported that when
both the Maslach Burnout Inventory and the Utrecht Work Engagement Scale are
combined, both negative and positive characteristics of occupational well-being (i.e.,
burnout and work engagement) can be incorporated into one model.
Prevalence of Employee Engagement
In the 2003 Towers Perrin Talent Report, employee engagement was assessed
across 40,000 employees (just under 36,000 in the U.S. and approximately 4,400 in
Canada). The report found 17% of employees were highly engaged; 64% of employees
were moderately engaged; and 19% were disengaged. Of these employees, the highest
percentage of employee engagement was found upon senior executives; the lowest
percentage of employee engagement was found among nonmanagement hourly
employees. Conversely, the highest percentage of disengaged employees were found
among nonmanagement hourly employees and the lowest percentage of disengaged
employees were found among senior executives. Considering industry type, employee
38
engagement was highest among employees in the nonprofit sector. Also, Sanford (2003)
reported that Gallup Poll’s research on employee engagement suggested engaged
employees comprise 29% of the U.S. workforce while 55% are not engaged and 16% are
disengaged.
Employee Engagement as a Multidimensional Concept
Many researchers have reported that employee engagement is a multidimensional
concept (Jones & Harter, 2005) with cognitive (or rational), emotional (or affective), and
behavioral components (Konrad, 2006). The Towers Perrin Talent Report confirmed a
definition of employee engagement that includes both emotional and rational variables.
According to the report, “[t]he emotional factors tie to people’s personal satisfaction and
sense of inspiration and affirmation they get from their work and from being part of their
organization” (p. 4). Furthermore, Alewweld and von Bismarck (2002/2003) reported
that Hewitt Associates considers engaged employees to have three characteristic
behaviors: first, employees “say” positive things about their organization to other
employees and customers; second, employees have a desire to “stay” in the company; and
third, employees “serve” the company by exerting additional, discretionary effort (p. 66).
Lockwood (2007) described the cognitive, emotional, and behavioral components as
follows:
Cognitive engagement refers to employees’ beliefs about the company, its leaders
and the workplace culture. The emotional aspect is how employees feel about the
company, the leaders and their colleagues. The behavioral factor is the value-
39
added component reflected in the amount of effort employees put into their work
(e.g., brainpower, extra time and energy) (p. 7).
In a recent article, Macey and Schneider (2008) suggested that both researchers
and practitioners have used the term employee engagement to refer to states (including
feelings of energy, absorption, satisfaction, involvement, and commitment), traits
(including positive life and work views as well as a proactive personality), and behaviors
(including extra-role behavior, initiative, and role-expansion) of employee engagement.
Several researchers have criticized Macey and Schneider’s (2008) position on employee
engagement. For example, Dalal, Brummel, Wee, and Thomas (2008) suggested that
engagement likely has both trait-like as well as state-like components, is a construct that
is cognitive-affective in nature (not behavioral), and that Macey and Schneider’s idea of
behavioral engagement would be better referred to as a behavioral consequence of
engagement. Hirschfeld and Thomas’s (2008) criticisms included the failure of Macey
and Schneider to explain how the personality-based constructs of trait engagement (i.e.,
autotelic personality, proactive personality, and conscientiousness) possess the central
theme of human agency. Human agency, according to Hirschfeld et al. (2008), can be
described as the individual differences that individuals have over their thoughts and
intentions that shape their circumstances in a manner to help the individual achieve their
goals. While Macey and Schneider focused on the construct of employee engagement at
the individual level, Pugh and Dietz (2008) recommended that employee engagement
should be conceptualized at the organizational level due to its theoretical usefulness and
40
practical utility as well as the nomological network. Newman and Harrison (2008) agreed
with Macey and Schneider position that employee engagement is simply a new term for
previously researched concepts and demonstrated this by comparing items of the Utrech
Work Engagement Scale with items measuring job satisfaction, organizational
commitment, and job involvement.
Employee Engagement vs. Organizational Commitment
Because some researchers have suggested that employee engagement is similar to
the concept of organizational commitment (Lockwood, 2007), it is important to
differentiate between the two. Organizational commitment includes the following
components: (a) affective commitment represents the employee’s attitudes regarding the
alignment of personal and organizational goals, (b) continuance organizational
commitment represents the employee’s desire to stay with organization in light of costs
associated with leaving (i.e., seniority, pension plans, etc.), and (c) normative
organizational commitment represents the employee’s decision to stay with an
organization because he or she feels obligated (Clugston, 2000). While it is likely that
highly engaged employees will remain with their organization, there does exist the
possibility that they will leave and may do so for a variety of reasons (e.g., unfulfilled
expectations, job-person mismatch, too little coaching, feeling devalued, and lack of trust
and confidence; Branham, 2005). Employee engagement does not imply organizational
commitment. The concepts have been further differentiated in a 2006 study where
41
Hallberg and Schaufeli found empirical support that work engagement, job involvement,
and organizational commitment are different constructs.
Personal Engagement
Contrasting with organizational views of employee engagement and taking a more
personal viewpoint, Kahn’s (1990) personal engagement theoretical frames explains that
people express themselves physically, cognitively, and emotionally in the roles they
occupy; people are more excited and content with their roles when they draw on
themselves to perform their roles; and people vary in their levels of attachment to their
roles. Kahn (1990) surmised that “People become physically involved in tasks, whether
alone or with others, cognitively vigilant, and empathetically connect to others in the
service of the work they are doing in ways that display what they think and feel, their
creativity, their beliefs and values, and their personal connections to others” (p. 700).
Furthermore, Kahn suggested that people vary their levels of personal engagement
according to the meaningfulness of a situation (or perceived benefits), the perceived
safety of a situation, and their availability based on resources they perceive they have.
May, Gilson, and Harter (2004) further explored the concepts of meaningfulness, safety,
and availability and found that meaningfulness had the strongest relationship with work
engagement via job enrichment and role fit while safety was linked to supportive
supervisor relations.
Kahn’s concept of disengagement is analogous to Hochschild’s (1993) term
robotic, Goffman’s (1959, 1961a, 1961b) terms apathetic or detached, Hackman and
42
Oldham’s (1980) concept called effortless, and Maslach and Jackson’s (1986; see also
Maslach, 1993; Maslach, Jackson, & Leiter, 1996; Maslach, & Leiter, 1997; Maslach, &
Schaufeli, 1993; Maslach, Schaufeli, & Leiter, 2001, and Llorens, Bakker, Schaufeli, &
Salanova, 2006) concept of burnout. According to Bakker et al. (2003), burnout develops
when demands on the job are high but resources are limited. These working conditions
frequently lead to a depletion of energy to the extent that motivation is undermined and
opportunities for learning are limited. According to Kahn, an individual can become
disengaged and defend the self (or protect himself or herself) by withdrawing and hiding
his or her true identity, ideas, and feelings. Or, said another way, the individual shuts
down who he or she really is to perform the task.
Kahn’s theory of personal engagement is useful for understanding how “self” can
be either expressed or thwarted through a work role. The theory suggests that for the
same role different employees will develop different levels of attachment (or
engagement). The theory is also helpful when explaining the “drivers” of personal
engagement and how these “drivers” may be related to indicators of personal
engagement, such as job satisfaction and turnover intent (Lockwood, 2007). The theory
suggests that the cognitive, emotional, and physical expression of self in a work role is
the individual’s reaction to characteristics of that particular role. The current study
focused on better understanding the work characteristics that likely influence the
engagement levels of employees.
43
Promotion of Employee Engagement
Employee engagement (the central focus for the current study) includes elements
within the workplace environment that “attract, focus, and keep the most talented
employees” (Buckingham and Coffman, 1999, p. 28). According to Lockwood (2007),
“HR leaders, as well as managers, have the mission to build and sustain a workplace
environment that fosters engagement and is also attractive to potential employees” (p.
11). The 12 employee engagement items derived from the Gallup Workplace Audit
(GWA) were grouped into four “camps” as suggested by Gallup and cited by
Buckingham and Coffman (1999). These camps (or groups) were created for conceptual
or utilitarian reasons (e.g., training and development) and not necessarily for empirical
reasons. After the GWA’s appearance in Buckingham and Coffman (1999), Harter,
Schmidt, and Hayes (2002) demonstrated that the 12 items are unidimensional. The first
group was referred to as Base Camp or “What do I get?” (Buckingham and Coffman,
1999), and consisted of the variables expectations and materials. The second grouping
was entitled Camp 1 or “What do I give?”, according to Buckingham and Coffman
(1999) Camp 1 consisted of the variables opportunity, recognition, care, and
development. The third group was referred to as Camp 2 or “Do I belong here?”
(Buckingham and Coffman, 1999) and included the variables opinions count, mission,
quality work, and best friend. The last group was entitled Camp 3 or “How can we all
grow?”, according to Buckingham and Coffman (1999), and included the variables
progress/appraisal and learn and grow.
44
One impediment for better understanding the Gallup Workplace Audit (GWA) is
the link between the 12 items of the GWA with related concepts in the literature. This
task was not satisfactorily presented when the GWA was first published in Buckingham
and Coffman (1999). One such link found in the literature is Oldham, Hackman, Janson,
and Purdy’s (1975) theory of job enrichment explaining how workers get “turned on” (p.
57) to work through certain job characteristics. These job characteristics (measured by
the Job Diagnostic Survey) included skill variety (i.e., different activities involving
different talents and skills of the employee) which is similar to one characteristic of
employee engagement referred to as learn and grow, task identity (i.e., the completion of
a job with an identifiable outcome) which mirrors expectations, task significance (i.e., the
degree the job has impact on others) which is similar to the characteristic of employee
engagement referred to as mission, autonomy (i.e., freedom for the employee to schedule
work and determine procedures to carry out tasks) which may mirror opportunity, and
feedback (i.e., information about performance effectiveness) which is similar to
progress/appraisal (Oldham & Hackman, 1981). According to Hackman, et al. (1975),
motivation and satisfaction on the job has been accredited by psychologists to critical
psychological states including meaningfulness of work, responsibility, and knowledge of
results. Of the five job characteristics, three of the job characteristics (i.e., skill variety,
task identity, and task significance) contribute to meaningful work, while autonomy
contributes toward personal responsibility, and feedback contributes to knowledge of
45
results (Hackman, Oldham, Janson, & Purdy, 1975). See below and refer to Table 2 in
Appendix C for references to the Job Diagnostic Survey.
The following paragraphs assign variable labels—the convention of the author—
to each of the 12 items of the GWA as well as define each of the 12 variables using
similar items from other commonly used scales in the literature such as the Job
Diagnostic Survey. See Table 2 in Appendix C.
Expectations
Expectations (as measured by the GWA item “Do I know what is expected of me
at work?”) is similar to Seigts and Crim’s (2006) idea of convey where leaders (i.e.,
management and supervisors) clarify work-related expectations for employees. Similar
items appear in Spector’s (1997) Job Satisfaction Survey, Campion’s (1988)
Multimethod Job Design Questionnaire, Ivancevich and Matteson’s (1980) Stress
Diagnostic Survey, and House, Schuler, and Levanoni’s (1983) measure of Role Conflict
and Ambiguity (i.e., “I don’t know what is expected of me” in Fields, 2002, p. 149).
According to Gupta-Sunderji (2004), goals should be clearly defined—“[n]o employee
should have to question what’s expected of them (p. 38).
Materials
The variable Materials (as measured by the GWA item “Do I have the materials
and equipment I need to do my work right?”) referred to the availability of materials,
equipment, and resources that workers need in order to accomplish their jobs
(Buckingham and Coffman, 1999; Towers Perrin Talent Report, 2003). Rentsch and
46
Steel’s (1992) measure of Satisfaction with Job Facets; House, McMichael, Wells,
Kaplan, and Landerman’s (1979) Occupational Stress Scale; and Rizzo, House, and
Lirtzman’s measure of Role Conflict and Ambiguity (i.e., “I receive assignments without
adequate resources and material to execute them” in Fields, 2002, p. 147) utilized similar
items (See Table 2 in Appendix C). Seigts and Crim (2006) stated that “not giving people
the knowledge and tools to be successful is unethical and de-motivating; it is also likely
to lead to stress, frustration, and, ultimately, lack of engagement” (p. 3).
Opportunity
Opportunity (as measured by the GWA item “At work, do I have the opportunity
to do what I do best every day?”) referred to occasions that employees have to do what
they do best on a daily basis (Buckingham and Coffman, 1999). Similar items have been
used in Bacharach, Bamberger, and Conley’s (1991) measure of Job Satisfaction Relative
to Expectations; Weiss, Dawis, England, and Lofquist’s (1967) Minnesota Satisfaction
Questionnaire; Cook, Hepworth, Wall, and Warr’s (1981) measure of Global Job
Satisfaction; Frese, Kring, Soose, and Zempel’s (1996) measure of Control and
Complexity; and Xie’s (1996) measure of Perceived Ability-Job Fit (i.e., “I feel that my
work utilizes my full abilities”, in Fields, 2002, p. 233). (See Table 2 in Appendix C).
Recognition
Recognition (as measured by the GWA item “In the last seven days, have I
received recognition or praise for doing good work?”) involved recognition or praise used
as a reward doing good work in an effort to encourage future efforts. Similar items have
47
appeared in Cook, Hepworth, Wall, and Warr’s (1981) measure of Global Job
Satisfaction; Balfour and Wechsler’s (1996) Organizational Commitment Scale;
Campion’s (1988) Multimethod Job Design Questionnaire; Oldham & Cummings’
(1996) measure of Supportive and Non-Controlling Supervision; Eisenberger,
Huntington, Hutchinson, and Sowa’s (1986) measure of Perceived Organizational
Support; and Spector’s (1997) Job Satisfaction Survey (i.e., “When I do a good job, I
receive the recognition for it that I should receive” in Fields, 2002, p. 15). (See Table 2 in
Appendix C).
Seigts and Crim (2003) reported that good leaders recognize frequently by
congratulating, coaching and conveying recognition. Unfortunately, as many as 65% of
Americans have reported that they have received no recognition for good work at their
job in the past year (Rath & Clifton, 2004). Strong, healthy organizations show
recognition and praise for small and large contributions to the organization on a frequent
basis which serves to boost worker self-esteem (Trivette, 1990; Stinnett & DeFrain,
1985).
Care
Care (as measured by the GWA item “Does my supervisor, or someone at work,
seem to care about me as a person?”) referred to the attention and interest senior
management, supervisors, and co-workers offer employees (Buckingham and Coffman,
1999; Towers Perrin Talent Report, 2003). Similar items have appeared in Balfour and
Wechsler’s (1996) Organizational Commitment Scale and Eisenberger, Huntington,
48
Hutchinson, and Sowa’s (1986) measure of Perceived Organizational Support (i.e., “The
organization really cares about my well-being” in Fields, 2002, p. 118). (See Table 2 in
Appendix C).
When supervisors care, listen, help, and protect their employees, the employee
feels supported (Baruch-Feldman, Brondolo, Ben-Dayan, & Schwartz, 2002). Care
includes affirmation, support, respect, and trust, which are viewed as necessities (Curran,
1983). Care creates cohesion or emotional bonding which also provides supportiveness,
psychological safety, and a sense of identification (Smith & Stevens, 1992) as well as
boosts members’ self-esteem (Stinnett & DeFrain, 1985).
Encouragement
Encouragement (as measured by the GWA item “Is there someone at work who
encourages my development?”) extended past opportunities for career advancement
(Towers Perrin Talent Report, 2003) and included support offered by other workers to
further the employee’s development through challenging and meaningful work
(Buckingham and Coffman, 1999; Towers Perrin Talent Report, 2003). Development
may also include supervisor endorsement of the training and development (Huczynski &
Lewis, 1980; Baldwin & Ford, 1988; Russ-Eft, 2002) as well as coaching (Deal, 2007).
Similar items have appeared in Hackman and Oldham’s (1974) Job Diagnostic Survey;
Oldham and Cummings’ (1996) measure of Supportive and Non-Controlling
Supervision; and Greenhaus, Parasuraman, and Wormley’s (1990) measure of
Supervisory Support (i.e., “My supervisor keeps me informed about different career
49
opportunities for me in the organization” and “My supervisor supports my attempts to
acquire additional training or education to further my career” in Fields, 2002, p. 108).
(See Table 2 in Appendix C).
Opinions Count
Opinions Count (as measured by the GWA item “At work, do my opinions seem
to count?”) referred to whether or not an employee’s opinions were taken into
consideration such as in a collaborative work environment (Tower Perrins, 2003). These
collaborative work environments are often characterized by trust and cooperation and
may outperform groups which were lacking in positive relationships (Seigts & Crim,
2003). Similar items have been used in Cook, Hepworth, Wall, and Warr’s (1981)
measure of Global Job Satisfaction; Eisenberger, Huntington, Hutchinson, and Sowa’s
(1986) measure of Perceived Organizational Support (i.e., “The organization cares about
my opinions” in Fields, 2002, p. 118); and Kahn, Wolfe, Quinn, and Snoek with
Rosenthal’s (1964) Job-Related Tension Index. (See Table 2 in Appendix C).
Mission
Mission (as measured by the GWA item “Does the mission/purpose of my
company make me feel my job is important?”) involved Seigts and Crim’s (2006) ideas
of both clarity (i.e., clear communication of the organization’s vision and goals) and
contribute (i.e., the communication to employees as to their contributions towards the
organization’s success) or “helping employees understand their significance in the big
picture” (Gupta-Sunderji, 2004, p. 38). Similar items appear in several other sources
50
including Spector’s (1997) Job Satisfaction Survey; Hackman and Oldham’s (1974) Job
Diagnostic Survey; Campion’s (1988) Multimethod Job Design Questionnaire;
Ivancevich and Matteson’s (1980) Stress Diagnostic Survey; and Remondet and
Hansson’s (1991)measure of Work-Specific Control Problems (i.e, “My job is
meaningless” in Fields, 2002, p. 141). (See Table 2 in Appendix C). Mission is important
for healthy organizations; this common mission can create congruence regarding the
value and importance of time and energy spent by the employees towards meeting the
mission, needs, and functions of the organization (Trivette, 1990).
Quality Work
Quality Work (as measured by the GWA item “Are my co-workers committed to
doing quality work?”) referred to the devotion that co-workers have in doing their best
work (Buckingham and Coffman, 1999), which may be useful in spurring healthy
competition among employees and employee work groups. Alternatively, incompetence
may breed resentment and animosity leading potentially to employee turnover. Similar
items appear in Spector’s (1997) Job Satisfaction Survey (i.e., I find I have to work
harder at my job than I should because of the incompetence of people I work with” in
Fields, 2002, p. 15) and Roznowski’s (1989) Job Descriptive Index. (See Table 2 in
Appendix C). Studies involving total quality management (Elçi, Kitapçi, & Ertürk, 2007)
and organization quality improvement environment (Karsh, Booske, & Sainfort, 2005)
have suggested that true quality in organizations go beyond that of employees doing good
work to a workplace environment that embraces continual improvement.
51
Best Friend
Best Friend (as measured by the GWA item “Do I have a best friend at work?”)
referred to employees having someone at the organization that they can both confide in
and trust. Similar items appear in Sims, Szilagyi, and Keller’s (1976) Job Characteristic
Survey (i.e., “How much opportunity is there to meet individuals who you would like to
develop friendship with?” and “To what extent do you have the opportunity to talk
informally with other employees while at work” in Fields, 2002, p. 76-78) and O’Reilly,
Chatman, and Caldwell’s (1991) Organizational Culture Profile. (See Table 2 in
Appendix C).
Dale Carnegie (1936) suggested in his book “How to Win Friends and Influence
People” that in order to make friends, one must show interest in others, smile, call people
by their name, listen to them, talk about their interests, and generally make them feel
important. Rath and Clifton (2004) suggest that making friends in the workplace is a key
strategy for increasing positive emotions. However, as suggested by the related survey
item from Sims et al.’s (1976) Job Characteristic Survey, there must be opportunity in the
work day to communicate, show care, and encourage others as well as endorsement from
superior’s to interact.
Progress/Appraisal
Progress/Appraisal (as measured by the GWA item “In the last six months, has
someone at work talked to me about my progress?”) referred to whether someone in the
organization has spoken to the employee about his or her progress toward personal or
52
company goals (Buckingham & Coffman, 1999). Similar items have appeared in
Roznowski’s (1989) Job Descriptive Index; Hackman and Oldham’s (1974) Job
Diagnostic Survey; Sims, Szilgyi, and Keller’s Job Characteristics Survey; Campion’s
(1988) Multimethod Job Design Questionnaire; and Greenhaus, Parasurman and
Wormley’s (1990) measure of Supervisory Support (i.e., “My supervisor gives me
helpful feedback about my performance” and “My supervisor gives me helpful advice
about improving my performance when I need it” in Fields, 2002, p. 108). (See Table 2 in
Appendix C).
Performance coaching can include both formal and informal feedback that an
employee receives from various individuals within an organization about performance on
the job (Holton, Bates, & Ruona, 2000) and is often a part of the performance appraisal
process, an evaluation of an employee’s performance, which includes three steps:
defining the job, appraising the performance, and providing feedback in an effort to
eliminate deficiencies in performance and encourage satisfactory work (Dessler, 2000).
Managers often provide this feedback as a part of the many resources that they are
responsible for providing to employees for continued employee growth and development
(Steelman, Levy, and Snell, 2004). While performance feedback may be given by
supervisors, performance appraisals can be performed by any number of individuals
within the organization (i.e., supervisors, peers, self, and subordinates) as well as
individuals outside the company (i.e., customers) as in the case of a 360-degree feedback
appraisal. The growth of the business or company rests in part on the quality of the
53
appraisals as appraisals often provide information for promotion and salary decisions as
well as information to guide improvement in both the employee and the organization
(Dessler, 2000). Michael, Leschinsky, and Gagnon (2006) reported findings that
employees that were provided with constructive feedback that was rich in content and
delivered in a timely manner are more likely to make improvements in their performance
on the job.
Learn and Grow
Learn and Grow (as measured by the GWA item “The last year, have I had
opportunities at work to learn and grow?”) referred to whether training and development
opportunities have been provided for the employee (Buckingham & Coffman, 1999).
Similar items have appeared in other surveys in the literature: Hackman and Oldham’s
(1974) Job Diagnostic Survey; Frese, Kring, Soose, and Zempel’s (1996) measure of
Control and Complexity; Greenhaus, Parasuraman, and Wormley’s (1990) measure of
Supervisory Support; Wayne, Shore, and Liden’s (1997) measure of Developmental
Experiences; Ivancevich and Matteson’s (1980) Stress Diagnostic Survey; and O’Reilly,
Chatman, and Caldwell’s (1991) Organizational Culture Profile (i.e., “Opportunities for
professional growth”, 1 of 54 Q-sort items, in Fields, 2002, p. 223). (See Table 2 in
Appendix C).
Compensation Fairness
The second antecedent for the current study is compensation fairness which may be
defined as the perceptions that employees have regarding equity in company practices
54
concerning internal compensation, external compensation, and benefits. The review will
begin with a discussion of compensation.
Compensation
According to Milkovich et al. (2005), compensation refers to “all forms of
financial returns and tangible services and benefits employees receive as part of an
employment relationship” (p. 602). Concerning compensation, there are two components:
direct financial payments and indirect payment (Dessler, 2000). Direct financial
payments include “wages, salaries, incentives, commissions, and bonuses” (Dessler,
2000, p. 396) and these are paid to employees based on increments of time or on
performance. Indirect payments include financial benefits and will be discussed under
Employee Benefits. Dessler (2000) stated that legal, union, policy, and equity factors
influence the design of organizational pay plans. Without these factors, compensation
plans may be perceived as unfair. Legal and equity factors will be discussed.
There are many legal factors that influence the design of organizational pay plans
and its administration. Across the last 76 years, the United States Congress has passed
many acts standardizing wages and making salaries “fair.” This is primarily due to four
concepts of comparable job worth used in the U.S.: “(1) equal pay for equal work, (2)
equal pay for similar work, (3) equal pay for equal worth, and (4) pay parity” (Patten,
1988, p. 4). There are several legal acts that have been instrumental in changing the shape
of compensation as it is regarded today. The Davis-Bacon Act of 1931 allowed the
Secretary of Labor to set wage rates for individuals employed by contractors working for
55
the federal government (McGregor, 2005). The Walsh-Healey Public Contract Act of
1936 set labor standards for employees working on government contracts totaling more
than $10,000 (Schwartz, 1983). The Fair Labor Standards Act of 1938 provided for
minimum wage, maximum hours, pay for overtime, and child labor protection (SHRM
Research, 2003; Irwin, 2007). The Equal Pay Act of 1963 required that women be paid
equally for doing the same work as men (Lax, 2007). The Civil Rights Act of 1964 made
it illegal to discriminate in employment based on race, color, religion, sex, or national
origin. Title VII is also known as the Equal Employment Opportunity Act and established
the Equal Opportunity Employment Commission (Tomascovic-Devey & Stainback,
2007). The Employee Retirement Income Security Act (ERISA) of 1974 provided for
government protection of employee pensions as well as regulated vesting rights (Gerbasi,
2003). Finally, the Tax Reform Act of 1986 overhauled the tax code and affected
compensation by changing the tax rates to three brackets (15%, 28%, and 31%) and the
distribution of benefits (Shulz, McGraw, & Steenbergen, 1992).
In addition to legal issues, specifically ones that govern equality for those of
different races, colors, religions, sexes, or national origins (e.g., The Equal Employment
Opportunity Act), the perception of equity is also a critical issue in the determination of
pay (Dessler, 2000). Pay should have both external equity (e.g., pay is considered
equitable to those doing similar work outside the organization) and internal equity (e.g.,
pay is considered equitable to those doing similar work within the organization). Without
external equity, employers will find it difficult to attract and retain qualified employees
56
(Dessler, 2000). Without internal equity, employers will likely face difficult situations
with employees. It is important that employees perceive equity in their pay. Without this
perception of equity, employees may solicit employers for more pay or less work, reduce
the amount of their work to an amount they feel is “fair,” or leave (Pritchard, 1969).
Employers (specifically human resources) can be instrumental in determining how
employees feel about pay equity through frequent surveys addressing the employees’
satisfaction with their pay (Dessler, 2000).
Employee Benefits
An employee benefit is an “indirect financial payment given to employees”
(Dessler, 2000, p. 476) Employee benefits may include holidays, vacations, personal
leave, funeral leave, jury duty leave, military leave, sick leave, short and long term
disability, life insurance, medical insurance, dental insurance, vision care, retirement
plans, severance pay, child care assistance, wellness programs, employee assistance
programs, and educational assistance (U. S. Department of Labor, 2000). It is important
to differentiate between defined benefit plans and defined contributions plans. According
to Dickerson (2004), “A defined benefit plan is a retirement plan that uses a specific,
predetermined formula to calculate the amount of an employee’s guaranteed future
benefit. A defined contribution plan is a type of retirement plan in which the employer
makes specified contributions to individual employee accounts, but the amount of the
retirement benefit is not specified” (http://www.bls.gov).
57
While benefits help round out the entire compensation package for an employee,
they are quite costly for an organization. For the 4
th
quarter of 2006, the U.S. Department
of Labor, Bureau of Labor Statistics, reported that the average cost of total benefits (i.e.,
cost per hour worked) for civilian occupations was $8.30 and was equivalent to 30.1 % of
total compensation (http://data.bls.gov/cgi-bin/surveymost
). In addition, the Bureau of
Labor Statistics reported that for private industry, the average cost of total benefits was
equivalent to $7.57 per hour and 29.5% of total compensation, and for state and local
government, the average cost of total benefits was $12.52 per hour and equal to 32.7% of
total compensation. Furthermore, Dessler (2000) reported that the administration of
benefits has become an increasingly difficult and specialized task, as benefits must be
administered in compliance with federal law. There are several laws that impact benefits
(and, thus, their perceived fairness). The Family and Medical Leave Act of 1993
guarantees employees up to 12 weeks of leave for illness of a child, spouse, parent, or
self as well as the adoption or birth of a child (Armenia & Gerstel, 2006). The Worker
Adjustment and Retraining Notification Act of 1989 necessitates that employers give
written notification (60 days) of closures or layoffs (Ryan, 1992). The Americans with
Disabilities Act (ADA) influences the handling of worker’s compensation cases
(O’Keeffe, 1993). The Pregnancy Discrimination Act of 1978 is an amendment to Title
VII of the Civil Rights Act prohibiting sex discrimination (Dorman, 1995). The
Comprehensive Omnibus Budget Reconciliation Act makes health benefits available to
retired and laid-off employees through the employer at a cost to the individual (Elliot,
58
1993; Milkovich et al., 2005). The Health Insurance Portability and Accountability Act
provides for tax deductions based on long-term health care insurance premiums (Krauss,
2003). The Employee Retirement Incomes Security Act restricts companies with regard
to pension plans (Gerbasi, 2003). The list continues.
Benefits have changed over time. Aside from the selection of benefits now
available, the increased costs associated with offering benefits, and the legal aspects that
influence benefits, there have also been changes in the accessibility of benefits.
According to a 2006 National Compensation Survey, not all workers have access to
retirement and health care benefits. White-collar workers are more likely to have access
to defined contribution benefits (65%) compared to blue-collar workers (53%) but less
likely to have access to defined benefits (23%) compared to blue-collar workers (25%).
Those workers in service occupations are less likely to receive retirement and healthcare
benefits compared to workers in white-collar and blue-collar occupations. For example,
both white-collar and blue-collar workers were found to have greater access to medical
care benefits (77% for both) than workers in service occupations (45%). Full time
workers were reported to have greater access to benefits than part time workers.
Unionized workers (70%) were found to have greater access to benefits than non-
unionized workers (15%). The accessibility (or lack of accessibility) of benefits may be
considered unfair by some. The availability of benefits does not imply the consumption
of the same. Peterson and Trout (2007) reported that there is an affordability gap with
respect to benefits. They reported that companies are paying the same or even larger
59
amounts for benefits for employees and buying a greatly diminished benefits package for
their employees. The rising cost of health care is primarily to blame. Employers respond
to this affordability gap by shifting responsibility to employees in the form of defined
contribution plans (versus pension plans) and high-deductible health plans. Therefore,
there are substantial differences in the consumption of employee benefits across time. For
example, according to Wiatrowski (2000), in 1979, the percentage of workers with health
insurance was 97%. In 1997, the percentage of workers with health insurance was 76%.
In 1979, the percentage of workers with defined benefit pensions was 87% compared to
50% in 1997. In 1997, the percentage of workers with a defined contribution plan was
57%.
According to Lowerre and Brazzell (2007), one of the most important goals of a
benefits plan is to attract and retain employees. Unfortunately, employee benefits are not
necessarily working to recruit and retain (Hiles, 2006). Hiles stated several reasons that
benefits are not working effectively: 1) benefits do not address specific issues with
precision (e.g., generous child care benefits generates resentment among employees with
no children); 2) benefits are costly and difficult to predict (and, therefore, to budget); 3)
benefits are on short-term and long-term time frames; 4) benefits change substantially
from year to year; and 5) benefits cannot be provided by the parent company alone.
According to Palmer (2006), today’s employees know how much they are worth and will
walk away from the negotiating table if an offer is not considered good enough. In order
to determine which benefits are most helpful in attracting and retaining employees, it may
60
be necessary to think outside the box. Ryan (2005) stated that many things not typically
associated with traditional benefits might be important if we will ask the right questions
(e.g., What do you like about working here?”) and listen to what employees say. Hiles
(2006) urged, “Study your employees’ benefit preferences as aggressively as if you were
trying to understand customer preferences for a product your company sells” (p. 66).
Then, perhaps, human resource professionals can begin to do a better job in recruiting
and retaining valuable employees.
Turnover Intent
The outcome variable specified for this study is turnover intent. In the literature, it is also
commonly referred to as intent or intention to leave and intent or intention to turnover.
The review will begin with a discussion of turnover.
Turnover
In 2000, Bernthal and Wellins reported that turnover was widespread. In fact, of
the employees surveyed by Bernthal and Wellins, almost 1/3 expected to leave their job
within the next year and 20% of them estimated the likelihood of their leaving was
greater than 50%. While Bernthal and Wellins suggested that turnover is likely to
increase, Ledford and Lucy (2002) reported just the opposite: in the period from 2000 to
2003, turnover (at its peak in 2000) decreased as unemployment increased. Specific to
higher education, some surveys (i.e., the National Center for Education Statistics’
National Study of Postsecondary Faculty Survey) have indicated that as many as half of
the nation’s faculty in higher education will retire by the year 2015 (Bland et al., 2006).
61
The costs of turnover can be staggering. For U.S. businesses, the Journal of
Business Strategy (2003) reported total turnover estimates at $5 trillion annually
(although by some standards this estimation appeared somewhat inflated). For individual
businesses, Bliss (n.d.) suggested that the calculations for the cost of turnover could reach
150% of the annual compensation figure for an employee (200% to 250% for those in
managerial and sales positions). Furthermore, Bliss suggested that for a mid-sized
company with 1,000 employees, experiencing a 10% turnover rate (per year), and
assuming an average salary of $50,000, the annual turnover costs are $7.5 million. The U.
S. Department of Labor (DOL, www.dol.gov/cfbci/turnover.htm) warned that businesses
and organizations cannot afford the continual practice of recruiting applicants, training
workers, and then watching them leave. The DOL presented a “cost-of-turnover”
worksheet so that one could determine how turnover may affect the organization’s
bottom line.
The problem of turnover is not always addressed effectively even though human
resource professionals consider it problematic. Bernthal and Wellins (2000) reported that
greater than 1/3 of human resource professionals they surveyed saw retention as a
pressing issue. However, almost half of organizations interviewed had no formal strategy
for addressing the problem of retention. International Survey Research (ISR, n.d.)
suggested that most organizations rely on the reactive strategy of gaining data from exit
interviews to make organizational changes to promote retention. This is problematic,
because according to ISR, not only is this reactive, but the data captured at an employee’s
62
exit does not accurately represent the state of mind the employee was in when he or she
contemplated leaving the organization. ISR suggested that in order to be truly proactive,
organizations need to understand the key factors that influence turnover. Furthermore,
Bernthal and Wellins (2000) suggested that the most effective interventions are those that
include the understanding of WHY employees leave.
Turnover Intent
For the current study, turnover intent refers to the voluntary (vs. involuntary as in
termination) intention of an employee to leave an organization. Carmeli and Weisberg
(2006) used the term turnover intentions to refer to 3 particular elements in the
withdrawal cognition process (i.e., thoughts of quitting the job, the intention to search for
a different job, and then intention to quit). See Figures 1 and 2 in Appendix B. While
employees may intend to leave voluntarily due to the relocation of a spouse, redefined
personal role (e.g., primary care giver for an aging parent or staying home with a child or
new infant), or retirement, of particular concern to the employer (and human resources) is
when highly-productive, key employees intend to leave based on reasons often within the
control of the employer.
Theoretically, turnover intent (and turnover) has been explained using Fishbein
and Ajzen’s (1975) theory of reasoned action which purports that intentions mediate the
relationship between attitudes and behavior. Consequently, attitudes about the job,
management, co-workers, supervisor, organization, available alternative jobs, and self
may encourage a behavioral predisposition to remain or withdraw from the organization.
63
Information regarding these linkages offers valuable insight to how and why employees
leave.
Research using turnover intent (vs. turnover) as the dependent variable is
common (Lum, Kervin, Clark, Rid, Sirola, 1998). This is due to both theoretical and
practical reasons. Theoretically, several researchers (Mobley et al., 1979; Arnold &
Feldman, 1982; Steel & Ovalle, 1984; Breukelen, Van Der Vlist, & Steensma, 2004)
have suggested that intention to turnover is the best predictor of actual turnover. Steel and
Ovalle (1984) reported calculating a correlation of .50 between intention and employee
turnover. Similarly, Ledford and Lucy (2002) found when using a matched sample, half
of those considered high risk for turnover changed employers compared to only 9% of
those rated at low risk for turnover. On the practical side, the examination of an
employee’s turnover intent allows the opportunity for human resources to take a
proactive approach to increasing retention and delaying turnover in an organization as
opposed to gleaning the same information from an exit interview associated with a
voluntary turnover. Additional research on turnover intention has revealed that the length
of time between obtaining predictor data influences the magnitude of the intention-
turnover relationships (Steel & Ovalle, 1984). Finally, Porter, Steers, Mowday, and
Boulian (1974) reported that relationships between attitudes and turnover are strongest at
times closest to when the individual exits the organization.
64
Employee Engagement with Turnover Intent
Because of its infancy, there is a dearth of information on the relationship between
employee engagement and turnover intent. Much of the information available addresses
employee engagement as a characteristic of the individual versus employee engagement
as a characteristic of the workplace environment. For example, in general, the results
have suggested that the more engaged an employee is, the less likely he or she is to leave.
For example, the 2003 Towers Perrin Report addressed employee engagement and
turnover and found that 66% of highly engaged employees reported that they have no
plans to leave compared to 36% of moderately engaged individuals and 12% of
disengaged employees. Furthermore, 2% of highly engaged employees reported they are
actively looking for another job compared to 8% of moderately engaged and 23% of
disengaged employees. Gubman (2004) also reported that disengaged employee are more
likely to actively look for another job. And, The Segal Group, Inc. (2006d) found an
inverse relationship between employee engagement and turnover intent. Additionally,
The Segal Group, Inc. (2006b) found that disengaged employees have the highest
turnover intentions (38%) compared to renegades (19%), enthusiasts (5%), and engaged
employees (1%). Finally, Ellis and Sorensen (2007) described that employees who
reported higher levels of engagement also reported lower levels of turnover intentions.
Concerning employee engagement as a characteristic of the workplace, surveys
such as the Job Diagnostics Survey have been useful in linking job characteristics (i.e.,
skill variety, task identity, task significance, autonomy, and feedback shown earlier to
65
overlap with many of the facets of employee engagement) with personal and work
outcomes including high quality work, increased satisfaction, low absenteeism, and
turnover (Hackman et al., 1975). To date, based on a review of the literature, there are no
studies that assess the relationship between 12 individual items assessing employee
engagement as measured by the GWA and turnover intent. Jones and Harter (2005)
assessed race effects on the employee engagement-turnover intent relationship using a
composite score for the GWA. Two studies report relationships between the 12 individual
items of the GWA and retention, but not the variable turnover intent. First, Buckingham
and Coffman (1999) reported that 5 of the 12 questions of the GWA have shown a link to
retention: (a) “Do I know what is expected of me at work?” (b) “Do I have the materials
and equipment I need to do my work right?” (c) “Do I have the opportunity to do what I
do best every day?” (d) “Does my supervisor, or someone at work, seem to care about me
as a person?” (e) “At work, do my opinions seem to count?” Second, Harter, Schmidt,
and Keyes (2002) found each of the previous items to have the strongest and positive
relationships to retention as well as “The last year, have I had opportunities at work to
learn and grow?” All other items were cited to have a weaker but positive relationship
with retention except best friend and progress/appraisal. Because of this apparent gap in
the literature to link the 12 individual items with turnover intent, the following review
seeks to show relationships between the 12 facets of employee engagement and turnover
intent. (See Table 2 in Appendix C).
66
Expectations with Turnover Intent
Expectations (as measured by the GWA item “Do I know what is expected of me
at work?”) has been found to be positively related to retention by both Buckingham and
Coffman (1999) and Harter et al., (2002). In general, researchers (Youngberg, 1963;
Macedonia, 1969; Lyons, 1971) have found a negative relationship between role clarity
(vs. role ambiguity) and turnover. Concerning turnover intent (also turnover motivation
or propensity to leave), researchers have generally found a positive relationship between
role ambiguity and turnover intent. House and Rizzo (1972) found that role ambiguity
and propensity to leave were significantly but weakly correlated. Using a sample of 651
employees across 5 organizations, Gupta and Beehr 1979) found intention to turn over
significantly and positively correlated with role ambiguity (.13) In a meta-analysis,
Jackson and Schuler (1985) found propensity to leave correlated with role ambiguity at
.29. Jamal (1990) found role ambiguity and turnover motivation correlated positively at
.31. Using House, Schuler, and Levanoni’s (1983) measure of Role Conflict and
Ambiguity, Westman (1992) and O’Driscoll and Beehr (1994) found that role ambiguity
correlated positively with turnover intention (in Fields, 2002). However, not all
researchers have found a negative relationship between role clarity and turnover. For
example, using similar survey items found in Rizzo, House, and Lirtzman’s (1970)
measure of Role Conflict and Ambiguity, Netemeyer et al. (1990) found that role
ambiguity did not directly affect propensity to leave (in Fields, 2002).
67
Materials with Turnover Intent
Materials (as measured by the GWA item “Do I have the materials and equipment
I need to do my work right?”) has been found to be positively related to retention by both
Buckingham and Coffman (1999) and Harter et al. (2002). In the related literature, the
lack of needed materials is frequently referred to as resource inadequacy. Several
researchers have found a positive relationship between resource inadequacy and turnover
intent. Using a sample of 651 employees across 5 organizations, Gupta and Beehr (1979)
found intention to turnover significantly and positively correlated with resource
inadequacy (15). Jamal (1990) found resource inadequacy and turnover motivation
correlated positively at .38. Next, in a study of job stress and using a sample for
Malaysian and Pakistani employees, Jamal (2007) found resource inadequacy positively
intercorrelated to turnover intention (.24 and .26, respectively). Finally, Deal (2007)
reported that approximately 45% of Silents (or Traditionalists), Boomers, Generation
Xers and Generation Y (or Millenials) cited availability of resources as one thing their
organization can offer employees in exchange for their retention and commitment.
Opportunity with Turnover Intent
Opportunity (as measured by the GWA item “At work, do I have the opportunity
to do what I do best every day?”) has been found to be positively related to retention by
both Bucking ham et al. (1999) and Harter et al. (2002). In the related literature,
Opportunity—or, congruence of job with vocational interests—has demonstrated a
negative relationship with turnover (Ferguson, 1958; Boyd, 1961; Mayeske, 1964). Using
68
a sample of 651 employees across 5 organizations, Gupta and Beehr 1979) found
intention to turnover significantly and positively correlated with underutilization of skills
(.29).
Recognition with Turnover Intent
Recognition (as measured by the GWA item “In the last seven days, have I
received recognition or praise for doing good work?”) was shown to have a weaker but
positive relationship to retention by Harter et al. (2002). Researchers (Ross & Zander,
1957; General Electric Company, 1964) have found a negative relationship between
receipt of recognition and the variable turnover. Spector (1985) found every subscale of
the Job Satisfaction Scale was significantly related to intention to turnover with the mean
correlation for contingent rewards and turnover intent highest at -.36. International
Survey Research (n.d.) cited that the lack of recognition and rewards was one of several
key drivers for turnover intent. Additionally, using a national sample of faculty, Rosser
(2004) found that perceptions of work life, including rewards, had a direct impact on
satisfaction and intentions to leave. Next, Fields (2002) reported that Oldham and
Cummings’ (1996) measure of Supportive and Non-Controlling Supervision was
correlated negatively with intentions to quit and Eisenberger, Huntinton, Hutchinson, and
Sowa’s (1996) measure of Perceived Organizational Support was correlated negatively
with turnover intentions (Eisenberger et al., 1990; Lee & Ashforth, 1993; Cropazano et
al., 1997). Both of these measures included items similar to the GWA measuring
Recognition. Finally, Deal (2007) reported that approximately 45% of Silents (or
69
Traditionalists), Boomers, Generation Xers and Generation Yers (or Millenials) cited
respect and recognition as one thing their organization can offer employees in exchange
for their retention and commitment.
Care with Turnover Intent
Care (as measured by the GWA item “Does my supervisor, or someone at work,
seem to care about me as a person?”) has been found to be positively related to retention
by both Buckingham and Coffman (1999) and Harter et al. (2002). Researchers (Evan,
1963; Hulin, 1968; Farris, 1971; Telly, French, & Scott, 1971) have found a negative
relationship between satisfactory peer group interactions and turnover. While care can be
communicated from management as well as from co-workers, it appears that the
supervisor, especially the immediate supervisor, may have the most critical role in
communicating care in an effort to reduce turnover. Jamrog (2004) has suggested that
“[t]he front line in building an environment that works to retain and engaged key talent
will be leaders, especially immediate supervisors” (p. 29). The role of supervisor is a
critical role in an organization as supervisors are agents of an organization (Rhoades &
Eisenberger, 2002). Researchers (Fleishman & Harris, 1962; Saleh, Lee, & Prien, 1965;
Ley, 1966; Hulin, 1968; Skinner, 1969; and Telly, French, & Scott, 1971) have
consistently found a negative relationship between satisfaction with supervisory relations
and turnover. And, O’Driscoll and Beehr (1994) reported that doubt about acceptance
from one’s supervisor generally predicted turnover intentions. Fleishman and Harris
(1962) reported that foremen who failed to show care toward their employees had higher
70
incidences of grievances and turnover. Conversely, care communicated by supervisors
(and others) appears to have positive effects on the workplace. According to Gubman
(2003), relationships that are characterized by care can increase worker’s investments in
the workplace: “Warm relationship help employee feel connected, like who they are
matters. This multiplies their motivations to help you meet your goals.” (p. 36-37).
Encouragement with Turnover Intent
Harter et al. (2002) cited development (as measured by the GWA item “Is there
someone at work who encourages my development?”) as positively related to retention.
After citing learning, advancement, opportunity, recognition, and resources as acceptable
exchanges for retention and commitment, coaching was indicated as one of the top 5
delivery methods for learning both “soft” skills and “hard” skills (Deal, 2007). For the
Deal (2007) study, 85% of surveyed workers indicated coaching as useful. Coaching is an
excellent way to help employees learn and grow due to the individualized and targeted
nature of the instruction. McCauley and Wakefield (2006) suggested that in order to
successfully manage talent effective communication through coaching is necessary.
Coaches (and mentors) present opportunities and challenges for growth, supports goal
setting, encourages, listens, and gives honest appraisals and feedback (DeLong, Gabarro,
& Lees, 2008). And, coaching has been cited as useful in retaining employees (Strategic
Finance, 2007).
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Opinions Count with Turnover Intent
Opinions Count (as measured by the GWA item “At work, do my opinions seem
to count?”) was cited by both Buckingham and Coffman (1999) and Harter et al. (2002)
are positively related to retention. Additional research tends to support the relationship
between opinions count and turnover intent. For example, one study suggested that when
employees feel involved in their job, they are less likely to turnover even if their pay is
poor (Van Yperen, Hagedoom, & Guerts, 1996). Based on studies by the U.S.
Department of Labor, not feeling appreciated (i.e., having the feeling that what one does
and what one says doesn’t matter) is the number-one reason people leave their jobs (Rath
& Clifton, 2004, p. 31). Concerning full-time faculty members at an urban community
college, Dee (2004) found that faculty who reported higher levels of support (for
innovation) were less likely to intend to leave.
Mission with Turnover Intent
Mission (as measured by the GWA item “Does the mission/purpose of my
company make me feel my job is important?”) was found to have a weak but positive
relationship with retention by Harter et al. (2002). Concerning the relationship between
Mission and turnover, the “tie” is two-fold. First, there must be mission or purpose within
an organization. Gupta-Sunderji (2004) suggested that by helping employees create a
sense of purpose within the organization, managers can reduce turnover. Second, the
mission must be tied to the individual’s job. This may require direct communication
between the immediate supervisor and the employee. Some positions may be easier to tie
72
(i.e., have a more direct link) to the purpose or mission than others. Brown and Yoshioka
(2003) reported that 3 principles influence employee attitudes toward an organization’s
mission: the employee must be aware of the mission (i.e., awareness); the employee must
agree with the mission (i.e., agreement); and the employee must see their work as aligned
with the mission (i.e., alignment). Mission attachment (i.e., awareness, agreement, and
alignment) was found to be significantly correlated with intention to stay (.43) for 304
employees in a nonprofit youth and recreation services organization. In a similar study,
Kim and Lee (2007) reported that mission attachment significantly correlated with
turnover intentions (-.40).
Quality Work with Turnover Intent
Quality Work (as measured by the GWA item “Are my co-workers committed to
doing quality work?”) was found to have a weak but positive relationship with retention
by Harter et al. (2002). Other studies involving organization quality improvement
environment and total quality management show negative relationships with turnover
intent. Karsh et al. (2005) reported that an organization quality improvement environment
was significantly and negatively correlated with turnover intention. Furthermore, Elçi et
al. (2007) reported findings that supported the idea that a quality culture is negatively
related to turnover intent but positively related to organizational commitment, job
satisfaction, and job performance. Total quality management, an organization-wide
activity, is a useful philosophy that requires a skilled and committed workforce and
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embraces business excellence; quality culture in an organization is a system of values
centered on excellence (Elçi et al., 2007).
Best Friend with Turnover Intent
Best Friend (as measured by the GWA item “Do I have a best friend at work?”)
was not reported to have a significant relationship with retention by either Buckingham
and Coffman (1999) or Harter et al., (2002). However, The Segal Group’s (2007)
Rewards of Work Study reported that for those respondents in higher education, 73%
rated friendly coworkers as “Important” or “Extremely Important” in considering whether
or not to leave their current job. Researchers (Evan, 1963; Hulin, 1968; Farris, 1971;
Telly, French, & Scott, 1971) have found a negative relationship between satisfactory
peer group interactions and turnover. Furthermore, researchers (Fleishman & Harris,
1962; Saleh, Lee, & Prien, 1965; Ley, 1966; Hulin, 1968; Skinner, 1969; and Telly,
French, & Scott, 1971) have consistently found a negative relationship between
satisfaction with supervisory relations and turnover. In a meta-analysis, Humphrey,
Nahrgang, & Morgeson (2007) found social characteristics (i.e., interdependence,
feedback from others, and social support) were more predictive of turnover intent than
work design characteristics (i.e., skill variety, task variety, significance, feedback from
the job, information processing). Others (Expansion Management, 2005) have reported
that employees with friends in the workplace are generally more satisfied (an antecedent
of turnover intent) and more productive.
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Progress/Appraisal with Turnover Intent
Progress/Appraisal (as measured by the GWA item “In the last six months, has
someone at work talked to me about my progress?”) was not reported to have a
significant relationship with retention by either Buckingham and Coffman (1999) or
Harter et al., (2002). In general, researchers (Ross & Zander, 1957; General Electric
Company, 1964) have found a negative relationship between receipt of feedback and the
variable turnover. Obstruction to receiving feedback is also correlated with turnover
intent. According to Walsh, Ashford, and Hill (1985) obstructed supervisor feedback
included the inaccessibility of supervisor and the perception of risk in asking one’s
supervisor for feedback, while obstructed co-worker feedback occurred when employees
felt they were not part of a work group with whom they could compare their work. In the
Walsh et al. (1985) study, obstruction of co-worker feedback correlated significantly with
turnover intent (.39), and obstruction of supervisor feedback correlated positively and
significantly with turnover intent (.56). Additionally, results of regression analysis
suggested that obstruction of supervisor feedback is contributory to intention to turnover
(Walsh et al., 1985). Progress/Appraisal appears to be important for respondents in higher
education as 41% rated coaching and mentoring as “Important” or “Extremely Important”
in considering whether or not to turnover (The Segal Group, 2007).
Learn and Grow with Turnover Intent
Learn and Grow (as measured by the GWA item “This last year, have I had
opportunities at work to learn and grow?”) was reported to have a strong positive
75
relationship with retention by Harter et al. (2002). Lankau and Scandura (2002) reported
that relational job learning (i.e., increased understanding about the connectedness of
one’s job to others) but not personal skill development (i.e., interpersonal skills) is
significantly related to intention to leave (-.16 vs. -.05). International Survey Research
(n.d.) cited that poor individual development and career advancement was one of several
key drivers for turnover intent. Grawitch, Trares, and Kohler (2007) found growth and
development correlated significantly with turnover intent (-.23). Finally, The Segal
Group’s (2007) Rewards of Work Study reported that for those respondents in higher
education, 44% rated training opportunities as “Important” or “Extremely Important” in
considering whether or not to leave their current job.
To summarize, turnover intent (or intention to turnover, intention to quit, etc.) has
been studied as the immediate precursor of turnover. And, research associated with the
manifest variables that comprise employee engagement has suggested that their resulting
factor is inversely related to turnover intent. Therefore, for the current study, the
following hypothesis was tested:
Hypothesis 1a: Employee Engagement is inversely related to Turnover Intent.
Compensation Fairness with Turnover Intent
For employees in any business or industry, compensation and benefits are important as
they provide the means for employees to meet their needs for basic necessities in life. For
the employer, compensation and benefits are important as well: they are one of the most
visible rewards in the process of recruitment (Milkovich & Newman, 2005); they are a
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means to retain the best employees (Vandenberghe & Tremblay, 2008); compensation
and benefits are used to motivate employees in the development of skills (Milkovich &
Newman, 2005); and compensation and benefits are exchanged for performance
(Vandenberghe & Tremblay, 2008). Concerning pay and turnover intent, the negative
relationship between pay level and turnover intent has been reported so frequently by
economists that the relationship has been accepted as a fact (Montowidlo, 1983). Even in
teaching institutions, pay is a significant element explaining turnover intent (Heckert &
Farabee, 2006). However, more information is needed to understand both the affective
and cognitive variables that mediate the relationship between pay and turnover intent
(Montowidlo, 1983). This includes concepts such as compensation fairness, pay
satisfaction, and pay expectation.
For the current study, compensation fairness referred to the perceptions that
employees have regarding equity in company practices concerning internal
compensation, external compensation, and benefits. Equity theory research from the
1970s (e.g., Carrell & Dettrich, 1976) supported the premise that workers who felt
unfairly paid leave their organizations, this being particularly true for those who felt they
were paid too little (Milkovich & Newman, 2005). According to Tekleab, Bartol, and Liu
(2005), perceptions of pay equity depend less on actual value than on comparative issues
as employees compare their pay with employees within their organization and across
other organizations. Many employees have the perception that pay allocations decisions
are sometimes unfair (Vandenberghe & Tremblay, 2008) in spite of the fact that details of
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employees’ compensation packages are not publicized. Hence, Vandenberghe and
Tremblay (2008) and Tekleab, Bartol, and Liu (2005) cited distributive and procedural
justice as determinants of pay satisfaction which impact turnover. (Distributive justice
focuses on the outcomes and includes “people’s feelings and behaviors in social
interactions [that] flow from their assessments of the fairness of their outcomes when
dealing with others” (Tyler & Blader, 2003, p. 350). Alternately, procedural justice
focuses on the process and involves the method in which decisions were made
concerning the delivery of outcomes). Accordingly, pay influences perceptions of pay
equity which determines pay satisfaction, which partially influences whether a worker
will remain with their current employer or seek for a different job (Montowidlo, 1983).
The goal? Reasonable pay reduces turnover (Hom & Griffest, 1995; Kim, 1999).
Pay satisfaction and intentions to quit mediate the relationship between effects of
pay on turnover (Motowidlo, 1983). Empirical support in favor of the pay satisfaction-
turnover relationship came from Hulin (1968). Empirical support not in favor included
Koch and Steers (1978); Kraut (1975); Mobley, Horner, & Hollingsworth (1978);
Newman (1974); Waters and Roach (1971). Inconsistencies could be attributed to other
variables that mediate the pay satisfaction-turnover relationship (e.g., intention to quit,
intention to search). Kraut (1975) and Mobley et al (1978) but not Newman (1974)
reported significant correlations between pay satisfaction and intention to quit but not
between pay satisfaction and turnover (Motowidlo, 1983). Concerning pay satisfaction,
there are four factors regarding pay satisfaction are at stake: pay level, pay raises,
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benefits, and pay structure and administration (Vandenberghe & Tremblay, 2008).
However, pay raise satisfaction (not level) was a significant predictor of intent to
turnover (Tekleab, Bartol, & Liu, 2005). This leads us to the idea of pay expectation--
“the perceived probability of receiving more satisfying pay in another job” (Motowidlo,
1983, p. 485—which may also impact turnover intent.
In sum, researchers have suggested that when pay is reasonable, especially in
comparison with other’s pay, a worker is less likely to turnover. Therefore, for the current
study, the following hypothesis was tested:
Hypothesis 1b: Compensation Fairness is inversely related to Turnover Intent.
Job Satisfaction
Job satisfaction, the contentment an individual has with her or her job, has been
researched among a wide variety of subjects including human services workers (Eisenstat
and Felner, 1984), retail pharmacists (Shulz, Bigoness, & Gagnon, 1987), academic
administrators (Glick, 1992), child care teachers (Pope and Stremmel, 1992), clergy
(Morris & Blanton, 1994), women and minority faculty (Olsen and Maple, 1995),
pediatric nurses (Lum, et al., 1998), academic faculty (Rosser, 2004), and non-academic
employees at a university (Smerek & Peterson, 2007). Job satisfaction has been reviewed
both qualitatively and quantitatively (Judge, Bono, Thoresen, & Patton, 2001).
Regardless of the population being surveyed, most researchers would tend to
agree that employers benefit when employees have high levels of job satisfaction as job
satisfaction among employees has been tied to increased productivity, creativity, and
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commitment to the employer (Syptak, Marsland, Ulmer, 1999). Piper (2006) reported that
a benefit of the employee satisfaction survey is the implied message that the employees in
an organization are valued and appreciated. Because of its relevance to working
conditions as well as its relationship to employee productivity, job satisfaction is
frequently researched and, therefore, one of the “best-researched concepts in work and
organizational psychology” (Dormann & Zapf, 2001, p. 483). Likely, job satisfaction will
continue to be frequently researched as some researchers (Jamrog, 2004) have reported
that employees are disclosing some of the highest levels of job dissatisfaction in years.
One important issue concerning job satisfaction that is addressed in the literature
is how to best measure the variable of job satisfaction: as a global variable or a
multifaceted variable. Measuring job satisfaction globally (i.e., “How satisfied are you
with your job in general?” [Brief, 1998, p. 15]) has its advantages: the measurement is
rapid and efficient, has good test-retest reliability (Kristensen and Westergaard-Nielsen,
2007) and gives an overall representation of the employee’s level of contentment.
However, the global measure tends to gloss over critical aspects related to the job that
would have been measured if a multifaceted measure of job satisfaction had been used.
Multifaceted measures of job satisfaction such as the Job Descriptive Index (JDI) used by
Glick (1992) measures facet-specific job satisfaction across the facets of coworkers, pay,
opportunities for promotion, supervision, and work (Brief, 1998). The Minnesota
Satisfaction Questionnaire consists of 100 items assessing 20 aspects of the work
environment including advancement, authority, compensation, coworkers, recognition,
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and working conditions (Brief, 1998). While multifaceted measures of job satisfaction are
designed to measure the facets of job satisfaction, these multifaceted measures are not
without criticism. Scarpello and Campbell (1983) asked the question, “Are all the parts
there?” referring to the inability of multifaceted measures of job satisfaction to
incorporate all of the elements that go into the employee’s overall judgment about job
satisfaction. These concerns were echoed by Highhouse and Becker (1993).
The consequences of job satisfaction are copious. Brief (1998) wrote that role
withdrawal was of chief importance. Other consequences according to Brief (1998) as
identified by Hulin include long coffee breaks, stealing, wandering around looking busy,
tardiness, absenteeism, and retirement. Others (Shulz, et al., 1987; Weisberg &
Kirschenbaum, 1991; Hellman, 1997) have cited turnover intent.
Employee Engagement, Job Satisfaction, and Turnover Intent
In the current study, the relationship between employee engagement and turnover is
hypothesized to be mediated by job satisfaction. Mediator variables are said to come
between the independent and outcome variables (Schwab, 2004). Full mediation has
occurred when the independent variable causes the mediator which, in turn, causes the
outcome variable. Partial mediation is said to occur when the independent variable causes
the mediator and the outcome variable, and the mediator causes the outcome variable.
While there are no studies that directly assess the mediating effect of job satisfaction on
the relationship between employee engagement and turnover intent, there are a number of
studies that support the relationship between employee engagement and retention but not
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turnover intent (Jones & Harter, 2005; Buckingham & Coffman, 1999), job satisfaction
and turnover intent (Hellman, 1997; Lum, et al., 1998; Bernthal et al., 2000), and still
others that relate employee engagement with jobs satisfaction. Several studies in the
research literature have documented a complex relationship between job satisfaction and
turnover intent. Shulz, et al. (1987) examined turnover intent among retail pharmacists
and found that job dissatisfaction was directly related to turnover intent. In a 1991 study,
Weisberg et al. determined that high and moderate levels of job satisfaction are similar in
their impact upon turnover intent; however, a lack of job satisfaction “drastically raises a
moving intent” (p. 368).Weisberg et al. suggested that it just may not be necessary for
employees to obtain high levels of job satisfaction to reduce their intentions to leave an
organization. Using meta-analytic procedures, Hellman (1997) found that the job
satisfaction-turnover intent relationship was “significantly different from zero and
consistently negative” (p. 1997). Using a longitudinal analysis of the turnover processes,
Youngblood, Mobley, and Meglino (1983) determined that changes in satisfaction over
time are related to turnover. Likewise, in a study of pediatric nurses, Lum, et al. (1998)
reported finding an inverse relationship between job satisfaction and intention to quit
(turnover intent). Also, Bernthal et al. (2000) found that employees who are either neutral
or dissatisfied (36% of employees) with their jobs are greater than two times as likely to
leave. Boswell, Boudreau, and Tichy (2005) determined that low satisfaction usually
precedes a voluntary change of employment followed by an increase in satisfaction
(honeymoon effect) and then a decrease in job satisfaction (hangover effect).
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There are several studies within the past 20 years that suggest the mediating
effects of job satisfaction on employee engagement and turnover intent. First, Lachman
and Diamant (1987) stated that “[m]ost models describing the psychological process that
leads to resignation or the intention to resign assume a sequence from the work
environment, through employees’ affective reactions to it, to the decision to remain or
leave the organization” (p. 219). In 2001, Lambert, Hogan, and Barton assessed the
relationship between the work environment, job satisfaction, and turnover intent. For the
study, the work environment was comprised of role conflict, task variety, financial
rewards, and relationships with co-workers, and autonomy/participation. Lambert et al.
reported in their findings that job satisfaction served as a key, mediating variable between
work environment and turnover intent. In an international study, Huang and Van de
Vliert (2003) reported that intrinsic job characteristics were linked more strongly with job
satisfaction in richer countries with better governmental social welfare programs and
those that were more individualistic. Finally, Karsh, Booske, and Sainfort (2005) found
that job and organizational factors predicted both commitment and satisfaction together,
which predicted turnover intentions among nursing home employees.
In sum, based on a review of the relevant research literature, it is surmised that
employee engagement (that is, the employee’s assessment of the work environment) is
expected to elicit an emotional response (i.e., job satisfaction, the mediator) which in
turn, affects turnover intent (the outcome variable). The relationship between employee
engagement and job satisfaction is expected to be positive; the relationship between job
83
satisfaction and turnover intent is expected to be negative (i.e., as job satisfaction
increases, turnover intent decreases). Therefore, for the current study, the following
hypothesis was tested:
Hypothesis 2a: Job Satisfaction mediates the relationship between the antecedent
Employee Engagement and outcome variable Turnover Intent.
Compensation Fairness, Job Satisfaction, and Turnover Intent
In this study, the relationship between compensation fairness and turnover intent is also
hypothesized to be one of mediation by job satisfaction. There are several studies in the
literature supporting the mediating effect of job satisfaction on the relationship between
compensation fairness and turnover intent. However, these studies did not address fully
the model proposed by the current study nor do these studies agree as to the direction of
the relationships between the variables. In a 1987 study of retail pharmacists conducted
by Shulz, et al., the researchers found a negative relationship between salary and turnover
intent as well as a positive relationship between dissatisfaction and turnover intent. In a
1991 study of managers, Summers and Hendrix reported that pay equity perceptions had
an indirect impact on voluntary turnover via pay satisfaction, job satisfaction,
organizational commitment, and turnover intent. In 1999, Igalens et al. found that flexible
pay did not increase job satisfaction for nonexempt employees and that benefits did not
increase job satisfaction for exempt and nonexempt employees. The results of the Igalens
et al. study did not support the model used for the current study. Huang et al. (2003)
reported that extrinsic job characteristics were linked strongly and positively with job
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satisfaction in all countries. Rosser (2004) reported that female faculty was less satisfied
than male counterparts based on workload, quality of benefits, job security, and salary.
Ambrose, Huston, and Norman (2005) listed commonly cited reasons for satisfaction (or
dissatisfaction) among faculty include: salary; collegiality; mentoring; reappointment,
promotion, and tenure processes; and department heads. Van Herpen, Van Praag, and
Cools (2005) reported a relationship between compensation system, work satisfaction,
and turnover intent. Finally, Daly and Dee (2006) found that job satisfaction and
organizational commitment mediated the relationship between the work environment
(including communication openness and distributive justice) and intent to stay for the
faculty.
In sum, there is research to support the mediating effects of job satisfaction on the
relationship between compensation fairness and turnover intent. In addition, there is
research to support the same for faculty. The relationship between compensation fairness
and job satisfaction is expected to be positive; the relationship between job satisfaction
and turnover intent is expected to be negative (i.e., as job satisfaction increases, turnover
intent decreases).Therefore, for the current study, the following hypothesis was tested:
Hypothesis 2b: Job Satisfaction mediates the relationship between the antecedent
Compensation Fairness and outcome variable Turnover Intent.
Age
For the current study, cohorts referred to those employees in the same age category (i.e.,
mature workers were aged 55 and older, late midcareer workers were aged 46-54, early
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midcareer workers were aged 36-45, and young workers were aged 18 to 35). These
particular age categories were utilized as dictated by the secondary data source and were
suggested by Dychtwald et al., (2006). Personal interview with David Baxter (2008),
SVP of Age Wave, indicated that these particular age categories were utilized in
Dychtwald et al. (2006) because (a) Human Resources commonly uses these age ranges;
(b) the Bureau of Labor Statistics commonly divides age into these same ranges; and (c)
these age categories roughly mirror the Traditionalists, Baby Boomers, and Generation
X/Millenials social cohorts.
Due to the cross-sectional nature of the data and expecting both cohort effects and
age effects in the data (Rhodes, 1983), these age categories will now be profiled based on
the cohort and age effects expected and contextualized as faculty in higher education.
Profile of the Mature Worker
Mature workers include those employees 55 and older (Dychtwald et al., 2006),
most of whom were born in the 1940’s. Collectively, they possess the strengths of
emotional maturity, experience, and loyalty, even building their career with only one
company (Dychtwald et al., 2006; Lancaster & Stillman, 2002). These workers are
characterized as wanting to make meaningful contributions (as in positions of leadership,
see Lancaster & Stillman, 2002) and interested in improving their skills. They hold more
traditional beliefs including those involving respect for authority. While they may shy
away from computers, they do have a desire to improve. They are typically more
engaged, according to Dychtwald (2006), less likely to report burnout and conflict on the
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job, and demonstrate greater overall satisfaction with both their jobs (68%) and with their
managers (54%) compared to Midcareer and Young Workers. They may be satisfied with
little feedback at work but enjoy the satisfaction of a job well done (Lancaster &
Stillman, 2002). These workers are in Super’s Maintenance and Decline Career Stages as
they are maintaining their positions but beginning to plan for and consider retirement
(Osipow, 1968) that they view as a reward (Lancaster & Stillman, 2002). Dychtwald
(2006) reported that many mature workers are working past retirement age and may do so
to stay mentally and physically active, to be productive, and have fun while others retire
due to health benefits or money. Conversely, others may choose to retire to alleviate
economic restraints tied to current I.R.S. tax code. Wright (2006) suggested that while
financial reasons may keep employees working, so does their valuation of their role as
worker, that is they value the social contacts as well as meaning and purpose to their lives
that work provides for them. The aging worker is important in today’s American
businesses and organizations with the eradication of mandatory retirement.
Profile of the Midcareer Worker
According to Dychtwald et al. (2006), the midcareer worker is aged 36 to 54 and
includes most of the Baby Boomers and the older 1/3 of Generation X. According to
Super’s Career Stages, the midcareer worker is in the establishment and Maintenance
Stages of Career Development and working on the vocational task of consolidation by
attempting to establish himself in his position (Osipow, 1968). While they try to maintain
their optimism (Lancaster & Stillman, 2002), the Midcareer Worker has a number of
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career crisis points: they are experiencing a lengthening work horizon, they are in a
career bottleneck (too many boomers in line for too few positions of leadership), they
experience work/life tension catering to both parents and children, they are not
accumulating wealth quickly enough to retire when they would like, they struggle to keep
up with new skills, they experience disillusionment with their employer including
distrust, and they frequently experience burnout. They are highly competitive and still
strive to build stellar careers while achieving money, recognition, fancy titles, and the
corner office (Lancaster & Stillman, 2002). Midcareer workers are more likely to express
dissatisfaction with their jobs than other cohorts and the lowest satisfaction with their
managers. According to Dychtwald et al. (2006), “the recognition of aging triggers the
quest for change” (p. 67), but they may feel that job changing only puts them behind
(Lancaster & Stillman, 2002). Dychtwald et al. (2006) reported that over half of the
midcareer works seek changes in responsibilities at work, 20% are looking for a new job,
20% are looking for a career change, and 36% say they feel dead-ended. At a time when
they should be at or near their peak of productivity, midcareer workers often face
frustration, alienation, and confusion before they may face a time a self-discovery and
new direction (Morison, Erickson, & Dychtwald, 2006). Benefits packages, retirement
packages, work that encourages them to grow and learn, and an enjoyable workplace are
high on the midcareer worker’s list (Dychtwald et al., 2006); too much training and
feedback more than once a year is not (Lancaster & Stillman, 2002).
Profile of the Late Midcareer Worker
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The Late Midcareer Worker is aged 46 to 54 and comprised primarily of baby
boomers. With respect to Super’s career stages, the late midcareer worker is in the
maintenance stage of development. The Late Midcareer Workers are sandwiched
between raising children and assisting with their aging parents. This may add to the stress
they already perceive at work from the career bottleneck and lengthening work horizon.
Profile of the Early Midcareer Worker
The Early Midcareer Worker is aged 36 to 45 and comprised primarily of
Generation Xers. With respect to Super’s career stages, the early midcareer worker is in
the establishment stage of development. The Early Midcareer Worker may have younger
children he or she is raising which may add to their stress load.
Profile of the Young Worker
The young worker group is aged 35 and under and is comprised of both
Generation X and Millenials (Dychtwald et al., 2006). The young worker is in the
exploration and establishment stage of Super’s Career Stages and working on the
vocational tasks of specification (i.e., narrowing down his vocational choices),
implementation (i.e., completing his or her training), and stabilization (i.e., settling in his
position, changing positions or jobs, if necessary) (Osipow, 1968). In spite of just starting
out, young workers report they feel they are in dead-end jobs (35% compared to the
midcareer worker’s 36%) and 2/3s of young workers are looking for a significant change,
26% are seeking promotions, 28% are seeking major career change, and 28% are looking
for a job at another company (Dychtwald et al., 2006). Twenge (2006) described these
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generations as having a feeling of entitlement that extends to salary and duties in the
workplace. Furthermore, salary is very important to them, especially at a time when the
housing market has far-outpaced inflation (Twenge, 2006). Dychtwald et al. (2006)
reported that young workers have high expectations from work including freedom to
make decisions (in fact, freedom in itself is rewarding to them, Lancaster & Stillman,
2002), a sociable workplace, opportunities to learn, opportunities to contribute, lots of
feedback, respect from older coworkers, flexible schedules as well as plenty of time off.
Younger workers want managers that serve as coaches but not order-givers (Dychtwald,
2006). They do not take criticism well but do work hard when praised and recognized
(Twenge, 2006), and, thus seek constructive feedback (Lancaster & Stillman, 2002).
Young workers have reported their managers provide plenty of useful feedback
(Dychtwald, 2006). They are open to learning (Lancaster & Stillman, 2002), learn best
through hands-on activities and not lectures (Twenge, 2006), and have reported that they
have plenty of opportunity to learn and grow (Dychtwald, 2006). While Generation X has
been described as skeptical and Millenials have been described as realistic (Lancaster &
Stillman, 2002), these young workers have reported that they work with bright,
experienced people (Dychtwald, 2006). Unfortunately, concerning the new workforce,
Jamrog (2004) had many concerns saying that the generation entering the workforce now
is different, is not better educated than predecessors, and is 21-23% functionally illiterate.
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Moderating Effects of Age
Moderator variables influence the relationship between the dependent and other
independent variables (Schwab, 2004). The direction and magnitude of the relationship
between the dependent and an independent variable is dependent on the value of a
moderator variable. In the current study, age is speculated to be a moderator variable
affecting the magnitude (but not the direction) of the relationship between the outcome
variable turnover intent and the antecedents employee engagement and compensation
fairness. Thus said, in the current study, it is expected that for the relationship between
antecedents employee engagement and compensation fairness and outcome variable
turnover intent there is an interaction effect with age that affects the strength of the
relationship between employee engagement and turnover intent and for compensation
fairness and turnover intent for the target age groups.
Researchers (Rhodes, 1983, for example) have suggested that age-related
differences that occur in work attitudes and behaviors may be a result of psychosocial
aging (e.g., social role changes) as well as biological aging. Steel and Ovalle (1984) have
suggested that age should be considered as a variable influencing work attitudes and
behaviors. They cite that much of the research on turnover intent has not considered the
differences across age groups. Concerning the employee engagement-turnover intent
relationship, Jones and Harter (2005) had suggested age may be a potential moderator.
Generally speaking, there are many reasons to suspect that age-related effects on the
employee engagement-turnover intent relationship exist. First, researchers suggest that
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age may affect both turnover intent and engagement. Lachman and Diamant (1987)
suggested that age and tenure are restraining factors keeping employees on the job and
decreasing turnover intent. Dychtwald et al. (2006) reported that mature workers had the
highest levels of engagement (i.e., characteristic of the worker) as did BlessingWhite
(2008). Second, profiles of the four cohort grouping suggest that there are differences in
worker’s needs, preferences, and work-related attitudes that are specifically related to the
12 employee engagement items. (See Table 3 in Appendix C for additional information).
For example, midcareer workers (defined as 36-55 for the current study) have a number
of crisis points (e.g., career bottleneck, work/life tension, disillusionment with employer,
burn out) yet may feel they cannot quit. And, young workers (defined as 35 and under for
the current study) have high expectations from the workplace (e.g., a sociable workplace,
opportunities to contribute, lots of feedback, etc.) and yet are at the highest risk for
turnover (Bernthal & Wellins, 2000). While there is a dearth of information on the
employee engagement-turnover intent relationship, there is even less information on the
age effects of the same.
The following paragraphs use Super’s Life-Space Life-Span Theory and
Generational Cohort Theory to conjecture the age-related effects on the 12 employee
engagement-turnover intent relationship. Empirical studies, if available, are also reported;
however, it is important to note that most studies on the employee engagement-turnover
intent relationship have used age as a descriptor and not a moderator.
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Expectations, Turnover Intent, and Age
Previous research (i.e.,Youngberg, 1963; Macedonia, 1969; Lyons, 1971; House
& Rizzo, 1972; Gupta & Beehr, 1979; Jackson & Schuler, 1985; Buckingham &
Coffman, 1999) has indicated an inverse relationship between expectations (as measured
by the GWA item “Do I know what is expected of me at work?”) and the outcome
variable turnover intent. Age-related effects were expected on the inverse relationship
between expectations and turnover intent. According to Super’s Life-Span, Life-Space
Theory, young workers are working on the vocational task of stabilization (i.e., trying to
“settle down” in a career of their choosing, changing position if necessary). Because of
their comparative youth and lack of experience, young workers likely have many more
questions about what is expected from them on the job compared to midcareer and
mature workers as they begin the career of their choice. Therefore, mean scores for young
workers are expected to be lower for the variable expectations as compared to mean
scores for both midcareer and mature workers, and, as suggested by research (Smart,
1990; Zhou & Volkwein, 2004) young workers are likely to have higher turnover
intentions compared to midcareer and mature workers. Futhermore, according to
Generational Cohort Theory, young workers have high expectations regarding the
workplace this likely includes the expectation that their job expectations will be
delineated for them. Unfortunately, this is not always the case, even in higher education.
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Materials, Turnover Intent, and Age
Based on previous research (i.e., Gupta & Beehr, 1979; Buckingham & Coffman,
1999; Harter et al., 2002; Deal, 2007), an inverse relationship was expected between the
antecedent materials (as measured by the GWA item “Do I have the materials I need to
do my work right?”) and the outcome variable turnover intent. Moreover, for the current
study, age-related effects were also expected on the same relationship. Super’s Life-
Space, Life-Span Theory suggested that midcareer workers are attempting to establish
themselves in their careers. They have moved past the training and implementation stages
characteristic of the young worker and are at a point where they may suffer crisis in an
attempt to maintain their place in their field. For faculty in higher education, materials
may certainly include technology and the availability of support staff. This being said,
resources in the form of materials (many of which are technologically based) may be
particularly important for the midcareer worker’s attempts to establish themselves in their
career but, unfortunately, are not there compared to younger workers who may have
negotiated better packages including start-up monies and mature workers who, as full
professors, have the benefits of receiving internal and external grants as well as contracts.
Based on this information and the fact that younger workers typically have higher
turnover rates, mature workers likely have the strongest inverse relationship between
materials and turnover intent.
Generational cohort theory likely suggests the same in that young workers and
mature workers have both been subjected to frugality because of the economic conditions
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of their time (Twenge, 2006; Lancaster & Stillman, 2002), they are accustomed to
“making do” or doing without. On the contrary, midcareer workers as Baby Boomers
grew up comparatively affluent (Lancaster & Stillman, 2002) and are somewhat
accustomed to having plenty. In addition, midcareer workers are highly competitive and
in search of a stellar career.
Opportunity, Turnover Intent, and Age
Past research (i.e., Ferguson, 1958; Boyd, 1961; Mayeske, 1964; Gupta & Beehr,
1979; Buckingham & Coffman, 1999; Harter et al., 2002) has suggested an inverse
relationship between the manifest variable opportunity (as measured by the GWA item
“At work, do I have the opportunity to do what I do best every day?”) and the outcome
variable turnover intent. For the current study, age-related effects were expected on the
employee engagement-turnover intent relationship. As a manifest variable of the
construct employee engagement, opportunity simply measures the extent the worker feels
he or she is able to do what they do best in his or her current position. For faculty in
higher education, being able to excel may include teaching particular courses, researching
selected topics, and leading desired committees. Vocational choice was clearly addressed
by Super’s Life-Span, Life-Space Theory. Young workers are attempting to answer the
questions “Who am I? And, what kind of job will be best for me?” Midcareer workers
know better who they are and where their skills lie. They are attempting to answer the
question: “Is this what I want to do for the rest of my life?” Mature workers are
attempting to answer the question “Have I used my skills and talents wisely?” There is an
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increased seriousness in how midcareer workers and mature workers approach their job
and its match with their skills. Concerning the age-related effects on the employee
engagement-turnover intent relationship, Generational Cohort theory suggested that the
goals of the mature workers and midcareer workers are more in line with seeking
opportunities to excel. For example, traditionalists (i.e., mature workers) want to make
contributions to the organization that reflects their skill (Martin & Tulgan, 2006), while
boomers (i.e., midcareer workers), due to their competitive nature, are in search of that
stellar career (Lancaster & Stillman et al., 2002). Young workers (i.e., Generation X)
seek authority, status, and reward while others (i.e., Millenials) seek to create meaningful
contributions (Martin & Tulgan, 2006).
Recognition, Turnover Intent, and Age
The lack of recognition and praise has been noted as a key driver for turnover
intent (International Survey Research, n.d.). Other research (Ross & Zander, 1957;
General Electric Company, 1964; Spector, 1985; Fields, 2002; Harter et al., 2002) further
supports the inverse relationship between recognition and turnover intent. For the current
study, age-related effects were expected on the inverse relationship between recognition
(as measured by the GWA item “In the last seven days, have I received recognition or
praise for doing good work?”) and outcome variable turnover intent. Super’s Life-Span,
Life-Space Theory suggested that midcareer workers are caught in a “slump” between
having previously benefited from the intrinsic rewards associated with the stabilization
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process (i.e., finding gainful employment after the completion of formal training) and not
yet ready for the rewards of retirement (Lancaster & Stillman et al., 2002).
Recognition from the organization may follow suit with young workers receiving
significant recognition for their accomplishments establishing themselves in their careers
and mature workers receiving significant recognition for their accomplishments over the
course of their careers. With turnover intent decreasing with age, mature workers (vs.
young workers) are more likely to have the strongest inverse relationship between
recognition and turnover intent. Generational Cohort Theory suggested that due to the
sheer volume of Baby Boomers, midcareer workers may feel lost against the masses, thus
receiving less recognition.
Care, Turnover Intent, and Age
Researchers (Evan, 1963; Hulin, Roach, & Waters, 1971; Telly, French, & Scott,
1971; Buckingham & Coffman, 1999; Harter et al., 2002) have demonstrated that there is
sufficient evidence to suggest that care (as measured by the GWA item “Does my
supervisor, or someone at work, seem to care about me as a person?”) is inversely related
to turnover intent. For the present study, age-related effects were expected on the
relationship between care and the outcome variable turnover intent, although an inverse
relationship between care and turnover intent was expected. The need for care in faculty
in higher education should likely include support and encouragement through the more
demanding tasks associated with the job. Care is a basic necessity for humankind. All
humans need to know that others support, respect, appreciate, and trust us. We have a
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need to give the same in return. When people sense they are not cared for in relationships
(e.g., friendships, marriage relationships, work relationships), then they pull away to seek
this basic need elsewhere.
Encouragement, Turnover Intent, and Age
Some researchers (Harter et al., 2002; Strategic Finance, 2007) have suggested
that development (as measured by the GWA item “Is there someone at work who
encourages my development?”) is inversely related to turnover intent. For the present
study, age was expected to have an impact on the inverse relationship between the
antecedent variable development and the outcome variable turnover intent. Super’s Life-
Span, Life-Space Theory has suggested that, with respect to their careers, individuals
proceed through several stages of career development (i.e., growth, exploration,
establishment, maintenance, and decline). Socialization into this career development
process has led us to expect formal training during the growth and exploration stages in
preparation for the careers to be started during the establishment stage. These young
workers are frequently given additional support through orientation, mentors, and
coaches especially at the beginning of their employment and are likely to rate the
presence of someone encouraging their development fairly high although they are
historically a little more likely to turnover than their older counterparts.
Between midcareer and mature workers, who both are less likely to turnover than
young workers, it seems plausible that the mature workers are more likely to encourage
the development of others and less likely to be encouraged in their personal development
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due to their position of influence and leadership in an organization. This may be
particularly true in higher education.
Opinions Count, Turnover Intent, and Age
Research (Buckingham & Coffman, 1999; Harter et al., 2002) has supported a
positive relationship between opinions count and retention. For the current study, an
inverse relationship between the antecedent variable opinions count (as measured by the
GWA item “At work, do my opinions seem to count?”) and the outcome variable
turnover intent was expected. Furthermore, age-related effects were expected on the
same. While research may suggest that there is a relationship between having one’s
opinions count in the workplace and turnover intent, there is even less information on
how age may impact this relationship. This is especially true for faculty in higher
education. Super’s Life-Span, Life-Space Theory has suggested that with respect to
careers, individuals proceed through several stages of career development (i.e., growth,
exploration, establishment, maintenance, and decline). It is during the decline stage that
workers are characterized by a decrease in mental and physical powers and career
deceleration and retirement occurs. Dychtwald et al. (2006) has suggested that mature
workers are characterized as wanting to make meaningful contributions. With their age
and experience, it is likely that mature workers do desire to have their opinions count.
And, when they feel they can no longer make meaningful contributions due to the
decreases in their mental and physical powers, they may consider turnover in the form of
retirement. Until such time occurs, many workers (higher education included) tend to
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respect, appreciate, and take into account the opinions of those that are more mature and
wiser
Mission, Turnover Intent, and Age
Research on the relationship between mission and turnover intent is rather limited.
Harter et al. (2002) found a positive relationship between Mission and retention. For the
current study, age-related effects were expected on an inverse relationship between
mission (as measured by the GWA item “Does the mission/purpose of my company make
me feel my job is important?”) and turnover intent. Mission addresses the idea that one’s
job is important due to its connection to the purpose of the company. Super’s Life-Span,
Life-Space Theory is helpful in hypothesizing this relationship. For the social cohorts, the
relationship is likely to be strongest for the mature workers. Young workers in the
exploration and establishment stages typically have entry-level positions and have not
had a chance to work through the ranks to positions of leadership. They are trying to fit in
with the purpose and needs of the company. Midcareer workers are in the maintenance
stage and bottlenecked in their attempt towards obtaining a stellar career into positions of
leadership. Mature workers see the connection between their job and the purpose of the
company (or, institution of higher learning) and know they are essential to the company
reaching its purpose.
Quality Work, Turnover Intent, and Age
Researchers (Karsh et al., 2005; Elçi et al., 2007) have demonstrated a negative
relationship between organizational quality improvement environment and quality culture
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with turnover intent suggesting that quality work is inversely related to turnover intent.
For the current study, age was expected to have an impact on the inverse relationship
between the antecedent variable quality work (as measured by the GWA item “Are my
co-workers committed to doing quality work?”) and the outcome variable turnover intent.
Super’s Life-Span, Life-Space Theory is useful in explaining age-related effects on the
quality work—turnover intent relationship. Young workers and midcareer workers are
likely to evaluate the commitment to quality work higher than mature workers. Mature
workers, in their wisdom, likely have come to realize that all workers do not have their
particular level of expertise yet but can be mentored.
Best Friend, Turnover Intent, and Age
While some researchers (Buckingham & Coffman, 1999; Harter et al., 2002) have
not found a significant relationship with best friend and turnover intent (or retention),
others (The Segal Group, 2007) have suggested that having friendly co-workers was
important when considering turnover and still others (Evan, 1963; Hulin; 1968; Farris,
1971; Telly, French & Scott, 1971) have found a negative relationship between
satisfactory peer group interactions and turnover. For the current study, age was expected
to have an impact on an inverse relationship between the antecedent variable best friend
(as measured by the GWA item “Do I have a best friend at work?”) and the outcome
variable turnover intent. Super’s Life-Span, Life-Space Theory has suggested that as
individuals progress through the stages of career development, they enter the workforce,
they maintain their position, then they enter the decline stage where retirement is
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considered and taken. Young workers may not have had the opportunity to develop
friends at work. Mature workers may likely find their friends have left the workplace.
Midcareer workers, as long as they are not too competitive, are most likely to agree that
they have a good friend at work. While Dychtwald et al. (2006) reported that young
workers expect a sociable workplace, friendships do take some time to develop.
Progress/Appraisal, Turnover Intent, and Age
Research has demonstrated somewhat mixed results concerning
progress/appraisal and turnover intent with both Buckingham and Coffman (1999) and
Harter et al. (2002) reporting a lack of significant relationships between the two while
The Segal Group (2007) reported that 41% of respondents in higher education rated
coaching and mentoring as important when considering turnover. For the current study,
an inverse relationship is expected between progress/appraisal (as measured by the GWA
item “In the last six months, has someone at work talked to me about my progress?”) and
turnover intent. Age-related effects are expected on the same. Super’s Life-Span, Life-
Space Theory suggested that as individuals progress through the stages of career
development, they move out of the growth and exploration stages where formal training
is expected and into establishment, maintenance, and decline stages where formal
training is not usually expected. However, as is customary for many organizations
including those in higher education, performance appraisals may generally be expected
throughout one’s career
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Learn and Grow, Turnover Intent, and Age
Several researchers (Harter et al., 2002; International Survey Research, n.d.) have
noted either a strong positive relationship between learn and grow with retention or cited
poor individual development and career development as a key driver for turnover intent.
An inverse relationship is expected between the manifest variable learn and grow (as
measured by the GWA item “This last year, have I had opportunities to learn and grow?”)
and the outcome variable turnover intent. Age-related effects are expected on the same.
Super’s Life-Span, Life-Space Theory suggested that as individuals progress through the
stages of career development, they move out of the growth and exploration stages where
formal training is expected and into establishment, maintenance, and decline stages
where formal training does not normally occur. Perhaps because of this expectation of
formal training during the early stages of career development, young workers are open to
learning (Lancaster & Stillman, 2002), have high expectations regarding opportunities to
learn, and report they have plenty opportunities to learn and grow (Dychtwald et al.,
2006). Similarly, mature workers are interested in improving their skills (Dychtwald, et
al, 2006). While midcareer workers strive to build stellar careers (Lancaster & Stillman,
2002) and seek work that encourages them to grow and learn (Dychwald et al., 2006),
midcareer workers are unfavorable to too much training (Lancaster & Stillman, 2002).
Because of this incongruity between needing to learn and grow to build their stellar
career and the dissatisfaction of too much training, midcareer workers in higher education
are expected to report fewer opportunities to learn and grow.
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In sum, psychosocial and biological aging are likely causes of age-related
differences that may occur in work attitudes and behaviors (Rhodes, 1983). Such age-
related differences likely impact the employee engagement-turnover intent relationship as
suggested by Jones and Harter (2005). Therefore, for the current study, the following
hypothesis was tested:
Hypothesis 3a: Age moderates the relationship between antecedent Employee
Engagement and outcome variable Turnover Intent.
Compensation Fairness, Turnover Intent, and Age
After an extensive search in the related literature, the author was unable to find
any articles that specifically addressed the three variables: compensation fairness,
turnover intent, and age. However, several articles were found that are suggestive of the
relationship between the three variables. While fair pay helps to maintain employees
(Siegfried, 2008), age may moderate how compensation fairness is perceived and used in
the decision to stay or leave a job. Rebecca Ryan (in Siegfried, 2008) reported that
generation X and generation Y perceive pay as a determinant of stay or leave decisions
differently than previous generations. According to generational cohort theory, young
workers are looking to leave for greener pastures, while mature workers are loyal and less
likely to turnover or intend to turnover. Older workers (i.e., mature workers) may
perceive compensation as fair as they likely possess the more desirable higher salaries
compared to their younger counterparts (White & Spector, 1987). Therefore, for the
current study, the following hypothesis was tested:
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Hypothesis 3b: Age moderates the relationship between antecedent Compensation
Fairness and outcome variable Turnover Intent.
Summary
Utilizing secondary data describing employees from an institution of higher education,
the current study tested the mediating effects of Job Satisfaction and the moderating
effects of Age on the relationship between antecedents Employee Engagement and
Compensation Fairness and the outcome variable, Turnover Intent. (See Figure 5 in
Appendix B for a model representing the proposed relationships.) While Turnover Intent
and Age appear frequently as variables in the related literature, Employee Engagement,
especially in higher education, is a fairly new concept lacking a research base that ties the
concept to the turnover literature. The inclusion of Job Satisfaction and Compensation
Fairness further ties the current study to the existing research base. The hypotheses for
the current study are reiterated below:
Hypothesis 1a: Employee Engagement is inversely related to Turnover Intent.
Hypothesis 1b: Compensation Fairness is inversely related to Turnover Intent.
Hypothesis 2a: Job Satisfaction mediates the relationship between the antecedent
Employee Engagement and outcome variable Turnover Intent.
Hypothesis 2b: Job Satisfaction mediates the relationship between the antecedent
Compensation Fairness and outcome variable Turnover Intent.
Hypothesis 3a: Age moderates the relationship between antecedent Employee
Engagement and outcome variable Turnover Intent.
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Hypothesis 3b: Age moderates the relationship between antecedent Compensation
Fairness and outcome variable Turnover Intent.
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CHAPTER III
Methodology
“A man can do nothing better than to eat and drink and find satisfaction in his work.”
(Ecclesiastes 2:24 NIV, Gospel Communications International, 2007)
Methods
The primary focus of the current study was to test the mediating effects of Job
Satisfaction and the moderating effects of Age on the relationship between antecedents
Employee Engagement and Compensation Fairness and the outcome variable, Turnover
Intent. (See Figure 3, Figure 4, and Figure 5 in Appendix B for a model depicting these
relationships.) The current study utilized secondary data describing employees from an
institution of higher learning. While secondary data has its limitations (i.e., the researcher
has no control over methodological concerns including selection of population,
instrumentation, and delivery methods), it can be a useful source of information. The
secondary data used in the current study was made available via invitation from the
director of human resources from the surveyed institution of higher learning. The current
study utilized survey methodology employing self-administered questionnaires while
making use of the Internet as a delivery method. Justifications for this methodology
follow.
Survey research was used based on its description (Kerlinger & Lee, 2000) and
purposes of comparison, evaluation (Isaac & Michael, 1997), and generalization (Babbie
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in Creswell, 2003). Survey research has several advantages and disadvantages (Kerlinger
& Lee, 2000). Advantages of survey research include a wide scope and accuracy. Bates
(2004) stated:
The employee survey is the diagnostic tool of choice in the battle for the hearts of
employees. Some companies ask workers about their work experiences as
infrequently as every other year, looking for major trends. Others take the pulse of
the people as often as every month to address the little things that get in the way
of employees doing their jobs. Regardless of frequency, the most effective
surveys ask questions that can lead to specific corrective action and that
demonstrate a long-term commitment to providing a rewarding work experience,
as several organizations have found (p. 48).
Disadvantages of survey research include the inability to gather anything more than
superficial data without much depth; the demands on time, energy, and money;
subjectivity to sampling error; and the requirement of knowledge concerning both survey
methodology and research. Many of the disadvantages can be ameliorated through careful
consideration of the design of the research; however, one major disadvantage still stands
and that is that survey research may be classified as a one group design or, according to
Campbell and Stanley (in Kerlinger & Lee, 2000), a “one shot case study” (p. 469). The
problems with this design include the facts that there is not random assignment to groups
and that treatment for the experimental group is assumed. As pointed out by Kerlinger
and Lee, the lack of control over any influences on the variables studied makes this
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design scientifically worthless; however, it is used quite frequently in research due to the
fact it is available and sometimes necessary depending on the variables to be studied.
The current study also utilized web surveys. Web surveys have several unique
advantages (Nesbary, 2000): (a) web surveys are relatively inexpensive; (b) responses
may be entered and stored in a format conducive to analysis; (c) there is increased
accuracy in data entry as well as decreased time; and (d) automatic coding saves a great
deal of time. Couper (2000) also stated that researchers could access “undreamed of
numbers of respondents at dramatically lower costs than traditional methods” (p. 464).
Web surveys also have several unique disadvantages: (a) only individuals with web
access can complete the survey (Nesbary, 2000) creating coverage problems (Couper,
2000): (b) web surveys may disproportionately limit the responses of minorities and poor
(Nesbary, 2000) creating problems with sampling (Couper, 2000); (c) unless security
measures are in place, anyone who happens upon the survey may take it and, thus, bias
results (Nesbary, 2000); (d) illiteracy is problematic (Couper, 2000); and (e) technical
problems including slow connections and connect-time costs might decrease response
rates. Couper (2000) suggested several solutions for correcting the coverage error
including limiting the study to individuals with computers and making computers
available to individuals without one.
Selection of the Population
While the study utilized a secondary data source, the survey population included faculty
from a land-grant institution holding the doctoral/research-extensive classification from
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the Carnegie Classification and serving about 42,000 students each year with graduates
totaling more than 9,000 per year. The university has a statewide budget of $1.4 billion
receiving $257 million in statewide research awards.
Sample
The current study made use of secondary data that utilized a convenience sample. Due to
the use of the convenience sample, sampling error resulted because those participating in
the study may have differed from those not participating.
The 2007 Employee Satisfaction Survey population included 3,180 faculty
members at a land-grant institution. With a total of 1,229 faculty responding, the response
rate was 38.6%. The sample included 1,229 faculty members that were diverse in age
(18-35: 18.3%, 36-45: 24.4%, 46-55: 31.0%, 56+: 25.0%), gender (female: 44.8%, male:
50.3%), years of service (0-2 years: 19.2%, 3-5 years: 18.4%, 6-10 years: 17.3%, 11-20
years: 21.6% , 21-30 years: 15.9%, 31+: 7.2%), exempt status (exempt: 43.9%, non-
exempt: 21.4%), and race (American Indian: 0.7%, Asian/Pacific Islander: 4.4%,
Black/Not Hispanic: 7.2%, Hispanic: 1.1%, White/Not Hispanic: 81.9%, Other: 2.3%).
Instrumentation
The secondary data utilized for the current study was derived from a 2007 employee
satisfaction survey. While comprised of several different survey instruments, the current
study focused on survey questions that ascertained employee engagement, compensation
fairness, job satisfaction, turnover intent, and demographics. Relevant survey items are
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reproduced in Appendix A. Those instruments utilized for the current study are described
below.
Employee Engagement
The secondary data set utilized by the current study made use of the Gallup
Workplace Audit (GWA) as published in Buckingham and Coffman (1999). Permission
for the use of the GWA was obtained from Robert Lockwood, a Gallup representative.
The GWA was designed to measure elements in the workplace culture that encourage
employee engagement and to reflect both attitudinal outcomes (e.g., satisfaction, pride,
loyalty) as well as issues within the control of the manager (Harter, Schmidt, & Hayes,
2002). After conducting over 1 million interviews across 25 years of qualitative and
quantitative research, Gallup determined 12 core statements that measure the core
elements needed to “attract, focus, and keep the most talented employees” (Buckingham
and Coffman, 1999, p. 28). These 12 statements (sometimes also presented as questions,
see below) utilized a 5-point Likert-type scale with options as follows: Strong Disagree,
Disagree, Neither Agree or Disagree, Agree, and Strongly Agree. For the 12 items,
validity estimates range from .057 to .191 (Buckingham and Coffman, 1999). At the
business unit level, Harter, Schmidt, and Hayes (2002) reported that the GWA has a
Cronbach’s alpha of .91 (n = 4,172). According to Buckingham and Coffman (1999),
Gallup School of Management breaks the 12 questions into four camps entitled “What do
I get?” , “What do I give?” , “Do I belong here?” , “Can we all grow?” ). (See Table 1 in
Appendix C).
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The GWA has been used in a variety of studies. Henderson (2006) used the GWA
to assess intervention and retention in a government agency. Yancey (2005) used the
GWA to predict performance. Buckingham and Coffman (1999) reported that 5 of the 12
questions in the GWA showed a link to retention: (a) “Do I know what is expected of me
at work?” (b) “ Do I have the materials and equipment I need to do my work right?” (c)
“Do I have the opportunity to do what I do best every day?” (d) “Does my supervisor, or
someone at work, seem to care about me as a person?” (e) “At work, do my opinions
seem to count?”
The GWA has been criticized by Macey and Schneider (2008) as measuring the
workplace characteristics promoting employee engagement but not employee
engagement itself. Furthermore, Macey and Schneider has remarked that some of the
items of the GWA have traditionally been conceptualized as facets of satisfaction.
Compensation Fairness
The 2007 Employee Satisfaction Survey assessed Compensation Fairness using
three questions and utilizing a 5-point Likert-type scale with options as follows: Strongly
Disagree, Disagree, Neither Agree or Disagree, Agree, and Strongly Agree. The first
question—“Compared to other people doing similar work at the University, I think I am
paid fairly”—assessed employees’ attitudes regarding Internal Compensation. The
second question—“Compared to other people doing similar work outside the University,
I think I am paid fairly”—assessed employees’ attitudes regarding External
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Compensation. The third question—“The University’s benefit programs meet my
needs”—assessed employees’ attitudes regarding Benefits.
Job Satisfaction
Employees’ Job Satisfaction was assessed using a single question (“Overall I am
satisfied with the University as a place to work”).
Turnover Intent
Employees’ Turnover Intent was assessed using a single question (“I have given
serious thought to leaving the University in the past six months”).
Demographics
Demographic information was also obtained. Length of employment was assessed
with answer options as follow: “1-2 years” “3-5 years”, “6-10 years”, “11-20 years”, “21-
30 years”, and “31 or more years”. A simple statement obtained supervisory status--“I
supervise other employees”. "No” and “yes” options were available. The survey assessed
exempt and non-exempt status among staff with a single question. The survey assessed
tenure track among faculty using the following options: non-tenure track, tenure track,
and tenured. The survey assessed place of employment with a single question: “I am
employed by: _______________”. The survey assessed gender. It also assessed
employees’ age (and also cohort) using the following categories: 18-25, 26-35, 36-45, 46-
55, and 56 or over. It assessed employees’ race using the following categories: American
Indian/Alaskan, Asian/Pacific Islander, Black/Not Hispanic, Hispanic, White/Not
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Hispanic, and Other. Finally, the survey solicited comments from employees by
providing a space for employees to respond.
Procedures
The questionnaire is one part of a well-executed survey (Dillman, 2000). In fact,
according to Dillman (2000):
Implementation procedures have a much greater influence on response rates.
Multiple contacts, the contents of letters, appearance of envelopes, incentives,
personalization, sponsorship and how it is explained, and other attributes of the
communication process have a significantly greater collective capability for
influencing response rates than does the questionnaire design (p. 149).
Researcher contact with those collecting the secondary data utilized in the current study
indicated that elements of the Tailored Design Method (TDM) were used in order to
increase the response rate and execute a more professional study. The 2007 survey was
announced via a website for employees with a designated representative to contact for
additional help, if needed. Employees were informed that their responses were
anonymous and that individual responses were destroyed. And, therefore, nonrespondents
could not be compared or examined with survey respondents. Vice President of
Administration and Finance of the surveyed organization communicated with employees
an invitation to participate including information on how to access the survey.
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Data Collection
Those collecting the data utilized both online format and paper surveys. The use of the
online format for capturing data decreased the amount of time necessary to manually
enter data into a spreadsheet, decreased error associated with data entry, and decreased
costs associated with the duplication of paper surveys. Paper surveys were also made
available to employees lacking access to computers or who desired to complete surveys
using pencil and paper. The researcher for the current study directed the secondary data
into a file and imported the data into SPSS for statistical analysis with AMOS (Analysis
of MOment Structures).
Missing data was sparse and spread out. To deal with data using listwise deletion
of cases would result in a significant reduction of cases. Therefore, missing data was
imputed and saved using Estimation Maximization.
Data Analysis
The current study utilized secondary data describing employees from an institution of
higher learning to assess the mediating effects of job satisfaction and the moderating
effects of age on the relationship between antecedents employee engagement and
compensation fairness on the outcome variable turnover intent. (See Figure 5 in
Appendix B for a model depicting these relationships.) For the current study, structural
equation modeling was utilized to test the several models proposed by this study. Because
the research addressed the moderating effects of age, a between-groups model was
employed.
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Structural equation modeling (SEM) is similar to multiple regression but due to its
simultaneous treatment of data is a more robust tool as it takes into account models of
interactions, correlations, measurement and correlated error, and both multiple latent
independent and dependent variables (Garson, 2008b). Moreover, SEM has several
advantages including flexible assumptions, ability to test models (compared to testing
individual relationships), the capacity to manage difficult data, and integral use of
confirmatory factor analysis. Four or more indicators (i.e., manifest or observed variables
such as items in a survey instrument) are recommended. Factor loadings of .4 may be
used as the minimal effect size for a lambda weight.
In order to test the measurement and structural models as specified in the
hypotheses for the current study using SEM, a two-step approach as suggested by
Anderson and Gerbing (1988) was employed. While full-information estimation methods
can estimate both measurement and structural submodels simultaneously, a two step
approach enables confirmatory assessment of construct, convergent, discriminant, and
nomological validity, then hypothesis testing use the validated constructs. Using a
maximum likelihood (ML) approach, a confirmatory measurement model is used to
specify the relationship of observed measures to hypothesized underlying constructs.
Acceptable fit is achieved through respecification. A confirmatory structural model is
used to specify the causal relations of such constructs to one another. In order to assess
the structural model, a series of nested structural models are estimated using sequential
chi-square difference tests. This two-step approach has been utilized by a number of
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researchers in recent publications (Farkas & Tetrick, 1989; Jang, 2008; Rego, Souto, &
Cunha, 2009).
By all standards, sample size is adequate. While methodologists differ in their
suggestions--i.e., some suggested not less than 50 cases; others suggested at least 10
cases for each instrument item; while others suggested at least 200 cases (Garson,
2008a)—the most conservative approach was reached with the minimum of 200 cases in
each age group. In the present case of n = 1229 and n in each age group of interest being
225 (age 18-35), 300 (age 36-45), 381 (age 46-55), and 307 (age 56 and over), all sample
size standards we could find were met. Accordingly, it followed that by the
methodological standards employed there was sufficient power to test the relationships it
was seeking to test.
Before the hypotheses could be addressed, the measurement models were tested
for both the latent variables--Employee Engagement and Compensation Fairness. Using
the Gallup Workplace Audit (GWA), the chi square difference test was employed to
compare the fit of the final or respecified measurement (CFA) model across the target age
groups. Similarly, for the 3 questions assessing Compensation Fairness by addressing
Internal Compensation, External Compensation and Benefits, the chi square difference
test was employed to compare model fit across age groups.
For both hypothesis 1a (i.e., Employee Engagement is inversely related to
Turnover Intent) and hypothesis 1b (i.e., Compensation Fairness is inversely related to
Turnover Intent) path weights of the model were tested for significance. This was the
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expected result based on decades of research (Ross & Zander, 1957; Ferguson, 1958;
Youngberg, 1963; Hulin, 1968; Telly et al., 1971; Gupta & Beehr, 1979; Eisenberger et
al., 1990; Buckingham & Coffman, 1999; Tekleab et al., 2005; Heckert & Farabee, 2006;
Kim & Lee, 2007).
For hypothesis 2a (i.e., Job Satisfaction mediates the relationship between the
antecedent Employee Engagement and outcome variable Turnover Intent) and hypothesis
2b (i.e., Job Satisfaction mediates the relationship between the antecedent Compensation
Fairness and outcome variable Turnover Intent) the process of testing mediation as
prescribed by Baron and Kenny was employed. According to Baron and Kenny (1986), a
variable operates as a mediator when the following conditions are met:
(a) variations in levels of the independent variable significantly account for
variations in the presumed mediator (i.e., Path a), (b) variations in the mediator
significantly account for variations in the dependent variable (i.e., Path b), and (c)
when Paths a and b are controlled, a previously significant relation between the
independent and dependent variables is no longer significant, with the strongest
demonstration of mediation occurring when Path c is zero.” (p. 1176)
Baron and Kenny (1986) also suggested that in order to test for mediation, the mediator
should be regressed on the independent variable; the dependent variable should be
regressed on the independent variable; and the dependent variable should be regressed on
both the independent variable and the mediator. Using the regression equations above to
establish the mediation relationship, the independent variable must be related to the
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mediator; the independent variable must be related to the dependent variable; and the
mediator must be related to the dependent variable (Baron & Kenny, 1986). Therefore, a
series of structural models tested the mediation model as specified for the current study
after an exploratory factor analysis established factors associated with employee
engagement factors.
Finally, for hypothesis 3a (i.e., Age moderates the relationship between
antecedent Employee Engagement and outcome variable Turnover Intent) and hypothesis
3b (i.e., Age moderates the relationship between antecedent Compensation Fairness and
outcome variable Turnover Intent), moderation was tested as suggested by Baron and
Kenny (1886) where the moderator hypothesis is supported if the interaction of predictor
and moderator on the outcome variable is significant. Therefore, path weights were
computed and compared for invariance across the target age groups using a Chi-Square
difference test.
Ethical Considerations
While the current study utilized data from a secondary source, the agency collecting data
did take several ethical concerns into consideration involving the current study as
suggested by Babbie (1973). Ethical concerns included the following: voluntary
participation, no harm intended to participants, anonymity and confidentiality of
participants ensured, and conveyance of purpose and sponsors of the study.
Concerning the purpose of the study, Coffman and Harter (1999) reported two
problems with research on employee perceptions and attitudes: first, the measurement
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usually lacks a well-defined purpose; and second, the measurement is perceived as way to
control instead of a way to communicate and gain understanding. The purpose of the
study was communicated to participants and other stakeholders via website prior to the
data collection phase. Results of the study were also communicated along with major
initiatives that resulted from employee responses.
Summary
The primary focus of the current study was to assess the mediating effects of job
satisfaction and the moderating effects of Age on the relationship between the
antecedents Employee Engagement and Compensation Fairness and the outcome
variable, Turnover Intent. The current study utilized survey methodology employing self-
administered questionnaires while making use of the Internet as a delivery method from
the 2007 Employee Satisfaction Survey. Data used for the survey was from a secondary
data source derived from faculty (n = 1,229) from a land-grant institution holding the
doctoral/research-extensive classification from the Carnegie Classification and serving
about 42,000 students each year with graduates totaling more than 9,000 per year.
Utilizing SPSS and AMOS, data analysis tested 3 hypotheses that addressed both
measurement models for Employee Engagement and Compensation Fairness as well as
the structural model addressing the mediating and moderating relationships. Ethical
considerations were addressed.
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CHAPTER IV
Data Analysis
“Pleasure in the job puts perfection in the work.”
(Aristotle, 2007, The Quotations Page)
The purpose of this chapter is to present the main findings of the current study including
describing the survey sample and presenting the results of the statistical analysis. The
results of this study are reported in three sections: (a) descriptive statistics; (b)
measurement model; and (c) structural model.
Descriptive Statistics
For faculty, descriptive statistics (i.e., mean, median, mode, standard deviation, and
variance) were reported. Items had a range of 5 based on a 5 point Likert-type scale
where 1 = “strongly agree” and 5 = “strongly disagree.” These statistics may be found in
Table 4 in Appendix C.
The 12 items of the Gallup Workplace Audit measuring Employee Engagement
were rank ordered based on mean. The results may be found in Table 4 in Appendix C.
Items with the strongest positive responses included items addressing Expectations (
=
1.64), having a Best Friend (
= 1.96), and Learn and Grow ( = 1.99). Items with the
least positive responses included Opinions Count (
= 2.27), Progress/Appraisal ( =
2.38), and Recognition (
= 2.85).
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Items measuring Compensation Fairness were rank ordered as well. Benefits had
the most positive mean response (2.23), then Internal Compensation ( = 2.96), and
finally External Compensation (
= 3.60).
Mean scores for both Turnover Intent and Job Satisfaction were also computed.
Turnover Intent had a mean score of 3.04. Job Satisfaction had a mean score of 2.27.
Measurement Model
Structural Equation Modeling (SEM) was used to test the three hypotheses associated
with the current study. Following the procedure recommended by Anderson and Gerbing
(1988), a measurement model was first constructed in order to test the construct validity
of the two latent variables: Employee Engagement had 12 items from the Gallup
Workplace Audit, and Compensation Fairness had 3 items. Also, since the study
proposed differences across 4 age groups, a common model was assessed simultaneously
for each age group. See Figure 6 in Appendix B.
Three criteria assessed the adequacy of the measurement model. First, all latent to
manifest variable regression weights were tested for both statistical and practical
significance. Statistical significance was assessed at alpha = .01. Practical significance
was considered met if each standardized regression weight was greater than .40 (Harman,
1976). All but one of the estimated weights met both statistical and practical significance.
The estimated weight for Best Friend associated with the Employee Engagement variable
met statistical significance but not practical significance. The measurement model was
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revised through the deletion of the weak variable. All weights in the revised model met
both statistical and practical significance. (See Tables 5 and 6 in Appendix C).
The second criterion for assessing the adequacy of the measurement model was an
assessment of the overall fit of the model based on two indices. The Comparative Fit
Index (CFI)—also known as the Bentler Comparative Fit Index—compares the fit of the
specified model to a worst case model assuming all latent variables are uncorrelated.
Bentler (1990) and Garson (2008b) recommended that a CFI index greater than .90
suggests adequate fit. The Root Mean Square of Approximation (RMSEA) assesses the
degree of error associated with covariation estimates resulting from the model. RMSEA
values near .05 are considered indicative of close fit, while estimates greater than .05 but
less than .08 are considered adequate (Schumacker & Lomax, 2004). Both the original
(12 and 3 item latent variables, CFI = .901, RMSEA = .040) and revised (11 and 3 item
latent variables, CFI = .904, RMSEA = .042) met both of these criteria. See Table 7 in
Appendix C.
A third criterion for assessing the adequacy of the measurement model was
required because this research proposed structural path differences between the 4 age
groups. Following Mullen (1995) and Singh (1995), the fit of the measurement model
was assessed allowing all regression weights to vary independently for each group and
then constraining all measurement weights to be equal for all four groups. Comparing the
fit of these two models allowed determination as to whether the measures of Employee
Engagement and Compensation Fairness were equally appropriate for the four target age
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groups. The fit of the two models was not significantly different (CMIN = 53.780 at 42
DF, P=.105); therefore, criterion 3 was met. See Table 7 in Appendix C.
Reliability coefficients were computed for both scales. Cronbach;s alpha for the
11-item Employee Engagement was .898. Cronbach’s alpha for the 3-item Compensation
Fairness scale was .739.
Structural Model
Continuing to follow the Anderson and Gerbing (1988) approach and upon acceptance of
the measurement model, the structural model was assessed. The structural model for the
current study consisted of the latent constructs Employee Engagement and Compensation
Fairness, Job Satisfaction as a mediator, and Turnover Intent as the outcome variable
(See Figure 5, Appendix B). Both Job Satisfaction and Turnover Intent were measured by
single items.
Prediction of Turnover Intent
For the structural model where both latent constructs Employee Engagement and
Compensation Fairness served as antecedent variables for both Job Satisfaction and
Turnover Intent and Job Satisfaction served as an antecedent variable for Turnover Intent,
the all paths model (i.e., the model testing all paths simultaneously without constraint)
was found problematic as convergence was not reached. Therefore, a reduced model (still
testing all paths) was tested where Job Satisfaction was eliminated thereby testing only
direct relationships from Employee Engagement to Turnover Intent and from
Compensation Fairness to Turnover Intent. This reduced model addressed both
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hypotheses 1a and 1b which tested the relationship between both Employee Engagement
and Compensation Fairness on Turnover Intent. The all paths model assessing direct
relationships had a CMIN of 1182.286 with DF of 396, CFI of .900, and RMSEA of .41
with PCLOSE of 1.000. All paths in this model were significant (p<.01). The
standardized regression weights for Employee Engagement to Turnover Intent was -.42
and for Compensation Fairness to Turnover Intent was -.16. The correlation between
Employee Engagement and Compensation Fairness was .52. In terms of predicting
Turnover Intent, Employee Engagement is a much stronger predictor of Turnover Intent
than Compensation Fairness. Hypothesis 1a assessing the relationship between Employee
Engagement and Turnover Intent was supported due to the significance and negative
value of the standardized regression weight (-.42). Likewise, hypothesis 1b assessing the
relationship between Compensation Fairness and Turnover Intent was supported due to
the significance and negative value of the standardized regression weight (-.16).
Therefore, for faculty surveyed in the current study, it was concluded that both Employee
Engagement and Compensation Fairness were both inversely related to Turnover Intent.
Mediating Effects of Job Satisfaction in the Structural Model
Following Baron and Kenny (1986), both hypotheses 2a and 2b assessed the
mediating effects of Job Satisfaction on the relationship between Employee Engagement
and Turnover Intent as well as between Compensation Fairness and Turnover Intent. The
incomplete mediation model, looking at both models simultaneously, could not be
estimated as that model is the same as the all paths model addressed earlier. However,
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constraining the respective paths to be equivalent across the four age groups (no
moderation) allows hypotheses 2a and 2b to be addressed. For this model assessing the
mediating effects of job satisfaction CMIN was 1456.804 with 464 DF, CFI of .891,
RMSEA of .042, and PCLOSE of 1.000. Following procedures outlined by Baron and
Kenny (1986), several competing models were tested assessing effects (i.e., direct effects
from either antecedent variable on Turnover Intent, direct effects from both antecedent
variables on Turnover Intent, effects from either antecedent variable on Job Satisfaction,
effects from both antecedent variables on Job Satisfaction, and effects from Job
Satisfaction to Turnover Intent). Based on CMIN, CFI, and RMSEA, the accepted model
was one where Job Satisfaction was not significantly related to Turnover Intent. This
finding was unexpected. For this model (i.e. no Job Satisfaction effects model), CMIN
was 1457.659 with DF 465, CFI was .891, RMSEA was .042, and PCLOSE was 1.000.
In a model comparison, the model where Job Satisfaction had no effect on Turnover
Intent was not significantly different from the all paths no group differences model
assessing the mediating effects of job satisfaction with DF of 1, CMIN of .855, and P of
.355. The no Job Satisfaction effect model was selected on parsimony grounds. For the
no Job Satisfaction effect model, the average standardized path weight from Employee
Engagement to Job Satisfaction was .69, from Compensation Fairness to Job Satisfaction
was .17, from Employee Engagement to Turnover Intent was -.44, and from
Compensation Fairness to Turnover Intent was -.16. See Figure 7, Appendix B.
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Both hypothesis 2a assessing Job Satisfaction as a mediator between Employee
Engagement and Turnover Intent and hypothesis 2b assessing Job Satisfaction as a
mediator between Compensation Fairness and Turnover Intent were not supported.
Therefore, it was concluded that Job Satisfaction does not mediate the relationship
between Employee Engagement and Turnover Intent or between Compensation Fairness
and Turnover Intent for faculty.
Moderating Effects of Age in the Structural Model
Following Kenny and Judd (1984), both hypothesis 3a and 3b tested the
moderating effects of Age on the relationships between antecedents Employee
Engagement and Compensation Fairness with outcome variable Turnover Intent. In an
assessment of competing models where group differences between the various constructs
of the model were evaluated, the model where paths were constrained to be equal across
groups and where Job Satisfaction did not have a significant effect on Turnover Intent
demonstrated best fit and was the accepted model. For this model, CMIN was 1457.659,
DF was 465, CFI was .891, and RMSEA was .042 with PCLOSE equal to 1.000.
Therefore, both hypothesis 3a (i.e., Age moderates the relationship between antecedent
Employee Engagement and outcome variable Turnover Intent) and hypothesis 3b (i.e.,
Age moderates the relationship between antecedent Compensation Fairness and outcome
variable Turnover Intent) were not supported, and it was concluded that Age does not
moderate the relationship between Employee Engagement and Turnover Intent nor
between Compensation Fairness and Turnover Intent for this population.
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Summary
After eliminating the variable Best Friend, an 11-item Employee Engagement
factor and 3-item Compensation Fairness factor was confirmed in the measurement
model. See Table 7 in Appendix C for a summary of measurement models. Concerning
the structural model, both factors were significantly and inversely related to Turnover
Intent. Both factors were significantly and positively related to Job Satisfaction. Job
Satisfaction was not found significantly related to Turnover Intent. And, the variable Age
was not found to moderate the relationships. See Table 8 in Appendix C for a summary
of structural models. See Table 9 in Appendix C for a summary of hypotheses and
findings.
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CHAPTER V
Conclusion and Recommendations
“So here's what I want you to do, God helping you: Take your everyday, ordinary life—
your sleeping, eating, going-to-work, and walking-around life—and place it before God
as an offering. Embracing what God does for you is the best thing you can do for him.”
(Romans 12:1, The Message, Gospel Communications International, 2009)
Conclusion
The American workforce is changing due to retiring babyboomers, lengthening life span,
changing ethnic makeup of workers, the evolving family life cycle, decreasing
educational level, and other external factors, thus, creating a “workforce crisis” for
American businesses and organizations (Dychtwald, et al., 2006). The voluntary turnover
of workers seeking to find better jobs further exacerbates the shortage of skilled laborers
(Dychtwald, et al, 2006; Jamrog, 2004). Human Resource Development (HRD)
professionals are in a position to ready their organizations for these changes by ensuring
the organizational culture is conducive to employee retention and employee engagement.
Even within the context of higher education, HRD professionals may be useful in
encouraging retention by creating an engaging environment, thus softening the blow of
the nearly 50% of faculty speculated to retire before 2015 (Harrison & Hargrove, 2006).
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Findings
The current study had a number of findings that were of importance, some
revealing of the faculty and the organization for which they work others contradictory to
findings in the related literature. Simple means were rather revealing of the faculty
surveyed. While all the means for Employee Engagement items were positive (i.e.,
faculty agreed with the statements), none were particularly high with several approaching
mid-range (e.g., Recognition, Progress/Appraisal, Opinions Count, Mission, and
Development). Suggestions are made below under “Recommendations for Practice” for
techniques that can be used to improve these scores. As far as the more positive scores,
these included Expectations, Best friend, and Learn and Grow.
Even more revealing were the scores for both Job Satisfaction and Turnover
Intent. For Job Satisfaction, the mean was 2.27 indicating that overall faculty agreed with
the statement but leaned toward a mid-range response. This finding could be considered
fairly positive as some researchers have reported that employees are disclosing some of
the highest levels of dissatisfaction in years (Jamrog, 2004).
Concerning Turnover Intent, faculty was mid-range in their response. With a
mean of 3.04 on a 5 point Likert-type scale, this response was somewhat troubling to the
researcher. It is important to note that data collection occurred before the recent recession
and tightening of the purse springs at this university. Therefore, the question remains as
to how many employees have disengaged themselves from their job because they want to
move to a new job but are unable to do so given today’s current economic conditions.
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For the measurement model for Employee Engagement (Buckingham et al.,
1999), an 11-item model was accepted that eliminated the variable Best Friend as
measured by the GWA item “I have a best friend at work”. This finding was not entirely
surprising when the related job characteristics of a faculty member were considered.
While faculty are hired to work with students (i.e., teaching, advising, etc.), there are
other components of their job, such as research and service, that offer opportunities for
faculty to develop friendships. For example, attending academic conferences and
workshops across the academy (not university) and reviewing works for publication—
interprofessional collaboration—allows these friendships occasion to grow. This
networking across the U.S. for the purposes of research and service is essential to the
success of American faculty in academia and further differentiates academic faculty from
those in higher education. Second, faculty in higher education may transfer several times
across the length of their career from institution to institution of higher education
necessitating relocations—many of great distance—of their families. Faculty who
relocate any significant distance are likely to have no (or few, at best) friends at their new
location. Therefore, because faculty are focused on students and may relocate in order to
maintain employment (or improve employment status) having a best friend at work may
not be as important a characteristic as it would be for someone in a non-academic career
who may choose to apply for a new job across town in order to be with his or her friends.
For this same measurement model for the latent construct Employee Engagement,
manifest variables Care (i.e., “My supervisor, or someone at work, seems to care about
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me as a person”), Development (i.e., “There is someone at work who encourages my
development”), and Opinions Count (i.e., “At work my opinions seem to count”) were
found to load consistently high across all 4 target age groups as evidenced by their
standard regression weights (see Table 5, Appendix C). This finding seems to imply that,
for faculty, whether they “matter” to someone and have “meaning” to others in their role
as faculty is important to them (Kahn, 1990; Ledford & Lucy, 2002; May et al., 2004).
Since faculty spend time supporting the academic growth and development of their
students, it is surmised that it is important that someone show them support on a personal
level (Smith & Stevens, 1992), support for training and growth (Greenhaus, et al., 1990),
and support for their ideas (Eisenberger, et al., 1986).
For hypothesis 1a (i.e., Employee Engagement is inversely related to Turnover
Intent) and hypothesis 1b (i.e., Compensation Fairness is inversely related to Turnover
Intent), it was concluded that both Employee Engagement and Compensation Fairness are
both inversely related to Turnover Intent. That is, as Employee Engagement and
Compensation Fairness go up, Turnover Intent for faculty goes down. This finding was
consistent with previous theory (i.e., one’s evaluation of current job is inversely related to
Turnover Intent; see Mobley, 1977; Mobley et al., 1978; Mobley et al., 1979; Muchinsky
& Morrow, 1980) as well as decades of research (Ross & Zander, 1957; Ferguson, 1958;
Youngberg, 1963; Hulin, 1968; Tell et al, 1971; Gupta & Beehr, 1979; Eisenberger et al.,
1990; Buckingham & Coffman, 1999; Tekleab et al, 2005; Heckert & Farabee, 2006;
EKim & Lee, 2007). And, with standardized regression weights at -.42 and -.16
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respectively, Employee Engagement is a much stronger antecedent of Turnover Intent
than Compensation Fairness for this population of faculty in higher education. Or, said
another way, for this population, salary is not nearly as important as the characteristics of
the work environment that encourage them to become engaged in what they do. These
results are somewhat consistent with the Segal Group’s (2007) Rewards of Work study
involving faculty in higher education which determined that compensation was cited less
often than work content (i.e., meaningfulness, feedback, and variety; see Ledford &
Lucy, 2002; The Segal Group, Inc., 2006d) and affiliation (i.e., work environment, trust,
and variety) as important for retention.
For hypothesis 2a (i.e., Job Satisfaction mediates the relationship between the
antecedent Employee Engagement and outcome variable Turnover Intent) and hypothesis
2b (i.e., Job Satisfaction mediates the relationship between the antecedent Compensation
Fairness and outcome variable Turnover Intent), it was concluded that Job Satisfaction
does not mediate the relationship between Employee Engagement and Turnover Intent or
between Compensation Fairness and Turnover Intent. This finding was quite unexpected
as Job Satisfaction is presented as a precursor to Turnover Intent in both theory (see
Mobley, 1977; Mobley et al., 1978; Mobley et al., 1979; Muchinsky & Morrow, 1980)
and the general research literature (see Youngblood, et al., 1983; Shulz, et al., 1987;
Weiberg, et al., 1991; Hellman, 1997; Lum, et al., 1998; Bernthal, et al., 2000). The
author speculated this finding could be due to several reasons. First, the failure of the
variable Job Satisfaction to mediate the relationship may be due to the current study’s
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investigation into a unique population—faculty as an occupational group—whose
satisfaction with their job is based on their work environment (i.e., their work
environment is conducive to them doing what they do best—research, instruction,
service—and they are satisfied with this) and the fairness of their pay. They do not intend
to turnover when their perceptions of the engagement climate and fairness of pay are
positive. But, they do not choose to stay or go based simply on their level of Job
Satisfaction. Second, the failure of the variable Job Satisfaction to mediate the
relationships between both Employee Engagement and Compensation Fairness and the
outcome variable Turnover Intent may be due to the specificity of the wording (of the
lack, thereof) of the survey item assessing Job Satisfaction (i.e., “Overall, I am satisfied
with the University as a place to work”). The definite article “the” may be misleading to
participants who perhaps read the survey item as “Overall, I am satisfied with any
University as a place to work” as opposed to the implied “Overall, I am satisfied with this
particular University as a place to work.” For participants who are satisfied with their
career choice of faculty at a university, their response to their intent to leave this
university is understandably unrelated.
For both hypothesis 3a (i.e., Age moderates the relationship between antecedent
Employee Engagement and outcome variable Turnover Intent) and hypothesis 3b (i.e.,
Age moderates the relationship between antecedent Compensation Fairness and outcome
variable Turnover Intent), it was concluded that Age does not moderate the relationship
between Employee Engagement and Turnover Intent nor between Compensation Fairness
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and Turnover Intent. This finding was also unexpected as the hypothesized relationship
was built on both theory and research. Theoretically, both Super’s Life-Span, Life-Space
Theory and Generational Cohort Theory were used to offer support for the argument that
Age would moderate the relationship through both age effects and cohort effects
respectively. Super’s theory (also called Theory of Career Development) has put forward
that at the various career stages (i.e., Growth, Exploration, Establishment, Maintenance,
and Decline), an individual can be characterized by particular attitudes and behaviors
(Pietrofesa & Splete, 1975). Generational Cohort Theory described ways in which social
cohorts could impose age-related effects on cross-sectional data through social cohorts
based on birth years, size, structure, social events, leaders, and values (Lancaster &
Stillman, 2002; Zemke et al., 2000; Deal, 2007). With regards to research, several
researchers (Rhodes, 1983; Steel & Ovalle, 1984; for example) have suggested that there
are certainly age-related differences in the work attitudes and behaviors of workers.
Based on their work with the GWA, Jones and Harter suggested that age could be a
potential moderator. Additionally, researchers such as Lachman and Diamant (1987) have
suggested that age is a restraining factor that keeps employees on the job and, therefore,
decreases turnover intent. Finally, Dychtwald et al. (2006) reported that mature workers
had the highest levels of engagement. Yet, in spite of the backing of both theory and
research, age-related differences were not seen.
In an effort to better understand the failure of age to moderate the prescribed
relationships, a post hoc ANOVA was conducted comparing means across target age
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groups for both Employee Engagement and Compensation Fairness scales as well as Job
Satisfaction and outcome variable Turnover Intent. Results indicated that Age was not a
factor influencing any of these variables as all F Scores were non-significant. (See Table
10 in Appendix C). Therefore, it was concluded that age was not a factor influencing
these variables for faculty in higher education. Explanations for this failure to find the
expected age-related differences may be in the instrumentation’s lack of sensitivity to the
variable Age.
Significance of the Study
While the study found no evidence for the mediating effects of Job Satisfaction
nor the moderating effects of Age, the study did prove significant in several ways. First, it
extended previous conceptualizations of turnover intent by incorporating both employee
engagement and compensation fairness as an antecedent of turnover intent and
demonstrated evidence for the same. Little research has done this, especially with a
unique population like faculty. Second, the study confirmed the use of the Gallup
Workplace Audit with faculty, albeit with minor alterations.
Objectives of the Study Satisfied
The study satisfied the objectives of the study by:
• Testing the measurement models for both Employee Engagement and
Compensation Fairness. (See Figures 3 and 4 in Appendix B).
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• Testing the prediction of the outcome variable Turnover Intent by antecedents
Employee Engagement and Compensation Fairness. (See Figure 5 in Appendix
B).
• Testing the mediating effects of Job Satisfaction on the relationship between
antecedents Employee Engagement and Compensation Fairness and the outcome
variable Turnover Intent. (See Figure 5 in Appendix B).
• Testing the moderating effect of Age on the relationship between antecedents
Employee Engagement and Compensation Fairness and the outcome variable
Turnover Intent. (See Figure 5 in Appendix B).
Improvements Made to Employee Engagement Literature
One improvement for better understanding the Gallup Workplace Audit (GWA) is
the link between the 12 items of the GWA with related concepts in the literature. This
task was not satisfactorily presented when the GWA was first published in Buckingham
and Coffman (1999). The current study addressed this problem linking the 12 items to
several prominent concepts and surveys commonly used in the literature. See Table 2 in
Appendix C.
Study LimitationsThere are a number of limitations to the current study. The
limitations of the study are addressed below:
The study utilized secondary data, which has its limitations including lack of control
over methodological concerns such as selection of sample from the population and
instrumentation. First, the study was limited by the selection of the sample. While a
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random sample could have been drawn, instead a convenience sample was used which
certainly could have impacted the types of responses received from respondents. For
example, employees that were concerned that information may be used against them may
have chosen not to respond.
Next, the study was limited by instrumentation. The Gallup Workplace Audit has
appeared relatively recently in the literature (Buckingham & Coffman, 1999) and for use
among non-Gallup researchers. The latent construct Compensation Fairness was assessed
with only three items resulting in just identification. Turnover Intent and Job Satisfaction
were assessed with only one item. Hence, more grounded instrumentation would have
been desirable, like the Utrecht which will be further discussed later under the section
“Recommendations for Future Research.”
While these are certainly valid concerns, secondary data can be a useful source of
information. Much research has been conducted on turnover in the past 30 years with the
general conclusion that affect influences subsequent behavior (Clegg, 1983). This
conclusion is evident in the various theories developed to explain turnover with most
theories or models generally falling into two categories (Maertz & Campion, 2004): first,
process models of turnover (i.e., Mobley, 1977; Mobley, Griffeth, Hand, & Meglino,
1979) endeavor to explain how people quit via a linear decision sequence frequently
involving job satisfaction and, second, content models of turnover (Maertz & Campion,
2004) endeavor to explain why people quit (i.e., their motivations for quitting). While
Maertz and Campion cautioned that the reliance on the use of any single model to explain
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turnover risks deficiency, the researcher acknowledges that the current study’s general
adherence to a process model of turnover (e.g., Fishbein and Ajzen’s theory of reasoned
action) is a limitation of the current study.
Responses of subjects limited the results of the study. Particularly, the freedom that
subjects felt in disclosing their beliefs about their work climate may have limited the
responses of the subjects and, therefore, the results of the study.
Recommendations
Based on the findings, recommendations were made for both future research and practice.
Recommendations follow.
Recommendations for Future Research
While every study has its strengths, weakness, limitations, and findings, this study
is no different. Recommendations for future research are included that address needs
regarding the Gallup Workplace Audit, measurement of job satisfaction, and
measurement of turnover intent including such measurement during times of various
economic conditions.
The first recommendation for future research is to further examine The Gallup
Workplace Audit (GWA) should be further examined. There are several reasons for this.
First, the GWA lacks significant scholarly research yet appears rather extensively in the
consulting literature. Therefore, the psychometric properties of the GWA should be
examined in scholarly research. Second, the GWA should be confirmed for use with a
number of different population groups (i.e., career, demographic, etc.) as the current
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study demonstrated the 12-item employee engagement scale could not be confirmed to be
used with faculty in this study without first omitting the variable best friend. Third, the
relationships between employee engagement and other variables should be explored and
expanded.
The second recommendation is to incorporate an instrument that assesses
employee engagement (i.e., vigor and absorbency of employees into their work). While
the current study focused on employee engagement as measured by the Gallup
Workplace Audit which assesses workplace characteristics that are purported to
encourage employee engagement, employee engagement (i.e., the passion one has for his
or her job) is frequently assessed using the Utrecht Work Engagement Scale (UWES), a
self-report instrument measuring engagement across vigor (e.g., “When I get up in the
morning, I feel like going to work” [p. 302]), dedication (e.g., “I am enthusiastic about
my job” [p. 302]), and absorption. (e.g., “When I am working I forget everything else
around me” [p. 302]) (Schaufeli et al., 2004). The UWES has demonstrated good internal
consistency with Cronbach’s alpha ranging from .80 to .90 (Schaufeli, Bakker, &
Salanova, 2006). Future research may benefit from using both the GWA and the UWES
together as it has proven to be a meaningful and grounded instrument (Schaufeli, et al.,
2004; Schaufeli, et al., 2006). Specifically, future studies could examine the relationship
between the 12 items of the GWA and the UWES. Differences in responses to the GWA
across various demographic groups (i.e., gender, age, etc.) as well as between satisfied
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and engaged employees and dissatisfied and unengaged employee (i.e., “time bandits;”
see Ketchen, Craighead, & Buckley, 2008) may also be examined.
A third area for suggested future research (also practice) is the application of the
employee engagement scale to other institutions such as churches, volunteer
organizations, marriages, families, and even schools. For example, concerning schools,
can the Gallup Workplace Audit be rewritten for research and application in schools to
address attendance and dropout issues? For students, questions could be rephrased as
follows: “Do you know what is expected of you at school in the classroom?” “Do you
have the clothes, transportation, materials, and supplies to come to school and do your
work?” “In the last week, have you received recognition for doing good work?” “At
schools, does someone seem to care about you as a person?” With the advent of No Child
Left Behind, many schools are scrambling to reduce dropout rates in order to increase
graduation rates. Engaging hard-to-reach students in the learning process is a difficult
task that could potentially benefit from reframing the Gallup Workplace Audit to fit the
academic domain.
A fourth recommendation made is to repeat the current study in order to better
understand the failure of Job Satisfaction to mediate the relationship between manifest
variables Employee Engagement and Compensation Fairness and outcome variable
Turnover Intent as this finding was contrary to both theory and research and, therefore,
unexpected. One explanation of this unexpected finding involved the use of the particular
item assessing job satisfaction that may be misleading to participants. Future research
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may benefit on the use of a different single-item measure of job satisfaction or on the use
of a scale assessing the multidimensionality of job satisfaction such as Spector’s (1997)
Job Satisfaction Index.
Finally, it was recommended that the job satisfaction-turnover intent relationship
be examined in light of economic conditions. The turnover model proposed by
Muchinsky and Morrow (1980) predicted that the relationship between job satisfaction
and turnover is moderated by economic conditions of the time. Specifically, in times of
plenty, employees are more likely to turnover if they are not satisfied with their job. And,
in times of recession or high unemployment, employees are more likely to maintain their
present employment. While the American economy has taken a turn for the worse in
recent months, the data collected for this study was just prior to this downward turn.
However, this change in economic conditions is suggestive of some interesting research
questions. For example, how do economic turns (i.e., positive or negative) affect the
prediction of turnover intent by employee engagement and compensation fairness?
Recommendations for Practice
The problem of turnover is not always addressed effectively even though human
resource professionals consider it problematic. Bernthal and Wellins (2000) reported that
greater than 1/3 of human resource professionals they surveyed saw retention as a
pressing issue, and almost half of organizations interviewed had no formal strategy for
addressing the problem of retention. On the practical side, the examination of an
employee’s turnover intent allows the opportunity for human resources to take a
142
proactive approach to increasing retention and delaying turnover in an organization as
opposed to gleaning the same information from an exit interview associated with a
voluntary turnover.
Based on the findings of this study, Employee Engagement is a much larger
antecedent of Turnover Intent than Compensation Fairness for faculty in the current
study. Therefore, it stands to reason that human resources and management at all levels
can decrease turnover intent by increasing employee engagement, at least among faculty.
The following paragraphs take the 12 variables of the employee engagement scale (i.e.,
Gallup Workplace Audit) in reverse rank order (i.e., lowest scored to highest scored) and
make recommendations for increasing employee engagement in each of the areas as it
stands to reason that the biggest differences in increasing employee engagement can
occur when the poorest scores are raised.
Recognition
Recognition (i.e., “In the last seven days, I have received recognition or praise for
doing good work”) had the lowest score in a rank ordering of the variables comprising
Employee Engagement based on mean. Therefore, improving Recognition can be
important in increasing the overall Employee Engagement score. The author
recommended the following to improve the score for Recognition:
• Recognize faculty formally in celebratory events. Do so frequently (Seigts
& Crim, 2003).
• Recognize faculty at the university, college, and departmental level.
143
• Congratulate faculty in university, college, and/or departmental
newsletters for professional achievements.
• Offer tangible rewards for service and professional achievements such as
preferred parking, sporting events tickets, etc.
• Recognize in faculty meetings things that employees do well, both small
and large (Trivette, 1990).
• Informally acknowledge faculty successes in conversations, phone calls,
emails, etc. (Campion, 1988) by offering praise for jobs well done
(Oldham & Cummings, 1996).
• Recognize workers weekly.
• Nominate faculty for awards when appropriate.
Progress/Appraisal
Holding the second lowest score in a rank ordering of the variables comprising
Employee Engagement based on mean, Progress/Appraisal (i.e., “In the last six months,
someone at work has talked to me about my progress”) can also be a critical factor in
increasing the overall Employee Engagement score. The author recommended the
following to improve the score for Progress/Appraisal:
• Complete job evaluations twice a year. One may be formal, the other more
informal. Document both meetings.
• Tell faculty exactly where they stand (Roznowski, 1989) but provide
constructive feedback rich in content and delivered in a timely manner
144
(Michael et al., 2006) in an effort to move them to where you want them
to go.
• Provide performance coaching for faculty. That is, provide both formal
and informal feedback from various individuals within an organization
about performance on the job (Holton, Bates, & Ruona, 2000). Consider
the use of a coach or mentor separate from one’s direct report to whom the
faculty member may ask questions or can discuss various issues without
fear of disciplinary action.
• Allow employees to establish goals and benchmarks for achieving those
goals and provide opportunities for self-evaluation and reporting.
Opinions Count
Opinions Count (i.e., “At work my opinions seem to count”) had the third lowest
score in a rank ordering of the variables comprising Employee Engagement based on
mean but had one of the highest factor loadings on the variable Employee Engagement.
Therefore, improving Opinions Count can also be important in increasing the overall
Employee Engagement score. The author recommended the following to improve the
score for Opinions Count:
• Give attention to employees’ opinions (Cook et al., 1981), especially those
that directly affect them (Kahn et al., 1964).
• Give all employees a chance to voice their concerns without retaliation or
punitive action.
145
• Conduct Town Hall Forums, Focus Groups, and Communities of Practice to
allow faculty to voice their opinion.
• Set ground rules for appropriate behavior in department meetings. Monitor
collegiality in meetings to ensure all have equal voice and no one is publicly
criticized for their opinion.
Mission
The fourth lowest score in a rank ordering of the variables comprising Employee
Engagement based on mean was Mission (i.e., “The mission/purpose of the University
makes me feel my job is important”). Improving the variable Mission can also be
important in increasing the overall Employee Engagement score. The author
recommended the following to improve the score for Mission:
• Include faculty in an effort to discuss, revise, and communicate the mission of
the organization.
• Make the goals of the organization clear (Spector, 1997) by including them in
various media (i.e., newsletters, email, and websites).
• Post these goals.
• Show faculty the significance of their job (Hackman & Oldham, 1974) in
relation to organizational objectives (Ivancevich et al., 1980).
• Align mission statements with job duties and include on faculty’s job
description.
146
Development
Development (i.e., “There is someone at work who encourages my development”)
had the fifth lowest score in a rank ordering of the variables comprising Employee
Engagement based on mean but had one of the highest factor loadings on the variable
Employee Engagement. Therefore, improving Development can also be important in
increasing the overall Employee Engagement score. The author recommended the
following to improve the score for Development:
• Take the time to learn about the career goals and aspirations of faculty
members.
• Make faculty aware of career opportunities within the university.
• Encourage faculty to develop new skills (Oldham & Cummings, 1996).
• Support faculty’s attempts to obtain additional training and education by
offering seed funding for workshops and new course preparation.
• Offer special projects to increase the faculty members’ visibility within the
university (Greenhaus, Parasuraman, & Wormley, 1990).
Materials
The variable Materials (i.e., “I have the materials and equipment I need to do my
work right”) had the next lowest score in a rank ordering of the variables comprising
Employee Engagement based on mean. The author recommended the following to
improve the score for Materials:
147
• Provide faculty with access to needed materials and equipment (Rentsch &
Steel, 1992).
• Regularly ask faculty to consider what materials may help them better
perform their jobs.
• Expose faculty to new technology and resources that they may be able to use
in the classroom to say on the cutting edge.
• Offer support for materials and equipment use including specific training, if
necessary.
Opportunity
Next was Opportunity (i.e., “At work I have the opportunity to do what I do best
every day”). The author recommended the following to improve the score for
Opportunity:
• Determine faculty’s specific abilities and skills (Weiss, Dawis, England, &
Lofquist, 1967).
• Consult with faculty to identify barriers that hinder their ability to maximize
their potential.
• Give faculty opportunities to use their abilities and skills (Weiss et al., 1967),
but don’t overwhelm faculty by imposing too many extra assignments on
them.
• Create teams that include people with a variety of skills so that each will have
a chance to contribute.
148
Quality Work
Although Quality Work (i.e., “My co-workers are committed to doing quality
work”) was the fifth highest score, the author recommended the following to improve the
score for Quality Work:
• Ensure all faculty are pulling their weight (Spector, 1997).
• Offer support in the form of training to those with difficulty completing their
job competently.
• Be open regarding responsibilities and tasks so that accurate assessments of
workload are made.
• Offer seed funding for those faculty developing new courses or overhauling
current courses to ensure quality education for students and quality
performance on behalf of faculty.
• Initiate continuous improvement techniques in each department.
• Avoid the temptation to reward high quality work with additional
responsibilities.
Care
While Care (i.e., “My supervisor, or someone at work, seems to care about me as
a person”) received the fourth highest score, it still deserves to be maintained and even
improved upon as it had one of the highest factor loadings on the variable Employee
Engaegment. The author made the following recommendations to improve Care:
149
• Support faculty by caring, listening, helping, and protecting them (Baruch-
Feldman, et al., 2002).
• Affirm, support, respect, and trust faculty (Curran, 1983).
• Offer special favors from time to time if needed (i.e., time off, early leave,
excused tardiness, etc.) (Eisenberger et al., 1986).
• Get to know your subordinates (BlessingWhite, 2008).
• Provide an ombudsman to mitigate differences between the university and
faculty.
Learn and Grow
Learn and Grow (i.e., “This last year, I have had opportunities at work to learn
and grow”) was the third highest score. The following recommendation may improve or
maintain this factor:
• Offer personal growth and development opportunities (Hackman & Oldham,
1974).
• Offer opportunities to learn new things (Frese et al., 1996) and opportunities
to develop and strengthen new skills (Greenhaus et al. (1990).Communicate
with faculty that it is acceptable to explore creative and less traditional outlets
for personal growth and development.
• Offer seed monies for faculty to attend workshops and conferences to develop
new skills associated with their position.
150
Best Friend
At second highest, Best Friend (i.e., “I have a good friend at work”) was removed
from the Employee Engagement scale due to being a weak variable. Rationalizations for
this occurrence have been offered. Nevertheless, steps can be made to improve the
workplace for the employee. The author suggested the following:
• Endorse faculty’s need to interact (Sims et al., 1976).
• Allow time to make and maintain friendships through communication,
showing care, and encouragement.
• Organize events outside the university setting to encourage friendships among
faculty (for example, family picnics).
Expectations
Coming in with the highest mean, Expectations (i.e., “I know what is expected of
me at work”) should not be overlooked. The author made the following suggestions to
continue to maintain or even improve the Expectations score:
• Explain work assignments fully (Spector, 1997).
• Create clear goals and objectives for faculty (House, Schuler, & Levanoni,
1983).
• Expectations should be articulated from day one and reviewed periodically.
Include information about expectations regarding time spent in the office to
service-related duties to teaching to scholarly activities.
• Allow faculty to have input in creating their job descriptions.
151
Each of the before mentioned recommendations can be implemented rather easily
in this university without adding significantly to their bottom line. Many of the
recommendations can be implemented at no cost. Thus, in times of a dismal economy,
actions can still be taken to improve employee morale and increase the retention rates of
faculty, even without providing salary increases.
Summary
In sum, the current study assessed the moderating effects of Age and the
mediating effects of Job Satisfaction on the relationship between antecedents Employee
Engagement and Compensation Fairness and the outcome variable Turnover Intent. The
theory of reasoned action and a theoretical framework for examining age-effects on
employee attitudes were used as the theoretical underpinnings for the study. The study
utilized a secondary data set including faculty (n = 1,229). Findings confirmed that 11 of
the 12 items of the Gallup Workplace Audit loaded on the Employee Engagement factor.
Findings also confirmed a 3-item solution for the Compensation Fairness factor. Both
Employee Engagement and Compensation Fairness demonstrated an inverse relationship
with Turnover Intent as expected. Job Satisfaction was found not to mediate the
relationship between both Employee Engagement and Compensation Fairness with the
outcome variable Turnover Intent. Finally, Age was not found to moderate the
relationship between antecedent variables and Turnover Intent. Recommendations were
made for future research and practice.
152
153
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APPENDICES
198
APPENDIX A
199
Employee Satisfaction Survey
Please take a moment to complete this questionnaire. Your answers will guide the
_________________________ _____ _______________ efforts to retain our employees and will
be reported in statistical form only. Thank you for your assistance.
For questions, please send an e-mail to _________________________________.
SA = Strongly Agree A = Agree N = Neither agree or disagree D = Disagree SD = Strongly
Disagree
SA A N D SD
1. I know what is expected of me at work.
2. I have the materials and equipment I need to do my work
right.
3. At work I have the opportunity to do what I do best every
day.
4. In the last seven days, I have received recognition or praise
for doing good work.
5. My supervisor, or someone at work, seems to care about me
as a person.
6. There is someone at work who encourages my development.
7. At work my opinions seem to count.
8. The mission/purpose of the University makes me feel my job
is important.
9. My co-workers are committed to doing quality work.
10. I have a good friend at work.
11. In the last six months, someone at work has talked to me
about my progress.
12. This last year, I have had opportunities at work to learn and
grow.
13. At the University my performance on the job is evaluated
fairly.
14. Compared to other people doing similar work at the
University, I think I am paid fairly.
15. Compared to other people doing similar work outside the
University, I think I am paid fairly.
16. The University's benefit programs meet my needs.
17. The University does an excellent job of keeping employees
informed about matters affecting us.
18. At the University we can speak our minds without fear of
reprisal.
19. I have given serious thought to leaving the University in the
past six months.
20. Overall, I am satisfied with the University as a place to work.
200
21. I have worked at the __________________________ _____ _______________________
0-2 years
3-5 years
6-10 years
11-20 years
21-30 years
31 – or more years
22. I supervise other employees:
No
Yes
23. I am staff:
Exempt
Non-exempt
24. I am faculty:
Non-tenure Track
Tenure Track
Tenured
25. I am employed by: ____________________________
26. Gender:
Female
Male
27. Age:
18 – 25
26 – 35
36 – 45
46 – 55
56 or over
201
28. Race:
American Indian/Alaskan
Asian/Pacific Islander
Black/Not Hispanic
Hispanic
White/Not Hispanic
Other
Comments:
202
APPENDIX B
203
Figure 1. Turnover Model Based on Mobley (1977), Mobley et al. (1978), Mobley et al.
(1979), and Muchinsky and Morrow (1980).
Evaluation of Current Job
Job Satisfaction
Thoughts of Quitting
Evaluates Usefulness of
Search/Cost of Quitting
Intends to Search
Searches for a New Job
Evaluates Alternatives
Compared to Present Job
Intends to Quit/Stay
Quits/Stays
Demographics, including Marital Status, Tenure, ;Individual Values, Interests, & Beliefs
Current Economic Conditions
204
Figure 2. Current Model: Mediating Effects of Job Satisfaction and Moderating Effects of
Age on the Relationship between Antecedents Employee Engagement and Compensation
Fairness (Evaluation of Job) and Outcome Variable Turnover Intent (Thoughts of
Quitting)
Evaluation of Current Job:
Employee Engagement &
Com
pe
nsation Fairness
Job Satisfaction
Thoughts of Quitting
Evaluates Usefulness of
Search/Cost of Quitting
Intends to Search
Searches for a New Job
Evaluates Alternatives
Compared to Present Job
Intends to Quit/Stay
Quits/Stays
Demographics, including Marital Status, Tenure, Individual Values, Interests, & Beliefs
Current Economic Conditions
205
Figure 3. Measurement Model for Employee Engagement.
Expectations
Materials
Recognition
Care
Development
Opinions Count
Progress/Appraisal
Best Friend
Quality Work
Mission
Opportunity to Excel
Learn and Grow
Employee Engagement
206
Figure 4. Measurement Model for Compensation Fairness.
Internal Compensation
External Compensation
Benefits
Compensation Fairness
207
Figure 5. Structural Model showing Prediction of Turnover Intent by Employee
Engagement and Compensation Fairness with Mediating Effects of Job Satisfaction and
Moderating Effects of Age.
Turnover Intent
Job Satisfaction
Compensation Fairness
Employee Engagement
Age
Y: High expectations with entitlement (Twenge,
2006), highest turnover intent (Lachman &
Diamant, 1987).
EMC &LMC: Has crisis points—lengthening
work horizon, work/life tension, career
bottleneck (Lancaster & Stillman, 2002), lower
turnover intent (Lachman & Diamant, 1987).
M: More engaged and more satisfied
(Dychtwald et al., 2006), lowest turnover intent
(Lachman & Diamant, 1987).
Age
Y: Looking for greener pastures (Ryan in
Siegfried, 2008), highest turnover intent
(Lachman & Diamant, 1987).
EMC & LMC: Maintenance Stage (Pietrofesa &
Splete, 1975) and sandwiched between 2
generations at home, lower turnover intent
(Lachman & Diamant, 1987).
M: Loyal (Lancaster & Stillman, 2002), possess
higher salaries (White & Spector, 1987), looking
to retirement (Pietrofesa & Splete, 1975), lowest
turnover intent (Lachman & Diamant, 1987).
-
+
-
-
+
Key:
Y = Young Worker
EMC = Early MidCareer Worker
LMC = Late MidCareer Worker
M = Mature Worker
208
Figure 6. Accepted Measurement Model for Employee Engagement, Compensation
Fairness. (Note: Best Friend was eliminated from measurement model).
Care
Development
Quality Work
Opinions Count
Mission
Recognition
Opportunity
Materials
Expectations
Benefits
External Compensation
Internal Compensation
Best Friend *
Progress/Appraisal
Employee Engagement
Compensation Fairness
Learn and Grow
209
Job Satisfaction
Turnover Intent
Employee Engagement
Figure 7. Accepted Model for Employee Engagement, Compensation Fairness, Job
Satisfaction, and Turnover Intent.
Compensation Fairness
-.44
-.16
.17
.69
210
APPENDIX C
211
Table 1. Employee Engagement Items (Gallup Workplace Audit), Variable Names of
Predictor Variables, and The Four Camps of the Gallup Workplace Audit (Buckingham
and Coffman, 1999).
Item Variable Names of
Predictor
Variables
GWA Camps
Do I know what is expected of me at work? Expectations
Do I have the materials and equipment I need
to do my work right?
Materials
Base Camp
or
“What do I get?)
At work, do I have the opportunity to do what
I do best every day?
Opportunity
In the last seven days, have I received
recognition or praise for doing good work?
Recognition
Does my supervisor, or someone at work,
seem to care about me as a person?
Care
Is there someone at work who encourages my
development?
Development
Camp 1
or
“What do I give?”
At work, do my opinions seem to count? Opinions Count
Does the mission/purpose of my company
make me feel my job is important?
Mission
Are my co-workers committed to doing
quality work?
Quality Work
Do I have a best friend at work? Best Friend
Camp 2
or
“Do I belong
here?”
In the last six months, has someone at work
talked to me about my progress?
Progress/Appraisal
This last year, have I had opportunities at
work to learn and grow?
Learn and Grow
Camp 3
or
“How can we all
grow?”
212
Table 2. Gallup Workplace Audit Items, Parallel Items in the Literature, Name of
Measure, Source, Relationship with Turnover Intent and/or Age.
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
Work assignments are
often not fully explained.
Respondents rate
satisfaction on a 6-point
Likert-type scale.
Job
Satisfaction
Survey
Spector
(1997)
NA 15
Task/goal clarity. The job
duties, requirements, and
goals are clear and
specific.
Respondents rate
agreement on a 5-point
Likert-type scale
Multimethod
Job Design
Questionnaire
Campion
(1988)
NA 79
My job duties and work
objectives are unclear to
me.
I am unclear about whom
I report to and/or who
reports to me.
I do not fully understand
what is expected of me.
Respondents rate amount
of stress of a 7-point
Likert-type scale.
Stress
Diagnostic
Survey
Ivancevich &
Matteson
(1980)
Job tension
correlated
positively
with
intention to
quit (Deluga,
1991; Rush,
Scheol, &
Barnard,
1985).
130
Expectations:
Do I know what is
expected of me at
work?
Being unclear on just
what the scope and
responsibilities of your
job are.
Respondents rated
frequency on a 5-point
Likert-type scale.
Job-Related
Tension Index
Kahn, Wolfe,
Quinn, &
Snoek (with
Rosenthal)
(1964)
NA 125
213
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
I don’t know what is
expected of me.
My responsibilities are
clearly defined.
I know what my
responsibilities are.
I have clear planned goals
and objectives for my job.
The planned goals and
objectives are not clear.
I know what is expected
of me.
Explanations are clear of
what has to be done.
Respondents rated
agreement on a 7-point
Likert-type scale.
Role Conflict
and Ambiguity
House,
Schuler, &
Levanoni
(1983)
Role
ambiguity
correlated
positively
with
turnover
intention
(O’Driscoll
& Beehr,
1994;
Westman,
1992).
149
I have clear planned goals
and objectives for my job
I know exactly what is
expected of me.
I know what my
responsibilities are.
I feel certain about how
much responsibility I
have.
My responsibilities are
clearly defined.
Respondents rated
agreement on a 5-point
Likert-type scale.
Cross-Cultural
Role Conflict,
Ambiguity,
and Overload
Peterson,
Smith,
Akande,
Ayestaran,
Bochner,
Callan, Cho,
Jesuino,
D’Amorim,
Francois,
Hofmann,
Koopman,
Leung, Lim,
Mortazavi,
Munene,
Radford,
Ropo,
Savage,
Setiadi,
Sinha,
Sorenson, &
Viedge,
(1995)
NA 155
214
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
I know exactly what is
expected of me.
Explanation is clear of
what has to be done.
I know what my
responsibilities are.
Clear, planned goals and
objectives exist for my
job.
Role Conflict
and Ambiguity
Rizzo,
House, &
Lirtzman
(1970)
Netemeyer,
Johnston,
and Barton
(1990) found
neither role
conflict nor
role
ambiguity
directly
affected
propensity to
leave.
147
How do you feel about
what you have available
for doing your job—I
mean the equipment,
information, good
supervision, and so on?
Respondents rate
satisfaction on a 7-point
Likert-type scale.
Satisfaction
with Job
Facets
Rentsch &
Steel (1992)
Measure
correlated
negatively
with
intention to
quit
(McFarlin &
Rice, 1992;
Steel &
Rentsch,
1997)
26
Not having enough help
or equipment to get the
job done well.
Respondents rate
frequency on a 5-point
Likert-type scale.
Occupational
Stress Scale
House,
McMichael,
Wells,
Kaplan, &
Landerman
(1979)
NA 135
Materials:
Do I have the
materials and
equipment I need
to do my work
right?
I receive assignments
without adequate
resources and material to
execute them.
Respondents rate
agreement on a 7-point
Likert-type scale.
Role Conflict
and Ambiguity
Rizzo et al.
(1970)
Netemeyer et
al.(1990)
found neither
role conflict
nor role
ambiguity
directly
affected
propensity to
leave.
147
Opportunity:
At work, do I have
the opportunity to
do what I do best
every day?
The chance your job gives
you to do what you are
best at.
Respondents rate
satisfaction on a 4-point
Likert-type scale.
Job
Satisfaction
Relative to
Expectations
Bacharach,
Bamberger,
& Conley
(1991)
NA 6
215
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
The chance to do
something that makes use
of my abilities.
Respondents rate
satisfaction on a 5-point
Likert-type scale.
Minnesota
Satisfaction
Questionnaire
Weiss,
Dawis,
England, &
Lofquist,
(1967)
Overall Job
Satisfaction
found
negatively
correlated to
propensity to
leave
(Klenke-
Hamel &
Mathieu,
1990; Smith
& Brannick,
1990) and
negatively
correlated
with
intention to
quit (Sagie,
1998)
8
Your opportunity to use
your abilities.
Respondents rate
satisfaction on a 7-point
Likert-type scale.
Global Job
Satisfaction
Cook,
Hepworth,
Wall, &
Warr (1981)
NA 27
Can you use all your
knowledge and skills in
your work?
End-point anchors are 1 =
very little, 5 = very much.
Control and
Complexity
Frese, Kring,
Soose, &
Zempel
(1996)
NA 98
I feel that my work
utilizes my full abilities.
I feel competent and fully
able to handle my job.
My job gives me a chance
to do the things I feel I do
best.
I feel that my job and I are
well matched.
I feel I have adequate
preparation for the job I
now hold.
Respondents rate
agreement on a 5-point
Likert-type scale.
Perceived
Ability-Job Fit
Xie (1996) Xie (1996)
found that
perceived
ability-job fit
was
correlated
positively
with age.
233
216
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
When I do a good job, I
receive the recognition for
it that I should receive.
There are few rewards for
those who work here.
I don’t feel my efforts are
rewarded the way they
should be.
Respondents rate
satisfaction on a 6-point
Likert-type scale.
Job
Satisfaction
Survey
Spector
(1997)
NA 15
The recognition you get
for good work.
Respondents rate
satisfaction on a 7-point
Likert-type scale.
Global Job
Satisfaction
Cook et al.
(1981)
NA 27
This organization
appreciates my
accomplishments on the
job.
This organization does all
that it can to recognize
employees for good
performance.
My efforts on the job are
largely ignored or
overlooked by this
organization.
Respondent rate
agreement on a 4-point
Likert-type scale.
Organizational
Commitment
Scale
Balfour &
Wechsler
(1996)
NA 60
Recognition:
In the last seven
days, have I
received
recognition or
praise for doing
good work?
Recognition. The job
provides acknowledgment
and recognition from
others.
Respondents rate
agreement on a 5-point
Likert-type scale.
Multimethod
Job Design
Questionnaire
Campion
(1988)
NA 79
217
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
My supervisor praises
good work.
My supervisor rewards
me for good performance.
Respondents rate
agreement on a 7-point
Likert-type scale.
Supportive and
Non-
Controlling
Supervision
Oldham &
Cummings
(1996)
Supportive
supervision
correlated
negatively
with
intentions to
quit
(Oldham, &
Cummings,
1996).
106-
107
Even if I did the best job
possible, the organization
would fail to notice
Respondents rate
agreement on a 7-point
Likert-type scale.
Perceived
Organizational
Support
Eisenberger,
Huntington,
Hutchinson,
& Sowa
(1986)
Perceived
organization
support
correlated
negatively
with
turnover
intentions
(Cropanzano,
Howes,
Grandey, &
Toth, 1997;
Eisenberger,
Fasolo, &
Davis-
LaMastro,
1993).
118
Offers praise for good
performance.
1 of 54 Q-sort items
Organizational
Culture Profile
O’Reilly,
Chatman, &
Caldwell
(1991)
O’Reilly et
al. (1991)
found
person-
organization
fit negatively
correlated
with
intention to
leave and
turnover.
223
218
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
I feel a strong sense of
belonging to this
organization.
I feel like “part of the
family” at this
organization.
The people I work for do
not care about what
happens to me.
Respondents rate
agreement on a 4-point
Likert-type scale.
Organizational
Commitment
Scale
Balfour &
Wechsler
(1996)
Affiliation
was
negatively
related to age
(Kacmar,
Carlson, &
Brymer,
1999).
60
Care:
Does my
supervisor, or
someone at work,
seem to care about
me as a person?
The organization really
cares about my well-
being.
The organization is
willing to help me when I
need a special favor.
The organization shows
very little concern for me.
Respondents rate
agreement on a 7-point
Likert-type scale.
Perceived
Organizational
Support
Eisenberger
et al. (1986)
Perceived
organization
support
correlated
negatively
with
turnover
intentions
(Cropanzano
et al, 1997;
Eisenberger
et al., 1990;
Lee &
Ashforth,
1993).
118
The amount of support
and guidance I receive
from my supervisor.
Job Diagnostic
Survey
Hackman &
Oldham
(1974)
Development:
Is there someone at
work who
encourages my
development?
My supervisor encourages
me to develop new skills.
Respondents rate
agreement on a 7-point
Likert-type scale.
Supportive and
Non-
controlling
Supervision
Oldham &
Cummings
(1996)
Supportive
supervision
correlated
negatively
with
intentions to
quit
(Oldham, &
Cummings,
1996).
106
219
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
My supervisor takes the
time to learn about my
career goals and
aspirations.
My supervisor cares about
whether or not I achieve
my goals.
My supervisor keeps me
informed about different
career opportunities for
me in the organization.
My supervisor supports
my attempts to acquire
additional training or
education to further my
career.
My supervisor assigns me
special projects that
increase my visibility in
the organization.
Respondents rate
agreement on a 5-point
Likert-type scale.
Supervisory
Support
Greenhaus,
Parasuraman,
& Wormley
(1990)
NA 108
The attention paid to
suggestions you make.
Respondents rate
satisfaction on a 7-point
Likert-type scale.
Global Job
Satisfaction
Cook et al.
(1981)
NA 27
Opinions Count:
At work, do my
opinions seem to
count?
The organization cares
about my opinions.
Respondents rated
agreement on a 7-point
Likert-type scale.
Perceived
Organizational
Support
Eisenberger
et al. (1986)
Perceived
organization
support
correlated
negatively
with
turnover
intentions
(Cropanzano
et al, 1997;
Eisenberger
et al., 1990;
Lee &
Ashforth,
1993).
118
220
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
Feeling unable to
influence your immediate
supervisor’s decisions and
actions that affect you.
Respondents rated
frequency on a 5-point
Likert-type scale.
Job-Related
Tension Index
Kahn et al.
(1964)
NA 125
I sometimes feel my job is
meaningless.
The goals of the
organization are not clear
to me.
Respondents rate
satisfaction on a 6-point
Likert-type scale.
Job
Satisfaction
Survey
Spector
(1997)
NA 15
In general, how
significant or important is
your job? That is, are the
results of your work likely
to significantly affect the
lives or well-being of
other people?
Respondents circle a
number on a continuum.
The job itself is not very
significant or important in
the broader scheme of
things.
Respondents rate the
accuracy of the statement
on a 7-point Likert-type
scale.
Job Diagnostic
Survey, with
revisions
Hackman &
Oldham
(1974)
Idaszak &
Drasgow
(1987)
NA 73
Mission:
Does the
mission/purpose of
my company make
me feel my job is
important?
Task significance. The job
is significant and
important compared with
other jobs in the
organization.
Respondents rate
agreement on a 5-point
Likert-type scale.
Multimethod
Job Design
Questionnaire
Campion
(1988)
NA 79
221
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
I do not understand the
part my job plays in
meeting overall
organizational objectives.
Respondents rate amount
of stress of a 7-point
Likert-type scale.
Stress
Diagnostic
Survey
Ivancevich et
al. (1980)
Job tension
correlated
positively
with
intention to
quit (Deluga,
1991; Rush
et al, 1985).
130
My job is meaningless.
Respondents rate items in
terms of frequency and
degree on a 5-point
Likert-type scale.
Work-Specific
Control
Problems
Remondet &
Hansson
(1991)
NA 141
I find I have to work
harder at my job than I
should because of the
incompetence of people I
work with.
Respondents rate
satisfaction on a 6-point
Likert-type scale.
Job
Satisfaction
Survey
Spector
(1997)
NA 15
Quality Work:
Are my co-workers
committed to doing
quality work?
People on your present
job:
Stimulating
Boring
Slow
Ambitious
Stupid
Responsible
Intelligent
Smart
Lazy
Active
Loyal
Work well together
Respondents rate as Y or
N.
Job
Descriptive
Index
Roznowski
(1989)
The
composite
measure was
negatively
correlated
with
turnover
intentions in
Cropanzano,
James, and
Konovsky
(1993).
25
222
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
How much opportunity is
there to meet individuals
who you would like to
develop friendship with?
To what extent do you
have the opportunity to
talk informally with other
employees while at work?
Friendship from my co-
workers.
The opportunity in my job
to get to know other
people.
The opportunity to
develop close friendships
in my job.
Respondents rate amount
using a 5-point Likert-
type scale.
Job
Characteristics
Survey
Sims,
Szilagyi, &
Kelller
(1976)
NA 76-
78
Best Friend:
Do I have a best
friend at work?
Developing friends at
work.
1 of 54 Q-sort items.
Organizational
Culture Profile
O’Reilly et
al. (1991)
O’Reilly et
al. (1991)
found
person-
organization
fit negatively
correlated
with
intention to
leave and
turnover.
223
Progress/Appraisal:
In the last six
months, has
someone at work
talked to me about
my progress?
Supervision on present
job:
Tells me where I stand.
Respondent rates as Y or
N.
Job
Descriptive
Index
Roznowski
(1989)
The
composite
measure was
negatively
correlated
with
turnover
intentions in
Cropanzano
et al. (1993).
25
223
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
To what extent do
managers or co-workers
let you know how well
you are doing on your
job?
Respondents circle a
number on a continuum.
Supervisors often let me
know how well they think
I am performing the job.
The supervisors and co-
workers on this job almost
never give me any
“feedback about how well
I am doing in my work.
Respondents rate accuracy
using a 7-point Likert-
type scale.
Job Diagnostic
Survey, With
Revisions
Hackman &
Oldham
(1974)
Idaszak &
Drasgow
(1987)
NA 74
To what extent do you
find out how well you are
doing on the job as you
are working?
To what extent do you
receive information from
your superior on your job
performance?
The feedback on how well
I’m doing.
The opportunity to find
out how well I am doing
on my job.
The feeling that I know
whether I am performing
my job well or poorly.
Respondents rate amount
on a 5-point Likert-type
scale.
Job
Characteristics
Survey
Sims et al.
(1976)
NA 76-
78
224
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
Extrinsic job feedback.
Other people in the
organization, such as
managers and co-workers,
provide information as to
the effectiveness (e.g.,
quality and quantity) of
your job performance.
Respondents rate
agreement on a 5-point
Likert-type scale.
Multimethod
Job Design
Questionnaire
Campion
(1988)
NA 79
My supervisor gives me
helpful feedback about
my performance.
My supervisor gives me
helpful advice about
improving my
performance when I need
it.
Respondents rate
agreement on a 5-point
Likert-type scale.
Supervisory
Support
Greenhaus et
al. (1990)
NA 108
The amount of personal
growth and development I
get in doing my job.
Job Diagnostic
Survey
Hackman &
Oldham
(1974)
Can you learn new things
in your work?
End-point anchors are 1 =
very little, 5 = very much.
Control and
Complexity
Frese et al.
(1996)
NA 98
Learn and Grow:
This last year, have
I had opportunities
at work to learn
and grow?
My supervisor provides
assignments that give me
the opportunity to develop
and strengthen new skills.
Respondents rate
agreement on a 5-point
Likert-type scale.
Supervisory
Support
Greenhaus et
al. (1990)
NA 108
225
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
In the positions that I have
held at [company name], I
have often been given
additional challenging
assignments.
IN the positions that I
have held at [company
name], I have often been
assigned projects that
have enabled me to
develop and strengthen
new skills.
Besides formal training
and development
opportunities, to what
extent have your
managers helped to
develop your skills by
providing you with
challenging job
assignments?
Regardless of [company’s
names}’s policy on
training and development,
to what extent have your
managers made a
substantial investment in
you by providing formal
training and development
opportunities?
For first 2 items,
respondents rate
agreement on a 7-point
Likert-type scale.
For items 3 and 4,
respondents rate extent on
a 7-point Likert-type
scale.
Developmental
Experiences
Wayne,
Shore, &
Liden (1997)
NA 109
I have few opportunities
to grow and learn new
knowledge and skills in
my job.
Respondents rate amount
of stress of a 7-point
Likert-type scale.
Stress
Diagnostic
Survey
Ivancevich et
al. (1980)
Job tension
correlated
positively
with
intention to
quit (Deluga,
1991; Rush
et al., 1985).
130
226
Predictor Variable:
GWA Item
Parallel Item Measure Source Relationship
with
Turnover
Intent/Age
Page
Opportunities for
professional growth.
1 of 54 Q-sort items.
Organizational
Culture Profile
O’Reilly et
al. (1991)
O’Reilly et
al. (1991)
found
person-
organization
fit negatively
correlated
with
intention to
leave and
turnover.
223
227
Table 3. Employee Engagement by Career Stage.
Variable Young Workers
(Age 35 and under)
Early and Late
Mid-Career Workers
(Age 36-54)
Mature Workers
(Age 55 and older)
Understand
Expectations
Are learning
expectations.
Know expectations.
May mentor others
teaching them
expectations.
Materials Technologically
savvy. Else, learning
materials/equipment
used on the job.
Has a fair
knowledge of
materials and
equipment needed to
do job.
New technology
may present
challenges.
Opportunity Searching for
opportunities to
excel. This may
necessitate lateral
move or job change.
May be ready for
leadership positions
held by mature
workers.
Likely have found a
job where they have
had the opportunity
to do what they do
best.
Recognition May be recognized
for growth, if
demonstrated.
May not be
recognized.
Likely receives
recognition for
years of service.
Care May receive care
based on marriage,
pregnancy,
becoming
acclimated to the
workforce
(mentored).
May receive less
care but in greatest
need.
May receive care
based on declining
health (or spouse’s
declining health) or
years/months left to
retirement.
Development May be encouraged
to develop
appropriate work
skills.
May be
overwhelmed by
encouragement to
continue
development and
take on additional
responsibilities.
Since they are
closer to retirement
age, may not be
encouraged to
continue
development of job-
related skills.
Opinions Count Opinions are likely
valued least.
Opinions are likely
valued.
If in leadership
positions, opinions
may have more
weight than if not.
228
Table 3. Employee Engagement by Career Stage, continued.
Variable Young Workers
(Age 35 and under)
Early and Late
Mid-Career Workers
(Age 36-54)
Mature Workers
(Age 55 and older)
Mission If in entry-level
position, may feel
job is not important
in mission of
company.
May feel job is
important to
company’s mission.
If in leadership
position, may feel
job is critical in
mission of
company.
Quality Work See co-workers as
doing quality work
and aspire to do the
same.
Feel sandwiched
between younger
workers who are
improving and
mature workers who
are at the top of their
careers.
See co-workers as
doing less than
quality work.
Best Friend May not yet have a
best friend at work.
May have a best
friend at work.
Best friends may
have retired.
Progress/Appraisal Is mentored and
evaluated
frequently.
Is mentored less. Is
evaluated less
frequently.
Evaluated least.
Mentors others.
Learn and Grow Have plenty of
opportunities. May
be overwhelmed by
all of opportunities
but have the energy
to put into them.
May be exhausted
from trying to meet
the demands of all
opportunities that are
available.
May not be
challenged by
opportunities that
are available or see
them as a waste of
time.
229
Table 4. Descriptive Statistics for Faculty for Employee Engagement Scale,
Compensation Fairness Factor, Job Satisfaction, and Turnover Intent.
Scale Variable Rank
Mean* Median Mode SD Variance
Expectations 1 1.64 1.00 1 0.860 0.740
Materials 7 2.22 2.00 2 1.067 1.138
Opportunity 6 2.18 2.00 2 1.068 1.140
Recognition 12 2.85 3.00 2 1.336 1.786
Care 4 2.01 2.00 1 1.116 1.245
Development 8 2.25 2.00 2 1.147 1.316
Opinions Count 10 2.27 2.00 2 1.158 1.342
Mission 9 2.26 2.00 2 1.092 1.192
Quality Work 5 2.05 2.00 2 0.977 0.954
Best Friend 2 1.96 2.00 2 0.961 0.924
Progress/Appraisal
11 2.38 2.00 2 1.199 1.438
Employee Engagement
Learn and Grow 3 1.99 2.00 2 0.959 0.920
Internal Comp. 2 2.96 3.00 2 1.250 1.563
External Comp. 3 3.60 4.00 5 1.229 1.510
Compensation
Fairness
Benefits 1 2.23 2.00 2 0.939 0.881
Turnover Intent NA 3.04 3.00 2 1.171 1.372
Job Satisfaction NA 2.27 2.00 2 0.982 0.965
230
Table 5. Standardized Regression Weights for A Priori Two-Factor Measurement
Weights Model.
Scale Variable Young
Workers
Early Mid-
Career
Workers
Late Mid-
Career
Workers
Mature
Workers
Expectations .618 .543 .574 .580
Materials .571 .584 .582 .590
Opportunity .655 .638 .651 .615
Recognition .699 .696 .694 .703
Care .812 .795 .795 .781
Development .829 .820 .797 .801
Opinions Count .788 .807 .823 .795
Mission .629 .645 .615 .620
Quality Work .493 .540 .527 .527
Best Friend .358 .333 .353 .341
Progress/Appraisal
.654 .624 .612 .586
Employee Engagement
Learn & Grow .721 .715 .673 .677
Internal
Compensation
.871 .871 .873 .918
External
Compensation
.787 .771 .781 .799
Compensation
Fairness
Benefits .450 .432 .456 .451
*All coefficients are p < .001.
231
Table 6. Standardized Regression Weights for Revised Two-Factor Measurement
Weights Model.
Scale Variable Young
Workers
Early Mid-
Career
Workers
Late Mid-
Career
Workers
Mature
Workers
Expectations .617 .541 .572 .578
Materials .572 .585 .583 .592
Opportunity .655 .638 .650 .614
Recognition .702 .698 .697 .706
Care .810 .795 .796 .781
Development .830 .820 .797 .801
Opinions Count .790 .809 .826 .796
Mission .629 .644 .614 .618
Quality Work .490 .536 .524 .523
Progress/Appraisal
.653 .623 .610 .586
Employee Engagement
Learn & Grow .720 .714 .671 .674
Internal
Compensation
.871 .872 .874 .918
External
Compensation
.786 .770 .780 .799
Compensation
Fairness
Benefits .449 .431 .455 .450
* All coefficients are p < .001.
232
Table 7. Summary Table of Measurement Models.
Model
CMIN DF CFI RMSEA
PCLOSE
A priori--12 and 3 items
Unconstrained
Measurement Weights
∆
1110.368
1163.754
53.386
356
401
45
.902
.901
.001
.042
.040
.002
1.000
1.000
n/a
Revised--11 and 3 items
Unconstrained
Measurement Weights
∆
1019.798
1073.579
53.781
304
346
42
.905
.904
.001
.044
. 042
.002
.999
1.000
.001
233
Table 8. Summary Table of Structural Models.
Model
CMIN DF CFI RMSEA
PCLOSE
All Paths Model Assessing Direct
Relationships
1182.286
396
.900
.41
1.000
Model Assessing Mediating
Effects of Job Satisfaction
No Job Satisfaction Effects
∆
1456.804
1457.659
0.855
464
465
1
.891
.891
<.001
.042
.042
<.001
1.000
1.000
n/a
Constrained Model with No Job
Satisfaction Effects
1457.659
465
891
.042
1.000
234
Table 9. Summary Table of Hypotheses.
Hypothesis
Finding
1a: Turnover Intent Inversely Related to Employee Engagement
Supported
1b: Turnover Intent Inversely Related to Compensation Fairness
Supported
2a: Job Satisfaction Mediates Employee Engagement—Turnover Intent
Relationship
Not
Supported
2b: Job Satisfaction mediates Compensation Fairness—Turnover Intent
Relationship
Not
Supported
3a:Age Moderates Employee Engagement—Turnover Intent Relationship
Not
Supported
3b:Age Moderates Employee Engagement—Turnover Intent Relationship
Not
Supported
235
Table 10. Post Hoc ANOVA for Age Differences in Study Variables
Variable Groups Sum of
Squares
Df Mean
Square
F Sig.
Employee
Engagement
Between Groups
Within Groups
Total
162.711
68388.456
68551.167
3
1209
1212
54.237
56.566
.959 .411
Compensation
Fairness
Between Groups
Within Groups
Total
12.933
7083.451
7096.384
3
1209
1212
4.311
5.859
.736
.531
Job Satisfaction Between Groups
Within Groups
Total
2.340
1154.637
1156.977
3
1209
1212
.780
.955
.817 .485
Turnover Intent Between Groups
Within Groups
Total
4.774
2398.371
2403.145
3
1209
1212
1.591
1.984
.802 .493
236
VITA
Mary Lynn Berry is a Family and Consumer Science teacher in Knoxville. She received
her B.S. in Psychology at Mississippi State University in Starkville, Mississippi and her
M.S. in Family Studies from The University of Tennessee, Knoxville. While completing
requirements for her PhD in Business Administration with concentration in Human
Resource Development, Mary Lynn served as Graduate Teaching Assistant for HRD 350:
Human Resource Development Training Systems: Strategies and Techniques. She is
currently employed with Knox County Schools as a Family and Consumer Sciences
Educator for high school career and technical education students.
Publications
Slayton, M. L. (1996) Marital Satisfaction, Family Strengths, and Gender: Implications
for Marriage Enrichment. Thesis. The University of Tennessee, Knoxville.
Conference Presentations and Proceedings
Berry, M.L., & Morris, M.L. (2005). Organizational factors influencing sexual
harassment prevention programs. Presented at the 14
th
Academy for Human
Resource Development Conference, Estes Park, Colorado.
Berry, M.L., & Morris, M.L. (2004). Research and theory: A theoretical framework for
addressing training needs associated with sexual harassment prevention programs.
Presented at the 13
th
Academy for Human Resource Development Conference,
Austin, Texas.
Whaley, H.M., Berry, M.L., & Morris, M.L. (2003). Exploring potential gender
237
differences in sexual harassment beliefs of pre-workforce participants: A
descriptive study. Presented at the 12
th
Academy for Human Resource
Development Conference, Minneapolis, Minnesota.
Whaley, H.M., Berry, M.L., & Morris, M.L. (2003). Exploring potential gender
differences in sexual harassment beliefs of pre-workforce participants: A
descriptive study. Presented at the 65
th
National Council on Family Relations,
Vancouver, B.C.
Morris, M. L., Roberts, L., Slayton, M. L., & Carter, S. (1996, February). The
B.E.S.T. (Building and Enriching Stronger Tennessee) Families Program.
Proposal submitted for the 1996 National Council on Family Relations Annual
Conference, Kansas City, Missouri.
