the influence of transformational middle leaders on work-life balance
TRANSCRIPT
University of Kentucky University of Kentucky
UKnowledge UKnowledge
Theses and Dissertations--Education Science College of Education
2018
THE INFLUENCE OF TRANSFORMATIONAL MIDDLE LEADERS ON THE INFLUENCE OF TRANSFORMATIONAL MIDDLE LEADERS ON
WORK-LIFE BALANCE WORK-LIFE BALANCE
Timothy D. Tanner University of Kentucky, [email protected] Digital Object Identifier: https://doi.org/10.13023/etd.2018.258
Right click to open a feedback form in a new tab to let us know how this document benefits you. Right click to open a feedback form in a new tab to let us know how this document benefits you.
Recommended Citation Recommended Citation Tanner, Timothy D., "THE INFLUENCE OF TRANSFORMATIONAL MIDDLE LEADERS ON WORK-LIFE BALANCE" (2018). Theses and Dissertations--Education Science. 37. https://uknowledge.uky.edu/edsc_etds/37
This Doctoral Dissertation is brought to you for free and open access by the College of Education at UKnowledge. It has been accepted for inclusion in Theses and Dissertations--Education Science by an authorized administrator of UKnowledge. For more information, please contact [email protected].
STUDENT AGREEMENT: STUDENT AGREEMENT:
I represent that my thesis or dissertation and abstract are my original work. Proper attribution
has been given to all outside sources. I understand that I am solely responsible for obtaining
any needed copyright permissions. I have obtained needed written permission statement(s)
from the owner(s) of each third-party copyrighted matter to be included in my work, allowing
electronic distribution (if such use is not permitted by the fair use doctrine) which will be
submitted to UKnowledge as Additional File.
I hereby grant to The University of Kentucky and its agents the irrevocable, non-exclusive, and
royalty-free license to archive and make accessible my work in whole or in part in all forms of
media, now or hereafter known. I agree that the document mentioned above may be made
available immediately for worldwide access unless an embargo applies.
I retain all other ownership rights to the copyright of my work. I also retain the right to use in
future works (such as articles or books) all or part of my work. I understand that I am free to
register the copyright to my work.
REVIEW, APPROVAL AND ACCEPTANCE REVIEW, APPROVAL AND ACCEPTANCE
The document mentioned above has been reviewed and accepted by the student’s advisor, on
behalf of the advisory committee, and by the Director of Graduate Studies (DGS), on behalf of
the program; we verify that this is the final, approved version of the student’s thesis including all
changes required by the advisory committee. The undersigned agree to abide by the statements
above.
Timothy D. Tanner, Student
Dr. Beth Rous, Major Professor
Dr. Margaret Bausch, Director of Graduate Studies
THE INFLUENCE OF TRANSFORMATIONAL MIDDLE LEADERS ON WORK-LIFE BALANCE
_________________________________
DISSERTATION _________________________________
A dissertation submitted in partial fulfillment of the requirements of the degree of Doctor of Philosophy
in the College of Education at the University of Kentucky
By
Timothy David Tanner
Jewett, OH
Director: Dr. Beth Rous, Professor of Educational Leadership Studies
Lexington, KY
2018
Copyright © Timothy David Tanner 2018
ABSTRACT OF DISSERTATION
THE INFLUENCE OF TRANSFORMATIONAL MIDDLE LEADERS
ON WORK-LIFE BALANCE
Work-life balance is a key indicator of employee satisfaction, retention, and social health as well as organizational creativity and productivity. These dual benefits for employee and employer have generated interest in promoting work-life balance. Supervisors who operate from a transformational leadership framework have been linked to greater work-life balance among employees (Lamm, 2011; (Kutilek, Conklin, & Gunderson, 2002). The role of a supportive organizational culture is also central (Lewis, 2001).
In this study, Cooperative Extension Service agents (N = 1390) participated in a
nationwide survey exploring the relationship between rated levels of transformational leadership among district directors, work-life balance, and work-life balance organizational culture. The results from confirmatory factor analyses indicate these three separate dimensions. The findings from the structural equation model demonstrate that all paths, except transformational leadership to personal life interference with work, are statistically significant. Work-life balance organizational culture is the largest contributor to the total effect of these associations.
This study confirms that the supervisor and organizational culture join together to
forge an important alliance of support for work-life balance among subordinates. Findings reveal the need for additional study of specific ways leaders foster positive work-life balance organizational culture.
KEYWORDS: Work-life Balance, Transformational Leadership, Organizational Culture, Structural Equation Model, Cooperative Extension Service
Tim Tanner Student’s Signature
07/10/2018 Date
THE INFLUENCE OF TRANSFORMATIONAL MIDDLE LEADERS ON WORK-LIFE BALANCE
By
Timothy David Tanner
Dr. Beth Rous Director of Dissertation
Dr. Margaret Bausch Director of Graduate Studies
07/12/2018 Date
iii
ACKNOWLEDGMENTS
Where to start?
On the academic side, thank you to Betty Tanner, Judy Dietrich, Thom
Reamsnyder, and Paulette Potts for ensuring I had the spelling, grammar, and writing
skills necessary for a 21st century leadership role. You were correct, good readers
become good writers—even if I still prefer fiction! Thanks to Professors Marion
Bontrager, Perry Bush, and Tricia Browne-Ferrigno for teaching me how to engage in
critical, continuous learning. Special mention to Michael Hecht, Michelle Miller-Day,
Janice Krieger and the rest of the Drug Resistance Strategies Project team who sparked
my interest in social research. You convinced me that plain-spoken academics can be a
potent, translational force for good.
On the professional side, several supervisors encouraged this pursuit and/or
modeled transformational leadership attributes: Jack Kerrigan, Jackie Kirby Wilkins,
Craig Smith, Jeff Rill, and Char Hochstetler. Equally important are the numerous
supervisors, athletic coaches, committee chairs, and other authority figures who modeled
poor leadership—valued lessons come from all sources! Numerous colleagues also asked
questions and provided encouragement throughout the process, chief among them
Heather Keller, Joseph Maiorano, and Katie Feldhues. Thank you for keeping the normal
normal.
From several colleagues who experienced difficult PhD journeys, I learned the
importance of a committed, well-rounded dissertation committee. I was never
disappointed by mine! Thank you to Lars Bjork for your good humor and guidance in
leadership theory and culture, Michael Toland for seeing the study’s comprehensive
value and patiently guiding me through the rigorous SEM analysis, and UK’s Community
iv
and Leadership Development faculty (Ken Jones and Kris Hains) for helping me
articulate the Extension middle leader context. My chair and champion, Beth Rous,
thank you for being exactly what I needed at each critical juncture. Beth, accomplishing
this process on your aggressive timeline is one of my life’s high honors.
Shouldn’t the work-life balance researcher talk about his family? Certainly! I
treasured Jack’s ornery smiles and breaks to pitch baseballs, Sophie’s hugs and outdoorsy
Sacagawean spirit, and Kendra’s listening ear and grounding. We were able to take our
scheduled National Park vacations (35 states and counting!), occasionally keep up with
the garden, and enjoy our family game nights together throughout. We all came of age a
lot during this venture—I’m excited for our future.
Finally, an encouragement to those who value both work and non-work life: with
good time management choices and a supportive team, the Ph.D. process really can be
accomplished with limited sacrifice. Go for it!
v
TABLE OF CONTENTS
Acknowledgments......................................................................................................iii List of Tables .............................................................................................................vii List of Figures ............................................................................................................viii Chapter 1: Introduction
Introduction ....................................................................................................1 Problem Statement .........................................................................................2 Rationale ........................................................................................................3 Purpose of the Study ......................................................................................4 Research Hypotheses .....................................................................................4 Design ............................................................................................................4 Methodology and Limitations ........................................................................5 Definitions......................................................................................................6 Summary ........................................................................................................6
Chapter 2: Literature Review
Operational Definition of Work-life Balance ................................................8 Structural Dimension of Work-life Balance ..................................................11 Cultural Dimension of Work-life Balance .....................................................15 Work-life Balance in Cooperative Extension ................................................18 Leadership Dimension of Work-life Balance ................................................23 Summary ........................................................................................................31
Chapter 3: Method
Conceptual Model ..........................................................................................33 Research Design.............................................................................................34 Context of the Study ......................................................................................35
Sample................................................................................................36 Ethical Considerations .......................................................................41
Measures ........................................................................................................42 Transformational Leadership Inventory ............................................42 Work/Life Balance Self-Assessment Scale .......................................42 Work Life Balance Culture Scale ......................................................43
Procedure .......................................................................................................45 Data Collection ..................................................................................45 Data Analysis Plan .............................................................................46
Delimitations and Limitations ........................................................................50 Summary ........................................................................................................51
vi
Chapter IV: Results Descriptive Statistics ......................................................................................53 Confirmatory Factor Analyses .......................................................................57 SEM Results...................................................................................................61 Summary ........................................................................................................63
Chapter V: Discussion
Discussion of Findings ...................................................................................66 Contribution of Study to the Field .................................................................69 Limitations of the Study.................................................................................71 Implications....................................................................................................72
Recommendations for Policy and Practice ........................................72 Recommendations for Future Research .............................................75
Conclusion .....................................................................................................78 Appendices
Appendix A: Institutional Review Board Approval ......................................80 Appendix B: Electronic Survey .....................................................................81
References ..................................................................................................................90 Vita .............................................................................................................................111
vii
LIST OF TABLES Table 3.1, Extension Organizational Structure Types ...............................................37 Table 3.2, State-level Summary Statistics for Final Sample .....................................39 Table 3.3, Demographic Characteristics of Participants ............................................40 Table 4.1, Descriptive Statistics for Transformational Leadership Inventory ...........53 Table 4.2, Descriptive Statistics for Work Life Balance Self Assessment Scale ......54 Table 4.3, Descriptive Statistics for Work Life Balance Culture Scale.....................55 Table 4.4, Global Measures of Fit for Transformational Leadership Inventory ........56 Table 4.5, Global Measures of Fit for Work Life Balance Self Assessment Scale ...57 Table 4.6, Global Measures of Fit for Work Life Balance Culture Scale .................59
viii
LIST OF FIGURES
Figure 3.1, Conceptual Model for the Study..............................................................33 Figure 3.2, Participating States in Final Research Sample ........................................36 Figure 4.1, Results for the Mediation Model .............................................................60
1
Chapter I
Introduction
The Cooperative Extension Service (CES) extends university learning to local
communities throughout the United States in fulfillment of its federal land-grant mission.
It is the largest and most dispersed outreach education purveyor in the country,
accounting for over 90% of all outreach education programs annually. In the outreach
education field, employees are expected to work irregular schedules among diverse
clientele while achieving documentable impact. CES employees face the additional
requirements of government reporting and the sizable performance expectations
associated with large universities. With such high stakes, it is of little surprise that new
CES agents are only somewhat committed to the organization and moderately satisfied
with their work (Martin & Kaufman, 2013). Given the broader trends associated with
turnover intention among Millennials (Thompson & Gregory, 2012), much work remains
to entice CES employees toward retention.
The essential, positive relationship between healthy work-life balance (WLB)
cultures and employee retention is newly established in organizational development
literature. As a result, researchers studying similarly educated and irregularly-scheduled
professions (e.g., nurses, athletic trainers, social workers, pharmacists) are investigating
what promotes this balance. The field of outreach education has not yet studied WLB
leadership culture, making this dissertation a timely launching point for broadening the
literature. Because positional longevity of CES outreach employees is critical to the
organization’s mission, studying this subset is of significant importance.
2
Problem Statement
Research surrounding the work and non-work interface adapted to social changes
and worker paradigm shifts. Work and family balance—the earliest construct—focused
on the impact of women entering the American workforce in the second half of the
twentieth century. This broad social upheaval challenged families in ways not previously
experienced. The next iteration considered the impacts on men within the work-family
dynamic. As conventional marital norms altered, the construct changed to work-life
balance (WLB). The WLB construct incorporated more than the responsibilities
associated with married couples, including items such as eldercare, vacations, and leisure
time. An argument for work-life integration persisted throughout.
As the study of WLB developed, research focused on structural elements
necessary to promote balance. Findings related to these studies encouraged employers to
adopt human resource policy improvements. Discovery that policy implementation was
insufficient led to research considering the impact of organizational culture and
supervisor support. This developing literature creates the foundation for this study which
considers the influence of transformational middle leaders on WLB factors and culture.
Building on the work of Schein (1985), Nitzsche et al. (2014, p. 139) defined
WLB culture as “an organizational culture that promotes work-life balance through a
prevailing attitude that this balance is something sensible and worth supporting.” The
research team found that organizational social capital and supportive supervisors were
critical elements in promoting this positive culture. The question that remains is this:
what attributes of these supportive supervisors most effectively foster a positive WLB
culture?
3
In their role as organizational leaders, supervisors influence outcomes among
individuals, groups, and systems (Rost, 1991). Though sometimes driven from leaders
near the bottom, most organizational change derives from leaders in higher positions of
authority. In CES the upper-most positional leaders are so geographically/physically
distant from their subordinates that the influencing relationship is diminished (Katz &
Kahn, 1978). Hence, the onus for culture change in CES falls to the mid-level leaders
who possess this relationship with dispersed county agents (Bass, 1998).
Rationale
Positive WLB has been associated with numerous benefits to organizations and
employees. For organizations, positive WLB correlates to stronger job satisfaction and
retention while mildly strengthening productivity. Employees experience reduced job-
life conflicts and improved health outcomes. Good WLB has even been shown to
possess a positive predictive influence on ethical behavior among organizational leaders
and subordinates (Jedlicka, 2007).
Despite these broad ranging positive outcomes, widespread use of WLB policies
remains limited. A major reason why WLB policies have not become more
mainstreamed is the failure to consider the effects of organizational culture. As Feeney,
Bernal, and Bowman (2014, p. 761) summarized the literature on this point, “no matter
how many formal policies and programs are offered, the culture of the organization is
critical for predicting policy utilization and effectiveness.” Though much research has
described this discrepant phenomenon, little research has been conducted on the WLB
cultural support provided by supervisors (Kossek et al., 2010). This research study seeks
to reduce the size of this knowledge gap.
4
Purpose of the Study
The purpose of this study is to add to the knowledge base on WLB organizational
culture, specifically as it relates to the influence of transformational middle leaders in
CES. Positive WLB culture is a key indicator of employee satisfaction, retention, and
social health as well as organizational creativity and productivity. Its absence is
detrimental to both organizations and employees. This survey study will assess WLB
culture and factors in CES and the role transformational middle leaders play in forging a
positive WLB culture. The following research hypotheses will be used to guide this
study.
Research Hypotheses
1. The rated levels of transformational leadership among Extension middle leaders will
positively influence WLB culture among subordinates.
2. The rated levels of transformational leadership among Extension middle leaders will
positively influence WLB factors among subordinates.
3. The relationship between transformational leadership among Extension middle
leaders and WLB factors is strengthened by the intervening influence of WLB
culture.
Design
Studies under the broad umbrella of organizational culture have traditionally
relied on qualitative inquiry (Jung et al., 2009). This is particularly important when an
examination of subliminal values, beliefs, and assumptions is warranted (Yauch &
Steudel, 2003). As this study describes the more overt and uniform WLB organizational
culture in CES, a quantitative approach is reasonable. Given that participant time
5
constraints are substantial and securing a large national sample is valued, this is the more
suitable approach (Tucker, McCoy, & Evans, 1990).
In this exploratory survey study, a single-level survey was disseminated to
Extension subordinates (i.e., agents) in 13 geographically distributed CES states. The
focus of the study was an examination of the relationship between three variables—
transformational leadership, organizational culture, and WLB—as perceived by
Extension agents. The foremost purpose of this study is an assessment of district
directors’ influencing capacity. Thus, agent demographic factors (e.g., education level,
ethnicity) were not considered.
Methodology and Limitations
In the interest of studying national-level WLB trends, this study sampled 13
geographically dispersed CES states. Using a survey approach, 1390 Extension
subordinates completed an online survey in mid-winter 2018. The survey response rate
of 53% was above average for assessment studies in CES. The composition of the
sample followed contemporary CES norms, resulting in a skew towards the female
gender and lesser years of service among employees.
Following the survey, confirmatory factor analyses (CFA) was independently
conducted on each survey instrument. Once the best fitting model was determined for
each instrument, a collective CFA was conducted in preparation for the intervention
analysis via structural equation modeling (SEM). Finally, SEM was conducted using a
design-based approach.
Beyond demographic concerns which may limit generalizability in other outreach
education organizations, two study weaknesses were evident. First, only CES systems
6
using a middle-leader structure were studied. Though this is still the majority
organizational structure in CES, smaller states and CES with non-majority structures
were not represented. In particular, this limits generalizability somewhat in the Northeast
region of the country. Second, the relationship between WLB and transformational
leadership style was studied exclusively. Any relationship to less favored CES leadership
frameworks (e.g., transactional) were not represented.
Definitions
Though the studied CES states use a common organizational structure overall, the
specific language of job titles varies. For clarity a single term was chosen for each role
and is defined below:
Agent- Extension uses a wide variety of titles in reference to directly subordinate county-
based educational staff members. For the purposes of this study the term Agent is used,
but synonymous titles include all of the following: County Specialist, County Extension
Director, Lead County Agent, and Extension Educator.
District Director- Extension uses a wide variety of titles in reference to geographical area
supervisors/leaders. For the purposes of this study the term District Director is used, but
synonymous titles include all of the following: Area Director, Area Chair, District
Coordinator, District Extension Administrator, Regional Director, Regional Extension
Coordinator, and Regional Lead Agent.
Summary and Overview
The purpose of this study will be to explore the influence of middle leaders on
work life balance factors and culture in cooperative extension. The influence of middle
leaders on work life balance as well as work life balance culture in cooperative extension
7
has received limited study. Therefore, the intent of this study is to focus on the role
transformational middle leaders play in creating a positive work life balance culture in
cooperative extension. In this context, the study will include the opportunity to
investigate how district directors impact work life balance among county agents.
In the forthcoming chapters, the study details and outcomes are presented. In
Chapter 2, a review of the relevant literature on work life balance, transformational
leadership theory, organizational culture, and the cooperative extension context are
presented. Chapter 3 includes a description of the survey research design and procedures.
In Chapter 4 the results of the study’s three research hypotheses are examined. Chapter 5
draws study conclusions and provides implications for cooperative extension and
researchers in the field.
8
Chapter II
Literature Review
The purpose of this chapter is to review the scholarly literature on work-life balance and
its relationship to organizational leadership and culture. The review first examines the
development of the work-life balance construct, including the operational definition for
this study. This is followed by a brief review of early work-life balance research findings
which emphasized employee support structures. Given these structural supports’ proven
insufficiency at promoting work-life balance, the review concludes by considering the
impact of supervisor support and organizational culture.
In this review of the literature, seminal authors (e.g., Schein, Bass, Kossek) are
discussed with support from more recent scholarly articles. The primary search
mechanisms for these articles included Academic Search Complete, ProQuest
Dissertation Abstracts, Journal of Extension search, and sources cited in related texts. In
combination these collective works describe the progression of work-life balance
literature.
Operational Definition of Work-life Balance
A challenge in the work-life balance (WLB) discourse is settling on a precise
definition. For the purposes of this study, WLB is inclusively defined as a perceived
state of balance between work and the rest of life (Guest, 2002). Work refers to hours
spent in paid employment and the rest of life refers to time spent away from work.
Though employees perceive this balance (a) uniquely and (b) at varying tolerance levels
for hours worked and conflicts experienced (Poelmans, Kalliath, & Brough, 2008),
Greenhaus et al. (2003) found the most satisfied workers mildly favored the non-work
9
side of the ledger. The literature finds a chronic imbalance toward the work domain and
calls for measures to address this socio-organizational concern.
Guest’s inclusive definition of WLB was not always apparent. Earlier
conceptions of WLB focused exclusively on the needs of employees with families,
beginning with women. The effects of work-life conflict remain greatest when imbalance
centers on family and home life, and much of the literature continues to study elements of
this divide (Ransome, 2007). Nevertheless, because family-centered constructs may be
patronizing and non-inclusive, the term work-life balance became common in the
literature (Jones, Burke, & Vestman, 2006; Lewis, 2001). It is important to understand
the journey toward Guest’s more inclusive definition of WLB and its value in this study.
The next several sections of this literature review provide this additional context.
Work-family Balance
Prior to the 1980s, the normative American family relied on a single income.
Males cared for the finances and females cared for the family and home. The cultural sea
change brought about by the feminist movement altered this family dynamic. As the
1980s commenced, dual-earner families slowly became the norm and traditional
assumptions about work and family life became less viable (Kanter, 1990).
The newfound role of women in the workplace created a time-crunch crisis at
home. With both partners working, who would care for the children and other home
responsibilities? Because the answer to that question was usually ‘women,’ mitigating
their stress, tiredness, and burnout became newfound socio-organizational concerns
(Tiedje et al., 1990) and the construct of work-family balance was born.
10
Governmental authorities and organizations initially responded to this family
imbalance problem with structural policies (e.g., flexible schedules, extended leave,
dependent care). As men became more willing partners in familial roles (O’Brien, 1992),
the literature shifted to focus on the effect of work-family policies on both genders. In an
early study in higher education, Grover and Crooker (1995) found that though women
were more supportive of work-family policies (e.g., medical leave) than men, both
genders were positively affected. The employing institutions also gained as these
policies improved employee commitment levels. Conversely, Lewis and Cooper (1995)
found that despite best efforts at reframing work-family policies as gender-neutral, most
employers and employees continued to view the policies as the domain of women.
Recent studies continued broadening the discussion of work-life issues toward a
less gendered perspective. In a 2006 survey of retail administrators, Moen, Kelly, and
Hill (2011) confirmed findings from an earlier study on employees in a Fortune 500
company (Major, Klein, & Ehrhart, 2002) that the implementation of work-life practices
(e.g., schedule control) reduced turnover intention and improved productivity without
regard to gender or child-rearing status. These findings mirrored a public sector study of
faculty at the University of Maine in which McCoy, Newell, and Gardner (2013) found
institutional support for WLB improved job satisfaction, wellness, and retention without
regard to gender or child-rearing status.
Work-life Integration
Persisting throughout the development of a balance construct was the
contravening notion that because work-life balance centers upon an employee’s
perception of role balance, only half the issue was being discussed. Theorists proposed
11
work-life integration (WLI) as a better descriptor because it placed the discussion
squarely in the workplace and placed more responsibility on the employer to create a
culture of integration (Kossek & Lambert, 2005). On the surface, the integration
perspective’s attention to organizational culture change makes it an ideal framework for
this study.
When Parasuraman and Greenhaus (1999) defined WLI as having a positive
spillover effect between work and non-work roles which mutually enriches the other role
in an employee’s life, they envisioned a more complete theoretical construct.
Unfortunately, the original intent of the theory faced challenges in practice. Schieman
and Glavin (2008) found that among professionals with schedule control options,
bringing work home and being contacted for work tasks while at home correlated with
higher work-home conflict. Further evidence suggested the WLI perspective can lead to
employee home-time being taken advantage of by employers (Van Echtelt, Glebbeek,
Lewis, & Lindenberg, 2009), especially in the high technology era.
Rather than framing the discussion as an ‘either/or,’ Kossek et al. (2010)
suggested the debate better resolves as a ‘both/and.‘ Though many employees need the
healthy boundary setting that WLB encourages, some employees—particularly those with
less settled or more technologically-centered lives—may benefit from the WLI
perspective. As CES is primarily comprised of a more settled employee base, WLB
remains the construct (and term) of choice for this study.
Structural Dimension of Work-life Balance
Growth in the understanding of WLB produced three dimensions in the literature.
The structural dimension addresses human resource concerns (e.g., retention,
12
productivity) whereas the more recent culture and leadership dimensions (e.g., supervisor
support, creative leadership) describe leader influence (Kossek, Lewis, & Hammer,
2010). The structural dimension is discussed in this section, with the cultural and
leadership elements discussed in subsequent sections.
With earnest effort in the 1990s, employers began targeting programs and policies
to promote WLB within their organizations. These structural efforts included family
friendly leave policies, flexible scheduling options, and dependent care provisions
(Kossek et al., 2010). Collectively these efforts sought to strengthen employee
engagement and satisfaction and reduce burnout and work-life conflict. The resultant
benefits of employee retention and increased productivity are discussed.
Employee Retention
The retention of qualified workers is of keen interest to employers (Pfeffer, 1994).
A stable workforce provides institutional memory and an adequate supply of labor.
Retention also prevents or reduces the significant costs associated with labor
replacement. In creative professions skewed toward rural locales, finding qualified
replacements may generate an additional burden for employers.
A series of studies have considered the link between WLB and employee
retention. A case study of high-performing female professionals by Abbott, De Cieri, and
Iverson (1998) was among the first to suggest WLB policies play a positive role in
employee retention. A case analysis by Klun (2008) discovered that a third of Accenture
employees had recently turned down better paying job offers elsewhere to continue
enjoying the positive WLB benefits at Accenture, especially the self-funded sabbatical
program called Future Leave. From a compiled 10-year employee response survey of
13
medium and large-sized companies, Richman et al. (2006) found employees who agreed
that work-life support and job flexibility needs were met by their employers were up to
20 percent more committed to retaining. This commitment had a direct effect on
turnover intention.
Two studies forge a connection between employee retention and leadership-
cultural factors discussed later in this review. In a longitudinal study of child welfare
professionals, Smith (2005) studied 11 factors associated with employee retention. Two
of the top three strongest associations were WLB and supervisor support. A similar study
focused on 29 factors associated with retention among Canadian nursing faculty
(Tourangeau et al., 2015). In this study, four of the top five strongest associations were
supervisor support or WLB-related. Further, these associations were most pronounced
among the two youngest and increasingly prolific generations in today’s workplace—a
common thread found in other WLB studies (Mathews et al., 2012; Coffey et al., 2009).
Productivity
The WLB construct is also important to employers from a productivity
perspective. Within the context of ever-constrained fiscal resources, employers must get
the most out of each individual they hire. High productivity reduces operational
overhead costs, thereby increasing profit margins. In creative professions, increased
productivity generally stems from collaboration-centric operation models and employees
experiencing positive wellness and WLB attributes.
Compared to the more proven connection between WLB and retention, WLB’s
positive influence on employee productivity is mild yet apparent. From a time-based
metric, it has been long established that working long hours leads to diminished
14
productivity among employees, particularly in the creative professions (Schor, 1991).
Similarly, a series of interviews conducted by Lewis (2001) suggested employees
working up to 7 fewer hours intensify their work to accomplish the same amount they did
prior to the reduction. Kossek et al. (2010) point to the recent global recession which did
not correspond with diminished national productivity measures despite employees
working fewer hours.
Beyond time-related metrics, several researchers have studied the relationship
between other WLB factors and employee productivity. In one of the earliest studies on
the subject, a modest positive relationship to employee performance was found among
employees experiencing greater WLB (Allen et al., 2000). This modest connection was
confirmed by Feeney, Bernal, and Bowman’s (2014) expansive faculty survey at over
150 research institutions which found WLB factors correlated with a statistically
significant improvement in male faculty productivity and a neutral response among
female faculty. Delving into more specific factors, Greenhaus, Collins, and Shaw (2003)
found an imbalance in work-life stimulates the human stress response which inhibits
workplace effectiveness and productivity. In a study of Australasian surveyors,
Wilkinson (2008) found work-life imbalance reduced employee effectiveness and
profitability. Employees also had greater sickness absences when experiencing work-life
imbalance (Jansen et al., 2006). Viewed in total the literature does not find WLB factors
generate a potent positive effect on employee productivity, rather it suggests a mildly
positive relationship.
15
Structure Dimension is Insufficient
As the 20th century drew to a close, Kossek and Ozeki (1998) compiled a
comprehensive review of early WLB policy and practice. They found work-life policies
alone were not enough to reduce work-life conflict and improve work-life satisfaction.
More recent studies further substantiated this claim. Haar (2003) confirmed that WLB
policy alone was insufficient to reduce turnover intention. Friedman and Greenhaus
(2000) noted that for WLB policies to improve outcomes, they must not only exist but be
perceived as useful by the employees. Lewis (2001) found when leaders were not
supportive, well-meaning policies sometimes limited the progress toward a culture of
WLB policy utilization. Given the discussed benefits to both employer and employee,
wide-spread utilization of WLB policy is critical.
Though policy is a crucial WLB starting point for employers, these sources
illustrate the misplaced confidence that human resource initiatives are enough to foster
WLB. By placing the onus on the employee to ensure WLB, the substantial barriers
workplace cultures engender are ignored. Todd and Binns (2013) described this attitude:
“The widespread assumption that individuals freely make choices and negotiate their
preferred working arrangements allows managers to ignore the need to transform
workplace structures, cultures, and practices that may be impeding the implementation of
WLB” (p. 221). Effective WLB policy implementation requires equal attention to
organizational culture (Lewis, 1997).
Cultural Dimension of Work-life Balance
Over long periods of time organizations develop shared assumptions and beliefs
which help employees navigate their roles and responsibilities. These often subliminal
16
assumptions and beliefs jointly produce an organization’s culture. Deal and Kennedy
(1982) described organizational culture succinctly as “the way things are done around
here” (p. 4). Schein (1985) further defined this culture as a pattern of shared common
assumptions learned by the organization as it adapts to external problems.
In his seminal work in the field, Schein (1985) described three levels of
organizational culture—artifacts, values, and assumptions. Artifacts are easily viewed by
employees and may include items such as policies, procedures, and conduct codes.
Values support these artifacts through more opaque constructs such as vision, mission,
philosophy, and strategy. According to Schein, the true essence of organizational culture
is governed by its underlying assumptions. These assumptions are difficult to pin down,
generally operate at the taken-for-granted level, and are continuously influenced by the
organization’s leaders, employees, and the culture-at-large.
Given their ability to influence organizational assumptions, Schein suggests that
leaders modify organizational culture based on six primary embedded mechanisms
(PEM). The six mechanisms are as follows: (a) What leaders regularly pay attention to;
(b) How they react during crisis; (c) Conditions by which they divvy scarce resources;
(d) Intentional role modeling/coaching; (e) Metrics by which they offer rewards and
status; and (f) Standards by which they recruit and promote employees. These are not
remarkable mechanisms of influence. Rather, they reflect a leader’s daily attention to
routine work.
Work-life Balance Culture
As research amalgamated around the construct that human resource policy alone
was insufficient to instigate positive WLB outcomes, Thompson, Beauvais, and Lyness
17
(1999) identified three necessary components for generating a WLB culture: supervisor
support, time/schedule norms, and career expectations. To use the language of Schein
(1985), leaders must give regular attention to these components in order for them to
become norms within an organization’s culture. Since this call-to-arms, the scholarly
literature has responded to validate each component.
Supervisor support. Supervisor support is defined as the perception by an
employee that the relationship with his/her supervisor supports career development
(Kram, 1985). Among other factors, this support includes (a) realistic expectations for
job performance and (b) help facing new work challenges. Supervisor support has been
positively linked to job engagement and life satisfaction (Gallup, 2006). Further, this
construct featured prominently as a ‘critical ingredient’ for creating an effective
workplace in a comprehensive analysis by Jacob, Bond, Galinsky, and Hill (2008).
Schedule control. Upon the fading of the long-held belief that an employee’s
presence at work denoted his/her level of commitment and contribution (Perlow, 1995),
organizations sought a new cultural norm centered upon schedule autonomy. Flexible
scheduling policies, time management training, and telecommuting were tried with
limited success. It became apparent that a new scheduling norm was required to move
the WLB cultural needle. The resulting construct—schedule control—describes the
employee’s perception that enough daily work is within his/her scope of control. When
employees have a healthy perception of schedule control their satisfaction and
engagement improve. The benefits of this construct have been reported in CES-similar
work contexts, such as those that are dynamic (Kelly & Moen, 2007), scholarly (Kinman
& Jones, 2008), and irregularly scheduled (Mazerolle & Gavin, 2013).
18
Career expectations. The final component for generating a positive WLB
culture relates to career expectations. Here, the organization’s stated performance
expectations and promotional systems must match the underlying culture of WLB
adoption. Disconnects can severely harm WLB adoption and cause long-term cultural
damage (Auster & Prasad, 2016; Moen & Roehling, 2005; Bailyn, 1993). The
combination of supportive supervisors who encourage schedule control without negative
career consequences is the hallmark of a positive WLB culture (Goodman, Mazerolle, &
Pitney, 2015).
Work-life Balance in Cooperative Extension
A job seeker considering a position with Extension might take a cursory look at
CES human resource websites and discover that WLB is well provisioned. Many state
CES agencies celebrate WLB policy initiatives such as dual-earner family supports,
flexible scheduling, and childcare stipends. These initiatives exist to keep public-service
roles competitive with private entities, but are they sufficient? Though it has made
strides in recent years, is Extension making the WLB grade in both policy and culture?
WLB Policy Context
In the early years of WLB becoming a known human resource consideration,
Extension was at the fore among public service organizations (Fetsch & Kennington,
1997). A 1981 position paper by the Extension Committee on Organization and Policy
(ECOP) noted that CES leaders needed to critically examine organizational policies for
their effects on employees’ non-work lives. Heeding this initial call, subsequent research
found room for concern. Patterson and McCubbin (1984) found agent stress levels were
greatest among 4-H agents (i.e., the agents with the greatest evening and weekend
19
responsibilities) with Igodan and Newcomb (1986) generating similar results on the topic
of employee burnout. In fact, a separate 1984 study (Fetsch, Flashman, & Jeffiers) on
stress found 4-H agents were more stressed than a control group of adults. St. Pierre
(1984) discovered that most agents perceived their work roles had a net negative
influence on family life.
As was common in this era—and remaining through today—the CES response to
these disheartening studies was a mix of policy and self-help protocols. Many CES
entities added or strengthened policy initiatives (e.g., family leave, childcare stipends,
flexible scheduling, employee assistance programs) to advance WLB concerns (Kutilek,
Conklin, & Gunderson, 2002). Notable among the self-help efforts, Kentucky piloted
successful stress reduction and time management workshops while Kansas, Florida,
Colorado, and Pennsylvania held effective workshops for balancing work and family
(Ensle, 2005; Fetsch & Pergola, 1991; Kennington, 1988; Thomson et al., 1987). After
all these efforts came to pass, the question still remained: was the WLB policy and self-
help approach enough to alter course?
A turn-of-the-century, nation-wide WLB study in CES produced several landmark
findings (Kutilek, Conklin, & Gunderson, 2002). Thirty-seven percent of employees
reported working more than 50 hours per week with administrators the most overworked
employee pool. Sixty-five percent of employees reported achieving poor WLB with
heavy workload, evening/weekend requirements, and lack of schedule control serving as
key culprits. Employees indicating an unsupportive WLB organizational culture were
more likely to report WLB imbalance. Supervisors were regarded as demonstrating
moderate effectiveness levels in promoting and modeling WLB. This was further
20
evidenced by poor supervision and inadequate training being listed as persistent barriers
to achieving WLB.
Though the authors overemphasized the continued importance of WLB policy
factors (e.g., paid leave, employee assistance programs) they deserve credit for being the
first in Extension to quantitatively confirm the essential nature of cultural transformation.
Calling attention to the finding that supervisors exhibited the least balance among all
employee pools, the authors implored organizational leaders to (a) personally “walk the
talk” in WLB, (b) consistently encourage subordinates to use existing benefits, and
(c) reduce the negative influence of clientele expectations. Unfortunately for Extension,
the authors’ beneficial suggestions were not formally heeded. The self-help and policy-
centric WLB focus remains while the intersection of WLB culture and leadership awaits
further examination. My study will consider this important linkage in greater detail.
WLB Cultural Context
Among other studies demonstrating the role of positive WLB culture in higher
education, McCoy, Newell, and Gardner (2013) noted its ability to mitigate detrimental
faculty behaviors such as non-collegiality and administrative favoritism. These faculty-
related findings are important, but one must consider: is Extension an entity of higher
education? Not fully. Agents working for the CES operate within two semi-distinct
worlds: the academy and the communities they serve. This dichotomy makes it somewhat
difficult to ascribe cultural commonality with higher education faculty.
Because the topic of WLB culture in CES is understudied (Ensle, 2005) and CES
roles are not synonymous with on-campus faculty, similar professional fields provide
additional context. These contextual similarities are found in fields (a) mildly skewed
21
female, (b) well-educated, (c) rural, and/or (d) for which irregular-work schedules are
normative. In a qualitative study on female collegiate athletic trainers, Mazerolle and
Gavin (2013) found that after having a first child these employees looked to leave the
profession. Though the athletic trainers expressed a strong desire to continue working in
the field, the perception of an either/or choice between work and family motivated them
to change career paths. A qualitative study of pharmacists (Mahaney, Sanborn, &
Alexander, 2008) found that retention was enhanced when advanced flexible scheduling
options were culturally normative. This included an option to keep professional ‘toes in
the water’ during major life events and crises. Finally, a longitudinal study of Canadian
lawyers (Kay, Alarie, & Adjei, 2013) linked the high-pressure nature of the job and long
hours with employee attrition. This was particularly pronounced among rural lawyers
who felt a great community obligation to serve their clientele.
In addition to the related work pressures of higher education faculty and other
similar professions, Extension agents face the often unrealistic expectations associated
with small community leadership (Young & Jones, 2015). With nearly 80 percent of
agents stationed in rural locales, non-work trips to the grocery store, church, school
event, etc. frequently become work-based encounters with clientele. After-hours service
to community organizations is subtly expected due to a shortage of highly qualified
professionals in the community. Maintaining local political support is critical which
requires a delicate balance in navigating relationships with elected officials, partners,
clientele, and volunteers (Seevers, Graham, Gamon, & Conklin, 1997). These extra-duty
responsibilities contribute to a normative culture of work-life imbalance among CES
agents.
22
This normalcy of imbalance is problematic when it becomes enmeshed as part of
the Extension agent culture. Agents are supposed to look a little tired, harried, and
overworked. They are supposed to gather around the bar at national conferences sharing
war stories of trial and tribulation (e.g., horse committee dysfunction, ‘I had 4 night
meetings last week’). In the reverse, agents who exhibit healthy WLB and project a more
effortless work approach are viewed as magicians or underachievers—regardless of their
often high performance levels. They may even try to hide their positive WLB attributes
for fear of not fitting in with the dominant culture (Forstadt & Fortune, 2016). This long-
held CES agent culture has been slow to adjust to employee demographic influences
toward greater balance. Persistent leader influence will be necessary to alter this
culture’s course.
Recent developments. With the onset of high Millennial employee turnover
rates, CES administration (Extension Committee on Organization and Policy, 2010) and
professional organizations (e.g., Joint Council of Extension Professionals, Epsilon Sigma
Phi) renewed their attention to WLB concerns. Through increased WLB-focused
professional development workshops, presentations, and conference posters, self-
improvement techniques are being discussed and a long-awaited culture of positive WLB
is slowly taking hold. More importantly, it is increasingly common to see CES
administrators and middle leaders projecting positive WLB narratives through weekly
email newsletters, blogs, and social media.
These cultural improvements are tempered by a recent study which found that
only 38 percent of Colorado CES employees reported positive WLB (Harder,
Gouldthorpe, & Goodwin, 2015). Of similar concern is Penrose’s (2017, para. 8) well
23
intended but easily misconstrued advice that elder agents should mentor newer agents to
succeed by taking “care of their clientele and their coworkers…Extension does not need
to be just a job: It can be a way of life.” As Kossek et al. (2010) suggests in other venues,
it appears the longstanding WLB policy supports in Extension have not yet paired with
enough culture support to swing the tide in favor of positive WLB. The proposed study
will add more clarity to the present standing of this linked dichotomy in Extension.
Leadership Dimension of Work-life Balance
The supervisor’s role is critical in supporting WLB culture generally and
employees specifically. Without the leader’s symbolic influence, WLB initiatives will
only attain limited success. How do leaders influence their subordinates in this manner?
A review of the literature on transformational leadership theory offers appropriate
context.
Early perspectives on leadership mirrored the mechanistic organizations from
which they derived. Leadership was viewed as a positional form of authority from which
subordinates received orders and completed organizational tasks. Unable to quantify the
traits necessary for defining such leaders (other than positional authority), this
perspective gave way to human resource typologies under which leaders used process and
influence to accomplish organizational goals. Discerning the process components were
essential but insufficient in postmodern America, Burns (1978) encouraged leaders to
focus on follower development. This simple addition revolutionized leadership theory
and practice in the post-industrial sector (Rost, 1991).
Burns’ concept that leaders develop other leaders set the stage for
transformational leadership theory (Bass & Riggio, 2006; Bass & Avolio, 1994; Bass,
24
1985). These scholars sought to discover what interactions between leaders and
followers moved followers to become leaders themselves. Avolio and Gardner (2005)
eventually found that transformational leaders are undergirded by authenticity. This
authenticity builds the ethical, considerate, inclusive, and strengths-based organizational
culture necessary for leadership development to occur (Komives & Dugan, 2010).
In order to foster this culture of leadership development, Bass and Avolio (1994)
suggest transformational leaders must exhibit four key characteristics. Under idealized
influence, leaders are authentic role models who generate respect and trust. Within
inspirational motivation leaders communicate high expectations and organizational
purpose via understandable methods and symbols. Intellectual stimulation refers to the
leader’s promotion of creative problem solving through intellectual wrestling. Finally,
individualized consideration describes the uniquely individualized coaching, mentoring,
and rewards a leader uses to support and challenge employees.
Transformational leadership is an attractive framework for complex, creativity-
centric workplaces. Unlike popular transactional leadership frameworks such as leader-
member exchange or path-goal emphasis that remain imbalanced toward productivity
(Komives & Dugan, 2010), transformational leadership engenders a wider array of
employee benefits such as reduced burnout (Corrigan et al., 2002), increased job
satisfaction (Watson, 2009), and an improved sense of well-being (Jacobs et al., 2013).
Further, because it motivates employee performance, it retains the strong business case
(Garcia-Morales et al., 2012) more endemic to transactional frameworks. Under
transformational leadership both employees and the organization experience gain.
25
Transformational leaders are particularly well positioned to work with the
generations comprising most of today’s workforce. Millennials wish to be inspired and
challenged with meaningful work which makes a difference. Personal development and
working within an innovative culture are important to them (Myers & Sadaghiani, 2010).
Generation X workers desire authenticity and transparency from organizational leaders
(Bickel & Brown, 2005). They are solution-centric fixers who crave the ability to
challenge norms for the good of the organization or communities they serve (Marston,
2007).
In addition to these broader strengths, transformational leaders are also well
situated to lead within the context of the Cooperative Extension Service (CES or
Extension). County-based CES agents are hired as largely autonomous local service
providers. They are adept thinkers, multi-tooled communicators, and skilled problem
solvers. They work flexible, irregular shifts to meet clientele needs. Though agents
reside near the bottom of the organization’s scalar chain, their creative problem-solving
aptitudes make them leaders within the community (Mumford et al., 2000). As
Northouse (2004) describes, transformational leaders “promote followers’ thinking things
out on their own and engaging in careful problem solving” (p. 177). These independent
local leaders need supervisors who are supportive and employee development minded,
key attributes of the transformational leadership framework. Further discussion of
leadership in the Extension context is provided below.
Leadership and the Extension Context
A recent synthesis of CES leadership literature noted that a creativity-centric
cultural transformation is (a) slowly percolating and (b) necessary for Extension to thrive
26
in an employee-driven future (Argabright, McGuire, & King, 2012). Once implemented,
this leadership framework would be a new paradigm for CES. Is Extension ready for this
leadership model? Is it the best choice among myriad employee-focused models?
Since Extension’s formal inception in the early twentieth century, agents have
been helping local clientele solve critical problems in agriculture, domestic arts, and
beyond. Early agents addressed multiple concerns with great autonomy—the needs of
local clientele always taking priority. With the popularization of structural leadership
models generated by the successful military accomplishments of World War II, agents
lost some autonomy as coordinated regional efforts were implemented and formal
assessments regularized (Schwieder, 1993). As the post-war era reached full bloom,
private industry began generating a profit from some of Extension’s historic public-
service roles. This forced CES recalibration led to greater diversification and
specialization among agents. Necessarily, this ballooned the administrative pool charged
with overseeing these newly specialized roles. The result was a bureaucratic and
specialized scalar chain led by transactional, organization-focused leaders.
Facing growing difficulties retaining talented young employees, a national CES
leadership assessment was conducted in the early 1990’s. The National Impact Study of
Leadership Development in Extension confirmed the existing prominence of the
transactional approach (Paxson, Howell, Michael, & Wong, 1993). In this study
creativity and concern for employees remained absent from a list of 13 leadership
competencies. In response, Extension was encouraged to move beyond hierarchical
forms of leadership in favor of less hero-driven, more employee-centered paradigms
(Sandmann & Vandenberg, 1995).
27
Despite this call, the transactional format held serve into the new century as
Astroth, Goodwin, & Hodnett (2011) lamented, “Much of Extension is still mired in the
classical model of leadership based on command and control…Changing times and a
post-modern world demand a new perspective on leadership.” Johnson (2015) echoed
this sentiment, noting that the lack of creative leadership still holds Extension back from
experiencing a more fruitful existence. He also reminded the organization that its roots
were far more autonomous and employee-driven. Seger and Hill (2016) painted a
similarly bleak picture, suggesting Extension’s most creative young leaders are still
leaving the organization rather than trudging through the slow transition toward a more
creative leadership framework.
Seeking to institute a more symbolic, employee-driven leadership framework in
Extension, four models have been proposed by CES leaders—soft, catalytic, servant, and
transformational. Each model has the potential to unleash a renewed creative problem-
solving emphasis in CES, but one shines above the rest. I will discuss these models in
ascending order of appropriateness for Extension’s leadership future and this study.
Soft leadership. In their call for soft leadership, Seger and Hill (2016) list
familiar public-sector leadership challenges. Extension is falling behind the private
sector in engaging new employees. Present leaders lack necessary employee motivation
skills. Reward and promotion systems are archaic and too infrequent in occurrence. The
authors then discuss so-called “soft leadership” tenets as the solution.
Soft leadership tenets were generated from a comprehensive study of over 4,000
companies (Torres, 2013). Results suggest leaders must possess 5 traits: (a) collect and
share trends that will influence the organization, (b) see around corners, (c) network
28
extensively, (d) take risks, and (e) care about themselves and others. This is a promising
list in the context of my study, particularly the emphasis of leader self-care and care for
others, but thus far Torres has failed to create a replicable model of soft leadership.
Should she do so, future researchers can investigate the model’s appropriateness for
Extension and the promotion of a positive WLB culture. Given the original study was
conducted exclusively in the private sector, future researchers should pay close attention
to key mission differentials in public and private sector organizations when investigating
the soft leadership approach.
Catalytic leadership. Two Iowa case studies serve as positive examples of the
second proposed leadership model (Morse, Brown, & Warning, 2006). Catalytic
leadership as coined by Luke (1998) was employed by Iowa State University Extension
to successfully address two separate community-based challenges: Hispanic immigration
and dairy farm profitability. Reports from these case studies suggest this model is
excellent for Extension’s work. What is the catalytic leadership model?
Catalytic leadership recognizes the interconnected and community-embedded
nature of Extension’s work. As Luke suggests, public sector becomes public—meaning
rather than serving merely as community experts in positions of authority, agents should
be collaborative engagers who work across traditional boundaries to build public-private
partnerships. Catalytic leaders accomplish this by raising awareness, forming new
working groups, creating strategies, and sustaining action.
Though promising for Extension’s community work, the author team stops short
of fully embracing catalytic leadership as an organizationally-appropriate leadership
model. Strategy creation and work group formation sound relatively hierarchical in the
29
CES organizational context which is already rife with plans and committees. What is
empowering and innovative in the community context would be perceived as arcane in
the organizational context. The catalytic leadership model is well considered for agents
embedded in communities, but not appropriate for my study on the middle leadership
level in Extension.
Servant leadership. Rooted in Taoist and mystical Christian traditions, the
servant leadership model was formally identified by Greenleaf in 1977. He called upon
organizational leaders to attend to staff concerns, serving their needs as the highest
priority. Keith (2008) suggests that servant leaders influence others by employing 7
personal or corporate attributes:
(a) self-awareness, (b) high capacity for listening, (c) hierarchical inversion, (d) colleague
development, (e) coaching and mentoring, (f) unleashing everyone’s aptitudes and
energy, and (g) foresight. In response, these staff members experience an unparalleled
level of trust which motivates them to fervently achieve organizational objectives
(Lencioni, 2002).
In calling for Extension’s adoption of the servant leadership model, Astroth,
Goodwin, and Hodnett (2011) make a strong case that only falters at the application
stage. They suggest that when administrators serve county-based agents, magical things
happen. Though anecdotally believable, the authors provide no evidence for what
magical things will happen. This is a persistent challenge in the servant leadership
literature. Kim, Kim, and Choi (2014) summarize that servant leadership principles are
ambiguous to measure which results in a lack of rigorous supporting studies. Further, the
necessary servant leadership elements are too normative and difficult to train into existing
30
leaders. Particularly in Western cultures that value heroism, aggression, and
independence, desirable servanthood traits may be difficult to find among applicants
during the hiring process. Though a promising approach, these shortcomings make the
servant leadership model an inappropriate model for Extension’s future and this study.
Transformational leadership: Model of choice. The transformational
leadership model has several advantages in the specific CES context. Its benchmark
aptitudes (similar to many discussed in the unchosen models) are appropriate to both the
creativity-centric challenges facing CES and Millennial employees joining the workforce.
Further, these aptitudes can be trained into existing leaders rather than only being
available through the hiring process. Transformational leadership theory also possesses a
robust research base supporting its applicability within public service and similar
organizations. The combination of these traits strengthens the case for its use in
Extension, yet what of its relationship to middle leadership and work-life balance?
A limited Tennessee CES study considered the effects of three prominent
leadership models—laissez faire, transactional, and transformational—among county
directors on agent job satisfaction (Elizer, 2011). Though transformational leaders were
difficult to find at the county director level (n = 14), they demonstrated a 40 percentage
point job satisfaction boost over the more common laissez fair and transactional leaders
(n = 69). This study indicates (a) transformational leadership may generate beneficial
outcomes in CES and (b) a more rigorous study on the effects of transformational middle
leaders in CES is warranted.
The seminal work on Extension WLB remains the nation-wide study reported by
Kutilek, Conklin, and Gunderson (2002). Among other prescient findings, the authors
31
were the first to link an unsupportive organizational culture to agent work-life imbalance.
This led the team to assert the importance of culture change at the leadership level and
they posited that transformational leadership was the appropriate model to generate this
change. The stated connection to WLB culture—in fact, the only WLB culture
connection made in the Extension literature to date—and the supporting study’s rigor
provide clarity that this is the most appropriate model moving forward. With these
considerations in mind, this study will explore the linkages between Extension’s
transformational middle leaders and perceptions of WLB culture and factors among
agents.
Summary
A supportive work-life culture is the extent to which the organization’s culture
supports the balancing of work and non-work lives (Thompson et al., 1999). This
chapter’s review of the literature described the field’s journey toward this understanding
of positive WLB culture. It noted that organizations are looking for win-win WLB
solutions which benefit the organization and employees (Bailyn, 1993). These solutions
require not only structural human resource policies but the more nebulous influences of
culture and leadership. The transformational leadership framework is ideally positioned
to bring forward these solutions for Extension.
In the next chapter, the methodology for this study is described. Chapter 4
follows with a presentation of the study data and results. The final chapter analyzes the
study data with recommendations for research and practice.
32
Chapter III
Method
The field of work-life balance (WLB) research has advanced from considering the impact
of policy alone to the dualist consideration of policy and organizational culture. Like
many public agencies, Cooperative Extension (CES) has the policy level in place but
struggles to engender widespread policy adoption. The policy adoption shortfall indicates
a cultural element is likely hindering employees, making this culture-exploring study
beneficial. Further, the WLB cultural influencing ability for leaders generally and middle
leaders specifically has not been covered in previous studies.
In their comprehensive review of civic leadership frameworks, Komives and
Dugan (2010) suggest transformational leadership studies need to go beyond the leader-
follower relationship to examine the interplay of organizational culture. This may be a
critical addition, as recent studies have vacillated between demonstrating a mild (Jiang,
2012) to significant (Munir et al., 2012) ability among transformational leaders to
influence positive WLB in other settings. Further, Lamm (2011) discussed
transformational leadership’s advantages for the CES culture, but only from a theoretical
perspective.
The adoption of a positive WLB organizational culture does not happen by
accident. Employees alone are unable to drive this culture forward. Leaders play a
critical role. As Rossiter (1997, p. 177) reminds, the supervisor “must promote [WLB]
policies for them to be effective.” A supportive supervisor who promotes and models
effective strategies is essential to this cultural transformation (Mazerolle, Goodman, &
Pitney, 2015; Ward & Wolf-Wendel, 2005; Lewis, 2001).
33
This survey research study adds to the growing body of research on WLB culture
by examining three significant areas of inquiry: a) the influence of middle leaders on
WLB culture; b) the influence of middle leaders on WLB-related factors; and c) the
intervening influence of WLB culture on WLB factors. To guide the inquiry process, a
conceptual model (see Figure 3.1) and three research hypotheses were employed in this
study.
Research Hypotheses
1. The rated levels of transformational leadership among Extension middle leaders will
positively influence WLB culture among subordinates.
2. The rated levels of transformational leadership among Extension middle leaders will
positively influence WLB factors among subordinates.
3. The relationship between transformational leadership among Extension middle
leaders and WLB factors is strengthened by the intervening influence of WLB
culture.
This chapter offers a methodological framework for addressing the research
hypotheses. Elements of research design, setting, and sample initiate the chapter. These
are followed by a discussion of ethical research obligations and data instrumentation,
Transformational leadership of middle leader
Work-life balance culture
Work-life balance factors
Figure 3.1. Conceptual model for influence of transformational middle leaders on work-life balance culture and factors among subordinates.
34
collection, and analysis. The chapter concludes with a brief discussion of researcher
roles and potential limitations.
Research Design
Approach
This exploratory study employed a quantitative, non-experimental research survey
design thru the use of three pre-existing instruments for data collection. Exploratory
research is appropriate when a topic of study is only semi-understood and gaining more
familiarity is beneficial (Fowler, 2002; Rea & Parker, 1992). Further, quantitative
research examines the relationships among variables through the use of instruments and
statistical analysis of data (Cresswell, 2014). Using a survey for data collection is not
only common in Extension research but also provides some time and cost efficiencies
(Pearson & Boruch, 1986). In this study, the use of existing instruments for WLB
culture, WLB factor, and transformational leadership variables further streamlined the
design process.
Cognizant of furthering the work of Kutilek, Conklin, and Gunderson’s (2002)
first nationwide CES study on WLB, this study used a close-ended electronic survey of
Extension subordinates (i.e., agents) in 13 geographically-distributed CES states securing
at least 1 state from each region (see Figure 3.2). The survey sample included 1390
agents which represented a 53 percent response rate. The study examined the
relationships between transformational middle leaders, WLB organizational culture, and
WLB individual factors. Due to the interest in nested relationships, design-based
multilevel modeling was the analysis mode of choice.
35
Rationale
Studies under the broad umbrella of organizational culture have traditionally
relied on qualitative inquiry (Jung et al., 2009). In many cases, the organization’s culture
is being studied for the first time, so this more exploratory approach is valued.
Qualitative inquiry is particularly important when an examination of subliminal values,
beliefs, and assumptions is warranted (Yauch & Steudel, 2003).
Extension’s organizational (Lamm, 2011) and middle leader (Leuci, 2005)
cultures have been previously explored. Additionally, Ensle (2005) examined historic
policy initiatives aimed at strengthening individual WLB in the CES context. This study
added the next dimension to this body of CES WLB knowledge through a quantitative
survey approach. Given the additional considerations of a) participant time constraints
and b) the desire to secure a large national sample for rigor purposes, an electronic survey
was a suitable format (Tucker, McCoy, & Evans, 1990).
Context of the Study
Setting
Under the auspices of the Association of Public and Land-grant Universities
Board of Agriculture Assembly, CES is structured into four geographical regions and one
classified region (Ruble, n.d.). The classified region is comprised by institutions known
as the 1890s (i.e., approximate year of their adoption into the land-grant system), which
tend to have smaller operations budgets and narrowly focused impact areas. Limited
employee bases exclude the 1890 institutions from the scope of inquiry as they lack a
parallel middle leadership structure. The four remaining regions are the Northeast which
has 13 member institutions, North Central (13), Southern (15), and Western (17). In the
36
three latter regions, these member institutions tend to have larger operational budgets,
scopes of impact, and employee bases which make them appropriate samples for this
study on middle leader influence. The Northeast region is almost exclusively comprised
of geographically small states which would be inefficiently served by a middle leader
structure.
Sample
Within the CES differing organizational structures exist. In the face of limited
government funding, some states have centralized operations. As discussed above, other
states are too geographically small to be well served by a middle leader structure; this
phenomenon is most pronounced in the territories and Northeast region. Of the 58 CES
member institutions, 11 institutions have centralized operations or use complex multi-
Western: 17 Clusters
Northeast: 7 Clusters
Southern: 22 Clusters
North Central: 22 Clusters
Image Credit: Univ. of Alabama
Figure 3.2. Participating states in final research sample by APLU Cooperative Extension regional divisions.
37
leader structures, and 17 institutions are too physically small to warrant a middle leader
structure (see Table 3.1). Given their non-majority structural composition, these 28
institutions were excluded from the potential scope of inquiry.
38
Table 3.1
Study StructureMiddle Leaders Other Formats Too Small 1890 Institutions*Arkansas [3] Alabama American Samoa Alabama A&MColorado [3] Alaska Connecticut Alcorn State*Florida [5] Arizona Delaware Central State*Georgia [4] California Guam Delaware State*Idaho [4] Iowa Hawaii Florida A&MIllinois [3] Maine Maryland Fort Valley State*Indiana [5] Nebraska Massachusetts Kentucky StateKansas [4] New York Micronesia Langston*Kentucky [7] South Dakota Northern Marianas LincolnLouisiana [5] Washington New Hampshire North Carolina A&TMichigan [14] West Virginia New Jersey Prairie View A&MMinnesota [15] Puerto Rico S. Carolina StateMississippi [4] Rhode Island Southern*Missouri [8] Vermont Tennessee State*Montana [3] Virgin Islands TuskegeeNevada [2] Washington D.C. Ark-Pine BluffNew Mexico [3] Md-Eastern ShoreNorth Carolina [5] Virginia State*North Dakota [3] West Virginia State*Ohio [5]*Oklahoma [3]*Oregon [10]*#Pennsylvania [7]South Carolina [8]Tennessee [3]Texas [12]Utah [2]Virginia [4]Wisconsin [22]Wyoming [2]Note. Brackets denote the number of districts within each state (January 2018).*Denotes final study participants. #Denotes unique middle leader structure.
Structures Not Pertinent to this Study
Extension Organizational Structure Type by State, Territory, or Institution
39
The majority organizational structure involves a middle leader level of district
directors which supervise single- or multi-county agents. The 30 institutions representing
this organizational structure-type were invited to participate. Among the 16 institutions
from which the state CES director initially agreed to allow employee participation in the
study, 13 institutions fulfilled their obligations and actively participated—together
producing 68 research clusters as shown in Figure 3.2. This technique generated a
geographically-dispersed stratified convenience sample which enhanced the national
generalizability of the study’s findings (Nardi, 2014).
Ensuring a robust study sample is critical when employing the Cluster-Robust
Standard Error (CR-SE) approach as this method requires a minimum of 50 clusters
(Angrist & Pischke, 2009; Mancl & DeRouen, 2001). As mentioned earlier, this study’s
sample originated with 82 potential clusters. [A cluster represents all the Extension
agents under a given district supervisor.] Only states that exhibited active participation in
the survey were retained in the final sample. This parameter reduced the total clusters
analyzed to 68. Within the clusters themselves, the number of agents ranged from 2 to 49
as shown in Table 3.2. In order to ward off convergence issues and justify its use over
hierarchical linear modeling, CR-SE requires the number of individuals within clusters to
be modestly balanced (i.e., less than 51x response separation between the minimum and
maximum n) (Baum, Nichols & Schaffer, 2010). Both of these requirements were met in
this study.
40
Within the 13 participating CES institutions, all county-level agents were invited
to participate. From this original pool of 2620 agents, 1390 agents completed the survey
resulting in a 53% response rate. As indicated by Table 3.2, the participation rate ranged
from 29% in Kentucky to 80% in Indiana. Further, Table 3.3 indicates the agent
demographic categories of gender (female=69%), career stage (early=61%) and
generational distinction (Millennial=35%) were appropriate representations of the
broader CES population.
Table 3.2
State System Name n Rate (%) Clusters M Low HighArkansas 114 67 3 38 27 48Florida 161 52 5 32 27 42Georgia 98 33 4 25 20 32Idaho 38 47 4 10 7 12Indiana [Purdue] 203 80 5 41 37 45Kentucky 123 29 7 18 10 26Missouri 137 60 8 17 7 23Montana (State) 30 36 3 10 9 12North Dakota (State) 65 66 3 22 19 23Ohio (State) 131 73 6 22 9 37Oklahoma (State) 127 77 3 42 37 49Oregon (State) 68 51 10 7 3 15Pennsylvania (State) 95 51 7 14 2 26 Total 1390 53 68 23 2 49Note. Clusters generally represent districts in the analysis phase.
Responses per Cluster
State-level Summary Statistics for Final Sample
41
Ethical Considerations
In order to protect the rights of study participants, authorization to conduct human
subjects research was received by the University of Kentucky’s Institutional Review
Board prior to survey administration (see Appendix A). Appropriate participant
protections included the following measures: a) secured informed participant consent; b)
study materials handled by appropriate research team members; c) data collected,
analyzed, and stored on an encrypted secure computer; and d) no descriptive findings
shared in a way that could potentially identify study participants. The latter was of
particular importance for middle leaders given the nested nature of the study.
In addition to concerns of individual participants, this study also faced an
institutional concern. Given the potentially sensitive nature of institution-level findings,
the study invitation letter to each state CES director specifically addressed the way the
findings would be disclosed as well as common study details. Each CES director
n %Generation
Millennial 490 35.4Generation X 469 33.8Baby Boomer 420 30.3Traditionalist 7 0.5
Career StageEarly 844 60.8Mid 306 22.0Late 238 17.1
GenderFemale 953 68.6Male 433 31.2Variant 3 0.2
Characteristic
Table 3.3Demographic Characteristics of Participants (N = 1,390)
42
provided institutional acceptance prior to respective agent invitations being delivered by
email.
Measures
To examine the relationships between transformational middle leaders, WLB
individual factors, and WLB organizational culture, an established survey instrument for
each variable was employed. The survey also included pertinent descriptive and
demographic questions to provide additional research clarity. Text from the full survey is
available in the Appendix B. The survey’s three primary instruments are described in
greater detail in the following paragraphs.
Transformational Leadership Inventory
The Transformational Leadership (Behavior) Inventory (TLI) was first developed
by Podsakoff et al. (1990) and adapted by Rowold and Heinitz (2007). It has been
validated across many cultural contexts, industries, and leadership frameworks. The full
TLI was recently shortened by Jacobs et al. (2013) from which this study derives its
instrumentation. This will be the instrument’s first psychometric evaluation in an
educational context. The shortened TLI uses a 5-point Likert-style response format and
asks one question each from seven transformational indicators (e.g., articulating vision,
individualized support, behavior modeling). The maximum potential score is 35 points
(i.e., indicating an exceptionally transformational leader) and the minimum potential
score is 7 points.
Work/Life Balance Self-Assessment Scale
The Work/Life Balance Self-Assessment Scale (WLB-SAS) was first developed
by Fisher-McAuley et al. (2003), refined by Hayman (2005) and notably confirmed by
43
Smeltzer et al. (2016). The refined WLB-SAS instrument asks 15 WLB individual factor
questions and uses a 7-point time scale (i.e., not at all, sometimes, all the time). The
combined responses generate assessments for participants in three dimensions: 1) work
interference with personal life; 2) personal life interference with work; and 3) work/
personal life enhancement.
Work Life Balance Culture Scale
Advancing beyond the common individual factor variables historically examined
in the WLB field, Nitzsche et al. (2014) developed the Work Life Balance Culture Scale
(WLBCS) to measure the relationship between WLB organizational and leadership
culture. This validated instrument uses a 4-point Likert-style response format and asks
five questions—three questions related to organizational culture and two questions
related to supervisor’s leadership culture.
Rationale
Providing answers to three separate instruments creates challenges for survey
participants. Therefore, finding a) established instruments that were b) efficient for the
participants and c) complimentary with one another took priority in the instrument
selection process. Unfortunately, the WLB culture variable required the use of the
WLBCS, which is the only previously validated scale in existence for this variable type.
However, transformational leadership and WLB factor variables presented several
measures for consideration.
Transformational leadership can influence subordinates to improve performance
while strengthening job satisfaction and organizational commitment (Bass, 1985). These
positive attributes have led to numerous scales seeking to measure this leadership style.
44
The Multifactor Leadership Questionnaire (MLQ) was the first comprehensive scale to
measure transformational leadership (Bass & Avolio, 1994). Because it also considered
multiple other styles—thereby adding extraneous variables—it was not the most suitable
choice for this study. Its derivative—the Transformational Leadership Questionnaire
(TLQ)—holds promise for studies of public sector leaders (Alban-Metcalfe & Alimo-
Metcalfe, 2000) but its exhaustive length also renders it unsuitable for this study.
Two efficient scales were closely considered: a streamlined version of the TLI
(Jacobs et al., 2013) and the Global Transformational Leadership (GTL) scale (Carless,
Wearing, & Mann, 2000). Because both scales are equally efficient, language served as
the determining factor. Notably, the GTL substituted leader charisma for a question
about high-performance expectations, which is a poor fit for the existing CES culture.
With the TLI’s longer stature in the literature and more pertinent language for
Extension’s leadership culture, it was the clear choice for this study’s transformational
leadership measure.
Prior to the work of Fisher-McAuley et al. (2003) and Hayman (2005), work-life
issues were considered from two frameworks: work-family balance and work-life
conflict. With the newfound challenges associated with dual-earner families, the
construct of work-family balance was born (Kanter, 1990; Tiedje et al., 1990).
Researchers studied this construct for over a decade until it became clear that a family-
based construct was too limited for the post-nuclear family era. The next study iteration
featured the concept of work-life conflict (Parasuraman & Simmers, 2001; Kossek &
Ozeki, 1998). This concept possessed a short run in the literature because it could only
identify factors associated with work-life imbalance. Discussing study results from the
45
negative perspective was difficult for the field. Hayman’s self-assessment scale provides
the only WLB measure from a positive-language perspective, which has made it the gold
standard for the field and clear choice for this study.
Procedure
Data Collection
Choosing the best season for Extension survey administration is complex.
Agriculture agents are generally busiest in February and March when farmers are
receptive to new ideas heading into the planting season. Youth development (4-H) agents
are busiest during the project, camp, and fair seasons which usually encompass the
summer and early fall months. All employees face end-of-year reporting concerns which
create challenges in December. Week-long national conferences upend employees
throughout the late summer and early fall. Combined, these circumstances leave only a
few narrow windows in early November, late January, and May for advantageous survey
administration. In the year of this study’s survey administration timeline, the 4-H
professionals’ national meeting was held later than normal (mid-November). This made
late January the most advantageous time for national CES survey administration.
In addition to seasonal concerns, determining the best day and time for employee
electronic survey solicitation is also complex. Employee surveys solicited on Monday
mornings/late afternoons or Friday late afternoons receive the best response rates
(CheckMarket, 2015; Zhen, 2011). In the year of this study’s survey administration
timeline, the third Monday in January fell on a federal holiday; therefore, initial survey
solicitation began late afternoon that Friday.
46
Monroe and Adams (2012) studied ways to increase response rates on electronic
surveys among CES employees. They discovered that assurances of confidentiality,
expressed support from administrative leaders, and survey length of 15 minutes or less
are key factors for promoting strong survey response rates. They also determined that the
well-known Tailored Design Method (Dillman, Smyth, & Christian, 2009) which uses
personalized, repeated contact increases response rates in Extension employee electronic
surveys.
The survey administration process of this study applied these principles.
Personalized encouragement from administrators preceded the survey’s release. The
focused survey design resulted in an average completion time of 9 ½ minutes. When
possible, non-responding participants were reminded twice during the three-week survey
availability period. The first reminder increased the response rate by 15 points and the
final reminder by 5 points. As a result, the cumulative response rate was 53 percent—
well above the 40 percent norm for CES assessment surveys (Archer, 2008).
Data Analysis Plan
Expanding beyond descriptive statistics common to many CES analyses, this
study’s analysis employed design-based structural equation modeling. It used the
maximum likelihood estimator with robust standard errors (MLR) to assist with the
handling of missing data. A confirmatory factor analysis (CFA) was conducted on each
measure, and coefficient omega was used to estimate reliability (Trizano-Hermosilla &
Alvarado, 2016). As the TLI and WLBCS are summative scales, a 1-factor structure
CFA was conducted. The WLB-SAS employs three structures which warranted a 3-
factor structure CFA to estimate reliability.
47
The study used a structural equation model (SEM) analysis based on data from n
= 1390 CES agents nationwide. Given that the research hypotheses were focused on
subordinate-level outcomes, a design-based (versus multilevel model-based) approach
was applied (Stapleton, McNeish, & Yang, 2016) using the “type=complex” command in
conjunction with the “cluster=distID” command in Mplus to correct standard errors for
the nested data structure (i.e., agents nested in district directors). As discussed in greater
detail below, SEM analysis benefits from its ability to detect and account for
measurement error and handling multiple latent variables simultaneously.
Rationale
Confirmatory Factor Analysis rationale. This study was concerned with
variables that were difficult to observe (e.g., work life balance, transformational
leadership, culture). Helpfully, previous authors have hypothesized scales that describe
these unobserved (latent) variables through more observable variables. Confirmatory
factor analysis (CFA) is a statistical technique that provides understanding for the
relationship among these constructed latent variables.
In a confirmatory factory analysis, latent variables explain the commonality
among observed variables. These variables are selected on the basis of prior literature,
and CFA examines if they load predictably on the expected number of factors. Further,
performing a CFA evaluates the degree to which hypothesized measures are consistent
with data derived from measurement scale responses.
Examination of parameter estimates (during SEM) and fit indices (during CFA)
formally test the dimensionality, reliability, and validity of the measurement model. In
1999, Hu and Bentler revised the thinking around commonly used global fit indices and
48
advocated for more stringent standards. Since then, good global fit is indicated by a
Comparative Fit Index (CFI) score greater than .95, Standard Root Mean Squared
Residual (SRMR) of less than or equal to .08, and Root Mean Square Error of
Approximation (RMSEA) of less than or equal to .06 while acceptable fit is characterized
by CFI ≥ .90 and RMSEA ≤ .10 (Weston & Gore, 2006). As Hu and Bentler warned,
these global fit indices are one tool in the toolbox for testing the model. They and others
(Fan & Sivo, 2005; Marsh, Hau, & Wen, 2004) remind that models should not be
overspecified to reach these fit index cutoffs or the analysis runs the risk of Type 1 error.
Examination of local fit assists in mitigating this concern.
For each of the measures used in this study, a corresponding CFA was performed
and reported below. Discussion regarding measures of fit, handling of missing data, and
model choice is provided for each. Additionally, coefficient omega—a key estimate of
internal reliability (McDonald, 1999 recommends a score of ≥ .70)—is also provided
thanks to the useful Bifactor Indices Calculator created by Dueber (2017). To assist the
reader as suggested by Kline (2016), a combined (i.e., best of each measure) CFA model
is reported after the independent CFA analyses.
Structural Equation Modeling rationale. This study investigated the
relationship between three variables: transformational leadership, WLB culture, and
WLB factors. These variables are all latent in nature as they are a) factors defined by
indicators and b) perceptions of leadership, culture, and factors that are ambiguous and
not easily observed. The transformational leadership variable is generated from scores on
the TLI which employs seven indicators to provide a summative result. The WLB
culture variable is generated from scores on the WLBCS instrument which uses six
49
questions to generate two indicators. The WLB factor variable is generated from scores
on the WLB-SAS which uses 15 questions to generate three indicators. Each of these
indicators feed into their respective latent variables.
To date Extension WLB studies have not considered multiple latent variables.
Existing studies generally remain within the realm of directly measured or observational
variables (e.g., effects of flexible scheduling policies and availability of childcare on
retention rates). Due to a lack of advanced statistical training among most CES personnel
(Boone & Boone, 2012), analysis of these variables is often limited to descriptive
statistics and multiple regression. Though helpful in identifying symptoms of work-life
imbalance, studies of observed variables are unsuitable for identifying complex
relationships (Kline, 2016).
According to Lei and Wu (2007), the ability to handle latent variables effectively
is one of the primary benefits of structural equation modeling (SEM) over multiple
regression. SEM allows researchers to induce and explain correlations among responses
(Rabe-Hesketh, Skrondal, & Zheng, 2012). As in this study’s WLB factor variable, latent
variables indicated by multiple indicators reduce measurement error (Byrne, 1998). The
paramount advantage of SEM analysis is the ability to handle multiple latent variables.
Structural equation modeling offers another subtle advantage over traditional
regression techniques within the context of this study. In multiple regression, variables
cannot respond and explain at the same time. Rather, models must be independently
postulated and analyzed. In the proposed model for this study, the WLB factor and WLB
culture variables are both response and explanatory. SEM has the capacity to consider
50
these roles simultaneously (Muthén & Muthén, 2009), thus providing a subtle advantage
over analyzing with multiple regression.
One common drawback in SEM analyses is lack of sufficient sample size.
Insufficient sample size can lead to misattributed findings. Though no minimum sample
size has been determined across all contexts (Tomarken & Waller, 2005), it is well
understood that simple-modeled SEM studies should incorporate at least 200 participants
(Boomsma & Hoogland, 2001). The sample for this study well exceeded that
recommendation.
Structural equation modeling’s ability to handle complex relationships among
variables also serves as this study’s primary drawback. Whereas scholars in
transformational leadership and WLB culture will benefit from this advanced
methodology, Extension personnel may find it difficult to understand the study’s results
as there are few comparisons in the existing CES literature. Mindful of this drawback
and the need for uncomplicated interpretation when presenting the findings to the CES
audience, SEM remains the appropriate analysis format for this study.
Delimitations and Limitations
Researcher’s Role
The researcher actively participated throughout the methodological process. With
assistance from committee members, the researcher designed the study to meet scholarly
rigor. Survey administration, data collection, and analysis were the sole purview of the
researcher with guidance from expert committee members. Any introduction of
researcher bias was unintentional and generally mitigated by committee oversight.
51
Limitations
The external and internal validity threats to this study were those common to
similar surveys in scope and detail. Of particular note, the scope of the survey which
included 37 questions and averaged 9 ½ minutes to complete was a modest concern for
internal validity. Though not evidenced, these length and timing challenges had the
potential to produce participant fatigue. Another limitation was the cross-sectional nature
of the analysis which mildly restricts generalizability. This survey was conducted among
Extension personnel at a specific moment in time and this snapshot does not fully capture
how their responses may change in different Extension seasons. A final limitation is the
inability to generalize the findings to all CES institutions nationwide due to a restricted
sample. This study’s sample only included the dominant CES organizational structure
paradigm thus rendering it unable to generate insights for CES paradigms that a) lack
middle leaders or b) use more complex administrative structures.
Summary
This study was designed to discover a broad-based understanding of the influence
of middle leaders on WLB culture and factors in CES. Survey research studies are
ideally suited to garner these broad perspectives, yet generally less adept at providing
specified data to researchers and organizational decision makers. With the winnowed
results generated from the design-based approach, this study pushed beyond some of
these traditional limitations of quantitative inquiry. In the forthcoming penultimate
chapter, these indirect and direct effects will be discussed in further detail. The final
chapter will conclude with recommendations for policy and practice.
52
Chapter IV
Results
Work-life balance (WLB) is a top concern among today’s workforce and has been
connected to job satisfaction, employee retention, and a host of other beneficial human
resource factors. Transformational supervisors possess the ability to influence positive
WLB among subordinate employees (Jiang, 2012; Munir et al., 2012). Does this ability
translate to the Cooperative Extension context? What impact does organizational culture
add to the relationship? The purpose of this survey research study was to investigate the
role of transformational leadership on WLB organizational culture and WLB in
Extension.
This study adds to the growing body of research on WLB culture by examining
three significant areas of inquiry: a) the influence of transformational leadership on WLB
culture; b) the influence of transformational leadership on WLB-related factors; and c)
the intervening influence of WLB culture on WLB factors. Three research hypotheses
governed the inquiry process:
1. The rated levels of transformational leadership among Extension middle leaders will
positively influence WLB culture among subordinates.
2. The rated levels of transformational leadership among Extension middle leaders will
positively influence WLB factors among subordinates.
3. The relationship between transformational leadership among Extension middle
leaders and WLB factors is strengthened by the intervening influence of WLB
culture.
53
This survey research study used an electronic survey of subordinates (i.e., agents)
in 13 geographically distributed Cooperative Extension System (CES) states securing at
least one state from each region. The survey was derived from three existing instruments
closely pertaining to the latent variables in question—transformational leadership, WLB
organizational culture, and WLB individual factors. Due to the interest in nested
relationships, design-based structural equation modeling was the analysis mode of choice.
The final survey sample included 1390 agents, a 53 percent response rate.
Analysis of the data was conducted and reported according to the American
Psychological Association Publications and Communications Board Task Force’s recent
recommendations for studies containing structural equation models (Appelbaum et al.,
2018; Hoyle & Isherwood, 2013). In accordance with these guidelines, this chapter
reports the performance of measures and models with specific attention to model
decision-making (i.e., to achieve optimal fit), reliability, and parameter estimates. The
chapter begins with descriptive statistics of the individual survey measures and the
approach to handling missing data.
Descriptive Statistics
Missing Data. Item level missing data ranged from 0.3 to 0.9% for TLI items, 0.0
to 0.2% for WLB-SAS items, and 0.4 to 4.7% for WLBCS items. Missing data were
addressed by including auxiliary correlates (i.e., district identification). This approach
was used to reduce bias and improve the efficiency of parameter estimates (Yuan, Yang-
Wallentin, & Bentler, 2012).
Transformational Leadership Inventory. Descriptive statistics of each item on
the TLI scale are presented in Table 4.1. The transformational leadership traits of high
54
performance expectations (Item 4; M = 3.99) and contingent reward (Item 7; M = 3.90)
scored highest while individualized support (Item 5; M =3.05) and intellectual
stimulation (Item 6; M = 2.88) scored lowest. Item responses on each item were
approximately normally distributed based on absolute values of univariate skewness and
kurtosis statistics not exceeding 1. Furthermore, item intraclass correlation coefficients
(ICCs) for TLI items ranged from .01 to .08, with an average of .04. This indicates that
on average 96% of the total item variance could be attributed by the within-district
individual differences in rated levels of transformational leadership, while differences
across (between) districts accounted for 4% of the total item variance.
Work Life Balance Self-Assessment Scale. Descriptive statistics of each item on
the WLB-SAS are presented in Table 4.2. Overall, Extension agents in this sample rated
themselves as experiencing mildly positive levels of work-life balance. The items I am in
a better mood at work because of my personal life (m = 4.61) and Personal life gives me
Table 4.1
Descriptive Statistics for Transformational Leadership Inventory (N = 1,390)
My supervisor…Variable (item number) M SD Skewness Kurtosis ICC
Inspires others with his/her plans for the future (1) 3.32 1.13 -0.38 -0.55 0.08
Leads by example (2) 3.79 1.08 -0.78 -0.04 0.07
Develops a team attitude and spirit among employees (3) 3.73 1.15 -0.72 -0.29 0.05
Shows me that he/she expects a lot from me (4) 3.99 0.97 -0.94 0.59 0.05
Treats me without considering my personal feelings* (5) 3.05 1.12 0.94 -0.12 0.01
Has ideas that have forced me to rethink some of my own ideas (6) 2.88 0.89 -0.18 0.18 0.04
Gives positive feedback when I perform well (7) 3.90 1.11 -0.90 0.04 0.01
Note. ICC = intraclass correlation coefficient. Items of this scale ranged from 1 (Never ) to 5 (Always ).*Reverse coded to ensure that higher values were associated with higher confidence levels.
55
energy for my job (m = 4.42) scored highest while I find it hard to work because of
personal matters (m = 2.18) and My personal life drains me for work (m = 2.03) scored
lowest. Item responses on each item were approximately normally distributed based on
absolute values of univariate skewness and kurtosis statistics not exceeding 1.
Furthermore, item ICCs for WLB-SAS items ranged from .01 to .10, with an average of
.05. This indicates that on average 95% of the total item variance could be attributed by
the within-district individual differences in self-rated levels of work-life balance, while
differences across (between) districts accounted for 5% of the total item variance.
56
Work Life Balance Culture Scale. Descriptive statistics of each item on the
WLBCS are presented in Table 4.3. Overall, Extension agents in this sample rated their
organizations as having moderately positive work-life balance cultures. Most items
scored in a tightly clustered range while My supervisor is trained to promote the work-life
balance of employees (m = 2.49) stood apart on the low end. Item responses on each
item were approximately normally distributed based on absolute values of univariate
skewness and kurtosis statistics not exceeding 1. Furthermore, item ICCs for WLBCS
Table 4.2Descriptive Statistics for Work Life Balance Self Assessment Scale (N = 1390)
Variable (item number) M SD Skewness Kurtosis ICCMy job gives me energy to pursue personal activities (1) 3.87 1.42 0.09 -0.64 0.04
My job makes my personal life difficult* (2) 2.89 1.31 0.02 -0.16 0.10
I am in a better mood at work because of my personal life (3) 4.61 1.36 -0.35 -0.33 0.02
My work suffers because of my personal life* (4) 4.66 1.05 0.88 0.67 0.01
I neglect personal needs because of work* (5) 2.93 1.42 -0.10 -0.41 0.08
I find it hard to work because of personal matters* (6) 4.82 0.93 0.91 0.89 0.06
I miss personal activities because of work* (7) 3.10 1.34 0.11 -0.17 0.07
My personal life suffers because of work* (8) 3.33 1.46 0.21 -0.43 0.08
I am too tired to be effective at work* (9) 4.61 1.05 1.00 1.65 0.03
I put my personal life on hold for work* (10) 3.17 1.51 0.14 -0.51 0.10
My personal life drains me of energy for work* (11) 4.97 0.86 1.24 3.39 0.05
I struggle to juggle work and non-work* (12) 3.47 1.46 0.39 -0.14 0.01
Personal life gives me energy for my job (13) 4.42 1.30 -0.15 -0.40 0.03
I am happy with the amount of time for non-work activities (14) 3.69 1.52 0.11 -0.79 0.01
I am in a better mood because of my job (15) 4.24 1.32 -0.20 -0.23 0.04
Note. ICC = intraclass correlation coefficient. Items of this scale ranged from 1 (not at all ) to 7 (all the time ).*Reverse coded to ensure that higher values were associated with higher confidence levels.
57
items ranged from .01 to .04, with an average of .02. This indicates that on average 98%
of the total item variance could be attributed by the within-district individual differences
in rated levels of work-life balance culture, while differences across (between) districts
accounted for 2% of the total item variance.
Confirmatory Factor Analyses
Transformational Leadership Inventory (TLI). Table 4.4 includes the global
measures of fit for the TLI. Jacobs et al. (2013) postulated the TLI as a 1-factor model
but provided insufficient data for future researchers to follow. In this study, the Jacobs et
al. (2013) 1-factor model exhibited good global fit with the exception of RMSEA=.095
which was acceptable. Item level analysis of the standardized residuals suggested Item
5—‘My supervisor treats me without considering my personal feelings’—should be
removed. Though this reduced model exhibited good global fit across all benchmarks, it
reduced the instrument’s purpose. That is, although some residuals (e.g., Item 5) were
large in the original model, removing an item from a short instrument minimizes content
evidence for fully capturing TLI (i.e., all seven components of transformational
Table 4.3Descriptive Statistics for Work Life Balance Culture Scale (N = 1390)
Variable (item number) M SD Skewness Kurtosis ICCMy organization values measures to promote WLB among employees (1) 2.66 0.73 -0.44 0.05 0.01
My organization supports employees in balancing their professional and private lives (2) 2.69 0.74 -0.40 0.01 0.02
At my organization, employees are informed about programs/policies promoting WLB (3) 2.61 0.73 -0.25 -0.15 0.03
My supervisor sets a good example of WLB (4) 2.64 0.74 -0.34 -0.11 0.03
(New) My supervisor promotes WLB in oral or written communications (5) 2.65 0.74 -0.33 -0.11 0.01
My supervisor is trained to promote the WLB of employees (6) 2.49 0.76 -0.19 -0.38 0.04
Note. ICC = intraclass correlation coefficient. Items of this scale ranged from 1 (strongly disagree )to 4 (strongly agree) .
58
leadership theory) and could artificially increase model fit and sample specific results.
Overall, the original 1-factor CFA model provided the best available fit and purpose and
was retained for the SEM analysis.
For the retained model, coefficient omega, a measure of model-level internal
consistency, was .86.
Work Life Balance Self-Assessment Scale (WLB-SAS). Table 4.5 includes the
global measures of fit for the SAS. Hayman (2005) postulated the WLB-SAS as a 3-
factor model though did not provide adequate reporting of his exploratory factor analysis.
Subsequent researchers determined poor to good fit (Agha, Azmi, & Irfan, 2017; Orkibi
& Brandt, 2015) for the scale.
Given the scale validation inconsistency in the extant literature, three options
were considered in this study’s factor analysis. To rule out the possibility that a single
factor solution might be optimal, a 1-factor CFA was examined as the first option. It
exhibited universally poor global fit across all measures and was discarded. The second
option rendered a 3-factor CFA as originally proposed by Hayman (2005). Similar to the
eclectic results in the subsequent literature (Agha, Azmi, & Irfan, 2017; Orkibi & Brandt,
2015), the 3-factor CFA indicated acceptable (CFI = .919; RMSEA = .08) to good
(SRMR=.067) global fit. Given the continued weakness in scale performance, the third
analysis considered the recent literature on the impact of negative phrasing (Wang et al.,
Table 4.4
Model χ2 df p CFI RMSEA 90% CI SRMR1-factora 189.631 14 < .001 .967 .095 [.083, .107] 0.0491-factor without item 5 42.136 9 < .001 .994 .052 [.036, .068] 0.023aDenotes model retained for final mediation analysis.
Global Measures of Fit for 7-item Transformational Leadership Inventory in a Sample of Extension Agents (N = 1,390)
59
2018) and the benefits of bi-factor analysis in these circumstances (Toland et al., 2017;
Rodriguez, Reise, & Haviland, 2016). The bi-factor analysis loaded the negatively
phrased items onto one factor and the positively phrased items onto a second factor. This
bi-factor analysis generated spurious results (e.g., negative variance); therefore, the
results were neither reported below nor considered as an option for the final model.
Overall, the 3-factor CFA model provided the best available fit and was retained for the
SEM analysis.
For the retained model, coefficient omega, a measure of model-level internal
consistency, was .94 (WIPL), .80 (PLIW), and .71 (WPLE).
Work Life Balance Culture Scale (WLBCS). Table 4.6 includes the global
measures of fit for the CS. Nitzsche et al. (2014) postulated the WLBCS as a 5-item, 1-
factor model with standard error correlations between two item pairs. Notably, their
unmodified 1-factor analysis indicated very poor fit. Subsequent research (MacDuff,
2017) has yet to validate this approach.
Given the WLBCS’s recency and its lack of subsequent validation in the extant
literature, four options were considered in this study’s factor analysis. To rule out the
original finding by Nitzsche et al. (2014) that a single factor solution was poor, a 1-factor
CFA was examined as the first option. It performed better than the original literature
would suggest with acceptable CFI = .915, poor RMSEA = .16, and good SRMR = .051.
Table 4.5
Model χ2 df p CFI RMSEA 90% CI SRMR1-factor 2150.737 90 < .001 .782 .128 [.124, .133] 0.1083-factora 853.649 87 < .001 .919 .080 [.075, .085] 0.067Note. Correlations for the 3-factor model were .70 [WIPL : WPLE], .40 [WIPL : PLIW], .38 [PLIW : WPLE].aDenotes model retained for final mediation analysis.
Global Measures of Fit for 15-item Work Life Balance Self Assessment Scale in a Sample of Extension Agents (N = 1,390)
60
The second option tested the Nitzsche et al. (2014) corrected model with correlated
residuals (i.e., item five with item six, item six with item four) and found universally
good global fit. Local fit statistics were poor (e.g., high standardized residuals) and with
the sample-specific nature of this analysis type which makes future replication difficult,
this model option was discarded.
Anticipating that insufficient fit might exist in the original 5-item scale, a sixth
survey item was added relating to the existing supervisor culture in Extension: my
supervisor promotes WLB in oral or written communications. Similar CFA procedures
were followed from above, and indicated relatively poor fit in both the 1-factor and
modified 1-factor analyses. Overall, the original 5-item, 1-factor CFA model provided
the best available fit and was retained for the SEM analysis.
For the retained model, coefficient omega, a measure of model-level internal
consistency, was .85.
Combined CFA. Figure 4.1 includes the global measures of fit for the best fitting
model used in the SEM analysis. The chi-square test statistic was 1,866.533 (314), CFI =
.917, RMSEA = .06 (90% CI [.057, .062]), and SRMR = .062. Collectively these global
measures of fit indicate acceptable fit at best. Good local fit was also present.
Table 4.6
Model χ2 df p CFI RMSEA 90% CI SRMR1-factor (5-item)a 190.187 5 < .001 .915 .164 [.144, .184] 0.051Corrected model (5-item) 12.495 3 .006 .996 .048 [.023, .077] 0.0141-factor (6-item) 520.515 9 < .001 .828 .203 [.188, .218] 0.064Corrected model (6-item) 407.448 7 < .001 .865 .203 [.187, .220] 0.070aDenotes model retained for final mediation analysis.
Global Measures of Fit for Work Life Balance Culture Scale in a Sample of Extension Agents (N = 1,390)
61
SEM Results
H1: The rated levels of transformational leadership among Extension middle
leaders will positively influence WLB culture among subordinates. Figure 4.1
includes the relationship between the TLI and Culture variables. The listed standardized
parameter estimate is .52 (SE = .03) and unlisted unstandardized parameter estimates is
.35 (SE = .02). The standardized parameter estimate is significant at the p <. 01 level.
The standardized parameter estimate indicates a moderately positive relationship
whereby 52% of the variance in Culture can be explained by the variance in TLI.
Hypothesis 1 performed as predicted.
Transformational leadership of middle leader
Work-life balance culture
WIPL.52 .63
Figure 4.1. Results for the mediation model depicting the relationships among transformational leadership, work-life balance culture, and work-life balance factors (WIPL: work interference with personal life; PLIW: personal life interference with work; WPLE: work personal life enhancement). Fit statistics: χ2 (df = 314, N = 1390) = 1866.533; P = .001; comparative fit index = .917; root mean square error of approximation = 0.060 (90% confidence interval: 0.057, 0.062); standard root mean square residual = .062. Unless noted (n.s. = not significant; * = significant at p < .05.) all paths are statistically significant at p < .001
PLIW
WPLE
-.06*
.02 n.s.
.08
.24
.62
.32
.30
.52
62
H2: The rated levels of transformational leadership among Extension middle
leaders will positively influence WLB factors among subordinates. Figure 4.1
includes the relationship between TLI and three WLB factor variables. For the WIPL
relationship, the listed standardized parameter estimate is -.06 (SE = .03) and unlisted
unstandardized parameter estimate is -.07 (SE = .03). The standardized parameter
estimate is significant at the p < .05 level (p = .034), but the linear relationship between
TLI and WIPL is minimal. For the PLIW relationship, the listed standardized parameter
estimate is .02 (SE = .03) and unlisted unstandardized parameter estimate is .01 (SE =
.03). The standardized parameter estimate is not significant (p = .626). For the WPLE
relationship, the listed standardized parameter estimate is .08 (SE = .03) and unlisted
unstandardized parameter estimate is .09 (SE = .03). The standardized parameter
estimate is significant at the p < .01 level, but the linear relationship between TLI and
WPLE is minimal. Viewed collectively, the three WLB factors are negligibly influenced
by TLI based on the standardized coefficients; thus, Hypothesis 2 did not perform as
predicted.
H3: The relationship between transformational leadership among Extension
middle leaders and WLB factors is strengthened by the intervening influence of
WLB culture. Results showed a statistically significant indirect effect for Culture for the
relationship TLI and WIPL (standardized indirect effect estimates=0.323 [95% CI: 0.280,
0.366]). All CIs were calculated as 95% bias-corrected bootstrap intervals based on 1000
resamples. Similarly, results showed a statistically significant indirect effect for Culture
for the relationship TLI and WPLE (standardized indirect effect estimates=0.328 [95%
CI: 0.291, 0.367]). Finally, results showed a statistically significant indirect effect for
63
Culture for the relationship TLI and PLIW (standardized indirect effect estimates=0.125
[95% CI: 0.082, 0.169]). Viewing the data collectively, Hypothesis 3 performed as
predicted.
Summary
This chapter provided analysis of data from a nationwide survey of Extension
agents conducted in the winter of 2018. Via three primary instruments, the survey asked
agents to rate transformational leadership levels among supervisors and their
organization’s WLB culture, and self-rate personal levels of three work-life balance
factors. The study’s three primary instruments were independently analyzed for global
and local fit and the best available model was retained for the final structural equation
model analysis. Resulting SEM analysis suggested transformational leadership
moderately influences Extension’s WLB culture and negligibly influences WLB factors
among agents. Additionally, WLB culture was found to exhibit a light to moderately
positive influence on various WLB factors.
In the final chapter, results of this study are discussed in both an Extension and
broader research context. The important role of organizational culture factors
prominently. Study limitations and generalizability of the findings are presented.
Considerations for future researchers and Extension leaders are also discussed.
64
Chapter V
Discussion
This study explored the influence of transformational leadership on work-life
balance culture and factors. Work-life balance has been shown to be a key factor in
employee performance, satisfaction, and retention (Kossek & Ozeki, 1998). Improving
work-life balance among employees has become a priority for both private and public
sector employers. Cooperative Extension became concerned with the overwork and
work-life imbalance of its employees as early as 1981 (Ensle, 2005). Since then many
self-help seminars and work-life policies have been offered to reduce this phenomenon
(Fetsch & Kennington, 1997). As Kutilek, Conklin, and Gunderson (2002) discovered,
Extension’s organizational culture remained unsupportive of work-life balance. This led
the team to assert the importance of culture change at the leadership level, and posit
transformational leadership as the appropriate framework to generate this long overdue
change. Greater understanding of the role leaders play in forging a more supportive
organizational culture could empower Extension decision-makers to mitigate the ongoing
effects of work-life imbalance.
Purpose of the Study
The purpose of this survey research study is to add to the knowledge base on
WLB organizational culture, specifically as it relates to the influence of transformational
middle leaders in CES. Positive WLB culture is a key indicator of employee satisfaction,
retention, and social health as well as organizational creativity and productivity. Its
absence is detrimental to both organizations and employees. This study will assess WLB
65
culture and factors in CES and the role transformational middle leaders play in forging a
positive WLB culture.
Research Hypotheses
Based on the review of relevant literature on transformational leadership,
organizational culture, and work-life balance as well as the purpose of this study, the
following research hypotheses directed the analysis of data:
1. The rated levels of transformational leadership among Extension middle leaders
will positively influence WLB culture among subordinates.
2. The rated levels of transformational leadership among Extension middle leaders
will positively influence WLB factors among subordinates.
3. The relationship between transformational leadership among Extension middle
leaders and WLB factors is strengthened by the intervening influence of WLB
culture.
This survey research study analyzed a nationwide survey of agents from 13
separate state Cooperative Extension Service systems. Independent variables were work-
life balance culture which included both organizational and supervisory components as
well as work-life balance factors which included items related to both interference and
enhancement. The dependent variable was levels of transformational leadership of
district directors as rated by Extension agents. Existing instruments were used to
measure all three variables in the study.
Organization of the Chapter
This chapter will begin with a discussion of study findings as well as the
contribution of the study to Extension administrators, leadership researchers, and work-
66
life balance scholars. Limitations will be presented, recommendations provided for
policy, practice, and research followed by final conclusions. The discussion will be
organized by the three research hypotheses.
Discussion of Findings
Major Findings
This study found transformational middle leaders significantly and positively
influence the work-life balance culture in the Cooperative Extension Service. However,
the rated levels of transformational leadership among Extension middle leaders exhibited
little influence on agents’ work-life balance factors. The limited overall influence of
transformational leadership suggests organizational culture is the more effective
mechanism for improving work-life balance in Extension. An intervention analysis
verified this important indirect effect influence of work-life balance organizational
culture. More detailed findings by research hypothesis are discussed below.
Research Hypothesis 1. The rated levels of transformational leadership among
Extension middle leaders will positively influence WLB culture among subordinates.
Findings from this study indicate transformational leadership had a significant and
moderately positive influence on WLB culture. In this study, 52% of the variance in
WLB culture was explained by the variance in transformational leadership.
These findings are consistent with the limited Extension literature exploring WLB
organizational culture and transformational leadership. In an effort to improve employee
outcomes, Kutilek, Conklin, and Gunderson (2002) assert the necessity for system-wide
improvement at the leadership level in the pursuit of organizational culture change. They
67
specifically point to the transformational leadership framework as the ideal framework
for influencing a more positive WLB culture.
A limited follow-up study in Tennessee (Elizer, 2011) fortified the assertion made
by Kutilek, Conklin, and Gunderson (2002). In this study transformational leadership
was found to be the best framework for advancing positive employee outcomes (e.g., job
satisfaction) at the local level. On a more comprehensive scale, the current study
continued this line of inquiry at the next level in the scalar chain by identifying a
beneficial link between transformational district-level leaders and WLB culture. This
suggests multiple levels of Extension’s leadership structure play a role in improving
WLB culture. Further inquiry into each leadership level’s unique contribution may
provide additional culture-support mechanisms for employees.
Research Hypothesis 2. The rated levels of transformational leadership among
Extension middle leaders will positively influence WLB factors among subordinates.
The current study revealed a mixed array of results in the influence of three WLB
factors by transformational leadership. In regards to the a) Work Interference with
Personal Life and b) Work Personal Life Enhancement factors, rated levels of
transformational leadership provided a statistically significant but limited positive
influence (just 6-8% of the variance explained). In regards to the Personal Life
Interference with Work factor, transformational leadership did not provide a significant
influence.
The limited influence of leaders (without culture) is unsurprising given the tone of
the extant literature. In Kossek and Ozeki’s (1998) early review of WLB policy
adoption, they found leaders’ communication of policies was not enough to improve
68
employee outcomes (e.g., reduced work-life conflict, improved job satisfaction).
Similarly, Haar (2003) found limited leader influence via policy on employee turnover
intention.
Seeking to explain this inability among leaders to motivate beneficial employee
policy adoption, Friedman and Greenhaus (2000) assert employees must find the policies
useful. Lewis (2001) continued this more employee-focused discussion by noting that
effective WLB policy adoption often hinged upon organizational culture. The current
study’s findings confirm this unbreakable linkage between leader, organizational culture,
and employee experience (Todd & Binns, 2013; Lewis, 1997).
Research Hypothesis 3. The relationship between transformational leadership among
Extension middle leaders and WLB factors is strengthened by the intervening influence of
WLB culture.
This study found a significant and moderate indirect effect for transformational
leadership on Work Interference with Personal Life (WIPL) and Work Personal Life
Enhancement (WPLE) via WLB culture. It found a significant and mild indirect effect
for transformational leadership on Personal Life Interference with Work (PLIW) via
WLB culture. Collectively, the relationship between transformational leadership and
these WLB factors was strengthened by the intervening influence of WLB culture.
This finding is consistent with Lewis’s (2001) seminal claim that WLB policy
adoption is enhanced by a supportive organizational culture. This culture is evident in
organizations that offer three essential elements: supervisor support, schedule control,
and career expectations (Thompson, Beauvais, & Lyness, 1999). Supportive supervisors
help employees face new work challenges and provide realistic expectations for job
69
performance. These supervisors also support short and long term career development
goals of the employee (Kram, 1995). Employees enjoy schedule control when they
perceive that enough of their daily work schedule is within their scope of control. Norms
of transparent communication, flexible scheduling, and performance evaluation based
upon productivity rather than proximity (i.e., time in the office) are important factors in
this pillar.
The final pillar indicative of a positive WLB organizational culture relates to
career expectations. Specifically, the performance management process must be linked
to positive WLB cultural elements rather than penalizing employees for using allotted
vacation or starting a family (Auster & Prasad, 2016; Moen & Roehling, 2005; Bailyn,
1993). Extension administrators should ensure these three pillars of positive WLB
culture are evident in order to attain the beneficial outcomes of well-balanced employees.
Contribution of the Study to the Field
Studies in the field of work-life balance have consistently determined its
importance for employee performance, satisfaction, and retention. The influence of
supervisors on such positive organizational outcomes has also been well researched, but
the specific influences of a) the Extension leadership context and b) middle leaders on
WLB factors and culture have not been rigorously pursued. This study examined these
influences to help researchers and Extension administrators develop strategies to
strengthen work-life balance culture among current and future employees.
With the relationship of WLB and CES leader influence well established in the
qualitative Extension literature (Forstadt & Fortune, 2016; Strong & Harder, 2009;
Thomson et al., 1987), Creswell (2014) suggests rigorous supporting studies from the
70
quantitative sphere become newly valuable for advancing the field. Prior to this study, no
Extension researchers have explored this relationship with advanced analytical
techniques or large national samples. The most promising—a Colorado study discussing
employee burnout, organizational culture, and leadership—constrained itself to
descriptive analyses (Harder, Gouldthorpe, & Goodwin, 2015). This followed an earlier
look at organizational effectiveness indicators and WLB which employed similar
descriptive analyses (Boltes, Lippke, & Gregory, 1995). Extension’s research tendency
of sharing results in an easily understandable manner (i.e., descriptive statistics) weakens
the ability to discuss variable impact and relationship. In an effort to advance CES
understandings of WLB and the influence of middle leaders, this study pushed beyond
descriptive analyses.
Beyond its importance for elevating inquiry within the Extension context, this
study generated several findings of interest to leadership, organizational culture, and
work-life balance researchers. First, this study confirmed findings that leaders influence
organizational culture (McCoy, Newell, & Gardner, 2013; Lewis, 2001). Specifically
transformational middle leaders account for a moderate level of influence fostering WLB
culture among subordinates. Second, by demonstrating negligible transformational
leadership influence on WLB factors, this study failed to confirm findings achieved in
studies of similar professions such as athletic training (Mazerolle, Goodman, & Pitney,
2015) and research faculty (Ward & Wolf-Wendel, 2005). This result is somewhat less
surprising given the mixed results in large sample studies (Jiang, 2012; Munir et al.,
2012). Finally, Komives and Dugan (2010) encouraged transformational leadership
researchers to study more than the one-to-one relationship between supervisor and
71
subordinate outcomes. This study was the first to consider the intervening influence of
organizational culture on WLB factors—finding a mild to moderate indirect effect. The
current study confirms the essential role of organizational culture in advancing positive
employee outcomes and further study of this phenomenon is warranted.
Limitations of the Study
Though prevalent in all research, limitations for this study must be discussed.
First, data for this study were collected in January-February 2018. This created findings
of a cross-sectional nature. Cross-sectional results describe a study group’s beliefs,
opinions, or judgments at a specific moment in time. Given this study’s timing and topic,
seasonal influences such as the winter blues and reduced vacation-taking may have
impacted participant results. Similarly, with the annual performance review process fresh
in the minds of some participating agents, ratings of transformational leadership levels
may have been affected.
Additionally, there are Extension populations this study did not consider. Middle
leaders in roles such as regional or district specialist were not the focus of the
investigation. The influence of co-workers at other levels in the organization (i.e.,
county-based, state-based) were also not addressed. Small states without a middle leader
structure were excluded (see Table 3.1). Among Extension administrators hoping to use
this study to advance workplace culture or leadership initiatives, findings should be
considered within this limited organizational context.
Beyond the Extension context, these findings contribute to the literature on WLB
culture in well-educated, creative professions. These findings are not representative of
WLB culture in blue collar organizations, organizations employing lower class citizens,
72
or non-Western societies, a persistent shortcoming in the field recently illuminated by
Warren (2017). Further, the complex, community-based nature of Extension’s work
reduces the possibility of replacement by artificial intelligence (Frey & Osborne, 2017).
Thus WLB is likely to remain a critical issue to the all-human workforce of Extension
longer than more replaceable worker paradigms.
Finally, the dependent variable reflects modern, transformational understandings
of leadership built on self-awareness, collaboration, transparency, productivity as a result
of employee care and development, and enhancing the common good (Komives &
Dugan, 2010). Though transformational leadership serves as a broad umbrella for
multiple employee-focused leadership frameworks, the characteristics are generally the
same (Puccio, Murdock, & Mance, 2007; Northouse, 2004). These new leadership
theories diverge significantly from conventional understandings which were
transactional, authority-based, and command-and-control. Thus, transferability of
findings from this study is limited to organizations leading from within the
transformational framework or those that are in the process of migrating to this
framework.
Implications
Recommendations for Policy and Practice
Leadership influence. A comprehensive review of transformational leadership’s
influence on various employee well-being factors found a generally positive influence
over a twenty-five year period (Arnold, 2017). The current study found a moderately
positive influence for transformational leadership on WLB culture and lessened direct
effect on WLB factors.
73
As more and more employers migrate toward the transformational leadership
framework, the influence of intervening variables (e.g., culture) will continue to grow in
importance (Arnold, 2017). A survey of over 300 upper-level universities notes that a
positive WLB culture is not only a key ingredient inspiring greater higher education
employee performance, but the most underleveraged as well (Mooney, 2013). Extension
systems that wish to be leading centers of creative problem solving must leverage a
positive WLB culture.
Leadership training. On the WLBCS instrument, the question my supervisor has
been trained to promote work-life balance scored significantly lower than any other
measure on the scale. Given the importance of WLB for employers, training middle
leaders to systemically promote positive WLB behaviors warrants a significant place at
the table in leadership training programs. Rather than being perceived as a topic for
disadvantaged or deficient workers, this training must service all employees (Kossek,
Lewis, & Hammer, 2010).
Untrained leaders mistakenly perceive productivity and WLB as oppositional
forces, leading them to influence subordinates against adopting positive WLB behaviors
(Todd & Binns, 2013). When subordinates perceive leader ambivalence toward positive
WLB culture, behavioral adoption decreases (Eaton, 2003). Employees need a clear and
consistent message; thus, CES should ensure middle leaders understand the benefits of a
positive WLB culture and are trained in its promotion. Further, the performance
appraisal of middle leaders should adequately reflect the ability to instill this WLB
culture among subordinates (Kossek et al., 2010). Finally, as evidenced by the high
number of non-respondents (n = 62) to the item in question, Extension administrators
74
would do well to communicate with employees that this topic has been “trained into” the
system’s middle leaders. This action would indicate administration’s priority attention to
WLB within the organization.
Extension leadership improvement. Though mean summative transformational
leadership scores were a little above average (m = 23.5), item-level means in the current
study indicate individualized support and intellectual stimulation need improvement in
the Extension middle leader context. Individualized support could be improved by
following the example of several recent state Extension systems (e.g., Wisconsin,
Michigan) that have reduced the number of agents supervised per middle leader thereby
enhancing the one-on-one time available for the coaching and mentoring relationship.
For states unable to use a more diffused leadership model, more time-focused attention
by leaders on agent check-up conversations should become a greater priority in the
leader’s portfolio. Intellectual stimulation could be similarly improved by more time
spent in the coaching relationship. Additionally, an institution-wide shift at professional
training in-services toward transformational rather than transactional learning topics
would promote more creative and meaningful professional development sessions among
the employee base.
American policy. Halpern (2005) describes work-life balance as a key indicator
of a vigorous and well-functioning society. Despite the considerable supporting evidence
discussed throughout this paper, the United States lags far behind other industrialized
nations with regard to work-life support at the government level (Anderson, Swan, &
Lewis, 2017; Esping-Anderson, 1996). Though it should be an important policy concern
of the state (Slaughter, 2015), in America the onus for change falls to benevolent
75
organizations which understand the value a positive WLB culture brings for both
employer and employee.
Analysis of top companies by Martel (2002) finds supervisors are the key to
helping employees understand and commit to the organization’s culture. The current
study confirms the supervisor’s importance in the WLB culture-building process. Thus,
once again, the selection and training of leaders is critical to WLB cultural norming. In
the near term American policy context, these leaders and the organizations they serve will
be the primary drivers toward an era of positive work-life balance.
Recommendations for Future Research
Instrumentation. Some of the rationale for choosing the three instruments
employed by this study related to participant completion concerns. Previous research
indicates that length of electronic survey time should be kept to 15 minutes or less to
ensure robust participant completion (Monroe & Adams, 2012). The average completion
time for this study’s survey was 9 ½ minutes; subsequently, the level of missing data
averaged less than 1% among all item responses. This exceptionally low level of missing
data suggests that lengthier, more established instruments might have been used without
dramatically increasing missing data issues. The WLB factor and culture-measuring
instruments were the most in need of replacement; however, the best available measures
of these two latent variables were already used in the current study. Given the inability
of these two instruments to generate consistently good fit in the literature, future
researchers should investigate their advanced psychometric properties and provide
improvement solutions for the field. These two latent variables are too important to be
studied with marginally suitable instruments.
76
The Jacobs et al. (2013) Transformational Leadership (Behavior) Inventory was
the best performing measure in the current study, but improvement remains available.
Items five and six (i.e., indicators for the transformational leadership attributes of
individualized support and intellectual stimulation) exhibited extremely low coefficients
of determination and item five produced abnormally high standardized residuals. Future
researchers should consider better options for these two indicators from the longer,
original inventory by Podsakoff et al. (1990). Exploratory factor analyses of a new, 7-
item TLI should be conducted until suitable replacements are generated.
Broader influences. Kossek, Lewis, and Hammer (2010) remind that WLB
cultural support derives from the organization’s policies and procedures as well as
relational support from supervisors and colleagues. The integration of these two
dynamics is essential for mainstream adoption of WLB initiatives. Given this study’s
findings that rated levels of transformational leadership among middle leaders negligibly
influence WLB factors among agents, the influencing role of other colleagues should be
further investigated particularly within the scope of organizational culture. Future
researchers should consider two related lines of inquiry, including a) which leadership
level (i.e., colleagues, office mates, middle leaders, state-level leaders) has the most
influence on WLB culture and WLB factors and b) what mechanisms will support
developing/training those influencers?
Further, because this study used three measures to investigate the latent variables
of interest, extracting causal claims would have been dubious. Given the importance of
the WLB culture variable, future researchers interested in making causal connections
about culture may wish to explore this measure independently. Making connections
77
regarding specific enhancers and detractors of WLB organizational culture would be an
important discovery for the field of WLB research.
Extension context. At one time Extension was on the cutting-edge of WLB
research. Ensle (2005) found an Illinois Extension initiative in the early 1980s which
sought to address employee challenges associated with work and family. Multiple
research-based policy initiatives developed through the late 1990s (Fetsch & Kennington,
1997), but since then these initiatives have slowed in the literature. Further, CES leaders
have known since a 1994 Ohio study that when they ignore WLB issues, employees quit
(Ensle, 2005). Why the limited ongoing research base? Rather than a case of exhausting
the literature, CES fell into the trap discussed earlier: belief that policy and employee
choice are sufficient to move the needle on WLB issues. This study provides a one link
to better understanding the culture and leadership components. Further CES studies on
the successful modification of organizational culture, by leaders at all levels of the
organization, are warranted.
Unlike the past when most leadership structure changes were dictated by
government funding crises, this is a ripe era for investigating employee-centric leadership
moves in Extension. New CES leadership paradigms are springing up across the nation
to improve support of Millennial employee coaching needs via more diffused leadership
structures (e.g., Wisconsin, Ohio) or program area-aligned models (e.g., Pennsylvania,
Iowa). The common thread of migrating toward employee-centered, transformational
leadership frameworks is promising. As several other Extension leaders confided their
intention to change leadership structures within the next few years, Extension researchers
78
should examine the merits of these recent structural reorganizations to find replicable
‘best practice’ models for others to follow.
Conclusion
This study found transformational middle leaders significantly and positively
influence the work-life balance culture in the Cooperative Extension Service. The rated
levels of transformational leadership among Extension middle leaders exhibited less
direct influence on agents’ work-life balance factors such as work interference with
personal life, personal life interference with work, and work-personal life enhancement.
Though still a significant relationship among the latter two factors, the minimal overall
influence by transformational leadership suggests organizational culture is the more
effective mechanism for improving work-life balance in Extension. An intervention
analysis verified this important indirect effect influence of organizational culture.
Following the plea of Komives and Dugan (2010) who advised that
transformational leadership studies need to pursue the role of organizational culture, this
study found culture to be the defining element. This was a critical finding because too
often employees are tasked with navigating their own work-life balance needs without
consideration of the broader organizational culture. This study confirms that the leader
and organizational culture join together to forge an important alliance of support for
work-life balance among subordinates.
A supportive supervisor who promotes and models effective work-life balance
strategies is essential to this cultural transformation (Mazerolle, Goodman, & Pitney,
2015; Ward & Wolf-Wendel, 2005; Lewis, 2001). As the leader alters long-held
underlying assumptions of the organization (Schein, 1985) and fosters a more pro-WLB
79
culture, subordinates begin to adopt work-life balance strategies and policies. This study
suggests the need for further study of specific ways leaders foster positive work-life
balance culture.
80
APPENDIX A
INSTITUTIONAL REVIEW BOARD APPROVAL
81
APPENDIX B
ELECTRONIC SURVEY
Work Life Balance 2018
Start of Block: Default Question Block
Q1 Introduction: Time is a valuable commodity. The irony of asking for a little bit of your time to complete a survey on work-life balance is not lost on me! As a fellow Extension agent/educator, I know that many surveys come across our desks in a given year so I have done my best to streamline this survey to the bare essentials I need to complete my research. When you have 10 minutes to give, I would greatly appreciate you fully completing this survey. It will remain open for 3 weeks. The results of this study will a) help Extension leaders better understand work-life balance and b) inform the training and work of our middle leaders. Description: You will be asked to complete 6 brief electronic survey pages. It will take an estimated 10 minutes to complete. Pages 1-2 cover demographic items, pages 3-5 deal with the crux of this study’s investigation of Extension middle leaders and work-life balance, and page 6 offers several unique questions that will further inform this inquiry. Completing the entire survey will provide maximum benefit to the scope of inquiry. Published findings are expected in the fall of 2018. Thank you for your time. Notice: The completion of this study is optional and you may withdraw at any time. Though your state’s Extension director has encouraged your participation, completion of the study is not a requirement of your position. Should you choose to participate no identifying information will be collected or retained. You will receive no compensation. Please be aware, while we make every effort to safeguard your data, given the nature of online surveys, as with anything involving the Internet, we can never guarantee the confidentiality of the data while still en route to us. If you would like more information about this study prior to beginning, please contact a member of the research team (Tim Tanner, Candidate 740.942.8823 or Dr. Beth Rous, Advisor 859.257.6389). If you have any questions about your rights as a volunteer in this research, contact the staff in the Office of Research Integrity at the University of Kentucky between the business hours of 8am and 5pm EST, Mon-Fri. at 859-257-9428 or toll free at 1-866-400-9428. Ready to Begin? If you agree to participate in this study, you may click on the button below when you are ready to start the survey.
82
Q2 Directions: Please select the best response for each demographic item on the next 2 pages.
Q7 Years in current position (please round to nearest whole number)
0-5 (1)
6-10 (2)
11-15 (3)
16-20 (4)
21-25 (5)
26+ (6)
Q8 Gender
Female (1)
Male (2)
Transgender Female (3)
Transgender Male (4)
Gender Variant/Non-conforming (5)
Q9 Birth Year
1928-1945 (1)
1946-1964 (2)
1965-1980 (3)
1981-1996 (4)
83
Q11 Directions: Select the best response for each line. The 5-option scale ranges from “never” to “always.” The supervisor you are evaluating is your regional/district/area director, not your state program leader, specialists, or county director. (Penn State respondents: evaluate your Assistant Program Director.)
Never (1) A little of the time (2) Sometimes (3) Most of the
time (4) Always (5)
My supervisor inspires others with
his/her plans for the future. (1)
My supervisor leads by example. (2)
My supervisor develops a team
attitude and spirit among the
employees of our region/district/area.
(3)
My supervisor shows us that
he/she expects a lot from us. (4)
My supervisor treats me without
considering my personal feelings.
(5)
My supervisor has ideas that have
forced me to rethink some of my
own ideas. (6)
My supervisor gives positive feedback when I perform
well. (7)
84
Q12 Directions: Select the best response for each line. The 7-option scale ranges from “not at all” to “all the time.”
Not at all (1) Rarely (2) Occasionally
(3) Sometimes
(4) Frequently
(5) Usually
(6) All the
time (7)
My job gives me energy to
pursue personal activities
(1)
My job makes my personal
life difficult (2)
I am in a better
mood at work
because of my
personal life (3)
My work suffers
because of my
personal life (4)
I neglect personal
needs because of
work (5)
I find it hard to
work because of personal matters
(6)
I miss personal activities
because of
85
work (7)
My personal
life suffers because of
work (8)
I am too tired to be effective
at work (9)
I put my personal
life on hold for
work (10)
My personal
life drains me of
energy for work (11)
I struggle to juggle work and non-work
(12)
Personal life gives
me energy for my job
(13)
I am happy
with the amount of
time for non-work activities
(14)
I am in a better mood
because of my job
(15)
86
Q13 Directions: Select the best response for each line. The 4-option scale ranges from “strongly disagree” to “strongly agree.” The organization you are evaluating is your state’s cooperative extension system, not national extension. The supervisor you are evaluating is your regional/district/area director, not your state program leader, specialists, or county director. (Penn State respondents: evaluate your Assistant Program Director.)
Strongly disagree (1) Disagree (2) Agree (3) Strongly agree (4)
My organization values measures to promote work-life
balance among employees. (1)
My organization supports employees
in balancing their professional and private lives. (2)
At my organization, employees are informed about
programs/policies promoting work-life
balance. (3)
My supervisor sets a good example of work-life balance.
(4)
My supervisor promotes work-life balance in oral or
written communications.
(5)
My supervisor is trained to promote
the work-life balance of
employees. (6)
87
Q14 Directions: The questions on this final page provide additional context to this study and may assist Extension’s understanding of work life balance. If you have 2 more minutes to give, please complete the questions on this page. If this survey has already taken enough of your time, please scroll down to the bottom and push the forward arrow button whenever you are ready to finish.
Q15 Compared to my peers, my annual performance ratings are usually...
Below average (1)
Average (2)
Above average (3)
Well above average (4)
Q16 Which response best describes your home-life status?
Single with no parenting or eldercare obligations (1)
Single with light parenting or eldercare obligations (2)
Single with medium parenting or eldercare obligations (3)
Single with heavy parenting or eldercare obligations (4)
Married/partnered with no parenting or eldercare obligations (5)
Married/partnered with light parenting or eldercare obligations (6)
Married/partnered with medium parenting or eldercare obligations (7)
Married/partnered with heavy parenting or eldercare obligations (8)
Q17 How much sleep do you get on an average night?
More than needed (1)
Just the right amount (2)
Not quite enough (3)
Not nearly enough (4)
88
Q18 How much of your allotted vacation time do you use in an average year?
75% or more (1)
50-74% (2)
25-49% (3)
24% or less (4)
Q19 When you use vacation, how many consecutive days is the longest vacation you take? (Consider this question for an “average” year.)
9 or more business days (1)
6 to 8 business days (2)
3 to 5 business days (3)
0 to 2 business days (4)
Q20 In an average year, what vacation types do you use? (Check all that apply.)
▢ Family obligations (e.g., care for others, holiday gatherings, reunions) (1)
▢ Medical obligations (e.g., sick leave runs out so I use vacation time) (2)
▢ Home obligations (e.g., farm planting/harvesting, yardwork, house repair) (3)
▢ Religious or service obligations (e.g., overseas missions trip) (4)
▢ Bookend to an out-of-state conference (e.g., a trip to the Grand Canyon right after a conference in Las Vegas, a trip to Disney World right before a conference in Orlando) (5)
▢ “No strings attached” lengthy trip (e.g., week long fishing trip, 8-day cruise, two week road trip) (6)
▢ Other: please describe (7) ________________________________________________
89
Q21 What important activities, experiences, etc. do you forego in your non-work time as a result of work-based demands? (Type responses for up to 3 activities.)
Activity 1 (type in box) (1) ________________________________________________
Activity 2 (type in box) (2) ________________________________________________
Activity 3 (type in box) (3) ________________________________________________
Q22 Extension State (select one from dropdown menu)
▼ Arkansas (1) ... Texas A & M (20)
Q23 – 33 Skip L:ogic Display Individual State District Questions
If Extension State (select one from dropdown menu) = XXX
End of Block: Default Question Block
90
References
Abbott, J., De Cieri, H., & Iverson, R. D. (1998). Costing turnover: Implications of work/
family conflict at management level. Asia Pacific Journal of Human
Resources, 36(1), 25-43.
Agha, K., Azmi, F. T., & Irfan, A. (2017). Work-life balance and job satisfaction: An
empirical study focusing on higher education teachers in Oman. International
Journal of Social Science and Humanity, 7(3), 164-171.
Alban-Metcalfe, R. J., & Alimo-Metcalfe, B. (2000). The transformational leadership
questionnaire (TLQ-LGV): A convergent and discriminant validation study.
Leadership & Organization Development Journal, 21(6), 280-296.
Allen, T. D., Herst, D. E., Bruck, C. S., & Sutton, M. (2000). Consequences associated
with work-to-family conflict: A review and agenda for future research. Journal of
Occupational Health Psychology, 5(2), 278-308.
Anderson, D., Swan, J., & Lewis, S. (2017). Towards a triple agenda for work-life
balance beyond recession and austerity. In S. Lewis et al. (Eds.), Work-life
balance in times of recession, austerity and beyond (pp. 180-190). New York,
NY: Routledge, Taylor & Francis Group.
Angrist, J. D., & Pischke, J.-S. (2009). Mostly harmless econometrics: An empiricist's
companion. Princeton, NJ: Princeton University Press.
Appelbaum, M., Cooper, H., Kline, R. B., Mayo-Wilson, E., Nezu, A. M., & Rao, S. M.
(2018). Journal article reporting standards for quantitative research in psychology:
The APA publications and Communications Board task force report. American
Psychologist, 73(1), 3-25.
91
Archer, T. M. (2008). Response rates to expect from Web-based surveys and what to do
about it. Journal of Extension, 46(3), Article 3RIB3.
Argabright, K., McGuire, J., & King, J. (2012). Extension through a new lens: Creativity
and innovation now and for the future. Journal of Extension, 50(2), Article
2COM2.
Arnold, K. A. (2017). Transformational leadership and employee psychological well-
being: A review and directions for future research. Journal of Occupational
Health Psychology, 22(3), 381-393.
Astroth, K., Goodwin, J., & Hodnett, F. (2011). Servant leadership: Guiding Extension
programs in the 21st century. Journal of Extension, 49(3) Article 3FEA1.
Auster, E., & Prasad, A. (2016). Why do women still not make it to the top? Dominant
organizational ideologies and biases by promotion committees limit opportunities
for destination positions. Sex Roles, 75(5-6), 177-196.
Avolio, B. J., & Gardner, W. L. (2005). Authentic leadership development: Getting to the
root of positive forms of leadership. The Leadership Quarterly, 16(3), 315-338.
Bailyn, L. (1993). Breaking the mold: Women, men, and time in the new corporate world.
New York, NY: Free Press.
Bass, B. M. (1985). Leadership and performance beyond expectations. New York, NY:
Free Press.
Bass, B. M. (1998). Transformational leadership: Industrial, military, and educational
impact. Mahwah, NJ: Erlbaum.
Bass, B. M., & Avolio, B. J. (1994). Improving organizational effectiveness through
transformational leadership. Thousand Oaks, CA: Sage Publications.
92
Bass, B. M., & Riggio, R. E. (2006). Transformational leadership. Mahwah, NJ: Erlbaum
Associates.
Baum, C. F., Nichols, A., & Schaffer, M. E. (2010).Evaluating one-way and two-way
cluster-robust covariance matrix estimates. Paper presented at the BOS10 Stata
Conference, Boston, MA.
Bickel, J., & Brown, A. J. (2005). Generation X: Implications for faculty recruitment and
development in academic health centers. Academic Medicine: Journal of the
Association of American Medical Colleges, 80(3), 205-10.
Boltes, B. V., Lippke, L. A., & Gregory, E. (1995) Employee satisfaction in Extension: A
Texas study. Journal of Extension, 33(5), Article 5RIB1.
Boomsma, A., & Hoogland, J. J. (2001). The robustness of LISREL modeling revisited.
Structural equation models: Present and future. A Festschrift in honor of Karl
Jöreskog, 2(3), 139-168.
Burns, J. M. (1978). Leadership. New York, NY: Harper & Row.
Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS:
Basic concepts, applications, and programming. Mahwah, NJ: Erlbaum
Associates.
Carless, S. A., Wearing, A. J., & Mann, L. (2000). A short measure of transformational
leadership. Journal of Business and Psychology, 14(3), 389-406.
CheckMarket. (2015, February). What’s the best time to send a survey? CheckMarket
Tips n’ Tricks Blog. Retrieved from https://www.checkmarket.com/blog/survey-
invitations-best-time-send/
93
Coffey, B. S., Anderson, S. E., Shuming, Z., Yongqiang, L., & Jiyuan, Z. (2009).
Perspectives on work-family issues in China: The voices of young urban
professionals. Community, Work & Family, 12(2), 197-212.
doi:10.1080/13668800902778967
Corrigan, P. W., Diwan, S., Campion, J., & Rashid, F. (2002). Transformational
leadership and the mental health team. Administration and Policy in Mental
Health and Mental Health Services Research, 30(2), 97-108.
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods
approaches. Thousand Oaks, CA: SAGE Publications.
Deal, T. E., & Kennedy, A. A. (1982). Corporate cultures: The rites and rituals of
corporate life. Reading, MA: Addison-Wesley.
Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, mail, and mixed-mode
surveys: The tailored design method. Hoboken, N.J: Wiley & Sons.
Dueber, D. M. (2017). Bifactor Indices Calculator: A Microsoft Excel-based tool to
calculate various indices relevant to bifactor CFA models.
https://dx.doi.org/10.13023/edp.tool.01 [Available at
http://sites.education.uky.edu/apslab/resources/]
Eaton, S. C. (2003). If you can use them: Flexibility policies, organizational commitment,
and perceived performance. Industrial Relations, 42(2), 145-167.
Elizer, A. H. (2011). Are transformational directors required for satisfied agents? Journal
of Extension, 49(2) Article 2RIB1.
Ensle, K. M. (2005). Burnout: How does Extension balance job and family? Journal of
Extension, 43(3), Article 3FEA5.
94
Esping-Anderson, G. (1996). Welfare states in transition: National adaptations in global
economies. Thousand Oaks, CA: Sage.
Extension Committee on Organization and Policy. (2010). Leadership Advisory Council
report. Washington, DC: Association of Public and Land Grant Universities.
Extension Committee on Organization and Policy. (1981). Extension's role:
Strengthening American families. Lincoln, NE: University of Nebraska.
Fan, X., & Sivo, S. A. (2005). Sensitivity of fit indexes to misspecified structural or
measurement model components: Rationale of two-index strategy revisited.
Structural Equation Modeling, 12(3), 343-367.
Feeney, M. K., Bernal, M., & Bowman, L. (2014). Enabling work? Family-friendly
policies and academic productivity for men and women scientists. Science &
Public Policy, 41(6), 750-764.
Fetsch, R. J., Flashman, R., & Jeffiers, D. (1984). Up tight ain't right: Easing the pressure
on county agents. Journal of Extension, 22(3), Article 3FEA4.
Fetsch, R. J., & Pergola, J. (1991). Effective burnout prevention program. Journal of
Extension, 29(4), Article 4RIB6.
Fetsch, R.J., & Kennington, M.S. (1997). Balancing work and family in Cooperative
Extension: History, effective programs, and future directions. Journal of
Extension, 35(1), Article 1FEA2.
Fisher-McAuley, G., Stanton, J. M., Jolton, J. A., & Gavin, J. A. (2003). Modeling the
relationship between work/life balance and organizational outcomes. Paper
presented at the Annual Meeting of the Society for Industrial and Organizational
Psychology, Orlando, FL.
95
Forstadt, L., & Fortune, A. (2016). Personal sustainability: Listening to Extension staff
and observing organizational culture. Journal of Extension, 54(2), Article 2RIB1.
Fowler, F. J. (2002). Survey research methods. Thousand Oaks, CA: Sage Publications.
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are
jobs to computerisation?. Technological Forecasting & Social
Change, 114(1), 254-280.
Friedman, S. D., & Greenhaus, J. H. (2000). Work and family--allies or enemies? What
happens when business professionals confront life choices. Oxford, UK: Oxford
University Press.
Gallup Organization. (2006, January 12). Feeling good matters in the workplace. Gallup
Management Journal. Retrieved from
http://gmj.gallup.com/content/20770/Gallup-Study-Feeling-Good-Matters-in-
the.aspx
García-Morales, V. J., Jiménez-Barrionuevo, M. M., & Gutiérrez-Gutiérrez, L. (2012).
Transformational leadership influence on organizational performance through
organizational learning and innovation. Journal of Business Research, 65(7),
1040-1050.
Goodman, A., Mazerolle, S. M., & Pitney, W. A. (2015). Achieving work-life balance in
the National Collegiate Athletic Association Division I setting, part II:
Perspectives from head athletic trainers. Journal of Athletic Training, 50(1), 89-
94.
96
Greenhaus, J. H., Collins, K. M., & Shaw, J. D. (2003). The relation between work-
family balance and quality of life. Journal of Vocational Behavior, 63(3), 510-
531.
Greenleaf, R. K. (1977). Servant leadership: A journey into the nature of legitimate
power and greatness. New York, NY: Paulist Press.
Grover, S.L., & Crooker, K.J. (1995). Who appreciates family-responsive human
resource policies: The impact of family-friendly policies on the organizational
attachment of parents and non-parents. Personnel Psychology, 48, 271-288.
Guest, D. E. (2002). Perspectives on the study of work-life balance. Social Science
Information, 41(2), 255-279.
Haar, J. M. (2003). Commitment, support and turnover intentions as outcomes of work-
family conflict in New Zealand. New Zealand Journal of Applied Business
Research, 2(2), 29-39.
Halpern, D. F. (2005). Psychology at the intersection of work and family:
recommendations for employers, working families, and policymakers. The
American Psychologist, 60(5), 397-409.
Harder, A., Gouldthorpe, J., & Goodwin, J. (2015). Exploring organizational factors
related to Extension employee burnout. Journal of Extension, 53(2), Article
2FEA2.
Hayman, J. (2005). Psychometric assessment of an instrument designed to measure work
life balance. Research and Practice in Human Resource Management, 13(1),85-
91.
97
Hoyle, R. H., & Isherwood, J. C. (2013). Reporting results from structural equation
modeling analyses in archives of scientific psychology. Archives of Scientific
Psychology, 1(1), 14-22.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure
analysis: Conventional criteria versus new alternatives. Structural Equation
Modeling, 6, 1-55.
Igodan, O. C., & Newcomb, L. H. (1986). Are you experiencing burnout? Symptoms and
coping strategies for extension professionals. Journal of Extension, 24(1), Article
1FEA1.
Jacob, J. I., Bond, J. T., Galinsky, E., & Hill, E. J. (2008). Six critical ingredients in
creating an effective workplace. Psychologist-Manager Journal, 11(1), 141-161.
doi:10.1080/10887150801967704
Jacobs, C., Pfaff, H., Lehner, B., Driller, E., Nitzsche, A., Stieler-Lorenz, B., Wasem, J.,
& Jung, J. (2013). The influence of transformational leadership on employee well-
being. Journal of Occupational & Environmental Medicine, 55(7), 772-778.
Jansen, N. W., Kant, I. J., van, A. L. G., Kristensen, T. S., Swaen, G. M., & Nijhuis, F. J.
(2006). Work-family conflict as a risk factor for sickness absence. Occupational
and Environmental Medicine, 63(7), 488-94.
Jedlicka, A. (2007). Leadership and good work-life balance promote ethical
behavior. Federal Ethics Report, 14(8), 7.
Jiang, H. (2012). A model of work–life conflict and quality of employee–organization
relationships (EORs): Transformational leadership, procedural justice, and
98
family-supportive workplace initiatives. Public Relations Review, 38(2), 231-245.
doi:10.1016/j.pubrev.2011.11.007
Johnson, S. B. (2015). Whither leadership, whither Extension? Journal of Extension,
53(6), Article 6COM2.
Jones, F., Burke, R. J., & Ṿesṭman, M. (2006). Work-life balance: A psychological
perspective. Hove, UK: Psychology Press.
Jung, T., Scott, T., Davies, H. T. O., Bower, P., Whalley, D., McNally, R., & Mannion,
R. (2009). Instruments for exploring organizational culture: A review of the
literature. Public Administration Review, 69(6), 1087-1096.
Kanter, R. M. (1990). When giants learn to dance. New York, NY: Touchstone Book.
Katz, D., & Kahn, R. L. (1978). The social psychology of organizations. New York, NY:
Wiley.
Kay, F. M., Alarie, S., & Adjei, J. (2013). Leaving private practice: How organizational
context, time pressures, and structural inflexibilities shape departures from private
law practice. Indiana Journal of Global Legal Studies, 20(2), 1223-1260.
Keith, K. M. (2008). The case for servant leadership. Westfield, IN: The Greenleaf
Center for Servant Leadership.
Kelly, E., & Moen, P. (2007). Rethinking the clockwork of work: Why schedule control
may pay off at work and at home. Advances in Developing Human
Resources, 9(4), 487-506.
Kennington, M. S. (1988). Perceived life and job satisfaction levels of Colorado
Cooperative Extension agents [Research Report]. Ft. Collins, CO: Colorado State
University.
99
Kim, S., Kim, K., & Choi, Y. (2014). A literature review of servant leadership and
criticism of advanced research. International Journal of Social, Behavioral,
Educational, Economic, Business, and Industrial Engineering, 8(4), 1154-1157.
Kinman, G., & Jones, F. (2008). A life beyond work? Job demands, work-life balance,
and wellbeing in UK academics. Journal of Human Behavior in the Social
Environment, 17(1/2), 41-60. doi:10.1080/10911350802165478
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.).
New York, NY: Guilford Press.
Klun, S. (2008). Work-life balance is a cross generational concern - and a key to retaining
high performers at Accenture. Global Business and Organizational
Excellence, 27(6), 14-20.
Komives, S. R., & Dugan, J. P. (2010). Contemporary leadership theories. In R. A. Couto
(Ed.), The handbook of political and civic leadership (pp. 109–125). Thousand
Oaks, CA: Sage.
Kossek, E. E., & Lambert, S. J. (2005). Work and life integration: Organizational,
cultural, and individual perspectives. Mahwah, NJ: Lawrence Erlbaum
Associates.
Kossek, E. E., Lewis, S., & Hammer, L. (2010). Work-life initiatives and organizational
change: Overcoming mixed messages to move from the margin to the
mainstream. Human Relations, 63(1), 3-19.
Kossek, E. E., & Ozeki, C. (1998). Work-family conflict, policies, and the job-life
satisfaction relationship: A review and directions for organizational behavior-
human resources research. Journal of Applied Psychology, 83(2), 139-149.
100
Kram, K. E. (1985). Mentoring at work: Developmental relationships in organizational
life. Glenview, IL: Scott, Foresman and Company.
Kutilek, L. M., Conklin, N. L., & Gunderson, G. (2002). Investing in the future:
Addressing work/life issues of employees. Journal of Extension, 40(1), Article
1FEA6.
Lamm, A.J. (2011). Effect of organizational context on extension evaluation behaviors.
Retrieved from ProQuest Dissertation Abstracts. (3467579)
Lei, P.W., & Wu, Q. (2007). Introduction to structural equation modeling: Issues and
practical considerations. Educational Measurement: Issues and Practices 26(3),
33–43.
Lencioni, P. (2002). The five dysfunctions of a team. San Francisco, CA: Jossey-Bass.
Leuci, M. S. (2005). The role of middle leaders in fostering organizational learning in a
state Cooperative Extension Service. Retrieved from ProQuest Dissertation
Abstracts. (3235850)
Lewis, S. (2001). Restructuring workplace cultures: The ultimate work-family
challenge? Women in Management Review, 16(1), 21-29.
Lewis, S. (1997). ‘Family friendly’ employment policies: A route to changing
organizational culture or playing about at the margins? Gender, Work &
Organization, 4(1), 13-23.
Lewis, S., & Cooper, C. L. (1995). Balancing the work/home interface: A European
perspective. Human Resource Management Review, 5(4), 289-305.
Luke, J. S. (1998). Catalytic leadership: Strategies for an interconnected world. San
Francisco, CA: Jossey-Bass.
101
MacDuff, T. (2017). Improving workplace commitment to change: A test of impact
reflection and motivation on perceived commitment constructs (Honor’s thesis).
Retrieved from https://ir.lib.uwo.ca/psych_uht/28/
Mahaney, L., Sanborn, M., & Alexander, E. (2008). Nontraditional work schedules for
pharmacists. American Journal of Health-System Pharmacy, 65(22), 2144-2149.
Major, V. S., Klein, K. J., & Ehrhart, M. G. (2002). Work time, work interference with
family, and psychological distress. The Journal of Applied Psychology, 87(3),
427-36.
Mancl, L. A., & DeRouen, T. A. (2001). A covariance estimator for GEE with improved
small-sample properties. Biometrics, 57(1), 126-134.
Marsh, H.W., Hau, K-T., & Wen, Z. (2004). In search of golden rules: Comment on
hypothesis-testing approaches to setting cutoff values for fit indexes and dangers
of overgeneralizing Hu and Bentler’s (1999) findings. Structural Equation
Modeling, 11(3), 320-341.
Marston, C. (2007). Motivating the "what's in it for me?" workforce: Manage across the
generational divide and increase profits. Hoboken, NJ: Wiley & Sons.
Martel, L. (2002). High performers: How the best companies find and keep them. San
Francisco, CA: Jossey-Bass.
Martin, M., & Kaufman, E. (2013). Do job satisfaction and commitment to the
organization matter when it comes to retaining employees? Journal of Extension,
51(4), Article 4RIB1.
Mathews, M., Seguin, M., Chowdhury, N., & Card, R. T. (2012). A qualitative study of
factors influencing different generations of Newfoundland and Saskatchewan
102
trained physicians to leave a work location. Human Resources for Health, 10(1),
18-25. doi:10.1186/1478-4491-10-18
Mazerolle, S. M., & Gavin, K. (2013). Female athletic training students' perceptions of
motherhood and retention in athletic training. Journal of Athletic Training, 48(5),
678-684.
Mazerolle, S. M., Goodman, A., & Pitney, W. A. (2015). Achieving work-life balance in
the National Collegiate Athletic Association Division I setting, part I: The role of
the head athletic trainer. Journal of Athletic Training, 50(1), 82-88.
McCoy, S., Newell, E., & Gardner, S. (2013). Seeking balance: The importance of
environmental conditions in men and women faculty's well-being. Innovative
Higher Education, 38(4), 309-322. doi:10.1007/s10755-012-9242-z
McDonald, R. P. (1999). Test theory: A unified treatment. Mahwah, NJ: Lawrence
Erlbaum.
Moen, P., Kelly, E. L., & Hill, R. (2011). Does enhancing work-time control and
flexibility reduce turnover? A naturally occurring experiment. Social
Problems, 58(1), 69-98.
Moen, P., & Roehling, P. (2005). The career mystique: Cracks in the American dream.
Lanham, MD: Rowman & Littlefield Publishers.
Monroe, M. C., & Adams, D. C. (2012). Increasing response rates to Web-based surveys.
Journal of Extension, 50(6), Article 6TOT7.
Mooney, C. (2013, July 26). Leadership, work-life balance help make great
colleges. Chronicle of Higher Education, A4-A6.
103
Morse, R. S., Brown, P. W., & Warning, J. E. (2006). Catalytic leadership: Reconsidering
the nature of Extension’s leadership role. Journal of Extension, 44(2), Article
2FEA9.
Mumford, M. D., Zaccaro, S. J., Harding, F. D., Jacobs, T. O., & Fleishman, E. A.
(2000). Leadership skills for a changing world: Solving complex social problems.
The Leadership Quarterly, 11(1), 11-35.
Munir, F., Nielsen, K., Garde, A. H., Albertsen, K., & Carneiro, I. G. (2012). Mediating
the effects of work-life conflict between transformational leadership and health-
care workers' job satisfaction and psychological wellbeing. Journal of Nursing
Management, 20(4), 512-521. doi:10.1111/j.1365-2834.2011.01308.x
Muthén, B., & Muthén, B. O. (2009). Statistical analysis with latent variables. New
York, NY: Wiley.
Myers, K., & Sadaghiani, K. (2010). Millennials in the workplace: A communication
perspective on Millennials’ organizational relationship and performance. Journal
of Business Psychology, 25(2), 225-238.
Nardi, P. (2014). Doing survey research: A guide to quantitative methods (3rd ed.).
Boulder, CO: Paradigm Publishers.
Nitzsche, A., Jung, J., Kowalski, C., & Pfaff, H. (2014). Validation of the Work-Life
Balance Culture Scale (WLBCS). Work, 49(1), 133-142.
Northouse, P.G. (2004). Leadership: Theory and practice (3rd ed.). Thousand Oaks, CA:
Sage.
104
O’Brien, M. (1992). Changing conceptions of fatherhood. In U. Bjornberg (Ed.),
European parents in the 1990s: Contradictions and comparisons (pp. 171-180).
London, UK: Transaction.
Orkibi, H., & Brandt, Y. I. (2015). How positivity links with job satisfaction: Preliminary
findings on the mediating role of work-life balance. Europe's Journal of
Psychology, 11(3), 406-18.
Parasuraman, S., & Greenhaus, J. H. (1999). Integrating work and family: Challenges
and choices for a changing world. Westport, CT: Praeger.
Parasuraman, S., & Simmers, C. A. (2001). Type of employment, work-family conflict
and well-being: A comparative study. Journal of Organizational Behavior, 22(5),
551-568.
Patterson, J. M., & McCubbin, H. I. (1984). Minnesota county extension agents: Stress,
coping, and adaptation. St. Paul, MN: Family Stress and Coping Project.
Paxson, M., Howell, R., Michael, J., & Wong, S. (1993). Leadership development in
Extension. Journal of Extension, 31(1), Article 2IAW3.
Pearson, R. W., & Boruch, R. F. (Eds). (1986). Survey research designs: Towards a
better understanding of their costs and benefits. Berlin, Germany: Springer-
Verlag.
Penrose, C. (2017). The role of experienced educators in attracting and retaining new
educators. Journal of Extension, 55(4), Article 4COM1.
Perlow, L. A. (1995). Putting the work back into work/family. Group & Organization
Management, 20(2), 227-239.
105
Pfeffer, J. (1994). Competitive advantage through people: Unleashing the power of the
work force. Boston, MA: Harvard Business School Press.
Podsakoff, P. M., MacKenzie, S. B., Moorman, R. H., & Fetter, R. (1990).
Transformational leader behaviors and their effects on followers' trust in leader,
satisfaction, and organizational citizenship behaviors. The Leadership
Quarterly, 1(2), 107-142.
Poelmans, S. A. Y., Kalliath, T., & Brough, P. (2008). Achieving work-life balance:
Current theoretical and practice issues. Journal of Management &
Organization, 14(3), 227-238.
Puccio, G. J., Murdock, M., & Mance, M. (2007). Creative leadership: Skills that drive
change. Thousand Oaks, CA: SAGE Publications.
Rabe-Hesketh, S., Skrondal, A. and Zheng, X. (2012). Generalized multilevel structural
equation modeling. In Hoyle, R. (Ed.). Handbook of Structural Equation
Modeling. Guilford Press, pp. 512-531.
Ransome, P. (2007). Conceptualizing boundaries between 'life' and 'work.' International
Journal of Human Resource Management, 18(3), 374-386.
Rea, L. M., & Parker, R. A. (1992). Designing and conducting survey research: A
comprehensive guide. San Francisco, CA: Jossey-Bass.
Richman, A. L., Civian, J. T., Shannon, L. L., Jeffrey Hill, E., & Brennan, R. T. (2008).
The relationship of perceived flexibility, supportive work-life policies, and use of
formal flexible arrangements and occasional flexibility to employee engagement
and expected retention. Community, Work & Family, 11(2), 183-197.
doi:10.1080/13668800802050350
106
Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016). Applying bifactor statistical
indices in the evaluation of psychological measures. Journal of Personality
Assessment, 98(3), 223-37.
Rossiter, M. W. (1997). Which science? Which women? Osiris, 12, 169-185.
Rost, J. C. (1991). Leadership for the twenty-first century. New York, NY: Praeger.
Rowold, J., & Heinitz, K. (2007). Transformational and charismatic leadership:
Assessing the convergent, divergent and criterion validity of the MLQ and the
CKS. The Leadership Quarterly, 18(2), 121-133.
Ruble, S. (n.d.). In APLU Cooperative Extension Regions. Retrieved from
http://www.aplu.org/members/commissions/food-environment-and-renewable-
resources/board-on-agriculture-assembly/cooperative-extension-section/ecop-
members/regions.html
Sandmann, L. R., & Vandenberg, L. (1995). A framework for 21st century leadership.
Journal of Extension, (33)6, Article 6FEA1.
Schein, E. H. (1985). Organizational culture and leadership. San Francisco, CA: Jossey-
Bass.
Schieman, S., & Glavin, P. (2008). Trouble at the border? Gender, flexibility at work,
and the work-home interface. Social Problems, 55(4), 590-611.
Schor, J. (1991). The overworked American: The unexpected decline of leisure. New
York, NY: Basic Books.
Schwieder, D. (1993). Taking the university to the people: Seventy-five years of
cooperative extension. Ames, IA: Iowa State University Press.
107
Seevers, B., Graham, D., Gamon, J., & Conklin, N. (1997). Education through
Cooperative Extension. Albany, NY: Delmar.
Seger, J., & Hill, P. (2016). The future of Extension leadership is soft leadership. Journal
of Extension, 54(5), Article 5COM1.
Slaughter, A. M. (2015). Unfinished business: Women, men, work, family. New York,
NY: Random House.
Smeltzer, S. C., Cantrell, M. A., Sharts-Hopko, N. C., Heverly, M. A., Jenkinson, A., &
Nthenge, S. (2016). Psychometric analysis of the work/life balance self-
assessment scale. Journal of Nursing Measurement, 24(1), 5-14.
Smith, B. D. (2005). Job retention in child welfare: Effects of perceived organizational
support, supervisor support, and intrinsic job value. Children and Youth Services
Review, 27(2), 153-169.
Stapleton, L. M., McNeish, D. M., & Yang, J. S. (2016). Multilevel and single-level
models for measured and latent variables when data are clustered. Educational
Psychologist, 51(3-4), 317-330.
St. Pierre, T. L. (1984, May). The relationship between work and family life of county
extension agents in Pennsylvania [Abstract]. University Park, PA: Pennsylvania
State University.
Strong, R., & Harder, A. (2009). Implications of maintenance and motivation factors on
Extension agent turnover. Journal of Extension, 47(1), Article 1FEA2.
Thomas, L. T., & Ganster, D. C. (1995). Impact of family-supportive work variables on
work-family conflict and strain: A control perspective. Journal of Applied
Psychology, 80(1), 6-15.
108
Thompson, C. A., Beauvais, L. L., & Lyness, K. S. (1999). When work-family benefits
are not enough: The influence of work-family culture on benefit utilization,
organizational attachment, and work-family conflict. Journal of Vocational
Behavior, 54(3), 392-415.
Thompson, C., & Gregory, J. B. (2012). Managing millennials: A framework for
improving attraction, motivation, and retention. The Psychologist-Manager
Journal, 15(4), 237-246.
Thomson, J. S., Kiernan, N., St. Pierre, T. L., & Lewis, R. B. (1987). Between the worlds
of work and home. Journal of Extension, 25(3), Article 3FEA5.
Tiedje, L. B., Wortman, C. B., Downey, G., Emmons, C., Biernat, M., & Lang, E. (1990).
Women with multiple roles: Role-compatibility perceptions, satisfaction, and
mental health. Journal of Marriage & Family, 52(1), 63-72.
Todd, P., & Binns, J. (2013). Work-life balance: Is it now a problem for management?.
Gender, Work & Organization, 20(3), 219-231.
Toland, M. D., Sulis, I., Giambona, F., Porcu, M., & Campbell, J. M. (2017).
Introduction to bifactor polytomous item response theory analysis. Journal of
School Psychology, 60(2), 41-63.
Tomarken, A. J., & Waller, N. G. (2005). Structural equation modeling: Strengths,
limitations, and misconceptions. Annual Review of Clinical Psychology, 1(1), 31-
65.
Torres, R. (2013, October). What it takes to be a great leader. Retrieved from
https://www.ted.com/talks/roselinde_torres_what_it_takes_to_be_a_great_leader
109
Tourangeau, A. E., Wong, M., Saari, M., & Patterson, E. (2015). Generation-specific
incentives and disincentives for nurse faculty to remain employed. Journal of
Advanced Nursing, 71(5), 1019-1031. doi:10.1111/jan.12582
Trizano-Hermosilla, I., & Alvarado, J. M. (2016). Best alternatives to Cronbach's alpha
reliability in realistic conditions: Congeneric and asymmetrical measurements.
Frontiers in Psychology, 7, 769.
Tucker, R. W., McCoy, W. J., & Evans, L. C. (1990). Can questionnaires objectively
assess organisational culture? Journal of Managerial Psychology, 5(4), 4-11.
Van Echtelt, P., Glebbeek, A., Lewis, S., & Lindenberg, S. (2009). Post-Fordist work: A
man's world? Gender & Society, 23(2), 188-214.
Wang, Y., Kim, E. S., Dedrick, R. F., Ferron, J. M., & Tan, T. (2018). A multilevel
bifactor approach to construct validation of mixed-format scales. Educational and
Psychological Measurement, 78(2), 253-271.
Ward, K., & Wolf-Wendel, L. E. (2005). Work and family perspectives from research
university faculty. New Directions for Higher Education, 2005(130), 67-80.
Warren, T. (2017). Work-life balance and class: In search of working class-work lives. In
S. Lewis et al. (Eds.), Work-life balance in times of recession, austerity and
beyond (pp. 112-130). New York, NY: Routledge, Taylor & Francis Group.
Watson, L. M. (2009). Leadership's influence on job satisfaction. Radiologic
Technology, 80(4), 297-308.
Weston, R., & Gore, P. A. (2006). A brief guide to structural equation modeling. The
Counseling Psychologist, 34(5), 719–751.
110
Wilkinson, S. J. (2008). Work-life balance in the Australian and New Zealand surveying
profession. Structural Survey, 26(2), 120-130.
Yauch, C. A., & Steudel, H. J. (2003). Complementary use of qualitative and quantitative
cultural assessment methods. Organizational Research Methods, 6(4), 465-481.
Young, J., & Jones, K. (2015). Examining the impact of community size on the retention
of county extension agents. Journal of Extension, 53(3), Article 3RIB2.
Yuan, K., & Bentler, P. (1998). Structural equation modeling with robust covariances.
Sociological Methodology, 28(1), 363-396.
Yuan, K., Yang-Wallentin, F., & Bentler, P. (2012). ML versus MI for missing data with
violation of distribution conditions. Sociological Methods and Research, 41(4),
598–629.
Zheng, J. (2011, August 16). What day of the week should you send your survey? Survey
Monkey Blog. Retrieved from
https://www.surveymonkey.com/blog/2011/08/16/day-of-the-week/
111
VITA
EDUCATION 2007 M.Ed. in Adult Education Penn State University (PA) 2002 B.A. in Youth Ministry and Recreation Bluffton University (OH) 2000 A.A. in General Studies Hesston College (KS)
POSITIONS 2018-present Area Leader Ohio State University Extension—Area 14 2008-present 4-H Educator Ohio State University Extension—Harrison Co. 2017-2018 (int.) Asst. Reg. Dir. Ohio State University Extension—NE Region 2008-2018 County Director Ohio State University Extension—Harrison Co. 2014-2016 (int.) County Dir. Ohio State University Extension—Columbiana Co. 2013 (int.) County Dir. Ohio State University Extension—Carroll Co.
HONORS 2015-2017 Service Ohio JCEP Early Career Award—4-H 2015 Grant ODNR-Division of Watercraft ($6,200) 2013 Teaching (team) Epsilon Sigma Phi (Alpha Eta Chapter) Excellence
in Multi-educator Team Teaching Award 2013 Grant ODNR-Division of Watercraft ($13,700) 2012 Service NAE4-HA Achievement in Service Award 2010 Research (team) Penn State University Community Engagement and
Scholarship Award 2009 Grant NIH-NIDA (Ohio project liaison portion; $23,500)
PUBLICATIONS Feldhues, K., & Tanner, T. (2017). Show me the money: Impact of county funding on
retention rates for Extension educators. Journal of Extension, 55(2), 2RIB3. Epley, T. & Tanner, T. (2017). Creative leadership in 4-H: Flatwater kayaking [4H-39,
Fact Sheet]. Epley, T. & Tanner, T. (2017). Creative leadership in 4-H: Stand up paddleboarding
[4H-41, Fact Sheet]. Faudie, A., Feldhues, K., Foxx, D., Heckel, K., Strickler, J., & Tanner, T. (2017). New
4-H Educator handbook for OSU Extension [Employee Manual]. Tanner, T. (2015). Organizing chaos: Time management for Extension professionals
[Curriculum].
Timothy D. Tanner 2018