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The employment of retired senior military officers with command experience

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The employment of retired senior military officers with command experience

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Content The Employment of Retired Senior Military Officers with Command Experience
Jason Alan Motes
Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education
December 2024

© Copyright by Jason Alan Motes 2024
All Rights Reserved

The Committee for Jason Alan Motes certifies the approval of this Dissertation
John Dexter
Anthony Maddox
Corinne Hyde, Committee Chair
Rossier School of Education
University of Southern California
2024

iv
Abstract
Employment outcomes for retired senior military officers are complex and vary based on many
influential factors. The purpose of this study was to examine employment outcomes for retired
senior military officers with commanding officer experience and identify gaps prevalent in their
transitional experiences. Using Clark and Estes’s knowledge, motivation, and organization
(KMO) framework, the study analyzed demographical data and transitional experiences for
retired senior military officers who entered the civilian employment sector and explored how
preparation for transition affected real and perceived transition success. The study utilized
quantitative analysis to identify statistically significant relationships from survey responses
provided by retired senior military officers from all seven branches of the armed forces. There
were 256 qualified survey respondents. This study’s findings suggest that although senior
military officer leadership experience was perceived to help prepare for and relate to roles of
equivalent levels of responsibility outside the military, post-military employment outcomes did
not systemically result in the immediate achievement of positional equivalency. Implications of
the study include the need for improvements in employer understanding of leadership attributes
and experiences of senior military officers, the establishment of transitional programs
specifically tailored for them, and the identification of key mentoring relationships to support
them through their transition.

v
Dedication
To my wife, Angel, and children, Taylor and Chandon, you are what drives me. Thank you for
your patience and for giving me the space to accomplish. I love you and our best days are right in
front of us.
To my parents, Jane, Keith, Jan, Tim, Shirley, and Howard, and my brothers and sisters, Joshua,
Lindsay, Thomas, Delissa, Patrick, Felicia, Mike, Caroline, Hope, Matt, and Howie; thank you
for constantly showering our family with love, prayer, and support.
To my closest friends, Ben, David, Peter, Richard, Rick, and William; thank you for answering
the phone when I needed to hear a voice of motivation and support. I will always be here for you.
To my mentors, Admirals Lacore, Jones, LeClair, Nowakowski, Haigis, Martinez de Pinillos,
and Sheldon, Dr. Dorsey, Dr. Vaughn, Chris, Jeff, John, Mark, and many others; thank you for
your influence and voices of counsel and guidance.
To all the men and women I have been blessed and privileged to work for, lead, and learn
alongside in the military, corporate America, and academia, thank you for giving me the
experiences and inspiration I needed to start and finish this work. My success shall always reflect
you.
To every veteran of the armed forces who desires to use their leadership experiences to
positively impact an organization, you are uniquely equipped with the skills to succeed; don’t
ever let anyone tell you otherwise.

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Acknowledgments
Writing a doctoral dissertation has been among the most challenging endeavors of my
lifetime. Born from a desire to explore experiences accumulated within the military and
corporate America and to give back, my research signifies my commitment to expanding the
academic body of knowledge to improve employment outcomes for military veterans.
This work would not have been possible without the commitment of many others,
beginning with my amazing dissertation chair, Dr. Corinne Hyde. Her confidence and patience
helped me cross the finish line exactly when I was supposed to, and she is a blessing for the
University of Southern California and its students. I also thank the other members of my
dissertation committee, Dr. Anthony Maddox and Dr. John Dexter, whose expertise and
guidance helped shape the research to achieve its desired outcomes.
In addition to my dissertation committee, several veteran employment advocates and
subject matter experts contributed to the study’s success as I sought to frame the problem and
analyze the research results: Misty Cook, Stephen Davis, Eddie Dunn, Don Gabrielson, Beau
Higgins, Joe Paschall, John Perez, Jason Roncoroni, Dr. Bill Sherrod, Jason Simon, and Gabe
Soltero. Thank you for helping shape the research!
Lastly, I’d like to acknowledge and thank the countless friends, colleagues, and peers
who helped distribute my research survey; your efforts helped capture the participants needed to
make the research study successful!

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Table of Contents
Abstract.......................................................................................................................................... iv
Dedication........................................................................................................................................v
Acknowledgments.......................................................................................................................... vi
List of Tables ................................................................................................................................. ix
List of Figures.............................................................................................................................. xiii
Context and Background of the Problem.........................................................................................1
Purpose of the Project and Research Questions...............................................................................2
Importance of the Study...................................................................................................................3
Overview of Theoretical Framework and Methodology .................................................................4
Literature Review.............................................................................................................................6
The Armed Forces Veteran..................................................................................................7
Employment of Veterans ...................................................................................................16
Factors Affecting Veteran Unemployment........................................................................22
Veterans as Leaders ...........................................................................................................29
Summary............................................................................................................................39
Conceptual Framework......................................................................................................39
Methodology..................................................................................................................................41
Research Setting.................................................................................................................44
The Researcher...................................................................................................................45
Data Source: Qualtrics Survey...........................................................................................46
Data Collection Procedures................................................................................................48
Data Analysis.....................................................................................................................48
Validity and Reliability......................................................................................................49
Findings .........................................................................................................................................50

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Survey Adjustments...........................................................................................................52
Research Question 1: What Motivational Influences Do SMOs With Command
Experience Report Helped to Prepare Them for Their Transition Into the Civilian
Employment Sector?..........................................................................................................58
Research Question 2: What Do SMOs With Command Experience Perceive As the
Organizational Gaps Related to Transitioning to Executive Leadership Roles at the
Completion of Their Military Service?..............................................................................60
Research Question 3: What Knowledge Gaps Do Post-command SMOs Report Are
Related to Their Transition Into Civilian Equivalent-Level Roles Upon Completion of
Their Military Service? ......................................................................................................64
Summary............................................................................................................................67
Recommendations..........................................................................................................................68
Discussion of Findings.......................................................................................................68
Recommendation 1: Mentoring .........................................................................................71
Recommendation 2: Additional Transitional Preparation Programs.................................72
Recommendation 3: Education for Civilian Employers....................................................73
Limitations and Delimitations........................................................................................................75
Recommendations for Future Research.........................................................................................78
Conclusion .....................................................................................................................................79
References......................................................................................................................................82
Appendix A: Retired Senior Military Officer Questionnaire ........................................................95
Appendix B: Ethics......................................................................................................................105
Appendix C: Supplemental Tables ..............................................................................................106
Demographic Questions (2–9, 19–28).............................................................................106
Description of Data: Knowledge Questions (13–18, 35, 37)...........................................117
Description of Data: Motivational Questions (12, 32-34, 36) .........................................121
Description of Data: Organizational Questions (10-11, 29-31).......................................124

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List of Tables
Table 1: Research Questions 42
Table 2: Knowledge, Motivation, and Organization-Related Survey Questions 42
Table 3: Correlation of Likert-Scale Questions Using Filter 1 (Baseline) 57
Table 4: Correlation of Likert-Scale Questions Using Filter 2 (Command) 57
Table 5: Regression Analysis of Motivation Variables Upon Question 35 Using Filter 2
(Command) 58
Table 6: Relationship Between Question 24 and Question 34 Using Filter 2 (Command) 59
Table 7: Regression Analysis of Organizational Variables Upon Question 35 Using Filter 2
(Command) 61
Table 8: Regression Analysis of Organizational Variables Upon Question 36 Using Filter 2
(Command) 62
Table 9: Relationship Between Question 24 and Question 11 Using Filter 2 (Command) 63
Table 10: Relationship Between Question 24 and Question 25 Using Filter 2 (Command) 64
Table 11: Regression Analysis of Knowledge Variables Upon Question 35 Using Filter 2
(Command) 65
Table 12: Regression Analysis of Knowledge Variables Upon Question 35 Using Filter 3
(Employed) 66
Table 13: Relationship Between Question 24 and Question 10 Using Filter 2 (Command) 66
Table C1: Question 2: How Many Years Has It Been Since You Retired From the Military?
(Demographic) 106
Table C2: Question 3: How Many Years of Commissioned Service Did You Serve in the
Military? (Demographic) 107
Table C3: Question 4: What Was Your Pay Grade Upon Retirement From the Military?
(Demographic) 107
Table C4: Question 5: What Branch of the U.S. Military Did You Retire From?
(Demographic) 108
Table C5: Question 6: During Your Career in Military Service, Did You Complete a Tour in
the Position of a Commanding Officer (USN/USMC/USCG) or Commander (USA/USAF) at
or Above the Pay Grade of O-5? (Demographic) 108

x
Table C6: Question 7: If You Answered Yes to the Previous Question, Was Your Assignment
to the Commanding Officer or Commander Position Based on a Selection Board or Screening
Process? (Demographic) 109
Table C7: Question 8: How Many Active Duty Commanding Officer/Commander Tours at or
Above the Pay Grade of O-5 Did You Complete During Your Commissioned Service?
(Demographic) 110
Table C8: Question 9: During your tour as a Commanding Officer/Commander at or above
the pay grade of O-5, did you have command of other commanding officers/commanders (i.e.,
Commodores, Wing Commanders, Brigade Commanders, etc.)? (Demographic) 110
Table C9: Question 19: How Many Employers Have You Had Since Retiring From the
Military? (Demographic) 111
Table C10: Question 20: How Many Months of Employment Experience Do You Have Since
Retirement, Regardless of Employment Type or Industry/Sector? (Demographic) 111
Table C11: Question 21: Are You Currently Employed? (Demographic) 112
Table C12: Question 22: If Yes, Which Industry or Sector Are You Employed in?
(Demographic) 113
Table C13: Question 23: If Currently Employed, How Many Employees Work for Your
Organization? (Demographic) 114
Table C14: Question 24: Are You Serving in an Executive-Level Leadership Role?
Executive-Level Roles Are Vice President or Higher (Demographic) 114
Table C15: Question 25: If You Answered “Yes” to the Previous Question, Is Your Current
Role Your First Employment Experience Since Retiring From the Military? (Demographic) 115
Table C16: Question 26: If Currently Employed, How Many Employees Do You Directly
Manage? (Demographic) 115
Table C17: Question 27: If Currently Employed, How Many of Your Direct Reports Also
Have Direct Reports? (Demographic) 116
Table C18: Question 28: If Currently Employed, Within Your Organization’s Reporting
Structure, How Many Personnel Are Between You and Your Organization’s President/CEO?
(Demographic) 116
Table C19: Question 13: Did You Have Professional Work Experience Before Becoming a
Commissioned Officer? 117
Table C20: Question 14: During Your Commissioned Service Career, Did You Experience a
Break in Service Where You Fully Separated From the Active Component and Obtained FullTime Employment, Regardless of Industry, Before Permanently Returning to Active Duty? 117

xi
Table C21: Question 15: During Your Commissioned Service, Did You Complete an
Internship, Fellowship, DoD SkillBridge, or Any Other Program Where You Worked FullTime for a Civilian Employer While on Active Duty? 118
Table C22: Question 16: Did You Complete Any Additional Transition-Related Programs
Besides DoD TAP? 118
Table C23: Question 17: If You Answered “Yes” to the Previous Question, How Many
Transitional Programs Did You Participate in Besides DoD TAP? Transitional Programs May
Include Corporate or Non-profit Programs to Assist Military Members With Their Career
Transition 119
Table C24: Question 18: Before Your Military Retirement, Did You Receive Mentoring From
Other Retired Military Officers? 119
Table C25: Question 35: On a Scale of 1–10, With “1” Being the Least Prepared and “10”
Being the Most Prepared, During Your Final Year of Military Service, How Prepared Were
You to Transition to the Civilian Employment Sector? 120
Table C26: Question 37: On a Scale of 1–10, With “1” Being the Least Confident and “10”
Being the Most Confident, While Serving in the Military, How Confident Were You About
Your Ability to Assume an Executive Leadership Position in the Civilian Employment Sect 120
Table C27: Question 12: Did You Plan to Work After Your Military Career? 121
Table C28: Question 32: What Was Your Primary Reason for Leaving the Military Service?
Please Choose the Most Appropriate Answer 121
Table C29: Question 33: What, if Any, Was a Secondary Reason for Leaving the Military
Service? Please Choose the Most Appropriate Answer 122
Table C30: Question 34: Upon Retirement From the Military, Did You Desire to Lead an
Organization in a Role Equivalent to a President, CEO, Executive Director, General Manager,
etc.? 123
Table C31: Question 36: On a Scale of 1–10, With “1” Being the Least and “10” Being the
Most, How Strong Was Your Desire to Assume an Equivalent Leadership Role Within the
Civilian Employment Sector? 124
Table C32: Question 10: On a Scale of 1–10, With “1” Being the Least and “10” Being the
Most, if Applicable, How Well Do You Think Your Time as a Commanding
Officer/Commander Prepared You for Executive Leadership Positions in the Civilian
Employment Sector? 124
Table C33: Question 11: On a Scale of 1–10, With “1” Being the Least and “10” Being the
Most, if Applicable, How Relatable Do You Feel Your Experiences as a Commanding
Officer/Commander Are in the Civilian Employment Sector? 125

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Table C34: Question 29: On a Scale of 1–10, With “1” Being Least Satisfied and “10” Being
Most Satisfied, How Satisfied Are You in Your Current Role? 125
Table C35: Question 30: On a Scale of 1–10, With “1” Being the Least Satisfied and “10”
Being the Most Satisfied, How Satisfied Are You About the Level of Responsibility Your
Current Role Entails? 126
Table C36: Question 31: On a Scale of 1–10, With “1” Being the Least and “10” Being the
Most, How Much Do You Feel Your Current Employer Values Your Executive Military
Leadership Experience? 126
Table C37: Statistical Relationships of Knowledge Questions Using Filter 1 (Baseline) 127
Table C38: Statistical Relationships of Knowledge Questions Using Filter 2 (Command) 128
Table C39: Statistical Relationships of Motivational Questions Using Filter 1 (Baseline) 130
Table C40: Statistical Relationships of Motivational Questions Using Filter 2 (Command) 131
Table C41: Statistical Relationships of Organizational Questions Using Filter 1 (Baseline) 133
Table C42: Statistical Relationships of Organizational Questions Using Filter 2 (Command) 134
Table C43: Statistical Relationship of a Demographical Question (24) 136
Table C44: Count of Statistically Significant Relationships With Filter 1 Applied (Baseline) 139
Table C45: Count of Statistically Significant Relationships With Filter 2 Applied
(Command) 140
Table C46: Count of Statistically Significant Relationships in Common With Filters 1 & 2
(Baseline & Command) 141

xiii
List of Figures
Figure 1: Conceptual Framework ................................................................................................. 41

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The Employment of Retired Senior Military Officers with Command Experience
A commanding officer holds one of the military’s most demanding and unique leadership
positions, comparable to that of a company’s president. When their military service ends, these
individuals, who represent an elite subset of the military’s officer corps, may not transition into
careers of equal or near-equal leadership responsibility in the civilian employment sector, and
this is a problem. The commanding officer is a position of exclusivity in the military, limited to
those selected through several screening processes and typically tied to a particular rank, usually
that of a senior officer (Kapp, 2018). Many veterans leave the service annually, yet only a few
will have held the title of commanding officer. Those in the civilian employment sector do not
easily understand the role of the commanding officer and the experiences associated with serving
in that role. The data demonstrates that a lack of understanding and misperceptions about
veterans’ skillsets and military experiences inhibit successful employment after military service
(Davis & Minnis, 2017). Narrowing that understanding to an even smaller grouping of highly
ranked veterans would present more significant challenges because of a lack of data available. If
the data demonstrates that the civilian employment sector does not understand veterans in
general, it is plausible that it may fail to understand a highly elite fraction of that population.
This study sought to further examine the factors related to post-military employment outcomes
of a subgroup of military veterans and provide a foundation for future research.
Context and Background of the Problem
Each year, hundreds of senior military officers (SMOs) will retire from the military, often
young enough to pursue a second career in the civilian employment sector. A typical SMO’s
career will include at least 20 years of service and much leadership experience. It is difficult to
be promoted as an officer in the U.S. military, and only those with exemplary performance

2
records will achieve high ranks. Even among those who make the more senior ranks affiliated
with the term “SMO,” the majority will not reach the pinnacle of service associated with being in
command. For those with exemplary leadership and performance records, only a small
percentage will earn the privilege of serving as a commanding officer, and even fewer will attain
the honor of serving as a commanding officer more than once. The process of obtaining this
position is highly selective and usually conducted by a board of the military branch’s most senior
and accomplished officers. For those that do earn the title, it is not without merit.
Command in the military entails navigating significant and rigorous responsibilities.
Commanding officers are considered the end-all, be-all in their organizations. They serve as their
organizations’ presidents and CEOs and are often left to make critical decisions without
guidance from a higher authority. They set policies and procedures, typically lead hundreds if not
thousands of service members, and answer for their units’ performance and ability to meet
mission requirements. They direct all preparation and training, often resulting from an arduous
budgeting and manning process. They are typically accountable for hundreds of millions of
dollars in equipment (e.g., planes, tanks, ships, and guns). Unlike their civilian counterparts, they
are also responsible for the behavior, care, food and shelter, and well-being of the service
members and their families under them. In summary, the post-command SMO has effectively
served as a CEO in the military. Therefore, it is logical that they could serve effectively in the
same capacity in the civilian sector.
Purpose of the Project and Research Questions
This study examined why post-command SMOs are not universally transitioning into
equivalent leadership opportunities in the civilian employment sector after leaving the military
service. This study addressed three principal research questions:

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1. What motivational influences do SMOs with command experience report helped to
prepare them for their transition into the civilian employment sector?
2. What do SMOs with command experience perceive as the organizational gaps related
to transitioning to executive leadership roles at the completion of their military
service?
3. What knowledge gaps do post-command SMOs report are related to their transition
into civilian equivalent-level roles upon completion of their military service?
Importance of the Study
This is a critical problem to examine for several reasons, and there are consequences for
not doing so. Prior studies have examined veteran employment and unemployment with myriad
findings. This study sought to determine whether there is inequity for a particular subgroup of
this population, which had yet to be thoroughly researched at the time of this study. The
literature suggests that veterans’ unemployment is related primarily to misunderstandings about
them, yet other factors contribute. The gaps in knowledge, motivation, and organization (KMO)
that the research identified will not just prove valuable to this subgroup itself. The research also
provides feedback on a more significant problem of practice: the valuation of military leadership
experience as it relates to inequities in veterans’ employment (and unemployment).
It is also vital to examine this problem of practice because of its impact on society. The
U.S. veteran population, which tops 15 million people, represents a significant portion of the
employable workforce. The subgroup identified in this study presents a potential opportunity to
create a domino effect for the employment of the larger veteran population. Because the
subgroup would theoretically be employed in senior-level positions, they may impact the hiring
trends of the general veteran population. Further, the data shows that veteran-led organizations

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may outperform nonveteran-led organizations (Gao et al., 2021). This may lend credence to the
experiences incurred as a commanding officer and highlight that veteran leaders may possess
significant transformational leadership skills. A study examining the transformational leadership
capability of retired military officers found that they can function effectively as civilian
managers and be measurably more effective than their civilian counterparts (Tiller, 2007).
Additionally, corporate boards value veteran memberships for their experiences and
integrity. They are interested in acquiring experiences cultivated in life far beyond technical
expertise and monitoring capabilities, specifically social identities developed as part of their
military service (Simpson & Sariol, 2019). Consistent with National Leadership Institute
findings, military leadership stands significantly above all other sectors concerning public
confidence and an aligning sense of trustworthiness, hopefulness, competence, and security
(Schaeffler, 2015). This was supported by research that determined that CEOs with prior military
service are related to lower corporate investment, are less likely to be involved in corporate
fraudulent activity, and perform better during industry downturns (Benmelech & Frydman,
2015). Veteran leaders can help transform private-sector organizations’ performance, increasing
veterans' employment. Their employment in the private sector is central to and has several
implications for decreasing their unemployment.
Overview of Theoretical Framework and Methodology
A reliable and relevant theoretical framework is essential for good research (Merriam &
Tisdell, 2015). The theoretical framework most applicable to this study is Clark and Estes’s
(2008) KMO model. The model presumes a deficit exists in the knowledge, motivational, or
organizational resources, ultimately affecting performance. Within the context of this proposed
study, the KMO model helps explore gaps associated with the problem and, finally, represents a

5
valuable framework for addressing and solving how post-command SMOs can earn similar
leadership roles after completing their military service.
The factors associated with this study necessitated conducting the research using a
quantitative approach. According to the authors, a quantitative research method tests objective
theories by examining relationships among variables (Creswell & Creswell, 2014). Using a
quantitative methods research approach, I sought to understand the experiences of post-command
SMOs upon completing their transition into the civilian employment sector. I attempted to
determine whether command experience as an SMO is perceived to be influential in an SMO’s
post-military career options and how it is perceived to be valued from the SMO’s perspective. I
used quantitative methods to determine if being post-command and an SMO are independent
variables to earning equivalent leadership opportunities (dependent variable) in the civilian
sector and will seek to add value by determining if any discernable motivational factors exist that
may guide the decision-making process when seeking and accepting employment in the civilian
sector. I also sought to determine if any motivational or organizational knowledge gaps are
identifiable in the hiring process, either by the service member or the hiring firm.
A theory of change may be defined as change that occurs through research as it compels
the change. In other words, when something is researched, there is an indication that a change is
needed, and the research will ultimately lead to change through social science (Paris & Winn,
2014). Simply put, a theory of change is the middle part that bridges what is to what should be.
In the context of this proposed study, what is may be defined as post-command SMOs not being
afforded opportunities in the civilian employment sector that are commensurate with their
experiences in the military, and what should be would represent these same SMOs transitioning
into such equivalent roles. This theory of change is purely strengths-based and represents the

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organizational aspect of KMO; resources are available to these SMOs, including their legitimate
leadership experiences. The gap is the lack of acceptance or recognition of their leadership traits
and ability by the civilian employment sector, the barriers to prevent their acceptance and
recognition, or both. Therefore, if the barriers, gaps, or both that prevent these qualified
individuals from systemically transitioning into equivalent leadership roles are removed or
eliminated, the change will have been implemented.
Literature Review
The problem of practice was to understand a lack of equivalent executive leadership
opportunities in the private sector for transitioning post-command (post-executive) SMOs.
I conducted a thorough literature review using a combination of online databases at the
University of Southern California (USC), including Google Scholar, JSTOR, and the consortium
of ProQuest libraries. I conducted additional searches using USC’s internal database, which pulls
from thousands of additional databases and consolidates searches on one platform. Keywords
searched during the literature included the following: “veteran,” “veteran executive,” “veteran
employment,” “employment of veterans,” “veteran unemployment,” “military CEOs,” “military
commanding officers,” “senior military officer,” “senior military officer employment,” and
myriad combinations of search terms, therein.
After reviewing the literature for relevancy, I prioritized the most recent research
available from peer-reviewed journal articles. The relevant literature includes 135 peer-reviewed
journal articles, seven official reports, four books, three newspapers, and six references to
websites, five of which are official U.S. government websites. The literature review revealed
multiple prominent themes, including 122 sub-topics worthy of further investigation. I

7
consolidated and refined all themes and sub-topics, producing four principal themes with 24
subordinate topics.
The Armed Forces Veteran
According to the U.S. Department of Veteran Affairs and Title 38 U.S.C. SS 102, the
term “veteran” means a person who served in the active military, naval, or air service and was
discharged or released under conditions other than dishonorable (U.S. Department of Veterans
Affairs, n.d.-a). In addition to the U.S. Department of Veteran Affairs, the U.S. government’s
executive branch contains several departments, including the U.S. Departments of Defense
(DoD) and Homeland Security (DHS). The department that governs the U.S. military is the DoD,
and its six different uniformed service branches are the Air Force, Army, Navy, Marine Corps,
and its newest one, the Space Force. DHS governs the U.S. Coast Guard (USCG). According to
Boros and Erolin (2021), each branch maintains identities for service member enrichment: Air
Force (airman), Army (soldier), Coast Guard (coast guardsman), Marines (marine), and Navy
(sailor). Service members are identified by rank type (enlisted or officer), rank (e.g., sergeant),
and grade (e.g., E-5; Boros & Erolin, 2021).
Dexter (2020a) posited that the USCG, with a comparatively smaller personnel base than
the other branches, at roughly 3% of the total active-duty population, and a division of DHS and
not the DoD, is widely considered a military service even though its mission consists primarily
of local law enforcement operations along the U.S. coastline and its deployments are typically
significantly shorter than naval ones. The author acknowledged that USCG assets often support
DoD assets during wartime scenarios, but only during those scenarios are USCG personnel
subject to the military’s law system, commonly known as the Uniform Code of Military Justice
(Dexter, 2020a). In addition, the author summarized that because the USCG has a different

8
administrative reporting structure and mission, its veterans may not have the same military
experience as those from the other (DoD) branches (Dexter, 2020a). The “armed forces veteran”
is a vast term rooted in cultures and experiences exclusive to the U.S. military and its many
branches.
The Armed Forces Experience
Experiencing life as a member of the U.S. military is an opportunity that shapes service
members’ individual identities (Boros & Erolin, 2021). The impact of that indoctrination is
significant: as of 2020, the U.S. military was one of the largest employers of young adults
(Werum et al., 2020). The experiences that an armed forces service member incurs differ from
those in the private and corporate sectors. Asch (2019) noted that the differences between the
military experiences and civilian experiences come down to the nature of the service; military
jobs incur more hazards, are more rigid, and often impose hardships on military personnel and
their families because of frequent moves, arduous deployments, and discipline for misbehavior,
whether the member is on or off duty. According to Kay and Gibbs (2022), the military’s
structure contrasts sharply with the less structured civilian world, and other characteristics
differentiate the military from the private sector, such as its bureaucracy, hierarchical structure,
guidelines, norms, discipline, and obedience expectations, and that civilian organizations are
more apt to change frequently (Shepherd et al., 2021). In summary, Minnis (2020) pointed out
that military veterans are unique to society because of their culture, demeanor, language,
clothing, job requirements, and relations, distinguishing them from the civilian sector. The
statistics related to these individuals highlight their experience.

9
Statistics of Veterans
The veteran community is a minority community compared to the nonveteran
community. As of 2016, only 7% of the U.S. population had served (Cox, 2019); as of 2020, less
than 8% of the civilian labor force were veterans (Dexter, 2020b). The data shows that veterans
chose to serve because of the opportunities afforded them, namely to prepare for a successful
future (Baktir & Sillah, 2021). The landscape of the military today is even smaller: 1% of the
U.S. population is serving on active duty, and only 9% identify as women (Boros & Erolin,
2021). As a matter of record, as of July 31, 2022, there were 1,317,864 active-duty military
personnel in the four branches of the U.S. military (U.S. Department of Veterans Affairs, n.d.-b).
According to the U.S. Department of Veterans Affairs (2022), there are approximately
19,162,515 veterans in the United States. This population is declining and is expected to reduce
to approximately 13.6 million by 2048 (U.S. Department of Veterans Affairs, 2018). Still,
regular military attrition contributes to the size of this population, and those relative
contributions have increased over the previous 2 decades because of ongoing extended combat
operations, leading to attrition numbers not seen in decades (Minnis, 2020).
Military service also represents a unique subset of the population, socioeconomically, and
it defies many ill-carried stereotypes that the military is for the poor who could not find other
options. According to P. Carter et al. (2017), the military is overwhelmingly comprised of the
middle class, with top and bottom-level population subsets represented as well, although minimal
and more likely than civilians to have completed some college and hold an advanced degree. Life
in the service influences life after the military, and as Oster et al. (2017) noted, there is room for
a better understanding of the impacts of military services, such as intensity and duration, on wellbeing post-transition. Related to their life in the service, according to the U.S. Bureau of Labor

10
Statistics, almost 22% of veterans continue working in government and public sectors after
military service because many see those sectors as relatable and may indicate a natural
preference. In comparison, nearly 10% become self-employed after military service (Baktir &
Sillah, 2021). Of the almost 18 million veterans, a small percentage will live and work abroad
after service, many in roles related to their previous military ones while stationed in other
countries (Hunter‐Johnson et al., 2020). The statistics on this population are numerous and may
help researchers better understand how their experiences have shaped their decision-making
process.
The Veteran Mindset
While government reports readily provide statistics on veterans, they do not present their
mindset. Some studies delve into outcomes regarding employment and experiences, but not
many discuss attitudes, values, and personal experiences. The culture of the military may
influence mindset. Teasley et al. (2021) found that veterans may value the military’s culture and
traditions and, as a result, may have a knack for getting the job done because, as the study found,
they tend to demonstrate that they present grit in the form of relentless and focused performancedriven behavior during stressful scenarios. Dixon et al. (2019) posited that completing the
mission is central to the military members’ ethos of loyalty and caring for each other. Separately,
Law and Mills (2017) noted that veterans’ culture is rooted in ethics. Another tenet of the
military members’ ethos is the concept of trust, protecting, and looking out for each other (Boros
& Erolin, 2021). Finally, in line with previous authors, Loughran (2014) noted that some
veterans’ drive and motivation, risk adversity, and respect for the chain of command differentiate
them from their nonveteran peers, which may affect their future employment outcomes.

11
Work-life balance is thought to be an essential factor for most military veterans. Many of
the younger veterans, known as millennial veterans, may prioritize work-life balance while
pursuing post-military employment, as one article noted that it may be their highest priority, even
over roles of leadership and opportunity (Business Wire, 2016). Not surprisingly, because of the
frequency of relocation and moves during military careers, job location and availability are
critical factors of priority consideration in the pursuit of civilian employment.
Motivational Factors for Remaining in Service
There are myriad reasons a service member may remain in the military. As Boros and
Erolin (2021) noted, the amount of change required to leave an organization that embodies a
culture of belonging may be a deterring factor; the sense of developed loyalty to the military may
be another factor for remaining in the service (Albertson, 2019). Dependence upon the military
structure and system could also be a deterring factor for leaving the military, such as the pay and
benefits associated with continued service (Asch, 2019). Compared to the civilian sector, feeling
and belonging to a system of perceived stability could also be factors for remaining in service
(Kay & Gibbs, 2022). Another less explored reason for remaining in service is the relative age
gap between veterans and their nonveteran peers in college. Relevantly, Werum et al. (2020)
noted an age gap between those who begin college after service versus their nonveteran peers, as
many may remain in service because of a desire not to go against social norms by pursuing an
education post-service at a relatively advanced age compared to their peers.
Types of Veterans
Understanding the various types of veterans first requires understanding how they served.
As noted, a veteran in the context of this paper is someone who has served in the U.S. military;
their type of service depends upon how they entered and, in some cases, how they exited the

12
service. They are pre-screened military applicants, and only 1% of the U.S. population is eligible
and inclined to discuss service (McMahon & Bernard, 2019).
There are two ways to serve in the military: as an officer or an enlisted member. Enlisted
members enlist for a period, usually under a service contract tied to a time ranging from 2 to 6
years. On the other hand, officers typically must have completed an undergraduate program
before earning their commissions; it is estimated that over 40% of officers have also finished
college at the master’s degree level (P. Carter et al., 2017).
Officers typically join the military through one of four different commissioning paths: a
service academy, Reserve Officer Training Corps (ROTC) at a college or university, officer
candidate school (OCS), which each branch offers, or a direct commissioning program, which is
typically provided to industry professionals such as doctors and lawyers (Kapp, 2018). There are
five service academies: U.S. Air Force Academy (Air Force), U.S. Military Academy (Army),
U.S. Naval Academy (Marine Corps and Navy), U.S. Coast Guard Academy (Coast Guard), and
U.S. Merchant Marine Academy (Merchant Marines). Service academies consist of a traditional
4-year academic course of study with service-specific military courses intertwined into the
program. When cadets complete their undergraduate studies, they are simultaneously
commissioned into the service academy’s branch of service.
The second primary option for earning a commission is via the ROTC program, which is
an avenue whereby students enroll in a traditional college or university and complete the ROTC
curriculum (and activities) in tandem with their undergraduate studies. Not every college or
university has an ROTC program on its campus, and in many cases, ROTC programs on
campuses are limited to one branch of service. There were 1,441 schools with an ROTC host,
cross-town, or extension unit during the academic year 2011 through the academic year 2021,

13
and all states have at least one ROTC program, with California having the most significant
number (U.S. Government Accountability Office, 2023). The branch of service that offers the
ROTC program is the branch of service that the college graduate commissions upon graduation
from the affiliated college or university. Of note, like the U.S. Naval Academy, Navy ROTC
programs offer their students the opportunity to commission into either the Marine Corps or the
Navy because the Marine Corps falls under the Department of the Navy (DON). The USCG does
not offer commission through an ROTC program.
The last primary source of commissioning newly minted officers is offered through a
branch’s OCS or officer training school (OTS). The Army, Navy, Marine Corps, and Coast
Guard refer to their programs as OCS, while the U.S. Air Force labels its OTS. In every instance,
whether OCS or OTS, an officer candidate enters the program after completing undergraduate
studies, as entry requires a bachelor’s degree. OCS and OTS programs vary in length, ranging
from 11 to 13 weeks, and are all located on different military bases in the United States.
Eligibility to serve as an officer is both exclusive and limiting. U.S. Title 10 stipulates the
requirements to serve as an officer, which include the requirement to be a citizen of the United
States, able to complete 20 years of active commissioned service before age 62, of good moral
character, physically qualified for active service, and possess other special qualifications as the
secretary of the military department concerned may prescribe by regulation (Kapp, 2018). Unlike
their enlisted counterparts, officers rise through the ranks according to a different, more complex
promotion standard based on a promotion system designed to be competitive to select the most
appropriate and qualified officers for the next higher rank. Officers who fail to be selected for
promotion are often force-retired or transitioned out of military service, and promotion is

14
constrained by strength count requirements, which reduce significantly as the ranks increase
(Kapp, 2018).
Officers
Officers are a carefully screened and exclusive U.S. military component representing its
middle and upper management leadership arms. They are charged with training and executing
military strategy and serving as the military’s moral force to guide their subordinates (Snider et
al., 2010). According to Swain and Pierce (2017), the officer is a leader of character, empowered
to protect through chaos with an unwavering sense of duty to national policy and procedure.
They carry the responsibility to make critical and vital leadership decisions (Caforio & Nuciari,
2018).
Senior Military Officers and Commanding Officers
The officer community represents 18% of the less than 1% of the U.S. population serving
on active duty. In the officer corps, a senior cadre exists, known as the SMO, which is exclusive.
Senior military officers represent just 19% of the officers, placing them in a minute category.
They often serve in significant leadership positions and can make decisions under high stress and
in complex situations (Biniecki & Berg, 2020). They typically retire between 42 and 52, young
enough to pursue a second career in the civilian sector upon retirement from the military, and
civilian organizations can build on their strengths. Still, they, too, experience transitional
challenges commensurate with their military peers of all ranks and categories (Bonica et al.,
2020).
A small subset of SMOs will achieve the position of commanding officer. The dictionary
defines a commanding officer as an officer in the armed forces in command of an organization or
installation (Merriam-Webster, n.d.). The military branches refer to the term “commanding

15
officer” differently. For example, the Army and the Air Force refer to them as commanders. The
Navy, Marine Corps, and Coast Guard, as commanding officers. According to the U.S. Code
Title 32, which defines the term for the U.S. DON, their authority in their organization is a
position of absolute and dominant influence that provides them responsibility for the economy
within their command and the duty to protect it through leadership and standard adherence (U.S.
Government Publishing Office, 2002). Another article defines the commanding officer role as
one that develops organizational plans to fulfill assigned missions, establishes policies and
procedures for operation, and exercises military control for their command (Navy Credentialing
Opportunities Online, n.d.). Command is the authority that a commander exercises over
subordinates. It is the pinnacle of military leadership, the goal that officers most often aspire to
attain, and the steppingstone to achieving the highest levels of military service (Swain & Pierce,
2017).
The most elite of the officers in the military attains the rank of Admiral (Navy and Coast
Guard) or its equivalent, general (Army, Air Force, Marine Corps). They are called flag officers,
representing the senior-most military officer ranks available (grades O-7 through O-10). As a
frame of reference, as of 2017, approximately 110,000 retired O-6s were living in the United
States compared to less than 8,000 retired O-7 to O-10s, who primarily work in government,
business, and academia in their post-military careers (Griffiths, 2020). Flag and general officers
are an exclusively elite category of military officers, having cleared the most challenging
promotional hurdles to attain the first rank of O-7 (one star). Less than 3.4% and 5% of O-6s are
estimated to be promoted to the first flag officer rank of O-7 (Snider et al., 2010). A better
understanding of the types of military members, their experiences, and the attributes and

16
characteristics that differentiate them from their nonveteran peers may help to understand how
they are employed in their post-military careers.
Employment of Veterans
The primary employment sectors in the U.S. economy are the public, private, and nonprofit sectors; the military falls under the public sector (Baktir & Sillah, 2021). Since the turn of
the century, nearly 3 million veterans have served, a population that the authors view as a skilled
workforce that experiences myriad challenges in finding the proper employment fit in their postmilitary careers (Curry Hall et al., 2014). Additionally, with the private sector’s renewed interest
and commitment to veteran hiring initiatives and with this increasingly qualified population
believed to soon represent nearly 8% of the U.S. workforce desiring positions of leadership and
managerial responsibility, Dexter (2020b) posited that it may be time for employers to more
carefully consider the applicability and translatable qualities of their military experience. Most
military transition programs focus on enlisted and junior officers because they represent the most
significant percentage of transitioning members. Still, retiring SMOs represent a small, diverse
group with experience in high-level leadership roles and senior managerial experiences (Biniecki
& Berg, 2020). Despite the transitioning programs available for all groups, unemployment is still
a challenge. It may be a result of many different factors, and as recently as 2020, veterans’
unemployment rate was approximately 7.3% (U.S. Bureau of Labor Statistics, 2021).
Motivational Factors for Leaving Service
There are numerous reasons veterans leave military service. The implications of the
motivational factors that steer them away from military service and into the civilian sector
warrant further research (Hunter‐Johnson et al., 2020). Among the most prevailing factors
known are the arduousness of their duty and frequent deployments abroad (Asch, 2019). Another

17
study posits that they leave the service because of a desire to continue to lead in the civilian
sector as a matter of purpose and fulfillment (Business Wire, 2016). The combination of multiple
factors has made the environment outside the military appealing (McMahon & Bernard, 2019).
Regardless of the reason for the transition, evidence suggests that many leave the military intent
on matriculating into the civilian workforce (Shepherd et al., 2021). Despite the myriad reasons
military members decide to leave the military, their experiences in the process vary.
Transitioning Experiences of Veterans
Transitioning from military service into the civilian workforce is considered the ultimate
career transition (Hunter‐Johnson et al., 2020). As a result, the needs and experiences of veterans
during their transition into civilian employment are a top priority for the U.S. Department of
Veterans Affairs and the U.S. government because these organizations have learned that they
may find the transition assistance programs to be inconsistently helpful and that their
employment may not be commensurate with their skillsets, leadership experience, and culture
(Harrod et al., 2017). The data suggests that the transition is vital to the military member, as
nearly 60% of younger veterans agreed that their eventual transition would be their most
significant challenge (Business Wire, 2016). Despite the government agencies’ initiative to
support their transition, there has been minimal research on veterans’ reintegration into the
civilian workforce, and given the large numbers of those transitioning annually, the area should
be further explored (Dexter, 2020a).
Veterans experience numerous challenges during their transition into civilian
employment, such as networking, career options, and finding the right cultural fit (Minnis, 2020).
Successfully transitioning into the civilian employment sector is a priority for veterans. As a
result, they may undergo career development to improve their outcomes (Ward, 2020). Research

18
indicates that the transition process and its associated adjustment from the military into civilian
life is complicated (M. Keeling, 2018). The transition process also encompasses transitioning
physically, mentally, economically, and culturally (Albright et al., 2018).
Current Veteran Hiring Statistics
The federal government and civilian employment sector have each tried to improve
veterans’ transitional experiences because they have noted that certain groups, including women
and post-9/11 veterans, excel in the workplace (Batka & Hall, 2016). Additionally, numerous
private-sector programs have been established to support their transition as they seek
employment in the private sector. Yet, current research indicates that their unemployment rates
still exceed that of nonveterans (Minnis, 2020). Despite the myriad initiatives and good-faith
efforts, the body of academic research available regarding the impact of military veterans on
civilian organizations is limited to standard publishing and opinion-based articles (Blank, 2019).
Therefore, there is room for improvement regarding scholarly research on their hiring statistics
and the many reasons private-sector organizations pursue them.
Why Companies Hire Veterans
The data shows that today, companies hire veterans with backgrounds from all branches
and ranks of military service (Curry Hall et al., 2014) in a manner consistent with how they hire
nonveterans, which is based on the requirements of their industries across all sectors (Hall et al.,
2015). There are many reasons why companies hire veterans. Ford (2017) suggested that
companies hire them for their leadership experiences, and M. J. Kirchner’s (2018) work supports
that the most cited reason civilian organizations hire these individuals is their leadership ability
and leadership capacity obtained through service. Hall et al. (2015) suggested that in addition to
their leadership experience, companies hire them for their ability to work effectively in teams.

19
Finally, and most importantly, some companies simply understand that given the right
opportunities, veterans tend to outperform their nonveteran peers, as Ford suggested that veterans
are a value-add to the private sector. Another suggests that veterans perform better than
nonveterans (Lampka & Kowalewski, 2017). Regardless of the reasons, as P. Carter et al. (2017)
noted, veterans are known to be a critical asset to the American workforce, and military
members’ skills and experiences can be invaluable to civilian employment organizations.
From a hiring perspective, former military members do reasonably well when placed into
the right roles. At the same time, companies do not typically track metrics related to their
performance; many private employers believe their veterans perform well and, as previously
indicated, in some cases, better than their nonveteran counterparts (Hall et al., 2015). The data
shows that companies value veteran experiences working in teams, operating under stress,
flexibility, adaptability, and the ability to do the job with ethics and integrity (Curry Hall et al.,
2014). Another reason why companies may hire these individuals is that some of them have
skills and experiences that are hard to find in the private sector, such as positions in operations,
mechanical, and other technical trades (Vick & Fontanella, 2017). They may also be preferred
for civilian employers because their experiences are perceived as generally broader than
nonveterans (Ward, 2020). The ability to handle stress is essential to private-sector employers,
and military members may have an advantage in demonstrating resiliency during a crisis
(Simpson & Sariol, 2019). As Hunter‐Johnson et al. (2020) noted, veterans may be perceived to
have competitively more substantial amounts of training, experiences, and personal
characteristics deemed valuable to the private sector. Finally, their retention is higher than
nonveterans, which may make them more attractive to companies (Pollak et al., 2019).

20
Veterans can also impact the organizations’ bottom line, as research indicates that
companies that effectively employ them achieve superior rates of return (Blank, 2019). In a firstof-its-kind study examining the effects of hiring veterans on a company’s financial performance,
Pollak et al. (2019) found that a notable percentage of veterans outperformed their nonveteran
peers and that among the study’s participating companies, companies deemed military-friendly
had more favorable financial returns than similar companies without the military-friendly
designation. The evidence also suggests that hiring veterans reinforces organizational diversity,
inclusion, and other metrically essential categories related to the organization’s bottom line
(Pollak et al., 2019).
New programs to attract more veterans because of the empirical evidence surrounding the
effectiveness of employing them are also increasing. Several large companies are incorporating
veteran hiring initiatives in recognition of their qualities and experiences (Shepherd et al., 2021).
As Curry Hall et al. (2014) found, these large companies have noted the value of hiring veterans
and can articulate that value when called upon. According to one article, the value of hiring
veterans is experienced by the company and the individual, creating a win-win scenario for both
(Business Wire, 2016). Despite the reasons for hiring and the benefits this population brings to
organizations, there is still a disparity in experiences transitioning into the civilian employment
sector.
Disparity in Veteran Civilian Employment Experiences
Every veteran will experience a transition from military service, whether after their first
enlistment or after a 30-year career. Transition is, therefore, inevitable. The disparity in
experiences relates to their employment in the civilian employment sector, which is natural and
expected. Still, there is scant research on the disparity of those experiences (Caamal, 2019). An

21
academic understanding of their experiences is limited and may be perceived as a social justice
issue (Kay & Gibbs, 2022). Bailey and Sykes (2018) suggested that a veteran’s status does not
affect income and other factors related to disparity in employment outcomes. Instead,
employment outcomes are tied to education and experience. On the contrary, because it is
difficult to query veterans’ career trajectories after they have left the military, there is little
research on the effectiveness of current programs and initiatives to help them translate their skills
and experiences, which could impact their transitional outcomes (Batka & Hall, 2016).
For some, the transition may be difficult because of the relative decrease in daily urgency
and stressful encounters (Curry Hall et al., 2014). Ward (2020) suggested that some veterans
may lack confidence in their abilities, which could impact their post-military employment
outcomes. The data also indicates that disparity in employment experiences could be tied to
differences in organizational structure, which could lead to awkwardness among those who
historically prefer robust, well-defined structures as they learn how to operate within new, less
structured organizational environments (Caamal, 2019). Lastly, as M. Keeling et al. (2018)
suggested, personal characteristics may also impact employment outcomes post-military and
represent an area for further investigation. As the literature review indicates, the reasons for
variance in veteran employment outcomes relate to factors associated with experiences, privatesector engagement and initiative, and preparation programs. The research also indicates that
employment disparity and variances may also, consequently, lead to adverse outcomes, such as
unemployment. Factors related to veteran unemployment should be explored to understand better
the variables involved in post-military employment experiences.

22
Factors Affecting Veteran Unemployment
Improving research on factors affecting veteran employment has become a public priority
(Schulker, 2017). However, limited studies are available regarding veteran experiences with
finding and maintaining employment (M. E. Keeling et al., 2019), and there has not been a
significant effort to devote resources toward understanding these experiences (Vanderschuere &
Birdsall, 2019). There is also a lack of veteran-friendly recommendations or guidelines to
improve understanding of their employment outcomes (M. J. Kirchner et al., 2020).
Reintegration for veterans remains a challenge (Werum et al., 2020) because, in part, the
employment landscape is diverse and complex (Schulker, 2017). Due to cultural differences,
veterans may face difficulties assimilating into the civilian employment sector (Hall et al., 2015).
Although the research suggests that this population tends to gain an advantage from favorable
stereotypes such as discipline, leadership, work ethic, and being goal-oriented, it also indicates
that veterans may struggle with coworker interaction because of other less-favorable stereotypes
such as rigidity and a perceived lesser ability to learn new tasks (Shepherd et al., 2019). Recent
studies help to understand employment-related outcomes by showing that perceptions of the
ability to integrate positively correlate to employment rates (Merritt et al., 2020).
Research also suggests that some private-sector employers believe veterans do not
possess skills that can transfer into their organizational environments. The research also indicates
other barriers, such as discrimination, resulting in adverse employment outcomes (Ward, 2020).
Translating skills and overcoming cultural differences are among the many post-military barriers
encountered (M. E. Keeling et al., 2019). Despite the increased attention given to veterans’
career transition services, there is room for improvement in their preparedness and understanding
of their characteristics by the companies seeking to employ them (M. J. Kirchner et al., 2020).

23
Pre-transition Preparation by Veterans
Pre-transition preparation, while positive in most cases, has shown varied results. A lack
of preparation for civilian life may hinder the transition experience (Ward, 2020), and the data
demonstrates room for improvement in the research on pathways to civilian employment
(Dempsey & Schafer, 2020). One critical study also found that soon-to-transition veterans may
not fully comprehend the challenges ahead (Dexter, 2020a), which could explain a perceived
lack of preparation. At the same time, another showed that transitioning military members’ needs
may vary depending on which stage of their careers they transition to (Hunter‐Johnson et al.,
2020).
Advanced preparation has played a critical role in transition success. Some data
demonstrates that external hiring barriers tend to deter veterans who prepare in advance less than
those who do not (M. E. Keeling et al., 2019). For example, in a study on advanced preparation,
Bonica et al. (2020) found that retired military officers who engaged in the planning process
early had favorable transitional experiences, and those with specialties also had higher levels of
transitional success. The authors also noted that over three-quarters of the retired officers
surveyed believed their military service had adequately prepared them, with nearly half having
secured employment before leaving the military (Bonica et al., 2020). Regardless of preparation
level, another factor related to preparation is a commitment to the time required to affect the
process successfully. The author concluded that extended deployments may negatively impact
pre-transition preparation because of a lack of access, which could lead to improvements in
current transitional assistance programs (Blank, 2019).

24
Existing Transitional Programs and Resources
According to the authors, veterans are talented applicants with diverse skills,
professionalism, initiative, and a desire for learning and should be prioritized for recruiting,
hiring, onboarding, and training (M. J. Kirchner et al., 2020). Additionally, prioritizing these
individuals for employment could reduce major stressors on a population group that may not be
adequately prepared for the transition to civilian jobs (Derefinko et al., 2019). Although the
literature regarding current transitional programs and the experiences of veterans who use them
is extensive, the majority of the literature appears to focus on programs related to mental health
and not on the broader program base available (Perkins et al., 2020).
According to Minnis (2020), the DoD’s Transition Assistance Program (TAP) was
created to address career-related transitional concerns and is a course of instruction taken by
veterans, usually at a minimum period of at least 90 days before separation. The program’s goal
is to make military members “career ready” and equip them with skills to translate their military
experiences by creating an individual transition plan, an indication that the DoD is aware of the
importance of transitional preparation, the effectiveness of which has resulted in ongoing
research (M. E. Keeling et al., 2019). Since 9/11, TAP has updated its curriculum to support
veterans’ needs better. Through the Veterans Opportunity to Work Act of 2011, it has become a
requirement for every military member to attend. Still, inadequacies with the program’s structure
may not provide all that is needed and could lead some to seek other programs outside the scope
of the DoD (Dempsey & Schafer, 2020).
There are also thousands of non-governmental transitional programs available for
veterans. Yet, there is no clear understanding of which are preferred or most frequently utilized,
nor do we know their effectiveness (Perkins et al., 2020). It is also not a simple process for

25
veterans to target the right program because of the multitude of options available or, potentially,
a lack of knowledge about which would be the most applicable (Dempsey & Schafer, 2020). The
effectiveness of the myriad programs is also disputed because there is little evidence to support
that they reduce the time it takes to obtain the proper role (Loughran, 2014). More research is
required to better understand the available external programs and their effectiveness. Aside from
external programs, companies and organizations are also delving into affinity groups.
Role of the Company and Employee Resource Groups
Employee resource groups (ERG) are an essential resource for the organization and its
members. Instituting affinity groups provides opportunities to engage cross-culturally and may
benefit the transition process (M. J. Kirchner et al., 2020). Military veteran employees may also
rely upon ERGs to help maintain their identities. According to one study, a veteran-friendly
company supports its veterans at all levels of the organization (Hunter‐Johnson et al., 2020).
However, the veteran-friendly differentiator that ERGs can become for an organization, which is
widely adopted, is loosely utilized (M. Kirchner & Minnis, 2018). In addition to ERGs, some
organizations institute mentoring programs specific to veteran employees (Curry Hall et al.,
2014).
Many companies attempt to appear military-friendly to distinguish themselves (M.
Kirchner & Minnis, 2018). In contrast, M. J. Kirchner et al. (2020) posited that many companies
claiming to be friendly to military veterans may have difficulty explaining why and how they are
friendly but are also unwilling to be characterized as unfriendly. Research suggests that
maintaining a veteran-friendly workplace requires effort, and civilian organizations should foster
an environment where these employees can exercise their military identity and contribute to
challenging positions because of their leadership experiences. Research may also suggest that

26
human resources leaders must recognize their veteran employees’ attributes (Hunter‐Johnson et
al., 2020) and that the organizations’ best practices should be imitated (Caamal, 2019). Despite
the advances in veteran-friendly practices, their employees may still misunderstand this
population.
Misunderstanding of Veterans by Employers in the Hiring Process
Many studies have evaluated the effects of military service on post-service employment
in the civilian sector. In those studies, the factors that relate to a misunderstanding by employers
in the hiring process are a prominent theme. Some studies have focused on employment-related
outcomes of veterans who served in arduous environments abroad (Merritt et al., 2020). It is
argued that employers must understand the process individuals must undergo after leaving the
military to improve their transitional outcomes and help them find the right hire for the right
opportunity (Dexter, 2020a). Still, the research demonstrates that civilian hiring managers
without military experience struggle to comprehend military service, which may negatively
affect hiring initiatives (Dempsey & Schafer, 2020). P. Carter et al. (2017) suggested that
articulating valuable military skill sets, such as leadership, on a resume may be difficult and
affect veteran employment outcomes.
Discrimination against veterans, which may also impact their employment outcomes, is
less understood and, until recently, was not well-researched (Stone et al., 2018). Discrimination
in the hiring process may be attributed to negative perceptions about mental stability and combat
experience (Ward, 2020). Loughran (2014) suggested, however, that while discrimination is
inevitable, the evidence does not support that it alone accounts for poor veteran hiring statistics.
Other authors note that veterans are associated with positive and negative stereotypes (Stone et
al., 2018). Challenges with capturing discriminatory dynamics may have prevented adequate

27
research because of small sample sizes and difficulty accessing the right population groups
(Dempsey & Schafer, 2020), and further research is needed.
Military work remains primarily misunderstood by civilian hiring managers (Minnis,
2017). In addition to veterans’ difficulties with translating their experiences and fighting through
discrimination, other factors may increase a misunderstanding of them. The HR community
generally does not understand how the skills acquired in the military are relevant and valuable to
the business environment; instead, they stigmatize their skills as those only related to combat
(Ward, 2020). In other cases, hiring managers and HR professionals have demonstrated an
inability to fully comprehend and understand the breadth and depth of military veterans’
experiences, knowledge, skills, and abilities (Blank, 2019). A supportive study also concluded
that the possibility of unfamiliarity with veterans’ experiences could decrease the HR
community’s ability to assess them as civilian job candidates properly (M. E. Keeling et al.,
2019). Another reason for misunderstanding could be related to the application systems
employers use. M. J. Kirchner et al. (2020) found that these systems may be ineffective in
capturing candidates with appropriate skill sets, which could filter out ideal candidates because
of a knowledge gap on the veteran’s part in correctly translating their experiences or, during the
interview phase, may not effectively translate their skillsets verbally. Finally, M. Kirchner and
Akdere (2019) concluded that more research needed to be conducted to understand better the
translation of those experiences by the HR community.
Despite efforts to better understand them, military veterans still struggle to translate their
experiences and stress the importance and criticality of their prior achievements. Even in a
specialized workforce such as the medical profession, translating standard skillsets is difficult.
One article demonstrated the difficulty in transitioning from an identical position in the military

28
into one in the civilian sector as an example to prove that the transition is more than just taking
off the uniform (Davis & Minnis, 2017). As the authors suggested, translating their skills is
among the most challenging parts of the transition process, and applying those skills is equally
difficult for the organization (Davis & Minnis, 2017). Further, Hanson and Lerman (2016)
suggested that despite the years of experience gained in the military, veterans may have to
undergo more training and education to earn certificates to demonstrate proficiency in a role they
have mastered through military service to be viable for employment in the civilian sector.
Employers misunderstanding in the hiring process, whether due to a compounded effect due to
discrimination, a lack of effort, a lack of knowledge, or a lack of willingness to improve within
the HR community, leaves room for improvement.
Misunderstanding of Veterans by Employers Once Employed
There are many reasons veterans may struggle with their employers after they begin
working for them. Misalignment in communication is an explanation for misunderstandings in
the workplace, as both sides may fail to fully understand the applicability of skillsets (Flatt &
Rhodes, 2019). Veterans also continue to face cultural challenges in adapting to civilian work
environments (Minnis, 2020). Challenges include fitting into the culture, identifying their
purpose, not understanding their career trajectory, and other issues not addressed (M. J. Kirchner
et al., 2020). As a result, veterans may develop negative perceptions of their employers and vice
versa (Yanchus et al., 2018). Lastly, additional barriers may create culture and communication
challenges, such as the military’s use of acronyms and differences in military collaborative,
collective, and team-based concepts versus the civilian world’s frequent focus on individuality
and individual achievement (M. E. Keeling et al., 2019). Therefore, ERGs may assist with
breaking down some of the barriers, and the HR community can improve upon their shared

29
experiences to create a better, more understanding environment for veterans to work within.
Aside from the general veteran population, the senior military officer is also misunderstood.
Misunderstanding of SMOs by Employers
Senior military officers represent a small, highly talented subset of the military’s officer
corps, but their skills and talents are not well-researched (Yanchus et al., 2018). One of the
challenges that SMOs may face in their pursuit of civilian employment is translating their
leadership achievements, ones that were duly earned over time but that may not be recognized in
totality by a civilian organization or may be miscategorized (Biniecki & Berg, 2020). Another
challenge SMOs may face is the enduring one of perceived skill transferability (Ward, 2020).
Biniecki and Berg (2020) suggested that civilian organizations do not understand the SMO’s
elite nature. Further, while they may be universally categorized as leaders, according to the
authors, they may struggle to demonstrate their leadership experience’s applicability within the
hiring process, which could lead to misalignment in employment (M. Kirchner & Akdere, 2019).
In addition, preparation programs, hiring initiatives and programs, manager training, and ERGs
all influence employment outcomes. Leadership is a principal attribute and experience that
research consistently demonstrates is related to military veterans. As leaders, their value to
organizations beyond their service is an area for further investigation.
Veterans as Leaders
The premise of this literature review is that veterans are leaders, and their leadership
attributes apply to the private sector beyond their military service. Research suggests that
military experience, as examined within the context of corporate leadership, is decidedly
valuable to a corporation (Simpson & Sariol, 2019). Military service, experiences, and skillsets
provide the qualifications to lead and direct at high levels. According to Swain and Pierce

30
(2017), “convincing others to collaborate effectively is the primary function of all armed forces
officers, and every officer is a leader expected to guide their followers to mission success at least
possible cost” (p. 57). The leadership attributes that veterans possess are quantifiable and welldocumented. Military leadership is believed to be comprised of attributes relevant to the civilian
employment sector: leadership, teamwork, resilience, work ethic, communication, attention to
detail, self-discipline, dependability, experience training others, experience with safety
compliance, flexibility, mission-focused, initiative, cross-cultural understanding, maturity, global
perspective, trustworthiness, loyalty, organizational commitment, problem-solving,
responsibility, courage, and knowledge/expertise in defense issues (Pollak et al., 2019). After
examining the leadership value of veterans in post-military academic settings, Cox (2019)
concluded that military veterans demonstrated several leadership-related attributes, such as team
membership, team leadership, diversity, punctuality, flexibility and adaptability, an ability to be
self-directed, a possession of outstanding work habits, a commitment to excellence, a global
outlook, and an investment in their communities.
Military leadership leads to successful outcomes during times of ambiguity (Dixon et al.,
2019). Replicating some organizational leadership dynamics within non-military organizations
could benefit those organizations because it may emphasize initiative and leadership at its lowest
levels (Dykes & Winn, 2019). The military can also teach the civilian sector another valuable
leadership tactic by exhibiting more frequent leadership rotation. S. P. Carter et al. (2016) noted
that firms that move employees routinely may experience higher retention than those that
minimize movement. It is essential to discuss veterans’ leadership traits, the transformational
characteristics of those traits, veteran-specific leadership experiences, how they, as leaders,
perform in the private sector, and why they continue leading in the private sector. This portion of

31
the literature review will summarize relevant literature that supports the notion that veterans are
leaders and that the leadership skills earned through service translate to organizations after
service.
Veteran Leadership Traits
The leadership traits of military veterans are well-documented and known to consist of
years of leadership training, problem-solving, and innovation attributes (U.S. Congress House
Committee on Veterans’ Affairs Subcommittee on Economic Opportunity, 2019). The ability to
lead and communicate effectively is a highly transferrable corporate skill (Minnis, 2020).
Leadership skills and teamwork are the most valuable veteran qualities (Curry Hall et al., 2014).
As Beehner (2018) noted, there are many parallels between leading on the battlefield and in the
business world, including an ability to inspire, think through a problem, learn, do, and address
inferior performance. Dexter (2020a) posited that levels of leadership in the military are
discernable, as leadership experience at the level of a commanding officer is strategic and
directive. Lastly and remarkably, Simpson & Sariol (2019) suggested that veterans may have a
higher propensity than their nonveteran peers to sacrifice all to preserve integrity, even at their
own expense.
Transformational Leadership in the Military
According to Northouse (2016), transformational leadership is the process whereby a
person engages with others and creates a connection that raises the level of motivation and
morality in both the leader and the follower. This type of leader is attentive to the needs and
motives of followers and tries to help followers reach their fullest potential (Northouse, 2016).
Military leaders have historically successfully transitioned into the civilian employment sector
(M. Kirchner & Akdere, 2019). The research also suggests that ethical, authentic, and

32
transformational leadership attributes are needed in the 21st-century business environment.
Moral leadership is considered the most effective in fostering positive outcomes (Copeland,
2016). Spain et al. (2021) noted that leadership has many similarities within military and nonmilitary settings, and Vigoda-Gadot et al. (2010) indicated that military members utilize their
experiences to succeed in their post-military careers.
There is room for improvement in understanding the military’s approach to leadership
development and how it can be applied within civilian organizations, and there is a strong
perception of veterans’ willingness to jump in and accept new leadership challenges
(“Developing Leaders,” 2018). The U.S. Army represents an ideal setting to study the impact of
leadership ability (S. P. Carter et al., 2016). According to Spain et al. (2021), battalion
commanders, representing the CEO-equivalent in the Army’s command organizational structure,
are strategically positioned because of their influence over organizational climate. These
battalion commanders are strategically positioned because of their ability to impact retention, a
critical and translatable human resources skill (Spain et al., 2021).
Building and developing leadership competencies is a unique commitment of the
military’s service branches not commonly replicated in the civilian employment sector, and M.
Kirchner and Akdere (2019) suggested that the emphasis on developing leaders is a reason
veterans frequently outperform their nonveteran peers. The U.S. Army envisions organizational
development as a continuous improvement process, and Teasley et al. (2021) noted the
similarities between the military leadership continuum and the civilian leadership continuum.
The U.S. Air Force has also invested in developing transformational leaders, incorporating
transformational leadership learning objectives into the curriculum at one of its principal officer
training schools (Arenas et al., 2017). Leadership skills are the most frequent reason the civilian

33
employment sector hires military veterans (M. Kirchner & Akdere, 2019). Grönqvist and
Lindqvist (2016), after investigating the correlation between leadership training received and
post-service employment, found that leadership training has a strong positive effect on the
probability of attaining a managerial position in the civilian employment sector, which may
prove that the civilian employment sector values military leadership experience.
Veteran Leadership Experiences
The Army defines leadership as “the process of influencing people by providing purpose,
direction, and motivation to accomplish the mission and improve the organization” (Teasley et
al., 2021, p. 63). Unlike the factors related to veterans’ employment outcomes, their leadership
experiences are well-documented and understood. Starbucks Corporation, for example, testified
to the U.S. Congress that the leadership and teamwork skillsets of military veterans make them
an excellent fit for their corporation (U.S. Congress House Committee on Veterans’ Affairs
Subcommittee on Economic Opportunity, 2019).
Leadership development is essential to the military career; its officers are groomed to
assume high-level leadership challenges to meet internal retainment requirements eventually
(S. P. Carter et al., 2016). Leadership development is not just emphasized throughout a military
member’s career; it may also help them in their post-military career (M. Kirchner & Akdere,
2019). In a supportive study, researchers found that leadership, decision-making, and
communication skills are part of the military’s work and will benefit all organizations at all
levels (Davis & Minnis, 2017). Lastly, Teasley et al. (2021) noted that grit, a term used to
describe a specific character attribute of military members, has been linked to achievement in
non-military settings.

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Veterans As Executives
Viewing veterans as executives implies that they, particularly certain SMOs with
executive-level leadership experience, can transition away from military service into the highest
levels of leadership in the civilian sector. The transferability of military leadership from the
battlefield into the office space may also be a two-way street, which supports the notion that
leadership does translate. However, one prominent retired Army general proclaimed that he had
worked with many civilian business executives who could immediately serve as military
executives (Kapp, 2018). At the core of the problem, however, is that the data shows few
companies hire veterans at the equivalent leadership level, focusing instead on hiring them for
lower, entry-level positions (Curry Hall et al., 2014). The concept of hiring SMOs into civilian
firms at the executive level is understood to be an intricate one. The author states that hiring
these types of personnel is complex because it is typically conducted through external hiring and
may require executive-level onboarding to prepare the member for a successful transition (Ford,
2017), which could represent a barrier for seasoned SMOs.
Notably, the number of executives with prior military service is decreasing. Between
1980 and 2006, despite a pool of over two hundred thousand retired SMOs, the number of CEOs
with prior military service declined from 59% to approximately 6% (Simpson & Sariol, 2019),
and the trend continued beyond 2014 (P. Carter et al., 2017). Despite the decline, the data still
demonstrates that the military service of CEOs drives their firm’s performance, as Gao et al.
(2021) linked the positive outcomes of leadership-related decisional behaviors directly to their
military service.
According to the press, military leaders can inspire, adapt, innovate, think strategically,
and drive their subordinates’ performance. The press also stipulates that military leaders are

35
learners and doers and can improvise when the environment necessitates deviation from an
intended course of action (USAWC Press, 2021). The data also supports the problem statement’s
intended research questions as prior service of an SMO as a commanding officer, if considered to
be equivalent CEO-level leadership experience, should lead to civilian CEO employment
because, in recent years, the data has shown that the incidence of hiring CEOs with prior CEO
experience has accounted for greater than 10% of all CEO hires (Bragaw & Misangyi, 2017).
The evidence supports the premise that hiring military veterans as CEOs provides tangible, real,
bottom-line impacts to an organization, as one study, comprised of several CEO interviews,
noted that leadership skills learned through military training enhance success in corporate life.
The study’s participants articulated six leadership skills essential to success: teamwork, planning,
communication, defining goals and motivation, ethics, and poise. The study further noted that
CEOs with military experience demonstrated superior management and organizational
performance (Blank, 2019).
Serving on corporate boards is another potential fit for SMOs transitioning into the
civilian sector and is an area for investigation. While there is limited data on military veteran
board membership, their membership could yield favorable results because related research has
demonstrated that CEOs with military backgrounds perform better during distress than CEOs
without military experience (Simpson & Sariol, 2019). The data suggests that the benefits of
military expertise are transferable and translatable (Simpson & Sariol, 2019), which underlines
this literature review’s premise.
Another benefit of hiring strong leaders into important leadership positions, such as
senior executive ones, is capitalizing on prior performance and experience. If it stands to reason
that individuals develop transformational and other valuable leadership traits while serving in the

36
military, and if the civilian sector will give credit to those SMOs with CEO-like experiences,
then those same organizations may benefit from SMO hiring and executive placement. First,
Bragaw and Misangyi (2017) suggested that CEOs with prior CEO experience in a highly
dynamic environment are more apt to succeed. The military checks the box for a highly dynamic
environment. Second, the results from a study by S. P. Carter et al. (2016) demonstrate that the
quality of leadership matters, which could support the argument that SMOs check the quality
box. Regardless of rank achieved in the military, Law and Mills (2017) found that prior military
service led to favorable financial performance results.
On the contrary, the literature demonstrates why SMOs may not obtain executive-level
positions because of their humble, team-first demeanor, which may appear less suitable for a
revenue-generating firm (Biniecki & Berg, 2020). Corporations may also consider military
executive hires, especially those without direct experience within the firm or even within the
industry, as counter-productive to their mission because data has shown that leadership changes
might diminish a firm’s competitive status when hiring from the outside (Kilduff, 2019). Lastly,
the research suggests that the practice of hiring SMOs into executive-level positions may have
decreased over time because of unfavorable experiences by civilian employers related to the
SMOs’ adaption to the civilian sector, arguing that the organizations were foreign to each other
and, as a result, led to less than optimal leadership outcomes (Ford, 2017). Overall, the literature
has demonstrated that the military produces strong leaders. Pairing strong leaders with
experience in the military in CEO-like positions may enhance the bottom line of corporations
and improve employee retention. Of course, pairing these SMOs assumes the SMOs are willing
to incur the post-service responsibility of serving as a CEO.

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Where Do SMOs Go After Service?
Senior military officers typically retire young enough to pursue a second career, and their
retirement consists of many dynamic considerations, factors, decisions, and plans. Being
prepared is optimal before the transition (Man & Man, 2019). Senior military officers are
distinguishable from their nonveteran peers in that they retire from their first career significantly
earlier (Warner, 2008, as cited in Man & Man, 2019). There is limited research regarding where
SMOs go after retiring from the military, but one potential avenue post-military is selfemployment. While research is limited, it is well-documented that veterans contribute
significantly to the self-employment and entrepreneur channels of the civilian sector. As Heinz et
al. (2017) pointed out, roughly 9% of all businesses nationwide are majority-owned by veterans,
who are significantly more likely to be prepared to lead others, handle change, and navigate
unpredictable circumstances (Heinz et al., 2017).
The research also suggests that many SMOs remain in the public sector after military
service. Approximately 18% to 45% of SMOs transition right back into government roles after
retirement (Biniecki & Berg, 2020), and the dynamic may be attributed to an increased
likelihood of disabled veteran status, which gives them priority over non-disabled veterans in the
hiring process (Winters, 2018). That study assumes that the priority placement is a perceived
benefit over the opportunity cost of working in the non-public sector. Schulker (2017) suggested
that the attractiveness of DoD federal employment may be related to a continuance of jobs in a
similar, if not familiar, industry. However, the dynamic of continued DoD employment may
increase difficulty in understanding reintegration challenges. If priority placement reduces the
pool of attractive SMOs available to the private sector, researchers will be less likely to achieve

38
meaningful research results (Schulker, 2017). Priority placement in public-sector roles may
contribute to an SMO’s post-military employment direction.
Reasons Why SMOs May Not Pursue Executive Opportunities
There are multiple reasons why SMOs may not pursue executive and senior executive
opportunities after military service. Considering the arduousness of a lengthy military career,
SMOs may not have the energy or desire to continue performing at a high level. They may want
to take a temporary or permanent break from senior-level responsibility. Man and Man (2019)
suggested that some SMOs may simply be tired and that their desire to transition into a position
of equivalent leadership responsibility may not be as strong as it is perceived to be, as some
might find a sense of relief from working less hard with less stress in their future endeavors.
Secondarily, Bonica et al. (2020) posited that some SMOs may want to get their footing
in the private sector before reaching CEO-like levels again. When the authors examined the
experiences of a former military treatment facility commanding officer in the Army, the
equivalent of the CEO of a hospital in the private sector, they found that while healthcare may be
standard, whether military or civilian, civilian healthcare is a different game (Bonica et al.,
2020). They learned that the research subject discourages future retirees from assuming
equivalent leadership roles upon retirement because, as suggested, taking a lower-level role to
understand the nuances of civilian healthcare is objectively likely to increase the chances of
survival once the top levels are reached again (Bonica et al., 2020).
Lastly, another reason SMOs may not pursue executive opportunities is like the
healthcare example: a sincere desire to start over. Bragaw and Misangyi (2017) suggested that
outsiders may benefit more from joining an organization closer to the ground level to learn,
grow, and undertake new challenges before jumping right back into executive-level leadership

39
roles. The authors argued that doing so may better equip them long-term for CEO-level positions
(Bragaw & Misangyi, 2017). Therefore, the reasons why SMOs may not pursue significant and
equivalent leadership opportunities upon leaving military service, either immediately or over the
long term, vary. Research should further examine the trends, opportunities, and barriers related
to SMO employment post-military and the outcomes when in senior leadership roles in the
private sector.
Summary
In summary, the literature review touched upon several principal ideas relevant to postmilitary experiences in the private sector. It included significant subject themes: the armed forces
veteran, the employment of veterans, factors affecting veteran employment, and veterans as
leaders. Each theme was expanded to cover critical and relevant literature summaries from the
previous 10-year period, including research from countless peer-reviewed journal sources,
official documents of the U.S. government, and published works written to amplify several
related themes. The literature review sought to exhaust every available academic resource to
ensure comprehensive coverage of relevant, related topics and to maximize the potential to
produce new and reliable data available to future researchers seeking to learn more about the
employment of SMOs in their post-military careers.
Conceptual Framework
Multiple factors are involved in how post-command SMOs transition from the military.
Within the KMO model, three key areas are available to identify and help explain these known
and unknown factors. The motivational aspect of the KMO model can help explain why postcommand SMOs decide to transition away from the military. It can also help to explain what
they desire in a second career, their heuristics, and the motivation behind accepting and declining

40
future roles. The motivational aspect can also apply to the hiring firm. Specifically, it can help
determine their motivation behind offering a post-command SMO a role with inequivalent
leadership responsibility and, conversely, their motivations for not doing so. The KMO model’s
knowledge aspect applies to the individual and the firm. It can help to discern if a gap exists with
a service member’s preparation and readiness for transition which the data suggests may be
inadequate to sustain the transitional needs of today’s military veterans. It may also help to
highlight gaps in employer knowledge levels as they pertain to the value that military veterans
and SMOs can provide to an organization.
Lastly, the organizational aspect of the KMO model will help identify entry barriers. It
may also provide insights related to organizational gaps that affect a military officer’s ability to
prepare, or it may provide insights into the obstacles that firms must navigate when searching for
potential CEOs and executives. The knowledge, motivational, and organizational factors
discerned through the conceptual framework should improve understanding of the influences that
affect post-command SMOs’ ability to transition into positions and roles of leadership
equivalency in the civilian sector after retiring from the military. Figure 1 is the conceptual
model showing post-command SMOs’ transition from military service into the civilian
employment sector with gaps identified by KMO.

41
Figure 1
Conceptual Framework
Methodology
The method for this study was quantitative, which presented the best pathway to collect
data about the employment experiences of a small subset of retired SMOs. The quantitative study
was the appropriate method for this study because research questions were tied directly to survey
questions, and the information needed to conclude findings related to perceptions of inequity
were easily captured, safely and anonymously, via a Qualtrics survey. Table 1 presents the KMO
aspects connected to the research questions, and Table 2 presents the connection between the
research and survey questions.

42
Table 1
Research Questions
Research questions KMO category
RQ1: what motivational influences do SMOs with
command experience report helped to prepare them
for their transition into the civilian employment
sector?
Motivation
RQ2: what do SMOs with command experience
perceive as the organizational gaps related to
transitioning to executive leadership roles at the
completion of their military service?
Organization
RQ3: What knowledge gaps do post-command SMOs
report are related to their transition into civilian
equivalent-level roles upon completion of their
military service?
Knowledge
Table 2
Knowledge, Motivation, and Organization-Related Survey Questions
Survey question Description RQ KMO
12 Did you plan to work after your military
career? 1 Motivation
32 What was your primary reason for leaving the
military service? Please choose the most
appropriate answer.
1 Motivation
33 What, if any, was a secondary reason for
leaving the military service? Please choose
the most appropriate answer.
1 Motivation
34
Upon retirement from the military, did you
desire to lead an organization in a role
equivalent to a President, CEO, Executive
Director, General Manager, etc.?
1 Motivation

43
Survey question Description RQ KMO
36
On a scale of 1-10, with “1” being the least
and “10” being the most, how strong was
your desire to assume an equivalent
leadership role within the civilian
employment sector?
1 Motivation
10
On a scale of 1-10, with “1” being the least
and “10” being the most, if applicable, how
well do you think your time as a
commanding officer/commander prepared
you for executive leadership positions in the
civilian employment sector?
2 Organizational
11 On a scale of 1-10, with “1” being the least
and “10” being the most, if applicable, how
relatable do you feel your experiences as a
commanding officer/commander are in the
civilian employment sector?
2 Organizational
29 On a scale of 1-10, with “1” being least
satisfied and “10” being most satisfied, how
satisfied are you in your current role?
2 Organizational
30 On a scale of 1-10, with “1” being the least
satisfied and “10” being the most satisfied,
how satisfied are you about the level of
responsibility your current role entails?
2 Organizational
31 On a scale of 1-10, with “1” being the least
and “10” being the most, how much do you
feel your current employer values your
executive military leadership experience?
3 Organizational
13 Did you have professional work experience
before becoming a commissioned officer? 3 Knowledge
14 During your commissioned service career, did
you experience a break in service where
you fully separated from the active
component and obtained full-time
employment, regardless of industry, before
permanently returning to active duty?
3 Knowledge
15 During your commissioned service, did you
complete an internship, fellowship, DoD 3 Knowledge

44
Survey question Description RQ KMO
SkillBridge, or any other program where
you worked full-time for a civilian
employer while on active duty?
16 Did you complete any additional transitionrelated programs besides DoD TAP? 3 Knowledge
17 If you answered “yes” to the previous
question, how many transitional programs
did you participate in besides DoD TAP?
Transitional programs may include
corporate or non-profit programs to assist
military members with their career
transition.
3 Knowledge
18 Before your military retirement, did you
receive mentoring from other retired
military officers?
3 Knowledge
35 On a scale of 1-10, with “1” being the least
prepared and “10” being the most prepared,
during your final year of military service,
how prepared were you to transition to the
civilian employment sector?
3 Knowledge
37 On a scale of 1-10, with “1” being the least
confident and “10” being the most
confident, while serving in the military,
how confident were you about your ability
to assume an executive leadership position
in the civilian employment sector?
3 Knowledge
Research Setting
The research setting for this study was fully online for the research participants and me.
Participants accessed and completed a Qualtrics-generated 37-question survey by clicking on a
survey link within an email or clicking on a link to the survey found within LinkedIn. I reviewed
aggregate respondent results online within the Qualtrics database. On LinkedIn, some

45
respondents may have indirectly indicated to me that they completed the survey by commenting
on one of the LinkedIn posts that advertised the survey. No survey participant respondents were
identified, and none were allowed to provide identifiable data tying any participant’s response to
any element of the data.
The Researcher
As the principal researcher in the study, I found it essential to approach the topic of
positionality carefully by reflecting upon and understanding how my relationship with the study
may have affected the study’s participants. As a member of the military veteran community, I, as
the principal researcher, can appreciate and relate to many of the topics uncovered through the
literature review. In contrast to the lived experiences of the study’s intended population, as an
SMO with commanding officer experience, I achieved most of my experiences in the military as
a member of the reserve component. Rather than remaining on active duty and serving through
standard military retirement, I transitioned into reserve duty after nearly 8 years of service. The
remainder of my tenure in the military, which has spanned over 2 decades, has primarily been
through reserve service. Although I experienced infrequent periods of definite recall onto active
duty, those periods were typically limited to 1 year or less.
Positionally, as a military officer, I transitioned into the private employment sector as a
junior officer, not a senior officer like the study’s target participant. Joining the corporate
workforce as a junior officer allowed my corporate career to mature differently than those who
retired from active duty after 20 years of service or more. My military leadership experience was
not at the same level as theirs, and therefore, my experiences with leadership were limited
comparably. Additionally, I did not gain my equivalent level of commanding officer experience

46
until later in my reserve career when I was simultaneously employed at or above the director
level in the civilian employment sector.
Being objective is essential to inquiry (Creswell & Creswell, 2014). I employ biases; I
have engaged in countless conversations with senior representatives from my current and
previous places of employment, all of whom hold status as members of the Fortune 500
community and have been privy to thoughts and experiences to which SMOs from the active
component may not. I understand the sentiment for the leadership skills of military officers and
the military veteran community, regardless of their seniority, and appreciate the pros and cons
that many of my corporate peers perceive. However, one comment from an executive at the
largest of my former employers planted the seed for this research when the executive posited that
“military leadership does not translate to corporate America.” While my lack of agreement with
the sentiment remains, I appreciated the position and used it to help craft a problem of practice as
the basis of this study’s intent. Through cautious and diligent analysis of this study’s results, I
have sought to understand better whether leadership opportunity inequities exist for postcommand SMOs in the private employment sector and why.
Data Source: Qualtrics Survey
I conducted the entirety of this research using a survey comprised of 37 questions
generated using Qualtrics.
Participants
Capturing the target participants was key to achieving study success. The target
participants for the study were post-command SMOs who transitioned into the private
employment sector. The study did not restrict participation based on time since retirement from
the military. While diversity of participation was critical to the study’s validity, the ideal

47
participant was broadly recruited through social media and surveyed to achieve the study’s
purpose. Ideal study participants were not many and were not easily accessible through any
commonly accessed public database. Recruitment of post-command SMOs occurred through a
combination of networking, word-of-mouth, and social platforms (primarily LinkedIn), all
required to gather enough participation to produce meaningful results.
Because participation was limited to post-command SMOs, social networking was the
most efficient avenue to capture participants. I used purposeful sampling to target the right
population by providing the survey’s access link to potential participants and those who could
readily forward the link to others. I used the survey’s screening mechanisms (Questions 1 and 6)
to determine whether a potential participant met the study criteria. A census-based approach,
such as posting the link on LinkedIn, was the primary means of broadcasting to share the
survey’s access link across a broad audience. LinkedIn, a professional social network, is believed
to provide the greatest return on investment in capturing the target population. Lastly, it was
important to recognize and understand how the participants make sense of their lived experiences
and how their understanding influences their behavior (Maxwell, 2006).
Instrumentation
The instrument used to collect data in this study was a survey. Surveys are the most
effective approach to collecting quantitative data because of their ease of distribution, flexibility
in question format, and ability to standardize questions that tie directly to the research questions.
Several questions within the survey utilized a Likert scale, while others had either binary or
multiple-answer choices. Some multiple-choice questions included the ability to choose options
other and not applicable. In the three instances where respondents selected the former, they had
the opportunity to write an answer. In other cases where a participant may find that more than

48
one selection choice applies, a follow-up question allowed for a second selection. In summary,
the survey aimed to understand the experiences of post-command SMOs better and determine if
causal relationships existed that may help close knowledge, motivational, and organizational
gaps in the employment of a uniquely small subset of military veterans.
Data Collection Procedures
Data collection was limited to survey response completion. As the surveys were
completed, the responses were recorded within Qualtrics for future survey response analysis. In
some instances, incomplete surveys still recorded answers. A small percentage of surveys were
recorded without ever being answered. Access to the surveys was provided continuously for
approximately 5 weeks or 42 days, and responses were analyzed once the survey link was
deactivated. After deactivating the survey link, I reviewed and examined the responses using
internal Qualtrics tools and resources. Surveys were only collected using Qualtrics; participants
could not print and mail their responses or provide survey responses to me directly. It was
ultimately my responsibility to proceed as ethically as possible (Glesne, 2011). No responses
were received outside of the Qualtrics tool. The review lasted approximately 2 weeks, with
findings provided in chapter four of this document. I did not take free-hand-written notes. The
hand-typed notes I took during the data collection shall be discarded in accordance with
approved research completion protocols.
Data Analysis
I examined the data using all resources and tools available within the Qualtrics survey
platform, including frequency, regression, and correlation. I posted a link to the survey on
LinkedIn, inviting prospective participants who met the study criteria. I also distributed The
anonymous survey access link to a handful of peers who could further distribute the link to their

49
peers or to those they felt met participation requirements. As a quantitative survey, response data
were limited in how they were reviewed. While Qualtrics enabled the exportation of data to
various formats, such as Microsoft Excel, 100% of the data analysis was conducted within the
tool for continuity of data analysis. Therefore, the data were not accessible via any other
medium. As anticipated, respondents spent approximately 6 minutes answering the survey’s 37
questions. The survey was accessible via web browser and mobile device. If a respondent’s
survey was interrupted for any reason, the survey was still accessible for up to 1 week after the
respondent began the survey. In those instances, if the respondent failed to return to the survey
within the allotted amount of time, their responses were recorded, and their survey was logged as
complete.
Validity and Reliability
Maximizing the validity and reliability of the study was an essential aspect of
contributing to academic research. Maintaining careful and strict compliance with validity and
reliability standards ensured continuity and endurance toward future research in the study’s
educational reach. The study’s validity ensured that the test measured what it was supposed to
measure, and its reliability ensured that measurements were consistent (Salkind, 2014).
I designed the study’s 37 survey questions tied to the study’s three research questions. I
constructed the designed questions using my real-world experience in the military and within
corporate America, the myriad conversations with HR leaders through a thorough review of the
literature, and countless conversations with veteran employment subject matter experts. The
questions were designed to understand the baseline demographical data of the participant’s
employment experiences and explore their perceptions of how their military leadership
experiences translated into the civilian employment sector.

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According to Merriam and Tisdell (2015), ensuring validity and reliability requires
ethically conducting the research. To address concerns related to the study’s reliability and
validity, I paid careful attention to the study’s data collection, analysis, interpretation, and
presentation. To further drive the study’s validity, all survey questions were directly related to
the study’s three research questions, and none sought to address items not explicitly covered
within the realm of the study’s proposed reach. I ensured the survey was comprehensible to drive
its reliability. Because of the unambiguous nature of the survey’s questions, it was easy for
respondents to comprehend and answer quickly based on their experiences in the military.
Therefore, unless participants choose not to be truthful with their answer choices, their answer
selections for any question would always result in the same answer choice because it could only
be unique to their experience, which may or may not be like their peers.
Findings
I conducted the research by collecting anonymous responses to a Qualtrics survey
comprised of 37 questions, as detailed in the methodology section. The survey was published on
June 8, 2024, and was accessible to the public through the end of July 14, 2024 (5 full weeks).
Using Qualtrics’ anonymous survey link creation tool, I created only one anonymous link to
access the survey. The link was distributed primarily through LinkedIn. Beginning on July 8,
2024, I initially posted an announcement to solicit survey respondents and marked the post to be
available to the public without restrictions as to who could see and comment on the post. I
detailed the requirements for participation as a screening mechanism within that post.
Approximately 2 weeks later, two peer connections who are active LinkedIn members with vast
networks of followers also created new posts featuring the survey with the same link. After each
of their posts encouraged participation and highlighted the importance of responding, there was a

51
surge in respondents. I also emailed the link to a small pool of potential respondents who may
have also distributed it.
Determining an ideal respondent size proved difficult. According to publicly available
data, the total population of retired SMOs is approximately 208,000 (U.S. Department of
Defense, 2022). The total population includes every retired officer representing pay grades O-5
and above (the study’s target population), up through the highest pay grade of O-10, from all
service branches, excluding the U.S. Coast Guard and National Guard. There is limited publicly
available data to determine the number of officers who held the position of commanding officer
or commander within their service branches. To approximate the total population that would
have completed tours in command, I used a report detailing the Navy’s recent manpower
analysis as a frame of reference (U.S. Government Accountability Office, 2021). According to
the report, approximately 20% to 25% of officers at or above the pay grade of O-5 will retire
with commanding officer experience.
Further, a conversation with a senior manpower subject matter expert within one of the
service branches estimated that the number could range between 25% and 35%, depending on
the officer community (job type) in which the SMO served. Using the more conservative number
of 35%, an estimation from the total population of retired SMOs would yield approximately
72,800 SMOs that retired at or above the pay grade of O-5 and completed at least one command
tour (at or above the pay grade of O-5) during their military careers. Using a sample size
calculation tool provided by Qualtrics, which is based on Slovin’s Formula, with N being 72,800,
the ideal sample size using a 95% confidence factor ranges from 96 respondents (10% margin of
error) to 383 respondents (5% margin of error). At the time of the survey’s close date for

52
analysis, 267 responses were collected, representing a less than 6% margin of error per Qualtrics’
sample size calculation tool.
Survey Adjustments
I made three edits to improve the validity and reliability of the survey data. I made the
first edit before the survey was published and before any responses were recorded. I added two
options (Army National Guard and Air National Guard) to a demographic question (Question 5)
inquiring about the branch of service from which the respondent retired. The first edit also
included the introduction of skip logic to bypass questions related to having command for
respondents who indicated they had not held command positions during their careers. Therefore,
if a respondent were to answer no on Question 6, indicating they had not completed a tour in the
position of a commanding officer or commander at or above the pay grade of O-5, they were
advanced to Question 12, bypassing all Questions 7–11, all of which are related to a yes response
on Question 6.
The second edit to the survey occurred after 191 responses had been recorded. It moved
two Likert-scale questions related to a yes answer on Question 6 toward the front of the survey
within the grouping of questions strictly related to an answer of yes to Question 6 (Questions 7
through 11). The second edit to the survey also introduced skip logic to bypass questions related
to current employment for those who indicated they were not currently employed (Question 21),
advancing respondents who answered Question 21 with a no to Question 32.
Lastly, the change moved Questions 30 and 31, which should have only been answered
by respondents who indicated that they were currently employed, into the grouping of questions
covered by the currently employed skip logic (Questions 22–31) to prevent them from being
responded to inappropriately. Before the second edit, 20 respondents answered no to Question 6

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inappropriately responded to Question 36, and 21 answered no to Question 6 inappropriately
responded to Question 37, which had a negligible impact on their average scores. Additionally,
two respondents inappropriately answered Question 22, two respondents inappropriately
answered Question 23, 18 respondents inappropriately answered Question 24, five respondents
inappropriately answered Question 25, two respondents inappropriately answered Question 26,
two respondents inappropriately answered Question 27, one respondent inappropriately answered
Question 28, 17 respondents inappropriately answered Question 29, 21 respondents
inappropriately answered Question 30, and eight respondents inappropriately answered Question
31, which were also assessed to have negligible impacts upon their average scores.
The third edit occurred after 220 recorded responses. It added three new skip logics to
refine response patterns further and prevent inappropriate responses. The first skip logic relates
to Question 16 about whether the respondent completed additional transitional programs. If the
respondent answered yes to Question 16, they would be advanced to Question 17, which then
asked how many additional programs the respondent participated in and completed. If the
respondent answered no to Question 16, they would bypass Question 17 and advance to Question
18, unrelated to Question 16. The second skip logic pertained to Question 24, which asked about
serving in an executive-level leadership role. If the respondent answered yes to Question 24, they
would advance to Question 25, which further investigates the answer. If they answered no to
Question 24, they would bypass Question 25 and advance to Question 26, unrelated to Question
24. The third skip logic relates to Question 26 about whether the respondent had any direct
reports. If the respondent answered yes to Question 26, they would advance to Question 27,
which further investigates the answer. If the respondent answered no to Question 26, they would
bypass Question 27 and advance to Question 28, unrelated to Question 26. Before the third edit,

54
four respondents answered no to Question 16 and inappropriately responded to Question 17, 28
answered no to Question 24 and inappropriately responded to Question 25, and two respondents
answered 0 to Question 26 and inappropriately responded to Question 27, which had a negligible
impact upon their average scores.
Data Filtering
Four data filters were created to understand better response patterns in preparation for
answering the study’s research questions. The data filters appropriately narrowed the responses
into four groups as follows:
Filter 1 (Baseline). Showed data for those who answered yes to Question 1, indicating
that they retired at or above pay grade O-5.
Filter 2 (Command). Included all respondents from Filter 1, plus those that answered
yes to Question 6, indicating that they completed a tour in the position of a commanding officer
(USN/USMC/USCG) or commander (USA/USAF) at or above the pay grade of O-5.
Filter 3 (Employed): Included respondents from Filters 1 and 2, plus those that answered
yes to Question 21, indicating that they were employed at the time of their response to the
survey.
Filter 4 (Executive): Included respondents from Filters 1, 2, and 3, plus those that
answered yes to Question 24, indicating that they were serving in an executive leadership role at
the time of their response to the survey.
Description of Data
The 37-question survey comprised 19 questions related to the respondent’s background
(demographical), eight questions related to respondent motivation, five questions related to
respondent knowledge, and five questions prospectively related to a respondent’s organization

55
(employer). The demographical questions provided insight into the respondent’s background and
were used to create the data filters because pay grade at retirement, having held a command
position, being employed, and being in an executive role were key screening factors for effective
analysis when searching for key relationships. All questions were described using Filter 1, which
removed 11 respondents who did not qualify to complete the survey because they were not
SMOs who retired at or above pay grade O-5. Therefore, 256 of 267 responses is the baseline
and the maximum number of responses for any question. Further, response counts to various
questions may differ as there was no mechanism to prevent a respondent from skipping a
question or choosing not to respond.
Relationship of Data
I conducted an examination of survey data to identify key relationships. To highlight
areas where significant statistical relationships existed, I used four data filters to refine the data
for appropriate analysis related to the study’s three research questions.
Filter 1 was necessary to remove non-eligible responses from the data set because,
despite the survey’s eligibility criteria announcement, two non-eligible respondents completed
the survey. Filter 2, which represented the next step in the filtering process, removed responses
from respondents who did not hold a commanding officer or commander position at or above the
pay grade of O-5 (Question 6). Because the study’s research questions were based on command
experience, Filter 2 was assessed to be the most appropriate for analyzing relationships to answer
the study’s research questions. Filter 1, however, also provided meaningful data related to the
study’s research questions because nearly an equal number of respondents to the survey met the
requirements of Filter 1 but did not have any command experience (Question 6) to pass the
screening function of Filter 2.

56
After filtering the data using Filter 2, a relationship analysis was conducted for each
survey question to determine if a statistically significant relationship existed between any two
questions. Additionally, a large amount of statistically significant data was found using Filters 3
and 4 pertaining to relationship analysis to highlight key statistically significant relationships.
Still, while insightful, those filters were beyond the study’s intent.
To conduct the required relationship analysis, I examined each of the survey’s 37
questions against each other using the most appropriate statistical significance testing method
available, as determined by Qualtrics, the survey’s collection tool. Two-tailed testing methods
utilized throughout the relationship analysis were ANOVA, t-test, chi-squared test, Fisher’s exact
test, and correlation. P-values less than 0.05 are statistically significant with a 95% confidence
factor.
I examined each relationship across two spectrums: Filters 1 and 2. I used Filters 3 and 4
to examine relationships in very few circumstances. Question 1 was a requirement to pass the
Filter’s test and was, therefore, not a viable question to pair with any other question for
relationship examination. Moving onto Filter 2, I examined 34 relationships (35 questions)
because Questions 1 and 6 were required to pass the Filter’s test and were excluded from
examination pairing. Additionally, I conducted a regression analysis within Filter 2 to examine
relationships between dependent and independent variables.
Beginning with the eight Likert-scale questions (10, 11, 29, 30, 31, 35, 36, 37), I
examined each to identify correlations for any set of pairs (Tables 3 and 4). For non-Likert-scale
questions, was conducted the same relationship analysis and tested each survey question for
statistically significant relationships against each of the survey’s remaining 36 questions. In each
relationship analysis, I used a filter to examine the relationship.

57
Table 3
Correlation of Likert-Scale Questions Using Filter 1 (Baseline)
10 11 29 30 31 35 36 37
10 - 0.0000 0.0293 0.0214 0.0039 0.0000 0.0001 0.0000
11 0.0000 - 0.0015 0.0639 0.0000 0.0001 0.0000 0.0000
29 0.0293 0.0015 - 0.0000 0.0000 0.0000 0.4470 0.7470
30 0.0214 0.0639 0.0000 - 0.0000 0.0000 0.6010 0.8780
31 0.0039 0.0000 0.0000 0.0000 - 0.0000 0.6450 0.0272
35 0.0000 0.0001 0.0000 0.0000 0.0000 - 0.2320 0.0044
36 0.0001 0.0000 0.4470 0.6010 0.6450 0.2320 - 0.0000
37 0.0000 0.0000 0.7470 0.8780 0.0272 0.0044 0.0000 -
Table 4
Correlation of Likert-Scale Questions Using Filter 2 (Command)
10 11 29 30 31 35 36 37
10 – 0.0000 0.0293 0.0214 0.0039 0.0000 0.0001 0.0000
11 0.0000 – 0.0015 0.0639 0.0000 0.0001 0.0000 0.0000
29 0.0293 0.0015 – 0.0000 0.0000 0.0000 0.5030 0.7020
30 0.0214 0.0639 0.0000 – 0.0000 0.0000 0.4310 0.6710
31 0.0039 0.0000 0.0000 0.0000 – 0.0000 0.9890 0.0301
35 0.0000 0.0001 0.0000 0.0000 0.0000 – 0.4050 0.0020
36 0.0001 0.0000 0.5030 0.4310 0.9890 0.4050 – 0.0000
37 0.0000 0.0000 0.7020 0.6710 0.0301 0.0020 0.0000 –
Note. Blank cells indicate that statistical test results could not be determined because the same
two questions cannot be tested against each other.

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Using Filters 1 and 2 to examine relationships between Likert-scale questions revealed
several statistically significant correlations. P-values highlighted in bold represented strongly
correlated relationships.
Research Question 1: What Motivational Influences Do SMOs With Command Experience
Report Helped to Prepare Them for Their Transition Into the Civilian Employment
Sector?
There were five survey questions related to motivation. Question 12 sought to understand
whether the respondent desired to seek employment after military retirement. Questions 32 and
33 sought to understand the primary and secondary reasons leading to military retirement.
Question 34 sought to understand how strong the respondent’s desire was to become a leader of
an organization, and Question 36 sought to understand how strong the respondent’s desire was to
assume a role of equivalent leadership responsibility. Based on analysis of survey responses and
identified statistically significant relationships (Table 5), including correlations between
“feeling-based” Likert-scale questions, there are several motivational influences that SMOs with
command experience reported may have helped prepare for their transition into the civilian
sector.
Table 5
Regression Analysis of Motivation Variables Upon Question 35 Using Filter 2 (Command)
12 32 33 34 36 TOT
Question 35 11.6% 19.3% 25.4% 31.2% 12.5% 100.0%
Sample size 183
R-squared 16.2%
Standard error 2.42
Coefficient of variation 0.432
P-value 0.0155

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Using a regression analysis model to examine the relationship between motivation-based
questions (independent variables) and the perceived level of preparedness to enter the civilian
workforce at military retirement (Question 35, the dependent variable), in combination, as
described in Table 5, Questions 33 and 34 explain over 50% of the model’s results. Further, as
reflected in Tables C28 and C29, Questions 32 and 33, which directly asked respondents about
their motivating factors leading to retirement, provided tremendous insight. Family and career
aspirations were the primary and secondary reasons for retirement among the Filter 2
(Command) cohort. That means that for those who completed commanding officer tours,
becoming an executive leader in the civilian employment sector was not the top reason for
military retirement. In combination, Questions 32–34 explained nearly 75% of the regression
model’s outcome at a statistically significant level. Of the five independent variables
(motivational questions), all were individually statistically significant factors related to
respondent perception about preparation for retirement. Table 6 presents the relationship between
Question 34 (desire to lead an organization) and Question 24 (attained an executive role).
Table 6
Relationship Between Question 24 and Question 34 Using Filter 2 (Command)
Question 34
Question 24 Yes No Total
Yes 18.6% 10.3% 28.9%
No 32.1% 39.1% 71.2%
Total 50.7% 49.4% 100%
Sample size 156
P-value 0.0342

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Based on the data, it is difficult to conclude that the motivational influences outlined in
Tables 5, C28, and C29 wholly explain the sufficiency of preparation for retired SMOs entering
the civilian employment sector. Additionally, the descriptive data provided in Tables C27
(Question 12), C30 (Question 34), and 6 (relationship between Questions 24 and 34) indicates
that while the relationships are statistically significant, it is inconclusive considering the large
percentage of respondents that indicated positional equivalency was neither their primary reason
for retirement (Table C28) nor their strong desire (Table C31).
Research Question 2: What Do SMOs With Command Experience Perceive As the
Organizational Gaps Related to Transitioning to Executive Leadership Roles at the
Completion of Their Military Service?
There were five survey questions related to organization. The organizational questions
are believed to signify respondent perception about how their lived experiences translate into the
civilian employment sector. Question 10 sought to understand how much the respondent’s
command experience prepared them for executive-level leadership positions in the civilian
employment sector, and Question 11 sought to understand how relatable the respondent felt their
command experience was in the civilian employment sector. Question 29 sought to understand
how satisfied the respondent was with their current role (if employed), Question 30 sought to
understand how satisfied the respondent was with their current level of leadership responsibility
(if employed), and Question 31 sought to understand, from the respondent’s perspective, how
much their employer valued their executive military leadership experience. All questions were
examined using Filter 2, and the examination highlighted organizational gaps related to
transitioning into executive leadership roles at the completion of a respondent’s military service.

61
Tables 7 and 8 describe regression analysis conducted on Questions 35 and 36 using
Filter 2 (Command). Table 7 describes the relationship between each of the five organizationalrelated questions and a dependent variable, Question 35, which assessed the respondent’s
perception of their preparation to transition into the civilian employment sector upon military
retirement. According to Table 7, the primary driver of the model’s results was Question 30,
which explored respondent satisfaction with their current level of leadership responsibility.
Question 29, the second largest driver, explored respondent satisfaction in their current role, and
Question 10, the third largest driver, explored respondent perception of how their command
experiences prepared them for executive-level leadership roles. Further, according to Table 4,
which describes the correlation between the dependent and each independent variable listed in
Table 7, each of the independent variables in Table 7 has a statistically significant correlation to
Question 35.
Table 7
Regression Analysis of Organizational Variables Upon Question 35 Using Filter 2 (Command)
10 11 29 30 31 TOT
Question 35 24.5% 11.8% 25.0% 29.3% 9.4% 100%
Sample size 183
R-squared 27.0%
Standard error 2.19
Coefficient of variation 0.391
P-value < 0.00001

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Table 8
Regression Analysis of Organizational Variables Upon Question 36 Using Filter 2 (Command)
10 11 29 30 31 TOT
Question 36 37.0% 47.5% 5.2% 7.0% 3.4% 100%
Sample size 182
R-squared 11.7%
Standard error 2.51
Coefficient of variation 0.367
P-value 0.000512
Table 8 also describes the relationship between each of the five organizational-related
questions and another dependent variable, Question 36, which asked respondents about the
strength of their desire to transition into roles of leadership equivalency upon military retirement.
As described in Table 4, there is also a statistically significant correlation between Question 36,
the dependent variable in Table 8, and Questions 10 and 11, which are the largest drivers of
Table 8’s regression model. Questions 10 and 11, which assessed respondent perception about
the preparational aspects and relatability of their command experiences, accounted for 84.5% of
the model’s results. Relatedly, the higher the response to Questions 10 and 11, the higher the
response to Question 36.
Table 9 describes the relationship between Questions 11 and 24. The relationship is not
statistically significant, yet the data shows that respondents had roughly the same organizational
perceptions regardless of whether they were currently serving in an executive-level leadership
role. Further, Questions 29–31, which were screened for those currently employed, tended to
have higher values for those who responded with a yes to Question 24, as indicated in Tables 3,
4, and E43.

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Table 9
Relationship Between Question 24 and Question 11 Using Filter 2 (Command)
Question 11
Question 24 Count Average Median
Yes 43 7.16 8.00
No 111 7.09 7.00
Sample size 154
P-value 0.852
The result of the analysis, as described in Tables C32–C36, demonstrates that employee
perception of their organization’s value for their SMO command leadership experience increased
for the respondents who affirmed that they held executive-level leadership roles. The data also
demonstrates that, despite the percentage of respondents who indicated they strongly felt their
command leadership experiences were relatable and held a desire to attain an executive-level
leadership role post-military retirement, the SMOs are not systemically transitioning into those
types of roles as their first employment experience after military retirement (Table 10).

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Table 10
Relationship Between Question 24 and Question 25 Using Filter 2 (Command)
Question 25
Question 24 Yes No Total
Yes 48.9% 51.1% 100.0%
Sample size 45
P-value N/a
Question 25 was covered under skip logic; only those respondents who answered
Question 24 could respond to Question 25. Therefore, no statistical relationship could be
determined between Questions 24 and 25.
Research Question 3: What Knowledge Gaps Do Post-command SMOs Report Are Related
to Their Transition Into Civilian Equivalent-Level Roles Upon Completion of Their
Military Service?
There were eight survey questions related to knowledge. Questions 13-18 sought to
understand factors that could contribute to a respondent’s knowledge about transitioning into the
civilian employment sector. Question 35 assessed respondent feeling of preparedness to
transition into the civilian employment sector upon military retirement and Question 37 assessed
respondent confidence about their ability to assume an equivalent leadership role in the civilian
employment sector. Based on analysis of each knowledge-related survey question and response
as examined through the lens of Filters 2 and 3, there are several knowledge-related insights that
SMOs with command experience report may be related to their transition into civilian-sector
equivalent-level leadership roles at the completion of their military service.

65
Tables 11 and 12 describe that the most significant factors related to respondent
knowledge, as it pertained to their preparation, were the completion of additional transitional
assistance/preparation programs beyond those offered through DoD TAP. While mentoring
(Question 18) had a role in their preparation as it pertained to their perception of readiness to
transition into roles of leadership equivalency, its effect was minimal. Question 37 was not a
driver in either regression model’s outcome. Table C38, however, does show that Question 35
had statistically significant relationships with respondents’ confidence to transition into
executive roles (Question 37) and having received pre-transition mentoring from retired SMOs
(Question 18).
Table 11
Regression Analysis of Knowledge Variables Upon Question 35 Using Filter 2 (Command)
13 14 15 16 17 18 37 TOT
Question 35 0.1% 0.0% 0.2% 33.6% 64.8% 1.2% 0.0% 100%
Sample size 184
R-squared 15.2%
Standard error 2.39
Coefficient of variation 0.425
P-value 0.0006

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Table 12
Regression Analysis of Knowledge Variables Upon Question 35 Using Filter 3 (Employed)
13 14 15 16 17 18 37 TOT
Question 35 0.2% 0.1% 0.3% 33.4% 65.2% 0.7% 0.0% 100%
Sample size 153
R-squared 15.1%
Standard error 2.24
Coefficient of variation 0.391
P-value 0.0023
Table 13 describes respondents who provided similar Likert-scale scores for Question 10
regardless of how they answered Question 24. While the relationship was not statistically
significant, similar scores indicate that respondent perception of their command experience only
slightly improved when respondents held executive-level leadership roles in the civilian
employment sector. Relatedly, none of the eight knowledge-based questions had statistically
significant relationships with Question 24, the study’s central question. Although the description
of actual responses indicates that a knowledge gap does not exist, it is difficult to prove without
statistically significant relationships to support the basis.
Table 13
Relationship Between Question 24 and Question 10 Using Filter 2 (Command)
Question 10
Question 24 Count Average Median
Yes 44 7.95 8.00
No 111 7.99 8.00
Sample size 155
P-value 0.916

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Summary
The study’s three research questions explored how KMO affected the ability of SMOs
with command experience to transition into equivalent leadership roles within the civilian
employment sector. Central to the research questions was also how translatable the SMO’s
leadership experiences were, with the premise being that if the experiences were translatable, the
outcomes of their transition would be equivalent to leadership opportunities in the civilian
employment sector. Question 24, which asked, “Are you currently serving in an executive-level
leadership role?” was one of the study’s most important questions. Although demographic in
nature, the results related to that question, as described in Table C14, were surprising in that the
number of respondents who answered yes was less than expected. Further, the results showed
that even for those who did attain executive-level leadership roles, they were disproportionately
attained in companies that had less than 100 employees and the majority did not attain the roles
until they had at least 72 months of work experience.
Along with the overt data presented for each question and relationship, it is important to
note that the findings outlined herein represent responses from SMOs in retrospect; survey
responses were not collected in advance of their transition into the civilian employment sector.
As described in Table C1, over 50% of the survey’s respondents, regardless of status and
background (command versus non-command), retired at least 4 years prior to completing the
survey. An additional 27% of respondents had retired between 1 and 3 years prior. The majority
of respondents, therefore, had at least 1 year’s time to reflect on their preparation, perception,
and satisfaction with outcomes. Additionally, with respect to satisfaction, survey respondents’
feelings may have changed over time in one direction or another.

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Understanding how knowledge, motivation, and organization-related questions described
their lived experiences is complex. Descriptive statistics of each response tell one story at face
value, yet when related to another question, the pair may tell a different story. When a collection
of independent variables was tested to determine how much they affected a dependent variable,
results were often lower than anticipated. In summary, the data shows that motivation is a factor,
knowledge is a factor, and organization is a factor in determining transitional outcomes for
SMOs with command experience.
Recommendations
This study represents what is believed to be first-of-its-kind research: exploring the
employment outcomes of retired, post-command SMOs while also exploring the translational
attributes of their leadership experience. This study’s findings connect closely and align with the
literature review and the study’s conceptual framework.
Discussion of Findings
Examining the knowledge-based questions and preparation that SMOs underwent in
advance of their military retirement helped to connect to the greater body of academic research
available to show, first, that DoD TAP is insufficient by itself and, second, that there are other
modalities that provide value. For example, SMOs who engaged in a mentoring relationship with
retired SMOs had statistically significant outcomes related to their post-transition perception of
preparedness. Additionally, SMOs that completed additional transitional preparation programs
may have landed in the industry/sector that they desired. Preparation also impacted SMO
confidence; those who felt prepared also felt confident. Educationally (knowledge), it was
difficult to discern where the organizations stood. At no point did the survey address knowledge
factors stemming from an organization’s perspective. From the perspective of knowledge, which

69
can be viewed both from the vantage point of the SMO and the organization, advancements to
close gaps in alignment with the conceptual framework may improve outcomes for SMOs and
the veteran community.
Motivationally, the study provided new insights into why SMOs chose to transition, their
intent through transition, and their long-term goals. The literature review demonstrated that
military veterans do very well in civilian employment settings. This study’s findings demonstrate
that when motivation was a factor, the likelihood of success increased. As an example, those who
held executive-level leadership roles were largely comprised of those who indicated they wanted
to attain those roles after military retirement. Speaking toward the grit and determination that the
literature review describes as common character attributes among the veteran community and
SMOs in particular, the motivational factors examined in this study did not provide surprising
results.
The respondents also provided insights that connected back to the literature in terms of
what they were not motivated to achieve. It was, therefore, not surprising that many SMO
respondents intimated they had no desire to continue their leadership journeys in the civilian
employment sector. When those motivational desires were explored across their reasoning for
opting to retire, career aspirations were not atop the lists as the primary drivers. The literature,
therefore, accurately depicted a scenario where an SMO may have fulfilled their leadership
aspirations through their service in the military. Motivationally, it was difficult to discern where
the organizations stood. At no point did the survey address motivational factors stemming from
an organization’s perspective. From the perspective of motivation, which can be viewed both
from the vantage point of the SMO and the organization, advancements to close gaps in

70
alignment with the conceptual framework may improve outcomes for SMOs and the veteran
community.
Organizationally, the study’s findings showed that perception of gaps existed. For
example, regardless of employment outcome, the respondents with command experience felt
nearly the same about the preparational and translational aspects of their military leadership. For
those who were employed, there was a contrast between the perception of employer valuation
among the SMOs currently serving in executive-level roles and those who were not. The
perception aligns back to the literature in that a lack of understanding exists about the value of
military leadership. While some employers may be very attuned to the value that military
leadership experience brings to an organization, other employers may not be, or worse, may not
be interested, either. Organizationally, it was difficult to discern where the organizations stood.
At no point did the survey address organizational factors stemming from an organization’s
perspective, although the perceptions of countless SMOs may provide insights. From the
organization’s perspective, which can be viewed both from the vantage point of the SMO and the
employer, advancements to close gaps in alignment with the conceptual framework may improve
outcomes for SMOs and the veteran community.
The study found that approximately 28% of survey respondents, regardless of command
experience, were serving in executive-level leadership roles. The study also found that roughly
half of respondents wanted those kinds of roles at the time of retirement. For those that had
command experience, the desire to assume one of those roles was slightly greater than 50%, and
when the entirety of the respondent population was examined, the percentage was reduced to just
under 50%. Collectively, it means that, at the time of retirement, in retrospect, about half of the
SMOs did not want to serve in executive-level roles. As it relates to the problem of practice, of

71
the 50% that did, only half of them were actively achieving their goal at the time of the study.
The result of that phenomenon is that the trickle-down effect of having an SMO background may
decrease the KMO gaps at the employer level. According to the conceptual framework, the
higher the inventory of SMOs with command experience serving in executive-level roles, the
stronger the ability to attack the problem of practice. The data from this study shows that
respondents with command experience believe their experiences prepared them for equivalent
roles in the civilian employment sector and that their experiences were relatable. The statistical
significance of the correlations observed indicates that the problem of practice stands as one of
notable relevance and importance.
Recommendation 1: Mentoring
The study’s findings showed statistically significant relationships existed between
mentoring and perceptions about employer valuation of SMO leadership experiences. Those
perceptions also had statistically significant relationships with job satisfaction. Mentoring
provides a valuable opportunity to gain insights not otherwise accessible. Mentoring comes in
different forms; it may be an informal process by which a mentee has a relationship with a
mentor or a formal mentoring process by which the mentee is assigned a mentor. Additionally,
mentoring, unlike formal educational-type programs, allows for more personal relationship
development, especially when mentoring is conducted in a one-on-one setting.
Whether a one-session process or a series of multiple sessions, the relationship
development process that occurs through mentoring opens doors in knowledge and may
underscore motivational aspects related to SMO transition. For example, information gleaned
through mentoring may impact a mentee’s decision-making process or incite extra motivation
when the art of the possible was otherwise not considered. Mentoring, therefore, may enlighten

72
and improve transitioning SMOs’ understanding of the civilian employment sector, alleviate
concerns related to transitioning, and help formulate a plan of action to break down preidentified barriers to entry.
The data showed that primary and secondary reasons for military retirement varied.
Mentoring could assist retiring SMOs with extra “tribal” knowledge to prepare for the transition
in alignment with their pre-chosen reasons for retirement. Mentoring may also help guide the
mentee into the community, sector, or industry where the mentee would best thrive, which could
improve their satisfaction and potentially improve employer valuation of their SMO experiences.
Lastly, mentoring may save time. The data did not investigate the value of lessons learned. The
data showed that SMOs who received mentoring represented nearly 75% of the SMOs who
earned executive-level leadership opportunities in the civilian employment sector. Further, other
than those employed, two-thirds also engaged in mentoring. Awareness surrounding the value of
mentoring, which falls within the confluence of KMO, must be raised to improve its impact on
SMO transition effectively.
Recommendation 2: Additional Transitional Preparation Programs
DoD Skillbridge, TAP, and supplemental programs provide varied levels of value to the
transitioning military community. While only 15.6% of SMOs who are currently serving in
executive-level roles completed a DoD Skillbridge program (Table C21), 42.2% of them
completed a program in addition to DoD TAP (Table C22), and of those former SMO executives
who did, over 75% of them only completed one program (Table C23). The perceived effort for
tremendous return on investment may, therefore, be minimal.
Programs should first be geared toward the interests and experiences of the SMOs. The
data showed that a percentage of SMOs did not desire to transition into executive-level roles;

73
programs should, therefore, be targeted to capitalize on their experiences in roles that best meet
their desire and intent. Consequently, SMOs that indicated serving in an executive-level role was
their desire should be afforded opportunities to complete programs that can improve the
likelihood of them achieving their goals. Such programs should specifically be designed to
bridge all gaps in existence that may be preventing them from accomplishing their goals and
dreams. Regardless of the size or scope of the gap, they should be closed through formal
transitional support programs specifically designed to assist SMOs and SMOs with command
experience. If the gaps are related to certifications, they, too, should be closed through the
offering of formal transitional support programs that specifically target the problem.
The data also showed that the SMOs who responded to the survey had some degree of
frequency in changing jobs. On the surface, without understanding the why because of the
frequency, a program could help to reduce the frequency of job-hopping, which may also have
significant long-term beneficial effects both on the SMO and the employer. Overall, additional
transitional preparation and support programs are recommended. Through this study’s
conceptual framework, programs of this nature would work to close identifiable KMO gaps
caused by the SMO, the employer, or both.
Recommendation 3: Education for Civilian Employers
The study’s data demonstrated that the SMO’s perception of their preparedness and the
relatability of their command-level leadership experience led to varied outcomes as they pursued
executive-level roles. The literature review indicated that, to an extent, employers struggle to
understand military veteran experiences. While the literature surrounding employer struggles in
this area was generally related to more junior levels of the veteran community, the SMO
represents a tenured community with vast experiences that would likely be more complex to

74
understand. The study did not directly query employers to determine if there was a knowledge
gap at the employer level; findings were based on self-reflection from retired SMO survey
respondents who answered questions based on their perceptions. The study’s findings indicated a
notable difference in perception of employer valuation, dependent on myriad circumstances.
As it pertained to the SMO’s perception about how much their time in commanding
officer roles prepared them to assume equivalent-level responsibility post-retirement, regardless
of their post-retirement career status, the average responses were nearly identical using a Likert
scale. However, when asked about how much their current employer valued their executive
leadership experience, the responses varied depending on whether they were currently serving in
executive-level roles. Even for those currently serving in executive-level roles, their average
responses on the Likert scale indicated there is still room for improvement. Improvements to
employer knowledge may help their understanding of the SMO veteran, including their
attributes, and thereby lead to improved outcomes for SMOs. Regardless of their post-military
retirement employment desires, intent, and objectives, improvements to the understanding of
their translational leadership attributes may lead to strengthened valuations by employers of
SMOs.
Employer knowledge could be improved by introducing formal employer-focused
education programs, which would provide several indirect benefits. First, increased knowledge
about the value of SMO experience, which is distinct from other subsets of the veteran
population, may result in an introduction of additional bridge programs, targeted hiring programs
for SMOs, in-house rotational programs designed to take advantage of SMO experiences, and
other programs designed to provide SMOs with an improved ability to translate their commandlevel leadership experiences into the organization. Engagement in employer education could also

75
improve human resources leadership’s general body of knowledge, which could be translated
into new organizations as HR leaders assume roles in different companies throughout their
careers. Third, employer-focused education would lead to better financial outcomes. The costs of
replacing employees are expensive; as the literature suggests, SMOs can think tactically through
a problem and drive mission accomplishment through team leadership. Retaining that talent level
after investing in their employer-specific training would be optimal for any organization. If
employers could engage in a practice to improve the retention of proven leaders on their payroll,
it would serve their best interests. Employee happiness, an indirect product of this
recommendation, directly correlates with the employer’s bottom line. It is imperative that once
an employer hires an SMO, especially one with command-level experience, they work diligently
to place the employee in an environment where they can best utilize their experience and
succeed.
Implementation of employer education programs is a recommended best practice. Unlike
any other hiring-related phenomenon, as the problem of practice suggests, SMOs represent a
viably tenured and experienced component of the workforce that should be allowed to swim
downstream, like many of their nonveteran peers. As applied through the study’s conceptual
framework, improvements in knowledge for employers should improve overall outcomes and
transitional experiences of SMOs and, as an indirect yet highly important result, improve
transitional outcomes for other, less senior subsets of the veteran community downstream.
Limitations and Delimitations
There are several known limitations of this quantitative study. First, as a single-method
study, analyzing answers to survey questions had to be conducted at face value, as the intent
behind each answer was unknown and, likewise, unable to be determined. Respondent

76
truthfulness was assumed; there was no mechanism to control it. The survey had no mechanism
to control duplicate responses or lack of truthfulness in responses. Although skip logic was
introduced and filters in the analysis phase to weed out inappropriate responses, it was difficult
to prevent inappropriate responses from being recorded. As a result, I was not able to investigate
a particular answer or the meaning behind an open-ended (only three questions provided room to
write in text) response in a qualitative manner. As this was a quantitative study, I was restricted
from conducting further research into any particular response. I was unable to speculate upon
inferences or intentions of survey respondents and was limited to basing conclusions upon what
the responses showed, either in totality or within categories.
I was also limited by the study’s survey questions, which may help better understand the
research questions to some extent but, in reflection, may prove insufficient to make certain
concrete conclusions about aspects of the research questions. For example, questions related to
desired outcomes may have been influenced by other factors such as burn-out and factors related
to mental health and physical limitations. I was also limited in my ability to predict response
rates. Although I sought to garner as many responses as possible, limiting the survey’s
accessibility to a defined date timeline to meet research review deadlines may have caused
missed opportunities to collect pertinent data from a prospective respondent who could not
access the survey before its close. Lastly, my survey research was limited in its distribution as I
will rely on professional social networks, LinkedIn, and peers to distribute the survey to
appropriate potential participants.
I delimited inappropriate participation or survey submission through discriminatory
questions that sought to filter out participants who were not central to the study (nonveterans,
junior veterans, and veterans who did not meet experience parameters). Additionally, the survey

77
was completely anonymous. There was no ability to contact a respondent and the study was not
intended to collect their personal data. No survey respondent was tracked, and no further
information about a respondent was collected beyond the 37 survey questions. Throughout the
entirety of the response collection process and the administration of the study, extreme care was
taken to collect and review the findings safely and productively solely in an attempt to shed light
on the problem of practice and contribute meaningfully to the more significant body of academic
research available regarding the employment of military veterans.
Additional limitations of the study included no ability to explore respondent job types in
the military and their job types in the civilian sector, including their job titles. No questions
asked about how their job type or job community in their branch of service helped prepare them,
regardless of command experience. The survey’s questions did not account for those who
changed their job types during their military career, nor did it account for the small community
of former reservists that transitioned into active duty for the remainder of their careers, although
some questions may have captured their experiences, especially if they had significant
professional work experience prior to their active duty careers. The survey did not explore how
certifications, if any, affected employment accounts, and it did not explore the supplemental
preparation program types, nor did it explore the various subsects that employed respondents,
such as corporate industry, including offering a response for those that were self-employed.
Additionally, the option to select “healthcare” as the employed industry may have misled
respondents as “healthcare” can be non-profit, for-profit (corporate), or provider-side traditional
healthcare.
Other limitations of the study include the fact that due to my network as a veteran,
responses were significantly larger for veterans of the U.S. Navy. The study did not delve into

78
education (graduate or post-graduate) and how those experiences may have affected their
employment outcomes. The survey did not investigate census-related demographics to explore
how, if at all, they may have affected their employment outcomes, nor did it explore the topic of
discrimination in the civilian employment sector, either due to veteran status or for other reasons.
There were no questions to determine if the respondent was permanently retired. Questions
related to previous employment in post-military retirement were not explored for respondents
who indicated they were unemployed, nor were topics related to how the respondent obtained
previous employment after retiring from the military investigated, such as usage of a recruiter or
networking. Finally, there were no questions to learn about the average amount of time that
respondents worked in their positions (if previously employed) regardless of current employment
status, whether they had already held executive-level positions, how satisfied they were with
previous roles, the employment attainment process immediately following their military
retirement, and whether they had changed the course of their professional aspirations/career.
Recommendations for Future Research
Continued research is important to expand the academic body of data available for
employers and transitional support organizations to improve outcomes for SMOs. The limitations
of the survey, particularly about questions that were not asked and questions that were too vague,
serve as starting points for further investigation. Based on the study’s limitations, it would be
important to understand what other modalities SMOs utilized to attain employment, such as
recruiters, networking, and mentoring. Future research should also explore employment
outcomes for specific communities or job types within the military, such as aviators, human
resources officers, supply corps officers, infantry officers, and intelligence officers.

79
Future research should deeply investigate industries where SMOs are employed to
examine commonalities and relationships and determine where SMOs with command experience
are predominantly employed within the larger employment sector, otherwise known as for-profit
business or corporate America. If employed within the government, more detail should be
provided to understand better the patterns. Understanding the post-military retirement roadmap
for each respondent may provide insight into the length of time to acquire their first role, whether
they landed where they wanted to land for their first role, and the length of time, if applicable,
they spent with their first organization. The same examination could help determine levels of
happiness and satisfaction with first employers, reasons why they changed employers, and
explore topics related to veteran discrimination, a known problem within organizations of all
types. It would also be important to investigate the commonalities of what a successful transition
looked like and the factors that affected the process with more granularity. Finally, future
research should investigate commonalities in career desire and potentially the reasons for a lack
of career ambition. Examples are the extent to which burnout affects career ambition and the
extent to which career ambition affects employment decisions. Researchers should also examine
how those decisions impact their experiences within their first career opportunities, postretirement.
Opening the aperture of the survey’s protocol to allow for more written text responses
and qualitative interviews could significantly improve the study’s effectiveness and outcomes.
Conclusion
The military veteran community represents a sizeable portion of the U.S. population and
the data has demonstrated that regardless of rank or branch of service, veterans possess attributes
both unique to them and desirable to employers, especially when viewed through the lens of

80
leadership. The SMO, a tenured, experienced leader in the armed forces, is a subset that has been
shown to significantly enhance an organization’s ability to accomplish its objectives. Beyond the
SMO community, there is the exclusive subset of SMOs who had the honor of serving in
commanding officer roles – essentially serving as presidents of their organizations. Despite the
remarkable experience they possess, their post-military retirement employment outcomes vary as
it pertains to attaining equivalent levels of leadership responsibility in civilian employment and
that represents a legitimate problem of practice.
Senior military officers’ leadership experiences are valued, yet they are systemically
valued inconsistently by employers. To break the chains of inconsistency, considering the
magnitude of influence these SMOs can have on their organization’s bottom line, work must be
done. Implementing recommendations like increasing the frequency and consistency of
mentoring for transitioning SMOs, implementing more effective transitional support programs
targeted for the right audience, and implementing programs to improve employer understanding
of SMO value are minimum efforts to break the employment outcome inconsistency chain by
which they are tied. During the process of conducting the study, one voice of influence, when
apprised of the study, lamented that fixing veteran employment is “not a top-down approach; it
starts at the bottom.” As a researcher who has poured into the process to understand the risks that
lie within the gaps and seams of this problem set, I can empathize with that position, along with
many others.
The argument that launched the study, however, still stands, as individuals with a
significant level of leadership experience who desire to continue to lead at or above equivalent
levels in the civilian employment sector still exist, and the data from this study proved it. From
the perspective of the data, while difficult to draw concrete conclusions about the why behind

81
some of the phenomena discovered, there is opportunity and capability to improve employment
outcomes in this subset of the retired military community. The question still yet to be answered
is whether the intent to improve at the stakeholder level exists. As the principal researcher, I am
inclined to believe that for the SMOs, the intent exists, and it is strong. For the other
stakeholders, the employers, if the answer is yes, this study and its recommendations for research
may provide a code to improve veteran employment outcomes moving forward on a repeatable
basis.

82
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Appendix A: Retired Senior Military Officer Questionnaire
The following sections present the survey used in this study.
1. Are you a retired military officer who retired on active duty at or above the pay grade
of O-5?
Yes
No
2. How many years has it been since you retired from the military?
Less than 1
1–3 years
4–6 years
7–10 years
More than 10 years ago
3. How many years of commissioned service did you serve in the military?
Less than 20 years
20–22 years
23–24 years
25–26 years
27–28 years
29–30 years
More than 30 years
4. What was your pay grade upon retirement from the military?
O-5
O-6

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O-7
O-8
O-9
O-10
5. What branch of the U.S. military did you retire from?
U.S. Air Force
U.S. Army
U.S. Coast Guard
U.S. Marine Corps
U.S. Navy
U.S. Space Force
Air National Guard
Army National Guard
6. During your career in military service, did you complete a tour in the position of a
commanding officer (USN/USMC/USCG) or commander (USA/USAF) at or above
the pay grade of O-5?
Yes
No
7. If you answered yes to the previous question, was your assignment to the commanding
officer or commander position based on a selection board or screening process?
Yes
No

97
8. How many active duty commanding officer/commander tours at or above the pay grade
of O-5 did you complete during your commissioned service?
0
1
2
3
4
5 or more
9. During your tour as a commanding officer/commander at or above the pay grade of O-5,
did you have command of other commanding officers/commanders (i.e., commodores,
wing commanders, brigade commanders, etc.)?
Yes
No
10. On a scale of 1-10, with “1” being the least and “10” being the most, if applicable, how
well do you think your time as a commanding officer/commander prepared you for
executive leadership positions in the civilian employment sector?
11. On a scale of 1-10, with “1” being the least and “10” being the most, if applicable, how
relatable do you feel your experiences as a commanding officer/commander are in the
civilian employment sector?

98
12. Did you plan to work after your military career?
Yes
No
13. Did you have professional work experience before becoming a commissioned officer?
Yes
No
14. During your commissioned service career, did you experience a break in service where
you fully separated from the active component and obtained full-time employment,
regardless of industry, before permanently returning to active duty?
Yes
No
15. During your commissioned service, did you complete an internship, fellowship, DoD
SkillBridge, or any other program where you worked full-time for a civilian employer
while on active duty?
Yes
No
16. Did you complete any additional transition-related programs besides DoD TAP?
Yes
No

99
17. If you answered “yes” to the previous question, how many transitional programs did you
participate in besides DoD TAP? Transitional programs may include corporate or nonprofit programs to assist military members with their career transition.
1
2
3 or more
18. Before your military retirement, did you receive mentoring from other retired military
officers?
Yes
No
19. How many employers have you had since retiring from the military?
0
1
2
3
4
5 or more

100
20. How many months of employment experience do you have since retirement, regardless of
employment type or industry/sector?
0
1–12
13–24
25–48
49–72
More than 72
21. Are you currently employed?
Yes
No
22. If yes, which industry or sector are you employed in?
Government (federal, state, local, auxiliary)
Corporate (public or private)
Non-profit
Academia
Healthcare
Other __________________________________________________

101
23. If currently employed, how many employees work for your organization?
Less than 100
100 –999
1,000–4,999
5,000–9,999
10,000–25,000
Greater than 25,000
24. Are you serving in an executive-level leadership role? Executive-level roles are Vice
President or higher.
Yes
No
25. If you answered “yes” to the previous question, is your current role your first
employment experience since retiring from the military?
Yes
No
26. If currently employed, how many employees do you directly manage?
0
1–9
10–50
51–100
101–500
Greater than 500

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27. Question 27: If currently employed, how many of your direct reports also have direct
reports?
0
1–5
6–10
11–50
51–100
101–500
Greater than 500
28. Question 28: If currently employed, within your organization’s reporting structure, how
many personnel are between you and your organization’s president/CEO?
0 - choose this answer if you are the president/CEO
1
2
3
4–6
5–7
8–9
10 or more
29. On a scale of 1-10, with “1” being least satisfied and “10” being most satisfied, how
satisfied are you in your current role?
30. On a scale of 1-10, with “1” being the least satisfied and “10” being the most satisfied,
how satisfied are you about the level of responsibility your current role entails?

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31. On a scale of 1–10, with “1” being the least and “10” being the most, how much do you
feel your current employer values your executive military leadership experience?
32. What was your primary reason for leaving the military service? Please choose the most
appropriate answer.
Forced retirement
Other career aspirations
Family
Medical
Failed to promote/select
Other __________________________________________________
33. What, if any, was a secondary reason for leaving the military service? Please choose the
most appropriate answer.
Forced retirement
Career aspirations
Family
Medical
Failed to promote/select
Not applicable (N/A)
Other __________________________________________________
34. Upon retirement from the military, did you desire to lead an organization in a role
equivalent to a President, CEO, Executive Director, General Manager, etc.?
Yes
No

104
35. On a scale of 1–10, with “1” being the least prepared and “10” being the most prepared,
during your final year of military service, how prepared were you to transition to the
civilian employment sector?
36. On a scale of 1–10, with “1” being the least and “10” being the most, how strong was
your desire to assume an equivalent leadership role within the civilian employment
sector?
37. On a scale of 1–10, with “1” being the least confident and “10” being the most confident,
while serving in the military, how confident were you about your ability to assume an
executive leadership position in the civilian employment sector?

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Appendix B: Ethics
In this study, although I, as the researcher, had no direct interaction with the survey’s
anonymous participants, their completion of the study’s survey may have evoked emotions and
frustrations as they recalled any negative experiences, feelings, and perceptions about their
employers and their employment outcomes post-retirement. When asked questions directly about
their employer’s valuation of their military experience, participants may have felt anger as they
reflected on a lifetime’s worth of relevant leadership experiences incurred through their military
service. As it relates to employer valuation, negative perceptions about employers could have
detrimental effects on employee performance. They might also have been harmed by assuming
that the study’s survey questions would lead to immediate improvements, leading to perceived
better outcomes and relief. According to England (1994), it is important to look at positionality,
power, and otherness when researching. My positionality as a reserve senior military officer
simultaneously employed in the civilian employment sector may have influenced participants’
willingness to be more open in their responses because of my access and reach in both sectors.
As a result of their transparency in responses, I am responsible for carefully and thoughtfully
analyzing the aggregate data and making meaningful recommendations that may positively
impact future transitional experiences of military personnel.

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Appendix C: Supplemental Tables
Regarding Survey Question 1, of the survey’s 267 respondents, using Filter 1
(“Baseline”), 256 were retired SMOs at or above the pay grade of O-5, which became the
baseline for future analysis. The 11 ineligible survey respondents were not considered in further
analysis. Over 95% of the respondents completed the survey in under 6 minutes.
Demographic Questions (2–9, 19–28)
Tables C1–C5 present the results for Questions 2 through 6.
Table C1
Question 2: How Many Years Has It Been Since You Retired From the Military? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
< 1 year 52 20.3% 40 19.7% 31 19.9% 8 17.8%
1–3 years 64 25.0% 55 27.1% 46 29.5% 11 24.4%
4–6 years 53 20.7% 45 22.2% 33 21.2% 6 13.3%
7–10 years 38 14.8% 25 12.3% 23 14.7% 7 15.6%
> 10 years 49 19.1% 38 18.7% 23 14.7% 13 28.9%
256 100% 203 100% 156 100% 45 100%

107
Table C2
Question 3: How Many Years of Commissioned Service Did You Serve in the Military?
(Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
< 20 years 4 1.6% 2 1.0% 1 0.6% 0 0.0%
20–22 years 75 29.3% 44 21.7% 36 23.1% 12 26.7%
23–24 years 27 10.5% 16 7.9% 9 5.8% 2 4.4%
25–26 years 52 20.3% 49 24.1% 41 26.3% 11 24.4%
27–28 years 29 11.3% 25 12.3% 16 10.3% 6 13.3%
29–30 years 42 16.4% 40 19.7% 35 22.4% 7 15.6%
> 30 years 27 10.5% 27 13.3% 18 11.5% 7 15.6%
256 100% 203 100% 156 100% 45 100%
Table C3
Question 4: What Was Your Pay Grade Upon Retirement From the Military? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
O-5 110 43.0% 61 30.0% 47 30.1% 13 28.9%
O-6 132 51.6% 128 63.1% 99 63.5% 26 57.8%
O-7 4 1.6% 4 2.0% 4 2.6% 2 4.4%
O-8 7 2.7% 7 3.4% 4 2.6% 2 4.4%
O-9 3 1.2% 3 1.5% 2 1.3% 2 4.4%
O-10 0 0.0% 0 0.0% 0 0.0% 0 0.0%
256 100% 203 100% 156 100% 45 100%

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Table C4
Question 5: What Branch of the U.S. Military Did You Retire From? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
U.S. Air Force 30 11.7% 25 12.3% 22 14.1% 6 13.3%
U.S. Army 48 18.8% 37 18.2% 20 12.8% 7 15.6%
U.S. Coast Guard 10 3.9% 7 3.4% 5 3.2% 3 6.7%
U.S. Marine Corps 50 19.5% 38 18.7% 30 19.2% 4 8.9%
U.S. Navy 116 45.3% 94 46.3% 78 50.0% 25 55.6%
Air National Guard 1 0.4% 1 0.5% 0 0.0% 0 0.0%
Army National Guard 1 0.4% 1 0.5% 1 0.6% 0 0.0%
256 100% 203 100% 156 100% 45 100%
Table C5
Question 6: During Your Career in Military Service, Did You Complete a Tour in the Position of
a Commanding Officer (USN/USMC/USCG) or Commander (USA/USAF) at or Above the Pay
Grade of O-5? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 203 79.3% 203 100.0% 156 100.0% 45 100.0%
No 53 20.7% 0 0.0% 0 0.0% 0 0.0%
256 100% 203 100% 156 100% 45 100%

109
Question 7 is a screened question; only those who responded with yes to Question 6 were
able to respond. Therefore, Filters 1 and 2 would yield the same response counts (Table C6).
Question 8 is a screened question; only those who responded with yes to Question 6 were able to
respond. Therefore, Filters 1 and 2 would yield the same response counts (Table C7). Question 9
is a screened question; only those who responded with yes to Question 6 were able to respond.
Therefore, Filters 1 and 2 would yield the same response counts (Table C8).
Table C6
Question 7: If You Answered Yes to the Previous Question, Was Your Assignment to the
Commanding Officer or Commander Position Based on a Selection Board or Screening
Process? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 179 95.7% 179 95.7% 151 96.8% 43 95.6%
No 8 4.3% 8 4.3% 5 3.2% 2 4.4%
187 100% 187 100% 156 100% 45 100%

110
Table C7
Question 8: How Many Active Duty Commanding Officer/Commander Tours at or Above the
Pay Grade of O-5 Did You Complete During Your Commissioned Service? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
1 90 48.1% 90 48.1% 77 49.4% 19 42.2%
2 53 28.3% 53 28.3% 43 27.6% 14 31.1%
3 26 13.9% 26 13.9% 22 14.1% 7 15.6%
4 13 7.0% 13 7.0% 11 7.1% 4 8.9%
5 or more 5 2.7% 5 2.7% 3 1.9% 1 2.2%
187 100% 187 100% 156 100% 45 100%
Table C8
Question 9: During your tour as a Commanding Officer/Commander at or above the pay grade
of O-5, did you have command of other commanding officers/commanders (i.e., Commodores,
Wing Commanders, Brigade Commanders, etc.)? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 86 46.2% 86 46.2% 64 41.3% 20 45.5%
No 100 53.8% 100 53.8% 91 58.7% 24 54.5%
186 100% 186 100% 155 100% 44 100%

111
Table C9
Question 19: How Many Employers Have You Had Since Retiring From the Military?
(Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
0 17 7.2% 12 6.4% 4 2.6% 3 6.7%
1 102 43.3% 85 45.5% 76 48.7% 18 40.0%
2 54 23.0% 40 21.4% 36 23.1% 11 24.4%
3 36 15.3% 32 17.1% 26 16.7% 6 13.3%
4 12 5.1% 7 3.7% 5 3.2% 3 6.7%
5 or more 14 6.0% 11 5.9% 9 5.8% 4 8.9%
235 100% 187 100% 156 100% 45 100%
Table C10
Question 20: How Many Months of Employment Experience Do You Have Since Retirement,
Regardless of Employment Type or Industry/Sector? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
0 11 4.7% 7 3.7% 0 0.0% 0 0.0%
1–12 58 24.7% 48 25.7% 40 25.6% 9 20.0%
13–24 31 13.2% 30 16.0% 25 16.0% 7 15.6%
25–48 34 14.5% 27 14.4% 25 16.0% 6 13.3%
49–72 33 14.0% 27 14.4% 23 14.7% 4 8.9%
More than 72 68 28.9% 48 25.7% 43 27.6% 19 42.2%
235 100% 187 100% 156 100% 45 100%

112
Table C11
Question 21: Are You Currently Employed? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 193 82.5% 156 83.9% 156 100.0% 45 100.0%
No 41 17.5% 30 16.1% 0 0.0% 0 0.0%
234 100% 186 100% 156 100% 45 100%
Question 22 is a screened question; only those who responded with yes to Question 21
were able to respond. The response count included 14 selections for the “other” category, which
allowed respondents to write a text response if desired. 12 of the 14 “other” selections included a
written text response. Each of the 12 text responses was examined for recategorization. All 12
text responses associated with “other” selections were appropriately recategorized into the
“Corporate” category, leaving the two remaining “other” selections with written text unchanged
(Table C12).

113
Table C12
Question 22: If Yes, Which Industry or Sector Are You Employed in? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Academia 11 5.7% 10 6.4% 10 6.5% 3 6.7%
Corporate 121 63.0% 98 62.8% 97 62.6% 29 64.4%
Government 41 21.4% 33 21.2% 33 21.3% 6 13.3%
Healthcare 5 2.6% 4 2.6% 4 2.6% 1 2.2%
Non-Profit 12 6.3% 9 5.8% 9 5.8% 5 11.1%
Other 2 1.0% 2 1.3% 2 1.3% 1 2.2%
192 100% 156 100% 155 100% 45 100%
Question 23 is a screened question; only those who responded yes to Question 21 were
able to respond (Table C13). Question 24 is a screened question; only those who responded yes
to Question 21 were able to respond (Table C14). Question 25 is a screened question; only those
who responded yes to Question 21 were able to respond (Table C15). Question 26 is a screened
question; only those who responded yes to Question 21 were able to respond (Table C16).
Question 27 is a screened question; only those who responded yes to Question 21 were able to
respond (Table C17). Question 28 is a screened question; only those who responded yes to
Question 21 were able to respond (Table C18).

114
Table C13
Question 23: If Currently Employed, How Many Employees Work for Your Organization?
(Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Less than 100 45 23.4% 40 25.6% 40 25.8% 20 44.4%
100–999 42 21.9% 36 23.1% 36 23.2% 13 28.9%
1,000–4,999 24 12.5% 16 10.3% 16 10.3% 4 8.9%
5,000–9,999 12 6.3% 9 5.8% 9 5.8% 1 2.2%
10,000–25,000 16 8.3% 14 9.0% 14 9.0% 3 6.7%
Greater than 25,000 53 27.6% 41 26.3% 40 25.8% 4 8.9%
192 100% 156 100% 155 100% 45 100%
Table C14
Question 24: Are You Serving in an Executive-Level Leadership Role? Executive-Level Roles
Are Vice President or Higher (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 53 27.6% 45 28.8% 45 29.0% 45 100.0%
No 139 72.4% 111 71.2% 110 71.0% 0 0.0%
192 100% 156 100% 155 100% 45 100%

115
Table C15
Question 25: If You Answered “Yes” to the Previous Question, Is Your Current Role Your First
Employment Experience Since Retiring From the Military? (Demographic)
Baseline Command Employ Executive
Selection Ct % Ct % Ct % Ct %
Yes 24 45.3% 22 48.9% 22 48.9% 22 48.9%
No 29 54.7% 23 51.1% 23 51.1% 23 51.1%
53 100% 45 100% 45 100% 45 100%
Table C16
Question 26: If Currently Employed, How Many Employees Do You Directly Manage?
(Demographic)
Baseline Command Employ Executive
Selection Ct % Ct % Ct % Ct %
0 82 42.7% 67 42.9% 67 43.2% 8 17.8%
1–9 73 38.0% 61 39.1% 61 39.4% 26 57.8%
10–50 26 13.5% 20 12.8% 20 12.9% 6 13.3%
51–100 5 2.6% 3 1.9% 2 1.3% 0 0.0%
101–500 4 2.1% 3 1.9% 3 1.9% 3 6.7%
Greater than 500 2 1.0% 2 1.3% 2 1.3% 2 4.4%
192 100% 156 100% 155 100% 45 100%

116
Table C17
Question 27: If Currently Employed, How Many of Your Direct Reports Also Have Direct
Reports? (Demographic)
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
0 40 36.4% 30 33.7% 30 34.1% 7 18.9%
1–5 49 44.5% 42 47.2% 42 47.7% 20 54.1%
6–10 16 14.5% 15 16.9% 15 17.0% 10 27.0%
11–50 3 2.7% 2 2.2% 1 1.1% 0 0.0%
51–100 1 0.9% 0 0.0% 0 0.0% 0 0.0%
101–500 0 0.0% 0 0.0% 0 0.0% 0 0.0%
Greater than 500 1 0.9% 0 0.0% 0 0.0% 0 0.0%
110 100% 89 100% 88 100% 37 100%
Table C18
Question 28: If Currently Employed, Within Your Organization’s Reporting Structure, How
Many Personnel Are Between You and Your Organization’s President/CEO? (Demographic)
Baseline Command Employ Executive
Selection Ct % Ct % Ct % Ct %
0 27 14.1% 26 16.7% 26 16.8% 22 48.9%
1 48 25.0% 38 24.4% 38 24.5% 16 35.6%
2 21 10.9% 17 10.9% 17 11.0% 3 6.7%
3 28 14.6% 23 14.7% 23 14.8% 3 6.7%
4–6 47 24.5% 35 22.4% 35 22.6% 1 2.2%
5–7 10 5.2% 8 5.1% 8 5.2% 0 0.0%
8–9 3 1.6% 2 1.3% 2 1.3% 0 0.0%
10 or more 8 4.2% 7 4.5% 6 3.9% 0 0.0%
192 100% 156 100% 155 100% 45 100%

117
Description of Data: Knowledge Questions (13–18, 35, 37)
Table C19
Question 13: Did You Have Professional Work Experience Before Becoming a Commissioned
Officer?
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 38 16.2% 32 17.1% 27 17.3% 7 15.6%
No 197 83.8% 155 82.9% 129 82.7% 38 84.4%
235 100% 187 100% 156 100% 45 100%
Table C20
Question 14: During Your Commissioned Service Career, Did You Experience a Break in
Service Where You Fully Separated From the Active Component and Obtained Full-Time
Employment, Regardless of Industry, Before Permanently Returning to Active Duty?
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 15 6.4% 12 6.4% 8 5.1% 1 2.2%
No 220 93.6% 175 93.6% 148 94.9% 44 97.8%
235 100% 187 100% 156 100% 45 100%

118
Table C21
Question 15: During Your Commissioned Service, Did You Complete an Internship, Fellowship,
DoD SkillBridge, or Any Other Program Where You Worked Full-Time for a Civilian Employer
While on Active Duty?
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 33 14.0% 22 11.8% 19 12.2% 7 15.6%
No 202 86.0% 165 88.2% 137 87.8% 38 84.4%
235 100% 187 100% 156 100% 45 100%
Table C22
Question 16: Did You Complete Any Additional Transition-Related Programs Besides DoD
TAP?
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 104 44.3% 83 44.4% 69 44.2% 19 42.2%
No 131 55.7% 104 55.6% 86 55.8% 26 57.8%
235 100% 187 100% 155 100% 45 100%

119
Table C23
Question 17: If You Answered “Yes” to the Previous Question, How Many Transitional
Programs Did You Participate in Besides DoD TAP? Transitional Programs May Include
Corporate or Non-profit Programs to Assist Military Members With Their Career Transition
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
1 56 53.8% 50 60.2% 40 58.0% 14 73.7%
2 28 26.9% 19 22.9% 17 24.6% 3 15.8%
3 or more 20 19.2% 14 16.9% 12 17.4% 2 10.5%
104 100% 83 100% 69 100% 19 100%
Table C24
Question 18: Before Your Military Retirement, Did You Receive Mentoring From Other Retired
Military Officers?
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 148 63.2% 124 66.7% 108 69.2% 34 75.6%
No 86 36.8% 62 33.3% 48 30.8% 11 24.4%
234 100% 186 100% 156 100% 45 100%

120
Table C25
Question 35: On a Scale of 1–10, With “1” Being the Least Prepared and “10” Being the Most
Prepared, During Your Final Year of Military Service, How Prepared Were You to Transition to
the Civilian Employment Sector?
Sample size Median Avg SD Min Max
Baseline 229 6 5.6 2.5 0 10
Command 184 6 5.6 2.5 1 10
Employ 153 6 5.7 2.4 1 10
Executive 44 6 6.0 2.2 1 10
Table C26
Question 37: On a Scale of 1–10, With “1” Being the Least Confident and “10” Being the Most
Confident, While Serving in the Military, How Confident Were You About Your Ability to Assume
an Executive Leadership Position in the Civilian Employment Sect
Sample size Median Avg SD Min Max
Baseline 227 8 7.7 2.2 1 10
Command 183 8 7.7 2.2 1 10
Employ 155 8 7.7 2.1 1 10
Executive 45 8 7..9 2.1 3 10

121
Description of Data: Motivational Questions (12, 32-34, 36)
Table C27
Question 12: Did You Plan to Work After Your Military Career?
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 228 97.0% 181 96.8% 152 97.4% 43 95.6%
No 7 3.0% 6 3.2% 4 2.6% 2 4.4%
235 100% 187 100% 156 100% 45 100%
Table C28
Question 32: What Was Your Primary Reason for Leaving the Military Service? Please Choose
the Most Appropriate Answer
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Career aspirations 56 24.1% 39 21.1% 33 21.4% 14 31.8%
Failed to promote/select 22 9.5% 16 8.6% 11 7.1% 2 4.5%
Family 85 36.6% 67 36.2% 57 37.0% 12 27.3%
Forced retirement 48 20.7% 44 23.8% 38 24.7% 8 18.2%
Medical 6 2.6% 5 2.7% 4 2.6% 1 2.3%
Other 15 6.5% 14 7.6% 11 7.1% 7 15.9%
232 100% 185 100% 154 100% 44 100%

122
The response count included 31 selections for the “other” category, which allowed
respondents to write a text response if desired. 19 of the 31 “other” selections included a written
text response. Each of the 19 text responses was examined for recategorization. 16 of the 19 text
responses associated with “other” selections were appropriately recategorized as follows:
“Career aspirations” (11 responses), “Forced retirement” (3 responses), and “Medical” (2
responses), leaving the three remaining “other” selections with their written text unchanged.
Table C29
Question 33: What, if Any, Was a Secondary Reason for Leaving the Military Service? Please
Choose the Most Appropriate Answer
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Career aspirations 72 31.7% 59 32.6% 49 32.5% 15 34.1%
Failed to promote/select 26 11.5% 21 11.6% 18 11.9% 2 4.5%
Family 55 24.2% 39 21.5% 31 20.5% 10 22.7%
Forced retirement 10 4.4% 9 5.0% 7 4.6% 2 4.5%
Medical 11 4.8% 10 5.5% 9 6.0% 2 4.5%
Not applicable (N/A) 39 17.2% 33 18.2% 28 18.5% 10 22.7%
Other 14 6.2% 10 5.5% 9 6.0% 3 6.8%
227 100% 181 100% 151 100% 44 100%

123
The response count included 37 selections for the “other” category, which allowed
respondents to write a text response if desired. 29 of the 38 “other” selections included a written
text response. Each of the 29 text responses was examined for recategorization. 23 of the 29 text
responses associated with “other” selections were appropriately recategorized as follows:
“Career aspirations” (17 responses), “Forced retirement” (1 response), “Failed to promote” (1
response), “Family” (1 response), and “Medical” (2 response), leaving the six remaining “other”
selections with their written text unchanged.
Table C30
Question 34: Upon Retirement From the Military, Did You Desire to Lead an Organization in a
Role Equivalent to a President, CEO, Executive Director, General Manager, etc.?
Baseline Command Employed Executive
Selection Ct % Ct % Ct % Ct %
Yes 112 48.1% 96 51.6% 79 51.0% 29 64.4%
No 121 51.9% 90 48.4% 76 49.0% 16 35.6%
233 100% 186 100% 155 100% 45 100%

124
Table C31
Question 36: On a Scale of 1–10, With “1” Being the Least and “10” Being the Most, How
Strong Was Your Desire to Assume an Equivalent Leadership Role Within the Civilian
Employment Sector?
Sample size Median Avg SD Min Max
Baseline 228 7 6.8 2.6 1 10
Command 183 7 6.8 2.6 1 10
Employ 154 7 6.8 2.6 1 10
Executive 45 8 7.5 2.6 1 10
Description of Data: Organizational Questions (10-11, 29-31)
Table C32
Question 10: On a Scale of 1–10, With “1” Being the Least and “10” Being the Most, if
Applicable, How Well Do You Think Your Time as a Commanding Officer/Commander Prepared
You for Executive Leadership Positions in the Civilian Employment Sector?
Sample size Median Avg SD Min Max
Baseline 183 8 7.9 2.0 1 10
Command 183 8 7.9 2.0 1 10
Employ 155 8 8.0 1.9 1 10
Executive 44 8 8.0 2.0 3 10

125
Table C33
Question 11: On a Scale of 1–10, With “1” Being the Least and “10” Being the Most, if
Applicable, How Relatable Do You Feel Your Experiences as a Commanding
Officer/Commander Are in the Civilian Employment Sector?
Sample size Median Avg SD Min Max
Baseline 180 7 7 2.3 1 10
Command 180 7 7 2.3 1 10
Employ 154 7 7.1 2.1 1 10
Executive 43 8 7.2 2.2 2 10
Table C34
Question 29: On a Scale of 1–10, With “1” Being Least Satisfied and “10” Being Most Satisfied,
How Satisfied Are You in Your Current Role?
Sample size Median Avg SD Min Max
Baseline 187 8 7.4 2.3 1 10
Command 152 8 7.5 2.2 1 10
Employ 151 8 7.5 2.2 1 10
Executive 43 8 8.0 1.8 3 10

126
Table C35
Question 30: On a Scale of 1–10, With “1” Being the Least Satisfied and “10” Being the Most
Satisfied, How Satisfied Are You About the Level of Responsibility Your Current Role Entails?
Sample size Median Avg SD Min Max
Baseline 192 8 7.2 2.7 1 10
Command 156 8 7.3 2.6 1 10
Employ 155 8 7.3 2.6 1 10
Executive 45 9 8.3 2.3 1 10
Table C36
Question 31: On a Scale of 1–10, With “1” Being the Least and “10” Being the Most, How
Much Do You Feel Your Current Employer Values Your Executive Military Leadership
Experience?
Sample size Median Avg SD Min Max
Baseline 192 8 6.9 3.0 0 10
Command 150 8 6.8 3.0 0 10
Employ 155 8 6.9 3.0 0 10
Executive 45 9 7.7 2.9 0 10

127
Table C37
Statistical Relationships of Knowledge Questions Using Filter 1 (Baseline)
13 14 15 16 17 18 35 37
1 – – – – – – – –
2 0.6850 0.1620 0.0136 0.0001 0.0728 0.3710 0.5160 0.2040
3 0.4140 0.1650 0.0250 0.3310 0.4090 0.3780 0.0688 0.0542
4 0.5750 0.0534 0.0924 0.8490 0.0779 0.1720 0.6770 0.3370
5 0.3070 0.2000 0.3740 0.0172 0.2730 0.4630 0.8130 0.1560
6 0.5160 1.0000 0.0614 1.0000 0.0334 0.0434 0.5320 0.9760
7 0.1390 0.0853 0.2390 1.0000 0.5280 0.7210 0.2660 0.8680
8 0.4330 0.1680 0.3780 0.5620 0.3110 0.4380 0.2500 0.5040
9 0.1210 0.5500 0.3690 0.0382 0.5180 0.0860 0.9010 0.0239
10 0.3350 0.9270 0.3510 0.8690 0.5820 0.0433 0.0000 0.0000
11 0.4500 0.9880 0.6250 0.2800 0.3600 0.3760 0.0001 0.0000
12 0.6020 1.0000 0.5970 1.0000 0.2660 0.7100 0.0740 0.2350
13 – 0.0041 0.4430 0.5940 0.3180 0.4670 0.5160 0.2450
14 0.0041 – 0.4490 1.0000 0.3790 0.0931 0.4420 0.8370
15 0.4430 0.4490 – 0.0005 0.0063 0.4430 0.0291 0.0990
16 0.5940 1.0000 0.0005 – – 0.0002 0.1780 0.8490
17 0.3180 0.3790 0.0063 – – 0.9180 0.9660 0.6370
18 0.4670 0.0931 0.4430 0.0002 0.9180 – 0.0000 0.1850
19 0.9580 0.5980 0.1230 0.0098 0.3390 0.2000 0.7230 0.1590
20 0.1920 0.8680 0.0217 0.0107 0.1560 0.4140 0.4600 0.7600
21 0.6410 0.3070 0.8090 0.8630 0.6960 0.0117 0.1650 0.6700
22 0.0961 0.7430 0.3190 0.0108 0.5640 0.1900 0.2890 0.4810
23 0.0144 0.2810 0.8360 0.1290 0.4270 0.5140 0.7220 0.6340
24 0.6750 0.2950 1.0000 0.5160 0.2890 0.1250 0.0354 0.5340
25 1.0000 0.4530 0.4440 1.0000 0.5250 0.5340 0.2860 0.7110
26 0.6020 0.1370 0.9180 0.6390 0.7600 0.4940 0.6430 0.2520
27 0.1580 0.9960 0.5220 0.6430 0.1570 0.2020 0.3460 0.6450
28 0.6890 0.0139 0.6300 0.3360 0.6920 0.3970 0.4360 0.3240
29 0.3590 0.3220 0.5800 0.5410 0.3690 0.0307 0.0000 0.7470
30 0.8040 0.3270 0.4870 0.1200 0.0437 0.0032 0.0001 0.8780
31 0.4920 0.1170 0.7490 0.9500 0.5110 0.0098 0.0000 0.0272
32 0.1360 0.0731 0.1040 0.4510 0.8180 0.0808 0.4030 0.0100
33 0.0998 0.5680 0.7910 0.7740 0.1860 0.3630 0.2340 0.8680
34 1.0000 0.4260 1.0000 1.0000 0.0708 0.4970 0.0475 0.0079
35 0.5160 0.4420 0.0291 0.1780 0.9660 0.0000 – 0.0044
36 0.8630 0.8620 0.4670 0.7430 0.1550 0.4220 0.2320 0.0000

128
13 14 15 16 17 18 35 37
37 0.2450 0.8370 0.0990 0.8490 0.5110 0.1850 0.0044 –
Note. The items in bold signify a P-value of statistical significance, indicating the relationship
between the two variables is consistent enough that it is unlikely to be a coincidence.
A value less than 0.05 means that a relationship is "statistically significant" - unlikely to be a
coincidence. The blank cells indicate that statistical test results could not be determined because
the same two questions cannot be tested against each other, or the filter used to evaluate the data
restricted the data available to conduct the statistical test.
Table C38
Statistical Relationships of Knowledge Questions Using Filter 2 (Command)
13 14 15 16 17 18 35 37
1 – – – – – – – –
2 0.4920 0.2400 0.3920 0.0121 0.4450 0.8200 0.6600 0.5020
3 0.1750 0.0254 0.0684 0.6720 0.3310 0.3860 0.2040 0.0762
4 0.1680 0.0537 0.4200 0.7670 0.1040 0.3450 0.7070 0.2790
5 0.2850 0.5340 0.2680 0.0185 0.1240 0.2350 0.5550 0.3380
6 – – – – – – – –
7 0.1390 0.0853 0.2390 1.0000 0.5280 0.7210 0.2660 0.8680
8 0.4330 0.1680 0.3780 0.5620 0.3110 0.4380 0.2500 0.5040
9 0.1210 0.5500 0.3690 0.0382 0.5180 0.0860 0.9010 0.0239
10 0.3350 0.9270 0.3510 0.8690 0.5820 0.0433 0.0000 0.0000
11 0.4500 0.9880 0.6250 0.2800 0.3600 0.3760 0.0001 0.0000
12 0.5920 1.0000 1.0000 0.6950 0.5950 0.4020 0.0205 –
13 – 0.0350 0.2240 0.4380 0.1680 0.2160 0.9880 0.0648
14 0.0350 – 1.0000 1.0000 0.5850 0.0220 0.4010 0.5600
15 0.2240 1.0000 – 0.1720 0.0518 0.8110 0.2460 0.1300
16 0.4380 1.0000 0.1720 – 1.0000 0.0001 0.2110 0.8900
17 0.1680 0.5850 0.0518 – – 0.4880 0.4870 0.3090
18 0.2160 0.0220 0.8110 0.0001 0.4880 – 0.0003 0.0552

129
13 14 15 16 17 18 35 37
19 0.7450 0.6690 0.2540 0.0856 0.2130 0.4660 0.6590 0.4430
20 0.1850 0.8510 0.3330 0.1450 0.1650 0.8530 0.7080 0.8650
21 1.0000 0.1070 1.0000 1.0000 0.3500 0.0862 0.3590 0.9550
22 0.2910 0.7810 0.6190 0.0040 0.6720 0.1020 0.6180 0.2010
23 0.0114 0.7040 0.9520 0.1050 0.1850 0.2930 0.8710 0.9320
24 0.8180 0.4400 0.4250 0.7240 0.2330 0.3400 0.2510 0.4010
25 1.0000 0.4890 0.2430 0.7670 0.3190 0.7380 0.2740 0.8360
26 0.7210 0.1040 0.6860 0.4670 0.6220 0.6870 0.6610 0.5480
27 0.4910 0.9480 0.1790 0.8260 0.2600 0.2510 0.7240 0.8530
28 0.5090 0.1510 0.7660 0.5240 0.4750 0.8060 0.0942 0.4100
29 0.1690 0.7890 0.3660 0.6610 0.0464 0.1620 0.0000 0.7020
30 0.8760 0.8490 0.7440 0.1210 0.0048 0.0438 0.0000 0.6710
31 0.3690 0.4920 0.7900 0.8100 0.2620 0.0108 0.0000 0.0301
32 0.1790 0.1200 0.2530 0.4850 0.5940 0.1700 0.4730 0.0090
33 0.6260 0.4100 0.9630 0.7820 0.1320 0.2670 0.4460 0.4730
34 0.5670 1.0000 0.8230 1.0000 0.6940 0.1210 0.0157 0.0619
35 0.9880 0.4010 0.2460 0.2110 0.4870 0.0003 – 0.0020
36 0.6220 0.3100 0.6940 0.9750 0.1350 0.5850 0.4050 0.0000
37 0.0648 0.5600 0.1300 0.8900 0.3090 0.0552 0.0020 –
Note. The items in bold indicate statistical significance and that the relationship between the two
variables is consistent enough that it is unlikely to be a coincidence. The blank cells indicate that
statistical test results could not be determined because the same two questions cannot be tested
against each other, or the filter used to examine the relationship restricted one of the two
variables’ data to a level that could prevent a testable relationship.
Tables C39 and C40 highlight several statistically significant relationships between the
survey’s 37 questions and the questions specifically identified as “knowledge” questions.

130
Table C39
Statistical Relationships of Motivational Questions Using Filter 1 (Baseline)
12 32 33 34 36
1 – – – – –
2 0.4730 0.1090 0.7860 0.6260 0.0075
3 0.4430 0.0000 0.0002 0.4290 0.2850
4 0.1670 0.0049 0.1890 0.9540 0.4920
5 0.9720 0.6190 0.0468 0.4480 0.6830
6 1.0000 0.0688 0.4740 0.0345 0.9460
7 1.0000 0.0000 0.8200 0.2800 0.6290
8 0.7470 0.1430 0.0729 0.2740 0.3660
9 0.4170 0.0097 0.7030 0.1400 0.7440
10 0.4430 0.3110 0.0124 0.2630 0.0001
11 0.8940 0.3270 0.1510 0.0248 0.0000
12 / 0.9470 0.5290 1.0000 0.9350
13 0.6020 0.1360 0.0998 1.0000 0.8630
14 1.0000 0.0731 0.5680 0.4260 0.8620
15 0.5970 0.1040 0.7910 1.0000 0.4670
16 1.0000 0.4510 0.7740 1.0000 0.7430
17 0.2660 0.8180 0.1860 0.7080 0.1550
18 0.7100 0.0808 0.3630 0.4970 0.4220
19 0.2570 0.0173 0.2460 0.2490 0.0239
20 0.0256 0.0054 0.3180 0.8170 0.1680
21 0.1050 0.8100 0.3410 0.4930 0.9900
22 0.4770 0.4830 0.7750 0.2370 0.3350
23 0.5550 0.2650 0.6670 0.1430 0.3500
24 0.1850 0.0126 0.2940 0.0098 0.0448
25 1.0000 0.7790 0.4310 0.1540 0.0012
26 0.6980 0.5360 0.8720 0.1660 0.1160
27 0.7990 0.3230 0.1740 0.1430 0.2840
28 0.2640 0.2220 0.6230 0.0360 0.1510
29 – 0.3370 0.1060 0.0220 0.4470
30 – 0.3310 0.0836 0.0340 0.6010
31 – 0.5370 0.2970 0.0431 0.6450
32 0.9470 – 0.0000 0.8190 0.5230
33 0.5290 0.0000 – 0.4230 0.5570
34 1.0000 0.8190 0.4230 – 0.0000
35 0.0740 0.4030 0.2340 0.0475 0.2320
36 0.9350 0.5230 0.5570 0.0000 –
37 0.2350 0.0100 0.8680 0.0114 0.0000

131
Note. The items in bold indicate statistical significance and that the relationship between the two
variables is consistent enough that it is unlikely to be a coincidence. The blank cells indicate that
statistical test results could not be determined because the same two questions cannot be tested
against each other, or the filter used to examine the relationship restricted one of the two
variables’ data to a level that could prevent a testable relationship.
Table C40
Statistical Relationships of Motivational Questions Using Filter 2 (Command)
12 32 33 34 36
1 – – – – –
2 0.4960 0.1240 0.5820 0.4350 0.0132
3 0.8650 0.0000 0.0018 0.2320 0.3280
4 0.4840 0.0393 0.2080 1.0000 0.5210
5 0.9060 0.5060 0.0539 0.3730 0.5330
6 – – – – –
7 1.0000 0.0000 0.8200 0.2800 0.6290
8 0.7470 0.1430 0.0729 0.2740 0.3660
9 0.4170 0.0097 0.7030 0.1400 0.7440
10 0.4430 0.3110 0.0363 0.2630 0.0001
11 0.8940 0.3270 0.1510 0.0248 0.0000
12 – 0.9300 0.3830 0.6740 0.9360
13 0.5920 0.1790 0.6260 0.5670 0.6220
14 1.0000 0.1200 0.4100 1.0000 0.3100
15 1.0000 0.2530 0.9630 0.8230 0.6940
16 0.6950 0.4850 0.7820 1.0000 0.9750
17 0.5950 0.5940 0.1320 0.6940 0.1350
18 0.4020 0.1700 0.2670 0.1210 0.5850
19 0.6820 0.0224 0.2230 0.4430 0.0079
20 0.2120 0.1090 0.3460 0.7030 0.3730
21 0.2490 0.8700 0.9720 0.6900 0.9700
22 0.4160 0.1870 0.6780 0.0735 0.7060
23 0.6180 0.2100 0.4430 0.2000 0.0853
24 0.2000 0.0210 0.6790 0.0342 0.0375
25 1.0000 0.7710 0.6340 0.2210 0.0003
26 0.6890 0.4710 0.6160 0.3010 0.3960
27 0.6010 0.0945 0.2620 0.2390 0.5000
28 0.3370 0.2950 0.8790 0.0761 0.3720

132
29 – 0.3170 0.2170 0.0197 0.5030
30 – 0.7190 0.2460 0.0057 0.4310
31 – 0.2530 0.4330 0.1610 0.9890
32 0.9300 – 0.0000 0.7430 0.8550
33 0.3830 0.0000 – 0.2980 0.7820
34 0.6740 0.7430 0.2980 – 0.0000
35 0.0205 0.4730 0.4460 0.0157 0.4050
36 0.9360 0.8550 0.7820 0.0000 –
37 – 0.0090 0.4730 0.0619 0.0000
Note. The items in bold indicate statistical significance and that the relationship between the two
variables is consistent enough that it is unlikely to be a coincidence. The blank cells indicate that
statistical test results could not be determined because the same two questions cannot be tested
against each other, or the filter used to examine the relationship restricted one of the two
variables’ data to a level that could prevent a testable relationship.
Tables C41 and C42 highlight several statistically significant relationships between the
survey’s 37 questions and the questions specifically identified as “motivational” questions.

133
Table C41
Statistical Relationships of Organizational Questions Using Filter 1 (Baseline)
10 11 29 30 31
1 – – – – –
2 0.7310 0.1920 0.2400 0.2910 0.9890
3 0.2850 0.4360 0.3600 0.0668 0.0246
4 0.7210 0.3080 0.0792 0.0870 0.0135
5 0.6160 0.1940 0.6880 0.2110 0.5920
6 - - 0.3420 0.5220 0.9030
7 0.0971 0.1060 0.0448 0.3170 0.8510
8 0.5810 0.1420 0.4060 0.1760 0.0607
9 0.0052 0.1220 0.3110 0.9360 0.1660
10 – 0.0000 0.0293 0.0214 0.0039
11 0.0000 – 0.0015 0.0639 0.0000
12 0.4430 0.8940 – – –
13 0.3350 0.4500 0.3590 0.8040 0.4920
14 0.9270 0.9880 0.3220 0.3270 0.1170
15 0.3510 0.6250 0.5800 0.4870 0.7490
16 0.8690 0.2800 0.5410 0.1200 0.9500
17 0.5820 0.3600 0.3690 0.0437 0.5110
18 0.0433 0.3760 0.0307 0.0032 0.0098
19 0.1690 0.2090 0.8520 0.1800 0.0878
20 0.8760 0.8510 0.0565 0.0610 0.6860
21 0.1910 0.4530 – – –
22 0.0305 0.0764 0.0941 0.2950 0.3390
23 0.8370 0.6750 0.0242 0.0824 0.0213
24 0.9160 0.8520 0.0583 0.0004 0.0153
25 0.5410 0.8470 0.4930 0.6900 0.1110
26 0.9160 0.2900 0.8300 0.4370 0.2860
27 0.9400 0.9490 0.2120 0.1250 0.3390
28 0.1030 0.4860 0.4160 0.0080 0.0472
29 0.0293 0.0015 – 0.0000 0.0000
30 0.0214 0.0639 0.0000 – 0.0000
31 0.0039 0.0000 0.0000 0.0000 –
32 0.3110 0.3270 0.3370 0.3310 0.5370
33 0.0363 0.1510 0.1060 0.0836 0.2970
34 0.2630 0.0248 0.0220 0.0340 0.0431
35 0.0000 0.0001 0.0000 0.0000 0.0000
36 0.0001 0.0000 0.4470 0.6010 0.6450
37 0.0000 0.0000 0.7470 0.8780 0.0272

134
Note. The items in bold indicate statistical significance and that the relationship between the two
variables is consistent enough that it is unlikely to be a coincidence. The blank cells indicate that
statistical test results could not be determined because the same two questions cannot be tested
against each other, or the filter used to examine the relationship restricted one of the two
variables’ data to a level that could prevent a testable relationship.
Table C42
Statistical Relationships of Organizational Questions Using Filter 2 (Command)
10 11 29 30 31
1 – – – – –
2 0.7310 0.1920 0.2400 0.2910 0.9890
3 0.2850 0.4360 0.3600 0.0668 0.0246
4 0.7210 0.3080 0.0792 0.0870 0.0135
5 0.6160 0.1940 0.6880 0.2110 0.5920
6 – – 0.3420 0.5220 0.9030
7 0.0971 0.1060 0.0448 0.3170 0.8510
8 0.5810 0.1420 0.4060 0.1760 0.0607
9 0.0052 0.1220 0.3110 0.9360 0.1660
10 – 0.0000 0.0293 0.0214 0.0039
11 0.0000 – 0.0015 0.0639 0.0000
12 0.4430 0.8940 – – –
13 0.3350 0.4500 0.3590 0.8040 0.4920
14 0.9270 0.9880 0.3220 0.3270 0.1170
15 0.3510 0.6250 0.5800 0.4870 0.7490
16 0.8690 0.2800 0.5410 0.1200 0.9500
17 0.5820 0.3600 0.3690 0.0437 0.5110
18 0.0433 0.3760 0.0307 0.0032 0.0098
19 0.1690 0.2090 0.8520 0.1800 0.0878
20 0.8760 0.8510 0.0565 0.0610 0.6860
21 0.1910 0.4530 – – –
22 0.0305 0.0764 0.0941 0.2950 0.3390
23 0.8370 0.6750 0.0242 0.0824 0.0213
24 0.9160 0.8520 0.0583 0.0004 0.0153
25 0.5410 0.8470 0.4930 0.6900 0.1110
26 0.9160 0.2900 0.8300 0.4370 0.2860
27 0.9400 0.9490 0.2120 0.1250 0.3390
28 0.1030 0.4860 0.4160 0.0080 0.0472
29 0.0293 0.0015 – 0.0000 0.0000

135
30 0.0214 0.0639 0.0000 – 0.0000
31 0.0039 0.0000 0.0000 0.0000 –
32 0.3110 0.3270 0.3370 0.3310 0.5370
33 0.0363 0.1510 0.1060 0.0836 0.2970
34 0.2630 0.0248 0.0220 0.0340 0.0431
35 0.0000 0.0001 0.0000 0.0000 0.0000
36 0.0001 0.0000 0.4470 0.6010 0.6450
37 0.0000 0.0000 0.7470 0.8780 0.0272
Note. The items in bold indicate statistical significance and that the relationship between the two
variables is consistent enough that it is unlikely to be a coincidence. The blank cells indicate that
statistical test results could not be determined because the same two questions cannot be tested
against each other, or the filter used to examine the relationship restricted one of the two
variables’ data to a level that could prevent a testable relationship.
Tables C43 and C44 highlight several statistically significant relationships between the
survey’s 37 questions and the questions specifically identified as “organizational” questions.

136
Table C43
Statistical Relationship of a Demographical Question (24)
Baseline Command
1 – –
2 0.0104 0.0440
3 0.2830 0.7650
4 0.0973 0.1340
5 0.4120 0.2060
6 0.5360 -
7 0.6270 0.6270
8 0.8280 0.8280
9 0.5880 0.5880
10 0.9160 0.9160
11 0.8520 0.8520
12 0.1850 0.2000
13 0.6750 0.8180
14 0.2950 0.4400
15 1.0000 0.4250
16 0.5160 0.7240
17 0.2890 0.2330
18 0.1740 0.3400
19 0.1530 0.0999
20 0.1180 0.1470
21 – –
22 0.3020 0.3630
23 0.0002 0.0021
24 – -
25 – –
26 0.0004 0.0000
27 0.0040 0.0181
28 0.0000 0.0000
29 0.0583 0.0404
30 0.0004 0.0010
31 0.0153 0.0340
32 0.0126 0.0210
33 0.2940 0.6790
34 0.0098 0.0342
35 0.0354 0.2510
36 0.0448 0.0375
37 0.3430 0.4010

137
Note. The items in bold indicate statistical significance and that the relationship between the two
variables is consistent enough that it is unlikely to be a coincidence. The blank cells indicate that
statistical test results could not be determined because the same two questions cannot be tested
against each other, or the filter used to examine the relationship restricted one of the two
variables’ data to a level that could prevent a testable relationship.
Out of 19 demographic questions, I chose only Question 24 (Are you currently serving in
an executive-level role?) for examination as a dependent variable because the question represents
the study’s most central question: are SMOs transitioning into positions of equivalency in
leadership responsibility? Table C44 describes that Question 24 had 11 statistically significant
relationships in each of the two applied filters (1 and 2). Notably, respondents who answered yes
to Question 24 tended to have a higher feeling of employer valuation for their leadership
experience (Question 31), a higher feeling of satisfaction with their current level of responsibility
and current role (Question 30), a higher feeling of having been prepared for their transition, a
higher desire to attain an equivalent leadership role (Question 36), and they tended to have a
higher desire to lead an organization in the civilian sector (Question 34).
I examined 19 of the survey’s 37 questions, representing the four categories of
knowledge (eight questions), motivation (five questions), organization (five questions), or
demographic (1 question) to produce a total count of statistically significant relationships
between questions identified in the examined categories and the survey’s 37 questions. Table
C44 describes that using Filter 1, out of a total possibility of 703 relationships (37 questions
times 37 questions), 139 (about 20%) statistically significant relationships were identified. Table
45 describes the same process but with Filter 2 applied instead, resulting in 119 (about 17%)

138
statistically significant relationships. The decrease from Filter 1 to Filter 2 is assessed to be
caused by Filter 2’s more selective screening process, which limited responses to only those who
indicated they completed a command tour on Question 6. The combined total number of
statistically significant relationships between both filters was 258 (139 + 119).

139
Table C44
Count of Statistically Significant Relationships With Filter 1 Applied (Baseline)
Filter Question Number of SS relationships
Baseline 31 13
Baseline 10 11
Baseline 24 11
Baseline 35 10
Baseline 34 10
Baseline 30 9
Baseline 29 9
Baseline 33 9
Baseline 37 8
Baseline 18 8
Baseline 36 8
Baseline 16 8
Baseline 11 7
Baseline 15 6
Baseline 32 4
Baseline 17 3
Baseline 13 2
Baseline 14 2
Baseline 12 1

140
Table C45
Count of Statistically Significant Relationships With Filter 2 Applied (Command)
Filter Question Number of SS relationships
Command 10 11
Command 24 11
Command 29 11
Command 31 10
Command 30 9
Command 35 9
Command 32 8
Command 36 8
Command 11 7
Command 37 7
Command 18 6
Command 34 6
Command 16 5
Command 14 3
Command 33 3
Command 13 2
Command 17 2
Command 12 1
Command 15 0
Table C46 describes the total number of statistically significant relationships held in
common from both filters, meaning the same relationship was statistically significant regardless
of which filter (1 or 2) was applied. The total number of common relationships between both
filters was 108, as represented in Table C46. This finding indicates that the same types of
relationships between questions existed regardless of whether the SMO held a command position
and may speak to broader demographic, knowledge, motivation, organization, and leadership
attributes of SMOs because it applied to the broader audience of survey respondents.

141
Table C46
Count of Statistically Significant Relationships in Common With Filters 1 & 2 (Baseline &
Command)
Filter Question Number of common SS relationships
1 and 2 10 11
1 and 2 24 10
1 and 2 31 10
1 and 2 29 8
1 and 2 30 8
1 and 2 32 8
1 and 2 35 8
1 and 2 36 8
1 and 2 11 7
1 and 2 37 7
1 and 2 34 6
1 and 2 16 5
1 and 2 18 5
1 and 2 33 3
1 and 2 13 2
1 and 2 14 1
1 and 2 17 1
1 and 2 15 0
1 and 2 12 0

Abstract (if available)

Abstract Employment outcomes for retired senior military officers are complex and vary based on many influential factors. The purpose of this study was to examine employment outcomes for retired senior military officers with commanding officer experience and identify gaps prevalent in their transitional experiences. Using Clark and Estes’s knowledge, motivation, and organization (KMO) framework, the study analyzed demographical data and transitional experiences for retired senior military officers who entered the civilian employment sector and explored how preparation for transition affected real and perceived transition success. The study utilized quantitative analysis to identify statistically significant relationships from survey responses provided by retired senior military officers from all seven branches of the armed forces. There were 256 qualified survey respondents. This study’s findings suggest that although senior military officer leadership experience was perceived to help prepare for and relate to roles of equivalent levels of responsibility outside the military, post-military employment outcomes did not systemically result in the immediate achievement of positional equivalency. Implications of the study include the need for improvements in employer understanding of leadership attributes and experiences of senior military officers, the establishment of transitional programs specifically tailored for them, and the identification of key mentoring relationships to support them through their transition.

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Asset Metadata

Creator Motes, Jason Alan (author)

Core Title The employment of retired senior military officers with command experience

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Degree Conferral Date 2024-12

Publication Date 10/17/2024

Defense Date 09/06/2024

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag command experience,commanding officer,military leadership,military retirement,military transition,retired senior military officer,veteran employment,veteran executives,veteran leadership

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Language English

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Advisor Hyde, Corrine (committee chair), Dexter, John (committee member), Maddox, Anthony (committee member)

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