Unit VII PP PFL

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Unit VII PowerPoint Presentation

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Instructions

For this assignment,
you will compose a 10-slide PowerPoint presentation
. Select a contemporary leadership challenge in your workplace or any organization you are currently or previously associated with, and propose an optimal leadership model to apply for success. In doing so, your presentation should include the elements listed below.

· Explain why leadership of this organization is not functioning to its potential.

· In analyzing the leader, determine which characteristics and leadership style exhibited require improvement through reflection or training.

· Examine the role that effective communication will serve toward conveying the scope of the problem and resolution in the situation.

· Describe the exhibited behaviors by the leader, and explain whether they add value.

· Determine what needs to change, and explain how your selected model will support success for the organization.

· Describe Tuckman’s teamwork performance stage, and recommend leader support to optimize conjoined efforts.

· Explain to what extent conflict is present, both positive to challenge the status quo and negative based on personal agenda pursuit.

Narration is optional. If you add narration, a transcript of your narration is required in the slide notes for each slide.

Utilizing the notes section for further information on each slide is optional. You may utilize bullets, lists, charts, tables, paragraphs, and images for your presentation. Ensure the presentation that you create is your own authentic work.

Please integrate a minimum of three peer-reviewed journal articles from the CSU Online Library to support your proposal for success. The required title and reference slides do not count toward the slide requirement. Adhere to APA Style when constructing this assignment, including in-text citations and references for all sources that are used.

Psychological Foundations of Leadership 1

Course Learning Outcomes for Unit VII

Upon completion of this unit, students should be able to:

6. Examine characteristics leaders exhibit to achieve organizational objectives.
6.1 Examine team-building skills.
6.2 Relate the ability of a leader to communicate and resolve conflict to the psychological

foundations.

Course/Unit
Learning Outcomes

Learning Activity

6.1

Unit Lesson

Chapter 9
Unit VII PowerPoint Presentation

6.2
Unit Lesson
Chapter 12
Unit VII PowerPoint Presentation

Required Unit Resources

Chapter 9: Developing Teamwork

Chapter 12: Communication and Conflict Resolution Skills

Unit Lesson

Introduction

Welcome to Unit VII! As we rapidly progress toward the finish line, let’s pause and contemplate the wealth of
knowledge that has been acquired thus far, as related to the psychological foundations of leadership. In this
unit, we will explore key characteristics essential for leaders to conduct and execute critical functions. First,
we will examine the acumen of skills necessary for a leader to effectively build high-performing teams.
Second, we will further explore the key role of effective communication and characteristics needed for leader
effectiveness. Third, we will investigate knowledge, skills, and abilities necessary to conduct negotiation and
resolve conflict. Finally, we will summarize, synthesize, and discuss how the psychological foundations of
leadership examined throughout this course directly relate to the aforementioned characteristics.

Team Building

What leadership characteristics are essential for building teams? DuBrin (2019) posits that leaders must be
viewed through a lens of trustworthiness by followers. So, how does a leader demonstrate this critical
characteristic? As we have all learned and observed from personal experience, teams evolve through
specific stages. Let’s pause for a moment and reflect upon when we were a part of a team. Did you look to
the leader to assess whether you could place your trust in the individual? From your personal observation,
what did you evaluate?

Teams assemble for a purpose and are driven to accomplish stated objectives. If a leader demonstrates and
conveys conflicting information and views, this certainly can prove problematic on the journey to gain the trust
of followers. Returning to our existing knowledge of the stages of team building, forming occurs first
(Tuckman, 1965). Typically, this is where the leader assembles the followers to initiate conversion from a
group to a team. Experience has shown that once trustworthiness is established, the self-identity of the team

UNIT VII STUDY GUIDE
Psychological Challenges of Leadership

Psychological Foundations of Leadership 2

UNIT x STUDY GUIDE
Title

emerges (DuBrin, 2019). Consequently, the effective leader demonstrates the skill and ability to inspire and
enables and empowers group members. These essential characteristics become the foundation for guiding
the team through the next stage of building, storming (Tuckman, 1965).

(Adapted from Tuckman, 1965)

Characteristically, teams often assemble, and the effective leader is able to guide brainstorming that may
lead to conflicting ideas. As a result, positive conflict emerges, resulting in establishing common ground,
further leading to the third stage, norming (Tuckman, 1965). It is during this stage that the leader empowers
followers to make decisions and to assume authority toward execution of steps realized through the planning
process. Finally, the team is now positioned to perform (Tuckman, 1965). The final stage for team
development is adjourning (Tuckman, 1965). Characteristics inherent with the effective leader in this stage
relate to guiding members to anticipate and influence change, a critical characteristic that is requisite to
achieving higher levels of performance. Next, let’s examine how communication and related characteristics
are critical for leader success.

Communication

Leaders can only influence and guide followers through highly effective communication skills. At first glance,
the emphasis is placed on how the leader speaks and gains attention. DuBrin (2019) asserts that two key
areas that are supported by the spoken word and effective communication rest upon the leader’s ability to
demonstrate characteristics that lead to a climate of trust, which is supported by the cooperation theory.
Again, calling on you to reflect on past experience, what key indicators did you look for in order to trust and
cooperate with the initiative set forth by the leader? How would you rate and evaluate the importance of tone,
eye contact, and body language, which are all critical evaluative measures?

Let’s consider the other key function of leader communication, effective listening. Anecdotally, experience
over the years leads to a sincere commitment to more actively listening to followers in organizations. Given
the pressures of time and scope of assignments that teams face, there is often a shortfall of leader effort in
this category. Returning to the stages of team building, effective listening through active inquiry is an essential
characteristic for leaders to better understand followers and to build a guiding coalition. Next, we will explore
conflict resolution and negotiation and required skills for leader efficacy.

Conflict Resolution

Leadership faces the inevitability of emerging conflict. Earlier, we examined the storming phase, where the
leader demonstrating effective listening promoted emerging conflict in order to identify solutions that will

Psychological Foundations of Leadership 3

UNIT x STUDY GUIDE
Title

support the execution of the plan. Reflect upon a time when you were a part of a team where a conflict
emerged. Did the leader demonstrate confidence—a critical characteristic in identifying disagreement—and
actively listen to gain a better understanding? Moreover, did the leader seek to inspire and to recognize the
value of contribution by each follower?

Successful leaders are persuasive and demonstrate this characteristic by resolving conflict through win-win
negotiation and serving the best interests of the team. Finally, integrity must be unilaterally observed and
displayed by the leader in all dealings in order to demonstrate trust. Hence, effective leaders are
communicative, not fearful of conflict, and committed to understanding differences, even through cross-
cultural boundaries. Next, we will be assessing how each of the characteristics examined for team building,
communication, and conflict resolution relate to the psychological foundations of leadership.

Summary

We have examined a host of different characteristics essential for leader success in driving followers forward.
First, the cognitive foundation of leadership necessitates demonstrated intelligence in order to assemble
teams that are driven through effective communication. Second, the social foundation requires the effective
leader to build relationships that are centered on trust and integrity in order to lead the team through
challenging circumstances. Third, the organizational foundation necessitates performance by the leader to
communicate, build teams, and resolve conflict to promote interrelationships that are supported by
harmonious interaction. Finally, the industrial foundation centers upon developing the characteristics of the
leader—cognitively, socially, and organizationally—while resting upon the importance of integrity,
trustworthiness, self-discipline, and self-confidence to achieve the stated organizational strategy. Further,
given that conflict can and will occur, the leader embraces each of the characteristics inherent with these
foundations toward achieving success.

References

DuBrin, A. J. (2019). Leadership: Research findings, practice, and skills (9th ed.). Cengage Learning.
https://online.vitalsource.com/#/books/9780357382837

Tuckman, B. W. (1965). Developmental sequence in small groups. Psychological Bulletin, 63(6), 384–399.
https://doi.org/10.1037/h0022100

InternationalLeadership Journal Summer 2019

The Millennial Effect: A Multi-Generational

Leadership Model*

Darlene Andert
Florida Gulf Coast University (Retired)

Accounting for Profitability LLC

George Alexakis
Florida Gulf Coast University

Robert C. Preziosi

Nova Southeastern University (Emeritus)

Each generation develops internal frameworks to understand the nature of effective
leadership against a backdrop of significant contemporary national and global events—in
effect, people are who they are based on the time in which they were raised. The civil
rights movement, military behavioral models adopted by management, technological
innovation, and mainstream media proliferation prompted the analysis of generational-
based leadership perspectives in North America. Diverse trends and events also shaped
the evolution of generational leadership mindsets in other countries. Arguably, there has
been some development toward global paradigms of business leadership with the
multiplying of business schools. The multi-generation leadership model presented in this
article uses a systems theory lens to view the evolving leadership models from the
traditionalists to the millennials in North America. It offers a broad temporal view and
discusses the extent to which each the above events acted as variables that gained or lost
critical mass in each respective generation. Based on the generational differences, this
article offers some recommendations with regard to leadership development, talent
management, and human resource practices in the new era and future foci for
generational leadership research.

Key words: generational leadership, millennials, multi-generational leadership model,
systems thinking, workplace

In modern society, traditional management principles can lose their efficiency

(Binham et al., 2018). Leadership is one of the most popular topics for executive

development programs, and the widely researched traditional approaches no

longer significantly meet the needs of organizations or individuals (Moldoveanu &

Narayandas, 2019). Karakas, Manisaligil, and Sarigollu (2015) spent seven years

exploring the “benefits of reflective, creative, and collaborative spaces for

millennials using practices from leadership and personal development courses”

*Andert, D., Alexakis, G., & Preziosi, R. C. (2019). The millennial effect: A multi-generational

leadership model. International Leadership Journal, 11(2), 32–63.

International Leadership Journal Summer 2019

(237) to understand and adjust for the differing needs of the next generation. In

1950, Stogdill’s seminal work acknowledged that leadership exists among people

in social situations, and that those who lead in one situation may not necessarily

lead in another. Diversified leadership theories followed. Understanding good

leadership’s composition, the factors contributing to future leader development

and the consistent replication of leadership models still challenge scholars and

practitioners nonetheless. In spite of an overabundance of scientific and

anecdotal work, a myriad of leadership-related questions have remained

unanswered (Gandolfi & Stone, 2018). Augmenting Stogdill’s groundbreaking

original work, Michel and LeBreton (2010) introduced the concept of leadership

coherence, which connotes that a leader’s behavior fluctuates in a consistent,

reliable, and predictable idiographic manner across situations. Haeger and

Lingham (2013) indicate that “leadership patterns are changing, not in theory, but

through intergenerational collisions between leaders’ behaviors and

interpretations from direct reports of what it means to lead” (1) Nonetheless, a

challenge for practitioners is that contemporary theories for understanding the

ways in which leaders can and should act in different situations typically depend

on context and may introduce numerous generational contingencies. Massey

(1979) posited early on that we are who we are based on the time in which we

were raised. Barbuto and Gottfredson (2016) explored three generational

cohorts, with particular emphasis on the millennial generation, estimated to be

50% of the workforce by 2020. They stressed the necessary progression of

general management and leadership practices needed to create an organization

rich in human capital. They suggest that servant leadership is the optimal

leadership style for the millennial generation and call for leadership process

adjustments that are in agreement with the current generational realities.

Conger and Kanungo’s (1998) landmark work demonstrates the complexity of

the issues and explains that even a well-researched theory like transformational

leadership, which depends on follower characteristics and emotions because

leadership is a process of attribution, implies the need for a theory of

followership. The authors conclude that people follow transformational leaders

International Leadership Journal Summer 2019

because they attribute to those leaders the capacity to impose order, security,

and direction in an otherwise chaotic and threatening world. Naseer, Raja, Syed,

Donia, and Darr (2015) indicate that people will follow even bad leaders when the

leader–member exchange (LMX) is high and the perceived organizational politics

(POP) is also high, thus discovering the dark side of leadership and the social

impact and complexity of

leadership.

Defining the Generations and Their Differences

Leadership research in the United States has spanned multi-generational

realities, commencing with the veteran generation, who grew up during the war

years, and culminating with the millennial generation, who were raised during the

digital age. The significant events that occurred during their formative adolescent

years greatly affect each generation (Myers & Sadaghiani, 2010). Expanded

media news content and opinions, the codification of human rights legislation,

and the timing of major military actions and the impact of returning veterans re-

entering the workplace in critical mass substantively shaped each respective

generation’s understanding of leadership and followership. The current

leadership model of the millennial generation has progressed from that of the

previous generation. The apparent shift from the time-of-war traditionalist view of

leadership to a more dynamic and flexible leader/follower perspective is evident

when viewed through the lens of the multi-generational leadership model.

Howe and Strauss (2007) describe the word generation as a cohort group

whose estimated span of life boundaries is fixed and thus develops a peer

personality. While research on the topic of generational differences has

dramatically increased in recent decades since multi-generational marketing is

very important to advertisers and marketers (Williams & Page, 2011), employers

and human resources professionals are equally concerned with how these

differences play out in workplace leadership. While the workplace composition

continues to shift, examining the interrelationships of workers of different

generations who have different skills, attitudes, expectations, and learning styles

increasingly makes sense (Helyer & Lee, 2012). This article uses the four

https://www.sciencedirect.com/science/article/pii/S1048984315001113#!

International Leadership Journal Summer 2019

existing generational cohorts that appear extensively in the literature as a

framework for analyzing the evolution of leadership using a systems approach,

acknowledging that significant societal events and the social learning experience

(Bandura, 1971) frame normative understandings and redefine leadership both

domestically and globally. The U.S. Census (Colby & Ortman, 2014) defines the

generations as

• traditionalists (also called the veteran generation; 1922–1943);

• baby boomers (1943–1960, or traditionally defined as 1946–1964);

• Generation X (also called Gen X; 1960–1980); and

• millennials (also called Generation Y or Gen Y; 1980–2000).

In 2018, after a decade of research, the Pew Research Center sought to “to keep

the Millennial generation analytically meaningful” in order to “begin looking at

what might be unique about the next cohort” and deconstructed the previous

generational frameworks (Dimock, 2019, para. 5).

[The] Pew Research Center decided a year ago to use 1996 as the last birth
year for Millennials for our future work. Anyone born between 1981 and 1996
(ages 23 to 38 in 2019) is considered a Millennial, and anyone born from 1997
onward is part of a new generation (Dimock, 2019, para, 5).

The newest delineation of the generations by the Pew Research Center is

offered in Figure 1 below.

Figure 1. Pew Center generational definitions
Source: From “Defining Generations: Where Millennials End and Generation Z Begins,” by M.
Dimock, January 17, 2019, Pew Research Center (https://www.pewresearch.org/fact-
tank/2019/01/17/where-millennials-end-and-generation-z-begins/ft_19-01-17_generations_2019/).

The generations defined

https://www.pewresearch.org/wp-content/uploads/2019/01/FT_19.01.17_generations_2019 ?w=640

International Leadership Journal Summer 2019

Millennial Characteristics

The multi-generational leadership model serves as a framework for

understanding the dynamic perspective of current leadership thinking to inform

American and international businesses. From viewing leadership during the

global financial crisis to the MTV icons who provided a distracting, fragmented,

rap-video culture (Kaufman, 1993), the millennial experience during their

formative years has considerably nullified the authority traditionally associated

with leaders. The Pew Research Center altered the millennial generation

boundaries in 2018 to encompass persons from 23 to 38 years of age who

represent “more than one in three (35%) American labor force

participants . . . making them the largest generation in the U.S. labor force (Fry,

2018, para. 1). Current thinking, especially among millennials, prioritizes a

balancing of personal and professional life (Ng & Gossett, 2013). They seek time

to pursue personal interests and personal goals as a life priority (Alexander &

Sysko, 2012). Campione (2015) states that

factors affecting Millennials’ job satisfaction are those that negatively impact
satisfaction, those that push Millennials out rather than positive factors that lure
them in. And, although employers have become quite creative in some of their
offerings to recruit Millennials, they have often failed to retain them. (69)

They are technically adept and engaged in their communities using their

expertise to fight for social justice (Gass & Bezold, 2013). Previous generations

have not possessed “anything close to their upbeat, high-achieving, team-

playing, and civic-minded reputation” (Howe & Strauss, 2003, 1). This assertive

orientation challenges traditional leader-centric, hierarchical leader/follower

theories. Katy Perry’s (2010) song “Firework,” with such lyrics as “Baby you’re a

firework—come on show them what you’re worth,” is a popular theme song for

much of today’s young generation. It represents an anthem of sorts and is

consistent with the civic-mindedness attributed to the current generational focus.

Pop singer Brandi Carlile’s lyrics for “The Joke: (2018) further cement this

generation’s perspective “Let ‘em laugh while they can/Let ‘em spin, let ‘em

scatter in the wind/I have been to the movies, I’ve seen how it ends/And the

joke’s on them.” Millennials have strongly stated in corporate surveys and

International Leadership Journal Summer 2019

academic studies that freedom to do their work, how they want to do it, is very

highly valued (Campione, 2015). Perhaps the preference represents the belief

that the previous generation did not get it right. The current millennial focus is

ostensibly a global generation, representing the most racially and ethnically

diverse cohort in U.S. history (Howe & Strauss, 2003).

With a keystroke or touch of a mobile telephone button, the current cohort can

summon their networks and swiftly amass people to any location or event. In

popular culture, this has led to the phenomenon of “flash mobs.” In political

arenas, the consequences can be more eventful. For example, as far back as

2011, the Egyptian revolution against the government served as an example of

this generation’s civic will and leadership–followership dynamic. Youthful pro-

democracy protesters used Twitter, YouTube, Facebook, and Twitpic to topple

an authoritarian regime that previous generations were unable to alter

(Ungerleider, 2011). The phenomenon compelled the mass news media to more

accurately report relevant stories. Distrusting of mainstream media and

established authorities, millennials not only supported the political revolution of

the Bernie Sanders’ U.S. presidential campaign but literally used technology to

gauge the accuracy of political claims (Uygur, 2016). PBS News Hour (2019)

notes that by Election Day 2020, millennials will be a larger share of America’s

adult population than baby boomers and destined to be politically wooed as an

important factor in the upcoming elections. Most recently, the control of the

media has radically changed with the origination of the Internet, mobile phones,

and online social networking (Alexander & Sysko, 2012). The current generations

have access to a highly expanded mainstream and independent media.

Millennials now teach others to use the media to create awareness of important

civic causes. Examples include the “flash mob to end violence against women”

(European Parliament, 2013) that occurred the week before a vote by the

European Parliament aimed at combating violence against women and girls. In

Aventura, Florida, millennial-aged local police officers advanced toward a holiday

celebration flash mob dance and joined in, rather than dispersing the crowd

(Wells, 2018), an expression of millennial egalitarianism.

International Leadership Journal Summer 2019

Millennials are the first “native” generation to technology while members of all

other generations are described as “immigrants,” regardless of their technological

proficiencies (Hershatter & Epstein, 2010, as cited in Alexander & Sysko, 2012).

The historically unique circumstances (i.e., a younger generation possessing

superior skills and knowledge) affect the flow of information. The situation

equalizes opportunities and can lead to a more equitable redistribution of power

among leaders and followers.

With their highly collaborative nature, millennials seek constant interaction and

feedback to assess progress. They seek consistent and constant interpersonal

contact to move in partnership with others, fostered by an open access media. In

2016, IBM joined many other large firms in eliminating annual appraisals for more

frequent, real-time feedback for millennials and their entire workforce (Peck,

2016). Their external locus of identity prompts a need for immediate feedback

and almost continuous recognition and approval (Crumpacker & Crumpacker,

2007, as cited in Gass & Bezold, 2013). Although most millennials are committed

to their work and careers, they are reluctant to become general managers,

largely because they see that new managers are often given lots of additional

responsibility with very little additional support—and support is essential to them

(Tulgan, 2011). Today, it is a hi-tech, constant-contact world in which action does

not exist in isolation (Silverman, 2011). This is quite different from the first half of

the century, when Stogdill’s (Bass, 1990) summative work framed the leadership

assumptions and beliefs that considered:

• leadership to occur when leaders do things to followers;

• leadership to be hierarchy based and linked to an office;

• leadership to make the crucial difference to organizational performance;

• leadership to reside in an individual rather than the system, as the source

or central to organizational accomplishment;

• leaders to be different from other people; and

• leaders to be the ones who shape the behavior of others in a desired

direction and theorized to set the moral climate and culture of the

organization or collective.

International Leadership Journal Summer 2019

By contrast, today’s workforce does not identify with being a corporate citizen

destined to retire with the gold watch but would rather be a world citizen destined

to retire after making a difference (Rhodes, 1983). Millennials’ expectations of

government and their own career goals are different from those of other

generations. The expectancies were cited as the main finding in a recent research

report on Brexit (Weinbaum, Girven, & Oberholtzer, 2016). This workforce is fluid

and mobile. POLITICO Magazine (Robertson & Henderson, 2018) began a series

of articles around the working title “The United States of Millennials,” which

explored how “the nation’s largest generation is transforming cities large and

small” (para. 1) and remaking each to fit their own image and beliefs.

Followers are indeed inspired by leaders who advocate for their moral freedom

(Lemoine, Hartnell, & Leroy, 2019). The financial industry downfall was blamed

on the traditionalist or greedy corporate senior executives, and the Egyptian

revolution of the millennials represented grassroots, emergent, and alternating

leadership (Andert, 2011). This brand of egalitarian and civic-minded leadership

is becoming ubiquitous, as the multidisciplinary nature of the management field

increasingly causes it to expand its sectors. Tesone (2003) best sums up the

growing intricacy of the contemporary manager’s leadership responsibilities and

challenges within an ever-widening group of products and service units with his

aptly titled book, The Leadership Cat with the Management Hat.

The purpose of this article is to compare and contrast generational influences

on the research and definition of leadership. We use a systems thinking lens to

view the various components of mainstream media, the codification of civil rights

and human relations legislation, and military behavioral modeling on the

perspectives of leadership from the traditionalist through millennial generations. It

offers a cross-functional view of the future foci for generational leadership

research, its applications, and implications on evolving organizational cultures.

A Systems Look at Leadership

Despite the frequent use of the term systems by academicians and management

practitioners, there is little agreement as to what the term really means (Kefalas,

International Leadership Journal Summer 2019

2011). A system is “the name of an abstract concept, that of a complex whole

entity of a particular kind,” according to Stacey, Griffin, and Shaw (2000, 46).

Systems theory, or the systems approach, originated in the physical sciences,

where it challenged the prevailing Cartesian orthodoxy by methodically testing

instability, nonlinearity, and other complex variables of the natural world (Mingers

& White, 2010). Kefalas (2011) describes this way of thinking (i.e., systems

thinking) in the human organizational context:

The systems approach sees organizations as organic systems that are in a
continuous interaction with their external environment. This process of
interaction is essentially a process of acquiring information about the changes
in the external environment, evaluating the impact of these changes, and
adapting the organization’s strategy, structure, and evolution. (370)

Palaima and Skaržauskienė (2010) established a link between systems thinking

and leadership performance. They empirically confirmed the theoretical insight that

a systems thinking approach is most important when dealing with the salient

conceptual strategic issues of an organization. This article uses systems thinking

as a theoretical insight to examine the dynamic nature of leadership, based on the

external changes affecting the human condition. It evaluates the evolution of those

changes on the generations, implementing a renewing definition of leadership.

Systems theory posits that a basic system consists of elements that function

interdependently and of inputs, throughputs, and outputs (Katz & Kahn, 1978; St.

Clair, Hunter, Cola, & Boland, 2018). Applied to generational cohorts, each

generation receives new inputs (i.e., social realities and norms) or raw materials

perpetuating the metaphorical systems cycle of life. The common inputs generally

affect a generation’s perspectives on life and specifically affect the meaning and

corresponding actions of the generation’s leadership. Coomes and DeBard (2004)

suggest that history and popular culture could be a useful frame through which one

can better understand various generations. Simply stated, the concept of

generational differences is that the time that one went through secondary school

generally affects one’s views regarding workplace matters (Raines, 2013). Teece

(2018) suggests that the application of systems theory in management ran its

course by the 1980s, yet today, its greater potential is for it to provide a holistic

International Leadership Journal Summer 2019

view of the business enterprise. This article supports the notion that systems

theory applies as a holistic view of the workforce within business.

Millennials have experienced major influencers since the time they could begin

to conceptualize (i.e., preteen). They were affected by computers; mobile

phones; school violence (e.g., Columbine); domestic terrorism (e.g., Oklahoma

bombings and 9/11); celebrity scandals (e.g., O. J. Simpson and Bill Clinton);

parental layoffs; and an ever-increasing diversity of languages, dual ethnicities,

sexual alignment, and nontraditional families (Dwyer, 2009; Rhodes, 1983;

Salahuddin, 2010). The millennial generation experienced the idea that the child

is a central family focus, which substantially changes the input portion of the

systems leadership equation. This generation’s influence on society is

noticeable. So influenced by social media, today, millennials are ‘influencers”

using Instagram, Twitter, and other forms of social media to make their mark on

society (Izea, 2019). However, millennials’ leadership style is embryonic and yet

to be fully discovered (Foot & Stoffman, 1998; Lancaster & Stillman, 2002;

Sahadi, 2007; Zemke, Raines, & Filipczak, 1999) as this generation gains

workplace status. Teamwork plays a main role as an input (Nicholas & Lewis,

2008). The Egyptian government overthrow represents an influential outcome of

a generation that can change situations with the touch of technology—

summoning thousands of previously unknown participants to a cause (Malik,

2014). The instant mass movement approach represents a leader–follower

paradigm disintegration of sorts, as leaders and followers become less

distinguishable. The roles can change within a person as well as among people.

This current reality has been a deliberate evolution, quietly occurring though

the maturation from the traditionalist through the baby boomer generation to the

current generations of Gen X and Gen Y. Daft (2013) provides a review of the

four eras of leadership theory development. Era 1 focuses on the greatness of

the individual person. Era 2 emerged with Taylorism and classical management.

It represents the formalization of rational thinking and organizational structuring.

Era 3 emerged during the time of the quality management and organizational

team structuring movements. Era 4 coincided with the increased societal

International Leadership Journal Summer 2019

consciousness of stewardship and servant leadership frameworks. The

contemporary era, which we label Era 5, is the emergence of the dynamic

interplay in the leader–follower relationship, characterized by distributive

utilization of these roles. The primary role of the individual acting as a leader

must be to develop a culture that enables individuals to coalesce around the

shared purpose of the enterprise (Allio, 2012). There is some caution raised. The

development of “I” among millennials needs to slow down, and maybe even

reverse itself, so that leaders will be able to see issues and pending events from

a total community perspective (Kets de Vries, 2019).

All the eras described above are the result of systemic generational

experiences. First, and most pronounced, are the changes that occurred in the

early 1960s and beyond (see Figure 2 on the next page). Second, millennials are

the first generation in quite some time to experience their formative years without

a global war and the reinforcement of the military model as returning soldiers re-

entered the workplace. In contrast, veterans returning from Vietnam underplayed

their military backgrounds because the populace found disfavor with a war

perceived to have been lost and unjust. For the first time, the military model was

less influential in the workplace. In addition, the baby boomers began to be

exposed from the mid-1960s on to the codification of the civil rights strife of the

1950s, including the Equal Pay Act of 1963, Civil Rights Act of 1964, Age

Discrimination in Employment Act of 1967, Pregnancy Discrimination Act of

1978, Immigration Reform and Control Act of 1986, and Americans with

Disabilities Act of 1990. Millennials benefited from the existence of all these

enactments, but experienced none of the struggles associated with inducing the

passing of these laws.

The final element displayed in the multi-generational leadership model depicts

the timing and expansion of the media messages that greatly influenced each

generation. The media’s effects commenced in the late 1960s with the

introduction of The Phil Donahue Show/Donahue (1967–1996); in the 1980s with

the introduction of The Sally Jesse Raphael Show/Sally (1983–2002); and in the

International Leadership Journal Summer 2019

1990s with Ricki Lake (1993–2004) and The Jerry Springer Show (1991–2019). This expansion of media brought

about the expansion of content well beyond traditional dialogue. Millennials were fully exposed, and remain

exposed, to the media’s timing, complexity, and sophistication.

Geraldo (Geraldo Rivera show; 1987–1998)

The Phil Donahue Show/Donahue (1967–1996) Ricki Lake (1993–2004)

The Sally Jesse Raphael Show/Sally (1983–2002)

The Jerry Springer Show (1991–present)

World War I World War II Gulf War 2
1914–1918 1939–1945 2003–2010

Korean War Vietnam War Gulf War 1 Afghanistan War
1950–1953 1955–1975 1990–1991 2007–present

Cold War
1946–1991

The Civic Rights Act of 1991; The Americans with Disabilities Act of 1990; Age Discrimination in Employment Act of 1967;

Vocational Rehabilitation Act; Pregnancy Discrimination Act of 1978; Equal Pay Act of 1963; Title VII of the 1964 Civil Rights Act

Figure 2. Multi-generational leadership model

1910–1920 1920–1930 1930–1940 1940–1950 1950–1960 1960–1970 1970–1980 1980–1990 1990–2000 2000–2010 2010–2020

Traditionalists Baby Boomers Generation X Millennials

1910–1920 1920–1930 1930–1940 1940–1950 1950–1960 1960–1970 1970–1980 1980–1990 1990–2000 2000–2010 2010–2020

The maturing baby boomers, Gen Xers, and millennials were fully exposed to

the changes associated with talk television, with no subject being too outrageous.

The full spectrum and velocity of information increased, and so too did the

predatory behavior of criminals. The 1981 abduction and slaying of Adam Walsh

brought national attention to a generation that needs to challenge those in

authority (Thomas, 2008). The 2009 financial collapse and the 2011 Occupy Wall

Street protest movement solidified the reaction against the establishment and

authority. Each life event added to the generational cohort’s discernment of

authority and leadership roles (Deal, 2007; Williams, 2007; Zemke et al., 1999).

The above inputs shaped the respective generations. It made Gen Xers “not as

a separate generation, but rather the concluding stages of the baby boom

generation” (Foot & Stoffman, as cited in Dwyer, 2009, 103). The cohort sought a

new work environment, as Gen X’s leadership style reflected fairness and

competence (Houlihan, 2007; Salahuddin, 2010). It also created a generation

that reportedly lacks the people skills of the previous generations, with a

straightforwardness that may negatively affect others (Sahadi, 2007). Gen Xers

are more concerned about productivity than the number of hours spent on the job

(Houlihan, 2007). They view the idea of “face time” as inefficient, wasteful, and

unnecessary. Generation X is characterized as the latchkey kids, independent

(yet dependent on their parents), selfish or cynical, questioning authority,

resilient, adaptable, culturally progressive, and technologically well informed,

expecting immediate results and committing their attention to the team and the

boss (Frandsen, 2009). Collectively, these are neither submissive followers nor

traditional coercive leaders (Bass, 1990).

The baby boomers, Gen Xers, and millennials seek a different understanding of

leaders and leading that is based in a temporal systems lens. Salahuddin (2010)

characterizes the summative differences among the generational understandings

of leadership (see Table 1).

International Leadership Journal Summer 2019

Table 1: Most Admired Leader Characteristics by Generation

Characteristic Veteran Baby Boomer Generation X Millennial

Ambitious 2 10 10 8

Caring 4 4 3 10

Competent 1 1 4 1

Determined 9 9 5 2

Forward-looking 10 2 5 5

Honest 3 5 1 4

Imaginative 6 6 7 9

Inspiring 8 3 9 7

Loyal 7 7 2 6

Self-controlled 5 8 6 3
Note: Bolding added for emphasis by authors. Source: Adapted from “Generational Differences
Impact on Leadership Style and Organizational Success” by M. M. Salahuddin, 2010, Journal of
Diversity Management, 5(2), p. 5. Copyright 2010 by the Clute Institute.

Table 1 offers some patterns that help compare and contrast the view of

leadership among the generations.

• Baby boomers, Gen Xers, and millennials place greater value on

ambitiousness than traditionalists.

• Being determined and forward-looking are no longer considered valuable

leadership characteristics by Gen Xers and millennials.

• Being loyal and inspiring are reemerging as valued characteristics of

leadership.

• Being caring is a highly valued characteristic of millennials.

Historically, the traditionalists valued quality, respect, and authority (Houlihan,

2007). In its simplest form, traditional leadership research adopted the

perspective of leadership as:

• the nucleus of all social movements,

• preeminent within a group of a few people,

• a centralization of effort as an expression of the power of all,

• influenced by the needs and wishes of the group,

• the central focus of activity,

• a position of high potential,

• a primary agent, and

• a person one pace ahead of the group (Stogdill & Bass, 1981).

International Leadership Journal Summer 2019

By contrast, the current generation values individualism. Ironically, millennials

embody core values that are similar to traditionalists in that they believe in

collective action, are optimistic about the future, and trust in centralized authority

of the organization, but only if it is caring (Houlihan, 2007; Howe & Strauss, 2003;

Hughes & Fiehl, 2013). Coworker trust is a significant predictor of lowered

turnover intention, while a trust-based environment encourages high levels of

management having trust in employees and vice versa, which undoubtedly

boosts organizational competitiveness (Semerciöz, Hassan, & Aldemir, 2011).

The root of trust lies in strong relationships.

Leadership and the Millennials

Hewlett, Sherbin, and Sumberg (2009) describe how the oldest and youngest

cohorts in the workplace demand many of the same things. They contend that

millennials are powerfully reshaping work agendas. Harris (2011) asserts that the

baby boomer leadership has failed, and millennials are displaying divergent

leadership behaviors.

The Millennials are entering and leaving college largely dedicated to issues that
exceed self-interest. Millennials are the new service generation, and like a true
Millennial, my first job out of college was working for the nonprofit I helped start.
I want the world to be a better place, and I think dedicating at least part of your
life to service is how we can make lasting change. This spirit runs at odds with
the dominating zeitgeist of the Baby Boom Generation. (Harris, 2011, para. 7)

Loehr (2013, as cited in Sullivan, 2013) warns that massive changes are coming

to workplace demographics, and if leaders do not begin preparing now, they may

find themselves outdone by a competitor whom they originally trained, or be left

with employees who are ill-equipped to perform their duties. One example of

such massive change is the #MeToo movement. It is fairly common knowledge

that the election of a record number of women in the November 2018

U.S. congressional elections will cause many changes. Sessa, Kabacoff, Deal,

and Brown (2007) examined leisure time and electronic personal connections

outside the workplace as the preferred friendship building arenas of what the

authors call GenMe (i.e., millennials). Leadership may be less personal to them.

This generation has lived through a series of Enron-like leadership debaucheries.

International Leadership Journal Summer 2019

Sessa et al. (2007) provide some of the first empirical evidence of a generational

shift in work values. Understanding the work values of these young individuals

helps organizations appreciate leadership evolution and how to support the

popular notion that leisure is a particularly salient work value for millennials

compared to baby boomers. Leaders should accept that the shift toward leisure

reflects the realities of the current work environment. Loehr (as interviewed in

Sullivan, 2013) says that today’s leaders should overhaul their leaders in training,

create an initiative and contribution culture, and fill the talent pipeline now.

Therefore, which leadership theory is most likely to accommodate this new

generation? Reviewing the leadership theories currently in use can be instructive.

Stewardship (Block, 1993) and servant leadership (Greenleaf, 1977) are earlier

models consistent with the millennial mindset, but rarely practiced in the

workplace. With the flattening of organizational pyramids and the loss of

management positions, most millennials are experiencing job enlargement and

increased committee responsibilities. This group work will alter the focus of the

zeitgeist leadership models and empowering leadership may be a form of

leadership that is acceptable in multiple cultures (Thomas & Rahschulte, 2018).

The multi-generational leadership model proposes that an egalitarian, fluid, and

dynamic leadership paradigm must emerge along with increased awareness to

address the changing generational expectations and shifting role of today’s

leaders. Emergent leadership (Chaturvedi, Zyphur, Arvey, Avolio, & Larsson,

2012), alternating leadership (Andert, 2011), grassroots leadership (Kezar,

2011), and transcendental leadership (Alexakis, 2011) are leadership styles that

fit the caring, democratic, and imaginative frameworks of millennials. These

developing theories reflect a move away from a predominantly top-down

management focus and toward a more egalitarian orientation with practical

applications and global inclusiveness (i.e., not strictly U.S. based). Organizations

today are flattening their pyramids and assigning workers as “team leaders,”

replacing the traditional entry-level supervisor’s role. Millennials’ team-based,

lackluster desire for organizational commitment complements a dynamic leader–

follower role exchange. Emergent leadership allows for natural self-selection of

International Leadership Journal Summer 2019

role diversity and permits millennials to select and re-select roles, as warranted.

The notion is analogous to self-leadership, which is “apparently not only

beneficial for individual performance, but fosters team members’ teamwork

(proficiency), leads to better adaptation to changes in the team environment

(adaptivity) and, especially, encourages participation in the improvement of the

team’s procedures (proactivity)” (Hauschildt & Konradt, 2012, 164).

Grassroots leadership, as demonstrated during the Egyptian revolution, allows

civic-minded millennials to circumvent the weaknesses of traditional authoritarian

leadership and act in a manner that aligns more with inclusive beliefs. Alternating

leadership aligns with the team-oriented nature of millennials versus the

autocratic-oriented inclinations of previous generations that color millennials’

reality. Finally, transcendental leadership focuses on personal development,

beginning with leader self-motivation toward peak performance, causing workers

to do the same as employee behavior is often indicative of superiors, and

organizational goals to be met or exceeded (Ling, Lin, & Wu, 2016). Similarly, the

transcendent follower expresses competence in terms of their management of

relations with self, others, and the organization (e Cunha, Rego, Clegg, & Neves,

2013). The effect of each generation’s experience redefines the leadership

paradigm. Though the generational realities are still developing for millennials,

researchers and business professionals would be wise to consider the lens

through which this generation views the workplace as unique and unlike previous

leadership perspectives.

Facilitating the Millennial Leadership Paradigm

Tulgan (2011) indicates that the following aids offer millennials the support and

guidance needed to effectively learn and practice general management and

leadership principles:

• Explain that a new role carries with it real authority. A huge new

responsibility should not be accepted lightly.

• Describe for new leaders exactly what their new leadership responsibilities

look like beyond extra paperwork. Explain the “people work” in detail and

International Leadership Journal Summer 2019

create standard operating procedures for managing that focuses on the

basics (e.g., articulating employee expectations, following up regularly,

tracking performance closely in writing, and holding people accountable).

• Formally deputize any new leader, no matter how small the project or how

short the duration of the leadership role. Announce the new leadership to

the whole team, articulate the nature of this person’s new authority, and

explain the standard operating procedures for management that the new

leader has been tasked to follow.

• Check in regularly (preferably daily) with new leaders and review the

standard operating procedures for managing people. Ask about the

management challenges that new leaders are facing. Reinforce their new

authority with the team and every individual on the team.

• Pay close attention every step of the way, and evaluate new leaders in their

new roles. With the right amount of guidance and support, most people

who are very good at their jobs and committed to their work and career

have the ability to grow into strong, competent leaders.

The transcendental leadership model holds that the leader’s role is that of a

facilitator in the motivation process without using punishments and rewards to

manipulate or coerce (Alexakis, 2011). Transcendental leaders invariably provide

corporate social responsibility beyond their organizations’ domains; an appealing

orientation that decidedly attracts and sustains millennial workers and managers.

As in servant leadership, the leader can be most effective when fostering, aiding,

supporting, collaborating, abetting, easing, promoting, cultivating, nurturing,

sponsoring, and otherwise advancing the motivational level that is intrinsically

present within every person (Alexakis, 2011). Both the baby boomer and Gen

Xer mentor and the millennial mentee can benefit as leadership skills are

developed and advanced. Harris (2011) reports that “the Millennial Generation

will be the most educated, and is the most service-minded generation, in

American History. [They] are also the most diverse” (para. 5).

Some empirical studies challenge the popular media concerning the vast

generational differences (Deal, 2007) and have determined that a true tipping

International Leadership Journal Summer 2019

point of change has been reached (Levenson, 2010). Contrary to many popular

press articles, the results of Zabel, Biermeier-Hanson, Baltes, Early, and

Shepard (2017) indicate that there are no generational differences in work ethic

between millennials and other generations. Their research supports Costanza

and Finkelstein’s (2015) broader contention that little actual empirical evidence

exists of generational differences in work attitudes. Others (e.g., Macky, Gardner,

& Forsyth, 2008) call for more research that controls for age and time period.

Deal, Altman, and Rogelberg (2010) sought a new direction that helps the

research and practitioner communities alike understand the realities of

generational similarities and differences so that there may be less reliance on

urban myths and stereotyping. Yet, the generation gap “endures as a staple

American political and social analysis” (Samuelson, 2010, para. 1). In 2000,

Howe and Strauss’s seminal work (as cited in Kowske, Rasch, & Wiley, 2010)

described millennials as having seven distinguishable traits, including being:

• special, vital, and full of promise for themselves and for the future of the

society and the world;

• sheltered from being smothered in their formative years with safety rules

and devices;

• confident, because of their trust and optimism;

• team-oriented, due to being raised in sports teams and group learning;

• achievement-oriented, which is the result of higher school standards and

an instilled sense of accountability;

• pressured by the desire to excel and do well; and

• conventional, rather than rebellious.

Meister and Willyerd (2010) list the “top five things millennials want to learn” from

their employers. Leadership is the third item below “technical skills in my area of

expertise” and “self-management and personal productivity” (Meister & Willyerd,

2010, in graphic).

According to Reinhardt, 2010, millennials recognize that they are

the youngest generation of current employees, say they understand the latest
technological devices, have the ability to multi-task, [and] have plenty of

International Leadership Journal Summer 2019

energy. They also recognize that their positive outlook on life, need for social
interaction and immediate results in their work advancement might be seen as
weaknesses by older colleagues. (para. 11)

The millennial generation can develop its leadership lens by executing the

following guidelines:

• Balance caring with authority when modeling sound leadership.

• Be imaginative and inclusive.

• Provide structure within an informal workplace atmosphere.

• Apply media and technology to everyday activities whenever appropriate.

• Be attentive and sensitive to use of face time only when it makes sense.

• Add teamwork and collaboration to the schedule whenever prudent.

• Provide for social opportunities and connections.

Companies such as Virgin, Google, Facebook, and SAS have gained notoriety

for moving well beyond the workforce commoditization paradigms that endorsed

command over human beings (Heilbroner, 1986) toward enacting an evolved or

enlightened systemic perspective—managing human resource synergy. The

approach points to an expression of a positive systems approach (i.e., holistic

perspective) to understand how to maximize the unique qualities of all current

workplace generations. Such interactive, generationally inclusive human

resource dimensions positively influence the modern organizational culture, in

contrast to the cost-oriented staffing practices of the early 20th century.

Leadership development cannot be separated from the context and culture of

organizational design (Swensen, Gorringe, Caviness, & Peters, 2016). The

paradigm shift toward human resource synergy is illustrated clearly by SAS CEO,

Dr. James Goodnight, who noted that “when 95 percent of a company’s assets

drive out the front gate every night, the CEO must see to it that they return the

following day” (Semerciöz et al., 2011).

Conclusions and Recommendations

Researchers and practitioners can be certain that the definition and application of

leadership is changing temporally and reactive to significant systemic

International Leadership Journal Summer 2019

generational events and experiences. What is obtainable for the current

workplace is to help mirror and model the emerging leadership changes

understood by millennials. Dwyer (2009) offers that “understanding the

differences may enable management to structure strategies and transformation

techniques to motivate employees to the full extent of their skills and abilities to

support the realization of organizational goals and objectives” (101). These

workers will be the next generation of leaders. Where, then, does the future

leadership style of the up-and-coming generation stand? According to Gass and

Bezold (2013):

leadership must also create a workplace culture that is collaborative and
empowers employees. Leaders must also show that they respect their
employees as individuals, openly communicating with them including listening
respectfully to what they have to say. Finally, [sic] leaders need to be open,
trusting and ethical. (691)

Each generation enters the workplace with an understanding and expectation

of leadership roles and processes based on the summative experiences and

major events occurring during their respective formative years. Millennials, as

generations before, arrive in the workplace with a set of predetermined realities

that have shaped their beliefs and values related to what constitutes leader,

leading, and leadership. As millennials learn to lead, Ancona and Bresman

(2018) note that they begin to build knowledge, skills, and applications around a

set of capabilities: sense-making, relating, visioning, inventing, and building

credibility. The authors go on to say that building credibility is central to the other

four. Others (e.g., Groysberg, Lee, Price & Cheng, 2018) suggest that strategy

and culture are the most important focal points for an organization’s success.

The media, human rights legislation, and military experience have played a major

role on each generation’s perceived reality. Millennials’ experiences, media

shrewdness, civic-mindedness, and collaborative nature will continue to mature,

transform, and refine. Leaders, researchers, and practitioners can frame the

future and the resultant redefinition of leadership for this next generation through

a systems thinking approach, working through conceptualizing strategic issues of

the organization as offered by the multi-generational leadership model. This

International Leadership Journal Summer 2019

model seeks to abandon the commoditization of employees offered by early

economic and human relations theorists. It further seeks to abandon the

constructivist cost approach that mechanistically can result in organizational

cultures focused on managing procedure, paperwork, and processes versus

creating synergy through people. The synergy caused by generational

intermingling cannot help but affect employers, sectors, and higher education

institutions (Helyer & Lee, 2012). Ultimately, the root of trust lies in individual

relationships, which create an institutional phenomenon beyond interpersonal

relationships (Semerciöz et al., 2011).

Temporal context represents the lens through which millennials view

leadership. An old lens empties the current reality. Millennials are clearly

rebuffing the norm established by earlier generations (Campione, 2015).

Consequently, researchers and practitioners alike need to reevaluate and frame

(Daft, 2013) an Era 5 of leadership, as millennials dynamically role-switch

between being leaders and followers in pursuit of an egalitarian expression of

leadership discrete from the role of management. Participatory decision making

in the Era 5 sharing economy (e.g., Airbnb and Uber) necessitates

interdependent decisions coupled with highly collaborative interactions pointing

to a robust leader–follower team dynamic.

Likewise, it is time to expand stewardship and servant leadership to include

emergent, grassroots, distributed, and alternating leadership styles as the

potentialities of the millennial generation’s redefinition of leadership unfolds.

Researchers must continue to identify and analyze the new generation’s

predominant leadership paradigm. They must consider an inclusive lens that allows

for a lessening of hierarchical-based, hero-worshipping leadership expressions. The

new focus should increase the fluidity of the role exchange between the leader and

follower. Current generations seek more flexibility when selecting the leader role—

and equally seek the follower role, as needed, when needed.

Limitations of the Research and Future Directions

The above analysis has been limited to North American examples in the

descriptions of the factors influencing generational cohorts. As Nayar (2013)

International Leadership Journal Summer 2019

notes, the challenges of millennial leadership are of more than passing interest to

economically emerging nations, such as India. The authors propose that similar

principles may apply in other nations. The specifics of how these will result in and

influence leadership development requires further examination. China is now

becoming more powerful, and its new leaders are often media subjects. The

events and trends that have influenced their mindsets undeniably merit

investigation. As noted by Wang and Chee (2011), these include the earlier

Western influences, the Soviet legacy, the Cultural Revolution, the resurgence of

classic models, and the rise of new entrepreneurs such as Jack Ma of Alibaba. In

Western Europe (e.g., Germany and the United Kingdom), leadership models

and the generational influences include the austerities of the 1950s, economic

revitalization, reunification, Thatcherism, and so forth. The authors hope and trust

that the research described in this article contributes to the debate as to how to

view and approach the complex study of leadership development globally.

Generation Z (also known as iGeneration) includes those born between

approximately 2000 and 2020. They were not included in this article because

they have not yet entered the workforce in large numbers. In addition, little peer-

edited research currently exists on Generation Z. Future research on

generational differences pertaining to workplace leadership should include the

most recent generational cohort.

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Darlene Andert, EdD, is retired from the faculty of Florida Gulf Coast University’s Lutgert
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earned an EdD in Human and Organizational Development from The George Washington
University. Dr. Andert’s research interests include leadership, group dynamics, and
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reached at dandert@fgcu.edu.

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consulting, and operations positions with academic institutions, corporate organizations,
and small business partnerships. He has provided management training for a variety of
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Adult Educators, he was named 1 of 50 quintessential adult educators of the 21st century.
He is on the editorial boards of Employment Relations Today, the Journal of Applied
Management and Entrepreneurship, and the Employee Responsibilities and Rights
Journal. Six of his books are on the shelves at the Baker Library at the Harvard Business
School. He can be reached at preziosi@nova.edu.

mailto:dandert@fgcu.edu

mailto:galexaki@fgcu.edu

mailto:preziosi@nova.edu

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Research Article
Construction of the Enterprise Human Resource Quality
Evaluation System Based on the WICS Leadership Mode

Na Zong

Huaxin College of Hebei Geo University, Hebei 050700, China

Correspondence should be addressed to Na Zong; 18407233@masu.edu.cn

Received 31 March 2022; Revised 23 April 2022; Accepted 6 May 2022; Published 7 June 2022

Academic Editor: Vijay Kumar

Copyright © 2022 Na Zong. is is an open access article distributed under the Creative Commons Attribution License, which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

With the advancement of society and economy, the market competition among various businesses has become increasingly �erce.
Nowadays, if businesses want to grow in the face of adversity, they must move forward boldly and make use of abundant human
resources to fuel their growth. Human resource management is becoming increasingly important. As a result, this paper develops
an enterprise human resource quality assessment system based on the WICS leadership model. e di�erences between the WICS
model and the traditional management model are �rst compared in this paper. e requirements of the WICS model in human
resource management are then described. Furthermore, this paper proposes a human resource evaluation algorithm that
combines data-driven and WICS models to address the current human resource cost evaluation algorithm’s low accuracy and
poor e�ect. e simulation results show that the proposed algorithm can re�ect changing human resource cost characteristics,
improve human resource cost evaluation results, and obtain better results than other human resource cost evaluation models and
has a wide range of applications.

1. Introduction

e term “leadership” is increasingly being used as a new
term in corporate human resource quality evaluations
(EHRQA). A model with strong leadership can help busi-
nesses attract talent, reduce internal con�ict at work, boost
productivity, and foster a positive work environment. e
corporate market is becoming increasingly competitive as
the information age progresses [1–6]. ere is de�nitely a
struggle for talent and resources going on behind the scenes
of this matchup. e loss of enterprise talents has emerged as
a signi�cant factor impeding the development of businesses.
e factors that have contributed to this occurrence warrant
careful investigation. e EHRQA technique, which is part
of the leadership model, is being implemented progressively
in order to alter the old talent management strategy.
Comparing the leadership model to the typical EHRQA
approach, the leadership model places a greater emphasis on
the applicability of employees to the organization and pays
more attention to the workability and performance of
employees while at work [7–12]. Evaluating employees’

initiative, creativity capacity, and cooperation ability, among
other traits, allows them to maximize their own initiative
and maximize the value of their own abilities, thus enabling
the �rm to enter a new stage of development [13, 14].

Davi-Mc Clelland, a Harvard University professor, was
the �rst to introduce the concept of leadership, which was in
1973. According to any traits that can be consistently
measured or counted, the notion of leadership refers to a
sharp division between outstanding and ordinary people at
work, which can be measured or tallied [15–17]. Examples of
such divisions include work motivation, workplace attitude
or values, personality traits and cognition as well as self-
image, expertise in a speci�c subject, professional abilities,
and so on. We must identify and separate outstanding
performers from those who perform below average, reuse
outstanding leaders, and scienti�cally cultivate ordinary
ability workers, so that they can assume leadership roles.
Currently, the concept of the leadership model is based on
leadership, which means that enterprises place a strong
emphasis on analyzing the leadership level of employees as
well as job requirements, and the standards for human

Hindawi
Mathematical Problems in Engineering
Volume 2022, Article ID 3259403, 8 pages
https://doi.org/10.1155/2022/3259403

mailto:18407233@masu.edu.cn

https://orcid.org/0000-0001-8071-764X

https://creativecommons.org/licenses/by/4.0/

https://doi.org/10.1155/2022/3259403

resource employees are defined in terms of “quality” and
measured in terms of “quantity.”

+e cost of human resources is a significant component
of EHRQA [18, 19]. If the cost of human resources cannot be
accurately estimated, it will result in a significant waste of
human resources, a huge number of lost manpower op-
portunities, and an increase in the operating costs of the
organization as a result. +e cost of EHRQA is therefore
directly tied to the survival of the organization, and the study
in EHRQA is of significant importance [20–25].

Despite this, some businesses, particularly in China, fail
to factor in human resource costs when making operational
decisions. Due to the planned economy’s influence, many
enterprises’ ideas and concepts have lagged behind tech-
nological advancements, highlighting the EHRQA problem.
Over the last decade, the EHRQA problem has garnered
increasing attention from domestic research institutions and
scholars, resulting in the development of a large number of
EHRQA algorithms [26–31]. +e majority of EHRQA is
completed manually, which is the most prevalent method.
Because of the presence of human elements and the poor
objectivity of the evaluation results, the EHRQA results are
blind to a certain extent and it is difficult to acquire the ideal
EHRQA results. With the existence of human factors and
poor objectivity of the assessment findings, using EHRQA
algorithms such as the gray model and neural network, some
researchers have argued that by defining EHRQA indicators,
collecting matching EHRQA data, and developing EHRQA
models, they can get better outcomes than manual tech-
niques in terms of EHRQA results. +e research has pro-
gressed to the point where data on human resource costs has
been amassed, and a considerable amount of EHRQA data
has emerged, which serves as the foundation for data mining
in the field of human resource cost assessment. Chaos theory
is a data-driven strategy that may be used to extract the
changing characteristics of situations from large amounts of
data. It is also a new technology for EHRQA modeling that is
being developed [32, 33].

+e continual appearance of quality difficulties in my
country’s economic market has intensified people’s attention
to quality management, resulting in the notion of overall
quality management becoming more prevalent as the times
have demanded it [34–37]. Personnel have a considerable
impact on the output quality of enterprise products and
services, and EHRQA has emerged as an important com-
ponent of total quality management practice in the process.
Due to the short time span in which comprehensive quality
management has been implemented in human resource
management, there are still some issues that need to be
addressed. Because of this, it is critical to investigate the role
of human resource management in the process of com-
prehensive quality management [38–40].

+is paper proposes a data-driven EHRQA algorithm in
order to improve EHRQA’s accuracy. +e results of this
paper demonstrate that the algorithm can accurately capture
the changing characteristics of human resource costs, im-
prove the results of human resource cost assessment, and
outperform existing human resource cost assessment
models (DDW).

2. The Specific Application of the Leadership
Model in EHRQA

Adopting the leadership model provides a new perspective
and a solid foundation for the EHRQA’s work, clarifies the
human resources departments’ fundamental responsibilities,
and establishes a solid foundation for enterprise develop-
ment. Meanwhile, it provides a solid foundation for the
company’s personnel recruiting, job assignment, employee
training and development, promotion and reward, and other
activities, and it heralds the start of a new era in human
resource development.

2.1. Employee Recruitment. When hiring personnel under
the traditional paradigm, businesses place a greater emphasis
on evaluating candidates’ academic qualifications as well as
their expertise and abilities. As a result, such inspections
have the disadvantage of not delving deeply into the char-
acteristics of employees, which is negative, because both
internal character qualities and employee characteristics are
in the process of long-term development. Marketing social
positions are tough to adapt to for people with avariety of
personality types, such as quiet and sensitive personalities,
who have received extensive long-term training in a timely
manner. As a result, if deep-level features of employees are
ignored, even long-term employee training and investment
training may be ineffective in retaining personnel. +is is a
significant waste of training resources for businesses. +e
features of WICS talents, on the other hand, are taken into
consideration throughout the selection process. Regarding
employees, we thoroughly investigate their fundamental
requirements and features, pay close attention to their fit for
certain positions, ensure that employees can find their dream
employment, and limit the waste of training resources
caused by high employee turnover.

2.2. Work Assignment. +e traditional job assignment is
based on a lack of available positions in the organization and
is centered on affairs, whereas the employee job assignment
under the guidance of the leadership model is centered on
observing the components of the work, analyzing the
characteristics of leadership, and evaluating the performance
of employees, among other things. Leadership tasks are
related to their positions in order to more effectively identify
talent and develop appropriate career planning and com-
pensation designs for employees.

2.3. Staff Training. Employee training in the traditional
sense is primarily concerned with introducing employees to
the job topic and improving their workability. In accordance
with the new model, employee training is based on the
principle of people-centeredness. +is company provides
employees with specialized training that is based on their
own quality conditions, as well as training that is tailored to
their own personal development. It assists employees in
enhancing their own deficiencies while simultaneously re-
ducing training requirements. +e time-consuming steps of

2 Mathematical Problems in Engineering

the content, increased publicity and training of corporate
culture, and instilling a strong feeling of professional belief
and work confidence in new employees are all important
goals.

2.4. Performance Appraisal. +e fundamental criterion of
the leadership model is the ability to discriminate between
the signs of exceptional talent and those of ordinary talent.
One must establish performance appraisal indicators on the
basis of this information, improve performance appraisal
standards by making them more scientific and standardized,
and implement systematic performance appraisal standards
to more accurately reflect employees’ work performance,
allowing outstanding employees to be recognized and
rewarded in a timely manner, as well as being beneficial to
employees and motivating and increasing the motivation of
the employees.

2.5. Career Promotion. Achieving career advancement is
something that every corporate employee hopes and expects
to happen. It is the direct result of the employees’ efforts, and
it signifies that the employees’ abilities and professional
development have advanced to a new level. It is beneficial in
inspiring people to enhance their work abilities, to actively
work hard, and to contribute to the improvement of the
overall competitiveness of the organization.

2.6. Future-Oriented EHRQA. Traditional EHRQA has the
issue of being static and backward-looking, which makes it
ineffective. It focuses on the historical job performance, as
well as the performance of job seekers and employees in the
future. One’s prior success, on the other hand, cannot be
compared to his potential contribution to the organization
in the future. Good performance in the previous year does
not necessarily imply great ability nor does it imply that the
employee will be able to adapt to the company’s future
strategy and culture and continue producing and contrib-
uting in the same manner in the future. It is vital to im-
plement a future-oriented human resource assessment in
order to increase the organization’s strategic flexibility.

Future-oriented personnel evaluation is not simply a
reversal of traditional evaluation; rather, it is a transfor-
mation of traditional evaluation. It necessitates not only the
evaluation of past and present performance but also the
evaluation of the behavior of obtaining performance and
then the inference of the assessee’s ability to adapt to the
future from the behavior performance of the assessee.
Traditional techniques of personnel selection are concerned
with determining the degree to which the candidate’s
existing knowledge, ability, and experience matches the
degree of knowledge, ability, and experience required by the
target position, and using this information as the selection
criteria. While there is nothing wrong with selecting talents
in this manner in order to quickly adapt to job requirements
when the external business environment is relatively stable,
when the external business environment is constantly
changing, or when the company is in a stage of rapid

development, it is possible to select talents in accordance
with the requirements of existing positions. It will diminish
the adaptability of the organization, which means that it will
reduce the firm’s strategic flexibility as well.

Companies must consider the demand for talents for the
role in the future when hiring, and they must select job
applicants based on the talent requirements required for
future opportunities in order to increase strategic flexibility.
Nokia Corporation had hidden concerns about the unex-
pected future instability of the industry at the beginning of
this century in the consideration and strategic layout of
talent selection, and it used this as a starting point. People
who are adaptable to future development and change have
been identified as the primary target of talent recruitment.
Instead of focusing on the most competent talents available
at the time, this strategy allows the company to make swift
adjustments when faced with organizational changes and
significant changes in the industrial environment, thereby
avoiding the creation of a talent crisis in the first place.

How is a future-oriented human resource assessment
conducted? By establishing standards, such as the Nokia’s
“two-dimensional” model, the universal competency model
based on future change and development, as well as industry
and organizational characteristics, lays the groundwork for
assessment. +e organization’s use of a professional com-
petency model enables it to conduct a future-oriented hu-
man resource evaluation. Human resource evaluation in the
future requires enterprise managers to have strong strategi

analysis capabilities. +ey can contribute actively to strategy
formulation and analysis of the organizational environment.
Businesses should focus on predicting the evaluation object’s
ability and performance in future situations from a timely
perspective when conducting talent evaluation activities
such as recruitment, selection, and assessment, following the
establishment of talent evaluation standards. Following the
evaluation, it is critical to adjust the prediction level of the
evaluation standard in accordance with actual employee
performance in order to improve the forecast’s accuracy and
thus the evaluation’s effectiveness.

2.7. 1e Importance of Establishing a Training System.
Enterprises have largely recognized the necessity of training,
but the majority of training sessions are conducted on an
emergency basis, frequently in response to group difficulties
in management or when performance has been slow for a
lengthy period of time. Retraining is an after-the-fact
remedy when it comes to increasing strategic flexibility,
according to this approach. If a company wishes to achieve
“longevity,” the concept of adapting to “cure” is a “disease-
prevention” approach, which involves developing a forward-
looking training system and strengthening the strategic
flexibility of the company, resulting in a driving force for
long-term development.

+e forward-looking training system is comprised of two
components. +e first component is forward-looking
training based on personal development, and the second
component is forward-looking training based on organi-
zational change. Employees’ knowledge of their own

Mathematical Problems in Engineering 3

personal development may increase, which may lead to a
demand for training in the form of a work transfer, job
promotion, or job skills enhancement as a result of this
increased awareness. After comparing the existing wor

skills of employees with the potential future work skills
requirements, businesses can �nally determine their training
requirements. In some circumstances, even though the
current work performance of employees is satisfactory to the
�rm, there is still a gap between the requirements of the
organization’s plan and the current work performance of
employees, which must be addressed in advance through
training.

Organizational change occurs as a result of a variety of
factors, including competition and technological innovation,
stagnation in industry development, strategic goal adjust-
ment, the evolution of the enterprise life cycle, and natural
and man-made disasters. Human resource managers can
anticipate this transition to the greatest extent possible,
enabling them to provide training support with a high
degree of match during the strategic planning and pro-
motion stages. Investing in this type of forward-thinking
training bene�ts the organization by assisting and pro-
moting the development and implementation of the overall
plan. It contributes to employees’ long-term ability and
competency development.

3. The DDW Model

is paper proposes the DDW model for EHRQA. e
model structure is shown in Figure 1.

EHRQA concerns are in�uenced by a variety of factors,
including human resource introduction policies and in-
centives, as well as the operational state of the business. e
implicit change trend provides a credible foundation for
human resource cost assessment modeling. Chaos theory is a
widely used data-driven method. It is possible to invert the
changing trend of human resource costs using phase space
reconstruction technology, and a learning sample of human
resource costs can be generated. As a result of the experi-
ment, chaos theory is applied to human resource cost data in
this work and a multidimensional human resource cost time
series is created.

Let the historical EHRQA data of a certain enterprise be
x(tj), j � 1,2, · · · ,n{ }, n represents the number of EHRQA
samples, and the original EHRQA data is transformed into a
more accurate EHRQA data by determining the delay time λ
and the embedding dimension m of x(tj). Regular EHRQA
cost data is as follows:

X(l) �[x(l),x(l + λ), · · · ,x(l +(m − 1)λ)],
l � 1,2, · · · ,M.

(1)

According to the results of the analysis of (1), the values
of the variables λ and m of x(tj) are extremely important for
accurately estimating the cost of human resources, where λ
represents the time interval between data points and m
represents that multiple data points are related to the current
human resource cost. e optimal value λ of human resource
cost data should be determined using the CC method, and

the optimal value m of human resource cost should be
determined using the CAO algorithm.

e steps to determine λ are as follows:

(1) Setting two EHRQA data as X(i) � [x(i), x(i + λ),
· · · ,x(i + (m − 1)λ)] and X(j) � [x(j), x(j + λ),
· · · ,x(j + (m − 1)λ)], the distance between them is

rij �‖X(i) − X(j)‖. (2)

(2) When calculating the value of a human resource cost
assessment, the critical radius r is used to de�ne its
valid range, the data points within the critical radius
are statistically sensitive, the logarithmic ratio of
statistical data points by the associated integral is
used, and the calculation formula is as follows:

C(m,N,r,λ) �
2

M(M − 1)
∑

1≤i≤j≤M
H(r − ‖X(i) − X(j)‖), (3)

where H(r − ‖X(i) − X(j)‖) is

H(x) �
0,x≤

1,x>0
{ . (4)

In accordance with the critical radius, we divide the
complete EHRQA data set into t subhuman resource cost
assessment data sequences, with the following results:

S(m,r,λ) �

t
∑

l�1
Cl(m,r,λ) − Cl(m,r,λ)[ ]

m{ }. (5)

e di�erence between the data is

ΔS(m,l) � max S m,rj,λ( )[ ] − min S m,rj,λ( )[ ]. (6)

en,

Human resource cost data

Chaos Analysis

Training set

Extreme training set

Particle Swarm
Optimization Algorithm

DDW

whether to quit

YES

Figure 1: structure of our framework.

4 Mathematical Problems in Engineering

ΔS(l) �
1
4
∑
k

m�1
ΔS(m,t). (7)

IfΔS(l) gets the �rst minimum value, it means that the λ
value at this time is the optimal EHRQA data delay time.

e steps to determine m are as follows: the ith
reconstructed human resource cost assessment data is
Xi(m + 1), and its nearest neighbor EHRQA data vector is
Xn(i,m)(m + 1); then,

α(i,m) �
Xi(m + 1) − Xn(i,m)(m + 1)
��

��
Xi(m) − Xn(i,m)(m)
��

��
,

i � 1,2, · · · ,N − mλ.

(8)

en,

E(m) �
1

N − mλ
∑
N− mλ

i�1
α(i,m). (9)

Suppose there are k EHRQA data in total, they form a
data set Sk (xp,tp){ }

p�1, and the EHRQA data set after

chaotic processing is xp � xp,xp+1, · · ·xp+m− 1{ }
T
,

wheretp � xp+m and m is the embedding dimension; we can
get

min
1
2
βTk βk +

2
εTk ε( ),

s.t. tp � ∑
L

i�1
βkf αkxp + bk( ) − εkp � 1,2, · · ·k


 .

(10)

en,

l w,ε,βk( ) �
1
2
βTk βk +

2
εTk ε − w Hkβk − Tk − ε( ),

s.t. tp � ∑
L

k�1
βkf αkxp + bk( ) − εkp � 1,2, · · · ,k


 .

(11)

β1 βi βL

oj
Output Node

L Hidden Nodes

n Input Nodes

(ai, bi)
i

l n

Figure 2: e structure of ELM.

0
0 50 100 150 200

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Figure 3: Comparison of di�erent models.

Mathematical Problems in Engineering 5

Let the partial derivative of (11) be 0; then,

zβL
⟶ βTk � wHk

zε
⟶ cεT + w � 0

zw
⟶Hkβk − T − ε � 0




. (12)

Let t and x be the input and output of EHRQA, re-
spectively; then the extreme learning machine of EHRQA is

t � ∑
L

i�1
βkf αkx + bk( ). (13)

e extreme learning machine is shown in Figure 2.

4. Results

For the purpose of evaluating the performance of the DDW
algorithm, an EHRQA data set has been selected as the study
object. ere are a total of 300 data points in this set, which
have been normalized to the range of 0–1, as shown in
Figure 3. As a validation set, we choose 100 data points.

Figure 3 illustrates how chaos theory was used to obtain
the EHRQA data. is demonstrates that the EHRQA data
exhibits a certain degree of temporal correlation, as indi-
cated by the ideal EHRQA data with T�5 and m�5. The
original EHRQA data is processed and normalized to the
time interval T�5 and m�5. ere are EHRQA learning
samples available.

Figure 4 and 5 illustrate EHRQA results obtained using
the algorithm described in this article. As can be seen, the
model presented in this research is capable of accurately
predicting the changing trend in EHRQA and producing

0 1 9 17 25 33 41 49 57 65 73 81 89 97 10
5

11
3

12
1

12
9

13
7

14
5

16
1

16
9

17
7

18
5

19
3

0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1

TRUE
Train predict

Figure 4: Train results.

1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97
0.1

0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
TRUE
Train predict

Figure 5: Test results.

6 Mathematical Problems in Engineering

near-perfect EHRQA results. e �ndings demonstrate that
chaos theory and extreme learning can be integrated into
EHRQA research and that the resulting human resource cost
assessment is reliable.

As part of the e�ort to make the experimental �ndings
of the human resource cost assessment algorithm in this
study comparable, the BPNN, ARIMA, and SVM algo-
rithms are utilized as comparison algorithms and the RMSE
and MAPE algorithms are employed to evaluate EHRQA
results, respectively. e comparison results are shown in
Figure 6.

It can be seen that the DDW method outperforms the
other methods on both metrics. Among the four methods,
BPNN has the worst performance, followed by SVM, and
ARIMA is slightly lower than the DDW model.

5. Conclusion

e enterprise-wide human resource quality assessment
(EHRQA) is a critical metric for determining an organi-
zation’s human resource management e�ectiveness. Due to
the fact that EHRQA is dependent on factors such as �-
nancial resources, reputation, personnel age and degree
structure, and other criteria, as well as the local human
resources introduction policy, the EHRQA procedure is
quite complex. To improve the accuracy of EHRQA, an
algorithm based on the data-driven and WICS leadership
model is developed and chaos theory is incorporated to
analyze the original data for the human resource cost as-
sessment and establish human resource costs. We evaluate
the learning samples to ascertain the underlying charac-
teristics of the data’s variance. In addition, the extreme
learning machine is used to learn the data for the human
resource cost evaluation, and as a result of this learning, the
human resource cost evaluation algorithm is developed. is
is the outcome of the cost-bene�t analysis of human
resources.

Data Availability

e data sets used to support the �ndings of this study are
available from the author upon request.

Conflicts of Interest

e author declares no con�icts of interest.

Acknowledgments

e paper was supported by (1) Human Resources and Social
Security Issues in the Hebei Province, the Research on the
Optimization of Human Resource Management Professional
Talent Training Model from the Perspective of the Big
Data—Taking Huaxin College as a case study, under JRSHZ-
2021-01077, and (2) Human Resources and Social Security
Issues in the Hebei Province, Discussion on the Path of
Improving the Young Teachers Instructional Leadership in
Colleges and Universities in the Hebei Province, under
JRSHZ-2022-01065.\\S1HCIFS01\DEMData\16955\MYFILE-
S\HINDAWI\MPE\3259403\PROOF\COPYEDITING\gs2

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articles for individual use.

OPTIMAL

TALENT
MANAGEMENT
O F T H E ACQ U I S ITI O N WO R K FO R C E
IN RESPONSE TO COVID-19:
DYNAMIC PROGRAMMING

APPROACH

Tom Ahn and Amilcar A. Menichini

A s the economic impact of the COV ID-19 pa ndemic lingers, w ith the speed of
recovery still uncertain, the state of the civilian labor market will impact the public
sector. Specifica lly, the relatively stable and insulated jobs in the Department of
Defense (DoD) are expected to be perceived as more attractive for the near future.
This implies changes in DoD worker quit behavior that present both a cha llenge
and an opportunity for the DoD leadership in retaining high-qua lity, experienced
ta lent. The authors use a unique panel dataset of DoD civilian acquisition workers
a nd a dyna mic progra mming approach to simulate the impact of the pa ndemic
on employee retention rates under a variety of recovery scenarios. Their findings
posit that workers will choose not to leave the DoD while the civilian sector suffers

 Image designed by Nicole Brate

OPTIMAL

TALENT
MANAGEMENT
O F T H E ACQ U I S ITI O N WO R K FO R C E
IN RESPONSE TO COVID-19:
DYNAMIC PROGRAMMING

APPROACH

from the impact of the pa ndemic. This a llows leadership to more ea sily reta in
experienced workers. However, once the civilian sector has recovered enough, these
same workers quit at an accelerated rate, making gains in ta lent only temporary.
These results imply that while the DoD can take short-run advantage of negative
shocks to the civilian sector to retain and attract high-qua lity employees, long-run
retention will be achieved through more fundamenta l reforms to personnel policy
that make DoD jobs more attractive, no matter the state of the civilian labor market.

DOI: https://doi.org/10.22594/dau.21-871.29.0

Keywords: Dynamic Retention Model, Dynamic Programming Model, Optimal Personnel

Policy,

Acquisition Workforce

Retention

Tom Ahn and Amilcar A. Menichini

a nd a dyna mic progra mming approach to simulate the impact of the pa ndemic
on employee retention rates under a variety of recovery scenarios. Their findings
posit that workers will choose not to leave the DoD while the civilian sector suffers

52 Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 7

Optimal Talent Management of the Acquisition Workforce in Response to Covid-19 https://www.dau.edu

The initial impact of the COVID-19 pandemic on the U.S. civilian labor
market was massive, with the unemployment rate spiking to 15% in May
2020. W hi le most world economies contracted in 2020, there is some
consensus among economists of a relatively robust recovery in the near
future, with average global economic growth projected to be about 5.5% in
2021 (International Monetary Fund, 2021). In the United States, the unem-
ployment rate has already recovered partway since the nadir. However, the
trajectory of recovery remains unclear, depending on a host of public health
programs, government stimulus, and the macroeconomic environment.
While the civilian labor market has seen extraordinary swings in employ-
ment numbers, the government sector has been somewhat immune to the
short-term effects of the pandemic. We examine the potentia l impacts of
the g yrations and continuing uncertainty in the civilian labor market on
the labor ma rket decisions of public-sector employees, focusing on the
civilian Defense Acquisition Workforce in the Department of Defense (DoD).
Historically, senior DoD leadership has been concerned with losing quali-
fied senior civilian workers to the private sector. However, the labor market
impact of COVID-19 may present a pressing need to adjust personnel policy,
as well as an opportunity to leverage the stability of DoD positions to com-
pete against the draw of more lucrative salaries at private firms.
We solve a dynamic programming model of worker retention behavior, where
long-lasting shocks in the civilia n labor ma rket a re explicitly modeled.
Retention behavior refers to the employee’s decision to remain on the job to
which currently assigned (i.e., Defense Acquisition Workforce, as defined in
this article) from one period to the next. By shocks, we mean sudden, unpre-
dictable events that affect the civilian labor market. Shocks in principle can
be positive (such as unanticipated government stimulus) or negative (such

as the COVID-19 pandemic). Many researchers model such shocks
as temporary, with their effects on the economy dissipating

after one period. Our model allows for negative shocks
to slowly recover through time. A f ter ca librat-

ing the model pa ra meters to the Defense
Acquisition Workforce using a unique

panel administrative personnel
dataset that tracks the civilian
DoD labor force over t he spa n
of 30 yea rs, we simulate civ i l-
ia n-side la bor m a rket shock s
t h at c or re spond t o e c onom ic
recoveries of varying speeds and
forecast the retention behavior
of the workforce.

53Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

January 202

We find that a persistent negative shock to the civilian sector (plus insula-
tion of the government/DoD labor market from the shock)—in our case, the
COVID-19 pandemic—leads workers to deva lue jobs in the private sector
in the short-run and remain in the government sector for a longer period of
time. Depending on the severity and persistence of the shock, it may take
more than a decade for workers to return to valuing civilian jobs as they did
before the pandemic. This relative increase in attractiveness of government
jobs is only temporary, however, and workers accelerate their exit from the
government sector into the private sector once the economic recovery is well
underway. That is, the retention rate when the economy recovers turns out
to be lower than the rate that would have prevailed had the global pandemic
not occurred.

The sections that follow review the relevant literature and describe in more
detail the labor market impact of COVID-19 on the private sector and the
long-run career trajectories of the typical Defense Acquisition Workforce
employee. Further discussion explains the dynamic programming model,
describes the data, and calibrates the model parameters. Final discussion
considers potential COVID-19 scenarios, projects behavior of the workforce
under differing scenarios of economic recovery, and states our conclusions.

Literature Review
Employee retention ha s been studied ex tensively in the personnel

economics literature. Most studies have been theoretic in nature or have
focused on the private sector due to data availability (Barron et al., 2006;
Fallick et al., 2006; Gibbons & Katz, 1991; Lazear, 1986; Wilson, 1969; among
many others). One strand of the literature examines retention issues in the
DoD, focusing on active-duty soldiers and officers at inflection points in
their careers, such as the end of the first Service obligation or promotion
(Goldberg, 2001; Warner, 1995). Others study the impact of reenlistment
bonuses (Hattiangadi et al., 2004), civilian sector options (Fullerton, 2003),
and nonmonetary job characteristics (Golding & Gregory, 2002).

While the civilian labor market has seen
extraordinary swings in employment
numbers, the government sector has been
somewhat immune to the short-term effects
of the pandemic.

54 Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

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Our article complements the literature on retention issues in the Defense
Acquisition Workforce. Guo et a l. (2014) a nd A hn and Menichini (2021)
investigated t he demog raphic factors a ssociated w it h hig her Defense
Acquisition Workforce employee retention, such as performance ratings
and education. Focusing on retention strategies, Schwartz et al. (2016) ana-
lyzed the pay flexibilities authorized by Congress and the Office of Personnel
M a n a gement t o en h a nc e ret ent ion of t a lent e d D efen s e A c qu i sit ion
Workforce personnel. Alternatively, Kotzian (2009) proposed organizational
culture and leadership style as effective strategies to increase retention in
the long-run. In line with Kotzian, Jenkins (2009) suggested that, instead of
monetary benefits, workplace satisfaction and organizational commitment
should be the focus of the leadership to achieve highly qualified employee
retention. Dobriansky (2009) noted the stability of government positions
as a draw for workers compared to the private sector.

Our article is a lso related to the literature using the Dynamic Retention
Model (DRM) to study employee stay/leave decisions in the government
sector. For instance, Asch et al. (2013) used the DRM to analyze how policy
changes affect retention decisions during the transition period between the
old and the new regulations (e.g., impact of changes in retirement policy).

The Impact on Unemployment
Arising from Covid-1

The short-run impact of COVID-19 has been extraordinary, with the
nation’s unemployment rate spiking to almost 15% from near historical lows
(3.5%) in 2 months. As Figure 1 shows, even during the Great Recession,
the nation’s unemployment rate peaked at 10.6%. As a further reference,
we added a yellow line in Fig ure 1 showing the previously recorded a ll-
time high in monthly unemployment rate from the U.S. Bureau of Labor
Statistics, which was about 11% at the end of 1982. The Cong ressiona l

55Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

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Budget Office (CBO) projects that the U.S. economy will grow 4.6% in 2021,
after contracting 3.5% in 2020. These are significantly upwardly revised
estimates from its report in July 2020, when the CBO projected a growth
rate of 4%. Correspondingly, employment has recovered sharply since May
2020 (CBO, 2021)

FIGURE 1. CIVILIAN UNEMPLOYMENT RATE

U.S. Unemployment Rate
1

6
4
2
0

JA
N

-0
1

A
U

G
-0

M
A

R
-0

O
C

T-
0

2
M
A

Y
-0

D
E

C
-0

JU
L
-0

F
E

B
-0

S
E

P
-0

A
P

R
-0
6

N
O

V
-0

JU
N

-0
7

JA
N

-0
8

A
U
G
-0
8
M
A
R
-0
9
O
C
T-
0
9
M
A

Y
10

D
E

C
-1

JU
L
-1

1
F
E

B
-1

2
S
E

P
-1

2
A
P

R
-1

3
N
O

V
-1

3
JU
N

-1
4

JA
N

-1
5

A
U

G
-1

5
M
A
R
-1
6
O
C

T-
16

M
A

Y
-1

7
D
E
C
-1
7
JU
L
-1
8
F
E
B
-1
9
S
E
P
-1
9
A
P

R
-2

0
N
O

V
-2

0
Note. Raw data from Bureau of Labor Statistics

FIGURE 2. CAREER TRAJECTORIES OF DOD AWF EMPLOYEES

AWF Retention by Gender

Years of Service
0 5 10 15 20 25

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

R
e

te
n

ti
o

n
R

at
e

Male

Female

Note. Adapted from Ahn and Menichini (2019).

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FIGURE 3. UNEMPLOYMENT RATE BY SECTOR, NOVEMBER 2020

Government workers
Financial activities

Education and health services
Manufacturing

Self-employed workers
Professional and business services

Wholesale and retail trade
Construction

Transportation and utilities
Other services

Information
Agriculture

Leisure and hospitality
Mining, quarrying, and oil and gas extraction

0 5 10 15 20

Note. Raw data from Bureau of Labor Statistics
However, it remains unclear when the economy can return to “business-as-
usual” and how much vigor it will have on the rebound. Public health factors
such as the efficacy of vaccines and their distribution, the spread of more
infectious variants of COVID-19, and sustained use of masks and socia l
distancing until herd immunity is reached, will all play a role. In addition,
the recovery of the rest of the world; additional federal, state, and local fiscal
stimuli; as well as permanent changes in the economy, such as expanded
work-from-home and reconfiguration of global supply chains, may impact
the private-sector labor market for years to come.

The impact of such changes to the private sector will inevitably affect the
public sector, especia lly for the civilia n workforce within the DoD. The
combination of uncertainty in the private sector and a comparatively stable
government sector is expected to alter their long-term career trajectories.
Figure 2 shows the retention rate of Defense Acquisition Workforce work-
ers, adapted from Ahn and Menichini (2019). The sample covers September
1987 to December 2018. Approximately 30% of workers leave the DoD after
about 8 years of service. After approximately 25 years of experience, roughly

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three-qua r ters of employees have lef t. W hile it is undeniably tr ue that
some employee turnover is beneficial (for instance, to jettison low-quality
or unmotivated employees and bring in fresh ta lent), DoD leadership has
consistently expressed a desire to hold on to highly skilled and experienced
civilian workers (e.g., Department of Navy, 2018).
W hile the shock of COVID-19 has been felt in a lmost ever y sector of the
labor market, the government sector has notably been shielded from the
worst of the impact. Figure 3 shows that, as of November 2020, government
workers experienced an unemployment rate around 4%. This rate is lower
than workers in the education and health services fields, who have received
much wider media coverage of labor shortages due to the health risks from
their proximity to the pandemic.

While job stability has always been a draw for the government sector, the
state of the economy as well as the continuing uncertainty about the speed
of economic recover y should ma ke jobs in the DoD relatively much more
attractive. Indeed, this argument parallels what has been known for a long
time in military recruiting: demand for military jobs is countercyclical to
the state of the civilian economy. With the backdrop of this large, negative,
persistent, and unpredictable shock to the civilian labor market, we model
the long-r un labor ma rket decisions of civ i lia n DoD employees using a
dynamic programming framework.

Model
I n t h i s sec t ion , we descr ibe t he d i f ferent pa r t s of t he D y n a m ic

Programming Model of employee retention that will be used to produce
policy simulations.
We assume Defense Acquisition Workforce workers are rational decision
ma kers who ma ke career choices to ma ximize utility over their lifetime.
The individual evaluates, at each decision point, all the costs and benefits
involved in each possible choice, including pecunia r y as well as nonpe-
cuniar y elements, which we describe in the following discussion. At the

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beginning of each period (i.e., 1 yea r in this a r ticle), the worker chooses
between leaving the Defense Acquisition Workforce to continue a career
in the private sector or remaining in the public sector one more period. In
addition, given that we observe in our data that only about 6% of workers
who leave the Defense Acquisition Workforce return at a later date, plus the
difficulty in discerning why they left (and why they returned), we further
assume that leaving the Defense Acquisition Workforce is a n irreversi-
ble decision.
We next describe all the costs and benefits (including monetary and non-
monetary elements) that the individual trades off in every decision point.
We assume that the pecuniary components include:

• Defense Acquisition Workforce compensation, including basic
pay, health insurance, locality adjustment, bonuses

• Compensation in the private sector

We also assume the Defense Acquisition Workforce employee is included
in the Civil Service Retirement System (CSRS), and model public retire-
ment accordingly. W hile our dataset conta ins employees from both the
discontinued CSRS and the current Federal Employee Retirement System
(FERS), we model the CSRS because more individuals belong to that system
in our sample. For employees working in the private sector, we assume they
are contributing to a 401(k) plan where the employer matches up to 10% of
gross pay. As we note in the data section, the moda l Defense Acquisition
Workforce employee has a bachelor’s degree or above and earns close to
$100,000 at the highest paygrade attained. Workers with these characteris-
tics in the civilian sector most often have employer matching 401(k) options.
The nonpecuniary components refer to the individual’s taste or preference
for a job in the Defense Acquisition Workforce versus a career in the pri-
vate sector. These components attempt to capture the taste of those agents
who prefer the higher predictability and stability of public sector employ-
ment, even at the cost of a lower salary compared to the private sector, and
vice versa. To capture these relative preferences, we use taste parameters
reflecting monetary-equivalent preferences for careers in the private versus
the public sectors.

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In particular, we use the following notation to construct the dynamic model:
• Wt

m i nd icat es compen sat ion i n t he Defen se Acqu isit ion
Workforce (including all pecuniary components) in period t

• Wt
c denotes compensation in the private sector in period t

• ωm is the public sector taste parameter, which captures the
monetar y-equiva lent preference for a career in the Defense

Acquisition Workforce

• ωc is the private sector taste parameter, which captures the
monetary-equivalent preference for a private sector career

• T denotes the labor time horizon (number of working periods
before final retirement)

• β = 11 + r is the discount factor, where r represents the subjective
discount rate

• εtm and εtc are the random shocks affecting government and
civilian jobs, respectively, in period t

• E [.|εt – 1] indicates the expectation operator, given the shock in
the previous period

The ma ximization problem faced by the Defense Acquisition Workforce
worker can be described by the following set of equations:

Vt
L = Wt

c + ωc+ βE [ Vt
L

+1|εtc ] + εtc (1)
Vt

S = Wt
m + ωm+ βE [ Vt+1 |εtc,εtm ] + εtm, and (2)

Vt
= Max [ Vt

L,Vt
S ] (3)

In these equations, superscript S denotes the agent ’s choice to continue
working one more period in the Defense Acquisition Workforce (i.e., S =
Stay). Alternatively, super-index L indicates the individual’s choice to quit

Given that we observe in our data that only
about 6% of workers who leave the Defense
Acquisition Workforce return at a later
date, plus the difficulty in discerning why
they left (and why they returned), we further
assume that leaving the Defense Acquisition
Workforce is an irreversible decision.

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the Defense Acquisition Workforce job to continue a career in the private
sector (i.e., L = Leave). Therefore, Vt

S denotes the (present) value of remain-
ing in the public sector one more period, while Vt

L indicates the (present)
value of switching to the private sector. Equation (3) implies that the indi-
vidual will decide to be part of the Defense Acquisition Workforce force in
every period in which Vt

S > Vt
L and will leave the force as soon as the opposite

is true. In economics terms, the va lue of leaving the Defense Acquisition
Workforce, Vt

L, represents the opportunity cost of choosing to stay in the
public sector one more period.
Regarding stochastic variables εtm and εtc, we assume they are independent
and mean reverting over time (t dimension). The specification of the random
shocks is the following:

εtc= μc + ρc εt-1c + τtc, τtc~ N ( 0, σc2 ) (4)
εtm= μm + ρm εt-1m + τtm, τtm~ N ( 0, σm2 ) , and (5)

τtc independent of τtm (6)

That is, the random shocks evolve independently of each other, oscillating
around their own long-run (unconditional) mean over time. In the context of
equations (1)–(3), these stochastic variables could be interpreted as sudden
and unpredicted events impacting the civilian and private sector salaries
(i.e., Wt

m a nd Wt
c, respectively) over time, stemming from, for insta nce,

fluctuations in the business cycle. As we describe later, we use these random
variables to introduce the COVID-19 shock. Ashenfelter and Card (1982)
found that nominal wages are well represented by autoregressive models of
order 1, also known as AR(1) processes. In this type of model, the forecast
of the variable of interest is based on the current value of the variable. For
instance, the prediction of nominal wages in the next period would be based

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on the current value of nominal wages. Over time, random variables follow-
ing A R(1) processes oscillate around their long-run means. Accordingly,
equations (4) and (5) define AR(1) representations for the random shocks.
These AR(1) processes play an important role for our main results as they
allow shocks to persist over time, that is, to gradually fade as time passes.
As we explain in more detail later, we use parameter ρ to define the speed at
which the economy (i.e., wages) recovers from a shock (e.g., from the COVID-
19 outbreak). In terms of the optimization problem described in equations
(1)–(3), random shocks εtm and εtc indicate state variables observed by the
Defense Acquisition Workforce worker at the time of the decision.

Data Description
and Model Calibration

In this section, we describe the Defense Acquisition Workforce sample
as well as the selection and calibration of the parameter values necessary
to implement the Dynamic Programming Model described previously. In
the next section, we show those parameters provide a good approximation
of the long-run labor market outcomes for the representative worker in the
Defense Acquisition Workforce.

Data: The Acquisition Workforce
The Defense Acquisition Workforce comprises approximately 150,000

employees, covering the period September 1987–December 2018. Civilians
make up about 90% of the workforce, while active-duty Service members
make up the remaining 10%. The Defense Acquisition Workforce’s mission is
the “timely and cost-effective development and delivery of warfighting capa-
bilities to America’s combat forces” (DoD, 2015). The Defense Acquisition
Workforce was responsible for overseeing the equipping and sustaining of
the nation’s military, spending over $1 trillion from FY 2016 to FY 2021.
About 26% of the Defense Acquisition Workforce belongs to the engineer-
ing career field, followed by contracting at 19%. Historically, the Defense
Acquisition Workforce was sharply reduced in size and capability during
the 1990s. The DoD started to rebuild the Defense Acquisition Workforce
in 2008 and increased it by approximately 50,000 employees over 13 years.
For this analysis, we restrict our sample to workers who were ever in the
contracting, industria l property management, or purchasing fields. Our
sample workers were born after January 1, 1950, but before December 31,
1980. Workers with birthdates outside this range are either too old, in that
the environment in which they made their labor decisions may not reflect

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current jobs in the Defense Acquisition Workforce; or too young, in that
these workers have not had time to make labor decisions that are pivotal to
their careers. Restricting the sample nets us over 2 million worker-month
records, with over 13,000 unique workers tracked through their careers.
Table 1 presents some summary statistics for our sample.

TABLE 1. SUMMARY STATISTICS

Variables Mean Std. Dev. Min Max

Female 0.632

Minority 0.278

Disability 0.202

Prior Military Service 0.619

Has Bachelor’s Degree 0.547

Has Postgraduate Degree 0.332

Gained Additional Education in AWF 0.441

Career Length in AWF (in years) 12.0 (8.6) 0.1 25.8

Age at Entry 33.0 (8.2) 15 65

Age at Exit 48.2 (10.55) 20 68

Position Type: Professional 0.657

(Ever Held) Technical 0.245

Blue-Collar 0.018

White-Collar 0.297

Ever Rated Not Fully Satisfactory 0.575

Highest Salary 95,143.67 (30,410.74) 27,397 189,600

Observations 13,590

The workforce is predominantly white and female. Over half the workforce
has a bachelor’s degree or above. Compared to the civilian sector, careers
in the Defense Acquisition Workforce are stable, with the average career
length lasting well over a decade. This workforce is also highly paid, with the
average employee earning almost $100,000 toward the end of their career.
On average, workers in this sector begin their career at age 33, which indi-
cates that the position in the Defense Acquisition Workforce is not their first
job. In fact, a large number of these workers have prior military experience.
To rigorously assess the impact of the civilia n sector on the attractive-
ness of the DoD position, every employee in the dataset must be “assigned”
and can expect to earn a civilian wage. To accomplish this, we estimate a
hedonic regression using the Outgoing Rotation Group (ORG) of the Current
Population Survey (CPS). As this dataset contains a representative sample
of workers in the United States, including, most importantly, those who are

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in the government sector, it is possible to make an apples-to-apples compar-
ison with workers in the private sector. (See Ahn and Menichini [2021] for
a detailed description.)
We run a hedonic regression using the individual socio-demographic char-
acteristics, professional and education experience, and locality indicators
from the ORG of the CPS, which broadly match the Defense Acquisition
Workforce variables summarized in Table 1, to obtain predicted civilian
and government sector wages. The difference in the wages across private
and public sectors, conditioned on individual characteristics, defines the
government sector “wage penalty.”

Calibration Results
Before simulating the model described in equations (1)–(3), we define the

parameter values, which we show in Table 2 and subsequently describe. We
can observe in Table 2 that all parameter values, except compensation, are
constant over the career of the Defense Acquisition Workforce employee.

TABLE 2. PARAMETER VALUES

Parameter Value

Wt
m

Wt
c

1.1761

T 25

β 0.95

ωm 1.2782

ωc 1

μm 0

μc 0

ρm 0.90

ρc 0.90

σm 0.005

σc 0.005

As we described earlier, estimates from the hedonic regressions suggest that
income in the private sector (i.e., Wt

c) is, on average, around 17.61% higher
than in the Defense Acquisition Workforce (i.e., Wt

m) for individuals with
similar characteristics. For this reason, after initially normalizing Wt

m = 1,
we let Wt

c = 1.1761. We then add the income from the different retirement
systems; thus, compensation changes over time. The data described earlier
also show that the longest observed labor time horizon among all individuals

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is 25 years. For that reason, we let T = 25. The subjective discount factor is
assumed to be 0.95, implying an interest rate of 5.26%, which is similar to
the average 30-Year T-Bond Constant Maturity Rate reported by the Federal
Reserve Bank of St. Louis for the period covered by the dataset.

Regarding the taste parameters, we ca librated parameter ωm so that the
survival curve predicted by the model approximates the empirical survival
curve as closely as possible via grid search (we show the graphical results of
this calibration in the next section). In more technical terms, the calibration
exercise searches for the value of ωm that minimizes the summed squared
distance between the points of the empirical Defense Acquisition Workforce
survival curve and the points of the survival curve predicted by the model.
As Table 2 displays, we normalize ωc= 1 and, from the calibration exercise,
we obtain ωm= 1.2782. These values are similar to those estimated by Ahn
and Menichini (2021), and imply that the representative Defense Acquisition
Workforce employee prefers the Defense Acquisition Workforce over the
private sector.
The remaining parameter values in Table 2 refer to the stochastic process of
the random variables εtm and εtc . We follow Ashenfelter and Card (1982) to
define the parameter values that govern the AR(1) processes of those terms.
Accordingly, we let parameters μm and μc be equal to zero, we assume values
of 0.005 for the standard deviation of the random shocks, σm and σc, and let
the mean-reversion coefficients, ρm and ρc, be equa l to 0.9. These va lues
depict the historical behavior of the shocks. In particular, those observed
va lues of the mean-reverting coefficients suggest that wages have a high
level of persistence over time; thus, the effects of shocks require a long time
to disappear.

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Model Solution and Policy Simulations
In this section, we describe our policy simulations to forecast evolution

in the behavior of the representative Defense Acquisition Workforce worker
under a number of scenarios with differing speed rates of economic recovery
from a large, abrupt, and unanticipated negative impact (i.e., COVID-19) to
the private sector. This is a major systematic event that adversely affects
all sectors of the economy, except for the public or government sector, which
we assume keeps its employment constant (in fact, any future unanticipa-
ted national shock to the economy and/or public health that is concentrated
mainly in the private sector can be expected to operate in a similar manner).
The assumption that the government sector is not affected by the shock
is consistent with the assumption of independent random shocks in equa-
tion (6).
Concisely, we introduce a large negative civilian shock at a point in time.
Then, we allow the system to recover and converge back to the steady state.
We sta r t a na lyzing retention behavior assuming the economy recovers
according to the empirical historical speed. However, given the observed
recovery from the current pandemic seems to be, so far, much faster than
normal, we also study the retention implications of different scenarios for
the speed of recovery. We “control” the speed of recovery of the economy
by setting the autoregressive term, ρ, which controls the velocity at which
shocks gradually disappear over time.

W hile the private sector goes through its g yrations, at ever y period the
representative Defense Acquisition Workforce agent in our model surveys
the current state of the private sector, forecasts the evolution of the state
of the economy, and makes the ex ante optimal decision to stay or leave the
Defense Acquisition Workforce. We describe the simulation procedure in
more detail next.
We solve the model described in equations (1)–(3) via backward induction.
(See Rust [1987] for an empirical treatment.) That is, we start from the final
period (i.e., t = T = 25) and decide whether to stay one more (final) period in

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the Defense Acquisition Workforce or to leave for the private sector. We then
move one period backward (i.e., t = 24) and select to stay one more period or
to leave the Defense Acquisition Workforce, considering the value from the
optimal decision in period T = 25. We continue moving backward, deciding
rationally in every period, until we reach the present period (i.e., t = 0). This
solution characterizes the retention behavior of a representative Defense
Acquisition Workforce employee in all possible states of the economy.

FIGURE 4. RETENTION BEHAVIOR

AWF Retention

Years of Service
0 5 10 15 20 25
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
R
e
te
n
ti
o
n
R
at
e
s

Dynamic Retention Model

Acquisition Workforce

FIGURE 5. PROBABILITY OF LEAVING

AWF Retention
Years of Service
0 5 10 15 20 25
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
R
e
te
n
ti
o
n
R
at
e
s
Dynamic Retention Model
Acquisition Workforce

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We then stochastically simulate the model forward (i.e., over the 25 years
of work) 100,000 times, which produces the stay/leave decisions of 100,000
employees in all possible different situations over the labor period. These
si mu lat ion s su m ma r i ze t he ret ent ion behav ior of t he represent at ive
employee, which we show in Figure 4. The figure exhibits the ca librated,
model-predicted sur viva l cur ve of the representative individua l ( purple
line) and displays the cumulative probability of the worker staying in the
Defense Acquisition Workforce after a certain period of time. For example,
the figure suggests that the likelihood that the employee is still part of the
Defense Acquisition Workforce after 10 years is about 65%. The figure also
shows the empirical survival curve for the Defense Acquisition Workforce
employees (yellow line) from the data described previously, suggesting that
the calibrated model predicts actual behavior quite closely. While Figure
4 displays the retention behavior of a representative Defense Acquisition
Workforce employee, each demographic group described in Table 1 would
have its own survival curve.

Associated with the previous sur viva l cur ves are the yearly, model-pre-
dicted probabilities of leaving the Defense Acquisition Workforce, which we
show as the blue line in Figure 5. The retention rate is relatively high every
year, as is shown by the fact that the likelihood of leaving is always below
10% per year, and below 5% in the great majority of years. In addition, the
probability of leaving is high initially, and diminishes through time before
increasing again toward the end of the individua l’s career. For instance,
the probability that the employee depa r ts from the Defense Acquisition
Workforce in year 10 is around 2%. As before, we also show the empirical
likelihood of leaving (yellow line) for comparison purposes.
We then proceed to shock the model with a large negative random draw on
the civilian side (i.e., εtc ) at year 10. The shock is equivalent to 3 standard
deviations below the mean and is intended to capture the large effect of the
sudden appearance of COVID-19. In economic terms, given the calibration
shown in Table 2, this shock could be interpreted as a roughly 1.5% reduction

Clearly, the historical coefficient implies
it would easily take a decade or more to
return to normality. However, a year after the
appearance of the virus, the economy seems
to be recovering much faster than suggested
by historical terms.

68 Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

Optimal Talent Management of the Acquisition Workforce in Response to Covid-19 https://www.dau.edu

in the civ ilia n sa la r y, Wt
c, while the public sector sa la r y, Wt

m, rema ins
unchanged. The fact that the random shocks ( both εtm and εtc ) are mean
rever ting over time implies that the impact of the negative shock on the
civilian salary gradually disappears as time passes. As mentioned before,
the speed of return to the pre-shock state will depend on the mean-reversion
coefficient, ρ.

FIGURE 6. EXPECTED IMPACT OF COVID-19 ON CIVILIAN SHOCK

Years of Service
0 5 10 15 20 25

-0.005

–

0.01

-0.015

–

0.02

-0.025

–

0.03

-0.035

E
xp

e
ct

e
d

C
iv

il
ia

n
S

h
o

Recovery Scenario 1 (Rho = 0.3)
Recovery Scenario 2 (Rho = 0.5)
Recovery Scenario 3 (Rho = 0.7)
Historical Recovery (Rho = 0.9)

FIGURE 7. RETENTION IMPACT OF COVID-19

Years of Service
0 5 10 15 20 25
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
R
e
te
n
ti
o
n
R
at
e
s

No COVID-19 Shock
Recovery Scenario 1 (Rho = 0.3)
Recovery Scenario 2 (Rho = 0.5)
Recovery Scenario 3 (Rho = 0.7)
Historical Recovery (Rho = 0.9)

In Figure 6 we show, given the initia l negative shock, how the shocks are
expected to evolve over time for four different va lues of the coefficient of
mean-reversion. The purple bars depict the historical case, which is based

69Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

January 2022

on the obser ved historica l mea n-reversion coeff icient of ρ = 0.9. Clea rly,
the historica l coefficient implies it would easily ta ke a decade or more to
return to normality. However, a year after the appearance of the virus, the
economy seems to be recovering much faster than suggested by historical
terms. We attempt to capture the faster rebound by reducing the coefficient
of mean-reversion (i.e., via a quicker dissipation of the shock). Accordingly,
we analyze three different scenarios featuring dissimilar speeds of recov-
ery, a ll of which are faster than the historica l speed. Scenario 1, with the
blue bars and ρ = 0.3, represents the case of a relatively faster return to the
pre-COVID economy. On the other hand, the yellow bars in scenario 3, with
ρ = 0.7, reflect a slower recovery to normality as compared to scenario 1. In
between are the red bars of scenario 2, showing an intermediate speed of
recovery with ρ = 0.5. Even in the more optimistic recovery scenario 1, the
effects of the large negative shock clearly remain in place for some years.
While we acknowledge that the magnitude and persistence of the shocks
are speculative, they are informed by very recent (and ongoing) research.
Many scholars are currently attempting to forecast the long-run impact of
COVID-19 on the economy. (See Petrosky-Nadeau and Valetta [2020], for
an example of such ongoing research.)

The effect on retention behavior of the representative Defense Acquisition
Workforce worker can be observed in Figure 7. The figure shows that, during
the initia l 10 yea rs, the retention behavior is equiva lent to the blue line
in Fig ure 4. At yea r 10, the COV ID-19 shock happens, a nd the retention
behavior changes considerably. As mentioned before, we study the reten-
tion behavior in four different contexts. The green line shows the retention
impact of the virus under historical terms (i.e., ρ = 0.9). The other lines depict
the expected retention behavior for three faster rates of economic recovery
(i.e., ρ = 0.3, ρ = 0.5, and ρ = 0.7 for recovery scenarios 1, 2, and 3, respectively).
In all cases, a kink and sudden flattening of the curve is evident, suggesting
that individua ls stay longer in the Defense Acquisition Workforce in a n

70 Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

Optimal Talent Management of the Acquisition Workforce in Response to Covid-19 https://www.dau.edu

attempt to avoid the sharp negative effect of the virus shock on the civilian
labor market. Depending on the speed of recovery, it might take a substan-
tia l amount of time for the employee to return to the pre-shock retention
behavior. For instance, in the historica l case it ta kes around 10 years for
the representative employee to return to the previrus retention behavior,
while in scenarios 1, 2, and 3, the return to normality takes roughly 2, 3, and
5 years, respectively. These long-lasting effects on retention behavior have
important implications for the hiring policies of the public sector.
It is worth noting that the time required to return to the “original” behavior
specified previously does not mean that all workers will choose to delay leav-
ing the Defense Acquisition Workforce by several years due to the impact
of COVID-19. Instead, all employees will process the negative shock in the
civilian economy as making the Defense Acquisition Workforce job more
attractive. Until the shock fully dissipates, the DoD position will be more
attractive tha n if no globa l pa ndemic had occurred. However, given the
substantial wage premium in the civilian sector, the pandemic shock does
not need to completely disappear before workers who were planning to move
to the civilian sector resume their plans.

FIGURE 8. LIKELIHOOD OF LEAVING WITH COVID-19

Years of Service
0 5 10 15 20 25
0.1

0.09

0.08

0.07

0.06

0.05

0.04

0.03
0.02
0.01

A
tt

ri
ti

o
n

R
a
te

s
No COVID-19 Shock
Recovery Scenario 1 (Rho = 0.3)
Recovery Scenario 2 (Rho = 0.5)
Recovery Scenario 3 (Rho = 0.7)
Historical Recovery (Rho = 0.9)

To complement the ana lysis of the return to the pre-COVID context, we
present Figure 8. The figure shows the model-predicted yearly probabilities
of leaving the Defense Acquisition Workforce for the four different values of
parameter ρ. The green line shows the retention behavior in the historical
recovery scenario, confirming that it takes around 10 years to return to the
pre-COVID retention behavior (the latter is represented by the no-COVID-
19-shock blue line). The red, yellow, and purple lines, reflecting faster speeds

71Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

January 2022

of economic rebound, suggest that around 2, 3, and 5 years, respectively, are
required to eliminate the effects of the COVID-19 shock on retention. In all
four scenarios, the likelihood of leaving the Defense Acquisition Workforce
goes roughly to zero in the year of the shock, and then slowly starts to return
to the no-shock levels as time passes and the effects of the shock dissipate.

It is also important to note that, after the return to normality, the probability
of leaving is higher in the slower recovery scenarios and lower in the faster
rebound scenarios. More generally, after the COVID-19 shock dissipates, in
all cases with shock, the likelihood of leaving is higher than in the no-shock
case, with that probability increasing in parameter ρ. Indeed, the slower the
recovery from the pandemic (i.e., higher ρ value), the larger the magnitude
of exit probability after the recovery. This outcome suggests that, as more
people decide to stay longer in the Defense Acquisition Workforce during
the pandemic, when the economy returns to norma l the pent-up demand
to leave for the private sector is expressed as a higher likelihood of leaving
in the later years. This implies an opportunity as well as a problem for the
Defense Acquisition Workforce leadership. While a slower recovery may
induce more employees to stay longer, it cannot be a permanent solution to
retain high-ability workers. A higher ρ will result in a much sharper exit of
workers from the Defense Acquisition Workforce once the civilian economy
recovers.

Given the substantial wage premium in the
civilian sector, the pandemic shock does
not need to completely disappear before
workers who were planning to move to the
civilian sector resume their plans.

72 Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

Optimal Talent Management of the Acquisition Workforce in Response to Covid-19 https://www.dau.edu

To reta in these workers, f unda menta l (a nd traditiona l) personnel pol-
icy reforms will be required. For example, a pay increase or expansion of
benefits before the civilian sector fully recovers may permanently induce
senior workers to remain in the Defense Acquisition Workforce. Similarly,
a one-time retention bonus, set far enough into the future when the civilian
economy is back to normal, could prevent that exit.

FIGURE 9. PROBABILITY OF LEAVING WITH COVID-19 AND A BONUS AT 25
YEARS OF SERVICE

Years of Service
0 5 10 15 20 25
0.1
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
A
tt
ri
ti
o
n

R
at

e
s

No COVID-19 Shock, No Bonus
Historical Recovery, No Bonus
Historical Recovery, Including Bonus

Although a full analysis of the available policy reforms is outside the scope
of this article, we show with more detail one particular way by which that
expected long-term effect could be counteracted. In particular, we analyze
the effect of a one-time bonus on the probabilit y of leaving the Defense
Acquisition Workforce when the economy returns to normality. We assume
the bonus is equivalent to 25% of the individual’s monthly salary and is paid
at year-of-service 25 (with the virus shock occurring at year 10). Figure 9
shows the main results of this exercise. The expected bonus has a fairly
sma ll effect on employee retention in the early- and mid-career years, as
the retention rates a re a lmost equiva lent w ith a nd w ithout the bonus.

73Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

January 2022

However, as expected, the effect of the bonus is more visible in the f ina l
years of the employee’s career, when the economy has fully recovered from
the COV ID-19 shock. Without the bonus ( purple line), the likelihood of
leaving is substantially higher than with the bonus (yellow line), suggesting
that, indeed, a bonus would induce experienced employees to stay longer in
the Defense Acquisition Workforce after the recovery. Fina lly, the bonus
is just one of the tools available to the Defense Acquisition Workforce to
affect individua l retention behavior (for instance, sa lary raises would be
another useful tool).

Conclusions
As of early 2021, the overall unemployment rate in the United States

stands at 6.2%—an 8-percentage point decrease in just 8 months from the
worst unemployment rate in almost 90 years arising from the COVID-19
global pandemic, yet still almost double the unemployment rate from just
one year ago. While the recovery has been as dramatic as the decline, the
future remains very much in doubt. For example, in December 2020, payrolls
shrank by 140,000. Outlook has considerably brightened since, but whiplash
in the long-run forecast of economic recovery itself adds uncertainty to
future labor market prospects in the civilian market.

In this environment, we a na lyzed the potentia l impact of the economic
re c over y on t he l a b or m a rket t r aje c t or y of t he D efen s e A c qu i sit ion
Workforce. The contrast in stability of jobs in the government compared to
the private sector should increase the attractiveness of DoD jobs, especially
if the recovery proves to be slow or unpredictable. We built and calibrated a
dynamic programming model of employee retention behavior, analyzed the
impact of a negative persistent shock to the civilian sector, and simulated
different recovery paths.

Forward-looking leaders should regard these
simulation results not as predictions of the
future, but as guides to help set personnel
policies that are flexible and adjustable,
and even take advantage of gyrations in the
civilian economy.

74 Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

Optimal Talent Management of the Acquisition Workforce in Response to Covid-19 https://www.dau.edu

The la rger the magnitude of the negative shock to the civilia n economy,
the more our results show that government positions become more attrac-
tive; while the slower the economic recovery, the more highly employees
may value government positions compared to the prepandemic period for
several years.

W hi le t his env ironment ca n increa se retention of t he avera ge worker
from the Defense Acquisition Workforce, leadership should understa nd
that, eventually, recovery of the civilian sector will push down the relative
desirability of government jobs. This may lead to a speedy exodus of many
senior-level workers who were being held back due to economic uncer-
tainty. Personnel planning without considering the temporary increment
in retention at the beginning of the shock may lead to overhiring, especially
at t he ju n ior-level s . Conver sely,
short-sighted reductions in hiring
due t o t he i n it i a l i mpa c t s of t he
negative shock may lead to a hol-
lowing out of the workforce, once
the shock impact wa nes. In addi-
tion, as the economy recovers, there
m ay b e f u nd a ment a l s t r uc t u r a l
cha nges to t he labor ma rket t hat
rem a i n , ch a n g i n g t he v a lu at ion
of b ot h gover n ment a nd pr iv at e
sector jobs in unpredictable ways.
For wa rd-look i n g lea ders shou ld
regard these simulation results not
as predictions of the future, but as
guides to help set personnel policies
that are flexible and adjustable, and
even take advantage of gyrations in
the civilian economy.

SCAN TO WATCH
Learn more about this article by
watching Dr. Tom Ahn and Dr.
Amilcar Menichini’s presentation,
Optimal Long-Run
Talent Management
of the DoD AWF in
Response to
COVID-19.

https://nps.box.com/s/cenxypjqs92vbmrzg9d2ezbclgkzn0rr

75Defense ARJ, January 2022, Vol. 29 No. 1 : 50 – 77

January 2022

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January 2022

Author Biographies

Dr. Amilcar A . Menichini
i s a n A s sociat e P rofes sor i n t he Gra duat e S chool of Defen se
Ma na gement at t he Nava l Postg raduate School. Before joining
t he Nava l Pos t g ra duat e School , he s t ud ied t o at t a i n h i s Ph D
in Fina nce f rom t he Universit y of A r izona . Dr. Menichini ha s
published in The Financial Review, Review of Quantitative Finance
and Accounting, a nd Souther n Economic Jour nal.

(E-mail address: aamenich@nps.edu)

The views expressed in this article are those of the author(s) alone and not of
the Department of Defense. Reproduction or reposting of articles from Defense

Acquisition Research Journal should credit the author(s) and the journal.

Dr. Tom Ahn
i s a n A s s i s t a nt P r ofe s s or i n t h e G r a du a t e S c h o ol of D e fe n s e
Ma na gement at t he Nava l Postg raduate School. A f ter ser v ing in
The R epublic of Korea A r my for 3 yea rs, he completed a 2-yea r
p o s t – do c t or a t e p o s it ion a t D u k e Un iv er s it y. He t a u g ht a t t he
Un iver sit y of K ent uck y for 7 ye a r s a nd h a s b e en a t t he Nav a l
Postg raduate School since 2017. Dr. A hn ha s published in Journal
of Econometrics, Journal of Business and Economic Statistics, a nd

Jour nal of Urban Economics.

(E-mail address: sahn1@nps.edu)

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