The Relationship Between Employee Engagement, Job Satisfaction

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The Relationship Between Employee Engagement, Job The Relationship Between Employee Engagement, Job

Satisfaction, And Employee Performance in The Federal Satisfaction, And Employee Performance in The Federal

Government Government

Alexis L. Shellow

Walden University

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Alexis Shellow

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Review Committee

Dr. Colleen Paeplow, Committee Chairperson, Doctor of Business Administration Faculty

Dr. Matasha Murrell Jones, Committee Member, Doctor of Business Administration Faculty

Dr. Natalie Casale, University Reviewer, Doctor of Business Administration Faculty

Chief Academic Officer and Provost

Sue Subocz, Ph.D.

Walden University

2022

Abstract

The Relationship Between Employee Engagement, Job Satisfaction, And Employee Performance

in The Federal Government

Alexis Shellow

MBA, Aurora University, 2018

BS, Westminster College, 2015

Doctoral Study Submitted in Partial Fulfillment

of the Requirements for the Degree of

Doctor of Business Administration Secondary Data Analysis Portfolio

Walden University

August 2022

Abstract

Leaders in the U.S. Federal Government face performance challenges due to disengaged

employees and employees with low satisfaction. Leaders within the federal government need to

understand the relationship between employee engagement, job satisfaction, and employee

performance, as decreased employee performance can result in decreased productivity, increased

turnover, and have negative financial implications. Grounded in Herzberg’s two-factor theory

and Kahn’s engagement theory, the purpose of this quantitative correlational ex post facto study

was to examine the relationship between employee engagement, job satisfaction, and employee

performance within the federal government. Data from the 2019 Federal Employment Viewpoint

Survey (n = 100) were analyzed using multiple regression analysis. The multiple linear

regression analysis results indicated the model was able to significantly predict performance

F(2,97) = 43.836, p < .001, R

= .475. Employee engagement (t = 3.594, p < .001, β = .504) was

the only statistically significant predictor. A key recommendation for leaders in the federal

government to engage federal employees is to recognize employee achievements, create a work

environment promoting psychological safety, provide employees with adequate resources, and

have well-defined roles and responsibilities for employees while allowing them to exercise

autonomy in their work processes. The implications for positive social change include the

potential for cost savings, helping leaders in the federal government assess areas of

improvement, creating a more productive environment for improved employee performance, and

increasing employee retention and job satisfaction in the workforce.

The Relationship Between Employee Engagement, Job Satisfaction, And Employee Performance

in The Federal Government

Alexis Shellow

MBA, Aurora University, 2018

B.S., Westminster College, 2015

Doctoral Study Submitted in Partial Fulfillment

of the Requirements for the Degree of

Doctor of Business Administration Doctor of Business Administration Secondary Data Analysis

Portfolio

Walden University

August 2022

Dedication

I want to dedicate my work to my family and friends who have supported me along this

journey; I love and appreciate all of you and would not have been able to do this without you. To

my mother, thank you for instilling in me the importance of hard work, perseverance, and

dedication. To my father, thank you for all the love and support you have shown me through my

journey. To my Gantzy, for showing me what it means to be strong and always welcoming me

with the warmest love. To all my siblings, who have been constant sources of love and support,

and continue to inspire me every day, thank you and I love you. To my Aunt Michelle, I don’t

know where I would be without your constant love, grace, and motivation. To my Uncle Myke,

for always believing in me and providing everything I needed whenever I needed it. To my

Uncle Jay for showing me the importance of following my passions and never giving up on

myself. To my Uncle Corey for always moving mountains to help me become successful. I

would not be where I am today without the love and support I have received from all of you.

Lastly, I would like to dedicate this work to the neurodivergent population. I have

struggled a lot with understanding my abilities and would often limit myself out of fear of failure

and societal perceptions. I hope it serves as a reminder and as motivation that we can do

extraordinary things, including everything that society has told us we couldn’t.

Acknowledgments

I want to extend a special thank you to all my friends, family, colleagues, and mentors.

Without you all, I would not have made it through this doctoral program. To my Chair, Dr.

Colleen Paeplow, thank you for giving me great instruction and guidance, while motivating and

mentoring me along the way. You have shown me so much patience, kindness, and empathy

throughout this journey and I am grateful to be one of your students. To Dr. George Bradley, Dr.

Jaime Klein, Dr. Natalie Casale, and Dr. Matasha Murrelljones, thank you for being a part of my

committee; your feedback and support have helped me to go the extra mile for my study. To my

friend and sister, Courtney, thank you for your unconditional love and support.

A special word of love and gratitude to my partner, Desmond, for being my rock as I

finished my study. Dr. Camille Black, we went through this journey together and you have been

my sounding board and have become one of my best and dearest friends. To my good friend

Chris, thank you for your continuous support and for always being that shoulder when I needed

it. To my amazing friend and greatest supporter, Dee, thank you for your constant reassurance

and for making sure I had everything I needed to finish this doctoral study. To my mentor and

my biggest advocate, Tonya Lovelace. You have pushed, encouraged, motivated, and inspired

me in so many ways. You continue to show up and support me, always willing to make sure I

have what I need to be successful. You’ve taught me the importance of speaking up and what it

means to be a great leader. Words can’t fully express my gratitude, but I thank you for pouring

into me and for everything you do.

Table of Contents

List of Tables ..................................................................................................................... iv

List of Figures ......................................................................................................................v

Section 1: Background and Content ....................................................................................1

Historical Background ...................................................................................................1

Organizational Context ..................................................................................................3

Problem Statement .........................................................................................................4

Purpose Statement ..........................................................................................................5

Target Audience .............................................................................................................6

Research Question .........................................................................................................6

Data Collection and Analysis.................................................................................. 7

Significance....................................................................................................................7

Theoretical Framework ..................................................................................................9

Representative Literature Review ................................................................................11

Theoretical Framework ................................................................................................13

Herzberg’s Two Factor Theory ............................................................................. 14

Kahn’s Engagement Theory ................................................................................. 18

Alternate Theories ................................................................................................. 33

Problem ........................................................................................................................40

Employee Engagement ......................................................................................... 42

Job Satisfaction ..................................................................................................... 49

Employee Performance ......................................................................................... 61

Transition .....................................................................................................................64

Section 2: Project Design and Process ...............................................................................67

Method and Design ......................................................................................................67

Method .................................................................................................................. 68

Design ................................................................................................................... 69

Ethics ................................................................................................................... 71

Transition and Summary ..............................................................................................71

Section 3: The Deliverable .................................................................................................73

The Deliverable ............................................................................................................73

Executive Summary .....................................................................................................73

Goals and Objectives ............................................................................................ 75

Overview of Findings ........................................................................................... 75

Recommendations ................................................................................................. 77

Presentation of Quantitative Data Analysis .................................................................78

Descriptive Statistics ............................................................................................. 78

Statistical Tests of Assumptions ........................................................................... 81

Inferential Statistical Analysis .............................................................................. 88

Results and Conclusions of Data Analysis ................................................................100

Recommendations for Action ....................................................................................117

Communication Plan ..................................................................................................120

Social Change Impact ................................................................................................121

Skills and Competencies ............................................................................................124

iii

References ........................................................................................................................125

Appendix A: Secondary Dataset Sources ........................................................................156

Appendix B: Employee Engagement Index, Global Satisfaction Index, Employee

Performance .........................................................................................................157

List of Tables

Table 1. Descriptive Statistics for Study Variables .......................................................... 81

Table 2. Gender, Minority, Education, Supervisory Status, and Years in Service ........... 81

Table 3. Multiple Model Regression Summary ................................................................ 82

Table 4. Tests for Normality ............................................................................................. 87

Table 5. Multiple Regression Model Summary ................................................................ 91

Table 6. ANOVA Summary ............................................................................................. 92

Table 7. Coefficients ......................................................................................................... 92

Table 8. Correlations of Study Variables While Controlling for Employee Engagement 94

Table 9. Analysis of Response Frequencies on Employee Engagement .......................... 97

Table 10. Analysis of Response Frequencies for Job Satisfaction ................................... 99

Table 11. Analysis of Response Frequencies for Employee Performance ..................... 100

Table B1. Employee Engagement Index ........................................................................ 157

Table B2. Global Satisfaction Index ............................................................................... 157

Table B3. Employee Performance Driver ....................................................................... 158

List of Figures

Figure 1. Theoretical Framework ..................................................................................... 11

Figure 2. Power Prior Analysis ......................................................................................... 80

Figure 3. Linearity Between Study Variables ................................................................... 83

Figure 4. Linearity between Employee Performance and Job Satisfaction ...................... 84

Figure 5. Linearity Between Employee Performance and Employee Engagement .......... 85

Figure 6. Normal Q-Q Plot of Studentized Residuals....................................................... 87

Figure 7. Employee Engagement Influencers ................................................................. 103

Figure 8. Mediator Variable ............................................................................................ 106

Figure 9. Motivation and Hygiene Factors ..................................................................... 107

Figure 10. I Feel Encouraged to Come up with New Ways of Doing Things ................ 110

Figure 11. When Needed I am Willing to Put in the Extra Effort to get a Job Done ..... 111

Figure 12. I Have Trust and Confidence in My Supervisor ............................................ 112

Figure 13. Are You Considering Leaving your Organization and Why? ....................... 113

Figure 14. Normal Q-Q Plot of Studentized Residual .................................................... 115

Figure 15. Q-Q Normality Plot of Employee Engagement............................................. 115

Figure 16. Q-Q Normality Plot of Employee Satisfaction .............................................. 116

Figure 17. Q-Q Normality Plot of Employee Performance ............................................ 116

Section 1: Background and Content

Historical Background

Employee performance is critical in maximizing organizational effectiveness

(Gruman & Saks, 2011). Highly performing employees are more likely to develop

innovative ideas to help the organization operate more efficiently (Copeland, 2020). To

improve employee performance, the U.S. Office of Personnel Management (OPM)

created a human capital framework to promote performance culture and engage, develop,

and inspire a diverse, high-performing workforce by designing, implementing, and

maintaining effective performance management strategies, practices, and activities that

support mission objectives (OPM, 2016). Employee engagement and job satisfaction

influence employee performance (Osborne & Hammoud, 2017), and employee

engagement is considered essential to business success within many federal agencies

(Lavigna, 2019).

The OPM has partnered with leaders across government agencies to support data-

driven changes to improve employee engagement, leading to organizational success. The

Federal Employee Viewpoint Survey (FEVS) provides vital data regarding the employee

work experience (Shih, 2020), measuring employee engagement, and assessing

engagement drivers (OPM, 2016). Each year, OPM administers the FEVS to measure

employees’ perceptions of whether and to what extent successful organizations’

conditions and characteristics are present in their agencies. OPM conducts the FEVS to

identify areas of improvement in the federal government.

Additionally, the OPM created an Employee Engagement Index (EEI) in 2010 to

assess the factors that impact employee engagement and identify engagement potential

within organizations (OPM, 2016). Items 3, 4, 6, 11, 12, 47–49, 51–54, 56, 60, and 61

make up the FEVS EEI. From 2010 to 2019, the average score among federal employees

on the EEI increased from 66% to 68% (Hameduddin & Fernandez, 2019; OPM, 2019),

with the lowest average score of 63% occurring in 2014 (Hameduddin & Fernandez,

2019; OPM, 2019). Organizational leaders can use this information to determine whether

their engagement strategies need improvement (OPM, 2016).

In 2015, OPM introduced the Employee Engagement Initiative to address

employee engagement issues within federal agencies (OPM, 2015). The initiative

emphasizes creating organizational conditions that foster employee engagement (OPM,

2016), expecting increased engagement to improve performance. (Kamensky, 2020).

Research suggests that high levels of employee engagement augment employees’ job

performance (Christian et al., 2011; Leiter & Bakker, 2010; Partnership for Public

Service, 2019). As the factors that influence employee engagement increase, employee

and organizational performance increases resulting in a direct positive relationship

between engagement and performance (Ahmed et al., 2016; Arifin et al., 2019).

Employee engagement levels can impact the overall health and performance of an

organization (McCarthy et al., 2020). Engaged employees contributes to lower employee

turnover (Bhatt & Sharma, 2019). In contrast, lack of employee engagement (McCarthy

et al., 2020) relates to low job satisfaction (Barden, 2017; Jin et al., 2016; McCarthy et

al., 2020), and low employee engagement and low job satisfaction can negatively

influence job performance (Osborne & Hammoud, 2017).

Using the FEVS to understand how employees feel about their job can help

human resource managers identify factors that increase employee engagement and job

satisfaction and how these variables relate to employee performance. The survey is

available to be taken online for 6 weeks. FEVS representatives recommend that

individual agencies compare their agencies with the overall results to understand better

how their employees feel about their jobs (OPM, 2018b). Employers need to have a

strong understanding of how the employees feel about their job, which can help human

resource managers and leaders determine how to help their employees stay engaged

(OPM, 2018b). Federal agencies can use this information to compare their results against

the total federal government. Combining the assessment of knowledge, skills, and

aptitudes required for the task with the organizational strategy can predict job satisfaction

and job performance (Paulo da Silva & Shinyashiki, 2014). An increase in an engaged

and satisfied workforce can increase job performance, reduce turnover (Byrne et al.,

2017; Paulo da Silva & Shinyashiki, 2014), and save organizations billions of dollars

annually (Barden, 2017).

Organizational Context

Each agency within the U.S. Federal Government has its own mission and vision.

However, OPM has determined that focusing on performance is essential to improving

the organization and meeting each agency’s mission and vision. Several governmentwide

initiatives have been implemented to assist agencies in reexamining and enhancing their

performance measures. The performance initiatives require agencies to set goals and

standards to align employee performance with agency goals (OPM, n.d.).

The FEVS is an annual assessment that OPM administers to evaluate employees’

perceptions of agency conditions that support success. The FEVS was designed to

provide agencies with employee feedback on factors that critically impact organizational

performance, such as perception of leadership, effectiveness, employee engagement, and

job satisfaction (Kamensky, 2020; Lappin, 2021; OPM, 2016). Some leaders at federal

agencies would create action plans to improve low-scoring items; however, this strategy

did not prove to improve employee satisfaction or engagement (Lappin, 2021;

Metzenbaum, 2019; OPM, n.d.). Furthermore, leaders in the federal government did not

understand the relationship between employee engagement, job satisfaction, and

employee performance (Lappin, 2021; Metzenbaum, 2019). This study explored

employee engagement, job satisfaction, and employee performance. Understanding the

relationship between these variables may help leaders create more efficient strategic

plans to improve employee performance.

Problem Statement

Low-performing employees reduce the team’s motivation and performance by

approximately 40% (Lee & Rhee, 2019), contributing to approximately $483 billion to

$605 billion in lost productivity each year in the United States (State of the American

Workplace, 2020). In addition, only 21% of employees in the United States feel that their

leadership manages their performance in a way that motivates them to do outstanding

work, and only 14% of employees are inspired to improve their performance (State of the

American Workplace, 2020). Research has shown that organizations with higher

employee engagement and job satisfaction demonstrate better performance (Bhatt &

Sharma, 2019; Budirianti et al., 2020; Cankir & Arikan, 2019; Concepcion, 2020; Gupta

& Sharma, 2016; Popli & Rizvi, 2015). The general business problem is a lack of

employee engagement, and low job satisfaction can result in low employee performance

(Osborne & Hammoud, 2017). The specific business problem that this study will address

is that leaders within the federal government do not understand the relationship between

employee engagement, job satisfaction, and employee performance among employees

within the federal government. The 2019 FEVS is the dataset that was used for this study

to examine whether a relationship exists between employee engagement, job satisfaction,

and employee performance among employees within the federal government.

Purpose Statement

The purpose of this quantitative correlational ex post facto study was to examine

the relationship between employee engagement, job satisfaction, and employee

performance among employees within the federal government. I conducted secondary

data analysis using data obtained from the 2019 FEVS. The independent variables

identified in the FEVS were employee engagement, measured by the EEI in the 2019

FEVS, and job satisfaction, measured by the Global Satisfaction Index (GSI), Items 40

and 69–71. The dependent variable was employee performance, measured by the

Performance Driver in the 2019 FEVS, consisting of Items 15,16, and 19. Previous

researchers have tested and confirmed the validity of the composite variable or close

variations to measure both employee performance and organizational performance (Choi

& Rainey, 2020; Lee, 2018; Metzenbaum, 2019; Pitts, 2009; Somers, 2018). The

implications for social change include contributing to leadership practices by identifying

job satisfaction and employee engagement influencers and determining how performance

is related to those factors. This information can help leaders in the federal government

create a more productive environment for improved employee and business performance

and maximize resources (Hejjas et al., 2019), increasing employee retention and job

satisfaction (Bhatt & Sharma, 2019) in the workforce.

Target Audience

The key stakeholders in this portfolio were agencies within the federal

government, employees within the federal government, U.S. citizens, and leaders in the

federal government focusing on improving employee engagement and job satisfaction.

Determining the relationship between employee engagement, job satisfaction, and

employee performance can help leaders implement strategies to improve employee

performance. Understanding the relationship between these variables can also reduce

costs, increase retention, and enhance job satisfaction. Furthermore, government business

operations are primarily funded by taxpayer dollars, making U.S. citizens essential

stakeholders. Maximizing the use of resources can be a positive result for stakeholders as

they are ensured that their tax dollars are being utilized efficiently and responsibly.

Research Question

Does a significant relationship exist between employee engagement, job

satisfaction, and employee performance among employees within the federal

government?

: There is no statistically significant relationship between employee

engagement, job satisfaction, and employee performance among employees within the

federal government.

: There is a statistically significant relationship between employee engagement,

job satisfaction, and employee performance among employees within the federal

government.

Data Collection and Analysis

I collected data using an archival data collection technique. I extracted data from

the OPM FEVS 2019 Public Release Data File provided on the OPM government

website. I conducted a multiple regression analysis to determine a relationship between

this study’s independent and dependent variables. Multiple linear regression examines the

relationship between multiple independent variables and a dependent variable. The

degree to which the dependent variable, employee performance, is explained by the

independent variables job satisfaction and employee engagement was the focus of this

study.

Significance

The federal government is making a continuous effort to increase employee

performance (Pecino et al., 2019). The findings of this quantitative multiple regression

study can provide value to leaders in the federal government. It also provides a model for

understanding the degree to which employee engagement and job satisfaction relate to

employee performance. Employee engagement and job satisfaction are vital indicators for

predicting employee performance. Understanding this relationship may assist leaders

within the federal government indicate productivity and possibly turnover intent.

Furthermore, leaders may also determine what factors influence employee performance

and incorporate those factors to create and implement more effective practices and

strategies to maintain employee engagement to increase employee performance (OPM,

2016). By implementing successful strategies, leaders within the federal government

mitigate risks of low productivity, decreased work quality, rising costs, and increased

turnover.

The implications for positive social change include the potential to increase

employee performance and productivity (Osborne & Hammoud, 2017), maximize the use

of resources (Hejjas et al., 2019), and increase employee retention and job satisfaction

(Bhatt & Sharma, 2019), and save the organization costs (Osborne & Hammoud, 2017).

Increasing employee engagement can lead to increased job satisfaction and performance

and lower organizational turnover rates (Paulo da Silva & Shinyashiki, 2014).

Additionally, increased job satisfaction can positively influence creating more innovative

strategies to complete tasks and contribute to the organization's cost savings due to a

more efficient allocation of resources. Increased employee engagement increases job

satisfaction and job performance (Paulo da Silva & Shinyashiki, 2014) and saves

organizations billions of dollars annually (Barden, 2017). Thus, this study’s findings

could further inform the field by examining the degree to which employee engagement

and job satisfaction relate to employee performance.

Theoretical Framework

I used two theories as the framework for my study: Herzberg’s two-factor theory,

often referred to as Herzberg’s dual-factor theory (Alshmemri et al., 2017), to address the

relationship between job satisfaction and job performance, and Kahn’s employee

engagement theory to address the relationship between employee engagement and job

performance. Herzberg’s two-factor theory, also known as the motivation-hygiene theory

and Herzberg’s dual-factor theory (Herzberg, 1959), is a motivation theory influenced by

Maslow’s hierarchy of needs (Jones, 2011). Herzberg’s two-factor theory identifies two

sets of factors: hygiene and motivation factors that affect job satisfaction. Hygiene factors

include company policies, coworker relationships, salaries, and supervision (Herzberg,

1966). Herzberg’s theory proposes that motivation factors result in satisfaction, and

hygiene factors prevent dissatisfaction (Hur, 2017). Motivation factors include

recognition, achievement, advancement, the work itself, and growth (Herzberg, 1966). A

decrease in hygiene factors can cause employees to work less, whereas an increase in

motivating factors can encourage employees to work harder. The factors presented by

Herzberg influence performance by assessing motivational and hygiene factors.

The second theoretical framework I applied to this study is Kahn’s employee

engagement theory (Kahn, 1990). Kahn’s theory measures employee engagement through

employees’ level of commitment to their work roles and how organizations influence

engagement to the extent that employees engross themselves in their performance to

reach organizational objectives (Gupta & Sharma, 2016; Kahn, 1990; Vaijayanthi et al.,

2011). The starting point for Kahn’s (1990) engagement theory was the work of Goffman

(1961), which suggests that employee levels of attachment to their roles vary, and

employees can demonstrate various levels of attachment and detachment with each

moment. The theory presented by Goffman was attributed to fleeting encounters and not

a consistent organizational experience (Kahn, 1990). Kahn argued that Goffman’s work

did not fit organizational life and focused on face-to-face interactions (Gruman & Saks,

2011; Kular et al., 2008; Kahn, 1990). Kahn classifies this as self-in-role, meaning that

when employees are engaged, they keep themselves within the role they are performing

(Gruman & Saks, 2011; Kahn, 1990).

The employee engagement theory states that meaningfulness, safety, and

availability, influence employee engagement levels (Kahn, 1990). When employees are

involved and invested in their jobs, employee engagement increases. Alternatively, when

employees withdraw from their duties, engagement decreases. Employees’ perceptions of

their performance’s meaningfulness, availability of resources to successfully complete

their jobs, and perception of employee safety influence employee engagement.

The aim of this study was to examine the relationship between employee

engagement, job satisfaction, and employee performance among employees within the

federal government. As applied to this study, the Herzberg two-step theory holds that I

would expect the independent variables to influence employee performance. The FEVS

(2019) identifies hygiene and motivation factors as influencers of employee performance

and engagement. Figure 1 depicts how each independent variable relates to the dependent

variable.

Figure 1

Theoretical Framework

Herzberg’s two-factor theory explains how job satisfaction relates to and explains

employee performance. Kahn’s employee engagement theory measures how employee

engagement influences employee and organizational performance (Kahn, 1990), which I

used to examine how employee engagement relates to and explains employee

performance (Albrecht et al., 2015).

Representative Literature Review

This literature review focuses on employee engagement and job satisfaction and

the relationship each variable has on employee performance. This literature review

contains comprehensive research from multiple business functions and applications to

describe a quantitative correlational study within the federal government. This literature

review was conducted to examine the relationship between the study’s independent

variables, employee engagement and job satisfaction, and the dependent variable,

employee performance amongst employees in the federal government.

I based the literature review on Herzberg’s (1959) two-factor theory and Kahn’s

(1990) engagement theory. The componential theory of creativity and social exchange

theory is also discussed in this literature review to provide further insight on the

expounding of the theories as time progressed. Herzberg’s two-factor theory most

adequately addresses job satisfaction’s impact on employee performance, and Kahn’s

engagement theory was best suited to address the relationship between employee

engagement and performance.

The literature reviewed for this study consisted of items published since 2017

with a few exceptions from beyond that time, as was necessary for a complete theoretical

foundation. The sources included in this section provide background, relevant theories,

contextual support, supporting data, and the impact on performance, productivity, and

profitability. I used Walden University’s library databases to research the literature,

providing a great deal of information on employee engagement and job satisfaction. For

research purposes, search terms consistent with this study were used, such as employee

engagement, job satisfaction, employee performance, organizational performance,

Federal Employment Viewpoint survey, resources and satisfaction, employee recognition,

employee dissatisfaction, disengaged employees, Maslow’s hierarchal theory, job

resources demand theory, self-determination theory, employee productivity, and burnout.

The purpose of the literature review was to identify and ascertain additional

information relative to the main factors of this study. An analysis of previously written

studies that focus on employee engagement, job satisfaction, and employee performance

are included—the foundation of the theoretical framework aided in completing this

section. Walden Library’s extensive databases accumulated peer-reviewed articles and

publications, specifically ABI/Inform Complete, Business Source Complete, and

EBSCOhost. Researching using the dissertations at Walden selection, mining other

authors’ reference sections, and keyword searching helped complete this review. I

exhausted the searches by using variations of the original terms to benefit from the

different tenses of the words by gaining additional resources such as satisfied,

satisfaction, satisfy, engage, engaged, engagement, engaging, motivate, motivation,

motivator, motivated, and motivating. I also utilized Google Scholar to identify relevant

sources I accessed using my Walden Library credentials.

Nine major themes, based on Herzberg et al.’s (1959) motivation-hygiene theory,

are included in this review. The themes included (a) achievement, (b) recognition, (c)

work itself, (d) responsibility, (e) advancement, (f) working conditions, (g) company

policies, (h) relations with supervisors, subordinates, or coworkers, and (i) pay. Three

major themes based on Kahn’s (1990) engagement theory are also included in this

literature review: (a) meaningfulness, (b) safety, and (c) availability. Applying these

factors to the variables included in the study and alternate theories is also discussed in the

literature review.

Theoretical Framework

A theoretical framework helps structure and organize a study (Dziak, 2020). The

theoretical frameworks used for this study were Herzberg’s two factor theory and Kahn’s

employee and engagement theory. This section of the literature provides a critical

analysis and complete synthesis of the applicability, basis, various perspectives,

comparative research, and alternative theories of the frameworks used to structure this

study.

Herzberg’s Two Factor Theory

Herzberg conducted a study in Pittsburgh, Pennsylvania using more than 200

engineers and accountants working in approximately nine different factories to explore

the factors contributing to employee job satisfaction and motivation (Herzberg et al.,

1959). Based in this research, Herzberg concluded that the factors affecting job

satisfaction consist of two categories: motivation factors and hygiene factors. Motivation

factors, or satisfiers, are considered intrinsic factors associated with the need for growth

or self-actualization (Herzberg, 1966). The factors that make up positive attitudes for

employee engagement and job satisfaction include achievement, recognition, the work

itself, responsibility, advancement, and the possibility for growth (Herzberg, 1966).

Hygiene factors, also known as dissatisfiers, are considered extrinsic factors. The

factors that comprise the negative job attitudes attributed to disengagement and

dissatisfaction include company policies, coworker relationships, salaries, working

conditions, and supervision (Herzberg et al., 1959). Low hygiene factors in an

organization can lead to higher employee dissatisfaction, which can cause employees to

work less. Alternatively, increasing motivating factors can encourage employees to work

harder by influencing their attitudes (Herzberg, 1966). Essentially, motivation factors

work to improve job satisfaction, and hygiene factors work to reduce job dissatisfaction.

But satisfaction and dissatisfaction are not on the same continuum, as each is affected by

different factors and is independent of one another.

Although hygiene factors and motivator factors influence employee satisfaction,

they do so differently. Lack of hygiene factors leads to dissatisfaction from the job’s

extrinsic conditions, making the employee unhappy with the job conditions (Herzberg,

1968). The employee can be disgruntled with the job conditions but still enjoy the work.

However, satisfying hygiene requirements is insufficient to improve an organization’s

productivity (Herzberg, 1987). Organization leaders must maintain motivation factors to

ensure employee satisfaction. Lack of hygiene and motivator factors can increase

dissatisfaction; however, motivator factors do not increase dissatisfaction but can

increase and decrease satisfaction.

It is assumed that performance results are more likely associated with motivator

and hygiene factors to maintain performance levels. Those with higher motivator factors

and more satisfaction are more likely to overperform and go above and beyond their job

duties (Azevedo et al., 2020; Barden, 2017). On the other hand, those with higher

hygiene factors are less dissatisfied with their job and will likely perform at a basic

maintenance level. Although still satisfactory, these employees develop fewer innovative

strategies and tend to generate less output (Bevins, 2018). Furthermore, dissatisfaction

psychologically leads employees to withdraw from business operations (Herzberg, 1959).

This reasoning is why the Herzberg theory is considered a motivation theory, as Herzberg

found a statistical relationship between performance effects and satisfaction (Bevins,

2018; Herzberg et al., 1959; Herzberg et al., 1979). To motivate employees to achieve

desired outcomes, business leaders must understand what factors drive their employees

(Baumeister, 2016; Copeland, 2020; Damiji et al., 2015).

Research Relative to Herzberg’s Two-Factor Theory

Herzberg’s two-factor theory is the basis for many research studies, and many

researchers have expanded on the theory. For example, Adil and Hamid (2019) used

Herzberg’s two factor theory to determine if there is a direct relationship between leader

expectations of creativity and performance and if intrinsic motivators affect the

relationship between leader expectations of creativity and performance. The

componential theory of creativity describes three components of employee creativity:

expertise, creative thinking, and intrinsic motivation (Adil & Hamid, 2019). This

componential theory of creativity was expanded in 2016 (Amabile & Pratt, 2016) to

include boundary conditions such as work orientation, meaningful work, and effect.

These conditions affect the individual, the team, and organizational creativity and

innovation (Adil & Hamid, 2019; Amabile & Pratt, 2016).

Empirical evidence suggests that intrinsic motivation is a mediator between

different variables and creative performance (Adil & Hamid, 2019; Hannam & Narayan,

2015; Hur et al., 2016; Muñoz-Pascual, & Galende, 2017). Expectations from leadership

to perform creatively could serve as a motivator for an employee; however, if an

employee feels that they cannot perform creatively or innovatively, they are more likely

not to perform may become more dissatisfied (Adil & Hamid, 2019). If employees felt

that policy or their supervisor allowed for creativity, they would be less dissatisfied and

willing to increase their output (Adil & Hamid, 2019; PPS, 2019). Furthermore, if the

employee is motivated, they are more likely to grow, develop, and improve their

performance (Adil & Hamid, 2019; State of the American Workplace, 2020). It is

important to note that although hygiene factors and motivation factors influence job

satisfaction and dissatisfaction, the impact of each component of the factors varies

between employees (Thibodeaux et al., 2015).

Herzberg’s theory is also used to evaluate job satisfaction. Shaikh et al. (2019)

conducted a study to determine the impact of job dissatisfaction on extrinsic factors and

employee performance in the textile industry. The results showed that performance

increased when leaders focused on employees’ satisfaction and implemented relevant

hygiene factors to decrease dissatisfaction. However, though hygiene factors decrease

dissatisfaction, they have no impact on satisfaction (Shaikh et al., 2019). Regardless, to

maintain positive attitudes in the workplace, leaders should focus on improving motivator

factors such as recognition, the possibility for growth, and advancement. These factors

help improve performance and increase employee engagement and job satisfaction

(Amiri et al., 2017; Calecas, 2019; Herzberg, 1959). For example, employee feedback

can help employees to understand their roles better. Additionally, feedback can inform

employees about their performance and allows employers to recognize employees’

accomplishments (Aye, 2019; Herzberg, 1959; Rahman & Iqbal, 2013). These strategies

will help leaders increase morale, create happier and more satisfied employees, and

increase employee performance, increasing overall productivity.

Herzberg’s theory has since been expanded and still serves as the basis for many

other researchers. The theory has been applied in various industries, including human

resources, retail, and academia. The theory still receives criticism for lacking substantial

influence in explaining motivation. Other researchers have also argued that one of the

hygiene factors was misclassified and is a motivator, with only work itself having a

significant impact on job satisfaction (Onen & Maicibi, 2004; Smerek & Peterson, 2007;

Yousaf, 2020). But research has also shown that each motivator factor (e.g, relationship

with supervisors, work itself) positively correlates with job satisfaction (Yousaf, 2020).

The amount of recognition an employee gets also affects satisfaction. Employees who

receive more recognition are more satisfied and find their jobs more challenging and

rewarding than those who receive less recognition. Recognition is essential in motivating

employees, contributing to increased satisfaction and performance (Lehtinen, 2018).

Literature often discusses the performance of those being recognized but not that of those

not receiving recognition. Those who do receive recognition increased their performance

to maintain or continue to receive recognition (Yusaf, 2020). Thus, recognition increases

employee motivation and performance (Bradler et al., 2016; Gupta & Tayal, 2013;

Herzberg, 1959; Lehtinen, 2018).

Kahn’s Engagement Theory

The degree to which individuals immerse themselves in their work role relates to

their level of personal engagement or disengagement. Kahn’s engagement theory premise

is that people use varying degrees of themselves, physically, cognitively, and emotionally

in the workplace (Ali et al., 2019; Gupta & Sharma, 2016; Kahn, 1990). When Kahn

began developing this theory, existing research primarily focused on engagement driven

by job involvement, organizational commitment, and self-estrangement. Kahn (1990)

conducted a study to understand the conditions contributing to employee engagement in

the workplace. Kahn interviewed 32 employees to explore how certain job variables

affected employee engagement and analyzed the data using Grounded Theory to

articulate the complexity of influences on engagement levels in particular performance

moments (Kahn,1990). Kahn completed two qualitative studies, including counselors

from a summer camp and members of an architecture firm. The purpose of this study was

to explore conditions that cause people to engage, disengage, withdraw, or defend

themselves. Kahn described these actions as self-in-role processes. Essentially, positions

that allow individuals to exercise their preferred skills and talents and have their work be

an expression of themselves result in employees bringing their energy in all three areas of

physical, cognitive, and emotional aspects (Albrecht et al., 2015; Arleth, 2019; Kahn,

1990)

An employee can be engaged psychologically in two dimensions: emotionally and

cognitively. Those who are emotionally engaged typically have good relationships with

their supervisors and peers. Cognitively engaged employees are aware of their mission

and role in their work environment (Barden, 2017; Kahn, 1990; Rothbard, 2001). The

effort an employee is willing to exert to meet their goals is the measure of the physical

aspect of employee engagement. Employees can experience engagement in any of these

dimensions at any time. The employee engagement theory states that meaningfulness,

safety, and availability, influence employee engagement levels (Kahn, 1990).

Employees determine meaningfulness based on their experiences with work

elements that create incentives or, in some cases, disincentives. When employees

experience meaningfulness, they are more likely to feel valued and worthwhile and give

to others and the work itself. Meaningfulness is influenced by task and role

characteristics and overall work interactions (Balkrushna et al., 2018; Risley, 2020; Tong

et al., 2019; Tracey et al., 2014). The goals of these tasks and roles should be clear and

should allow for autonomy and creativity (Ma et al., 2020). Essentially, employees are

looking to have their jobs meet their needs for survival and their psychological needs.

Nikolova and Cnossen (2020) found that competence, autonomy, and relatedness explain

approximately 60% of the variation in work meaningfulness perception.

On the other hand, factors related to compensation are relatively unimportant

(Nikolova & Cnossen, 2020; Terkel, 1997). Employees that have meaning in their work

find value in more than just their paycheck. Kahn (1990) defines meaningfulness as a

return on investment, and employees are looking for more than just a paycheck.

Approximately one in two employees report that their jobs lack meaning and they feel

disconnected from their company's mission. Being detached is a sign of personal

disengagement.

Employee perspective on meaningfulness can predict absenteeism, skills training,

retirement intentions, and employee turnover (Bhatt&Sharma;2019; Byrne et al., 2017;

Nikolova & Cnossen, 2020; Paulo da Silva & Shinyashiki, 2014). A 2017 study

conducted by BetterUp, Inc. that included 2,285 United States residents revealed that

approximately nine of 10 employees would be willing to trade an average of 23% of their

lifetime earnings for greater meaning at work (Reece et al., 2018). Additionally,

employees who experience higher levels of meaningfulness at work tend to take fewer

leave days, work approximately an additional hour per week, and are 69% less likely to

leave their jobs within the next six months (Reece et al., 2018). When employees feel

they are receiving a return on investment, they are more likely to offer their resources and

perform effectively in their role. Employees with higher engagement are more likely to

provide additional time and dedication, share ideas willingly, and utilize creativity to

stimulate innovation.

For employees to experience safety in the workplace, they must have a sense of

ability to show and employ themselves without fear of negative consequences to their

self-image, status, or career. The influencers of safety are interpersonal relationships,

group, intergroup dynamics, management style and process, and organizational norms

(Kahn, 1990). A safe environment fosters support and trust and allows employees to learn

and improve their performance without fearing negative consequences. Increased levels

of trust also increase the amount of influence that leaders have. The management style in

this environment is supportive and resilient and provides clarity and consistency (Arleth,

2019; Gruman & Saks, 2010; Kahn, 1990; Lee & Huang, 2018). Leaders allow

employees to have some control over their work while providing reinforcement.

Employees' autonomy plays a significant role in fueling intrinsic motivation. A

lack of sense of safety can result from a manager not allowing an employee to have any

control over their work (Probst et al., 2020). An environment that does not promote

employee autonomy can make employees feel that their leadership does not trust them,

causing anxiety and frustration (Kahn, 1990; Kwon & Park, 2019). An employee must be

in an environment where critical thinking is openly exercised to have a sense of

psychological safety. Promoting openness in the work environment is also pivotal for

knowledge sharing, a crucial element in an organization's survival (Naujokaitien et al.,

2015).

Without the feeling of safety, employees are less likely to contribute their ideas,

beliefs, and values (Hyde, 2017; Snell et al., 2015). An environment that does not

promote a safe environment can contribute to inconsistency, unpredictability, and a

threatening environment that negatively impacts employee engagement. Researchers

argue that variables such as a leader's behavior influence motivation and can promote or

inhibit voluntary employee behavior (Parker et al., 2010; Qian et al., 2020). Employees'

willingness to improve their skills or performance can decrease for fear of negative

consequences due to a lack of perceived safety (Wang, 2021). The notion that employees

refrain from improving their skills is supported by research conducted by Qian et al.

(2020). Qian et al. found that levels of perceived safety impact the psychological

availability of employees.

Psychological availability is experienced when employees have physical,

emotional, or psychological resources to engage at a particular moment personally (Kahn,

1990) and apply to work and non-work experiences. Physical energy, emotional energy,

individual insecurity, and issues in personal life all impact psychological availability.

Insecurity impacts an employee's willingness to fully harness themselves in their role and

can create anxiety and diminish confidence. When employees are physically and

emotionally drained, they are likely to become disengaged, even if only for a moment,

decreasing their psychological availability (Ali et al., 2019; Bergdahl; 2020; Cao & Chen,

2019; Kahn, 1990; Kwan & Park, 2019).

Availability is driven by an employee's degree of confidence in their roles.

Organizational awareness of employee morale and training and development can be

supported by organizational awareness and the ability to create a work environment that

promotes positive social interaction (Bergdahl, 2020; Lee & Huang, 2018). Creating an

open environment can help alleviate the negative influencers and positively affect

employees' psychological states (Qin, 2020). Organizations have implemented dedicated

quiet rooms, Employee Assistance Program (EAP) access, stress retreats, resilience

training, and other resources to help employees alleviate tensions and help improve

employee mental health. The abovementioned strategies help employees accumulate,

manage, and reinforce positive beliefs about their physical, emotional, and cognitive

resources and enhance their psychological availability. Having availability can help

employees to accomplish extra tasks and requirements. Employees with psychological

availability have the physical energy and resources to help others in the organization and

cognitive resources to help generate new ideas (Fletcher, 2019; Kahn, 1990; Kultalahti &

Viitala, 2014; Nikolova et al., 2020; Smit et al., 2016; Upadyaya & Salmela-Aro, 2020),

creating a more efficient work environment (Naujokaitien et al., 2015). A more efficient

environment conducive to psychological meaningfulness, availability, and safety may

positively influence an employee's workplace engagement level.

When employees are engaged, they are more involved and invested in their jobs

and more expressive in the workplace. Alternatively, when employees withdraw from

their duties and disconnect and insulate themselves cognitively, physically, and

emotionally from their work roles, they become more disengaged (Hyde, 2017; Kahn,

1990). Engagement levels are a critical factor in employees' investment in their work

roles. Employees' energy contributes to engagement, and when engagement is present,

employees tie themselves to their roles freely without giving up their beliefs and values.

However, when employees are disengaged, they create barriers to their self-preservation.

It is important to note that Kahn (1990) suggests that people can move anywhere along

the spectrum of engagement and disengagement daily. Furthermore, where people fall on

the spectrum can also be influenced by work tasks, not just the job environment, as

previous research indicates (Kahn, 1990).

Some employees may ultimately enjoy their work environment and are engaged

when completing their day-to-day tasks; however, there may be an instance where an

employee has to complete an outside task. Being assigned that external task can influence

an employee's level of engagement, either positively or negatively (Kahn, 1990). For

example, if the employee is instructed to complete a task or role that makes them feel

important, they may become more engaged (Balkrushna et al., 2018; Tong et al., 2019).

Alternatively, if the role or task is perceived as unimportant and the employee sees no

value, the employee may disengage (Balkrushna et al., 2018). Employees are personally

engaged when they have the opportunity to express their best self within their role in an

optimal work environment without any emotional, cognitive, or physical sacrifice (Kahn,

1990; Balkrushna et al., 2018; Tong et al., 2019).

Kahn (1990) emphasized the different impact variables can have on people's

placement on the spectrum and went as far as to describe each moment as a contract

between person and role (Arleth, 2019; Handayani et al., 2017; Kahn, 1990). Employee

engagement is often viewed in its totality; however, Kahn's theory suggests that

engagement can be a summation of individual events. Having the understanding that the

events can be isolated allowed Kahn to analyze separate events in his study to determine

which variables impacted employee engagement.

Research Relative to Kahn’s Engagement Theory

Each year the federal government administers the FEVS, which measures

conditions conducive to engagement using the EEI as a metric. This metric includes 15

questions focusing on leaders leading, supervisor relationships, and intrinsic work

experiences for employees (OPM, 2019). The National Aeronautics and Space

Administration (NASA) was ranked number one as the best place to work in the federal

government by the Partnership for Public Service (PPS). NASA had the highest

employee engagement score of 81.5% (OPM, 2019; Partnership for Public Service [PPS],

2019). A study conducted by PPS (2019) found that employees at agencies with increased

engagement agree that they are allowed to improve their skills, encouraged to come up

with new ways to complete tasks, and feel their work is essential (Partnership for Public

Service [PPS], 2019). In addition, NASA employees rated the questions included in the

FEVS that relate to trust, improving skills, recognition, and innovation much higher than

other agencies, especially those with lower EEI scores (OPM, 2019), which further

supports Kahn's (1990) influencers of engagement. Another study by the PPS compared

employee engagement rates in the private sector against those in the public sector.

Understanding how the public sector compares to the private sector in employee

engagement is essential. The public sector must compete with the private sector to recruit

and retain high-performing employees. The PPS administered a 29-question survey

comprised of questions included in the FEVS issued to private-sector employees. This

study showed that the federal government fell behind the private sector in nearly every

question (PPS, 2019). The most significant gap was a 30-point gap on the issue of

employee voice. Eighty-two percent of private-sector employees reported trust in their

leadership instead of only 71% of federal employees (PPS, 2019). Another area in that

federal employees are rated lower than private-sector employees is awards and

recognition. Approximately 51% of federal employees feel they receive recognition for

their high-quality work, and only 45% believe that awards are given based on how well

they perform their jobs (OPM, 2019; PPS, 2019). The ratings for these items in the

private sector were 51% and 67%, respectively. Other lower-ranking areas for federal

employees are related training, supervisor support for development, and the ability to

develop innovative ideas. These issues resulted in a gap between seven and 17 points

(PPS, 2019). The overall engagement score for the Federal Government in 2019 is 61.7,

whereas the score for the private sector is 77 (PPS, 2019).

The PPS (2019) study findings suggest that trust within the organization, having

the opportunity to improve skills, receiving recognition, and having a safe environment to

foster innovation relate to increased engagement. These concepts support Kahn’s

engagement theory as it supports the notion that meaningfulness, safety, and availability

impact levels of employee engagement (Arleth, 2019; Gruman & Saks, 2011; Kahn,

1990; Osborne & Hammoud, 2017). Kahn (1990) defines meaningfulness as a sense of

return on investment on self-in-role performance. Tasks, roles, and work interactions are

all influencers of meaningfulness (Gruman & Saks, 2011; Kahn, 1990). Tasks should

have some level of challenge and allow for autonomy and creativity. Employees also

experience meaningfulness when they feel worthwhile and valued (Kahn, 1990; Osborne

& Hammoud, 2017; Upadyaya & Salmela-Aro, 2020). Federal employees had lower

ranking scores than the public sector regarding questions concerning innovation and

employee voice. Federal employees also felt undervalued, as 49% of the federal

employees who participated in the FEVS (2019) did not feel recognized for their quality

work. The results show a negative impact on meaningfulness felt by the federal

employees, which could contribute to the lower engagement rating. The scores were

higher in the private sector, ultimately contributing to the higher engagement rating (PPS,

2019).

The findings of PPS (2019) suggest a lack of safety in the federal employee work

environment. Safety relates to trust, openness, flexibility, and lack of threat in the

workplace (Kahn, 1990). Employees feel safe when leaders are supportive, consistent,

and trustworthy (Feuerahn, 2019; Funez et al., 2021; Morton et al., 2019). Fewer federal

employees expressed trust in their leadership than in the private sector (PPS, 2019). The

private sector employees rated this area 11 percentage points higher than the federal

employees (PPS, 2019). The third factor is availability, which relates to emotional,

physical, and psychological resources (Kahn, 1990). Training was rated lower and

received less support by leadership in the federal workplace (PPS, 2019), an example of a

lack of physical resources. Finally, insecurity is also an influencer of the availability

factor. Lack of training or support for professional development can contribute to

employees being insecure in their skills and capabilities (Funez et al., 2021; Lee &

Huang, 2018; Upadyaya & Salmela-Aro, 2020). Suppose the employees feel they are not

provided enough resources to do their job adequately or that their leadership did not

support their development. In that case, they are likely to refrain from sharing innovative

ideas, hiding how they feel, and becoming less secure in their overall performance.

Ultimately, the three areas that impact engagement were rated lower by the federal

employees, potentially contributing to the overall lower engagement score.

Researchers have continued to use and expand upon Kahn's (1990) engagement

theory. For example, Nguyen et al. (2018) conducted a study to examine the relationships

between job engagement, transformational leadership, high-performance human resource

practices (HPHRP), climate for innovation, and contextual performance. The researchers

were looking to investigate what variables generate engagement and how the levels of

engagement improve contextual performance in higher education. Engagement, in this

study, is described as an enduring state of mind that refers to an employee's investment of

physical, cognitive, and emotional energies. Thus, the definition of engagement in this

study aligns with Kahn's definition of engagement.

Understanding how engagement influences organizational and employee

performance and knowing what variables influence engagement can help organizations

create more conducive environments to meet the needs of their employees and the

organization. Nguyen et al. (2018) gathered the data for their study by sending an online

and paper-based questionnaire to 14 public and private universities in Ho Chi Minh City,

Vietnam, in 2016 (Nguyen et al., 2018). The data for both the dependent and independent

variables were collected from two sources, university academics, and their leaders, in two

different phases. During the first phase, the academic staff completed a questionnaire

regarding the transformational leadership styles of their leaders, job engagement, and

HPHRP. During the second phase, the same team completed another questionnaire

relating to their school's climate for innovation. The staff leaders were also surveyed in

this phase, and their questionnaire addressed the organizational citizenship behavior

(OCB) and the innovative work behavior of their staff. The researchers created a data file

by matching the responses of demographics, transformational leadership, HPHRP,

climate for innovation, and job engagement ratings by the staff during phase one and

phase two, and the responses by leadership on OCB and innovative work behavior using

assigned codes.

The framework for Nguyen et al.'s (2018) study is based on Kahn's (1990)

engagement theory and social exchange theory to create a conceptual model that

demonstrated a relationship between job engagement and transformational leadership,

HPHRP, climate for innovation, OCB, and innovative work behavior. The findings

suggest that transformational leadership and HPHRP are critical drivers of employee

engagement levels, HPHRP having more influence than transformational leadership.

HPHRP consists of selection, training and development, job security, promotion,

performance-related pay, autonomy, and communication. Transformational leadership

includes idealized influence, inspirational motivation, individualized consideration, and

intellectual stimulation (Nguyen et al., 2018). The significant and positive relationship

between these variables and employee engagement supports Kahn's engagement theory.

HPHRP encompasses concepts influencing psychological meaningfulness, such as skill

development, performance recognition, and autonomy. When employees experience

meaningfulness, in this case through HPHRP, they feel useful and valuable.

Transformational leadership relates to safety concepts (Lee & Huang, 2018). Safety

provides an environment where employees can try and fail without fear of consequence,

have supportive and trusting leadership with significant influence, and create and test

new ideas and concepts (Kahn, 1990; Lee & Huang, 2018).

Creating an innovative climate can influence engagement (Funez et al., 2021;

Kahn, 1990). Leaders who want success within their organizations must develop

strategies to attain engaged employees (George & Joseph, 2014; Ghlichlee & Bayat,

2020; Kwon & Park, 2019). Employee engagement is fostered by a fulfilling experience

that accounts for vigor, dedication, and absorption (Kim et al., 2016; Schaufeli et al.,

2002). Ultimately, the study's findings by Nguyen et al. (2018) supported Kahn's (1990)

engagement theory by identifying a positive relationship between the influencers,

variables, and engagement. Furthermore, Nguyen et al. (2018) found that when

engagement was present, employees were more willing to be involved in additional tasks

outside their work tasks, complete tasks more effectively, and try more innovative

approaches, contributing to increased OCB (Morton et al.,2019).

Implications of Kahn’s Engagement Theory

Employees need to be able to express themselves and have a sense of autonomy in

their work lives (Lee & Huang, 2018). Employees' psychological experience in the

workplace drives their attitudes and behavior, ultimately impacting their involvement in

their roles. The lack of meaningfulness, safety, and availability can lead to personal

disengagement, causing employee burnout and robotic performance (Kahn, 1990;

Upadyaya & Aro, 2019). Employees become unexpressive and refrain from sharing

thoughts and creativity instead of being innovative when experiencing burnout (Kahn,

1990; Kwon & Park, 2019; Upadyaya & Aro, 2019).

Organization leaders should be more cognizant of the effects of burnout on

employees and their performance. Upadyaya and Aro (2019) conducted a study to

determine what types of groups of employees can be identified according to the level of

burnout, which consists of changes in their exhaustion, cynicism, feelings of inadequacy,

and levels of engagement, consisting of energy, dedication, and absorption. The

researchers also explored how work-related demands and resources and personal-related

demands and resources predict employees belonging to the burnout or engagement

profiles. Seven hundred sixty-six employees participated in this study, filling out a

questionnaire concerning their burnout symptoms, work engagement, perceived demands

and resources, and occupational health. The participants were surveyed twice. The results

were analyzed in multiple phases. First, the results were assessed and grouped based on

similar indicator means, burnout and engagement. Subsequent different work-related

demands and personal demands and work-related resources and personal resources were

added as covariates. The first group, 84% of the participants, were characterized by an

average level of burnout and high engagement, which slightly increased over time. The

second group represented 16% of the participants and was characterized by high levels of

burnout that grew over time and an average level of engagement that decreased over

time. Employees who experienced high work-related and personal resources, such as

servant leadership, resilience, and self-efficacy, were likelier to belong to the high

engagement group. Employees who experienced high work-related and personal

demands, such as project and relationship demands, were more likely to belong to the

increasing burnout group.

Organizational leaders need to understand the impact of burnout and the

importance of a workplace conducive to decreasing burnout. The results of Upadyaya and

Aro's (2019) study suggest that employees were experiencing increasing levels of

exhaustion, cynicism, and feelings of inadequacy and experiencing decreasing levels of

energy, dedication, and absorption. Creating a work environment where employees have

adequate resources and support to meet work demands can positively impact employee

engagement and the effort they put into their work (Ghlichlee & Bayat, 2020; Seriki et

al., 2020; Upadyaya & Aro, 2019).

Suppose employees believe their organization invests in them and provides the

necessary resources to create an optimal workspace. In that case, employees are more

likely to offer their resources and exhibit more effort, becoming more cognitively alert,

emotionally attached, and physically involved (Concepcion, 2020; Lee & Huang, 2018;

Kahn, 1990; Upadyaya & Aro, 2019). These three attributes represent a fully harnessed

employee, and when all are applied, employees tend to be more productive and efficient

(Kahn, 1990). Therefore, if leaders focused on creating a work environment that

minimizes the negative impact on the cognitive, physical, and emotional engagement

attributes, they could foster employee engagement and inspire more positive productivity

(Anithat, 2014; Kahn, 1990; Lin & Hsiao, 2014; Rana et a., 2014).

Alternate Theories

Although Herzberg's theory and Kahn’s engagement theory are used in the

theoretical framework for this study, it is essential to note that similar theories explore

job satisfaction and employee engagement. Maslow’s hierarchy of needs theory and SDT

are two popular theories of motivation. Both of these theories are alternate theories to

Herzberg’s two-factor theory. In this section, I will present these theories and provide an

analysis of each. Additionally, I analyze Job Demands-Resources Theory in this section

as this is an alternate theory to Kahn’s engagement theory.

Maslow’s Hierarchal Theory

Maslow (1943) introduced a motivation theory known as the Hierarchy of needs

theory. In his theory, Maslow suggests five basic needs: physiological needs, safety,

social, self-esteem, and growth needs, also known as self-actualization. The hierarchy of

these goals is in a pyramid shape, with physiological needs at the base as the basic needs.

The pyramid also depicts the importance of some needs over others, showing how the

order of satisfaction influences motivation. Physiological needs refer to one's most basic

needs, such as thirst, air, and food (Gawel, 1996; Maslow, 1943). Staying safe from

physical and psychological harm, security, stability, and protection are related to safety

needs. The social need implies the need to feel a sense of belonging, esteem focuses on

respecting self and others, and self-actualization is the need to reach one's maximum

potential. Maslow's theory suggests that the goals are all related and range in a hierarchy

of prepotency, meaning before the higher-level needs can be met, the lower-level needs

must first be met. When a lower-level need is met, motivation for satisfying that need

decreases, and people will try to meet the needs of the next level (Gawel, 1996; Maslow,

1943; Stefan et al., 2020; Suyono & Mudjanarko, 2017).

Maslow's (1943) theory offers a practical theory of management for organizations

and a psychological and social theory that explains changing social values and needs. In

response to this, organizations that utilized Maslow's theory made efforts to make work

more meaningful and fulfilling (Lusier, 2019). However, Maslow's theory has faced

criticisms for not being supported by empirical data, assuming that employees are

comparable, prioritizing the needs of the worker, and discounting employees' ability to

achieve higher-order needs before lower-order needs (Graham & Messner, 1998; Kaur,

2013; Lusier, 2019; Stefan et al., 2020).

It is challenging to standardize organizational hierarchy goals as the needs differ

from person to person based on multiple factors. A study by Lussier (2019) found that the

assumption that employees are comparable proved to be a detriment of Maslow's theory

as it neglected inequalities and poverty in the minds of organizations. Additionally,

research has shown that motivation levels are higher when the higher-level needs are met

(Deci & Ryan, 2014; Stefan et al., 2020). If leaders want to increase motivation in their

organizations, they should focus on improving the higher-level needs.

Herzberg's Two-factor theory and Maslow's Hierarchy of needs theory are similar

in that both theories agree that a specific set of needs must be fulfilled to achieve

satisfaction. Additionally, each theory recognizes intrinsic and extrinsic motivators as

factors that influence job satisfaction. However, Herzberg's theory provides more insight

regarding the factors to measure motivation and job satisfaction in the workplace, making

it more applicable to this study.

Self-Determination Theory

Self-determination theory (SDT) is a motivation theory that suggests that people

continually seek challenges and new experiences to master (Deci & Ryan, 2012; Legault,

2017; Link, 2021). Deci and Ryan (2012) examined the effects of extrinsic rewards on

intrinsic motivation. The focus of SDT is on the influences of social environments on

attitudes, values, motivations, and behaviors both developmentally and in current

situations. Essentially, SDT suggests that humans naturally seek upward growth and

strive to expand through new experiences, fulfilling their desires, and connecting with the

outside world (Legault, 2017). However, that is not to say that humans cannot be

controlled, fragmented, or alienated if their psychological needs for autonomy,

competence, and relatedness are not met in a social environment.

According to SDT, people have an innate desire to perform and grow, and

supporting action may need external motivators to enhance internal needs (Deci et al.,

2017; Deci & Ryan, 2012). External motivators can contribute to a person reevaluating

the importance of a task. An example would be an employee being offered a monetary

award for completing a task within a specific timeframe. Employees may place more

importance on completing tasks because they now have an extrinsic motivator. External

motivators can also contribute to increased intrinsic motivation. If the extrinsic motivator

is positive reinforcement, such as verbal praise, intrinsic motivation will increase as the

employee feels appreciated and valued.

The SDT is similar to Herzberg's Two-factor theory, as both theories focus on

how internal and external factors motivate employees. However, SDT introduces

motivation as a spectrum and is either autonomous or controlled (Deci & Ryan, 2012;

Deci & Ryan, 2017; Legault, 2017; Link, 2021; Story et al., 2009). Autonomous

motivation is intrinsic, meaning the employee completes the task because it is inherently

satisfying. Controlled motivation is extrinsic. People are extrinsically motivated when

performing duties because of the positive or negative consequences of the task.

The SDT places the external motivators on a spectrum ranging from non-self

determined to most self-determined. The four types of extrinsic motivation include

External Regulation, Introjected Regulation, Identified Regulation, Integrated Regulation.

External Regulation is an entirely external driver; without the stimulus of the possible

consequence, a person has no motivation to complete the task. This type of motivator

does not stimulate innovation. Ultimately, employees motivated by external regulation

have no other goals than receiving the reward or avoiding potential negative

consequences. (Deci et al., 1991; Link, 2019; Service Innovation, 2019). Introjected

regulation relates to people seeking approval from others or avoiding feelings of guilt or

shame. Employees motivated by these factors often do not complete tasks out of

satisfaction but merely because they do not want to feel guilty and pressured into doing

something even though they may not want to. This factor can also contribute to

employees' feelings of safety in the workplace, as described in Kahn's Theory (1990),

Herzberg's two-factor theory (1959), and Maslow's theory (1943).

Identified regulation includes internal characteristics; however, it requires

external reinforcements. Employees internalize the tasks they have to complete and

identify the value. Although employees may not want to complete the task, they

understand that it is for a greater purpose. An example would be employees who love

their jobs; however, they must complete mandatory training to remain certified.

Employees may not want to do the training, but they understand the value and recognize

that continuing to do the work they enjoy is necessary.

The last type of extrinsic motivation is integrated regulation. This regulation type

is the closest on the spectrum to intrinsic motivation. These employees may not enjoy the

tasks they have to do, but they perform well because the outcome aligns with their

personal goals and values (Deci & Ryan, 2012). Like Herzberg's two-factor theory, SDT

identifies the importance of autonomy, and integrated regulation is the most autonomous

form of extrinsic motivation.

Although this theory shares similarities with Herzberg's two-factor theory, the

foci for these theories are different. The SDT focuses on the impact of the social

environment on motivation. Furthermore, the SDT does not explore the differences

between motivation and satisfaction or how the external factors contribute to satisfaction.

Because of this, Herzberg's two-factor theory proved to be more suitable for this study.

Job Demands-Resources Theory

The Job Demands-Resources Model (JDRM) has grown more popular throughout

the early 2000s (Bakker & Demerouti,2014). The JDRM is used to predict job burnout,

organizational commitment, and work enjoyment, connectedness, and work engagement.

The JDRM is also used to indicate the consequences such as performance and

absenteeism (Bakker & Demerouti, 2014; Bakker & Demerouti, 2018; Bakker & de

Vries, 2021). Since the use of the JDRM has grown, the model has since developed into

the Job Demands-Resources theory (JDRT), which can be used to understand and predict

employee well-being and job performance (Bakker & Demerouti, 2014).

JDRT is similar to other engagement and job satisfaction theories, as it supports

the notion that internal and external variables influence job satisfaction and employee

engagement. According to JDRT, all working environments can be modeled using job

demands and resources (Bakker & Demerouti, 2014). Job demands refer to the physical,

psychological, social, or organizational requirements needed to complete work duties

(Bakker & Demerouti, 2014; Schaufeli, 2017). In short, job demands would be anything

that drains employee energy. An example would be employees being overworked, which

is when burnout is often referenced. Job resources are the physical, psychological, social,

or organizational aspects that reduce job demands and the associated physiological and

psychological costs, help achieve work goals, and stimulate personal growth, learning,

and development.

Organizational leaders should understand the influencers of engagement and

burnout and the resources needed to help their employees maintain positive well-being.

Different levels of various demands and resources can be unique to specific jobs.

Researchers continue to use JDRT because it allows the flexibility to tailor to particular

occupations (Bakker & Demerouti, 2014; Kular, 2008; Schaufeli, 2017). JDRT posits

similar concepts as Kahn’s engagement theory as Kahn's theory developed to fit

organizational life (Kahn, 1990; Kular, 2008). However, JDRT is an alternative model to

engagement as the primary focus is on burnout, which erodes engagement (Schaufeli,

2017).

Two psychological processes are integrated into JDRT (Bakker & Demerouti,

2014). The first is a stress process (Bakker & Demerouti, 2014). This process evaluates

the relationship between burnout and adverse outcomes. Essentially, having excessive job

demands without sufficient resources can lead to employees having increased

absenteeism, low performance, lack of energy, and, ultimately, mental exhaustion

(Bakker & Demerouti, 2017; Bakker & de Vries, 2021; Schaufeli, 2017). The second

process is the motivation process (Bakker & Demerouti, 2014). This process integrates

engagement as a mediator, suggesting that an abundance of job resources may result in

positive outcomes such as increased performance, extra-role behavior, and retention. It is

important to note that JDRT suggests that burnout can result from high job demands and

insufficient job resources. Alternatively, only abundant job resources contribute to work

engagement. Ultimately, if resources are increased, engagement can increase, and

burnout can decrease. However, if demand decreases, only burnout decreases; there is no

impact on engagement. This is not to say that job resources and demand do not interact.

Researchers have found that resources and demand may impact performance and help

predict occupational well-being (Bakker & Demerouti, 2017). Job resources can assist

employees in managing job demands and mitigate the risk of employee burnout.

A notable extension of the JDRT was the addition of personal resources. These

resources are considered motivators and are deemed to have an impact on both

engagement and burnout. Personal resources include aspects such as autonomy,

resilience, and positive self-evaluation. Essentially, positive personal resources can lead

to intrinsic motivation, resulting in improved performance and overall employee well-

being (Bakker & Demerouti, 2017; Bakker & Demerouti, 2018; Bakker & de Vries,

2021; Radic et al., 2020; Schaufeli, 2017).

Job demands and resources are essential in assessing employee well-being,

burnout, motivation, and engagement. Like Kahn’s engagement theory (1959), the JDRT

explores the influencers of engagement; however, these theories differ in many ways.

Kahn’s engagement theory explores the factors contributing to employee engagement and

disengagement within their work roles. Kahn's theory also suggests that engagement and

disengagement are not on the same spectrum. Alternatively, the JDRT assesses employee

engagement as a mediator via job resources. The spectrum for the JDRT ranges between

engaged and employee burnout with the aim of preventing burnout. Because of the

different focal points of the JDRT, Kahn’s engagement theory was the best-suited

framework for this study.

Problem

Low employee performance directly impacts organizational performance. To

maintain satisfactory performance, organizational leaders should improve the factors that

influence employee performance. Job satisfaction and employee engagement have a

positive relationship with employee performance. The United States Federal Government

implemented an initiative in which the objective is to improve the performance of

mission-related objectives and support (Metzenbaum, 2019). Leaders at federal agencies

primarily focus on improving metrics such as budget and percentage of targets met for

compliance. Government agencies were making progress in tracking performance and

setting outcome-focused goals. However, agency leaders did not use the goals to motivate

their employees or identify problematic practices that needed improvement.

The government began to assess agency performance to motivate mission-focused

improvement. Unfortunately, these assessments did not include a mechanism that

motivated high-scoring programs to continue to improve (Metzenbaum, 2019).

Furthermore, low-rated programs resulted in agencies developing long-range planning

efforts to address the issue rather than taking immediate action based on experience.

Leaders focused more on improving their assessment scores than on the factors that led to

the decreased scores. Federal agencies began to experience increased targets met;

however, overall performance decreased (Lee, 2018; Metzenbaum, 2019). A decrease in

employee performance can result in more employees being transferred, reprimanded,

quitting, or fired (Lee, 2018). The federal government's organizational performance

began to suffer as employee morale and productivity decreased. Additionally, with

turnover increasing, agencies were experiencing a lack of adequate resources.

To remain competitive, organizations must focus on improving job satisfaction

and employee engagement instead of meeting target metrics (PPS, 2019). Although

reaching targets reflects well on organizational performance, this performance is not

sustainable, and overall performance decreases. Corporate leaders should understand the

relationship between employee engagement, job satisfaction, and employee performance

to sustain competitive advantage. The literature presented in this section aims to discuss

the influencers of employee engagement and job satisfaction and how each factor relates

to performance.

Employee Engagement

Research relating to employee engagement has focused on identifying the

definitions and corresponding measurements of employee engagement and investigating

the antecedents, outcomes, and boundary conditions of employee engagement.

Defining Employee Engagement

A prominent issue regarding engagement is the lack of a consistent definition

which causes fundamental discrepancies. Researchers have expanded upon the

engagement definition provided by Kahn (1990); however, the definitions are not

synonymous. The lack of a clear definition can cause difficulty in understanding how

organizational leaders can leverage, foster, and measure engagement (Barden, 2017;

Byrne, 2015; Dewing & McCormack, 2015; Gruman & Saks, 2011; Kular et al., 2008; St.

Aimee, 2020). Kahn defined employee engagement as the degree to which individuals

immerse themselves in their work role, suggesting that people use varying degrees of

themselves, physically, cognitively, and emotionally in the workplace (Dahl., 2019;

Gupta & Sharma, 2016; Kahn, 1990).

Many researchers supported Kahn's view of employee engagement. Schaufeli and

Bakker (2002) defined employee engagement as the positive, fulfilling, work-related state

of mind characterized by dedication, vigor, and absorption. Vigor is defined as high

levels of energy and mental resilience while working (Gera et al., 2019; Schaufeli et al.,

2016). Dedication is defined as a sense of significance, enthusiasm, pride, and challenge,

and absorption is characterized as being fully concentrated and deeply engrossed in their

work, demonstrating difficulty detaching from their work (Arleth, 2019; Gera et al.,

2019; Schaufeli & Bekker, 2002). Truss et al. (2006) defined employee engagement as an

employee's passion for their work. Zacher et al. (2016) supported Truss's view. Further,

Zacher et al. expanded their definition of engagement to the involvement, commitment,

passion, and empowered outlook demonstrated by employees' work behavior (Zacher et

al., 2016). Although there are varying definitions of employee engagement, researchers

have found a familiar premise of employee engagement being determined by

psychological factors and an employee’s commitment to an organization, and the amount

of effort they put into their work (Gruman & Saks, 2011; Joplin et al., 2021; Kular et al.,

2008; Osborne & Hammoud, 2017; Pham-Thai et al., 2018; White, 2017).

Even with the familiarity in defining the construct of employee engagement

between various researchers, it is essential to note that there are differences in

understanding what constitutes a lack of engagement. Kahn (1990) defined

disengagement as an employee withdrawing and decoupling themselves from their role.

Disengaged employees display incomplete role performances and show decreased effort

in completing tasks, often performing on autopilot. Alternatively, some researchers have

found that engagement is the positive antithesis of burnout (Bakker & Demerouti, 2014;

Kular et al., 2008; Upadyaya & Aro, 2019). The different definitions make examining

employee engagement difficult as various studies use different protocols. OPM defines

engagement as an employee's sense of purpose that is evident in their display of

dedication, persistence, effort in their work, and attachment to their organization and its

mission (OPM, 2020). For this study, OPM's definition will be utilized to support Kahn's

(1990) definition and measurement approach. OPM’s definition is similar to Kahn’s as

both suggest that employees’ level of engagement is depicted through their involvement

in their roles. OPM’s definition further expands on Kahn’s definition by incorporating an

employee’s sense of purpose related to meaningfulness, an engagement influencer.

Influencers of Employee Engagement

Organizational leaders continue to take an interest in how to engage their

employees adequately. Employee engagement is recognized as a driving factor for talent

development, employee well-being, and employee performance and as means for

organizations to gain a competitive advantage (Ali et al., 2019; Chin et al., 2019; Dewing

& McCormack, 2015; Kwon & Park, 2019). Leaders must create and implement

engagement strategies to influence their employees to increase their performance and

productivity, leading to increased overall organizational performance (Albrecht et al.,

2015; Bakker & Albrecht, 2018; Kahn, 1990). Leaders must first understand what

influences employee engagement to create effective engagement strategies successfully.

Organizations are investing in designing, implementing, and evaluating

interventions to improve employee engagement (Kwon & Park, 2019). To drive

engagement, employers need to foster an environment that creates conditions to improve

productivity and profitability while contributing to the well-being of their employees

(Byrne et al., 2017). Ultimately, leadership style and leadership's ability to understand

what motivates their employees is critical in determining ways to engage employees.

Although motivation and engagement are two different concepts, they are still related;

employees' motivation levels can influence how easily they can be engaged (Adil &

Hamid, 2019; Azevedo et al., 2020; Byrne et al., 2017; Gera et al., 2019). For example,

intrinsically motivated employees connect with their position and desire to grow and

develop. The intrinsic connection leads to increased employee engagement as they want

to become more active in their role (Adil & Hamid, 2019; Amabile & Pratt, 2016).

Understanding the difference between motivation and engagement and the relationship

between motivation and engagement can help organizations determine strategies to

sustain engagement levels.

Employees are critical assets and determinants of an organization's ability to gain

and maintain a competitive advantage; therefore, leaders must be aware of essential

factors of success or influencers of employee engagement. Job resources, management

support, efficient technology and equipment, and professional development opportunities

are all factors that influence engagement levels (Ghlichlee & Bayat, 2020; Sadatsafavi et

al., 2016; Seriki et al., 2020; Srivalli & Mani-Kanta, 2016; Upadyaya & Aro, 2019).

Leaders should assess the needs of their employees to determine which influencers of

engagement are lacking. Understanding where employees feel their organization lacks

can significantly benefit an organization by creating awareness and positioning leaders

with the ability to improve and monitor engagement levels, ultimately providing the

opportunity to develop a solution to improve and sustain positive engagement levels

(Kwon & Park, 2019; Narseen et al., 2019). By gaining buy-in from the employees,

leaders also create an open environment, making employees feel valued, and fostering

levels of trust between management and leadership. Having a connection with leadership

can contribute to improved employee performance.

Employee Engagement and Performance

Leaders can determine an employee's level of engagement through their physical

connection to their team and organization and their actions towards achieving their

organizational goals. From an organizational performance stance, disengaged employees

cost U.S. businesses approximately $550 billion annually in lost productivity (Aslam et

al., 2018; Kang & Busser, 2018). Furthermore, disengaged employees can lead to higher

turnover rates; decreased quality of customer service, less efficient practices, increased

stress levels, and an increased chance of accidents (Bhatt & Sharma, 2019; Gupta &

Sharma, 2016; Jugdev et al., 2018; Risley, 2020; Seriki et al., 2020). Research has shown

that leaders who emphasize improving engagement result in employees demonstrating

creativity, staying with the organization, promoting work achievement, and increasing

overall employee performance (Concepcion, 2020; Gupta & Sharma, 2016; Popli &

Rizvi, 2015). Risley (2020) explored evidence-based strategies to motivate employees at

a public library to do their best work and eliminate any processes that demotivated and

discouraged employees. Personnel accounted for approximately 80% of the yearly

budget, and therefore, the objective was to determine a method to engage employees

leading to better performance. One area of consideration was the effectiveness of annual

performance reviews.

Annual performance reviews were expensive and representative of flawed and

unreliable data that demotivates and holds back employees (Risley, 2020). Annual

reviews were perceived as an unhelpful focus on the past but provided no guidance to

employees on doing the best work in the immediate future (Risley, 2020). Risley

implemented an approach of managers and supervisors meeting with their employees

weekly. Employees were required to complete a weekly single-question pulse survey.

The results showed that employees felt less anxiety about talking to their supervisors

through weekly meetings and felt more familiar and comfortable with their bosses due to

the consistent face time. The manager's role naturally shifted to that of a coach due to this

change. It was discovered that agencies often provide coaching training but do not

provide real-time opportunities to allow the managers to coach.

The coaching approach resulted in employees developing more efficiently as they

were not as afraid to make mistakes or ask for help, assisting in developing a growth

mindset approach. It is essential to encourage a growth mindset in an organization and be

cautious about promoting a fixed mindset approach. Fixed mindsets can create inaccurate

perceptions of employees and an inability to see growth potential in valued employees

and improvements in less valued employees (Risley, 2020). Coaching employees and

promoting growth is an approach that leaders can implement to improve engagement and

improve productivity. Positive results were found in Risley's (2020) study. The amount of

manager-employee coaching increased; between 80% and 90% of employees participated

in the pulse check, confirming an accurate representation of employee perspective, 91%

of staff reported improved communication, and the overall employee engagement level

increased as employee performance and satisfaction. Furthermore, Risley credited these

changes as a contributing factor to maintained performance during the COVID pandemic.

Confidence in employee retention and skill level increased, and the organization

transitioned the entire workforce to telework in a single day.

When employees are engaged, managers notice the physical changes in their work

performance (Kahn, 1990). Employees respond to leaders being interested in their well-

being, challenging work, collaborative work environments, and clear goals. A positive

response to leadership engagement strategies results in increased engagement resulting in

employees being more dedicated to reaching organizational goals (Ali et al., 2019;

Gruman & Saks, 2017; Huertas-Valdivia et al., 2018; Pham-Tai et al., 2019; Rozman et

al., 2019). Risley's (2020) study supported the notion that increased engagement leads to

better overall performance. As leadership focused on measuring engagement and

determining what influenced engagement, they were able to implement more efficient

strategies, yielding a greater return from their employees to the point of being prepared

for a rapid work environment change to accommodate the restrictions of the COVID-19

pandemic.

Leadership should assess the needs of their employees to determine what

resources and demands are being sufficiently met and which need improvement.

Resources such as self-efficacy, organization-based self-esteem, optimism, and

psychological needs have been empirically determined as antecedents of employee

engagement. Additionally, the balance between job resources and job demands is critical

to high levels of engagement (Kwon & Park, 2019). Sharing information and getting buy-

in from employees contributes to developing trust between employees and leadership

(Marouf, 2016). Organizations that do not address engagement issues tend to breed more

engagement issues, further hindering performance. Creating trust and addressing the

needs of the employees can help increase overall engagement and can lead to improved

performance. Employee job satisfaction levels also contribute to improved performance.

Job Satisfaction

Job satisfaction describes the degree to which an employee is satisfied with their

type of work. An employee's level of job satisfaction is indicative of an employee's

willingness to perform at an optimum level of performance (Hoffman-Miller, 2019).

Furthermore, job satisfaction is related to the nature of job tasks and duties, the results

achieved, supervisory relationships, and the overall liking of the job (Arifin et al., 2019;

Prihadini et al., 2020; Wang & Brower, 2019). Employees can have different satisfaction

levels depending on how tasks align with their individual intrinsic and extrinsic

motivators (Herzberg, 1966; Prihadini et al., 2020). Extrinsic and intrinsic motivators

significantly influence job satisfaction and, in turn, affect employees' work performance

(Arifin et al., 2019; Taba, 2018; Wang & Brower, 2019).

Understanding job satisfaction is essential for an organization to maximize

productivity and operations. Organizations with high satisfaction can reduce the long-

term costs of employee turnover, sick leave, and workplace stress (Bakker & de Vries,

2021; Clark, 2017; Satuf et al., 2018; Schaufeli, 2017; Wnuk, 2017). Profitability is

greatly affected by job satisfaction. Replacing employees who quit can cost an

organization between approximately six to nine months of their salary. The company will

also suffer a loss in productivity, engagement, and overhead when an employee quits,

potentially creating an overall cost of between 100 percent and 200 percent (Society for

Human Resource Management [SHRM], 2019).

Additionally, employees with low satisfaction are 15 percent less profitable and

18 percent less productive than those with higher levels of satisfaction (Culibrk et al.,

2018; SHRM, 2019). Approximately 71% of U.S. employees reported looking for

another job due to a lack of satisfaction or influencers of satisfaction (Mental Health

America [MHA], 2017). Furthermore, lack of satisfaction can impact the reputation of an

organization. Dissatisfied employees often have higher absenteeism rates, affecting an

organization's productivity. Lack of consistent work decreases customers' positive

experience and risks essential tasks not getting completed (Kadotani et al., 2017).

Employees with high satisfaction levels are more inclined to be dedicated to their

organization and are less likely to leave their jobs, resulting in organizations retaining

quality employees.

Influencers of Job Satisfaction

Understanding what factors influence job satisfaction is essential for business

leaders to create a conducive work environment. All employees are not motivated by the

same factors that influence satisfaction. Furthermore, they can experience different levels

of satisfaction and dissatisfaction at varying times (Herzberg, 1959). Therefore, leaders

should make efforts to understand which factors motivate their employees.

Understanding the prominent factors influencing satisfaction can help leaders manage

their teams more efficiently (Herzberg, 1959; Kotni & Karumuri, 2018; Metzenbaum,

2019).

Many researchers have studied job satisfaction to determine the influential factors

and how these factors motivate employees. The most prominent factors that researchers

have found to influence satisfaction are (a) organization development, (b) policy, (c)

advancement opportunities, (d) job security, (e) working conditions, (f) relationship with

supervisors, (g) workgroup, and (h) leadership styles (Culibrk, 2018; Kang et al., 2021;

Keith et al., 2021; Moraru & Popa, 2019; Norbu & Wetprasit, 2021; Shin & Hur, 2020).

Each factor aligns with the factors Herzberg (1959) identified that cause satisfaction and

dissatisfaction. Herzberg (1959) grouped the factors that affect satisfaction into two

groups: motivation factors and hygiene factors.

Motivation Factors. Motivation factors are identified as satisfiers and pertain to

motivating factors that are intrinsic to employees. Motivation is the process of inspiring

employees to complete tasks to achieve specific organizational and personal goals and

targets (Khezendar & Hamas, 2021; Ozsoy, 2019). Satisfiers make up positive attitudes

for employee engagement and job satisfaction. An increase in motivation factors

increases an employee's job satisfaction. The motivation factors are (a) achievement, (b)

recognition, (c) the work itself, (d) responsibility, (e) advancement, and (f) possibility for

growth (Herzberg, 1959; Kang et al., 2021). Positive achievement relates to an employee

successfully completing a task, solving a job-related problem, or seeing positive results

from their work (Alshmemri et al., 2017; Carvalho et al., 2020).

When employees notice positive results from their work, they feel more motivated

to improve their skills. Identifying employees' achievements allows employees to

determine their progress and, in turn, makes them more confident in their capabilities.

Recognizing achievements and increased capabilities results in employees improving

decision-making skills, creating more innovative ways to complete job tasks, becoming

more efficient at completing tasks, acquiring additional skills, and increasing job

satisfaction (Carvalho et al., 2020; Forjan et al., 2020; Kleine et al., 2019). Notably, when

employees do not experience achievement often decrease in performance and are less

satisfied with their jobs. Furthermore, employees avoid similar tasks that they have

experienced past failures.

Experiencing a lack of achievement can result from a lack of awareness of

successfully completed tasks. An example would be an employee who consistently makes

deadlines but has not seen the metric to demonstrate their achievements. These types of

achievements are also typically overlooked during annual reviews. Since negative

achievement can impact performance, leaders and managers should acknowledge

accomplishments and create an environment where employees feel safe when making

mistakes. Having this safety can contribute to employees making another attempt to

improve. Otherwise, organizations risk continued performance failure (Hyde, 2017;

Lemaire, 2021; Risley, 2020; Snell et al., 2015). Organizational leaders provide awards

and recognition to employees for superior performance, contributing to an employee's

sense of achievement.

Positive recognition occurs when employees receive praise or rewards for

reaching goals or producing high-quality work. Recognition of employees contributes to

an organization's feeling valued and appreciated (Alshmemri et al., 2017; Baranwal et al.,

2016; Chauhan & Singh, 2018; Osborne & Hammoud, 2017). Bevins (2018) conducted a

study that found that Generation Z and Millennials rated recognition as a primary

motivator factor over salary. Recognition and rewards demonstrate employee

appreciation and influence employee commitment, dedication, and trust (Performance

Related Pay, 2019).

Advancement and the possibility for growth are two factors that contribute to

positive attitudes to the job, as these two factors satisfy the intrinsic need for growth.

Advancement is defined as the upward status or position of the employee in the

organization. Possibilities for growth include promotion opportunities, chances to learn

skills, and gain new professional knowledge. Opportunities for growth and advancement

impact an organization's ability to recruit and retain employees (Ali, 2020; Osborne &

Hammoud, 2017; Wang & Brower, 2019).

Employees who can exercise autonomy within their role often experience

increased job satisfaction. When employees have the freedom to make decisions, known

as responsibility, they experience meaning in their work (Ma et al., 2020; Nikolova &

Cnossen, 2020). The final motivation factor identified by Herzberg (1959) is the work

itself. An employee's satisfaction level depends on the work's actual content. If

employees are not motivated by the work itself, they are often not satisfied with their job

(Alshmemri et al., 2017; Herzberg et al., 1959; Osborne & Hammoud, 2017).

Ensuring that motivator factors are maintained will help leaders keep their

employees satisfied. Organizations with highly motivated employees are more likely to

overperform and experience increased job satisfaction. Furthermore, highly motivated

employees contribute to long-term organizational success. Highly motivated employees

are more likely to stay at their current job, develop innovative processes to complete

tasks, operate more efficiently, share knowledge, improve performance, and increase

their effort to help the organization to meet its goals (Bhatt & Sharma, 2019; Byrne et al.,

2017; Hejjas et al., 2019; Lee & Rhee, 2019 Paulo da Silva & Shinyashiki, 2014).

Hygiene Factors. Hygiene factors are referenced as dissatisfiers and are extrinsic

motivators (Herzberg, 1959). When employees experience low hygiene factors, they are

likely to experience increased dissatisfaction. Alternatively, employees experiencing

positive hygiene factors result in reduced dissatisfaction. It is important to note that

employees who do not experience hygiene factors are not necessarily unsatisfied with

their job or role; however, they are experiencing increased levels of dissatisfaction

(Yadav, 2019; Herzberg, 1959). Job satisfaction and dissatisfaction are measured by

different sets of factors and therefore are measured on two different continuums

(Alshmemri et al., 2017; Herzberg, 1959). The hygiene factors include (a) company

policies, (b) interpersonal relationships, (c) salaries, (d) working conditions, and (e)

supervision (Kang et al., 2021; Herzberg et al., 1959).

Hygiene factors relate to the work environment and job conditions (Herzberg,

1966). Leaders should be aware of this distinction to address issues causing

dissatisfaction adequately. For example, if an employee is in a hostile work environment,

promoting or recognizing them will not result in less dissatisfaction. The employee may

feel higher levels of satisfaction as their intrinsic needs are met (Alshmemri et al., 2017;

Herzberg, 1966; Herzberg et al.,1959; Hur, 2017). The opposite is also true. If an

employee is not satisfied, a high salary will not increase their level of satisfaction;

however, the employee may experience reduced levels of dissatisfaction. The factors that

lead to satisfaction are distinct and separate from those that lead to job dissatisfaction

(Alshmemri et al., 2017; Herzberg, 2003; Herzberg, 1959; Yin et al., 2021; Lee, 2018;

Rahman & Iqbal, 2013). Therefore, eliminating factors that cause dissatisfaction will not

necessarily motivate employees to improve performance.

Interpersonal relationships between coworkers, employees, and supervisors are an

integral determinant of employee dissatisfaction. Interpersonal relations are limited to

personal and work relationships and include job-related interactions and social

discussions in the work environment during breaks (Alshmemri et al., 2017; Herzberg,

1959). Organizations should create an environment that allows for a balance of work and

personal interaction. Research has found that organizations that operate in this manner

develop a sense of latitude between coworkers, peers, and supervisors. Having latitude

contributes to trust-building and increased communication and collaborative efforts in

completing work tasks (Azeem et al., 2020; Cao et al., 2021; Concepcion, 2020; Rouse,

2020; Soergel, 2020; Yen, 2021). When the balance of interpersonal relationships is

offset, the latitudinal dynamic shifts to a longitudinal power dynamic and can cause

tensions in the workplace. An imbalance in interpersonal relationships is typically

identified when micro-managing occurs and when employees attempt to exert influence

or supervisory status over their coworkers and peers. Employees perceive the imbalance

as mistreatment, leading to turnover, reduced mental health, and increased difficulty

integrating new employees (Cao et al., 2021; Lee et al., 2021; Oyet & James, 2021;

Soergel, 2020; Zhou et al., 2021).

Organizations often try to use salary to overcompensate for shortcomings. A

common misconception is that salary s a primary indicator of employee satisfaction.

According to Herzberg (1959), pay does not contribute to job satisfaction but the level of

job dissatisfaction. Additionally, a handsome salary may lower dissatisfaction if the

working conditions are inferior and do not favor the employee. However, if the work

environment is not pleasant, the intrinsic value of compensation becomes relatively

unimportant and is no longer a motivator for the employee (Alshmemri et al., 2017; Kang

et al., 2021; Nikolova & Cnossen, 2020).

Company policies are considered one of the leading causes of employee

dissatisfaction in the workplace. Company policies that do not favor the employees can

lead to lethargy, demotivation, dissonance, and employees losing trust in leadership.

Additionally, if policies and procedures are not followed, or employees feel they do not

represent their values, employees can develop a feeling of betrayal against their

supervisors and leadership (Azeem et al., 2020; Chimote & Malhotra, 2020). Employees

experiencing dissatisfaction resulting from company policies often begin to look to leave

their workplace. Employee dissatisfaction is detrimental to the organization as this

increases the turnover rate but may also reveal that company policies are not in the best

interest of their employees.

Supervisors are often in direct contact with employees and serve as the liaison

between the employees and leadership. Because of the relationship that supervisors have

with employees, supervisors greatly influence employees' perception of the organization

and leadership (Carvalho et al., 2020; Kleine et al., 2019; PPS, 2019; Roberts et al., 2020;

White, 2017). Organizational leaders should consider who they select for supervisory

roles as these positions directly correlate to management and the organization, as

perceived by employees. Furthermore, employees trust their supervisors to adequately

represent and advocate for them and communicate their needs to leadership. Leadership

should ensure that they are intentional with the use of their supervisors. Supervisors can

provide real-time feedback to help acknowledge and resolve issues impacting

performance. Serving as a communication channel and gaining insight from employees to

provide leadership with input from the employees to contribute to the solution helps

create trust in the organization (Alshmemri et al., 2017; Bevins, 2018; Ozsoy, 2021;

Roberts et al.,2020; Udin & Yuniawan, 2020).

Hygiene factors are related to the conditions that apply to the job and the

workplace. By ensuring hygiene factors are present, leadership can foster an environment

that decreases dissatisfaction. When employees are content with their job context,

organizational leaders can expect no dissatisfaction, but that does not necessarily mean

that they will receive positive employee attitudes. Ultimately, poor hygiene factors can

cause dissatisfaction, while better hygiene factors can reduce dissatisfaction. However,

hygiene factors do not contribute to satisfaction. Understanding that the opposite of

dissatisfaction is no dissatisfaction can help leaders develop better strategies to reduce

employee dissatisfaction.

Job Satisfaction and Performance

Job satisfaction is an employee's positive and negative feelings towards their job.

Satisfied employees are more productive, dedicated to their jobs, more reliable,

innovative, and willing to share knowledge with coworkers (Amiri et al., 2017; Budirianti

et al., 2020; Culibrk, 2018; Mughal et al., 2021; Inayat & Khan, 2021). Job satisfaction

strongly contributes to organizational performance (Bhatt & Sharma, 2019; Budirianti et

al., 2020; Cankir & Arikan, 2019). For an organization to perform well, employees must

demonstrate the necessary skills to perform tasks successfully and have the intention to

stay with the organization. Efficient, dedicated, and high-performing employees save

companies billions yearly (Barden, 2017; Budirianti et al., 2020; SHRM, 2019; State of

the American Workplace, 2020). To remain competitive, leaders must invest in their

employees and cultivate an environment that creates job satisfaction by increasing

hygiene and motivator factors.

Leaders should understand the impact that satisfaction has on performance.

Satisfied employees are willing to go above and beyond their job description to help an

organization achieve its goals (Budirianti et al., 2020; Cankir & Arikan, 2021; Cao et al.,

2021). When organizations fail to reach performance goals, whether financial or

operational, leadership relies on employees to contribute to making up lost ground.

However, if employees are not satisfied with their jobs or the organization, they are less

likely to contribute more than required to help the organization reach its goals (Budirianti

et al., 2020). Although employees should not be expected to do more than needed,

creating an environment that keeps employees satisfied is essential. Hence, they are

willing to contribute increased effort to help the organization reach its goal (Norbu &

Wetprasit, 2021), which can be critical for the livelihood of some organizations as job

satisfaction is an essential factor in the continuity and success of an organization

(Budirianti et al., 2020; Carvalho et al., 2020; Norbu & Wetprasit, 2021).

When assessing performance, leaders and decision-makers should be aware and

consider their impact on their workforce. Company policies and practices influence

employee perceptions of job security, fairness, and transparency. Employees observe

policies and practices and measure how they align with their individual goals and values.

When there is no alignment between employee values and company policy, employees

often experience negative perceptions of job security, fairness, and transparency

(Carvalho et al., 2020; Khezendar & Hamas, 2021; Lee et al., 2021; Yavuzkurt & Kiral;

2020). Employees are less likely to try new strategies to improve their skills or work

processes and often withdraw from work when experiencing misalignment. Furthermore,

when employees are not satisfied and have negative perceptions of job security, they are

more likely to leave an organization in times of adversity.

Employees place a high amount of emphasis on job security. Lee et al. (2021)

conducted a study that examined the effects of contracting out in US Federal agencies.

Contracting out federal positions has provided substantial benefits to government

organizations. However, federal employees sometimes interpret the hiring of contractors

as a threat to their jobs. The study by Lee et al. found that as government agencies

increased their contracted positions, federal employees' intention to leave increased.

Furthermore, once satisfied employees decreased, federal employees' quality of

work and overall productivity decreased (Lee et al., 2021). To alleviate employee

concerns, leadership should be transparent with employees and provide emotional

support, build trust, and take steps to address employee fears and anxieties (Kahn, 1990;

Gruman & Saks, 2011). Additionally, leadership should give evidence of the gains that

the organization stands to benefit from contracting out work while communicating its

impact on their current jobs. Providing conducive information can reinforce safety for

employees and help agencies retain their employees and maintain productivity (Lee et al.,

2021; Metzenbaum, 2015; Norbu & Weprasit, 2021).

Employees will not perform optimally if they are not motivated to do so. A

satisfied employee does not necessarily equate to increased work performance. Leaders

should ensure that they are making efforts to increase motivator factors and hygiene

factors. Employees may be satisfied with their job; however, they will feel undervalued

and unappreciated if they do not receive recognition or rewards for their work.

Motivation is used to influence employees to work productively, and reinforcing the

appreciation of effort contributes to employees' maintenance of productive work but will

also encourage them to work harder to increase performance (Azeem et al., 2020;

Budirianti et al., 2020; Carvalho et al., 2020; Kang et al., 2021; Keith et al.,2021;

Khezendar & Hamas, 2021; Sherwood et al., 2018; Yavuzkurt & Kiral, 2020). An

organization’s success is highly determinant of employee performance. Low satisfaction

levels have led to counterproductive behaviors in the workplace, declining employee

performance, and organizational performance (Azeem et al., 2020; Lee et al., 2020;

Seriki et al., 2020; White, 2017). Organizational leaders should create environments

conducive to employee needs and implement job satisfaction strategies to improve

employee performance.

Employee Performance

Understanding what motivates employees is critical for leaders to maintain higher

organizational commitment and performance. Employee performance is a performance

result that can be achieved by a person or team in an organization, both qualitatively and

quantitatively (Cankir & Arikan, 2019; Carvalho et al., 2020; Yen et al., 2021).

Employee performance levels are significant indicators of the success and sustainability

of an organization (Buditianti et al., 2020; Carvalho et al., 2020; Norbu & Wetprasit,

2021). Companies should focus on maintaining and managing employee motivation so

that employees are focused on helping the organization reach its goals.

Various factors impact employee performance. As discussed in the previous

section of this literature review, employee engagement and job satisfaction have been

found to have a positive relationship with employee performance. Motivation, leadership

style, employee capability, and red tape are significant influencers of employee

performance. Organizations that focus on improving these factors experience increased

employee performance and organizational performance. Alternatively, organizations that

have low-performing employees are at risk of decreasing the overall performance of the

organization. Low-performing employees can negatively impact their team performance

and cost organizations billions of dollars annually due to lost productivity (Lee & Rhee,

2019; Ward, 2021). Customer satisfaction decreases as employee performance decreases,

especially if consumers observe firsthand. Employees' low performance is often reflected

in their attitudes and quality of service (Berraies et al., 2020; Copeland, 2020; Keith et

al., 2021; Martinaityte et al., 2019; Ward, 2021; Yen et al., 2021). Customers who have a

negative experience are less likely to return, especially first-time customers.

Organizational leaders can improve their customer satisfaction rates by ensuring that they

are creating an environment that is conducive to employee performance.

Motivating employees creates a situation that can relieve employee anxiety and

can stimulate the employee to carry out tasks and achieve higher goals. Organizational

leaders and managers attempt to motivate employees through employee performance

appraisals (Khezendar & Hamas, 2021; Norbu & Wetprasit, 2021; Pradana et al., 2021).

Employees are more likely to be satisfied with their positions when they reach levels of

achievement in the workplace and, in turn, are more driven to surpass performance

metrics (Concepcion, 2020; Erum et al., 2020; Kang et al., 2015). Performance

evaluations are used to provide feedback and as a motivator for employees to eliminate

declines in performance.

Performance evaluations also contribute to the physiological needs of employees.

However, some employees feel that the assessments do not adequately represent their

work. Furthermore, annual performance reviews do not produce opportunities for

employee performance improvement as the feedback may occur months after the

unfavorable event. Such a large gap between feedback and occurrences can negatively

affect an employee’s perception of security. Leaders should consider providing real-time

feedback or feedback more frequently, as this motivates employees to increase their

performance on a more consistent basis (Pradana et al., 2021; Risley, 2020). Furthermore,

Offocevibe (2021) found that 98% of employees prefer to receive regular feedback, and

the quality of feedback would increase if provided more frequently. Using an opportunity

to provide more frequent and relevant feedback can help an organization motivate its

employees to improve their performance (Girdwichai & Sriviboon, 2020; Grvina et al.,

2021).

Leadership style is another critical factor that influences employee performance.

Organizational leaders can influence employee performance levels through techniques

that influence employees’ perception of organizational performance and the meaning of

their work. Employee performance depends on a proper match between a leader’s ability

to adapt to various situations. If the leadership style does not align with the objective or

business problem, employees have demonstrated lower performance by missing targets,

decreased productivity, and insufficient innovation (Iqbal et al., 2015). Leadership styles

must stimulate employees to improve performance and adapt to change (Iqbal et al.,

2015; Peng & Chen, 2021; Shah et al., 2021). For example, an autocratic leadership style

would not fit an organization promoting collaboration and developing new innovative

strategies.

Autocratic leadership styles promote a one-sided leader-driven dynamic. This

leadership style intimidates employees and restricts their comfort in producing creative

ideas. Furthermore, they may withdraw from the role, decreasing their performance

(Khan et al., 1959; Shah et al., 2021; Yen et al., 2021; Zhang & Chen, 2021).

Alternatively, employees are more likely to adapt and improve performance if the

leadership style aligns with the goals and objectives. Research has shown that employees

in service-related career fields improve performance when the leaders demonstrate

servant-style leadership (Brouns et al., 2020; Peng & Chen, 2021).

Employee performance directly impacts organizational performance.

Organizational leaders should focus on determining how to improve the influencers of

employee performance to remain competitive. To perform efficiently, employees must

have the proper resources to complete their jobs successfully. A primary resource is

training. Training helps develop employee skills and motivates them to contribute more

time and effort to their organization. Training also contributes to closing skill gaps within

the organization, resulting in increased productivity (Almalki, 2021; Girdwichai &

Sriviboon, 2020; Tarmidi & Arsjah, 2019). Employees are an organization’s most

valuable asset as they spearhead the production. Increasing the factors that directly

improve employee performance results in overall organizational performance (Paais &

Pattiruhu, 2020; Tarmidi & Arsjah, 2019). Organizations can experience improved

productivity, higher employee retention, and maximized use of resources, saving the

organization costs and contributing to their competitive advantage.

Transition

Employee engagement and job satisfaction are critical factors in improving

employee performance. Federal agencies consider employee engagement an essential

driver of successful organizational performance (Lavigna, 2019). In 2015, OPM

introduced the Employee Engagement Initiative to address employee engagement issues

within federal agencies (OPM, 2015). The Employee Engagement Initiative emphasizes

creating organizational conditions that foster employee engagement (Kamensky, 2020) to

expect increased employee engagement to improve performance. (Kamensky, 2019). This

study conducted secondary data analysis on the 2019 Federal Employee Viewpoint

Survey (FEVS) data. The independent variables identified in the FEVS were employee

engagement, measured by the in the 2019 FEVS, and job satisfaction, measured by the

GSI, items 40 and 69–71, in the 2019 FEVS. The dependent variable was employee

performance, which will be measured using a composite variable consisting of items

15,16, and 19 in the 2019 FEVS.

As of 2017, the federal government employed approximately two million federal

employees. Low levels of job satisfaction and engagement have a positive relationship

with decreased productivity, turnover, and quality of work (Bhatt & Sharma, 2019).

Government agencies would benefit from understanding the relationship between

employee engagement, job satisfaction, and employee performance. Understanding the

relationship between the variables could help leaders create an environment that creates a

culture to foster improved performance by identifying influencers of job satisfaction and

employee engagement and determining how performance is related to those factors.

Furthermore, increased employee performance can improve organizational performance

(Pitts, 2009; Choi & Rainey, 2010; Metzenbaum, 2015; Lee, 2018; Somers, 2018).

The literature review provides a critical analysis and complete synthesis of the

applicability, basis, various perspectives, comparative research, and alternative theories

of the frameworks used to structure this study. Herzberg’s two-factor theory and Kahn’s

engagement theory are the theoretical frameworks for this secondary data analysis. Both

frameworks provide insights regarding job satisfaction and employee engagement

influencers, respectively. Employee engagement, job satisfaction, and employee

performance are the variables explored by this literature review. Section two of this study

includes the project design and process.

Section 2: Project Design and Process

This study aimed to examine the relationship between employee engagement, job

satisfaction, and employee performance. I used secondary data collected from the 2019

FEVS. Section 2 of this study includes a discussion of the method and design used to

conduct this study. This section also contains information regarding how the data were

collected and analyzed for this study.

Method and Design

The purpose of this quantitative correlational ex post facto study was to examine

the relationship between employee engagement, job satisfaction, and employee

performance among employees within the federal government. The research question

(RQ) and hypotheses of this study were as follows:

RQ: Does a significant relationship exist between employee engagement, job

satisfaction, and employee performance among employees within the federal

government?

: There is no statistically significant relationship between employee

engagement, job satisfaction, and employee performance among employees within the

federal government.

: There is a statistically significant relationship between employee engagement,

job satisfaction, and employee performance among employees within the federal

government.

Method

The three primary research methodologies are qualitative, quantitative, and mixed

(Ezer & Aksut, 2021; Saunders et al., 2016). The qualitative research method is used to

examine and understand the perceptions and experiences of individuals and social life.

Qualitative research tools include field notes, observations, and interviews. Qualitative

research provides the researcher with the flexibility to ask follow-up questions to gain

additional insights and the flexibility to incorporate multiple realities for analysis of

people’s understanding and perception of how or why a phenomenon occurs (Ezer &

Aksut, 2021; Rahman, 2017; Saunders et al., 2016; Wolday et al., 2019). The findings

produced by qualitative research are not arrived at by statistical procedures or any other

quantification. Therefore, it was not the best research method for this study, because I

wanted to determine whether a relationship exists between the independent and

dependent variables.

Quantitative research is used to examine the association or relationship between

variables by analyzing data using statistical techniques. This research methodology was

most appropriate for this study as I analyzed existing data to determine whether there is a

statistically significant relationship between employee engagement, job satisfaction, and

employee performance. A primary disadvantage of the quantitative research method is

the failure to identify deeper underlying meanings and explanations for phenomena

(Rahman, 2017; Yin, 2014). However, the primary advantage of this research method is

the use of objective data, which separates the researcher from the research object, and the

results can be reproduced, determining reliability (Rahman, 2017).

It is important to note that the quantitative and qualitative research methods are

not substitute methods and cannot be used interchangeably. However, these two research

methods can be used together, known as the mixed methods research method. The mixed

methods research methods use both statistical data and textual data. Since this study did

not use any qualitative data collection techniques, the mixed method research method

was inappropriate for this study.

Design

The intent of this study was to determine whether a statistically significant

relationship exists between employee engagement, job satisfaction, and employee

performance. This study was an ex post facto study as secondary data were analyzed. An

ex post facto design allows for examining how independent variables affect dependent

variables. A disadvantage of utilizing the ex post facto research design is that the

researcher cannot manipulate the variables and cannot reassign research subjects to

different groups (Akinulua, 2019; Apkan, 2020). Despite this limitation, the ex post facto

research design has distinct advantages. This research design is useful for analyzing

causal relationships between independent and dependent variables and can be less time-

consuming than experimental research as the researcher can use previously collected data

(Akinulua, 2019; Salkind, 2010).

Data were collected from the 2019 FEVS data set, a pre-existing public dataset

initially collected by OPM, to test the relationship between employee engagement, job

satisfaction, and job performance amongst employees in the federal government.

Employee engagement was measured using the FEVS Employee Engagement Index

(EEI); job satisfaction was measured using the FEVS Global Satisfaction Index (GSI),

and job performance was measured using a composite variable of Items 15, 16, and 19.

Missing data have the potential to bias future research findings. The 2019 FEVS

consists of responses from 615,395 employees, which represents approximately a 42.6%

response rate. The participants are federal employees representing 83 agencies (OPM,

2019). Missing data can occur due to refusal to respond, partial response, loss of data,

and indecipherable responses (Gorard, 2020). Missing data can negatively impact the

reliability and validity of this study (Mohajan, 2017). Missing data were addressed as

they occurred. For this study, cases that were missing a response to any of the core and

demographic questions were removed.

The data were analyzed using SPSS statistical software. I used SPSS to present

descriptive and inferential statistics, including assumptions of outliers, multicollinearity,

normality, linearity, homoscedasticity, and independence of residuals, while noting any

violations. The data assumptions of this study are (a) archival data collected is valid,

credible, and reliable; (b) all data were collected ethically; (c) data were not manipulated

to create a specific outcome; (d) all data were obtained voluntarily; (e) data are

unchanged and raw. I described the mean and standard deviation and used power analysis

to determine the sample size. Furthermore, I used the Pearson correlation parametric test

to determine the relationship between linearly related variables. Once a relationship was

established, I ran a multiple linear regression analysis.

I used multiple linear regression to test if a statistically significant relationship

exists between this study's independent and dependent variables. The data were analyzed

using the multiple linear regression function within SPSS statistical software. Multiple

linear regression analyses can be used in quantitative correlational research designs,

which test the relationship between two or more variables (Aderibigbe & Mjoli, 2019;

Salkind, 2010). Quasi-experimental and experimental designs are also used for

quantitative research. However, experimental designs focus on causation, and quasi-

experimental designs determine impact after manipulating predictor variables. Since the

focus of this study is to determine if there is a relationship between employee

engagement, job satisfaction, and job performance, a correlational design is most

appropriate for this study.

Ethics

For this study, I used archival data collected by the OPM. The data are available

on the OPM website. The FEVS was administered to all full-time and part-time federal

employees in Spring 2019. OPM mandates agencies to allow employees to participate in

the FEVS and submit responses anonymously. The archival data do not contain any

personal information from the participants. Although the data do not contain any of the

participants’ personal information, I will maintain the data in a safe place for 5 years to

protect the rights of the participants. IRB approval was also obtained for the final

doctoral degree credit (approval number no. 01-13-22-0981064).

Transition and Summary

The purpose of this quantitative correlational ex post facto study was to examine

the relationship between employee engagement, job satisfaction, and employee

performance among employees within the federal government. This study was an ex post

facto study as it used after-the-fact data. The quantitative research method was the most

appropriate for this study as the quantitative methodology is used to determine the

relationship between variables. Data for this study was collected from the 2019 FEVS

data set, which is publicly available on the OPM website. A multiple linear regression

analysis was used to test if a statistically significant relationship exists between this

study’s independent and dependent variables. The archival data used for this study do not

contain any personal information from the participants. Although the data does not

contain any of the participants’ personal information, I will maintain the data in a safe

place for 5 years to protect the rights of the participants, and IRB approval was obtained.

In Section 3, I present the quantitative data analysis and recommendations for future

research and discuss the impact of social change.

Section 3: The Deliverable

The Deliverable

This section includes a comprehensive executive summary with a presentation of

quantitative data analysis to include graphs and figures. The executive summary includes

an overview of the study, identifies the goals and objectives, and provides the results and

conclusions of the analysis, recommendations for actions, a communication plan, and the

social change impact. This section also includes the presentation of quantitative data

analysis, results (descriptive and inferential) and conclusions of the analysis,

recommendations for action, communication plan, social change impact, and skills and

competencies,

Executive Summary

The purpose of this quantitative ex post facto study was to examine the

relationship between employee engagement, job satisfaction, and employee performance

among employees within the federal government. The independent variables were

employee job satisfaction and employee engagement, and the dependent variable was

employee performance. A multiple linear regression analysis was used to determine if

there was a statistically significant relationship between job satisfaction, employee

engagement, and employee performance. Empirical research found that employee

performance is influenced by both employee engagement and job satisfaction (Bhatt &

Sharma, 2019; Choi & Rainey, 2010; Lee, 2018; Metzenbaum, 2015; Pitts, 2009; Somers,

2018).

The data used for this study were secondary data obtained via the 2019 FEVS.

FEVS is an annual survey that measures employees’ perception of whether or to what

extent conditions characterize successful organizations in their agencies (OPM, 2019).

FEVS data are appropriate and relevant to my research study. They are the most cost-

effective, convenient, and efficient way to meet my research objective: to measure the

relationship between employee engagement, job satisfaction, and employee performance

within the federal government. Using secondary data enabled me to conduct my research

without directly interacting with the respondents. My portfolio study did not require the

use of standard data collection instruments. Using archival data eliminated the

requirement for the second level of IRB approval.

My portfolio study provided much-needed insight into how employee engagement

and job satisfaction relate to employee performance. Furthermore, the research in this

study provided additional insight into the influencers of job satisfaction and employee

engagement. I plan to share the results of this study with leaders in the federal

government. Leaders within the federal government will find the result of this study

beneficial as the information can help leaders assess areas of improvement better when

trying to increase performance. The information provided can assist leaders in developing

programs and strategies that more accurately evaluate and measure employee engagement

and job satisfaction in the workforce. Furthermore, these strategies can help leaders

identify overarching issues that negatively impact engagement and satisfaction and create

innovative ideas to address the issue. Federal employees that are highly engaged will

result in improved performance.

Goals and Objectives

The goal of this study was to determine whether there is a relationship between

job satisfaction, employee engagement, and employee performance in federal

government employees. This study’s objectives included collecting and analyzing the

data from the 2019 FEVS dataset, establishing a sample size, running a multiple linear

regression analysis, and interpreting the results. A total of 615,395 employees

participated in the 2019 FEVS. The Codebook, DataSet, and Analysis from the U.S.

Office of Personnel were used to run a multiple linear regression. Demographic data were

also used in the study to describe the sample, including the following information:

gender, education, tenure with the federal government, and supervisory status. The 2019

FEVS consisted of 101 questions asked to employees regarding personal work

experiences, satisfaction, leadership, training, performance, employment and unique

demographics, supervisor, work-life programs, and the partial government shutdown. For

this study, I measured employee engagement using the EEI, job satisfaction by the GSI,

and employee performance (dependent variable) by using a composite variable consisting

of Items 15, 16, and 19 in the 2019 FEVS (see Appendix B).

Overview of Findings

The responses of the 615,395 participants were included in the 2019 FEVS

dataset. A priori power analysis using G*Power determined that a sample size of 68 cases

would be considered a successful sample. The sample size was based on a medium effect

size (.15), a significance level of .05, two predictor variables, and a complement of

probability of Type II error (1-β) = .90. Though a total of 68 cases was determined to be

the threshold based on the power analysis, the power to detect a result continued to

significantly increase from .80 to approximately .95 as the sample size increased from 68

cases to approximately 100 cases and did not significantly increase after a sample size of

100. Based on these results, a sample of 100 cases was used for this study. Preliminary

analyses were conducted to assess whether the assumptions of multicollinearity, outliers,

normality, linearity, homoscedasticity, validity, and independence of residuals

were met;

no serious violations were noted.

The independent variables were employee engagement and job satisfaction. The

dependent variable was employee performance. Multiple regression was run using SPSS

Version 28.0 to predict employee performance from employee engagement and job

satisfaction. The multiple regression model statistically significantly predicted employee

performance, F(2,97) = 43.836, p < .001, R

= .475. Employee engagement was

statistically significant (t = 3.594, p < .001, β = .504). Job satisfaction was not significant

(t = 1.788, p > .05, β = .225). Regression coefficients and standard errors can be found in

Table 7. Standard multiple linear regression, α = .05 (two-tailed), was used to examine

the efficacy of employee engagement and job satisfaction in predicting employee

performance. Job satisfaction and engagement statistically significantly predicted

employee performance: F(2,97) = 43.836, p < .001, R

= .475 with an adjusted R

of .464.

The R

value indicated that employee engagement and job satisfaction explained

approximately 47% of the variability of employee performance. Employee engagement

was statistically significant (t = 3.594, p < .001, β = .504), accounting for a higher

contribution to the model than job satisfaction (t = 1.788, p > .05, β =.225) based on the β

value of .504. This value represents an approximate 50% variability of employee

performance as opposed to job satisfaction which represents a 22% variability of

employee performance. Although job satisfaction was not significant, the relationship

between job satisfaction and employee engagement is statistically significant.

There was linearity as assessed by partial regression plots and a plot of

studentized residuals against the predicted values. The independence of residuals was

assessed by a Durbin-Watson statistic of 1.891. There was homoscedasticity, as assessed

by visual inspection of a plot of studentized residuals versus unstandardized predicted

values. There was no evidence of multicollinearity, as assessed by tolerance values

greater than .1. One case included in the sample used for this study was identified as

having a value greater than three standard deviations in which the value was 4.544. It was

noted that this case was considered an outlier; however, it did not demonstrate high

leverage or a high level of influence, as there were no leverage values greater than .2 and

values for Cook’s distance above 1. The assumption of normality was met, as assessed by

a Q-Q Plot.

Recommendations

This study’s results determined a statistically significant relationship between

employee engagement and employee performance. Furthermore, it was found that job

satisfaction, as measured by the GSI, did not directly influence employee performance;

however, employee engagement serves as a mediating variable. Leaders in the federal

government would benefit from researching what elements affect satisfaction and

employee engagement and to what degree. The recommendations for leaders within the

federal government are (a) determine motivational and hygiene factors; (b) determine

influencers that improve the physical, emotional, and cognitive factors of employee

engagement; (c) address issues that could impact job satisfaction and engagement; and

(d) redesign or develop a more accurate measurement of employee engagement and job

satisfaction with FEVS data by regrouping questions that represent motivators, hygiene

factors, and employee engagement. These actions could contribute to increased and

improved employee performance in the federal government. With this understanding,

leaders in the federal government can use the FEVS data to identify low-performing

influencers and invest in strategies that positively influence job satisfaction and employee

engagement.

Presentation of Quantitative Data Analysis

In 2019, 615,395 responses were included in the 2019 FEVS dataset. All

permanently employed, non-political, non-seasonal, full- and part-time federal employees

in pay status, or those eligible to receive pay, as of October 2018, were eligible to

participate in the 2019 survey. This study used a sample size of 100 fully completed

cases. In this subsection, I will discuss testing the assumptions, present descriptive

statistics, and present inferential statistics results.

Descriptive Statistics

The responses of the 615,395 participants were included in the 2019 FEVS

dataset; however, there were instances where employees did not answer all the questions

resulting in missing data. Missing data can occur due to refusal to respond, partial

response, loss of data, and indecipherable responses (Gorard, 2020) and can negatively

impact the reliability and validity of this study (Mohajan, 2017). Any employee

submission that did not include a response to all questions provided in the dataset was

considered an incomplete response and removed from the dataset for this study. Once

incomplete responses were omitted, a total of 267,983 complete responses remained. The

2019 FEVS was administered to employees on May 14, 2019, and closed on June 18,

2019. The 2019 FEVS was provided to federal employees approximately 3-and-a-half

months after the longest U.S. Federal Government partial shutdown in history.

The U.S. Federal Government shut down from December 22, 2018, until January

25, 2019 was due to Congress and former President Donald Trump not reaching a

resolution regarding the appropriations bill to fund government operations in the 2019

fiscal year. The shutdown affected nearly 800,000 federal employees, with approximately

380,000 being furloughed and the rest of the employees working without pay (Williams,

2019). Furthermore, this shutdown was the second shutdown that resulted in furloughs

under the Trump Administration. Consequently, questions related to the shutdown were

included in the 2019 FEVS. The 2018 government shutdown was a unique situation that

may have influenced employee’s engagement, performance, and satisfaction levels at the

specific time, which could have skewed the data per employee response from what would

have otherwise been a response indicative of ordinary circumstances. To mitigate this

potential risk, responses that identified being impacted by the 2018 shutdown were not

included in the population, resulting in a total of 100,747 responses remaining.

An a priori power analysis using G*Power, an online power analysis tool,

determined that a sample size of 68 cases would be considered a successful sample. The

sample size was based on a medium effect size (.15), a significance level of .05, two

predictor variables, and a complement of probability of Type II error (1-β) = .90. As

shown in Figure 2, an adequate sample size would be 68.

Figure 2

Power Prior Analysis

Figure 2 shows that the power of the test does not significantly increase after a

sample size of 100. A total sample size of 68 shows the power of the test being

approximately .80. Between a sample size of 68 and 80, the power increases from about

.83 to .88, a .05 increase. A sample size from 80 to 90 showed an increase in power from

approximately .87 to .91, a .04 increase. The power of the test only increased by about

.03 from .91 to .94, with a sample size of between 90 and 100. A sample size of 100 is

sufficient as it meets the required threshold of 68 and the power of the test is .90

indicating a lower probability of receiving a Type II error (Ampatzoglou et al., 2019).

Tables 1 and 2 depict descriptive results for the study sample. Table 1 displays the

descriptive statistics for the independent and dependent variables included in this study.

Table 2 presents the demographic representation data obtained from the 2019 FEVS that

describes the sample used for this study.

Table 1

Descriptive Statistics for Study Variables

Variable

Employee Engagement

100

4.0856

.82183

Job Satisfaction

100

3.9300

.91638

Employee Performance

100

4.0533

.86550

Table 2

Gender, Minority, Education, Supervisory Status, and Years in Service

Variable

Percent

Male

66.0%

Female

34.0%

Minority

33.0%

Non-Minority

67.0%

Less than a Bachelor's Degree

27.0%

Bachelor's Degree

39.0%

Beyond a Bachelor's Degree

34.0%

Non-Supervisor/Team Leader

86.0%

Supervisor/Manager/Senior Leader

14.0%

Ten years or fewer

49.0%

Between 10 and 20 years

29.0%

More than 20 years

22.0%

Statistical Tests of Assumptions

The sample size for this study (N = 100) was larger than the required sample size

of 68. Assumptions of independence, linearity, homoscedasticity, multicollinearity,

normality, outliers, and unusual points were tested. This study consisted of one dependent

variable, employee performance, and two independent variables, job satisfaction, and

employee engagement. Each variable is measured at the continuous level from 1 to 5,

where 5 is a positive response and 1 represents a negative response. The data in this study

have been used to analyze the relationship between the dependent variable and two

independent variables, making it suitable for multiple regression analysis (Zakeri et al.,

2020).

Independence of Errors

The Ordinary Least Squares assumption states that error terms are uncorrelated

(Uyanto, 2020). Autocorrelation of error terms violates the Ordinary Least Squares

assumptions (Uyanto, 2020). If the Ordinary Least Squares assumption is violated, an

autocorrelation error may be detected, which is problematic for linear regression as there

is a lack of independence of residuals. In this instance, multiple regression is not a

suitable analysis method (Uyanto, 2020). The Durbin Watson test is the most frequently

used test to detect autocorrelation errors (Uyanto, 2020; Draper & Smith, 1998). The

Durbin-Watson statistic ranges from 0 to 4, where 2 represents no correlation between

residuals. Table 3 depicts the Durbin-Watson statistic for this study. The Durbin-Watson

statistic for this study is 1.891. This value is very close to 2; therefore, it can be accepted

that the errors were independent.

Table 3

Multiple Model Regression Summary

Model

Adjusted R

SE of the

Estimate

Durbin-

Watson

.689

.475

.464

.63370

1.891

a. Predictors: (Constant), Global Satisfaction Mean, Employee Engagement

Index Mean

b. Dependent Variable: Performance Mean

Linearity, Homoscedasticity, Outliers, and Normality

To test linearity between employee performance (dependent variable) and

employee engagement and job satisfaction (independent variables) collectively,

studentized residuals were plotted against unstandardized predicted values. The degree to

which a change in the dependent variable is related to the change in the independent

variables determines linearity and is depicted when the data follow a straight line

(Saunders et al., 2016). Figure 3 shows a linear relationship between the dependent and

independent variables as these data follow a straight line.

Figure 3

Linearity Between Study Variables

Furthermore, Figure 3 was used to determine homoscedasticity. Homoscedacity is

the assumption that the variance is equal for all dependent variable values (Flora &

Ocana, 2022). Figure 3 was assessed by visual inspection, and the residuals were found to

be homoscedastic as the residuals have constant variance (Flores & Ocana, 2022). This

means that the variance is equal for all dependent variable values.

Figure 4 shows a somewhat linear relationship between job satisfaction (Global

Satisfaction Mean) and employee performance (Performance Mean). The data shown in

Figure 4 follow a straight line that is slightly positive. Although Figure 4 shows a partial

correlation, the R value was .636, indicating a positive relationship between job

satisfaction and employee performance. Additionally, the R

value is approximately .40.

The closer this value is to 1, the stronger the correlation (Khedidja & Moussa, 2022); this

lesser value of .40 may contribute to the somewhat linear relationship depicted in Figure

Figure 4

Linearity between Employee Performance and Job Satisfaction

Figure 5 depicts a linear relationship between employee engagement ( Means) and

performance. The R value was .676, indicating a positive relationship between job

satisfaction and employee performance. Additionally, the R

value is approximately .46,

slightly greater than that in Figure 4. This increase contributes to the more defined

relationship shown in Figure 5.

Figure 5

Linearity Between Employee Performance and Employee Engagement

Outliers are standardized residuals with values greater than three standard

deviations or less than -3 standard deviations (Ugah et al., 2021). SPSS was used to

evaluate the presence of outliers, leverage points, and influential points. Variable SDR_1

is the studentized deleted residual, which is the deleted residual divided by its estimated

standard deviation. Studentized residuals are more effective for identifying outliers

because they quantify how large residuals are in standard deviation units (Arimie et al.,

2020). Therefore, the values of SDR_1 were assessed to determine if any of the cases had

a standardized residual value greater than ± standard deviations. Only one case was

identified as having a value greater than three standard deviations, which was 4.544. It

was noted that this case was considered an outlier; however, the case did not demonstrate

high leverage or a high level of influence. Essentially, leverage values less than .2 are

deemed safe, .2 to .5 are risky, and .5 and above are considered dangerous (Laerd, 2015).

Cook’s Distance is a measure of influence and was used to determine if any cases in this

study were found to have high levels of influence. Generally, any case with a Cook’s

Distance value greater than 1 should be investigated (Laerd, 2015; Menzel et al., 2017).

No cases in this study were found to have high leverage or high levels of influence.

A Q-Q plot was used to evaluate normality. If the residuals are aligned with the

diagonal line, the normality assumption can be supported (Green & Salkind, 2017).

Examination of the Q-Q plot, as shown in Figure 6, indicates that it may violate the

assumption of normality. Non-normal data can be transformed to establish normality. The

data was approximately normally distributed. Although the points on the Q-Q Plot are not

perfectly aligned, the residuals are close enough to normal to proceed with the analysis as

multiple regression analysis is robust to non-normality (Kneif & Forstmeier, 2020). A

Shapiro-Wilk Test of Normality was also used to determine if the normality assumption

was violated. Table 4 shows that p < .05, indicating normal distribution. Furthermore,

Central Limit Theorem suggests that a sample size of 30 or more, in which N = 100 for

this study, is sufficiently large, and normality becomes less critical (Mordkoff, 2016;

Zhang et al., 2021).

Figure 6

Normal Q-Q Plot of Studentized Residuals

Table 4

Tests for Normality

Variable

Kolmogorov-Smirnov

Shapiro-Wilk

Statistic

Sig.

Statistic

Sig.

Employee

Engagement

.149 100

<.001 .870 100 <.001

Employee

Performance

.165 100

<.001 .879 100 <.001

Job Satisfaction

.230

100

<.001

.880

100

<.001

Multicollinearity

Multicollinearity occurs when two or more independent variables are highly

correlated (Ali et al., 2019; Byrne et al., 2017; Laerd, 2015). Multicollinearity was

evaluated by viewing the tolerance Variance Inflation Factor (VIF). The VIF measures

the amount of multicollinearity between variables in a multiple regression analysis

(Laerd, 2015). Multicollinearity is present when the tolerance values are less than

.1which is a VIF greater than 10. Generally, a VIF between 1 and 3 indicates some

degree of multicollinearity. A VIF between 3 and 5 indicates moderate multicollinearity

and may not require correcting (Yen et al., 2021). Lastly, a VIF higher than 5 indicates a

severe issue, and steps should be taken to overcome the multicollinearity problem (Singh

& Kumar, 2021; Thompson et al., 2017). The tolerance value for this study was .306, and

the VIF was 3.269. Although the VIF indicates a moderate degree of multicollinearity,

the tolerance value is greater than .1. Therefore, it can be assumed that the independent

variables, job satisfaction and employee engagement, are not highly correlated with each

other, and no violation of the multicollinearity assumption was evident.

Inferential Statistical Analysis

A multiple linear regression analysis, α = .05 (two-tailed), was conducted to

examine the efficacy of employee engagement and job satisfaction in predicting

employee performance. The independent variables included in the model were employee

engagement and job satisfaction. The dependent variable was employee performance.

The null hypothesis (H

) was: There is no statistically significant relationship between

employee engagement, job satisfaction, and employee performance among employees

within the federal government. The alternative hypothesis (H

) was: There is a

statistically significant relationship between employee engagement, job satisfaction, and

employee performance among employees within the federal government. Preliminary

analyses were conducted to assess whether the assumptions of multicollinearity, outliers,

normality, linearity, homoscedasticity, and independence of residuals

were met; no

serious violations were noted (see Tests of Assumptions). The model was able to

significantly predict employee performance: F(2,97) = 43.836, p < .001, R

= .475.

The R

(.475) value indicated that approximately 47.5% of the variations in

employee performance are accounted for by the linear combination of the predictor

variables (employee engagement and job satisfaction). In the final model, the

independent variable employee engagement was statistically significant (t = 3.594, p <

.001, β = .504), accounting for a higher contribution to the model than job satisfaction

based on theβ values. Job satisfaction was not significant (t = 1.788, p > .05, β = .225).

The final predictive equation was: Employee Performance = 1.113 + .225 (Employee

Satisfaction) + .504 (Employee Engagement).

Cronbach’s alpha is used to estimate variance between survey responses to

determine consistency (Menon et al., 2021). Cronbach’s alpha assesses how one or more

items achieve validity. Values greater than .9 are considered excellent, .7 are acceptable,

.6 is questionable, and any value less than .5 is unacceptable (Menon et al., 2021). The

Cronbach’s alpha was measured for each scale used in this study. The Cronbach’s alpha

for employee engagement, which includes 15 questions, was .965. The Cronbach’s alpha

for job satisfaction was .877, which included four questions, and the Cronbach’s alpha for

employee performance was .847, which included three questions. Based on Cronbach’s

alpha values, each scale had a high level of internal consistency (Menon et al., 2021). I

also conducted a factor analysis to determine the relationship between the items that

make up each variable. The Correlation Matrix Determinant for this study was .161 and a

p-value = < .001 for each independent variable. A Kaiser- Meyer-Olkin (KMO) = .705

and Bartlett’s Test p-value = < .001, confirming the validity and reliability of the

measures used and the results (Flores & Ocana, 2022).

SPSS was also used to determine the Pearson Correlation Coefficient, which

measures dependency between two variables (Chen & Wu, 2014; Green & Salkind,

2017). The Pearson Correlation Coefficient values range between -1 and 1, representing a

negative to a positive relationship. Employee performance had a .676 relationship with

employee engagement and a .636 relationship with employee satisfaction indicating a

strong positive relationship.

Model Fitting

The multiple correlation coefficient was used to determine whether the multiple

regression model was a good fit for the data. The multiple correlation coefficient (R) is

the Pearson coefficient between the predicted values and the actual values of the

dependent variable. R measures the strength of the linear correlation between the

independent and dependent variables. The measure ranges from 0 to 1, with the linear

association being stronger as the value is closer to 1 and a perfectly linear association at

1. The R value is a measure of strength and can indicate the goodness of fit with a value

ranging from 0 to 1 (Laerd, 2015). The R value in this study was .689, which means a

strong positive linear association.

The coefficient of determination (R

) indicates the proportion of variance in the

dependent variable explained by the independent variable. The adjusted R

value provides

a value that would be expected in the population and an estimate of the effect size and

assesses the overall model fit. In this study, R

= .475 with an adjusted R

of .464

indicates that approximately 47.5% of the variability of the dependent variable is

explained by the addition of both independent variables, as shown in Table 5.

Table 5

Multiple Regression Model Summary

Model Summary

Model

Adjusted R

SE of the Estimate

Durbin-

Watson

.689

.475

.464

.63370

1.891

a. Predictors: (Constant), Global Satisfaction Mean, Employee Engagement Index Mean

b. Dependent Variable: Performance Mean

Statistical Significance of the Model

Table 6 is the ANOVA table showing the model's statistical significance. As

shown in Table 6, p < .001, which indicates a statistically significant result. This result

suggests that the overall model is better at predicting the dependent variable than the

mean model and is a statistically significantly better fit to the data (Habiger, 2015;

Turhan, 2020). Therefore, employee engagement and job satisfaction statistically and

significantly predicted employee performance, F(2, 97) = 43.836, p < .001.

The R

(.475) value indicated that approximately 47.5% of variations in employee

performance are accounted for by the linear combination of the predictor variables

(employee engagement and job satisfaction). The R

(.475) value indicated that

approximately 47.5% of the variation in employee performance is accounted for by the

linear combination of the predictor variables (employee engagement and job satisfaction).

In the final model, the independent variable employee engagement was statistically

significant (t = 3.594, p < .001, β = .504), accounting for a higher contribution to the

model than job satisfaction based on the β values. Job satisfaction was not significant (t =

1.788, p > .05, β = .225). The final predictive equation was: Employee Performance =

1.113+.225 (Employee Satisfaction) + .504 (Employee Engagement).

Table 6

ANOVA Summary

ANOVA

Model Sum of

Squares

df Mean Square F Sig.

Regression

35.207

17.604

43.836

<.001

Residual

38.953

.402

Total

74.160

a. Dependent Variable: Performance Mean

b. Predictors: (Constant), Global Satisfaction Mean, Employee Engagement Index

Mean

Table 7

Coefficients

Employee Engagement

The slope coefficient for employee engagement was .504, indicating that for each

1-point increase for employee engagement, employee performance increases by

approximately .504. Thus, employee performance increases as employee engagement

increases. The squared semi-partial coefficient (sr

) is an estimate of how much of the

variance of the dependent variable is predicted by independent variables (Green &

Salkind, 2017). The sr

value for employee engagement (independent variable) is .343,

indicating that 34.3% of the variance in employee performance (independent variable) is

accounted for by employee engagement when job satisfaction (dependent variable) is

controlled.

Job Satisfaction

The slope coefficient for job satisfaction was .225, indicating that for each 1-point

increase in job satisfaction, employee performance increases by approximately .225.

Thus, employee performance increases as job satisfaction increases. The sr

value for job

satisfaction is .179, indicating that 17.9% of the variance in employee performance is

accounted for by job satisfaction when employee engagement is controlled. When

employee engagement isn’t controlled, the sr

value for job satisfaction is .636, indicating

that when employee engagement is not controlled, job satisfaction accounts for 63.6% of

the variance of performance is accounted for by job satisfaction.

Partial Correlations

Partial correlations measure the strength and direction of a linear relationship

between two continuous variables while controlling for another variable (Li &

Wiedermann, 2020). Although the relationship between job satisfaction was not

significant, a positive correlation between job satisfaction and employee performance

was still identified. Furthermore, Table 8 shows a statistically significant relationship

between job satisfaction and employee engagement. A partial correlation was used to

determine how job satisfaction results in increased employee performance, with

employee engagement being the control variable. As shown in Table 8, the correlation

between job satisfaction and employee performance (r = .636, p < .001) is statistically

significant when employee engagement is not controlled. However, when employee

engagement is controlled, the correlation between job satisfaction and employee

performance (r = .179, p = .077) becomes statistically insignificant, indicating that

employee engagement is a mediating variable. Mediating variables are caused by the

independent variables and explain job satisfaction's role in influencing employee

performance.

Table 8

Correlations of Study Variables While Controlling for Employee Engagement

Sobel Test for Mediation

The Sobel test determines whether a variable mediates the effect of independent

variables on dependent variables (Neiheisel, 2018). A mediator variable dominates the

significant relationship between the independent and dependent variables. The Sobel test

statistic was conducted to determine whether employee engagement (independent

variable) mediates the effect of job satisfaction (independent variable) on employee

performance (dependent variable). The Sobel test statistic was determined by using the

following formula:

z = (ab)/√(b

)+(a

)

z = (.747*.504)/ √((.504

)(.050

))+((.747

)(.140

))

= (.376)/ √((.254016)(.0025))+((.558009)(.0196))

= (.376)/ √ (.00063504)+(.0109369764)

= (.376)/ √(.0115720164)

= (.376)/ (.1075)

= 3.5

The final p-value is p = (1-.99977)(2) = .00046. It can be determined that the mediation

is significant via the Sobel Test as p < .05. Essentially, the relationship between job

satisfaction (independent variable) and employee performance (dependent variable) is

mediated by employee engagement (independent variable).

Frequency Tests

Frequency tests were conducted to determine how often specific answers were

given for the particular questions that make up the dependent and independent variables.

Tables 9-11 include the frequency test findings.

Table 9

Analysis of Response Frequencies on Employee Engagement

Question

Response

Frequency

Percent

3. I feel encouraged to come up with new

and better ways of doing things.

Strongly Disagree

7.0

Disagree

8.0

Neither Agree nor Disagree

13.0

Agree

38.0

Strongly Agree

34.0

4. My work gives me a feeling of personal

accomplishment.

Strongly Disagree

3.0

Disagree

1.0

Neither Agree nor Disagree

13.0

Agree

47.0

Strongly Agree

36.0

6. I know what is expected of me on the

job.

Strongly Disagree

4.0

Neither Agree nor Disagree

9.0

Agree

46.0

Strongly Agree

41.0

11. My talents are used well in the

workplace.

Strongly Disagree

5.0

Disagree

9.0

Neither Agree nor Disagree

11.0

Agree

49.0

Strongly Agree

26.0

12. I know how my work relates to the

agency's

goals.

Strongly Disagree

1.0

Disagree

5.0

Neither Agree nor Disagree

2.0

Agree

48.0

Strongly Agree

44.0

47. Supervisors in my work unit support

employee development.

Strongly Disagree

5.0

Disagree

4.0

Neither Agree nor Disagree

8.0

Agree

45.0

Strongly Agree

38.0

(table continues)

Question

Response

Frequency

Percent

48. My supervisor listens to what I have to

say.

Strongly Disagree

3.0

Disagree

5.0

Neither Agree nor Disagree

5.0

Agree

39.0

Strongly Agree

48.0

49. My supervisor treats me with respect.

Strongly Disagree

2.0

Disagree

3.0

Neither Agree nor Disagree

4.0

Agree

38.0

Strongly Agree

53.0

51. I have trust and confidence in my

supervisor.

Strongly Disagree

4.0

Disagree

6.0

Neither Agree nor Disagree

8.0

Agree

30.0

Strongly Agree

52.0

52. Overall, how good a job do you feel is

being done by your immediate supervisor?

Very Poor

4.0

Poor

3.0

Fair

7.0

Good

39.0

Very Good

47.0

53. In my organization, senior leaders

generate high levels of motivation and

commitment in the workforce.

Strongly Disagree

9.0

Disagree

7.0

Neither Agree nor Disagree

12.0

Agree

48.0

Strongly Agree

24.0

54. My organization's senior leaders

maintain high standards of honesty and

integrity

Strongly Disagree

7.0

Disagree

4.0

Neither Agree nor Disagree

13.0

Agree

42.0

Strongly Agree

34.0

56. Managers communicate the goals of the

organization.

Strongly Disagree

6.0

Disagree

7.0

Neither Agree nor Disagree

6.0

Agree

46.0

Strongly Agree

35.0

(table continues)

Question

Response

Frequency

Percent

60. Overall, how good a job do you feel is

being done by the manager directly above

your immediate supervisor?

Very Poor

5.0

Poor

3.0

Fair

14.0

Good

36.0

Very Good

42.0

61. I have a high level of respect for my

organization’s senior leaders.

Strongly Disagree

5.0

Disagree

3.0

Neither Agree nor Disagree

16.0

Agree

40.0

Strongly Agree

36.0

Table 10

Analysis of Response Frequencies for Job Satisfaction

Question

Response

Frequency

Percent

40. I recommend my organization as a good place to

work.

Strongly Disagree

5.0

Disagree

5.0

Neither Agree nor

Disagree

10.0

Agree

43.0

Strongly Agree

37.0

69. Considering everything, how satisfied are you with

your job?

Strongly Dissatisfied

3.0

Dissatisfied

9.0

Neither Satisfied nor

Dissatisfied

6.0

Satisfied

47.0

Very Satisfied

35.0

70. Considering everything, how satisfied are you with

your pay?

Strongly Dissatisfied

4.0

Dissatisfied

13.0

Neither Satisfied nor

Dissatisfied

12.0

Satisfied

46.0

Very Satisfied

25.0

71. Considering everything, how satisfied are you with

your organization?

Strongly Dissatisfied

4.0

Dissatisfied

11.0

Neither Satisfied nor

Dissatisfied

7.0

Satisfied

44.0

Very Satisfied

34.0

100

Table 11

Analysis of Response Frequencies for Employee Performance

Question

Response

Frequency

Percent

15. My performance appraisal is a fair

reflection of my performance

Strongly Disagree

3.0

Disagree

10.0

Neither Agree nor Disagree

16.0

Agree

34.0

Strongly Agree

37.0

16. I am held accountable for achieving

results.

Strongly Disagree

2.0

Disagree

1.0

Neither Agree nor Disagree

5.0

Agree

50.0

Strongly Agree

42.0

19. In my most recent performance

appraisal, I understood what I had to do

to be rated at different performance

levels (for example, Fully Successful,

Outstanding)

Strongly Disagree

4.0

Disagree

7.0

Neither Agree nor Disagree

13.0

Agree

42.0

Strongly Agree

34.0

Results and Conclusions of Data Analysis

A standard multiple linear regression analysis was run to examine if a statistically

significant relationship existed between employee engagement, job satisfaction, and

employee performance. The independent variables were employee engagement and job

satisfaction. The dependent variable was job performance. The null hypothesis was there

is no statistically significant relationship between employee engagement, job satisfaction,

and employee performance. The alternative hypothesis was that there is a statistically

significant relationship between employee engagement, job satisfaction, and employee

performance. Assumptions of multicollinearity, normality, linearity, outliers,

homoscedasticity, and independence of errors were tested to identify potential violations.

101

The tests of assumptions identified a possible violation of normality; however, I

continued with the regression analysis as the sample size was large, and the residuals

were close enough to normal to proceed with the analysis as multiple regression analysis

is robust to non-normality (Kneif & Forstmeier, 2020).

The model was able to significantly predict employee performance: F(2,97) =

43.836, p < .001. Employee engagement is statistically significantly associated with

employee performance in the federal government, which is in line with the alternative

hypothesis. The correlation between job satisfaction was not statistically significantly

associated with employee performance within the federal government; however, an

analysis of partial correlations determined that employee engagement is a mediating

variable between job satisfaction and employee performance. Furthermore, the Sobel Test

for Mediation determined that the mediation between job satisfaction and employee

performance via employee engagement was statistically significant.

The 2019 FEVS, Governmentwide Management Report, indicates that employee

engagement and performance management are foundational to achieving strategic

management for building and sustaining the 21

-century workforce. However, leaders

within the federal government do not understand the relationship between employee

engagement, job satisfaction, and employee performance among employees within the

federal government. Furthermore, leaders in the federal government are unaware of the

influencers of employee satisfaction and engagement or how to measure them correctly.

According to the 2019 FEVS, the average score for employee engagement was 68%, as

indicated by the EEI. The framework used for EEI assumes that organizational conditions

102

will lead to feelings of engagement. The FEVS assesses elements such as effective

leadership, meaningful work, and learning opportunities (OPM, 2019). While these

elements contribute to engagement, they are not directly correlated to employee

engagement. These elements are more related to motivation which correlates with job

satisfaction (Adil & Hamid, 2019; Amabile & Pratt, 2016; Byre et al., 2017; Herzberg et

al., 1959).

Employee engagement is measured by the degree individuals immerse themselves

in their work roles. Positions that allow employees to work autonomously, use their

preferred skills and talents, and express themselves through their work result in increased

performance as it will enable employees to contribute energy in physical, cognitive, and

emotional aspects. As shown in Figure 7, Psychological engagement can occur in two

dimensions, emotionally and cognitively, and engagement can be experienced in any one

of these dimensions at any given time. Employees willing to exert more effort and go

above and beyond are physically engaged, and those aware of the mission and their role

are cognitively engaged. Meaningfulness, safety, and availability influence engagement

(Balkrushna et al., 2018; Kahn, 1990; Risley, 2020; Tong et al., 2019; Tracey et al.,

2014).

103

Figure 7

Employee Engagement Influencers

Note. From “An Investigation of The Relationship Among Honesty-Humility, Authentic

Leadership and Employee Engagement,” by Simone Barreto de Azevedo Meskelis, 2018.

https://www.researchgate.net/figure/Kahn-1990-Model-of-Employee-

Engagement_fig2_326262753

When employees clearly understand their role and can work autonomously while

implementing creativity, they experience meaningfulness in their roles and are often more

engaged. Additionally, those employees that find their jobs lack meaningfulness are more

likely to be absent and leave their position altogether. Organizational leaders should

monitor employee perceptions of meaningfulness as this can predict issues, such as gaps

in skillsets, and identify training needs. Safety is determined by employees' perception of

being able to express themselves without negative consequences. Employees’ perceptions

of safety are influenced by leadership, management style, and organizational norms.

For employees to feel safe, a learning environment must exist where employees

can make mistakes and are provided an opportunity to learn. A safe environment also

104

encourages employees to develop innovative ideas and approaches because they are not

afraid of negative repercussions. Increased safety also results in increased trust in

leadership and consequently increases the influence leaders have over employees.

Ultimately, a safe environment includes support while also providing clarity and

reinforcement. Managers and leaders should develop methods of promoting a safe

environment for employees. Lack of safety can result in a lack of performance because

employees are unwilling to improve skills, inconsistent work quality, and unpredictable

behaviors from employees. Lastly, knowledge sharing is influenced by perceptions of

safety. Knowledge safety helps alleviate the costs associated with providing training, as

knowledge sharing presents the opportunity to leverage resources. Ultimately, safety is

critical for organizational performance as it contributes to individual performance by

increasing employee confidence which is an influencer of availability.

Availability is driven by employees’ confidence in their roles and is experienced

when employees have physical, emotional, or psychological resources to personally

engage at a particular moment (Kahn, 1990). This is relevant to both work and non-work

experiences. Physical energy, emotional energy, individual insecurity, and issues in one’s

personal life all impact psychological availability (Ali et al., 2019; Bergdahl; 2020; Cao

& Chen, 2019; Kahn, 1990; Kwan & Park, 2019). Employers can help improve

availability by providing efficient resources to employees that can help alleviate stress,

tensions, and insecurities. Ensuring that employees are not overworked is essential to

availability. Leaders should be mindful of how much their employees are working.

Noticing things such as employees may be working more hours, taking longer to

105

complete tasks, and inconsistency in the quality of work may indicate a lack of

availability and may also predict employee burnout. Employees with psychological

availability have the physical energy and resources to help others in the organization to

accomplish extra tasks and requirements and the cognitive resources to help generate new

ideas (Fletcher, 2019; Kahn, 1990; Kultalahti & Viitala, 2014; Nikolova et al., 2020; Smit

et al., 2016; Upadyaya & Salmela-Aro, 2020), creating a more efficient work

environment (Naujokaitien et al., 2015)

Without understanding what influences employee engagement, leaders in the

federal government cannot adequately measure or identify areas of improvement. The

elements included in the 2019 FEVS EEI do not capture the factors influencing employee

engagement, supporting the indications that a prominent issue regarding engagement is

the lack of a consistent definition which causes fundamental discrepancies. In this study,

there is a statistically significant relationship between employee engagement and

performance. Increased engagement can yield increased employee performance, while

lack of engagement can lead to elevated stress, increased workloads, and eventually

burnout. Disengaged employees may also struggle to complete tasks and not strive to

advance or take on more challenging assignments. Failure to adequately measure

engagement can lead to overworked employees, lack of innovative ideas, decreased

efficiency, and an overall decrease in performance (Barden, 2017; Byrne, 2015; Dewing

& McCormack, 2015; Gruman & Saks, 2011; Kular et al., 2008; St. Aimee, 2020).

Engagement is the degree to which individuals immerse themselves in their work role,

suggesting that people use varying degrees of themselves, physically, cognitively, and

106

emotionally in the workplace (Dahl., 2019; Gupta & Sharma, 2016; Kahn, 1990). This

means that levels of engagement can change at any given time.

It is important to note that the findings of this study suggest that employee

engagement serves as a mediator variable between job satisfaction and employee

performance, as shown in Figure 8. Without employee engagement, job satisfaction does

not significantly impact performance.

Figure 8

Mediator Variable

The Global Satisfaction Index (GSI) was used to represent job satisfaction in this

study. The GSI assesses employees' satisfaction with their job, pay, organization, and

willingness to recommend their organization as a good place to work (OPM, 2019). The

GSI includes questions 40, 69, 70, and 71 (see Appendix B). The questions included

indicate Hygiene Factors, and the data captured in the GSI does not actually reflect

satisfaction levels but instead levels of dissatisfaction. Furthermore, the FEVS does

identify questions that correlate to satisfaction; however, the possible responses to these

Employee

Engagement

Employee

Performance

Job

Satisfaction

107

questions range from very satisfied to highly dissatisfied. Figure 9 depicts the influencers

of satisfaction and dissatisfaction. Satisfaction and dissatisfaction are not opposites and

should not be measured on the same continuum (Alshmemri et al., 2017; Herzberg,

1959).

Figure 9

Motivation and Hygiene Factors

Note. From “Two-Factor Theory of Herzberg” by Skazal Chandra Barman, 2015. https://

https://kazalbarman.wordpress.com/2015/06/22/herzberg-two-factor-theory/

Job satisfaction describes the degree to which an employee is satisfied with their

work, and the level of job satisfaction reflects their willingness to perform optimally. Job

satisfaction is influenced by both intrinsic and extrinsic motivators known as Motivator

Factors and Hygiene Factors, respectively. Motivator factors represent satisfaction levels

and make up for positive attitudes for employee engagement and job satisfaction. An

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increase in motivation factors increases an employee's job satisfaction, whereas a

decrease results in no satisfaction.

Hygiene factors are extrinsic motivators and are referenced as dissatisfiers, and

the factors measure levels of dissatisfaction. The observation that engagement increases

as satisfaction decreases support the Herzberg Theory (1959) as satisfaction, as

represented in this study, is determined by the use of Hygiene factors. Low hygiene

factors result in increased levels of dissatisfaction, whereas positive hygiene factors result

in reduced dissatisfaction. The opposite of dissatisfaction is not satisfaction, but instead

no dissatisfaction (Alshmemri et al., 2017; Herzberg, 1959). As mentioned previously in

the study, it should be noted that employees who do not experience hygiene factors are

not necessarily unsatisfied with their job or role; however, they are experiencing

increased levels of dissatisfaction (Yadav, 2019; Herzberg, 1959).

Job satisfaction and dissatisfaction are indicators of an employee’s willingness to

perform. High levels of satisfaction and low levels of dissatisfaction relate to employee

engagement. The findings of this study suggest that employee engagement is a mediator

variable, which supports both Kahn’s engagement theory (1990) and the Herzberg two-

factor theory (1959). Motivators increase satisfaction, and although motivation and

engagement are two different concepts, they are still related. Employees' motivation

levels can influence how easily they can be engaged (Azevedo et al., 2020; Adil &

Hamid, 2019; Byrne et al., 2017; Gera et al., 2019). Employees with high satisfaction

levels are willing to perform effectively in their role, complete tasks promptly, take less

time off, and enjoy their work overall. Lower levels of satisfaction and increased

109

dissatisfaction may result in employees being less willing to perform most optimally in

their role.

Additionally lower satisfaction and dissatisfaction can result in turnover.

Employee engagement is measured by how immersed an employee gets in their role.

Suppose an employee is not satisfied or dissatisfied and is unwilling to perform

optimally. In that case, it can be assumed that that employee will not be fully immersed in

their role, indicating a lack of engagement.

Disengaged employees cost U.S. businesses approximately $550 billion annually

in lost productivity (Aslam et al., 2018; Kang & Busser, 2018). Furthermore, disengaged

employees can lead to higher turnover rates, decreased quality of customer service, less

efficient practices, and increased stress levels (Bhatt & Sharma, 2019; Gupta & Sharma,

2016; Jugdev et al., 2018; Risley, 2020; Seriki et al., 2020). When employees are

engaged, they are willing to try innovative approaches, take on challenging work, and

experience greater trust in the workplace. They ultimately increase employees’ dedication

to reaching organizational goals. Empirical research has shown that leaders who

emphasize improving engagement and satisfaction increase employee performance and

commitment (Concepcion, 2020; Gupta & Sharma, 2016; Popli & Rizvi, 2015). Sample

questions related to employee intent to stay, motivation to come up with innovative

solutions, and trust in the workplace were taken from the 2019 FEVS and used to

compare the results against job satisfaction and employee engagement. The results are

represented in Figures 10–13.

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Figure 10 shows a positive relationship between employee satisfaction,

engagement, and willingness to develop new ideas among Federal Government

employees. Employees with increased satisfaction and engagement are more encouraged

to create innovative systems and practices. The information presented positively

contributes to performance as employees try to improve and work more efficiently.

Figure 10

I Feel Encouraged to Come up with New Ways of Doing Things

Note. The information in Figure 10 demonstrates that the more satisfied and engaged an

employee is, the more willing and encouraged they are to come up with new innovative

ideas. This supports the relationship between job satisfaction, employee engagement, and

performance.

Figure 11 provides insight into employees' willingness to go above and beyond to

meet agency needs.

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Figure 11

When Needed I am Willing to Put in the Extra Effort to get a Job Done

Note. As employees are more satisfied and engaged, the willingness to go above and

beyond to complete tasks increases. This supports the findings of this study; the more

satisfied employees are, the more willing they are to increase work efforts, which, in turn,

increases employee engagement and employee performance.

Figure 12 provides information on the importance of developing trust between

employees and supervisors. Employees with less trust in their leadership are less satisfied

and less engaged. This presents the opportunity for a decrease in performance. Leaders in

the federal government could use this information as an indicator of lacking performance

and determine what is needed to increase trust between employees and supervisors.

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Figure 12

I Have Trust and Confidence in My Supervisor

Note. Employees who demonstrate lower levels of trust and confidence in their

supervisors are less engaged and less satisfied. The findings presented are supported by

Kahn’s Engagement theory (1990). Trust in leadership is a characteristic of a safe

environment that influences engagement levels.

Figure 13 shows that the less satisfied and engaged employees are, the more likely

they are to leave their employers.

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Figure 13

Are You Considering Leaving your Organization and Why?

Note. Approximately 60% of employees are considering leaving their job. Employees

with higher levels of satisfaction and engagement are more willing to stay with their

organization. Those with moderate scores are looking to take another job within the

federal government, and those employees looking to leave the federal government

altogether represent the lower range of employee satisfaction and engagement.

Federal employers would benefit from understanding engagement and

satisfaction's influence on intent to leave. Furthermore, by understanding the influences

of employee engagement and job satisfaction, leaders can better identify the

organizational issue impacting employee engagement and job satisfaction. These data can

also predict performance as the agencies will suffer a loss in productivity, engagement,

and overhead when an employee quits, potentially creating an overall cost of between

100% and 200% (Society for Human Resource Management [SHRM], 2019). Replacing

employees who quit can cost an organization approximately six to nine months of their

salary. Ultimately, job satisfaction and employee engagement impact employee

performance, impacting organizational performance.

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The results of the multiple linear regression show a p-value less than .05 showing

a statistically significant relationship between employee engagement (the independent

variable) and employee performance (the dependent variable) in the federal government.

Therefore, employee engagement and job satisfaction statistically significantly predicted

employee performance: F(2, 97) = 43.836, p < .0001, R

= .475 with an adjusted R

.464. The R

value indicated that employee engagement and job satisfaction explained

approximately 47% of variations in employee performance are accounted for by the

linear combination of the independent variables, employee engagement, and job

satisfaction. Employee engagement was statistically significant (t = 3.594, p < .001, β =

.504), accounting for a higher contribution to the model than job satisfaction (t = 1.788, p

> .05, β = .225) based on the β value of .504. This value represents an approximate 50%

variability of employee performance as opposed to job satisfaction which represents a

22% variability of employee performance. Job satisfaction was not significant (t = 1.788,

p > .05, β = .225). As shown in Table 6, The residual degrees of freedom = 97 and the

regression degree of freedom = 2. The sum of squares of the regression = 35.207, and the

sum of squares for the residual = 38.953. I conducted a Q-Q plot of normality for job

satisfaction, engagement, and employee performance. The diagonal line of the Q-Q plot

represents normality within the data set, and the individual points represent the data

results. The data should run in a straight diagonal line in a Q-Q normality plot with

minimal deviation. The results are represented in Figures 14–17.

115

Figure 14

Normal Q-Q Plot of Studentized Residual

Figure 15

Q-Q Normality Plot of Employee Engagement

116

Figure 16

Q-Q Normality Plot of Employee Satisfaction

Figure 17

Q-Q Normality Plot of Employee Performance

117

Recommendations for Action

The results of this study determined that there is a statistically significant

relationship between employee engagement and employee performance. Furthermore, it

was found that job satisfaction, as measured by the GSI, did not directly influence

employee performance; however, employee engagement serves as a mediating variable.

Leaders in the federal government would benefit from researching what elements affect

satisfaction and employee engagement and to what degree. As indicated previously in the

study, the EEI does not adequately represent the factors influencing engagement. Instead,

it includes questions that relate to satisfaction. Employee engagement is the degree to

which employees immerse themselves in their work. It consists of a positive work-related

state of mind characterized by dedication, vigor, and absorption (Gera et al., 2019;

Schaufeli et al., 2016). Kahn’s engagement theory (1990) states that meaningfulness,

safety, and availability, influence employee engagement levels. With this understanding,

leaders in the federal government can invest in strategies that positively influence

meaningfulness, safety, and availability. Furthermore, the FEVS can be used to identify

low-performing influencers.

Federal leaders could benefit by grouping together questions in the FEVS related

to the factors that directly influence employee engagement. Assessing the influencers can

allow leaders to identify the overarching issue that may be negatively impacting

engagement and use that information to develop strategies or innovative ideas to address

the issue. Additionally, focusing more on the influencers can ensure that leaders manage

and accurately measure and monitor engagement.

118

Another recommendation for action would be to investigate the factors that

influence satisfaction. Federal government leaders should understand that satisfaction and

dissatisfaction are not opposites and, therefore, are not measured on the same continuum.

As it stands, the GSI is comprised of questions related to Hygiene factors, which measure

dissatisfaction. Similar to the suggestion for measuring employee engagement, leaders in

the federal government would benefit by learning what factors are considered hygiene

factors and what factors are considered motivators. By determining motivators and

hygiene factors, leadership can decide if the lack of satisfaction is based on intrinsic or

extrinsic factors.

Furthermore, understanding whether employees are not satisfied versus

dissatisfied will give leadership insight into whether potential areas for improvement are

related to job conditions or the work itself. Often if an issue arises regarding job

satisfaction, employers will attempt to address the issue when employees complain about

hygiene factors. Hygiene factors and motivator factors influence employee satisfaction

differently. Motivation factors contribute to an organization's long-term success, whereas

hygiene factors contribute to short-run success. Satisfying hygiene requirements is

insufficient to improve an organization's productivity (Herzberg, 1987). Lack of hygiene

and motivator factors can increase dissatisfaction; however, motivator factors do not

decrease dissatisfaction but can increase and decrease satisfaction. Essentially,

eliminating causes of dissatisfaction will not result in satisfied employees, as this will not

create satisfaction, but instead, employees that have no dissatisfaction. Addressing

hygiene factors does not enhance performance. Addressing hygiene factors without

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addressing or improving motivators will calm the workforce but will not motivate them

to improve performance.

To motivate employees to improve performance, employers must create

conditions for satisfaction. Focusing on areas that contribute to job enrichment will make

employees more willing to perform efficiently and go above and beyond their duties.

Those employees with no dissatisfaction are not likely to overperform but will perform at

the basic maintenance level. The FEVS can be used to identify which factors are lacking.

Identifying the lacking factors will allow leaders to utilize resources to address the causes

of lowered satisfaction adequately.

Highly satisfied employees are approximately 18% more productive than those

with less satisfaction, which positively impacts performance. Employees with high

satisfaction levels are more inclined to be dedicated to their organization and are less

likely to leave their jobs, resulting in organizations retaining quality employees. By

increasing satisfaction levels, employees will be more likely to develop innovative

strategies. They will be willing to be involved in operations necessary to meet the

organization's mission and goals—increased satisfaction results in increased productivity,

output, and optimal performance. Alternatively, increased levels of dissatisfaction may

result in decreased output. Increased dissatisfaction and low motivation levels result in

slowed productivity, reduced output, and declining quality of work. Furthermore, lower

levels of satisfaction result in decreased willingness to improve knowledge or go beyond

the minimal expectations of the job. Increased willingness, in turn, positively influences

120

employee engagement—increased engagement results in overall increased employee

performance.

It is important to note that satisfaction has a positive relationship with

engagement. More so, satisfaction contributes to employees’ intentions to leave and their

willingness to immerse themselves in their work roles. Although this study determined a

statistically significant relationship between employee engagement and performance, it is

vital to understand job satisfaction's influence on employee engagement. The federal

government has put a lot of emphasis on employee engagement and performance.

Leaders should realize that satisfaction influences engagement levels and emphasize the

importance of motivators and hygiene factors relating to job satisfaction. Without job

satisfaction, employees will perform at minimally successful or below minimally

successful levels. Satisfaction sets the baseline for performance levels and determines

employees' willingness to become more engaged. By improving hygiene and motivator

factors, leaders can create an environment where employees have positive attitudes and

are happy with their work, which will increase the degree to which employees will

immerse themselves in their work roles.

Communication Plan

I plan to share these findings with leaders within the federal government to help

create more effective strategies to measure and improve employee engagement and job

satisfaction as it relates to employee performance. I will also look to communicate the

findings of this study through conferences, leadership seminars, and other public means.

121

Lastly, I will seek out opportunities to share this information with leaders in the private

sector as the implications of this study are not necessarily industry specific.

Social Change Impact

Employee performance directly impacts organizational performance. To perform

efficiently, employees must have the proper resources to complete their jobs successfully.

Determining how to improve the influencers of employee performance can directly

improve employee performance and results in overall organizational performance (Paais

& Pattiruhu, 2020; Tarmidi & Arsjah, 2019). Job satisfaction and employee engagement

are both factors that influence employee performance. Employees that have increased job

satisfaction are more motivated to improve their skills. Increased capabilities result in

employees improving decision-making skills, creating more innovative ways to complete

job tasks, becoming more efficient at completing tasks, and acquiring additional skills

(Carvalho et al., 2020; Forjan et al., 2020; Kleine et al., 2019). Motivator factors and

Hygiene factors are what increase job satisfaction. Highly motivated employees are more

likely to share knowledge, improve performance, and increase their effort to help the

organization to meet its goals (Bhatt & Sharma, 2019; Byrne et al., 2017; Hejjas et al.,

2019; Lee & Rhee, 2019; Paulo da Silva & Shinyashiki, 2014).

Additionally, employees who experience low or no levels of dissatisfaction are

more likely to stay at their job, reducing turnover costs in an organization. These

employees are more trusting of their leadership. By focusing on job satisfaction and the

factors that influence job satisfaction, employers could improve employee performance

within the workforce.

122

In addition to focusing on job satisfaction, employers should focus on employee

engagement to improve employee performance. Disengaged employees display

incomplete role performances and show decreased effort in completing tasks, often

performing on autopilot. Job resources, management support, efficient technology and

equipment, and professional development opportunities influence engagement levels.

Disengaged employees cost U.S. businesses approximately $550 billion annually in lost

productivity (Aslam et al., 2018; Kang & Busser, 2018). Alternatively, highly engaged

employees tend to take fewer leave days, work approximately an additional week per

week, and are 69% less likely to leave their jobs within the next six months (Reece et al.,

2018). When employees feel they are receiving a return on investment, they are more

likely to offer their resources and perform effectively in their role. Employees with higher

engagement are more likely to provide additional time and dedication, share ideas

willingly, and utilize creativity to stimulate innovation.

This study provided evidence of a relationship between job satisfaction, employee

engagement, and employee performance, finding that the relationship between employee

engagement and employee performance is statistically significant amongst employees

within the federal government. This study identified the importance of understanding the

relationship between employee engagement, job satisfaction, and employee performance.

Furthermore, this study provided insight into what factors influence job satisfaction and

employee engagement. Implications for social change are that managers can use this

information to assess areas of improvement better when trying to increase employee

performance. The information provided in this study can be used to identify areas for

123

improvement at the team and organizational levels. Furthermore, leaders can use the

information in this study to develop programs and strategies that more accurately assess

and measure employee engagement and job satisfaction in the workforce. A more

accurate measure will help organizations focus resources and efforts to address potential

issues adequately.

Increased engagement and job satisfaction result in lower turnover, increased

quality of work, reduced costs, and knowledge sharing that improves team and

organizational performance. This study is essential as it provides insight into the

information captured in the FEVS and suggestions on how to interpret better the data

provided in the FEVS. Additionally, insight is provided on demographics such as tenure,

education, supervisory status, minority status, and the correlation between those

individuals and employee engagement and job satisfaction. The findings of this study can

assist leaders in the federal government in identifying gaps in engagement and

satisfaction based on demographics. The results of this study can also be applied to other

organizations where leaders are looking to increase employee performance.

The purpose of this study was to examine the relationship between employee

engagement, job satisfaction, and employee performance among employees within the

federal government. Based on the 2019 FEVS data (N=100), the study revealed a positive

relationship between employee engagement, job satisfaction, and performance. The

recommendations for leaders within the federal government are: (a) determine

motivational and hygiene factors, (b) determine influencers that improve the physical,

emotional, and cognitive factors of employee engagement, and (c) address issues that

124

could impact job satisfaction and engagement, and (d) redesign or develop a more

accurate measurement of employee engagement and job satisfaction with FEVS data by

regrouping questions that represent motivators, hygiene factors, and employee

engagement. These actions could contribute to increased employee performance in the

federal government.

Skills and Competencies

To create an environment conducive to impacting employee engagement and job

satisfaction, leaders in the federal government require specific skills and competencies.

Skills and competencies needed include leadership skills and competencies (Sparrow,

2015), technological skills, business acumen, emotional intelligence, problem-solving,

and collaboration (Mcdonnel & Sikander, 2017). Employee-focused approaches can lead

to a more engaged and satisfied workforce as this approach considers the needs of the

individual. Understanding how to work with others and understand and communicate

with others are essential skills when developing methods and strategies to improve

motivators for employees. Leadership skills are imperative as effective leadership

influences others to follow the organization's vision; however, this results from the trust.

Technological skills are needed to measure performance, engagement, and satisfaction

effectively. This study highlights skills and competencies that focus on employee

engagement and job satisfaction, and they can impact employee performance among

employees within the federal government.

125

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157

Appendix B: Employee Engagement Index, Global Satisfaction Index, Employee

Performance

Table B1

Employee Engagement Index

Item

Number

FEVS Question

I feel encouraged to come up with new and better ways of doing things.

My work gives me a feeling of personal accomplishment.

I know what is expected of me on the job.

My talents are used well in the workplace.

I know how my work relates to the agency's goals and priorities.

Supervisors in my work unit support employee development.

My supervisor listens to what I have to say.

My supervisor treats me with respect.

I have trust and confidence in my supervisor.

Overall, how good a job do you feel is being done by your immediate supervisor?

In my organization, senior leaders generate high levels of motivation and

commitment in the workforce.

My organization's senior leaders maintain high standards of honesty and integrity.

Managers communicate the goals and priorities of the organization.

Overall, how good a job do you feel is being done by the manager directly above

your immediate supervisor?

I have a high level of respect for my organization's senior leaders.

Note. The Employee Engagement Index is a measure of the conditions conducive to engagement. The index

consists of 15 items grouped into three subindices: Leaders Lead, Supervisors, and Intrinsic Work

Experience (FEVS, 2019).

Table B2

Global Satisfaction Index

Item

Number

FEVS Question

I recommend my organization as a good place to

work.

Considering everything, how satisfied are you

with your job?

Considering everything, how satisfied are you

with your pay?

Considering everything, how satisfied are you

with your organization?

Note. Global Satisfaction Index is a combination of four items assessing employees’ satisfaction with their

job, their pay, and their organization, plus their willingness to recommend their organization as a good

place to work (FEVS, 2019).

158

Table B3

Employee Performance Driver

Item

Number

FEVS Question

My performance appraisal is a fair

reflection of my performance

I am held accountable for achieving results

In my most recent performance appraisal, I

understood what I had to do to be rated at

the next performance level

Note. Employee performance is being measured using a composite variable consisting of items 15,16, and

19 in the 2019 FEVS, that make up the Employee Performance Driver (FEVS, 2019).