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2020

A Correlational Study of Manager-Employee Relationship, A Correlational Study of Manager-Employee Relationship,

Employee Rewards, and Employee Engagement Employee Rewards, and Employee Engagement

Hilda M. Concepcion Walden University

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Walden University

College of Management and Technology

This is to certify that the doctoral study by

Hilda M. Concepcion

has been found to be complete and satisfactory in all respects, and that any and all revisions required by the review committee have been made.

Review Committee Dr. Craig Martin, Committee Chairperson, Doctor of Business Administration Faculty

Dr. Sylnovie Merchant, Committee Member, Doctor of Business Administration Faculty

Dr. Edward Paluch, University Reviewer, Doctor of Business Administration Faculty

Chief Academic Officer and Provost Sue Subocz, Ph.D.

Walden University 2020

Abstract

A Correlational Study of Manager-Employee Relationship, Employee Rewards, and

Employee Engagement

by

Hilda M. Concepcion

MS, St. Peter’s University, 1997

BS, St. Peter’s University, 1993

Doctoral Study Submitted in Partial Fulfillment

of the Requirements for the Degree of

Doctor of Business Administration

Walden University

December 2020

Abstract

Organizational leaders are challenged with loss of productivity due to lack of employee

engagement, making employee engagement a top priority for organizational executives

worldwide. Grounded in Emerson’s social exchange theory, the purpose of this

quantitative correlational study was to examine the relationship between manager-

employee relationship and employee rewards and employee engagement. Employees (N

= 31) of a U.S. organization completed the Intrinsic Work Rewards Survey, Extrinsic

Rewards on Creativity Measure, and the Work and Well-being Survey. The results of the

multiple linear regression indicated a statistically significant relationship, F(2, 28) =

32.875, p < .001, R2 = .701. Employee rewards was the only statistically significant

predictor of employee engagement (t = 6.074, p < .001). A recommendation is for

organizational leaders to establish reward programs that address employee needs for

compensation, achievement, and development. This implications for positive social

change include the potential for employees to benefit from financial stability and well-

being. The organization may achieve higher performance and profitability, enabling the

organization to invest in job creation and community economic development.

A Correlational Study of Manager-Employee Relationship, Employee Rewards, and

Employee Engagement

by

Hilda M. Concepcion

MS, St. Peter’s University, 1997

BS, St. Peter’s University, 1993

Doctoral Study Submitted in Partial Fulfillment

of the Requirements for the Degree of

Doctor of Business Administration

Walden University

November 2020

Dedication

I would like to dedicate this study to my wonderful husband and children. I could

not have accomplished this dream without the strength and grace of God and the support

from my wonderful family.

Acknowledgments

Thank you to my husband for his encouragement and kindness. He made it

possible for me to dedicate the time to pursue my dream. I would also like to thank my

mother; she is my example of perseverance, love, and understanding. I would also like to

thank my friend Nicole for her support.

I would like to also acknowledge and thank my chair, Dr. Martin, for his support

and encouragement and my committee members, Dr. Merchant and Dr. Paluch. Thank

you for your insight and feedback.

i

Table of Contents

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

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

Section 1: Foundation of the Study ......................................................................................1

Background of the Problem ...........................................................................................1

Problem Statement .........................................................................................................2

Purpose Statement ..........................................................................................................3

Nature of the Study ........................................................................................................3

Research Questions and Hypotheses .............................................................................5

Theoretical Framework ..................................................................................................6

Operational Definitions ..................................................................................................7

Assumptions, Limitations, and Delimitations ................................................................7

Significance of the Study ...............................................................................................8

Contribution to Business Practice ........................................................................... 9

Implications for Social Change ............................................................................. 10

A Review of the Professional and Academic Literature ..............................................10

Social Exchange Theory ....................................................................................... 12

Complementary Theories ...................................................................................... 19

Management Styles ............................................................................................... 34

Employee Engagement ......................................................................................... 39

Employee Disengagement .................................................................................... 44

Summary ......................................................................................................................46

ii

Transition .....................................................................................................................47

Section 2: The Project ........................................................................................................49

Purpose Statement ........................................................................................................49

Role of the Researcher .................................................................................................49

Participants ...................................................................................................................52

Research Method and Design ......................................................................................53

Research Method .................................................................................................. 53

Research Design.................................................................................................... 54

Population and Sampling .............................................................................................55

Ethical Research...........................................................................................................58

Data Collection Instruments ........................................................................................60

Data Collection Technique ..........................................................................................64

Data Analysis ...............................................................................................................66

Study Validity ..............................................................................................................71

Internal Validity .................................................................................................... 71

Statistical Conclusion Validity ............................................................................. 71

Transition and Summary ..............................................................................................75

Section 3: Application to Professional Practice and Implications for Change ..................77

Introduction ..................................................................................................................77

Presentation of the Findings.........................................................................................77

Tests of Assumptions ............................................................................................ 78

Descriptive Statistics and Inferential Results ....................................................... 82

iii

Multiple Regression Analysis ............................................................................... 82

Applications to Professional Practice ..........................................................................86

Implications for Social Change ....................................................................................87

Recommendations for Action ......................................................................................88

Recommendations for Further Research ......................................................................90

Reflections ...................................................................................................................91

Conclusion ...................................................................................................................92

References ..........................................................................................................................93

Appendix A: Survey ........................................................................................................122

iv

List of Tables

Table 1. Correlation Coefficients Among Study Predictor Variables .............................. 78

Table 2. Reliability Statistics for Study Constructs .......................................................... 82

Table 3. Means and Standard Deviations for Quantitative Study Variables .................... 82

Table 4. Regression Analysis Summary for Manager-Employee Relationship and

Employee Rewards ................................................................................................... 84

v

List of Figures

Figure 1. Normal probability plot (P-P) of the regression standardized residuals............ 80

Figure 2. Scatterplot of the standardized residuals. .......................................................... 80

Figure 3. Histogram of the standardized residuals. ........................................................... 81

1

Section 1: Foundation of the Study

Employee engagement strongly contributes to organizational performance (Bhatt

& Sharma, 2019). In today’s fast-changing global markets, employee engagement serves

as a form of differentiation and competitiveness that contributes to organizational growth

and survival. Engaged employees feel positive about their work, the organization, their

associates, and the organization’s products (Aftab, Monowar, & Luo, 2019).

Organizational leaders worldwide view employee engagement as a strategic focus

(Loerzel, 2019). To increase employee engagement, organizational leaders need to

identify the factors that drive and sustain employee engagement. In this correlational

study, I examined the relationship between manager-employee relationship and employee

engagement and between employee rewards and employee engagement.

Background of the Problem

Scholars and practitioners have shown great interest in the concept of employee

engagement as it relates to organizational performance and competitiveness. Employee

engagement refers to the full presence of the employee at work and affects how much

effort they put into their job. Employees reflect their effort by being enthusiastic,

creative, and focused on propelling their performance to meet organizational goals (Bhatt

& Sharma, 2019). Engaged employees create value for the organization by way of

knowledge, ability, caring about the organization’s stakeholders, and remaining with the

organization longer (Shenoy & Uchil, 2018).

Understanding what drives employee engagement has let researchers focus on

how employees experience engagement, the organizational culture, and the perception of

2

their managers and the organization’s support (Shenoy & Uchil, 2018). Organizational

leaders should understand how employee engagement affects the employee’s job

satisfaction and organizational commitment to attract and retain employees necessary for

organizational success and survival (Lardner, 2015; Victor & Hoole, 2017). Researchers

have made substantial progress in addressing employee engagement from the

performance perspective (Lam, Kind, Kropp, Schneider, & Yost, 2018) and associating

employee engagement to high-quality supervisor relationships (Altinay, Dai, Chang, Lee,

Zhuang, Liu, 2019). The results of this research study help to expand the research on

manager-employee relationship, employee rewards, and employee engagement. The

findings may help managers understand how they can close the gap in the percentage of

engaged employees and disengaged employees in their organization.

Problem Statement

Employee engagement is critical to achieving organizational performance (Lam,

Kind, Kropp, Schneider, & Yost, 2018). Employee engagement leads to higher individual

performance and higher retention rates (Cesario & Chambel, 2017). Gallop’s research

data in 2016 from studies of employee engagement worldwide of 230,000 full-time and

part-time employees in 142 countries indicated that 24% were actively disengaged, 63%

not engaged, and only 13% percent of employees were highly engaged in their jobs

(Eliyana & Fauzan, 2018). Disengaged employees, on average, cost U.S. organizations

$350 billion annually (Osborne & Hammoud, 2017). The general business problem is a

loss of productivity of employees due to the lower performance without adequate

employee engagement. The specific business problem is that some managers do not

3

understand the relationships between the manager-employee relationship and employee

engagement and employee rewards and employee engagement.

Purpose Statement

The purpose of this quantitative correlational study is to examine the significance

of the relationship between manager-employee relationship and employee rewards and

employee engagement. The independent variables are manager-employee relationship

and employee rewards. The dependent variable is employee engagement. The targeted

population comprised of employees from one organization in the United States. The

implication for positive social change is that organizations can have a better

understanding of the potential benefits of employee engagement. Researchers have

associated employee engagement with employee motivation, work performance, and

organizational performance (Al Zaabi, Ahmad, & Hossan, 2016). Therefore,

organizations can be competitive, provide job stability, and expand to other markets to

create jobs. Local communities could benefit from having more employment

opportunities and the derivative benefits for reducing poverty. Organizations that are

achieving organizational goals may expand their community programs by enhancing their

corporate social responsibility (CSR) efforts for supporting communities’ needy citizens.

Nature of the Study

A researcher should consider the research question and philosophical assumptions

before selecting the research method for a study (Saunders, Lewis, & Thornhill, 2015). I

chose the quantitative method for this research. The quantitative research method is used

to examine the relationships among variables using statistical analysis (Park & Park,

4

2016). Using quantitative research may enable the generalizability of the research

outcome to the larger population (Saunders et al., 2015). The quantitative method would

best help me answer the research question because I can analyze data to explain the

nature and strength of the relationships among variables. The qualitative research method

is associated with an interpretive philosophy to obtain an in-depth understanding of

research phenomena. Using the qualitative method allows a researcher the flexibility to

get closer to the phenomenon by interacting with the research participants (Park & Park,

2016). Using the mixed method requires combining the quantitative and qualitative

methods and analysis in the same study. Researchers can obtain an in-depth analysis of

the phenomena by using qualitative research method data collection such as interviews.

Moreover, strengthening the validity and reliability of the research by using quantitative

research method data statistical analysis and charts can help to explain the phenomena

(Carins, Rundle-Thiele, & Fidock, 2016). I did not select the qualitative method or mixed

method as the purpose of my research was to examine the relationships among variables

and not to explore strategies managers use to engage employees (Bansal, Smith, &Vaara,

2018).

I considered experimental and quasi-experimental designs but concluded that

these designs were not appropriate to answer my research question. The focus for an

experimental design is on establishing the cause and effect relationships among variables

by manipulating a variable and controlling and measuring the changes in other variables.

Researchers who use experimental design use a control group and randomly assign

participants between groups (Boettger & Lam, 2013). Using a quasi-experimental design,

5

researchers intervene in the research by manipulating an aspect of the research to observe

the impact of the intervention. The researcher has multiple groups and assigns the

participants to the groups (Kohler, Landis, & Cortina, 2017). Experimental and quasi-

experimental designs require the ability to either randomly or purposely assign

participants to treatment groups, but because I am not able to assign participants to

specific treatment settings, I selected correlational design. Researchers use correlational

design to examine the relationship among variables using statistical analysis (Nimon &

Oswarld, 2013) without manipulating the variables (Aggarwal & Ranganathan, 2016).

Using correlational design, researchers do not expect to show a cause and effect

relationship between variables but instead demonstrate the degree of association

(Aggarwal & Ranganathan, 2016). I chose the correlational design because my research

focus was on examining the relationship between manager-employee relationship and

employee rewards and employee engagement.

Research Questions and Hypotheses

RQ1: Is there a significant relationship between manager-employee relationship

and employee engagement?

H01: There is no significant relationship between manager-employee relationship

and employee engagement.

Ha1: There is a significant relationship between manager-employee relationship

and employee engagement.

RQ2: Is there a significant relationship between employee rewards and employee

engagement?

6

H02: There is not a significant relationship between employee rewards and

employee engagement.

Ha2: There is a significant relationship between employee rewards and employee

engagement.

Theoretical Framework

The theoretical framework for my research is social exchange theory (SET). SET

was developed by John Thibaut and Harold Kelley in 1959 and enhanced by George

Homans in1961 and Peter Blau in1964 (Emerson, 1976). The fundamental constructs of

the theory, as per Emerson (1976), are the success, stimulus, deprivation-satiation, and

value propositions. The success proposition states that the more frequently an

individual’s actions are rewarded, the higher the likelihood the individual is to perform

that action. The stimulus proposition states that past experiences with positive rewards

are used as guidelines to perform the action. The deprivation-satiation proposition is that

the frequency of receiving the reward diminishes the individual’s perception of the value

of future rewards. The value proposition associates the individual’s perception of the

value of their actions to the likelihood to perform the action (Emerson, 1976).

Social structure is the cornerstone of SET, as relationships consist of social

interactions (Jinyang, 2015; O’Connor & Crowley, 2019). SET serves as a theoretical

guide to help explain how individuals learn from their experiences (Tanskanen, 2015).

The positive value of the experience becomes the guideline for future relationships and

repeated interactions between individuals or organizations (O’Connor & Crowley, 2019;

Tanskanen, 2015). The SET constructs my research focused on are manager-employee

7

relationships and employee rewards. These correlations of these constructs’ variables

were analyzed in the context of employee engagement to identify the relationship

between the independent and dependent variables. I selected SET as the lens to view

employee engagement through because manager-employee relationships are an exchange

process that involves reciprocity and rewards.

Operational Definitions

Employee engagement: An employee’s complete immersion into the work role

that includes their physical, cognitive, and emotional state (Kahn, 1990).

Employee rewards: Both extrinsic rewards, such as compensation and

recognition, and intrinsic rewards, such as personal commitment and satisfaction (Rice,

Fieger, Rice, Martin, & Knox, 2017).

Manager-employee relationship: This relationship is an exchange process

nurtured over time that involves reciprocity of socioemotional benefits that can have

behavioral, cognitive, or emotional consequences (Teoh, Coyne, Devonish, Leather, &

Zarola, 2016).

Assumptions, Limitations, and Delimitations

Assumptions refer to what the researcher assumes without scholarly research that

proves or disproves the information presented. The reader may overlook the researcher’s

assumptions or those assumptions may not be perceived by readers in the same form,

leaving room for their interpretation (Ellis & Levy, 2009). Therefore, it is essential for a

researcher to outline the research assumptions to be able to withstand rigorous critics and

to avoid misleading readers into accepting research data without verification (Greener,

8

2018). My study assumptions are that all participants received the questionnaire for data

collection at the same time and that research participants would respond honestly and

self-report data that are current and pertinent to their work.

Limitations refer to the research limitations beyond the researcher’s control and

might question the internal validity of the study regarding the design and integrity (Ellis

& Levy, 2009; Greener, 2018). Also, the external validity of the study or generalizability

(Greener, 2018). Greener (2018) recommended that researchers include research

limitations as part of their research study. The research limitations may be part of the

research design, methodology, discussion of findings, or conclusion. The research

limitations may highlight any research bias that may influence the research findings and

data reported. My research study limitation is that the data were collected from one

organization in the United States, limiting the study to the organization’s industry and

geographic location.

Delimitations are aspects of the research study purposely excluded. Researchers

set delimitations to outline the boundaries of the research (Ellis & Levy, 2009). The

delimitations of my research study are the constructs of SET power and trust were left out

as measurable variables in the study as the focus of my research was on the relationship

between manager-employee relationship and employee rewards and employee

engagement.

Significance of the Study

The study findings may add value to organizations by providing insights to

managers on the importance of manager-employee relationship, employee rewards, and

9

employee engagement. Employee engagement affects organizations regardless of the

industry or size and location. Enhancing employee engagement is one of the top five

strategies organizational leaders worldwide are focusing on (Loerzel, 2019). Disengaged

employees underperform, are absent more often, and are more likely to leave the

organization, affecting the organization’s bottom line (“Increasing Employee

Engagement,” 2015; Kundu & Lata, 2017). Managers may benefit from this study

because the results may help them understand the importance of the manager-employee

relationship and employee rewards relationship with employee engagement. Managers

may, therefore, implement engagement strategies that best suit the organization and

employees for improving performance and enabling the organization to increase support

for the community’s citizens.

Contribution to Business Practice

The study findings may contribute to the effective practice of business by

informing managers of the benefits of having a culture that promotes employee

engagement. Engaged employees are motivated, proactive, absorbed in their work,

connected, committed to the organization and the organization’s values, and loyal and

they perform exceptionally (Mercy & Choudhary, 2019). Employee engagement can

affect an organization’s performance and competitiveness (Cesario & Chambel, 2017;

O’Connor & Crowley, 2019). Engaged employees are motivated to improve their work

tasks, improving the overall performance of the organization. A 5-year longitudinal

analysis performed by AON Hewitt concluded that high performing organizations had

engagement levels of 72% and above. Lower-performing organizations had engagement

10

levels of 46% and below (Taneja, Sewell, & Odom, 2015). Organizations with higher

levels of employee engagement can achieve revenue growth of up to 2.5 times more than

organizations with a lower level of employee engagement (Taneja et al., 2015).

Therefore, engaging employees enables organizations to achieve higher levels of

performance. Engaged employees remain longer in their job, allowing organizations to

retain talent (Kundu & Lata, 2017). Also, engaged employees build relationships with

customers that increase customer loyalty, creating stakeholder value, and overall

organizational competitiveness (Taneja et al., 2015).

Implications for Social Change

Engaged employees positively affect an organization’s performance and

profitability (Taneja et al., 2015). Profitable organizations may support a larger

workforce, providing employment opportunities and training for underemployed

communities. Furthermore, profitable organizations may provide additional employee

benefits like on-premises childcare and tuition reimbursement for employee self-

development. Engaged employees may be active in corporate social responsibility,

supporting community programs by volunteering their time and engaging the support of

other members of the organization. Employees can also benefit from financial gains that

enable them to support their communities through tax revenues.

A Review of the Professional and Academic Literature

The objective of this quantitative correlational study was to explore the

relationship between manager-employee and employee rewards and employee

engagement. The hypotheses are that a significant relationship exists between manager-

11

employee relationship and employee engagement and a significant relationship exists

between employee rewards and employee engagement. The purpose of this literature

review is to provide an in-depth synthesis of the current literature to support the need for

this study. The literature review includes contemporary scholars’ and practitioners’ views

on employee engagement from the perspective of employees and organizations focusing

on the challenges of the business environment. The literature review includes a global

perspective and multiple industries addressing the need to engage employees to achieve

organizational goals and competitiveness.

I used Walden University’s online library to search for business management

peer-reviewed articles for this review. Using the Walden library, I accessed EBSCO to

search the business and management databases that include ABI/INFORM Collection,

Business Sources Complete, Emerald Insight, SAGE Journals, Science Direct, ProQuest

Dissertations and Theses Global, and Walden Dissertations and Theses. I also used

Google Scholar to search for articles. I searched using the following terms: employee

engagement, social exchange theory, reciprocity, value, rewards, organizational

commitment, and organizational culture.

The literature review includes 190 sources identified as peer-reviewed. The

publication dates of 151 of the articles was between 2015 and 2020, which is 5 years

from anticipated completion of the study, addressing the current state of manager-

employee relationship, employee rewards, and employee engagement from the points of

view of scholars and practitioners.

12

I arranged this literature review based on the constructs of SET, the theoretical

framework for my study. The first part of the literature review covers both the

independent variables, manager-employee relationship and employee rewards, and the

dependent variable, employee engagement. The rest of the literature review includes

theories about employee engagement and leadership and research about topics that may

influence employee engagement, including high-performance work practices. This in-

depth review of scholarly research serves as the foundation for my research study.

Social Exchange Theory

Social structure is the framework of social exchange as relationships consist of

social interactions (Jinyang, 2015). Personal motivations might drive interaction (Chang,

Hsu, Shiau, & Yi, 2015), and members learn from experience and try to minimize the

adverse outcomes of interactions and maximize the positive results. The interactions take

place over time between individuals or organizations, and there is a level of attraction of

the parties in the relationship (Presbitero, 2017; Tanskanen, 2015). The attraction might

require adjustments to be made in the offering to meet the demands of the relationship.

Tanskanen (2015) described attractiveness as one of the key elements of SET as the

parties in the relationship are aware of what attracts them to the relationship. Social

attraction influences interactions, and interactions encourage the exchange of valuable

resources among willing participants, emphasizing the need to reciprocate (Jinyang,

2015; Ketchen & Reimann, 2017; Tanskanen, 2015).

Reciprocity. Reciprocity is a significant component of SET, and it is the

exchange that takes place in relationships that benefits both parties (Bailey, Madden,

13

Alfes, & Fletcher, 2017). Kac and Gorenak (2016) described reciprocity as the effort

individuals place in an ongoing relationship that is worth maintaining, and each party is

affected by the actions regardless of whether the actions are positive or negative. Huang

et al. (2016) and Carter, Nesbit, Badham, Parker, and Sung (2018) established that an

employee’s favorable relationship with the organization contributed to reciprocity where

a favorable treatment received obligates a favorable treatment in return, contributing to

organizational commitment and engagement.

Researchers have used SET as a framework to study social and ethical behavior in

work settings, and SET has two elements: economic and social. The economic element is

the written contract between the parties that states the economic exchange. The social

element represents the noncontractual implied agreement between the parties formed by

shared values such as CSR (Slack, Corlett, & Morris, 2015). Slack et al. (2015)

investigated employee engagement with CSR from the SET perspective. Under SET,

employees voluntarily contribute to the social relationship without financial

compensation. CSR represents organization and employee social involvement in the

improvement of society and employees’ donation of their time and effort to the

organization’s CSR causes. The organization may benefit from CSR practices by creating

goodwill that contributes to corporate and brand recognition, competitiveness, and

financial gain, as well as attracting and retaining talent. The employees may benefit from

increased morale and a rewarding social contribution (Slack et al., 2015). Slack et al.

(2015) found that employees’ level of engagement with CSR ranged from involved to

uninterested as a result of lack of communication of CSR initiatives, lack of alignment

14

between employee personal and the organization’s CSR causes, emphasizing the need for

human resource management (HRM) practices that ensure the communication and

understanding of organizational objectives.

SET as the framework to study HRM practices, such as talent management and

employee perception of organizational justice, stresses the need for balance in the social

exchange. The lack of stability in the relationship may cause employees to compare their

work situation with other work members, resulting in a lack of engagement and an

increased attrition rate (O’Connor & Crowley, 2019). Presbitero (2017) used SET as the

base to study how changes in HRM practices affect employee engagement using a sample

group from a hotel chain in the Philippines, focusing on how rewards, employee training,

and development drive employee engagement. Presbitero (2017) concluded that

organizations that invest resources in HRM systems could enhance employee

participation, commitment, and loyalty to the organization. Presbitero (2017) emphasized

the concept of reciprocal interdependence in which the organization rewards employees

for their commitment, dedication, and effort to meet organizational goals. Therefore, the

employee is motivated to continue to add value to the organization, and the organization

is motivated to reward the employee—satisfying the employee and the organization

(Presbitero, 2017). Training and development are also mutually interdependent: When the

employer invests in the employee, the employee puts more effort into the work,

demonstrating appreciation for the organization, and the organization continues to invest

in employee training and development. Presbitero (2017) concluded that positive changes

in HRM practices, training, and development enhance employee engagement. Fletcher’s

15

(2019) research on 152 workers from various occupations and organizations in the United

Kingdom support Prebitero’s results. Fletcher stated that employee personal development

is an essential role of HRM systems, as organizations depend on employees for

competitiveness. Personal development enhances employee engagement because it

allows employees the opportunity to grow within their field and achieve personal

fulfillment (Fletcher, 2019). The employee’s perception of opportunity for development

increases engagement as the employee feels appreciated and valued, supported by the

employee’s perception of a high-quality relationship with the manager. The perception of

a high-quality relationship with the manager encourages the employee to invest more

time at work, find ways to improve the task, and increase efficiency, creating a strong

bond and mutual reciprocity (Fletcher, 2019).

SET has also been used by researchers as the framework to study the relationship

between organizational justice and job engagement (Haynie, Flynn, & Baur, 2019).

Haynie et al. (2019) studied a sample group from an engineering firm in the United States

and concluded that employees who perceived just treatment from the organization

develop a deeper connection with the organization. Perceived organizational support by

way of distributive (fair and just treatment) and procedural justice (unbiased process)

positively impact employee work engagement as employees feel the organization is

treating them fairly, and in exchange, employees develop a sense of security and identify

with the organization (Haynie et al., 2019). Perceived organizational support is also

associated with additional resources provided by the organization that may include

16

rewards, and employees who are rewarded reciprocate by being more engaged in their

work (Victor & Hoole, 2017).

Rewards. Hinkin and Schriesheim (2015) stated that rewards are a result of

benefits provided, and reciprocity and rewards are a necessary component of exchange

behavior. Employees perceive rewards as an appreciation for their work and reciprocate

by maintaining or increasing performance (Baranwal, Chauhan, Ghosh, Rai, &

Srivastava, 2016). Baranwal et al. (2016) referred to the employee’s sense of obligation

towards the organization as normative commitment. Baranwal et al. (2016), Hinkin and

Schriesheim (2015), and Taba (2018) identified two types of rewards intrinsic such as

gratifications and extrinsic such as products. Intrinsic rewards are the individual’s

internal rewards achieved by their positive perception of how meaningful their work is

providing a positive experience. Extrinsic rewards are the individual’s external rewards

such as financial compensation, additional benefits, and promotions (Chawla, Dokadia, &

Rai, 2017; Jacobs, Renard, & Snelgar, 2014; Stumpf, Tymon, Ehr, & van Dam, 2016;

Taba, 2018; Victor & Hoole, 2017). Lee and OK (2016) determined that intrinsic rewards

have a positive relationship between employee engagement and job satisfaction. The

employee feels a sense of accomplishment when completing their work, adding value to

the experience and may lead to job satisfaction. Taba (2018) concluded that extrinsic and

intrinsic rewards significantly influence employee’s work performance and employee’s

organizational commitment; as a result, affecting employee’s work satisfaction.

Organizations invest substantial resources in developing reward packages as

incentives to attract and retain talent. Also, to motivate employees to increase

17

performance to achieve organizational objectives (Antoni, Baeten, Perkins, Shaw, &

Vartiainen, 2017). Lardner (2015), in their study of Gemserv, an organization in the UK

looking to review their rewards and benefits strategy to engage, retain and attract

employees stated that employees are looking to be engaged, rewarded and motivated in a

more comprehensive effective manner. Therefore, it is necessary to understand

employee’s needs, aspirations, and perceptions of the organization to develop a package

of benefits that can help to retain key employees (Antoni et al., 2017) and, at the same

time, link performance with rewards (Lardner, 2015). Baranwal et al. (2016) stated that

employees might perceive rewards without recognition and recognition without rewards

as insufficient and not carry the same force. Rewards and recognition are the

organizational leader’s sign of appreciation for an employee’s effort and dedication. The

rewards and recognition need to be perceived by the individual as valuable to impact

engagement and performance (Baranwal et al., 2016; Lardner, 2015; Rai, Ghosh,

Chauhan, & Singh, 2018). Furthermore, presenting the principle of marginal returns

based on the concept that providing little of a scarce benefit is perceived as a reward and

providing a lot of a benefit that is plentiful is not very rewarding (Hinkin & Schriesheim,

2015). Rewards encourage employee’s commitment, dedication, and trust in the

management and organization (Performance related pay, 2019). Rewards are positively

related to employee performance as employees can increase their income, and income is a

legitimate concern for most employees (Performance related pay, 2019). Rewards may be

material things or psychological rewards, for example, support, trust, and self-esteem,

exemplifying trust (Chang, Hsu et al., 2015; Jinyang, 2015; Tanskanen, 2015).

18

Trust. Trust is a crucial component of SET and the foundation of interpersonal

and interorganizational relationships. Trust is a result of reliability, fairness, and goodwill

(Ketchen & Reimann, 2017; Saba & Tahir, 2017). Trust is an individual’s willingness

and confidence to depend on a partner (Kac & Gorenak, 2016), and reliance and

disclosure influence the level of trust. Reliance refers to the employee’s acceptance of the

manager’s competencies and abilities to manage, delegate, and support the employees.

Disclosure refers to the ability to share work or personal information and accepting

responsibility for work errors when performing the task. The quality of the relationship

between the manager and employee drives the level of disclosure (Heyns, 2018).

Therefore, trust is a pivotal contributor to the relationship associating trust with

dependence. Trust and dependence motivate the parties involved to participate in a

beneficial exchange relationship. Trust also helps to reduce uncertainty and allows

individuals to take the risk (Park, Lee, & Lee, 2015). Employees are empowered to make

decisions and are energized by the flexibility and ability to contribute to their daily work

and the organization’s plans (Morton, Michaelides, Roca, & Wagner, 2019). In the

manager-employee relationship, the employee’s trust in their manager increases when

they perceived the manager as capable, reliable, knowledgeable, dedicated, and able to

access the situation when making decisions that may affect the employee (Morton et al.,

2019). Trust influences relationship behaviors and knowledge sharing. When there is

trust amongst individuals, they are more open to sharing information (Jinyang, 2015;

Mosteller & Poddar, 2017). Tanskanen (2015) identified two components of trust:

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kindness, and integrity, and kindness can develop into loyalty and support that may

extend to the manager, work associates, and the organization.

Complementary Theories

Researchers have used conservation of resources theory (COR) in studies that

investigate the role of work resources in employee well-being as related to stress and

employee engagement (Babakus, Deitz, Karatepe, & Yavas, 2018; Kuijpers, Kooij, &

van Woerkom, 2020; Yang, Sliter, Cheung, Sinclair, & Mohr, 2018) and job-resource

theory in studies about employee’s motivation and engagement based on resource

offering and job demands (Boonzaier, Vermooten, & Kidd, 2019; Breevaart & Bakker,

2018; “Investigating internships: Optimising performance using theories of self-

determination and job demand-resources,” 2019). I did not select COR or job-resource

theory for my study framework because the emphasis of my study is the relationship that

takes place between the manager-employee and the impact of rewards and employee

engagement. COR and job resource theory emphasis is on the resource and demands

aspects of a job as it pertains to employee’s perception of employee growth and

development, stress, turnover intent, and employee engagement. It is essential for the

understanding of the employee engagement topic to have a well-rounded approach that

incorporates all aspects of the work environment. Therefore, COR and job-resource

theory add to the body of knowledge of this research study.

Conservation of resources theory. COR was conceptualized by Hobfoll in 1989

to study stress. Hobfoll (1989) focused on the individual’s exposure to stress, the ability

to withstand stress, and its effects on mental and physical health. Hobfoll and Shirom in

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1993 expanded the research to understand work-related stress (Chen, Westman, &

Hobfoll, 2015). The COR primary constructs are the preservation and acquisition of

resources (Halbesleben, Neveu, Paustian-Underdahl, & Westman, 2014; Bailey et al.,

2017), focusing on resource investment, resource loss, and resource exchange (Chen et

al., 2015; Hagger, 2015; Islam & Tariq, 2018). The central concept of COR is that

individuals who hold the most resources can mitigate resource loss and more likely to

have the knowledge and know-how to obtain more resources (resource gain) (Hagger,

2015). Hagger (2015) classified resources into four main categories; object resources

referring to resources of ownership such as owning a house, condition resources relating

to agreements or contracts such as work and personal commitments, personal resources

referring to personal attributes, and energy resources referring to the individual’s

knowledge and monetary funds. Depending on the employee’s resource hierarchical

level, the employee may be able to manage, adapt, or fail to regulate stress (Hagger,

2015). Also, the employee’s experience may influence the value of the resources

(Halbesleben et al., 2014). The objective is to invest or exchange resources and minimize

or avoid loss and to grow with the experience, emphasizing resilience, which is the

individual’s ability to cope with stressful situations and maintain balance even during

challenging conditions (Chen et al., 2015; Islam & Tariq, 2018). Researchers have used

COR as the framework for studies about employee burnout, employee engagement,

employee well-being, customer satisfaction, and productivity as organizations rely on

their employees to increase performance, meet organizational objectives, and remain

competitive.

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Harju, Hakanen, and Schaufeli (2016) used COR as the framework in their study

to determine if job crafting can reduce employee job boredom and increase work

engagement, associating hindrance demands with employee boredom and challenge

demands with work engagement. Harju et al. (2016) emphasized the individual’s desire to

obtain, retain, and accumulate resources to deflect work stress. Job crafting is a

challenging demand and refers to the employee’s proactive behavior to alter their work in

an attempt to improve, be more efficient, and satisfied with work. Therefore, reducing

boredom and increasing work engagement (Harju et al., 2016). Chung, Liu, and Xu’s

(2017) study focused on COR to determine the impact of the leader’s psychological

capital on employee work engagement and employee psychological capital and

teamwork. Psychological capital is an area of interest to scholars and practitioners as it

refers to the positive and supportive state of mind that may encourage and motivate

employees to perform and accomplish personal and organizational objectives (Chung,

Liu, & Xu, 2019). Managers may use COR to understand the association between

psychological capital (job resources) and employee outcomes. A trustworthy and

confident manager that can make decisions is considered a valuable resource (Zhou, Ma,

& Dong, 2018). Chung et al. (2017) concluded that work engagement is an outcome of

psychological capital. Lee, Patterson, and Ngo (2017) used COR as the framework to

study how employee’s resources can improve service and customer satisfaction. In

today’s competitive markets, organizational managers are looking to achieve a

competitive advantage by focusing on customer needs. Frontline employees that have

access to job, personal, and organizational resources can cope with stressful work

22

situations as they have job autonomy, management support, and an organizational culture

that encourages individuals to influence the work environment and be resilient (Lee,

Patterson, & Ngo, 2017). The support of an empowering manager is critical for

employee’s morale, motivation, and performance. Employees who feel that they can

count with their manager, are appreciated and respected are likely to be more positive at

work, enhance customer service and avoid any deviant behavior that may negatively

affect the organization (Zhou, Ma, & Dong, 2018), as a result, enhancing work

engagement, productivity, and customer satisfaction (Lee et al., 2017).

Job demands-resources theory. The job demands-resources theory (JD-R) dated

back to less than two decades ago and developed to address employee burnout. Employee

burnout is the outcome of overworked, exhaustion, and overwhelming state at work. The

premises of JD-R are that work includes demands and resources. Demands refer to the

work role requirements to fulfill work duties and can be mental, physical, or both. Work

resources allow the employee to meet work objectives, minimize work demands, and get

the work done (Schaufeli, 2017). Schaufeli (2017) referred to the stress process as the

result of an imbalance between demands and resources, causing burnout in one extreme

and work engagement in the other extreme. Researchers have used JD-R as the

framework to study employee burnout and employee engagement. Personal resources and

engaging leadership are two extensions of JD-R that help to explain the employee’s

perception of their role, optimism, and resilience and the manager’s ability to motivate

and engage employees (Schaufeli, 2017).

23

Tadic, Bakker, and Oerlemans (2015) used JD-R as the framework for their

research on hindrance demands and impact on well-being using a sample group of 158

teachers in Croatia and concluded that hindrance demands have a negative effect on well-

being and employee engagement. Job resources have a positive impact on employee well-

being and engagement, primarily during challenge work demands, where available

resources can help to boost employee’s self-esteem, provide social support, encourage

autonomy, provide feedback, and employee development. De Beer, Pienaar, and

Rothmann’s (2013) research associated job demands to employee health issues and job

resources to a state of energy, motivation, and ability to deal with high work demands.

Employees may view job resources as a motivation to take the initiative to redesign their

job to be more efficient and improve performance (Van Wingerden, Bakker, & Derks,

2016). Lara and Salas-Vallina (2017) using, JD-R theory as the foundation for their

research, concluded that managerial competencies positively impact employee

engagement, as managerial competencies enhance organizational learning.

Organizational learning promotes effective communication, experimentation, risk

management, and participation in decision making, and these resources drive positive

employee attitudes. However, the employee’s perception of the manager’s and peer’s

support is affected by employee burnout as it can create friction in the relationships.

Therefore, employees who do not feel they have the manager’s support may withdraw

and be at work but not engaged (De Beer, Pienaar, & Rothmann, 2013). As a result,

employees may look to change jobs, seeking opportunities to enhance their career,

compensation, or better working conditions that may increase work engagement. Job

24

demands and job resources may be perceived differently by satisfy and engaged

employees compared to employees looking to change jobs (Seppala, Hakanen, Mauno,

Perhoniemi, &Tolvanen, 2015). Job demands and job resources as per the JD-R theory

are critical factors in analyzing employee motivation, employee burnout, well-being,

managerial competencies, human resource strategies, employee development and

retention, which are essential for organizational resilience and success.

Manager-employee relationship. Researchers have used SET as the lens to view

the manager-employee relationship and determined that relationship is an exchange

process that involves reciprocity (Jinyang, 2015; Ketchen & Reimann, 2017; Tanskanen,

2015). The manager-employee relationship is nurtured over time, and it involves

reciprocity of socio-emotional benefits that can have behavioral, cognitive, or emotional

consequences (Teoh et al., 2016). Teoh et al. (2016) described the manager’s behavior as

supportive manager behavior and unsupportive manager behavior. Supportive manager

behavior refers to the support managers provide to employees that address personal and

professional employee needs; as a result, employees reciprocate by being engaged.

Rahmadani, Schaufeli, Stouten, Zhang, and Zulkarnain (2020) identified four critical

leadership behaviors that motivate and support employee’s needs, strengthening,

empowering, connecting, and inspiring. These leadership behaviors encourage

employee’s competencies, belongingness, autonomy, and meaningfulness (Rahmadani,

Schaufeli, Stouten, Zhang, & Zulkarnain, 2020). Nonsupportive manager behavior refers

to the unsupportive management style that may be abusive and deviant that may lead to

the employee’s negative reciprocity. Managers can address employee relationships by

25

expressing positive emotions (Islam & Tariq, 2018; Wu & Wu, 2019). By being

supportive and providing constructive feedback, which can result in the employee

reciprocating by being engaged and having higher job satisfaction, that may result in

higher employee commitment to the work and the organization (Islam & Tariq, 2018;

Rozman, Shmeleva, & Tomic, 2019; Teoh et al., 2016; Wu & Wu, 2019). Managers need

to take a proactive approach to employee relationships by allocating resources and

providing consistent attention to employees (Islam & Tariq, 2018; Matthews, 2018;

Pedler & Hsu, 2019).

Thompson, Lemmon, and Walter’s (2015) research focused on psychological

capital. Psychological capital refers to the individual’s well-being concerning who they

are and who they are becoming, a positive outlook and perseverance. The four constructs

of psychological capital are hope, efficacy, resilience, and optimism. Managers can

influence hope by developing employee fit expectations and communicating with the

employee, allowing employee autonomy, and providing constructive feedback. Efficacy

refers to the individual’s confidence in their ability to perform the task. Managers can

support efficacy by providing an opportunity for employee development and training.

Resiliency refers to the individual’s ability to face challenges and work towards goals,

even when experiencing setbacks (Thompson, Lemmon, & Walter, 2015). Managers can

enhance resilience by creating an environment that supports psychological health, trial

and error, employees are not put down, and resources are available when they need it

(Thompson et al., 2015). Loerzel (2019) emphasized the importance of an environment

that promotes flexibility, feedback, and purpose. Flexibility in providing guidance and

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goals that would allow employees the freedom to decide how they manage their work and

workday. Feedback refers to the communication between managers and subordinates,

providing frequent feedback to the employees and receiving feedback from subordinates.

Purpose refers to the organization’s reason for being in business and the future of the

organization, establishing a shared vision that allows employees to see the organization

as purposeful and meaningful, encouraging collaboration and team participation (Loerzel,

2019; Rahmadani et al., 2020). Managers may also enhance employee’s optimism, which

is the individual’s perception of a positive outcome by discussing employee’s goals and

assigning attainable goals (Thompson et al., 2015). The relationship between the manager

and employee is vital to communicate the organization’s expectations and create

alignment between the organization’s expectations and employee’s expectations.

Leader-member exchange. Leader-member exchange (LMX) is an expansion of

the research on work socialization and Vertical Dyad Linkage that postulated that

managers develop a different relationship with each subordinate based on the need to

accomplish the desired goal. The relationship takes place as dyads within groups or

independent dyads (Graen & Uhl-Bien, 1995). LMX theory focuses on the relationship

between the manager and employee using SET as the lens to view the relationship. A

relationship is a form of reciprocity between the manager and employee (Garg & Dhar,

2017; Khalili, 2018; Wang, 2016). LMX is a predictor of relationship quality (Altinay et

al., 2019). The manager’s relationships are limited as they require time to develop higher-

quality relationships, and the rest are brief interactions with subordinates (Graen & Uhl-

Bien, 1995). Researchers have associated high-quality LMX to employee engagement

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(Altinay et al., 2019), job satisfaction, enhance communication, career opportunities,

higher salaries, quality job assignments (Herdman, Yang, & Arthur, 2017) and

organizational commitment (Morton, Michaelides, Roca, & Wagner, 2019). Lower

quality LMX was associated with lack of communication, lack of growth opportunities,

less significant work assignments, less employee support, and higher turnover rates

(Herdman et al., 2017; Lai, Chow, & Loi, 2016). Researchers expanded the research on

LMX and focused on how the manager-employee relationship is created and sustained by

looking at the interaction, reciprocity, and group relationships. Also, the effectiveness of

LMX as a leadership style evaluating how the manager works with each individual to

develop a partnership and offering the relationship opportunity to all subordinates (Graen

& Uhl-Bien, 1995). Researchers continued to investigate the impact of the manager-

employee relationship on the organization in terms of group relationships across the

organization, employee performance, interaction with customers, suppliers, and other

stakeholders (Graen & Uhl-Bien, 1995). Also, the employee’s perception of their

relationship with their manager and impact on the employee’s well-being (Ellis, Bauer,

Erdogan, & Truxillo, 2019).

Leader-member exchange and employee’s perception. The employee’s

perception of the relationship with the manager contributes to the employee’s well-being.

A quality relationship supports the employee’s need for job security and social support,

and the lack of these resources may result in employee burnout (Ellis et al., 2019; Lai et

al., 2016). The relationship between employee and manager varies from day to day, and

in the days where the employee’s perception of quality LMX employees reported higher

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levels of relatedness demonstrated by higher energy and lower fatigue (Ellis et al., 2019).

The more consistent the employee’s perception of quality LMX results in a positive

impact on employee’s well-being as employees have higher energy levels. Less

consistency, on the other hand, may result in higher levels of employee fatigue,

increasing stress, and limiting employee engagement (Ellis et al., 2019). However, the

LMX quality can be bivalent, having both a positive and a negative side towards the

relationship. This is referred to by Lee, Thomas, Martin, and Guillaume’s (2019) as LMX

ambivalence. The LMX quality is not the only predictor of performance; LMX

ambivalence has a negative effect on employee performance regardless of LMX quality

(Lee, Thomas, Martin, & Guillaume, 2019). Clarke and Mahadi (2017) emphasized that

when there is a mutual perception (manager and employee) of a high-quality LMX

relationship, the relationship is stronger. Organizational support and coworker support

have a positive impact on LMX and performance, reversing the negative effect of LMX

ambivalence and performance (Lee et al., 2019). However, the organization’s culture and

environment should be supportive at the individual level and group level.

Leader-member exchange and group effectiveness. LMX theory emphasizes the

relationship more than the role or behavior of the manager classifying the relationships

between manager and employee as an ingroup or outgroup relationship (Yu, Matta, &

Cornfield, 2018). The different manager-employee relationships within groups are known

as LMX differentiation (Lai et al., 2016; Martin, Thomas, Legood, & Dello Russo, 2018).

When the LMX relationship is similar, or the same with all group members, the level of

differentiation is low (Kauppila, 2016). Group members may perceive LMX

29

differentiation as an opportunity or as a threat depending on the manager’s traits

(Kauppila, 2016). The relationships may share the same quality or different qualities

among group members and group members may compare their relationship with the

manager to the relationship of the other team members (Martin et al., 2018). Martin,

Thomas, Legood, and Dello Russo (2018) referred to it as a relative position and LMX

variation, stating that a significant variation in LMX quality would result in a more

substantial range of the relative position. The organization’s environment is a conduit for

the relationship to take place, and it may be beneficial or detrimental for the individual or

groups (Kauppila, 2016; Yu et al., 2018). Yu, Matta, and Cornfield (2018) used the

allocation preference theory as the lens to view the LMX relationship in groups. The

allocation preference theory focuses on equity and equality. Equity refers to the

manager’s allocation of resources and rewards to employees according to the contribution

of each group member (Yu et al., 2018). Equality refers to managers evenly allocating

resources and rewards to all group members regardless of their individual contribution to

the group (Yu et al., 2018). The use of either equity or equality may vary depending on

what outcome the manager is looking to achieve. The equity distribution rewards high

performing team members, and it may motivate performance. The equality distribution

may improve the group member’s self-steam, and as a result, it may increase team

performance (Yu et al., 2018). Herdman, Yang, and Arthur (2017) emphasized that

within a group, LMX may serve to develop a hierarchy of command that can enhance

group coordination, social harmony, efficiency, and engagement.

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Leader-member exchange and employee engagement. Organizational leaders are

challenged to increase work engagement as the relationship between the manager and

employee impacts the employee’s initiative towards work. A high-quality relationship

between the manager and employees enhances the employee’s work engagement, and

engaged employees are more likely to have a proactive attitude towards their work

(Radstaak & Hennes, 2017). The manager’s engagement level also influences the quality

of LMX and follower’s engagement. Highly engaged managers are more excited,

committed, and involved in their everyday roles. Therefore, impacting the quality of

LMX as a good relationship between manager and employee motivates and energizes

employees (Boer, Born, Gutermann, Lehmann-Willenbrock, & Voelpel, 2017). Work

engagement impacts employee performance, and it reduces turnover intention among

employees. LMX is the outcome of the manager’s state of mind at work, and it serves to

shape the follower’s perspective about their work, which can significantly impact work

effectiveness, innovation, and performance.

Leader-member exchange, innovation, and performance. The manager’s role in

enhancing innovation and creativity has been an area of interest for researchers and

practitioners as creativity and innovation are pivotal for organizational success and

competitiveness (Khalili, 2018). Assessing the value of the LMX quality as a trigger for

creativity and innovation requires investigating the role the relationship plays in the

availability of resources, opportunities, and ultimately in stimulating employee initiative.

The initiative refers to the employee’s ability to act before a problem arises, see beyond

the task assigned, find ways to facilitate, expedite and improve tasks without having to be

31

asked by the manager (Khalili, 2018). LMX significantly impacts the employee’s level of

creativity and innovation, and employees with a higher level of the initiative have a

stronger quality of LMX. The employee’s initiative serves as a moderator to the high-

quality LMX as managers may be able to rely on the employee’s proactive behavior

(Khalili, 2018). A high-quality LMX also supports employees learning orientation on

innovative work behavior (IWB). Supportive managers trust and develop employees and

benefit from employee’s IWB as employees feel the need to reciprocate by being

engaged, motivated, and go beyond their work duties, which may result in improved

performance (Atitumpong & Badir, 2018). In a team environment, the manager and team

members’ relationships are unique, influencing the teams’ attitudes and building team

camaraderie that impacts the teams’ performance (Morton, Michaelides, Roca, &

Wagner, 2019). Supportive managers that are emotionally involved may contribute to job

performance as they may be able to recognize employee’s frustrations and encourage

optimism and confidence (Clarke & Mahadi, 2017).

Researchers have established a significant relationship between LMX, innovation,

creativity, and performance (Atitumpong & Badir, 2018; Khalili, 2018). However, there

is a link between the manager’s and follower ‘s expectations for creativity. Creativity is

not a result of high LMX alone, but the congruency of the manager and employee

expectation for creativity (Qu, Janssen, & Shi, 2017). The foundation of LMX theory is

the relationship between manager and employee, and since time is limited, managers can

only focus on a limited number of relationships. Both parties should be aware of the

relationship expectations (Qu et al., 2017). Also, each relationship may have different

32

expectations depending on the task complexity, employee knowledge, employee’s

expectations, and manager’s desire to enhance creativity. Therefore, high quality LMX

and high leader and follower creativity expectations have a positive impact on the level of

follower creativity (Qu et al., 2017).

In today’s fast-changing global markets, organizations tend to rely on their

employees to provide services and differentiate themselves from competitors (Garg &

Dhar, 2017; Khalili, 2018; Kim & Koo, 2017; Wang, 2016). Employee service innovative

behavior refers to the employee’s creativity and innovation demonstrated by their ability

to recognize problems, find solutions, share knowledge, and participate (Garg & Dhar,

2017). Innovative work behavior is the employee’s initiative to find efficient ways to

perform the job (Schuh, Zhang, Morgeson, Tian, & van Dick., 2018). It is essential to

evaluate the role the manager plays in developing high-quality, long-lasting relationships

with employees that may enhance performance to achieve organizational goals

(Audenaert, Decramer, George, Verschuere, & Van Waeyenberg, 2019; Garg & Dhar,

2017; Kim & Koo, 2017; Wang, 2016). A high-quality LMX enhances employee

engagement by motivating employees, supporting job autonomy, and innovative behavior

(Garg & Dhar, 2017; Kim & Koo; 2017), as a result increasing performance (Wang,

2016).

LMX consistency and employee performance management provide feedback,

guidance, and support that allows employees to know if they are meeting or exceeding

goals (Audenaert et al., 2019). LMX theory explains the value of the relationship between

the manager and employee and the impact on employee performance. Employees who

33

perceive the LMX relationship as high-quality view employee performance management

as helpful in achieving goals rather than a burden (Audenaert et al., 2019). At the same

time, employees who demonstrate innovative work behavior and are in a high-quality

LMX receive better performance reviews compared to employees in a low-quality LMX

(Schuh et al., 2018). The performance review goals assigned to each employee should be

realistic and an indicator of performance and not invariable (Kuvaas & Buch, 2018), to

minimize employee dissatisfaction, and turnover intent.

Leader-member exchange and employee turnover intent. Turnover intent is the

employee’s intent to leave the organization as a result of a lack of satisfaction with the

work, the organization, management, training, or lack of opportunities for growth. The

employee has the intent to look for another opportunity that best meets their career and

personal goals (BeomCheol, Poulston, & Sankaran, 2017). It is to the organization’s

benefit to reduce turnover intent as high turnover intent is a predictor of employee

turnover. Employee turnover is costly to organizations as organizations must recruit and

train new employees (Elanain, 2014). Employees that perceived to be in a high-quality

LMX experience higher levels of job satisfaction and are committed to the relationship.

LMX is negatively associated with turnover intent as satisfy employees feel the need to

reciprocate by committing to their work (BeomCheol et al., 2017; Elanain, 2014).

Therefore, establishing the need for organizations to assess the manager’s style as an

influence in LMX.

Leader-member exchange and the manager’s style. Management style is the

manager’s characteristics, trades, skills, and behaviors used when interacting with

34

subordinates. It plays an essential role in the manager-employee relationship. Mitoga-

Monga and Hlongwane’s (2017) study focused on the employee’s perception of the

manager’s style and the influence on work engagement. The employee’s sense of

coherence or perception of the manager’s leadership style influences their attitude toward

their work (Hong, Zeng, & Higgs, 2017; Mitoga-Monga & Hlongwane, 2017). The study

by Taneja et al. (2015) focused on the importance of employee engagement for an

organization’s success, emphasizing the role managers play in creating an environment

and culture that promotes engagement. Organizations are competing in global markets,

creating a greater need for managers to encourage cultural diversity, cultural knowledge,

attract and develop talent and expand their workforce across markets to gain competitive

advantage (Taneja et al., 2015). Therefore, organizational managers need to understand

management styles and select the style that best suits the organization’s environment and

recruit and develop managers to embrace the characteristics to build an organizational

culture that can outperform the competition and survive even in turbulent times.

Management Styles

Authentic leadership. Authenticity has its roots in Greek philosophy, and Avolio

and Gardner (2005) traced authentic leadership (AL) to the studies of Carl Rogers from

1959 to 1963 and Abraham Maslow from 1968 to 1971, as their studies focused on

developing individual’s self- actualization. Stating that authenticity is the individual’s

expressions of their experiences, thoughts, emotions, needs, wants, preferences, and

beliefs that are consistent with their inner thoughts and feelings (Avolio & Gardner,

2005). Avolio and Gardner’s study focused on the development of constructs that

35

describe an authentic leader to address environmental and organizational forces (ethics,

technology, market demands, competition, terrorism, and disease outbreak) worldwide

that have initiated the need to identify what makes a genuine leader. Walumbwa, Avolio,

Gardner, Wernsing, and Peterson (2008) defined AL as the leader’s pattern of behavior

when working with followers that pulls from and furthers positive psychological

aptitudes and ethical climate that fosters self-awareness, internalized moral perspective,

balanced processing of information, and relational transparency. These constructs reflect

the leader’s truthful desire to be genuine and understand both their leadership style and

the follower’s authentic emotions, values, and aspirations, and as a result, successfully

lead. Walumbwa et al. also reviewed the constructs of ethical and transformational

leadership and concluded that the four constructs of AL are positively related to measures

of ethical and transformational leadership without redundancies. Also, the follower

perception of AL is positively associated with job satisfaction and job performance.

Avolio and Gardner’s (2005) study and Gardner, Avolio, Luthans, May, and

Walumbwa (2005) focused on the authentic leader and follower relationship,

emphasizing that the qualities of self-awareness, self-regulation, and positive influence

bring about authenticity in followers. They are also focusing on SET as the lens to view

the relationship and reciprocity. The actions of the authentic leader foster employees need

to reciprocate by increasing and sustaining performance. Gardner et al. emphasized the

importance of finding the real individual (leader or follower) without compromising to

meet today’s job and personal demands that may limit the authentic (me) within. The

authentic leader relationship with the followers extends beyond a working relationship

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and encompasses transparency, openness, trust, guidance, and development (Gardner et

al., 2005). The values and qualities of an authentic leader are drivers of developing

authentic followers. However, requiring an organizational environment that promotes

open communication, leader and follower development, empowerment, and support (Al

Zaabi et al., 2016). Walumbwa et al. studies focused on testing and developing a theory-

based measure of AL using the authentic leadership questionnaire, testing the constructs

of AL compared to ethical and transformational leadership, and examining how AL

contributes to follower job satisfaction and performance. Organizational ethical scandals

and social challenges are calling for a change in leadership styles to influence followers

positively and restore confidence in the ability to lead public and private sector

organizations (Avolio & Gardner, 2005; Walumbwa, Avolio, Gardner, Wernsing, &

Peterson, 2008). Organizational board of directors and leaders are feeling pressure to take

action and be accountable. Therefore, at the organizational level and individual leader

level, an AL approach may be effective by promoting the well-being of employees and

achieving organizational objectives (Avolio & Gardner, 2005; Walumbwa et al., 2008).

Al Zaabi et al.’s (2016) research concluded that AL significantly increases work

engagement and organizational citizenship behavior. Furthermore, psychological

empowerment strengthens the relationship between work engagement and organizational

citizenship behavior. The research participants were employees of a petroleum company

in the United Arab Emirates. Al Zaabi et al. (2016) stated that AL refers to the leader’s

self-awareness, demonstrated by their actions, values, beliefs, morals, and ethics that

enhance the relationship with subordinates. Authentic leaders can work with

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subordinates, cooping, and understanding their perceptions to achieve organizational

objectives (Al Zaabi et al., 2016).

Transformational leadership. The transformational leadership theory (TFL) was

coined by James Burns in 1978 and advanced Bernard Bass in 1985. The TFL theory

focuses on the relationship between the manager and his team. The relationship serves as

a transformational agent that inspires employees to change their behaviors, attitudes, and

beliefs to synchronize with the managers by focusing on effort and rewards. The study by

Bass (1995) is the trajectory of his study of leadership psychology and organizational

behavior, focusing on contingent reinforcement to explain who tried to lead, who

succeeds, and who is effective. Emphasizing that the leaders self-bestowed status and

self-esteem motivates the individual to try to lead and reinforced by others reaction

accepting or rejecting the attempt of the leader. Bass reflected on his studies of TFL in

South Africa, where he interviewed 70 senior male executives. This research served to

establish the constructs of TFL that focused on the relationship with subordinates that

inspires, motivates, empowers, develops, and transcends followers by being respectful,

leading with integrity, fairness, and setting clear and high expectations for followers.

Bass also reviewed Maslow’s hierarchy of needs and the influence of transformational

leadership. Bass used the multifactor leadership questionnaire for his research to measure

behaviors and some attributions and effects.

The TFL theory encompasses the following constructs; idealized influence with

two sub-components idealized attributes, and idealized behaviors, inspirational

motivation, intellectual stimulation, and individualized appreciation (Barbinta, Dan, &

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Muresan, 2017; Bass, 1995; Jha, Srirang, & Malvija (2017). Idealized influence refers to

the manager’s attributes to build confidence and the ethical behavior that allows the

manager to lead with integrity and inspire employees to follow. Inspirational motivation

refers to the manager’s ability to inspire subordinates to have an optimistic view of the

future and the goals of the organization. Intellectual stimulation refers to the manager’s

ability to stimulate thinking and innovation to find solutions to problems. Individualized

appreciation refers to the manager’s expertise and success in developing his team by

paying attention to each individual (Barbinta et al., 2017; Bass, 1995; Jha et al., 2017).

Leaders who exhibit these constructs addressed employee’s needs and inspired

employees to achieve their goals at the same time, promoting creativity, innovation, and

encouraging employees to go beyond their regular work duties (Breevaart & Bakker,

2018; Lalatendu-Kesari, Sajeet, & Nrusingh-Prasad, 2018). Transformational leaders

influence employee’s feelings motivating and empowering them to perform (Buil,

Martínez, & Matute, 2019). The transformational leader develops an organizational

culture and environment with shared values and vision where employees transcend

beyond their individual needs to achieve the organization’s goals (Barbinta et al., 2017;

Bass, 1995; Jha et al., 2017; Buil et al., 2019).

Researchers have associated transformational leader’s behavior to employee

engagement. Breevaart and Bakker’s (2018) studies of elementary teachers from a school

in the Netherlands concluded that the transformational leader’s behavior impacts

employee engagement and the employee’s environment affects their level of enthusiasm.

The teacher’s workload and cognitive demands positively impact work engagement and

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closely related to the transformational leader’s behavior on the days that the behavior was

high. Furthermore, the teacher’s hindrance demands were negatively impacting work

engagement and closely related to the transformational leader’s behavior on the days that

the behavior was low (Breevaart & Bakker, 2018). The study by Hong, Zeng, and Higgs

(2017) focused on the effect of the employee’s perception of transformational leadership

and person-job fit on employee engagement. Hong et al. stated that the transformational

leader’s behaviors influence the behavior and attitudes of employees and promote

organizational citizenship behavior. Therefore, increasing an employee’s self-esteem,

optimism, shared values, and self-efficacy. The study by Lalatendu-Kesari, Sajeet, and

Nrusingh-Prasad (2018) of executives in service industries in eastern India concluded that

psychological well-being and transformational leadership facilitate employee engagement

and organizational trust (Lalatendu-Kesari et al., 2018). Employee’s psychological well-

being relies on the constructs of transformational leadership to create a culture that allows

positive relationships, autonomy, personal growth, and purpose, creating an engaging

environment that can lead to trust (Lalatendu-Kesari et al., 2018). Trust inspires and

empowers the relationship between the transformational leader and employee, increasing

employee engagement (Buil et al., 2019).

Employee Engagement

Kahn’s (1990) research in employee engagement set the foundation for future

research. Kahn’s focused his research on the premise that individuals can use their

physical, cognitive, and emotional state in their work, and it affects their work

performance and experience. Kahn described engaged employees as having an active

40

role, being present, having a connection to work and others, and a sense of fulfillment

that brings out the best of them demonstrated in their work outcome. The individuals’

perception of their work affected their level of engagement and given the appropriate

conditions such as knowing what the manager expects of them, having the resources to

perform the task, having the opportunity to develop and advance, feeling connected with

co-workers, and the organization promotes engagement. Kahn described individuals at

the opposite side of the engagement continuum as disengaged. Disengaged individuals

are not mentally present in their roles and lack a personal connection with co-workers.

Harter, Schmidt, and Hayes (2002) advanced Kahn’s research and focused on the impact

of employee engagement and business outcomes, finding a positive relationship between

employee engagement, customer satisfaction, productivity, profit, employee retention,

and employee safety. Employee engagement is the individuals’ purpose and energy that

distinguishes them and evident in their initiative, adaptability, persistence, and

determination (Carter et al., 2018; Gupta & Sharma, 2016). Employee engagement is

putting extra effort, going the extra mile beyond the work requirements to perform the

job (Cesario & Chambel 2017; Buil, Martínez, & Matute, 2019; Gupta & Sharma, 2016;

Jiang & Men, 2017).

Employee engagement and performance. Researchers associate employee

engagement with employee performance because engaged employees show dedication to

their work, fulfillment, motivation, and persistent (Cesario & Chambel, 2017; Buil et al.,

2019; Gupta & Sharma, 2016; Jiang & Men, 2017; Rahmadani, Schaufeli, Stouten,

Zhang, & Zulkarnain, 2020). According to a 2017 Gallup report, only 31% of employees

41

in the US service occupation, are engaged. This represents the second-lowest level of

engagement by occupation beat only by manufacturing (Kang & Busser, 2018). The cost

to US businesses is $550 billion a year due to low employee performance (Kang &

Busser, 2018). Fast-changing global markets and technology innovation has drastically

altered the way organizations compete, emphasizing the need for engaged employees to

increase customer satisfaction, enhance the organization’s reputation, create stakeholder

value, and competitiveness (Bhatt, & Sharma, 2019; Baranwal et al., 2016; Eldor &

Harpaz, 2016; Gupta & Sharma, 2016; Sekhar, Patwardhan, & Vyas, 2018). In 2004

Hewitt Associates reported that organizations with the highest employee engagement had

a 4-year average total shareholder return of 20 % or higher, representing almost triple the

return of organizations with lower employee engagement (Gupta & Sharma, 2016).

Organizations are depending on the employee’s knowledge, involvement, proactive

behavior, and need for challenging tasks to maximize competence and performance (Al

Mehrzi & Singh, 2016; Song, Lim, Kang, & Kim, 2014). Patel, Moake, and Oh’s (2019)

determined that increasing employee demands may increase employee engagement

because employees are challenged and can utilize their personal resources (education,

talent, and experience). Employees that are challenged show their capabilities, tap into

their expertise, and bring out their creativity (Hla, Mayuree, &Tanakorn, 2019; Patel,

Moake, & Oh, 2019; Sekhar et al., 2018). The organization’s effort in busting the

employee’s resources results in promoting work achievement, performance, and desire to

remain with the organization (Bailey et al., 2017; Cesario & Chambel, 2017; Hla et al.,

2019). Employee engagement and performance also affects employee happiness.

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Happiness is an emotion that may spread from one person to another (Wu & Wu, 2019).

Happy and satisfied employees outperformed unhappy, disengaged employees

(Makikangas, Aunola, Seppala, & Hakanen, 2016) and invigorate others to perform

(Kang & Busser, 2018; Wu & Wu, 2019), stressing the role managers place in creating an

environment where employees motivate each other to perform and share their knowledge

and experience.

High-performance work practices (HPWP) is a working model of high

commitment and involvement to develop the employee’s skills that involve the

organization as a whole. Managers use HPWP to develop employee’s talents and offer

opportunities that benefit both the employees and the organization (Ogbonnaya

&Valizade, 2018). HPWP has a positive association with employee engagement and job

satisfaction. Employees who are engaged are satisfied with their work, relationships with

peers, opportunities, and look to enhance their role to achieve higher levels of

performance at the individual level and organizational level (Ogbonnaya &Valizade,

2018).

From the individual’s perspective, Othman, Hasnaa, and Mahmood (2019)

focused on the impact of HRM in employee engagement and individual work

performance. Organizations are competing to recruit the best talent and retain talent

(Gupta & Sharma, 2016), making it a top priority for managers to implement human

resource (HR) programs to propel the hiring, training, and development process (Bhatt, &

Sharma, 2019). Also, to ensure that organizations have the talent need it to sustain and

grow the business, emphasizing the need for a talent pipeline. HRM is also critical to

43

evaluate an individual’s performance. Performance evaluation is a method of assessing an

individual’s goal attainment, developmental needs to evaluate strengths and weaknesses

(Othman, Hasnaa, & Mahmood, 2019), that allow managers to prepare the workforce to

meet organizational financial objectives (Ogbonnaya & Valizade, 2018).

Employees who perceived the organization as supportive, careering, and with

potential for growth work harder, find ways to improve work tasks, and are present

mentally and physically (Othman et al., 2019). Othman, Hasnaa, and Mahmood (2019)

concluded that employee engagement drives individual performance by way of human

resource management. An essential role of human resources (HR) is to encourage the

positive energy that motivates individuals, such as emotional, relational, and

organizational energy associated with a shared vision, engagement, and job satisfaction

— as a result, increasing creativity and innovation (Baker, 2019). Therefore, employee

performance is an outcome of the employee’s abilities and opportunities to perform

(Katou, 2017), and HR provides the tools necessary for the organization to develop the

employees. Organizations that have an effective HRM process benefit from a holistic

view of the employee’s and the organization’s needs that drive employee engagement,

performance, and empower the organization’s culture.

From the organization’s perspective, HRM serves to assess business strategies

related to cost, innovation, and quality. HRM ensures that there is a shared vision in

terms of resources, development, reward programs, and relations across the organization.

HRM practice promotes individuality, dependability, and unanimity (Katou, 2017). The

shared vision of the HRM system allows employees to focus on the organization’s

44

objectives and have a collective view of the organization’s purpose and vision. As a

result, increasing performance. Also, the employees shared perceptions of the

organization’s training, development, and rewards enhance job satisfaction, and

employee motivation, and engagement (Katou, 2017; Meng & Berger, 2019). Adapting

flexible HRM strategies may also assist managers in overcoming any unexpected

changes. Flexible HRM refers to the coordination of resources, where employees are

cross-trained to perform different tasks associated with job satisfaction, employee

engagement, and performance (Sekhar et al., 2018). Flexible HRM allows employees the

opportunity to have work-life balance and, as a result, reciprocating by working hard and

efficiently (Sekhar et al., 2018).

Employee Disengagement

Employee disengagement is a significant struggle for organizational managers as

it affects the organization’s productivity and profitability, Gallup data from 2017 reported

that two-thirds of U.S. workers are disengaged (Wolff, 2019). Disengagement is the

opposite of engagement. The employee is present at work but has a loss of enthusiasm,

drive, interest, are pessimists, and complaints (Wolff, 2019). Researchers have associated

employee burnout with employee disengagement and turnover. Employee burnout refers

to overwhelm and stress at work that erodes engagement (Cole, Walter, Bedeian, &

O’Boyle, 2012; Lai, Chow, & Loi, 2016). Cole et al. (2012) identified three elements of

employee burnout fatigue, distrust, and ineffectiveness. Employees who are physically

and mentally tired are more likely to develop feelings of anxiety and distrust towards co-

workers and the organization that result in lower performance. Therefore, associating job

45

demands with emotional and physical burnout, that may result in health issues,

employees complaining about the job (Cole et al., 2012), and turnover.

Employees who experience conflicts that affect their emotional engagement, such

as lack of appreciation, intimidation, micromanagement, and high demands resulting in

high levels of stress, are more likely to emotionally disengaged and result in turnover

(Reina, Rogers, Peterson, Byron, & Hom, 2018). In 2017 3.2 million employees quit their

jobs a 10.3 % increase from the year before, as per the US Bureau of Labor Statistics,

making employee turnover a problem for the organization’s success (Memon, Salleh,

Nordin, Cheah, Ting, & Chuah, 2018). Employee turnover costs an organization an

average of 90% to 200% of annual salary as a result of hiring cost and training. It also

may result in loss of productivity, customer relationships, and organizational knowledge

(Reina et al., 2018). Organizations that dedicate resources to find employees that fit the

organization’s culture may decrease employee turnover, associating person-organization

fit (P-O fit) to employee retention, organizational commitment, job satisfaction, and

performance. P-O fit refers to employee’s talents, expertise, knowledge, values, and

objectives align with the organization’s (Memon et al., 2018). Managers should look at

the root causes of disengagement and make changes to the organization’s culture and

setting a plan of action that includes taking a close look at the employee’s needs (Wolff,

2019). Wolff (2019) recommended addressing employee’s needs by listening and

understanding employee’s concerns, align employee’s work tasks with the employee’s

capabilities, create a clear vision, and making employees accountable for their

performance. Addressing disengagement from an employee’s needs perspective would

46

change the organization’s culture to more inclusive, caring, and empowering, enhancing

employee engagement and reducing employee turnover.

Summary

The review of the literature addressing the effect of the management style and

LMX focusing on the quality of the relationship clarified the concepts of reciprocity.

Reciprocity is the exchange that takes place in relationships, and high-quality

relationships motivate employees to reciprocate by been engaged. Rewards are incentives

to motivate employees to perform, and rewards can be intrinsic rewards such as personal

goals and professional development. Intrinsic rewards are usually driven by how the

employee feels about the manager and organization and include autonomy, work

flexibility, and work-life balance. Extrinsic rewards can be monetary rewards or

promotions and are usually controlled by the manager. Managers also affect the

employee’s perception of the organization’s culture and rewards system, and ultimately

employee engagement.

Researchers emphasized the impact of employee engagement in organizational

performance and competitiveness by providing worldwide research on the effect of

employee engagement and organizational profitability. There is ample literature available

in the employee engagement topic that addressed job satisfaction, organizational

commitment, corporate social responsibility, emotional and psychological impact,

employee rewards, and human resource management. Therefore, managers and

practitioners may benefit from a current outlook on the employee-manager, employee

47

rewards, and employee engagement topic that may serve as a new lens to view the current

and future state of the organization.

Transition

Researchers have established that employee engagement is necessary for an

organization’s growth and survival. Organizations depend on their employees to develop

new products, services, efficiency, productivity, and overall performance. Therefore,

organizational managers are challenged to increase employee engagement as a form of

competitiveness. Section 1 provides the literature review that summarizes previous

research on the topic of SET, manager-employee relationship, employee rewards, and

employee engagement. Literature reviews are used by the researcher to evaluate current

research in the subject of the study that helps to assert the need for the study and answer

the research question, which is what is the relationship between the manager-employee

relationship, employee rewards, and employee engagement?. Section 1 covers the

relationship between manager-employee from the SET view focusing on reciprocity and

rewards. Also, reviewing elements such as the organization’s culture, organizational

performance, leader-member exchange, employee perception of LMX, turnover-intent,

and disengagement. The role of the manager and organization in building an

organizational culture that supports employee engagement is emphasized by reviewing

leadership styles and engagement and performance.

Section 2 encompasses my role as the research, the role of the participants,

research method, design, data collection methods, ethics in research, data analysis, and

48

reliability and validity of the research instrument. These are essential elements in

answering, supporting, and validating the study.

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Section 2: The Project

Employee engagement is associated with organizational performance and

profitability (Bhatt & Sharma, 2019). Engaged employees are more confident about their

work and can face challenges and work toward their goals even when experiencing

setbacks (Teoh et al., 2016; Thompson, Lemmon, & Walter, 2015). Enhancing and

sustaining employee engagement requires assessing employee needs and addressing

employee expectations from the organization (Chawla, Dokadia, & Ria, 2017). This

study focuses on the relationship between manager-employee relationship and employee

rewards and employee engagement.

Purpose Statement

The purpose of this quantitative correlational study was to examine the

relationship between manager-employee relationship and employee rewards and

employee engagement. The independent variables are manager-employee relationship

and employee rewards. The dependent variable is employee engagement. The targeted

population comprised employees from one organization in the United States. The

implication for positive social change is to inform employees and members of the

community of the importance of employee engagement for the advancement of the

employee’s career, financial gain, and organizational performance and survival, which

contributes to employment security and investment in the community.

Role of the Researcher

The role of the researcher is to identify the research method and data collection

method for the research process (Saunders et al., 2016). My role as the researcher in this

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study on the topic of employee engagement was to ensure that my research established

rigor. Kohler et al. (2017) defined rigor as the reliability of the research theoretical

development, the use of analytical tools and transparency of the research process, data

collection, data analysis, interpretation, and reporting. The data collection process is a

critical component of the research process. Therefore, ensuring the appropriate sample

size for the study is vital (Kyvik, 2013). During the data collection process, the role of

the researcher is to avoid personal bias and social selection bias that can encourage a

desirable outcome (Daigneault, 2014; Noble & Smith, 2018). My role as the researcher

was to ensure the reliability of the research process by conforming to appropriate sample

size, transparency, and accuracy of the data to mitigate research bias.

My knowledge of the research topic was limited to my personal work experience

as a sales professional. I had worked for the same organization for over 18 years and had

long-term relationships with organization executives and associates. I did not have

previous experience in conducting research, but my education and professionalism

allowed me to remain objective in the research process. The study topic was of interest to

me as employees are essential for the success of organizations. Employee engagement is

associated with employee performance (Cesario & Chambel, 2017) and organizational

competitiveness (Bhatt, & Sharma, 2019; Baranwal et al., 2016; Eldor & Harpaz, 2016;

Sekhar, Patwardhan, & Vyas, 2018).

I used an anonymous online survey to collect data. A researcher can mitigate

research bias by using an online survey offered to the entire research population (Landoy

& Repanovici, 2009). Using an online survey allows researcher to conduct an

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anonymous survey, obtain consent, track the response rate, and avoid multiple

submissions (Landoy & Repanovici, 2009). My role as the researcher was to mitigate

bias by not having contact with the research participants. My communication with the

organization, ABC Corporation (a pseudonym), was limited to one executive. My contact

allowed the research study and distributed the link to the online survey to the

participants.

Researchers conducting research that involves human participants should

incorporate the principles of ethical conduct (Kaewkungwal & Adams, 2019). Ethics in

research includes the protection of participants’ rights, self-worth, and welfare. A

researcher’s conduct can influence the research results and have possible consequences

for society (Kaewkungwal & Adams, 2019). I followed the ethical guidelines outlined in

the Belmont report. The Belmont report emphasizes the protection of the research

participants, addressing the topics of respect, beneficence, and justice (National

Commission for the Protection of Human Subjects of Biomedical and Behavioral

Research, 1979). Respect refers to respect for participants by ensuring that they

understand their right to consent and to confidentiality in the research. Beneficence refers

to the researcher’s avoidance of unnecessary harm to participants. Justice refers to

allowing the equal opportunity to participants without exploiting vulnerable groups or

excluding participants who might benefit from the research (National Commission for the

Protection of Human Subjects of Biomedical and Behavioral Research, 1979). To protect

the research participants, I provided the participants with equal opportunity to participate

in the study, and I informed participants of the research purpose and who may benefit

52

from the research outcome. I provided a consent form, informed participants of their right

to participate or withdraw from the research, and ensured confidentiality.

Participants

The criteria for selecting the research participants are as follows: (a) 18 years of

age or older, (b) current full-time employees of ABC Corporation, (c) have at least 1year

experience working for ABC Corporation, (d) volunteered to participate, and (e) able to

sign the consent form. My contact at the ABC Corporation communicated with the

employees by email and informed them of the research purpose and why and how they

were selected to participate in the study. Participants provided consent by clicking on the

link to the survey through Survey Monkey. The survey was anonymous. The Belmont

report emphasizes the role of the researcher in data collection and ethical implications to

protect the research participants. Individuals should be able to choose to participate in the

study, and the researcher has the responsibility to inform participants of any potential

harm as the result of participating in the study and provide the right to withdraw from the

research (National Commission for the Protection of Human Subjects of Biomedical and

Behavioral Research, 1979).

The participants’ characteristics aligned with the research question by being

employees of an organization in the United States, the ABC Corporation. Investigating

the manager-employee relationship, employee rewards, and employee engagement

required employed participants. Roof (2015) stated that employee engagement research,

by definition, requires employed adult participants. Breevaart and Bakker’s (2018)

research participants comprised of elementary teachers working for a school in the

53

Netherlands. Walden, Jung, and Westerman’s (2017) research participants were members

of the millennial generation in the United States born between 1982 and 2004 and

employed full-time or part-time.

Research Method and Design

Research Method

I selected the quantitative research method for my research study. The

quantitative research method is rigorous and relies on controlled measurements, such as

surveys to assess the phenomenon (Rutberg & Bouikidis, 2018). The quantitative method

allows researchers the use of statistics for data analysis and hypothesis testing (Gunn,

2017; Zyphur & Pierides, 2019). Researchers use the quantitative research method to

estimate the probability of error and determine if hypotheses should be accepted or

rejected (Zyphur & Pierides, 2019). Using the quantitative research method, I was able to

determine if a relationship existed between manager-employee relationship and employee

engagement and employee rewards and employee engagement to accept or reject the null

hypothesis.

Other research methods I considered for my research study were the qualitative

research method and the mixed method. The qualitative research method is associated

with an interpretive philosophy to obtain an in-depth understanding of the research

phenomenon (Park & Park, 2016; Solis, Aristomene, Feitosa, & Smith, 2016). The

qualitative method allows the researcher the flexibility to get closer to the phenomenon

by interacting with the research participants (Park & Park, 2016) and by listening to the

participants’ experiences and perceptions of the phenomenon (Rutberg & Bouikidis,

54

2018). The qualitative researcher can capture details, assess the conditions of the

participant (or participants) if in a team environment, and identify cultural differences

(Solis et al., 2016). The qualitative research method allows researchers to draw rich

conclusions that incorporate the dynamics and complexity of the phenomenon (Solis et

al., 2016).

The mixed method combines quantitative and qualitative data collection and

analysis in the same research (Carins et al., 2016; Gunn, 2017; Rutberg & Bouikidis,

2018; Solis et al., 2016). The mixed method allows researchers to collect two sets of data

and introduce statistical analysis at any point in the research study. Therefore, researchers

can estimate changes in the research variables over time and incorporate writing and

numerical conclusions (Rutberg & Bouikidis, 2018; Solis et al., 2016). I did not select the

qualitative research method for my research study because the primary data collection

tools, as per Mackenzie and Knipe (2006), are interviews, observations, document

reviews, and visual data analysis. The data obtained using these data collection tools are

best represented through words and analyzed using thematic analysis (Mackenzie &

Knipe, 2006) and are not directly measurable and suitable for statistical analysis to

determine the relationship between the research variables. I did not select the mixed

method as it is a combination of quantitative and qualitative components requiring a

qualitative component.

Research Design

The research design for this study is correlational design. The correlational design

is a nonexperimental design used to examine the relationship between variables (Park &

55

Park, 2016), without the manipulation of variables (Rutberg & Bouikidis, 2018).

Researchers collect data using existing measurements and analyze data to determine if a

relationship exists between the variables (Rutberg & Bouikidis, 2018). The quantitative

research method can also be done using experimental design and quasi-experimental

design. The experimental design uses a control group and random assignment of

participants. Researchers would use experimental design when the phenomenon is

identifiable and isolated in a controlled environment where the experiment takes place

(Becker et al., 2017; Rutberg & Bouikidis, 2018). The experimental design does not work

for my research project. I do not have a control group and control conditions, and I am

looking for the relationship between variables. The quasi-experiment design allows

interventions (control variables) in the design in an effort to control confounders and

biases (Becker et al., 2017). The quasi-experiment design does not require a control

group, and it does not randomly assign the participants (Becker et al., 2017; Rutberg &

Bouikidis, 2018). In a quasi-experimental design, the interventions are measured before

and after the intervention to determine if the intervention created a change in the

phenomenon (Rutberg & Bouikidis, 2018). I did not select the quasi-experimental design

as the intent of my study is to find the relationship between variables without

intervention.

Population and Sampling

The research population comprises of the group of individuals the researcher is

attempting to generalize the research findings (Elli, 2001). The population for my

research project consists of full-time adult employees of the ABC Corporation

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(organization’s name was changed for confidentiality) with a minimum of one year with

the organization. The population aligned with the research questions as adult full-time

employees of the ABC Corporation were able to classify their relationship with their

manager and their perception about rewards and work engagement by completing the

survey.

The researcher’s sampling method is either probability or nonprobability

sampling (Erba, Ternes, Bobkowski, Logan, & Liu, 2018). The probability sample is used

to obtain a random sample of the population that may be generalized to the general

population (Ellis, 2001). Probability sampling can be done using one of the types of

random sampling; random sampling (all members of the population have an equal chance

of selection) systematic random (the researcher chooses participants, for example, every

10th person from the complete list, stratified (the samples represent the proportions of the

population), multi-stage cluster (a multiple-stage process used when a population is too

large for random sampling, or disproportionate sampling (unequal sampled subpopulation

increasing the probability of selection; Ellis, 2001).

Researchers can use nonprobability sampling by using any of the following

nonrandom sample techniques; convenience sampling (the sample is readily available to

the researcher), snowball (a selected population refers other members), quota (the sample

is based on known proportions of the population) or purposive sampling (the researcher

selects the sample based on the objective of the study; Ellis, 2001). Nonprobability

sampling may result in data that does not represent the population of interest and

jeopardize the researcher’s ability to generalize the results to the general population (Erba

57

et al., 2018). Nonprobability data and participants’ availability to the researcher should

not be the drivers for the research question (Erba et al., 2018). Researchers should remain

focus on the research purpose and best research method to answer the research question.

Convenience sampling is a type of nonprobability sampling technique and one of

the most commonly used sampling techniques (Spekle & Widener, 2018; Ismail, Iqbal, &

Nasr (2019). Spekle and Widener (2018) stated that the purpose of the research study

should be considered to determine the effect of using a convenience sample. Also, the

concepts of prototypically (how common the research is within a large sample paradigm

and sample relevance (sample members are defined the same as members in the targeted

population; Spekle & Widener, 2018). I collected data from a convenience sample.

Convenience sampling is the appropriate sampling method for my research study as the

purpose of the research study is to determine the relationship between variables using a

nonexperimental correlational design. The target population is fulltime employees of the

ABC Corporation, excluding consultants and part-time or seasonal employees as they

would not be prototypical for this research study. I did not select the probabilistic sample

method because it requires having access to a larger population to select from that

population randomly. Furthermore, my research intent is to provide knowledge on the

research subject by examining the relationship between variables and not to generalize to

a larger population. The sample size requirement is a critical component of research

planning (Moinester & Gottfried, 2014). The researcher must obtain a representative

sample of the population (Ellis, 2001). Researchers use confident interval analysis to

compute the optimal sample size in the cross-sectional correlational design. The sample

58

size helps researchers to identify any significant correlation between variables (Moinester

& Gottfried, 2014). The sample size for this research study was calculated using the G*

Power 3, a free program available to download for statistical analyses (Buchner,

Erdfelder, Faul, & Lang, 2009). Calculating the F test assuming a large effect size f2 =

.35, a = .05, and two predictor variables requires a minimum sample size of 31

participants to achieve power (1- β) of .80. Researchers have adopted .80 as the minimum

power, .80 power indicates an 80% or higher chance of rejecting a null hypothesis

(Kretzschmar & Gignac,2019). The data were collected from 32 participants, and the

sample requirement was met.

Ethical Research

Protecting the human subject is an integral part of ethics in research, and it is the

foundation of the Belmont Report, especially the protection of vulnerable subjects

(National Commission for the Protection of Human Subjects of Biomedical and

Behavioral Research, 1979). It is the role of the researcher to ensure that the research

participants are aware of any potential harm as a result of the research and are willing

participants by provident consent (National Commission for the Protection of Human

Subjects of Biomedical and Behavioral Research, 1979). Rogers and Meek Lange (2013)

expanded on the concept of vulnerable populations by emphasizing that vulnerability

should not only be regarded as being able to provide consent but the inclusion or

omission of minority groups that might alter the research outcomes. Rogers and Meek

Lange identified three types of vulnerability: inherent (part of all humans), situational

(influenced by social, political, or economic conditions of each individual), and

59

pathogenic (part of situational vulnerability that is influenced by unfavorable social

experiences). Furthermore, recommending that priority should be given to pathogenic

vulnerabilities that can avoid discrimination and racism in research (Rogers & Meek

Lange, 2013), presenting a broader view to research ethics that goes beyond providing

consent.

In addition to protecting the research participants, research ethics involves all

aspects of the research process. The researcher should ensure the transparency of the

research (Abston et al., 2016; Zyphur, 2019). Zyphur and Pierides (2017) emphasized

that quantitative research should be driven by the research purpose and the ethical

consequences of the research purpose, referring to it as research orientation. Ethics

should be rooted in the design method, regardless of the type of design (Zyphur, 2019).

Abston et al. (2016), in their research about questionable research practices, emphasized

that in addition to legal ethics and protection of human participants, students should be

taught ethics related to the research design, analysis, and reporting of data. The concept

of questionable research practices calls attention to the standards that researchers should

follow regardless of their desire for a specific result (Abston et al., 2016). Researchers,

regardless of pressure to achieve a desirable result, should adhere to ethical guidelines

that can ensure the validity and reliability of the research.

My role as the researcher is to ensure that my research project can stand

rigorous critics from the Walden University review board to scholars and practitioners.

Ethics is part of all aspects of the research project from the review of the professional

literature, adhering to plagiarism guidelines dictated by the APA manual, obtaining

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permission to use measures, and selecting analysis techniques that can best answer the

research question. Also, storing the research data and research notes for a minimum of

5 years. I informed the research participants that the data collected will be stored in a

secure safe for 5 years and destroyed after 5 years. Furthermore, to ensure that I met

all the ethical requirements for my research project, I did not begin the data collection

process until I obtained permission from Walden University’s Institutional Review

Board (IRB). Walden University’s IRB approval number for this study is 06-19-20-

0451487, and it expires on June 18, 2021. Once I had the IRB approval number, I

communicated with my contact at the ABC Corporation, who communicated with the

participants through e-mail. The e-mail address and organization’s name will be kept

confidential; the name of the organization was changed to the ABC Corporation to

protect the identity of the research participants.

Data Collection Instruments

I used the LMX Scale to measure the independent variable manager-employee

relationship. Graen and Cashman developed the LMX scale in 1975. In 1980 Liden and

Graen changed the LMX scale from 5 items to 7 items to measure productivity and

satisfaction. Graen, Novak, and Sommerkamp (1982) used the LMX 7 item scale to

measure LMX quality. The 7 items are measured using a 5-point Likert scale, and the

Cronbach alphas were .86 and .84 at two different time points. The test-retest correlation

over a 6-month interval was .67. Khalili (2016) used the LMX survey to gather data from

1,221 employees in Australia and determined that LMX has a substantial positive

relationship with the employee’s level of creativity and innovation. Atitumpong and

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Badir (2018) used the LMX survey in their study of LMX, learning orientation, and

innovative work behavior with a sample of 362 employees in manufacturing in Thailand.

As per Graen and Uhl-Bien (1995), the scale may be used for educational

purposes and non-commercial research without the need to request written permission

from the author and publisher. To measure the independent variable employee rewards, I

used two scales the Intrinsic Work Rewards Scale (IWRS) developed by Renard and

Snelgar (2016) and Extrinsic Rewards on Creativity Measure developed by Baer,

Oldham, and Cummings (2003). These two scales addressed the two components of

employee rewards. The IWR`S test includes 25 items measured using a 5-point Likert

scale item ranging from 1 strongly disagree to 5 strongly agree (Renard & Snelgar, 2016).

Renard and Snelgar validated the IWRS using a sample that consisted of nonprofit

employees from Australia, South Africa, and the United States. The scale measures

meaningful work, flexibility work, challenging work, varied work, and enjoyable work

(Renard & Snelgar, 2016). The reliability coefficient is 0.86 and hold simultaneously

content and construct validity (Renard & Snelgar, 2016). Renard and Snelgar confirmed

satisfactory content validity by conducting an exploratory factor analysis. Construct

validity was verified using Pearson’s Product Moment Correlations, which produced

significant results showing that the IWRS scores and its factors related to work

engagement and intention to quit. The exploratory and confirmatory factor analyses

confirmed the five-factor structure. They concluded that five eigenvalues were more

significant than the 1.0 limit, which represents five distinct factors: Meaningful work,

flexible work, challenging work, varied work, and enjoyable work. The confirmatory

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factor analysis showed satisfactory fit indices for the five-factor model (Renard &

Snelgar, 2016). Renard and Snelgar’s researched focused on quantifying non-profit

employee’s desires to work using the IWRS. The IWRS encompasses three factors, the

personal connection to the work, the personal motivation to impact others by making a

difference, and the personal desire for accomplishment. The study concluded that

intrinsic rewards are positively related to work engagement and employee’s satisfaction

with their compensation and negatively related to employee’s intention to quit. To use the

IWRS for this research study, I obtained permission from one of the authors Michelle

Renard.

The extrinsic rewards on creativity scale consist of three items and measured

using a 5-point Likert scale ranging from 1 strongly disagree to 7 strongly agree. Baer et

al. proved reliability and internal consistency by taking the average of the three items to

create an index alpha =.77. Baer et al. addressed discriminant validity by conducting a

maximum likelihood confirmatory analysis and determined and acceptable fit. Malik,

Butt, and Choi (2015) assessed extrinsic rewards for creativity with an eight-item scale

incorporating items from Baer, Oldham, and Cummings (2003). Malik’s et al. (2015)

study based on a sample group of 181 employee-supervisor dyads concluded that

extrinsic rewards for creativity positively influence creative performance when

employees have high creative self-efficacy and consider rewards, as necessary. Fuli,

Hong, Kwok, and Yang (2017) used the three items scale from Baer et al. (2003) to

measure reward for creativity based on a sample of 196 employees from a construction

company in China. Fuli et al. (2017) concluded that there was a significant relationship

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between high perceived rewards and challenge appraisal when challenge appraisal was

high; it significantly influences creative performance. Baer et al. provided a statement

permitting to use the test for non-commercial and educational research without the need

for written permission.

I used the Work and Well-Being Survey (UWES-9) to measure the dependent

variable employee engagement. The UWES-9 was developed by Schaufeli, Bakker, and

Salanova in 2006 to measure employee engagement addressing the employee’s vigor,

dedication, and absorption. The original scale consisted of 17 items and reduced to 9

items after collecting data from 10 countries with a total sample size of 14, 521. The 9

items are measured using a 7-point Likert scale ranging from 0 (never) to 6 (always/every

day) (Schaufeli, Bakker & Salanova, 2006). The UWES-9 reliability consists of internal

consistency Cronbach’s alpha for the 9-item scale across 10 countries wide-ranging from

.85 and .92 with a median of .92 (Schaufeli et al., 2006). Schaufeli et al. (2006) did not

provide a factor analysis. I converted the 7-point Likert scale to a 5-point Likert scale by

omitting two items and ranging from 1(never) to 5 (always/every day). Researchers have

used these scales in numerous researches around the world. Altinay et al. (2019), in their

study of 310 employees in the hotel industry in Taiwan, used the UWES-9 to measure

work engagement based on the role of LMX, role overload, and job security. Teoh et al.

(2016), in their studies of a UK based global data management organization with a

sample of 288 employees, used the UWES-9 to measure employee work attitudes based

on manager interactions that either support or do not support employees. Schaufeli et al.

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granted permission for researchers to use the UWES-9 for non-commercial and

educational research without seeking written permission.

Data Collection Technique

The researcher selects the data collection method that best suits the research

study. The cross-sectional survey design may save the researcher time and cost (Nimon &

Astakhova, 2015). I have selected the cross-sectional survey as it best fits my research

requirements of time, budget, and geographical location. Surveys can be an excellent

source to obtain information, need it for a research study (Phillips, 2015). Researchers

can reach a broader sampling group regardless of their location, and it allows participants

the flexibility to respond at their convenience (Walsh & Brinker, 2015). However, the

survey should be well design and address the intent of the study to obtain reliable data

(Phillips, 2015). Therefore, I used questions from proven sources used by researchers in

research studies about employee engagement, job satisfaction, LMX, rewards, creativity,

and innovation. Please see Appendix A for the questionnaire.

I did not conduct a pilot study for the study as researchers have used the survey

instruments to measure the constructs of manager-employee relationships, employee

rewards, and employee engagement and have proved to be valid and reliable. To measure

the independent variable manager-employee relationship, I used the items from the

Leader-Member-Exchange (LMX) Survey (see Appendix A). The LMX survey includes

seven statements that describe how the employee feels about the relationship with their

manager (Graen & Uhl-Bien, 1995).

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To measure the independent variable employee rewards, I used two scales the

Intrinsic Work Rewards Scale (IWRS) by Renard and Snelgar (2016) and Extrinsic

Rewards on Creativity Measure by Baer, Oldham, and Cummings (2003). The IWRS test

includes 25 items (Renard & Snelgar, 2016). The Extrinsic Rewards on Creativity

Measure test consists of three items (Baer, Oldham, & Cummings, 2003). I used the

Work and Well-Being Survey (UWES-9) to measure the dependent variable employee

engagement. The UWES-9 includes 9 items that describe how employees feel at work

(Lee & Ok, 2016). The survey consists of 4 sections; section 1 includes demographic

questions without requiring any personal information. Section 2 consists of the scale of

measurement for the construct manager-employee relationship using the LMX survey

consisting of 7 questions. Section 3 includes two scales of measurement to measure the

construct employee rewards. The IWRS survey consists of 25 questions and extrinsic

rewards on creativity comprised of 3 questions. Section four includes the scale of

measurement to measure employee engagement using the UWES-9 survey consisting of

9 questions. The total number of questions is 44, not including the demographic

questions. The Likert Scale, as indicated by each instrument, was used to measure the

responses. The Likert Scale can help to gauge respondents’ feelings about the situation

described in the questions (Phillips, 2015).

I did not begin the data collection process until I obtained IRB approval from

Walden University. Once I had the IRB number, I used a web-based survey Survey

Monkey and sent the electronic survey link to my contact at the ABC Corporation.

Survey Monkey, as per Phillips (2015), is a very popular survey tool that offers

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researchers the ability to design the survey and send it to the targeted participants by

embedding a link to the survey in the email. Survey Monkey provides the ability to

export data to statistical software such as Statistical Package for Social Sciences (SPSS)

(Phillips, 2015). I converted the 7-point Likert scale UWES-9 to a 5-point Likert scale by

omitting two items to ensure the data elements measure is comparable for the linear

regression analysis using SPSS as the statistical software.

Data Analysis

The purpose of my research study is to answer the research question using the

following hypothesis.

RQ1: Is there a significant relationship between manager-employee relationship

and employee engagement?

H01: There is no significant relationship between manager-employee relationship

and employee engagement.

Ha1: There is a significant relationship between manager-employee relationship

and employee engagement.

RQ2: Is there a significant relationship between employee rewards and employee

engagement?

H02: There is not a significant relationship between employee rewards and

employee engagement.

Ha2: There is a significant relationship between employee rewards and employee

engagement.

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I conducted a multiple linear regression analysis to determine the relationship

between variables. Multiple linear regression tests are used to evaluate how independent

variables are related to the dependent variable. Multiple linear regressions can also

identify the contribution of each independent variable to the dependent variable (Chao,

Nylander-French, Kupper, & Zhao, 2008). Researchers in different fields of study are

using multiple linear regressions to interpret meta-analytic data as they can test complex

models (Rosopa & Kim, 2017). Rosopa and Kim (2017) presented several examples of

studies using multiple linear regressions to examine whether engagement mediates job

characteristics and job performance and whether the relation between telecommuting and

performance is mediated by autonomy. Multiple linear regression tests are appropriate to

assess the relationship between manager-employee relationship, employee rewards, and

employee engagement. I considered two-way ANOVA for my research study. Still, it was

not suitable as two-way ANOVA is used to identify the effects of the independent

variables on the dependent variable and commonly used in experimental science (Zhang,

2012). Researchers used two-way ANOVA to examine whether to accept or reject

hypotheses when the hypotheses involve differences between two or more groups (Green

& Salkind, 2014), and the purpose of this research is to find the relationship between the

variables. I also considered logistic regression for this research study. Researchers used

logistic regression to determine how two groups differed, and it is the leading method for

modeling binary results. The data are usually reported using percentage point effects

(Terhanian, 2019). My research study does not include binary questions. Terhanian

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(2019) stated that the data’s character is essential in selecting the data analysis method.

Therefore, multiple linear regression is most appropriate for my research study.

Data cleaning, screening procedures, and missing data were done by visually

inspecting the data for consistency and accuracy. The researcher can view the data file

and review each case to detect any discrepancies in the data entry and scales that may

jeopardize the analysis (Green & Salkind, 2017). Wang and Johnson (2019) stated that

handling missing data has been an area of interest in statistical research for over 3

decades. Data cleaning methods available are data deletion, single imputation, and

multiple imputation. Ismail, Iqbal, and Nasr (2019) deleted the cases missing data as the

percentage of cases missing data from the complete data set was between 0 to 3.2

percent, stating that if the percentage is below 5% and the missing data is completely

random, the cases can be deleted. Multiple imputation computing is done using random

drawings of imputed data from a Bayesian posterior distribution (Wang & Johnson,

2019). Researchers can use SPSS for the imputation of missing data and create multiple

complete data sets, generate results by conducting statistical analysis on the imputed data,

and analyze the results for uncertainty from missing data imputations for valid

probabilistic inferences (Wang & Johnson, 2019). Data cleaning before the multiple

linear regression analysis helped to evaluate the assumptions.

The multiple linear regression analysis assumptions of sample size, outliers,

multicollinearity, normality, linearity, and homoscedasticity were assessed to determine

their validity (Green & Salkind, 2017). Testing for the normality assumption of the data

first allows the researcher to decide whether the mean value represents the data or not and

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whether to use parametric or nonparametric tests (Mishra, Pandey, Singh, Gupta, Sahu, &

Keshri, 2019. Normality was assessed using graphics (histogram and normal probability

plot) and numerical (Shapiro-Wilk test) methods. These two methods may allow the

researcher objective judgment for cases with low sample size and large samples

accordingly (Mishra et al., 2019). The assumption of sample size was met by meeting the

sample size requirement of 31 calculated using G* Power 3 (Buchner, Erdfelder, Faul, &

Lang, 2009). Cook’s distance can be used to detect outliers (Cousineau & Chartier, 2010)

and scatterplots (Green & Salkind, 2017). I evaluated multicollinearity by viewing the

correlation coefficients among the independent variables. And linearity and

homoscedasticity by examining the scatterplots of standardized residuals (Green &

Salkind, 2017).

If the assumptions are violated, the research conclusion may not be as meaningful.

The mean value is used to calculate the significance level or p-value; consequently, if the

data is not normally distributed, the mean is not representative of the value of the data

(Mishra et al., 2019). When the assumption of normality is violated, medians are used

using non-parametric tests to compare groups (Mishra et al., 2019). Bootstrapping can

also be used to estimate the sampling distribution as it provides the researcher with the

largest number of resampling combinations (Bishara & Hittner, 2012). Multicollinearity

is present when the independent variables correlate with each other with a value higher

than .8. If multicollinearity is present, the variables can be reassessed by obtaining more

information about where and how there is interdependence and potentially remove the

variable. Or partial least square estimation can be performed (Farrar & Glauber,1967).

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Homoscedasticity is when the error variance is the same in all observations. When this

assumption is violated the use of a weighted least square estimator is recommended or

adaptive estimation procedure transformation (Aslam, Riaz, & Altaf, 2011). Summary

details using descriptive statistics showed the impact of the assumptions in the statistical

analysis.

I presented a summary of the data using descriptive statistics. Descriptive

statistics include measures of frequency, frequency percentage. Measures of central

tendency mean, median, mode, measures of dispersion variance, standard deviation (SD),

standard error, and coefficient of variation (CV; Mishra et al., 2019). The letter (n)

represents the sample size and the letter (r) the value of the correlation coefficient. The

R2 value indicates the proportion of variance shared by the variables and degrees of

freedom (df). The confidence level of p-value .05 was used to support or reject the null

hypothesis. A confidence level of 95% indicates a 5% chance of type I one error

(rejecting the null hypothesis when it is true). The confidence level and power of analysis

decrease the possibility of a Type II error (accepting the null hypothesis when it is false)

(Green & Salkind, 2017). If there is a significant relationship between the independent

and dependent variables, the p-value will be p ≤ .05. A p-value p ≤.01 or .001 indicates

that the relationship is more significant and highly significant. P-value of ≥ 0.05 suggests

that there is not a significant relationship, and the null hypothesis will be rejected (Green

& Salkind, 2017). The value ranges from -1 to +1. A coefficient of -0 or +1 would

indicate a perfect linear relationship. The closer the coefficient value to -1 or +1, the

stronger the relationship between the variables (Mukaka, 2012). Mukaka (2012) stated

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that a positive coefficient means that the variables are directly related; for example, if the

value of one variable goes up, the value of the other variable goes up. A negative

coefficient means that the variables are inversely related if the value of a variable goes

up; the value of the other variable goes down.

Study Validity

The main objective of quantitative research is to view the phenomenon under

study as a dataset and establish any connections by using statistical tools that can identify

and verify through inferences which connections are real. Creating a representation of the

phenomenon under study that is verifiable establishing the validity and reliability of the

study (Barnham, 2015). It is essential to address the internal validity, external validity,

and construct validity in quantitative research (Broniatowski & Tucker, 2017).

Internal Validity

Internal validity refers to the connection between variables that results from a

causal relationship between the variables and not from forged relationships (Broniatowski

& Tucker, 2017; Yin, 2018). Internal validity is only relevant in experimental or quasi-

experimental design, where researchers seek to examine causal relationships. This study

is a nonexperimental design (i.e., correlational), and threats to internal validity do not

apply to correlational studies. However, threats to statistical conclusion validity are

relevant concerns.

Statistical Conclusion Validity

Statistical conclusion validity refers to how dependable is the knowledge

produced by the researcher based on adequate data analysis (Garcia-Perez, 2012). Threats

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to statistical conclusion validity are conditions that affect the research outcome by

inflating the Type I error rates (rejecting the null hypothesis when it is true) and Type II

error rates (accepting the null hypothesis when it is false; Garcia-Perez, 2012). The three

conditions that impact statistical conclusion validity are (a) reliability of the instrument,

(b) data assumptions, and (c) sample size.

Reliability of the instrument. Reliability of the instrument refers to the

researcher’s ability to replicate the results of a study obtained using a specific

measurement (Bolarinwa, 2015). Researchers use instruments of data collection that have

a published reliability coefficient (Heale & Twycross, 2015). Researchers also use

indices of internal consistency to infer reliability of instruments (Heale & Twycross,

2015). Heale and Twycross (2015) stated that the reliability coefficient ranges from 0 to

1, and the closer the coefficient to 1, the higher the internal consistency, an acceptable

value is (i.e.,>.7). The instruments used in my research study have reliability coefficient

values > 0.7. Cronbach’s α is a commonly used test by researchers to conduct an internal

consistency reliability check to determine the reliability of the instrument (Heale &

Twycross, 2015). I used Cronbach’s alpha to compare the instrument’s internal

consistency to my research sample.

Data assumptions. Data assumptions is another condition that impacts statistical

conclusion validity. The multiple linear regression analysis assumptions are outliers,

multicollinearity, normality, linearity, and homoscedasticity (Green & Salkind, 2017).

Researches can control threats to statistical conclusion validity and reduce the possibility

of Type 1 and Type II error by using an appropriate statistical test and by not violating

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the assumptions (Garcia-Perez, 2012). Violating the data assumptions of

homoscedasticity, linearity, and normal distribution jeopardizes the statistical conclusion

validity by not controlling Type I and Type II error rates (Garcia-Perez, 2012) and

producing misleading and biased confidence intervals (Green & Salkind, 2014). Green

and Salkind (2014) recommended that researchers examine the normal probability plot of

the regression standardized residuals, scatterplots, and skewness, and kurtosis coefficient

ranges to verify the assumptions of homoscedasticity, linearity, and normality.

Researchers also use bootstrapping an inferential technique in statistics to address data

assumption violations (Warton, Thibaut, & Wang, 2017) and parameter dependency

(Chang, Sickles, & Song, 2015). Bootstrapping is a resampling technique that uses the

sample to randomly pull a replacement sample that is used for constructing confidence

intervals and not relying on one statistical sample to estimate a standard error (Warton et

al., 2017). I used bootstrapping to ensure the assumptions were not violated.

Sample size. The sample size affects the statistical conclusion validity of a study.

The smaller the sample size, the more chances of misleading output, and the larger the

sample size, the more significant the accuracy of the output. Researchers can conduct a

statistical power of analysis provides the sample size necessary to test the hypothesis

(Hughes, 2017). The probability of committing a Type I error increases when researchers

use an inadequate sample size (Hawkins, Gallacher, & Gammell, 2013). Hawkins et al.

(2013) stated that an 80% level of power is acceptable, translating to a 20% chance of

committing a Type II error. Increasing the level of power reduces the chance of Type I

and Type II errors (Hawkins et al., 2013). Increasing the number of participants increases

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statistical power (Meyvis & Van Osselaer, 2018). I used G*Power to conduct a power of

analysis to determine the sample size and minimize the threat to statistical conclusion

validity.

External Validity

External validity refers to the researcher’s ability to generalize the data to a

broader population other than the population under the study (Bolarinwa, 2015;

Broniatowski & Tucker, 2017). Research lacks external validity when the relationship is

unsustainable when changes occurred in the context of the study (Broniatowski &

Tucker, 2017). Having a large data set allows patterns to emerge (Barnham, 2015).

Increasing the sample size strengthens the researcher’s ability to generalize findings to a

larger population (Hawkins et al., 2013). The sampling method and population make up

the population validity, a critical component of external validity that enable the

generalizability of results to the general population (Erba et al., 2018). Using a

probabilistic sampling method and selecting a random sample from a large population

strengthens external validity. Using a non-probabilistic sampling method and

convenience sample limits the ability to generalize the research results to the population

sample (Landers & Behrend, 2015). The participant’s social, professional characteristics

and demographics can alter the external validity of the study (Erba et al., 2018). I used a

convenience sample that limits the ability to generalize the study results. I used a

statistical power of analysis to obtain the appropriate sample size for my study using 80%

power the sample size is 31 participants.

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Construct Validity

The constructs of the study were obtained from SET, the theoretical framework

for this research study. Construct validity refers to whether the scale of measurement the

researcher used to measure the construct of the study adequately measures the construct

of the research theory (Broniatowski & Tucker, 2017; Yin, 2018). The scales of

measurement to measure the constructs of this study are the LMX Survey to measure the

construct manager-employee relationship. The construct employee rewards was measured

using two scales of measurement the IWRS survey to measure Intrinsic Rewards and the

Extrinsic Rewards on Creativity survey to measure extrinsic rewards. The UWES-9 scale

was used to measure employee engagement. Researchers have validated these scales of

measurement, providing indices of internal consistency to infer reliability of instruments.

Transition and Summary

Section 2 of this study, reintegrated the purpose of the research focusing on the

role of the researcher in all aspects of the research method. The ethical implications of the

research process were discussed as it pertains to the participant’s confidentiality, data

security, and IRB approval. The quantitative research method, design, population, and

sampling are reviewed and justified. The instrument used to measure the constructs of the

manager-employee relationship, employee rewards, and employee engagement are

introduced, and validity is established. The data collection technique, an online survey, is

discussed, and the data analysis techniques are presented to confirm the validity of the

research. The data were analyzed using SPSS.

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In section 3, I presented the research findings and provided statistical results,

tables, and graphs that support the study findings. I also, provided a research summary,

and theoretical association of the findings, and finally discussed how the research

impacted the professional practice and social change and made recommendations that

may impact practitioners and future research studies.

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Section 3: Application to Professional Practice and Implications for Change

Introduction

The purpose of this quantitative correlational study was to examine the

relationship between the manager-employee relationship, employee rewards, and

employee engagement. The independent variables are the manager-employee relationship

and employee rewards. The dependent variable is employee engagement. The first null

hypothesis (H01: There is not a significant relationship between manager-employee

relationship and employee engagement) was accepted, and the second null hypothesis

(H02: There is not a significant relationship between employee rewards and employee

engagement) was rejected. Employee rewards significantly predicted employee

engagement.

Presentation of the Findings

I used an online survey to generate the data (see Appendix A) to test the

relationship between the independent variables of manager-employee relationship and

employee rewards and the dependent variable employee engagement. The data were

collected over 4 days, and 32 employees of the ABC Corporation responded to the

survey. Of the 32 responses, one was eliminated because of missing data, resulting in a

sample size of 31. Using an online survey facilitated the use of follow-up emails by the

ABC Corporation, resulting in a higher response rate. The response rate for the survey

was 97%, based on a population size of 32. According to Sanchez-Fernandez et al.

(2012), the response rate of online surveys is between 25% and 30%, and it could double

when follow-up messages are sent to the participants.

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In the presentation of the findings, I discuss testing of the assumptions, present

descriptive statistics and inferential statistic results, provide a theoretical examination

relevant to the findings, and conclude with a summary.

Tests of Assumptions

The assumptions of multicollinearity, outliers, normality, linearity,

homoscedasticity, and independence of residuals were evaluated. Researchers must

present a transparent analysis of the assumptions to support the study’s informational

value. Violation of the assumptions without proper analysis may result in plausible

results (Flatt & Jacobs, 2019). The assumptions can be evaluated statistically or using

graphs (Flatt & Jacobs, 2019). I used both techniques to analyze the assumptions and

present the statistical model and visual overview of the data.

Multicollinearity was evaluated by viewing the correlation coefficients among the

predictor variables. All bivariate correlations were medium; therefore, the assumption of

multicollinearity was not violated. Table 1 contains the correlation coefficients.

Table 1 Correlation Coefficients Among Study Predictor Variables

Variable Manager-employee relationship Employee rewards

Manager-employee relationship 1 .623

Employee rewards .623 1

Outliers, normality, linearity, homoscedasticity, and independence of residuals

were evaluated by examining the normal probability plot (P-P) of the regression

standardized residuals (Figure 1), the scatterplot of the standardized residuals (Figure 2),

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and the histogram of the standardized residuals (Figure 3). The examinations indicated

there were no major violations of these assumptions. The data points lie in a reasonably

straight line (Figure 1), diagonal from the bottom left to the top right, providing visual

evidence supporting that the assumption of normality has not been violated (Hickey,

Kontopantelis, Takkenberg, & Beyersdorf, 2019). The histogram of the standardized

residuals (Figure 3) supports the statistics of the standardized residual a minimum value

of –1.796 (left) and maximum value of 2.264 (right), supporting that the assumption of

normality has not been violated. The scatterplot of the standardized residuals (Figure 2)

does not show a systematic pattern indicating that the assumption of linearity and

homoscedasticity have been met (Green & Salkind, 2017; Hickey et al., 2019). I

conducted a bootstrapping test using 2,000 samples to address the possibility of

assumption violations. Bootstrapping using 1,000 samples is sufficient to achieve a 95%

confidence level and prevent the possible influence of assumption violations (Puth,

Neuhayser, & Ruxton, 2015). Table 3 includes the 95% confidence intervals based on the

bootstrap samples.

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Figure 1. Normal probability plot (P-P) of the regression standardized residuals.

Figure 2. Scatterplot of the standardized residuals.

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Figure 3. Histogram of the standardized residuals.

I performed a Cronbach’s alpha reliability test to check the internal consistency of

the survey instrument. The Cronbach’s alpha reliability test is widely used by researchers

in the social and organizational sciences (Bonett & Wright, 2015; Kei, 2018; Lopez,

Valenzuela, Nussbaum, & Tsai, 2015). Using a Cronbach’s alpha reliability test, a

researcher can obtain the reliability of the sum (average) of multiple questionnaire items

(Bonett & Wright, 2015). The Cronbach’s alpha coefficient (average) for the items in this

study was .722; per Lopez et al. (2015), a 0.7 or higher is an acceptable level for

Cronbach’s alpha. Therefore, the survey instrument for this research study has a good

level of internal consistency.

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Table 2 Reliability Statistics for Study Constructs

Cronbach’s Alpha N of Items .722 3

Descriptive Statistics and Inferential Results

I received a total of 32 surveys, and I eliminated one survey due to missing data. I

used 31 surveys for the analysis. Table 3 depicts the descriptive statistics of the study

variables. The minimum and maximum mean and standard deviation values for the

population are reported in Table 3.

Table 3 Means and Standard Deviations for Quantitative Study Variables

Variable n Min Max M SD Bootstrapped 95% CI (M)

Employee engagement 31 25.00 45.00 34.09 5.77 [31.87, 35.61]

Manager-employee relationship 31 16.00 35.00 26.72 4.62 [24.97, 27.94]

Employee rewards 31 78.00 137.00 102.35 14.44 [97.545, 107.19] N = 31

Multiple Regression Analysis

A standard multiple linear regression, α = .05 (two-tailed), was used to examine

the relationship between manager-employee relationship, employee rewards, and

employee engagement. The independent variables were manager-employee relationship

and employee rewards. The dependent variable was employee engagement. The first null

hypothesis was that there was not a significant relationship between manager-employee

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relationship and employee engagement. The second null hypothesis was that there was

not a significant relationship between employee rewards and employee engagement. The

first alternative hypothesis was that there is a significant relationship between manager-

employee relationship and employee engagement. The second alternative hypothesis was

that there is a significant relationship between employee rewards and employee

engagement. 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 as a whole was able to significantly predict employee engagement, F(2, 28) =

32.875, p=.000, R2 = .701. The R2 (.701) value indicated that approximately 70% of

variations in employee engagement is accounted for by the linear combination of the

predictor variables (manager-employee relationship and employee rewards). In the final

model, employee rewards was statistically significant (t= 6.074, p= .000) and (beta =

.306) accounting for a higher contribution to the model than manager-employee

relationship (t = .414, p=.682) and (beta = .068). Table 3 represents the regression

summary.

Manager-employee relationship. The slope for the manager-employee

relationship (.068) as a predictor of employee engagement indicated there was about a

.068 increase in employee engagement for each one-point increase in manager-employee

relationship. In other words, employee engagement tends to increase as manager-

employee relationship increases. The squared semi-partial coefficient (sr2) that estimated

how much variance in employee engagement was uniquely predictable from manager-

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employee relationship was .0018, indicating that .18% of the variance in employee

engagement is uniquely accounted for by manager-employee relationship when employee

rewards is controlled.

Employee rewards. The slope for employee rewards (.306) as a predictor of

employee engagement indicated there was a .306 increase in employee engagement for

each additional one-unit increase in employee rewards, controlling for manager-employee

relationship. In other words, employee engagement tends to increase as employee

rewards increase. The squared semi-partial coefficient (sr2) that estimated how much

variance in employee engagement was uniquely predictable from employee rewards was

.39, indicating that 39% of the variance in employee engagement is uniquely accounted

for by employee rewards when manager-employee relationship is controlled. The

following table depicts the regression summary.

Table 4 Regression Analysis Summary for Manager-Employee Relationship and Employee Rewards

Variable B SE B Β T p

Constant .660 4.217 .156 .877 Manager-employee relationship .068 .164 .055 .414 .682 Employee rewards .306 .050 .802 6.074 .000 Note. N = 31. Outcome variable: employee engagement

Analysis summary. The purpose of this study was to determine if there was a

relationship between manager-employee relationship, employee rewards, and employee

engagement. I used standard multiple linear regression analysis to examine the existence

of a relationship between the variables of manager-relationship, employee rewards, and

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employee engagement. The multiple regression assumptions were assessed with no

serious violations noted. The model as a whole was able to significantly predict employee

engagement, F(2, 28) = 32.875, p=.000, R2 = .701. Employee rewards was statistically

significant predictor of employee engagement (t= 6.074, p= .000) and (beta = .306)

accounting for a higher contribution to the model than manager-employee relationship (t

= .414, p=.682) and (beta = .068). The conclusion from this analysis is that employee

rewards is significantly associated with employee engagement, even when manager-

employee relationship is controlled (e.g., held constant).

Based on my analysis of the study, I accepted the null hypothesis (H1: There is not

a significant relationship between manager-employee relationship and employee

engagement) and rejected the null hypothesis (H2: There is not a significant relationship

between employee rewards and employee engagement). The alternative hypothesis (H1:

There is a significant relationship between manager-employee relationship and employee

engagement) was rejected and the alternative hypothesis

(H2): There is a significant relationship between employee rewards and employee

engagement was accepted.

The theoretical foundation of this study SET serves to understand employee

engagement from a reciprocity perspective. The study findings are aligned with the

literature review about SET and employee rewards. When employees feel that the

organization supports them economically or socioemotionally, they reciprocate by being

engaged (Jha, Potnuru, Sareen, & Shaju, 2019; Khodakarami, & Dirani, 2020). The

employee’s perception of the rewards system (value and equality) motivates the exchange

86

(engagement) and strength of the commitment (Oconnor & Crowley, 2019). The results

of this study support the concept of an exchange process between the organization and

the employee as employee rewards significantly predict employee engagement.

Applications to Professional Practice

The purpose of this study was to determine if there was a relationship between

manager-employee relationship, employee rewards, and employee engagement. Based on

the research findings of the overall model, I concluded that there is a significant

relationship between manager-employee relationship, employee rewards, and employee

engagement. However, employee rewards had a significant contribution to employee

engagement than manager-employee relationship. Employee engagement is driven by the

exchange process between the organization and employee (Aktar & Pangil, 2018; Jha et

al., 2020; Oconnor & Crowley, 2019). Organizational leaders who understand the impact

of employee engagement to organizational performance have made employee

engagement 1 of the top 5 priorities (Loerzel, 2019).

In today’s fast-changing volatile economic conditions, organizational leaders have

identified employee engagement as a critical driver for organizational performance and

competitiveness (Taneja, 2015). Furthermore, employee rewards and recognition are

predictors of employee engagement (Aktar & Pangil, 2018). Organizational leaders, who

understand that employee rewards have a significant impact on employee engagement

invest in developing their employees, providing career advancement, and performance

feedback (Aktar & Pangil, 2018). Also, develop reward packages that are fair, inclusive,

and offer benefits that may impact the employee’s well-being, such as healthcare and

87

employer pension contributions (An exploration of magnetizing employees, 2020). The

organizational leader’s objective is to continually engage employees (Aktar & Pangil,

2018); employee rewards culminate the motivation and satisfaction with the organization

impacting their decision to stay (An exploration of magnetizing employees, 2020).

Employee engagement has been linked to (a) employee retention, (b) higher productivity,

(c) higher profitability (An exploration of magnetizing employees, 2020; Taneja et al.,

2015), (d) increased customer satisfaction (Taneja et al., 2015).

Implications for Social Change

The implications for positive social change from this study are based on the

research results showing a significant relationship between employee rewards and

employee engagement. Organizational leaders may benefit from this research by

developing reward programs to increase employee engagement. The development of

reward programs may serve to attract and retain talent necessary for competitiveness,

customer loyalty, and organizational performance. Increased performance leads to

profitability (An exploration of magnetizing employees, 2020), allowing organizations to

expand their workforce, reducing unemployment, and investing in social programs.

Organizations that invest in their community may impact families’ well-being by

providing employment, economic development opportunities, contributing to education

programs, and environmental programs (Appiah, 2019). Therefore, creating mutual

prosperity and sustainability for the organization and society (Matten, 2020).

Engaged employees are what differentiate organizations providing a competitive

advantage (Taneja et al., 2015). From a social investment, organizations that invest in

88

their employees and treat them fairly may see a 50% to 100% returned on their

investment (Matten, 2020). Employees’ perception of their work, opportunity,

compensation, colleagues, and work environment impacts their level of satisfaction with

the organization (Appiah, 2019; Performance-related pay, 2019). Supporting the need for

reward programs to increase employee engagement; that may result in immediate and

long-term benefits to employees by promoting (a) employee satisfaction, (b) employee

well-being, (c) longevity with organizations, (d) employee resilient, (e) increase

creativity and innovation. Employees may thrive in an environment of inclusiveness that

allows them to grow and may yearn to pass it forward by volunteering in programs to

help the community and society as a whole.

Recommendations for Action

Organizational leaders’ understanding of the importance of employee engagement

may help develop and implement strategies to increase employee engagement. The study

findings found a significant relationship between manager-employee relationship,

employee rewards, and employee engagement. However, a more significant contribution

to the model was associated with employee rewards, associating a significant relationship

between employee rewards and employee engagement. Organizational leaders may

benefit from this study results by assessing their reward programs and develop strategies

to improve manager-employee relationships that can lead to a better understanding of

employee’s needs and enhanced employee engagement. Organizational leaders may also

develop strategies for employee recruiting, promoting, training, and retention. The

following recommendations to organizational leaders to increase employee engagement

89

stem from the results of this study; (a) assess reward programs (long-and short-term), (b)

rewards should be equitable, (c) focus on employee development and training, (d)

associate rewards to creativity and innovation, (e) link compensation to performance (f)

create a positive and safe work environment, (g) create an environment of shared values,

(h) provide management training to ensure cohesive implementation of engagement

strategies, (i) encourage communication and transparency.

The manager-employee relationship can be enhanced by proper communication,

clear job demands, and adequate resources to perform the work (Ellis et al., 2019; Lai et

al., 2016). Also, by managing by example, including employees in task assignment,

providing constructive feedback, and promoting a participative work environment

(Shmailan, 2016; Zhou et al., 2018). The manager-employee relationship is crucial for

identifying employees’ strengths and career ambitions (Tegan, 2020). The manager can

direct the employee by providing feedback and empowering employees to achieve their

goals. The employee’s perception of a good quality relationship with the manger and

opportunity for development increases engagement as the employee feels appreciated and

valued (Fletcher, 2019). Open communication and understanding employees’ needs are

also essential to develop reward programs that are meaningful and beneficial to all

employees (Tegan, 2020); and create alignment between the organization’s and the

employee’s expectations. The organization’s employee engagement strategy should

ensure that managers are adequately trained, share a cohesive plan for recruiting, and

developing employees (Shmailan, 2016).

90

To enhance employee engagement through rewards, organizational leaders should

consider creating a reward program that encourages collaboration and creates a positive

organizational culture (Tegan, 2020). The rewards should be valuable and attainable to

encourage engagement (Baranwal et al., 2016; Lardner, 2015; Rai, Ghosh, Chauhan, &

Singh’s, 2018) and linked to performance (Lardner, 2015). A comprehensive rewards

package requires organizational leaders to understand employees’ needs and aspirations

(Antoni et al., 2017). It should include extrinsic rewards such as additional compensation

and promotions (Fuli et al., 2017), and intrinsic rewards such as personal development,

work-life balance, and work flexibility (Lee & OK, 2016; Renard & Snelgar, 2016).

I will provide a summary of the study’s findings to the ABC corporation’s

leadership team. I will communicate my study findings to business professionals by

including a link to the study in my Linkedin account. I am also searching for speaking

opportunities at professional business conferences, where I can assist organizational

leaders in developing employee engagement strategies.

Recommendations for Further Research

In this study, I examined the relationship between manager-employee

relationship, employee rewards, and employee engagement. Future researchers may want

to conduct a similar study using a different industry and geographic location. The current

research was limited to a specific population and geographic location; another sample

may uncover a different relationship between manager-employee relationship, employee

rewards, and employee engagement.

91

I would recommend that future researchers consider adapting this study’s

quantitative design to a qualitative design. The qualitative method may allow researchers

to explore the manager-employee relationship, employee rewards, and employee

engagement phenomena from a closer and more profound perspective and obtain a

different conclusion.

I would also recommend studies that examine the relationship of other predictor

variables derived from SET the framework of the study, such as trust to employee

engagement. Furthermore, studies examining the relationship between leadership styles

and employee engagement would contribute to the engagement literature.

Reflections

Obtaining a DBA was a lifetime dream and one that I kept postponing until it was

the right time, but the right time sometimes is just deciding to do something and not

looking back. It has been a challenging experience, but it has strengthened me, I realized

that where there is a will, there is a way.

As I look back at the time dedicated to reading business articles and becoming an

expert in the employee engagement subject, I realized how much I learned. Overall it was

a good experience and one that has broadened my knowledge. Furthermore, the study

results may help organizational leaders from different industries better understand the

relationship between manager-employee relationship, employee rewards, and employee

engagement.

92

Conclusion

The primary purpose of this quantitative correlational study was to examine the

relationship, if any, between manager-employee relationship, employee rewards, and

employee engagement. The study findings show that there is a significant relationship

between manager-employee relationship, employee rewards, and employee engagement

the p-value for alpha was less than 0.05. However, employee rewards was a statistically

significant predictor of employee engagement. The p-value for alpha was less than 0.05,

accounting for a higher contribution to the model than manager-employee relationship.

The manager-employee relationship p-value for alpha was greater than 0.05. As a result, I

accepted the null hypothesis (H01: There is not a significant relationship between

manager-employee relationship and employee engagement) and rejected the null

hypothesis (H02: There is not a significant relationship between employee rewards and

employee engagement). The alternative hypothesis (Ha1: There is a significant

relationship between manager-employee relationship and employee engagement) was

rejected and the alternative hypothesis (Ha2): There is a significant relationship between

employee rewards and employee engagement was accepted.

93

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Appendix A: Survey

A Correlational Study of Manager-Employee Relationship, Employee Rewards, and

Employee Engagement

Survey Questions

Section I: Background Information

What is your gender?

Male

Female

What age group do you belong?

18 – 30 31 – 40 41 – 50 51 – 60 61- and older

What is your level of education?

1. Less than a high school diploma

2. High school diploma

3. Bachelor’s degree

4. Master’s degree

5. Doctorate

Section II: Manager/Employee Relationship - Leader-Member-Exchange (LMX)

Survey

The following 7 statements are about how you feel about your relationship with your

manager. Please read each statement carefully and choose the option that best describes

your relationship with your manager.

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1. Do you know where you stand with your leader? Do you usually know how

satisfied your leader is with what you do?

Rarely Occasionally Sometimes Fairly Often Very Often

2. How well does your leader understand your job problems and needs?

Not a Bit A Little A Fair Amount Quite a Bit A Great Deal

3. How well does your leader recognize your potential?

Not at All A Little Moderately Mostly Fully

4. Regardless of how much formal authority he/she has built into his/her position,

what are the chances that your leader would use his/her power to help you solve

problems in your work?

None Small Moderate High Very High

5. Again, regardless of the amount of formal authority your leader has, what are the

chances that he/she would “bail you out” at his/ her expense?

None Small Moderate High Very High

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6. I have enough confidence in my leader that I would defend and justify his/her

decision if he/she were not present to do so?

Strongly Disagree Disagree Neutral Agree Strongly

Agree

7. How would you characterize your working relationship with your leader?

Extremely Worse Than Better Than

Extremely

Ineffective Average Average Average

Effective

Section III: Employee Rewards-Extrinsic Rewards on Creativity Measure

1. We have programs in this organization that reward individual creativity.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

2. This organization rewards people financially for developing unique ideas or

products.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

3. Individuals in my work unit receive special recognition for unique contributions.

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Strongly Disagree Disagree Neutral Agree Strongly

Agree

Employee Rewards-Intrinsic Work Rewards Scale

Enjoyable Work

1. My work personally satisfies me.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

2. My work fulfils me.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

3. It is a delight to perform my work.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

4. My work is enjoyable.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

5. I love the nature of my job tasks.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

6. I find my work stimulating.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

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7. My work feeds my soul.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

Varied Work

8. My work is comprised of diverse responsibilities.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

9. I have a variety of tasks to focus on within my job.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

10. I am exposed to an assortment of activities within my work.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

11. My work presents me with daily challenges.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

12. My job presents me with an array of projects on which I can work.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

Meaningful Work

13. My work has positive consequences for society.

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Strongly Disagree Disagree Neutral Agree Strongly

Agree

14. The work that I do has the potential to make the world a better place.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

15. I can see the difference that my work makes in the lives of others.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

16. My work is important in fulfilling the organisation’s greater purpose.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

17. I can see the bigger picture into which my work fits.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

18. I can see the end results of the work I do.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

Flexible Work

19. The nature of my work provides flexibility in terms of working hours.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

20. My job provides me with control over my own agenda.

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Strongly Disagree Disagree Neutral Agree Strongly

Agree

21. I am able to organise my own work.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

22. My job provides me with opportunities to make my own decisions.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

Challenging Work

23. My skills have developed as I have worked in this position.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

24. Challenges at work help me to grow.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

25. I frequently have the opportunity to learn new things when I am at work.

Strongly Disagree Disagree Neutral Agree Strongly

Agree

Section IV: Employee Engagement – Work and Well-Being Survey (UWES-9)

The following statements are about how you feel at work. Please read each statement carefully and decide if you ever feel this way about your job. If you have had this feeling, indicate how often you felt it by using the number (from 1 to 5) that best describes how frequently you feel that way.

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Please use the following scale:

1= Never 2 = Rarely – Once a month or less 3 = Sometimes – A few times a month 4 = Often - Once a week 5= Always – Every day

Work & Well-being Survey (UWES) 1. ________At work, I feel bursting with energy 2. ________At my job, I feel strong and vigorous 3. ________I am enthusiastic about my job 4. ________My job inspires me 5. ________When I get up in the morning, I feel like going to work 6. ________I feel happy when I am working intensely 7. ________I am proud of the work that I do 8. ________I am immersed in my work 9. ________I get carried away when I’m working