Assignement introduction Leadership Organizational.pdf

Section 1: Foundation of the Study

Background of the Study

Retaining talented employees is an ambitious challenge for any organization

(Dunnagan, Maragakis, Schneiderjohn, Turner, & Vance, 2013). American businesses

face a shortage of executive talent (Oladapo, 2014). Retaining knowledgeable and

experienced executives is required to respond proficiently to market challenges such as

consumer satisfaction. Competent executives may leave because they must perform for

uninspiring leaders. Retention intervention is a necessary strategy, specifically when

qualified executives leave corporations for other opportunities.

The purpose of this quantitative correlational study was to examine the attrition of

executives promoted within a company. The data instrument used in this study explained

the nature of the relationship that exists between the two independent variables (Xn),

direct leaders’ leadership styles (X1) and junior executives’ organizational commitments

(X2), and the dependent variable (Y1), junior executives’ intent to stay with the

corporation. The intent of this study was to understand how junior executives’ intent to

stay with a company relates to leadership style and organizational commitment. Retaining

the best employees of a company is vital to business success (Dunnagan et al., 2013).

Business leaders need to continuously invest in retention strategies to maintain a

competitive edge in the global market (Atif, Ijaz-Ur-Rehman, & Nadeem, 2011; Oladapo,

2014). Current trends in the global economy challenge human resource specialists’

abilities to maintain a perceptive employee retention program.

Business leaders suffer from a shortage of skilled workers, loss of experience, and

lack of knowledge for many reasons (Mohd Daud, Mohd Abdul Nassir, Nurul'Ashikin

Izany, & Salwani Mohamed, 2013). The loss of executive talent creates a skills gap and a

shortage of executive-level leadership (Martin & Hunt-Ahmed, 2011). Business leaders

are in constant competition to recruit and retain the best talent available, offering

lucrative options to candidates (George, 2015). Literature on retention shows that job

satisfaction and organizational commitment can affect good junior executives’ intent to

stay with a company (Chen, Ployhart, Thomas, Anderson, & Bliese, 2011).

Junior executive is a title given to a novice executive training under a senior

executive. Senior executives expose junior executives to the company’s practices to

ensure uniformity and professionalism (Pang &Yeo, 2012). Retention of junior

executives provides consistent leadership experiences, teamwork, work ethics, and

problem-solving skills essential in the future of a company (Chen et al., 2011). Explored

in this study were the problem of junior executive retention and the relationship between

direct leader’s leadership style, junior executives’ organizational commitment, and junior

executives’ intent to stay with a company.

Problem Statement

Leaders’ retention is an issue, particularly at the executive level (Cappelli &

Keller, 2014). As 70 million experienced and skilled baby boomers retire, American

businesses face the challenge of hiring replacement personnel (Oladapo, 2014).

Information regarding the relationship between leadership styles and intent to stay is

important for company leaders who want to improve employee retention practices, lower

upfront costs of training new hires, and reduce the limited job fit between an employee

and the company. The general business problem was that executive-level attrition rates

from the retiring baby boomer generation may result in a shortage of qualified

replacement junior executives. The specific business problem was that some leaders lack

understanding of the relationship between a direct leader’s leadership style and junior

executives’ commitment and intent to stay with a company.

Purpose Statement

The purpose of this quantitative correlational study was to examine the

relationship between a direct leader’s leadership style and junior executives’ commitment

and intent to stay with a company. The two independent variables (Xn) were the direct

leader’s leadership style (X1) and junior executives’ organizational commitment (X2).

The dependent variable was junior executives’ intent to stay with a company (Y1). The

targeted population consisted of business managers from state and federal government

agencies located in the southeastern region (Alabama, Arkansas, Delaware, District of

Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North

Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia).

This study provides management with specific variables that influence junior executive

retention. Executive-level attrition rates from the retiring baby boomers may result in a

shortage of qualified junior executives to replace the retirees. In order to aid in creating a

more desirable workplace, higher job satisfaction, improvement to the overall

organizational environment, and help in reducing the risk of company turnover and

higher unemployment rates, leaders need an understanding of the relationship between a

direct leader’s leadership style and junior executives’ organizational commitment with

junior executives’ intent to stay with a company.

Nature of the Study

The methodology of this study was quantitative research with a correlation

design. Quantitative methods involve examining the relationship that may exist between

two or more significant variables (Allwood, 2012). Shurbagi (2014) chose the

quantitative method to examine the relationship among transformational leadership style,

job satisfaction, and organizational commitment in a research study. The aim of this

study was to examine the relationship of leadership style, organizational commitment,

and intent to stay with a company and ensure alignment with the concept of quantitative

research method and correlational design. This section includes a discussion of the nature

of the study. I used a correlational descriptive design in this study by applying the

research methodology used by Vadell (2008) and the same variables. A quantitative

method with a correlation design involves examining the relationship between the

independent variables and the dependent variable.

Quantitative, qualitative, and mixed methods are the three research methods used

by researchers when conducting a study (Venkatesh, Brown, & Bala, 2013). The choice

of a particular research method depends on the focus of the study, the type of data used,

and the method used to analyze data (Venkatesh et al., 2013). A quantitative method was

the appropriate method because the focus of this study was the relationship between two

independent variables (Xn), leadership style (X1) and organizational commitment (X2), and

the dependent variable (Yn), intent to stay (Y1; Venkatesh et al., 2013).

A qualitative method was not suitable for this study because the goal of a

qualitative method is to understand personal experience, actions, and motivations, rather

than to challenge existing theories (Hays & Wood, 2011). Qualitative studies focus on

collecting and analyzing qualitative data (Elo et al., 2014). The mixed methods approach

presents challenges for a researcher considering various types of data and requires a

substantial amount of time (Cameron, 2011). Mayoh and Onwuegbuzie (2013) postulated

that a mixed methods research study requires a researcher to gather an extensive

collection of data and analyze the numerical data within a specific period.

The research method for this quantitative study was correlational relationship

design. A quantitative analysis can be either experimental or survey-type research, also

referred to as correlational research (Venkatesh et al., 2013). In an experimental study,

the researcher manipulates the participants to assess the effect of a specific intervention

on those participants (Venkatesh et al., 2013). A correlational research design was the

appropriate method for this study to investigate relationships without any manipulations

or changes to participants.

After consideration of the different research methods and related research designs,

a quantitative research method with a correlation design was selected for this study. The

quantitative method was the relevant research method for this study because the intent of

the study was to focus on examining the relationships between variables (Venkatesh et

al., 2013). Correlational design was the appropriate quantitative design for this study to

investigate the relationship between variables without manipulating participants.

Research Questions

The focus of this study was how leadership style and organizational commitment

relate to a junior executive’s intention to stay with a company. The two research

questions that guided this study were as follows:

Research Question 1: What is the relationship between direct leaders’ leadership

styles and junior executives’ intent to stay with a company?

Research Question 2: What is the relationship between junior executives’

organizational commitment and intent to stay with a company?

Hypotheses

A set of hypotheses for each research question provided testable concepts to

answer the two research questions. The two independent variables in this study were

leadership style and organizational commitment. The following were the hypotheses for

the two research questions. For each relationship, there was a null hypothesis (H10) and

alternate hypothesis (H1a). The first two hypotheses relate to Research Question 1, and

last two relate to Research Question 2.

H10: Direct leaders’ leadership styles do not significantly statistically correlate

with junior executives’ intent to stay with a company.

H1a: Direct leaders’ leadership styles do significantly statistically correlate with

junior executives’ intent to stay with a company.

H20: Executives’ organizational commitment does not significantly statistically

correlate with junior executives’ intent to stay with a company.

H2a: Executives’ organizational commitment does significantly statistically

correlate with junior executives’ intent to stay with a company.

Survey Questions

Clear and direct survey questions enabled the participants to choose a plausible

answer from a set number of responses. To collect data for this study, I asked survey

questions for each variable (see Appendix A). To comply with the agreement of consent

for using the leadership measurement instrument, I used five questions for the leadership

style variable.

Leadership style questions. To collect leadership style data, I asked the

participants survey questions obtained from the Multifactor Leadership Questionnaire

(MLQ) 5X-short form. The MLQ 5X-short form is best suited for research and

organizational survey, while the long form is best suited for training, development, and

feedback (Bass & Avolio, 2004). Following were the first five questions from the MLQ 5

X-short form that best suited this study. The license for using the survey authorized

display of only five questions in a research paper (Bass & Avolio, 2004).

Participants evaluated former directors’ leadership styles using a Likert-type scale

of 0 to 4 (0 = Not at all, 1 = Once in a while, 2 = Sometimes, 3 = Fairly often, 4 =

Frequently if not always) on each of the following statements:

1. Provided me with assistance in exchange for my efforts.

2. Reexamined critical assumptions to question whether they are appropriate.

3. Failed to interfere until problems become serious.

4. Focused attention on irregularities, mistakes, exceptions, and deviations from

standards.

5. Avoided getting involved when important issues arose.

Organizational commitment questions. To measure organizational

commitment, participants marked the affective and continuance scales on the Three-

Component Model (TCM) Employee Commitment Survey. The instrument used a 5-

point Likert-type scale ranging from 1 to 5, with 1 being strongly disagree and 5 being

strongly agree.

1. I would be very happy to spend the rest of my career with this organization.

2. I really feel as if this organization's problems are my own.

3. I do not feel a strong sense of belonging to my organization.

4. I do not feel emotionally attached to this organization.

5. I do not feel like part of the family at my organization.

6. This organization has a great deal of personal meaning for me.

7. Right now, staying with my organization is a matter of necessity as much as

desire.

8. It would be very hard for me to leave my organization right now, even if I

wanted to.

9. Too much of my life would be disrupted if I decided I wanted to leave my

organization now.

10. I feel that I have too few options to consider leaving this organization.

11. If I had not already put so much of myself into this organization, I might

consider working elsewhere.

12. One of the few negative consequences of leaving this organization would be

the scarcity of available alternatives.

Intent to stay questions. To collect data for the intent to stay variable, I asked the

participants to mark the intent to stay scale. The originators of the intent to stay

instrument substantiated the reliability and validity of the instrument for this study. I

modified Ruel’s version of the intent to stay scale to fit the purpose of this study. The

questions on the instrument used a 5-point Likert-type scale: 1 = I will stay less than 2

years, 2 = I will stay 2 to 5 years, 3 = I will stay 6 to 10 years, 4 = I am undecided, 5 = I

will stay until full Social Security retirement age.

Theoretical Framework

The intent of this study was to examine the relationship between direct leaders’

leadership styles, junior executives’ organizational commitments, and junior executives’

intent to stay with their organization. In studying these relationships, motivation theories

provided a realistic method for formulating a theoretical framework. The content of

motivation theories focused on specific factors that motivated an individual at work

(Lamptey, Boateng, & Antwi, 2013).

Motivation refers to the initiating and guiding force of goal-oriented behaviors

(Smith, 2009). In attempts to explain the concept of motivation, researchers have

developed several motivation-based theories (Maslow, 1943; McClelland, 1985; Vroom,

1964). Classified as internal (intrinsic), external (extrinsic), and process theories,

motivation theories attempt to explain and predict unexplained recognizable physical

behaviors (Smith, 2009). No single theory covers all the drivers of motivation; each

theory focuses only on specific variables of observable behaviors (Smith, 2009).

Internal (intrinsic) theory focuses on a person’s internal motivation factors

(Smith, 2009). Internal (intrinsic) motivation is a yearning quest to fulfill one’s desire

(Cho & Perry, 2012). A good example of an internal theory is Maslow’s (1943) hierarchy

of needs theory. Maslow developed a motivation theory that goes beyond physical and

financial needs of an individual and includes the emotional and interpersonal needs that

lead to motivation. Maslow’s hierarchy of needs includes five categories of needs

grouped into theory X and theory Y. Theory X includes physiological, safety, security,

and security needs, while theory Y includes social, esteem, and self-actualization needs

(Maslow, 1943).

External (extrinsic) theories emphasize external elements, such as consequences

of behaviors and external incentives, as drivers for motivation (Smith, 2009). Extrinsic

motivation refers to accomplishing a task for reasons that originate from outside of the

self (e.g., rewards), (Achakul & Yolles, 2013). Maslow’s (1943) hierarchy of needs has

elements of both internal and external theories. McClelland’s (1985) needs theory is a

good example of an external theory. McClelland’s needs theory assumes that three

needs—the need for achievement, need for power, and need for affiliation—are the

drivers of motivation.

Process theories focus on the interactions between an individual and the

environment (Smith, 2009). In developing the expectancy theory, Vroom (1964)

attempted to explain motivation based on how a person valued performance. Vroom’s

expectancy theory is an excellent example of an external theory (Smith, 2009). Vroom’s

expectancy theory assumes that people expect certain rewards or consequences for their

behaviors or performances and that there is a relationship between effort and

achievement.

Motivation theories provide a solid foundation for understanding the relationship

among leadership style, organizational commitment, and intent to stay. Understanding

motivation theories can allow business leaders to understand and meet the needs of their

employees (Smith, 2009). Motivation relates to all the three variables used in this study.

Prewitt, Weil, and McClure (2011) described leadership as the process of motivating

people toward achieving goals that are beneficial to their organization. Galletta,

Portoghese, and Battistelli (2011) found positive relationships among motivation, intent

to stay, leadership styles, and organizational commitment. Figure 1 illustrates the

theoretical framework used in this study.

Figure 1. Motivation theory model and key components specific to leadership styles,

organizational commitment, and intent to stay.

Motivation was an essential factor for measuring retention (Alarcon & Edwards,

2013). Motivation theory relates to leadership styles, organizational commitment, and

intent to stay with a company. Understanding motivation theories helps leaders identify

drivers of individual motivation that can promote willingness to remain with a company.

Operational Definitions

Intent to leave: Intent to leave denotes an employee’s contemplation of the

probability of leaving an organization in the future (Vadell, 2008).

Intent to stay: Intent to stay denotes an employee’s expected plan of remaining in

an organization (Vadell, 2008).

Junior executive: Junior executive is a title given to a novice executive training

under a senior executive (Pang &Yeo, 2012).

Leadership: Leadership is a mutual synergy between leaders and followers

(Kopperud, Martinsen, & Humborstad, 2014).

Assumptions, Limitations, and Delimitations

Assumptions

According to Simon (2011), assumptions are events that are out of one’s control

but presumed to be true. For example, if a researcher conducts a survey, the assumption is

that people will answer the questionnaire truthfully. Three assumptions underlay this

study. The first assumption was that the participants would respond truthfully and

accurately complete the survey. The second assumption was that the participants would

understand the content of the questionnaires. The third assumption was that only junior

executives would participate in the survey.

Limitations

Simon (2011) defined a limitation as a potential weakness in a study that is out of

the researcher’s control. Researchers can find limitations in everything humans do. If a

researcher uses a convenience sample, as opposed to a random sample, the study’s results

are only a suggestion without application to the general population. For example, if one is

looking at a specific aspect, say achievement tests, the information is only as good as the

test itself. Another limitation can be time. A study conducted during a specified period

may represent a snapshot of that time and may depend on the conditions of the period

(Salthouse, 2011). The researcher must explain the limitations in the study without

changing the outcome of the study.

The first limitation of this study was that the results related only to junior

executives. The results of this study might change when using information from

individuals of lower-level management positions change when using information from

individuals of lower-level management positions. The second limitation of this study was

time. Because Walden University requires completion of a study within a year from

Institutional Review Board (IRB) approval, the data collection for this study involved a

cross-sectional or a single-point-in-time data collection strategy.

The third limitation related to the questions on the survey questionnaire.

Although the questions resulted from a comprehensive evaluation of the literature review,

unasked questions might have provided additional information related to executives’

beliefs. These limitations present opportunities for future research.

Delimitations

Simon (2011) defined delimitations as those characteristics that define the

boundaries and limit the scope of one’s study. Delimitations are factors that are in the

researcher’s control. Delimiting factors include the research questions, choice of

objectives, theoretical perspectives, variables of interest, and the population one choses to

investigate. The first delimitation was the problem itself. I could have chosen other

related problems, but I screened off or rejected those problems. The purpose statement

also includes an explicit or implicit understanding of what the study will not cover and

explains the intended accomplishments of the study.

The scope of this study included only junior executives employed in the southern

region in the United States. The design of this study focused on junior executives and not

all levels of management. Results of this study may not apply to other executives’

intention to stay with a company.

In summary, the assumptions of this study related to the truthful responses of the

participants to the survey questions, as well as the accurateness of the information

provided. The limitations included the participants’ willingness and availability to

participate within the set period for this study. Delimitations related to the selected

population of participants in the study. Integrating the factors of assumptions, limitations,

and delimitations articulated the scope of this study.

Significance of the Study

The aim of this study was to examine the relationships among leadership style,

organizational commitment, and intent to stay in an organization. Examination of these

relationships among executives was particularly notable for understanding underlying

factors of high attrition rates in this population to reduce future shortages. The results of

the study may benefit businesses by adding to the field of knowledge that develops future

leaders and business practices.

The outcomes of the study could prove crucial for developing a course of action

to identify and reconcile concerns regarding leadership style and commitment levels

among executives into long-term strategies that encourage executives to continue their

commitment. Viewing how both leadership styles and commitment levels affect intent to

remain in an organization may contribute to successful business practices. Implications of

the results of this research toward social change include possible reduction in training

costs to an organization, employment stability in host cities, and retaining expertise and

knowledge of company operations.

Value to Business and Social Impact

This doctoral research encompasses a host of information to help business leaders

of organizations of all sizes. The extensive training and leadership skills executives

acquire in various business industries are marketable talents desired by competitive

businesses. Companies may benefit from this research in developing retention strategies

to retain top talent employees, which would limit attrition cost. The recommended

practices in this study might assist companies in tracking and calculating attrition levels.

Gurunathan and Vijayalakshmi (2012) claimed that an organization with an 80%

employee retention rate is a successful business.

Society could benefit from the results of the research. I have provided a

framework to uncover vulnerability in the effectiveness of leadership style and

organizational commitment. The results of this study could be of value both to business

and to society, as they are interdependent. Companies are key financial contributors to

society and the principal institutions of wealth, investment, and employment. Companies’

decisions and actions could resonate throughout society.

Contribution to Business Practice

The results of this study could be of benefit to junior executives, business leaders,

and businesses in general. Business leaders may benefit from this study by reducing the

employee attrition rate and reevaluating strategies and policies to retain valued

employees (Saniewski, 2011). The outcomes of the research could increase an

organization’s retention strategies to improve employee retention practices, lower upfront

costs of training new hires, and reduce the limited job fit between an employee and the

company.

The results of the study may prompt change to incentive programs. The results

could also lead to a more realistic evaluation of organizational stability. This study may

be of benefit to local government, local communities, and society in supporting

recognition of the significant effect that leadership style and organizational commitment

have on the mission of the organization.

Implications for Social Change

The results of this study could serve as an aid in reducing organizational spending

in the federal budget without compromise to national security. This cost reduction may

result in benefits to stakeholders including creditors, employees, customers, and the

government by changes in policies, practices, and systems of a company. The retention of

qualified junior executives may allow organizations to maintain constant workforce

stability and reduce the cost of retraining new hires. Retaining these junior executives

could benefit society through reduced prices for products and services, which leaders

could equate to cost savings in new hires and compensation benefits. Implications of the

results of this research toward social change include possible reduction in organizational

training costs, increases in employment stability, and tax savings to society.

In summary, the results of this study could benefit business practices as well as

promote social change. The results of the study could improve business practices by

increasing the awareness of business and government leaders concerning factors that

affect retention of employees. These results could be a valued aid in planning and

implementing retention programs. Retaining experienced and qualified junior executives

could increase organizations’ bottom line. This study could foster social change by

serving as a resource for junior executives, business organization leaders, company

stakeholders, and government agencies.

A Review of the Professional and Academic Literature

The objective of this study was to examine the relationship between leadership

style, organizational commitment, and junior executives’ intent to stay with a company.

In the process of achieving the goal of this study, I considered the following research

questions and hypotheses:

Research Question 1: What is the relationship between leadership style and intent

to stay with a company?

H10: Direct leaders’ leadership styles do not significantly statistically correlate

with junior executives’ intent to stay with a company.

H1a: Direct leaders’ leadership styles do significantly statistically correlate with

junior executives’ intent to stay with a company.

Research Question 2: What is the relationship between organizational

commitment and intent to stay with a company?

H20: Executives’ organizational commitment does not significantly statistically

correlate with junior executives’ intent to stay with a company.

H2a: Executives’ organizational commitment does significantly statistically

correlate with junior executives’ intent to stay with a company.

Synopsis of the Literature Review

The EBSCOhost database served as the search engine for this literature review

using the key words leadership, leadership style, affective commitment, continuance

commitment, and intent to stay, resulting in a list of reliable sources. These sources

included dissertations, books, and scholarly journal articles. The main source of the

literature review articles was the online multidisciplinary research database EBSCO,

which has an infrastructure that includes several databases such as Academic Search,

Business Source Complete, ABI/INFORM Global, ProQuest, Google Scholar, Science

Direct, ERIC, Sage Journals, PSY Info, WorldCat, and Thoreau. Additional sources for

the literature review came from the University of Roanoke and the Major Hilliard Public

Library.

The initial research provided a plethora of peer-reviewed articles from primary,

secondary, and tertiary sources. To meet the Walden University DBA requirements, the

document search focused on articles published from 2011 to 2015. To maintain academic

rigor, the final study contained only peer-reviewed articles, dissertations, conference

proceedings, and books. Table 1 summarizes the sources used in this literature review.

Table 1

Synopsis of Sources in the Literature Review

Reference type

Total

Less than 5

years

Greater than 5

years

Research-based peer reviewed journals

150

143

Dissertations

Seminal and contemporary books

Websites

This literature review includes relevant current and previous studies related to the

relationship among leadership style, organizational commitment, and intent to stay with a

company. The review starts with a section on leadership, follows with a section on

organizational commitment and a section on intent to stay, and ends with a summary of

the studies reviewed. Topics covered in this literature review includes the definition of

leadership, leadership theories, leadership styles, leadership in businesses, drivers of

organizational commitment, types of organizational commitment, organizational

commitment with a company, the relationship between leadership and intent to stay,

organizational commitment and intent to stay, and the factors that drive intent to stay.

Figure 2 represents the flow of the literature review.

Figure 2. Literature review organization for examination of leadership styles,

organizational commitment, and a junior executive’s intent to stay with a company.

Leadership Style

Understanding the concept of leadership is essential in examining the relationship

between leadership style and intent to stay. This section includes relevant studies related

to the concept of leadership. Topics covered in this section include the definition of

leadership, leadership theories, leadership styles, and leadership with a company.

Definition of leadership. Leadership is a crucial concept for any organization.

The meaning of this concept varies based on the circumstances. This subsection of the

literature review covers relevant studies related to the definition of the concept of

leadership.

Organizations need strong leaders to inspire and maintain their employees.

The concept of leadership has attracted the attention of scholars and practitioners to

recognize that leaders can influence the synergy in an organization (Dinh et al., 2014).

Leadership is a key factor that world leaders should evaluate to remain competitive in this

economy (Arias-Bolzmann & Stough, 2013). Choi (2012) asserted that leadership is

having the ability to influence individuals from diverse backgrounds to come together in

harmony. Because of its pivotal role in the relationship between leaders and followers,

the concept of leadership has been a riveting topic in the business world (Ruiz, Ruiz, &

Martínez, 2011). Leadership plays an important role in improving organizational

citizenship behavior, job satisfaction, organizational commitment, innovation, and

organizational loyalty (Tsai & Su, 2011). Yammarino (2013) and Gentry and Sparks

(2012) agreed that leadership stimulates the motivation of cohorts to implement change

toward an organization’s desired future. The success of any organization in any domain

or field depends on the effectiveness of the leader of that organization (Parris & Peachey,

2013).

Despite the growing interest of scholars and practitioners in the concept of

leadership, the definition of the concept remains vague. The word leadership suffers from

difficulty in its definition (Volckmann, 2012). The definition of leadership varies based

on the source and the person who defines it (Rupprecht, Waldrop, & Grawitch, 2013).

The definition of leadership may also vary based on geographical location and culture

(Dunnagan et al., 2013). Knowing the different meanings associated with the word

leadership is a relevant step in investigating the relationship between leadership styles

and likelihood to stay with a company. Mohammed, Othman, and D'Silva (2012) argued

that the definition of leadership is a critical element in understanding the effect of

different leadership styles in a diversified workplace.

Several researchers have tried to explain the word leadership and develop theories

to promote the understanding of the concept (Ruiz et al., 2011; Volckmann, 2012). In a

recent publication, Kellerman (2012) identified 1,400 definitions and 44 theories of

leadership. Leadership is among one of the most difficult tasks to perform (Kawar, 2012).

Often, people refer to leadership as a system of social influence (Prewitt et al., 2011).

Love and Singh (2011) defined leadership as the process of influencing the relationship

between employees and employers.

Leadership is about influencing the attitudes and behaviors of others (Limbare,

2012). Leadership allows leaders to shape the behavior of their followers (Thomas,

Martin, & Riggio, 2013). The essential core of successful leadership is setting goals and

managing personal and organizational development (Kawar, 2012). Similarly, Prewitt et

al. (2011) argued that leadership is the process of motivating people toward achieving

goals that are beneficial to their organization. Malos (2011) supported the theory that

leadership is a social influence process through which a person can receive support from

another person in achieving a common goal.

Traditional definitions of leadership have often focused on the relationship

between leaders and followers (Kellerman, 2012; Love & Singh, 2011; Rupprecht et al.,

2013). Because organizations withstand the demands of different external stakeholders,

failing to meet the expectations of these external stakeholders can weaken the company’s

survival (Voegtlin, 2011). Leaders should be able to ensure the survival of their

organizations (Voegtlin, 2011). Therefore, the definition of leadership should go beyond

the relationship between leaders and followers and include the relationship between

leaders and all stakeholders (Voegtlin, Patzer, & Scherer, 2012). Ahn and Ettner (2014)

expanded the scope of the leadership definition to include humility, empathy, and

dedication.

This subsection covers relevant studies related to the definition of leadership.

Although there are various definitions of the term leadership, most of the definitions

focus on the relationship between leaders and followers. Researchers have suggested

recently that the definition of leadership should go beyond the relationship between

leaders and followers and include the relationship between leaders and external

stakeholders.

Leadership theories. Researchers in the field of leadership have developed

several theories to advance the understanding of the concept of leadership. Exploring the

different leadership theories provides knowledge in examining the relationship between

leadership styles and likelihood to stay with a company. This subsection of the literature

review includes relevant studies related to leadership theories.

The literature contains a large and growing collection of leadership theories. The

growing interest of scholars and practitioners in developing new management theories

has led to the emergence of a variety of leadership theories (Zhang, Everett, Elkin, &

Cone, 2012). Although more than 44 leadership theories exist (Kellerman, 2012), this

literature review focuses on three prevailing theories: trait theory, behavioral theory, and

situational theory.

Leadership trait theory. Traits refer to a number of behavioral consistencies that

describe people’s conduct (Chen, 2011). Formerly known as the great man theory

(Malos, 2011), trait theory considers a person’s innate specific abilities as the primary

method of leadership (Stentz, Clark, & Matkin, 2012). The main assumption of this

theory is that leaders have specific traits that nonleaders do not have (Malos, 2011).

During the mid-20th century, some scholars opposed the trait theory and argued that there

is no single set of leadership traits (Chen, 2011).

Behavioral theory. Behavioral theory emerged in the mid-20th century following

the increasing popularity of Skinner’s behaviorism (Adams, 2012). This theory focused

on identifying and providing leaders with behaviors to follow to promote the most

positive reactions from subordinates (Mujtaba & Kennedy, 2014). Looking at task-

oriented behaviors, relationship oriented behaviors, and participatory leadership as key

variables, behavioral theories support a relationship between subordinate satisfaction and

group processes (DeRue, Nahrgang, Wellman, & Humphrey, 2011). Behavioral theory is

the best leadership theory to ensure that the best team members of an organization work

together for increased performance (Vieito, 2012).

Situational theory. Situational theory functions with the concept that the behavior

of a strong leader changes according to unpredictable demands (Ramkissoon, 2013). The

main attributes of situational theory include participation, constraint, and cognition of a

problem when seeking information (Kim & Grunig, 2011). Effective leaders are able to

be both task-oriented and relations-oriented based on the situation and the behavior

required to achieve the organization’s goals (Ramkissoon, 2013). Situational leadership

applies to professionals in business, those in government, and community leaders

(Mujtaba & Kennedy, 2014).

Although the number of leadership theories is growing, this subsection of the

literature review covers three theories: trait theory, behavioral theory, and situational

theory. The difference between these theories lies in what a good leader is claimed to be.

The claim of trait theory is that leaders have specific personality traits that nonleaders do

not have. In behavioral theory, no one is born a leader; rather, individuals learn

leadership and develop as good leaders. Trait theory and behavioral theory are similar in

the sense that both theories indicate that a good leader should be able to perform well in

any situation. The declaration of situational theory is that behavior of a strong leader

changes according to random demands. The three leadership theories covered in this

literature review are similar in that they all focus on the relationship between leaders and

followers.

Leadership styles. Leadership style is one of the two independent variables used

in this study. Leaders distinguish themselves from other leaders by their leadership style.

Understanding leadership styles was required to achieve the intent of this study. This

subsection of the literature review covers current and previous studies related to the

different leadership styles.

Since the 1980s, a large body of knowledge has been devoted to the analysis and

comparison of different leadership styles (Greer & Carter, 2013). A leadership style is a

behavior method used by a leader to resolve organizational issues (Imanzadeh,

Esmaeilzadeh, Elyasi, & Sedaghati, 2012). The classifications of leadership help define

not only the relation between the individual in the position of leadership and the

organization’s performance, but also leadership mechanisms of traits, behaviors, affect,

and cognition, and whether the characteristics relate to the leaders, followers, or goals of

the organization (Eberly, Johnson, Hernandez, & Avolio, 2013). Leaders use different

leadership styles to influence their followers (Greer & Carter, 2013). No single leadership

style can address all organizational issues (Malik, 2012). Each leadership style has its

own set of good and challenging characteristics.

Various classifications of leadership styles exist in the literature (Imanzadeh et al.,

2012; Limbare, 2012). A leader’s style of leadership demonstrates the leader’s values,

norms, beliefs, and ideas (Iqbal, Inayat, Ijaz, & Zahid, 2012). Early studies on leadership

style focused on charismatic, inspirational, and visionary leadership styles (Groves &

LaRocca, 2011). Reddin (as cited in Limbare, 2012) categorized the behavior of leaders

into eight leadership styles: (a) deserter leadership, (b) missionary leadership, (c)

autocratic leadership, (d) compromised leadership, (e) bureaucratic leadership, (f)

developer leadership, (g) benevolent autocratic leadership, and (h) executive leadership

(Limbare, 2012). Iqbal et al. (2012) identified the (a) democratic leadership style, (b)

autocratic leadership style, (c) task-oriented leadership style, (d) relationship-oriented

leadership style, (e) transformational leadership style, and (f) transactional leadership

style. Burns (1978) initiated the idea of transactional leadership, making a distinction

between transactional and transformational leadership styles.

The laissez-faire leadership style emerged later (Sahaya, 2012). Imanzadeh et al.

(2012) summarized leadership styles into three main types, including transformational

leadership, transactional leadership, and laissez-faire leadership. The laissez-faire

leadership is the newest category of the leadership styles (Imanzadeh et al., 2012; Sahaya,

2012). Transactional and transformational leadership styles are the focus of this research.

Iqbal et al. (2012) argued that transformational and transactional leadership are the most

influential leadership styles.

Transformational leadership. A successful leader in today’s global marketplace

is contingent upon a leader’s ability to communicate and encourage positive changes to

capture the mindset of cohorts (Fairhurst, & Connaughton, 2014). Leaders should be able

to formulate and develop ideas that could increase productivity and services to promote a

profitable outcome for the organization (Vaccaro, Jansen, Van Den Bosch, & Volberda,

2012). Leaders often rely on their leadership style in performing their duty.

Researchers have addressed transformational leadership in the past 3 decades

(Zhu, Sosik, Riggio, & Yang, 2012). Transformational leaders develop a plan for the

future and inspire followers toward achieving results beyond what would normally be

expected (Nielsen & Daniels, 2012). These leaders have the ability to influence followers

to go beyond requirements and surpass their own interests for the goals (Sahaya, 2012).

The behaviors of a transformational leader include inspirational motivation, idealized

influence, intellectual stimulation, and individualized consideration (Shin, Kim, & Bian,

2012). Although very effective (Sahaya, 2012), the behaviors of transformational leaders

might lead to difference processes, based on the situation and the industry (Hoffman,

Bynum, Piccolo, & Sutton, 2011). A diverse leadership style may be useful in one field

and ineffective in another industry (Hoffman et al., 2011).

Transactional leadership. Transactional leadership consists of rewarding

followers for their performance (Sahaya, 2012). With the transactional leadership style,

leaders define performance requirements and the rewards followers could receive when

they achieve these performances (Zhu et al., 2012). Transactional leaders may also define

compliance standards and corrective actions for followers who fail to comply with these

standards (Overbey, 2013). Because it is reward-based, Sahaya (2012) argued that the

effectiveness of transactional leadership might be short-term.

The literature presented different classifications of leadership styles; however, this

literature review covers two popular leadership styles including transformational

leadership and transactional leadership. Although both transformational and transactional

leaders focused on motivating followers toward achieving the organization’s goals, these

two categories of leaders are different in the way they inspire followers. While

transformational leaders focused on arousing passion in their followers to motivate them,

transactional leaders rely on bonuses and incentives to encourage followers (Breevaart et

al., 2014).

Leadership in business. Leadership is a matter of historical interest in global

business programs (Morrison, 2013). Researchers in business literature asserted the role

of responsible leadership is to measure the variables of the relationships in fostering

organizational success to balance the success of the business (Stone-Johnson, 2013).

Ethical decisions and behavior of leaders shape the employee behaviors in the climate of

the workplace (Zhang, Walumbwa, Aryee, & Chen, 2013).

Ahn and Ettner, (2014) examined other behaviors such as humility, empathy, and

dedication as better shaping attributes than focusing solely on the leader position of

power as a source of leadership influence. Tsai and Su (2011) suggested including

employees in the decision making process to provide the employees with a sense of

ownership. This approach showed effectiveness in promoting organizational citizenship

behavior, job satisfaction, organizational commitment, innovation, and organizational

loyalty.

This section of the literature review covered relevant studies related to the concept

of leadership. Topics covered in the section include definition of leadership, leadership

theories, leadership styles, and leadership in the business. Researchers have investigated

various aspects of leadership and its relationship with employees’ intent to stay with a

company. The concept of leadership has different definitions, several theories, and

different styles.

Organizational Commitment

The type and level of organizational commitment influenced an employee’s intent

to stay or leave an organization. One of the goals of this study was to assess how two

types of organizational commitment, continuance and affective, relate to junior

executives’ intent to stay with a company. For a better understanding of this relationship,

it was a necessity to understand the concept of organizational commitment. This section

of the literature review covers relevant studies related to organizational commitment. The

section begins with a brief overview of organizational commitment and included topics

such as drivers of organizational commitment, types of organizational commitment, and

organizational commitment in business.

Organizational commitment is an employee’s desire to belong to an organization

and an employee’s willingness to make extra effort for the benefit of the organization

(Sani, 2013). Organizational commitment drives many workplace related behaviors and

attitudes such as satisfaction, organizational citizenship, and intent to stay or leave

(Taing, Granger, Groff, Jackson, & Johnson, 2011). The need for retaining employees

who can add value to an organization has become a problem for business leaders

(Balassiano & Salles, 2012). The concept of organizational commitment has intrigued

scholars and practitioners for many years (Morrow, 2011).

Researchers in the field of management and behavioral sciences describe

organizational commitment as a major influence in the relationship between individuals

and organizations (Rehman, Shareef, Mahmood, & Ishaque, 2012). Ellenbecker and

Custman (2012) defined organizational commitment as a personal attachment and the

desire to stay with a company for various reasons. Similarly, Dey (2012) argued that

organizational commitment was the level of attachment that employees have to their

employing organizations, their willingness to work on behalf of these organizations, and

their likelihood to remain members of the company. All these definitions focused on the

bond between employees and their employing organizations.

Drivers of organizational commitment. Many work and nonwork related factors

drive an employee’s organizational commitment. Understanding the drivers of

organizational commitment is vital in examining the relationship between organizational

commitment and intent to stay in an organization. This sub-section of the literature

review covers relevant studies related to drivers of organizational commitment.

Several factors influence organizational commitment among employees (Dey,

2012). Farjad and Varnous (2013) examined the relationship between several dimensions

of quality of work life and organizational commitment, using data from staff managers

and deputies from a communications and an infrastructure company. From the chosen

quality of work life dimensions, the results of the study indicated that the effects of

health, security, work conditions, and development of human capabilities were the

highest on organizational commitment (Farjad & Varnous, 2013). A year earlier, Dey

(2012) argued that a confident practice of employers increases organizational

commitment. Procedural justice also affects organizational commitment (Gumusluoglu,

Karakitapoğlu-Aygüna, & Hirst, 2013).

Job satisfaction is another key driver of organizational commitment (Qamar,

2012). Gallato et al. (2012) argued that leadership and organizational culture have a

significant influence on job satisfaction. Understanding this relationship is likely to help

employers increase organizational commitment among employees (Gallato et al., 2012).

Using survey data from 247 middle level managers in private sector, Srivastava (2013)

examined the relationship between job satisfaction and organizational commitment. The

results showed a positive relationship between job satisfaction and organizational

commitment.

Job stressors and emotional exhaustion can also affect organizational commitment

(Kemp, Kopp, & Kemp, 2013). Kemp et al. (2013) used qualitative and quantitative data

from 435 professional truck drivers to examine the relationship between job stressors,

emotional exhaustion, and organizational commitment. The results indicated that a

positive relationship exists between job stressors and emotional exhaustion. Kemp et al.

also showed these two variables have negative effects on organizational commitment.

Leroy, Palanski, and Simons (2012) introduced authentic leadership and integrity

as another set of drivers of organizational commitment. Using survey data from 49 teams

in the service industry, Leroy et al. investigated how authentic leadership and integrity

relate to one another in driving organizational commitment. The results showed a positive

relationship between authentic leadership and affective organizational commitment,

mediated through integrity. Similarly, Khan, Hafeez, Rizvi, Hasnain, and Mariam (2012)

found a relationship between leadership style and organizational commitment.

Furthermore, a study by Fritz, O'Neil, Popp, Williams, and Arnett (2013) also supported

the positive relationship between behavioral integrity and organizational commitment.

This subsection included a review of literature related to factors that drive an

employee’s organizational commitment. Tourigny, Baba, Han., & Wang (2013) and

Leroy, Palanski., & Simons (2012) have found factors such as authentic leadership,

integrity, job stressors, emotional exhaustion, job satisfaction, health, security, work

conditions, and development of human capabilities to be the drivers of organizational

commitment. Understanding how these drivers affect organizational commitment

explains the role of organizational commitment as an independent variable in this study.

Types of organizational commitment. As the need of retaining good employees

increase, it is particularly beneficial to establish a stronger connection between these

employees and their employing organizations. Based on the type of connection

employees have with their employer, organizational commitment can be affective,

continual, and normative (Wilson, 2014). This sub-section of the literature review covers

relevant studies related to three types of organizational commitment: affective

commitment, continuance commitment, and normative commitment.

Affective commitment. Affective commitment is an employees’ emotional

attachment to his or her organization (Leroy et al., 2012). Emotional attachment does not

reflect the obligation to commit to an organization (Jussila, Byrne, & Tuominen, 2012).

In an affective organizational commitment, employees commit because of good feelings,

sense of belonging, and satisfaction (Lee & Kim, 2011). Jussila et al. (2012) argued that

affective organizational commitment is an essential element of a sustainable and

successful corporation.

Continuance commitment. Continuance commitment is the extent to which an

employee commits to an organization because of the consequences related to leaving

(Balassiano & Salles, 2012). Taing et al. (2011) defined two dimensions of continuance

commitment including commitment due to lack of alternative employment opportunities

and commitment due to the perceived sacrifice of investments related to leaving. In the

continuance organizational commitment, employees commit because they need to

(Balassiano & Salles, 2012). Continuance commitment represents a particular concern

because it relies on social and economic costs that employees will face when they break

their commitment with their employing organizations (Jaros, 2012). Ahmadi (2011)

argued that it might be unethical to promote continuance commitment.

Normative commitment. Normative commitment is the extent employees commit

to their employing organizations because of a moral duty (Balassiano & Salles, 2012).

This type of organizational commitment deals with the moral obligations employees feel

to commit to their employing organizations (Gelaidan & Ahmad, 2013). In a normative

commitment, employees commit because they feel a moral obligation to the organization

(Balassiano & Salles, 2012).

Based on the reasons why employees commit to their organizations, Top, Tarcan,

Tekingündüz, & Hikmet (2013) and Meyer (2012) identified three types of organizational

commitment. These types include affective commitment, continuance commitment, and

normative commitment. Emotional attachment, consequences of leaving, and moral duty,

are the drivers of affective commitment, continuance commitment, and normative

commitment, respectively. The focus of this study is on affective commitment and

continuance commitment.

Organizational commitment in business. Organizational commitment is a

useful concept in understanding several issues in the business, including intent to stay.

Understanding the issues related to organizational commitment in business is relevant for

the focus of this study. This subsection covers relevant studies related to organizational

commitment in business.

Business leaders need tools that allow them to increase employees’ organizational

commitment within a business (Al Ariss, Cascio, & Paauwe, 2014). Several factors

influence organizational commitment in business (Froese & Xiao, 2012). Using data from

a sample of 197 automotive employees, Froese and Xiao (2012) examined the

relationships between work values, job satisfaction, and organizational commitment.

The results showed a correlation between job satisfaction and affective

commitment, but work value had no effect on organizational commitment. Khasawneh,

Omari, and Abu-Tineh (2012) analyzed survey data from 340 vocational teachers and

showed a positive relationship between transformational leadership of school principals

and organizational commitment of vocational teachers. Using data from 150 bank

employees, Akhter, Ghayas, and Adil (2012) found a positive relationship between self-

efficacy and optimism and self-efficacy and organizational commitment.

This subsection covered literature related to organizational commitment to a

business. The review focused on the drivers of organizational commitment in business.

The literature review indicated that factors such as self-efficacy, optimism, leadership

style, and job satisfaction are the drivers of organizational commitment in business.

In summary, as the need of retaining skilled employees increase, business leaders

are facing the challenge to increase organizational commitment. Several factors such as

job satisfaction, self-efficacy, optimism, and leadership drive organizational commitment

(Albrecht, Bakker, Gruman, Macey, & Saks, 2015).

Based on these drivers, Top, Tarcan, Tekingündüz, & Hikmet (2013) and Meyer

(2012) identified three types of organizational commitment including affective,

continuance, and normative commitments. The desire, the need, and the obligation to

commit describe affective, continuance, and normative commitments, respectively.

Intent to Stay

The relationship between leadership style, organizational commitment, and intent

to stay with a company was the focus of this study. Intent to stay was the dependent

variable in this study. Intent to stay is a strong predictor of turnover; therefore, factors

affecting intent to stay are likely to affect turnover as well as retention. This section of

the literature review covered relevant studies related to intent to stay, retention, and

turnover. The section started with a brief overview of the concept of intent to stay and

covered literature related to the relationship between leadership and intent to stay;

organizational commitment and intent to stay; and the factors that drove intent to stay.

Employee retention is an employer’s retentive practice with an aspiration to

persuade employees to remain with the organization (Sandhya & Kumar, 2011).

Retaining skilled employees is a competitive challenge, particularly during the economic

recovery phase, and increases global competition with its demands for skilled workers

(Dunnagan et al., 2013). Employee retention has become one of the main challenges for

many organizations today (Moussa, 2013). Most employees leave their hiring

organizations within the first 5 years of employment (Bagga, 2013). In 2008, the U.S.

Bureau of Labor Statistics (USBLS) reported that 30% of employees leave their hiring

organizations within the first 2 years of employment, and more than 50% leave within the

first 5 years (Ballinger, Craig, Cross, & Gray, 2011). According to Ballinger et al. (2011),

the cost associated with hiring and training an employee ranges from 25% to extrinsic

awards such as salary increases and other financial benefits to retain top talent.

Leadership and intent to stay. Leaders’ abilities to inspire, motivate, and satisfy

their employees are significant drivers of employees’ intent to stay with their

organizations (Shuck & Herd, 2012). Leaders who are more effective are likely to retain

their employees. Reviewing what previous studies found on the relationship between

leadership and intent to stay proved vital for this study. This sub-section of the literature

review covered relevant studies related to the relationship between leadership and intent

to stay.

Costs associated with employee turnover, increasing employee retention, and

increasing turnover has become a prominent topic of debate in both scholars’ and

practitioners’ perspectives (Kim & Jogaratnam, 2010). As the intent to stay is the best

predictor of turnover, Brewer, Kovner, Greene, Tukov-Shuer, and Djukic (2012) factors

affecting intent to stay are likely to affect turnover. This subsection of the literature

review covered studies related to the relationship between leadership style and either

intent to stay or to retire.

In a case study using an insurance company, Cotton and Stevenson (2008)

investigated the effect of transformational leadership on employees’ intent to stay with

their organization during a scandal-exacerbated decline. The results showed a positive

correlation between CEO’s transformational leadership and employees’ intentions to stay

with the organization. The study by Cotton and Stevenson focused only on

transformational leadership and did not include other leadership styles. The reason for

using transformational leadership in the study was that Cotton and Stevenson believed

that transformational leadership is the leadership style needed during a scandal-

exacerbated decline.

Kim and Jogaratnam (2010) investigated how individual and organizational

factors affect job satisfaction and employee intent to stay in the hotel and restaurant

industry. In their study, Kim and Jogaratnam used data from a survey of 221 hotel and

restaurant employees. Direct leader leadership was one of the independent variables of

the study. Direct leader leadership is a leadership style that focuses on accomplishment of

tasks and welfare of subordinates (Kim & Jogaratnam, 2010). The results of Kim and

Jogaratnam’s study indicated that direct leader leadership does not affect job ratification,

but it is a strong predictor of employees’ intention to stay with the organization.

Liu, Cai, Li, Shi, and Fang (2013) have found substantial relationships between

leadership styles and an employee’s turnover intention. Long, Thean, Ismail, and Jusoh

(2012) conducted an extensive literature review on the relationship between leadership

styles, job satisfaction, and voluntary turnover intention. Long, Thean, Ismail, and Jusoh

study indicated a negative relationship between transformational leadership and turnover

intention, meaning that transformational leadership can increase intention to stay.

Using data from 200 volleyball and softball coaches from National Collegiate

Athletic Association Division 1 in the United States, Wells and Peachey (2011)

investigated the relationship between leadership styles, satisfaction, and turnover

intention. Wells and Peachey used transformational leadership and transactional

leadership as leadership styles variables. The results showed that both transformational

leadership and transactional leadership styles are likely to reduce turnover intention.

Similarly, Furtado, Batista, and Silva (2011) investigated the relationship between

managers’ leadership styles and nurses’ turnover intentions in Portugal. The study sample

consisted of 266 participants including 244 staff nurses and 22 head nurses. The outcome

indicated that persuading leaders and sharing leaders are more likely to reduce nurses’

turnover intentions in Portugal.

To understand the relationship between leadership and retention of nurses, Forest

and Kleiner (2011) discussed the effects of the nursing management style, which is

transactional leadership, on nurses’ retention and recruitment. The outcome indicated that

transactional leadership decreases nurses’ moral, and increases their turnover retention.

Forest and Kleiner recommended transformational leadership and argued that this

leadership style is likely to empower nurses and increase their intention to stay.

This subsection covered literature related to the relationship between leadership

and intent to stay. Researchers covered in this review used different leadership styles as

independent variables. Several studies (Furtado, Batista, & Silva, 2011; Forest & Kleiner,

2011) indicated that leadership style is a reliable predictor of intent to stay; however, the

researchers did not discuss how two or more different leadership styles could affect intent

to stay.

Organizational commitment and intent to stay. One of the objectives of this

study was to examine the relationship between organizational commitment and intent to

stay. Reviewing previous studies related to this relationship prove vital in this study. This

sub-section of the literature review covered relevant studies related to the relationship

between organizational commitment and intent to stay.

Organizational commitment affects several work related outcomes including

employees’ intent to stay or leave their organizations (Olsen, Orr, Bell, & Stuart, 2013).

As the intent to stay is the best predictor of turnover, Brewer, Kovner, Greene, Tukov‐

Shuser and Djukic (2012) factors affecting intent to stay are likely to affect turnover. This

sub-section of the literature review covered studies related to the relationship

organizational commitment and either intent to stay or turnover intent.

To determine the reasons why employees stay with their employers, Hausknecht,

Rodda, and Howard (2009) developed and tested a content model for employee retention.

The study sample included 24,829 workers in the fields of hotel and leisure in China. The

results indicated that organizational commitment is among one of the most mentioned

factors as a reason for staying.

In a quantitative study, Rashid and Raja (2011) used data from 300 employees

from six banks in Pakistan to investigate the relationship between organizational

commitment and employee retention. The results showed a positive relationship between

the two variables. The study of Rashid and Raja also showed that corporate culture has a

mediating effect on the relationship between organizational commitment and retention.

Using survey data from 206 employees from a medical and information

technology company in South Africa, van Dyk and Coetzee (2012) investigated the

relationship between organizational commitment and retention. The results showed a

significant and positive relationship between organizational commitment and retention.

Van Dyk and Coetzee argued that factors such as gender, race, age, and tenure groups

affect the relationship between these two variables.

Although all three types of organizational commitment including affective,

normative, and continuance relate positively to intent to stay, different types of

organizational commitment may have different levels of relationship with intent to stay

(Yücel, 2012). The results of the study showed that both affective commitment and

continuance commitment correlate with turnover intention; but affective commitment and

turnover intention had the strongest relationship.

Researchers have emphasized the mediating role of affective commitment on the

relationship between intent to stay or leave and other organizational factors (Galletta et

al., 2011; Joarder, Sharif, & Ahmmed, 2011). Joarder et al. (2011) demonstrated the

mediating role affecting commitment on the negative relationship between human

resource management practices and turnover intention using data from 317 faculty

members of private universities. Through a cross-validation technique, Galletta et al.

(2011) analyzed data from 442 nurses and showed that job autonomy and intrinsic work

motivation relate negatively to turnover intention, with affective commitment as the

mediator. Using data from 20 human resource managers and 1,748 employees from 93

different job groups, Gardner, Wright, and Moynihan (2011) found that affective

commitment plays a critical mediating role in the negative relationship between

empowerment, and skill enhancing practices and turnover intention.

This subsection covered relevant literature related to the relationship between

organizational commitment and intent to stay. Studies reviewed in this subsection used

affective commitment, continuance commitment, and normative commitment as

independent or control variables. Although all the researchers found a positive

association between organizational commitment and intent to stay, the level of

relationship indicated different for the three types of organizational commitment.

Affective commitment and continuance commitment had a stronger correlation with

intent to stay than normative did. Researchers also highlighted the mediating role of

affective commitment in the relationship between intent to stay and other factors such as

job satisfaction, job autonomy, and empowerment.

Drivers of intent to stay. In addition to leadership style and organizational

commitment, several other factors drive employees’ intentions to stay with their

employing organizations. This sub-section of the literature review covered relevant

studies addressing other factors that drive intent to stay. The review focused on the

drivers of intent to stay, turnover, and retention.

G. Chen et al. (2011) found job satisfaction as an important driver of employee

turnover in organizations. G. Chen et al. conducted two different studies to investigate the

relationship between job satisfaction and turnover intention. The sample of the first study

included 198 soldiers from the U.S. Army, 228 soldiers from the British Army, and 198

employees from a British consulting company. In the second study, G. Chen et al.

surveyed 93 MBA students from the United States. The results of the both studies

showed that job satisfaction is a powerful driver of turnover intention. Lopez, White, and

Carder (2014) believed that job satisfaction affects intent to stay. Similarly, Costen and

Salazar (2011) argued that job satisfaction is an important driver of an employee’s intent

to stay with a company.

Compensation policy is a significant driver of intent to stay (Riddell, 2011). Using

employee-employer benchmarking data, Riddell (2011) examined the effect of

compensation policy and employees’ intentions to stay. Riddell focused on pay equality

among individuals within the same hierarchy. The results showed that companies with

egalitarian pay policies have higher retention rates.

Workplace justice is another driver of intent to stay (Cantor, Macdonald, & Crum,

2011). In a study involving data from 604 commercial truck drivers from two different

trucking companies, Cantor et al. (2011) found a positive relationship between workplace

justice and drivers’ intent to stay. Cantor et al. argued that the results of their study

agreed with previous studies. Similarly, using survey data from 163 employees from

various organizations in Malaysia, Poon (2012) found a positive relationship between

organizational justice and employee intent to stay with a company.

A. Smith, Oczkowski, and Smith (2011) found learning within an organization as

a driver of intent to stay. In their study, A. Smith et al. made a distinction between short-

term turnover and long-term skill retention. The study involved data from 300 Australian

organizations. The results indicated that learning decreases short-term turnover and

increases long-term skill retention. A. Smith et al. defined long-term skill retention as an

employer’s confidence in retaining skills necessary to achieve the organization’s long-

term goals.

This subsection covered literature related to factors that drive intent to stay. In

addition to leadership style and organizational commitment, researchers have found

factors such as job satisfaction, compensation, workplace justice, and learning within an

organization to be drivers of an employee’s intent to stay with a company. This review

reinforces the assumption that factors that influence retention and turnover also affect

intent to stay or leave.

The intent to stay section of the literature review covered relevant studies related

to intent to stay and its relationship with organizational commitment and leadership. The

section also covered studies related to other drivers of intent to stay. Researchers who

conducted previous studies found leadership to be an important driver of intent to stay;

however, researchers reviewed in this section did not address how different leadership

styles affect intent to stay. The outcome of studies on the relationship between

organizational commitment and intent to stay showed three patterns.

First, all three types of organizational commitment positively affect intent to stay

(Yücel, 2012). Second, affective commitment has a stronger relationship with intent to

stay than continuance commitment. Finally, affective commitment plays a mediating role

in the relationship between other organizational factors and intent stay. In addition to

leadership style and organizational commitment, several other factors such as job,

compensation policy, workplace justice, and learning within the organization affect intent

to stay.

The literature review covered relevant previous and current studies related to the

relationship between leadership style, organizational commitment, and intent to stay. The

organization of this literature review consisted of three main sections, including a section

on leadership, a section on organizational commitment, and a section on intent to stay.

Topics covered in the leadership section included a definition of leadership, leadership

theories, leadership styles, and leadership in business. A thorough review of the literature

revealed that the concept of leadership has various definitions, theories, and styles.

Organizational commitment included topics such as drivers of organizational

commitment, types of organizational commitment, and organizational commitment in a

company. Several factors such as job satisfaction, hope, health, security, emotion, and

leadership drive organizational commitment. Researchers found three different types of

organizational commitment including affective, continuance, and normative

commitments. The desire, the need, and the obligation to commit describe affective,

continuance, and normative commitments, respectively.

Topics covered in the intent to stay section included; leadership and intent to stay,

organizational commitment and intent to stay, and other drivers of intent to stay.

Researchers have found leadership to be an influential driver of intent to stay; however,

researchers reviewed in this section did not address how different leadership styles affect

intent to stay (Furtado et al., 2011; Shuck & Herd, 2012). The results of studies on the

relationship between organizational commitment and intent to stay showed three patterns.

First, all three types of organizational commitment positively affect intent to stay.

Second, affective commitment has a stronger relationship with intent to stay than

continuance commitment. Finally, affective commitment plays a mediating role in the

relationship between other organizational factors and intent to stay. In addition to

leadership style and organizational commitment, several other factors such as job,

compensation policy, workplace justice, and learning within the organization affect intent

to stay.

A thorough review of the literature revealed that businesses present a compelling

opportunity to investigate the relationship between leadership style, organizational

commitment, and intent to stay. The results of the studies in this literature review

indicated that leadership affects intent to stay; however, none of the authors of the

reviewed studies addressed how different leadership styles affect intent to stay. This

literature review revealed that affective commitment, continuance commitment, and

normative commitment affect intent to stay; however, this effect is stronger with affective

commitment.

Transition and Summary

The objective of this quantitative correlational study was to examine the

relationship between leadership style, organizational commitment, and junior executive

intent to stay with a company. Section 1 of this study contains the foundation and the

background of the study. This section includes a demonstration of the worthiness of

conducting this study. Topics covered included the background of the study; the problem

and purpose statement; the nature of the study; the research question, hypotheses, and

interview questions; the definition of terms; the assumptions, limitations, and

delimitation; the significance of the study; and the literature review.

Grounded on motivation theories, this study addressed an unknown population

size of executives employed near the southern region in the United States: Alabama,

Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana,

Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas,

Virginia, and West Virginia. The sample of the study included 107 junior executives

located in the above geographic locations. The results of the study are likely to apply only

to junior executives. The results of this study may benefit businesses as well as the

military by increasing the understanding of senior leaders on the factors affecting

employee retention. The results may benefit social change by providing a means to

increasing the retention of employees, hence, improving productivity, and profits. The

study results may add to the literature by contributing to the body of knowledge related to

employee retention. Section 2 of the study covers the strategy used to select participants,

collect, validate, organize, and analyze data. Section 3 covers the representation of the

results, the implication of the study, recommendation for action, and further research.

Section 2: The Project

Section 2 contains further description, in detail, of the facets of this study centered

on predictions relating to the credible outcome of this study. Section 1 of the study

included an introduction to the research, as well as the logic for conducting the study.

This section includes discussions of the strategies used to collect and analyze data as well

as elements such as the (a) purpose of the study, (b) role of the researcher, (c)

participants, (d) research method and design, (e) population, (f) sampling, (g) concerns

related to ethical research, and (h) and reliability and validity.

Purpose Statement

The purpose of this quantitative correlational study was to examine how a direct

leader’s leadership style and junior executives’ organizational commitment relate to a

junior executive’s intent to stay with a company. The two independent variables (Xn)

were the direct leader’s leadership style (X1) and junior executives’ organizational

commitment (X2). The dependent variable was junior executives’ intent to stay with a

company (Y1). The population addressed in this study included 100 junior executives

employed in the southern region. The study results may contribute to social change by

providing senior executives with tools to aid retention through prediction of attrition and

possible reduction of causes of attrition. Retention methods and strategies developed

using this study’s findings may benefit companies in corporate America and

governmental organizations. Findings may provide insight as to when to offer an

incentive such as bonus pay, higher education, and other training options for retention.

Society may further benefit as experienced junior executives remain in their companies to

help sustain communities.

Role of the Researcher

In a quantitative study, a researcher examines the relationship among variables

(Frels & Onwuegbuzie, 2013). When conducting a quantitative research study, a

researcher functions as the instrument and must remain objective about the research and

remain uninvolved with human subjects (Venkatesh et al., 2013). My role as the

researcher in this quantitative study was to compile, organize, analyze, and interpret data

to test the hypotheses and answer the research questions. I maintained the highest ethical

standard possible in every stage of the study.

In addition, I obtained the necessary permissions from the Walden University

Institutional Review Board (IRB) to conduct research. In this process, informed consent

is a vital component. The content of the e-mail invitation to participate/consent form

educated the participants about this study before they decided to participate. Informed

consent allows research participants to understand their rights (Myers & Venable, 2014).

Finally, to ensure that my personal biases and opinions did not affect the study, I used

preexisting surveys validated through empirical research to collect data.

In summary, as the researcher in this study with respect to the data, I followed

steps to collect, compile, organize, analyze, and interpret the results. During each stage of

the study, I sought to maintain the highest ethical standards. Furthermore, I ensured that

my personal biases and opinions did not affect the results of the study.

Participants

This section includes a description of the process used to obtain participants and

protect participants’ rights. Researchers often need participants to collect data. Selecting

the right participants is a decisive stage in any research. This study population consisted

of individuals currently working as junior executives. For the purpose of this study, a

junior executive is a person working as a manager or director under a chief executive

officer (CEO), chief financial officer (CFO), or any senior executive. As such, I collected

data using a nonprobability, purposive sampling technique. Purposive sampling refers to

the targeting of groups based on specific inclusion criteria. Purposive sampling is a

nonprobability sampling technique employed to obtain participants for a study that fit a

specific demographic or other specified criterion when probability sampling cannot be

used (Smith et al., 2011).

The sample size power calculation involved the usage of G*Power 3 to calculate

the required sample size to find significance (Faul, Erdfelder, Buchner, & Lang, 2009).

Using an alpha level of .05, a power of .80, and an effect size of .15, the required sample

size to find significance with three predictors is 77. This sample size was not

accomplishable in the allocated time for the study. The allotted timeframe to conduct the

data collection was 2 weeks. Wertheimer (2015) posited that researchers must maintain

ethical standards, meet legal requirements, abide by the code of conduct, and embrace

social responsibility when conducting research. Conducting the survey online minimized

the probability of harm to the participants of this study.

SurveyMonkey®, an online data collection website, collected the data from the

junior executives in place of me. Upon receiving Walden University IRB approval for the

survey instruments as well as the informed consent form, I entered the information into

the SurveyMonkey application. The application then forwarded the survey to the

participants, collected the data, and returned an electronic version of the data stripped of

participant identifying information to me. The data excluded participants’ identification

to ensure confidentiality. As part of the data collection process, an electronic signed

informed consent form opened the survey.

Upon receipt of the de-identified data, I stored the data in TrueCrypt on my

personal computer, where the data will remain for 5 years. TrueCrypt is a secure and

encrypted electronic storage system. At the end of 5 years, I will permanently delete all

data from my computer. Other researchers can obtain the data from this study upon

written request.

Research Method and Design

The approach used in this study was a quantitative method and correlational

research design using survey methodology to collect data from willing participants. The

aim of this study was to examine the relationship among organizational commitment,

leadership style, and intent to stay. A quantitative method measured the interaction

among variables to answer the research question (Crede & Borrego, 2014). This section

explains the rationale for why the quantitative method was the most appropriate design

for this study, as opposed to a qualitative method or mixed method.

Method

Researchers have three research methods to choose from—quantitative,

qualitative, and mixed method—when conducting a study (Venkatesh et al., 2013).

Researchers explore the contingencies of their studies before making a decision to use a

specific research method (Migiro & Magangi, 2011). The choice of a specific research

method depends on the purpose of the study, type of data used, and method used to

analyze data (Tsai & Su, 2011).

This study was a quantitative study. A quantitative method was appropriate rather

than a qualitative or mixed method for several reasons, including the objectives of the

study, type of data collected, and planned statistical tests. This section covers the

justification for choosing this method over the other two research methods.

Quantitative approaches typically support ideas with deductive reasoning,

whereas qualitative designs focus on the formulation of theory through inductive

reasoning (Welbourne, 2012). Frels and Onwuegbuzie (2013) categorized statistical

studies as quantitative and other methods as qualitative. Furthermore, Frels and

Onwuegbuzie referred to mixed method as a third type of research that uses components

of both qualitative and quantitative methods. Positivist researchers use quantitative

research methods to predict the relationships between variables and subsequently define

these relationships as research questions or hypotheses (Lunde, Heggen, & Strand, 2013).

The purpose of this study, which was to examine the relationship between two

independent variables (Xn), leadership style (X1) and organizational commitment (X2), and

a dependent variable (Yn), intent to stay (Y1), aligned with the principles of a quantitative

research method. Furthermore, the extraction and analysis of numerical data from surveys

were empirical statistical procedure steps. Accordingly, a quantitative method was the

most appropriate method for examining the relationship between variables (Venkatesh et

al., 2013).

A qualitative method was not appropriate for this study because the goal of a

qualitative method is to comprehend individual experiences, actions, and motivations,

rather than test existing theories (Hays & Wood, 2011). A mixed methods approach may

provide additional information not gleaned from statistically testing the hypotheses but

does not align with a deductive reasoning approach. In addition, a mixed methods

approach presented challenges when considering the time and resource constraints in this

study. Mayoh and Onwuegbuzie (2013) postulated that a mixed methods approach

requires a researcher to gather both qualitative and quantitative data and analyze the

information via deductive and inductive methods, respectively.

The choice of a quantitative method for this study proved consistent with recent

similar studies. Bressler (2010) used a quantitative research method to examine the

relationship between organizational commitment and intent to stay among U.S. Army

Reserve soldiers. Similarly, Stowers (2010) used a quantitative research method to

examine the relationship between support and organizational commitment in the United

U.S.States Army Reserve. Moreover, Vadell (2008) examined the relationship between

organizational commitment and intent to stay of Air Force officers via the quantitative

method (Bressler, 2010; Stowers, 2010; Vadell, 2008).

Research Design

The aim of the research was to test the relationship between two independent

variables and a dependent variable. A correlational design was an appropriate strategy

given the nature of the variables. This section includes a discussion of the choice of a

correlational design over an experimental design.

A quantitative study can be either experimental or survey research. Survey

research is also known as correlational research (Venkatesh et al., 2013). According to

Salthouse (2011), a correlation design is a type of descriptive quantitative research that

involves examining possible relationships among variables. In contrast, an experimental

study is appropriate when a researcher manipulates participants to examine the effect of a

specific intervention on these participants (Venkatesh et al., 2013). A correlational design

cannot prove that one variable causes change in another variable; rather, it tests the

relationship between variables (Rowe, Raudenbush, & Goldin-Meadow, 2012). A

correlational research design fit the purpose of this study because this study examined

relationships without manipulations of participants. In studies similar to this, Bressler

(2010), Stowers (2010), and Vadell (2008) used a correlational design in their research.

After considering the different research methods and associated research designs,

I determined that a quantitative research method with a correlational design fit this study.

The quantitative method was the appropriate strategy for this study because the focus of

the study aligned with the objective associated with the quantitative method (i.e.,

examining the relationship between variables). Moreover, correlational design was

appropriate given that the focus of the study was to examine the relationship between

variables without changing the research environment or manipulating participants.

Population and Sampling

The population for this study included junior executives in various companies.

The sample population included 107 junior executives. For the purpose of this study, a

junior executive is a person working as a manager or director under a chief executive

officer (CEO), chief financial officer (CFO), or any senior executive. This section covers

the description of the population for this study and the strategy used to select participants.

Given time and resource constraints, it was not feasible to collect data from the

entire population. To obtain a distribution similar to the one found in the population, I

used a random purposive sampling method to obtain willing participants. The basic

definition of criterion purposive sampling indicates that this sampling method targets a

group within a population based on specific criteria from the researcher (Emmerton,

Fejzic, & Tett, 2012). In support of this approach, Vadell (2008) used purposive sampling

in a quantitative study examining the relationship between organizational commitment

and intent to stay in the U.S. Air Force.

The data collection process for this study included sending the survey to

SurveyMonkey®. Those junior executives who met the three conditions to participate and

were willing to participate completed the survey. The data collection process aligned with

the concepts of purposive sampling in that participants were required to meet three

conditions to be eligible for participation.

At the time of the study, (a) a prospective participant need to be an employed

junior executive, and (b) the prospective participant needed to work in the southern

region of the United States. The participation goal of the study was at least 96 junior

executives. The sample size and the sampling method used in this study were consistent

with similar recent studies.

Specifically, Azeem and Akhtar (2014) invited 210 employees to participate in a

correlational study examining the relationship between job satisfaction and organizational

commitment. Similarly, Alsaraireh, Quinn Griffin, Ziehm, and Fitzpatrick (2014) invited

179 nurses in a correlational study examining the relationship between job satisfaction

and turnover intention. Eligibility criteria for participants of this study included

employment as a junior executive in the southern region of the United States at the time

of the study. The population of this study included 107 junior executives employed in the

south region of the United States who met the criteria to participate in the study.

Ethical Research

Researchers face ethical dilemmas at every stage of their research. Walden

University’s IRB compels each doctoral student to have an approved IRB application and

ethical research training before data collection. This section covers the steps taken to

ensure that this study met ethical requirements.

A copy of the letter of invitation to participate sent by e-mail is located in

Appendix F. In this letter, I introduced myself as the researcher and a student at Walden

University pursuing a Doctorate of Business Administration. The first page of the e-mail

invitation provided informed consent information. The letter contained information on

the purpose behind the study, a statement that participants would receive no incentives

for completion of the survey, and a statement that participants could withdraw from the

study at any time without consequence.

Participants could stop the survey at any point simply by closing the survey. A

participant lost the right to withdraw from the study after stopping or completing the

survey because the survey program replaced identifying information with a code, making

it impossible to connect the individual responses. The informed consent form stated that

participants’ individual identities remained confidential and that I would not collect any

names or other identifying information during the survey.

The informed consent letter included a statement that there were no foreseeable

risks associated with participating in this study and that completing the study might

benefit companies or leadership practices. The letter also contained information about the

role of Walden University’s IRB and the approval process of the IRB prior to collecting

data. Walden University’s approval number for this study is 12-20-13-0182801. Using

the SurveyMonkey® application, I administered the survey instrument. This protected the

privacy and confidentiality of the junior executives who participated in the research

survey.

I provided SurveyMonkey® a written explanation for participants regarding the

data collection instruments and the approximate time to complete the survey. Participants

partaking in the survey received an e-mail with an electronic link to launch the survey.

The survey remained available for participants to self-administer at their convenience.

Participants’ confidentiality, stated on the first page of the online survey, reinforced the

understanding of commitment.

The survey remained open for 2 weeks. Participants received no penalty for

choosing not to complete the survey. At the end of the survey period, SurveyMonkey®

made the data collection accessible to download in an SPSS file from a secured website.

The downloaded data collection remains stored in TrueCrypt on my personal

computer for 5 years, after the publication of my doctoral study, with a plan to delete

after the 5 years expires. TrueCrypt is a secured and encrypted electronic storage system.

Requests for a copy of the data require a written request to me.

This section focused on my knowledge about the importance to adhere to ethical

norms and the standards of conduct in research. Participation in the research study was on

a voluntary basis. By design, participants reserved the right to withdraw from the study at

any time without penalty. Furthermore, I retained the data collected in TrueCrypt on a

password-protected computer, with deletion of all electronic files and destruction of any

paper documents pertaining to the data collection.

Data Collection

Data collection is an essential factor in any field of research. This section

discusses the three subtopics that unified the data collection process. A researcher must

also consider what data will best answer the research questions listed in the study. The

first topic explains the choice of the instrument for this study, which is a web-based

survey. The data collection technique is the second subtopic chosen to collect the data

with the online survey. The concluding topic expands on the data organization techniques

used to organize and secure the data throughout the study.

Instruments

The survey instruments used in this study provided a system to assess the

relationship among leadership style and organizational commitment as independent

variables, and the intent to stay as the dependent variable. Three different instruments

formulated the survey for this study, which included the Multifactor Leadership

Questionnaire, the Three-Component Model, the Employee Commitment Survey, and the

intent to stay scale to measure leadership style, organizational commitment, and intent to

stay. All the instruments used in this study received validation in previous studies;

therefore, a validity test was not necessary in this study (Rahman & Post, 2012). Data

collection instruments produced the same validity score when using data from different

populations and samples (McCrae, Kurtz, Yamagata, & Terracciano, 2011; Rahman &

Post, 2012).

Two Walden University DBA alumni who used quantitative research methods in

their doctoral studies reviewed this study and provided feedback to confirm that the

instruments measured the intended variable. The feedback suggested that the instruments

are likely to provide accurate measure of intended variables. Based on the peer feedback,

I changed the tense of the first word of each sentence in the surveys to fit the specific

context of this study. Such changes would not affect the validity of an instrument (Meyer

& Allen, 2004). This section includes a separate discussion for each of the three

instruments. This section includes a separate discussion for each of the three instruments.

Multifactor leadership scale (MLQ). To collect data on leadership style, I

purchased the MLQ 5X-short form and its manual from Mind Garden. Based on the

license for using the MLQ survey (see Appendix B), five questions were published in the

final paper to ensure information propriety. Both this section and Appendix A include the

five selected questions from the MLQ used to collect data for this study.

According to Bass and Avolio (2004), researchers developed surveys to measure

leadership style; however, these previous surveys ignored important factors such as

inspirational motivation. Bass and Avolio developed the MLQ to cover behaviors of

leaders in a broader range, from laissez-faire leadership to idealized leadership, while

highlighting the difference between effective and ineffective leaders. The MLQ is the

most commonly used instrument to measure transformational and transactional leadership

style (Sahaya, 2012). According to Bass and Avolio, researchers used the MLQ for the

past 25 years to measure leadership effectiveness in various domains including military,

government, correctional, healthcare, manufacturing, education, and nonprofit.

The latest version of MLQ is the Form 5X, which includes 5X-short that includes

45 items and 5X-long that includes 63 items (Bass & Avolio, 2004). Bass and Avolio

(2004) alleged that the 5X-long is more useful for consultants than it is for researchers;

therefore, a researcher should use the form 5X-short. Based on Bass and Avolio’s

recommendation, the MLQ form 5X-short was a reliable instrument to collect data for

this study. The 5X-short has two different types, including a leader form in which the

leaders rate themselves, and the rater form, in which another individual rates the leaders.

Because the focus of this study was on the perception of junior executives about their

leaders’ style, it was more appropriate to use the rater form.

The 5X-short form includes nine different scales with four items each to measure

transformational, transactional, and passive avoidant leadership styles. The 5-point

Likert-type scale items are 0 = Not at all, 1 = Once in a while, 2 = Sometimes, 3 = Fairly

often, and 4 = Frequently, if not always. In this study, only the six scales measured

transformational and transactional leadership styles. The six scales included (a) idealized

attributes, (b) idealized behavior, (c) inspirational motivation, (d) intellectual stimulation,

(e) individual consideration for the measure of transformational leadership, and (f)

contingent reward and management by exception for the measure of transactional

leadership (Bass & Avolio, 2004). To comply with the agreement, I published five

sample questions in this study; three for transformational leadership and two for

transactional leadership. The sample items included:

1. Provided me with assistance in exchange for my efforts.

2. Reexamined critical assumptions to question whether they are appropriate.

3. Failed to interfere until problems become serious.

4. Focused attention on irregularities, mistakes, exceptions, and deviations from

standards.

5. Avoided getting involved when important issues arose.

Using the MLQ form 5X-short, participants rated their previous direct leaders

using the scale of 1 = Not at all, 2 = Once in a while, 3 = Sometimes, 4 = Fairly often,

and 5 = Frequently, if not always. I assigned two scores to each participant based on the

results of the survey. A score for transformational leadership was the average of the

scores from all items measuring transformational leadership and a score for transactional

leadership was the average of the scores from the items measuring transactional

leadership. This score in the data analysis measured the relationship between leadership

style and intent to stay.

The MLQ 5X is a valid and reliable instrument to measure transformational and

transactional leadership (Bogler, Caspi, & Roccas, 2013). To test the reliability of this

instrument, Bass and Avolio (2004) collected and analyzed data from 2,154 individuals;

no self-ratings included. After analyzing the data, Bass and Avolio found reliabilities for

the total items and for each scale ranging from 0.74 to 0.94. According to Yunus (2010),

scores greater than 0.70 indicates strong internal consistency. The sample population data

from 107 participants validated the instrument through the analysis of Cronbach’s alpha

ranging from 0.79 to 0.97. Cronbach alpha provides a means for testing the reliability of a

survey instrument (Yunus, 2010).

Three-Component Model (TCM) Employee Commitment Survey. To measure

organizational commitment, the affective and continuance scales, I used Meyer and

Allen’s (2004) revised TCM Employee Commitment Survey. The academic version of

the instrument as well as the user guide remains available as a free download on the

employee commitment website. The TCM Employee Commitment Survey is a valid

instrument used to measure affective, continuance, and normative commitment (Bressler,

2010). The revised TCM Employee Commitment Survey is an 18-item instrument with

six items for affective commitment, six items for continuance commitment, and six items

for normative commitment (Meyer & Allen, 2004). The items in this instrument are

scaled using a 5-point Likert-type format ranging from 1 to 5 where 1 = strongly

disagree, 2 = disagree, 3 = neither disagree nor agree, 4 = agree, 5 = strongly agree

(Meyer & Allen, 2004).

Because this study focused only on affective and continuance commitments, only

12 items were used to measure affective and continuance commitments. Meyer and Allen

(2004) reversed some questions to force respondents to read each question carefully

instead of going through them haphazardly. To align these items with the purpose of the

study and stronger groupings, I used a 5- point Likert- type format ranging from 1 to 5

where 1 = strongly disagree, 2 = disagree, 3 = neither disagree nor agree, 4 = agree, and 5

= strongly agree (Meyer & Allen, 2004).

Following was the list of the 12 items. This list is also available in Appendix C.

Reversed scored items are marked with R:

1. I would be very happy to spend the rest of my career with this organization.

2. I really feel as if this organization's problems are my own.

3. I do not feel a strong sense of "belonging" to my organization. (R)

4. I do not feel "emotionally attached" to this organization. (R)

5. I do not feel like "part of the family" at my organization. (R)

6. This organization has a great deal of personal meaning for me.

7. Right now, staying with my organization is a matter of necessity as much as

desire.

8. It would be very hard for me to leave my organization right now, even if I

wanted to.

9. Too much of my life would be disrupted if I decided I wanted to leave my

organization now.

10. I feel that I have too few options to consider leaving this organization.

11. If I had not already put so much of myself into this organization, I might

consider working elsewhere.

12. One of the few negative consequences of leaving this organization would be

the scarcity of available alternatives.

The first six items measure affective commitment and the second six items

measure continuance commitment (Meyer & Allen, 2004). To use the TCM Employee

Commitment Survey in research, Meyer and Allen (2004) recommended grouping each

participant’s scores by scale. Meyer and Allen suggested averaging the score of the

individual items to obtain the overall score for each scale. Based on these

recommendations, each participant’s score became part of the affective commitment

score and a continuance commitment score.

Bressler (2010) used the organizational commitment scale to measure affective

and continuance commitment of United States Army Reserve soldiers. The reliability

Cronbach’s alpha (α) coefficient of affective scale and continuance scale of the TCM

Employee Commitment Survey are .72 and .77, respectively (Krishnaveni & Ramkumar,

2008). These are acceptable reliability scores given that they exceed .70 (Yunus, 2010).

To confirm the reliability of the instrument, I gathered data from all participants of the

study to compute the Cronbach Alpha (α).

Intent to stay scale. The modified version of the intent to stay scale was the

instrument used to collect data for the dependent variable (Yn), which was intent to stay

(Y1), (Price & Mueller, 1981). The intent to stay scale uses a single question to measure

an employee’s intention to remain with an organization. The single question was; “Which

of the following statements most clearly reflects your feelings about your future in the

hospital? (a) Definitely will not leave, (b) Probably will not leave, (c) Uncertain, (d)

Probably will leave, (e) Definitely will leave” (Price & Mueller, 1981, p. 546). Several

researchers modified the intent to stay scale to fit their purposes (Garbee, 2006;

Kosmoski & Calkin, 1986; Ruel, 2009). Kosmoski and Calkin (1986) expanded the intent

to stay scale to increase the reliability of the instrument. Garbee (2006) modified the

scale to measure nurses’ intent to stay with three questions and nurses’ intent to leave

with three questions. Ruel (2009) converted Garbee’s three 7-points Likert-type scale

items. A sample question of Ruel’s intent to stay scale was “I intend to stay in my current

job and present university for one year” (p. 43). I modified Ruel’s version into one-item

to fit the purpose of this study. The question on the instrument used a 5 point Likert type

scale, with 1 to 5; 1 = I will stay less than 2 years, 2 = I will stay 2 to 5 years, 3 = 5 to 10

years, 4 = I am undecided, 5 = I will stay until full Social Security retirement age.

The following item included:

1. When do you plan to leave the company?

The question and the intent to stay scale are available in Appendix F. The intent to

stay score was the average of the scores of the question. An instrument cannot be valid

without being reliable (Engbe rg & Berben, 2012). The intent to stay scale is a reliable

instrument (Ruel, 2009). Kosmoski and Calkin (1986) showed an alpha value of 0.90 for

the intent to stay scale. A 0.90 alpha value is a strong reliability score (Yunus, 2010). To

confirm the reliability of the instrument in this study, I computed the Cronbach Alpha (α)

using the data from all participants.

The three instruments in this study measured direct leader’s leadership style,

junior executive’s organizational commitment, and the junior executive’s intent to stay

with a company. The procurement of the MLQ survey and authorization for use are in

Appendix B. The TCM employee commitment and intent to stay scale are free for

academic use and do not require permission to use. Each participant had five different

scores including two scores for the leadership style (transformational and transactional),

two scores for organizational commitment (affective and continuance), and one score for

intent to stay. Five scores per participant provided data to examine the relationship

between leadership style, organizational commitment, and intent to stay.

Data Collection Technique

In a quantitative study, data are in number or numerical form. Data collection

techniques vary among research methods and designs. This section covers the steps used

to collect data for this study. The data collection for this study required the approval of

Walden University’s IRB.

A cross-sectional survey allows a researcher to collect data at one particular point

in time (Francesconi, Sutherland, & Zantomio, 2011). This survey method is popular

because of its rapid turnaround in data collection and the economy of design (Francesconi

et al., 2011). Given the current growth in the use of Internet, an online survey is a rapid

and convenient way to reach a large number of participants in less time. Because of its

low cost and the high speed, an online survey is one of the most popular methods for

quantitative data collection (Vu & Hoffmann, 2011).

SurveyMonkey® automatically created an e-mail invitation from an electronic

roster with access to the survey link to each participant. Each invitation e-mail sent to

participants contained a survey link for participants to click to start the survey. The

participants had to acknowledge informed consent to start the survey. Participants could

withdraw from the survey at any time by closing their web browser.

The survey remained available online 1 week after reaching the minimum number

of responses. After the completion of the survey, SurveyMonkey® stores the data for 5

years behind a secured firewall in a data storage system. Survey data are available by

written request to me.

After receiving collected data from SurveyMonkey®, I stored electronic data on a

private, encrypted electronic file storage system on my personnel computer for 5 years.

The online survey served as the instrument used in this study to collect data from a

purposive sample of 107 junior executives employed in the South Census region in the

United States: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia,

Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina,

Tennessee, Texas, Virginia, and West Virginia. SurveyMonkey® collected the data using

the survey instruments and supplied an electronic file of the data results. SurveyMonkey®

stored the data and I stored the data in TrueCrypt for 5 years until time of deletion and

destruction.

Data Organization Techniques

After collecting data, I organized and prepared the data for analysis. This process

included coding and transforming data in an analyzable format. This section covers the

steps used to prepare and organize the data collected for analysis in this study. The

process of coding and organization of the data began after receiving data from

SurveyMonkey®.

The scores from the MLQ questions provided data to compute the scores for

transformational leadership and transaction leadership constructs. The scores from the

TCM Employee Commitment Survey questions section applied to the affective and

continuance commitment constructs. Finally, the intent to stay score provided the data for

the scores of the questions using the intent to stay scale. The process of data organization

followed the computation. The data did not include any personal information about

participants. To avoid confusion in the data, I coded the data for each participant by a

four-digit alphanumeric code ranging from P001 to PXXX. In this coding, XXX

represented the number of participants, assuming the study had less than 1,000

participants.

For study variables, I coded each question within each instrument by a three-digit

alphanumeric code ranging from Q01 to QXX, with XX representing the number of

questions within a specific data collection instrument. For example, the first and second

questions of the MLQ were Q01 and Q02, respectively. I grouped the coded questions

according to instrument and by scale. The organizational commitment and leadership

style variables included two scales each and the intent to stay includes one scale. Each

participant had a score in each of the five scales; these five scales represented the

variables used in the data analysis. The score of each variable was the average of the

scores of the questions within that variable.

In this study, I coded data for each leadership style, two organization commitment

variables, and the intent to stay variable. The six columns included one column for

participant identification (P001 to PXXX), one column for each of the leadership style

variables, one column for each of the two organizational commitment variables, and one

column for the intent to stay variable. After coding the data and computing the scores for

each variable, I organized the transformed data into six columns in SPSS version 20.

To conduct the data analysis, I used a six-column table. Electronic data remains

stored in TrueCrypt and hard copies stored in a locked container for 5 years.

At the end of 5 years, after the publication of my doctoral study, I will destroy all hard

copies including backup copies of data using a shredding device and permanently delete

all data from my password-protected computer.

After receiving the data from SurveyMonkey®, I coded the data and computed

scores for each variable. Following computing the scores, I organized the data into a six-

column SPSS table for data analysis. The data remain stored in TrueCrypt for 5 years

after the publication of my doctoral study, and deleted afterward.

Data Analysis Technique

The data analysis process for this study focused on testing the hypotheses to

answer two research questions:

1. What is the relationship between leadership style and intent to stay with a

company?

2. What is the relationship between organizational commitment and intent to stay

with a company?

This section covers the process used to analyze the data for this study. After

coding and transforming the data into a five-column table as described in the previous

sub-section, the data were loaded into SPSS version 20 for data analysis. SPSS is a menu

driven user interface statistical software package suited for academic research (Yunus,

2010). All statistical analysis tools have strengths and weaknesses depending on the

circumstances (Sherman & Serfass, in press).

The choice of SPSS for the data analysis of this study relates to my academic

experience with the software. SPSS is a well-documented and easy to learn statistical

analysis program. Learning SPSS and passing the quantitative research class were part of

the requirements for completing Walden University’s DBA program.

Reliability Testing

Researchers found sufficient reliability of all the three survey instruments used in

this study. The reliability of each instrument depends on the data collection from each

willing participant. To confirm the reliability of the instruments, I used data from all

participants to compute Cronbach’s alpha (α). The transformational leadership questions

tested at .97, the transactional leadership questions tested at .81, affective commitment

questions tested .88, and the final set of questions about continuance commitment tested

at .79. Cronbach’s alpha allows for testing the reliability of a survey instrument (Yunus,

2010). Scholars such as AbuAlRub and Alghamdi (2012) and Vadell (2008) used

Cronbach’s alpha to test the reliability of instruments they used to measure the same

variables used in this study.

Descriptive Analysis

In the data analysis process, descriptive analysis followed reliability testing.

Descriptive statistics allows for describing quantitative variables within levels of

qualitative variables (Yunus, 2010). I coded the descriptive statistics to examine the

distribution of data. Some of the measures included the standard deviation, mean, and

variance.

Hypotheses Testing

The focus of this study was to examine the relationship between leadership style,

organizational commitment, and intent to stay. Following were the research questions and

hypotheses considered in this study.

Research Question 1: What is the relationship between leadership style and intent

to stay with a company?

H10: Leadership style does not correlate with intent to stay with a company.

H1a: Leadership style correlates with intent to stay with a company.

Research Question 2: What is the relationship between organizational

commitment and intent to stay with a company?

H20: Organizational commitment does not correlate with intent to stay with a

company.

H2a: Organizational commitment correlates with intent to stay with a company.

Multiple linear regressions were the omnibus analysis in this study. In the process

of the regression analysis, I assessed bivariate correlations between each independent

variable and the dependent variable. Bivariate correlation is a statistical analysis method

used to assess the degree of linear relationship between variables in a sample (Yunus,

2010). The correlation between two variables is high when points of the two variables

converge toward a straight line called a regression line (Cho & Fryzlewicz, 2012). The

index for bivariate correlation ranges from -1 to +1, indicating the degree of relationship

(Yunus, 2010). A required p value of less than 0.05 controlled for type 1 errors. This

analysis allowed me to reject or accept the null hypotheses H10 and H20, and answer the

two research questions of the study.

The choice of multiple linear regressions for this study tested consistent with

recent similar studies. Using data from Saudi Arabian hospital, AbuAlRub and Alghamdi

(2012) used multiple linear regressions to examine the relationship between leadership

style, nurse satisfaction, and intent to stay. Similarly, Bressler (2010) used multiple linear

regressions to examine the relationship between hope, organizational commitment, and

intent to stay of United States Army Reserve soldiers.

SPSS version 20 served as the data analysis tool in this study. The multiple linear

regressions were the omnibus analysis in this study. In the process of the regression

analysis, I assessed bivariate correlations between each independent variable and the

dependent variable. The results of these statistical tests allowed me to reject or accept the

null hypotheses, hence answering the research questions.

Reliability and Validity

This section contains a discussion on reliability and validity of the instruments

used in the study. Researchers employ reliability and validity in quantitative research to

measure the internal consistency of an instrument and measure continuity of the

construct, (i.e., validity). This section contains an outline of the steps implemented to

ensure reliability and validity.

Reliability

In a quantitative study, reliability depends on the instrument used to collect data

(McCrae et al., 2011; Rahman & Post, 2012). Researchers have found support for the

reliability of the instruments used in this study (Bass & Avolio, 2004; Kosmoski &

Calkin, 1986; Krishnaveni & Ramkumar, 2008). To test reliability of the MLQ

instrument, Bass and Avolio (2004) collected and analyzed data from 2,154 individuals;

no self-ratings were included.

After analyzing the data, Bass and Avolio (2004) found reliabilities for all items

and for each leadership factor scale ranging from 0.74 to 0.94. Reliability for the

affective scale and continuance scale is acceptable, with a Cronbach’s alpha coefficient

(α) of 0.716 and 0.767, respectively (Krishnaveni & Ramkumar, 2008). Kosmoski and

Calkin (1986) showed an alpha value of 0.90 for the intent to stay scale.

Although the instruments in this study tested as reliable instruments, another

reliability test occurred to confirm the reliability of each instrument to ensure the data

reflected internal consistency. To confirm the reliability of the instruments, I gathered

data from all participants to compute the Cronbach’s alpha (α). The reliability and

validity of the instruments were a crucial component of research quality.

The reliability and validity of the instruments were a crucial component of

research quality.

Validity

Threats to validity in the study can come from both internal and external sources

(Ronau et al., 2014). Internal validity is often associated with validity of instruments used

in the study. A valid instrument means that the questions provide an accurate measure of

the relevant constructs. External validity is often associated with generalization of the

results to the population of study. This section covers steps used to establish the internal

and external validity of this study.

Internal validity. Instrument validity affects the internal validity of a study.

When an instrument is not valid, the study may not have sufficient internal validity.

Instrument validity means that the questions in an instrument accurately measure the

defined construct (Evans, Hartshorn, Cox, & De Jel, 2014). This correlation design is a

nonexperimental design and threats to internal validity are not applicable. Threats to

internal validity apply to experimental studies only (Rahman & Post, 2012); therefore,

threats for internal validity do not affect this study.

External validity. External validity relates to the ability of the sample to be

representative of the population (Olsen, Orr, Bell, & Stuart, 2013). Rahman and Post

(2012) argued that when calculating the mean of a score, outliers could have a negative

effect, especially for a small sample. A representative sample size reduced the threat

related to external validity. Because of the unknown population size, I left blank the

estimated population size in the G*Power 3 calculator to compute the required sample

size to find significance (Faul, Erdfelder, Buchner, & Lang, 2009). Using an alpha level

of .05, a power of .80, and an effect size of .15, the required sample size to find

significance with three predictors is 77. An alternative for increasing external validity is

to eliminate outliers. Outliers are data that exist outside of the scope. The observation of

outliners is a concern when raw scores converts to z-scores and evaluated to determine if

any score exceed +/-3.29 (Tabachnick & Fidell, 2013). In cases where scores that exceed

this value, they were eliminated from the analysis provided they were true outliers.

The reliability and validity section covered steps necessary to establish reliability,

internal validity, and external validity of this study. In the process of establishing

reliability, data from all participants of the study provided statistics to compute

Cronbach’s alpha (α) for each survey instrument. The internal validity of the study

included a peer review of the survey instruments. The minimum sample size for the study

was not large enough to establish external validity.

Transition and Summary

Section 2 describes the process used in the approach of this study. The discussion

of the research method and design revealed the purpose of the study, which aligns with a

quantitative method and correlational design. A purposive sample of junior executives

proved necessary to achieve at least a 95% probability of finding a relationship if one

exists in the population. SurveyMonkey® was the research site with an online survey

system. The data collection instrument used in this study had tested reliably in previous

studies. Using SPSS version 20, I run and analyzed the necessary statistical tests on the

data. The data analysis included reliability testing, descriptive analysis, and multiple

linear regression analysis. Based on the results of the data analysis, I can either reject or

accept the null hypotheses, and answer the research questions. Section 3 includes the

presentation and discussion of the results of the study, as well as the application of these

results to business practice and social change.

Section 3: Application to Professional Practice and Implications for Change

This research study is presented in three sections. In Section 1, the research

paradigm provided the underpinning of the study to include the subheading of descriptive

contexts that focused on the business problem. Section 2 contained an outline of the

strategic plan to investigate the specific business problem. The literature review presented

an objective account of several research theories from scholarly resources to develop the

theoretical framework for this study. Section 3 provides a detailed explanation of the

evidence that relates to the research questions and substantiates the findings and

conclusions of the study.

Overview of Study

The purpose of this correlational study was to determine the relationship among

the direct leader’s leadership style, junior executives’ organizational commitment, and

junior executives’ intent to stay with a company. In an effort to provide senior executives

with an increased understanding of factors that affect junior executives, I used a 52-

question survey instrument to collect data to test the reliability and validity of the survey

instrument in this study. The two research questions that guided this study were as

follows:

Research Question 1: What is the relationship between direct leaders’ leadership

style and junior executives’ intent to stay with a company?

Research Question 2: What is the relationship between junior executives’

organizational commitment and intent to stay with a company?

The hypotheses to address the research questions of this study were as follows:

H10: Direct leaders’ leadership styles do not significantly statistically correlate

with junior executives’ intent to stay with a company.

H1a: Direct leaders’ leadership styles do significantly statistically correlate with

junior executives’ intent to stay with a company.

Research Question 2: What is the relationship between organizational

commitment and intent to stay with a company?

H20: Executives’ organizational commitment does not significantly statistically

correlate with junior executives’ intent to stay with a company.

H2a: Executives’ organizational commitment does significantly statistically

correlate with junior executives’ intent to stay with a company.

Presentation of the Findings

This subsection of the study presents the conclusions from the findings of this

quantitative study that answer the research questions and address the hypotheses. The

data collected from the 52-question survey answered by the participants provided the

results findings as well as the relationship between the two independent variables (Xn)

and dependent variable (Yn). In addition, this subset includes information on how the

findings substantiate the theoretical frameworks for this study and correlates to the

prevailing body of knowledge on effective business practice.

I collected data purposefully from selected junior executives in the southern

region of United States using SurveyMonkey®. Data were downloaded for 183

participants directly from SurveyMonkey® as an SPSS data file. The exclusion of 43

participants occurred because they did not complete the survey. I deleted an additional 34

participants for not being self-identified junior executives. I reverse-coded questions as

appropriate and created composite scores. I conducted multiple linear regressions to

address the research questions.

Descriptive Statistics

Data analysis proceeded with 107 junior executive participants. The majority of

these participants were women (61, 57%). Forty (37%) participants were between 40 and

49 years of age. Most of the participants had been with their company either for 1 to 2

years (41, 38%) or for more than 5 years (44, 41%). Intent to stay within the company

varied heavily for the participants. Table 2 presents frequencies and percentages for

participant demographics.

Table 2

Frequencies and Percentages for Participant Demographics

Demographic

Gender

Female

Male

Age

21-29

30-39

40-49

50-59

60 or older

Length of time at company

1-2 years

3-5 years

More than 5 years

Intent to stay

Stay less than 2 years

Stay 2 to 5 years

Stay 6 to 10 years

Undecided

Stay until full Social Security retirement age

I created four composite scores for the study: transformational leadership,

transactional leadership, affective commitment, and continuance commitment. The

appropriate responses to affective commitment were reverse-coded. When calculating the

transactional leadership score, three of the questions did not exist on the survey

(Questions 22, 24, and 27 from the MLQ). Therefore, I proceeded with caution in the

interpretation of results concerning transactional leadership.

Cronbach’s alpha reliability testing provided the subscales to assess the internal

reliability of the sample. George and Mallery’s (2014) guidelines for alpha levels

explained how to assess the reliability of the scales. Excellent reliability (> .90) tested for

transformational leadership (.97). Good reliability (> .80) tested for transactional

leadership (.81) and affective commitment (.88). Acceptable reliability (> .70) tested for

continuance commitment (.79). Table 3 presents Cronbach’s alpha reliability statistics

and descriptive statistics for the subscales.

Table 3

Cronbach’s Alpha Reliability for Subscales

Subscale

No. of items

Transformational leadership

.97

2.34

1.15

Transactional leadership

.81

2.36

1.06

Affective commitment

.88

3.26

1.13

Continuance commitment

.79

2.89

0.95

Preliminary Correlations

A Pearson correlation matrix measured the strength of linear relationship among

intent to stay, transformational leadership, transactional leadership, affective

commitment, and continuance commitment. Intent to stay significantly positively

correlated with transformational leadership, transactional leadership, and affective

commitment. Transformational leadership significantly positively correlated with

transactional leadership and affective commitment.

Transactional leadership significantly positively correlated with affective

commitment. The correlation between transactional leadership and transformational

leadership indicated very strong (.89). Because of the strong correlation between the two

independent variables (thus the presence of multicollinearity), they were combined into a

single leadership variable; therefore, a bivariate regression analysis was conducted. Table

4 shows the full correlation matrix.

Table 4

Correlation Matrix Among Intent, Transformational, Transactional, Affective, and

Continuance

1. Intent to stay

2. Transformational leadership

.46**

3. Transactional leadership

.43**

.89**

4. Affective commitment

.50**

.63**

.55**

5. Continuance commitment

.14

.13

.17

.00

* p ≤ .05. ** p ≤ .01.

Research Question 1

A bivariate regression analysis was conducted to assess whether leadership scores

significantly predicted intent to stay. The predictor variable was leadership style. The

dependent variable was intent to stay. Transformational and transactional leadership

styles combined into a single leadership style score due to multicollinearity between the

two variables. I assessed the assumptions of normality, linearity, homoscedasticity, and

standardized residuals of the residuals by viewing the normal probability (P-P) plot

(Figure 3) and scatterplot of the standardized residuals (Figure 4). One or more of the

assumptions were in violation. The existence of a systematic pattern in the scatterplot of

the standardized residuals (Figure 4) supports the tenability of the assumptions not being

met. Thus, the reader should view the results with caution.

Figure 3. Normality P-P scatterplot for leadership predicting intent to stay.

Figure 4. Scatterplot for leadership predicting intent to stay.

The results of the bivariate regression were significant, F(1, 105) = 27.82, p <

.001, R2 = .21, suggesting that leadership style significantly predicted intent to stay. The

R2 value indicated that approximately 21% of variations in intent to stay are accounted for

by leadership score. The positive slope for leadership (B = 0.62) indicated that for every

one unit increase in leadership score, intent to stay increased by 0.62 units. The higher a

person’s leadership score, the more likely the person’s intent to stay. The null hypothesis

was rejected, and the alternative hypothesis was accepted. Table 5 presents the results of

the simple linear regression.

Table 5

Bivariate Linear Regression for Leadership Score Predicting Intent to Stay

Variable

Leadership

0.62

0.12

.46

5.27

.001

Research Question 2

Multiple linear regression analysis was conducted to assess whether affective

commitment and continuance commitment significantly predicted intent to stay. The

predictor variables were affective commitment and continuance commitment. The

dependent variable was intent to stay. I assessed the assumptions of normality, linearity,

homoscedasticity, and standardized residuals of the residuals by viewing the normal

probability (P-P) plot (Figure 5) and scatterplot of the standardized residuals (Figure 6).

One or more of the assumptions were in violation. The existence of a systematic pattern

in the scatterplot of the standardized residuals (Figure 6) supports the tenability of the

assumptions not being met. Thus, the reader should view the results with caution.

Figure 5. Normality P-P scatterplot for organizational commitment predicting intent to

stay.

Figure 6. Scatterplot for organizational commitment predicting intent to stay.

The results of the multiple linear regression were significant, F(2, 104) = 19.42, p

< .001, R2 = .27, suggesting that the model as a whole was able to significantly predict

intent to stay. Affective commitment, B = 0.64, p < .001 was the only significant

contributor to the model. Continuance commitment was not a significant predictor, B =

0.22, p = .08. The positive slope for affective commitment (B = 0.64) indicated that for

every one-unit increase in the affective commitment score, intent to stay increased by

0.64 units. In other words, as a person’s affective commitment increased, the more likely

the person’s intent to stay. The null hypothesis was rejected, and the alternative

hypothesis was accepted. Table 6 presents the results of the multiple linear regression.

Table 6

Multiple Linear Regressions for Organizational Commitment Score Predicting Intent to

Stay

Variable

Affective commitment

0.64

0.11

.50

5.99

.001

Continuance

0.22

0.13

.15

1.74

.084

Applications to Professional Practice

The study results present senior executives of companies with information on how

leadership style and organizational commitment can affect junior executives’ intent to

stay with a company. The results of this study may add to the body of knowledge

concerning the relationship among leadership style, organizational commitment, and

intent to stay with a company. The costs of employee turnover are evident in the

sustainability of companies. The results of this study offer statistical data and

recommendations to senior executives of companies to review, analyze outcomes, and

focus on strategic planning efforts for employee retention.

Implications for Social Change

The implications for positive social change include the potential to provide senior

management with a better understanding of factors that relate to junior executive

retention. The potential exists to provide senior executives with the necessary tools to

increase retention through prediction of attrition and possible reduction of causes of

attrition. The social change implications include the potential to create a more desirable

workplace, higher job satisfaction, and overall organization environment; making it more

desirable to stay with the organization.

Society may benefit, as experienced executives remain in their organization to

reduce the risk of company turnover and higher unemployment rates. Businesses and

governmental agencies may be able to developing better retention methods and strategies.

Business leaders may better understand when to offer an incentive, such as bonus pays,

higher education, and other training options for retention. Society may further benefit as

experienced junior executives remain with a company to help sustain communities.

Recommendations for Action

Company leaders may use the data from this study as an analytical tool to predict

turnover risk among employees. Senior executives should pay attention to the results of

this study, as well as evaluate which leadership style positively correlates with

organizational commitment among company employees. Senior executives should work

toward implementing new strategies to address the challenges that will retain employees.

Senior leaders should ensure these strategies are visible to share with employees.

Recommendations for Further Study

This study expands the option for future researchers to examine mid-level

management in the business industry and branches of the military that have the rank of

equivalent to junior executives. Using the instruments from this study with a larger

sample size could substantiate the results of this study on a wider scale range. A similar

study inclusive of a census area or even several census areas with higher populations of

junior executives would yield a large enough sample to provide generalizability to the

junior executive populations in organizations. Stratification, as it affects test results of

those affected, suggest a need for further study. In addition, future researchers may wish

to use a qualitative model to code junior executives’ perceptions towards leadership

styles and intent to stay. A longitudinal study following junior executives’ employment

from start to finish at a company suggests a need to determine junior executives’

perceptions of leadership styles, and the effects of those leadership styles on intent to

stay.

Reflection

After retiring from years of serving as a leader within the military, I understand

how leadership styles and organizational commitments influence many factors for

individuals. The origin of this research stems from the leadership direction of the

committee members appointed to guide me through the process of this study. The

continuous feedback from committee members and making revisions of the study

strengthened the scholarly writing in this research. Following the guidelines of the DBA

rubric was an essential task that benchmarked and measured the progress of the study.

Developing the survey in Survey Monkey® proved beneficial in protecting the

participants and collecting the data; however, in analyzing the data, I still had unyielding

concepts of the results based on previous research finding and personal experience in the

military. However, these biased notions were not an influential factor in the data

collection process, because I had no contact with the participants of the survey and the

data excluded participant’s identification to ensure confidential of answers.

Summary and Study Conclusions

The attrition of junior executives who are promoted within the company and the

understanding how junior executives’ intent to stay with a company relates to leadership

style and organizational commitment was the purpose of this quantitative correlational

study. This study results compared the independent variables of leadership styles and

organizational commitment with a dependent variable and intent to stay.

This study consisted of 107 participants employed as junior executives in the

southern region of the United States (which includes Alabama, Arkansas, Delaware,

District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi,

North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West

Virginia). The random assignment of 107 participants occurred using the G*Power 3

Calculator (Faul, Erdfelder, Buchner, & Lang, 2009).

The assessed participants in this study were junior executives with concerns of

existing leadership practices and their relationships between leadership styles,

organizational commitment, and intent to stay in the organization to identify the potential

weakness of employee retention. Section 3 provided an in-depth description of statistical

results regarding the quantitative correlation design study directed on the relationship

between leadership style, organizational commitment, and intent to stay in the

organization. The research findings reflected junior executives’ responses to the 52-

question survey. Senior executives should view the results of this study as a catalyst for

assessing existing leadership practices and using the data generated from the study to

identify the potential weakness of employee retention.

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