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Employee Turnover in the IT Industry

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									EMPLOYEE TURNOVER IN THE IT INDUSTRY

                         by

                  Francesca Abii




   A Dissertation Presented in Partial Fulfillment

        of the Requirements for the Degree

Doctor of Management in Organizational Leadership




           UNIVERSITY OF PHOENIX

                  September 2008
© 2008 by Francesca E. Abii
ALL RIGHTS RESERVED
                 EMPLOYEE TURNOVER IN THE IT INDUSTRY

                                           by

                                 Francesca Ekaette Abii

                                      September 2008


Approved:


                               Barry Foster, PhD, Mentor

                         Brett Gordon, PhD, Committee Member

                        Kevin Banning, PhD, Committee Member


Accepted and Signed:
                       Barry Foster                            Date


Accepted and Signed:
                       Brett Gordon                            Date


Accepted and Signed:
                       Kevin Banning                           Date



Dawn Iwamoto, Ed.D.                                            Date
Dean, School of Advanced Studies
University of Phoenix
                                       ABSTRACT

Employee turnover can be a costly problem for information technology (IT) companies.

When employees leave, organizations have to attend to the high cost of training and

development, burnout of existing staff, and decreased quality of service and products due

to staff shortages. Skilled IT workers are scarce commodities, and the U.S. Department of

Commerce estimated that the United States would require more than 1.3 million new and

highly skilled IT workers to address the projected staff shortage (Kamal, 2005). DeMers

(2002) noted that organizations struggle to recruit skilled IT workers and indicated a

1998 report by the Information Technology Association of America that estimated the

gap at 190,000 unfilled core IT positions. Employee turnover is a problem that

organizations cannot ignore because of the financial burden, negative impact on

employee morale and employee relationships, and adverse impact on the quality of

services and products that organizations deliver to customers (Wagar & Rondeau, 2006).

The IT industry is experiencing high employee turnover (Foote, 2006). This quantitative

study examined the organizational and individual factors that influence IT employees‟

decisions to leave an organization. The results of the study indicate that employee

compensation and workplace relationships are factors that influence turnover.
                                                                                         iv


                                     DEDICATION

       I dedicate this study to my parents Dr. and Mrs. Ekanem for believing in me and

giving me the extra “push” when I needed it. As a child, my parents instilled the value of

education in me—this value has been pivotal through out this journey. Mommy and

daddy—this study is dedicated to you.

       I dedicate this study to my wonderful and incredibly supportive husband, Michael

Ogechi Abii. Honey you have been incredible throughout this journey. You reminded me

that I could do all things through Christ who strengthens me. You also reminded me that

God had a purpose for me so quitting before completing the study was not an option.

From the bottom of my heart, I say thank you!

       I dedicate this study to my two wonderful children Priscilla-Lynn Abii and

Nnaemeka Sebastian Abii. My wonderful kids have been patient with mommy

throughout the dissertation process. Mommy loves you both dearly.
                                                                                          v


                               ACKNOWLEDGMENTS

       The first acknowledgement goes to my Lord and Savior Jesus Christ! The Lord

was my strengthener throughout my dissertation journey. All things have really been

possible with the Lord on my side.

       I would like to acknowledge my wonderful husband for being so supportive

throughout my dissertation journey. He knew when to hold my hand, when I needed the

extra push, and when I needed a “pep talk” to get me through some tough moments.

Honey I know I could not do this without you. I would also like to acknowledge my

wonderful children who were patient with mommy.

       Many thanks to Pauline Young—my very best friend who has always been an

incredible supporter and confidante. Your friendship has meant so much to me over the

years. I appreciate your encouraging words of support.

       I would also like to acknowledge my fellow cohorts, David Ogula, Jonathan Rose,

and Dorothy Webb-Moody who were a source of support and encouragement throughout

my dissertation journey. Words alone cannot express how much I appreciate your

support.

       I cannot even imagine how I could have completed this study without the

guidance of my dissertation committee. Dr. Foster—thanks for your leadership and

guidance throughout the process. I really appreciate it! Dr. Banning—I cannot thank you

enough. Your feedback and guidance were pivotal throughout the review process. Dr.

Gordon—thanks for your help. Your knowledge of statistics was invaluable. I cannot

thank you enough.
                                                                                            vi


       Many thanks to Dr. Cheryl Winsten-Bartlett! You went above and beyond during

my third year residency class to make sure that I had a well-aligned problem statement,

purpose statement, and research question. Your guidance was invaluable in getting me

started on my proposal. I would also like to acknowledge Stephanie Bowens for her

support throughout my data collection process—Stephanie you were such an

encouragement! Last and absolutely not least, I would like to thank Schola Wilson for

reviewing the initial draft of my dissertation. I cannot thank you enough for sacrificing

the time to review my dissertation.
                                                                                                                                  vii


                                                TABLE OF CONTENTS

LIST OF TABLES .................................................................................................... xi

LIST OF FIGURES ................................................................................................xiii

CHAPTER 1: INTRODUCTION .............................................................................. 1

Background of the Problem ....................................................................................... 4

Problem Statement ..................................................................................................... 7

Purpose of the Study .................................................................................................. 9

Significance of the Study ......................................................................................... 10

Significance of the Study to Leadership .................................................................. 11

Nature of the Study .................................................................................................. 12

Research Question ................................................................................................... 13

Hypotheses ............................................................................................................... 13

Theoretical Framework ............................................................................................ 14

Definition of Terms.................................................................................................. 18

Assumptions............................................................................................................. 19

Scope, Limitations, and Delimitations ..................................................................... 19

      Scope................................................................................................................. 19

      Limitations ........................................................................................................ 20

      Delimitations..................................................................................................... 20

Summary .................................................................................................................. 20

CHAPTER 2: REVIEW OF THE LITERATURE .................................................. 22

Documentation ......................................................................................................... 23

      Gaps in Literature ............................................................................................. 25
                                                                                                                                    viii


Historical Perspectives on Employee Loyalty ......................................................... 25

Historical Perspectives on Employee Retention ...................................................... 26

Historical Perspectives on Employee Motivation .................................................... 28

Leadership and Employee Relationships ................................................................. 30

      Dynamics of Transformational Leadership and Employee Loyalty ................. 32

      Dynamics of Transformational Leadership in a Culture of Trust..................... 32

      Cultivating a Trusting Work Environment ....................................................... 34

Employee Job Satisfaction ....................................................................................... 35

Employee Turnover ................................................................................................. 35

Turnover Models ...................................................................................................... 37

      Appraisal Theory of Emotions Model .............................................................. 38

      Stimulus-Response Model of Coping ............................................................... 40

      Ethical Climate Structural Model ..................................................................... 41

Factors Affecting Job Satisfaction ........................................................................... 42

      Gender............................................................................................................... 42

      Employee Recognition...................................................................................... 43

Factors Affecting Turnover...................................................................................... 43

      Race .................................................................................................................. 43

      Age .................................................................................................................... 44

      Personality Traits .............................................................................................. 44

      Training............................................................................................................. 45

      Pay .................................................................................................................... 45

      Challenging Work ............................................................................................. 46
                                                                                                                                  ix


      Respect .............................................................................................................. 47

      Full-Time and Part-Time Workers ................................................................... 47

Conclusion ............................................................................................................... 47

Summary .................................................................................................................. 48

CHAPTER 3: METHOD ......................................................................................... 51

Research Design....................................................................................................... 51

Appropriateness of Design ....................................................................................... 53

Research Questions .................................................................................................. 54

Population ................................................................................................................ 54

Sampling .................................................................................................................. 55

Informed Consent..................................................................................................... 55

Confidentiality ......................................................................................................... 56

Geographic Location ................................................................................................ 56

Instrumentation ........................................................................................................ 56

Data Collection ........................................................................................................ 57

Data Analysis ........................................................................................................... 58

Reliability & Validity .............................................................................................. 59

Summary .................................................................................................................. 60

CHAPTER 4: RESULTS ......................................................................................... 61

Data Collection ........................................................................................................ 61

Data Analysis ........................................................................................................... 63

Descriptive Analysis ................................................................................................ 64

Hypothesis Testing................................................................................................... 73
                                                                                                                                 x


      Pearson Correlation .......................................................................................... 74

      Multiple Regression Results ............................................................................. 74

Acceptance or Rejection of Hypotheses .................................................................. 85

Summary .................................................................................................................. 87

CHAPTER 5: CONCLUSION AND RECOMMENDATIONS ............................. 88

Research Questions and Hypotheses ....................................................................... 88

Implications.............................................................................................................. 90

Limitations ............................................................................................................... 91

Significance to Leadership ....................................................................................... 91

Recommendations for Leadership ........................................................................... 92

Recommendations for Further Studies..................................................................... 93

Conclusion ............................................................................................................... 93

Summary .................................................................................................................. 94

REFERENCES ........................................................................................................ 97

APPENDIX A: QUESTIONNAIRE...................................................................... 109

APPENDIX B: E-MAIL NOTIFICATION ........................................................... 111

APPENDIX C: INFORMED CONSENT FORM ................................................. 112

APPENDIX D: PERMISSIONS ............................................................................ 114

APPENDIX E: RESULTS TABLES ..................................................................... 119
                                                                                                                            xi


                                                  LIST OF TABLES

Table 1 Employee Work-Life Experiences ................................................................. 6

Table 2 Documentation ............................................................................................ 24

Table 3 Description of the Final Sample (N = 144) ................................................ 63

Table 4 Descriptive Statistics of Job Satisfaction Factors ...................................... 65

Table 5 Descriptive Statistics of Employee Turnover Factors (N =144) ................ 66

Table 6 Frequencies of CPOV Turnover Factor ..................................................... 67

Table 7 Frequencies of BSR Turnover Factor ......................................................... 68

Table 8 Frequencies of EA Turnover Factor ........................................................... 69

Table 9 Frequencies of EC Turnover Factor ........................................................... 70

Table 10 Frequencies of PD Turnover Factor ........................................................ 71

Table 11 Frequencies of IT Turnover Factor .......................................................... 72

Table 12 Frequencies of WR Turnover Factor ........................................................ 73

Table 13 Regression Model for BSR and Job Satisfaction ...................................... 78

Table 14 Regression Model for EA and Job Satisfaction (Including Other

Turnover Factors) .................................................................................................... 78

Table 15 Regression Model for PD and Job Satisfaction (Including Other

Turnover Factors) .................................................................................................... 79

Table 16 Regression Model for IT and Job Satisfaction (Including Other

Turnover Factors) .................................................................................................... 79

Table 17 Regression Model for WR and Job Satisfaction (Including Other

Turnover Factors) .................................................................................................... 80

Table 18 WR Coefficients Table .............................................................................. 81
                                                                                                                                  xii


Table 19 Regression Model for EC and Job Satisfaction (Including Other

Turnover Factors) .................................................................................................... 82

Table 20 EC Coefficient Table ................................................................................. 83

Table 21 Regression Model for CPOV and Job Satisfaction (Including Other

Turnover Factors) .................................................................................................... 84

Table 22 Correlation between Turnover Factors and Intrinsic Job Satisfaction

Factors ................................................................................................................... 120

Table 23 Correlation between Turnover Factors and Extrinsic Job Satisfaction

Factors ................................................................................................................... 122

Table 24 ANOVA table for WR .............................................................................. 124

Table 25 ANOVA table for EC ............................................................................... 125
                                                                                                                       xiii


                                                LIST OF FIGURES

Figure 1. Key organizational cultural factors. ........................................................... 2

Figure 2. Voluntary turnover model of extension employees. .................................. 4

Figure 3. Fully mediated model of coping with organizational change based on

appraisal theory of emotions. ................................................................................... 39

Figure 4. Fully mediated model of coping with organizational change based on

the stimulus-response theory of coping. .................................................................. 40

Figure 5. Ethical climate structural model. ............................................................. 41
                                                                                            1


                             CHAPTER 1: INTRODUCTION

       Employee turnover can be a costly problem for information technology (IT)

companies. When employees leave, organizations have to attend to the high cost of

training and development, burnout of existing staff, and decreased quality of service and

products due to staff shortages (Beauchesne, 2006; Chandler, 2004; Moore, 2006;

Quigley, 2006; Siebenmark, 2006). Since the 1990s, organizations have struggled to

recruit and retain qualified IT workers (DeMers, 2002; Lock, 2003; West & Bogumil,

2001; Whitaker, 1999). Skilled IT workers are scarce commodities, and the U.S.

Department of Commerce estimated that the United States would require more than 1.3

million new and highly skilled IT workers to address the projected staff shortage (Kamal,

2005). DeMers (2002) noted that organizations struggle to recruit skilled IT workers and

indicated a 1998 report by the Information Technology Association of America that

estimated the gap at 190,000 unfilled core IT positions.

       The study examined the factors that motivate IT employees to leave

organizations. Many researchers have examined the factors that influence employees to

remain (Capps, 2007; Carson, Carson, Birkenmeier, & Toma, 2006; Chang & Lee, 2006;

Chiaburu & Marinova, 2006). Lock (2003) indicated that the following factors influence

IT employees‟ decisions to remain with organizations: (a) challenging work, (b) respect,

(c) a balanced work life, (d) effective leadership, (e) and a workplace that fosters risk

taking and strengthens social bonds inside and outside the organization. Figure 1

illustrates a survey by Kanter (2001) of 785 IT organizations (as cited by Lock 2003).

The results of Kanter‟s study indicate that IT workers value workplace characteristics,
                                                                                                     2


such as effective leadership and a workplace fostering risk taking and strengthening

social bonds.




Figure 1. Key organizational cultural factors.

Note. From “Living, valuing and sharing”—A case study of retaining IT professionals in the British

Columbia public service, by G. E. Lock, 2003. Copyright 2003 by MCB UP Limited (MCB). Reprinted

with permission.

        Lock (2003) suggested that multiple factors influence employees‟ decisions to

remain with organizations. Other studies illustrated that even when employees remain,

organizations need to determine if people who remain do so because they are motivated

to stay (Anuradha, 2005; Chandler, 2004; Foote, 2006; Vu, 2006). Li (2006) and Klie

(2006) noted that organizations need effective strategies to address employee turnover.

Organizations should not wait until too late to implement retention strategies
                                                                                             3


(Anastasopoulos, 2005; Li, 2006) because retention strategies are ineffective when

implemented as reactive measures.

       Foote‟s (2006) study indicated that though retention strategies such as competitive

pay, promotions, paid time-off, flexible schedules and work-life balance can lead to “on

the job contentment” (p.14), some employees will still choose to leave organizations.

These strategies do not involve considering the dynamic factors that motivate employees

to remain with organizations (Li, 2006; Lock, 2003; Thozhur, Riley, & Szvivas, 2006).

Various factors contribute to an employee‟s decision to remain, and retention strategies

will be effective only when leaders consider these factors (Foote, 2007; Johnson, 2007;

Li, 2006).

       Chapter 1 introduces the literature on turnover and describes how organizations in

several industries are impacted by employee turnover. The chapter also briefly describes

some of the factors that influence employees‟ decisions to leave organizations. Some of

the turnover models are described as well as how these models can be used to predict

employee turnover. Chapter 1 also provides an overview of the turnover issue in the IT

industry and identifies the contributing factors to the issue. Several studies on employee

turnover are discussed in chapter one and a brief discussion is provided to explain how

these studies are similar with the current study. Also included in Chapter 1 is the purpose

for the study, the type of method that was used to conduct the study and an explanation

regarding why the quantitative method was the most appropriate method for this study.
                                                                                                   4


                                   Background of the Problem

        Employee turnover is an issue in the IT industry. Wagar and Rondeau (2006)

stated that turnover is a matter that organizations must consider seriously. Chandler

(2004) indicated that organizations have to address the following concerns during a

vacancy: (a) loss of work time, (b) time spent trying to fill vacant positions, (c) burnout

of coworkers attempting to fill the void of vacant positions, (d) time spent by supervisors

on the orientation of new employees, and (e) adverse impact on the quality of products

and services that organizations deliver to customers.

        Chandler (2004) examined organizational, individual nonwork factors, and

individual work factors that affect employee retention. Figure 2 illustrates the voluntary

turnover model of extension employees.




Figure 2. Voluntary turnover model of extension employees.

Note. From Organizational and Individual Factors Related to Retention of County Extension Agents

Employed by Texas Cooperative Extension, by G. D. Chandler, 2004. Copyright 2005 by

ProQuest Information and Learning Company. Reprinted with permission.
                                                                                           5


The voluntary turnover model of extension employees shows the relationship between

various factors that lead to employee turnover. The model indicates that identifying and

grouping the various factors that lead to employee turnover form an important part of the

analysis necessary to understand and address employee turnover. The model reflects

factors grouped into organizational, individual non-work-related factors, and individual

work-related factors.

        Retention of IT workers is becoming critical (Foote, 2006). Foote noted that

approximately half of the respondents in a survey of 51,000 North American IT workers

indicated that they were looking for another job actively or passively. Retention strategies

are deficient in addressing employee turnover because the strategies do not involve

examining the real reasons employees leave (Foote, 2007; Li, 2006).

        Several authors noted that employees value other factors such as job autonomy

more than compensation (Foote, 2006; Li, 2006; Lock, 2003). Messmer (2006) cited

workplace dynamics as factors that influence employees to remain with organizations.

Lock (2003) identified challenging work, respect, and a balanced work life as workplace

dynamics that can influence an employee‟s decision to remain with an organization. Lock

(2003) presented various factors that affect employees‟ work life. Table 1 illustrates some

of the factors identified in Lock‟s study with the factors organized into three groups: most

satisfactory experiences, most areas of concern, and top employer of choice

characteristics.
                                                                                                     6


Table 1

Employee Work-Life Experiences

Most satisfactory                                                          Top employer of choice
experiences                            Most areas of concern                    characteristics

Good relations with                 Poor morale (72%)                   Employers that provide
co-workers (97%)                                                        advancement opportunities
                                                                        (85%)
Good/flexible hours of              Ineffective internal                Employers that balance
work (92%)                          communications                      work with family and other
                                    (51%)                               non-work activities
                                                                        (81%)
Good benefits (88%,                 Lack of recognition                 Employers that reward
excluding salary)                   (38%)                               learning and sharing
                                                                        information (73%)
Good working conditions
(69%)
Good support from
supervisor (69%)

Note. From “Living, valuing and sharing”—A case study of retaining IT professionals in the British

Columbia public service, by G. E. Lock, 2003. Copyright 2003 by MCB UP Limited (MCB). Reprinted

with permission.
                                                                                             7


       Foote (2006) stated that employees want a certain amount of control of their work

and careers. Li (2006) noted that the strategies organizations use for employee retention

are not effective because they are not flexible enough to address the dynamic factors in

the workforce. DeMers (2002) indicated that even if retention strategies are implemented,

they are ineffective when they are implemented after employees leave an organization.

                                    Problem Statement

       Employee turnover is a problem that organizations cannot ignore because of the

financial burden, negative impact on employee morale and employee relationships, and

adverse impact on the quality of services and products that organizations deliver to

customers (Wagar & Rondeau, 2006). The IT industry is experiencing high employee

turnover (Foote, 2006). Literature indicates that most retention strategies do not address

employee turnover adequately (Li, 2006).

       One of the reasons IT workers change jobs is career advancement (Good, 2007).

Another article illustrated that one in three employees indicated they would remain in

their next job for under 2 years (“Employees Keep,” 2006). Employee turnover can be

financially burdensome for organizations because of the need to train new staff members

each time employees leave (Chandler, 2004).

       According to Chandler (2004), studies suggest that when employees leave, a

decline in the quality of products and services that organizations deliver to customers

occurs. Other problems that organizations have to address when employees leave include

the following: decline in staff morale, employee burnout, decline in quality of products

and services due to staff shortage, and decline in customer satisfaction (Building

employee commitment, 2007). Several authors indicated that retention strategies are not
                                                                                          8


addressing employee retention effectively because the strategies do not involve

addressing the dynamic factors that make employees leave organizations (Brodie, 2006;

Foote, 2006; Vu, 2006). Retaining and recruiting IT workers in the government and the

private sector has become increasingly difficult since the early 1990s (Lock, 2003).

       Researchers have examined why employees remained with organizations (Al-

Ajmi, 2006; Chandler, 2004; Foote, 2006; Robinson, Murrells, & Smith, 2005; Ryan,

2006; Vu, 2006). Al-Ajmi (2006), Chandler (2004), Foote (2006), and Vu (2006)

examined the effect of various factors on employee retention. The factors included the

following: wages, environmental conditions, work relationships, and opportunities for

career growth. While examining the factors revealed the reasons employees remained

with organizations, the current study examined the factors that influence IT employees‟

decisions to leave organizations.

       According to Gemignani (1998), the average cost of employee turnover is

$10,000 (as cited in McKay, Avery, Tonidandel, & Morris, 2007). Goshe, Huffstutter,

and Rosenzweig (2006) noted that hiring and training replacement employees accounts

for approximately 50% of an IT worker‟s annual salary. As noted by the Employment

Policy Foundation in Washington, DC, “employee turnover costs [an] average [of] 25

percent of an employee's annual salary” (as cited in Muck, 2006, p.44).

       The current study was conducted because of the need to examine the factors that

influence IT employees‟ decisions to leave an organization. This quantitative study

included an examination of the organizational and individual factors that influence IT

employees‟ decisions to leave an organization. The study included a focus on the IT
                                                                                             9


industry and IT professionals located in the Washington, DC metropolitan area; the

research design was a survey design.

                                   Purpose of the Study

       The purpose of the quantitative study was to identify the factors that influence IT

employees‟ decisions to leave organizations. The IT industry has changed since the 1990s

(Lock, 2003), and the study involved examining the extent to which industry trends have

affected employee retention. Westerman and Simmons (2007) noted that organizational

factors, such as workplace relationships, organizational culture, and opportunities for

advancement, are factors that affect employee retention. The study involved examining

the individual, nonorganizational and organizational factors that affect employee

retention.

       The study involved the use of a questionnaire of 25 questions: The first 20

questions incorporated a Likert-type scale, and the last five questions were open-ended

questions. The first 20 questions were grouped into two categories, intrinsic and extrinsic

job satisfaction. The Minnesota Satisfaction Questionnaire (MSQ), an existing validated

instrument, was used to measure job satisfaction across 20 different dimensions, with five

questions on each dimension. The five open-ended questions aided in gaining a better

understanding of the factors that influence employee decisions to leave organizations.

The data from the job satisfaction survey were analyzed to determine the factors that

influence employees‟ decisions to leave organizations.

       The research design was appropriate because the study involved examining IT

employee job satisfaction as well as the factors that influence IT employees to leave

organizations. A quantitative method was appropriate because the study involved
                                                                                            10


examining if job satisfaction influences an IT employee‟s decision to leave an

organization. Creswell (2002) emphasized that a quantitative method is appropriate for

explaining the relationship between variables. Creswell indicated that quantitative

methods are appropriate when asking specific, narrow questions to obtain measurable and

observable data on variables. A survey design was used for this study. Survey designs are

appropriate when administering surveys or questionnaires to a small group of people to

identify trends in attitudes, opinions, behaviors, or characteristics of a large group of

people (Creswell, 2002). The population for the study included 200 IT professionals (i.e.

IT managers, software developers, analysts, etc.) in the DC metropolitan area. The

dependent variable was employee turnover and the independent variable was job

satisfaction.

                                  Significance of the Study

        The study involved examining the factors that affect employee turnover in the IT

industry. Many researchers have examined the impact of employee job satisfaction on

employee retention (Anuradha, 2005; Bien-Aime, 2007). The study included an

examination of employee job satisfaction to determine the factors that influence IT

employees‟ decisions to leave organizations.

        The focus of the study was on the IT industry for several reasons:

    1. There is a shortage of IT workers in the IT industry (Kamal, 2005).

    2. Retention strategies have failed to address the retention problem in the IT industry

        (Foote, 2006).

    3. The IT industry has a higher turnover rate than other industries (Kamal, 2005).

    4. The IT industry is a young and emerging industry (Foote, 2006).
                                                                                           11


        Current research suggests that even if employees remain, their decision to remain

does not indicate satisfaction with their jobs (Anuradha, 2005; Chandler, 2004). The

study was significant because the research did not involve an examination of job

satisfaction alone but included an examination of the organizational and individual

factors that influence IT employees‟ decisions to leave organizations. Most studies on

employee retention focused on other industries besides the IT industry; some of these

studies were based on the following industries: accounting, education, investment

management, law enforcement, nursing, manufacturing, and retail industries (Curran,

2006; Dahm, 2006; Evergreen focuses on employee retention, 2006; Klie, 2006; McKay

et al., 2007; Yaying, 2007). Few empirical studies examining employee turnover in the IT

industry exist. Foote‟s (2006) article focused on employee retention in the IT industry,

but his work was non-empirical. Burnes‟s (2006) study was based on the IT industry but

the study examined the phenomenon of voluntary turnover of Generation X employees in

the IT marketplace in profit-making organizations in the Rocky Mountain and

Midwestern states. Based on the literature review, the current study appears to be one of

the few industry wide studies to examine turnover of IT workers in the DC metropolitan

area.

                         Significance of the Study to Leadership

        Employee retention is an important leadership concern because the success of

organizational initiatives is compromised when employees leave (Conroy, 2007; “The

Secrets,” 2006; Siebenmark, 2006). Employee retention is costly in the IT industry, and

literature indicates that retention strategies do not effectively address employee turnover

in the IT industry (DeMers, 2002; Foote, 2006; Lock, 2003). The study builds on
                                                                                              12


previous studies that involved examining job retention and job satisfaction in various

industries, such as education, psychology, and nursing (Chandler, 2004; Curran, 2006;

Parrish, 2006; Sweeney & McFarlin, 2005; Watlington, Shockley, Earley, Huie, Morris,

& Lieberman, 2004). The study also involved determining if the findings from previous

studies based on other industries are relevant to the IT industry.

       The study included examining key organizational, nonorganizational, and

individual factors to determine the factors that influence IT employees‟ decisions to leave

organizations. The findings from the study may provide specific guidance for leaders to

make strategies for retaining IT employees more effective. The findings may be relevant

to human resource practitioners, IT managers, and benefits specialists.

                                    Nature of the Study

       The focus of the quantitative study was the IT industry and the survey sample was

144 IT professionals (i.e., IT managers, software developers, analysts, data modelers,

database developers, etc.) in the DC metropolitan area. The objective of the study was to

examine the contributing factors that influence IT employees to leave their organizations.

A quantitative method was appropriate for the study because the purpose of the study was

to determine the factors that cause employees to leave organizations. According to

Creswell (2002), researchers choose to use a quantitative method to ask specific, narrow

questions to obtain measurable and observable data on variables. Data collection involved

research participants completing a survey. Creswell clarified that surveys are procedures

in quantitative research in which researchers administer a survey to a sample or to the

entire population to describe the attitudes, opinions, behaviors, or characteristics of the

population.
                                                                                          13


       A qualitative method was not selected for this study because a qualitative method

would be appropriate when exploring a problem that has not been examined before for

deeper insight (Creswell, 2002). A mixed approach was not appropriate for this study

because mixed methods are used to examine or explore trends to obtain a deep

understanding of a research problem (Creswell, 2002). Various authors (Chandler; 2004;

Foote, 2006; Li, 2006) have studied employee turnover. Other authors have developed

turnover models to predict employee turnover (Fugate et al., 2008; Yaying, 2007). A

quantitative method was selected over a qualitative or mixed method because a

quantitative method is the most appropriate research method to use to examine

relationships between variables (Creswell, 2002).

                                    Research Question

       This quantitative descriptive survey study examined the factors that influence

employees‟ decisions to leave organizations. The dependent variable was employee

turnover and the independent variable was job satisfaction. The survey instrument

included 25 questions. The first 20 questions were used to gather data on the

organizational, individual, and non-organizational factors that influence job satisfaction.

The last five questions were open-ended questions, which were used to examine the

reasons why employees left their previous jobs. The research question was the following:

What role does job satisfaction play in IT employees‟ decisions to leave organizations?

                                        Hypotheses

       This study had one null hypothesis and one alternative hypothesis. A null

hypothesis predicts that there is no relationship between independent and dependent

variables. Null hypotheses also make predictions that there is no difference between
                                                                                        14


groups of an independent variable on a dependent variable. The hypotheses for this study

include the following:

       H10: Job satisfaction does not influence IT employees‟ decisions to leave

organizations.

       H1A: Job satisfaction does influence IT employees‟ decisions to leave

organizations.

                                 Theoretical Framework

       Due to the severity of the turnover issue in the IT industry, a comprehensive study

was required to guide the study. The research included reviewing several motivational

theories and studies on retention, turnover, and job satisfaction. The conceptual

framework for the study also included research on the impact of management on

employee motivation. Horn and Griffeth‟s (1995) turnover model illustrated job

satisfaction and organizational commitment as two antecedents of voluntary turnover (as

cited in Hwang & Kuo, 2006). Horn et al. (1992) noted that employees who are

dissatisfied with their jobs or who have lost organizational commitment would have

intentions or make decisions to quit (as cited in Hwang & Kuo, 2006).

       Horn et al. (1992) emphasized that turnover intention would lead to actual

turnover (as cited in Hwang & Kuo, 2006). Organizations do not have to pay employees

high salaries to encourage them to remain with organizations (Hwang & Kuo, 2006).

Other factors, such as good relations with supervisors, trust, and confidence in

organizational leaders, are paramount to job satisfaction (Hwang & Kuo, 2006; Wade-

Hahn, 2006).
                                                                                          15


       Anuradha (2005) stated that turnover intentions can indicate employees‟ plans to

leave but will not provide the insight to determine if people who remain do so because

they are motivated to stay. Even if organizational leaders know why their employees

leave, they cannot effectively retain employees until they understand the factors that

encourage employees to remain. Anuradha noted the following:

       In accordance with motivation theory, it was hypothesized that employee MTS

       could be assessed by examining four facets—whether employees (a) were

       choosing to stay with the organization (MTS-choice), (b) felt good about staying

       (MTS-affect), (c) would exert extra effort to ensure a future with the organization

       (MTS-effort), and (d) would persevere in staying through organizationally

       challenging times (MTS-persistence) (para. 1).

The quantitative study was different from Anuradha‟s study because Anuradha focused

on employee retention and this study focused on employee turnover. Anuradha did not

focus on a specific industry but this study focused on the IT industry. This study

examined the factors that influence IT employees‟ decisions to leave organizations.

       Chandler (2004) examined the organizational, nonorganizational, and individual

factors related to job retention of Texas county extension agents to determine why the

agents chose to stay employed by Texas Cooperative Extension. The quantitative study

was similar to Chandler‟s study because the study also involved examining the

organizational, nonorganizational, and individual factors that relate to job retention. The

other similarity between the two studies is that the current study involved examining the

factors that cause employees to leave organizations. The difference between the two

studies is that Chandler exclusively examined turnover at an extension agency in Texas;
                                                                                           16


this study included an examination of IT employee job satisfaction as well as the factors

that influence IT employees to leave organizations.

         Research indicates that factors other than money motivate employees (Foote,

2006; Li, 2006). Dickson (1973) found that money is not the sole motivator of

employees, and employee behavior relates to employee attitude (as cited in Chandler,

2004). The study illustrated two points: factors other than money motivate employees,

and when employees feel motivated, their attitude about the job will be affected. Another

important point that Dickson revealed is that employees‟ attitudes about the job will vary,

but the most important goal for an organization is to determine what strategies to

implement to encourage employees to remain with organizations (as cited in Chandler,

2004).

         Other studies illustrated that while money and salary are important to most

employees, in many cases, remuneration is not the primary reason employees choose to

remain with organizations (Chandler, 2004; Muck, 2006). Chandler (2004) noted that the

following factors are important to employees: career growth; challenging and meaningful

work; to work with good people; recognition and appreciation for work well done;

opportunities to contribute ideas on work processes; flexibility in work hours; and fair

pay, good benefits, and job security. Though Chandler conducted the study at an

extension agency in Texas, this study involved a focus on the IT industry in the DC

metropolitan area.

         A study by Lock (2003) indicated that IT workers are motivated by the following

workplace factors: (a) effective leadership, (b) sound workplace relationships, (c)

challenging work, (d) respect, and (e) a balanced work life. DeMers (2002) suggested that
                                                                                          17


IT professionals do not rank compensation as the most important factor in decisions to

accept jobs. Such studies illustrate that leaders of organizations must examine the factors

that motivate employees carefully. The quantitative study involved examining various

individual and organizational factors to determine the factors that motivate employees.

       According to Chandler (2004), management can be most effective when

cultivating an environment where employees have a sense of self-worth, involvement,

recognition, responsibility, advancement, and growth. Chandler‟s position is consistent

with the transformational model of leadership based on leaders inspiring and motivating

employees as opposed to leading by fear and coercion. Chandler‟s study also indicated

that leadership and management abilities are factors that are important to employees.

       Drucker (1963) noted that management would not be effective if based on rank or

power. The main point of Drucker‟s text is that management is about responsibility as

opposed to leaders telling their subordinates what to do. Drucker noted that management

is a discipline, and leaders must know the fundamentals of the practice of management to

be effective managers.

       Drucker (1963) noted that leaders must possess certain behaviors and skills and

must implement certain strategies to be successful. Drucker‟s text included various

topics, such as the practice of management, managing for results, and the behaviors of

effective managers. The quantitative study involved examining the theory that leadership

skills and abilities affect employee retention. Through the questionnaire and open-ended

questions, the survey aided in gathering data from employees about the effect of leaders‟

decision making abilities on employees‟ decisions to leave organizations. The study also
                                                                                          18


involved examining the impact of employees‟ perceptions of leaders‟ abilities and skills

on employees‟ decisions to leave organizations.

                                      Definition of Terms

         The definitions of terms that appear prominently in the study are as follows:

         Employee burnout. Employee burnout is the degree to which employees are

overextended at work (Siebenmark, 2006).

         Employee morale. Employee morale involves the attitude that employees have

towards the work and the organization (“The Secrets,” 2006).

         Employee turnover. Employee turnover is the rate at which organizations lose

employees (Moore, 2006).

         Employee turnover intention. Employee turnover intention refers to the reasons

employees choose to remain with organizations (Chandler, 2004).

         Hostile work environment. A hostile work environment depicts an environment

where employees have negative relationships with each other (McLellan, 2006a).

         IT professional. An IT professional is anyone who works in the IT industry. The

term is not limited to any particular job function in the IT industry (Foote, 2006).

         Job retention. Job retention illustrates an organization‟s ability to retain

employees (Chandler, 2004).

         Job satisfaction. Job satisfaction is the degree to which an employee finds

fulfillment in the work (Foote, 2006).

         Motivation. Motivation involves how a supervisor is able to inspire employees to

enjoy the job and ultimately optimize employees‟ job performance (Berry, 2006; Li,

2006).
                                                                                          19


        Organizational culture. Organizational culture involves the values and norms of

an organization (Buhler, 2007).

        Workplace orientation. Workplace orientation depicts the nature of an

organization‟s work environment as it relates to how people in the organization socialize

with each other (McLellan, 2006a; “The Secrets,” 2006).

                                       Assumptions

        One of the assumptions for this study was that using a web survey would provide

a quick and easy method for collecting survey data. Creswell (2002) noted that

“electronic data collection provides an easy, quick form of data collection” (p.159). A

second assumption was that because the survey participants would be IT professionals,

they would be familiar with electronic mail and internet technologies. The assumption

was that respondents would understand how to use the internet to send the survey

questionnaire, and respondents would be able to access electronic mails. Another

assumption was that participants would respond to the survey in a timely fashion and

would be able to complete and submit the surveys within 2 weeks.

                          Scope, Limitations, and Delimitations

Scope

        Though several studies exist on the topic of employee retention and employee job

satisfaction, this study included a focus on turnover of IT workers in the DC metropolitan

area. The research population for the study was 200 IT workers and the study was not

limited to any particular function within the IT profession. The MSQ was the survey

instrument for the study and was appropriate because the survey questions measured job
                                                                                        20


satisfaction (across 20 dimensions) assessing organizational, individual, and

nonindividual work factors.

Limitations

       The study had limitations that could not be controlled. The period for completing

the survey depended on each respondent because the survey was administered at the

respondents‟ convenience. The demographic of the research population could not be

controlled because the survey was administered anonymously via the internet. Another

limitation was that some employees might not have shared their views honestly due to

concern about their jobs.

Delimitations

       One of the delimitations of the study was that the research population would be IT

workers. The IT workers represented various functional areas, such as software

development, systems analysis, database development, software testing, and data

modeling. The study involved a focus on IT workers in the DC metropolitan area:

Washington DC, Virginia, and Maryland. The sample for this study was 144 IT workers.

Because the sample included all IT workers, the findings from this study may be

generalized to all IT professionals. However, the findings from this study may not be

generalized to other industries.

                                         Summary

       Employee turnover can be a costly problem for IT companies because

organizations have to address concerns such as the high cost of training and development,

lost work time during a vacancy, and employee burnout due to staff shortage. Most

retention strategies are ineffective because they do not include consideration of the
                                                                                          21


dynamic factors that influence employee retention (Li, 2006). Studies indicate that skilled

IT workers are scarce commodities (Kamal, 2005), and the U.S. Department of

Commerce estimated that the United States will require more than 1.3 million new and

highly skilled IT workers to address the staff shortage (Kamal, 2005). IT organizations

must make employee retention a priority to ensure a strong workforce. The study

involved examining the factors that motivate IT employees to leave organizations.

Chapter 2 includes a review of the literature that forms the theoretical framework for the

quantitative research.
                                                                                              22


                    CHAPTER 2: REVIEW OF THE LITERATURE

       The purpose of this study was to examine employee turnover in the IT industry.

The literature review revealed that employee job satisfaction and employee job retention

are two topics that researchers have studied extensively. Job satisfaction studies included

examining employee attitudes toward their jobs (Curran, 2006; Lock, 2003; Klie, 2006;

Shields, 2006; Shore, Sy, & Strauss, 2006). The results of job satisfaction studies reveal

the various issues that organizations must address to ensure that employees feel fulfilled

in their jobs (Beauchesne, 2006; Brodie, 2006; “Excellent People,” 2007; “The Secrets,”

2006). Employee retention involves an organization‟s ability to retain its employee base

(Chandler, 2004; Messmer, 2006; Samad, 2006; “The Secrets,” 2006).

       Low employee retention can be financially burdensome for organizations because

of the need to train new staff members each time employees leave organizations

(Goughnour, 2001; Kamal, 2005; Muck, 2006; “The Secrets,” 2006; Stetenfeld, 2007;

“Study Shows,” 1999). When employees leave, organizational knowledge is lost and

organizations have to expend time and money to redevelop lost knowledge (De Long &

Davenport, 2003; Siebenmark, 2006; Waldman & Arora, 2004). Organizations also have

to spend time and money to train replacement employees to ensure continuity of

organizational initiatives (Siebenmark, 2006). Another matter that organizations must

consider is the loss of employees to competitors (Messmer, 2006).

       Chapter 2 is organized into 9 sections. The first section provides a list of all the

sources of information for this study. The second section provides a historical perspective

on employee loyalty. The third section provides a historical perspective on employee

motivation. The fourth section provides a discussion on leadership and employee
                                                                                              23


relationships. The fifth section provides an overview on employee job satisfaction. The

sixth section provides a summary on employee turnover. The seventh section describes

several turnover models and describes how they can be used to predict employee

turnover. The eighth section provides a summary of the various contributing factors to

employee turnover. The ninth section includes descriptions of the various factors that

affect job satisfaction.

                                       Documentation

        The literature review for this study included reviewing journal articles,

empirically based research documents, and books. The literature review was performed

by searching the following data sources: (a) Apollo, (b) ABI/INFORM, (c) EBSCOhost,

(d) ProQuest, and (e) Google. Literature on employee retention and employee turnover

encompasses various topics some of which include the following: (a) employee

motivation, (b) job satisfaction, and (c) turnover intentions. Table 2 below provides the

following: (a) a detailed list of the topics that were covered during the literature review,

(b) the data sources, and (c) the total of the literature that was reviewed for each topic.
                                                                                      24




Table 2

Documentation

                             Peer                                      Popular    Total
     Research area      Reviewed                       Doctoral         Press
                            Articles       Books   Dissertations       Articles

Job Satisfaction        10                         1               5              16
Job Retention           43                                         7              50
Employee Turnover       11                         3               7              21
Turnover Models         4                                                         4
Workplace orientation   2                                          1              3
Employee Motivation                                                3              3
Employee Morale                                                    1              1
Employee Burnout        1                                                         1
Workplace                                                          2              2
Relationships
Employee Loyalty        4                                                         4
Leadership Models                                                  2              2
Management Skills       1                                          1              2
Research Methods                       1                                          1
MSQ (Minnesota          2              1                                          3
Satisfaction Survey)
Totals                  34             2           4               73             113
                                                                                          25




Gaps in Literature

       The literature review revealed gaps in research relating to turnover decisions of IT

workers. Though various authors have examined employee retention and employee

turnover, most of these studies were based on other industries besides the IT industry

(Curran, 2006; Dahm, 2006; Evergreen focuses on employee retention, 2006; Klie, 2006;

McKay et al., 2007; Yaying, 2007). Few of the literature reviewed on IT employee

turnover were based on empirical data.

       Burnes (2006) examined retention in the IT industry but the author focused on a

specific group of IT workers. Though Burnes‟s study was based on the IT industry, the

study examined the phenomenon of voluntary turnover of Generation X employees in

profit-making organizations in the IT industry in the Rocky Mountain and Midwestern

states. The current study was significant because the research did not involve an

examination of job satisfaction alone but included an examination of the organizational

and individual factors that affect IT employees‟ decisions to leave organizations. No

literature was found on employee retention or employee turnover of IT employees in the

DC metropolitan area. The current study examined the factors that influence IT

employees‟ decisions to leave and the study was based in the DC metropolitan area.

                      Historical Perspectives on Employee Loyalty

       Prior to the 1990‟s, employee loyalty was common, and employees remained with

organizations (Carson et al., 2006; “Employees Keep,” 2006; Ranii, 2007). Employees

joined organizations with plans to remain at the same organization until retirement (Lock,

2003). The workforce consisted of employees who remained at the same organization for
                                                                                         26


an average of 15 years. Studies indicated that employees who remained with the same

organization were viewed as stable and reliable (Coughlan, 2005); conversely, employees

who worked in an organization for fewer than 10 years were viewed as unstable (Carson

et al., 2006). Organizations expected employees to remain; special concessions were

unnecessary to ensure employee loyalty (Li, 2006).

       Since the 1990‟s, employees in the information technology (IT) industry have

changed jobs rapidly (“Employees Keep,” 2006; Lock, 2003; Whitaker, 1999).

Organizations are becoming more aware that they must cultivate the right work

environment in which employees will want to work (Anastasopoulos, 2005; Lovett,

Hardebeck, Coyle, & Torres, 2006). Organizations are investing in initiatives to cultivate

nonhostile work environments and inspire employees to be productive and perform

optimally (“IT Staff,” 2004; Russell, 2005).

                     Historical Perspectives on Employee Retention

       Researchers have examined employee retention from various perspectives

(Hartley, 2005; Kleiman, 2006; Maureen, Houser, Jarrar, Moy, & Wall, 2003; McLellan,

2006b; Muck, 2006; Parrish, 2006; Whitaker, 1999). Studies by researchers such as Al-

Ajmi (2006) and Thozhur et al. (2006) included a focus on the impact of gender on

employee retention. Long (2005) examined the effect of age on employee retention.

Though authors have addressed employee retention from various angles, the authors

agreed that employee retention is an issue that organizations must take seriously (Al-

Ajmi, 2006; Anuradha, 2005; Berry, 2006; Korney, 2007; Moore, 2006; Retaining good

employees take commitment, 2006; Thozhur et al., 2006).
                                                                                        27


       According to Berry (2006), employers unable to retain the best performers

experience adverse effects. The issues include the costs of recruiting new employees,

decline in product quality, and decline in customer satisfaction. Moore (2006) noted that

the cost of recruiting and replacing employees is high; when organizations are unable to

recruit new employees, the morale of existing employees suffers. Thus, organizations

should make employee retention a priority from the onset. When making retention a

priority, organizations will retain employees and avoid spending unnecessary funds to

replace employees.

       Low employee retention can be financially burdensome for organizations because

of the need to train new staff members each time employees leave (Chandler, 2004).

According to Gemignani (1998), organizations spend approximately 50% of an

employee‟s annual salary each time an employee leaves (as cited in McKay et al., 2007).

Turnover cost includes the cost of recruiting, hiring, and training new employees. Steiger

and Fillichio (2007) stated that when U.S. organizations lose employees, they lose

business continuity, technical expertise, and institutional knowledge.

       When employees leave, organizations lose the knowledge base and have to spend

time and money to redevelop the knowledge base (Quigley, 2006). As organizations hire

new employees, time and money are required for training. Another potential issue that

organizations must consider is losing employees to competitors. Yaying (2007) stated

that organizations must address employee job satisfaction because of its effect on

employee retention. The quantitative study involved examining employee job satisfaction

to determine the factors that encourage employees to leave organizations.
                                                                                                28


                      Historical Perspectives on Employee Motivation

        The basis of the study was older and modern motivational theories. Herzberg et

al. (1959) examined the factors that affect how people feel about their jobs and grouped

the factors into job satisfiers and job dissatisfiers (as cited in Jasper, 2007). Herzberg et

al. noted that people experience stress at work. Employees are either satisfied or

dissatisfied based on their values, and employees are either constrained or repelled based

on stress factors.

        The basis of the motivator-hygiene theory by Herzberg et al. (1959) is the

relationship between work values and work stress. Employees have intrinsic and extrinsic

work values (as cited in Jasper, 2007). When organizations meet the intrinsic values,

employee stress decreases; when organizations meet the extrinsic values, employees are

satisfied. Intrinsic values include achievement, recognition, the value of the work itself,

and responsibility, and extrinsic values include working conditions, security, and

benefits. The study involved examining if the intrinsic and extrinsic values of IT workers

affect their attitudes toward the job and the organization.

        According to Maslow (1943), people have needs as early as conception (as cited

in Jasper Associates, 2007) and these needs include food, drink, and warmth. Maslow

noted that people‟s needs must be met as part of survival. Maslow‟s hierarchy of needs

illustrates groups of human needs in the following order: physiological needs; safety

needs; needs for love, affection, and belongingness; needs for esteem; and needs for self-

actualization (Jasper Associates, 2007).

        The most important human needs are physiological. According to Maslow‟s

theory (1943), once people have met the physiological needs, people will look to satisfy
                                                                                           29


other needs based on the order in which they appear in the pyramid of needs (as cited in

Jasper, 2007). Studies indicated that retention strategies have been ineffective because

they did not include consideration of the fact that employees‟ needs vary and are dynamic

(Buhler, 2007; DeMers, 2002; Foote, 2006; Johnson, 2007; Vu, 2006). Literature

illustrates that even offering workers high salaries and attractive benefit packages has not

addressed the turnover problem in the IT industry effectively (“IT Staff,” 2004). The

quantitative study included five open-ended questions to aid in examining the reasons

employees who have changed jobs chose to leave the former employer.

       McGregor (1960) developed the X and Y theory (as cited in Jasper Associates,

2007). McGregor defined assumptions that underpinned the practices and stances of

managers in relation to employees and dubbed two sets of propositions theory X and Y.

Maslow‟s (1943) need satisfaction model of motivation theory was the foundation for

McGregor‟s X and Y theory because Maslow‟s theory established the notion that needs

provide the driving force motivating behavior and general orientation (as cited in Jasper

Associates, 2007). Maslow‟s theory indicated that employee dissatisfaction with work

was not due to something intrinsic to the employees but due to poor job design,

managerial behavior, and too few opportunities for job satisfaction. McGregor‟s theory

on managerial behavior had a profound effect on management thinking and practice and

provided a unitary and normative frame of reference for managerial practice.

       Porter and Lawler‟s (1968) model of motivation indicated that people at work are

motivated to perform because of expectations of perceived payoffs or rewards arising

from the performance (as cited in UK Essays, 2008). As in McGregor„s (1960) X and Y

theory, the model of motivation illustrated that the perception of expectancy and force of
                                                                                            30


expression are intrinsic to each person (as cited in Jasper Associates, 2007). Porter and

Lawler‟s (1968) model shows that each person‟s view of what is challenging or

interesting will vary, and each person will invariably have a different regard for extrinsic

payoffs, such as pay and material rewards (as cited in UK Essays, 2008). Porter and

Lawler‟s model of motivation was important to the quantitative study because the basis

of the study was the theory that employees have differing reasons for leaving

organizations. One of the theories postulated in the study was that the same factors would

not motivate all employees.

                         Leadership and Employee Relationships

       The transformational leadership style is vital for the business world (“The

Secrets,” 2006). The greatest outcome of the transformational leadership style is that it

fosters strong relationships between leaders and followers (Moore, 2006). Unlike

transactional leaders who focus on accomplishing tasks through followers,

transformational leaders focus on using relationships to inspire and motivate employees

(Bass & Steidlmeier, 1998). The transformational leader has a vision and seeks to inspire

and motivate followers to embrace the vision. For transformational leaders to be

successful, they must be able to establish meaningful relationships with followers

(Kleiman, 2006). When leaders establish meaningful relationships with followers, leaders

and followers engage in a mutual process of raising one another to higher levels of

morality and motivation (Vu, 2006).

       Dyer (2001) provided an effective description of the relational leadership

observed in the transformational style of leadership. Dyer made four important points

about relational leadership:
                                                                                            31


   1. Relational leadership involves being attuned to and in touch with the intricate web

       of inter and intrarelationships that influence an organization.

   2. Relational leadership is more than being a “people person.”

   3. Relational leadership is cultivated when leaders are willing to receive input from

       followers.

   4. Leadership success depends on how leaders relate with followers.

Dyer indicated that organizational leaders must realize that processes, tools, plans, and

strategic plans cannot replace building meaningful relationships with employees. Dyer

highlighted the importance of leaders building and nurturing the interrelationships and

intrarelationships in the organization.

       Leaders cannot relate with employees effectively if they do not take the time to

build meaningful relationships (Shore et al., 2006). Employees in a transactional system

follow orders out of fear of punishment or reproof; this type of system does not help

followers to be motivated or inspired by the organizational vision. Employees simply

work because they have to work and not because they want to work.

       Unlike transactional leaders, transformational leaders inspire followers to

participate in accomplishing the vision (Bass & Steidlmeier, 1998). Because

transformational leaders welcome feedback from followers, followers feel empowered to

contribute skills, knowledge, and experiences to the organizational knowledge base. Such

empowerment builds a diverse workforce with various talents and skills. Leaders are able

to create effective teams and accomplish organizational work more efficiently.
                                                                                            32


Dynamics of Transformational Leadership and Employee Loyalty

       Studies show that employees who embrace the organization‟s vision are more

likely to remain with the organization than employees who do not embrace the vision

(Berry, 2006; McKenzie, 2007). Other studies illustrate that expecting employees to

follow the vision is not enough (Moore, 2006; Siebenmark, 2006). Employees will only

embrace visions they understand.

       The transformational style of leadership is important because leaders need to be

able to connect with employees (Moore, 2006; Siebenmark, 2006). The greatest outcome

of the transformational leadership style is that it fosters strong relationships between

leaders and followers. Transformational leaders seek to inspire and motivate followers to

embrace the vision, which cannot happen without a genuine bond between leaders and

followers. Unlike transactional leaders who focus on accomplishing tasks through

followers, transformational leaders are able to inspire employees to embrace the vision

(Bass & Steidlmeier, 1998).

Dynamics of Transformational Leadership in a Culture of Trust

       Russell (2005) stated that employees would only be confident and enthusiastic

about a leader they trust. Russell noted that leaders must earn trust, and trust will not

happen overnight. Russell‟s text indicated that trust is an important part of relationships

between employees and leaders. The first and most important point is that people cannot

trust people they do not know. The second point is that when people do not take the time

to know each other, they tend to make wrong assumptions and presumptions about

motives and intentions; however, when people truly know each other, they are able to

understand each other better. Trust does not occur quickly and will not happen unless it is
                                                                                           33


cultivated and sustained in an environment of respect (Buhler, 2007; Employee

engagement, 2006; Lock, 2003). In an organization that reflects respect, people will be

able to value others for whom they are and the value they bring to the organization.

       According to George (2003), “authentic leaders” are more interested in

empowering employees to be the best they can be (as cited in Geller 2007, p.14). The

author noted that authentic leaders are more concerned about employees than about

power, money, or prestige. This type of leadership is consistent with the transformational

model of leadership where passion and compassion for employees guide leaders, and

with the passion, leaders can inspire employees.

       Transformational leaders are effective through cultivating meaningful

relationships with employees. George (2003) noted that when leaders are consistent in

character and in actions, they are able to develop trusting relationships with employees

(as cited in Geller, 2007). Trust emerges in an environment where people respect and

value each other (Lewin & Regine, 2000).

       Trust is an important ingredient for teamwork if team members must collaborate

and share ideas and skills with each other (Buhler, 2007). As teams form, members

become interdependent with each other for success. Members are willing to see every

success as the team‟s success, and everyone is willing to share the limelight. In the same

way, when a problem arises on the team, team members are able to see the problem as a

team issue and are willing to work in unity to resolve the issue.

       The strongest impact of the transformational leadership model is a vital

relationship between leaders and followers. People cultivate trust when they take the time

to know each other. According to Klempner (2005), transformational leaders are mainly
                                                                                           34


concerned with treating people well. Klempner added that transformational leaders focus

on motivating people to feel fulfilled in their work. The benefit of this type of

relationship is an empowered workforce where people have a shared vision, and the basis

of relationships in the organization is sound principles and values (Bass & Steidlmeier,

1998; Lewin & Regine, 2000).

       The effect of the trusting relationships in the transformational leadership model is

efficiency, effectiveness, and creativity. As opposed to transactional leaders who use

commands and instruction to prompt followers to work, transformational leaders seek to

generate change in the hearts and minds of people. The result of the transformational

leadership approach is a culture of trust (Bass & Steidlmeier, 1998). According to

Kemper (2005), transformational leaders first inspire followers and provide the right

environment for employees to grow.

Cultivating a Trusting Work Environment

       Employees are most productive in an environment where trust exists (Buhler,

2007; Salerno, 2006). Gerald (1994) mentioned that leaders must strive to eliminate fear

from the organization to cultivate a work environment where people can trust each other

and work cooperatively. Gerald indicated that as employees work cooperatively, overall

organizational productivity and product quality would improve. Moos (1981) pointed out

that three dimensions of work environment settings could measure work environment

preferences: system maintenance, goal orientation, and relationship dimensions (as cited

in Westerman & Simmons, 2007).
                                                                                         35


                                Employee Job Satisfaction

       Employee job satisfaction is “the extent of employee‟s expectation that their job

will provide a mix of features (such as pay, promotion, or autonomy), and for which each

employee has certain preferential values” (Hwang & Kuo, 2006, p. 254). Studies show

that when employees are satisfied with their jobs, productivity will be high (Building

employee commitment, 2007; Carbery, Garavan, O‟Brien, & McDonnell, 2007). Bien-

Aime (2007) suggested that job satisfaction rates indicate the degree to which employees

are content with their jobs. Employee satisfaction may be hard to measure because

employees may be dissatisfied with the jobs but not leave the organization (Yaying,

2007). Employees may also like the organization but not like the jobs (Li, 2006).

       Researchers suggested that when leaders want to determine employee satisfaction,

they must assess employee satisfaction from various angles (Chiaburu et al., 2006; Foote,

2006; Kanter, 2001; Li, 2006; Mayfield & Mayfield, 2006). The implication is that

measuring employee satisfaction is not as simple as it may seem (Chang & Lee, 2006;

Emmerik & Sanders, 2005; Ferris, 2006; Kahn, 2007; Li, 2006). Research indicates that

employee satisfaction may vary based on demographical factors, such as race, gender,

age, and religion (Madsen, 2006; McKay et al., 2007; McLellan, 2006a; Watlington et al.,

2004). As the workplace becomes more diverse, employee satisfaction will become more

challenging because of the unique values that each employee brings to the workplace (Al-

Ajmi, 2006; Chang & Lee, 2006).

                                   Employee Turnover

       Anuradha (2005) stated that turnover intentions can indicate employees‟ plans to

leave but will not indicate if people who remain do so because they are motivated to stay.
                                                                                           36


Kamal (2005) noted the shortage of IT workers as a critical issue. Lock (2003)

emphasized that since the early 1990s, organizations within the government and private

sector have had challenges recruiting and retaining IT workers. The quantitative research

involved identifying the factors that motivate IT employees to leave organizations.

Turnover can be financially costly for organizations (McKay et al., 2007; Wagar &

Rondeau, 2006). Employee turnover can cost over $10,000 for each employee who leaves

an organization (McKay et al., 2007). Conroy (2007) indicated that companies do not

have to pay employees high salaries to lower turnover rates, so employee turnover may

not relate directly to salary.

        Other factors besides money may affect employee turnover (Good, 2007;

Goodboe, 2002; Goshe et al., 2006; Goughnour, 2001; Hartley, 2005; Wilson, Moore, &

Paulson, 1993). Conroy (2007) indicated that when employees do not trust the leaders,

they will look for work elsewhere. Conroy mentioned that “[Companies on Fortune‟s]

100 Best Companies to Work For…have turnover rates of 2 to 4 percent—and most are

not even close to being the highest payers in their field” (p. 1); thus, turnover has more to

do with the relationships employees have with supervisors than how much employees

earn.

        On the contrary, Carrillo (2006), Thozhur et al. (2006), and Sweeney and

McFarlin (2005) noted that salary is one of the most important incentives for employees.

Sweeney and McFarlin (2005) noted that dissatisfaction with pay is a reliable predictor of

employee absenteeism and turnover. Literature illustrates that when employees do not

receive adequate compensation, they will leave the organization (Business Wire, 2004;

Foote, 2006).
                                                                                          37


                                     Turnover Models

       Several authors have identified factors that predict turnover intentions (Samad,

2006). The factors include age, gender, personality traits, race, and employee recognition.

Many authors have also developed turnover models that illustrate the components

involved in an employee‟s decision to leave an organization (Fugate, Kinicki, & Prussia,

2008; Hwang & Kuo, 2006; Samad, 2006; Thomas & Mowday, 1987; Yaying, 2007).

Organizational psychologists, management scientists, and sociologists have examined

turnover intentions, organizational commitment, and job satisfaction to understand how

each of the components factors into an employee‟s decision to resign. The identification

of factors that influence turnover intentions is an important step in reducing actual

turnover (Fugate et al., 2008; Yaying, 2007).

       Two of the factors identified as contributing to turnover intentions are

organizational commitment and job satisfaction (Fugate et al., 2008). Several authors

examined turnover models to uncover the contributing factors to employee turnover

(Thomas & Mowday, 1987; Yaying, 2007) and indicated that turnover models are helpful

in predicting employee turnover (Fugate et al., 2008). Yaying (2007) explored the

structural equation model (SEM) to determine employee propensity to leave the

accounting profession. Yaying indicated that firms could develop two retention programs

for employees with high and low movement capital.

       Yaying‟s (2007) turnover model illustrates that leader member exchange (LMX)

and team-member exchange (TMX) are two precedents of organizational commitment

and job satisfaction. Yaying noted that organizational commitment and employee job

satisfaction affect turnover decisions among accounting knowledge workers. The findings
                                                                                           38


from Yaying‟s study indicated that when both organizational commitment and job

satisfaction variables are present in the turnover model, job satisfaction is the most

important factor in determining employee propensity to leave. Yaying also noted that an

effective human resource development strategy should include a focus on increasing

employee job satisfaction, which will reduce turnover.

       Prior to Yaying (2007), researchers had developed turnover models. Thomas and

Mowday (1987) proposed a turnover model that illustrates how job satisfaction and

organizational commitment would affect employee intent to leave an organization. Horn

and Griffeth‟s (1995) turnover model also illustrated job satisfaction and organizational

commitment as two antecedents of voluntary turnover (as cited in Hwang & Kuo, 2006).

Yaying (2007) noted that employees who have turnover intentions would eventually

leave the organization.

Appraisal Theory of Emotions Model

       Fugate et al. (2008) based the appraisal theory of emotions model on the appraisal

theory of emotions. The model illustrates how employees respond to stressful situations

in the organization. Fugate et al. noted that three types of responses exist: stimulus-

response, partial mediation, and moderated. According to Fugate et al., coping with

organizational change is a completely mediated process best represented by the stimulus-

response theoretical structure. The model depicts how employees respond positively and

negatively to the changes in organizations.

       In the appraisal theory of emotions model (see Figure 3), Fugate et al. (2008)

identified the process of processing negative and positive stimulus as negative and

positive appraisal respectively. The negative appraisal process includes reduced control
                                                                                                    39


and increased escape coping tendencies. The model also illustrates how negative

emotions can affect human coping tendencies. Negative emotions will influence how

employees will use sick time; negative emotions will ultimately predict voluntary

turnover.




Figure 3. Fully mediated model of coping with organizational change based on appraisal

theory of emotions.

Note. From “Employee Coping With Organizational Change: An Examination of Alternative Theoretical

Perspectives and Models,” by Fugate, M. et al., 2008. Copyright 2007 by Blackwell Publishing Ltd.

Reprinted with permission.




        The basis of the model of coping is the cognitive appraisal theory of emotions

(Fugate et al., 2008). The model illustrates how employees cope with organizational

change. Employee appraisal of stimuli in organizations precipitates emotional responses,

and the emotional responses will influence employees‟ coping strategies and outcomes.
                                                                                           40


       Fugate et al. (2008) linked appraisal, emotions, and behaviors within larger

biobehavioral systems of withdrawal and engagement. The authors explained that the

behavioral inhibition system (BIS) depicts how people respond to perceived threats. The

inevitable response to perceived threats is withdrawal or avoidance, and this reaction will

involve negative emotions. The behavioral facilitation system (BFS) is another concept in

the appraisal theory of emotions model to explain how people react to situations. In the

BFS system, people respond to situations they perceive as beneficial or desirable.

Stimulus-Response Model of Coping

       The basis of the stimulus-response theory (see Figure 4) is that people will have

immediate and unmediated coping reactions in stressful situations (Fugate et al., 2008).

When people feel threatened, their response to the threat is their coping strategies to deal

with the stress. Fugate et al. noted that when people appraise situations as stressful, they

use coping strategies, such as control and escape, to deal with the situations.




Figure 4. Fully mediated model of coping with organizational change based on the

stimulus-response theory of coping.
                                                                                                        41

Note. From “Employee Coping With Organizational Change: An Examination of Alternative Theoretical

Perspectives and Models,” by Fugate, M. et al., 2008. Copyright 2008 by Blackwell Publishing Ltd.

Reprinted with permission.

Ethical Climate Structural Model

        The ethical climate structural model (see Figure 5) is another model that

illustrates turnover intentions (Mulki, Jaramillo, & Locander, 2008). The model depicts

how the following variables relate to turnover intentions: (a) ethical climate, (b) trust in

supervisor, (c) emotional exhaustion, (d) interpersonal conflict, (e) job satisfaction, (f)

role ambiguity, and (g) role conflict. Mulki et al. examined the relationship between

ethical conflict and turnover intention (EC-TI) by testing an empirical model that

simultaneously tests the mediation of the following: role stress (RS); trust in supervisor

(TS); and job satisfaction (JS).




Figure 5. Ethical climate structural model.

Note. From “Effect of Ethical Climate on Turnover Intention: Linking Attitudinal and Stress,” by Mulki, J.

P. et al., 2008. Copyright 2007 by Springer. Reprinted with permission.
                                                                                           42


Mulki et al. noted, “A better understanding of the mechanisms through which EC affects

TIs has significant implications for both practitioners and academicians” (p. 560).

Linking EC to important organizational variables can yield positive job attitudes, lower

stress, and lower TI.

                             Factors Affecting Job Satisfaction

         Several researchers have examined factors that affect job satisfaction (Kahn,

2007; McKay et al., 2007; Shields, 2006). The factors include how gender affects job

satisfaction (Shields, 2006), how race affects job satisfaction (McKay et al., 2007), how

pay affects job satisfaction (Shields, 2006; Sweeney & McFarlin, 2005), and how

employee recognition affects job satisfaction (Kahn, 2007). Organizations must realize

that not all employees may be motivated by the same organizational incentives.

Gender

         Shields (2006) examined how gender influences job satisfaction. Men who

worked evening or night shifts were more likely to report dissatisfaction than those who

worked regular daytime schedules. Men who worked rotating shifts also demonstrated

dissatisfaction with their jobs. In contrast, women who worked irregular shifts were more

likely to be satisfied.

         Shields (2006) indicated that both men and women who worked longer than the

standard hours (more than 40 hours a week) were less likely to be dissatisfied with their

jobs compared to coworkers who worked regular hours (30 to 40 hours a week). Men

who worked part-time seemed more dissatisfied than men who worked regular hours. In

contrast, women who worked part-time were more likely to be content with their jobs.
                                                                                         43


Employee Recognition

       Kahn (2007) examined how employee recognition influences job satisfaction.

Kahn expressed that money is usually an inadequate employee motivator. When

employees work hard, they need recognition for their hard work. Kahn noted that when

employees receive recognition for exceptional work, they feel motivated to raise their

work standard and embrace the company‟s goals. Recognition programs are an important

tool that organizations can use to increase loyalty, retention, employee and customer

satisfaction, and financial gain.

                                    Factors Affecting Turnover

       Employee turnover is an important issue for organizations because of the cost of

recruiting new employees, the loss of money that organizations have invested in the

departing employee, and the impact that staff shortages can have on organizational

productivity (Chandler, 2004). Several researchers examined the factors that influence

employee turnover (Chang & Lee, 2006; Lambert, Kass, Piotrowski, & Vodanovich,

2006; McKay et al., 2007; Moyes, Williams, & Koch, 2006; Woodruffe, 2006). Some

authors noted that other factors besides money motivate employees (Conroy, 2007; Lock,

2003; Mayfield & Mayfield, 2006). Other authors suggested that effective retention

strategies should include a combination of pay, training, recognition, and respect (Lock,

2003; Stetenfeld, 2007).

Race

       McKay et al. (2007) examined the influence of diversity climate perceptions on

turnover intentions among managerial employees in a national retail organization. The

results of the study, which included a sample of 5,370 managers, indicated that Black
                                                                                          44


workers would have negative turnover intentions in prodiversity work climates.

Additional results from the study illustrated that Hispanic workers would have the next

strongest turnover intentions, and White employees would have the weakest turnover

intentions. Turnover rates are considerably lower for minority workers than White

employees.

Age

       Moyes et al. (2006) examined how age affects job satisfaction in the accounting

industry. The authors investigated the extent to which age could lead to differences in

perceptions of work-related attributes, such as advancement opportunities and relations

with supervisors. Research findings illustrated that older female and older male

accounting professionals felt more fulfilled in their jobs than did their younger

counterparts. Younger female employees reported that they received better treatment and

support from supervisors than did younger males; younger female employees also

reported that they experienced less gender discrimination than did older female

accounting professionals.

Personality Traits

       Chang and Lee (2006) examined how personality traits influence job satisfaction.

The authors used the path analysis to explore the relationships among personality traits,

job characteristics, job satisfaction, and organizational commitment. The research

findings indicated that “job characteristics influence personal job performance through

individual psychological perceptions, including internal motives, job performance, job

satisfaction or resignation behaviors” (p.201). Chang and Lee noted that extroversion
                                                                                              45


correlates positively to job satisfaction, evident in the conscientiousness that extroverts

are more likely to display.

Training

       Woodruffe (2006) suggested that training and development are invaluable

incentives that organizations can provide to encourage employees to remain. Woodruffe

noted that by training employees, organizations invest in the talent pool of the

organization. Training and development is a win-win retention strategy for organizations:

When organizations train employees, organizations develop the knowledge base and

increase an employee‟s marketability in the job workforce. Woodruffe indicated that

organizations should take retention strategies seriously because losing employees costs

more money.

       Stetenfeld (2007) examined the extent to which training could influence employee

retention decisions in the banking industry, specifically the retention decisions of Credit

Union employees. Stetenfeld noted that employees leave organizations even when they

have prestige positions and receive high salaries. An effective retention strategy for

organizations is to hire qualified people and provide professional development,

education, and training to ensure that employees are successful in their jobs. Stetenfeld

did not dispute the importance of pay and promotions but suggested that managers

usually underestimate the importance of training. Providing employee training and

development is the responsibility of managers and supervisors.

Pay

       Sweeney and McFarlin (2005) indicated that pay is one of the most important

reasons people work. The authors noted that dissatisfaction with pay is a reliable
                                                                                           46


predictor of employee absenteeism and turnover. Fair compensation and reward directly

affect employee attitude toward job and organization.

        Similarly, Thozhur et al. (2006) noted that employees would be dissatisfied with

their jobs if they did not receive adequate compensation. Shields (2006) suggested that

job satisfaction relates to personal income. Shields examined the degree to which pay

affects job satisfaction. Research findings indicated that men who earned $20,000 to

$39,000 a year were satisfied with their jobs; over 50% of men who earned less than

$20,000 were dissatisfied with their jobs, and men who earned $40,000 or more were less

likely to be dissatisfied.

Challenging Work

        Conroy (2007) emphasized that organizations do not have to pay employees high

salaries to experience lower turnover. According to Conroy, “[Organizations on

Fortune‟s] annual list of „100 Best Companies to Work For‟…have turnover rates of 2 to

4 percent—and most are not even close to being the highest payers in their field” (p.1).

Conroy indicated that managers motivate employees by giving employees challenging

projects and opportunities. When managers give employees challenging work, managers

provide opportunities for employees to grow and ultimately avoid loosing them.

        Lock (2003) examined the extent to which challenging work motivated employees

in the IT industry. Like Conroy (2007), Lock (2003) suggested that managers usually

underestimate the impact of challenging work as a motivation strategy. Lock indicated

the importance of challenging work but noted that the following factors motivate

employees: (a) reward, (b) freedom to be creative and innovative, (c) recognition, (d)

respect, and (e) a balanced work life.
                                                                                       47


Respect

       Maureen et al. (2003) noted that the way managers treat employees would affect

employees‟ attitudes towards their jobs. The authors noted that managers often think that

money is the only employee motivator. Even if managers pay employees high salaries,

employees will not be motivated if managers do not respect them. Maureen et al.

suggested that recognition and respect are important to employees. Allen, Armstrong,

Riemenschneider, and Reid (2006) cited lack of respect as one of the factors that female

IT workers perceived as a reason for not advancing in the IT industry.

Full-Time and Part-Time Workers

       Mayfield and Mayfield (2006) examined the relationship between work structure

(i.e., part-time, permanent, and contract) and employee turnover. Mayfield and Mayfield

indicated that organizations hire part-time workers because part-time work structures are

convenient and inexpensive. Though organizations experience immediate benefits in

choosing part-time workers over permanent workers, research findings illustrate that “the

national estimated turnover rate for these employees is generally high, with a U.S.

average turnover rate in 2002 for part-time workers of 45.9% compared to 23.8% for full-

time positions” (p. 131). Mayfield and Mayfield also mentioned that the use of part-time

workers is a growing trend in the IT industry.

                                       Conclusion

       Chapter 2 provided the theoretical framework for the study through an

examination of the following topics: employee job satisfaction, employee motivation,

employee loyalty, employee turnover, employee retention, and organizational

relationships. Chapter 2 included descriptions of the key contributions of previous
                                                                                           48


studies, which will form the basis for this study. The chapter provided an overview of

employee turnover and employee job satisfaction. The overview included a discussion of

the contributing factors to employee turnover.

        Several authors noted that employees are not all motivated by the same factors

(Avery, Tonidandel, Morris, et al., 2007; Conroy, 2007; Foote, 2007; Li, 2006). Other

authors noted that when employees are satisfied with their jobs they will remain with

their organization (Kahn, 2007; McKay et al., 2007; Shields, 2006). Chapter 2 provided

illustrations of several turnover models that can be used to predict employee turnover

(Fugate, Kinicki, and Prussia‟s, 2008; Hwang & Kuo, 2006; Samad, 2006; Thomas &

Mowday, 1987; Yaying, 2007). The turnover models identified various factors such as

job satisfaction, organizational commitment, leader member exchange, team member

exchange, trust in supervisor, and interpersonal conflict and the models illustrated how

these factors can lead to employee turnover.

                                         Summary

        Studies on employee retention indicated that losing employees will affect

organizational initiatives negatively (Berry, 2006; Hiring and keeping quality workers,

2006; Moore, 2006). The impact of employee turnover includes a decline in the morale of

existing employees, a decline in productivity, a decline in product quality, and a decline

in customer satisfaction. Foote (2006) noted that employee loyalty is the absence of

employee turnover. The author mentioned that employee loyalty is crucial to customer

satisfaction.

        Researchers have examined employee job satisfaction to understand how it relates

to job retention (Hwang & Kuo, 2006; Long, 2005; Lovett et al., 2006). Researchers have
                                                                                          49


also examined the variables that affect employee job satisfaction to understand areas that

leaders must address to influence employee retention (Herman, 2004; Foote, 2006).

Conversely, some studies included examining why employees leave (Berry, 2006;

Chandler, 2004; Woodruffe, 2006). The studies illustrated variables such as

compensation (Kahn, 2007), organizational work climate (McKay et al., 2007), work

relationships (What is your bank's employee retention strategy?, 2007), and work-life

balance (Lambert, Kass, Piotrowski, & Vodanovich, 2006) as factors that influence

employees‟ decisions to leave organizations.

       Researchers have noted the criticality of employee retention in the IT industry

(Chang & Lee, 2006; Kahn, 2007; Li, 2006). IT organizations must make employee

retention a primary responsibility (Al-Ajmi, 2006; Anuradha, 2005; Berry, 2006; Korney,

2007; Moore, 2006; Thozhur et al., 2006). Most retention strategies are ineffective

because organizations do not consider the dynamic factors that affect employees‟

decisions to resign.

       Employee retention is an important issue that leaders must address (Beauchesne,

2006; Foote, 2006). When leaders ignore retention issues, an organization may suffer

financially (McKay et al., 2007; Moore, 2006; Ryan, 2006; Vu, 2006). The quantitative

study involved examining both employee retention and employee job satisfaction. The

study included a job satisfaction survey to determine the factors that contribute to

employees‟ decisions to leave organizations. The questionnaire also included five open-

ended questions to aid in understanding why employees choose to leave organizations.

       Chapter 3 will include a description of the method for the study. Chapter 3 will

reflect a discussion of the research design, research population, and method to collect and
                                                                                           50


analyze the research data. The quantitative study involved determining (a) the role job

satisfaction plays in the decision of IT employees to leave an organization, and (b) the

components of job satisfaction.
                                                                                           51


                                  CHAPTER 3: METHOD

         The purpose of this quantitative descriptive study was to identify the factors that

motivate IT employees‟ decisions to leave organizations. Chapter 3 will include a

discussion of the research method, the research design, identify the instrument that was

used in the study, describe the research population and sampling, describe the data

collection procedures, and describe the data collecting techniques. Though several studies

exist on the topic of employee retention and employee job satisfaction, this study

included a focus on employee turnover in the IT industry. Researchers have examined

employee retention to determine what it entails, to understand the predictive variables of

employee retention, and to understand the role leaders must play to address employee

retention (Hwang & Kuo, 2006; Sweeney & McFarlin, 2005). Other studies involved

examination of employee retention in the investment management, law enforcement,

nursing, manufacturing, retail, and accounting industries (Curran, 2006; Dahm, 2006;

Evergreen focuses on employee retention, 2006; Klie, 2006; McKay et al., 2007; Yaying,

2007).

                                      Research Design

         The research took the form of a quantitative study, which included an employee

job satisfaction survey. The employee job satisfaction survey was conducted using the

Minnesota Satisfaction Questionnaire (MSQ) survey instrument, which included 20

Likert-type questions. The MSQ measures an employee‟s satisfaction with his or her job.

The MSQ was an appropriate survey instrument that aided in measuring the job

satisfaction of groups of individuals accurately using numerous workplace factors.
                                                                                              52


        The MSQ is a tool that respondents can use to provide feedback to survey

questions. The questionnaire contained 20 questions and incorporated a Likert-type scale

that ranged from very dissatisfied (1) to very satisfied (5). The questionnaire addressed

three categories: intrinsic satisfaction (Questions 1, 2, 3, 5, 8, 9, 10, 11, 13, 14, 15, 16, 19,

and 20) and extrinsic satisfaction (Questions 4, 6, 7, 12, 17, and 18).

        The MSQ measures job satisfaction across 20 dimensions (Wong, 2007, p. 10).

The survey aided in measuring job satisfaction by assessing the following:

    1. Ability utilization—chance to use one‟s abilities

    2. Achievement—feelings of accomplishment

    3. Activity—being able to stay busy on the job

    4. Advancement—opportunity to advance

    5. Authority—chance to direct others

    6. Company—satisfaction with company policies

    7. Compensation—pay for the work done

    8. Coworkers—relationships with coworkers

    9. Creativity—chance to try one‟s own work methods

    10. Independence—opportunity to work alone

    11. Moral values—not having to violate conscience at work

    12. Recognition—praise received from work done

    13. Responsibility—freedom to use own judgment

    14. Security—steady employment of the job

    15. Social service—chance to do things for others

    16. Social status—opportunity to be “somebody”
                                                                                           53


   17. Supervision (HR)—way the boss handles employees

   18. Supervision (technical)—competence of supervisor

   19. Variety—chance to do different things occasionally

   20. Working conditions—all facets of the work environment

                                Appropriateness of Design

         The study involved administering a job satisfaction survey to examine employee

job satisfaction of IT professionals in the DC metropolitan area. The study also gathered

data on the factors that influenced employees‟ decisions to leave their previous jobs. A

correlative descriptive design was used for the study. A correlative descriptive design is a

quantitative research approach that is used to examine the relationship between two or

more existing phenomena. Correlation designs examine surface relationships and do not

necessarily investigate if there are causal reasons for relationships (Creswell, 2002). The

study included examining the factors that affect job satisfaction to determine if a

relationship exists between job satisfaction and employee turnover. A quantitative

method was more appropriate than a qualitative approach because, as Creswell (2002)

noted, quantitative studies help researchers determine if one or more variables influence

another variable. Creswell emphasized that a quantitative method is appropriate for

explaining the relationship between variables. A survey design was chosen for this study

because surveys are used to measure variables (Creswell, 2005). The survey was

administered via the internet for convenience. The MSQ was used as opposed to

developing a survey instrument because it was easier to use an existing tool (Creswell,

2005).
                                                                                           54


                                    Research Questions

       The objective of this quantitative descriptive survey study was to examine the

factors that influence employees‟ decisions to leave an organization. The dependent

variable was employee turnover and the independent variable was job satisfaction. The

survey instrument was used to collect data on the organizational, individual, and

nonorganizational factors that influence job satisfaction. The first 20 questions of the

instrument collected data on job satisfaction. The last five questions were open-ended

questions, which were used to examine the reasons why employees left their previous

jobs. The research question was as follows: What role does job satisfaction play in the

decision of IT employees to leave organizations?

                                        Population

       The research population for the study was 200 IT professionals in the DC

metropolitan area. The population included IT workers such as software developers,

software testers, data modelers, system analysts, IT project managers, and database

developers. The population included various types of employees, such as full-time and

part-time employees, contract and permanent employees, and salaried and exempt

employees.

       The population included employees from different demographic groups. For

example, the population consisted of employees of various ages, races, and educational

backgrounds. The population included IT managers and nonmanagers. The resulting

sample size was 144 professionals from various organizations and disciplines in the IT

industry.
                                                                                          55


                                         Sampling

       The sample for the study was 144 IT workers from various functions in the IT

profession. Research participants were solicited randomly. Electronic mail messages

were sent to 200 IT workers, who were former coworkers and classmates residing and

working in the DC metropolitan area. According to Creswell (2002), “Many survey

studies in leading educational journals report a response rate of 50% or better. However,

this rate will fluctuate depending on proper notification, adequate follow-up procedures,

respondent interest in the study, the quality of the instrument, and use of incentives”

(p.367). The participants received a request to complete the survey instrument and they

were reminded that their participation would remain anonymous. According to Creswell

(2002), simple random sampling ensures that individuals have equal probability of being

selected from the population. The intent of simple random sampling was to choose

individuals who will be representative of the population. Creswell noted that any bias in

the population would be distributed equally among the people chosen.

                                     Informed Consent

       The survey instrument was published on the web and a sample of the survey is

provided in Appendix A. A link to an informed consent form was provided for survey

participants‟ approval before proceeding to the survey section. To participate in the

survey, participants were asked to read the informed consent form and answer yes to the

consent form. The form explained the steps that would be taken to ensure the

confidentiality of the research participants and the form explained what would be done

with the data that was collected. A sample of the informed consent form is provided in

Appendix C.
                                                                                             56


                                      Confidentiality

       The privacy and confidentiality of research participants must be protected in

research studies (Creswell, 2005). When respondents completed the survey and submitted

the responses, their identity was protected to ensure that the data-gathering process was

anonymous. The instrument did not include identifying questions; respondents did not

have to disclose their identity. Submitted surveys were downloaded and information

collected was stored in an Access database to which only the researcher had access. The

data collected will be stored for three years following the study. The data collected will

be destroyed after the three-year holding period. The collected data will be destroyed by

deleting the Access file; once the Access file is deleted, the data will no longer be

available or accessible.

                                   Geographic Location

       Information technology employees in the Washington DC metropolitan area were

the focus of this study. The study was limited to the DC metropolitan area. The specific

location included all regions in the District of Columbia and the states of Maryland and

Virginia.

                                      Instrumentation

       An existing validated survey instrument was used for this study because it was

easier to use an existing instrument (Creswell, 2005). The survey was a standardized

web-based survey, which had 20 questions that covered these two areas: intrinsic

satisfaction, and extrinsic satisfaction (Weiss, Dawiss, England, & Lofquist, 1967). The

survey consisted of Likert-type scale questions with possible responses that ranged from

1 to 5, with 1 being the lowest and 5 being the highest. The instrument also included five
                                                                                             57


open-ended questions and instructions to help respondents understand how to use the

instrument. The study included the following five open-ended questions:

   1. Why did you leave your previous job?

   2. How would you describe your experience at your previous job?

   3. What did you like least about your previous job?

   4. What did you like best about your previous job?

   5. How would you describe your relationships with your boss and your co-workers

       at your previous job?

                                      Data Collection

       The survey was administered via the internet; using an online survey encouraged

IT professionals to participate in the study. The online approach was selected over a

paper-based survey to give respondents the flexibility to participate in the survey at any

time and from any location. The employee survey instrument was published on the

internet, and random requests were sent to solicit people to participate in the survey.

Seven days after the random e-mails, respondents received follow-up e-mails to remind

them about the survey. When respondents completed the survey and submitted responses,

their identity was protected to ensure that the data-gathering process was anonymous.

The instrument did not include questions that solicited information that could disclose the

identity of respondents.

       The first contact with participants included a pre-notice e-mail informing them of

the study and the importance of their participation. Four days after the initial contact a

second contact was initiated. The second e-mail included a link to the informed consent

form; after survey participants completed the consent form and submitted the form, they
                                                                                           58


proceeded to the survey section. The first part of the survey instrument included an

explanation of how to answer the survey questions; the second part of the instrument

included the questionnaire. If people who were contacted declined participating in the

study, a message displayed thanking them for their consideration.

       The MSQ was the survey instrument for the study and was appropriate because

the survey questions measured job satisfaction (across 20 dimensions) assessing

organizational, individual, and nonindividual work factors. Respondents had access to

instructions on completing the web survey in each section of the survey. The survey

instrument was used to collect data about the organizational, nonorganizational, and

individual factors that affect the decisions of IT employees to leave organizations.

                                      Data Analysis

       SPSS Version 16 for Windows was used to analyze the survey data. The results of

the survey were compiled to obtain the individual scores for each variable of the study.

Descriptive statistics was used to analyze the data, including means, medians, standard

deviations, percentages, and frequencies. The Pearson correlation coefficient was used to

analyze the relationship between the dependent and independent variables (Creswell,

2002). Descriptive analysis was used to determine the points of central tendency and

frequency of distributions of the dependent variables (Creswell, 2002). A linear

regression analysis was used to see if there were relationships between each of the job

satisfaction factors and motivations to leave. The purpose of the analysis was to reveal if

any of the factors influence IT employees‟ decisions to leave. A multiple regression was

used to determine the effect of various job satisfaction factors on employee turnover

(Creswell, 2002).
                                                                                               59


                                    Reliability & Validity

       Weiss et al. (1967) developed the MSQ and the MSQ is a well-regarded

instrument that has been used in various studies to measure job satisfaction (Ozyurt,

Hayran, & Sur, 2006; Wong, 2007). The short form of the MSQ includes 20 questions

that cover several job factors. Survey respondents indicated their responses using a 5-

point, Likert-type scale ranging from 1 (very dissatisfied) to 5 (very satisfied).

       Creswell (2002) indicated that “the internal validity of a research study is the

extent to which the research design and the data that is yielded from the study allow the

researcher to draw accurate conclusions about the cause-and-effect and other

relationships from the study” (p. 150). The MSQ has been validated by various tests

(Dionne, 2000; Ozyurt, Hayran, and Sur, 2006; Wong, 2007). According to Kouzes and

Posner (2002), “The median reliability coefficient for the MSQ is measured by Hoyt

reliability coefficients as 0.85” (as cited in Wong, 2007, p.63). Ozyurt, Hayran, and Sur

(2006) noted that the MSQ was reliable, with a Cronbach's alpha (α) of 0.88.

According to Dionne (2000), the “Evidence for the validity of the MSQ is derived mainly

from its performing according to theoretical expectations” (p.16).

       Much of the evidence that supports the validity for the MSQ is indirectly based on

the construct validation studies of the Minnesota Importance Questionnaire (MIQ), which

is based on the theory of work adjustment (Dionne, 2000; Wong, 2007). Creswell (2002)

indicated that the external validity of a research study is the “extent to which its results

apply to situations beyond the study itself—in other words, the extent to which the

conclusions drawn can be generalized to other contexts” (p. 165). Wong (2007) used the

MSQ to examine job retention in the nursing industry.
                                                                                            60


                                         Summary

       Chapter 3 described the methodologies used in this study. Chapter 3 also

described various types of methodologies and provided the rationale for the research

method and design for this study. Descriptive statistics was used to analyze the data,

including means, medians, standard deviations, percentages, and frequencies. The

Pearson correlation coefficient was used to analyze the relationship between the

dependent and independent variables. Descriptive analysis was used to determine the

points of central tendency and frequency of distributions of the dependent variables. A

linear regression analysis was used to see if there were relationships between each of the

job satisfaction factors and motivations to leave. A multiple regression analysis was

performed to determine the effect of various job satisfaction factors on employee

turnover. SPSS Version 16 for Windows was used to analyze the survey data. The

purpose of the analysis was to reveal if job satisfaction influenced IT employees‟

decisions to leave. The results of the survey were compiled to obtain the individual

scores for each variable of the study.

       Chapter 4 will provide the findings of the research study. The main objective of

chapter 4 is to provide the results obtained from the data collection process. The

following sections will also be provided: (a) the data collection procedures, (b) the

gathering of the data, (c) the data analysis procedures, and (d) analysis of the data and

findings.
                                                                                           61


                                 CHAPTER 4: RESULTS

        The purpose of this quantitative descriptive study, involving an electronic survey,

was to identify the factors that influence IT employees‟ decisions to leave organizations.

Chapter 4 illustrates the findings of the survey that 200 IT employees, based in the DC

metropolitan area, completed via the internet. The study involved the use of a

questionnaire of 25 questions: The first 20 questions incorporated a Likert-type scale, and

the last five questions were open-ended. Of the 200 respondents who received an

invitation to participate, 144 completed the survey, which resulted in a 70% response

rate.

        The research question in this descriptive study read as follows: What role does job

satisfaction play in the decision of IT employees to leave organizations? Pearson Product

Moment correlation and multiple regression analysis aided in testing the null hypothesis,

H10. The null and alternative hypotheses appeared as follows:

        H10: Job satisfaction does not influence IT employees‟ decisions to leave

organizations.

        H1A: Job satisfaction does influence IT employees‟ decisions to leave

organizations.

                                      Data Collection

        Data collection occurred via the internet using an online survey to encourage IT

professionals to participate in the study. The online approach was more appropriate than a

paper-based survey because of the flexibility to participate in the survey at any time and

from any location. After publication of the employee survey instrument on the internet,
                                                                                            62


200 IT professionals in the DC metropolitan area, who were randomly selected, received

e-mails requesting their participation in the survey.

       Seven days after the random e-mails, respondents received follow-up e-mails to

remind them about the survey. The data-gathering process was anonymous allowing

respondents to complete the survey and submit their responses without revealing their

identities. The instrument did not include questions that solicited information about the

identity of respondents.

       The first contact with participants included a prenotice e-mail informing them of

the study and the importance of their participation. The second contact occurred 4 days

after the initial contact. The second e-mail included a link to the informed consent form.

       After survey participants completed and submitted the consent form, they could

access the survey. The first part of the survey instrument included an explanation of how

to answer the survey questions; the second part of the instrument included the

questionnaire. The IT professionals who declined to participate in the study accessed a

screen displaying a message thanking them for their consideration.

       The Minnesota Satisfaction Questionnaire (MSQ) was appropriate as the survey

instrument for the study because the survey questions measured job satisfaction (across

20 dimensions) assessing organizational, individual, and nonindividual work factors.

Respondents received instructions on how to complete each section of the survey. The

survey instrument aided in collecting data about the organizational, nonorganizational,

and individual factors that affect the decisions of IT employees to leave organizations.

Table 3 indicates the final sample.
                                                                                         63


Table 3

Description of the Final Sample (N = 144)

                                     Total                      Description

Surveys distributed                   200       Total surveys distributed via e-mail

Surveys collected                     150       Total surveys collected via e-mail

Incomplete surveys                     6        Total surveys submitted with missing
                                                sections
Valid participants                    144       Net sample



                                      Data Analysis

       The goal of the quantitative study was to determine whether a relationship exists

between job satisfaction and employee turnover intention for IT employees working in

the DC metropolitan area. The purpose of the analysis was to reveal if any of the job

satisfaction factors influence IT employees‟ decisions to leave. The significance level for

the study was set at α = .05. The data obtained from the sample (N = 144) was analyzed

for the study. SPSS Version 16 for Windows aided in analyzing the survey data. The

Pearson correlation coefficient was used to analyze the relationship between the

dependent and independent variables (Creswell, 2002). Descriptive analysis was used to

determine the points of central tendency and frequency of distributions of the dependent

variables (Creswell, 2002). A linear regression analysis was used to see if there were

relationships between each of the job satisfaction factors and motivations to leave. A

multiple regression was used to determine the effect of various job satisfaction factors on

employee turnover (Creswell, 2002).
                                                                                          64




                                   Descriptive Analysis

       Compilation of the results of the survey yielded individual scores for each

variable of the study. Descriptive statistics aided in analyzing the data and included

means, medians, standard deviations, percentages, and frequencies. Descriptive analysis

resulted in the points of central tendency and frequency of distributions of the dependent

variables. Table 4 displays the mean and standard deviation for each of the job

satisfaction factors. Table 5 indicates the mean and standard deviation for each of the

turnover factors.
                                                                                     65


Table 4

Descriptive Statistics of Job Satisfaction Factors


                        N     Range     Min     Max      ∑      M     SE     SD     Variance

Ability Utilization    144       4        1          5   575   3.99   .082   .979     .958
Achievement            144       4        1          5   568   3.94   .077   .922     .850
Activity               144       4        1          5   561   3.90   .080   .959     .919
Advancement            143       4        1          5   522   3.65   .084 1.002     1.004
Authority              144       4        1          5   513   3.56   .100 1.204     1.451
Company                143       4        1          5   526   3.68   .091 1.092     1.192
Compensation           144       4        1          5   575   3.99   .080   .964     .930
Coworkers              143       4        1          5   555   3.88   .094 1.129     1.275
Creativity             141       4        1          5   540   3.83   .074   .878     .771
Independence           144       4        1          5   490   3.40   .069   .831     .690
Moral Values           143       4        1          5   546   3.82   .092 1.098     1.206
Recognition            144       4        1          5   478   3.32   .092 1.107     1.226
Responsibility         144       4        1          5   504   3.50   .092 1.109     1.231
Security               143       4        1          5   467   3.27   .093 1.113     1.239
Social Service         144       4        1          5   545   3.78   .088 1.059     1.121
Social Status          144       4        1          5   539   3.74   .087 1.049     1.101
HR Supervision         143       4        1          5   543   3.80   .085 1.018     1.036
Technical              144       4        1          5   583   4.05   .069   .831     .690
Supervision
Variety                143       4        1          5   529   3.70   .090 1.075     1.155
Working                143       4        1          5   549   3.84   .085 1.018     1.037
Conditions
Valid N (listwise)     134
                                                                                            66


Table 5

Descriptive Statistics of Employee Turnover Factors (N =144)


                            Min          Max            M            SD

CPOV                         0             1           .12          .326
BSR                          0             1           .31          .462
EA                           0             1           .41          .493
EC                           0             1           .36          .479
PD                           0             1           .19          .393
IT                           0             1           .36          .481
WR                           0             1           .06          .230
Valid N (listwise)



        Descriptive statistics tests aided in examining the factors associated with

employee turnover to determine the factors that lead to employee turnover. Descriptive

and inferential statistics were run for the demographics to show the frequency and the

mean, minimum, and maximum for each variable (see Tables 6 - 12). The turnover

factors were as follows: Conflict between personal values and organizational values

(CPOV), boss-specific reason (BSR), employee aspiration (EA), employee compensation

(EC), personal development (PD), involuntary turnover (IT), and work relationship

(WR).

        Most respondents indicated that EA was one of the reasons for leaving (M = .41),

and some respondents reported that EC and IT were equally good reasons for leaving (M

= .36). A slightly lower mean score indicated that employees did not believe that a BSR

significantly contributed to their decision to leave (M = .31). Respondents reported that
                                                                                             67


PD and CPOV did not significantly contribute to their reasons for leaving (M = .19 and

.12 respectively). Respondents expressed that WR was the least likely reason to leave an

organization (M = .06). Table 6 indicates the frequencies of the CPOV turnover factor.

Table 6

Frequencies of CPOV Turnover Factor


                          f           %        Cumulative %

Valid
        DISF             69          12.0           12.0
        NDISF           504          88.0         100.0
        Total           573        100.0
Missing
        System          927
Total                  1500



         Table 6 presents the frequency of responses that participants attributed to CPOV.

The responses were grouped into two categories: dissatisfied (DISF) and not dissatisfied

(NDISF). If respondents indicated that a turnover factor contributed to their decision to

leave their organization the responses were grouped into the DISF category. Similarly, if

respondents indicated that a turnover factor did not contribute to their decision to leave

their organization the responses were grouped into the NDISF category.

Few employees (12.0%) indicated that CPOV contributed to their reason for leaving.

More respondents (88.0%) expressed that CPOV did not contribute to their decision to

leave. Table 7 that follows displays the frequencies of the BSR turnover factor.
                                                                                           68




Table 7

Frequencies of BSR Turnover Factor


                          f            %        Cumulative %

Valid
        DISF             176          30.7           30.7
        NDISF            397          69.3          100.0
        Total            573         100.0
Missing
        System           927
Total                  1500



         Table 7 illustrates the frequency of responses that participants attributed to BSR.

More respondents (69.3%) indicated that BSR did not contribute to their reason for

leaving. Few employees (30.7%) indicated that BSR contributed to their decision to leave

an organization. Table 8 that follows displays the frequencies of the EA turnover factor.
                                                                                        69


Table 8

Frequencies of EA Turnover Factor


                         f           %           Valid %     Cumulative %

Valid
        DISF            236         15.7           41.2              41.2
        NDISF           337         22.5           58.8          100.0
        Total           573         38.2          100.0
Missing
        System          927         61.8
Total                 1500         100.0



         Table 8 shows the frequency of responses that respondents attributed to EA. More

respondents (58.8%) indicated that EA did not contribute to their reason for leaving.

Fewer employees (41.2%) indicated that EA contributed to their decision to leave. Table

9 that follows displays the frequencies of the EC turnover factor.
                                                                                           70


Table 9

Frequencies of EC Turnover Factor


                          f            %          Valid %     Cumulative %

Valid
        DISF            204          13.6           35.6            35.6
        NDISF           369          24.6           64.4          100.0
        Total           573          38.2          100.0
Missing
        System          927          61.8
Total                  1500         100.0



         Table 9 presents the frequency of responses that participants attributed to EC.

More respondents (64.4%) indicated that EC did not contribute to their reason for

leaving. Few employees (35.6%) indicated that EC contributed to their decision to leave

an organization. Table 10 that follows displays the frequencies of the PD turnover factor.
                                                                                            71


Table 10

Frequencies of PD Turnover Factor


                          f           %           Valid %     Cumulative %

Valid
        DISF            109           7.3           19.0           19.0
        NDISF           464          30.9           81.0         100.0
        Total           573          38.2         100.0
Missing
        System          927          61.8
Total                  1500         100.0



         Table 10 indicates the frequency of responses that respondents attributed to PD.

More respondents (81.0%) indicated that PD did not contribute to their reason for

leaving. Few employees (19.0%) indicated that PD contributed to their decision to leave.

Table 11 that follows displays the frequencies of the IT turnover factor.
                                                                                               72


Table 11

Frequencies of IT Turnover Factor


                          f            %           Valid %      Cumulative %

Valid
        DISF             208          13.9           36.3            36.3
        NDISF            365          24.3           63.7           100.0
        Total            573          38.2          100.0
Missing
        System           927          61.8
Total                  1500          100.0



         Table 11 illustrates the frequency of responses that participants attributed to IT.

More respondents (63.7%) indicated that IT did not contribute to their reason for leaving.

Few employees (36.3%) indicated that IT contributed to their decision to leave an

organization. Table 12 that follows displays the frequencies of the WR turnover factor.
                                                                                          73


Table 12

Frequencies of WR Turnover Factor


                          f            %           Valid %     Cumulative %

Valid
        DISF              32           2.1            5.6             5.6
        NDISF           541           36.1           94.4          100.0
        Total           573           38.2         100.0
Missing
        System          927           61.8
Total                  1500          100.0



         Table 12 shows the frequency of responses that employees attributed to WR.

More respondents (94.4%) indicated that WR contributed to their reason for leaving. Few

employees (5.6%) indicated that WR did not contribute to their decision to leave.

                                     Hypothesis Testing

         The null hypothesis of the study indicated that no relationship exists between job

satisfaction factors and employee turnover. The alternative hypothesis of the study

reflected that a relationship exists between job satisfaction and employee turnover.

Measurement of job satisfaction occurred across 20 dimensions, which included intrinsic

and extrinsic factors. Measurement of turnover occurred across seven factors. The null

hypothesis was tested at p     .05. To test the hypothesis, a Pearson r correlation was

conducted to determine if a relationship exists between job satisfaction and an

employee‟s decision to leave an organization. Multiple regression analysis was also run

to determine the effect of various job satisfaction factors on employee turnover.
                                                                                              74


Pearson Correlation

        The Pearson correlation coefficient aided in analyzing the relationship between

the dependent and independent variables (Creswell, 2002; Neuman, 2003). Tables 22 and

23 display the Pearson correlation between the seven turnover factors and the job

satisfaction factors. The questionnaire addressed two categories: intrinsic satisfaction

(Questions 1, 2, 3, 5, 8, 9, 10, 11, 13, 14, 15, 16, 19, and 20) and extrinsic satisfaction

(Questions 4, 6, 7, 12, 17, and 18).

        The results revealed that there was significance between the turnover factors and

the intrinsic satisfaction factors. The confidence level was set at p    .05 for the

independent variables. The highest correlation (-.201) was between WR and Q20

(Working conditions). The second highest correlation (-.199) was between PD and Q2

(Achievement). The third highest correlation (.183) emerged between BSR and Q3

(Advancement). The fourth highest correlation (.173) was between BSR and Q8

(Creativity).

        The results revealed that there was significance between the turnover factors and

one of the extrinsic satisfaction factors. The only correlation between extrinsic job

satisfaction and employee turnover was between IT and Q13 (responsibility) (.170). The

results revealed that no significant relationships existed between the turnover factors and

the other extrinsic factors because all the significant values for all job satisfaction

variables were greater than .05.

Multiple Regression Results

        Multiple regression aided in analyzing the survey data to determine the effect of

various job satisfaction factors on employee turnover. The Pearson product-moment
                                                                                          75


correlation coefficient (Pearson r) allowed for the presentation of the linear relationship

of the correlation. Multiple regression is a statistical method used to examine the

collective relationship of two or more independent variables with one dependent variable

(Creswell, 2002). The variance or relative significance of the dependent variables

(designated by R²) explains the variation in the independent variable.

       Analysis of the turnover factors and job satisfaction occurred through multiple

regression. The regression of CPOV with the job satisfaction factors produced a large

standard error (SE) value R2 value (R2 = .099; SE = .330). Upon elimination of the

independent variable with a low correlation coefficient, the goodness of fit improved (R2

= .116; SE = .330). The rejection of the regression of CPOV, modified job satisfaction

factors, and the turnover variables followed because of a large SE value (R2 = .092; SE =

.326) (see Table 21).

       Rejection of the regression of BSR and job satisfaction occurred because of a

larger SE value (R2 = .073; SE = .485). The regression of BSR and a modified set of job

satisfaction factors was rejected because of a large SE value (R2 = .044; SE = .648). A

lower SE value led to the acceptance of the regression of BSR, modified job satisfaction

factors, and other turnover variables (R2 = .100; SE = .478) (see Table 13).

       Rejection of the regression of EA and job satisfaction occurred because of a larger

SE value (R2 = .176; SE = .489). The regression of EA and modified job satisfaction

factors was rejected because of a larger SE value (R2 = .042; SE = .486). A lower SE

value resulted in the rejection of the regression of EA, modified job satisfaction factors,

and other turnover factors (R2 = .047; SE = .484) (see Table 14).
                                                                                             76


       The regression of EC and job satisfaction was accepted because of a lower SE

value (R2 = .109; SE = .472). A lower SE value led to the acceptance of the regression of

EC, modified job satisfaction factors, and other turnover factors (R2 = .102; SE = .469).

Acceptance of the regression of EC and a modified set of job satisfaction and turnover

factors led to a lower SE value (R2 = .140; SE = .463) (see Table 19).

       Rejection of the regression of PD and job satisfaction occurred because of a large

SE value (R2 = .110; SE = .389). The regression of PD and job satisfaction was rejected

because of a larger SE value (R2 = .155; SE = .402). A lower SE value led to the

acceptance of the regression of PD, modified job satisfaction factors, and other turnover

factors (R2 = .109; SE = .388) (see Table 15).

       Rejection of the regression of IT and job satisfaction occurred because of a larger

SE value (R2 = .158; SE = .474). A larger SE value resulted in the rejection of the

regression of IT, modified job satisfaction factors, and other turnover factors (R2 = .112;

SE = .472). The regression of IT and modified job satisfaction factors was accepted

because of a lower SE value (R2 = .110; SE = .471) (see Table 16).

       Rejection of the regression of WR and job satisfaction occurred because of a

larger SE value (R2 = .142; SE = .239). The regression of WR and job satisfaction was

rejected because of a larger SE value (R2 = .133; SE = .232). A lower SE value led to the

acceptance of the regression of WR, the modified job satisfaction factors, and the

turnover factors (R2 = .159; SE = .223) (see Table 17).

       Entering both intrinsic and extrinsic job satisfaction as predictors of each of the

seven turnover intention factors resulted in regression models. Five of the seven models

did not reflect significant values, leading to rejection (see Tables 13, 14, 15, 16, and 21).
                                                                                     77


At the 95% confidence level, only the WR and EC turnover factors displayed significant

values (.029 and .028 respectively) (see Tables 17 and 19).
                                                                                                                 78




Table 13

Regression Model for BSR and Job Satisfaction


                                                                                     Change statistics

                                                        SE of          R2
    Model       R          R2       Adjusted R2       estimate      change     F change df 1           df 2   Sig. F change

1             .316a       .100          -.041           .478         .100         .709        18       115          .796
a
    Predictors: (Constant), Working Conditions, Achievement, Responsibility, Coworkers, Compensation, Authority,
Independence, Ability Utilization, Recognition, Advancement, Social Status, Activity, HR Supervision, Creativity,
Variety, Security, Moral Values, and Company.



Table 14

Regression Model for EA and Job Satisfaction (Including Other Turnover Factors)


                                                                                         Change statistics

                                                         SE of          R2
    Model       R          R2       Adjusted R2        estimate      change      F change      df 1      df 2 Sig. F change

1             .414a       .172          .042             .486          .172        1.325        18       115          .186

2             .460b       .212          .047             .484          .040        1.124           5     110          .352
a
    Predictors: (Constant), Working Conditions, Achievement, Responsibility, Coworkers, Compensation, Authority,
Independence, Ability Utilization, Recognition, Advancement, Social Status, Activity, HR Supervision, Creativity,
Variety, Security, Moral Values, and Company. bPredictors: (Constant), Working Conditions, Achievement,
Responsibility, Coworkers, Compensation, Authority, Independence, Ability Utilization, Recognition,
Advancement, Social Status, Activity, HR Supervision, Creativity, Variety, Security, Moral Values, Company,
CPOV, PD, IT, Technical Supervision, and Social Service.
                                                                                                                    79




Table 15

Regression Model for PD and Job Satisfaction (Including Other Turnover Factors)


                                                                                      Change statistics

                                                                         R2                                        Sig. F
    Model      R        R2       Adjusted R2        SE of estimate change F change df 1                 df 2       change

1            .331a     .109           .040                .388          .109       1.583       10       129         .118
a
    Predictors: (Constant), Advancement, Achievement, Responsibility, Technical Supervision, Social Status, HR

Supervision, Activity, Security, Working Conditions, and Social Service.


Table 16

Regression Model for IT and Job Satisfaction (Including Other Turnover Factors)


                                                                                      Change statistics

                                                                                                                     Sig. F
    Model      R        R2     Adjusted R2 SE of estimate R2 change F change df 1                       df 2         change

1            .331a     .110         .031             .471             .110         1.400       11        125             .181
a
    Predictors: (Constant), Activity, Authority, Responsibility, Technical Supervision, Coworkers, Compensation,

Creativity, HR Supervision, Social Service, Variety, and Moral Values.
                                                                                                                  80




Table 17

Regression Model for WR and Job Satisfaction (Including Other Turnover Factors)


                                                                                    Change statistics

                                                                     R2                                           Sig. F
                        2                   2
    Model     R        R       Adjusted R       SE of estimate change         F change        df 1      df 2      change

1           .399a     .159         .080              .223           .159        2.006          12       127        .029
a
    Predictors: (Constant), Working Conditions, IT, CPOV, BSR, EC, Compensation, Ability Utilization, Technical

Supervision, Social Status, HR Supervision, Variety, and Moral Values.
                                                                                        81




Table 18

WR Coefficients Table


                                                              Standardized
                                Unstandardized coefficients   coefficients

Model 1                              B             SE              β            t     Sig.

(Constant)                          .271          .112                        2.421   .017
CPOV                              -.082           .059          -.115        -1.380   .170
BSR                                 .101          .042           .201         2.403   .018
IT                                  .095          .041           .197         2.312   .022
EC                                -.059           .042          -.121        -1.402   .163
Ability Utilization                 .004          .027           .018         .164    .870
Moral Values                        .001          .031           .007         .047    .963
Compensation                      -.005           .026          -.019        -.180    .857
Social Status                       .010          .026           .047         .399    .690
HR Supervision                    -.015           .027          -.064        -.541    .589
Technical Supervision             -.033           .031          -.119        -1.080   .282
Variety                             .032          .029           .146         1.086   .280
Working Conditions                -.057           .041          -.249        -1.396   .165

Note. Dependent variable: WR.
                                                                                                                  82




Table 19

Regression Model for EC and Job Satisfaction (Including Other Turnover Factors)


                                                                                    Change statistics

                                                  SE of           R2
    Model      R      R2     Adjusted R2        estimate       change       F change      df 1      df 2        Sig. F change

1            .375a .140          .074              .463          .140         2.107        10       129             .028
a
    Predictors: (Constant), Variety, CPOV, IT, WR, Ability Utilization, Recognition, Activity, Company, Moral

Values, and Security.
                                                                                        83




Table 20

EC Coefficient Table


                                                              Standardized
                                Unstandardized coefficients   coefficients

Model 1                              B             SE              β            t     Sig.

(Constant)                          .580          .207                        2.797   .006
WR                                -.200           .175          -.097        -1.142   .256
CPOV                              -.138           .123          -.094        -1.125   .263
IT                                -.133           .086          -.133        -1.549   .124
Ability Utilization                 .039          .057           .077         .686    .494
Activity                          -.041           .060          -.079         -.688   .493
Company                           -.072           .054          -.163        -1.336   .184
Moral Values                      -.069           .056          -.158        -1.243   .216
Recognition                       -.003           .049          -.007         -.062   .951
Security                          -.044           .057          -.099         -.774   .440
Variety                             .147          .050           .328         2.968   .004

Note. Dependent variable: EC.
                                                                                                                      84




Table 21

Regression Model for CPOV and Job Satisfaction (Including Other Turnover Factors)


                                                                                        Change statistics

                                                                   R2
    Model      R       R2    Adjusted R2 SE of estimate change                F change        df 1      df 2         Sig. F change

1            .304a .092          .038              .326           .092          1.703          8        134                .103
a
    Predictors: (Constant), Technical Supervision, Recognition, Compensation, Activity, Authority, Social Service,

Ability Utilization, and HR Supervision.
                                                                                              85


                          Acceptance or Rejection of Hypotheses

       Pearson Product Moment correlation and multiple regressions aided in

determining the acceptance or rejection of the null hypothesis and answering the research

question. The null and alternate hypotheses appeared as follows:

       H10: Job satisfaction does not influence IT employees‟ decisions to leave

organizations.

       H1A: Job satisfaction does influence IT employees‟ decisions to leave

organizations.

       Rejection of the null hypothesis (H10) occurred due to significance (p      .05) in the

regression analysis. At the 95% confidence level, with significance set at p    .05, only the

WR and EC turnover factors displayed significant values, .029 and .028 respectively (see

Tables 17 and 19). The Pearson correlation analysis allowed for the examination of the

relations between employee job satisfaction and employee turnover.

       Five correlations were statistically significant. The results revealed that there was

significance between the turnover factors and the intrinsic satisfaction factors. The

confidence level was set at p   .05 for the independent variables. The highest correlation

(-.201) was between WR and Q20 (Working conditions). The second highest correlation

(-.199) was between PD and Q2 (Achievement). The third highest correlation (.183)

emerged between BSR and Q3 (Advancement). The fourth highest correlation (.173) was

between BSR and Q8 (Creativity).

       The results revealed that there was significance between the turnover factors and

the extrinsic satisfaction factors. The only correlation between extrinsic job satisfaction

and employee turnover was between IT and Q13 (responsibility) (.170). The results
                                                                                                86


revealed that no significant relationships existed between the turnover factors and the

other extrinsic factors because all the significant values for all job satisfaction variables

were greater than .05.

       Multiple regression allowed for the analysis of the survey data to determine the

effect of various job satisfaction factors on employee turnover. The Pearson product-

moment correlation coefficient (Pearson r) aided in presenting the linear relationship of

the correlation. Multiple regression is a statistical method used to examine the collective

relationship of two or more independent variables with one dependent variable (Creswell,

2002). The variance or relative significance of the dependent variables (designated by R²)

explained the variation in the independent variable.

       Entering both intrinsic and extrinsic job satisfaction as predictors of each of the

seven turnover intention factors resulted in the development of regression models. Five of

the seven models did not reflect significant values, leading to their rejection. Two models

were accepted; at the 95% confidence level, only the WR and EC turnover factors

displayed significant values (.029 and .028 respectively) (see Tables 17 and 19).

       An analysis of variance (ANOVA) aided in testing the fit of the regression model.

Statistical significance is evident when the observed values exceed the predetermined

alpha level (Creswell, 2002). ANOVA results reflected that 15.9% is a significant amount

of variance in employee turnover intentions based on WR, R2 = .159, F(12, 127) = 2.006,

and p = .029 (see Table 24). ANOVA results illustrated that 14.0% is a significant

amount of variance in employee turnover intentions based on EC, R2 = .140, F(10, 129) =

2.107, and p = .028 (see Table 25).
                                                                                             87


                                            Summary

       This quantitative descriptive survey study involved examining the factors that

influence employees‟ decisions to leave organizations. The dependent variable was

employee turnover, and the independent variable was job satisfaction. Data collection

involved an online survey.

       Survey participants received an e-mail inviting their participation and a link to the

website. Of the 200 people contacted, 144 IT professionals returned completed surveys

resulting in a response rate of 70%. The results of the research provided insight into the

reasons IT employees leave organizations. The analysis helped to examine the turnover

intentions of IT employees.

       Chapter 4 presented the results of this quantitative study. The quantitative analysis

involved examining the relationships between intrinsic and extrinsic job satisfaction

factors and seven turnover factors (CPOV, BSR, IT, EA, EC, PD, and WR). Chapter 4

included the analysis of the job satisfaction and turnover factors and the results of the

multiple regression and correlations. Rejection of the null hypothesis (H10) occurred due

to significance (p      .05) in the regression analysis. At the 95% confidence level, with

significance set at p     .05, only the WR and EC turnover factors displayed significant

values, .029 and .028 respectively (see Tables 17 and 19). Chapter 5 reflects the

conclusions and recommendations drawn from the findings in chapter 4.
                                                                                          88


              CHAPTER 5: CONCLUSION AND RECOMMENDATIONS

       The purpose of this quantitative descriptive study, involving an electronic survey,

was to identify the factors that influence IT employees‟ decisions to leave organizations.

According to Chandler (2004), research indicates that when employees leave, a decline

occurs in the quality of products and services that organizations deliver to customers.

Other problems that organizations have to address when employees leave include decline

in staff morale, employee burnout, decline in quality of products and services due to staff

shortage, and decline in customer satisfaction (“Building Employee Commitment,”

2007). According to Gemignani (1998), the average cost of employee turnover is $10,000

(as cited in McKay et al., 2007). Goshe et al. (2006) noted that hiring and training

replacement employees account for approximately 50% of an IT worker‟s annual salary.

The Employment Policy Foundation in Washington, DC, noted, “Employee turnover

costs average 25 percent of an employee‟s annual salary” (as cited in Muck, 2006, p. 44).

        Chapter 4 included a summary of the findings from the data collection and

analysis. The chapter involved an analysis of the research question and hypothesis. The

analysis of the data indicated that a relationship exists between job satisfaction and

turnover of IT workers, supporting rejection of the null hypothesis. Chapter 5 includes a

summary of the findings, an explanation of the limitations of the study, and a presentation

of the data supporting or disproving the hypothesis. The final sections of chapter 5 reflect

recommendations for future research and the conclusion of the study.

                           Research Questions and Hypotheses

       The objective of the quantitative descriptive survey study was to examine the

factors that influence employees‟ decisions to leave an organization. The dependent
                                                                                              89


variable was employee turnover, and the independent variable was job satisfaction. The

survey instrument aided in collecting data on the organizational, individual, and

nonorganizational factors that influence job satisfaction.

        The first 20 questions of the instrument related to job satisfaction. The last five

questions were open-ended questions to examine the reasons employees left their

previous jobs. The research question was as follows: What role does job satisfaction play

in the decision of IT employees to leave organizations?

        The study included a null hypothesis and an alternative hypothesis. A null

hypothesis is a prediction that no relationship exists between independent and dependent

variables. Null hypotheses also involve predictions that no difference exists between

groups of an independent variable on a dependent variable. The hypotheses for this study

included the following:

        H10: Job satisfaction does not influence IT employees‟ decisions to leave

organizations.

        H1A: Job satisfaction does influence IT employees‟ decisions to leave

organizations.

        The Pearson correlation analysis allowed for the examination of the relationship

between employee job satisfaction and employee turnover. Multiple regression allowed

for the analysis of the survey data to determine the effect of various job satisfaction

factors on employee turnover. The null hypothesis (H10) was rejected due to significance

(p   .05) in the regression analysis. At the 95% confidence level, with significance set at

p    .05, only the WR and EC turnover factors displayed significant values, .029 and .028

respectively (see Tables 17 and 19).
                                                                                           90


                                        Implications

       The results of the study indicate that job satisfaction has an influence on an IT

employee‟s decision to leave an organization. The study may help leaders to address

employee turnover. One of the insights upon completion of the study is that not all job

satisfaction factors have the same influence on an IT employee‟s decision to leave an

organization. Thus, leaders cannot generalize all job satisfaction factors.

       Leaders should not wait until employees leave to address employee turnover;

employees remaining does not mean that organizations do not have turnover issues

(Anuradha, 2005). The turnover models presented in this study may help organizations

understand how to predict employee turnover. The results may assist leaders in

addressing turnover proactively instead of waiting for employees to leave before

addressing the problem.

       The study results indicate that employee compensation influences IT employees‟

decisions to leave their organizations. The results are in line with Sweeney and

McFarlin‟s (2005) position that dissatisfaction with pay is a reliable predictor of

employee absenteeism and turnover. The finding also reinforces Thozhur et al. (2006)

and Shields‟s (2006) position that money is an important motivator for employees.

Thozhur et al. (2006) noted that employees would be dissatisfied with their jobs if they

did not receive adequate compensation. Shields (2006) suggested that job satisfaction

relates to personal income.

       The study results also indicate that workplace relationships influence IT

employees‟ decisions to leave their organizations. This finding is consistent with the

views of Chandler (2004), who emphasized that employees want to work with good
                                                                                           91


people. The finding is also in line with Lock‟s (2003) position that the following

workplace factors motivate IT workers: (a) effective leadership, (b) sound workplace

relationships, (c) challenging work, (d) respect, and (e) a balanced work life.

                                        Limitations

       Controlling for certain limitations of the study was not possible. The period for

completing the survey depended on each respondent because the respondents completed

the survey at their convenience. Though the target population was 200 IT employees, the

sample was 144 IT employees. The sample reflected more than 50% of the target

population, which is sufficient for a study involving examination of the relationship

among variables (Creswell, 2002). MaCorr‟s (2008) sampling size calculator aided in

determining the sample size. The confidence level for the study (95%) indicated a 95%

chance that survey responses are accurate. The sampling size calculator indicated that a

sample size of 144 from a population of 200 was sufficient.

       Another limitation of this study was the lack of demographic data. The scope of

the study was to solicit data from IT workers, regardless of their age, gender, or race.

Though demographic data may have provided some insight into the diverse experiences

of IT workers, the lack of demographic data did not reduce the effectiveness of the data

collected.

                                Significance to Leadership

       Employee retention is an important leadership concern because employees

leaving can compromise the success of organizational initiatives (Conroy, 2007; “The

Secrets,” 2006; Siebenmark, 2006). Employee retention is costly in the IT industry, and

literature indicates that retention strategies do not effectively address employee turnover
                                                                                             92


in the IT industry (DeMers, 2002; Foote, 2006; Lock, 2003). The study also involved

determining whether the findings from previous studies based on other industries are

relevant to the IT industry. The results of the study are consistent with previous studies

that involved examining job retention and job satisfaction in various industries, such as

education, psychology, and nursing (Chandler, 2004; Curran, 2006; Parrish, 2006;

Sweeney & McFarlin, 2005; Watlington et al., 2004).

       The study included examining key organizational, nonorganizational, and

individual factors to determine the factors that influence IT employees‟ decisions to leave

organizations. The findings from the study may provide specific guidance for leaders to

make strategies for retaining IT employees more effective. Two turnover models

developed in this study may be helpful in predicting turnover. The findings may be

relevant to human resource practitioners, IT managers, and benefits specialists.

                             Recommendations for Leadership

       Turnover is complicated, so leaders must avoid rushing to develop and implement

turnover strategies without taking the time to understand the factors that motivate

employees to leave. Several authors examined various factors that contribute to turnover

(Fugate et al., 2008; Hwang & Kuo, 2006; Samad, 2006; Thomas & Mowday, 1987;

Yaying, 2007). Other authors examined various factors that motivate employees to

remain with their organizations (Anuradha, 2005; Kahn, 2007; McKay et al., 2007;

Shields, 2006). The implication is that measuring employee satisfaction is not as simple

as it may seem (Chang & Lee, 2006; Emmerik & Sanders, 2005; Ferris, 2006; Kahn,

2007; Li, 2006). Research indicates that employee satisfaction may vary based on

demographical factors, such as race, gender, age, and religion (Madsen, 2006; McKay et
                                                                                             93


al., 2007; McLellan, 2006a; Watlington et al., 2004). As the workplace becomes more

diverse, employee satisfaction will become more challenging because of the unique

values that each employee brings to the workplace (Al-Ajmi, 2006; Chang & Lee, 2006).

One of the insights gleaned from this study is that leaders must not wait until employees

leave to address turnover.

                             Recommendations for Further Studies

       The study did not involve targeting any particular demographic group; the

population for the study included all IT employees regardless of age, gender, or race.

Future researchers could focus on specific demographic groups in the DC metropolitan

area. Concentrating on specific demographic groups may help determine whether certain

IT workers possess certain turnover tendencies. The research involved a quantitative

study because the scope of the study was to determine the factors that influence an IT

employee‟s decision to leave an organization. A recommendation for a future study is to

include follow-up interviews to examine the turnover intentions of employees further.

                                         Conclusion

       The study results indicate that job satisfaction does influence the turnover

decisions of IT workers. Analysis of specific job satisfaction factors with certain turnover

factors illustrated that certain job satisfaction factors influence turnover more than other

job satisfaction factors. Analysis of specific job satisfaction factors with certain turnover

factors also illustrated that not all job satisfaction factors influence employee turnover

decisions. Results indicate that the following intrinsic job satisfaction factors influence an

IT workers turnover decisions: (a) working conditions, (b) achievement, (c)

compensation, (d) advancement, and (e) creativity. Results also indicate that only one of
                                                                                            94


the extrinsic job satisfaction factors (responsibility) influences an IT workers turnover

decisions.

       Rejection of the null hypothesis (job satisfaction does not influence IT

employees‟ decisions to leave organizations) occurred. All statistical tests involved an

alpha level of .05. With an alpha level of p   .05, the relationship between job satisfaction

and employee turnover was statistically significant. Rejection of the null hypothesis

occurred because there was significance (p     .05) in the regression analysis. At the 95%

confidence level, with significance set at p   .05, only the work relationship and

employee compensation turnover factors displayed significant values (.029 and .028

respectively) (see Tables 18 and 20).

                                         Summary

       This quantitative descriptive survey study involved examining the factors that

influence employees‟ decisions to leave organizations. The dependent variable was

employee turnover, and the independent variable was job satisfaction. Data collection

involved an online survey, and 144 IT professionals returned completed surveys resulting

in a response rate of 70%. The results of the research provided insight into the reasons IT

employees leave organizations, and the analysis of the results provided insight into the

turnover intentions of IT employees.

       The results are consistent with the motivational theory that postulates that needs

provide the driving force motivating behavior and general orientation (Jasper Associates,

2007). The study results indicate that employee compensation influences IT employees‟

decisions to leave their organizations. The results are in line with Sweeney and
                                                                                          95


McFarlin‟s (2005) position that dissatisfaction with pay is a reliable predictor of

employee absenteeism and turnover.

       The study also reinforces Thozhur et al. (2006) and Shields‟s (2006) position that

money is an important motivator for employees. Thozhur et al. (2006) noted that

employees would be dissatisfied with their jobs if they did not receive adequate

compensation. Shields (2006) suggested that job satisfaction relates to personal income.

       The results of the study also indicate that workplace relationships influence an IT

employee‟s decision to leave. This finding is consistent with the views of Chandler

(2004), who emphasized that employees want to work with good people. The finding is

also in line with Lock‟s (2003) position that the following workplace factors motivate IT

workers: (a) effective leadership, (b) sound workplace relationships, (c) challenging

work, (d) respect, and (e) a balanced work life.

       The study involved examining intrinsic and extrinsic job satisfaction, and the

survey results indicated that dissatisfaction with workplace relationships is a significant

contributor to employee turnover decisions. Trust and mutual respect are necessary in

building meaningful workplace relationships; employees need to trust and respect their

leaders as well as their co-workers. Trust is an important ingredient for teamwork if team

members must collaborate and share ideas with each other (Buhler, 2007). As teams

form, members become interdependent on each other for success. Members must be

willing to see every success as the team‟s success, and everyone should be willing to

share the limelight. In the same way, when a problem arises on the team, team members

should see the problem as a team issue and be willing to work in unity to resolve the

issue. An effective retention strategy for leaders is to cultivate a work environment that
                                                                                       96


upholds values such as trust, and mutual respect. Trust emerges in an environment of

respect; where respect exists, people can value others for whom they are and are willing

to get to know each other (Lewin & Regine, 2000).
                                                                                        97


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                            109


APPENDIX A: QUESTIONNAIRE
110
                                                                                              111


                          APPENDIX B: E-MAIL NOTIFICATION

March 30, 2008

Dear Respondents,

          I am a student at University of Phoenix working on a Doctorate of Management. I

am conducting a research study entitled Employee Turnover in IT Industry. The purpose

of this quantitative descriptive study, using an electronic version of the Minnesota

Satisfaction Questionnaire (MSQ) is to examine the factors that make IT employees leave

an organization.

          Your participation in this study will involve participation in an on-line survey,

which will take an average of 20 minutes. Your participation in this study is voluntary. If

you choose to participate in this study, you will access the on-line questionnaire; if you

decide not to participate in this study, you can also opt out of participating in the study. If

you decide to participate in the study your participation will be anonymous; you will not

have to disclose your name.

          Your individual response will be kept strictly confidential. To participate in the

survey, please read the informed consent form, sign it, and date it. Follow the instructions

on the site to respond to the survey questions. Your participation will take approximately

20 minutes. Once you complete the survey, click on the submit button to submit your

survey.

          Thank you for participating in this survey. Please contact me at 301-793-4166 if

you have any questions concerning the research study.

Sincerely,

Francesca Abii
                                                                                           112


                APPENDIX C: INFORMED CONSENT FORM

Dear Survey Participant,

      I am a student at University of Phoenix working on a Doctorate of Management. I

am conducting a research study entitled Employee Turnover in the IT Industry. The

purpose of this quantitative descriptive study, using an electronic version of the

Minnesota Satisfaction Questionnaire (MSQ) is to examine the factors that make IT

employees leave an organization.

       Your participation in this study will involve participation in an on-line survey,

which will take an average of 20 minutes. Your participation in this study is voluntary. If

you choose to participate in the study, you will access the on-line questionnaire; if you

decide not to participate in this study you can also opt out of participating in the study. If

you decide to participate in the study your participation will be anonymous; you will not

have to disclose your name. The results of this survey may be published but your name

will not be included in this study.

       By signing this form you acknowledge that you understand the nature of the

study, the potential risks to you as a participant, and the means by which your identity

will be kept confidential. Your signature on this form also indicates that you are 18 years

or older and that you give your permission to voluntarily serve as a participant in the

study described.

       Although you will not be compensated for your participation in this study, your

involvement will be instrumental in improving employee retention strategies and helping

organizations stabilize their workforce.
                                                                                    113


       If you have questions or concerns about this research study you may contact me at

301-793-4166.

Agreement of participation: please sign below.


      Signature:




Please sign and submit the form.

Sincerely,



Francesca Abii
                          114


APPENDIX D: PERMISSIONS
115
116
117
118
                             119




APPENDIX E: RESULTS TABLES
                                                                                                                               120


Table 22

Correlation between Turnover Factors and Intrinsic Job Satisfaction Factors

                            Achieve Activi Autho Cowor Creati Indepen Moral Respons Secur Social Social Variety Working
                     Ability ment    ty     rity kers vity dence values ibility ity service status              conditions
CPOV   Pearson        .067     -.023 .085
                             -.032 -.032      -.125   .059   .047 -.032       .102    -.019   .023    .057     .053    .043     .019
       Correlation
       Sig. (2-       .423    .786    .310    .137    .485   .579    .706     .227    .821    .784    .496     .530    .613     .826
       tailed)
       N              144     144     144     144     144    144     144      144     144      144    144      144     144       144
BSR    Pearson        .144    .057    .183*   .091 .165*     .114    .041     .111    .082    .127    .021     .062    .102     .044
       Correlation
       Sig. (2-      .085     .501    .028    .278    .049   .180    .621     .188    .330    .130    .802     .460    .224     .603
       tailed)
       N              144     144     144     144     144    144     144      144     144      144    144      144     144       144
EA     Pearson        .049    -.026   -.101 -.014     .101   -.049   .021     .059    -.019   -.009   -.071    -.119   -.123    -.091
       Correlation
       Sig. (2-       .557    .753    .227    .868    .227   .567    .802     .483    .820    .918    .398    .154     .144     .279
       tailed)
       N              144      144     144     144    144     144    144       144    144      144    144      144     144       144
EC     Pearson     -.084      -.034   -.117   .004    .001   -.056   -.062    -.143   .033    -.113   .000     -.026   -.123    -.091
       Correlation
       Sig. (2-       .317    .684    .163    .964    .992   .510    .459     .088    .696    .181    .997     .754    .191     .517
       tailed)
                                                                                                                                             121


     N                  144        144        144       144      144    144    144       144      144     144     144       144     144        144
PD   Pearson     -.014           .199*       -.057     .004      -.042 -.086   -.027     -.047 -.063      .041    -.133    -.181*   -.026     -.082
     Correlation
     Sig. (2-          .863       .017       .500      .965      .620   .310   .747      .579    .450     .630    .113     .030     .758      .330
     tailed)
     N                 144         144       144       144       144    144    144       144     144      144     144       144     144        144
IT   Pearson     -.009            .045       .097     -.123      .093   .040   .018      .046    .170*    .019    -.052    .019     -.073     .020
     Correlation
     Sig. (2-          .910       .588       .247      .140      .270   .639   .826      .586    .042     .823    .535     .823     .388      .817
     tailed)
     N                 144         144       144       144       144    144    144       144     144      144     144       144     144        144
WR   Pearson     -.092            -.018      -.037 -.139 -.028 -.057           .028      -.126   .000     -.058   -.094    -.085    -.131    -.201*
     Correlation
     Sig. (2-          .275       .827       .660      .097      .737   .499   .735     .133     1.000    .489    .262     .309     .120      .016
     tailed)
     N                    144         144      144       144      144    144      144      144      144    144       144      144      144           144
     * Correlation is significant at the 0.05 level (2-tailed)
                                                                                                                          122


Table 23

Correlation between Turnover Factors and Extrinsic Job Satisfaction Factors

                                                                                      Supervision Supervision

                              Advancement Company Compensation Recognition            (HR)           (technical)



CPOV       Pearson
                                     .027     -.043            .112           -.071          .076                  .048
           Correlation
           Sig. (2-tailed)           .746      .612            .181           .395           .368                  .571
           N                          143       143             144            144            144                  144
BSR        Pearson
                                     .051      .052            .146           .136           .118                  .070
           Correlation
           Sig. (2-tailed)           .542      .538            .081           .104           .159                  .402
           N                          144       144             144            144            144                  144
EA         Pearson
                                     -.010     .052            .050           -.049          -.003             -.049
           Correlation
           Sig. (2-tailed)           .903      .538            .538           .558           .968                  .560
           N                          144       144             144            144            144                  144
EC         Pearson
                                     -.046    -.129            -.025          -.096          -.053                 .027
           Correlation
            Sig. (2-tailed)          .583      .125            .767           .253           .532                  .751
            N                         144       144             144            144            144                  144
                                                                                                123


PD     Pearson
                                            .049           .016   .004   .001   -.127   -.114
       Correlation
       Sig. (2-tailed)                      .863           .847   .966   .992   .992     .175
       N                                     144            144   144    144     144     144
IT     Pearson
                                           -.041          -.115   .081   .093   -.024    .079
       Correlation
       Sig. (2-tailed)                      .627           .170   .337   .270   .777     .777
       N                                     144            144   144    144     144     144
WR     Pearson
                                           -.006          -.096   .061   .019   -.024   1.97*
       Correlation
       Sig. (2-tailed)
                                            .777           .255   .255   .611   .054
                                                                                         .018
       N                                     144            144   144    144     144     144
     **Correlation is significant at the 0.01 level (2-tailed).

     * Correlation is significant at the 0.05 level (2-tailed).
                                                                                                                  124


Table 24

ANOVA table for WR

                                                         b
                                                ANOVA

Model                       Sum of Squares          df         Mean Square           F           Sig.
                                                                                                              a
1        Regression                     1.202             12              .100           2.006         .029

         Residual                       6.341            127              .050

         Total                          7.543            139

a. Predictors: (Constant), Working conditions, IT, CPOV, BSR, EC, Compensation, Ability utilization,
Technical Supervision, Social status, HR Supervision, Variety, Moral values

b. Dependent Variable: WR
                                                                                                             125


Table 25

ANOVA table for EC


                                                       b
                                              ANOVA

Model                      Sum of Squares         df         Mean Square          F           Sig.
                                                                                                         a
1        Regression                   4.512             10             .451        2.107         .028

         Residual                    27.630            129             .214

         Total                       32.143            139

a. Predictors: (Constant), Variety, CPOV, IT, WR, Ability utilization, Recognition, Activity, Company,
Moral values, Security

b. Dependent Variable: EC

								
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