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Employee Turnover Intention in the U.S. Fast Food
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Imelda A. Bebe
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Walden University
College of Management and Technology
This is to certify that the doctoral study by
Imelda Bebe
has been found to be complete and satisfactory in all respects,
and that any and all revisions required by
the review committee have been made.
Review Committee
Dr. Charles Needham, Committee Chairperson, Doctor of Business Administration
Faculty
Dr. Kenneth Gossett, Committee Member, Doctor of Business Administration Faculty
Dr. Matthew Gonzalez, University Reviewer, Doctor of Business Administration Faculty
Chief Academic Officer
Eric Riedel, Ph.D.
Walden University
2016
Abstract
Employee Turnover Intention in the U.S. Fast Food Industry
by
Imelda A. Bebe
MS, Kaplan University, 2011
BSBA, Philippine School of Business Administration, 1995
Doctoral Study Submitted in Partial Fulfillment
of the Requirements for the Degree of
Doctor of Business Administration
Walden University
January 2016
Abstract
Employee turnover in the U.S. fast food industry has been high, averaging rate 150% per
annum. The purpose of the correlational design study was to examine the relationships
between job satisfaction factors, job dissatisfaction factors, and employee turnover
intentions among fast food employees to determine whether a statistically significant
relationship exists between these variables. The population for the study consisted of 144
fast food restaurant employees working in the East Coast in the United States. The
theoretical framework was Herzberg’s 2-factor motivation-hygiene needs theory, which
describes job satisfaction factors and job dissatisfaction factors. Internet survey data of
144 participants were analyzed using Pearson-product correlation coefficients and
multiple linear regressions analysis. The study findings revealed statistically significant
relationships between job satisfaction factors and employee turnover intentions (p < .01),
and job dissatisfaction factors and employee turnover intentions (p < .01). Among the job
satisfaction factors, responsibility had a stronger relationship with employee turnover
intentions (-.52) compared with other factors. Under job dissatisfaction factors, company
policy had a stronger relationship with employee turnover intentions (-.52) compared
with other factors. In addition, criterion variance of employee turnover intentions
associated with combined job satisfaction factors was stronger (35%) than were the
combined job dissatisfaction factors (31%). The study findings are designed to inform
fast food restaurant managers in taking actions to reduce employee turnover, resulting in
improved business financial sustainability and long-term growth.
Employee Turnover Intention in the U.S. Fast Food Industry
by
Imelda A. Bebe
MS, Kaplan University, 2011
BSBA, Philippine School of Business Administration, 1995
Doctoral Study Submitted in Partial Fulfillment
of the Requirements for the Degree of
Doctor of Business Administration
Walden University
January 2016
Dedication
Praise to the Lord for this great opportunity entrusted me. I thank God for his
guidance and help throughout this journey. Once again, God showed me that nothing is
impossible in the world that I can do all things through Christ who strengthens me. This
achievement is greatly dedicated to my beloved father and mother who instilled in me the
importance of education. I always remembered what my father said, “Education is the
greatest treasure that you can have in this world that no one can take away from you;” he
was definitely right!!!
I dedicate this achievement also my husband, Fred Jr., our kids (Christina,
Danika, Fred III, and Nenita), brothers, sisters, relatives, and friends who gave me the
reasons to aim high and kept me going despite of many challenges. Completing this
journey was challenging yet rewarding in the end. This achievement is so remarkable that
I cannot compare. I hope this great achievement will inspire Christina, Danika, Fred III,
and Nenita to obtain their doctoral degrees in the future!
Acknowledgments
Thank God for this wonderful achievement I have accomplished in life and for all
the blessings given to me and to my family. I extend my immense gratitude to my faculty
members, Dr. Charles Needham and Dr. Kenneth Gossett for their endless support, help,
guidance, and understanding throughout this journey. I cannot thank you enough for
helping me in many ways. Without your guidance and assistance, I would have not able
to accomplish this task. To my URR, Dr. Matthew Gonzalez, thank you for your great
support. Dr. Reginald Taylor, thank you for sharing your knowledge that helped me
understand the whole research study process. Thanks to Dr. Jet Mboga and Dr. Trenessa
Williams for your moral and spiritual support; you both inspired me to keep going, be
strong, and persevere throughout this journey.
To all my Kaplan and Walden University former professors, Dr. Carmen Castro,
Dr. Wanda Curlee, Dr. Sherry Giddings, Dr. John Yelvington, Dr. Ray Kalinski, Dr.
Steve Roussas, and Dr. George Spark, thank you for all your advices and prayers. Your
successful achievements in life have also inspired me to finish this challenging journey.
Thanks to all the participants who willingly helped me complete the collection of data. I
thank Walden University staff for their endless support and abundant resources to support
this challenging journey. Thank you, also, to the IRB members for your great feedback to
meet the IRB requirements.
i
Table of Contents
List of Tables .......................................................................................................................v
List of Figures ................................................................................................................... vii
Section 1: Foundation of the Study ......................................................................................1
Background of the Problem ...........................................................................................1
Problem Statement .........................................................................................................3
Purpose Statement ..........................................................................................................3
Nature of the Study ........................................................................................................4
Research Questions ........................................................................................................5
Hypotheses .....................................................................................................................6
Theoretical Framework ..................................................................................................8
Operational Definitions ..................................................................................................9
Assumptions, Limitations, and Delimitations ..............................................................10
Assumptions .......................................................................................................... 10
Limitations ............................................................................................................ 11
Delimitations ......................................................................................................... 11
Significance of the Study .............................................................................................12
Contribution to Business Practice ......................................................................... 12
Implications for Social Change ............................................................................. 13
A Review of the Professional and Academic Literature ..............................................14
Herzberg’ Motivation-Hygiene Needs (Two-Factor Theory) ............................... 16
Rival Theories of the Theoretical Framework ...................................................... 23
ii
Measurements ....................................................................................................... 29
Job Satisfaction ..................................................................................................... 33
Job Satisfaction Factors ........................................................................................ 37
Job Dissatisfaction Factors ................................................................................... 51
Employee Turnover Intention ............................................................................... 69
Employee Turnover .............................................................................................. 73
Employee Commitment ........................................................................................ 78
Employee Engagement ......................................................................................... 81
Employee Retention .............................................................................................. 82
Transition .....................................................................................................................83
Purpose Statement ........................................................................................................86
Role of the Researcher .................................................................................................86
Participants ...................................................................................................................89
Research Method and Design ......................................................................................91
Research Method .................................................................................................. 91
Research Design.................................................................................................... 93
Population and Sampling .............................................................................................94
Ethical Research...........................................................................................................96
Data Collection Instruments ........................................................................................98
Job Satisfaction Survey (JSS) ............................................................................... 98
Turnover Intention Survey .................................................................................... 99
Demographic Survey .......................................................................................... 102
iii
Data Collection Technique ........................................................................................104
Data Analysis .............................................................................................................106
Study Validity ............................................................................................................109
Transition and Summary ............................................................................................112
Section 3: Application to Professional Practice and Implications for Change ................114
Introduction ................................................................................................................114
Presentation of the Findings.......................................................................................115
Job Classification .......................................................................................................128
Pearson Product-Moment Correlation Coefficient ............................................. 132
Research Question 1 ........................................................................................... 133
Research Question 2 ........................................................................................... 135
Research Question 3 ........................................................................................... 137
Research Question 4 ........................................................................................... 138
Research Question 5 ........................................................................................... 139
Research Question 6 ........................................................................................... 140
Research Question 7 ........................................................................................... 142
Research Question 9 ........................................................................................... 144
Research Questions 10 ........................................................................................ 145
Multiple Regression ............................................................................................ 146
Applications to Professional Practice ........................................................................151
Implications for Social Change ..................................................................................152
Recommendations for Action ....................................................................................152
iv
Recommendations for Further Research ....................................................................160
Reflections .................................................................................................................161
Summary and Study Conclusions ..............................................................................162
References ........................................................................................................................166
Appendix A: Job Satisfaction Survey ..............................................................................208
Appendix B: Turnover Intention to Leave the Job Scale .................................................213
Appendix E: Permission to use the Turnover Intention Survey ......................................217
Appendix F: Copyright Clearance to Reuse Herzberg’s Motivation-Hygiene
Theory ..................................................................................................................219
Appendix G: Certification of Completion .......................................................................223
Appendix H: Consent Form .............................................................................................224
Appendix I: Confidentiality Agreement ..........................................................................226
Appendix J: Letter of Cooperation from a Research Partner ...........................................227
Appendix K: Participant Invitation to Participate ............................................................229
Appendix L: Participants’ Reminder ...............................................................................230
v
List of Tables
Table 1. Frequency and Percentage of the Study Sources…………………………….. 16
Table 2. JSS Instrument Reliability Statistics–Cronbach’s Alpha................................. 116
Table 3. ILJ Instrument Reliability Statistics–Cronbach’s Alpha.................................. 117
Table 4. Frequency Distribution of Fast Food Participants’ Gender............................. 118
Table 5. Frequency Distribution of Fast Food Participants’ Age .................................. 120
Table 6. Frequency Distribution of Fast Food Participants’ Educational Attainment....122
Table 7. Frequency Distribution of Fast Food Participants’ Job Position...................... 125
Table 8. Frequency Distribution of Fast Food Participants’ Job Classification..............127
Table 9. Frequency Distribution of Fast Food Participants’ Years of Service............... 129
Table 10. Descriptive Statistics for Age and Years of Working Variables.................... 131
Table 11. Pearson Product-Moment Correlation Coefficient Between Job Satisfaction
Factors and Employee Turnover Intentions........................................................133
Table 12. Pearson Product-Moment Correlation Coefficient Between Job Dissatisfaction
Factors and Employee Turnover Intentions....................................................... 140
Table 13. Multiple Regressions With Linear Combination of Job Satisfaction Factors and
Employee Turnover Intentions........................................................................... 147
Table 14. Multiple Regressions With Individual Factor of Job Satisfaction Factor and
Employee Turnover Intentions ...........................................................................148
Table 15. Multiple Regressions With Linear Combination of Job Dissatisfaction Factors
and Employee Turnover Intentions......................................................................149
vi
Table 16. Multiple Regressions With Individual Factor of Job Dissatisfaction and
Employee Turnover Intentions............................................................... ............150
vii
List of Figures
Figure 1. Depiction of Herzberg’ motivation-hygiene needs (two-factor theory) as a
theoretical framework............................................................................................33
Figure 2. Depiction of Herzberg’ motivation-hygiene needs (two-factor theory) as a
theoretical framework ............................................................................................50
Figure 3. Fast Food Participants’ Gender Distribution ....................................................119
Figure 4. Fast Food Participants’ Age Distribution. ........................................................121
Figure 5. Fast Food Participants’ Educational Attainment Distribution. .........................124
Figure 6. Fast Food Participants’ Job Position Distribution ............................................126
Figure 7. Fast Food Participants’ Job Classification Distribution ...................................128
Figure 8. Fast Food Participants’ Years of Service Distribution.................................... 130
1
Section 1: Foundation of the Study
Fast food restaurants make up a major segment of the U.S restaurant industry
(Batt, Lee, & Lakhani, 2014). The U.S. fast food industry comprised 25% of the total
restaurant sales (DiPietro, Gregory, & Jackson, 2013). The four segments of the fast food
industry are (a) quick-service restaurants (QSR), (b) takeaways, (c) mobile and street
vendors, and (d) leisure locations (Kamal & Wilcox, 2014). Quick-service restaurants are
a top segment in the fast food industry in terms of sales performance (Kamal & Wilcox,
2014).
U.S. fast food industry is a vital business sector in the economies because of its
more than 53% market value, contributing to economic growth (Kamal & Wilcox, 2014).
In 2011, the fast food market value in U.S. was approximately $66.2 billion, having
grown by 20% since 2006 (Kamal & Wilcox, 2014). The fast food restaurants throughout
the United States numbered more than 200,000 (Sena, 2014). The growth sales in the fast
food industry increased dramatically, from $6 billion in 1970 to $16 billion in 1975
(Sena, 2014). In 2013, growth sales reached $160 billion, equivalent to about 8.6%
annual rate (Sena, 2014). With effective strategic approaches, the fast food industry
expanded internationally successfully (Sena, 2014).
Background of the Problem
The fast food industry has contributed nationally to U.S. economic growth;
however, increasing employee turnover rates have become the main concern of many fast
food managers (Batt et al., 2014; Dike, 2012). The turnover in the fast food industry is
high compared to other industries (Dike, 2012; Perez & Mirabella, 2013; Sterrett, 2011;
2
Wyld, 2014). Employees’ voluntary withdrawal from a workplace occurs because of (a)
low wages and benefits, (b) lack of training, (c) autonomy, (d) job opportunities, (e) lack
of support from management, (f) and from unfavorable working conditions (Batt et al.,
2014; Royle, 2005; Ryan, Ghazali, & Mohsin, 2011).
Employee turnover is both disruptive and costly to employers, involving
increased direct and indirect costs (Batt et al., 2014; French, 2014; Kacmar et al., 2006;
Ryan et al., 2011). The increasing number of voluntary withdrawals has caused many fast
food managers to experience the hardship of replacing the quitters (Dipietro & Strate,
2008). The fast food industry is popular for having low skilled-labor that discourages
highly skilled workers from applying for vacant positions (Batt et al., 2014; Kwon,
2014). Fast food restaurants primarily hire students with less experience or no experience
that implies highly skilled workers are over qualified.
Employee turnover has an effect on employee efficiency that influences business
financial performance in a negative fashion (Kacmar, Andrews, Van Rooy, Steilberg, &
Cerrone, 2006). The lack of organizational support, work socialization, and employee
involvement creates isolation among employees, which results in lower productivity and
effectiveness (DiPietro & Pizam, 2008; Mathe & Slevitch, 2013). Employee turnover is
caused by lack of employee training, which affects employee competence (Perez &
Mirabella, 2013). Employee incompetence affects the quality service of the fast food
restaurants and thus diminishes the frequency of positive customer experiences
(Harrington, Ottenbacher, Staggs, & Powell, 2012).
3
Problem Statement
The employee turnover rate in the U.S. fast food industry is high at approximately
150% per annum (Dike, 2012; Perez & Mirabella, 2013). Turnover is as high as 300%
per annum for the lowest-level hourly paid employees in some fast food stores (Royle,
2010; Ryan et al., 2011). The general business problem is business operations become
costly and disruptive for many organizational managers because of high turnover
(Dipietro & Strate, 2008; Kacmar et al., 2006). The specific business problem is that
some managers in the fast food industry did not understand the relationship between
employee job satisfaction, employee job dissatisfaction, and employee turnover
intentions.
Purpose Statement
The purpose of this quantitative correlational study was to examine the
relationship between employee job satisfaction, employee job dissatisfaction, and
employee turnover intentions in the U.S. fast food industry. It specifically analyzed
associations between five job satisfaction independent variables: (a) achievement or
quality performance, (b) recognition, (c) responsibility, (d) work-itself, and (e)
advancement and growth (Herzberg et al., 1959). It also tracked five job dissatisfaction
independent variables: (a) company policy, (b) supervision, (c) interpersonal
relationships, (d) working conditions, and (e) salary (Herzberg et al., 1959). The
dependent variable was employee turnover intentions in the U.S. fast food industry.
The targeted population included lower level managers and fast food workers
throughout the East Coast of the United States. This population suited the needs for the
4
study because fast food workers in lower-level management and nonmanagerial positions
in the fast food industry experience high turnover (Perez & Mirabella, 2013; Ryan et al.,
2011). This study promotes positive social change by identifying information to help
managers in the fast food industry reduce employee turnover intentions and target factors
important to employees for which managers have control.
Nature of the Study
A quantitative method suited the needs for this study because of the statistical
nature of the data and the quantitative method’s suitability for evaluating hypotheses with
inferential statistics (Singleton & Straits, 2010). The qualitative method did not meet the
needs of this study because the nature of a qualitative approach is to explore and
understand why and how the targeted participant experienced the phenomenon, which
was not the purpose of the study (Bernard, 2013). Mixed methods did not suit the needs
for this study, because the purpose of the study was to examine the relationships between
predictors (independent) and criterion (dependent) variables. Mixed methods require the
combination of exploration of experience to gain an in-depth understanding regarding the
phenomenon with examination of variables to determine the relationship between the
variables (Cronholm & Hjalmarsson, 2011; Venkatesh, Brown, & Bala, 2013), which was
not the case for this study.
I used a correlational design because only correlations would determine the
existence and the strengths of the relationships with a multiple linear regression analysis
(Green & Salkind, 2011). A qualitative phenomenological design did not suit the needs
for the quantitative study, because the nature of the research did not involve analyzing
5
lived experiences to describe and understand the meaning of the phenomenon (Bernard,
2013). In a phenomenological design, a researcher must explore to understand the
importance of the phenomenon to create a new theory; whereas, in a correlational design,
a researcher must examine the relationship of the variables how all predictor variables, as
a whole, predict the dependent variable (Bernard, 2013; Green & Salkind, 2011). A
sequential mixed-methods design did not apply for the study because it used complex
requirements that include observations, interviews, and statistical procedures to support
the argument, as suggested by Naidu and Patel (2013).
Research Questions
The objective of the quantitative correlation study was to examine the relationship
between (a) factors of employee job satisfaction, (b) factors of employee job
dissatisfaction, and (c) employee turnover intentions in the fast food industry.
Research Question 1: Is there a statistically significant relationship between
employee achievement and turnover intentions?
Research Question 2: Is there a statistically significant relationship between
employee recognition and turnover intentions?
Research Question 3: Is there a statistically significant relationship between
employee work and turnover intentions?
Research Question 4: Is there a statistically significant relationship between
employee responsibility and turnover intentions?
Research Question 5: Is there a statistically significant relationship between
employee advancement and growth and turnover intentions?
6
Research Question 6: Is there a statistically significant relationship between
employee job dissatisfaction involving company policies and turnover intentions?
Research Question 7: Is there a statistically significant relationship between
employee job dissatisfaction involving supervision and turnover intentions?
Research Question 8: Is there a statistically significant relationship between
employee job dissatisfaction involving interpersonal relationships and turnover
intentions?
Research Question 9: Is there a statistically significant relationship between
employee job dissatisfaction involving working conditions and turnover intentions?
Research Question 10: Is there a statistically significant relationship between
employee job dissatisfaction involving salary and turnover intentions?
Hypotheses
In this research study, I tested 10 null and alternative hypotheses to determine
whether a relationship exists and how well the independent variables predict the
dependent variables.
H1
o
: There is no statistically significant relationship between employee
achievement and employee turnover intentions.
H1
a
: There is a statistically significant relationship between employee
achievement and employee turnover intentions.
H2
o
: There is no statistically significant relationship between employee
recognition and employee turnover intentions.
7
H2
a
: There is a statistically significant relationship between employee recognition
and employee turnover intentions.
H3
o
: There is no statistically significant relationship between employee work and
employee turnover intentions.
H3
a
: There is a statistically significant relationship between employee work and
employee turnover intentions.
H4
o
: There is no statistically significant relationship between employee
responsibility and employee turnover intentions.
H4
a
: There is a statistically significant relationship between employee
responsibility and employee turnover intentions.
H5
o
: There is no statistically significant relationship between employee
advancement and growth and employee turnover intentions.
H5
a
: There is a statistically significant relationship between employee
advancement and growth and employee turnover intentions.
H6
o
: There is no statistically significant relationship between employee company
policies and employee turnover intentions.
H6
a
: There is a statistically significant relationship between employee company
policies and employee turnover intentions.
H7
o
: There is no statistically significant relationship between employee
supervision and employee turnover intentions.
H7
a
: There is a statistically significant relationship between employee
supervision and employee turnover intentions.
8
H8
o
: There is no statistically significant relationship between employee
interpersonal relationships and employee turnover intentions.
H8
a
: There is a statistically significant relationship between employee
interpersonal relationships and employee turnover intentions.
H9
o
: There is no statistically significant relationship between employee working
conditions and employee turnover intentions.
H9
a
: There is a statistically significant relationship between employee working
conditions and employee turnover intentions.
H10
o
: There is no statistically significant relationship between employee salary
and employee turnover intentions.
H10
a
: There is a statistically significant relationship between employee salary and
employee turnover intentions.
Theoretical Framework
The theoretical framework for the study was Herzberg’s (Herzberg, 1974;
Herzberg, Mausner, & Snyderman, 1959) motivation-hygiene theory, which is also
known as Herzberg's two-factor theory of job attitude, or satisfier-dissatisfier
(motivators-hygiene) theory. Frederick Herzberg developed this motivation-hygiene
theory in 1950 (Herzberg et al., 1959). Herzberg et al. (1959) used the theory to explain
how the factors of job satisfaction and the factors of job dissatisfaction influence
employee turnover intentions. Herzberg et al. identified the following key constructs for
job satisfaction: (a) achievement or quality performance, (b) recognition, (c)
responsibility, (d) work-itself, and (e) advancement and growth. Herzberg et al. also
9
identified the following key constructs for job dissatisfaction: (a) company policy, (b)
supervision, (c) interpersonal relationships, (d) working conditions, and (e) salary.
Herzberg’s (1959, 1974) motivation-hygiene theory implied that if factors related
to job satisfaction go up, turnover intention should go down. According to this model, if
the factors of job dissatisfaction go up, turnover intention should go up as well (Lumadi,
2014). Herzberg’s motivation-hygiene theory includes information about the factors that
foster increased motivation and satisfaction to reduce employee turnover intentions
(Derby-Davis, 2014; Ghazi, Shahzada, & Khan, 2013). For this study, I purchased a
license from Herzberg’s (1974) publisher, Rightslink, to reuse an excerpt from the
theory’s motivation-hygiene profiles (Appendix F). This license allowed me to use both
of Herzberg’s works because the concentration of the works mainly focuses on
motivation and hygiene theory.
Operational Definitions
Actual turnover: The self-assessment and outcome evaluation associated with
leaving the current job (Stanley, Vandenberghe, Vandenberge, & Bentein, 2013).
Criterion variable: The effect or outcome variable as employee turnover (Petter,
DeLone, & McLean, 2013).
Employee turnover: Employee withdrawal in the form of voluntary and
involuntary withdrawal (Mobley, Griffeth, Hand, & Meglino, 1979).
Informed consent: A process that protects participants from any harm, allowing
participants to participate voluntarily (Judkins-Cohn, Kielwasser-Withrow, Owen, &
Ward, 2014).
10
Involuntary withdrawal: When an employee withdraws from work based on the
company’s decision (Mobley et al., 1979; Phillips, 2012).
Negative correlation: A negative correlation means an inverse correlation occurs
between two variables (Green & Salkind, 2011).
Positive correlation: A positive correlation means a direct relationship exists
between two variables (Green & Salkind, 2011).
Predictor variable: The independent or cause variable that predicts another
variable (Petter et al., 2013).
Turnover intention: The process of leaving the current job (Mobley, 1977).
Turnover intention is the last stage before the actual turnover takes place (Mobley, 1977).
Voluntary withdrawal: An employee’s intentional withdrawal from work (Mobley
et al., 1979; Phillips, 2012).
Assumptions, Limitations, and Delimitations
Assumptions
Assumptions are parts of the study that researchers believe are true, where no
verification exists regarding the theory, phenomenon, methodology, instrument, analysis,
participants, power, and results of the study (Dusick, 2014). The assumption in the study
was that the participants answered the survey questions based on what they experienced
and perceived inside the organization regarding employee job satisfaction independent
variables (achievement, recognition, responsibility, work-itself, and advancement and
growth), job dissatisfaction independent variables (company policy, supervision,
interpersonal relationships, working conditions, and salary), and employee turnover
11
intentions in the fast food industry. A review of the literature substantiated the inclusion
of these variables as they related to turnover intentions.
Each participant responded with honesty and accuracy. Participants’ availability
and voluntary participations executed without problems in conducting this research.
Participants who responded to the survey invitation were the representatives of the target
population.
Limitations
The limitations are factors that beyond control of the researchers including (a) the
time constraints, (b) sample size, (c) process of analysis, (d) reporting, and (e) the
instrument used in the study (Dusick, 2014). The process of inquiry design was a cross-
sectional approach, as opposed to a longitudinal process. The success of the process
depended on a limited timeframe. Participants’ busy schedules limited their
participations. The responses of the participants depended on the choices set by the
survey questionnaire, which limited participants to express their views.
The study involved measuring the employee turnover intention and not the actual
turnover. Results of the study data did not generalize with other groups of participants.
The correlational quantitative study only included the fast food industry along the eastern
seaboard in the United States with limited sample size of 130 participants based on the
formula by Tabachnick and Fidell (2007).
Delimitations
The delimitations are factors controlled by me such as (a) selection of
participants, (b) definition of population, and (c) targeted setting (Dusick, 2014). The
12
research problem of this quantitative study was the increasing turnover in the fast food
industry. Employee turnover was one of the major problems of many fast food
organizations, because turnover was costly and disruptive for their business operations.
The targeted population in the study was the fast food workers located in the east
coast seaboard in the United States. The sample of the population was the low-level
employees or non-managerial employees who worked in the fast food restaurants. The
Herzberg’s (1959, 1974) motivation-hygiene theory was the basis theoretical framework
used in the study. The Herzberg’s (1959, 1974) motivation-hygiene theory helped
understand the factors that fostered job satisfaction and job dissatisfaction for many
employees to avoid increasing turnover in the fast food industry.
Significance of the Study
Contribution to Business Practice
The study is important for managers to understand the factors that promote
employee job satisfaction and employee job dissatisfaction that influence employee
turnover intentions to actual turnover. The financial costs involved in employee turnover
in the restaurant industry including fast food restaurants are expensive and costly because
of recruitment problems (Batt et al., 2014; French, 2014; Murphy et al., 2009; Perez &
Mirabella, 2013). Understanding and addressing the factors that led to employee turnover
intentions in the fast food industry might help managers reduce increasing turnover.
The study results may also contribute to effective business practices. By
examining and determining the factors that promote employee job satisfaction and job
dissatisfaction, managers can assess the aspects of job and focus on factors that need
13
attentions. With proper strategies to implement, managers can avoid turnover intention
from happening. For examples, to increase employee job satisfaction with achievement
and recognition, managers must have a periodic performance evaluation based on the
employee performance with feedback. The strategy may increase employee productivity
and increased productivity can increase business profits (Gkorezis & Petridou, 2012;
Haines III & St-Onge, 2012; Kehoe & Wright, 2013).
Another factor that managers can focus on is pay. Pay is a motivating factor for
many employees that influence performance and intention to leave (Kwon, 2014; Misra,
Jain, & Sood, 2013). If business managers improved the employees’ compensation
structure based on the effective performance and competence, then increased employee
performance could affect business performance as well.
Empowering employees by providing an advanced training, autonomy, and
control can help employees perform the jobs with skills, resulting to increased employee
job satisfaction and customer satisfaction. Satisfied customers can result to repeat
business orders, which increase organizational business profit. Satisfied employees
increase employee retention rate.
Implications for Social Change
In examining and determining relationships and the extent of the relationships of
the variables, employers may help improve the business practices or policies. Some of the
business practices are (a) evaluating the employee compensation periodically, (b)
recognizing the effortless contributions and performances of the employees, (c)
empowering the employees, and (d) providing safe and healthy environment. Improving
14
business practices may also improve the conditions of the employees, and increase
employee and business performance that influence business profitability and long-term
growth.
Other implications for positive social change are to help employees to enhance (a)
organizational commitment, (b) employee engagement, (c) job satisfaction, and (d)
motivation. With increased employee job satisfaction and decreased job dissatisfaction,
managers can minimize the employee turnover intentions. Minimizing the turnover
intention can prevent an increasing employee turnover from occurring.
A Review of the Professional and Academic Literature
The literature review examines topics including Herzberg’s (1959, 1974)
motivation-hygiene theory consisted with the primary theoretical framework for the
study. Maslow’s (1943) hierarchy of needs and the Hackman and Oldhams’ (1976) job
characteristics model, including strengths, limitations, and weaknesses of other theories,
and the reasons why Herzberg’s motivation-hygiene theory was the priority theoretical
framework. Other topics include the psychometrical scales such as Job Satisfaction
Scales (JSS) and Job Descriptive Index (JDI), including their established reliability and
validity properties that were used as a guide for choosing the right scale for this study.
The other parts of the literature review include the variables used for the study
such as job satisfaction independent variables and job dissatisfaction independent
variables, and the dependent variable turnover intentions. The job satisfaction
independent variables were (a) achievement, (b) recognition, (c) responsibility, (d) work-
itself, and (e) advancement and growth (Herzberg, 1974; Herzberg et al., 1959). The job
15
dissatisfaction independent variables were (a) company policy, (b) supervision, (c)
interpersonal relationships, (d) working conditions, and (e) salary (Herzberg, 1974;
Herzberg et al., 1959). Each variable tracked in this study had empirical support from
different fields of research to support the relationship between variables.
Other related topics described in this section are employee turnover, causes of
turnover, and implications of the turnover, employee engagement, commitment, and
employee retention. The investigation involved an intensive review of previous research
and findings related to the variables and the theoretical framework guided in the study.
The purpose of this literature review was to clarify research questions, hypotheses, and
identify gaps in previous research.
Strategy for Searching the Literature
I used the following databases and search engine used to locate peer-reviewed
journal articles, dissertations, books, and U.S government and private websites:
ABI/Inform Complete; Academic Search Complete; Business Source Complete;
Dissertation, and Theses at Walden University; eBook Collection (EBSCOhost); Emerald
Management Journal; Google Scholar; Hospitality & Tourism Complete; and PsycINFO.
The following search terms used employee achievement, employee recognition, employee
communication, employee responsibility, employee growth, employee advancement, pay,
company policy, training, and working conditions. Other terms used for the study were
voluntary withdrawal, involuntary withdrawal, employee turnover, turnover intention,
job satisfaction, job dissatisfaction, employee engagement, and employee commitment.
To further expand the topic of the study, the other words used were restaurant industry,
16
fast food industry, quick-service restaurants, intention to leave, Herzberg’ motivation-
hygiene theory (two-factor theory), Maslow’s hierarchy of needs, Hackman and
Oldham’s job characteristics model, job satisfaction scale (JSS), and job descriptive
index (JDI). The literature review included different peer-reviewed journal articles,
dissertations, books, and other sources published within 5 years of my anticipated
graduation. The frequency and percentages of the resources such as books, dissertations,
peer-reviewed articles, and other sources are listed in Table 1.
Table 1
Frequency and Percentage of the Study Sources
References
Resources Within 5 years Older than 5 years Total %
Books 4 3 7 3%
Dissertations 1 1 2 1%
Peer-reviewed articles 178 13 191 95%
Other resources 2 0 2 1%
Total 202 100%
Herzberg’ Motivation-Hygiene Needs (Two-Factor Theory)
The theoretical framework for this study was based on Herzberg’s (1959, 1974)
motivation-hygiene theory, which is also known as Herzberg's two-factor theory.
Psychologist Frederick Herzberg developed the motivation-hygiene theory in 1950
(Herzberg et al., 1959). In the early 1960s, Herzberg used the motivation-hygiene theory
17
first in AT&T’s College Recruitment program for employee selection and training
purposes (Herzberg et al., 1959). Herzberg et al. (1959) incorporated the two factors with
job enrichment. The reprinting of the books occurred for more than 200 times
internationally and applied in different fields and various business sectors (Herzberg,
1974; Herzberg et al., 1959).
Herzberg’s (1959) and Herzberg et al.’s (1974) motivation-hygiene theory
describes the factors that promote employees’ job satisfaction and job dissatisfaction. The
key factors for job satisfaction listed in this theory are (a) achievement, (b) recognition,
(c) work-itself, (d) responsibility, and (e) advancement and growth. The key factors for
job dissatisfaction listed in this theory are (a) company policy, (b) supervision, (c)
interpersonal relationships, (d) working conditions, and (e) salary. Herzberg et al.
described the motivation as motivational factors or satisfiers and hygiene as dissatisfiers.
Herzberg et al. (1959) also emphasized that both job satisfaction and job
dissatisfaction are two different phenomena. According to this theory, the absence of
hygiene factors does not create employee job satisfaction or motivation; instead, an
employee can consistently feel the job dissatisfaction even when hygiene factors were
present (Herzberg, 1974). The increasing complaints of many employees because of
hygiene factors accelerates hygiene crisis for many business managers (Herzberg, 1974).
Herzberg (1974) added that motivation and hygiene factors had different job employee-
performance outcomes. Motivators are factors that provide long-term results to the
employees’ performance as opposed to hygiene factors or dissatisfiers that produce short-
term effects towards employees’ performance and job attitudes.
18
Herzberg (1974) also noted that the source of employee job satisfaction was
because of job content, whereas job dissatisfaction was because of work context. Job
content is related to jobs that make employees happy through recognition, achievement,
and career growth (Herzberg, 1974). Job context has an indirect relationship with the
employees’ job performance, but relates to factors under the control of companies such as
salary, working condition, and security (Herzberg, 1974).
Herzberg et al. (1959) further explained the factors of job satisfaction,
emphasizing that employee achievement or a quality performance was a leading factor to
employee job satisfaction. In short, employees can achieve higher job satisfaction if they
achieve their goals or if employees performed well with quality. High-quality
performance is associated with employee satisfaction and produces positive behavior
towards employees’ jobs (Herzberg et al., 1959). In addition, employee recognition
increases employee satisfaction where feedback based on the employee’s performance
plays a vital role (Herzberg et al., 1959).
Having a good relationship with customers provides motivation and job
satisfaction to the employees (Herzberg et al., 1959). Responsibility involves self-
scheduling, authority to communicate, control of resources, and accountability (Herzberg
et al., 1959). Self-scheduling consists of how employees make a schedule for customers
to meet their high expectations. Having authority to communicate with the customer(s)
and others to avoid delays in completing the job makes employees satisfied with their
job. Employee job satisfaction increases when employees have rights and when tools are
19
available to complete the assigned tasks with complete responsibility (Herzberg et al.,
1959).
Advancement and growth is one of the job satisfaction factors. Advancement and
growth refer to learning new things to enhance (on the job training) employee’s
competence (Herzberg et al., 1959). Advancement and growth can achieve by training.
Employees with proper and sufficient training are competent to do the assigned job.
Herzberg et al. asserted with proper and effective training, employees can grow and
advance their career. Salary and relationship with employees are hygiene factors or job
dissatisfaction factors (Herzberg et al., 1959). Copyright clearance location exists in
Appendix F. Issued license applies to both Herzberg’s works because the concentration
of works primarily focuses on motivation-hygiene theory.
Research findings of using motivation-hygiene theory. Many researchers in
different fields later extended the motivation-hygiene theory. Lumadi (2014) used the
theory of Herzberg’s (1959) motivation-hygiene theory for the exploration of factors that
promote dissatisfaction for many teachers to implement the new school curriculum.
Lumadi (2014) found some factors that influence employee job dissatisfaction such as job
security, training, job responsibility, and curriculum transformation process. Lumadi
(2014) added that empowering employees can promote new effective school curriculum.
Research findings include the suggestion that employees must have an active
participation in school transformation process including in decision-making (Lumadi,
2014).
20
Derby-Davis (2014) also used the same theory for the purpose of job satisfaction
and intention to stay on the job. Derby-Davis found that motivation and hygiene factors
are significant factors to meet job satisfaction to decrease turnover intent in a nursing
industry. Ghazi et al. (2013) utilized the Herzberg’s (1959) motivation-hygiene theory to
quantify the level of satisfaction and motivation of employees towards the job. The study
findings revealed that the motivation of employees relied on the fulfillment of hygiene
factors. As suggested, hygiene factors must remain a priority to achieve a higher level of
motivation and satisfaction to increase employee performance (Ghazi et al., 2013).
Islam and Ali (2013) used the model of Herzberg’s (1959) motivation–hygiene
theory to determine the work factors that promote job satisfaction and job dissatisfaction
to the teachers in the university private sector. Islam and Ali (2013) found work factors
that promote employee satisfaction for many teachers such as: (a) achievements, (b)
recognition, (c) work itself, (d) responsibility, and (e) advancement. Among the
motivators, achievement and work itself include better employee satisfaction than other
motivators (Islam & Ali, 2013).
In contrary, Islam and Ali (2013) discovered that employee pay, university policy,
and growth opportunity are dissatisfiers that affect employee job dissatisfaction. Islam
and Ali (2013) also found that supervisions, relationships with the supervisors and co-
workers, and working conditions positively affect employee satisfaction. Relationship
with co-workers provides better satisfaction as opposed to other hygiene factors (Islam &
Ali, 2013).
21
Teck-Hong and Waheed (2011) decided to use the Hezberg’s (1959) motivation-
hygiene theory with convenience sampling. Teck-Hong and Waheed found that working
condition, recognition, policy, and salary increase job satisfaction. Teck-Hong and
Waheed added that working condition has the highest level of employee’s motivation, as
opposed to employee salary. Flores and Subervi (2013) argued that growth and
advancement are the leading motivators to keep satisfied with the job and reasons to stay.
Implications of using motivation-hygiene theory. The implications of applying
motivation-hygiene theory to employee management brought different outcomes for
many researchers. To analyze the results of using Herzberg’s (1959) motivation-hygiene
theory, most of the motivator factors such as achievements, recognition, work itself,
responsibility, and advancement supported the views of Herzberg in motivation-hygiene
theory in terms of job satisfaction (Islam & Ali, 2013). On the other hand, the hygiene
factors such as pay and university policy also supported the view of Herzberg in terms of
job dissatisfaction.
However, other hygiene factors such as supervision, relationships with the
supervisors and co-workers, and working conditions promoted satisfaction for many
teachers instead of promoting job dissatisfaction (Islam & Ali, 2013). The research result
found contradicted to Herzberg’s (1959) view in motivation-hygiene theory added by
Islam and Ali (2013). The researchers found growth opportunity motivational factors as
opposed to the belief of Herzberg in motivation-hygiene theory (Herzberg, 1974;
Herzberg et al., 1959).
22
The study results could not generalize to all private university sectors in Pakistan
except in the district of Peshawar (Islam & Ali, 2013). The sample size used in the study
was small; therefore, future researchers could use bigger sample sizes by considering
more districts (Islam & Ali, 2013). Potential consideration in the future research is a
comparison of job level satisfaction among teachers in private and public sectors (Islam
& Ali, 2013). The results of the study can enhance the quality of teaching performance
among teachers regardless of service sectors to improve the learning experiences of many
students (Islam & Ali, 2013).
Teck-Hong and Waheed (2011) used the motivation-hygiene theory to determine
the factors that motivate and satisfy employees working in retail stores in Malaysia. The
research results demonstrated that hygiene factors overweighed the motivation factors,
meaning the employees had more job satisfaction with the contributions of the working
conditions, company policies, and salaries than other motivators excluding recognition
(Teck-Hong & Waheed, 2011). The employees found recognition as a motivating factor,
which supported the findings of Herzberg (1974). In addition, hygiene factors as a source
of job satisfaction contradicted to the view of Herzberg. The hygiene factors according to
Herzberg (1974) and Herzberg et al. (1959) are sources of job dissatisfaction and not job
satisfaction for many employees.
Teck-Hong and Waheed (2011) suggested that retailing store managers must
focus on working conditions, company policy, recognition, and salary when employing
rewards scheme to increase employee satisfaction, resulting to increased productivity and
performance. Considering employees’ needs and concerns, employees can provide better
23
service performance that can affect business profitability because of customer satisfaction
(Teck-Hong & Waheed, 2011). Moreover, meeting the needs of the employees can
minimize the employee turnover. Reduced turnover can save money, because managers
do not need to spend money for advertising, hiring, and training new employees (Teck-
Hong & Waheed, 2011).
Ghazie et al. (2013) found that teachers from university are both satisfied with
hygiene and motivation factors, but only fulfillment of hygiene factors can motivate
teachers from university. The study results contradicted with Herzberg’s (1974) findings
regarding the hygiene factors that promote job dissatisfaction or no motivation. From the
perspective of Ghazi et al., (2013), researchers recommended considering hygiene factors
as source of employee motivation and satisfaction to increase employee performance.
Rival Theories of the Theoretical Framework
In 1943, Abraham Maslow introduced the Maslow’s hierarchy of needs.
Maslow’s hierarchy of needs include five sets of goals such as (a) physiological needs,
(b) safety, (c) social, (d) self-esteem, and (d) growth needs or self-actualization (Maslow,
1943). The hierarchy of needs include a foundation of goals of predominance, meaning
employees cannot achieve the higher needs without meeting the lower needs (Maslow,
1943). Maslow added that each need correlates to one another. Once an individual meets
the lower needs, the higher needs emerge (Maslow, 1943).
Maslow (1943) described the five sets of goals. Physiological needs are the basic
needs of individuals to survive such as water, air, and food. Once individuals met these
physiological needs, safety and security needs are the next target (Maslow, 1943). Safety
24
and security needs occur when individuals feel the threats of the situations such as
economic condition and competition. When individuals feel satisfied with the safety
needs, social (love and belonging) needs occur (Maslow, 1943). Individuals need love
and belongingness as part of the community, groups, or family to communicate,
participate, and share their visions. After achieving love and belonging needs, individuals
want to gain respect from others and feel that others value their contributions to feel the
self-esteem. Self-esteem increases when individuals receive recognition or
acknowledgement in the job performance. Once the individuals satisfied the deficiency
needs, individuals’ growth needs (self-actualization) emerge. Self-actualization occurs
when an individual realizes personal potential and self-fulfillment where growth becomes
the highest need target (Maslow, 1943). Another rival theory of Herzberg’s motivation-
hygiene theory is Hackman and Oldham’s (1976) job characteristic model.
Hackman and Oldham (1976) proposed the Job characteristics model (JCM). The
JCM includes the core job dimensions that influence three psychological states, such as
(a) meaningfulness of work, (b) responsibility of outcomes, and (c) knowledge of results,
resulting in positive and negative outcomes. Positive outcomes increase job satisfaction,
job performance, and employee motivation. Negative outcomes decrease employee
absenteeism and turnover (Hackman & Oldman, 1976). The core job dimensions are skill
variety, task identity, task significance, autonomy, and feedback (Hackman & Oldham,
1976).
According to Hackman and Oldham (1976), meaningfulness of work can
materialize if skill variety, task identity, and task significance are present. Responsibility
25
of outcomes can occur when employees have autonomy towards aspects of the job
(Hackman & Oldman, 1976). Employees can achieve the results of knowledge through
feedback added by Hackman and Oldman. Meeting the core job dimensions, employees
can increase their motivation, job performance, and work satisfaction, which contribute to
decreased absenteeism and turnover (Hackman & Oldman, 1976). Another tenet of the
theory is that employees have higher personal growth and development, where employees
have ability to do the complex job with higher motivation (Hackman & Oldham, 1976).
Strengths and limitations of rival theories of the theoretical framework.
Maslow’s (1943) hierarchy of needs focuses on the individual needs as a powerful
motivator in the workplace. Deci and Ryan (2014) noted that needs are subdivided into
two categories based on its importance that include lower and higher needs. Higher order-
needs include self-esteem, achievement, and actualization whereas the lower-order needs
include physiological needs (Deci & Ryan, 2014). With research findings, Deci and Ryan
found that higher-order needs are a powerful motivator in the workplace, contributing to
job enrichment. With job enrichment such as feedback, employee performance and
satisfaction can increase (Deci & Ryan, 2014).
Maslow’s (1959) hierarchy of needs include the deficiency and growth needs of
the employees, which may assist employers on what needs motivate and satisfy the
employees the most (Lester, 2013; Matache & Ruscu, 2012). If managers know what
needs, motivate, and satisfy employees the most, then managers can focus primarily on
these needs. Addressing the issues with proper strategies can avoid turnover intentions.
The concept of Maslow’s (1959) hierarchy of needs also consists of individual needs that
26
provide importance and benefits to the employees (Cao et al., 2013). Maslow’s (1959)
hierarchy of needs emphasizes the importance of well-being for not only survival
purposes, but also general purposes to minimize turnover intentions (Jackson et al.,
2014).
Taormina and Gao (2013) concluded that the two needs have the same satisfaction
outcomes. The satisfaction of the lower-order needs is the same as meeting the higher-
order needs (Taormina & Gao, 2013). Under the study findings of Adiele and Abraham
(2013), having low levels of satisfaction in five hierarchies of needs affect the
performance and effectiveness of employees. Enhancing the employees’ working
environment can increase employees’ productivity and commitment. Meeting the
employees’ needs help encourage employees to exceed employer expectations
(Eisenberger, Fasolo, & Davis-LaMastro, 1990).
The job characteristic model can apply to management staff in identifying the job
characteristics that need improvement, what existing potential jobs may help increase
employee work motivation, and what job core dimensions do or do not work as expected
(Hackman & Oldham, 1976). On the view of Kanten (2014), enhancing the core job
dimensions can help employees increase positive job attitudes and quality work
performance. The job characteristics such as feedback and skill variety are effective
factors to use for employees’ job constructing to meet the demands of customers in hotel
(Kanten, 2014). Kanten used the model for four five star hotels in one city, where results
cannot not generalize to other hotels in a different city.
27
The job characteristics model includes individual employees, because each
individual has different response to the situation (Hackman & Oldham, 1976). The job
characteristics model consists of aspects of the job that create incentives for motivational
purposes (Hackman & Oldham, 1976). On the other hand, Kanten (2014) found that job
characteristics such as feedback and skill variety have direct correlations with job
constructing, but not the autonomy and task significance.
Kanten (2014) suggested that employees from a hotel must have varied skills and
talents to cope up with the nature of the working environment. In addition, feedback from
managers and coworkers help increase employees’ confidence in performing the jobs
(Kanten, 2014). Employees from the hotel industry do not perceive high autonomy and
task significance because of the nature of job (Kanten, 2014).
Reasons not to choose rival theories of the theoretical framework. The reason
why I did not choose Maslow’s (1943) hierarchy of needs or Hackman and Oldham’s
(1976) job characteristic model as a theoretical lens in solving my problem because each
theory has a different nature of study. Each theory has different purposes, contrary to my
study to address the research question and hypotheses. The concept of Maslow’s
hierarchy of needs primarily focuses on the needs of the employees according to the level
of importance. The implication of Maslow’s theory is that employees cannot achieve the
higher needs without meeting the lower needs first (Maslow, 1943).
The job characteristics model involves the core job dimensions that influence
psychological states resulting to behavioral outcomes (Hackman & Oldham, 1976). The
presence of a psychological state is important to achieve the personal and work outcomes
28
(Hackman & Oldham, 1976). In both rival theories, researchers discussed the same topics
regarding job satisfaction, motivation, and turnover (Hackman & Oldham, 1976; Maslow,
1943). However, the theory constructs for Maslow’s (1943) hierarchy of needs and
Hackman and Oldham’s (1976) job characteristics model are different from Herzberg’s
(1959) motivation-hygiene theory. The intent of study was to examine and determine the
factors that promote employee satisfaction and employee job dissatisfaction for many
employees that influence turnover intentions to reduce the turnover in the fast food
restaurants. Herzberg’s (1959) motivation-hygiene theory includes the constructs used in
this study. Therefore, the theoretical framework used in the study is appropriate.
Weaknesses of the rival theories of the theoretical framework. The concept of
Maslow’s (1943) hierarchy of needs is that employees must meet the needs in order from
lower-to higher needs, which is in contrast with Başlevent, Cem, and Hasan
Kirmanoğlu’s (2013) findings. Başlevent et al. (2013) found that employees have higher
concerns with the needs directly influenced them, but not necessarily in order. Bayoumi
(2012) supported the notion. Bayoumi found that patients need the self-actualization the
most, and the least is the love and belonging needs. The study findings indicated that
patients meet their needs without first meeting the physiological and security needs,
which is a contradiction to Maslow’s theory.
The weakness of the JCM is that not all core job dimensions (skill variety, task
identity, task significance, feedback, and autonomy) must follow in order to achieve
higher job satisfaction, motivation, and quality performance to lower turnover and
absenteeism (Fried & Ferris, 1987). Samples have unique demographic characteristics
29
and different methods used have different results that influence job characteristics and
personal and work behavioral outcomes (Fried & Ferris, 1987). Added by Hauff and
Richter (2015), in JCM, job satisfaction increases based on the specified situation and
intrinsic aspects of the job outweigh the extrinsic aspects of the job.
Measurements
Job Satisfaction Survey (JSS). A study grounded in Herzberg’s motivation-
hygiene theory, which promotes the factors of job satisfaction and the factors of job
dissatisfaction to measure the constructs (Spector, 1985). Spector’s JSS has nine facet
scales with four questions, equivalent to 36 questions. The nine facet scales are (a) pay,
(b) promotion, (c) supervision, (d) fringe benefits, (e) contingent rewards (performance-
based rewards), (f) operating procedures (required rules and procedures), (g) coworkers,
(h) nature of work, and (i) communication (Spector, 1985). Each question has an ordinal
scale with a 6-point-Likert-type scale from strongly disagree to strongly agree.
To assess the employees’ attitude towards the job or aspects of the job,
researchers used the JSS in different field of researches, privately or publicly (Spector,
1985, 1997). The internal consistency reliability of JSS instrument is .91 using
Cronbach’s coefficient alpha derived from 2,870-sample size (Spector, 1985, 1997).
Avdija and Roy (2012) used the JSS in different prisons in Atlanta to assess the level of
employees’ job satisfaction. The JSS internal consistency reliability was α =.878 obtained
from 480 participants (Avdija & Roy, 2012). Using multivariate regression analysis,
Avdija and Roy (2012) found that age and working conditions had direct correlations
30
with job satisfaction, where the total variation in the job satisfaction among the prison
employees was 30% (Avdija & Roy, 2012).
Wozencroft and Hardin (2014) indicated that previous researchers tested the
original JSS in 19 different samples to meet reliability and validity norms. Primarily,
researchers used JSS for human services, but since then JSS applies to all organizations.
To conduct a research in Phoenix, Arizona for employees and volunteers in recreation
management, Wozencroft and Hardin suggested utilizing the JSS questionnaire for
assessing the employees’ level of job satisfaction to determine the influence of job
satisfaction for future services. One hundred and thirteen students successfully
completed the questionnaires. Wozencroft and Hardin study findings indicated that job
satisfaction directly related to turnover intention, commitment, and retention with .85
Cronbach coefficient alpha.
Job Descriptive Index (JDI). Smith, Kendall, and Hulin introduced the JDI in
1969; this index was subsequently revised by JDI Research Group in 1985 (Kihm, Smith,
& Irwin, 2014). In 1985 according to DeMeuse, JDI was a popular scale used by many
researchers, professors, and employees in different fields for rating employees’ job
satisfaction to include pay, promotional opportunities, supervision, work itself, and
coworkers (Kihm et al., 2014). The development and refinement of JDI continued for
more than 50 years under the JDI research group, which includes different individuals
with different backgrounds in research, psychology, and behavioral science (“Bowling
Green,” n.d.).
31
The JDI instrument has five facets where employees can rate their job satisfaction
on each area to include (a) coworkers, (b) the work itself, (c) pay, (d) opportunities for
promotion, and (e) supervision (Kihm et al., n.d). The continued revision of JDI helped
increase the internal reliability of an instrument using coefficient alpha (a) opportunities
for promotion .87, (b) people at work .88, (c) present pay .86, (d) supervision .91, and (e)
work on present job .90 (Holt, 2001). Holt indicated that researchers can measure the JDI
through a nominal scale Yes, No, and ?, which is equivalent to 1, 2, and 3 answers. The
JSS questionnaire includes positive and negative short words or phrases. In a positive
response, Y response shows satisfaction (Holt, 2001). In scoring, Y is 3 points, N is 0
point, and ? is 1 point. In a negative response, Y means dissatisfaction. An unfavorable
item is the reversed score, where N has 3 points, Y has 0 point, and ? has a 1 point (Holt,
2001). Each subscale must have an individual score, where some items are reversed
scores.
To collect the data, secondary resources were appropriate such as SSS and census
databases with random and stratification sampling. The participants included current
employed employees between 18 and 70 years of age and located within the United
States. The response rate was approximately 23%, equivalent to 1600 cases involving
data for intention to quit, job satisfaction, trust management, and demographic variables
(Kimh et al., n.d.). Follow up mailings were appropriate along with incentive provisions,
and multiple survey administrations to avoid biased information.
In other instances, Graeff, Leafman, Wallace, and Stewart (2013) successfully
employed the JDI scale in one of the faculties in the United States. The purpose is to
32
assess the job satisfaction level among physician assistants. With 1,241 target
participants, only 239 respondents successfully participated. Graeff et al. found that the
reliability of JDI is greater than .80. Gui, Gu, Barriball, While, and Chen (2014) also
found the JDI reliability greater than .70 when they assessed the working environment of
many nurse teachers in two different countries. The overall responses from China and UK
are 56.8% through cross-section interview process according to Gui et al.
By analyzing the two instruments, JSS and JDI have acceptable internal
consistency reliability. The reliabilities of JSS in three different sample sizes are .91, .87,
and .85 respectively (Avdija & Roy, 2012, Spector, 1985; Wozencroft & Hardin, 2014).
The reliabilities of JDI is .80 (Graeff et al., 2013; Gui et al., 2014; Holt, 2001). The
reliability result of the JSS is higher than JDI. Therefore, JSS instrument would apply
throughout the study process. Matkar (2012) noted that >0.90 is excellent, 0.80 – 0.89 is
good, 0.70 – 0.79 is acceptable, 0.60 – 0.69 is questionable, 0.50 – 0.59 is poor, and
<0.50 is unacceptable. This implies that JSS is a reliable tool to assess participants’
satisfaction towards aspects of job or job as a whole.
In terms of constructs of both instruments, the JSS has nine facet scales that cover
all theoretical constructs related to the study topic, which met the content and construct
validity. The JDI has five facet scales (pay, promotions and promotion opportunities,
coworkers, supervision, and the work itself), which unfortunately did not meet the
theoretical framework constructs for measurement (Kihm et al., n.d). Therefore, JSS
would apply to measure the constructs. Lack of constructs to measure could violate the
required validity that adversely affects the study findings (Barry et al., 2014). The
33
theoretical model for this study is Herzberg’s motivation-hygiene theory (Two-factor
theory) (see Figure 1).
Theoretical Model: Herzberg’s Motivation-Hygiene Theory
Figure 1. Depiction of Herzberg’s motivation-hygiene theory (two-factor theory) as a
theoretical framework. Adapted from “Motivation-Hygiene Profiles: Pinpointing What
Ails the Organization,” by F. Herzberg, 1974, Organizational Dynamics, 3(2), pp.18-29.
Copyright 1974 by the American Psychological Association and Adapted from The
motivation to work (2nd ed.),” by F. Herzberg, B. Mausner, & B. B. Snyderman, 1959,
New York, NY: John Wiley. Copyright 1959 by John Wiley. Used with permission.
Job Satisfaction
The topic includes an employee job satisfaction in many work settings, private,
public, non-profit organization, and government sections (Herzberg 1974; Herzberg et al.,
1959; Maslow, 1943). The research includes employee job satisfaction using different
conceptual or theoretical frameworks with Herzberg’s (1959) motivation-hygiene theory,
Maslow’s (1943) hierarchy of needs, and the Job characteristics model (Fried & Ferris,
1987; Herzberg 1974). The term job satisfaction has defined in many ways.
Achievement or Quality
Performance
Recognition
Work Itself
Turnover
intentions
Responsibility
Advancement and Growth
Job
Satisfaction
34
Hofaidhllaoui and Chhinzer (2014) described a job satisfaction as a main source
of turnover, describing the level of contentment and attachment of employees toward
their job, specifically or generally. Job satisfaction is the characteristics of the job itself
and the work environment (Cho, Rutherford, & Park, 2013). Locke (1976) defined the
job satisfaction as a pleasurable or positive emotional state resulting from the appraisal of
an individual job (as cited in Skaalvik & Skaalvik, 2011; Ünal, 2013). Job satisfaction is
how an employee felt contented with the job (Spector, 1997). Job satisfaction is an
employee’s attitude towards aspects of job or as a whole (Ünal, 2013). Herzberg et al.
(1959) described a job satisfaction as how employee likes or dislikes the job. In
summary, employee job satisfaction includes how individual likes or dislikes the job or
how individual assess his contentment towards his job as a whole or aspects of job. The
employee job satisfaction can measure using psychometric scale. A psychometric scale is
a scale that has a preestablished internal consistency reliability using Cronbach’s
coefficient alpha, which according to Matkar (2012) >0.90 is excellent, 0.80 – 0.89 is
good, 0.70 – 0.79 is acceptable, 0.60 – 0.69 is questionable, 0.50 – 0.59 is poor, and
<0.50 is unacceptable.
To measure job satisfaction constructs, a researcher can use a general or facet-
specific job satisfaction using different psychometrical scales such as JSS, JDI, and JCM
(Jang & George, 2012; Skaalvik & Skaalvik, 2011). A facet-specific job satisfaction is to
measure the employee’s attitudes toward specific aspects of job whereas a general job
satisfaction is to measure the employee’s attitudes towards the whole aspects of job (Jang
& George, 2012; Skaalvik & Skaalvik, 2011). In organizational behavior literature using
35
psychometric scales, researchers found that job satisfaction had a positive relationship to
many variables.
For example, Bang, Ross, and Reio (2013) found that job satisfaction is a
mediating factor between the motivation and affective commitment. A committed
employee can work with high motivation and high job satisfaction (Bang et al., 2013).
Jyothi and Ravindran (2012) noted that job satisfaction, commitment, human resource
(HR) practices, and employee turnover have correlations to one another. Ünal (2013)
added that job satisfaction directly related to organizational commitment and best
predictor to organizational commitment. When employees feel satisfied with their jobs,
they become more committed to the organization (Ünal, 2013).
In addition, Brewer, Kovner, Greene, Tukov‐Shuser, and Djukic (2012) and Matz,
Wells, Minor, and Angel (2013) asserted that job satisfaction is a mediating variable
between the work environment and the employee turnover. Kumar, Ahmed, Shaikh,
Hafeez, and Hafeez (2013), on the other hand, stated that job satisfaction has a
relationship with employee work environment, compensation, and job specification.
Moreover, in a hospitality industry, Lam and Chen (2012) used a multiple-wave
longitudinal analysis from 424-hotel service employees and supervisors. Lam and Chen
found job satisfaction has a significant relationship with higher service quality that
reduces employee turnover. Gazzoli, Hancer, and Park (2010) emphasized that
employees who feel satisfied with the job and feel empowered promote a high-service
quality to the customers.
36
On the other hand, using data collected from 868 employees working in various
firms in the United States with a self-reporting questionnaire and convenience sampling,
Valentine, Godkin, Fleischman, and Kidwell (2011) found that job satisfaction is a
predictor of turnover intention. Job satisfaction is one of the causes of employee turnover
(Tews, Stafford, & Michel, 2014). Hofaidhllaoui and Chhinzer (2014) suggested that job
satisfaction is an important factor for employee retention or turnover intention; therefore,
employers must focus on facets of job satisfaction that influence these outcomes to
prevent turnover. Other study findings indicated that the job satisfaction directly affect
the employees and business performance (Kehoe & Wright, 2013) whereas others affect
the communication between management and employee (Zelnik, Maletič, Maletič, &
Gomišček, 2012). Consequently, Zelnik et al. (2012) suggested that both employees and
employer must be satisfied to maintain a quality system in an organization.
Using 157 employees and 1600 customers from targeted grocery retailer in South
Africa with quantitative survey method, the findings result indicated that job satisfaction
related to employee motivation (Scheers, & Botha, 2014). Employee motivation
influences employee effective commitment with the organization that reduces the
employee turnover (Roche & Haar, 2013). Employee motivation is also a source of
increased employee productivity that impacts employee performance and turnover that
sustain human resource to produce differentiation from the competitors (Gomes, Asseiro,
& Ribeiro, 2013; Panagopoulos, 2013; Zedelius, Veling, Bijleveld, & Aarts, 2012).
Therefore, employee motivation must increase so employee and business performance
will increase (Zedelius et al., 2012). Other suggestion is managers must listen to
37
employees’ opinions and hear employees’ voices to increase job satisfaction and
motivation as well (Scheers, & Botha, 2014).
Moreover, Spasova (2010) asserted that high motivation promotes high well-
being of one individual. Considering a lack of motivational factors, employees feel
dissatisfied with the job (Islam & Ali, 2013; Linz & Semykina, 2012; Teck-Hong &
Waheed, 2011). Herzberg et al. (1959) described the factors that influence job
satisfaction such as (a) achievement or quality performance, (b) recognition, (c) work
itself, (d) responsibility, and (e) advancement and growth.
Job Satisfaction Factors
Achievement or quality performance. Employee achievement or quality
performance is a primary leading factor to job satisfaction (Herzberg et al., 1959).
Employee achievement derives through training and development as well (Islam & Ali,
2013; Teck-Hong & Waheed, 2011). Career satisfaction manifests when employees
receive self-achievement from their perspective jobs (Kang, Gatling, & Kim, 2015).
Therefore, employers must train and develop their employees to increase their
achievement or quality performance to satisfy with the job (Lester, 2013; Matache &
Ruscu, 2012).
In a service sector, on the other hand where employee-customer relationship is
critical, empowering employees directly affects the customer quality. Therefore, giving
employees extrinsic rewards such as promotion opportunities, financial incentives, and
organizational prestige helps increase high quality performance (Gkorezis & Petridou,
38
2012). Morgan, Dill, and Kalleberg (2013) added that extrinsic rewards such as wages
and benefits are factors that influence job satisfaction and turnover intentions.
The quality performance demonstrates the competence of the employees, which affect the
customers’ experiences (Harrington et al., 2012). Lumadi (2014) supported that training
can affect the quality of work in teaching and learning. With managers’ customer
orientation, employees can provide a quality service because employees have ability to
communicate with customers with honesty and trust, which might create prestige for the
organization (Mathe & Scott-Halsell, 2012).
In contrast, low customer orientation can lead to low employee self-efficacy
(Mathe & Scott-Halsell, 2012). Kanten (2014) suggested improving the job
characteristics such as (a) skill variety, (b) task identity, (c) task significance, (d)
feedback, and (e) autonomy to increase the quality of work. Lee, Lee, and Kang (2012)
found that high-performance work systems affect employees’ attitude towards the job
that impact service quality. The other factor of job satisfaction is recognition.
Recognition. Employees want recognition, achievement, personal growth, and
advancement to feel satisfied with the job (Lester, 2013; Matache & Ruscu, 2012).
Recognizing employees’ effort and contribution is an effective and less expensive
approach in attracting employee to commit with the organization (Hogan, Lambert, &
Griffin, 2013). Employees also need recognition, appreciation, and feeling valued to
increase contributions to the success of the organization (Eisenberger et al., 1990).
Showing employee appreciation and recognition delivers a high quality service to the
customers (Gavino, Wayne, & Erdogan, 2012). Haines III and St-Onge (2012) agreed
39
that employee recognition fosters positive performance. In addition, employee
recognition outperforms the salary factor (Handgraaf, Van Lidth de Jeude, & Appelt,
2013).
Moreover, a work climate with employee respect, recognition, and appreciation
reduces employee turnover (Stinchcomb & Leip, 2013). Bhatnagar (2014) added that
recognition and appreciation can attract employees to stay with the organization.
Employee recognition and appreciation positively affect the work engagement as well
(Choo, Mat, & Al-Omari, 2013; Nyman, Sarti, Hakonen, & Sweins, 2012). Consequently,
lack of employee recognition leads to voluntary turnover (Bauer, 2012).
Using feedback, managers recognize employees’ achievement (Herzberg et al.,
1959). Work feedback from the superior encourages employees’ creativity (Hon, Chan, &
Lu, 2013; Kanten, 2014). With meta-analytic results, Byron and Khazanchi (2012) agreed
that high affirmative feedback on the employees’ task-focused performance increases
employees’ creativity. Yao and Cui (2010) said that task feedback from managers’ help
empowered employees psychologically. Empowering employees psychologically
increases employee motivation resulting in a healthy organizational climate (Yao & Cui,
2010).
On the other hand, employer can recognize employees’ participations in two
ways: performance and nonperformance (Webster & Beehr, 2012). In justice and social
exchange theories, researchers emphasized promotional criteria based on performance
and nonperformance. Performance rewards influence the employee turnover (Lee &
40
Jimenez, 2011). To recognize employees, managers use financial incentives and
promotional opportunities.
Financial incentives reflect on quality performance (Gkorezis & Petridou, 2012).
Financial incentives have a significant relationship with empowerment, where private
sector employers emphasized the importance of rewards according to Gkorezis and
Petridou (2012). Giving employees’ financial rewards impacts employees’ attitudes; thus
rewarding employees based on performance and competency increases employee
productivity and company productivity added by Gkorezis and Petridou
Promotional opportunities are critical factors that motivate employees to increase
job performance (Gkorezis & Petridou, 2012). Using employees from two-business
sectors, public and private, Gkorezis and Petridou (2012) argued that promotional
opportunities positively affect the private employees’ psychological empowerment.
Promotional opportunity is also a significant factor for many employees to remain
committed with the company and be satisfied with the career choice (Wan, Sulaiman, &
Omar, 2012). Therefore, managers must increase employees’ promotional opportunities
to increase their commitment, satisfaction, and job performance. By contrast, Jung and
Kim (2012) asserted that promotional opportunity is also the source of employee
emotional exhaustion, meaning that employees feel stressed to achieve the job promotion,
which turns to employee burnout that affects employee commitment and the intention to
leave.
Furthermore, internal work events such as promotion lead to reduced turnover
(Tews et al., 2014). Giving promotions to deserving employees are signs of appreciation
41
for their efforts in which management leaders demonstrate care for employee’s well-
being (Tews et al., 2014). Gkorezis and Petridou (2012) supported the views of Tews et
al. (2014) stating that giving promotional opportunities is a sign of employers’
commitment and show value for employees’ performance. Employees who perceive
promotional opportunities increase employees’ job embeddedness (Gkorezis & Petridou,
2012). Without perceived promotional opportunities, employees show a lack of
motivation (Gkorezis & Petridou, 2012).
Moreover, often employees who have promotional opportunity and additional
professional development impact self-esteem and self-efficacy (Gkorezis & Petridou,
2012). Self-esteem is one of the higher-order level needs mentioned in Maslow’s (1943)
hierarchy of needs, which is a need that needs gratification to reach growth needs. Gavino
et al. (2012) added that promotional opportunities such as promoting employees in their
positions influence employees’ behavior and performance that affect customer service.
The other factor of job satisfaction is work itself.
Work itself. Herzberg et al. (1959) described work itself as the relationship of the
employee to the customer or group of customers inside or outside the organization. A
customer or a group of customers inside of the organization is the employees of the
organization itself (Scheers, & Botha, 2014). The external customers are those customers
who receive products or services in exchange for money (Scheers, & Botha, 2014).
Building relationships between employees and customers help organization succeed,
because customers are the source of business income (Scheers, & Botha, 2014).
42
The satisfaction of customers depends on the customer service provider; thus, the
customer service provider must prove satisfaction to motivate customers (Scheers, &
Botha, 2014). Previous research also suggested that empowering employees provides
higher satisfaction that creates a better employee-customer relationship, leading to repeat
business transactions, reducing turnover (Ryan et al., 2011). However, other research
findings revealed that job satisfaction has a negative relationship with turnover intention;
but, when employees felt the high extent of job dissatisfaction, employee turnover exists
regardless of external factors (Hofaidhllaoui & Chhinzer, 2014). Another factor of job
satisfaction is responsibility.
Responsibility. Employee responsibility has four aspects of jobs: (a) self-
scheduling, (b) authority to communicate, (c) control of resources, and (d) accountability
(Herzberg, 1974; Herzberg et al., 1959). In self-scheduling, the customer needs are more
important than employee needs added by Herzberg (1974) and (Herzberg et al., 1959).
Moreover, communicating with the customers and handling the resources with authority
are important to accomplish the job. Therefore, managers must empower employees to
execute the job with competence.
To achieve the assigned responsibility, empowering employees plays a vital role
(Herzberg, 1974; Herzberg et al., 1959). Empowerment is the transferring of power to all
employees inside the organization, allowing employees to have control, power, and
authority (Gkorezis & Petridou, 2012). Empowering employees allows them to show
innovation in many ways such as improving the customer service quality and business
process (Fernandez & Moldogaziev, 2013). The innovative approaches improve the
43
employee performance and business performance overall. Without innovated approaches,
empowerment programs become useless and ineffective (Fernandez & Moldogaziev,
2013).
Further, employees need intrinsic rewards such as (a) autonomy, (b) competence,
and (c) relatedness to increase motivation (Roche & Haar, 2013). Previous researchers
emphasized the importance of autonomy as a motivator particularly in decision-making
when job requires more attention (Toode, Routasalo, & Suominen, 2011). Under the soft,
HR management and self-determination theory, the employee autonomousness and
satisfaction influence the HR practices and results (Marescaux, De Winne, & Sels, 2013).
Higher autonomy means higher employee emotional attachment towards the organization
(Newman & Sheikh, 2012). Another factor of job satisfaction is advancement and
growth.
Advancement and growth. Employee advancement and growth depend on new
learning; therefore, training is a significant factor to achieve employee’s growth needs
(Herzberg, 1974; Herzberg et al., 1959; Maslow, 1943). Herzberg et al. (1959) added that
employees remain accountable with their jobs as long as they remain equipped with
training and the appropriate resources. Therefore, managers must train and develop their
employees to enhance job competence (García, Lajara, Sempere, & Lillo, 2013; Salazar,
Torres, & Reche, 2012). Besides, competent employees bring success to the organization,
which affects the business performance (Ji, Huang, Liu, Zhu, & Cai, 2012). Business
with competent employees can achieve business profitability and growth sustainability (Ji
et al., 2012). Employees who perceive organizational leader’s support in training and
44
development are more likely to engage, commit, satisfy, and stay in the organization
(Biswas, Varma, & Ramaswami, 2013; Nouri & Parker, 2013).
Developmental opportunities inside the organization can influence the employee
turnover, according to Carter and Tourangeau (2012). Results from the previous study
confirmed that employees with the opportunity to advance learning skills and develop
professionally are significant factors to employee retention (McGilton, Boscart, Brown,
& Bowers, 2013). The lack of inside opportunities gives a negative signal for many
employees (Carter & Tourangeau, 2012). When the inside opportunities are low, the
employee turnover rate is high, or the opposite when the opportunities are high (Carter &
Tourangeau, 2012). Van Dam, Meewis, and Van der Heijden (2013) supported the
assertions stating that nurses’ career development is a source of turnover intention;
therefore, hospital leaders must create better work environment to meet the high
expectation of the employees. When employers provide an internal growth opportunity
such as training, which increases employee competence, employees feel committed
resulting to lower employee turnover (Nouri & Parker, 2013).
Moreover, employees want personal growth and advancement to feel satisfied
with the job (Lester, 2013; Matache & Ruscu, 2012). In the hotel industry, employee
turnover increased because of employees’ interest to pursue their career advancement
somewhere else (Yang, Wan, & Fu, 2012). Career advancement promotes employee
happiness (Van der Meer & Wielers, 2013). When career advancement is high within the
organization, the voluntary turnover decreases, which is contradicted when career
45
advancement is low (Kraimer, Seibert, Wayne, Liden, & Bravo, 2011). Employee career
advancement also influences employee turnover directly (Choi et al., 2012).
Additionally, employees need career advancement to achieve the fulfillment in
life, and to meet job satisfaction (Islam & Ali, 2013; Teck-Hong & Waheed, 2011). Lack
of career advancement drives employees to find alternative jobs resulting to increased
employee turnover (Carter & Tourangeau, 2012; Nouri & Parker, 2013). In the IT
government sector, promotion, advancement opportunities, training, and development are
factors that influence employees to stay within the organization (Kim, 2012).
Career growth opportunities are benefits that employees perceive as part of social
exchange relationship with the employer (Nouri & Parker, 2013). Employees will commit
to the organization in exchange for career growth opportunities (Nouri & Parker, 2013).
With perceived career growth opportunities, employees’ commitment increases, while
turnover intention decreases (Nouri & Parker, 2013). Career growth opportunities depend
on advanced training that employees receive from the organization (Yang et al., 2012).
Yang et al. suggested that organizational managers must provide significant training that
helps employees increase their chances to grow in their chosen career. Nouri and Parker
(2013) also commented that increased growth career opportunity affects the commitment
of the employee positively and reduce the level of employee turnover.
Training. Training is a tool used to enhance individual’s behavior, skills, and
knowledge to assist organization to gain its competitive advantages in the business
industry (Garcia et al., 2013). Training employees is one of the effective approaches to
gain business differentiation and positioning (Garcia et al., 2013). Training enhances
46
employees’ capabilities that set them apart from the business competitions (Salazar et al.,
2012). In the restaurant industry, lack of training in managerial skills can contribute to
business failures (Perez & Mirabella, 2013). Incompetent leaders can affect their
employees’ performance resulting to increased turnover rates (Perez & Mirabella, 2013).
Perez and Mirabella (2013) found that leadership with no formal training increases
employee turnover rates. Leaders with formal leadership training, contribute to business
success (Perez & Mirabella, 2013).
Within a challenging business environment and competition increases, business
sustainability and competitive advantages become challenging (Stambaugh, Zhang, &
DeGroot, 2013). Armstrong and Taylor (2014) explained the significance of human
capital theory proposed by Barney in 1991. The theory indicated that employers can
sustain competitive advantages by having human capital advantages (Armstrong &
Taylor, 2014). In a challenging business environment, business leaders must replenish
their employees’ skills to meet the competition competitively (Bapna, Langer, Mehra,
Gopal, & Gupta, 2013). Bapna et al. (2013) found that training has a direct correlation
with increased performance by 2.4%. Investing in training programs can enhance
employees’ skills (Bapna et al., 2013). Garcia et al. (2013) stated that employee training
is an effective tool to enhance business’ competitiveness globally, and makes the
business apart from its competition. Therefore, training and developing employees’
capabilities and skills in a continual basis increase employees engagement and focus on
organization’s goals and objectives, leading to business success as suggested by Salazar
et al. (2012) and McSweeney-Feld and Rubin (2013).
47
On the other hand, in the fast pace environment, managers require employee
improvement in skills to catch up with the technological changes (Bapna et al., 2013).
Replenishing skills through effective training are one way to enhance employee
performances and the overall business performances. Gavino et al. (2012) discovered that
training and development have a direct relationship with customer-oriented behaviors.
However, Chang, Wang, and Huang (2013) found that training and development have no
significant relationships with employee turnover intention.
To facilitate training inside the organization, business leaders can use the internal
facilitator, self-study, or online (McSweeney-Feld & Rubin, 2013). Training programs
that include development and leadership programs may help prepare employees to more
challenging assignments and responsibilities (McSweeney-Feld & Rubin, 2013). Through
training programs, business leaders can face any internal and external environmental
changes that may occur overtime (McSweeney-Feld & Rubin, 2013).
Effect of training to employees. As described by Fulmer and Ployhart (2014) and
Mulvaney, McKinney, and Grodsky (2012), managers considered human capital as an
important asset in the organizations. The success and failure of the organization rely on
human capital and human resources (Jehanzeb, Rasheed, & Rasheed, 2013; Walker et al.,
2013). Consequently, employees’ skills need training to support employees’ personal and
professional interests, and for the employees’ development purposes (Boxall, 2013).
On the other hand, Cheung and Chan (2012) noted that employee training has a
direct relationship with employee motivation and organizational competence. Tabassi,
Ramli, and Bakar (2012) added that training positively influences teamwork activities
48
that increase efficiency and development of the assigned work. Training fosters work
enhancement for the group activities (Tabassi et al., 2012). Further, Jehanzeb et al. (2013)
found that training has a direct relationship with organizational commitment and turnover
intention. In conclusion, managers must train their employees to increase their
competence and commitment to minimize employee turnover intention.
Cherian and Jacob (2013) also suggested using effective training to increase
employees’ self-efficacy. Having an effective training, employees can manage the
complex task competently and help succeed in their chosen career (Cherian & Jacob,
2013; Vance, Chow, Paik, & Shin, 2013). In addition, employees can develop their target
career, job security, competence, job satisfaction, and organizational commitment
(Jehanzeb et al., 2013). Moreover, training programs can help employees achieve career
growth (Yang et al., 2012). In IT sector, Bapna et al. (2013) discovered that employees’
training provides high returns of investments. Having an effective training and
development, employees can participate at the workplace effectively (Cavanagh, McNeil,
& Bartram, 2013).
In accounting firm, Nouri and Parker (2013) asserted that lower level employees
perceive career growth opportunity when organizational leaders provide effective training
programs. With effective training, employees become committed, which reduces the
intention to leave the current job (Nouri & Parker, 2013). Employees need training for
moral development to manage moral dilemmas in a healthcare workplace environment
(Rowe, 2013). In addition, the employee training affects the affective commitment of the
49
employees positively but negatively affects the employees’ exhaustion (Chambel &
Castanheira, 2012).
Effect of training to business. Employees’ skills enhancement is the challenging
problem of management to manage the fast pace of the business environment and to
obtain and retain a competitive edge in the business industry (Percival, Cozzarin, &
Formaneck, 2013). To keep pace with the consistent changing business technology,
Percival et al. (2013) suggested that business leaders must invest in human capital and
different training programs because training increases employees’ productivity. Training
is also a determining factor that helps an organization competes in the marketplace
globally and a source of employee motivation (Cheung & Chan, 2012).
Having long-term business competitive edges globally, the business leaders must
know what skills can set them apart from the competition (Salazar et al., 2012). Leppel,
Brucker, and Cochran (2012) revealed that the characteristics and accessibility of training
provide gratification for the older employees. Exemplary customer services with effective
procedures to handle customers’ complaints are critical to the success of the organization
(Shooshtari, Clouse, & Stan, 2012). Therefore, organizational managers must provide
employee training to ensure meeting the higher degree of customer services inside the
organization as suggested by Shooshtari et al. (2012). However, Chang et al. (2013)
found training and development has no significant relationship with employee turnover
intention. Figure 2 includes the factors of job dissatisfaction.
50
Theoretical Model: Herzberg’s Motivation-Hygiene Theory
Figure 2. Depiction of Herzberg’s motivation-hygiene theory (two-factor theory) as a
theoretical framework. Adapted from “Motivation-Hygiene Profiles: Pinpointing What
Ails the Organization,” by F. Herzberg, 1974, Organizational Dynamics, 3(2), pp.18-29.
Copyright 1974 by the American Psychological Association and Adapted from “The
motivation to work (2nd ed.),” by F. Herzberg, B. Mausner, & B. B. Snyderman, 1959,
New York, NY: John Wiley. Copyright 1959 by the John Wiley (Appendix F).
Job Dissatisfaction
Employee job dissatisfaction is one of the phenomena’s that Herzberg (1974) and
Herzberg’s et al. (1959) mentioned in motivation-hygiene theory. According to Herzberg,
employees can still experience the job dissatisfaction regardless of meeting or not
meeting the hygiene factors satisfaction. Hofaidhllaoui and Chhinzer (2014) added that
employees can experience job dissatisfaction at work; however, if employees cannot bear
the extent of job dissatisfaction, employees may leave the organization. Previous research
findings also revealed job dissatisfaction is a predictor to turnover intention (Jang, &
Company Policy
Supervision
Turnover
intentions
Interpersonal Relationship
Job Dissatisfaction
Working Conditions
Salary
51
George, 2012). Dike (2012) agreed stating business leaders believe that job
dissatisfaction is a cause of turnover.
Other study findings revealed that job dissatisfaction leads to decreased
productivity, commitment, and disloyalty (Brewer et al., 2012; Islam & Ali, 2013; Teck-
Hong & Waheed, 2011). Stringer, Didham, and Theivananthampillai (2011) discovered
that job satisfaction has a direct relationship with intrinsic motivation; therefore, giving
employees a fair salary enhances employees’ job satisfaction as decreases job
dissatisfaction. On the other hand, job dissatisfaction is a determining factor for
employees’ emotional exhaustion to work burnout that causes employees not to commit
with the organization and intention to leave follows (Jung & Kim, 2012).The
determinants of job dissatisfactions are poor working environment and low salaries that
make employees quit from the current job (AlBattat & Som, 2013). Therefore, managers
must minimize or prevent employee job dissatisfaction by addressing the hygiene factors
to decrease employee turnover rates as suggested by Chen et al. (2013) and Rahman and
Iqbal (2013). Factors that influence job dissatisfaction are (a) company policy, (b)
supervision, (c) interpersonal relationship, (d) working conditions, and (e) salary
(Herzberg, 1974; Herzberg et al., 1959).
Job Dissatisfaction Factors
Company policy. A company policy consists of general guidelines that HR
management follows to manage any issues within the organization based on the
philosophies and values of the organization (Armstrong & Taylor, 2014). The overall HR
policy demonstrates the HR managers’ responsibilities toward their employees in terms
52
of equity, consideration, organizational learning, performance, quality of working life,
and working conditions (Armstrong & Taylor, 2014). Company policy is one of the
dimensions of job satisfaction (Ünal, 2013). As suggested by Armstrong and Taylor
(2014), managers must communicate the company policy with the employees to have a
productive and rewarding relationship. With effective policies or practices, managers can
encourage employees to participate, gain employees’ trust, loyalty, and commitment to
the organization (Tuzun & Kalemci, 2012). In addition, management with proper
assessments and analyzes of the HR policies may increase employee job satisfaction,
resulting in the high level of employee commitment and may reduce employee turnover
(Kehoe & Wright, 2013). Other job dissatisfaction factor is supervision.
Supervision. The role of supervisors is important, because they communicate
organizational culture and often empower employees to enhance self-worth and self-
esteem (Dike, 2012; Gkorezis & Petridou, 2012). Employees who perceived
organizational culture as friendly, collaborative, and supportive feel satisfied with their
jobs, and often increase employee morale and decrease employee turnover intention
(Dike, 2012). However, if employees are not happy with supervisors’ behavior, the
negative organizational culture can lead to decreased morale and high turnover intention
(Dike, 2012). Hofaidhllaoui and Chhinzer (2014) added that even though employees feel
satisfied with supervisors’ performance, outside external factors such as high external
opportunities or low perceived organizational support can influence employee decision to
leave. Furthermore, employees become irresponsible and powerless towards their job
when their superiors are not supportive (Gkorezis & Petridou, 2012). Job satisfaction
53
supervision is a significant factor to turnover intention; thus, employers must provide
training to improve supervisors’ skills and must focus on securing and rewarding the
effective supervisors. Rewarding must be based on their performances, feedback, and
level of competence to retain knowledge workers as suggested by Hofaidhllaoui and
Chhinzer (2014).
Based on social exchange theory, previous research suggested that supervisory
support can impact employee attitude and behavior positively (Eisenberger et al., 1990).
The level of organizational support affects the level of employee commitment
(Eisenberger et al., 1990). Employees’ commitment influences an employee retention
resulting to a low rate of employee turnover (Paillé, Boiral, & Chen, 2013). An employee
becomes highly committed when managers support employee participation and needs to
accomplish the job requirement (Paillé et al., 2013).
Allowing employees to participate with full support from the organizational
leaders produces a positive and effective motivation (Paillé et al., 2013). Employee’s
engagement depends on the perceived support of the organizational leaders and fairness
in treating employees (Biswas et al., 2013). Previous study results suggested that
employee organizational commitment relies on employees’ feeling about their
supervisors (Kang et al., 2015). When supervision is higher, the emotional attachment of
employees toward the organization is also higher (Newman & Sheikh, 2012).
In hospitality industry, as achieving the goals and objectives of the organization
depend on the front line employees, the latter expects supervisors to support them
achieving their goals professionally (Kang et al., 2015). Kang et al. (2015) also found that
54
perceived supervisory support directly influences affective employee support and career
satisfaction, and an important role in turnover intention. Increased positive exchange
relationship with employees reduces turnover intention, and increases career satisfaction
and organizational commitment by employees added by Kang et al.
Additionally, managers who display high supervisory support can show high
regard to employees’ value, well-being, and feelings (Kang et al., 2015). When
employees perceive less support from the supervisors, employees’ organizational
commitment can decrease, and turnover intention can increase at the same time (Kang et
al., 2015). Supportive managers can delegate duties based on employees’ skills, teach
employees how to improve performance, and respect employees. As implication to
management, employees leave the supervisors and not the organization (Kang et al.,
2015).
On the contrary, abusive supervision occurs when a supervisor displays a hostile
behavior, verbally and nonverbally (Priesemuth, Schminke, Ambrose, & Folger, 2014).
Abused supervision can come in the form of unfair treatment, silent treatment, private
intrusion, and spreading rumors (Priesemuth et al., 2014). Abusive power is detrimental
to a boss-employee relationship, which often includes bitterness in the relationship,
mistrust, and fear (Chan & Mcallister, 2014). Empirical studies show that abused
supervision can foster psychological distress, emotional exhaustion, and anxiety. Distrust,
anxiety, and fear are components of paranoid arousal (Chan & Mcallister, 2014).
In addition to psychological problems, negative behavior can reduce trust, state of
self-esteem, organizational commitment, and job satisfaction. Moreover, other research
55
findings found that abused supervision has a significant relationship with employee
performance, turnover, organizational citizenship behavior, resistant behavior, and
counter productive work behavior (Chan & Mcallister, 2014). Priesemuth et al. (2014)
supported that having an abusive supervision climate affects individual and group as a
whole that influences employees’ performance, health status, and even social
interactions. The negative effects of abusive supervision can cost $24 billion for many
business leaders annually (Henle & Gross, 2014).
Moreover, many researchers successfully studied antecedents and consequences
of abusive supervision. Some antecedents are supervisor-level factors such as (a) abusive
supervision experiences from previous managers, (b) perception of injustice, (c) work
stress, (d) emotional intelligence, and (e) perceived deep-level dissimilarity with
subordinates (Rong & Jiang, 2014). To address the issue of abusive supervision, Chan
and McAllister (2014) suggested that supervisor and subordinates must have training to
know what behaviors need to accept or not and what behavior requires reporting to a
higher authority. Another suggested approach is to have management performance
system that allows reporting of abused behavior or establish hotlines to report any
observed behavior (Chan & McAllister, 2014). The next factor of job dissatisfaction is
interpersonal relationships.
Interpersonal relationships. The interpersonal relationships are personal
relationships between two or more people that develop within the organization (Gkorezis
& Petridou, 2012). The relationships occur when both parties expect something in returns
56
(Armstrong & Taylor, 2014). Interpersonal relationships include employee-employer
relationships, employee-supervisors relationships, and employee-peer relationships.
Employee-employer relationships. Baron and Kreps (2013) described
employment as a relational contract between employee and employer where social
relationship and economic factors exist for the benefits of both parties. Armstrong and
Taylor (2014) stated that employment relationship has interconnections between
employee and employer through informal contract. As described by Armstrong and
Taylor, informal contract is a psychological contract, where both parties have perceived
assumptions and expectations from each other. The basis of an employer-employee
relationship is the employees render their skills, effort, and knowledge in favor of salary
or wages provided by the employer (Armstrong & Taylor, 2014).
The employment relationship includes value, because the development and
application of HR process, policies, and procedures depend on this employment
relationship (Armstrong & Taylor, 2014). Expressing what both parties need or not to
have a productive and rewarding relationship is also part of employment relationship
(Armstrong & Taylor, 2014). To achieve a productive and rewarding relationship,
Armstrong and Taylor (2014) suggested that managers must communicate the company
policies, where managers must implement the rewards system with justice and
consistency.
On the other hand, understanding the factors that influence employees’ behavior
makes the employment relationship effective and successful (Baron & Kreps, 2013).
Expectation and value are also some factors that affect employees’ behavior (Armstrong
57
& Taylor, 2014). Armstrong and Taylor (2014) described expectations as how people
learn to expect their behavior and others behavior and values as people beliefs of what is
important, which are classifications of personal characteristics.
In economic situation, however, the employee-employer relationship becomes a
significant factor to implement the mission and vision of many business leaders and to
fulfill the needs of the employees. Employee and employer in an economic view share
the same risks, financially and non-financially (Baron & Kreps, 2013). Both parties
contribute their assets to satisfy their demands, and one party affects another party (Baron
& Kreps, 2013). Therefore, employee and employers must emphasize the critical
purposes of the business relationships. Without one party, common goals are not
achievable.
Employee-supervisor relationship. The employee-supervisor relationship is a
core relationship that develops inside the organization (Gkorezis & Petridou, 2012). A
manager’s role is vital to the success of the employees (Gkorezis & Petridou, 2012).
A positive relationship with the supervisors can influence a positive attitude towards the
employees, increasing employee competence to execute the job. Supporting the
employee-supervisor relationship can affect customer relationship as well (Gkorezis &
Petridou, 2012). Often, employees prefer supervisors who are considerate, competitive,
honest, and fair (Ünal, 2013). Without perceived support from their superiors, employees
become powerless and irresponsible in performing the assigned tasks (Gkorezis &
Petridou, 2012). Additionally, previous different research reviews revealed that leader-
member exchange relationship is critical because it directly affects job performance,
58
organizational commitment, and job satisfaction (Gkorezis & Petridou, 2012). Thus,
understanding the roles of the employee and supervisor to make the relationship works as
expected may lead to successfully meeting their common goals and objectives.
Employee-peers relationship. The relationship with peers is also important to
employees, because this relationship influences employee motivation, employee well-
being, and mental health (Gkorezis & Petridou, 2012). With healthy relationship and
interactions among peers, employees enhance their personal power, competence, and
self-control. Positive relationship with peers can also increase employee autonomousness
and job initiation.
In addition, employee-coworkers relationship is critical in relationship with
turnover intention and actual turnover (Tews, Michel, & Ellingson, 2013). With high
quality interpersonal relationship, employees and co-workers can minimize the turnover
intention resulting in increased employee retention (Tews et al., 2013). Developing
extensive and high quality relationship with management and subordinates inside the
organization can increase attachment and job embeddedness as well (Tews et al., 2013).
Furthermore, relationship with coworkers can help reduce job overload, stress, and
burnout because coworkers can support instrumentally and emotionally, resulting to
reduced turnover intention and increased employee stay. Using 188 samples of entry-
level employees from restaurants national chain, study findings revealed that coworker
support has significant influence to turnover (Tews et al., 2013). Conclusively, managers
must emphasize the importance of the employee-peers relationship to increase their job
engagement and participation. Other factor of dissatisfaction is working conditions.
59
Working conditions. Under the Occupational Safety and Health Act 1970,
employers’ responsibility is to maintain a safe and healthy workplace for employees
(McSweeney-Feld & Rubin, 2013). The Occupational Safety and Health Administration
(OSHA) clearly and strongly supported the act of 1970 (McSweeney-Feld & Rubin,
2013). The importance of having a good working environment is vital to the success of
the employees (AlBattat & Som, 2013; Leip & Stinchcomb, 2013). A safe, healthy, and
friendly environment is what the employees perceive or need from the organization (Matz
et al., 2013). In addition, when working condition is good managers can motivate
employees to work with dedication, commitment, and job satisfaction (AlBattat & Som,
2013; Leip & Stinchcomb, 2013; Matz et al., 2013). When employees feel safe, employee
turnover decreases (Stinchcomb & Leip, 2013; Yang, Liu, Huang, & Zhu, 2013).
On the contrary, when employees who feel stressed within the work environment
because of job overload (lack of staff), unfair treatment, and lack of organizational
support create employee low satisfaction and commitment, resulting to increased
employee turnover (Jung & Kim, 2012; Stinchcomb & Leip, 2013; Yang et al., 2013).
Ryan et al. (2011) supported that feeling stressed and feeling burnout increase the
intention to leave among the fast food workers working in international fast food chain in
Malaysia. AlBattat and Som (2013) noted that the poor environment is a source of
employees’ dissatisfaction increasing the number of turnover intention. Moreover, work
environment and job satisfactions are the influential factors to voluntary turnover than
age, gender, and race (Leip & Stinchcomb, 2013). The quality of employment affects the
60
employees’ satisfaction at the workplace, which influences employee retention (Lee &
Way, 2010). Other working environment factor is employee fairness.
Human resource management practices such as employee fairness affects public
service motivation and business performance (Giauque, Anderfuhren-Biget, & Varone,
2013). Treating employees with justice can reduce employee turnover (Stinchcomb &
Leip, 2013). Injustice practices toward employees may contribute to turnover intention to
actual turnover (AlBattat & Som, 2013). The organization managers who focus on the
employees’ welfare or employees’ welfare with objective fulfillment increase the level
safety climate and reduce safety accidents (Colley, Lincoln, & Neal, 2013). In contrast,
managers who focus on a formal process and procedures or formal process and
procedures with objective fulfillment, decrease level safety climate and increase safety
accidents (Colly et al., 2013).
Effects of positive working conditions. Michel, Kavanagh, and Tracey (2013)
reported that work conditions affect the employee motivation, performance, and intention
to leave directly. Positive work climate produces a high level of employee motivation and
performance, which affects the customer service relationship (Michel et al., 2013). Also,
a positive working environment attracts employees to stay with the organization, which
influences employee turnover (Vasquez, 2014). A work climate with employee respect,
recognition, and appreciation reduces employee turnover rates (Stinchcomb & Leip,
2013).
As suggested by Cherian and Jacob (2013), a workplace must be free from any
physical distractions that promote work stressors and low-team spirit. Cavanagh et al.
61
(2013) added that a safe and healthy workplace can foster positive participation
(Cavanagh et al., 2013). With a safe and healthy work environment, employees feel
satisfied with the jobs resulting to a negative employee turnover (Matz et al., 2013).
Therefore, fostering positive work environment can minimize employee turnover
(Stinchcomb & Leip, 2013).
On the other hand, effective and efficient operational management strategy
produces positive responses from customers such as loyalty and satisfaction (Lee, Lee, &
Kang, 2012). Lee et al. (2012) found that high-performance work systems affect
employees’ attitude towards the job that impact service quality. Kuo (2013) noted that the
trust is a significant value that promotes knowledge-sharing experiences between
employer and employees inside the organization. Thus, positive relationship with trust
inside the workplace is critical. However, organizations with strong group orientations do
not affect the organizational operation regardless of high-turnover rate (Mohr, Young, &
Burgess, Jr., 2012).
Effects of negative working conditions. Some of the determinant factors of the
turnover intentions are emotional exhaustion (Choi, Cheong, & Feinberg, 2012), burnout
(Jung & Kim, 2012), and job stress (Jung & Yoon, 2014). Emotional exhaustion occurs
when an individual feels exhausted with psychological and emotional demands (Cho et
al., 2013). Emotional exhaustion also occurs when employees feel overwhelmed at work
with numerous demands from managers to customers (Cho et al., 2013). Cho et al. (2013)
found that employee emotional exhaustion reduces the degree level of employees’ job
62
satisfaction. Pressure at work contributes to employees’ unhappiness feelings (Van der
Meer & Wielers, 2013).
In addition, perceived support whether supervisors or organizational support,
found no effect on employees’ emotional exhaustion (Campbell, Perry, Maertz, Allen, &
Griffeth, 2013). Jung and Kim (2012) also noted that having no supportive work
environment, employees are more likely to feel exhausted emotionally, promoting
employee burnout. Employees with burnout often result in having less commitment with
the organization resulting in higher turnover intention (Jung & Kim, 2012). Emotional
exhaustion however does not affect the employee commitment directly (Campbell et al.,
2013).
Moreover, other research results revealed that emotional exhaustion is a mediator
between customer verbal aggression and intention to leave (Li & Zhou, 2013). Emotional
exhaustion is a part of employee burnout (Choi et al., 2012). Cho et al. (2013) agreed and
suggested that managers must conduct an employee survey regularly to determine their
performance development and psychological welfare to minimize exhaustion. In addition,
focusing on employees’ emotions besides performance can assist organization minimizes
the turnover rates, and cost expenses (Cho et al., 2013).
On the other hand, Campbell et al. (2013) noted that support through fair
treatment with respect and dignity helps employees avoid the emotional exhaustion.
Thus, Karatepe (2013) suggested that the organization must support the employees to
balance responsibilities between work and family. As a result, employees reduce the
63
experiences of exhaustion at work and organizational managers help retain skilled
workers (Karatepe, 2013).
Furthermore, Campbell et al. (2013) defined burnout as a component of
exhaustion where individual feels overwhelmed with job demands. The cost of employee
burnout reveals higher than $300 billion annually for U.S. corporate businesses
(Campbell et al., 2013). The determinants of employees’ burnout were family and work
roles, social support, justice in policies, and other personal matters (McCarty & Skogan,
2013). Burnout also affects the health of the employees, physical, and psychological
(Campbell et al., 2013). Besides employees’ health, burnout impacts employee
performance, motivation, and may accelerate the rate of employee turnover (McCarty &
Skogan, 2013). The commitment of the employees toward the organization is also at risk,
which promotes higher turnover (Campbell et al., 2013). Employees feel work burnout
when they do not feel the supportive environment, causing employees not to commit to
the organization, which in turn lead to leaving their jobs intentionally (Jung & Kim,
2012).
In contrast, work overloads can cause employee’s emotional exhaustion affecting
the job embeddedness and employee’s performance negatively, which also affects
customer service quality (Karatepe, 2013). Van Dam et al. (2013) found that the
antecedents of perceived work pressure include emotional and physical demands. Jung
and Kim (2012) also agreed that work overload contributes to employee emotional
exhaustion that leads to employee burnout, which reduces employees’ commitment
resulting in high turnover intention. Using regression analysis of data from 309 customer-
64
contact hotel employees in the United States, the study findings revealed that burnout is a
mediating factor of employees’ performance that affects the business profitability and
growth (Lee & Ok, 2014).
Additionally, accidents occur in the work environment because of lack in
following rules and regulations and safety measure precautions (Dahl & Olsen, 2013).
Work injuries and illnesses occur, which promotes job stress, job dissatisfaction, and
intention to leave for employees (McCaughey, DelliFraine, McGhan, & Bruning, 2013).
Employee turnover also increases when employees get hurt physically because of the job
responsibilities and lack of organizational commitment (Brewer et al., 2012). A poor
working condition affects the employees’ job satisfaction (Kumar et al., 2013). As
suggested by Kumar et al. (2013) an overall improvement in working environment
contributes to positive results. Added by McCaughey et al. (2013) business managers
must increase their positive engagement in developing safety and healthy work
environment to enhance the safety climate perception and to promote positive results for
employees. These precautionary measures can minimize incidents from happening,
leading to increase employee retention rates as decreases employee turnover rates.
Furthermore, AlBattat and Som (2013) also discovered that bad working
environment encourages employees to leave the current job intentionally before the
actual turnover will occur. Matz et al. (2013) noted that the work environment affects
employee job satisfaction and commitment, leading to employee turnover intention. Matz
et al. suggested providing a better workplace because satisfaction and commitment
depend on it. An effective approach with care for workplace learning can produce
65
important benefits for employees and organization (Teare, 2011). Therefore, safety
compliance requires leadership involvement, directly or indirectly where employees’
competence, role clarity, and follow-up contractors influenced leadership effectiveness
(Dahl & Olsen, 2013). Managers’ daily participations at workplace also influence the
level of safety compliance (Dahl & Olsen, 2013).
Employee performance and employee turnover have strong relationships when
safety variable is a mediator (Hancock, Allen, Bosco, McDaniel, & Pierce, 2013). Poor
well-being at the workplace is a determining factor for job stress resulting to job
dissatisfaction but not commitment (Sang, Teo, Cooper, & Bohle, 2013). Employees with
job dissatisfaction can perceive that organizational leaders do not care about their well-
being that demotivates them in becoming less committed to the organization (Sang et al.,
2013). AlBattat and Som (2013) noted that employees working with stress at the
workplace are a significant contribution of turnover intention to actual turnover. Sang et
al. (2013) recommended that business leaders must implement strategic approaches that
reduce the job stress to increase the employee commitment, job satisfaction, and health
status effectively.
Salary. Mello (2006) described compensation as an effective tool to entice
applicants, maintain employees, and optimize employee’s performance in meeting
organization’s goals and objectives. Larkin, Pierce, and Gino (2012) also characterized
compensation as a strategic key to allure and motivate employees where the influence to
co-workers and business performance is apparent. Employee compensation is important
because it can affect job satisfaction, motivation, performance, retention, and turnover
66
intent (Misra et al., 2013). With proper implementation of compensation structure,
competitive edges can achieve effectively (Misra et al., 2013). Nyberg (2010) added that
a periodic assessment and modification of compensation packages entice employees to
improve the organization’s bottom line of making a profit.
On the contrary, although high performers promote company innovation, study
findings indicated that employee compensation has an indirect relationship with
organizational innovation (Yanadori & Cui 2013). Misra et al. (2013) mentioned,
however that compensation has a direct impact to employee turnover intention, job
satisfaction, and intention to stay. Having a fair compensation and strategic compensation
structure helps achieve organizational goals and objectives (Misra et al., 2013). Brewer et
al. (2012) added that regardless of job responsibilities, turnover rate decreases when
employees receive high compensation and overtime pay. High performing employees
with high compensation will likely to stay with the organization compared to employees
who have less salary and benefits (Carnahan, Agarwal, & Campbell, 2012).
Furthermore, employee’s base pay is one of the components of the compensation
system (Mello, 2006). The classification of pay is an extrinsic reward, which derived
from the employees’ work outcomes (Wakefield, Curry, Mueller, & Price, 2012).
Extrinsic rewards, incentives, and penalties influence the employee’s behavior (Pereira &
Anderson, 2012). Herzberg (1974) and Herzberg et al. (1959) treated salary as a hygiene
factor that affects employee job dissatisfaction. Kwon (2014) also supported that the pay
is a tool used to motivate employees.
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Positive effects of base pay. The pay performance appraisal is a tool used to
evaluate the performance of the employees (Mulvaney et al., 2012). Mulvaney et al.
argued that base pay may increase depending on the employees’ performance. Individual
appraisal affects motivation and business performance positively (Giauque et al., 2013).
O’Halloran (2012) noted that pay related performance is an approach used for
employees’ incentive rewards improvement to increase employee performance. Larkin et
al. (2012) added that performance based-pay separates the good performers from the bad
performers. However, pay related performance (PRP) indirectly influences the turnover
(O'Halloran, 2012).
On the other hand, in a pay system, managers can increase employees’ effort and
motivation that affects’ business profitability (Larkin et al., 2012). Employee pay requires
annual evaluation (Kumar et al., 2013). With periodic assessment and modification of
compensation packages, employers can entice employees to improve the organization’s
bottom line of making a profit (Nyberg, 2010). Extrinsic rewards, incentives, and
penalties influence employee behavior (Pereira & Anderson, 2012). Increased employee
salary and wages help improve employee morale, productivity, and performance,
resulting to a positive business financial performance (Kwon, 2014; Zedelius et al.,
2012). Having effective employee salary and wages can also affect the immediate job and
future performance of the employee (Zedelius et al., 2012).
Additionally, high-employee pay prevents future employee turnover (Choi et al.,
2012). High-employee salary increases employee job performance, job satisfaction, and
reduces employee turnover (Linz & Semykina, 2012; Nitesh, NandaKumar, & Asok
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Kumar , 2013). Drawn from study findings, Nitesh et al. (2013) said that pay has a direct
contributions to perceived organizational support, employees’ commitment with the
organization, and employee retention. Porter and Steer (1973) noted that pay is always a
significant factor to turnover, which is contradicted to Mobley et al. (1979).
Moreover, using a case study in retail stores featuring front employees with open-
ended questions and secondary resources, Stringer et al. (2011) noted that establishing
justice in employees’ pay, the employee job satisfaction increases (Stringer et al., 2011).
Larkin et al. (2012) also emphasized that once employees have low-job satisfaction
because of inequity regarding pay, performance decreases and absenteeism increases,
affecting the turnover rates. The study findings from Morgan, Dill, and Kalleberg (2013)
indicated a positive correlation of intrinsic (meaningful tasks) and extrinsic (wages and
benefits) motivation factors to job satisfaction, but only the latter have a positive impact
to turnover intention. Thus, managers must maintain the justice in pay to increase
employee satisfaction and job performance to reduce turnover intention.
Negative effects of base pay. Employee’s salary and wages are factors that
influence job dissatisfaction (Islam & Ali, 2013; Linz & Semykina, 2012; Teck-Hong &
Waheed, 2011). Tews et al. (2013) concluded that salary is less important than job
embeddedness, particularly in the hospitality industry where young workers prefer to stay
when positive relationship with co-workers and managers are high. Additionally, salary
and compensation affect the employee performance (Chen et al., 2013). Other research
results indicated, however that pay factor does not affect employee turnover (Smith,
Wareham, & Lambert, 2013; Zhoutao, Jinxi, & Yixiao, 2013).
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In contrast, using different model theories, the connotation of the fast food
restaurants for being a low-wage sector and low-skilled labor market where workers are
primarily students with no experience or less experience influences employee turnover
(Kwon, 2014). Dissatisfaction in salary leads to turnover intention, which is a source of
employee turnover (Choi et al., 2012; Hwang, Lee, Park, Chang, & Kim, 2014; Nitesh et
al., 2013). AlBattat and Som (2013) agreed stating the low salary is the antecedent of
turnover intention before the actual turnover. The level of pay affects the employees’
emotional exhaustion that leads to employee burnout and reduced commitment with the
organization, which influences high-employee turnover intention (Jung & Kim, 2012).
On the contrary, Chang et al. (2013) noted that employees favor a good
relationship between coworkers and leaders compared to pay level. By contrast,
Bhatnagar (2014) noted that aside from pay, recognition, appreciation, and training
encourage skilled employees to stay. Thus, managers must not only assess pay factor, but
also other factors to reduce employee job dissatisfaction.
Employee Turnover Intention
Turnover intention is a process of leaving the current job or willingness of the
employees to leave their current jobs (Chang et al., 2013; Mobley, 1977). The behavioral
intentions can lead to actual behavior (Hofaidhllaoui & Chhinzer, 2014). A turnover
intention is one of the best predictors of actual employee turnover (Christian & Ellis,
2014; Feng-Hua, You-Shiun, & Kun-Chih, 2014). Mobley (1977) said turnover intention
is the last stage before the actual turnover takes place, which is the reason why turnover
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intention is the focus for the study. Actual turnover include self-assessment and outcome
evaluation associated with leaving the current job (Stanley et al., 2013).
In addition, thinking of quitting can occur when an employee feels dissatisfied
with the job (Mobley, 1977). Before the intention to leave happens, the employee starts to
evaluate the factors that affect their decision process (Mobley, 1997). Some of the factors
are the costs of quitting, availability of the job market, and the benefits associated with
leaving the current job (Mobley, 1977). If employees think that costs overweigh the
benefits, absenteeism and other negative behaviors toward the company may occur. If
employees found the alternatives favorable for the current jobs, then intention to quit
occurs, leading to actual quitting (Mobley, 1977).
In the food service industry, more than 100 managers plan to leave their jobs
(Ghiselli, La Lopa, & Bai, 2001). Out of hundred food service managers, 50 service
managers left because of salary and benefits (Ghiselli et al., 2001). In their study
findings, Ghiselli et al. (2001) found that intent to leave for a short period has a positive
relationship with intrinsic job satisfaction. Herzberg (1974) and Herzberg et al. (1959)
mentioned that intrinsic job satisfaction derives from the work itself, as opposed to
extrinsic job satisfaction, where employees did not have control. In addition, intrinsic job
satisfaction has a long-term result in terms of employee performance as compared to
extrinsic job satisfaction (Herzberg, 1974; Herzberg et al., 1959). Added by Ghiselli et al.
(2001), when the intrinsic job satisfaction is high among employees, the employees are
more likely to stay with the organization.
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By contrast, Van Dam et al. (2013) found that age, social support, and
developmental opportunities are antecedents of turnover intention. Ghiselli et al. (2001)
supported the research findings of Van Dam et al. that age is a predictor of intention to
leave. Consequently, age is a contributing factor why fast food turnover increases
dramatically.
Wyld also found that job embeddedness influences employee retention within the
organization. Job embeddedness occur when employees feel satisfaction with their salary,
benefits, and relationships with others (Wyld, 2014). Job embeddedness is a recognizable
force that encourages employees to stay within the organization according to Tews,
Michel, Xu, & Drost, (2015). Other variable that affects turnover intention is job stress
(Jung & Yoon, 2014). The sources of job stresses include (a) dissatisfaction in pay, (b)
lack of support from the management, (c) organizational culture, and (d) unfair treatment
(Hwang et al., 2014). Among job stresses, however, unfair treatment leads to strong
turnover intention (Hwang et al., 2014). Furthermore based on the U.S government IT
employees, Kim (2012) found that (a) promotion and advancement opportunities, (b)
training and development, (c) supervisory communications, (d) pay and reward
satisfaction, and (e) family-friendly policies are determining factors of turnover
intentions.
As suggested, focusing on employee job satisfaction and commitment may reduce
employee turnover intentions (Ryan et al., 2011). When employee job satisfaction is high,
the employee commitment is also high, which influence employee turnover intention
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(Ryan et al., 2011; Wyld, 2014). According to Mignonac and Richebé (2013),
minimizing the turnover intention helps reduce the employee voluntary turnover.
In contrary, in behavioral psychology and management literature, researchers
used turnover intention as a dependent variable for job satisfaction (Hofaidhllaoui &
Chhinzer, 2014). In examining the relationship between job satisfaction, and turnover
intention for knowledge workers (engineers) in France, Hofaidhllaoui and Chhinzer used
a quantitative correlational study. From study participants of 1,980, only 548 (27.7%)
participants responded, where 481 participants completed the survey. To measure the job
satisfaction and the turnover intention variables, Hofaidhllaoui and Chhinzer applied the
previously-validated Minnesota Satisfaction Questionnaire (MSQ) developed by Weiss et
al. in 1967 and the scale of Rusbult et al. in 1988 with a 5-point Likert-type scale (1 =
strongly disagree and 5 = strongly agree).
The collected data included analysis using regression analysis. Hofaidhllaoui and
Chhinzer (2014) found that job satisfaction (supervisor relationship and employee work)
had significantly no relationship with turnover intentions (r = –0.30, p < 0.01, r = –0.30, p
< 0.01). However, the variance in turnover intention was 28.4% associated with job
satisfaction with work and job satisfaction with supervisor (Hofaidhllaoui & Chhinzer,
2014). The implications of the study are that satisfaction with work and satisfaction with
one’s supervisor are two different aspects of job satisfaction. Although satisfaction has no
relationship with turnover intention, when employees feel dissatisfied with job, employee
turnover intention occurs regardless of the perception within the organization
(Hofaidhllaoui & Chhinzer, 2014).
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However, Hofaidhllaoui and Chhinzer (2014) suggested that improving
satisfaction with supervisor is critical in retaining knowledge workers; thus, management
must secure and reward the effective supervisors and managers. Employers must also
train employees to remain competent in their assigned tasks and be satisfied with their job
to avoid leaving the job to reduce the turnover according to Hofaidhllaoui & Chhinzer,
2014).
Employee Turnover
Employee turnover has been a major topic for many personnel researchers,
behavioral scientists, and management practitioners (Mobley et al., 1979). Even in
private business sectors such as hospitality, tourism, and the fast food industry, employee
turnover becomes a main concern for many business leaders because of the costs
involved, both direct and indirect costs (Pearlman & Schaffer, 2013). Examples of direct
costs are recruitment, hiring, and training costs, where indirect costs include overtime and
customer dissatisfaction (Pearlman & Schaffer, 2013; Ryan et al., 2011).
Employee turnover also affects the health care industry, where costs are high that
affect the workplace safety and quality of service (Li & Jones, 2013). In the restaurant
industry to include fast food restaurants, employee turnover is high, approximately more
than 100% as compared to other industries (Batt et al., 2014; Perez & Mirabella, 2013;
Ryan et al., 2011, Wyld, 2014). Tews et al. (2014) found that an entry-level position has
the highest turnover rate in the hospitality industry. In the United States, researchers
found non-managerial positions have higher turnover rates in the fast food industry,
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because of poor salary, working conditions, and job boredom for repeat job process
(Ryan et al., 2011).
On the other hand, having high employee turnover rates, business leaders are
forced to deliver better customer service and better financial performance for their
stakeholders (Wyld, 2014). Hancock et al. (2013) also noted that employee turnover may
affect business performance including (a) financial status, (b) customer services, (c)
recruitment, (d) selection costs, and (e) work environment (safety and quality). Turnover
is expensive and distracting for organizational managers, because recruitment, selection,
and training for new employees can occur (Tews et al., 2014). As suggested, leaders must
know what factors associated with turnover to reduce these negative effects (Memon et
al., 2014).
In contrast, Ahmed and Kolachi (2013) emphasized that employee turnover is
healthy and necessary for the business, welcoming the arrival of new employees who
contribute and share new ideas to lead to business innovations. Conversely, Ahmed and
Kolachi noted that the turnover is not good for the organization, because of the negative
effects on the business, financially and non-financially. In addition, having high-turnover
rates endanger investments of stakeholders resulting in a negative business financial
performance (Bauer, 2012).
Causes of employee turnover. Employee turnover can occur in two different
ways, voluntary and involuntary (Mobley et al., 1979; Phillips, 2012). Voluntary turnover
occurs when an employee leaves the organization intentionally, whereas the involuntary
turnover happens when an organization forces an employee to resign because of poor
75
performance (Mobley et al., 1979; Phillips, 2012). Memon, Salleh, Baharom, and Harun
(2014) noted that this voluntary turnover reduces employee’s morale and productivity.
Sources of voluntary turnover are (a) lack of employee recognition, (b) feeling of
isolation, as well as (c) poor leadership style of a manager (Bauer, 2012). Boyar, Valk,
Maertz, and Sinha (2012) added that the managerial support and work-related stress are
primary reasons why employees are voluntarily leaving the organization. Aside from
human management practices, employees constantly look for alternative jobs (Direnzo &
Greenhaus, 2011). Other causes of voluntary employees include (a) parenting obligations,
(b) other job opportunities, and (c) educational pursuits (Hom, Mitchell, Lee, & Griffeth,
2012). Vanderpool and Way (2013) argued that work-balance is the determining factor
for intention to leave, leading to voluntary turnover. Grissom (2012) noted that
incompetent managers can affect the employees’ performance, resulting in employee
voluntary withdrawal.
Furthermore, breach of contract is one of the major causes of voluntary turnover,
because of the loss of trust and faith of the employees toward the relationship with
managers (Clinton & Guest, 2013). When a reciprocal exchange relationship is missing
and not in balance, breach of contract occurs (Clinton & Guest, 2013). The breach of the
psychological contract can also happen when the situations are beyond the control of the
employer and employee referred to as the external locus of control (Hermida & Luchman,
2013). Breach of contract can cause the loss of the employee-employer relationship, loss
of commitment, and trust issues (Benard & Chepngetich, 2013).
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Other cause of voluntary withdrawal is lack of coworker support. Employees
decided to leave their current jobs because of coworker instrumental support (Tews et al.,
2014). Coworker instrumental support occur when employees cannot do the jobs
independently, which demonstrates (a) the employees’ incompetence, (b) an inferiority
complex, and (c) the lack of self-efficacy (Tews et al., 2014). Using data from 188
servers in restaurant chain, Tews et al. (2013) examined the effects of coworker supports
on employee turnover, emotionally and instrumentally. Study findings showed that the
instrumental support from coworkers directly impacts the turnover rate (Tews et al.,
2013). Instrumental support however provides a positive result if used to focus on
teamwork goals (Tews et al., 2014).
Kim (2012) suggested that in combating voluntary employee turnover, managers
must focus on the following factors (a) training and development, (b) pay and reward
satisfaction, (c) promotion and advancement opportunities, (d) supervisory
communications, and (e) family-friendly policies. Training is critical to help employees
to be competent in their job roles, which contributes to positive performance results
(Haines III & St-Onge, 2012). Vanderpool and Way also recommended that work-family
balance must be a priority by managers. Moreover, Ghiselli et al. (2001) suggested that
managers must increase employee job satisfaction to minimize the turnover. Determining
and addressing the determinants of the employee turnover help business leaders’ succeed
in their business operations according to Subramanian and Shin (2013).
Impacts of employee turnover. The negative impact of employee turnover is
costly to the organization (Pearlman & Schaffer, 2013; Perez & Mirabella, 2013). Bauer
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(2012) asserted that having increased voluntary turnover puts the stakeholders’
investment and benefits at risks. As a result, stakeholders and shareholders are unable to
meet their business financial goals. With training costs related to employee turnover
alone, the business owners spend $126 billion yearly (Bauer, 2012).
Tews et al. (2013) also agreed that the turnover is expensive and can disrupt
business operation because of the repetitive process in hiring and training employees. The
costs of the operation affect the financial stability of the organization (Pearlman &
Schaffer, 2013; Perez & Mirabella, 2013; Selden, Schimmoeller, & Thompson, 2013).
Expensive turnover challenges HR management of staff focusing on retaining the high
performer (Pearlman & Schaffer, 2013; Perez & Mirabella, 2013; Soltis, Agneessens,
Sasovova, & Labianca, 2013).
Aside from the costs involved, employee turnover can also affect employees’
morale and productivity (Huffman, Payne, & Casper, 2013). López and Sune, (2013)
noted when employee turnover occurs, employee performance productivity decreases.
Employee turnover can disrupt the core business operations especially when the high
performers leave, where business success depends on them (Tzabbar & Kehoe, 2014).
Kwon and Rupp (2013) agreed stating that high performers leave the organization
regardless of pay and benefits received from the organization. By contrary, according to
Hancock et al. (2013) employee turnover does not affect the organizational performance
directly. To reduce employee turnover costs financially and nonfinancially, managers
must focus on factors that increase employee motivation and job satisfaction.
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Employee Commitment
Organizational commitment includes emphasis on the employees’ sense of unity
and shared values with the organization, focusing on the calculative aspect of employee-
employer relationship (Eisenberger et al., 1990). Employee commitment is a determinant
factor of turnover intention to actual turnover (Campbell et al., 2013; Stanley et al.,
2013). Islam, Ahmad, and Ahmed (2013) added that employee commitment is a vital role
between the organizational learning culture and turnover intention. As recommended
strategies, organizational managers must foster a supportive environment and learning
culture to reduce employees attempting leaving the job according to Islam et al. (2013).
Additionally, Lee and Chen (2013) discovered that the employees’ biographical
characteristics as age and years of services influence job attitude and commitment. Lee
and Chen added that employee motivation was a vital role in employees’ success. When
motivation increases, an employee commitment also increases. To motivate employees to
commit, Lee and Chen suggested increasing employee salary, providing job security, and
supporting the employees. These suggestions are critical to increase employee positive
job attitude, commitment, and to maintain skilled workers (Lee & Chen, 2013).
Other researchers concluded that employee motivation has a significant
relationship with the employee’s commitment resulting in positive performance
(Battistelli, Galletta, Portoghese, & Vandenberghe, 2013). Motivational factors can
influence the attitude and commitment of the employee, resulting in better job
performance (Battistelli et al., 2013). Employees with satisfied monetary rewards have a
higher commitment to the organization (Nitesh et al., 2013). When employees feel
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satisfied, their job commitment increases and employee turnover decreases (Brewer et al.,
2012).
Smith and Kumar (2013) added that corporate social responsibility (CSR) has a
positive impact on employees’ organizational commitment. CSR makes the relationship
strong between employee and employer that foster employee loyalty (Smith & Kumar,
2013). Further results of the study indicated that when employees perceived strong CSR,
employees’ affective commitment and continuance commitment increase, resulting in
increased employee loyalty (Smith & Kumar, 2013). In conclusion, employers focusing
on CSR can enhance employees’ organizational commitment and loyalty suggested by
Smith & Kumar (2013).
Study findings indicated that career commitment directly affects the self-efficacy
of the employees as well (Bang et al., 2013). High levels of self-efficacy have a high
level of career commitment (Bang et al., 2013). Employee commitment develops when
an individual feels motivated and satisfied with the job (Bang et al., 2013). Job equality
affects the employee commitment and job performance positively (Misra et al., 2013;
Suliman & Al Kathairi, 2013).
Employee compensation and recognition based on job performance increase
social involvement and commitment (Misra et al., 2013; Suliman & Al Kathairi, 2013).
Human resource practices affect the commitment and loyalty of the employees positively
(Kehoe & Wright, 2013). Based on the examination of Chong and Monroe (2013), an
employee with a lack of commitment has the intention to look for an alternative
opportunity outside of their organization. By contrary, according to Jehanzeb et al.
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(2013), employee commitment has no relationship with employee turnover, but training
directly affects the commitment.
Moreover, the three components of organizational commitments are (a) affective,
(b) continuance, and (c) normative commitment (Jung & Kim, 2012). Affective
commitment is an employees’ emotional attachment to the organization (Stanley et al.,
2013). Continuance commitment refers to employees’ attachment based on instrumental
considerations. Normative means employees’ commitment out of moral obligation to the
organization (Stanley et al., 2013). All components of organizational commitments are
relative to each other (Jung & Kim, 2012).
Xerri and Brunetto (2013) found that employees with affective commitment
promotes innovation in the workplace, which fosters an effective business environment.
However, affective commitment does not affect the turnover intention or actual turnover
(Stanley et al., 2013). Using multi regression analysis, Garland, Hogan, Kelley, Kim, and
Lambert’s (2013) study findings also indicated the insignificant relationships between
affective commitment, absenteeism, and intention to leave.
Furthermore, utilizing the affective events theory, Craig, Allen, Reid,
Riemenschneider, and Armstrong (2012) found that the affective organizational
commitment (AOC) is a mediating factor between mentoring and employee turnover.
Employees who had positive involvement and mentoring increase the AOC, minimizing
the employee turnover (Craig et al., 2012). Some organizational managers fail to
motivate the employee to commit to the organization, because employees have a low
level of involvement in the decision-making (Appelbaum et al., 2013; Hill, Seo, Kang, &
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Taylor, 2012). Allen, Ericksen, and Collins (2013) noted that as employee involvement
increases, employee commitment increases. Having high-employee commitment reduced
the chance of voluntary withdrawal, where at the same time increasing organizational
performance, profitability, and growth (Allen et al., 2013).
On the other hand, using hierarchical regression analysis, a role of the tradition
influences the AOC and other variables such as pay, autonomy, and supervision factors
(Newman & Sheikh, 2012). Employees understand the commitment with the organization
through cultural orientation (Niu, 2010). When supervision and autonomy level are low,
employee commitment is high, because of employee tradition (Newman & Sheikh, 2012).
When autonomy and satisfaction with supervision accelerate, the emotional level of
employees’ attachment with the organization is high (Newman & Sheikh, 2012).
In addition, continuance commitment of the employees provides no direct correlation
with employee absenteeism and turnover intention, after controlling the demographic
variables as gender, age, and tenure (Garland et al., 2013). As suggestions, Garland et al.
(2013) emphasized the importance of affective commitment, because of the significant
relationship with business and employee performances.
Employee Engagement
Employee engagement is vital to organizational success, because disengaged
employees affect the productivity, profitability, and sustainability of the organization
(Simon, 2013). Motivating employees to engage in sharing knowledge, as a team in work
environment is an issue that management faces (Hung, Durcikova, Lai, & Lin, 2011).
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Employee recognition and appreciation have also a direct relationship with work
engagement (Nyman et al., 2012).
Moreover, Choo et al. (2013) found that organizational practices, such as
communication, employee development, rewards, and recognition can affect the
employee engagement directly. Study findings indicated that organizational practices
influence employee engagement by 43.2% (Choo et al., 2013). Therefore, using
organizational practices effectively increase employee’s engagement and work
participation (Choo et al., 2013; Webster & Beehr, 2012).
Employee Retention
Employee retention and motivation challenge businesses owners, leaders, and
personnel in the hospitality industry (Arendt et al., 2012; Choudhury & McIntosh, 2012;
Namkung, Jang, & Choi, 2011; Pearlman & Schaffer, 2013; Steele et al., 2012). Even
retention in new employees is a problem for many businesses (Allen & Shanock, 2013).
Vasquez (2014) asserted that retaining employees helps improve business performance.
Knowing what factors or causes of employee turnover can assist employers to maintain
employees in the hospitality industry (Vasquez, 2014).
By using a phenomenological study, Vasquez (2014) indicated that management
support helps achieve employee retention. Allen and Shanock (2013) agreed that when
employees perceived the support of the organization, employees become committed and
content within the organization. Stumpf, Tymon Jr., Favorito, and Smith (2013) added
that intrinsic rewards (meaningfulness and voice) can influence the employees’ decision
to stay.
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Other findings indicated that satisfied employees will stay with the organization,
particularly employees who receive positive feedback from the customers concerning
their performance (Frey, Bayón, & Totzek, 2013). Consequently, satisfied employees
influence customer retention (Gounaris & Boukis, 2013). Ortlieb and Sieben (2012)
suggested evaluating the retention strategy based on the employees’ skills and
performances.
Transition
Section 1 includes the foundation of the study, background of the problem,
problem statement, and purpose statement. The foundation study focuses on the
background of the fast food industry. Background of the study involves the problems
faced by fast food leaders and employees caused by increasing turnover in the fast food
industry within the United States. The problem statement includes the hook, anchor,
general problem, and specific business problem, where the specific problem is the reason
why the research study takes place.
The purpose statement includes the purpose of the study, descriptions of research
method and design, population, setting, and the contributions of the study towards
business practices and social change. Other sections include the nature of the study,
research questions, hypotheses, conceptual framework, operational definitions,
assumptions, limitations, delimitations, significance of the study, and literature review.
The nature of the study includes descriptions of chosen methods and designs, and
the reasons for choosing the preferred method and design. The research question is the
central question provided in the quantitative correlational study that needs to address with
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reliable and valid processes, instruments, and research study. Hypotheses include
statements that pertain to the study variables to accept or reject the existence of the
variable relationship, and if the relationship does exist what is the extent of the
relationship.
The Herzberg’s motivational-hygiene theory is the theoretical framework for this
quantitative study. Definitions refer to terms used in this study. Assumptions involve
facts assumed true, but not verified. Limitations are the weaknesses of the study, while
delimitations are the strengths of the study. Significance of the study comprises of the
importance of the study to the business, how the results of the study contribute to the
business effective practices and to social changes. The literature review includes the
topics regarding the theoretical framework and study variables supported by different
views, perspectives, and opinions of the researchers from different fields.
Section 2 includes the purpose of the study, a role of the researcher, the
participants, methods and designs, population, sampling, and ethical research. This
section also describes the data collection process, study instruments, data collection
technique, data organization approach, data analysis, and validity of instruments,
processes, and study.
The purpose of the study includes method, design, population, setting, and social
impact. The role of the researcher is to ensure participants’ benefits overweigh
participants’ risks. Participants are employees currently working at fast food restaurants
in East Coast in the United States. Quantitative correlational method is used to address
the hypotheses using Pearson’s correlation coefficient and multiregressions analysis.
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Section 2: The Project
This section comprises the purpose statement, role of the researcher, descriptions
of participants, research method and design, population and a) sampling, b) ethical
research, c) instrumentations, d) data collection technique, e) analysis and study validity.
The intent of the purpose statement is to describe the chosen method, design, variables,
population, setting, and the implication for positive social change. The role of the
researcher emphasizes the importance of consent form and Belmont Protocol to protect
the participants from any harm. The research method and design includes descriptions of
method and design and the reasons why the chosen method and design outweigh the
others.
The targeted population consisted of fast food workers in U.S. fast food
restaurants. The population was recruited using a purposive nonprobabilistic sampling
method, in which the participants were specifically and nonrandomly selected. Per the
standard guidelines ethical research, I was responsible for ensuring the participants’
consent and communicating participants’ rights to decline the invitation to participate and
withdraw anytime. As the researcher, I was required to protect the anonymity of the
participants and secure participants’ data for safety within 5 years.
The instrumentation described in this chapter includes the job satisfaction survey
(JSS), intention to leave the job, and demographic scale. An Internet survey played a vital
role in collecting participants’ data. Pearson correlation coefficient and multiregression
serve as the statistical tools to accept or reject the hypotheses and to determine the
variance of employee turnover associated by job satisfaction and job dissatisfaction
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factors. Using pre-established psychometric scales and consistent recording, analyzing,
and interpreting data support the validity of the data.
Purpose Statement
The purpose of the quantitative correlational study was to examine the
relationship between the employee job satisfaction, employee job dissatisfaction, and
employee turnover intentions in the U.S. fast food industry. The employee job
satisfaction and dissatisfaction variables were taken from Herzberg et al. (1959). The job
satisfaction independent variables tracked were (a) achievement, (b) recognition, (c)
responsibility, (d) work-itself, and (e) advancement and growth. The job dissatisfaction
independent variables tracked were (a) company policy, (b) supervision, (c) interpersonal
relationships, (d) working conditions, and (e) salary. The dependent variable was
employee turnover intentions in the fast food industry.
The targeted population consisted of fast food workers throughout the East Coast
region of the United States. The population suited the needs for the study, because fast
food workers in lower-level management or non-managerial positions experienced high
turnover in the fast food industry. The implication for positive social change included
helping managers in the fast food industry reduce turnover intentions of their employees
by focusing on factors important to employees for which managers had control.
Role of the Researcher
My role as the researcher was to implement the informed consent process.
Informed consent is a process that protects participants from any harm, allowing them to
participate voluntarily (Judkins-Cohn et al., 2014). Informed consent in this study
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included the disclosure, capacity, comprehension, and permission request. Understanding
the process included meeting the expectations of the Walden Institutional Review Board
(IRB), as well as informing participations of the requirements needed for meeting and
completing the consent form (Judkins-Cohn et al., 2014; see Appendix H). A researcher
must be an advocate in the best interest of the participants (Judkins-Cohn et al., 2014).
Therefore, before starting the research participation, I explained to managers and
participants the nature of the study, purpose of the study, rights of the participants and my
responsibility to protect their identity and confidentiality. Ensuring participants
understand the informed consent process and the importance for maintaining the ethical
procedures of conducting the research may avoid any ethical and legal issues as
suggested by Judkins-Cohn et al. (2014).
Using the Belmont Report Protocol included description of the fundamental
ethical principles and guidelines in conducting research involving human participation
(U.S. Department of Health & Human Services [USDHHS], n.d.). Proper application of
research using human subjects must avoid ethical problems (USDHHS, n.d). The
fundamental ethical principles included respect of persons, beneficence, and justice
(USDHHS, n.d.).
Respect for persons included the acknowledgment of participants’ autonomy, as
well as providing protection for those participants incapacitated or immature (USDHHS,
n.d.). My responsibility was to respect participants’ views, choices, or ideas based on
participants’ judgments. As a sign of respect, I disclosed the nature of the research,
process, and instrument, as well as explain that a participant may withdraw at any time as
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suggested by Judkins-Cohn et al. (2014). The other fundamental ethical principle is
beneficence.
Beneficence in research involves optimizing the potential benefits and
diminishing the potential risks of the participants (USDHHS, n.d.). Preventing harm,
providing benefits, and balancing benefits against risks and costs are characteristics of
beneficence (Ferris & Sass-Kortsak, 2011; Judkins-Cohn et al., 2014). Appropriate
distribution of benefits, risks, and costs fairly is a trait of justice (Ferris & Sass-Kortsak,
2011; Judkins-Cohn et al., 2014). The principles are critical for informed consent process
and institutional review process to protect the rights of the participants and maintain their
safety during the survey participation (Judkins-Cohn et al., 2014). To meet the principle
of benevolence and nonmaleficence to optimize the benefits of the participants as
minimizing the danger of the participants as suggested by Judkins-Cohn et al. (2014), I
clearly specified and explained to managers and participants oral and written with flyers
and consent form that their participations were anonymous. Participants have rights to
decline the invitation to participate or withdraw anytime. Participations were anonymous
to protect their identity and confidentiality. In addition, data collected are stored with
encrypted password and lock for five years. Data will receive deletion after 5 years.
Another fundamental ethical principle is justice.
Justice included demonstration by ensuring that participants in the study
participated equally regardless of demographic background, capability, or ability
(USDHHS, n.d.). My target participants were invited equally regardless of gender,
religion, and educational attainment. Data came from employees who currently work in
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fast food restaurants in East Coast in the United States to avoid bias suggested by Gibson
and Fedorenko (2013). Gibson and Fedorenko also recommended that a researcher must
have a rigorous data collection process and reporting standards by using valid methods to
see different views of the researchers theoretically. Data collection started upon receiving
my Walden IRB approval number. After receiving the approval, I approached the fast
food restaurant managers asking permission for employees to participate. Receiving the
managers’ approval allowed me to approach the participants. Before signing the consent
form, the study process was giving to them explaining the nature of the study, purposes
of the study, rights of the participants, and my role. The benefits overweigh the risks to
avoid any ethical issues during research participations. The survey questionnaire used
was a psychometric scale with pre-established internal consistent reliability.
The targeted participants had no direct affiliation with my profession. I used
communication with fast food managers and the participants through social media and
used personal meetings to establish a neutral relationship. The research topic relates to
my business profession because employee turnover is one of the problems I face as a
business owner.
Participants
The selection of the most knowledgeable participants regarding the problem
statement was critical to this quantitative study, because the validity of the study results
depended on participants’ honest and accurate participation (Saunders, 2011). I selected
participants who represented the target population to avoid biases that might have
otherwise adversely affected the study findings, as suggested by Englander (2012) and
90
Saunders (2011). The eligibility criteria for study participants were to have (a) a full-time
or part-time job at a lower-level management or non-managerial position, (b) a minimum
age of 18, (c) be of either gender, and (d) be workers in fast food restaurants located in
the east coast of the United States.
To access participants, I conducted personal meetings with fast food managers for
franchises such as McDonalds, Burger King, KFC, Wendy’s, Taco Bell, and Subway that
were located on the East Coast of the United States and provided them with a copy of the
letter of cooperation (Appendix J). Meeting with these fast food managers allowed me to
discuss the purpose, nature of the study, rights of the participants, and measures to protect
the confidentiality and privacy of the participants. I also gave the fast food managers
copies of the participant invitation and participant reminder (Appendix K & L) to notify
employees about the importance of participating. Once these fast food managers
approved my request to conduct the research inside the facility at their convenience, I
then personally approached their employees to solicit their participation.
Prior to participation, further explanations about the purpose and nature of the
research study, rights of the participants, and measures to protect their identity and
confidentiality including answering participants’ questions, if arise, helped emphasize the
importance of employees’ participations. Participants answered survey questions through
Survey Monkey web link. A Survey Monkey is a web-based tool used in quantitative
research for collecting data online (Saunders, 2011; Survey Monkey, n.d).
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Research Method and Design
Research Method
In the study, a quantitative method was appropriate, because the research process
involved examination of the variables to determine if a correlation exists regarding the
predictors and criterion variables using statistical analysis (Singleton & Straits, 2010). In
addition to examination of variables, a quantitative method includes a multi-regression
analysis to determine how predictor variables as a whole predicted the dependent variable
(Green & Salkind, 2011). Predictor and criterion variables apply instead of independent
or dependent variables, because the design is non-experimental to collect data from the
targeted participants (Green & Salkind, 2011).
Predictor variables are variables used to predict another variable (Petter et al.,
2013). The job satisfaction predictor variables included (a) achievement, (b) recognition,
(c) responsibility, (d) work-itself, and (e) advancement and growth (Herzberg, 1974;
Herzberg et al., 1959). The job dissatisfaction independent variables included (a)
company policy, (b) supervision, (c) interpersonal relationships, (d) working conditions,
and (e) salary (Herzberg, 1974; Herzberg et al., 1959). A criterion variable is the effect or
outcome variable (Petter et al., 2013). The dependent variable was employee turnover
intentions in the fast food industry.
The qualitative method did not meet the needs of the research study, because the
purpose related to exploring the experience of an individual regarding the phenomenon
whether personal or professional (Bernard, 2013; Marshall & Rossman, 2006). In a
qualitative method, a theory emerges from the experience of the participants. The
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information collected creates a theme or category for further explanation of the
phenomenon, which was not the purpose of this research study (Bernard, 2013; Marshall
& Rossman, 2006). Instead, I found to understand the relationships of the predictor and
criterion variables.
In a qualitative method, the main purpose is also to explore the topic, because of
limited knowledge about the phenomenon (Cronholm & Hjalmarsson, 2011). Individuals
tend to understand the world they live in or work. A research must include themes or
categories to understand the related aspects of the phenomenon (Marshall & Rossman,
2006). A rigorous process is the goal of this method to understand the phenomena with
depth and breadth (Arendt et al., 2012).
Furthermore, a researcher focuses on the descriptions of the phenomena with
words, rather than numbers or graphics (Arendt et al., 2012). A researcher uses a
semistructured interview with open-ended questions to expand the topic of interest
(Arendt et al., 2012). Observations, recordings, video tapings, and taking notes are
common strategies to uncover the qualitative longitudinal process, and the researcher
does the analysis using thematic and coding approaches to gain deeper insights regarding
the phenomena (Arendt et al., 2012).
On the other hand, a mixed methods approach is a combination of quantitative
and qualitative methods, where one method can support the other method in terms of
narration or statistical approaches (Venkatesh et al., 2013). Mixed method is a research
strategy that involves data collection, analysis, integrated findings, and interpretation
93
using quantitative and qualitative approach (Östlund, Kidd, Wengström, & Rowa-Dewar,
2011).
The mixed method approach did not meet the needs of the research study, because
the intent of the quantitative study was to examine the relationship of the variables and
not to explore the phenomenon at the same time (Cronholm & Hjalmarsson, 2011;
Venkatesh et al., 2013). In a mixed methods approach, the use of different approaches
and designs are important to create comprehensive results to address the research
questions and hypotheses (Rozin, Hormes, Faith, & Wansink, 2012; Zachariadis, Scott, &
Barrett, 2013). In mixed methods, a researcher requires a phenomenon exploration and
data collection measurement in a long period by using inferential statistics (Vergne,
2012). A quantitative method cannot apply alone without the qualitative method
(Cronholm & Hjalmarsson, 2011; Venkatesh et al., 2013).
Research Design
The research design of this quantitative study was a non-experimental
correlational design with regression analysis. A correlation research is a form of
quantitative descriptive design (Stanley, 2011). In a correlational design, researchers
examine the relationship between two or more variables (Green & Salkind, 2011). Only a
correlational design can determine the level of effect of the variables. Using multi-
regression analysis for a study helped examine the correlation between two variables, and
the linear combination of predictor variables as a whole predicts the criterion variable
(Green & Salkind, 2011).
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A qualitative phenomenological design did not suit the needs for the study
because the nature of the study was to get an in-depth understanding how and why
individuals experienced the phenomenon (Venkatesh et al., 2013). The phenomenological
design includes a semistructured questionnaire with open-ended questions, which may
include a personal appearance of the interviewer and interviewee or face-to-face, and
personal connection (Keough & Tanabe, 2011). In a phenomenological design, a
researcher requires one-on-one or focus groups interviews with participants to expand the
topic interest with depth (Downes-Le Guin, Baker, Mechling, & Ruyle, 2012).
Population and Sampling
The population for this study included workers in fast food restaurants located in
the East Coast of the United States. Workers included male and female, must have a
minimum age of 18, full-time or part-time employees regardless of educational
background. Workers must work under low-level management or non-managerial
positions.
The sampling method proposed in the study was nonprobabilistic sampling. Non-
probabilistic sampling includes non-random selection related to the behavior or
characteristics in the population (Coolican, 2014). The weakness of a non-probabilistic
sampling method is a researcher cannot employ explicit selection unlike the probabilistic
sampling method (Hall, Higson, Jo Pierce, Price, & Skousen, 2013).
The category sampling method for the study was a purposive nonprobabilistic
sampling, because the participants of targeted population were specific and fit for the
purpose of the study, and did not depend on random selection (Coolican, 2014). Maxwell
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(2012) added that in purposive sampling selected participants, settings, and activities
provide information for the purpose of the study. The simple random sampling did not
meet the needs for the study, because the selection of participants was random. The
strength of the random sampling is participants can participate freely without specific
demographic characteristic requirements, where participants have equal chances of being
selected that helps avoid bias (Anthes, 2011; Coolican, 2014; D'Onofrio, Lahey,
Turkheimer, & Lichtenstein, 2013; Olagbemi, 2011; Olsen, Orr, Bell, & Stuart , 2013).
A stratified probabilistic sampling did not apply because a selection depended on
demographical characteristics (Coolican, 2014). The weakness of stratified random
sampling is when the response rates of each group are not equal bias occurs,
demonstrating a lack of representation (Bernard, 2013). The strength of the stratified
random sampling strategy is that a researcher can divide the group of participants equally
based on their demographic characteristics to meet accurate representations.
On the contrary, in a convenience nonprobabilistic sampling, a researcher can
select a sample based on their availability (Coolican, 2014). The strength of the
convenience sampling is the researchers can invite available participants to answer the
research questions (Bernard, 2013). Convenience sampling does not involve biased
awareness (Hall et al., 2013). The weakness of this strategy is that participants may not
represent the population (Bernard, 2013). Therefore, this type of sampling was not
applied.
To calculate the sample size, I used the formula provided by Tabachnick and
Fidell (2007) with 10 predictor variables. Sample size is important to reduce the mean
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standard error (Bernard, 2013). To compute the necessary sample size, I followed the
standard formula given by Tabachnick and Fidell, 50 + 8 (m). The symbol m means
desired number of predictor(s) (Tabachnick & Fidell, 2007). To get the sample size, 50 +
8(10) = 130.
Providing the right numbers of participants can generate better information results
to support the research study argument (Chen, Luo, Liu, & Mehrotra, 2011). Using a
large sample size, strong and effective data is important to support the hypotheses (Olsen,
2013). Exceeding the targeted sample size ensures enough participants for the study
(Olsen et al., 2013).
Ethical Research
Informed consent is a process that protects participants from any research ethical
problems that may arise during an interview process (Judkins-Cohn et al., 2014). The
employees accessed the survey link through flyers, participant invitation, and participant
reminder to participate (Appendices K and L). Prior to data collection, I submitted the
short-form ethics approval application to the Walden University IRB member to secure
my IRB approval number. According to Keough and Tanabe (2011), a researcher must
secure approval from the IRB before conducting the study (Appendix H).
With IRB committee approval, copies of consent form were sent to managers and
participants to understand the process of data collection (Walden University, n.d.). The
consent form included the invitation to participate, purpose of the study, research
procedures, and rights of participants to withdraw or decline the survey invitation
(Walden University, n.d.). Risks and benefits of a participant, payment if any, privacy
97
and confidentiality of participant were also included. Before the participants participated
online, they needed to read and sign the consent form (Walden University, n.d.). Signing
the consent form or clicking the survey link provided in the participant invitation and
participant reminder to participate were required to understand their rights, benefits, and
risks (Walden University, n.d.). Copies of the letter of consent and confidentiality
agreement are located in the table of contents and Appendices H and I.
Study participants had the option to withdraw at any time by declining the survey
invitation, not answering the survey questionnaire, or not submitting the survey
questionnaire (Judkins-Cohn et al., 2014). The online survey invitation stayed open until
receiving the required number of participants. Study participants did not receive any
incentives, benefits, or penalties for participating or declining the invitation.
For security purposes, the information data collected remained confidential and
safely secured for 5 years using Microsoft Office with an encrypted password. Any
submissions and summary results remain confidential suggested by Judkins-Cohn et al.,
2014). No one personally or by electronic devices retrieved any information from the
participants (Judkins-Cohn et al., 2014). Participants were required not to give their
names and workplace to protect their identities. Thus, participants remained anonymous
throughout the process to avoid any legal matters that might affect the research study
result. My contact number remained available to the targeted participants for any
questions that arose during the research process. Participants or fast food managers
requested a copy of the study results by checking the question yes at the end of the survey
or by sending a request to im[email protected].
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Data Collection Instruments
Job Satisfaction Survey (JSS)
Spector (1985) developed the job satisfaction survey (JSS). The JSS has nine
facet scales such as (a) pay, (b) promotion, (c) supervision, (d) fringe benefits, (e)
contingent rewards (performance based rewards), (f) operating procedures (required rules
and procedures), (g) coworkers, (h) nature of work, and (i) communication (Spector,
1985). Each facet scale has four questions, with 36 total items. The JSS includes an
ordinal scale, where each question has a 6-point Likert-type scale ranging from strongly
disagree to strongly agree. Some of the questions require reverse scoring because some
used negative statements and others used positive statements. The JSS proves important
in organizations, private, and public sector to assess employees' attitudes toward their job
and aspects of their job (Spector, 1985, 1997). Based on a sample size of 2,870, the
internal consistency reliability (coefficient alpha) of JSS is .91 (Spector, 1985, 1997)
Avdija and Roy (2012) also used the JSS in the state of Atlanta between October
2009 and January of 2010. The purpose includes the assessment level of employees’ job
satisfaction in different prisons (two medium security prisons and one maximum-security
prison). Avdija and Roy also used job satisfaction as a dependent construct. Participants
include 480 people (157 females and 322 males) to participate. More males participated
than women in the study. The JSS internal consistency reliability is α =.878 (Avdija &
Roy, 2012).
Furthermore, Avdija and Roy (2012) used multivariate regression analysis, where
age variable has a direct significant correlation with job satisfaction, β = .140, p < .001.
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Older employees are more satisfied with their jobs than younger employees. Based on the
R
2
result, only 2% of the variance in job satisfaction is associated by employee’s age. The
working conditions construct also correlated with job satisfaction with R
2
change = .147,
F (3, 471) = 27.839, p < .001). Overall, the total variation in the job satisfaction among
the prison employees is 30% (Avdija & Roy, 2012).
On the contrary, Wozencroft and Hardin (2014) emphasized that researchers
tested the original JSS in different 19 samples, where reliability and validity norms met.
Primarily, researchers applied the JSS for human services, but since then many
researchers used the JSS to all organizations. The JSS includes relevance to employees
and volunteers in the recreation management setting in Phoenix, Arizona. Wozencroft
and Hardin employed the JSS to assess the level of job satisfaction of students’ staff who
worked in university recreational services to determine the influence of job satisfaction
for future services. The participants include students totaling 211, but only 113 students
successfully completed the questionnaires. Some facet scales did not apply, because of
the nature of the study. With the result of the findings, the job satisfaction of the
employees is high. Researchers found job satisfaction related to turnover intention,
commitment, and retention. The reliability of the instrument is .85 using Cronbach
coefficient alpha: supervision .77, contingent rewards .73 operating conditions .55,
coworkers .68, nature of work .62, and communication .56. Appendix A includes JSS.
Turnover Intention Survey
Hom, Griffeth, and Sellaro (1984) developed the Intention to leave the job (ILJ)
with a 2-item scale. The ILJ includes a nominal scale with a 5-point Likert-type scale
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ranging from certainly not (1) to certainly (5). ILJ has an alpha value of 0.93 with a
Cronbach’s Alpha factor of 0.728. The reliability value of this instrument is above 0.70,
indicating acceptance in the research community (Hom et al., 1984).
Galletta, Portoghese, Penna, Battistelli, and Saiani (2011) also employed the
turnover intention scale in public hospitals in Italy to examine the variables that influence
person-environment fit. Supervisor and organizational supports play important roles
between the relationship of nurses’ perceptions care adequacy, job satisfaction, and
turnover intention (Galletta et al., 2011). Approximately 1,240 nurses from different
public hospitals participated using a self-administered questionnaire survey with internal
reliability of .85 (Galletta et al., 2011), which is good according to Matkar (2012).
Researchers tested the discriminate validity of the constructs using an exploratory factor
analysis (EFA). The results indicated five factors with Eigenvalues > 1, describing ~ 58%
of the variance of the indicators (Galletta et al., 2011).
On the contrary, researcher used the turnover intention survey on 2,042 women
engineers for self-efficacy and outcome expectations that influence job satisfaction and
turnover intention (Singh, 2013). The reliability found .91, which is excellent according
to Matkar (2012), and CFI = .99 (Singh et al., 2013). CFI is an assessment for model fit
ranging from .0 to 1.0, where values closer to 1 means good fit and values greater
than .90 is required to avoid model misspecification (Singh et al., 2013). Appendix B
includes ILJ survey.
Using Microsoft Office 2007, the generated results download into a spreadsheet
or database for review, analysis, and interpretation purposes. The purpose of the results of
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the raw data collected is to address the research questions. The Microsoft Office 2007
includes an encrypted password and backup, critical for security purposes in case of
unexpected events.
I used Pearson’s correlation coefficient to determine whether relationships
between two variables exist or not, using p value, which is less than .001 or .005.
Negative correlation coefficient demonstrates the inversed relationship of the two
variables, meaning that if employee satisfaction score is high, therefore employee
turnover intention score is low or reversed. The magnitude of the relationship is
categorized as low (.10), medium (.30), and high (.50) regardless of sign.
Multiple regression analysis was also applied to determine how well combined
predictor variables predicted dependent variables using R. Multiple correlation ranges
from 0 to 1. Zero result means no linear relationship exists between predictor scores and
criterion score (Green & Salkind, 2011). With a linear relationship, a value of 1 is
necessary. The values of R between 0 and 1 represent less-than perfect linear relationship
between two variables (Green & Salkind, 2011). The symbol of R squared represents how
well the criterion variance is predicted associated with combined linear predictors. R
squared must be multiplied by 100 to get the percentage, meaning that if R is .5
multiplied by 2 is equal to 25. Then multiplied by 100 is equal to 25% of criterion
variance (Green & Salkind, 2011).
Multiple regression analysis also evaluated the significant relationship of the
combined predictor variables and criterion variable using p value, which is less .05 or .01
(Green & Salkind, 2011). On an individual level of factor variable, I was also required to
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determine the significant relationship of the two variables using p value, which is less
than .001 or .005. Beta symbol (β) under standardized coefficient represents the
correlation coefficient and the magnitude of the relationship regardless of the sign.
Negative correlation coefficient means two variables have inversed relationship and a
positive correlation represents two variables have the same relationship results. In short, a
high score of job dissatisfaction is equal to a low score of job dissatisfaction. Therefore,
the score of the intention to leave factor is high. A positive correlation coefficient
represents a high score of job dissatisfaction, which equivalent to a low score of
dissatisfaction factor. Therefore, a low score is equivalent to low score in turnover
intentions. The magnitude of the relationship can categorize as low, medium, and high,
which is .10, .30, and .50 respectively.
Demographic Survey
The demographic questions include seven open-ended questions that pertain to
employee’s current personal information such as age category, gender, educational
background, workplace, job classification, position, and years of service. I analyzed the
demographic questions with descriptive statistical design to determine the frequency and
percentage distributions of the demographic variables. Descriptive statistics were also
used to measure the central tendency of specific variable using minimum, median,
maximum, and standard deviation (Green & Salkind, 2011; Olagbemi, 2011). In this
research survey, Appendix C includes the demographic questions.
A researcher measures the variables or constructs through the sound psychometric
scale. Using acceptable reliability and validity value, I used the psychometric scales for
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the study. The internal reliability of the psychometric scale can manifest by using
Cronbach’s alpha coefficient (α) (Barry et al., 2014; Doğan & Torlak, 2014; Matkar,
2012; Ünal, 2013). The Cronbach’s alpha coefficient can range from 0 to 1 (Matkar,
2012). Matkar (2012) noted that >0.90 is excellent, 0.80 – 0.89 is good, 0.70 – 0.79 is
acceptable, 0.60 – 0.69 is questionable, 0.50 – 0.59 is poor, where <0.50 is unacceptable,
which according to Spector (1985, 1997) and Hom et al. (1984), JSS and ILJ have proven
internal consistency reliability of more than .90, which is excellent and more than .70,
which is acceptable according to Matkar (2012). The psychometric scale’s score proved
reliable because participants came from the subset of the population. Data collection
process was implemented based on the Belmont protocols required by USDHHS (n.d),
and suggestions of Barry et al. (2014) and Tavakol and Dennick (2011).
Validity is the accuracy and trustworthiness of the psychometric scale scores
(Barry et al., 2014). To meet the quantitative validity, a rigorous process exists along with
a quality design, accurate analysis, and interpretation of the data (Venkatesh et al., 2013).
The validity factors of the research relates with the accuracy and consistency of the
collected data, estimation, and unbiased opinions from the participants (Xie, AbouRizk,
& Zou, 2012). To achieve the validity of my survey questionnaire score, I decided to use
the psychometric scale that has proven internal consistency value. The facet scales
covered the required research constructs that I needed to address to answer the research
hypotheses. Participants required signing the consent form to understand the process of
the data collection. After signing the consent form, participants visited the Survey
Monkey link to answer the questions based on their experience. Data collected were
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analyzed using Pearson’s correlation coefficient and multiregressions analysis. Study
findings were interpreted based on the honest responses of the participants, following the
suggestions of Barry et al. (2014) that focus on the following factors (a) test content, (b)
response processes, (c) internal structure, (d) relations to other variables, and (e)
consequences of testing to maintain a valid study.
Any adjustments or revisions on the instruments used needed approval by Walden
IRB to meet the validity and reliability of the instruments, process, and study.
Appendices A-C includes the instruments. Appendices D-E includes permissions to use
existing instruments. Appendix M includes raw data.
Data Collection Technique
To collect data from the targeted population, I used the online survey. An online
survey is a main preference of consumers, companies, and researchers to obtain different
views, perspectives, and opinions for particular services or products (Callegaro, 2013).
Participants for the online survey are pre-recruited (Bosnjak et al., 2013).
The purpose of using an online survey was to collect data from the targeted lower-
level employees. The objective of the data collection was to measure the level of job
satisfaction and job dissatisfaction towards the aspects of job, and to measure the degree
level of turnover intentions among fast food employees. The purpose was to make
inferences regarding the employees who worked in a fast food industry to reject or accept
the null hypotheses.
One advantage of using an online survey was participants could access the web
survey anywhere and anytime with multiple devices, which gives respondents an
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opportunity to respond in a quick manner regardless of time and place (Callegaro, 2013).
A participant could receive an instant message for missed questions or incorrect
responses (Albaum, Wiley, Roster, & Smith, 2011). A research survey online did not
include a personal appearance of the interviewer or interviewee, unlike in an interview
approach (Downes-Le Guin et al., 2012). A web-based survey was inexpensive, reaching
a higher number of potential participants, accessible, and participants responded at their
convenience (Keough & Tanabe, 2011). Using an online survey saved money in printing
and postal services (Middleton, Bragin, Morley, & Parker, 2014). However, visiting
participants to remind them incurred substantial costs. An online survey was anonymous.
Therefore, participants’ name or company was not required to protect their identity and
confidentiality (Dodou & de Winter, 2014).
The disadvantage of the online survey was questionnaire was longer; participants
withdrew without hesitation or survey was incomplete (Middleton et al., 2014). Thus, the
format must appear brief and concise to avoid higher withdrawal rate in the next research
project (Middleton et al., 2014). An online survey is mandatory, which requires complete
answers before the participant moves to the next question (Smith, King, Butow, & Olver,
2013). However, participants could withdraw anytime or decline to answer the questions
if needed as their rights stated. Some target participants did not have computer aptitude
that affected their capability to participate. Thus research design must align with
participants’ capabilities (Gill, Leslie, Grech, & Latour, 2013).
Pilot testing did not apply to the study. Using pre-established psychometric scales
with acceptable reliability and validity values supported the validity of my study
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(Eisenberger et al., 1986; Ertürk, 2014; Holt, 2001; Hom et al., 1984; Kihm et al., 2014).
Matkar (2012) noted the acceptable reliability value ranges from .70-.90 where both of
JSS and ILJ met the requirements.
Data Analysis
The overarching research question for the study was, “What is the relationship
between the employee job satisfaction factors, job dissatisfaction factors, and employee
turnover intentions?” The null hypothesis for this study was, “There is no statistical
significant relationship between the employee job satisfaction factors, employee job
dissatisfaction factors, and employee turnover intentions?” The alternative hypothesis
was, “There is a statistically significant relationship between the employee job
satisfaction factors, employee job dissatisfaction factors, and employee turnover
intentions.”
To analyze the data collected, I used the Pearson-product correlation coefficients
to determine the relationship between the two variables whether relationship exists or not,
using p value, which is less than .001 or .005. Determining the effect size of the
correlation coefficient r, sign must be considered. Positive correlation coefficient means
both relationships of the variables have the same effect. Example, when job satisfaction is
high, then turnover intention is high as well. Negative correlation coefficient means both
variables have inversed relationships. In short, when satisfaction is high, turnover
intention is low. Magnitude of relationship can be low, medium, and high as suggested by
Green and Salkind (2011). Zero means no relationship between two variables.
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Multiregression analysis was used to evaluate whether the predictor variable
predicted the criterion variable and to what extent. The p value evaluated whether the two
variables significantly correlated or not. R square (r2) determines the criterion variance
associated with a predictor variable (Green & Salkind, 2011). Negative correlation
coefficient means two variables have inversed relationship. Example, high score of
dissatisfaction means greater dissatisfaction, which was equivalent to low score. Low
score means high score in intention to leave. Positive correlation coefficient means two
variables have the same effect. Example, high score in job dissatisfaction, which is
equivalent to low score, is equal to low score in intention to leave. This is a case to case
scenario. Zero means no relationship. Level of relationship depends on .10, .30, and .50.
according to Green and Salkind (2011).
Demographic survey was analyzed using descriptive statistics analysis. Utilizing
descriptive statistics determines the points of central tendency such as minimum, mean,
maximum, and standard deviation (Green & Salkind, 2011). The importance of
determining the frequency and the percentage level of each variable was to understand
the general distributions (Green & Salkind, 2011).
The purpose of this study was to determine the relationship between two variables
and that extent of the existing relationship. Other objective was to evaluate the
relationship between predictor variables and criterion variable to find the criterion
variance associated by combined predictor variables using multiregression analysis.
Independent-sample t did not apply, because the purpose of the study was to evaluate the
differences between the means of two independent groups, the grouping variable, and the
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test variable. Grouping variables includes demographic variables (gender) while test
variable includes quantitative dimension. The t test is used to evaluate the mean
differences of these two groups (Green & Salkind, 2011). Another statistical test that did
not meet the needs of the study was the partial correlation, because a researcher used a
mediating variable (Green & Salkind, 2011).
In the quantitative study, 10-testing hypotheses occurred. The null hypotheses
(
H1o, H2o, H3o, H4o, H5o, H6o, H7o, H8o, H9o, and H10o
) for the study included employee job
satisfaction factors, employee job dissatisfaction factors, and employee turnover
intentions in the fast food industry. The purpose of the data analysis was to determine the
statistically significant relationships of the variables to accept or reject the hypotheses.
The statistical test for hypotheses proved significant, statistically rejecting the existing
null hypotheses (
H1o, H2o, H3o, H4o, H5o, H6o, H7o, H8o, H9o, and H10o
). I presumed that the existing
null hypothesis was true (fail to reject). However, the research findings rejected the null
hypotheses.
To support the rejection or acceptance of the null hypotheses, the confidence level
of p value must reach the significant level of less than .05 or .005, .01 or .001 (Green &
Salkind, 2011). The employee job satisfaction factors and job dissatisfaction factors are
the predictor variables, where employee turnover intentions serve as the criterion
variable. If r is positive, this polarity indicated each variable had the same effect with
each other. If r is negative, one variable has a contrast effect on the other. Zero
correlation means no relationship between the variables exist (Green & Salkind, 2011).
Based on the Pearson-product correlation coefficients results, all null hypotheses were
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rejected because the p value was less than .001. Effect size means the strength level of the
variable relationship (Green & Salkind, 2011). The effect sizes have inversed results.
Therefore, having high job satisfactions means low intention to leave. Level of
relationships varied based on the participants responses.
IBM SPSS Version 22.0 for Windows is a computer software tool that has ability
to analyze the data statistically and graphically. IBM SPSS software was used to analyze
the data collected because it provides Pearson’s correlation coefficient analysis,
multiregression analysis, and descriptive statistics to describe the general distributions by
frequency and percentage (Green & Salkind, 2011). The purpose of the IBM SPSS
Version 22.0 for Windows is to analyze the relationships between employee job
satisfaction factors, employee job dissatisfaction factors, and employee turnover
intentions with multiregression analysis.
Study Validity
Validity means the accuracy and trustworthiness of the psychometric scale scores
(Barry et al., 2014). I used the JSS and ILJ psychometric scales because of its proven
internal consistency reliability, which are .70 and .91 that have acceptable and excellent
value properties. Three characteristics of validity are content, construct, and criterion-
related validity (Barry et al., 2014). Content validity is a researcher assessing the degree
to which the scales items represents or covers all related information to the concept of
interest. In construct validity, a researcher assesses whether the scale accurately measures
the theoretical construct. Criterion-related validity is a researcher comparing the scores of
two different scales (Barry et al., 2014). Pärl (2013) stressed the importance of validity
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with consistent data collection, documentation, analysis, and interpretation. I relied on the
rigor and quality of the design, analysis, and interpretation of the data to achieve the
validity of the study. Therefore, I used the psychometric scales with facets scale that
covered and aligned to my research study constructs. Data collection started with IRB
approval. Upon receipt of approval, I asked the permissions of the managers to allow the
participants to participate. Before signing the consent form, nature of the study, purpose
of the study, rights, and my responsibility were explained thoroughly to maximize the
benefits as well minimize risks to protect the participants from any harm, as well as to
avoid any ethical and legal issues.
The external validity threats can occur when participants are not the true
representatives of the targeted population. External threats were avoided because the
participants were subset of the target population. The nature of the study design was a
web-based survey where personal connection was not present. To prevent any threats to
external validity, I discussed my concerns with managers and participants before the
collection of data process started to ensure they understood the process of the data
collection, rights to participate, and knew the importance of their participation. The
setting of the participants was critical. To avoid any threats to external validity, targeted
population was only located in East Coast in the United States. I only visited and met
managers and participants who met the criteria within the targeted setting.
If the instrument is not the right tool to measure the constructs, then the
instrument cannot support the hypotheses, known as instrument validity (Callahan, 2014).
Therefore, in the study I decided to use the JSS to ensure meeting the internal validity of
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the instrument. Internal validity threats occur when the items of the scale do not cover all
the necessary information pertaining to the concept of interest (Barry et al., 2014). The
items of the JSS included all the predictor variables for employee job satisfaction and
predictor variables for employee job dissatisfaction; therefore, the threat was reduced
significantly (Barry et al., 2014). When the scores of the scale do not measure the
construct accurately, which is construct validity, a researcher encounters the validity
threat (Barry et al., 2014). Therefore, rechecking the scores was necessary ensuring
proper and accurate distribution of scores to the right constructs (Xie, AbouRizk, & Zou,
2012).
When the contents of the scale do not represent the information to support the null
hypothesis (Type I error), a content validity threat occurs (Barry et al., 2014). A content
validity was met because the contents of the scale were aligned to study constructs. A
type I error occurs when a researcher rejects a null hypothesis when it is true (Menon,
Massaro, Pencina, Lewis, & Wang, 2013). A type I error did not occur, because the null
hypotheses were rejected based on responses of the participants. To address the issue that
can harm the statistical conclusion validity, Barry et al. (2014) suggested focusing on test
result, response process, internal structure, relations to other variables, and consequences
of testing. In addition, consistency in data collection, documentation, analysis, and
interpretation makes the study, process, and instrument valid (Pärl, 2013). Statistical
conclusion was valid, because the test results were based on the Pearson’s correlation and
multiregression analyses supported by rigorous response process, valid instruments, and
valid study process.
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A researcher can generalize the research findings to the larger population when
the samples are the subset of the target population to avoid biases that can influence the
validity of the study (Gibson & Fedorenko, 2013). Englander (2012) supported the notion
that participants must have relationships with the larger population and must have a
representation. Different settings have different participants’ demographic characteristics;
therefore, research findings can generalize to different setting. My study findings could
only generalize in the fast food restaurants located in East Coast in the United States
because they were the subset of the target population that represented the population.
Transition and Summary
The purpose of the quantitative correlational research study was to examine the
relationship between employee job satisfaction, employee job dissatisfaction, and
employee turnover intentions in the fast food industry. Factors that affect the employee
turnover intentions help fast food managers, HR personnel, and business owners to
understand how to combat increasing employee turnover. The study findings provided
information regarding the factors that affect employee turnover intentions the most.
Understanding the factors could assist fast food employers to avoid job
dissatisfaction, and thereby increase the job satisfaction resulting in decreased employee
turnover in the fast food industry. The study results also could help managers improve
business practices to meet business sustainability, profitability, and growth. Meeting the
employee needs and job satisfaction could help maintain the skilled workers, and
sustained the business operations (Kwon & Rupp, 2013).
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The preferred instrument to collect data was an online survey. An online survey is
one of the popular tools used by many researchers because of the following beneficial
factors (a) convenience, (b) flexibility, (c) mass distribution, (d) demographic advantages,
and (e) inexpensive. The Survey monkey website served as my survey link. The target
sample size was 130. The targeted population included employees in a fast food industry
throughout the East Coast of the United States with a minimum age 18, male and female,
and full-time or part-time lower-level management or non-managerial position. The
selection of participants was a purposive nonprobabilistic sampling because fast food
lower-level employees suited the purpose of the study. The objective of my study was to
protect the privacy and confidentiality of the participants to ensure their safety and
security by maintaining their anonymity throughout the research study. Raw data
collected would store using the hard drive and external drive with Microsoft encrypted
password to remain safe and secured for 5 years. After 5 years, all data collected will
receive deletion.
A pilot study did not apply here, because the study required pre-established
psychometrical scales. I analyzed the data collected using Pearson’s correlation
coefficient and multi-regression analysis to examine the relationship between the two
variables and to determine how predictor variables predicted the criterion variable.
Determining the correlation of predictor and criterion variables may assist the fast food
restaurants’ business owners, HR personnel, and managers to provide effective strategies
to combat the increasing employee turnover rates. Increasing employees’ job satisfaction
and decreasing job dissatisfaction can prevent or minimize the employee turnover from
114
happening. Meeting the employee needs can also help maintain the skilled workers to
sustain the business operations profitability and growth (Kwon & Rupp, 2013).
Section 3: Application to Professional Practice and Implications for Change
Introduction
The purpose of this correlational quantitative study was to examine the
relationships between the job satisfaction factors, job dissatisfaction factors, and
employee turnover intentions in the fast food industry. The objective was to determine
whether job satisfaction factors and job dissatisfaction factors had statistically significant
relationships with employee turnover intentions to accept or reject the hypotheses. An
additional objective was to evaluate how well the linear combination of job satisfaction
factors and job dissatisfaction factors predicted the employee turnover intentions using
the multiple regressions analysis.
The research study findings revealed that job satisfaction factors and job
dissatisfaction factors had statistically significant relationships with employee turnover
intentions (p < .001). Both job satisfaction factors and job dissatisfaction factors showed
different magnitude of relationships with employee turnover intentions. In terms of job
satisfaction factors, employee responsibility (-.52) had the highest statistical significant
relationship with employee turnover intentions, followed by work itself (-.51),
recognition (-.49), advancement and growth (-.37), and achievement or quality
performance (-.26). In terms of job dissatisfaction factors, company policy (-.52) had the
highest magnitude of relationship with employee turnover intentions, followed by salary
(-.42), interpersonal relationships (-.39), supervision (-.37), and working condition (-.34).
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On the other hand, the criterion variance of employee turnover intentions associated with
job satisfaction factors (35%) was higher than job dissatisfaction factors (31%).
Presentation of the Findings
The findings from the data analysis clearly addressed the research question of
what is the relationship between the job satisfaction factors, job dissatisfaction factors,
and employee turnover intentions. The purpose of the examination was to determine if
there was a statistically significant relationship between two variables to accept or reject
the research hypotheses. The other objective was to evaluate how well the linear
combination of job satisfaction factors (predictors), job dissatisfaction factors (predictors)
predicted employee turnover intentions (criterion). The job satisfaction factors were
achievement or quality performance, recognition, work itself, responsibility, and
advancement and growth. The job dissatisfaction factors were company policy,
supervision, interpersonal relationship, working condition, and salary.
The data came from 144 participants working in the lower-level management or
nonmanagerial positions at fast food restaurants in the east coast in the United States.
Participants completed an Internet survey hosted by Survey Monkey and containing the
JSS survey, ILJ scale, and the demographic question. The JSS survey had 36 items,
which were divided into nine subscales. These nine subscales were (a) pay, (b)
promotion, (c) supervision, (d) fringe benefits, (e) contingent rewards, (f) operating
procedures, (g) co-workers, (nature of work), and (h) communication. Each subscale was
comprised of four items, which consisted of both negative and positive statements. To
sum up the total scores for each subscale, the negative statements had reversed scoring.
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The JSS scale had a 6-item Likert-type scale ranging from 1 to 6, which 1 represented a
strongest disagreement and 6 supported a strongest agreement. The negative statements
such as 2, 4, 6, 8, 10, 12, 14, 16, 18, 19, 21, 23, 24, 26, 29, 31, 32, 34, and 36 were
reverse-scored based on the suggestions of Spector (1985, 1997).
The validity of a psychometric scale depends on its internal consistency reliability
(Barry et al., 2014). The internal consistency reliability of the JSS using coefficient alpha
(α) was important in establishing the validity and reliability of the research study
findings. Table 2 shows the result of the internal consistent reliability of the JSS survey
based on the sample size of 144.
Table 2
JSS Instrument Reliability Statistics – Cronbach’s Alpha
Subscales Cronbach’s Alpha (α) n
Pay 0.771 4
Promotion 0.734 4
Supervision 0.784 4
Fringe Benefits 0.585 4
Contingent Rewards 0.715 4
Operating Conditions 0.354 4
Coworkers 0.686 4
Nature of Work 0.787 4
Communication 0.716 4
Total JSS scale 0.933 36
Note. α > .90.
As shown in Table 2, the consistent reliability of JSS survey instrument was .93.
Matkar (2012) discribed psychometric scale reliability higher than .90 is indicative of
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excellent consistent reliability for a reliable instrument. The coefficient alpha of .93
therefore suggested that scale scores are reliable for participants. The other psychometric
scale used in the study was the 2-item ILJ scale. The ILJ is an ordinal scale with a 5-point
Likert-type scale ranging from certainly not (1) to certainly (5). The Cronbach’s alpha
value was .60. Table 3 showed the consistent reliability result of the ILJ scale based on
the 144 participants.
Table 3
ILJ Instrument Reliability Statistics – Cronbach’s Alpha
Scale Cronbach's Alpha (α)
n
Intention to Leave the Job
0.6
2
Note. α <0.60 – 0.69.
I exported the raw data from Survey Monkey to Microsoft Excel to recheck each
response to meet the accuracy reporting. The corrected raw data was then exported into
IBM SPSS version 21 to determine the frequency and percentage distributions and the
correlations of the variables using descriptive statistics, Pearson-product correlations
coefficient, and multiple regression analysis.
Descriptive Statistics for Demographic Variables
I used descriptive statistics to determine the general distributions of the variables
using frequency and percentage levels, as suggested by Green and Salkind (2011).
Utilizing descriptive statistics also determine the points of central tendency such as mean,
minimum, maximum, and standard deviation. The sample size came from 144
participants who currently work at the fast food restaurants within east coast in the United
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States. The required sample size reflects the formula used by Tabachnick and Fidell
(2007). Table 4 shows the frequency distribution of the fast food worker participants’
genders.
Table 4
Frequency Distribution of Fast Food Participants’ Gender
f % Valid % Cumulative %
Valid
Female 95 66.0 66.0 66.0
Male 49 34.0 34.0 100.0
Total 144 100.0 100.0
Missing System 0 0.0
Total 144 100.0
Note. N = 144. The f column denotes the number of participants identified as female or
male. The row identified as missing displays the total count of survey responses minus
responses identified as male or female, f =0. The percentage column computes using the
total of survey responses, f = 144, the sum of which is 100%. The valid percent column
computes using the 144 male or female participants. The cumulative percent column is
the cumulative sum of the f column or 144 participants, the total of which is 100%. The
sample size N = 144, indicates participants who completed the survey.
The purpose of the frequency distribution was to illustrate the distribution of
female and male participants participated and completed the survey. Out of the 144
participants, 95 participants were female and 49 participants were male. Figure 3
shows the percentage of participants’ gender distribution.
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Gender
Figure 3. Fast food participants’ gender distribution (N = 144). The purpose was to
illustrate the percentage distribution of female and male participants completed the
survey. Women represented 66% of the participants and men represented 34% of the
participants.
As shown in Figure 3, fast food participant are female and male. One hundred
forty-four successfully participated and completed the survey. Out of 144 participants
65.97% were female and 34.03% were male. Female percentage was higher than male
percentage. Table 5 shows the frequency distribution of fast food participants’ age.
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Table 5
Frequency Distribution of Fast Food Participants’ Age
f % Valid % Cumulative %
Valid
18-28 years
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74.3
74.3
74.3
29-39 years
19
13.2
13.2
87.5
40-50 years
11
7.6
7.6
95.1
51-61 years
7
4.9
4.9
100.0
Total
144
100.0
100.0
Note. N = 144. The f column denotes the number of participants with specified age
brackets. The percentage column computes using the total of survey responses, f = 144,
the sum of which is 100%. The valid percent column computes using the 144
participants. The cumulative percent column is the cumulative sum of the f column or
144 participants, the total of which is 100%. The sample size N = 144, indicates
participants who completed the survey with different age category.
In Table 5, age brackets were broken down into 4 categories. Under 18-28, 107
participants participated and completed the survey questionnaire. Nine-teen participants
were under 29-39 years old. Under 40-50 years old, only 11 participants participated.
Under 51-61 years old, seven participants accepted the invitation. Overall, the number of
participants participated and completed the survey was 144, which exceeded the sample
size requirement. Figure 4 shows the percentage age brackets of fast food participants.
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Age
Figure 4. Fast food participants’ age distribution (N = 144). The age categories of the
participants participated and completed the survey invitation. Age was divided into 4
categories: 18-28 years old (74%), 29-39 years old (13%), 40-50 years old (8%), and 51-
61 years old (5%).
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Figure 4 represented the percentage age distribution of the participants based on the
144 sample size. The highest percentage of participation was age 18-28 years old
followed by 29-39 years old, 40-50 years old, and 51-61 years old, which was the lowest
percentage of participation. In conclusion, majority workers at fast food restaurants in
east coast in the United States were ages 18-28 years old and 51-61 years old were the
least workers. Table 6 represents the frequency distribution of fast food participants’
education attainment.
Table 6
Frequency Distribution of Fast Food Participants’ Educational Attainment
f % Valid % Cumulative %
Valid Other (please
specify)
5
3.5
3.5
3.5
High school
50
34.7
34.7
38.2
Vocational
21
14.6
14.6
52.8
Undergraduate(1-3)
38
26.4
26.4
79.2
Bachelor degree
29
20.1
20.1
99.3
Master
1
.7
.7
100.0
Total
144
100.0
100.0
Note. N = 144. The f column denotes the number of participants with different
educational attainment in life. The % column computes using the total of survey
responses, f =144, the sum of which is 100%. The valid percent column computes using
the 144 participants with different educational background. The cumulative percent
column is the cumulative sum of the f column or 144 participants, the total of which is
100%. Five participants did not specify the achieved education.
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In Table 6 shows different educational background of the participants. Educational
level backgrounds of participants are high school, vocational, undergraduate, bachelor,
master, and others. Fifty fast food workers were high school graduate. Twenty-one
workers went to vocational school. Thirty-eight workers did not finish bachelor degree.
Twenty-nine workers had bachelor degree, and one worker had master degree.
Unfortunately, five participants did not specify the educational attainment. Overall, the
highest participants with high school diploma (50), followed by bachelor degree (29),
undergraduate (38), vocational (21), and master (1). Only one participant worked at fast
food restaurant with master background. Figure 5 illustrates the percentage distribution
of participants’ educational attainment.
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Educational Attainment
Figure 5. Fast food participants’ educational attainment distribution (N = 144). Bar chart
for participants’ educational background representing different educational attainment
received by workers at Fast food restaurants in the east coast in the United States.
Figure 5 represented the percentage of participants who received high school
diploma (35%), vocational course (15%), undergraduate degree (26%), bachelor degree
(20%), and master degree (1%). Four participants did not specify the educational
attainment (3%). In summary, majority participants had high school background,
followed by undergraduate degree, bachelor degree, vocational, and master background,
which was the least number of participants. Table 7 shows the frequency distribution of
fast food participants’ job positions.
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Table 7
Frequency Distribution of Fast Food Participants’ Job Positions
f % Valid % Cumulative %
Valid Other (please
specify)
4
2.8
2.8
2.8
Cashier(Drive/Front
line)
69
47.9
48.3
51.0
Runner(Counter
and Drive thru)
15
10.4
10.5
61.5
Fry person
5
3.5
3.5
65.0
Meats person
7
4.9
4.9
69.9
Initiator
2
1.4
1.4
71.3
Assembler
7
4.9
4.9
76.2
Manager
14
9.7
9.8
86.0
Assist Manager
6
4.2
4.2
90.2
Cook
6
4.2
4.2
94.4
Driver
5
3.5
3.5
97.9
Server
3
2.1
2.1
100.0
Total
143
99.3
100.0
Missing
System
1
.7
Total
144
100.0
Note. N = 144. The f column denotes the number of participants with different job
position in the fast food restaurants. The row identified as missing displays the total count
of survey response f =1. The % column computes using the total of survey responses, f
=144, the sum of which is 100%. The valid percent column computes using the 144
participants with low-level management position and non-managerial position. The
cumulative percent column is the cumulative sum of the f column or 144 participants, the
total of which is 100%.
In Table 7 shows the 144 participants participated in the research study. Only one
participant did not answer the job position question and 4 participants did not specify job
position. Participants worked from different job positions under low-level management or
nonmanagerial positions. Numbers of participant from different job assignment were as
follows: cashier (69 participants), runner (15 participants), fry person (5participants),
meats person (7 participants), initiator (2 participants), assembler (7 participants),
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managers (14 participants), assistant managers (6 participants), cook (6 participants),
driver (5 participants), and server (3 participants). Conclusively, the highest participants
came from cashier, runner, and manager positions. The least participants were from
initiator, server, fry person, and driver. Figure 6 represents the percentage of fast food
participants’ job position.
Job Position
Figure 6. Fast food participants’ job position distribution (N = 144). The graph is an
illustration of percentage participants’ specific positions in the fast food restaurants. The
graph represents the percentage of participants’ job category.
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As shown in Figure 6, 144 participants responded to the invitation, which
represented different jobs of the participants. Participants’ job percentages were cashier
(48%), runner (10%), fry person (3%), meats person (5%), initiator (1%), assembler
(5%), managers (10%), assistant managers (4%), cook (4%), driver (3%), and server
(2%). Four participants did not specify job position, which equivalent to 3%. In
Conclusion, the highest percentages of participants were from cashier (48%), runner
(10%), and managers (10%). The least percentages of participants were from initiator
(1%), server (2%), driver (3%), and fry person (3%). Table 8 shows the frequency
distribution fast food participants’ job classification.
Table 8
Frequency Distribution of Fast Food Participants’ Job Classification
F % Valid % Cumulative %
Valid
Part-time 90
62.5
62.5
62.5
Full-time
54
37.5
37.5
100.0
Total
144
100.0
100.0
Note. N = 144. The illustration of participants’ job classification in the fast food
restaurants in east coast in the United States. Participants are classified as part-time and
full-time employees. The column f is a representation of the number of participants who
work as a part-time employee or full-time employee. The % column denotes the
percentage of participants who work as a part-time or full-time employee. The valid
percentage column is the percentage total of each employee job classification, which is
equal to 100%. The cumulative % shows the total 100% of both job classifications.
As shown in Table 8, the total number of participants participated and completed
the survey was N=144. Participants’ job classification is part-time or part-time. Ninety
participants classified as part-time employee. Fifty-four classifies as full-time employee.
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In conclusion, part-time workers had higher number of participation than full-time
workers. Figure 7 represents the percentage distribution of fast food job classification.
Job Classification
Figure 7. Fast food participants’ job classification distribution (N = 144). This is the
illustration of fast food employee job classification, part-time and full-time in the east
coast in the United States. The purpose is to illustrate the number of employees who work
as part-time and full-time.
As shown in Figure 7, participants in Fast food restaurants in east coast in the
United States classified as part-time and full-time employees. Part-time employees had
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62.50% participation and full-time employees had 37.5% participation. In conclusion,
part-time employees had higher percentage of participation than full-time employees.
Table 9 illustrates the frequency distribution of fast food participants’ years of service.
Table 9
Frequency Distribution of Fast Food Participants’ Years of Service
F % Valid % Cumulative %
Valid 5 years
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90.3
90.9
90.9
10 years
10
6.9
7.0
97.9
15 years
2
1.4
1.4
99.3
20 years
1
.7
.7
100.0
Total
143
99.3
100.0
Missing
System
1
.7
Total
144
100.0
Note. N = 144. The table represents the frequency distributions of fast food participants in
terms of services. The purpose is to illustrate the numbers of participants, percentage of
participants, valid percentage, and cumulative percentage of the participants who worked
under 5 years, 10 years, 15 years, and 20 years.
In Table 9, years of service categorized as 5 years, 10 years, 15 years, and 20
years. In 5 years, one hundred thirty participants (90.3%) worked under lower-level
management or non-managerial position. In 10 years, 10 participants (6.9%) worked in
the same level of management. In 15 years, 2 participants (1.4%) and in 20 years,
1 participant (.7%) worked in the same level. One participant missed the question.
Conclusively, majority of the participants had 5 years of working services at Fast food
restaurants in the east coast in the United States. The least number of participants found
in 15 and 20 years services. Figure 8 shows the percentage distribution of fast food
participants’ years of service.
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Years of Service
Figure 8. Fast food participants’ years of service distribution (N = 144). This is the
illustration of percentage participants’ year of services at Fast food restaurants in east
coast in the United States. The purpose is to illustrate the percentage of participants
worked within 5 years, 10 years, 15 years, and 20 years. One participant did not specify
the years of experience working at Fast food restaurants.
In Figure 8, participants’ work experiences categorizes within 5 years, 10 years,
15 years, and 20 years. Participants worked under lower-level management or
nonmanagerial positions at the Fast food restaurants. Ninety percent of participants
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worked within 5 years. Seven percent of participants worked for 10 years. One percent of
participants worked within 15 years and other 1 percent worked for 20 years already. The
remaining 1% of participant did not specify the years of service. In conclusion, majority
of participants worked at fast food restaurants within five years. Only 1% of participant
worked within 20 years. Table 10 shows the descriptive statistics for specific
demographic variables.
Table 10
Descriptive Statistics for Age and Years of Working Variables
Variables Minimum
Mean
Maximum
SD
Age 1
1.43
4
0.83
Years of Working
1
1.12
4
0.42
Note. N = 144. The descriptive statistics for participants age and years of working with
the fast food restaurants in the east coast in the United States. The purpose is to illustrate
the minimum, mean, maximum, and standard deviation of participants’ age and years of
working under lower-level management or nonmanagerial position.
In Table 10 described the participants’ age and years of working with fast food
restaurants in the east coast in the United States. The minimum age of the participants
completed the survey was 1(18-19 years old) and the maximum age was 4(5-61 years
old). The mean age was 1.43(29-39 years old) with standard deviation of 0.83. The
minimum number of years of working was 1(5 years) and the maximum years was 4(20
years). The mean years of working was 1.12(more than 5 years) with 0.42 standard
deviation.
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Pearson Product-Moment Correlation Coefficient
Findings in the study derived from 144 participants participated and completed
the survey invitation. Participants comprised of individuals who currently work at fast
food restaurants in the East Coast in the United States with the designated positions in the
low-level management or non-managerial positions. Participants responded to the JSS
survey that comprised 36 items, which was equivalent to 9 facets or variables. Each
subscale contained 4-items. The other instrument used in this study was intention to leave
scale, which comprised 2-items. An analysis of data proved instrumental in determining
whether variables have significant relationships.
The research question addressed in the study was is there a significant relationship
between job satisfaction factors, job dissatisfaction factors, and employee turnover
intentions? The central research question had 10-sub research questions to address to
accept or reject the hypotheses. The null hypotheses suggested that no statistically
significant relationship between job satisfaction factors, job dissatisfaction factors, and
employee turnover intentions. The alternative hypotheses suggested that there is a
significant relationship between job satisfaction factors, job dissatisfaction factors, and
employee turnover intentions.
The purpose of the data analysis was to determine whether there was a
statistically significant relationship between the predictor variables and criterion variable
to accept or reject the provided hypotheses using the confidence level of p value, which
must reach the significant level of less than .05 or .005, .01 or .001 (Green & Salkind,
2011). Effect size means the strength level of the variable relationship (Green & Salkind,
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2011). The strength level of the variable relationship can be small (.10), medium (.30),
and large (.50) regardless of sign. Pearson product-moment correlation coefficient can
range from -1 to +1. If r is positive, this polarity means each variable has the same effect
with each other. If r is negative, one variable has a contrast effect on the other. Zero
correlation means no relationship existed between two variables (Green & Salkind,
2011). Table 11 shows the correlation coefficient results between job satisfaction factors
and employee turnover intentions.
Table 11
Pearson Product-Moment Correlation Coefficients Between Job
Satisfaction Factors and Employee Turnover Intentions
Job Satisfaction Factors
Employee Turnover
Intentions Correlations
(Predictor Variables)
(Criterion Variable)
r
Achievement/quality
performance
Employee turnover
intentions
-0.26
Recognition
Employee turnover
intentions
-0.49
Work itself
Employee turnover
intentions
-0.51
Responsibility
Employee turnover
intentions
-0.52
Advancement and Growth
Employee turnover
intentions
-0.37
Note. N=144. All correlations were significant at the p < .001 level.
Research Question 1
Research Question 1 was, “Is there a statistically significant relationship between
employee job satisfaction achievement and employee turnover intentions?” The null
hypothesis stated that there is no statistically significant relationship between employee
134
job satisfaction achievement and employee turnover intentions. A Pearson product-
correlation applied to determine whether there was a statistically significant relationship
between employee job satisfaction achievement or quality performance and employee
turnover intentions.
As shown in Table 11, the resulting correlation coefficient was r = -.26 (p < .001).
In conclusion, there was a statistically significant relationship between employee job
satisfaction achievement or quality performance and employee turnover intentions
because the p value was less than .001, which rejected the null hypothesis and the
assumptions. The magnitude of the relationship was low. The result showed an inverse
relationship. Therefore, the lower scores on employee job satisfaction achievement, the
higher scores on employee turnover intentions.
Statistically, achievement or quality performance found significantly related to
employee turnover intentions. The research study findings supported Herzberg’s
motivation-hygiene theory (1959). Herzberg argued that when job satisfaction factors
increased, employee turnover decreased. Herzberg added that employee achievement was
a source of employee job satisfaction. Employee achievement or quality performance
derived from training and development (Islam & Ali, 2013; Teck-Hong & Waheed,
2011). Therefore, business leaders must have visions on improving employees’ training
and development program to increase employees’ competence in the market.
Managers must empower the employees by giving them training periodically.
Training allows employees to increase self-efficacy and communication with the
customers, resulting to increased quality performance (Mathe & Scott-Halsell, 2012).
135
Kanten (2014) suggested improving job characteristics, such as skill variety, task identity,
task significance, feedback, and autonomy.
Derby-Davis (2014) also supported the research study results using nursing
industry, emphasizing that job satisfaction factors were significant factors to increase job
satisfaction to reduce employee turnover intentions. Islam and Ali (2013) found
achievement as work factor that promoted employee job satisfaction in private teaching
sector, which was better factor than other job satisfaction factors.
Research Question 2
Research Question 2 was, “Is there a statistically significant relationship between
employee job satisfaction recognition and employee turnover intentions?” The null
hypothesis stated that there is no statistically significant relationship between employee
job satisfaction recognition and employee turnover intentions. A Pearson product-
correlation applied to determine whether there was a statistically significant relationship
between employee job satisfaction recognition and employee turnover intentions.
As shown in Table 11, the resulting correlation coefficient was r = -.49 (p < .001).
In conclusion, there was a statistically significant relationship between employee job
satisfaction recognition and employee turnover intentions because the p value is less
than .001, which rejected the null hypothesis and the assumptions. The magnitude of the
relationship was high. The result showed an inverse relationship. Therefore, as scores on
employee job satisfaction recognition increase, the scores on `employee turnover
intentions decrease.
136
The research findings revealed that employee job satisfaction (recognition) had a
statistically significant relationship with employee turnover intentions. Herzberg’s
motivation-hygiene theory (1959) supported the study results, arguing that when job
satisfaction factors increased, employee turnover intentions decreased as well. In
addition, Herzberg mentioned that employee recognition could assess by using feedback.
Derby-Davis (2014) also supported the study findings, emphasizing that increasing job
satisfaction factors could decrease employee turnover intentions. Moreover, using data
from teachers in private teaching sectors, Islam and Ali (2013) noted that employee
recognition indeed increased employee job satisfaction. Teck-Hong and Waheed (2011)
supported the notion using convenience sampling.
Maslow (1943) added that employee recognition developed employee self-
esteem. Stinchcomb and Leip (2013) and Tews et al. (2014) supported the results as well,
stating that when work climate had employee recognition, employee turnover decreased.
Bauer (2012) added that recognizing employees could prevent the voluntary withdrawal.
Moreover, not only did reduce the employee turnover, high employee recognition could
increase employee positive performance, work engagement, motivation, self-esteem,
commitment, and contribution that produced high quality services to the customer (Cho
et al., 2013; Eisenberger et al., 1990; Gavino et al., 2012; Gkorezis & Petridou, 2012;
Haines III & St-Onge, 2012; Hogan et al., 2013; Nyman et al., 2012). High employee
recognition could also encourage employees to stay with the company in which employee
embeddedness and career satisfaction increased (Bhatnagar, 2014; Gkorezis & Petridou,
2012; Wan et al., 2012).
137
Research Question 3
Research Question 3 was, “Is there a statistically significant relationship between
employee job satisfaction work itself and employee turnover intentions?” The null
hypothesis stated that there is no statistically significant relationship between employee
job satisfaction work itself and employee turnover intentions. A Pearson product-
correlation coefficient was used to determine whether there was a statistically significant
relationship between employee job satisfaction work itself and employee turnover
intentions.
As shown in Table 11, the resulting correlation coefficient was r = -.51 (p < .001).
In conclusion, there was a statistically significant relationship between employee job
satisfaction work itself and employee turnover intentions because p value is less
than .001, which rejected the null hypothesis and the assumptions. The magnitude of the
relationship was high. The result showed an inverse relationship. Therefore, as scores on
employee job satisfaction work itself increase, the scores on employee turnover intentions
decrease.
The study findings revealed the statistically significant relationship between
employee job satisfaction work itself and employee turnover intentions. Study findings
supported the Herzberg’s motivation-hygiene theory (1959). Herzberg argued that when
job satisfaction factors increased, employee job satisfaction increased as well. Islam and
Ali (2013) added that work itself influenced the job satisfaction. Hofaidhllaoui and
Chhinzer (2014) did not support the research findings, believing that satisfaction with
work itself did not influence the employee turnover intentions. In contrary, Ryan et al.
138
(2011) supported the finding results, emphasizing that high satisfaction with work itself
could provide a better employee-customer relationship and increase business relationship.
Research Question 4
Research Question 4 was, “Is there a statistically significant relationship between
employee job satisfaction responsibility and employee turnover intentions?” The null
hypothesis stated that there is no statistically significant relationship between employee
job satisfaction responsibility and employee turnover intentions. A Pearson product-
correlation coefficient applied to determine whether there was a statistically significant
relationship between employee job satisfaction responsibility and employee turnover
intentions.
As shown in Table 11, the resulting correlation coefficient was r = -.52 (p < .001).
In conclusion, there was a statistically significant relationship between employee job
satisfaction responsibility and employee turnover intentions because p value is less
than .001, which rejected the null hypothesis and the assumptions. The magnitude of the
relationship was high. Therefore, as scores on job satisfaction responsibility increase, the
scores on employee turnover intentions decrease.
The study results showed that employee job satisfaction had a statistically
significant relationship with employee turnover intentions. The study results supported
the claim of Herzberg in motivation-hygiene theory (1959). According to Herzberg, when
job satisfaction factors went up, employee turnover intentions went down. Added by
Herzberg that employees must have authority to communicate and authority to use the
resources to accomplish the job assigned without any delays, and be accountable to
139
increase employee performance that influences customer service quality. Gkorezis and
Petridou (2012) and Fernandez and Moldogaziev (2013) supported the notion, stating that
giving authority could empower employees to be innovative in many ways that affects
employee performance and business performance as well.
Research Question 5
Research Question 5 was, “Is there a statistically significant relationship between
employee job satisfaction advancement and growth and employee turnover intentions?”
The null hypothesis stated that there is no statistically significant relationship between
employee job satisfaction advancement and growth and employee turnover intentions. A
Pearson product-correlation coefficient applied to determine whether there was a
statistically significant relationship between employee job satisfaction advancement and
growth and employee turnover intentions.
As shown in Table 11, the resulting correlation coefficient was r = -.37 (p < .001).
In conclusion, there was a statistically significant relationship between employee job
satisfaction advancement, growth, and employee turnover intentions because p value is
less than .001, which rejected the null hypothesis and the assumptions. The magnitude of
the relationship was high. Therefore, as scores on employee job satisfaction advancement
and growth increase, the scores on employee turnover intentions decrease.
The research study findings showed the statistically significant relationship
between job satisfaction advancement, growth, and employee turnover intentions. The
results of the study findings confirmed the claim of Herzberg in motivation-hygiene
theory (1959), proving that when job satisfaction factors increased, and the employee
140
turnover intentions decreased. Van Dam et al. (2013) supported the research study
findings as well, emphasizing that career advancement and growth were indeed sources
of employee turnover intentions. Kraimer et al. (2011) and Carter and Tourangeau (2012)
agreed that with high career growth and advancement, voluntary withdrawal decreased,
and job alternative options decreased. McGilton et al. (2013) added that study results
might increase employee retention rate. Table 12 shows the correlation coefficient results
between job dissatisfaction factors and employee turnover intentions.
Table 12
Pearson Product-Moment Correlation Coefficients Between Job Dissatisfaction Factors
and Employee Turnover Intentions
Job Dissatisfaction Factors
Employee Turnover
Intentions Correlations
(Predictor Variables)
(Criterion Variable)
r
Company policy
Employee turnover
intentions
-0.52
Supervision
Employee turnover
intentions
-0.37
Interpersonal relationship
Employee turnover
intentions
-0.39
Working conditions
Employee turnover
intentions
-0.34
Salary
Employee turnover
intentions
-0.42
Note. N = 144. All correlations were significant at the p < .001 level.
Research Question 6
Research Question 6 was, “Is there a statistically significant relationship between
employee job dissatisfaction company policy and employee turnover intentions?” The
null hypothesis stated that there is no statistically significant relationship between
employee job dissatisfaction company policy and employee turnover intentions. A
141
Pearson product-correlation coefficient applied to determine whether there was a
statistically significant relationship between employee job dissatisfaction company policy
and employee turnover intentions.
As shown in Table 12, the resulting correlation coefficient was r = -.52 (p < .001).
In conclusion, there was a statistically significant relationship between employee job
dissatisfaction company policy and employee turnover intentions because p value is less
than .001, which rejected the null hypothesis and the assumptions. The magnitude of the
relationship was high. The result had an inverse relationship. The greater dissatisfaction
represents the lower scores. Therefore, as scores on employee job dissatisfaction
company policy decrease, the scores on employee turnover intentions increase.
The findings of the study showed the statistically significant relationship between
job employee dissatisfaction company policy and employee turnover intentions. Using
Herzberg’s motivation-hygiene theory with participants in nursing industry, Derby-Davis
(2014) supported the study findings, arguing that satisfying the job dissatisfaction factors
could decrease employee turnover intentions. Kehoe and Wright (2013) agreed that
stating with proper implementation of company policy, employee commitment and job
satisfaction increase resulting in lower employee turnover. Tuzun and Kalemci (2012)
added not only commitment and employee participation would increase, employers could
gain employee trust and loyalty. Moreover, Ghazi et al. (2013) noted that fulfilling the
job dissatisfaction factors increased job performance. Ghazi et al. suggested prioritizing
the job dissatisfaction factors because employee motivation and satisfaction depended on
it.
142
Research Question 7
Research Question 7 was, “Is there a statistically significant relationship between
employee job dissatisfaction supervision and employee turnover intentions?” The null
hypothesis stated that there is no statistically significant relationship between employee
job dissatisfaction supervision and employee turnover intentions. A Pearson product-
correlation coefficient applied to determine whether there was a statistically significant
relationship between employee job dissatisfaction supervision and employee turnover
intentions.
As shown in Table 12, the resulting correlation coefficient was r = -.37 (p < .001).
In conclusion, there was a statistically significant relationship between employee job
dissatisfaction supervision and employee turnover intentions because p value is less
than .001, which rejected the null hypothesis and the assumptions. The magnitude of the
relationship was high. The result had an inverse relationship. The greater dissatisfaction
represents the lower scores. Therefore, as scores on job dissatisfaction supervision
decrease, the scores on employee turnover intentions increase.
The research findings claimed there was an existing statistically significant
relationship between employee job dissatisfaction supervision and employee turnover
intentions. Dike (2012) supported the study findings, arguing that employee supervision
was critical. With high employee supervision inside the organization, employee morale
and job satisfaction increased resulting to negative employee turnover intentions (Dike,
2012). Hofaidhllaoui and Chhinzer (2014) and Kang et al. (2015) also agreed with the
study findings, believing that job satisfaction supervision played an important role in
143
employee turnover intentions. However, Kang et al. emphasized that lack of employee
supervision, employee commitment decreased resulting to increased employee turnover
intentions. Newman and Sheikh (2012) added that with high employee supervision,
employee attachment with the organization was high.
Research Question 8
Research Question 8 was, “Is there a statistically significant relationship between
employee job dissatisfaction interpersonal relationship and employee turnover
intentions?” The null hypothesis stated that there is no statistically significant relationship
between employee job dissatisfaction interpersonal relationship and employee turnover
intentions. A Pearson product-correlation coefficient applied to determine whether there
was a statistically significant relationship between employee job dissatisfaction
interpersonal relationship and employee turnover intentions.
As shown in Table 12, the resulting correlation coefficient was r = -.39 (p < .001).
In conclusion, there was a statistically significant relationship between employee job
dissatisfaction interpersonal relationship and employee turnover intentions because p
value was less than .001, which rejected the null hypothesis and the assumptions. The
magnitude of the relationship was high. The result had an inverse relationship. The
greater dissatisfaction represents the lower scores. Therefore, as scores on employee job
dissatisfaction interpersonal relationship decrease, the scores on employee turnover
intentions increase.
The research findings revealed that employee job dissatisfaction interpersonal
relationship had statistically significant influence to the employee turnover intentions.
144
Derby-Davis (2014) agreed with the results, proving that job dissatisfaction factors
influenced the employee turnover intentions. Tews et al. (2013) added that interpersonal
relationship influenced the actual turnover directly, retention rate, and job embeddedness.
Ghazi et al. (2013) noted that satisfying the interpersonal relationship could influence
motivation and satisfaction. Thus, employee performance increased.
Research Question 9
Research Question 9 was, “Is there a statistically significant relationship between
employee job dissatisfaction working conditions and employee turnover intentions?” The
null hypothesis stated that there is no statistically significant relationship between
employee job dissatisfaction working condition and employee turnover intentions. A
Pearson product-correlation coefficient was formulated to determine whether there was a
statistically significant relationship between employee job dissatisfaction working
conditions and employee turnover intentions.
As shown in Table 12, the resulting correlation coefficient was r = -.34 (p < .001)
In conclusion, a statistically significant relationship exists between employee job
dissatisfaction working conditions and employee turnover intentions because p value was
less than .001, which rejected the null hypothesis and the assumptions. The magnitude of
the relationship was high. The result had an inverse relationship. The greater
dissatisfaction represents the lower scores. Therefore, as scores on employee job
dissatisfaction working conditions decrease, the scores on employee turnover intentions
increase.
145
The research study results revealed the statistically significant relationship
between job dissatisfaction working conditions and employee turnover intentions.
Stinchcomb and Leip (2013) and Yang et al. (2013) agreed with the results, stating that
working conditions influence the employee turnover. With increased employee working
conditions, employee commitment and employee satisfaction increased resulting to low
employee turnover (Jung & Kim, 2012; Stinchcomb & Leip, 2013; Yang et al., 2013).
Morevoer, AlBattat and Som (2013) argued that poor working conditions was a factor to
job dissatisfaction leading to employee turnover intentions. Employee working conditions
was an influential factor to employee voluntary turnover compared to age, gender, and
race (Leip & Stinchcomb, 2013).
Research Questions 10
Research Question 10 was, “Is there a statistically significant relationship
between employee job dissatisfaction salary and employee turnover intentions?” The null
hypothesis stated that there is no statistically significant relationship between employee
job dissatisfaction salary and employee turnover intentions. A Pearson product-
correlation coefficient applied to determine whether there was a statistically significant
relationship between employee job dissatisfaction salary and employee turnover
intentions.
As shown in Table 12, the resulting correlation coefficient was r = -.42 (p < .001).
In conclusion, a statistically significant relationship exists between employee job
dissatisfaction salary and employee turnover intentions because p value was less
than .001, which rejected the null hypothesis and the assumptions. The magnitude of the
146
relationship was high. The results had inverse relationship. The greater dissatisfaction
represents the lower scores. Therefore, as scores on job dissatisfaction salary decrease,
the scores on employee turnover intentions increase.
The study findings results showed that job dissatisfaction salary had statistically
significant relationship with employee turnover intentions. Misra et al. (2013) supported
the research findings, stating that employee salary influenced the employee turnover
intentions directly. Hwang et al. (2014) and Choi et al. (2012), and Nitesh et al. (2013)
supported the notion that employee salary dissatisfaction could lead to turnover
intentions. Nevertheless, employee salary impacted the retention rate and job satisfaction
directly. Brewer et al. (2012) and Carnahan et al. (2012) argued that high salary could
increase retention rate reducing the turnover rate. Choi et al. (2012) added that future
turnover could prevent from occurring with high employee salary.
Multiple Regression
A multiple regression is a statistical test used to determine the criterion variance
associated with the linear combination of predictor variables using R square (R
2)
(Green
& Salkind, 2011). Multiple correlation R can range in value from 0 to 1. The value of
zero means no linear relationship existed between predictor scores and criterion scores
(Green & Salkind, 2011). The value of 1 means the linear combination of predictor
variables predicts the criterion variable perfectly. Values between 0 to 1 means the
relationship is less than perfect linear between predicted variables and criterion variable
(Green & Salkind, 2011).
147
Two multiple regressions were in order to test if the combined factors of the job
satisfaction dimension and the combined factors of the job dissatisfaction dimension
would significantly predict turnover intentions. Table 13 includes the result of R
2
, the
variance of employee turnover intentions associated by the linear combination of job
satisfaction factors and the significant p value. The R
2
results depend on the sample size
of 144 participants.
Table 13
Multiple Regressions With Linear Combination of Job Satisfaction Factors and Employee
Turnover Intentions
R
2
SE of
estimate F P
Model 1 0.35 1.83 5, 138=14.72 .000
Note. R
2
= .35, p < .01.
As Table 13 shows, the five job satisfaction factors used as predictors and
regressed on intention to leave, resulted in an R
2
= .35. This process indicates that
approximately 35% of the variance in the intention to leave scores by the combined
influence of the factors. Further, the ANOVA shows that this value was statistically
significant (p = .000). Examining in the standardized coefficients is important to assess
the relative strengths of the individual contribution of the predictors to the equation.
Table 14 shows the multiregression results with individual factor of job satisfaction.
148
Table 14
Multiple Regressions With Individual Factor of Job Satisfaction and Employee Turnover
Intentions
Predictor Variables
B β t Sig (p)
(Constant) 11.268
14.023
Achievement
.018
.034
.399
.691
Recognition
-.079
-.164
-1.312
.192
Work itself
-.137
-.257
-2.753
.007
Responsibility
-.144
-.275
-2.831
.005*
Career and
advancement -.002
-.003
-.031
.976
Note. * p < .05, ** p < .01.
Table 14 also shows the results that only one factor was statistically significant on
an individual level, responsibility (β = -.275, p = .005). The other factors (achievement,
recognition, work itself, and career advancement and growth) failed to achieve
significance. Thus, five factors of the job satisfaction dimension do significantly predict
intention to leave, and on an individual basis, a significant negative correlation exists
between the responsibility factor and intention to leave. Specifically, higher scores, which
indicate greater job satisfaction, predict less intention to leave. Table 15 includes the
result of R
2
, the variance of employee turnover intentions associated by the linear
combination of job dissatisfaction factors and the significant p value. The R
2
results
correlates with the sample size of 144 participants.
149
Table 15
Multiple Regressions With Linear Combination of Job Dissatisfaction Factors and
Employee Turnover Intentions
R
2
SE of
estimate F P
Model 1 0.31 1.88 5, 138=15.50 .000
Note. R
2
= .31, p < .01.
Table 15 shows the results of the second multiple regressions wherein the five job
dissatisfaction factors regressed on the intention to leave scores. The resulting
R
2
= .31, indicates that approximately 31% of the variance in the intention to leave scores
is by the combination of the dissatisfaction scores. Table 16 shows the multiregression
results in individual basis.
150
Table 16
Multiple Regressions With Individual Factor of Job Dissatisfaction and Employee
Turnover Intentions
Predictor Variables B β T Sig (p)
(Constant) 11.187
11.028
Company policy -.206
-.393
-3.939
.000**
Supervision -.032
-.057
-.612
.542
Interpersonal
relationship .033
.064
.575
.566
Working conditions -.058
-.088
-1.044
.298
Salary -.085
-.189
-1.887
.061
Note. * p < .05, ** p < .01.
On an individual basis, a review of the standardized coefficients in table 16
reveals that one of the factors had significant contributor, which was company policy (β =
-.393, p = .000). The remaining four factors (supervision, interpersonal relationship,
working conditions, and salary) were not statistically significant. The five combined
factors in the dimension of job dissatisfaction do significantly predict intention to leave.
In addition, a negative association exists between intentions to leave and the individual
factor of company policy so that lower score on this factor is with higher intention to
leave score.
151
Applications to Professional Practice
The examination involved determining the potential relationship between job
satisfaction factors, job dissatisfaction factors, and employee turnover intentions to accept
or reject the research study hypotheses. The research findings results rejected the
hypotheses, showing that job satisfaction factors and job dissatisfaction factors had
statistically significant relationships with the employee turnover intentions. The study
results also revealed different criterion variances of employee turnover intentions
associated with job satisfaction factors and job dissatisfaction factors. In this case, job
satisfaction factors had higher criterion variance than the job dissatisfaction factors.
The findings of the research study are relevant to improving business practices,
because the results provided better information about the job satisfaction factors and job
dissatisfaction factors that influence employee turnover intentions. Managers can assess
and analyze each factor based on the magnitude of the relationship. Through analysis,
managers can provide better recommendations to improve the situations. With proper and
effective implementation, managers may reduce or prevent employee turnover from
occurring, leading to business financial sustainability and long-term growth.
In addition, addressing the concerns of the employees in effective ways can assist
managers concentrating on the core functions of the business to meet the business goals
and objectives. Employees on the other hand will be able to focus on the job assignments
resulting to increased work participation, engagement, and commitment. Customers’
satisfaction will increase and business-relationship will develop leading to repeat orders
152
and business referrals. In community aspect, community will enjoy having peace,
healthy, and friendly environment.
Implications for Social Change
The implications of the research study findings to social change are leaders may
focus on the well-being of the employees by providing better promotional opportunity,
career advancement and growth, compensation packages, company policy, organizational
support, and healthy and safe working environment. Focusing on employees’ well-being
enhances employee competence, morale, motivation, performance, engagement, and
commitment leading to increased retention rate and decreased employee turnover.
Organizational business financial performance can be sustainable and long-term business
growth can achieve successfully. Rates of poverty and crime will decrease. Therefore,
communities will be able to enjoy safe, healthy, and friendly environment.
Recommendations for Action
The research study findings are very critical because it plays important roles to
employees, managers, leaders, customers, vendors, and community. Leaders need to pay
attention to the results because the increasing employee turnover is costly and disruptive.
By addressing the job satisfaction factors and job dissatisfaction factors that influence
the employee turnover intentions directly can help reduce or prevent the employee
turnover.
In addition, improving their business visions can impact the employees’ situation
and business image as whole. Focusing on nonfinancial aspects of the business, such as
improving the well-being of employees will lead to positive results. Maslow (1943)
153
stated that employees have five basic needs (a) physiological needs, (b) safety, (c) social,
(d) self-esteem, and (d) growth needs or self-actualization. Without satisfying the human
basic needs, employee performance and employee effectiveness decreases (Adiele &
Abraham, 2013).
Managers need to pay attention to the results as well so they can focus more on
the core functions of the business. Table 11 includes the significant relationships between
the job satisfaction factors and employee turnover intentions. In job satisfaction factors,
employee responsibility (-.52) had a higher statistically significant relationship with
employee turnover intentions, followed by work itself (-.51), recognition (-.49), career
advancement and growth (-.37), and achievement or quality performance (-.26), which
had a lower statistically significant relationship with employee turnover intentions.
Correlation coefficient results (magnitude) can categorize as low (.10), medium (.30), and
high (.50) regardless of sign.
Employee responsibility had a statistically significant relationship with employee
turnover intentions (r = -.52, p < .001). Therefore, manager must focus on increasing
employee responsibility. Employee responsibility is critical to employee and business
performance. Thus, managers must empower the employees to do the jobs with
competence. Empowering employees such as giving the authority to communicate with
customers, handle the resources, and be accountable allows them to be innovative in
many ways such as improving the quality customer services and business process
(Fernandez & Moldogaziev, 2013; Herzberg, 1974; Herzberg et al., 1959).
154
Work itself had a statistically significant relationship with employee turnover
intentions (r = -.51, p < .001). Therefore, managers must focus on empowering
employees to increase employee communication inside and outside the organization. In
work itself factor, Herzberg et al. (1959) emphasized the important roles of employee
communication that impacted business relationship with customers and employee
relationship. Effective communication with customers can lead to increased customer
quality performance and customer-employee business relationship, leading to increased
business transactions and reducing employee turnover (Ryan et al., 2011).
Employee recognition had a statistically significant relationship with employee
turnover intentions (r-.49, p < .001). Therefore, managers must recognize employees
based on the performance or non-performance with feedback (Byron & Khazanchi, 2012;
Herzberg et al., 1959; Webster & Beehr, 2012). Positive feedback allows employees to be
creative and empower them psychologically (Byron & Khazanchi; Yao & Cui, 2010).
Managers can also recognize employees through financial incentives or promotional
opportunities (Gkorezis & Petridou, 2012; Wan et al., 2012). Financial incentives can
increase employees’ performance that impact company performance (Gkorezis &
Petridou, 2012). Promotional opportunity can lead to increased employee commitment
and job embeddedness with the organization. Recognizing and appreciating employees’
effort can increase employees’ commitment, contribution to the organization, employee
performance that impacts customer services (Eisenberger et al., 1990; Gavino et al.,
2012; Haines III & St-Onge, 2012; Hogan et al., 2013).
155
Advancement and growth had a statistically significant relationship with
employee turnover intentions (r = -.37, p < .001). Therefore, managers must pay attention
on improving this factor. According to Lester (2013) and Matache and Ruscu (2012),
advancement and growth increases employee job satisfaction. Nouri and Parker (2013)
added that having employee advancement and growth, employee commitment increases
as employee turnover intentions decreases. Advancement and growth depends on
learning where employee training is critical (Herzberg, 1974; Herzberg et al., 1959;
Maslow, 1943). Therefore, managers must train and develop employees to increase their
competence as to increase their opportunity to achieve their advancement and growth.
Achievement or quality performance had a statistically significant relationship
with employee turnover intentions (r = -.26, p < .001). Employee achievement is a
leading factor to employee job satisfaction (Herzberg et al., 1959). Therefore, managers
must focus on increasing employee achievement. Employee achievement can achieve by
providing employee training and development (Islam & Ali, 2013; Teck-Hong &
Waheed, 2011). Managers must train their employee periodically to increase their
competence. Training allows employees to increase self-efficacy and communication
with the customers, resulting in an increase of quality performance (Mathe & Scott-
Halsell, 2012). Kanten (2014) suggested improving job characteristics, such as skill
variety, task identity, task significance, feedback, and autonomy.
Table 12 includes the significant relationships between the job dissatisfaction
factors and employee turnover intentions. Among the job dissatisfactory factors,
company policy (-.52) had a higher statistically significant relationship with the employee
156
turnover intentions, followed by salary (-.42), interpersonal relationship (-.39),
supervision (-.37), and working conditions (-.34). Correlation coefficient results
(magnitude) can categorize as low (.10), medium (.30), and high (.50) regardless of sign.
Company policy had a statistically significant relationship with employee
turnover intentions (r = -.52, p < .001). Therefore, managers must communicate the
company policy with employees clear and easy to understand. Kehoe and Wright (2013)
said that with proper assessment and implementation of company policy, employee job
satisfaction and commitment increases as employee turnover decreases. Tuzun and
Kalemsi (2012) added that with effective company policy, employee participation,
loyalty, and trust increases as well.
Salary had a statistically significant relationship with employee turnover
intentions (r = -.42, p < .001). Thus, manager must reassess the employee salary
periodically. Nyberg (2010) argued that periodic reassessment can improve the employee
performance resulting to improve business performance as well. Maslow (1943)
mentioned the importance of physiological needs. Without paying attention to employee
salary, employees will not be able to meet the physiological needs. Misra et al. (2013)
emphasized that employee salary can impact job satisfaction, motivation, retention,
performance, and employee turnover intentions.
Interpersonal relationship had a statistically significant relationship with
employee turnover intentions (r = -.39, p < .001). Interpersonal relationships such as
relationships with employers, co-workers, and peers are critical to employees. Thus,
managers need to focus on developing the relationships. Having effective interpersonal
157
increases job embeddedness, attachment, retention rate, and reduces employee turnover
intentions (Tews et al., 2013). Gkorezis and Petridou (2012) added that interpersonal
relationship can increase employee motivation and support the employees’ well-being
and mental health. With positive interpersonal relationships, employee competence
increases as customer service relationship increases as well (Gkorezis & Petridou, 2012).
Employee supervision had a statistically significant relationship with employee
turnover intentions (r = -.37, p < .001). Therefore, the role of the manager or supervisor is
critical because they communicate the culture of organization (Dike, 2012). With
collaborative, friendly, and supportive culture, employee morale and participation
increase as employee turnover intentions decrease (Dike, 2012). Supervisor’s role is
important because employee’s behavior and attitude can impact positively (Eisenberger et
al., 1990). With full support from superiors, employees become powerful and responsible
and show that managers value employees as individuals, and they care about their
feelings and well-being (Gkorezis & Petridou, 2012; Kang et al., 2015).
Working conditions had a statistically significant relationship with employee
turnover intentions positively (r = -.34, p < .001). Working conditions is vital for
employees’ success. Therefore, managers must consider reassessing their working
conditions to increase employees’ performance. Maintaining safe, friendly, and healthy
environment can also invite employees to stay and increase job satisfaction that affects
employee turnover (Matz et al., 2013; Vasquez, 2014). In addition (Michel et al., 2013)
supported that healthy environment increases employee performance and motivation
resulting to high quality customer service.
158
In addition, Table 13 and 15 include the statistically significant relationships
between variables and variances of employee turnover intentions associated by combined
job satisfaction factors and combined job dissatisfaction factors. In conclusion, the
combined linear job satisfaction factors predicted the employee turnover intention
because the p value was less than .001, which revealed a statistically significant
relationship between variables. The combined linear job dissatisfaction factors predicted
the employee turnover intention as well, because the p value was less than .001, which
revealed a statistically significant relationship between variables.
Overall, the combined linear job satisfaction factors (35%) had greater predictions
on employee turnover intentions than combined linear job dissatisfaction factors (31%).
Thus, fast food managers must focus on enhancing the job satisfaction factors to increase
the rate of employee retentions, reducing the rate of employee turnover. Other suggestion
is to leverage the job dissatisfaction factors to decrease employees’ dissatisfaction,
reducing the employee turnover intentions.
In individual level of job satisfaction factors and employee turnover intentions
using multiregression analysis, Table 14 shows that only employee responsibility had a
statistically significant relationship with employee turnover intentions using p value with
less than .005. The Beta (β) weight under standardized coefficient (β -.275) shows that
employee responsibility had an inversed relationship with employee turnover intentions.
The magnitude of the relationship varies from .10, .30, and .50; low, medium, and high
respectively. A lower score in employee dissatisfaction factor is equal to higher score in
159
dissatisfaction factor. Therefore, employees have less chance to leave the current job. The
magnitude of the relationship is low. Therefore, the employee turnover intention is low.
In individual level of job dissatisfaction factors and employee turnover intentions
using multiregression analysis, Table 16 shows that only company policy had a
statistically significant relationship with employee turnover intentions using p value,
which was less than .001. The Beta (β) weight under standardized coefficient (β -.393)
shows that company policy had a reversed relationship with employee turnover intention.
The magnitude of the relationship varies from .10, .30, and .50; low, medium, and high
respectively. Higher score of dissatisfaction factor is equal to lower score of the
employee dissatisfaction. Therefore, employees have greater chance to leave the current
job.
The findings results can be disseminated using networking, blogging, meetings,
and trainings. Networking can start with affiliation at organizations, universities,
institutions, and corporations. Membership allows members share their research study so
other members can benefit from it. Sharing may help improve the situation of the
individuals, organizations, employees, and customers. Creating a personal website can
also use for disseminating the research findings. Oftentimes, blogging can lead to
exchanging ideas, expanding the research topics, and increasing knowledge about the
phenomenon. On the other hand, training and meeting inside the office job are helpful to
disseminate the research findings. Sharing the research findings via PowerPoint can
enhance the knowledge of employees and management team to understand why and how
employee turnover can prevent from occurring.
160
Recommendations for Further Research
The correlational quantitative method was used in this study to determine the
relationships between two variables to answer the given hypotheses. An Internet survey
was employed to address the hypotheses based on the opinions or experiences of the
employees. The survey questionnaires were psychometric scales using preformatted
survey questions, which limited the participants to express their opinions. Therefore,
recommending using the case study may help further explain the phenomenon and get
better understanding why and how individuals experienced the phenomenon.
The design used in the study was an internet survey. Although online survey
could access based on the convenience of the participants, busy job schedules, no
computer access, and low computer aptitude became issues for participants to access the
online survey. However, hard copies of survey questionnaire helped employees’
participate successfully.
The survey questionnaire was a Likert-type scale where participants could choose
the answer based on their understanding, which limited participants to expand or express
their opinions about the phenomenon. Therefore, using personal interview with
semistructured design may help improve the situation. Using the design, the participants
could explain their experiences in a more meaningful way than just answering the
questions by using ordinal scale. A better explanation of the phenomenon can provide a
better understanding. Having a broad understanding about the phenomenon can lead to
better solutions to the problems.
161
The targeted sample size was 130 participants based on the recommended
computation by Tabachnick and Fidell (2007). Although participants were able to
participate, completing the survey was challenging in terms of target time completion.
Most of participants had busy schedules, alternate job assignments, changed their
decisions not to participate, and management approval was delayed that required more
than one week visit. Therefore, suggesting increasing the targeted sample size may help
resolve the issues. The target population of the study included employees working at fast
food restaurants on the East Coast in the United States, under lower-level management or
nonmanagerial positions. Therefore, the study findings results could only generalize on
this specific region, participants, and job positions.
Reflections
The DBA Doctoral Study process was very challenging. Every process needed to
be rigorous to ensure meeting and exceeding the requirements of the Walden University,
such as DBA rubric requirements, APA, IRB review process, and faculty members to
protect the participants and myself as a researcher from any legal issues. Meeting and
exceeding the requirements implied a higher scholarly recognition by writing,
communicating, and networking with others.
Collection of data was a challenging process. Some participants and community
supporters understood and appreciated the importance and benefits of the research study.
That is why invitation to participate became smooth. Other participants and community
supporters considered the research study participation was a waste of time, a conflict of
interest, a conflict with their schedule, and often they did not care at all. I had to increase
162
my targeted areas and spend more time achieving saturation to ensure I exceeded the
required sample size.
The JSS and ILJ surveys covered most of the variables of the study. The JSS and
ILJ survey results provided better understanding about the relationships of job
satisfaction factors, job dissatisfaction factors, and employee turnover intentions.
Different views and perspectives of the participants of the study helped understand the
employees’ concerns to minimize the increasing employee turnover. On the other hand,
because the JSS survey was a Likert-type scale where participants depended on multiple
choices, participants became limited to express their opinions and perspectives about the
phenomenon.
Conducting the research study as a whole was a challenging yet rewarding at the
end. It was rewarding because I had a chance to meet people with diverse background.
This journey increased my confidence personally and professionally. Friendship and trust
were developed that might lead to another opportunity to invite them for future research.
Opportunity to hear their concerns and shared my concerns were the best things I had
ever experienced in this challenging journey. Although research study was not as easy as
I had thought, learning that many out there needed to share their concerns to give proper
attentions had encouraged me to do it again in the near future.
Summary and Study Conclusions
The purpose of the quantitative correlational study was to examine the
relationships of the job satisfaction factors, job dissatisfaction factors, and employee
turnover intentions to answer the given hypotheses. With the help of SPSS analysis using
163
Pearson’s correlation coefficient and Multi regression, both job satisfaction predictors
and job dissatisfaction factors had statistically significant relationships with the criterion
variable because the p value is less than .001, which rejected the null hypotheses and the
assumptions. The magnitude of the relationships between variables varies.
In conclusion, research study findings in Table 11 show that in job satisfaction
factors, employee responsibility (-.52) had a higher statistically significant relationship
with employee turnover intentions, followed by work itself (-.51), recognition (-.49),
career advancement and growth (-.37), and achievement or quality performance (-.26),
which had a lower statistically significant relationship with employee turnover intentions.
As the results show in Table 12, in job dissatisfactory factors, company policy (-.52) had
a higher statistically significant relationship with the employee turnover intentions,
followed by salary (-.42), interpersonal relationship (-.39), supervision (-.37), and
working conditions (-.34), which had a lower statistically significant relationship with
employee turnover intentions. Correlation coefficient results (magnitude) can categorize
as low (.10), medium (.30), and high (.50) regardless of sign.
The other purpose of the study was to evaluate how well the linear combination of
job satisfaction factors and job dissatisfaction factors predict the criterion variance. In
Table 13, the results show the R
2
results for the combined job satisfaction factors and the
p value. The p value was less than .001, which shows the significant relationship between
the linear combination of job satisfaction factors and employee turnover intentions. The
criterion variance of employee turnover intentions associate with job satisfaction factors
was 35%. For an individual factor level based on the results in Table 14, only
164
responsibility had a significant negative relationship with employee turnover intentions,
which influences the employee turnover by .27, which scores low. Therefore, the lower
scores on job satisfaction responsibility, the higher the scores on employee turnover
intentions. The rest of the factors indicate no significant relationships with employee
turnover.
Table 15 illustrates the R
2
results for the combined job dissatisfaction factors and
the p value. The p value was less than .001, which shows the significant relationship
between the linear combination of job dissatisfaction factors and employee turnover
intentions. The criterion variance of employee turnover intentions associated with job
dissatisfaction factors was 31%, which significantly relates to employee turnover
intentions. On individual factor level based on the results in Table 16, company policy
had a negative relationship with employee turnover intentions, which impacts .39 of
employee turnover intentions. The greater dissatisfaction represents lower scores.
Therefore, the lower scores on dissatisfaction factor, the higher scores on employee
turnover intentions. The remaining factors did not show any significant relationships with
employee turnover intentions. In conclusion, the linear combination of job satisfaction
factors predicted the criterion variance of employee turnover intentions by 35%, which
was higher than job dissatisfaction factors at 31%.
As suggested, managers must focus on the results of the statistical significant
relationships between job satisfaction factors, job dissatisfaction factors, and employee
turnover intentions. Reassess, analyze, and evaluate them effectively, so they will be able
to implement effective strategies and approaches to resolve the issues. Resolving the
165
issues in ways that are more effective can prevent the employee turnover from occurring,
leading to business stability and long-term growth. In addition, employee job satisfaction,
engagement, commitment, motivation, and morale increases, leading to increased
retention rates and decreased employee turnover rates.
166
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208
Appendix A: Job Satisfaction Survey
JOB SATISFACTION SURVEY
Paul E. Spector
Department of Psychology
University of South Florida
Copyright Paul E. Spector 1994,
All rights reserved.
PLEASE CIRCLE THE ONE
NUMBER FOR EACH QUESTION
THAT COMES CLOSEST TO
REFLECTING YOUR OPINION
ABOUT IT.
Disagree very much
Disagree moderately
Disagree slightly
Agree
slightly
Agree moderately
Agree very much
1
I feel I am being paid a fair amount for
the work I do.
1 2 3 4 5 6
2 There is really too little chance for
promotion on my job.
1 2 3 4 5 6
3 My supervisor is quite competent in
doing his/her job.
1 2 3 4 5 6
4
I am not satisfied with the benefits I
receive.
1 2 3 4 5 6
209
5 When I do a good job, I receive the
recognition for it that
I should receive.
1 2 3 4 5 6
6 Many of our rules and procedures make
doing a good job difficult.
1 2 3 4 5 6
7 I like the people I work with. 1 2 3 4 5 6
8 I sometimes feel my job is meaningless. 1 2 3 4 5 6
9 Communications seem good within this
organization.
1 2 3 4 5 6
10
Raises are too few and far between. 1 2 3 4 5 6
11
Those who do well on the job stand a
fair chance of being promoted.
1 2 3 4 5 6
12
My supervisor is unfair to me. 1 2 3 4 5 6
13
The benefits we receive are as good as
most other organizations offer.
1 2 3 4 5 6
14
I do not feel that the work I do is
appreciated.
1 2 3 4 5 6
15
My efforts to do a good job are seldom
blocked by red tape.
1 2 3 4 5 6
16
I find I have to work harder at my job
because of the incompetence of people I
1 2 3 4 5 6
210
PLEASE CIRCLE THE ONE
NUMBER FOR EACH QUESTION
THAT COMES CLOSEST TO
REFLECTING YOUR OPINION
ABOUT IT.
Copyright Paul E. Spector
1994, All rights reserved.
Disagree very much
Disagree moderately
Disagree slightly
Agree slightly
Agree moderately
Agree very much
19
I feel unappreciated by the organization
when I think about what they pay me.
1 2 3 4 5 6
20
People get ahead as fast here as they do
in other places.
1 2 3 4 5 6
21
My supervisor shows too little interest
in the feelings of subordinates.
1 2 3 4 5 6
22
The benefit package we have is
equitable.
1 2 3 4 5 6
work with.
17
I like doing the things I do at work. 1 2 3 4 5 6
18
The goals of this organization are not
clear to me.
1 2 3 4 5 6
211
23
There are few rewards for those who
work here.
1 2 3 4 5 6
24
I have too much to do at work. 1 2 3 4 5 6
25
I enjoy my coworkers. 1 2 3 4 5 6
26
I often feel that I do not know what is
going on with the organization.
1 2 3 4 5 6
27
I feel a sense of pride in doing my job. 1 2 3 4 5 6
28
I feel satisfied with my chances for
salary increases.
1 2 3 4 5 6
29
The benefit package we have is
equitable.
1 2 3 4 5 6
30
I like my supervisor. 1 2 3 4 5 6
31
I have too much paperwork. 1 2 3 4 5 6
32
I don't feel my efforts are rewarded the
way they should be.
1 2 3 4 5 6
33
I am satisfied with my chances for
promotion.
1 2 3 4 5 6
34
There is too much bickering and
fighting at work.
1 2 3 4 5 6
35
My job is enjoyable. 1 2 3 4 5 6
36
Work assignments are not fully 1 2 3 4 5 6
212
explained.
213
Appendix B: Turnover Intention to Leave the Job Scale
(Hom, Griffeth, & Sellaro, 1984)
1……………... 2……………… 3…………...... 4……………. 5 …………….
Certainly Probably Not sure Probably Certainly
Not Not
Certainly Certainly
not
1. What are the chances that you will remain in the 1 2 3 4 5
profession but leave the organization at or before
the end of the year?
2. What are the chances that you will leave your job 1 2 3 4 5
214
Appendix C: Demographic Questions
The following statements are for demographical classification only. Please check
one response per statement.
Gender (Please Check One): __ Male __ Female
Age (Please Check One): __ 18-28 years __29-39 years __40-50 years __51-61
years __62-72 years
Educational Attainment (Please Check One): __ High
school__Vocational__Undergraduate(1-3)__Bachelor degree__Others
Current Position (Please Check One): __ Cashier(Drive thru/Front line)__Runner
(Counter and drive thru)__Fry person__Meats person__Initiator__Assembler__Others
Job classification (Please Check One): __ Part-time__ Full time
Years of working with current (Please Check One): __ 5 years__ 10 years__15
years__ 20 years
Would like to view results of survey___yes___no. If yes, send to
_________________________________________________.
215
Appendix D: Permission to use Job Satisfaction Survey
From: Spector, Paul <pspector@usf.edu>
Date: Fri, Feb 27, 2015 at 7:23 AM
Subject: RE: Permission to use Jo Satisfaction Survey
To: Imelda Bebe <imelda.bebe@waldenu.edu>
Dear Imelda:
You have my permission to use the JSS in your research under the conditions you
describe. You can find copies of the scale in the original English and several other
languages, as well as details about the scale's development and norms in the Scales
section of my website http://shell.cas.usf.edu/~spector. I allow free use for
noncommercial research and teaching purposes in return for sharing of results. This
includes student theses and dissertations, as well as other student research projects.
Copies of the scale can be reproduced in a thesis or dissertation as long as the copyright
notice is included, "Copyright Paul E. Spector 1994, All rights reserved." Results can be
shared by providing an e-copy of a published or unpublished research report (e.g., a
dissertation). You also have permission to translate the JSS into another language under
the same conditions in addition to sharing a copy of the translation with me. Be sure to
include the copyright statement, as well as credit the person who did the translation with
the year.
Thank you for your interest in the JSS, and good luck with your research.
Best,
Paul Spector, Distinguished Professor
Department of Psychology
PCD 4118
University of South Florida
Tampa, FL 33620
813-974-0357
http://shell.cas.usf.edu/~spector
216
From: Imelda Bebe [mailto:[email protected]]
Sent: Friday, February 27, 2015 12:43 AM
To: Spector, Paul
Subject: Permission to use Jo Satisfaction Survey
Dear Dr. Spector:
I am a doctoral student from Walden University writing my dissertation titled “Employee
Turnover Intention in the Fast Food Industry in the United States” under the direction of
my dissertation committee chaired by Dr. Charles Needham.
I would like to request your permission to use an existing survey instrument (Job
Satisfaction Survey) in my research study. I would like to use and print your survey
instrument under the following conditions:
· I will use this survey instrument only for my research study
· I will not sell or use it with any compensated or curriculum development activities.
· I will include a copyright statement on all copies of the instrument.
· I will send my research study and one copy of reports, articles, and the like that
make use of these survey data promptly to your attention.
If these are acceptable terms and conditions, please indicate by signing one copy of this
letter. Kindly return it to me either through postal mail or e-mail: Imelda A. Bebe, 163
Russell Dr. Tiverton, RI 02878 or [email protected].
Sincerely,
Imelda A. Bebe
Walden University-Doctoral student
Signature
217
Appendix E: Permission to use the Turnover Intention Survey
Peter Hom <peter.hom@asu.edu> Tue, Nov 18, 2014 at 12:20 AM
To: Imelda Bebe <imelda.bebe@waldenu.edu>Sure, you have my permission.
Best, peter hom
From: Imelda Bebe [mailto:[email protected]]
Sent: Monday, November 17, 2014 10:19 PM
To: Peter Hom
Subject: Permission to use the survey Turnover Intention
November 17, 2014
Dr. Peter Hom
Professor
Department of Management
W.P Carey School of Business
Arizona State University
Tempe, Arizona 85287-4006
Dear Dr. Hom:
I am a doctoral student from Walden University writing my dissertation titled “Employee
Turnover Intention in the Fast Food Industry in the United States” under the direction of
my dissertation committee chaired by Dr. Charles Needham.
I would like to request your permission to use an existing survey instrument (Turnover
Intention) in my research study. I would like to use and print your survey instrument
under the following conditions:
I will use this survey instrument only for my research study
I will not sell or use it with any compensated or curriculum development
activities.
I will include a copyright statement on all copies of the instrument.
I will send my research study and one copy of reports, articles, and the like that
make use of these survey data promptly to your attention.
If these are acceptable terms and conditions, please indicate by signing one copy of this
letter. Kindly return it to me either through postal mail or e-mail: Imelda A. Bebe, 163
Russell Dr. Tiverton, RI 02878 or [email protected].
Sincerely,
Imelda A. Bebe
Walden University-Doctoral student
218
Signature
_______________________________________
Expected date of completion _/_/2015
Excerpted from Simon, M. K. (2011). Dissertation and scholarly research: Recipes for
success (2011 Ed.). Seattle, WA, Dissertation Success, LLC.
219
Appendix F: Copyright Clearance to Reuse Herzberg’s Motivation-Hygiene Theory
Title: Motivation-hygiene
profiles: Pinpointing
what ails the
organization
Author: Frederick Herzberg
Publication:
Organizational
Dynamics
Publisher: Elsevier
Date: Autumn 1974
Copyright © 1974 Published by
Elsevier Inc.
Permission Request Submitted
Your request is now under review.
You will be notified of the decision via email.
Please print this request for your records.
Get the printable order details.
Order Number 501081492
Order Date Nov 18, 2015
Licensed content publisher Elsevier
Licensed content
publication
Organizational Dynamics
Licensed content title Motivation-hygiene profiles: Pinpointing what ails the
organization
Licensed content author Frederick Herzberg
220
Licensed content date Autumn 1974
Licensed content volume
number
3
Licensed content issue
number
2
Number of pages 12
Type of Use reuse in a thesis/dissertation
Portion Excerpt
Number of excerpts 1
Format both print and electronic
Are you the author of this
Elsevier article?
No
Will you be translating? No
Title of your
thesis/dissertation
Employee Turnover Intention in the Fast Food Industry
in the United States
Expected completion date Dec 2015
Elsevier VAT number GB 494 6272 12
Customer Tax ID UM0
Permissions price Not Available
VAT/Local Sales Tax Not Available
Total Not Available
Copyright © 2015 Copyright Clearance Center, Inc. All Rights Reserved. Privacy
.
Terms and Conditions.
Comments? We would like to hear from you. E
-mail us at custom[email protected]
221
License Details
Thank you very much for your order. This is a License Agreement between Imelda Bebe
("You") and Elsevier ("Elsevier"). The license
consists of your order details, the terms and conditions provided by Elsevier, and the
payment terms and conditions.
Get the printable license.
License Number 3753040305326
License date
Nov 18, 2015
Licensed Content
Publisher
Elsevier
Licensed Content
Publication
Organizational Dynamics
Licensed Content Title Motivation-hygiene profiles:
Pinpointing what ails the organization
Licensed Content
Author
Frederick Herzberg
Licensed Content Date Autumn 1974
Licensed content
volume number
3
Licensed content issue
number
2
Number of pages 12
Type of Use reuse in a thesis/dissertation
Portion excerpt
Number of excerpts 1
Format both print and electronic
Are you the author of
this Elsevier article?
No
Will you be translating?
No
Title of your Employee Turnover Intention in the
222
thesis/dissertation Fast Food Industry in the United States
Expected completion
date
Dec 2015
Elsevier VAT number GB 494 6272 12
Customer Tax ID UM0
Price 0.00 USD
VAT/Local Sales Tax 0.00 USD / 0.00 GBP
Total 0.00 USD
223
Appendix G: Certification of Completion
The National Institutes of Health (NIH) Office of Extramural Research certifies that
Imelda Bebe successfully completed the NIH Web-based training course “Protecting
Human Research Participants”.
Date of completion: 03/10/2012
Certification Number: 885747
224
Appendix H: Consent Form
You are invited to take part in a research study of Employee turnover intentions in the
fast food industry. The researcher is inviting employees who work in the fast food
industry in the east coast of United States under low-level management or non-
managerial position with minimum age 18, part-time or full-time, and either gender to be
in the study. This form is part of a process called “informed consent” to allow you to
understand this study before deciding whether to take part.
This study is being conducted by a researcher named Imelda A. Bebe, who is a doctoral
student at Walden University.
Background Information:
The purpose of this study is to ask your opinions regarding the factors that contribute to
employee job satisfaction, job dissatisfaction, and turnover intentions in the fast food
industry.
Procedures:
If you agree to be in this study, you will be asked to:
• Participate in a 15 minutes survey
• Data will be collected once
• Survey must be answered completely
• Questions are multiple choices
Here are some sample questions:
____ I feel I am being paid a fair amount for the work I do.
____There is really too little chance for promotion on my job.
____My supervisor is quite competent in doing his/her job.
Voluntary Nature of the Study:
This study is voluntary. Everyone will respect your decision of whether or not you
choose to be in the study. No one at Walden University will treat you differently if you
decide not to be in the study. If you decide to join the study now, you can still change
your mind later. You may stop at any time.
Risks and Benefits of Being in the Study:
Being in this type of study involves some risk of the minor discomforts that can be
encountered in daily life, such as fatigue or stress. Being in this study would not pose risk
to your safety or wellbeing.
225
This study helps participants share their opinions regarding the factors that contribute to
their satisfaction and dissatisfaction towards their job, or aspects of job to improve the
employees’ conditions.
Payment:
No rewards are provided for participants.
Privacy:
Any information you provide will be kept confidential or anonymous. The researcher
will not use your personal information for any purposes outside of this research project.
Also, the researcher will not include your name or anything else that could identify you in
the study reports. Data will be kept secure by using encrypted password through MS
Office and will be stored in a locked cabinet. Data will be kept for a period of at least 5
years, as required by the university.
Contacts and Questions:
You may ask any questions you have now. Or if you have questions later, you may
contact the researcher via [email protected] or 401-855-1772. If you want to
talk privately about your rights as a participant, you can call Dr. Leilani Endicott. She is
the Walden University representative who can discuss this with you. Her phone number
is 612-312-1210. Walden University’s approval number for this study is 07-16-15-
0327769 and it expires on July 15, 2016.
Please print or save this consent form for your records.
Statement of Consent:
I have read the above information and I feel I understand the study well enough to make a
decision about my involvement. By clicking the link below, “I consent,” I understand that
I am agreeing to the terms described above.
226
Appendix I: Confidentiality Agreement
Name of Signer:
During the course of my activity in collecting data for this research: “Employee
Turnover Intention in the Fast Food Industry in the United States” I will have access to
information, which is confidential and should not be disclosed. I acknowledge that the
information must remain confidential, and that improper disclosure of confidential
information can be damaging to the participant.
By signing this Confidentiality Agreement I acknowledge and agree that:
1. I will not disclose or discuss any confidential information with others, including
friends or family.
2. I will not in any way divulge, copy, release, sell, loan, alter or destroy any
confidential information except as properly authorized.
3. I will not discuss confidential information where others can overhear the
conversation. I understand that it is not acceptable to discuss confidential information
even if the participant’s name is not used.
4. I will not make any unauthorized transmissions, inquiries, modification or purging of
confidential information.
5. I agree that my obligations under this agreement will continue after termination of
the job that I will perform.
6. I understand that violation of this agreement will have legal implications.
7. I will only access or use systems or devices I’m officially authorized to access and I
will not demonstrate the operation or function of systems or devices to unauthorized
individuals.
Signing this document, I acknowledge that I have read the agreement and I agree to
comply with all the terms and conditions stated above.
Signature: Date:
227
Appendix J: Letter of Cooperation from a Research Partner
Community Research Partner Name
Contact Information
Date
Dear Imelda,
Based on my review of your research proposal, I give permission for you to conduct the
study entitled Employee Turnover Intentions in the Fast Food Industry within the Insert
Name of Community Partner. As part of this study, I authorize you to access
participants, use the facility to conduct research if necessary, and use personnel time for
the purpose of research. Individuals’ participation will be voluntary and at their own
discretion.
We understand that our organization’s responsibilities include: room for research study
inside the facility, support and supervision from in charge personnel, and connection to
WIFI. We reserve the right to withdraw from the study at any time if our circumstances
change.
The student will be responsible for complying with our site’s research policies and
requirements, including Describe requirements.
I confirm that I am authorized to approve research in this setting and that this plan
complies with the organization’s policies.
I understand that the data collected will remain entirely confidential and may not be
provided to anyone outside of the student’s supervising faculty/staff without permission
from the Walden University IRB.
Sincerely,
Authorization Official
Contact Information
Walden University policy on electronic signatures: An electronic signature is just as valid
as a written signature as long as both parties have agreed to conduct the transaction
electronically. Electronic signatures are regulated by the Uniform Electronic Transactions
Act. Electronic signatures are only valid when the signer is either (a) the sender of the
email, or (b) copied on the email containing the signed document. Legally an "electronic
signature" can be the person’s typed name, their email address, or any other identifying
228
marker. Walden University staffs verify any electronic signatures that do not originate
from a password-protected source (i.e., an email address officially on file with Walden)
229
Appendix K: Participant Invitation to Participate
Dear Participants,
My name is Imelda A. Bebe. I am a candidate student for Doctor in Business
Administration (DBA) at Walden University. I would like to invite you to participate in
this doctoral study research. The title of the research study is “Employee Turnover
Intentions in the Fast Food Industry in the United States.” The purpose of the study is to
examine the relationship between employee job satisfaction factors, job dissatisfaction
factors, and employee turnover intentions in the fast food industry. Your participation is
vital to the success of this study, because your shared experiences and insights toward
aspects of job or job as a whole may help improve the employees’ situation.
The completion and submission of your survey will serve as your consent to include the
research study analysis with your submitted responses. Your participation in this study is
voluntary and anonymous. Participants can withdraw anytime, or decline the invitation if
necessary. Please note that data collected will be safe and secured with Microsoft Office
encrypted password and locked cabinet for a minimum of five years before data deletion
or destroy will take place. Participants are not required to give names or company names
to protect their identity and confidentiality.
Study research result will be presented as aggregate, summary data only. Should you
have desire to have a copy of the research study result, please check yes and provide your
email address at the end of the survey, or email me at imelda.bebe@waldenu.edu. Please
respond to the survey by __________________. To participate in the survey, please click
on this link: https://surveymonkey.com/
230
Appendix L: Participants’ Reminder
Dear Participants,
Pleased be inform that this is only a cordial invitation or a friendly reminder about your
study research participation. You still have time to complete the survey if you have not
done it yet. Your participation to share your experiences and insights toward aspects of
job or job as a whole can help improve the employees’ situation.
Please accept my apology for this reminder if you have already responded and submitted
the survey. Please accept my sincere thanks and gratitude for your insights, time, effort,
and support. Thanks again for your continued support in this study, researching for the
employees’ job satisfaction and job dissatisfaction toward aspects of job or job as a
whole.
To participate in this study, please click on this link: https://surveymomkey.com. Please
respond to the survey by_____________ at your convenience. For further information
about the research study, please do not hesitate to contact me at 401-855-1772, or email
me at imelda.bebe@waldenu.edu. You may also contact Dr. Charles Needham at
[email protected]. The university’s Research Participant Advocate is also
available at 1-800-925-3368 ext. 1210# from within the USA, or email address
Thank you for your participation.
Sincerely,
Imelda A. Bebe
Doctor of Business Administration Candidate
