influence of transformational leadership style on job satisfaction among employees in commercial
TRANSCRIPT
INFLUENCE OF TRANSFORMATIONAL LEADERSHIP
STYLE ON JOB SATISFACTION AMONG EMPLOYEES IN
COMMERCIAL BANKS IN KENYA
BY
NJIINU ANDREW NJIRAINI
UNITED STATES INTERNATIONAL UNIVERISTY -
AFRICA
FALL 2017
INFLUENCE OF TRANSFORMATIONAL LEADERSHIP
STYLE ON JOB SATISFACTION AMONG EMPLOYEES IN
COMMERCIAL BANKS IN KENYA
BY
NJIINU ANDREW NJIRAINI
A Dissertation Report Submitted to the Chandaria School of
Business in Partial Fulfillment of the Requirement for the
Degree of Doctor of Business Administration (DBA)
UNITED STATES INTERNATIONAL UNIVERSITY –
AFRICA
FALL 2017
ii
STUDENT’S DECLARATION
I, the undersigned, declare that this is my original work and has not been submitted to any
other institution, or university other than the United States International University –
Africa in Nairobi for academic credit.
Signed_______________________________ Date___________________
Njiinu Andrew Njiraini (ID 615143)
This dissertation has been presented for examination with our approval as the appointed
supervisors.
Signed____________________________________ Date___________________
Prof. George O. K’Aol
Signed____________________________________ Date___________________
Prof. Teresia K. Linge
Signed____________________________________ Date___________________
Dean, Chandaria School of Business
Signed____________________________________ Date___________________
Deputy Vice Chancellor, Academic & Student Affairs
iii
COPYRIGHT
All rights reserved. No part of this dissertation report may be photocopied, recorded or
otherwise reproduced, stored in retrieval system or transmitted in any electronic or
mechanical means without prior permission of USIU-A or the author.
Njiinu Andrew Njiraini © 2017
iv
ABSTRACT
The purpose of this study was to examine the influence of transformational leadership
style on job satisfaction among employees in commercial banks in Kenya. The study was
guided by these research questions: To what extent does idealized influence affect job
satisfaction among employees in commercial banks in Kenya? To what extent does
individualized consideration influence job satisfaction among employees in commercial
banks in Kenya? To what extent does inspirational motivation influence job satisfaction
among employees in commercial banks in Kenya? To what extent does intellectual
stimulation influence job satisfaction among employees in commercial banks in Kenya?
To what extent does job security moderate the relationship between transformational
leadership and job satisfaction among employees in commercial banks in Kenya?
The study adopted a positivism research philosophy and a descriptive correlation research
design. The target population consisted of 10,310 managerial employees in the
commercial banks in Kenya. A sample size of 424 was obtained from the population
using stratified random sampling technique and data was collected using structured
questionnaires. A response rate of 82% was obtained. Data analysis was conducted using
both descriptive statistics and inferential statistics. Descriptive statistics used were mean
and standard deviation. The inferential statistical methods used to analyze the data were:
Chi-square, Pearson’s correlation, ANOVA and multiple linear regression. The Statistical
Package for Social Sciences (SPSS) was used as a tool to analyze data.
In regard to the first research question, correlation analysis results revealed a positive and
significant relationship between idealized influence and job satisfaction r (346) =.496,
p<.05. Multiple linear regression results revealed that idealized influence significantly
predicted job satisfaction (R2 = .246, F (1, 97.750) = 112.421, p < .05). Therefore, the
null hypothesis that there is no significant influence of idealized influence on job
satisfaction was rejected. Regarding the second research question, correlation analysis
results revealed a positive and significant relationship between individualized
consideration and job satisfaction r (347) =.595, p<.05. Multiple linear regression results
revealed that individualized consideration significantly predicted job satisfaction (R2 =
.354, F (1, 138.779) = 188.851, p < .05). Therefore, the null hypothesis that there is no
significant influence of individualized consideration on job satisfaction was rejected.
v
In regard to the third research question, correlation analysis results revealed a positive and
significant relationship between inspirational motivation and job satisfaction r (347)
=.587, p<.05. Multiple linear regression results revealed that inspirational motivation
significantly predicted job satisfaction of the employees (R2 = .344, F (1, 126.302) =
180.980, p < .05). Therefore, the null hypothesis that there is no significant influence of
inspirational motivation on job satisfaction was rejected. Regarding the fourth research
question, correlation analysis revealed a positive and significant correlation between
intellectual stimulation and job satisfaction r (347) =.541, p<.05. Chi-square test revealed
a significant association between intellectual stimulation and job satisfaction X2 (144, N =
347) = 426.404, p<.05). Multiple linear regression results revealed that intellectual
stimulation significantly predicted job satisfaction (R2 = .292, F (1, 106.274) = 142.533,
p<.05). Therefore, the null hypothesis that there is no significant influence of intellectual
stimulation on job satisfaction was rejected.
In regard to the fifth research question, correlation analysis results revealed that there was
a statistically significant correlation on the extent to which job security moderated the
relationship between transformational leadership and job satisfaction r (347) =.697,
p<.05. Multiple linear regression results revealed that job security significantly
moderated the relationship between transformational leadership and job satisfaction (R2 =
.446, F (5, 27.760) = 54.780, p < .05). Therefore, the null hypothesis that there is no
significant moderating effect of job security between transformational leadership and job
satisfaction was rejected.
The study concluded that transformational leadership significantly influenced job
satisfaction among employees in commercial banks in Kenya. The study recommends that
transformational leadership style should be used to enhance job satisfaction among
employees in commercial banks in Kenya. Individualized consideration through support,
mentoring and delegation together with job security aspects play an important role in
determining job satisfaction. The study recommends that further research should be
carried out on the influence of transformational leadership and job satisfaction among
employees in microfinance institutions in Kenya.
vi
ACKNOWLEDGMENT
First, I wish to thank God for enabling me to dream big and providing me with an
opportunity to actualize this dream; To God be the Glory.
Secondly, I wish to acknowledge with sincere gratitude the support and guidance I got
from my supervisors Prof. George O. K’Aol and Prof. Teresia K. Linge. I appreciate your
invaluable time, patience and guidance through the process.
Thirdly, a special appreciation to all those who took part in my doctoral journey; my
fellow doctoral students, the respondents who took part in the research and Paul who
provided me with the support I required.
Lastly, I wish to acknowledge my family who cheered me on; thank you for your
unwavering support and dedication to see that I completed this course successfully.
vii
DEDICATION
I dedicate this dissertation to all leaders; both existing and aspiring with a special
dedication to all commercial bank employees who seek to become effective leaders. May
this research project demystify your role as a leader and help you build organizations
where employees will experience job satisfaction, become engaged and transition to
inspired employees.
I also dedicate this dissertation to my family: Mr. & Mrs. Njiinu Gachanja, Shiro,
Gachanja & Wairimu, Kuria & Wangare, and Grace. Thank you for the investment you
made in me, both financial and moral, the discipline has gotten me this far. You have all
constantly been a source of wisdom, encouragement and support. Your support and
prayers have been my greatest source of strength. Please accept my sincere gratitude for
the significant roles that you have all played in my life and doctoral journey.
viii
TABLE OF CONTENTS
STUDENT’S DECLARATION ........................................................................................ ii
COPYRIGHT ....................................................................................................................iii
ABSTRACT ....................................................................................................................... iv
ACKNOWLEDGMENT .................................................................................................. vi
DEDICATION.................................................................................................................. vii
LIST OF TABLES ............................................................................................................ xi
LIST OF FIGURES ........................................................................................................ xvi
ABBREVIATIONS ........................................................................................................ xvii
CHAPTER ONE ................................................................................................................ 1
1.0 INTRODUCTION........................................................................................................ 1
1.1 Background of the Study ............................................................................................... 1
1.2 Statement of the Problem ............................................................................................... 8
1.3 The Purpose of the Study ............................................................................................... 8
1.4 Research Questions ........................................................................................................ 9
1.5 Hypotheses ................................................................................................................... 10
1.6 Justification of the Study ............................................................................................. 10
1.7 Scope of the Study ....................................................................................................... 11
1.8 Definitions of Terms .................................................................................................... 11
1.9 Chapter Summary ........................................................................................................ 13
CHAPTER TWO ............................................................................................................... 1
2.0 LITERATURE REVIEW ......................................................................................... 14
2.1 Introduction .................................................................................................................. 14
2.2 Theoretical Review ...................................................................................................... 14
2.3 Conceptual Framework ................................................................................................ 19
2.4 Empirical Review......................................................................................................... 20
2.5 Chapter Summary ........................................................................................................ 78
ix
CHAPTER THREE ......................................................................................................... 79
3.0 RESEARCH METHODOLOGY ............................................................................. 79
3.1 Introduction .................................................................................................................. 79
3.2 Research Philosophy .................................................................................................... 79
3.3 Research Design........................................................................................................... 80
3.4 Target Population ......................................................................................................... 82
3.5 Sample Design ............................................................................................................. 82
3.6 Data Collection Methods ............................................................................................. 85
3.7 Research Procedures .................................................................................................... 86
3.8 Data Analysis Methods ................................................................................................ 90
3.9 Chapter Summary ........................................................................................................ 97
CHAPTER FOUR ............................................................................................................ 98
4.0 RESULTS AND FINDINGS ..................................................................................... 98
4.1 Introduction .................................................................................................................. 98
4.2 General Information ..................................................................................................... 98
4.3 Influence of Idealized Influence on Job Satisfaction ................................................. 101
4.4 Influence of Individualized Consideration on Job Satisfaction ................................. 115
4.5 Influence of Inspirational Motivation on Job Satisfaction ......................................... 129
4.6 Influence of Intellectual Stimulation on Job Satisfaction .......................................... 143
4.7 Moderating Effect of Job Security on the Influence of Transformational Leadership
on Job Satisfaction ........................................................................................................... 157
4.8 Chapter Summary ...................................................................................................... 172
CHAPTER FIVE ........................................................................................................... 175
5.0 SUMMARY, DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS
.......................................................................................................................................... 175
5.1 Introduction ................................................................................................................ 175
5.2 Summary of the Study ............................................................................................... 175
5.3 Discussion of Results ................................................................................................. 176
5.4 Conclusions ................................................................................................................ 191
5.5 Recommendations ...................................................................................................... 193
x
REFERENCES ............................................................................................................... 195
APPENDICES ................................................................................................................ 224
Appendix I: Cover Letter .............................................................................................. 224
Appendix II: Questionnaire .......................................................................................... 225
Appendix III: USIU Research Introduction Letter .................................................... 231
Appendix IV: NACOSTI Research Permit ................................................................. 232
Appendix V: Classification of Banks in tiers ............................................................... 233
xi
LIST OF TABLES
Table 2.1: Operationalization of Variables and Hypothesis Testing ................................. 20
Table 3.1: Employment of Managerial Staff in the Banking Sector .................................. 82
Table 3.2: Sample Size Distribution Based on Tiers of the Banks .................................... 85
Table 3.3: Cronbach’s Alpha ............................................................................................. 87
Table 3.4: Hypothesis Testing ........................................................................................... 97
Table 4.1a: KMO and Bartlett's Test on Idealized Influence .......................................... 101
Table 4.1b: Total Variance Explained for Idealized Influence ........................................ 102
Table 4.1c: Component Matrix on Idealized Influence ................................................... 103
Table 4.2a: KMO and Bartlett’s Test on Idealized Influence on Job Satisfaction .......... 103
Table 4.2b: Total Variance Explained on Idealized Influence ........................................ 104
Table 4.2c: Component Matrix of Idealized Influence on Job Satisfaction .................... 105
Table 4.3: Mean and Standard Deviation of Idealized Influence .................................... 106
Table 4.4: Chi-square Test of Idealized Influence and Job Satisfaction .......................... 106
Table 4.5a: Correlation Analysis between Idealized Influence Variables and Job
Satisfaction ……………………………………………………………………………107
Table 4.5b: Correlation Analysis between Idealized Influence and Job Satisfaction ...... 107
Table 4.6a: One-way ANOVA on Idealized Influence .................................................... 108
Table 4.6b: One-way ANOVA on Idealized Influence on Job Satisfaction .................... 109
Table 4.7a: One-Sample Kolmogorov-Smirnov Test on Idealized Influence ................. 110
Table 4.7b: Linearity Test on Idealized Influence ........................................................... 111
Table 4.7c: Multicollinearity Test on Idealized Influence ............................................... 112
Table 4.7d: Homoscedasticity Test on Idealized Influence ............................................. 112
Table 4.8: Model Summary of Idealized Influence and Job Satisfaction ........................ 113
Table 4.9: Regression ANOVA of Idealized Influence on Job Satisfaction .................... 113
Table 4.10: Coefficients of Idealized Influence on Job Satisfaction ............................... 114
xii
Table 4.11a: KMO and Bartlett's Test on Individualized Consideration. ........................ 116
Table 4.11b: Total Variance Explained for Individualized Consideration ...................... 116
Table 4.11c: Component Matrix on Individualized Consideration ................................. 117
Table 4.12a: KMO and Bartlett's Test ............................................................................. 118
Table 4.12b: Total Variance Explained for Individualized Consideration ...................... 118
Table 4.12c: Component Matrix of Individualized Consideration on Job Satisfaction ... 119
Table 4.13: Mean and Standard Deviation of Individualized Consideration................... 120
Table 4.14: Chi-square Test on Individualized Consideration and Job Satisfaction ....... 120
Table 4.15a: Correlation Analysis between Individualized Consideration Variables and
Job Satisfaction ................................................................................................................ 121
Table 4.15b: Correlation Analysis between Individualized Consideration and Job
Satisfaction ……………………………………………………………………………121
Table 4.16a: One-way ANOVA on Individualized Consideration .................................. 122
Table 4.16b: One-way ANOVA of Individualized Consideration on Job Satisfaction ... 123
Table 4.17a: One-Sample Kolmogorov-Smirnov Test on Individualized Consideration 124
Table 4.17b: Linearity Test on Individualized Concentration ......................................... 125
Table 4.17c: Multicollinearity Test on Individualized Consideration ............................. 126
Table 4.17d. Homoscedasticity Test on Individualized Consideration ........................... 126
Table 4.18: Model Summary of Individualized Consideration on Job Satisfaction ........ 127
Table 4.19: Regression ANOVA of Individualized Consideration on Job Satisfaction .. 127
Table 4.20: Coefficients of Individualized Consideration on Job Satisfaction ............... 128
Table 4.21a: KMO and Bartlett's Test on Inspirational Motivation ................................ 130
Table 4.21b: Total Variance Explained for Inspirational Motivation.............................. 130
Table 4.21c: Component Matrix on Inspirational Motivation ......................................... 131
Table 4.22a: KMO and Bartlett's Test Inspirational Motivation and Job Satisfaction .... 132
Table 4.22b: Total Variance Explained for Inspirational motivation on Job Satisfaction
………………………………………………………………………………132
xiii
Table 4.22c: Component Matrix on Inspirational Motivation and Job Satisfaction ........ 133
Table 4.23: Mean and Standard Deviation of Inspirational Motivation .......................... 134
Table 4.24: Chi-square Test on Inspirational Motivation and Job Satisfaction ............... 134
Table 4.25a: Correlation Analysis between Inspirational Motivation Variables and Job
Satisfaction ....................................................................................................................... 135
Table 4.25b: Correlation Analysis between Inspirational Motivation and Job Satisfaction
……………………………………………………………………………135
Table 4.26a: One-way ANOVA on Inspirational Motivation ......................................... 136
Table 4.26b: One-way ANOVA of Inspirational Motivation on Job Satisfaction .......... 137
Table 4.27a: One-Sample Kolmogorov-Smirnov Test on Inspirational Motivation ....... 138
Table 4.27b: Linearity Test on Inspirational Motivation ................................................. 139
Table 4.27c: Multicollinearity Test on Inspirational Motivation ..................................... 140
Table 4.27d: Homoscedasticity Test on Inspirational Motivation ................................... 140
Table 4.28: Model Summary on Inspirational Motivation and Job Satisfaction ............. 141
Table 4.29: ANOVA for Inspirational Motivation and Job Satisfaction ......................... 141
Table 4.30: Coefficients of Inspirational Motivation on Job Satisfaction ....................... 142
Table 4.31a: KMO and Bartlett's Test on Intellectual Stimulation .................................. 143
Table 4.31b: Total Variance Explained for Intellectual Stimulation ............................... 144
Table 4.31c: Component Matrix on Intellectual Stimulation .......................................... 144
Table 4.32a: KMO and Bartlett's Test on Intellectual Stimulation on Job Satisfaction .. 145
Table 4.32b: Total Variance Explained for Intellectual Stimulation ............................... 145
Table 4.32c: Component Matrix on Intellectual Stimulation and Job Satisfaction ......... 147
Table 4.33: Mean and Standard Deviation of Intellectual Stimulations .......................... 148
Table 4.34: Chi-square Test on Intellectual Stimulation and Job Satisfaction ................ 148
Table 4.35a: Correlation Analysis between Intellectual Stimulation Variables and Job
Satisfaction ....................................................................................................................... 149
xiv
Table 4.35b: Correlation Analysis between Intellectual Stimulation and Job Satisfaction
………………………………………………………………………………149
Table 4.36a: One-way ANOVA on Intellectual stimulation ........................................... 150
Table 4.36b: One-way ANOVA on Intellectual stimulation on Job Satisfaction ............ 151
Table 4.37a: One-Sample Kolmogorov-Smirnov Test on Intellectual Stimulation ........ 152
Table 4.37b: Linearity Test on Intellectual Stimulation .................................................. 153
Table 4.37c: Multicollinearity Test on Intellectual Stimulation. ..................................... 154
Table 4.37d: Homoscedasticity Test on Intellectual Stimulation .................................... 154
Table 4.38: Model Summary on Intellectual Stimulation on Job Satisfaction ................ 155
Table 4.39: ANOVA of Intellectual Stimulation on job satisfaction ............................... 155
Table 4.40: Coefficients of Intellectual Stimulation on job satisfaction ......................... 156
Table 4.41a: KMO and Bartlett's Test ............................................................................. 158
Table 4.41b: Total Variance Explained for Job Security as Moderating Variable .......... 158
Table 4.41c: Component Matrix on Job Security as Moderating Effect ......................... 159
Table 4.42a: KMO and Bartlett's Test ............................................................................. 159
Table 4.42b: Total Variance Explained for Job Security as Moderating Variable .......... 160
Table 4.42c: Component Matrix on Job Security as Moderating Variable on Job
Satisfaction ……………………………………………………………………………161
Table 4.43: Distribution of Job Security as Moderating Variable ................................... 162
Table 4.44: Chi-square Test of Job Security and Job Satisfaction .................................. 162
Table 4.45a: Correlation Analysis between Job Security Variables and Job Satisfaction
………………………………………………………………………………163
Table 4.45b: Correlation Analysis between Job Security and Job Satisfaction ............... 163
Table 4.46a: One-way ANOVA on Job Security............................................................. 164
Table 4.46b: One-way ANOVA on Job Security on Job Satisfaction ............................. 165
Table 4.47a: One-Sample Kolmogorov-Smirnov Test .................................................... 166
Table 4.47b: Linearity Test on Job Security .................................................................... 167
xv
Table 4.47c: Multicollinearity Test on Job Security ........................................................ 167
Table 4.47d: Homoscedasticity Test on Job Security ...................................................... 168
Table 4.48: Model Summary of the Moderating Effect of Job Security between
Transformational Leadership and Job Satisfaction .......................................................... 169
Table 4.49: ANOVA Transformational Leadership and Moderating Variable on Job
Satisfaction ……………………………………………………………………………170
Table 4.50: Coefficients of Independent Variables and Moderating Effect on Job
Satisfaction ……………………………………………………………………………171
xvi
LIST OF FIGURES
Figure 2.1: Transformational Leadership Theory Model .................................................. 15
Figure 2.2: Conceptual framework .................................................................................... 20
Figure 4.1: Gender of Respondents ................................................................................... 98
Figure 4.2: Age of Respondents......................................................................................... 99
Figure 4.3: Education Qualification ................................................................................... 99
Figure 4.4: Duration of Working ..................................................................................... 100
Figure 4.5: Tier of the Banks ........................................................................................... 100
Figure 4.6. Scree Plot for Idealized Influence ................................................................. 102
Figure 4.7: Scree Plot for the Individualized Consideration............................................ 117
Figure 4.8: Scree Plot for the Inspirational Motivation ................................................... 131
Figure 4.9: Scree Plot for the Intellectual Stimulation .................................................... 146
Figure 4.10: Scree Plot for the Job Security .................................................................... 160
xvii
ABBREVIATIONS
CBK Central Bank of Kenya
CEO Chief Executive Officer
CFA Confirmatory Factor Analysis
CSR Corporate Social Responsibility
FMCG Fast-moving consumer goods
GLC Government Link Company
IMF International Monetary Fund
IT Information Technology
MLQ Multifactor Leadership Questionnaire
MSQ Minnesota Satisfaction Questionnaire
NACOSTI National Commission for Science, Technology & Innovation
SEM Structural Equation Modelling
SHRM Society for Human Resource Management
1
CHAPTER ONE
1.0 INTRODUCTION
1.1 Background of the Study
An organization’s success largely depends on the leadership style provided by the leaders.
They have the mandate of overseeing the internal context, business context and external
context, which may include but not limited to the human resource and financial contexts.
Leadership actions have a direct impact on cost, social and sustainable financial
performance. Consequently, these actions may yield long term sustainable firm
performance. Organizational success is characterized by performance, employee job
satisfaction and employee affective commitment (Abouraia & Othman, 2017). This is
achieved through effective leadership and a clear understanding of the organization’s
vision and purpose of existence. To enhance job satisfaction, scholars have argued that
leadership must provide motivation, inspiration, analytical skills and good remuneration
to employees; all of these have a combined effect of low attrition rates and decreased
absenteeism (Hurduzeu, 2015).
The transformational leadership style helps to create follower job satisfaction and
commitment to the organization both of which lead to superior customer service and
improved organizational performance (Patiar & Wang, 2016). Transformational
leadership style yields inspiration which enables transformational leaders to build
motivation within the followers. This enables the followers to go beyond their personal
interests and focus on the collective gain of the organization. To achieve all these,
transformational leaders offer intellectual challenges while paying regard to the followers
needs (Belias & Koustelios, 2014).
The transformational leadership style is characterized by high interaction of the leaders
with the followers and it has a significant positive effect on job satisfaction of the
followers. Additionally, the transformational leadership style has a positive relationship
with job satisfaction based on the impact the leader has on the followers (Muterera,
Hemsworth, Baregheh & Garcia-Rivera, 2015). By demonstrating a high concern for
followers, their needs, comfort, autonomy, empowerment, encouragement, reward and
recognition, transformational leadership style has a positive impact on job satisfaction
(Alonderiene & Majauskaite, 2016).
2
Job satisfaction is a pleasurable state that produces positive emotions when one evaluates
his job or job experiences (Belias & Koustelios, 2014). Job satisfaction parameters can be
broadly divided into two: extrinsic and intrinsic factors. Intrinsic factors are growth and
advancement opportunities, recognition, responsibility, the work itself and achievement.
Extrinsic factors are supervision, pay, policies, working conditions and relationships at
the workplace. They help to prevent job dissatisfaction among the followers (Alonderiene
& Majauskaite, 2016). Job satisfaction has also been described as happy feelings that
result from how one perceives a job in light of meeting important personal values
(Mahmoud & Reisel, 2014).
Job satisfaction is considered to be a sentimental response of an employee towards the job
which emanates from their experience on the job. It can be seen when a job is perceived
to fulfill a person’s needs and when a job possesses important job values. Additionally,
job satisfaction is an acceptable measure of well being in the workplace which contributes
to the psychological well being of the employees (Mencl, Wefald & Ittersum, 2016). Job
satisfaction is also viewed as accepting the organization’s goals, the willingness to work
hard and the intent to stay on in an organization (Jain, Sharma & Jain, 2012). Job
satisfaction is also considered to be the amount of belief and emotional connection the
followers have towards their respective organizations (Emmanuel & Hassan, 2015). It is
also the attitude that people have regarding their jobs which emanates from their
perception of the job and the fit between the individual and the organization. As put by
George and Zakkariya (2015), job satisfaction is very important for the service industry
employees because it is only satisfied employees who can offer good service that yields
customer satisfaction. Thus, it is not only customers who should be satisfied but also the
employees of the organization.
According to the full range leadership model, transformational leadership style is one of
the leadership styles that make a difference in the outcomes of the leader’s associates. In
this regard, when a leader pays attention to the needs of his associates, challenges them,
influences them as a role model and inspires them, the associates’ needs are significantly
addressed thereby yielding a level of satisfaction with their jobs (Tesfaw, 2014). This
goes on to validate the fact that coupled with other factors like the organizational culture,
which is also largely driven by the leadership of the organization, a style of leadership is
an important antecedent of job satisfaction (Munir, Rahman, Malik & Ma’amor, 2012).
3
Therefore, job satisfaction or dissatisfaction is a function of the perceived relationship
between the expectations from a job, what one receives from the job and the value
attributed to it (George & Zakkariya, 2015; Ahmad, Adi, Noor, Rahman, & Yushuang,
2013). Job satisfaction plays a big role in reducing employee turnover and increasing the
performance levels; but all these depend on the kind of leadership that is provided by the
top management (Sattar & Ali, 2014). Effective leadership goes beyond the traditional
managerial authority to relying on influence through social interactions between the
leaders and the employees. Transformational leadership is a form of leadership where
leaders are not only connected to their followers but also engaged with them (Mencl et
al., 2016). Emmanuel and Hassan (2015) argued that amongst the many aspects of
employee satisfaction, the most important is the leadership style.
Dissatisfied employees are less committed to their work and will more often look for
other opportunities in order for them to leave an organization. When opportunities are not
available, they are emotionally and mentally withdrawn from the organization.
Dissatisfied employees cannot produce the same quality of work with employees who are
highly satisfied with their jobs (George & Zakkariya, 2015). This makes job satisfaction a
key factor that determines the employee’s intentions of leaving an organization. To
improve the level of job satisfaction among employees, it calls for appropriate leadership
styles which enhance job satisfaction levels. Job satisfaction is important because it helps
to retain talent and ensures that employees perform their jobs as expected. Satisfied
employees not only become faithful but also become deeply committed to the
organization. They come up with ways of improving the business and endeavor to
contribute positively to the organization. Therefore, job satisfaction becomes one of the
most fundamental sources of motivation for employees surpassing pay and benefits. Job
satisfaction creates a work environment where employees strive to effectively serve
customers and ensure follow through of the customer value proposition (Mallikarjuna,
2014).
A leadership style is therefore an antecedent of job satisfaction and is considered to be a
predictor of job satisfaction (Munir et al., 2012; Long, Yusof, Kowang & Heng, 2014).
Attaining employee job satisfaction is important as it enables retention of productive and
efficient employees. Productivity coupled with performance of an organization is largely
based on the satisfaction the employees derive from their jobs. Additionally, employee
4
commitment to the organization also affects their output (Bushra, Usman & Naveed,
2011). The transformational leadership style enhances the performance, effectiveness,
confidence and motivation of followers as a result of the effect it has on the employee’s
attitude, motivation and sense of well-being. It enhances job satisfaction since it is
anchored on idealized influence, inspirational motivation, intellectual stimulation and
individualized consideration (Hetland et al., 2015).
Yang and Islam (2012) stated that when a leader fails in fostering the employees’ job
satisfaction, it then becomes difficult to achieve the organization’s objectives.
Transformational leadership helps a leader to inspire employees to achieve the
organizational goals by yielding to a commitment that transcends personal achievement.
It begins with the development of a vision which is aimed at exciting the employees and
converting them into followers. Job satisfaction has a significant and direct impact on
employee input, and it has an influence on both staff and organizational performance
(Alonderiene & Majauskaite, 2016).
Transformational leadership interventions affect both small organizations with minimal
turnover as well as big organizations where there is higher employee turnover (Arthur &
Hardy, 2014). Transformational leadership employs four elements to create
transformation and influence employees to perform beyond expectations. First, is
idealized influence which refers to influencing by serving as a role model through
charisma, demonstration of high performance and moral standards. Leaders earn credence
and trust because of their consistency in influencing employees. Second, is inspirational
motivation which refers to the ability to come up with a vision and communicating it in a
convincing and attractive manner to ultimately create excitement and buy-in from the
employees (Lussier & Achua, 2013).
Third, is intellectual stimulation which refers to inclusion through participation;
questioning assumptions, re-evaluating problematic and challenging situations to engage
their minds and create an opportunity to be heard. As a result, this encourages both
creativity and innovation. Fourth, is individualized consideration which refers to leaders
acting as coaches or mentors and taking into consideration the needs of their employees.
Leaders in this context recognize people’s varying needs and embrace their differences in
the various spectrums of personal attributes. Thus, followers are not reduced to their
5
functions and tasks but are considered as unique individuals (Yang & Islam, 2012).
Employees possess higher levels of job satisfaction when a leader uses the
transformational leadership style for example as compared to use of the transactional
leadership style. This is because transformational leadership not only considers but also
addresses the employees’ needs whereas transactional leadership looks at a model of
exchange (Ramos, 2014).
Alonderiene and Majauskaite (2016) found that in the developed countries like the United
States and Germany, jobs have been characterized with insecurity, high work intensity,
increased stress levels and long working hours which help to explain the declining levels
of job satisfaction. Some low paying jobs report higher job satisfaction levels thus
validating the fact that increasing pay levels helps to improve the employees’ well-being
but does not influence job satisfaction. Employees may register increased job satisfaction
based on increased pay, but this is only to a certain threshold beyond which pay ceases to
yield satisfaction but rather helps to reduce dissatisfaction. One of the direct
consequences of low job satisfaction is absenteeism and turnover of employees from the
organization. Factors like working environment, performance measurement policies and
employee relations together with the grievance handling mechanisms were found to affect
job satisfaction levels of employees in Canara Bank. Additionally, not having effective
training and development of employees, nature of work, salaries and incentives are a
great cause of dissatisfaction (Shrivastava & Purang, 2009).
In Bangladesh, according to Hossain (2014), the economic development in the world has
resulted in a rapid evolution of the banking industry. This development has resulted in
managerial problems in banks, mainly around the low level of employee job satisfaction,
which has resulted in mediocre service quality. Among the problems cited by the
employees are long working hours, pressure from the job itself, poor treatment, non-
conducive working environment, minimal promotion opportunities and unfairness. The
job satisfaction levels affect the quality of service and ultimately satisfaction of
customers. In Pakistan job satisfaction challenges in the banking sector are also evident as
a result of new rules, values and working conditions as seen to be resulting from policy
changes and effects of globalization (Sattar & Ali, 2014).
6
Banks play a critical role in economies and are crucial in ensuring economic stability and
growth. They act as the lifeline of modern trade and commerce by providing finance and
payments infrastructure (Akotch & Munyoki, 2016). They are essential in the financial
sector of any economy because they perform critical activities like lending and providing
liquidity. Banks also facilitate payments and settlements which are aimed at supporting
trade which then enables the transfer of goods and services. In economic development,
they also support development of new businesses hence creating the employment
opportunities whilst catalyzing economic growth (Arif & Anees, 2012). In Kenya, the
sector is changing at a very fast pace which calls for a lot of dynamism not only in areas
of profitability but also in policies regarding the employees’ welfare and job satisfaction
because they are the greatest assets the banks have (Njuguna & Owuor, 2016).
Hagendorff, Collins and Keasey (2007) stated that in the recent past the banking sector
has undergone a lot of changes owing to deregulation, globalization and technology.
These have led to restructuring, mergers, acquisitions and consolidation, resulting in
excess work demands thereby affecting job satisfaction of employees. This has been seen
predominantly in the United States of America, Italy and Germany as a result of
deregulation of the industry as seen with the abolition of the geographic restrictions and
demolition of demarcation lines in various financial services. These consolidations are
seen to come with benefits of costs, liquidity and risk diversification. During the world
financial crisis, many financial institutions were exposed and there were demands from
stakeholders to improve performance by adopting new management practices to
strengthen their capital, reduce non-performing loans, reduce costs, improve corporate
governance and come up with customer focused products (Munir, Baird & Perera, 2013).
This has resulted in new rules, regulations and guidelines from the various regulators and
the world financial systems all of which affect the employees’ attitudes, behaviors and
ultimately job satisfaction levels (Sattar & Ali, 2014).
In Nigeria, Osibanjo, Kehinde and Abiodun (2012) stated that the banking sector has
faced shocks and stresses in the past resulting from the economic meltdown in the world.
This has resulted in restructuring of the banking system which has had a noteworthy
influence on employee job satisfaction. For example, there has been anxiety regarding job
security with reduction of the number of banks. The pressure has brought a lot of job
demands on employees and resulted in the need for training and retraining on one hand,
7
and lack of job security on the other hand, thereby affecting job satisfaction of employees
to a great extent. With the constant changes, human resource policies need to be in
tandem with the changes to ensure that employees are constantly satisfied with their jobs.
In Kenya, Mukururi and Ngari (2014) noted there has been an endearing shift from a
twelve-hour economy to a twenty four-hour economy. This has resulted in work intensity
as banks move to more working hours. This has led not only to greater workload where
shifts are not managed properly but also to higher stress levels from the long working
hours. Additionally, the banks lacked policies to adequately support the well being of
their employees hence lack of work life balance. Every employee has a personal and
professional life and employers need to ensure the employee can attend to both parts
adequately otherwise lack of balance results in lack of satisfaction. Banks have been
awash with scandals which have led to loss of trust from customers, employees, the
public, governments and other stakeholders. Banks must complement the pursuit for
profitability with social good (ProtusKiprop, Kemboi & Mutai, 2015).
According to the Central Bank of Kenya (CBK), which is the regulator of financial
institutions in Kenya, there are 44 banks in Kenya made up of 43 commercial banks and
one mortgage financial institution. Out of these, 31 were locally owned and 13 foreign
owned. The government has a stake in 3 banks namely National Bank of Kenya,
Consolidated Bank and Development Bank of Kenya. Whereas performance for some
banks has grown tremendously, performance for others has declined in equal measure. In
the recent past, three of the commercial banks were placed under statutory receivership by
the regulator owing to compliance issues (CBK, 2017).
The Kenyan banking sector has recently undergone a lot of turmoil with three banks
being closed and placed under receivership: Dubai Bank Kenya Limited, Imperial Bank
Limited and recently Chase Bank Kenya Limited. Chase Bank Kenya Limited has been
re-opened and is operating under a receiver manager (CBK, 2017). Additionally, with
new regulation capping interest rates, the profitability of commercial banks’ has fallen
significantly. This has led to investment in technology to save on costs as well as
capitalize on efficiencies. As a result, majority of the banks have closed branches in
rightsizing exercises, offering retirement packages and declaring redundancies. These
8
changes have resulted in a lot of anxiety and fear of job losses, thereby inevitably
affecting job satisfaction significantly among the bank employees (IMF, 2017).
1.2 Statement of the Problem
Leadership plays a significant role when dealing with people. Specific variables like job
satisfaction have gained prominence in the contemporary era and have become areas of
focus for organizations (Malik, Javed & Hassan, 2017). Banks are very important
institutions in any economy because of the significant role they play by offering financial
services. Many economies have gone through financial crisis which has resulted in far
reaching effects on many banks globally. These effects have significantly affected the
employees’ levels of job satisfaction. As a result, organizations are in need of leadership
that will strive to create job satisfaction because such periods of crisis result into negative
defensive behaviors and attitudes which result from uncertainty, all of which affect job
satisfaction (Belias & Koustelious, 2014). Hanaysha et al. (2012) found that
transformational leadership had a significant influence on job satisfaction among nurses
in Malaysia and proposed further research in other sectors.
Globalization and recent developments in the banking sector have led to sporadic changes
resulting in heightened competition among the banking institutions (IMF, 2017). These
changes have brought to light leadership practice gaps and the resultant effects. One of
the significant effects is on job satisfaction which has resulted from long working hours
and increased work load (Mwangi & Omondi, 2016). Additionally, other effects have
been revealed on employee motivation, performance and productivity (Bushra et al.,
2011). Bader, Hashim and Zaharim (2013) carried out a study on job satisfaction among
bank employees in Eastern Libya and found that gender and age affected job satisfaction.
They recommended further studies to determine other factors that affect job satisfaction.
Globally, further research has been proposed in the area of transformational leadership
and job satisfaction. In Malaysia, a study conducted by Omar and Hussin (2013) revealed
a significant relationship between transformational leadership and employee job
satisfaction in the academic sector. They proposed further research in other sectors like
banking. E.O Darko and T.O Darko (2015) in Ghana noted that as a result of high
competition in the banking industry, employees are now expected to work harder
notwithstanding the dependence of performance on job satisfaction. The study proposed
9
further studies on the effect of leadership styles on employee job satisfaction in other
regions. Tetteh and Brenyah (2016) found out that transformational leadership enhanced
employee job satisfaction among employees in the telecommunication sector in Ghana.
They recommended that further studies should be carried out in other sectors like
banking. Walumbwa, Orwa, Wang and Lawler (2005) found a positive correlation
between transformational leadership in Kenyan and American banks in a comparative
study and recommended further research where each individual element of
transformational leadership is assessed against job satisfaction.
The studies presented here indicate that there is need for further research in the area of
transformational leadership and job satisfaction. Therefore, the motivation of this study
was to establish the influence of transformational leadership on job satisfaction among
employees in commercial banks in Kenya.
1.3 The Purpose of the Study
The purpose of this study was to examine the influence of the transformational leadership
style on job satisfaction among employees in commercial banks in Kenya.
1.4 Research Questions
This study was guided by the following research questions:
1.4.1 To what extent does idealized influence affect job satisfaction among employees in
commercial banks in Kenya?
1.4.2 To what extent does individualized consideration influence job satisfaction among
employees in commercial banks in Kenya?
1.4.3 To what extent does inspirational motivation influence job satisfaction among
employees in commercial banks in Kenya?
1.4.4 To what extent does intellectual stimulation influence job satisfaction among
employees in commercial banks in Kenya?
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1.4.5 To what extent does job security moderate the relationship between
transformational leadership and job satisfaction among employees in commercial banks in
Kenya?
1.5 Hypotheses
This study was guided by the following null hypotheses:
H01: There is no significant influence of idealized influence on job satisfaction among
employees in commercial banks in Kenya.
H02: There is no significant influence of individualized consideration on job satisfaction
among employees in commercial banks in Kenya.
H03: There is no significant influence of inspirational motivation on job satisfaction
among employees in commercial banks in Kenya.
H04: There is no significant influence of intellectual stimulation on job satisfaction among
the employees in commercial banks in Kenya.
H05: There is no significant moderating effect of job security between transformational
leadership and job satisfaction among employees in commercial banks in Kenya.
1.6 Justification of the Study
1.6.1 The Banking Sector
The findings of this study will provide new knowledge in the banking sector on the
influence of transformational leadership on job satisfaction. This will therefore, enlighten
senior management of banks and other financial institutions on how enhance employee
job satisfaction; this will help to retain employees in the organizations. Additionally, it
will demonstrate how the various components of transformational leadership can be used
to harness employee performance by enhancing employee job satisfaction. This will
ultimately boost achievement of the set objectives and goals.
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1.6.2 Policies and Policy Makers
For policy and policy makers, the findings of this study will inform policies in financial
institutions and other organizations on how to enhance employee job satisfaction. Thus,
organizations will be able to come up with more effective policies around job satisfaction
in the financial services sector. This is very crucial given the sensitivity of this sector and
the important role it plays in the economy. This study will therefore contribute immensely
by informing policies around job satisfaction.
1.6.3 Researchers and Academicians
The findings of this research will add value to the existing knowledge base on
transformational leadership and job satisfaction of employees. The findings of this study
will also provide knowledge on transformational leadership and job satisfaction of
employees in commercial banks in Kenya. This will therefore add to the existing body of
knowledge in the area of transformational leadership and job satisfaction.
1.7 Scope of the Study
This study examined the extent to which transformational leadership style influences job
satisfaction of employees in commercial banks in Kenya. The study focused on the
transformational leadership theory and the four dimensions commonly referred to as the
4Is. The target population was 10,301 employees who fall under the management
category as per the Banking Supervision Report of 2015 (CBK, 2017). The study focused
on all the 43 commercial banks in Kenya and adopted stratified random sampling
technique. The Central Bank of Kenya has classified commercial banks in three tiers; tier
one comprising of big banks, tier two comprising of medium sized banks and tier three
comprising of small banks. The study focused on all the three tiers of commercial banks
in Kenya. The research was carried out in September 2017.
1.8 Definitions of Terms
1.8.1 Transformational Leadership
Transformational leadership is a leadership style where the leader aims to articulate a
compelling vision and offers clear goals whilst providing support and stimulating
followers to work (Chan & Mak, 2014). Transformational leadership style has the
12
capability to motivate and also to inspire followers to identify with the leader and the
organization thereby enabling employees to perform beyond expectation. It comprises of
four dimensions: idealized influence, individualized consideration, inspirational
motivation and intellectual stimulation (Bass & Avolio, 1997).
1.8.2 Idealized Influence
Idealized influence is also termed as charisma which is a behavior which brings out
positive emotions from the followers and leads them to emulate the leader who in this
case acts as a role model. A leader seeks to be a personal example and also maintains high
ethical standards to ensure he is a role model. Idealized influence behavior constructs are
charisma, trust and ethics (Bass & Avolio, 1994).
1.8.3 Individualized Consideration
Individualized consideration involves the leaders displaying attention to the
developmental needs of the followers. They offer support through coaching and
mentorship programs and also provide feedback on the performance of tasks. This is
displayed when the leaders delegate tasks which in turn present the followers with growth
opportunities. Individualized consideration behavior constructs are delegation, mentoring
and support (Bass & Avolio, 1997).
1.8.4 Inspirational Motivation
Inspirational motivation involves the development and communication of an appealing
vision which results in helping to focus the efforts of the followers to the organization’s
vision and mission. Basically, the leader creates and communicates the vision with
passion, enthusiasm and optimism to the followers. Inspirational motivation behavior
constructs are communication, teamwork and motivation (Bass, 1985).
1.8.5 Intellectual Stimulation
This behavior seeks to grow the awareness of problems and leads followers to a different
perception of the problems. They are influenced to creativity with a view of challenging
the existing beliefs and values. Intellectual stimulation also helps leaders to challenge
their follower’s ideas, values and problem-solving capabilities. It encourages followers to
challenge and question status quo. Intellectual stimulation behavior constructs are
knowledge sharing, creativity and risk taking (Bass & Avolio, 1994).
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1.8.6 Job Satisfaction
Job satisfaction refers to how content a person is with his or her job, or how a person feels
about their job or the various aspects of their job (Pravin & Kabir, 2011). It is how an
employee perceives their job and the resultant emotions. Job satisfaction was measured
by the level of commitment an employee has to the organization, absenteeism and
employee’s intentions to leave the job (Emmanuel & Hassan, 2015; Ramos, 2014).
1.8.7 Job Security
Job security can be defined as the perceived stability and continuation of a job together
with its features in future. Accordingly, it can be attributed to Maslow’s second hierarchy
of needs which is security and safety. Job security constructs are anxiety, fairness and
stress (Mahmoud & Reisel, 2014; Akpan, 2013).
1.9 Chapter Summary
This chapter presented an overview of the background of the study, the problem
statement, research questions, hypotheses, scope of the study and definition of terms.
Chapter two presents the theoretical framework, conceptual framework and the empirical
review. Chapter three presents the research methodology. Chapter four presents the
results and findings of the study. Chapter five presents the summary, discussion,
conclusions and recommendations of the study.
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CHAPTER TWO
2.0 LITERATURE REVIEW
2.1 Introduction
This chapter presents the theoretical review and the conceptual framework of
transformational leadership. The chapter also presents an empirical review of existing
literature on transformational leadership and job satisfaction based on the research
questions.
2.2 Theoretical Review
A theoretical review refers to a study of theories that have been formulated to explain,
predict and understand various phenomena. A theory is an organized and systematic set of
interrelated statements which specify the nature of relationships between variables
(Green, 2014). This study was underpinned by the transformational leadership theory
which was developed by James MacGregor Burns in 1978. The transformational
leadership theory consists of four constructs namely idealized influence, individualized
consideration, inspirational motivation and intellectual stimulation which lead to
performance beyond expectations (Burns, 1978).
2.2.1 Transformational Leadership Theory
Transformational leadership theory was first articulated by Burns in the year 1978 (Burns,
1978). It was then advanced by Bernard Bass almost ten years after Burns had brought up
the theory of leadership. According to Bass (1985) transformational leadership theory
consists of four dimensions which are idealized influence, individual consideration,
inspirational motivation and intellectual simulation which lead to performance beyond
expectation as shown in Figure 2 which represents the transformational leadership theory
model. Empirical studies have documented significant influence of transformational
leadership on job satisfaction. Therefore, leaders should strive to integrate these attributes
in their day to day leadership so as to simulate employees to work hard and perform
beyond their expectations (Liao & Chuang, 2007; Liang, Chang & Chih-Wei Lin, 2017).
15
Transformational Leadership Theory Model
Figure 2.1: Transformational Leadership Theory Model
Source: (Bass & Avolio, 1985).
The leader is able to attain a high level of output from the followers because they do not
work for self-gain. The leader provides the followers with an inspiring mission which
enables them to pursue organizational objectives beyond their self-interests (Bass &
Avolio, 1997). Through transformational leadership, a leader is able to drive change both
in people and organizations. These four elements provide a compelling vision and
leadership, encourage the followers by considering their needs, encourage followers to be
innovative and to challenge the status quo, and finally provide a source of motivation.
Consequently, they also help to ensure that the employees feel valued and remain inspired
to perform beyond expectations (Bass, 1985; Northouse, 2013; Ramos, 2014).
Transformational leadership is grounded on the idea of transformational leaders
motivating their followers to commit to the organizational objectives and to perform
beyond expectations. According to Bass (1985), four leadership processes are involved in
achieving these outcomes. First, leaders raise the followers’ consciousness levels about
what is important and the value attached to the desired outcomes and the means within
which the outcomes will be achieved. Secondly, leaders induce followers to go above and
outside their self-interests for the sake of the organization by demonstrating care for their
individual needs and treating them with a human touch. Thirdly, leaders foster the need to
achieve higher level needs by stimulating the followers’ intellect by presenting challenges
and giving them the opportunity to solve problems, offer solutions and challenge status
quo. Fourthly, leaders seek to motivate and inspire the followers so that they can keep
their eyes on the goal which is the organizational objectives and the means within which
to attain the desired outcomes and results. When all these are fulfilled, followers perform
beyond expectations, realizing the desired results and surpassing set expectations.
16
Performance beyond expectations is in relation to the collaborative, collective will and
action yielded by transformational leadership which results in empowering the followers
who participate in the process (Pamela, 2010).
2.2.1.1 Idealized Influence
Idealized influence is the capability to exert influence by serving as a role model through
demonstration of high performance and moral standards. By this, the leaders persuade the
followers to share in the organizations vision and objectives. The leaders possess a strong
personal appeal and a power to influence the followers by providing direction, sense of
purpose and fostering perseverance in pursuit of the goals (Muenjohn, 2010). The leaders
earn legitimacy based on personal integrity and competence. From this, the followers
admire and respect the leaders and further desire to emulate them (Liang, Chang & Chih-
Wei Lin, 2017). Some attributes of idealized influence are vision, trust, respect, integrity
and modeling. Idealized influence enables a leader to become a role model for high
ethical behavior and to gain respect from the followers (Stone, Russel & Patterson, 2004).
Through charisma, a leader is able to instill pride, attract faith and respect from the
followers and to make them see the bigger picture thereby communicating a sense of
mission. This produces energy for achieving high work objectives (Brandt, Laitinen &
Laitinen, 2016). The leaders display conviction, place emphasis on important personal
values and connect those values with the organizational objectives. Transformational
leaders rely on their charismatic attributes; charisma here being a form of personal power.
Thus, they focus on their charismatic and enthusiastic attributes to gain influence over
their followers and to motivate the followers.
2.2.1.2 Individualized Consideration
Individualized consideration refers to the degree to which leaders attend to the needs of
the followers and act as coaches and mentors. They are able to recognize the employees’
unique needs for achievement, growth and desires by keenly listening to their needs and
concerns. This takes care of the varying needs of autonomy, encouragement,
responsibility, structure and instructions which fosters individual attention of followers as
unique persons and doesn’t reduce them to their function and roles (Brandt et al., 2016).
Individual consideration enables a leader to pay attention to the followers’ developmental
17
needs and therefore delegates work projects in a way that stimulates the learning
experiences of the followers. A transformational leader allows the followers more
discretion and opportunities in their work which satisfies their developmental needs
resulting in enhanced commitment to the organization and the work. This stimulates them
to achieve high levels of creativity (Cheung & Wong, 2011).
Bass and Avolio (1997) stated that leaders should share in the concerns of their followers
together with their developmental needs and this paves way for each person’s individual
consideration. Encouragement from the leaders allows the followers to express
themselves freely and also to implement their ideas (Muenjohn, 2010). Leaders provide a
supportive environment and carefully consider the needs of their followers. They also
advice, teach, coach with an intent of helping their followers to develop themselves.
Some attributes to individualized consideration are personal attention, mentoring,
listening and empowerment. Individualized consideration enables a leader to keep
communication open and also the celebration of individual employees and their
contribution to the team. They provide the followers with sources of motivation within
their jobs and through other avenues.
2.2.1.3 Inspirational Motivation
Inspirational motivation is the ability of a leader to behave in a way that motivates
followers, generates enthusiasm and challenges people (Stewart, 2006). Leaders do this
when they develop and communicate a convincing attractive future vision and also when
they clearly communicate the expectations. It enables leaders to display optimism, power
and encouragement to their followers (Felfe & Schyns, 2004). A leader is able to
articulate an appealing vision of the future and challenge the followers’ expectations
hence providing encouragement, optimism and a collective sense of purpose. Further, it
allows a leader the opportunity to use symbols and emotional appeal to unite group efforts
on a central purpose. This then encourages followers to achieve more than they would
achieve in pursuit of their own self-interests (Cheung & Wong, 2011).
Leaders are able to motivate the followers through a compelling vision for the future and
by expressing confidence in the followers which in turn nudges the followers to willingly
increase their efforts to attaining the vision. It could also be a function of leaders
expressing high expectations of the followers to achieve extra ordinary achievements and
18
at the same time displaying confidence in their potential. Inspirational motivation could
easily overlap with charisma. However, it is worth noting that inspirational motivation
could occur without a need for identifying with the leader which is the case for
charismatic leaders (Muenjohn, 2010). A leader is able to achieve this by constantly
encouraging the team and verbalizing confidence in their abilities, reviewing
achievements progressively and also giving recognizing the follower’s efforts to achieve
the set vision (Antonakis, 2006).
2.2.1.4 Intellectual Stimulation
Intellectual stimulation refers to the leader’s actions which persuade the followers to use
their sense of logic and analyze situations using their creative thinking in a bid to find
solutions. This tenet of transformational leadership goes on to challenge followers to
come up with new ways of doing things and not to accept status quo if there is an option
(Antonakis, Avolio & Sivasubramaniam, 2003). Therefore, intellectual stimulation also
refers to the degree to which the leader challenges assumptions, status quo, takes risks
and seeks for contributions of ideas from the followers. Transformational leaders are able
to influence the followers’ creativity by ensuring the followers feel challenged and
energized to seek new and novel approaches in their jobs which will translate into
effectiveness (Cheung & Wong, 2011). A leader is able to arouse the followers to think in
new creative ways which focus on problem solving and use of reason in judgment.
Creative and innovative solutions are required and encouraged to stimulate followers
(Felfe & Schyns, 2004).
Intellectual stimulation allows a leader to encourage and back up the followers to
challenge the status quo, question existing or old assumptions, redefine problems, explore
their intellectual curiosity and also use imagination. Leaders cheer their followers to think
differently and in creative ways in order to address existing and future challenges. A few
accompanying attributes are rationality and problem solving (Stone et al., 2004). This
yields new ideas for the organizations on product lines or processes which have the
possibility of yielding better returns or helping in the achievement of the organization’s
objectives. To sustainably stimulate the followers, leaders avoid correcting the followers
in public or criticizing the followers so that they are not limited in their creativity
(Stewart, 2006).
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2.2.1.5 Performance beyond Expectation
According to Bass (1985), when leaders practice transformational leadership, they are
able to act as exemplary role models, motivate their employees to commit to the
organizational vision, encourage innovation and creativity, and act as coaches and
advisors to the employees; these actions result in performance that exceeds organizational
expectations. Cheung and Wong (2011) note that intensive research has been carried out
and findings indicate that transformational leadership is effective in enabling followers to
perform beyond expectations and also transforming their personal values into higher level
needs and aspirations. Additionally, they note that transformational leadership is linked to
creativity of followers, performance, organizational commitment, absenteeism and
satisfaction. All the above enhance innovation and a competitive advantage for the
organization.
The attribute of idealized influence and inspirational motivation which enable a leader to
instill pride in the followers also contributes towards inducing the follower’s interests
beyond personal interests for the good of the organization. The attributes do this by
reassuring the followers that together they will overcome the obstacles ahead and also by
building confidence in the achievement of the set goals. Additionally, the leader’s
optimistic talk about the future also helps to build hope in the followers because the
leader provides an exciting image of organizational change (Guay, 2013). By constantly
aligning the values of the followers to the organizational values, followers put in more
effort which leads to performance beyond expectations since they can chose to operate
below their thresholds. By supporting teams, transformational leadership builds a
psychological attachment of the followers to the organization hence leading to a
collective identity which motivates the followers (Rao & Abdul, 2015; Bass, 1985).
2.3 Conceptual Framework
A conceptual framework is a diagrammatic representation of variables or constructs that
is used to map and guide the research process (Green, 2014). The conceptual framework
was derived from the transformational leadership theory and consists of the four
dimensions of transformational leadership which include idealized influence,
individualized consideration, inspirational motivation and intellectual stimulation (Burns,
1978). Figure 2.2 presents the conceptual framework.
20
Independent Variables Dependent Variable
Figure 2.2: Conceptual Framework
Source: Author (2017)
2.3.1 Independent Variables
A variable is a characteristic or attribute that can be tested or observed and may vary from
context to context depending on subject of study. Independent variables are variables that
cause, influence or affect outcomes and can also be referred to as treatment or predictor
variables (Creswell, 2014). The independent variables for this study included idealized
influence, individualized consideration, inspirational motivation and intellectual
stimulation.
Idealized Influence
Charisma
Trust
Ethics
Trust
Ethics
Job Security
Anxiety
Fairness
Stress
Individualized Consideration
Delegation
Mentoring
Support
Inspirational Motivation
Communication
Team Work
Motivation
Intellectual Stimulation
Knowledge Sharing
Creativity
Risk Taking
Job Satisfaction
Organizational
Commitment
Absenteeism
Employee Turnover
Intentions
H01
H02
H03
H04 H05
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2.3.1.1 Idealized Influence (X1)
Idealized influence is the first tenet of transformational leadership that determines the
effectiveness of transformational leadership. Leaders use idealized influence to wield
influence through charisma, trust and ethics. Leaders earn credence and trust because of
their consistency in behavior. It is a characteristic that enables the leader to create a
perception of power, charisma, confidence and trust among the followers which results in
admiration and a desire to imitate, respect and a need to be associated with the leader
(Omar & Hussin, 2013). Idealized influence results from the leader’s behavior, beliefs,
moral standards and conformity of values (Avolio & Bass, 2002; Ibraheem, Hussein &
Ayat, 2011). Idealized influence is an emotional component of leadership. It describes the
leaders who act as good role models and in turn arouses a desire in the followers to
emulate them. Their behavior is comprised of high ethical and moral standards and this
earns them a deep level of trust from their followers. Charisma tends to make people
special and also make others to want to follow the vision they offer (Voon, Lo, Ngui, &
Ayob, 2011).
Idealized influence helps the followers to acknowledge the unique capabilities of the
leader, such as the leader’s persistence and desire to take risks in a bid to achieve the set
objectives. It can also be explained as setting of knowledge creation as a means of
influencing over ideals (Ngaithe, K’Aol, Lewa & Ndwiga, 2016). Idealized influence also
helps the leader to provide a vision for the followers which doubles up as a driver to
achieving the set objectives. It creates a sense of pride in the followers from the aspect of
association with a leader who is viewed as a role model because of their boldness,
dynamic capabilities, ethical nature, consistency and zeal to offer solutions. All these
aspects yield motivation for the followers and result in achievement of the objectives and
also performance beyond expectation (Ahmad, Abbas, Latif & Rasheed, 2014). Leaders
demonstrate their willingness to sacrifice personal gain for the good of the team (Ogola,
Sikalieh & Linge, 2017).
Ngaithe et al. (2016) refer to idealized influence as a way in which leaders behave that
makes them role models for their followers. As a result, the leader is not only admired but
also respected. This also results in trust and a desire by the followers to emulate the
leader. The followers notice and give credence to the extra ordinary capabilities possessed
by the leader which result in admiration. Followers have a sense of trust and respect for
22
leaders who possess idealized influence. As a result, they are readily willing to take on
instructions from the leader notwithstanding the complexity of the tasks that may be
involved. Idealized influence is similar to the highest level of moral reasoning; meaning
such leaders are willing to forgo their interests for the benefit of their group or
organization. Such leaders set high behavior standards and are role models because they
walk the talk (Ogola et al., 2017).
Huang and Lin (2014) defined the most important characteristics of a charismatic leader
as knowledgeable, friendliness, approachable, patient and enthusiastic. Max Weber
referred to charisma as a quality of a person that sets them apart from ordinary people
(Nikoloski, 2015). Charisma is also viewed as an attribute based on the followers’
perception of their leader’s behavior which goes on to suggest that charisma exists in the
eyes of the beholder. Another definition is that charisma refers to attributes of personal
characteristics that enable an individual to influence other people thereby impacting their
feelings, opinions and behavior. Research conducted in organizations has shown that
charisma is positively related to individual, group and firm level outcomes. This is
because leaders are able to inspire followers to higher levels of performance and to impart
in them behavioral attributes of commitment. As a result, there is a very positive
perception of leaders possessing charisma because they are perceived as effective by their
subordinates in comparison with less charismatic leaders. However, there are emerging
theoretical advances challenging the correlation between charisma and leader
effectiveness (Vergauwe, Wille, Hofmans, Kaiser & De Fruyt, 2017).
Bell (2013) referred to charisma as an untraditional form of influence where the leader
has exceptional qualities which are perceived by his followers. It is a trait one perceives
and is hard to describe without making reference to some known characteristics or
behaviors. In his research, Bell examined behaviors like communication skills, visionary
attributes, integrity, humor and expertise which were attributed to the charisma of Ronald
Reagan. According to Nikoloski (2015), the ethics of charismatic leaders refers to how
they use their power and in what. Charismatic leaders who are ethical have better
workplace environments with less interpersonal and workplace deviance. These leaders
act as role models and their behavior more often than not cascades through the
organization. Human resource has become a source of competitive advantage especially
23
for the leaders with charisma because they have ability to inspire followers to own the
vision and achieve the set objectives.
Ethics is an important element of an organization because it plays a big role in
determining the performance of employees in the organization. The term was derived
from Greek and it means moral character, custom and habit (Athar, Shahzad, Ahmad &
Ijaz, 2016). Business ethics can be referred to as a criteria that is used to determine
between wrong and right, good or bad. Ethical forces across the world are making
businesses and business leaders to transcend their personal interests to ensure ethical
issues are addressed effectively. An ethical climate refers to individual beliefs about the
organizational practices, procedures, standards and ethical values. An ethical climate in
organizations has been associated with enhanced levels of satisfaction (Ahmed, Shad,
Mumtaz & Tanveer, 2012). Organizational ethics goes beyond the climate and involves
top executive support for the ethical behavior and the association of ethical behavior with
career success which are all associated with job satisfaction. Additionally, research states
that organizational outcomes can be influenced by the leaders’ support and reward of
ethical behavior (Awasthi, 2015).
Interpersonal trust has been described as a social lubricant which helps to facilitate
collective efforts and perceptions within an organization. It is a psychological state which
involves the willingness to accept helplessness based on positive expectations on the
intent of another person (Kelly, Lercel & Patankar, 2015). Organizational trust is a
general organizing principle; thus, the foundation of a general governing system of the
contractual relations which can be invoked to control opportunism, costs and monitor
problems in organizations. It has been argued that organizational trust enhances job
satisfaction (Mincu, 2015). It was also found that the length of service in an organization
influenced job satisfaction in some instances (Sarker, Crossman & Chinmeteepituck,
2003).
Research indicates that trust leads to participation in organizations and collaboration
between people, groups and other organizations. Employees look for trust between them
and their managers which affects their level of confidence in the organization leading to
motivation and greater effectiveness. Mistrust leads to rumors, conflict and politics in the
organization which are not desired. However, mutual trust can be a source of success for
all (Pourkeiani & Tanabandeh, 2016). Organizations with higher levels of mutual trust
24
existing between management and employees could more ably maintain and sustain
human talent which is a great source of competitiveness in the corporate world.
Additionally, trust has been associated with employee job satisfaction and perceived
organizational effectiveness. It is important but has sometimes been taken for granted by
organizational leaders yet it remains a critical element in achieving the organizational
objectives (Usikalu, Ogunleye & Effiong, 2015).
2.3.1.2 Individualized Consideration (X2)
Individualized consideration is the second tenet of transformational leadership where
leaders show concern for their employees. Some behavioral attributes of individualized
consideration consist of delegation, mentoring and support. Leaders build their people by
delegating tasks to them, mentoring them and supporting them as they pursue the set
objectives. Leaders in this context recognize people’s needs for achievement, growth,
desires and demonstrate personal interest in helping them to satisfy their needs (Avolio &
Bass, 2002). They also embrace people’s differences in the various spectrums of personal
attributes; thus, followers are not reduced to their function and tasks but are considered as
unique individuals (Felfe & Schyns, 2004). Leaders also use this to help them develop the
abilities of their followers and empower them to accomplish higher tasks which can be
achieved through delegation, support, training, guidance and effective supervision. To
achieve this, a leader acts as both a referee and as a coach (Ibraheem et al., 2011).
Leaders achieve this by giving personal attention to the followers and recognizing their
uniqueness thus being able to help them through specific structured directions
(Northouse, 2013).
This quality in the leaders helps them to pay more attention to the followers’ individual
needs which yields happiness and comfort in the followers since they feel their needs are
addressed from a personal and not a group point of view. The leaders train the followers
on how to achieve the set goals and objectives and upon accomplishment, this leads to
aspects of recognition which is a key driver of job satisfaction (Ahmad et al., 2014). The
leader’s ability to create a supportive environment by listening, coaching and mentoring
the followers speaks volumes to the followers because the leaders consider their needs by
ensuring that as the organization grows, the employees also grow in their areas of interest.
The leaders also help the employees to get through their personal challenges because they
25
are concerned not only about the work but also their followers personal matters
(Alkahtani, 2016).
Delegation is one of the fundamental roles that leaders perform and it is widely credited
as a result of effective management. Delegation involves giving subordinates the
responsibility for decisions which are usually handled by the leader thereby enhancing
their latitude and discretion (Drescher, 2017). Delegation is also referred to as the process
of assigning responsibilities to subordinates by the leaders and it involves transferring
authority from the leader to the employee. It results in empowering the employees to
make commitments on behalf of the leader to use the resources available and also to make
decisions relating to the roles assigned. Delegation stems from the fact that one individual
cannot discharge all the responsibilities in an organization successfully. It can only work
effectively if the person to whom responsibility is delegated is given commensurate
authority to discharge the responsibilities. When it is implemented well it becomes a
source of motivation and satisfaction for the employees (Agada, 2014).
Research in the area of delegation indicates that delegation positively affects the
employee’s performance and satisfaction. Research goes further to differentiate the
relative degrees of delegation because it is not a dichotomous element but it depends on
how much authority is delegated. Delegation is similar to other forms of empowerment
like consultation and participative leadership because decision making is shared and only
the amount of involvement of the other parties differ (Drescher, 2017). Delegation is an
inescapable practice in organizations and it helps to legitimize lower level managers by
way of boosting their esteem and positive perception by the subordinates. In the modern
world, where a lot is expected from the leaders, failure to delegate is almost a guarantee
to failure on the job. However, it is important to note that as much as leaders should
delegate authority and responsibility, they still remain accountable. Leaders should boost
the confidence levels of their juniors to ensure they are confident enough to take on the
tasks that are delegated to them (Badder, Salem & Hakami, 2016).
Mentoring has benefits that accrue to both the mentee and the mentor. Some of the
outputs of mentoring include job performance, motivation and attitudinal benefits
regarding the work (Xu & Payne, 2014). It is a subject that is attracting more and more
attention because of the benefits associated with it which also include job satisfaction,
organization commitment, reduced turnover intentions, career development and better
26
remuneration. It is also a key factor in the learning process in organizations and it plays a
big role when it comes to work identity, improvement of outcomes and boosting the self
esteem of the employees. It serves as a bridge which facilitates information exchange and
knowledge acquisition in the organization (Cetin, Kizil & Zengin, 2013; Salami, 2010).
Research suggests that organizations should formally support mentoring by incorporating
mentoring tasks in senior employee’s development plans and performance requirements
(Hartman, Rutherford, Friend & Hamwi, 2016).
Research has shown that mentoring is one of the successful ways of facilitating
organizational learning and has demonstrated positive results coupled with enhanced job
satisfaction. It has also shown that protégés who received mentoring support performed
better in their jobs and had reduced intentions to leave the organization (Lo, Ramayah &
Kui, 2013). Additionally, organizations that have effective mentoring programs in place
are able to attract professional job seekers and retain good employees. Another positive
result of mentoring is strengthening the relationships between the supervisors and the
subordinates through the mentoring interactions (Lo et al., 2013). Mentoring is an
important practice for organizations which helps to boost interpersonal relationships,
learning, development and job satisfaction. It should be established with clear objectives
to enable measurement of the impact and evaluation vis-à-vis the desired outcomes and
objectives (Horner, 2017).
Perceived organizational support reflects employee’s perception that their supervisor
values their contribution and cares for their well-being (Nicklin & McNall, 2013). It also
refers to the extent in which the organization is perceived to value employees, contributes
and cares for their wellness. An organization that supports its employees is committed to
its workers and their needs. Research has shown that perceived organizational support is
positively correlated with work attitude and effective work performance. Employees go to
the extent of determining their action or inaction based on the nature of support they
perceive the organization accords them through their leaders. Similarly, when there is a
positive perception of organization support, then employees become more committed and
work harder in their jobs. Perceived organizational support determines the organizational
citizen behavior, performance, commitment, satisfaction and turnover intentions among
the employees (Miao & Kim, 2010). Research has found that age had an influence on the
effect of job satisfaction due to the different expectations employees have at different
stages of their lives (Olorunsola, 2012).
27
2.3.1.3 Inspirational Motivation (X3)
Inspirational motivation is the third tenet of transformational leadership. It consists of
attributes such as communication, teamwork and motivation. This is where leaders
communicate and express themselves, encourage their followers to embrace team work
and motivate them in the quest to achieve the set objectives (Lussier & Achua, 2013). It
helps to express clearly and coherently the expectations of the employees through a
shared vision which ultimately motivates the employees (Ngaithe et al., 2016). The leader
convincingly emphasizes the need to perform and meet the set objectives to the followers
which gives them a drive to achieve. Leaders who practice this possess the ability to
influence their follower’s attitudes towards them and the objectives at hand. Such leaders
also possess great communication skills which help them to communicate effectively to
the followers (Bass & Avolio, 1994). The leader continues to express enthusiasm in the
objectives, eagerness to achieve them and the confidence to deliver what is required of
him and his followers (Trmal, Bustamam & Mohamed, 2015).
Inspirational motivation also enables leaders to communicate high expectations to the
teams and inspire them to own and become part of the organization’s vision. The leaders
rely on emotional appeals to focus group member’s efforts to achieve more as a group, as
opposed to pursuing self-interests. It advocates for teamwork and the encouragement is
achieved by ensuring everyone knows the critical role they play in the organization
through their work (Tetteh & Brenyah, 2016). Additionally, inspirational motivation
enables the leader to effectively communicate to the followers about the future goals of
the organization and helps them to find ways of fitting into the organizational objectives
by clearly identifying their roles and responsibilities. In line with this, leaders also
encourage their followers to communicate and voice their ideas which create a feeling of
satisfaction since their opinions are heard and valued (Ahmad et al., 2014).
Ngaithe et al. (2016) from their study noted that communication is one of the key
elements of inspirational motivation. Inspirational motivation stems from the use of
effective and communicative influence styles. The leaders effectively communicate the
expectations from the employees and this inspires and motivates them. This also helps the
leader to come up with a vision that the employees easily own. Managers who inspire
employees align the individual objectives to the organizational objectives which makes
the achievement of the organizational objectives an attractive way of achieving the
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personal objectives. Inspirational motivation helps the leader to confidently and positively
communicate the vision and stir energy and enthusiasm in the followers. Research
indicates that communication between co-workers and between employees and
supervisors can have a significant influence on the employee’s psychological outcomes
including and not limited to job satisfaction. Additionally, employee perception of top
management openness in communication and inclusivity in the decision-making process
influences the overall job satisfaction of the employees (Winska, 2010).
Effective communication is one of the key attributes a leader should have because
communication is critical for achievement of the organizational objectives; it is also a key
success factor. It has been referred to as the social glue that holds the organization
together. Research indicates that better communication skills lead to enhanced job
satisfaction and job commitment (Paksoy, Soyer & Calik, 2017). An effective
organization communication culture encourages feedback which raises the esteem of the
employees. Consequently, effective communication yields increased job satisfaction,
safety, productivity and performance of the organization. Additionally, communication is
very important for the functioning of the organization because it reduces grievances and
turnover intentions. Poor communication leads to poor performance because there is
ineffective flow of important information upwards especially where employees do not
trust their managers. Communication provides a platform for the provision of intrinsic
needs such as recognition, appreciation and feedback which are a source of motivation for
the employees (Shonubi, Abdullah, Hashim & Hamid, 2016).
Motivation refers to the psychological processes that determine the onset, direct and
maintain voluntary actions towards organizational goals. It can also be referred to as a set
of energetic forces that emanate from both inside and outside of the individual which
helps to determine the form, direction, intensity and duration of behavior. It is a critical
factor in organizations because it significantly influences job satisfaction and job
performance (Rajan, 2015). Motivation plays a pivotal role in ensuring that employees
achieve the set objectives because it enhances cooperation, morale, commitment and
enthusiasm of employees. It is a psychological process which gives the employees
behavior purpose and direction. Motivation can stem from fairness and equity, effective
communication and providing performance-based rewards and incentives. Research has
concluded that motivation is a set of both internal and external factors which stimulate the
29
desire and energy in people to achieve, be committed to a job and pull their weight in
achieving the set objectives (Bwire, Ssekakubo, Lwanga & Ndiwalana, 2014).
One of the factors that really helps employees in achieving the set organizational goals is
motivation and its absence results in lethargy and increased turnover intentions.
Motivation is important as it determines the kind of excitement one pursues the set goals
with. Motivation enables employees to do their work efficiently and effectively and with
enjoyment. Research points to a strong positive correlation between motivation and job
satisfaction (Singh & Tiwari, 2011). A motivated employee feels satisfied with their job
and is empowered to strive for excellence and growth. Motivation boosts commitment
and satisfaction with the job and yields greater productivity. Research notes that there is a
significant difference between the productivity of motivated employees and non-
motivated employees (Osakwe, 2014).
A team refers to a unit of two or more people who come together, interact and coordinate
themselves in pursuit of a common goal. For there to be teamwork, the people need to
interact, share a common goal and remain committed in pursuit of the goal. In a team,
people are able to use their individual skills, have mutual accountability and complement
each other. In order to create effective teamwork, there must be clear goals, relevant
skills, mutual trust, employee commitment, effective communication, negotiation skills,
good leadership coupled with both internal and external support. Teamwork has a positive
impact on team performance (Musriha, 2013). Teamwork has a positive impact on
achievement of job efficiency and enhancing productivity in organizations. Additionally,
research has revealed that teamwork reduces human errors due to complimentary skills,
enhanced performance and enhances job satisfaction of employees (Benrazavi & Silong,
2013).
A few factors like the willingness to work in team which refers to the attitude of an
employee to cooperate and collaborate with others determine the effectiveness of
teamwork (Benrazavi & Silong, 2013). Motivation in a team helps to overcome
challenges and to create energy for achieving the objectives of the team and is therefore a
catalyst for team performance (Irfan & Lodhi, 2015). Teamwork has become the standard
unit of working in organizations. Through teamwork, employees are able to achieve more
through collaboration which also helps them to enhance their knowledge and skills.
Organizations seeking to boost productivity and satisfaction should support a teamwork
30
culture because not only does it increase results but also gives employees opportunities to
participate in challenges that provide learning and feelings of accomplishment. Research
goes on to indicate that organizations that encourage teamwork are more likely to attract
and retain good talent (Manzoor, Ullah, Hussain & Ahmad, 2011).
2.3.1.4 Intellectual Stimulation (X4)
The fourth tenet of transformational leadership is intellectual stimulation. Examples of
attributes associated with intellectual stimulation are knowledge sharing, creativity and
risk taking. It refers to a leader’s ability to stimulate the followers by allowing them to be
creative and innovative; thus, encouraging and allowing them to question assumptions,
re-evaluate problematic and challenging situations thereby engaging their minds. The
leader not only encourages but also supports creativity and innovation. Intellectual
stimulation helps the leader to keep the followers constantly engaged in the tasks at hand
by allowing them the free will to ask questions and provide any solutions they may have.
Followers are involved in tackling setbacks and discovering new solutions (Long et al.,
2014).
It allows followers to propose new ideas and also offer solutions based on their personal
understanding of issues. Through this, leaders do not criticize their followers in public but
encourage the followers to use the best suited approaches and to provide solutions (Omar
& Hussin, 2013). Intellectual stimulation encourages the followers to challenge their own
beliefs, the existing organizational beliefs and even those of the leaders. This component
supports new approaches of doing things and encourages the followers to come up with
new innovative ways of doing things or solving problems (Voon et al., 2011).
By encouraging followers to be creative, critical and logical, leaders help to create a
feeling of satisfaction among the followers. Leaders encourage the followers to think
creatively and offer new problem-solving skills. These same aspects lead to new
innovations which in turn lead to recognition and career advancement thus driving job
satisfaction (Ahmad, 2014). Leaders support followers because they do not necessarily
see problems as a bad thing because the problems lead to creativity, critical thinking and
innovation all of which could yield new profitable business ventures; for example, new
products or services, efficient processes or procedures which contribute to the
organization goals and objectives (Alkahtani, 2016). This quality of leaders values the
ingenuity of followers and also leads to incorporation of the followers in decision making
31
and problem resolution forums so that they can give their ideas which help in
sustainability and growth of the organization (Trmal et al., 2015).
Creativity is defined as the ability to bring something into being; it is differentiated by
novelty and originality and is inventive in nature. In the ancient times, it was seen as a
human gift to those born with creative talents. The ability to produce novel ideas and
express oneself fluently are traits associated with creativity (Raju, 2017). Creativity is
very important as a measure of contributing to an organization’s innovation. It has also
been defined as the generation of new ideas whereas innovation is the implementation of
those ideas. Organizations need to provide a supportive process and environment for
employees to be creative. Additionally, the organization should provide challenges,
involvement of staff and trust because these motivate employees to make contributions.
An environment that allows creativity is catalyzed by some room for ambiguity, freedom
and some room for risk taking (Chen, Hou & Fan, 2009).
Today, organizations have placed emphasis on productivity which involves maximum
output at minimum cost. Companies are now competing on the basis of new products or
business ideas which have proven to be significant sources of competitive advantage.
Therefore, organizations need to encourage their employees to bring forth their novel
ideas and solutions to problems be it in products, services, processes and systems all of
which will allow them to be creative (Carine, Oduor & Shukla, 2015). An ethical
organizational climate has been cited as an enabler of creativity for employees in
organizations. Additionally, employees are more associated with organizations which
encourage creativity and provide a platform with freedom of expression (Iqbal, Bhatti &
Zaheer, 2013). Research has revealed that there is a positive and significant relationship
between creativity and job satisfaction (Raju, 2017).
Innovation is basically the introduction of new processes or practices by creating new
goods or services or for example by adopting new patterns. It is considered a strategic
means through which organizations can advance their performance, growth and
efficiency. In some organizations, innovation conflicts the existing status quo which is
something leadership should encourage if they want to move ahead (Park, Tseng & Kim,
2016). Organizations are today considering innovation as a key source of competitive
advantage especially in entrepreneurship. Organizational leadership needs to provide
employees with a conducive and supportive environment to enable them to be creative
32
and innovative while also allowing room for implementation of their innovations.
Research indicates that organizations that encourage innovation and provide a supportive
climate are likely to experience growth and retention of talent (Farrukh, Iqbal & Khan,
2014).
It is impossible for organizations to escape innovation; whether new or existing,
organizations need to be innovative in order to survive. Market leaders in the various
segments emerge from the innovations they provide to the market. Innovation is a process
that leaders can influence directly and positively with the aim of improving products,
processes and profitability. For organizations to achieve innovation there needs to be
coordination of the various efforts from different employees and integration across the
specialist functions (Ghoochkanloo & Eshlaghi, 2016). Transformational leadership aims
to create a good environment which is conducive for both innovation and creativity
(Khalili, 2016). Such an environment encourages employees to be involved in problem
resolution because all the different opinions are considered (Thamrin, 2012). Research
indicates that creativity and innovation have a positive impact on job satisfaction (Park et
al., 2016). Consequently, research also indicates that job satisfaction reflects on several
variables like innovation and risk taking in the job (Al-Mahayreh & Abdel-Qader, 2015).
2.3.2 Dependent Variable (Y)
Dependent variables are outcomes of the independent variables and could also be termed
as the response variables (Creswell, 2014). This study focused on job satisfaction as the
dependent variable. Job satisfaction was studied through three elements; employee
turnover intentions, employee commitment and absenteeism. The three elements were the
key measures of job satisfaction in this study.
Job satisfaction according to Spector (1985) is defined as the attitudes of employees,
compensation, promotion, rewards, fringe benefits, operating procedures, coworkers,
nature of work and communication. Job satisfaction can be considered in terms of
intrinsic and extrinsic factors with intrinsic factors being opportunities for advancement,
growth, recognition, responsibility and achievement (Alonderiene & Majauskaite, 2016).
Job satisfaction can be viewed from the perspective of employees’ cognitive, affective
and evaluative reactions towards their jobs. Thus, it is the general attitude towards one’s
job or the difference between the amount of rewards received and the amount the
33
employees believe they should receive (Akpan, 2013). It plays a big role in understanding
employees’ behavior (Islam & Zaman2, 2013).
Job satisfaction results in higher employee retention rates and higher productivity from
the employees (Emmanuel & Hassan, 2015). Job satisfaction cannot be overemphasized
in the contemporary world especially because of the high dynamic and complex business
environments that people are operating in. It is also fundamental in the creation of a well-
developed leadership style (Ramos, 2014). Additionally, human resource is regarded as
the organization’s most valued asset and a major source of competitive advantage. This
emanates from the fact that organizations depend on people to achieve their objectives
and when there is no job satisfaction then the employees are faced with choices of
whether to quit or to continue staying. This negatively affects the organizational
effectiveness (Tetteh & Brenyah, 2016).
Job satisfaction is mainly driven by intrinsic factors among them the work itself,
recognition, autonomy, advancement and ability utilization. Work itself refers to the
employees’ likes or dislikes with their job and goes on to determine whether the
employee’s job is enjoyable or not. A study done on employees of various types of
organizations in Pakistan indicates that there is a significant correlation between work
itself with work motivation and satisfaction (Danish, 2010). Consideration of this topic in
the past was by Gilbreth and Taylor in 1911 whose focus was more on specialization and
simplification of tasks in order to maximize the efficiency of the workers. However, with
time, this could not hold as it resulted in decreased employee satisfaction, turnover,
absenteeism and difficulties in managing employees in simplified jobs (Humphrey,
Nahrgang & Morgeson, 2007).
In this study, job satisfaction was measured through three constructs namely
organizational commitment, absenteeism and turnover intentions which are discussed in
the next section. The study formulates questions related to all the constructs intended to
measure organizational commitment, absenteeism and turnover intentions.
2.3.2.1 Organizational Commitment
Organizational commitment can be defined as a bond or a link of the employee to the
organization. Additionally, it can be referred to as the strength of an employee’s
identification and involvement in and with the organization and can be characterized by; a
34
strong belief and acceptance of the objectives of the organization, the willingness to go
out of your way on behalf of the organization and a relatively strong need to continue
being a member of the organization (Suma & Lesha, 2013). There has been an increased
focus on organizational commitment because committed employees are known to be
engaged in more organizational citizenship behaviors and go out of their way to perform
as required and even above expectations. Organizational commitment could vary in
relation to the emotional attachment to an organization, the costs associated with leaving
the organization and feelings of obligation to remain in the organization (Park, Christie &
Sype, 2014).
According to Islam and Rahman (2016), the banking industry has been curbed with
problems like extended working hours, pressure, non-conducive working environments,
lack of fairness, reducing career growth opportunities and poor treatment all which have a
significant impact on the level of organizational commitment and job satisfaction. Noting
the level of commitment can greatly influence the quality of service rendered to
customers, then organizational leaders need to ensure that they promote job satisfaction
and commitment yielding policies and activities. Employee commitment is beyond being
passively loyal to being actively involved, ready to transcend beyond personal gain for
the organizational gain (Yucel & Bektas, 2012).
2.3.2.2 Absenteeism
Absenteeism refers to a habitual pattern of absence from duty or an obligation. This has in
the past been viewed as an indicator of poor performance which could result from
managerial problems. High rates of absenteeism could be as a result of poor or low
morale or the work environment. Additionally, people who are dissatisfied with their
jobs, and more so the work itself, have a higher frequency of absence compared to people
who have job satisfaction (Thirulogasundaram & Sahu, 2014). Job satisfaction is an
important area for organizations to address especially due to its impact on employee
absenteeism, turnover intentions and behavior. This is because a satisfied person is more
often present at work making positive contributions whereas a dissatisfied person will be
absent more often and is likely to experience stress and ultimately leave the organization.
Studies in this area reveal that satisfied employees are usually present at work and
consequently indicate that dissatisfied employees are likely to leave the organization
(Islam, Mohajan & Datta, 2012).
35
According to Ram (2013), absenteeism is costly to the organization because human
resources are the engine in most organizations. It has been attributed to employees
avoiding a painful or a dissatisfying work environment which could also result from lack
of motivation. Therefore, management and the organization leaders must be able to
understand the relationship between job satisfaction and other factors with employee
absenteeism, so that they can be able to provide the right work environment and other
factors to obviate absenteeism. Understanding the factors resulting in absenteeism will
help the leaders to come up with policies to address the problem. For example, motivation
and communication are considered to affect how often an employee is absent (Gangai,
Agrawal & Gupta, 2015).
2.3.2.3 Employee Turnover Intentions
Employee turnover refers to the number of employees moving in and leaving an
organization; it is usually presented as employee turnover ratio or simply referred to as
the number of employees leaving an organization. Employee turnover is a ratio that
compares the number of employees leaving an organization to the average number of
total employees in a given time period. It is a big concern for organizations because it is a
costly expense with a direct impact on the organizations performance (Shukla & Sinha,
2013). Turnover depends on an employee’s level of satisfaction (Awasthi, 2015). Total
turnover is the total number of employees leaving the organization during a given period
divided by average number of employees during that period. Turnover could be as a result
of many factors like right sizing, hiring freezes, layoffs, lack of career growth, leadership
among others, which ultimately affect the level of satisfaction an employee derives from
the job (Shukla & Sinha, 2013).
Studies have revealed that the lack of satisfaction has consequences among them turnover
intentions which consequently affect the quality of service rendered, productivity and
ultimately the overall organizational success. Knowledge of this and a vision of the bigger
picture of the consequences of turnover and job satisfaction should spur leaders into
providing the best environments to prevent this (Joarder & Ashraf, 2012). Employee
turnover may be voluntary or involuntary; the involuntary turnover is initiated by the
organization while voluntary turnover is initiated by employees. Job satisfaction is the
attitudes and feelings people have about their work. Positive and favorable attitudes
towards the job indicate job satisfaction while negative and unfavorable attitudes towards
36
the job indicate job dissatisfaction (Armstrong, Riemenschneider, Allen & Reid, 2006).
Employee job satisfaction is the fulfillment, gratification, and enjoyment that come from
work. It is not the money or the fringe benefits, but the feelings employees receive from
the work itself (Asegid, Belachew & Yimam, 2014). Job satisfaction has been found to be
a consistent predictor of turnover intentions in many organizations.
Kanwal and Majid (2013) investigated the factors which are the major contributors
towards employee’s job satisfaction. It was found that low pay, long working hours,
bonuses, rewards and effective communication were the contributors towards job
satisfaction or dissatisfaction and have impact to the employee’s intention to leave or stay
in the organization. Nyamekye (2012) argued that non-monetary benefits had a direct
bearing on employees’ job satisfaction. The employees were dissatisfied with supervision
and non-participation in the decision-making process which may influence their intention
to leave the job. Lee and Jimenez (2011) stated that performance-based rewards and
supervision support reduce the possibility that employees will opt to leave their current
jobs, and that job satisfaction is the most important predictor of turnover intention. In a
recent study, it was observed that it is bad working conditions, lack of career growth,
unfair compensation, negative supervisory support, the lack of employee development
and job stress that caused the employees to leave organizations (Sattar & Ahmed, 2014).
2.3.3 Moderating Variable (Z)
Moderating variables are variables that affect the direction or strength of a relationship
between independent variables and dependent variables (Creswell, 2014). This study had
job security as the moderating variable between transformational leadership and
employee job satisfaction. The elements considered under job security were anxiety,
fairness and stress.
Job security refers to one’s expectations regarding the continuity in a job situation. Job
security goes over and above the loss or retention of a job to the continuation or loss of
certain desirable job features such as promotion opportunities, favorable working
conditions and long-term growth opportunities with the organization (Akpan, 2013). The
importance of job security comes from its influence on work related outcomes for
example employee health, turnover and job satisfaction (Yousef, 1998). This has become
a key variable in management with growing emphasis on understanding employee
37
reactions to changes in the organizations, for example mergers and downsizing which
result in uncertainty and major concerns on job security (Davy, Kinicki & Scheck, 1997).
Job security is a key factor that influences the employee’s perception of job satisfaction
and employers should therefore strive to constantly provide it so as to ensure that
employees have a positive perception of satisfaction, which in turn yields greater
organizational commitment (Alonderiene & Majauskaite, 2016). Job security provides
employees with job satisfaction and has an impact on their motivational levels. It has an
important role in maintaining peace and contributing to the productivity of the
organizations (Islam & Zaman2, 2013). Job security is also the feeling of having a proper
job with the assurance of its continuation in the foreseeable future and also the absence of
factors that could threaten the continuation of that job. Industrial psychologists refereed to
job security as one of the key elements that yield job satisfaction and the lack of it
reduces job satisfaction levels of the employees (Jandaghi, Mokhles & Bahrami, 2011).
Job security transcends from the aspect of job loss to the aspect of availability of other
jobs in case the loss does happen. It has been inferred that job insecurity threatens
employees given the risk of loss of material, social or psychological benefits associated
with the job. Research reveals that job insecurity yields negative employee attitudes,
health and behavior as well as having direct consequences on satisfaction and
performance. One common source of insecurity is competition among institutions which
yields pressure on profitability and results in cost-cutting initiatives which come by way
of lay-offs, redundancies and reduced benefits (Reisel, Chia, Maloles & Slocum, 2007).
The Kenyan banking sector is currently going through a lot of changes causing the banks
to downsize and is currently characterized with offers of voluntary early retirement,
redundancies and lay-offs in a bid to cut on costs. Job insecurity results in anxiety, anger
and stress resulting in distraction from the organization (Reisel, Probst, Chia, Maloles &
Konig, 2010).
2.3.4 Operationalization of Variables and Hypothesis Testing
Operationalization of variables refers to the translation of the variables into parameters
that can be measured quantitatively (Saunders, Lewis & Thornhill, 2016). Based on the
conceptual framework, the study had four independent variables, one moderating variable
and one dependent variable. They were all measured using three parameters. The
independent variables were idealized influence, individualized consideration,
38
inspirational motivation and intellectual stimulation. Idealized influence was measured
using charisma, trust and ethics. Individualized consideration was measured using
delegation, mentoring and support. Inspirational motivation was measured using
communication, teamwork and motivation. Intellectual stimulation was measured using
knowledge sharing, creativity and risk taking. The moderating variable was job security
which was measured using anxiety, fairness and stress. The dependent variable job
satisfaction was measured using organizational commitment, absenteeism and employee
turnover intentions. Table 2.1 indicates the operalization of the variables and hypothesis
testing.
Table 2.1: Operationalization of Variables and Hypothesis Testing
Variables and Measurement Hypothesis Test
Independent
Variables
Parameters
Idealized
Influence (X1) Charisma
Trust
Ethics
H01: There is no significant
influence of idealized influence on
job satisfaction among employees in
commercial banks in Kenya
Multiple Linear
Regression, p ≤
.05
Individualized
Consideration
(X2)
Delegation
Mentoring
Support
H02: There is no significant
influence of individualized
consideration on job satisfaction
among employees in commercial
banks in Kenya
Multiple Linear
Regression, p ≤
.05
Inspirational
Motivation
(X3)
Communication
Teamwork
Motivation
H03: There is no significant
influence of inspirational motivation
on job satisfaction among
employees in commercial banks in
Kenya
Multiple Linear
Regression, p ≤
.05
Intellectual
Stimulation
(X4)
Knowledge
Sharing
Creativity
Risk Taking
H04: There is no significant
influence of intellectual stimulation
on job satisfaction among the
employees in commercial banks in
Kenya
Multiple Linear
Regression, p ≤
.05
Moderating Variable (Z)
Job Security Anxiety
Fairness
Stress
H05: There is no significant
moderating effect of job security
between transformational leadership
and job satisfaction among
employees in commercial banks in
Kenya
Multiple Linear
Regression, p ≤
.05
Dependent Variable (Y)
Job
Satisfaction Organizational Commitment
Absenteeism
Employee Turnover Intentions
39
2.4 Empirical Review
Empirical review is an analysis of studies that have been done by other scholars in the
area under study. Empirical review for this study focused on studies done in the area of
transformational leadership and job satisfaction. An empirical review is important
because the review of past studies helps to bring out the methodologies used and findings
of other authors. It sheds more insight on how to conduct the research and helps to inform
the research methodology, data collection, analysis and presentation. The empirical
review for the study is based on the research questions.
2.4.1 Influence of Idealized influence on Job Satisfaction
This section discusses the influence of idealized influence on job satisfaction. Idealized
influence is broken down into three constructs which are charisma, trust and ethics.
2.4.1.1 Charisma
Ansar, Aziz, Majeed and Rassol (2016) define charisma as a certain quality of a person
which sets him apart from ordinary people allowing him to be treated in a unique way
since he is perceived to have supernatural powers. Such an individual enjoys loyalty and
authority by virtue of a unique mission which he appears to carry. Research has shown
that charismatic leaders are masters of social skills who are mindful of the social
environment around them. They are able to attract a following based on the things they
say which appeal to the follower’s innermost desires. They have a unique ability to put
across a message in a convincing way which also charms the followers. Followers are
able to identify with charismatic leaders because the leaders portray conformity of needs,
desires and aspirations. A leader who possesses charisma is able to influence his
followers because they already identify with him; this in turn boosts the employee’s
satisfaction (Khuong & Hoang, 2015).
Charisma is an important element of transformational leadership style which has a big
influence on team outcomes and leaders who adopt it become an inspiration to others
through their dedication (Yang & Islam, 2012). Charisma enables a leader to inspire the
followers as a result of their self confidence, boldness and communication skills (Avolio
& Bass, 2002). A research study sought to examine the extent leadership, charisma and
vision could be discriminated by followers and how they influenced follower
commitment and performance across three countries; Singapore, New Zealand and India.
40
The results of the study revealed that charisma was positively related to the follower’s
commitment to the performing unit. There was consistency across the three countries
studied. Additionally, there was also a correlation between commitment and performance
which are a function of satisfaction (Hwang, Khatri & Srinivas, 2005).
Bacha (2010) conducted a study on the relationships among organizational performance,
environmental uncertainty and employee’s perceptions of CEO charisma, and found that
CEOs who are found to be increasingly energetic have an impact on organizational
performance, as opposed to model CEOs who have no significant impact on
organizational performance. According to Khuong and Hoang (2015), as much as
compensation and fringe benefits matter, the leader’s personality and characteristics are
more important as they affect the motivational work environment for the staff which in
turn yields positive job attitudes. Huang, Cheng and Chou (2005) in their study dubbed
fitting in organizational values sought to investigate whether CEO charismatic leadership
had a positive effect on the following employee outcomes: extra effort to work,
satisfaction with the CEO and organizational commitment. Their findings demonstrated
that charisma did indeed have significant effects on employee outcomes of extra effort,
satisfaction with the CEO and organizational commitment.
According to Belias and Koustelios (2014), idealized influence or charisma produces
positive emotions from followers which lead to emulation of the leader making them a
role model. This leads to loyalty and high moral standards among the employees.
Leadership is a process where a person influences another to perform certain tasks in a
certain way for the achievement of an objective. It is anchored mainly on behavior which
is aimed at obtaining respect, being trusted and gaining confidence which leads to a
strong buy-in of the vision. Transformational leaders are viewed as role models who
provide the guidance that followers require by letting them know of their values by what
they exemplify in their daily behavior (Rowold & Vogel, 2014; Beerel 2009). By virtue
of their positions in the organizations, leaders are perceived as the representatives of the
organization and from this, followers who perceive their leaders as transformational role
models are more probable to trust the organizations top management.
Yang and Islam (2012) conducted a study that sought to demonstrate the influence of
transformational leadership on job satisfaction using the balanced scorecard perspective.
The study was done on the sales employees of the top four insurance firms in Taiwan that
41
had the greatest market share. The findings showed that charisma played a role in
fostering job satisfaction among the employees and was a significant predictor of job
satisfaction. Hanaysha et al. (2012) conducted a study in Malaysia among administrative
and clerical staff involved in graduate and postgraduate affairs in three universities. They
sought to establish if there was a positive relationship between charisma and job
satisfaction. The research was conducted among 320 employees through an 18-item scale
questionnaire from the MLQ and a response rate of 31.5% was obtained. The findings
revealed that there was a positive relationship between charisma and job satisfaction
which was statistically insignificant. This finding necessitates more research in the area
since majority of the studies showed a positive correlation between charisma and job
satisfaction with statistical significance.
Charisma has been studied widely and according to a study in Vietnam it was found to
catalyze motivation. The research was conducted in the auditing field and it sought to
establish the effect of leadership styles on employee motivation. A sample size of 320
respondents was chosen in a city in Vietnam. The researcher sought to establish if
charismatic leadership positively affects the employee motivation. A structured
questionnaire that employed the Likert scale was used to collect data. The findings of the
study revealed a positive correlation between charisma and employee motivation; thus,
charisma positively affects motivation (Khuong & Hoang, 2015).
Emmanuel and Hassan (2015) carried out a study to establish the effect of
transformational leadership on job satisfaction in four and five-star hotels in Kuala
Lumpur. They sought to examine through one of their research objective the effect
charisma has on employee job satisfaction. A total of 130 questionnaires were distributed
and 123 questionnaires were returned. The findings of the study revealed that charisma
had a positive and significant relationship with job satisfaction. Arzi and Farahbud (2014)
who studied the impact of leadership style on job satisfaction in Iranian Hotels and found
that a vision is very critical in sustaining and growing employee job satisfaction. Their
study found that the leadership style significantly impacts job satisfaction.
Ngaithe et al. (2016) examined the influence of idealized influence on staff performance
in state owned enterprises performance in the Kenyan perspective. The study mainly
sought to examine the influence of idealized influence and inspirational motivation on
employees’ performance. The study was anchored on the positivism research philosophy
42
and stratified random sampling technique was used to obtain the sample size of 163
respondents. Primary data was analyzed using both exploratory factor analysis and
regression analysis. Findings of the study revealed a positive relationship between
idealized influence and performance. The choice of positivism research philosophy and
stratified sampling technique but the choice of descriptive research design was contrasted
by analysis of data using regression analysis it would have been appropriate to adopt
descriptive-correlation research design. Moreover, since the data was in ordinal scale
structural equation modeling (SEM) would have been the most appropriate.
Gitoho, Muchara and Ngugi (2016) examined the influence of idealized influence on
employee satisfaction amongst listed companies in Nairobi securities exchange. Stratified
sampling technique was used to draw 400 employees working in heterogeneous
managerial positions within the listed companies. Data was analyzed using exploratory
factor analysis. Further, regression analysis was used to examine the nature of the
relationship between idealized influence and employee satisfaction. The findings revealed
a positive and significant relationship between idealized influence and employee job
satisfaction. From the study it was deduced that management have a great role in
determining employee motivation.
Metwally, Eli-bishsishy and Nawar (2014) examined the link between transformational
leadership and employee job satisfaction in multinational FMCG firms in Egypt. Simple
random sampling was used to draw 200 respondents who were stratified according to
three departments within the company. Primary data was collected using MLQ developed
by Bass in 1978 to measure leadership and job satisfaction was measured using
Minnesota Satisfaction Questionnaire (MSQ), the duo adopted a 5-point Likert scale.
Data was analyzed using regression and correlation analysis whose results revealed a
positive and significant relationship between idealized influence, individualized
consideration, inspirational motivation, intellectual simulation and job satisfaction. The
study recommended that organizations ought to adopt transformational leadership to
motivate their employees and consequently achieve superior performance.
Emu and Umeh (2014) empirically examined the relationship between leadership style
and job satisfaction among customer relationship officers in Nigerian banks using a
quantitative correlation research design. Simple random sampling was used to draw 85
customer relationship officers. The study adopted MLQ nine attributes as the main tool of
43
primary data collection. A correlation analysis revealed a positive and significant
relationship between idealized influence and employee job satisfaction. The study
findings acted as a benchmark which Nigerian banks can adopt to manage their
employees effectively. From the study transformational leadership was perceived to be an
ideal leadership style to drive job satisfaction.
Bayram and Dincs (2015) examined the role of transformational leadership on employee
satisfaction in private universities in Bosnia. Simple random sampling was used to draw
150 respondents from the private universities. Data was analyzed using exploratory factor
analysis, mean, standard deviation, correlation and regression analysis. The results of the
study revealed a positive and significant relationship between idealized influence and
employee job satisfaction. Although, the results revealed that employees were highly
satisfied with the nature of work they were not satisfied with work assignment and
operating conditions which needed further examination to boost the employee’s morale.
Thus, private universities needed to check on the issues triggering employee motivation
which should drive their primary goal of promoting firm performance.
Ahmad et al. (2014) examined the impact of transformational leadership on employee
motivation in the telecommunication sector in Punjab. Simple random sampling
technique was used to draw a sample of 400 respondents. Data was collected using
questionnaires which were anchored on the MLQ. Descriptive analysis, correlation
analysis and regression analysis were used to analyze the data. The results of the study
revealed a positive and significant relationship between transformational leadership and
employee motivation. A close scrutiny of transformational leadership attributes revealed
that they had a positive and significant relationship with each other. The study concluded
that transformational leadership had a significant influence on employee motivation.
Long et al. (2014) examined the impact of transformational leadership on job satisfaction
in Malaysia. Under a descriptive research design, stratified sampling was used to draw a
sample of 378 respondents from 6 departments of Government Link Company (GLC) in
Malaysia. Data was collected using questionnaires anchored on the MLQ and MSQ
questionnaire. Correlation and regression analysis tests revealed a positive but non-
significant relationship between idealized influence and job satisfaction, though there was
a positive and significant relationship between individualized consideration and job
satisfaction. The study concluded that there is need for leadership to be effective, to
44
continuously replenish their knowledge and offer positive attributes which will trigger
superior employee performance within their organization.
2.4.1.2 Trust
Trust occurs in a framework of interaction which is influenced by both the personality
systems and the social systems. Personal trust involves a bond between individuals, one
that is preserved by the emotional pain one is bound to experience in case of betrayal.
Trust is a very important component in the organization’s long term stability and well
being of the employees and is described as a social lubricant to relationships.
Additionally, the higher the organizational trust, the more satisfied and productive
employees tend to be (Salleh, Zahari, Ahmad, Aziz & Majid, 2015). It has further been
described as a psychological state comprising the intention to accept vulnerability based
on positive expectations of the intentions or behavior of another (Kelly et al., 2015).
Fard and Karimi (2015) conducted a study with the aim of establishing the relationship
between organizational trust and job satisfaction. The study was conducted among
employees of a university. The study employed a descriptive correlation research design
and out of 340 employees, 180 were selected using simple random method and sampling
table for the research which employed research questionnaires. A Pearson correlation
coefficient test and structural equations modeling were used to analyze the data. The
results of the study revealed a positive and significant relationship between trust and job
satisfaction. Additionally, trust binds people together and enables the people to focus on
long-term results which are necessary for organizational success.
Meral, Yashoglu and Semercioz (2016) carried out a study that sought to establish the
effects of trust on job satisfaction and the mediatory role of new identification between
trust and job satisfaction in mergers. They studied 143 employees of a newly merged
bank called TEB and Fortis banks which consisted of 335 branches and 5646 employees
before the merger and 603 branches 9945 employees after the merger. A correlation
analysis was conducted to measure the strength of the relationship between trust and job
satisfaction. The results of the study revealed a positive and statistically significant
correlation between trust and job satisfaction. Trust enables coordination and effective
performance of work, yields less anxiety amongst employees and fosters an acceptance of
45
changes that occur in the bank. The study concluded that trust to management
significantly affects the employee’s job satisfaction.
Srivastava (2013) conducted a study titled job satisfaction and organizational
commitment relationship with the effect of personality variables, and had trust and locus
of control as the moderating variables. The research instruments were administered to 247
middle level managers in the private sector. Data was analyzed and the findings revealed
that job satisfaction was positively related to organizational commitment, and trust
moderated the job satisfaction and organizational commitment relationship. These
findings were consistent with findings of a study dubbed the relationship between
organizational trust and job satisfaction, whose context was the Federal organization of
US which found that trust in an organization led to employee job satisfaction and that the
two variables had a direct correlation (Callaway, 2007).
Kelly et al. (2015) studied the influence of trust and job satisfaction on safety climate
among managers in a large U.S. air carrier. They developed a conceptual model to
establish the influence of trust and job satisfaction on the safety climate. The study used
questionnaires as the research instruments and the responses were ranked using a five-
point Likert scale. The questionnaires were administered to 1299 management employees
and a total of 729 usable questionnaires were returned indicating a response rate of
57.7%. Data was analyzed and the findings revealed that coworker trust and supervisor
trust were significantly and directly associated with both job satisfaction and safety
climate. However, the results cannot be generalized to entire organization or to other air
carriers or other types of organizations because the research did not include other
employees.
In the age of globalization and technological advancement, trust enables effective
communication in organizations which is a key determinant of job satisfaction. Research
revealed that trust lubricates organizational processes by fostering increased cooperation,
acceptance and buy-in of objectives, boosting discretional performance, job and team
satisfaction, organizational citizenship behavior, enhanced loyalty and reducing
employee’s intentions to leave the organization (Nair & Salleh, 2015). Research indicates
that people who are in high trust environments live longer, enjoy greater wellness and job
satisfaction. In contrast, a low trust environment sucks energy, results into stress and
46
reduced wellness which has the possibility of destroying performance. Lack of trust also
suppresses expressions which may lead to a lot of dysfunctions in the organization hence
the need to cultivate a trust culture which is a precursor to job satisfaction and
performance (Jameson, 2010).
Sharkie (2009) in the study titled trust in leadership is vital for employee performance
discusses the importance of trust in boosting performance. The study states that trust is a
very important component in the leader-employee relationship because it is one of the
characteristics that motivate employees to perform beyond expectations. Trust is referred
to as the key to cooperation in organizations and it derives discretional input from the
employees. In other words, trust influences employee’s attitudes, cooperation and
performance. The findings of the study revealed that employee reciprocity which comes
in the form of commitment to the organization, the personal will to engage in extra roles
depends strongly on the employee’s assessment of the level of support management
accords them. Such assessment is based on the beliefs, integrity and trustworthiness of
management. Hence it is critical for management to build trust in order to earn
discretionary support from the employees since it plays a major role in the leader-
employee psychological contract (Abdullah, Hamzah, Arshad & Isa, 2011). A study on
the impact of CSR on casino employees’ organizational trust, job satisfaction and
customer orientation found that CSR has a positive effect on organization trust and
additionally, organization trust positively influences job satisfaction (Lee, Song & Lee,
2013).
2.4.1.3 Ethics
According to Yates (2014), ethics in leadership refers to a leader’s ability to demonstrate
appropriate conduct through their actions and relationships with others. Additionally,
ethics influences the impact of a leader, his relationship with the followers and also
determines the organizational values (Northouse, 2013). In a study among United
Kingdom companies and some continental Europe companies, it emerged that the key
issues around ethics are bribery, corruption, facilitation of payments, whistle blowing,
discrimination and harassment. Globally, organizations are facing many problems
resulting from unethical practices. Ethical behaviors basically involve principles like
honesty, integrity, fairness and concern for people. Unethical leadership leads to
47
increased costs that arise with employee turnover, the need for increased supervision,
decreased employee job satisfaction and productivity (Bello, 2012).
According to Anaza, Rutherford, Rollins and Nickell (2015), job satisfaction can be
triggered by an employee’s perception of the organization’s ethical climate. A good
ethical environment has the potential to boost employee’s job satisfaction levels while the
consequences of ethical misgivings are detrimental to the organization. Globalization has
resulted in a myriad of interactions within and outside the country borders and this has
resulted in conflicting expectations and ethical dilemmas which need a good ethical
background to enable the employees handle them appropriately. Their study confirms that
ethical climate influences job satisfaction and helps to develop affective commitment
from organizational buyers.
Ren and Chadee (2017) conducted a study titled ethical leadership, self-efficacy and job
satisfaction in China with the moderating role of guanxi. The purpose was to find out how
employee perceptions of the ethical conduct of the leaders affect their job satisfaction.
They developed a model to conduct the research and had a sample size of 388
professional employees. The findings revealed a positive correlation between ethical
leadership and job satisfaction which is negative if moderated by guanxi. Guanxi is a
complex relational phenomenon in Chinese tradition which may act as a substitute for
ethical leadership in the Chinese workplace. The research instrument was a questionnaire
that utilized the Likert scale. This research revealed the fact that different
conceptualizations of ethical leadership cannot be applicable across all cultural contexts
because for example in China guanxi played a substituting role and reduced the impact of
ethical leadership on job satisfaction.
Ahmed et al. (2012) carried out a study that sought to establish the relationship between
organizational ethics and job satisfaction among bank employees in Pakistan. The study
collected data from 230 employees from a convenience sample. The study used a
questionnaire to collect data from the employees and also used a 20-item job satisfaction
scale and the responses were ranked in a Likert scale. A Cronbach’s alpha test was carried
out for reliability and other tests, tests for correlation and structural model were run in the
data analysis. Results revealed that three ethical climates existed; thus, egoistic ethical
climate, benevolent ethical climate and principled ethical climate. Egoistic ethical climate
focused on organizational self-interest, benevolent ethical climate focused on employee’s
48
interests and principled ethical climate focused on obedience due to cultural differences.
Egoistic ethical climate was negatively related to job satisfaction, principled ethical
climate had no relationship with job satisfaction while benevolent ethical climate and top
management support for ethical behavior were positively related to job satisfaction.
Koh and Boo (2004) in their study on organizational ethics and employee satisfaction and
commitment sought to establish the relationship between organizational ethics and
organizational outcomes. They note that ethical values influence not only employee
attitudes but also employee behavior. They interviewed 237 managers in Singapore and
their results revealed a positive and significant relationship between ethics and job
satisfaction. The ethics herein referred to top management support for ethical behavior
and the association of ethical behavior with career success. They concluded that high
ethical levels were associated with higher job satisfaction levels and that favorable
organizational ethics produced favorable organizational outcomes like satisfaction.
According to Kim and Brymer (2011), their study on the effects of ethical leadership on
manager job satisfaction, commitment, behavioral outcomes and firm performance found
that executive’s ethical leadership was positively related to the organizational manager’s
job satisfaction and also to the organizational commitment.
Dinc and Aydemir (2014) conducted a study titled the effects of ethical climate and
ethical leadership on employee attitudes in Bosnia. They studied employees from private
universities in Bosnia and Herzegovina (BIH) and used a sample size of 213 employees.
The sample size for the study was 260 but only 220 respondents undertook the survey
with only 213 being usable. The questionnaire used a five-point Likert scale as the points
of measure. Tests for correlation and regression analysis were conducted on the data that
had been collected. The findings of their study revealed a positive correlation between an
ethical climate and job satisfaction. A further analysis showed that there was a positive
correlation between the employee’s perception of ethics in the organization and job
satisfaction, which results in reduced turnover intentions from the employees (C.
Pettijohn, L. Pettijohn & Taylor, 2008).
Yates (2014) conducted a study to establish whether ethical leadership contributed to job
satisfaction, organizational commitment and organizational citizenship behavior. The
results of the study revealed that indeed followers led by highly ethical leaders reported
49
higher levels of job satisfaction and organizational commitment than did followers who
perceived their leaders as less ethical. In a study conducted by Tsai and Huang (2008),
they found that employees who worked in professional environments which had concern
for others derived greater satisfaction from their jobs. The study was conducted among
352 nurses who worked in Taiwan and their study sought to establish the relationship
among ethical climate types, facets of job satisfaction and components of organizational
commitment. Their study sought to establish the relationship between variables using
factor analysis, reliability, descriptive statistics, correlation and regression. Research also
indicates that good ethics is good business which points to a correlation between ethical
values and performance.
In the study of ethics and job satisfaction, there is an opinion that job satisfaction leads to
integrity. Research was conducted among police officers and one of the hypotheses being
tested was whether job satisfaction led to integrity among the officers. Results revealed
that there was indeed a positive and significant relationship between job satisfaction and
the integrity of the police officers. Additionally, a code of ethics was also found to have a
positive and significant relationship with integrity among the officers (Othman, 2014).
Further research in the area of team virtues and performance was conducted with one of
the dependent variables being satisfaction with the leader. Results revealed that there is a
relationship between the leader’s behavioral integrity and follower satisfaction with the
leader which is a facet of job satisfaction (Palanski & Yammarino, 2011).
2.4.2 Influence of Individualized Consideration on Job Satisfaction
This section discusses the influence of individualized consideration on job satisfaction.
Individualized consideration is broken down into three constructs which are delegation,
support and mentoring.
2.4.2.1 Delegation
Delegation refers to a conceptualized process that involves assigning crucial tasks to
subordinates and giving them the responsibility for decisions which are usually made by
the manager. It leads to an enhanced amount of discretion being given to the followers
which is anchored on the authority to make decisions without the prior consent from the
manager. It is basically where the leader allows the followers to make decisions without
necessarily running their ideas with the manager before deciding. It also comes with the
50
aspects of authority, responsibility and accountability for the decisions (Musenze,
Thomas & Lubega, 2014). Additionally, the concept of delegation is highly anchored on
trust between the leader and the follower. Thus, leaders usually assign authority and
power to followers whom they trust will not misuse the power and authority given to
them. Delegation helps to overcome obstacles of corporate decision making and results in
perceived empowerment and yields job satisfaction (Noblet, Rodwell & Allisey, 2009).
Delegation has been found to have a positive relationship with job satisfaction, task
performance and organization commitment. It provides an avenue for leaders to empower
their followers by affording them new opportunities to gain new experience (Banford,
Buckley & Roberts, 2014). Joiner and Leveson (2015) carried out a study on effective
delegation among Hon Kong Chinese male managers with the mediating effects of Leader
Member Exchange (LMX). They found a direct association between delegation and job
satisfaction. In their research, they interviewed 186 Chinese subordinate managers in a
transport company. Data was analyzed and the results revealed that employees who are
entrusted with decision making and receive support from their supervisors and colleagues
are more satisfied with their jobs.
Musenze et al. (2014) conducted a research on delegation and job satisfaction and
evaluated the relationship within Uganda’s primary education sector. They sought to
establish the effect of delegation on primary school teachers’ job satisfaction. They
employed a cross sectional research design and a total of 247 survey questionnaires were
distributed. Data was analyzed using Structural Equation Modelling (SEM) and the
results indicated that save for decision making, the other dimensions of delegation like
autonomy, authority and responsibility predicted job satisfaction. Riisgaard, Nexoe, Le,
Sondergaard and Ledderer (2016) did a review paper with the aim of establishing the
relationship between task delegation and job satisfaction in general practice. The review
found that a few nurses had negative attitudes and experiences towards task delegation
especially due to an increased workload. However, majority were generally satisfied with
their jobs and the various tasks they performed which were delegated to them by the
general physicians. Additionally, they attributed this satisfaction to the autonomy which
they enjoyed.
51
Ukil (2016) studied the impact of employee empowerment on employee satisfaction and
service quality in financial enterprises. They noted that one of the ways in which
delegation occurred was through empowerment. The sample for this study was 240
employees drawn from 20 different financial institutions in Bangladesh. Questionnaires
were used to collect data. Results of data analysis revealed that employee satisfaction and
service quality largely depended on employee empowerment. Additionally, satisfied
employees were found to offer better quality service. The study concluded that by
empowering employees, organizations can increase the level of satisfaction their
employees have with their jobs which consequently raises the quality of service they
provide to their stakeholders.
Ameer, Bhatti and Baig (2014) carried out a study on the impact of employee
empowerment on job satisfaction. The study adopted a descriptive research design and
conducted a survey among the respondents. Data was collected using questionnaires with
nineteen closed ended questions and the responses were ranked using the five-point Likert
scale. The data was analyzed using correlation and regression analysis. The results
revealed that empowerment was based on the notion of giving employees skills,
resources, authority, opportunity, motivation, responsibility and accountability for their
actions which not only contributed to job satisfaction but also their competence levels.
Kombo, Obonyo and Oloko (2014) also found that delegation had a strong relationship
with satisfaction and performance thorough raised enthusiasm among the employees.
Additionally, delegation is not only rewarding for the employees but it also raises the
employee’s sense of accomplishments and self-esteem.
Drescher (2017) conducted a study to examine the relationships between delegation,
employees’ perception of leader performance and likeability, and the followers’ job
satisfaction. A convenience sample of 304 participants was selected from social networks
and invited to participate in an online survey. The results of regression analysis revealed
that delegation leads to a positive evaluation of the leader and the mediation analysis of
likeability influences the relationship between delegation and employee’s job satisfaction.
Delegation affected how employees rated the leader’s performance related and affective
qualities which in turn influenced the level of satisfaction.
52
Farmer (2011) sought to establish the effects of empowerment on supervisory relations,
burnout, and job satisfaction in two American prisons. The study was a comparative case
study and one of the objectives sought to assess the effect of an empowered staff
management model on staff perceptions of delegation of authority on job satisfaction. The
research process obtained 149 responses and data was analyzed using factor analysis and
a bivariate analysis. Results revealed that contrary to most of the studies in this thematic
area, the effect of delegation of authority and responsibility was not significant on job
satisfaction but there were significant effects of empowerment on job satisfaction.
2.4.2.2 Mentoring
Mentoring is a reciprocal relationship bound with an emotional commitment between an
apprentice worker and an experienced worker. It refers to the teaching and learning
process of knowledge and competence, which involves sharing of advice and role
development with both formal and informal support from the experienced worker to the
apprentice. Mentoring provides people with opportunities for professional growth and job
satisfaction and lack of satisfaction results in turnover (Mariani, 2012). Mentoring helps
to facilitate continuous interactions between a more experienced person and a less
experienced person. This results in the less experienced person becoming more skilled.
Among the advantages associated with mentoring are the outcomes of positive attitudes
and behavior among the less skilled workers, rejuvenation, enhanced job performance,
job satisfaction, satisfaction with colleagues and the organization (Hartman et al., 2016).
Lo and Ramayah (2011) studied the thematic area of mentoring and job satisfaction in
Malaysian SMEs. They sought to establish the impact of mentoring on employee job
satisfaction. They conducted a survey among employees from small and medium
enterprises in Malaysia. They sent out a total of 200 questionnaires and 158 Malaysian
executives participated in the survey. Data was analyzed and the results revealed that
there was a positive relationship between career mentoring and all dimensions of job
satisfaction; for example, co-workers, the job itself, promotion opportunities and
supervisors. Conversely, no significant relationship was found between psychosocial
mentoring and three aspects of employee job satisfaction which were co-workers, job
itself and promotion. Other scholars agree that managers should improve their career
development plans and the mentoring process in order to increase job satisfaction and
organizational commitment (Weng, Huang, Tsai, Chang, & Lin, 2010).
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Cetin et al. (2013) sought to investigate the impact of mentoring on job satisfaction and
organizational commitment among accounting-finance academics employed in Turkey.
The researchers conducted a survey among the scholars and considered mentoring to
cover aspects of career development, role modeling and social support. Questionnaires
were distributed to the faculty and a response of 90 questionnaires was obtained and
analyzed using SPSS version 13. Other tests like factor analysis and regression analysis
were also conducted. The results of data analysis revealed that social support and
professional commitment were positively related to job satisfaction and that they were
both aspects of mentoring. However, career development and role modeling were found
not to have a relationship with job satisfaction. This was attributed to the fact that career
development and role modeling were a factor of age and had an impact on affective
commitment.
Shujaat, Sana, Aftab and Ahmed (2013) in the study on the impact of career development
on employee satisfaction in the private banking sector in India sought to determine the
impact of aspects of career development on job satisfaction. A survey was conducted
using structured questionnaires that were administered through both soft copy and hard
copies to 500 respondents in India. The sampling procedure used was the convenience
sampling method. There were 395 responses received and data was analyzed using SPSS
and analytical tests like the Chi-square were conducted. The findings of the study
revealed that mentoring and counseling programs have a positive impact on employee job
satisfaction and that this was one important driver of job satisfaction among the
employees in the private banking sector in India.
Kim (2011) sought to establish the effect of mentoring in the public sector in Georgia and
Illinois. Data from 1220 public and non-profit sector managers was collected and a few
tests like regression were conducted in the analysis of the data. The results of the study
found a significant and positive relationship between intrinsic motivation and job
satisfaction. Whereas trust was positively related to job satisfaction, economic benefits
were not. Mentoring was found to have a significant mediating effect on the effect of
intrinsic and extrinsic motivation factors on job satisfaction. Thus, mentoring was not
only found to help employees develop their careers and to build better coworker
relationships but also to have a significant effect on job motivation and job satisfaction.
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Gosh and Reio (2013) conducted a research on the career benefits associated with
mentoring for mentors. Mentoring is an extensively studied area and is linked with
mentee career development and growth; additionally, mentors can also draw significant
benefits from mentoring. An analysis was conducted on the provision of career,
psychosocial and role modeling mentoring support and how it was linked with outcomes
like job satisfaction, commitment, turnover intentions, performance and success on the
job. Results of the study revealed that mentors vis-à-vis mentees were more satisfied with
their jobs and committed to the organization. These results are in support of the
mentoring theory where mentoring is a reciprocal and collaborative agenda and not only
beneficial to the mentees but also to the mentors who are noted to experience increased
job satisfaction.
Horner (2017) carried out a study to establish if mentoring based on Watson’s caring
model positively influences nurses’ job satisfaction. The study used a mixed methods
design and data was collected using an online survey which was composed of closed and
open-ended questions. There was a response rate of 54% which represented 37 of 69
respondents. All the participants reported that mentor experience or relationship
positively influenced job satisfaction. Additionally, job satisfaction was associated with
reduced turnover of staff and improved patient retention. Salami (2010) studied the
relationships of mentoring and satisfaction with mentoring and work attitudes. The study
was conducted among nurses in Nigeria and data was collected using questionnaires from
a sample size of 470 nurses. One of the findings of the study was that employee
satisfaction with the mentoring experience significantly predicted the work attitudes
which in turn determined job satisfaction, organizational commitment and job
involvement.
Lo et al. (2013) conducted a study on mentoring and job satisfaction in Malaysia in small
medium enterprises. One of the aims of the study was to test whether mentoring
positively influences employees’ job satisfaction. The study was conducted among 21
small and medium enterprises with 200 questionnaires being sent out to middle and lower
level management. The study used a 7-point Likert scale to gauge each of the key
variables in the study. In measuring job satisfaction, the variables that were used were
promotion, supervisor and co-worker relationship and the dimensions of the job itself.
The study found that career mentoring had a significant and a positive relationship with
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the job satisfaction dimensions of the job itself, co-workers, supervisors and promotions.
Additionally, employees who are mentored learn better than those who are not mentored
in their jobs. Xu and Payne (2014) contribute to the field of mentoring and job
satisfaction stating that the value of mentors, mentorship quality and satisfaction with
mentoring all predict job satisfaction, affective commitment and turnover intentions.
2.4.2.3 Support
Support refers to a leader’s sensitivity to the needs of the followers needs which may be
organizational or personal. Sensitivity to the needs of the employees has a direct influence
on the employees’ commitment and performance. A leader demonstrates individualized
consideration when providing a wide support for the efforts of the followers (Anderson &
Sun, 2015). They went on to note that the improvement of individualized consideration
around supportive and developmental leadership is likely to have a transformational
impact (Long et al., 2014). Social support also predicts job involvement and job
satisfaction because it acts as a buffer to stressors that arise from the work or interaction
with colleagues (Salami, 2010).
Belias and Koustelios (2014) stated that individualized consideration fosters the provision
of support, encouragement, coaching, feedback mechanisms and delegation, which play a
big role in the follower’s personal development. It is viewed as personal attention of the
leaders to the needs of the followers which makes the followers all feel valued. It also
helps to ensure equitable treatment to the followers avoiding favoritism and enhancing
individuality as opposed to a group treatment. Miao and Kim (2010) investigated the
influence of perceived organizational support and job satisfaction as positive correlations
of employee performance in China among 130 employees and their 34 immediate
supervisors. The study determined four dimensions of organizational citizenship
behavior. Data was analyzed and the results revealed that organizational citizenship
behavior increases with more favorable perception of organizational support and job
satisfaction.
Long et al. (2014) conducted a study on the impact of transformational leadership style on
job satisfaction and found that only the aspect of individualized consideration and more
so the support a leader offers to his employees had a significant impact on job
satisfaction. A sample size of 378 employees was obtained for the study. The research
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adopted a descriptive research design and there was a response rate of about 67%. The
research instrument used the Multifactor Leadership Questionnaire (MLQ) to measure the
transformational leadership style. The results of the study found that leaders should coach
followers, pay attention to their follower’s needs and provide a supportive environment
for the followers to develop their talents and this will boost their job satisfaction.
Cheung and Wong (2011) carried out a study on transformational leadership, leader
support and employee creativity seeking to examine the moderating role played by
leaders’ tasks and relations support in the relationship between transformational
leadership and followers level of creativity. They conducted their research among 182
supervisor-subordinate dyads. Their findings revealed that leader relations support had a
direct impact on an employee’s creativity. Thus, continuous concern for employees’
socio-emotional needs catalyze the generation of more creative ideas which impact
performance and satisfaction. A supportive management style which is evidenced by open
communication, respect and recognition enhances employees’ job satisfaction. The study
also revealed that job satisfaction has a direct correlation with management support
among other factors like recognition and job security (Mosadeghrad & Ferdosi, 2013).
Emmanuel and Hassan (2015) carried out a study to establish the effect of
transformational leadership on job satisfaction in four and five-star hotels in Kuala
Lumpur. They sought to examine through one of their research objective; how
individualized consideration affects employee job satisfaction. A total of 130
questionnaires were distributed and a response rate of 95% being 123 questionnaires was
obtained. The results of the study revealed a positive correlation between individualized
consideration, support and job satisfaction backed by statistical significance of the
relationship. Arzi and Farahbod (2014) in their study on the impact of leadership on job
satisfaction in Iranian hotels found that supportive leadership had a significant impact on
job satisfaction but recognition did not affect job satisfaction which is contrary to the
findings of many studies.
Kula and Guler (2014) sought to establish the influence of supervisor support on job
satisfaction levels in the Turkish National Police Officers. The theory underpinning the
study was Herzberg’s Two-Factor theory. The respondents were 216 employees of the
police service. Data was analyzed using descriptive statistics, confirmatory factor analysis
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(CFA) and structural equation modeling (SEM). The results of the study revealed that
supervisor support had a statistically significant effect on job satisfaction; the more the
employees perceived their supervisors as supportive, the higher their job satisfaction
levels were. This study underscores the fact that job satisfaction emanates from what the
employee receives from the job and discredits remarks linking demographic factors to job
satisfaction.
Baloyi, Waveren and Chan (2014) carried out a study on the role of supervisor support in
predicting employee job satisfaction from their perception of the performance
management system. One of the hypotheses of the study was supervisor support increases
employee’s job satisfaction. The study stated that the support from supervisors may be
important in helping employees to understand the performance management system and
that support could mediate the relationship between the performance management system
and job satisfaction. The study revealed that when employees perceive a good
performance management system, they attribute the good experience to the support from
the supervisor and this leads them to feeling satisfied with their jobs. In support,
supervisors not only give feedback about performance of their employees but also provide
encouragement, more information about the expectations and how to achieve what is
required. In the process, they also recognize, praise and celebrate successes.
Hwang et al. (2005) carried out a study that sought to find out the extent to which
leadership charisma and vision could be discriminated by followers and how they
influenced follower commitment and performance across three countries Singapore, New
Zealand and India. They discovered a relationship across the three countries of their study
that revealed the need for sensitivity to followers needs in influencing their commitment,
satisfaction and performance. According to Mustafa and Lines (2014), supportive
leadership has a positive impact on job satisfaction which reaffirms that a leader’s
characteristics and behaviors play an important role in boosting job satisfaction which
ultimately leads to positive outcomes in the workplace.
2.4.3 Influence of Inspirational Motivation on Job Satisfaction
This section discusses the influence of inspirational motivation on job satisfaction.
Inspirational motivation is broken down into three constructs which are communication,
team work and motivation.
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2.4.3.1 Communication
Communication refers to the transfer of information from one person to another. In an
organization, this refers to the signs, signals, and interactions between the employees.
Many organizations spend considerable resources in the deployment of an effective
communication system because it is a must have for the organization to achieve its
objectives (Farahbod, Salimi & Dorostkar, 2013). However, important as it is,
communication is an elusive organizational characteristic despite its importance in the
organization. A good communication climate means that communication must be
effective both from management to employees and from employees to management, and
there must be an element of trustworthiness for it to be effective. Studies have linked a
good communication climate to organizational identification, commitment and job
satisfaction; thus, an employee’s perception of the supervisor’s communication style,
credibility and the overall organizational communication climate influences the amount of
satisfaction the employee receives from the job (Paksoy et al., 2017).
D. Ilozor, B. Ilozor and Carr (2011) carried out a study in the field of telecommuting
which sought to examine the relationship between several management communication
strategies and the job satisfaction of telecommuters. A sample of 43 telecommuters
mostly from IBM Australia was surveyed. Results were analyzed using Pearson’s
correlation. A number of aspects of the strategies were found to have a significant
influence on the job satisfaction of the telecommuters. Examples of the strategies were
communicating on job responsibilities, goals, deadlines and expectations, communicating
freely and regularly, providing appropriate equipment, training, review of work and
salary. The results revealed that there is need for effective communication as
communication ultimately affects job satisfaction. Another study revealed that
communication whether horizontal or vertical, formal or informal is an important factor
that influences the organization’s success. The study concluded that job satisfaction is
strongly impacted by communication (Epure, Ionescu & Nancu, 2013).
According to SHRM (2012), in their study on job satisfaction and engagement, 57% of
the employees ranked communication as one of the top five contributors of job
satisfaction. Communication between both employees and management is therefore very
important. Among the older employees of between 11 to15 years, communication was the
most important contributor to job satisfaction and engagement. It is very important that
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senior management and managers communicate effectively on the organizations goals,
policies and the vision. Effective communication helps to engage employees, provide
direction and foster trust and respect. In effect, communication should be encouraged
both from senior management to employees and vise versa. This factor was considered
very important by employees in middle management and non-management employees
than did the professional non-management employees. Ramos (2014) underscores the
importance of communication and notes that it is one of the greatest factors influencing
satisfaction.
A. Monga, Verma and O. Monga (2015) conducted a study on job satisfaction among
employees of ICICI bank in India. The primary focus of the study was to examine the
level of job satisfaction of the employees. The research was conducted in six branches of
the bank using questionnaires that had responses rated using the five-point Likert scale.
The results obtained revealed the importance of communication as one of the key factors
determining job satisfaction at the branches of ICICI bank that were studied. This study
focused on the hygiene factors of the Herzberg Two Factor theory and had many aspects
like pay that also contributed to the job satisfaction of employees at ICICI bank branches
that were studies.
Kakakhel, Khan, Gul and Jehangir (2015) carried out a study on the impact of
organizational communication on organizational commitment and job satisfaction in
Pakistan. Data was collected from a sample of 300 employees working in different
organizations using a questionnaire that had closed ended questions. Data was analyzed
and the findings of the study revealed that organizational communication had a positive
effect on job satisfaction. The study goes on to state that job satisfaction increases when
employees receive proper communication about their roles, responsibilities and
performance expectations. Thus, the supervisor’s role of communication cannot be
overemphasized because of the significant impact it has on job satisfaction.
Darijani, Soltani and Pourroostaei (2014) carried out a study on the impact of the
effectiveness of organizational communication on job satisfaction of employees of a
telecommunication company. Simple random sampling technique was used to select a
sample of 248 respondents and data collection was done using questionnaires. After data
analysis, the results revealed that the effectiveness of organizational communication had a
significant impact on job satisfaction. The study recommended that the directors of the
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company should focus more on communication in order to improve on job satisfaction of
the workers. Paksoy et al. (2017) found that the impact of managerial communication
skills on job satisfaction was significant thereby raising the need for management to
communicate effectively since this is one of the factors that affect job satisfaction levels.
The study stated that effective communication is important and any gaps should be
addressed through training and re-training of the managerial staff in order to build and
sustain communication competence.
Shonubi et al. (2016) conducted a study to establish the psychological influence of
organizational communication on employee job satisfaction. The study found that
communication plays a vital role in organizations and contributes to creating a
motivational organizational climate. Winska (2010) found that job satisfaction was to a
significant extent predicted and moderated by the communication of the superior. The
study went on to note that aspects like appreciation from the boss, feedback from the
supervisors and downward communication were elements that predicted and moderated
job satisfaction. The key elements they stated as predictors of job satisfaction were
supervisor skills and behavior, leader’s oral communication, perception of the supervisory
communication competence, leader effectiveness and the communication climate.
A. Akpinar, Torun, Okur and O. Akpinar (2013) in their study found that job satisfaction
is a result of organizational commitment and not organizational communication. They
conducted a study to establish the effect of organizational communication and job
satisfaction on organizational commitment in small businesses. The study was conducted
among 118 small businesses in Turkey and data was analyzed using Pearson correlation
and multiple regression analysis. The results revealed a positive relationship between
employee’s perception of organizational communication and organizational commitment.
However, unlike many studies, the results indicate that communication to a greater extent
predicts organizational commitment and not job satisfaction. Effective communication
leads to increased trust levels and attachment to the organization. The study was however
limited to only small businesses and thus the results cannot be generalized which
necessitates a more comprehensive study.
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2.4.3.2 Teamwork
A team comprises of two or more people who interact and coordinate their work to
achieve a common goal. It then follows that work teams are people who come together to
work on a common goal and leverage on their positive synergies and complementary
skills. A team is one of the most ideal approaches of ensuring information sharing,
effective coordination and exchange of material necessary for successful task
accomplishment. It has been found that good team work results in good attitudes for
example self-management skills, increased commitment, responsibility and turns the
work environment into a fun place (Musriha, 2013). Teams have become the primary unit
in organizations in the contemporary business world because they are more effective.
Monga et al. (2015) who studied job satisfaction of employees of ICICI bank found that
among other factors like communication, attitudes of supervisors and job security, team
work had a significant role in determining employee job satisfaction.
Halepota and Shah (2010) carried out an empirical investigation of organizational
antecedents on employee job satisfaction in a developing country. They sought to
establish in one of their hypothesis whether team work affects job satisfaction. The study
adopted a positivist research philosophy and research was qualitative. The sample
comprised of 200 full time medical practitioners who were randomly selected. The
findings of the study revealed that team spirit among employees had a positive and
significant impact on employee’s job satisfaction. Polychroniou (2009) carried out a
research to establish the relationship between emotional intelligence and transformational
leadership of supervisors in Greek organizations. They interviewed 267 managers
working at various units and in different levels. Data was analyzed and the results
revealed that organizations which adopt their prescriptions are likely to empower
teamwork and boost employee satisfaction which will ultimately lead to superior
performance.
Hanaysha and Tahir (2015) examined among other factors the effect of team work on job
satisfaction in Malaysia public universities. They collected data from 22 employees and
the data was then analyzed using structural equation modeling. The findings revealed that
teamwork had a positive and significant effect on job satisfaction. Rizwan et al. (2012)
carried out an empirical study on employee job satisfaction aimed at establishing the
crucial problems faced by employees and finding ways to enhance employee loyalty. A
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survey was conducted among 200 employees located in Punjab Pakistan. A model
incorporating theoretical considerations and employee job satisfaction constructs was
used for the study. Findings revealed that there was a strong and positive relationship
between team work and job satisfaction.
Shujaat, Manzoor and Syed (2014) conducted a research to establish the impact of team
work on employee job satisfaction. Their study was informed by the importance of team
work in achieving organizational goals. They conducted a survey among 384 employees
from various organizations using questionnaires and applied regression analysis to
establish the significance of the linear relationship between team work and job
satisfaction. Results of the study revealed that team work had a significant impact on job
satisfaction. This shows that it is important for organizational leaders to build a team
work culture, build team skills and hold it in high regard because of its significant effect
on job satisfaction and achievement of organizational goals.
Rana (2015) sought to determine the job satisfaction factors affecting employees in the
Bangladesh banking sector. A point of focus was to determine the impact of the human
resource management practices like team work, job autonomy and leadership behavior on
job satisfaction. A sample size of 450 employees working in different bank branches in
Bangladesh were selected for the study and data was collected through questionnaires
which employed the 5-point Likert scale. There was a response of 65% was received
representing 295 questionnaires which were processed and data analyzed through SPSS.
The results of the study revealed that there was a significant and positive relationship
between human resource management practices like team work, job autonomy and
leadership behavior on job satisfaction; however, team work was the most important
factor affecting job satisfaction.
Irfan and Lodhi (2015) conducted a study on the impact of teamwork on employee
motivation in the banking sector of Pakistan. Among the hypotheses tested was whether
teamwork at the banking sector had an impact on job security and job satisfaction of the
employees. The findings of correlation analysis tests revealed that there was a positive
correlation between teamwork and motivation. Additionally, the individuals working in a
team were more satisfied with their jobs and considered themselves as an asset to the
organization. Teamwork is an important attribute through which people are able to
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achieve more and is an important tool for organizational success especially in today’s
competitive world.
2.4.3.3 Motivation
The word motivation refers to the force that constantly induces someone to move or to
perform in a certain desired way. It is a psychological process that yields stimulation,
direction and persistence in behavior towards a desired cause. A number of factors could
be considered as motivational but this varies depending on how they are perceived by the
employees. A good example is rewards, incentives and recognition which could have
varying effects on the receiver. Research states that in some instances, employees’ job
satisfaction is influenced by the rewards or motivation they receive from their job.
Workers who are motivated tend to give their best efforts and work hard at their job
because they feel fulfilled (Jehanzeb, M. Rasheed, A. Rasheed & Aamir, 2012).
Additionally, there are the intrinsic motivators and extrinsic motivators and it was found
that there is a significant and positive correlation between intrinsic motivators and job
satisfaction in banks in India (Chatterjee & Chattopadhyay, 2015).
Panagiotakopoulos (2014) conducted a study which explored the motivational techniques
used by 30 CEOs in the context of an advancing economy and evaluated the impact of the
motivational tools on staff performance. The study collected data from 113 workers and
30 CEOs. The study revealed that 87% of the CEOs argued that employee motivation
needs to be around the threat of punishment; thus, they direct behavior with threats of
punishment and replacement. Four leaders opined that involvement in decision making,
recognition of employee contribution, team work and learning were appropriate tools to
boost motivation. It was evident that the benefits that accrue to the organization from use
of inspirational motivation were outnumbered by benefits of using fear motivation. The
four leaders emphasized that most employees work with enthusiasm, had job satisfaction
and increased productivity. The employees confirmed that their relations with the firm
were harmonious, their jobs were interesting and that trust existed. This raised their
morale, job satisfaction and led to a decline in mistakes.
Wambui, Maru and Cheruiyot (2017) examined the link between leadership personality
traits and job satisfaction among employees in the media industry in Kenya through
exploratory research. Regression analysis revealed that there was a positive and
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significant relationship between leader extraversion, leader agreeableness, leader
conscientiousness, leader openness, leader emotional stability and employee job
satisfaction. The findings are timely since organizational survival in the current dynamic
environment calls for leadership qualities which will enhance employee motivation.
Hanaysha et al. (2012) conducted a study in Malaysia among administrative and clerical
staff involved in graduate and postgraduate affairs in three universities. They sought to
establish if there was a positive relationship between individualized consideration and job
satisfaction. The research was conducted among 320 employees through an 18-item scale
questionnaire from the MLQ and a response rate of 31.5% was obtained. The findings
revealed that individualized consideration was negatively related to job satisfaction which
goes against most research findings and thus necessitates further research to validate the
findings. It is however attributed to the fact that perhaps employees could not meet their
leaders due to their busy schedules. However, the study found that intellectual stimulation
was positively correlated to job satisfaction because leaders foster inspiration and which
in turn creates excitement and yields renewed efforts from the employees in pursuit of the
organizational goals.
According to Bass (1985), transformational leaders motivate the followers and raise their
performance to higher levels through inspiration. This is done by use of an appealing
vision, symbols and images aimed at enhancing appropriate behaviors among the
followers (Belias & Koustelios, 2014). It is also achieved when a leader communicates
the vision with confidence which in turn raises optimism. Transformational leadership
goes beyond transactions and aims to improve the follower’s achievements through an
influence of their needs and values which yield higher levels of performance, effort and
satisfaction. Transformational leadership can thus be viewed as an extension of
transactional behavior because transformational leaders motivate their followers to
achieve more than they ought to achieve by addressing and modifying their values and
self-esteem. This yields an inspiration to go beyond the basic call of duty to voluntarily
and willingly doing more (Felfe & Schyns, 2004). According to Groves (2006), a leader’s
ability to articulate a powerful and a compelling vision is very important because it acts
as a source of motivation to the followers which ultimately leads to satisfaction in some
employees.
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Transformational leadership is a leadership style that employers can use to motivate
employees by stirring their interests in the organization thus enabling them to look
beyond their personal interests and placing focus on the organizations interest (Stone et
al., 2004). Additionally, according to Lussier and Achua (2013), transformational
leadership helps in a shift from personal to collective interests and through inspiration and
motivation, the followers are able to follow the leader as a result of enhanced trust and
confidence. According to Indermun and Bayat (2013), rewards and benefits are extrinsic
needs to the employee and they are important in job satisfaction. Good rewards are
intended to attract and retain suitable employees in the organization. The promise of
rewards and benefits encourages and motivates employees to perform in order to ensure
they reap the rewards and the benefits; hence they are a source of motivation. In modern
society, there is a shift to performance related pay which unfortunately assumes that pay
alone satisfies the workers yet this notion has been discredited. This is because a worker
with a good pay but no intrinsic rewards will probably not be satisfied and will look for
satisfaction even if it means leaving the organization.
The SHRM (2012) survey among 600 employees in the US on job satisfaction and
engagement revealed that 6 out of every 10 employees ranked compensation as the first
factor affecting their job satisfaction. Compensation has remained on the list of the top
five job satisfaction factors consistently for many years. It is an important strategy for
attracting and retaining talent in the organizations. However, age affects the perception
because it was ranked as the most important by employees of three to five years working
tenure and showing that as one grows in age, other factors affecting job satisfaction come
into play. Benefits also ranked highly and came in as the sixth factor affecting job
satisfaction. It was found to be a critical factor in large organizations. Benefits and pay
are to some people very important and greatest source of their motivation and job
satisfaction.
2.4.4 Influence of Intellectual Stimulation on Job Satisfaction
This section discusses the influence of intellectual stimulation on job satisfaction.
Intellectual stimulation is broken down into three constructs which are knowledge
sharing, creativity and risk taking.
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2.4.4.1 Knowledge Sharing
Knowledge sharing falls under the umbrella of knowledge management in an
organization. Knowledge management consists of processes such as knowledge creation,
sharing and transfer together with the processes and capabilities which help to support the
advancement of knowledge. Knowledge sharing is fundamental for managing tacit
knowledge hence organizations should encourage regular communication and the creation
of shared learning experiences by encouraging a knowledge sharing culture (Kianto,
Vanhala & Heilmann, 2016). A knowledge sharing culture paves way for communication
and information exchange, problem resolution, team work and decision making
(Trivellas, Akrivouli, Tsifora & Tsoutsa, 2015).
Raisi and Forutan (2017) conducted a study of the relationship between a knowledge
sharing culture and job satisfaction in the context of Bank Sepah Branches in shriraz,
Iran. They interviewed 392 employees from 53 Bank Sepah branches in Shiraz. The study
obtained a response rate of 159 employees and the data was collected using
questionnaires based on a job satisfaction. Ratings were based on a 5-point Likert scale.
Data was analyzed using SPSS and the critical test conducted was the Pearson Correlation
coefficient. The results revealed that there was a positive and significant relationship
between a knowledge sharing culture and components of job satisfaction.
Kianto et al. (2016) sought to establish whether knowledge management could be used to
nurture job satisfaction. They also examined how knowledge management could be used
to increase individual employee job satisfaction. One of the hypotheses of the study was
knowledge sharing will be positively associated with job satisfaction. Research data was
sought from 824 respondents who worked in a municipal organization in Finland. Data
was analyzed using Structural Equation Modeling and the results revealed that knowledge
sharing was a key component of the knowledge management process which was found to
have a correlation with job satisfaction. The overall study concluded that having
knowledge management processes in place was linked to high job satisfaction.
Trivellas et al. (2015) noted that globalization, competition and financial crisis have
brought about the need to have a knowledge driven economy. In a study on the impact of
knowledge sharing on job satisfaction in accounting firms, the researchers sought to
establish if knowledge sharing exerted a significant positive impact on individual job
satisfaction. In the research, 84 accounting officers were interviewed using questionnaires
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and data was analyzed using principal component analysis and regression analysis. The
results revealed that there was a positive and significant relationship between a
knowledge sharing and job satisfaction. Tong, Tak and Wong (2014) sought to establish
the impact of knowledge sharing on the relationship between organizational culture and
job satisfaction among ICT practitioners in Hong Kong. They found that knowledge
sharing had a significant mediating effect between organization culture and job
satisfaction.
Masa’deh (2016) carried out a study to establish the role of knowledge management
infrastructure in enhancing job satisfaction in five-star hotels in Jordan. A total of 216
respondents were sampled for this study and data was collected using questionnaires. The
hypotheses were tested using regression analysis. The results revealed that there was a
positive and significant impact of the knowledge management infrastructure on job
satisfaction. Saleh and Khoualdi (2015) in a similar study in Saudi public universities also
found that there was a positive and significant relationship between the knowledge
management structures and job satisfaction.
Malik and Kanwal (2018) sought to establish the impact of organizational knowledge
sharing practices on employee job satisfaction. The study had learning commitment and
adaptability as the mediating roles. The study was conducted among the service sector
organizations in Pakistan. The sample size consisted of 435 employees from banks,
insurance and telecommunications companies. The findings of regression analysis
revealed that the organization’s support for knowledge sharing promotes learning,
commitment and adaptability which ground job satisfaction. Mogotsi, Boon and Fletcher
(2011) modeled the relationships between knowledge sharing, organizational citizenship
behaviour, job satisfaction and organizational commitment among school teachers in
Botswana. However, the results revealed that both job satisfaction and organizational
commitment were not related to knowledge sharing.
Jadidi, Ehsanifar and Moshtaghi (2013) carried out a study which sought to establish the
effect of knowledge management on job satisfaction in the Iranian texture industry. The
study used questionnaires to collect data from 230 employees. Data was analyzed using
structural equation modeling to test the hypotheses. The results of the study revealed that
organizational learning and organizational improvement positively influenced job
satisfaction of the Iranian texture workers.
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2.4.4.2 Creativity
Cheung and Wong (2011) refer to creativity as the generation of new and novel ideas or
new useful ideas in the lines of products, services, processes or procedures. It enables
employees to utilize their diverse skills, abilities, knowledge and experience to come up
with the new ideas that aid decision making, problem solving and effective task
management (Mohammadi & Azizmalayeri, 2016). It can be a task in a job or it may
happen outside the scope of work. In their study on transformational leadership, leader
support and employee creativity, the study sought to examine the moderating role played
by leader’s tasks and relations support in the relationship between transformational
leadership and follower’s level of creativity. They sampled 182 supervisor-subordinate
relations from a hotel, restaurant, bookstore and a bank. Their findings of the study
revealed that there was a positive relationship between transformational leadership and
the follower’s creativity and it is stronger when there is a high degree of leader’s tasks
and relations support (Cheung & Wong, 2011).
Mittal and Dhar (2015) in their study on transformational leadership and employee
creativity sought to establish the effect of transformational leadership on employee
creativity. The study was conducted among 348 manager-employee dyads from the Indian
IT small medium enterprises professionals. The findings revealed that transformational
leadership has a positive significant effect on employee creativity and went on to suggest
that transformational leadership does indeed foster employee creativity which leads to a
creative work environment. Creativity is the key to competitive advantage in the growing
area of IT. It leads, provokes and allows employees to think and front new ideas or
solutions thereby making them feel valued and ultimately yielding job satisfaction.
Carine et al. (2015) carried out a study on the determinants of employee creativity and
project performance in Rwanda. Data was collected from a sample of 90 project members
and analyzed. The findings of the study revealed that creativity was a fundamental source
of competitive advantage and should be a focus for organizations that wish to
differentiate themselves. Additionally, job satisfaction positively and significantly
influenced the creativity of employees.
Cheung and Wong (2011) examined the link between transformational leadership and
employee creativity in Hong Kong. Primary data was collected using questionnaires
among respondents who were drawn from strata that included; restaurants, banks, hotel,
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retail store and travel agents. Data was analyzed using regression analyses. The results of
the study revealed a positive and significant relationship between transformational
leadership and employee creativity which in turn boosts employee job satisfaction.
Although the study contributed to the empirical link between transformational leadership
and employee creativity, a sample size of 182 was too small considering it was stratified
amongst the different groups. However, there was need for leadership to create an
environment for creativity amongst employees.
Yee, Pink and Sern (2014) conducted a study on the effect of a psychological climate for
creativity on job satisfaction and work performance. They did a cross sectional study and
sampled 118 electrical engineers working in Malaysia. Data was collected using
questionnaires which were distributed by means of the snowball technique via electronic
mail. The results of the study revealed that a good working environment is a key factor in
creating job satisfaction. Additionally, a creative climate is a key predictor of job
satisfaction and work performance among electrical engineers. It is an antecedent for
innovation and change which also affects the outcomes of the employees. In this regard,
leaders need to create a culture and an environment that promotes creativity in their
organizations and eliminate organizational factors that bar creativity since it is a predictor
of job satisfaction in organizations.
Abraiz, Tabassum, Raja and Jawad (2012) carried out a study on the empowerment
effects and employee job satisfaction in Pakistan. The dimensions of empowerment in the
study were autonomy, responsibility, information and creativity. The context of the study
was the service sector which involved hotels, hospitals and the education sector with 600
respondents. Data was analyzed and the results revealed a positive relationship between
creativity and job satisfaction. The study stated that there was a strong relationship
between creativity and job satisfaction than the other dimensions. Valentine, Godkin,
Fleischman & Kidwell (2011) conducted a study to establish the degree to which
perceived corporate values work with group creativity to influence job satisfaction and
turnover intention. Information was collected from 781 healthcare and administrative
employees and 127 sales and marketing employees. The results revealed that group
creativity and ethical values were positively related and that both were associated with
increased job satisfaction.
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Raju (2017) conducted a study on the relationship between teacher creativity and job
satisfaction among degree holders in India. One of the objectives of the study was to
establish the impact of creativity on job satisfaction. Data was collected from 146
lecturers using questionnaires as the data collection instruments. The hypotheses of the
study were tested and the results revealed a positive and significant relationship between
the teacher’s creativity and teacher job satisfaction. Dallal, Ahmadi and Barzegar (2013)
conducted a study on the relationship between creativity and job satisfaction in Shiraz
hand craft employees. A sample size of 89 employees was selected for the study and
questionnaires used to collect data. Results of the study revealed that the higher the
creativity and innovation rates, the higher the job satisfaction was. Therefore, the study
concluded that creativity significantly predicted job satisfaction.
2.4.4.3 Risk Taking
Hosseini and Shahmandi (2014) examined the effects of creativity and innovation, self-
control and risk taking on job satisfaction of staff in a social security organization in Iran
through a descriptive research. They stated that risk tolerance in the organization was
important as opposed to stressing rules with no risk taking. The sample size was
comprised of 150 respondents. The findings of the research revealed that the three
elements of creativity and innovation, self-control and risk taking were related to job
satisfaction. Specific to risk tolerance, there was a strong and significant relationship with
a correlation coefficient of 53 percent to job satisfaction.
Habib, Aslam, Hussain, Yasmeen and Ibrahim (2014) carried out a study dubbed the
impact of organizational culture on job satisfaction, employee commitment and turnover
intention. They broke down organization culture into a few constructs one among them
innovation and risk taking. The study was carried out among 235 bank employees in
Pakistan and data was collected through questionnaires. Data was analyzed and the results
revealed that organization culture, specifically, innovation and risk taking highly
influenced employee commitment, job satisfaction and retention.
Abbaspour and Noghreh (2015) examined the relationship between organizational culture
and job satisfaction of Tourism bank employees in Iran. Among the components of
organizational culture was risk taking and its relationship with job satisfaction was
measured. The study had a sample size of 196 employees which was arrived at through
stratified random sampling technique. Data was collected using questionnaires. The
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results revealed that there was a relationship between organizational culture factors like
risk taking and job satisfaction. Specifically, there was a relationship between risk-taking
which was not significant statistically in the level of job satisfaction.
Shah, Memon and Laghari (2011) studied risk as a variable of organizational culture in
their study on the impact of organizational culture on employee job satisfaction among
faculty of public universities of Pakistan. The research obtained a response rate of 72%
from a sample size of 300 respondents. The Pearson correlation coefficient was used to
analyze the data. The results of the study could not find a relationship of innovation and
risk taking with employee job satisfaction; thus, the increase or decrease of innovation or
risk taking was deemed not to affect the level of employee job satisfaction among the
faculty of public universities of Pakistan.
Lee (2016) in a study titled comparison of job satisfaction between nonprofit and public
employees had risk perception as one of the hypotheses. The results of the study found
that perception of top management’s risk taking is negatively associated with public
manager’s job satisfaction. However, it also did not explain nonprofit manager’s
likelihood of higher job satisfaction. Thus, for public employees, the perception of
organizational stability through minimal risks positively influenced their job satisfaction.
Qazi and Kaur (2017) conducted a study on the impact of culture on job satisfaction
among university faculty members. They sought to understand the correlation between
organizational culture and job satisfaction and come up with ways of improving the
culture and ultimately job satisfaction. The study was conducted among 368 faculty
members from both private and public universities. The results of the study revealed that
organizational culture was positively and significantly correlated with job satisfaction
with culture components like openness and risk-taking leading among the components
that yielded job satisfaction among the university faculty members.
2.4.5 Moderating Effect of Job Security on the Influence of Transformational
Leadership on Job Satisfaction
This section discusses the moderating effect of job security on the influence of
transformational leadership on job satisfaction. Job security is broken down into three
constructs which are anxiety, fairness and stress.
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2.4.5.1 Anxiety
The fear of the unknown or unpredictability of things in the work place causes anxiety
which is a factor that influences job satisfaction. It leads to uncertainty of the future and
this makes employees anxious and when in this situation they are unable to react to issues
appropriately. Research notes that anxiety is accompanied with negative attitudes in the
work place such as feelings of dissatisfaction, strained coworker relationships, reduced
organization commitment and heightened turnover intentions as the employees seek a
safer haven (Silla, Gracia, Manas & Peiro, 2010). Anxiety manifests itself through future
concerns and the inability to predict the future employment and career concerns, all which
have the possibility of affecting the employee’s judgments, perceptions, satisfaction and
productivity. A leader should endeavor to reassure his employees through effective and
accurate communication to dismay any anxieties for there to be job satisfaction (Kler,
Leeves & Shankar, 2015).
Ferguson, Frost and Hall (2012) sought to investigate predictors of anxiety, depression
and job satisfaction among teachers in North Ontario, Canada. They used data obtained
through self-report questionnaires and conducted factor analysis and multiple linear
regression to determine the sources of stress, stress symptoms and also to explore the
effects of stress, depression and anxiety on job satisfaction. The results revealed that
workload and student behavior were significant predictors of depression among the
teachers. However, anxiety, gender, grade level and position were not found to have
significant statistical influence on teacher job satisfaction. Thorsteinsson, Brown and
Richards (2014) examined the association between stress, organizational support and staff
health which incorporated anxiety, depression and fatigue together with work outcomes
like turnover intentions, organizational commitment and job satisfaction. They collected
data from 201 staff who were recruited through email and snowball sampling. The
findings of the study revealed that high work stress was associated with worse staff health
like anxiety, depression and fatigue all of which lead to negative work outcomes like low
job satisfaction, high turnover intentions and less organizational commitment.
Poursadeghiyan et al. (2016) carried out a study to establish the relationship between job
stress and anxiety, depression and anxiety among nurses in Iran. They obtained 250
nurses to participate in the research and data was collected using questionnaires. The
results showed that stress is a big contributor to anxiety but this was negatively associated
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with depression and job satisfaction. Zalewska (2011) agrees with the findings that job
anxiety is negatively correlated with the level of job satisfaction from their study carried
out among 240 employees. Nadinloyi, Sadeghi and Hajloo (2013) sought to examine the
relationship between job satisfaction and mental health. Their study was composed of 90
respondents and data was analyzed using multiple regression analysis. One of the findings
of the study based on their hypotheses revealed that there was a relatively weak but
significant correlation between job anxiety and job satisfaction meaning leaders need to
ensure there is no anxiety for job satisfaction to grow.
Allan, Dexter, Kinsey and Parker (2016) carried out a study on meaningful work and
mental health with job satisfaction as a moderator. They looked at depression, anxiety and
stress as variables of mental health which were some of the common problems modern
workers face. They noted that although having meaningful work is important and
facilitates personal growth, it is also important that work is satisfying and enjoyable in
order to improve outcomes. The sample was comprised of 212 working adults of various
age groups and data was analyzed using correlation and regression analysis. The study
found that having meaningful work was associated with better mental health which
translated to lower rates of depression, anxiety and stress. This also predicted lower
depression but did not significantly predict anxiety or stress. Thus, meaningful work
contributes to the level of job satisfaction.
According to Yaacob and Long (2015), anxiety that is not addressed ultimately leads to
stress. They sought to investigate the relationship between occupational stress and job
satisfaction among teachers through a cross sectional study. The study hypothesized
occupational stress as role ambiguity, role overload and work-family conflict. The sample
consisted of 386 teachers and data was collected using questionnaires. Thereafter, data
was analyzed and the results revealed that there was a significant relationship between
occupational stress and job satisfaction; therefore, organizational leaders should ensure
their employees have no anxiety and no work-related stress to ensure they feel satisfied
with their work. Higher job satisfaction levels yield better quality service which
culminates in better quality service.
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2.4.5.2 Fairness
Fairness refers to the appropriateness or rightfulness in the way outcomes should be
divided in the organization, the procedure used to determine the distribution and basically
how people are treated. It is an important element in human relations. Perceived fair
treatment influences employees to reciprocate by actively pursuing the organizational
objectives. It also elicits and sustains positive attitudes towards the organization. It acts as
an inducement and nudges employees to perform beyond expectations. Additionally, the
positive attitudes and behaviors that are elicited also include job satisfaction, enhanced
commitment and fewer turnover intentions (Silla et al., 2010). According to a study done
on why employees worry about their jobs, fairness was a construct presented in the study
because its absence led to insecurity (Keim, Pierce, Landis & Earnest, 2014).
Silla et al. (2010) studied job insecurity and employees’ attitudes with the moderating role
of fairness. Their study sought to examine the relationships between both job insecurity
and fairness and employees’ attitudes. They sampled 697 employees from a Spanish
public organization and conducted a cross sectional study based on self reported data. The
results of the study revealed that job insecurity was significantly and negatively
associated with organizational commitment and positively associated with turnover
intentions. However, the relationship between job insecurity and job satisfaction was not
significant.
Imran, Majeed and Ayub (2015) carried out a study on the relationship between
organizational justices, job security, and job satisfaction on organizational productivity in
Pakistan. Data was collected using questionnaires and was later analyzed using inferential
statistics. Both correlation and regression analysis revealed a positive and significant
relationship between job security and job satisfaction therefore making job security one of
the most important considerations leaders should offer their employees. Susanj and
Jakopec (2012) in their study exploring the role of justice perceptions and job satisfaction
concluded that employee job satisfaction depends on the perceived justice levels in the
organization.
Rai (2013) examined the impact of organizational justice on satisfaction, commitment and
turnover intentions with a view of establishing if fair treatment by organizations could
make a difference in the attitudes and behaviors of workers. He collected data from 511
employees from 10 health and rehabilitation centers and analyzed the data using Pearson
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correlation and hierarchical regression. The results of the study revealed that perceived
justice influenced job satisfaction, organizational commitment and the intention to leave.
If organizations want to effectively enhance job satisfaction while reducing turnover
intentions, they must pay attention to developing policies and procedures that encourage
fairness whilst adopting leadership styles that promote fairness.
Baah (2014) carried out a study on the organizational antecedents and perceptions of
fairness in policy implementation among employees in the banking sector of Ghana. The
study adopted a correlational research design and selected 100 participants randomly.
Data was collected using questionnaires and analyzed using the Pearson correlation and
ANOVA. The findings of the study revealed that job satisfaction and commitment were
positively and significantly related to the employees’ perception of fairness in the
implementation of policies. The study recommends implementation of policies that
enhance employee job satisfaction in the organization.
Kaur (2016) in a study on the psychological effect of organizational justice perceptions
on job satisfaction stated the importance of the perception of fairness in the organization.
The study noted that fairness results in favorable work outcomes like job satisfaction and
the lack of it thereof results in unfavorable work outcomes. A study of 218 employees
from the Indian Public Sector was carried out. Results from the Pearson correlation and
multiple regression revealed that distributive justice perceptions are likely to yield
positive organizational justice perceptions; therefore, organizational justice is a predictor
of job satisfaction. Paposa and Kumar (2015) also noted that there was a positive and
significant impact of performance measurement systems on job satisfaction.
Umair, Javaid, Amir and Luqman (2016) investigated the employee’s perception of
fairness in the performance appraisal system and the effect this had on job satisfaction of
the employees. They noted that the perception of fairness consisted of distributive justice,
procedural justice and interactional justice all of which were used as the independent
variables. Data was analyzed and the results of the study revealed that perceived fairness
in the appraisal system had an impact on job satisfaction among employees. Al-Ansi,
Rahardjo and Prasetya (2015) analyzed the impact of leadership style and pay fairness on
job satisfaction and organizational commitment. One of their research objectives was to
examine the relationship between pay fairness and job satisfaction. They had a
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convenience sample size of 120 employees. They concluded that pay fairness has a
positive and direct effect on job satisfaction but no effect on organizational commitment.
Yamazaki and Yoon (2012) studied fairness and job satisfaction of Japanese
multinationals in Asia with a focus on procedural justice and fairness. They focused on
HR practices of fairness where they sought to describe the processes that are used in
evaluating employee performance and promotion, by which employees can generally
judge how they are treated through how fair they perceive the process to be. Data was
collected and analyzed using various statistical tests. The results of the study revealed that
the perception of procedural and transparent justice had a significant impact on job
satisfaction in Asian multinational contexts of Japan, China, Hong Kong and Thailand.
Management therefore needs to review the processes to ensure there is a fair perception of
justice which will in turn enhance the satisfaction levels of the employees. However,
Khalifa and Truong (2010) conducted a study to establish the relationship between
employee perceptions of equity and job satisfaction in Egyptian private universities and
found a relationship where a motivator was involved and no relationship where a hygiene
factor was in consideration.
2.4.5.2 Stress
Riaz et al. (2016) sought to establish the impact of job stress on employee job satisfaction
in the nursing sector of DHQ Hospital of Okara. The study measured job stress under
workload, role conflict and physical environment and their impact on employee job
satisfaction. The sample size was composed on 100 nurses from the hospital and data was
collected using questionnaires. Data was analyzed using SPSS and different tests
including reliability, regression and correlation analysis were carried out. The results of
the study showed that there was a positive and very strong correlation between job stress
and employee job satisfaction. However, according to Agarwal (2015) who measured the
relationship of job stress and job satisfaction in the Indian IT Sector, there is no
relationship between job stress and job satisfaction.
Mansoor, Fida, Nasir and Ahmad (2011) carried out a study to determine the impact of
job stress on employee job satisfaction in the telecommunication sector of Pakistan. The
study had a sample size of 134 employees and job stress was measured under the
variables of conflict at work, workload and physical environment. Data was collected
using an instrument adapted from the Minnesota Satisfaction Questionnaire (MSQ). The
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results revealed that the people who had stressful jobs found their jobs less satisfying. The
findings are contradicted by a similar study in private colleges in Pakistan where the
results of the study reveal that stress is positively related to employee job satisfaction but
depending on the context (Ur Rehman et al., 2012).
Lin, Bahron and Boroh (2014) conducted a study on role stress and job satisfaction
among bank employees in Sabah, Malaysia. The study was inspired by many changes in
the industry’s competitive environment. One of the key variables under study was the
relationship of roles stress and job satisfaction. Role stress was measured using role
ambiguity and role conflict. The study had 163 respondents from 14 commercial banks
and data was collected using questionnaires. The hypotheses of the study were tested and
the results of the study showed that there was a significant relationship between role
stress and job satisfaction.
Khan, Ramzan and Butt (2013) sought to determine whether job satisfaction of Islamic
banks operational staff was determined through organizational climate, occupational
stress, age and gender. To this end, they interviewed 40 bank managers and officers from
five Islamic bank branches and had a response rate of 85%. The study was grounded on
exploratory research in which meetings, observations and interviews were conducted. The
results of the study revealed that organizational climate and occupational stress had a
significant impact on the level of job satisfaction. The study goes on to note that
occupational stress may not be avoided as it stems from both internal and external factors
such as political, economic and technological sources.
AbuRuz (2014) contends that there is a negative relationship between job stress and job
satisfaction among nurses in Jordan and Saudi. The cross-sectional study was carried out
among 150 nurses from 250 nurses from hospitals in both jurisdictions and the results
from both contexts were similar. Khamisa, Oldenburg, Peltzer and Ilic (2015) in a study
on nurses and job satisfaction found that the highest amount of variance in job satisfaction
was explained by job stress. Iqbal and Waseem (2012) sought to establish the impact of
job stress on job satisfaction among air traffic controllers from Pakistan. They found that
there was a negative relationship between job stress and job satisfaction and those who
had high job stress had low job satisfaction.
Ramos, Ales and Sierra (2014) carried out a study on role stress and work engagement as
antecedents of job satisfaction among Spanish workers and hypothesized that the role
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stress would negatively predict job satisfaction. The study was carried out among 435
Spanish workers from both public and private companies. Collection of data was done
through questionnaires which were administered by the researcher. The hypothesis was
tested using regression analysis having passed the preliminary tests to ensure that there
was no violation of the assumptions of regression. The results of the study revealed that
there was a negative relationship between role stress and job satisfaction. Hoboubi,
Choobineh, Ghanavati, Keshavarzi and Hosseini (2017) also found that job stress
influenced job satisfaction and workforce productivity in the Iranian petrochemical
industry.
2.5 Chapter Summary
This chapter has presented the theoretical review of the transformational leadership
theory, the conceptual framework for the study and an empirical review. Chapter three
presents the research methodology.
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CHAPTER THREE
3.0 RESEARCH METHODOLOGY
3.1 Introduction
This chapter presents the research methodology used in this study. The chapter discusses
the research philosophy of the study, the research design used, the target population and
sample population for the study. The data collection method, the research procedures and
the data analysis methods are also discussed in this chapter.
3.2 Research Philosophy
According to Saunders et al. (2016), a research philosophy is a belief in which data about
a phenomenon should be gathered, analyzed and used. The philosophy of a study serves
as a base for the research strategy. Examples of research philosophies are pragmatism,
positivism and constructivism. Pragmatism as a world view comes from actions,
situations and consequences as opposed to antecedent conditions and is not committed to
any one philosophy. It encourages the use of the approaches available to understand a
problem. It mainly underpins the use of mixed methods in research. It also suggests that
the most critical determinants of the research philosophy which a research adopts are the
research questions and objectives (Saunders & Lewis, 2018).
The positivism philosophical approach contends that reality is stable, can be observed and
described objectively. Positivism also holds a deterministic ideal where causes determine
effects and outcomes. It is mainly related to the observations and experiments which
guide the research process and help to identify and assess the causes that influence
outcomes. The main concern for a positivist research is to study observable and
measurable variables in controllable conditions and to also illustrate the reactions of the
variables to the treatment applied by the researcher. Therefore, the emphasis is on
predicting the outcomes of the research so that the variables can be controlled in future
(Saunders et al., 2016; Bryman & Bell, 2015).
Constructivism contends that individuals seek to understand the world and the
environment in which they live and work in. They go on to develop subjective meanings
of their encounters directed towards understanding certain phenomenon. It relies on the
individual’s or participant’s view of what is being studied (Creswell, 2014).
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Constructivism challenges the thought that items like organization and culture are
predetermined and confronts social issues as external realities (Saunders & Lewis, 2018).
Positivism research philosophy was adopted in this study. This is because the positivism
research philosophy relates to the philosophical standpoint of natural science and is
concerned with an observable social reality to produce law-like generalizations (Bryman
& Bell, 2015). Additionally, positivism yields unambiguous accurate knowledge and
allows for a causal explanation and prediction of the relationship between variables. The
researcher developed hypotheses on the basis of the existing theory of transformational
leadership. To test the hypotheses the study translated idealized influence, individualized
consideration, intellectual simulation and intellectual simulation into testable hypotheses
in measurable forms (Saunders et al., 2016).
3.3 Research Design
A research design is a plan or a structure of investigation which is conceived with the aim
of helping a researcher to obtain answers to research questions. It can also be referred to
as a plan to be followed for data collection, measurement and analysis (Cooper &
Schindler, 2014). A research design helps to integrate the different components of a study
in a coherent, logical and acceptable way which helps in ensuring the study effectively
addresses the research problem under review. Examples of research designs are
exploratory, descriptive and causal (Creswell, 2014). Exploratory research design tends to
have loose structures and is mostly useful when researchers lack a clear idea of the
problem. It also tends to be qualitative as opposed to quantitative and in many cases does
not provide conclusive evidence. It is ideal when the researcher has little information,
where the researcher knows little about the problem and is designed to discover new
relationships, patterns, themes and ideas. It is therefore useful where a researcher wishes
to clarify an understanding of a phenomenon (Hair, Money, Samuel & Page, 2007).
Causal research seeks to identify the cause and effect relationships among variables and
its main aim is to determine cause and effect. Causality is difficult to prove without
examination and therefore the studies are done through experiments and simulations. The
main aim is to try to explain relationships among interacting variables. For example, a
causal predictive study aims to determine an effect of one variable on another by
manipulating the former and holding the latter constant (Cooper & Schindler, 2014). It
helps to bring out the causes of the variable being predicted and answers questions like
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why. Causal research is mostly recommended in experiments and is also known as
experimental designs (Shajahan, 2009).
Descriptive research design aims to generate data that describes the characteristics of the
research item. The main aim of descriptive research design is to reveal an accurate profile
of the phenomenon under study (Shajahan, 2009). With the descriptive research design,
data collection is usually structured. Studies under descriptive are either cross sectional or
longitudinal studies (Hair et al., 2007). It also illustrates characteristics of a phenomenon
by answering questions like, when, who, where what and how. It seeks to determine the
frequency of occurrence and whether a relationship exists between two variables.
Descriptive research design consists of case study, survey, meta-analysis and correlation
(Sekaran & Bougie, 2016).
Case studies focus on gathering information regarding a specific object, event or activity,
for example a specific organization or business unit. It is an in-depth study of a bounded
entity. Survey is a way of collecting information from or about people to describe,
compare and explain their behavior. It involves setting objectives for data collection,
designing the study, preparing a survey instrument, administering it, managing the data
collection process, analyzing the data and reporting the results (Bryman & Bell, 2015;
Hair et al., 2007). Meta-analysis involves a quantitative analysis of data sets from
previous research projects. It is a process of amalgamating existing data sets, combining
them and analyzing them. The researcher does not guarantee validity of the data since
they were not involved in the research process of the existing data sets (Quinlan, 2011).
Correlation helps to predict relationships; for example, the relationship between an
independent and dependent variable can be examined using correlation. Correlation
examines the relationship between two or more variables and tries to determine whether
and to what degree a relationship exists between them. It is highly recommended where a
study is seeking to test the relationship of two variables because it provides a platform for
description of the relationships between variables (Cooper & Schindler, 2014).
This study adopted a descriptive correlational research design because it was relevant to
the study at hand whose aim was to determine the influence of transformational
leadership on job satisfaction among employees in commercial banks in Kenya. The
descriptive correlational research design was chosen because it is ideal in revealing
accurate information about a phenomenon. The information derived is useful in making
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inferences on the extent of association and the relationship between variables; in this case
the relationship between transformational leadership and job satisfaction (Harrison &
Reilly, 2011).
3.4 Target Population
Cooper and Schindler (2014) describe the target population as a complete enumeration of
all the elements in consideration. Additionally, the target population is the total number of
individual elements with common observable characteristics. The target population in this
study was composed of all the managerial employees working in the 43 commercial
banks in Kenya (Appendix V). The target population was comprised of 10310 managerial
employees from the three bank tiers as indicated in Table 3.1 (CBK, 2017).
Table 3.1: Employment of Managerial Staff in the Banking Sector
Tier Population
One 4,495
Two 3,629
Three 2,186
Total 10,310
3.5 Sample Design
According to Cooper and Schindler (2014), a sample design is a plan for obtaining a
sample from a given population. Sampling helps to boost the accuracy of results because
it enables the researcher to focus on a specific group of people as opposed to focusing on
the entire target population. Under the sample design, the sampling frame, sampling
technique and the sample size are discussed.
3.5.1 Sampling Frame
A sampling frame refers to the collection of source information from which the sample is
drawn (Cooper & Schindler, 2014). The sampling frame consists of all items from which
the sample is to be drawn from. The sampling frame was obtained from the Banking
Supervision Report by the Central Bank of Kenya which outlined the number of
employees in the banking sector in four categories; management, supervisory, clerical and
secretarial, and support staff. In this study, the sampling frame was constituted of 10,310
employees serving in the commercial banks at the management level who were likely to
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experience leadership decisions firsthand and also be charged with implementation (CBK,
2017). Management employees were selected since they constitute the team which is
mostly impacted on by the nature of leadership; they are also the key persons running
with the day to day strategy implementation meaning there is substantial interaction
between them and the executive leadership.
3.5.2 Sampling Technique
A sampling technique refers to the identification of the process through which a sample
will be selected. There are various ways of sampling which can be divided into
probability and non-probability sampling. Non-probability sampling refers to sampling
techniques which are used to select a sample when there is no complete list of the
population; thus no sampling frame which introduces an element of subjective judgment.
Examples of sampling techniques are convenience and snowball. Convenience refers to
selecting elements that are easily available to obtain from the sample whereas snowball
refers to making contact with one or two elements in the population then asking them to
identify more elements and so on and stopping when the required sample is attained or
there are no more elements (Sekaran & Bougie, 2016).
Probability sampling presents an equal chance of selection or when the elements have a
known and nonzero chance of being chosen as samples in a population. It can be simple
random sampling where all elements have a known and equal chance of being selected as
a subject which could be cumbersome and expensive not withstanding an updated listing
of the population may not be available. Probability sampling is guided by restricted
sampling which offers viability and more efficiency in the sample selection. It takes the
form of simple random, systematic random, stratified random, cluster or multi-stage
sampling (Saunders et al., 2016).
Simple random sampling involves the selection of a sample at random from the sampling
frame using a computer or random number tables. Systematic random sampling involves
selecting a sample at regular intervals from a sampling frame (Creswell, 2014). Stratified
random sampling involves dividing the target population in strata based on one or more
attributes thus dividing the sampling frame in sub-sets from which a random sample
which could be simple or systematic is drawn from each stratum (Cooper & Schindler,
2014). In cluster sampling, the target population is divided into distinct groups before
sampling and the groups are based on any naturally occurring grouping. The sampling
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frame then becomes the complete set of clusters from which a few clusters are selected
using simple random sampling and data collected from every case in the selected clusters.
Multi-stage sampling is a development of cluster sampling which occurs where sampling
is done in several stages by modifying a cluster sample by adding another stage of
sampling which may take the form of random sampling (Saunders et al., 2016).
This study adopted stratified random sampling technique where the banks were grouped
into three tiers as per the Central Bank of Kenya classification which is based on
capitalization, market share and profitability (CBK, 2017). Tier one comprised of 7
banks, tier two 14 banks and tier three 22 banks. Tier one was comprised of the big banks,
tier two the medium sized banks and tier three the small banks. The target population was
distributed proportionately across the three tiers based on the sample size and the number
bank branches in each tier. Thereafter, the sample size for each tier was determined using
simple random sampling technique. Specifically, simple random sampling was carried out
by using computer generated random numbers for each tier.
3.5.3 Sample Size
A sample is a subset of the target population which is used in order to answer the research
questions. Additionally, the use of the entire target population as study respondents is
faced with several difficulties such as inadequate research budget, limited time factor and
large geographical coverage of the respondents which can be mitigated by drawing of a
subset of the target population as a true representative of the study population (Sekaran &
Bougie, 2016). This study used Yamane (1967) formula to obtain the sample size.
Yamane (1967), Formula:
Where:
N = target (total) population (10, 310)
n = desired sample size
d= confidence interval (0.05 testing at 5% significant level)
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The total sample size was 424 which included an additional 10% which was 39
employees to cater for non respondents as indicated in table 3.2.
The formula is recommended for determining a sample size where the population is
known and finite. A finite population is a population whose total number of elements is
known or can be counted. It is also suitable because it assumes a normal distribution, a
95% confidence level and a p< 0.05 (Yamane, 1967).
Table 3.2: Sample Size Distribution Based on Tiers of the Banks
Tier Target Employees Sample Employees
One 4495 (424/10301)4495 = 185
Two 3629 (424/10301)3629 = 149
Three 2186 (424/10301)2186 = 90
Total 10, 310 424
The study obtained the respondents from all the commercial banks in Kenya in the three
tiers as grouped by the Central Bank of Kenya; this was achieved by distributing the
sample employees per tier between all banks in a particular tier. Additionally, the study
focused on employees from the head offices of the various commercial banks all of which
were located in Nairobi. The focus on head office was informed by the fact that most of
the employees at management level were located in the head office.
3.6 Data Collection Methods
According to Sekaran and Bougie (2016), data collection methods include interviews,
observations and questionnaires. Interviews involve the researcher asking or interrogating
the respondents to obtain information on the issues of interest and it is suitable for
exploratory studies. They may be structured or unstructured, conducted face to face, by
telephone or online. Observation involves going into the field and watching what the
subjects of the study do, describing, analyzing and interpreting what one has seen. It is
most suited for research that requires behavior to be examined without directly asking the
respondents. A questionnaire is a written set of questions formulated by the researcher to
which respondents record their responses (Cooper & Schindler, 2014).
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This study sought to collect primary data by use of questionnaires. The questionnaires
were informed by the Multifactor Leadership Questionnaire (MLQ) which contains the
most commonly used and validated measures of transformational leadership which are
idealized influence, individualized consideration, inspirational motivation and intellectual
stimulation developed by Bass (1985). The questionnaire had six sections which
addressed the demographic and general information, idealized influence and job
satisfaction, individualized consideration and job satisfaction, inspirational motivation
and job satisfaction, intellectual stimulation and job satisfaction, and the moderating
effect of job security between transformational leadership and job satisfaction. The
questions were all closed ended and adopted a five-point Likert scale which was used to
rate the answers from the respondents; the ratings were: 1= Strongly Disagree (SD), 2 =
Disagree (D), 3 = Neutral (N), 4 = Agree (A), 5 = Strongly Agree (SA). Under each
research question, there were two sub-sections; the first was to determine if the leader
was transformational and the second one was to determine the influence of the constructs
of transformational leadership on job satisfaction.
3.7 Research Procedures
The research procedures outline how the pilot study was carried out, the results of the
reliability and validity tests from the pilot study, how the research instruments were
administered and the ethical considerations made by the researcher. The pilot study was
conducted after approval of the research proposal and the research instrument by the
researcher’s supervisors and the business school at USIU-Africa. The researcher also
obtained a permit to conduct the research from the National Commission for Science,
Technology and Innovation (NACOSTI). The questionnaires were administered to the
respondents by the researcher. The researcher visited banks in every tier and approached
the respondents to participate in the research. The respondents were briefed about the
research and the ethical considerations of anonymity and confidentiality of their
responses. Thereafter, they were requested to complete the questionnaires.
3.7.1 Pilot Study
A pilot study refers to the process of testing a questionnaire, interview schedule or
whichever data collection method with a small group of respondents who are similar to
those who will be used in the actual research to see if it works. Any issues that arise from
the pilot study can be corrected before the undertaking the actual research (Saunders et
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al., 2016). The primary aim of the pilot study was to test the reliability and validity of the
research instrument and also to ensure there were no problems in recording the data.
Cooper and Schindler (2014) explain reliability as the true measure of whether the
research instrument meets the intended purpose. With a pilot study, the researcher is able
to detect weaknesses in design of the questionnaire used and to adjust it accordingly
(Bryman, 2012).
This study focused on the influence of transformational leadership on job satisfaction
among employees in commercial banks in Kenyan. The total number of respondents
involved in the pilot study was 42 representing 10% of the entire sample size for the
study. The pilot response rate was 100% from 9 different banks; 17 respondents from tier
one, 14 respondents from tier two and 9 respondents from tier three. Collected data was
coded and entered in SPSS Version 22, cleaned and analyzed. The statistical test
conducted was Cronbach Alpha to test the reliability of the questionnaires.
3.7.2 Reliability of the Instruments
Reliability refers to the consistency of a measure of a concept; thus, the characteristic of
consistency of a measure which gives the same results when conducted on several
occasions (Bryman, 2012; MCBurney & White, 2007). Reliability is also known as
internal consistency and provides an estimate of the equivalence of sets of items from the
same tests. In this research, reliability was measured using Cronbach’s alpha which has
been used widely to measure reliability of research instruments. Sekaran and Bougie
(2016) highlighted that Cronbach’s alpha coefficient is a good measure of reliability; it
ranges between 0 and 1 with values of 0.7 or above indicating that the questions
combined in the scale are measuring the same thing and values 0.5 and less are
considered unacceptable and not measuring the same thing. The summary of the
combined variables in the study showed the item total Cronbach’s Alpha was .978. This
indicates that the questionnaire was highly reliable to be used in the study as indicated in
Table 3.3.
Table 3.3: Cronbach’s Alpha
Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items
.966 .978 30
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3.7.3 Validity of the Instruments
The ability of a research instrument to be a true measure of what it claims to measure or
the ability to gain meaning out of what the tool was supposed to measure is referred to as
validity (Bryman, 2012). In this research, validity was measured in three forms; content,
criterion, and construct validity. Face validity was performed to evaluate the outlay of the
tool while factor analysis was performed to evaluate construct validity.
The face validity of the instrument was used to determine criterion, and construct validity.
This was performed by observing the number of questionnaires filled (43 questionnaires).
Further the researcher collected feedback from the respondents on the flow of the
questions, understanding and comprehension. The questions raised as not clear were as
follows. My leader delegates work and authority to me: these were found to be two
questions in one. This was rephrased to ‘My leader delegates work to me’. My leader
persuades me to be creative and innovative in my job, ‘creative and innovation’ were
different and this was rephrased to ‘My leader permits me to be creative in my job’. I am
committed to the organization because my leader treats everyone fairly, the term ‘treats
everyone fairly’ was vague and was replaced to ‘My leader encourages fair treatment to
everyone’.
Content validity involves testing the items to ensure they give appropriate measures for
the concepts under study (Cooper & Schindler, 2014). Factor analysis was used to
determine the content validity of the questions. These questions were grouped based on
the number of items in each objective. The items with nearly zero difference had strong
content validity while those with bigger margins were not valid hence needed to be
rephrased.
3.7.4 Administration of the Instruments
Before data collection, the researcher obtained a clearance letter from USIU-Africa
(Appendix III) and a research permit from National Commission for Science, Technology
and Innovation (NACOSTI) (Appendix IV). All the approvals, NACOSTI and USIU
were presented to the respective bank managers by the researcher when collecting data.
This helped to authenticate the research and helped to obtain feedback from the
respondents with more ease.
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The corrected questionnaire based on the pilot study report was administered to the
respondents by the researcher. The research instrument had a cover letter which
introduced the research and gave details of the researcher, the USIU-Africa permit and
NACOSTI permit authorizing the researcher to carry out the study. The researcher
recruited and trained one research assistant on the study objectives and the content of the
questionnaires to be administered. Further, the research assistant was trained on the nature
of ethics and confidentiality that is required during the data collection exercise since
banks are very sensitive institutions as far as information concerned. Data was collected
by administering the questionnaires to the respondents through drop and pick method
where questionnaires were dropped at the respondent’s desk and collected upon
completion as requested by the researcher. The respondents were given ten days to
complete the questionnaires but as observed by the researcher it took two to three days.
Reminders were sent after four days to the respondents who had not returned the
questionnaires. All questionnaires, filled and unfilled were collected by the researcher and
prepared for data entry. A total of 347 questionnaires were returned representing an 82%
response rate; they were all coded to ensure they could all be accounted for.
3.7.5 Ethical Considerations
Research ethics refers to the appropriateness of the researcher’s behavior in regard to the
rights of those who become the subject of the research project or those who are affected
by it (Saunders et al., 2016). The researcher addressed the following ethical issues:
participant’s consent, confidentiality and anonymity through the research process and the
reporting. The researcher obtained a clearance letter from USIU-Africa and a research
permit from National Commission for Science, Technology and Innovation (NACOSTI).
All the approvals, NACOSTI and USIU-Africa clearance letters were presented to the
respective bank managers by the researcher and research assistant to obtain the final
authority to reach out to the staff in their organizations. Upon obtaining authority from
the bank management, the respondents were requested to participate in the study
voluntarily. The researcher notified the participants of their rights for information, asking
questions, and that they can withdraw from the research at will. The respondents were
also assured of their anonymity and that the information they provide towards the study
would be treated with confidentiality and for the sole purpose of this study. Information
received was also to be treated objectively and not to be altered for a desired objective.
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3.8 Data Analysis Methods
Descriptive and inferential statistical analyses used in the study are discussed. The
descriptive statistics adopted were mean, standard deviation, percentages and frequency
of response while inferential statistics adopted included test of correlations, Chi-square,
the ANOVA tests and regression analysis to obtain the relationship between the variables
of the study. The quantitative data analysis was done using Statistical Package for the
Social Sciences (SPSS). Presentations were done using tables and figures with detailed
interpretation of the findings.
3.8.1 Data Preparation
After data collection, the following iterative steps were taken. First, data was coded,
secondly, data was cleaned which meant detecting and correcting illogical, inconsistent,
illegal data and omission of information received from the respondents. Lastly, data was
transformed; this meant changing the ordinal numerical representation of a quantitative
value to another value to avoid problems in successive stages of the data analysis process.
This was done using the most suitable methods (Sekaran & Bougie, 2016).
3.8.2 Descriptive Analysis
According to Christensen, Johnson and Turner (2014), descriptive statistics are statistical
analysis focused on describing, summarizing and explaining a set of data. Descriptive
statistics are broken down into measures of central tendency and measures of variability.
A measure of central tendency refers to a single numerical value that is considered most
typical of the values of a quantitative variable and the measures include the mean, median
and mode. Cooper and Schindler (2014) state that a measure of variability is a numerical
index that provides information about how much variation there is in a variable and the
measures include standard deviation, range and variance. According to Sekaran and
Bougie (2016), descriptive statistics enable meaningful description of a distribution of
scores or measurements using a few indices or statistics. Descriptive statistics used
included mean, standard deviation, frequencies and percentages.
3.8.3 Inferential Analysis
According to Bandyopadhyay and Forster (2011), inferential statistics are concerned with
making inferences based on relations found in the sample to relations in the population.
The goal of inferential statistics is to go beyond the immediate available set of data and to
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infer characteristics of populations based on the sample data; thus, researchers use sample
data to make generalizations about populations. The inferential statistics that were used in
this study were correlation analysis, ANOVA, factorial analysis and multiple linear
regression analysis. Inferential analysis was majorly for testing the hypotheses (Sekaran
& Bougie, 2016). In this study, regression analysis aimed to predict the dependent
variable - job satisfaction - based on the independent variables – the four dimensions of
transformational leadership. Details of each of the inferential statistics are explained in
the successive sections.
3.8.3.1 Factor Analysis
Factor analysis is a statistical analysis used to determine the number of dimensions in a
set of items and informs the researcher if a test is unidimensional or multidimensional
(Cooper & Schindler, 2014). The tests conducted were Kaiser-Meyer-Olkin (KMO)
measure of sampling adequacy and Bartlett’s sphericity tests. From the test, values greater
than 0.6 qualified the use of factor analysis. Factor analysis was used to reduce the items
of analysis into few related items. In this study, questions with 5 scale measures under
each variable were tested. Factor analysis was based on component matrix where any
value of the component matrix above 0.6 indicated that there was no redundancy in the
questions and therefore the particular questions should not be dropped.
3.8.3.2 Correlation Analysis
According to Sekaran and Bougie (2016), correlation analysis is a method of statistical
evaluation used to study the strength of a relationship between two, numerically
measured, continuous variables. Any correlation value of the variable between 0.0-0.3
would indicate ‘no correlation’, correlation value between 0.31-0.69 would indicate
‘weak correlation’ and any correlation value above 0.7 would indicate strong correlation
between the variables. However, the statistical significance of the strength of the
correlation was based on a 5% significance level (P<.05). Correlation analysis was done
to test the correlation between the transformational leadership variables and job
satisfaction.
3.8.3.3 Chi-square
Chi-squared test is a statistical test applied to sets of categorical data to evaluate if two
variables are independent or whether the observed pattern occurred by chance (Sekaran &
Bougie, 2016). It is suitable for unpaired data from large samples (Bandyopadhyay &
92
Forster 2011). It was used to test whether job satisfaction was related to transformational
leadership. The Chi-square test was at a 5% significance level (P<=.05). Chi-square value
above 5% significance level (P<.05) indicated job satisfaction was not related to
transformational leadership while any value below 5% significance level (P<=.05)
indicated job satisfaction was related to transformational leadership not by chance but by
factors alone.
3.8.3.4 One-way ANOVA
According to Bailey (2008), analysis of variance (ANOVA) is a collection of statistical
models used to analyze the differences among group means. The One-way ANOVA test
was performed to test the mean differences between idealized influence and the
demographic information of respondents; gender, age, education level, duration of
working at the bank and the tier of the bank. The significance measure was set at 5%
significance level (P<.05). Where the results were not statistically significant, it indicated
there was no significant difference between the mean values of all the respondents’
demographic information – gender, age, education level, duration of working, tier of the
bank - and the independent variables – idealized influence, individualized consideration,
inspirational motivation and intellectual stimulation.
3.8.3.5 Regression Analysis
Regression analysis is a model used to determine the relationships among variables;
direction, strength and projection. It includes many techniques for modeling and
analyzing several variables and it helps one to understand how the typical value of the
dependent variable changes when any one of the independent variables is varied
(Creswel, 2014). In this study, regression analysis was used to determine the relationship,
magnitude of the influence and the extent to which transformational leadership predicted
job satisfaction among employees in commercial banks in Kenya.
3.8.3.5.1 Assumptions of Regression Analysis
This section discusses the assumptions of the regression analysis that were tested. The
assumptions of regression have great impact in regression analysis (Ghasemi &
Zahediasl, 2012). The assumptions tested included normality, linearity, homoscedasticity
and multicollinearity.
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3.8.3.5.1.1 Normality
Normality test was conducted using Skewness test and Kurtosis test where Kurtosis was
demonstrated based on three distributions; smallest or flattest peak, medium peak and
peak (leptokurtic) (Cooper & Schindler, 2014). Any skewness value between -2 to 0
indicated that there was no excessive skewness in that data. Kurtosis was used to measure
the level of data pickiness based on the normal distribution of data. Any kurtosis value
between -1 to +2 would indicate that there was no excessive skewness in the data. Lack of
excessive skewness and kurtosis in the data indicated that the normality assumption was
not strictly violated and the research data (job satisfaction and transformational leadership
data) was fit for regression analysis.
3.8.3.5.1.2 Linearity
Linearity is the property of a mathematical relationship or function which means that it
can be graphically represented as a straight line. For the linear regression model to be
used, the expected value of the dependent variable is a straight-line function of each
independent variable holding others constant. Additionally, effects of different
independent variables on the expected value of the dependent variable are additive
(Bewick, Chuck & Ball, 2003). The linearity test was conducted to determine whether the
nature of the relationship between transformational leadership and job satisfaction was
linear or not. This was done on the basis of 5% significance level, one tail test where any
significant deviation from linearity (deviation > 0.05) greater than 0.05 would indicate
that there was linear relationship between the between transformational leadership and
job satisfaction variables.
3.8.3.5.1.3 Homoscedasticity
In statistics, Homoscedasticity test establishes if the dependent and independent variables
have similar variance on their distribution. Homoscedasticity test was done using the
Leven statistics at 5% significance level. One tail test would indicate that the variance
was homogenous and hence fitted for regression analysis (Hair et al., 2007). In this
research Homoscedasticity test was carried out to determine if transformational leadership
had similar variance to job satisfaction of the bank employees on the regression values.
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3.8.3.5.1.4 Multicollinearity
Multicollinearity was tested using variance inflation factors (VIF). According to Lather
(2004), VIF assesses how much the variance of an estimated regression coefficient
increases if the predictors are correlated. If the VIF measure is equal to or less than one
(1) or above ten (10) there is multicollinearity among factors. This means the correct
measure of VIF should be above 1 and less than 10 (Sekaran & Bougie, 2016; Oakshott,
2014). The test was done on the transformational leadership and job satisfaction variable
and the overall interpretation of multicollinearity test was based on the VIF values where
any VIF value between 1 to 10 indicated that the level of multicollinearity that exists in
the study was fit for regression analysis.
3.8.3.5.2 Regression Model and Hypotheses Testing
This section presents the regression model used for the regression analysis and
hypotheses testing.
3.8.3.5.2.1 Regression Model
Linear regression was used to determine the influence of transformational leadership on
job satisfaction among employees in commercial banks in Kenya. Multiple linear
regression analysis was used where there was more than one independent variable to
explain the variance on the dependent variable (Cooper & Schindler, 2014; Sekaran &
Bougie, 2016; Saunders et al., 2016).
Fischer distribution test called F-test was applied to test the joint significant contribution
of attributes of transformation leadership on job satisfaction. The p-value for the F-
statistic was applied in determining the robustness of the model. The conclusion was, if
the value was significant (p<.05) the model was significant and had good predictors of the
dependent variable hence null hypothesis rejected. Alternatively, if the p-value was
greater than 0.05, then the model would not be significant and cannot be used to explain
the variations in the dependent variable hence the null hypothesis would not be rejected.
Y =β0 + β1X1 + β2X2 + β3X3 + β4X4+ β5Z + ∑
Where;
Y = Job Satisfaction
β0 = Constant
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X1 = Idealized influence
X2 = Individualized consideration
X3 = Inspirational motivation
X4 = Intellectual Stimulation
Z = Moderating Variable (Job security)
∑ = Standard Error
In the model, β0 = the constant term while the coefficient βi = 1…4 was used to measure
the sensitivity of the dependent variable (Y) to unit change in the predictor variables. ∑
was the error term which captured the unexplained variations in the model. In each test,
the null hypothesis was rejected or not rejected; if the p-value was less than 0.05, the
model was significant hence null hypothesis rejected. Alternatively, if the p-value was
greater than 0.05, then the model was not significant hence the null hypothesis not
rejected.
3.8.3.5.2.2 Hypotheses Testing
The hypotheses were tested using multiple linear regression analysis which is
recommended where there is more than one independent variable to explain the variance
on the dependent variable (Sekaran & Bougie, 2016). The five hypotheses of the study
were all tested through the regression models outlined hereunder.
To test for H01: There is no significant influence of idealized influence on job
satisfaction among employees in commercial banks in Kenya.
Regression model 1:
Job Satisfaction = β0 + βi x idealized influence + ∑……… Equation 1
To test for H02: There is no significant influence of individualized consideration on job
satisfaction among employees in commercial banks in Kenya.
Regression model 2:
Job Satisfaction = β0 + βi x individualized consideration + ∑……… Equation 2
To test for H03: There is no significant influence of inspirational motivation on job
satisfaction among employees in commercial banks in Kenya.
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Regression model 3:
Job Satisfaction = β0 + βi x inspirational motivation + ∑……… Equation 3
To test for H04: There is no significant influence of intellectual stimulation on job
satisfaction among the employees in commercial banks in Kenya.
Regression model 4:
Job Satisfaction = β0 + βi x intellectual stimulation + ∑……… Equation 4
To test for H05: There is no significant moderating effect of job security between
transformational leadership and job satisfaction among employees in commercial banks in
Kenya.
Regression model 5:
Job Satisfaction = β0 + β1 x Idealized influence + β2 x Individualized consideration + β3 x
Inspirational motivation + β4 x Intellectual Stimulation + β5 x Job security + ∑….......
Equation 5
Table 3.4 presents a summary of the hypotheses testing.
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Table 3.4: Hypothesis Testing
Variable Hypothesis Test
Idealized
influence
To test for H01: There is no
significant influence of idealized
influence on job satisfaction among
employees in commercial banks in
Kenya
Linear regression:
Y =β0 + β1X1 + ∑
Accept if p<.05 or otherwise
reject
Individualized
consideration
To test for H02: There is no
significant influence of
individualized consideration on job
satisfaction among employees in
commercial banks in Kenya
Linear regression:
Y =β0 + β2X2 + ∑
Accept if p<.05 or otherwise
reject
Inspirational
motivation
To test for H03: There is no
significant influence of inspirational
motivation on job satisfaction
among employees in commercial
banks in Kenya
Linear Equation:
Y =β0 + β3X3 + ∑
Accept if p<.05 or otherwise
reject
Intellectual
Stimulation
To test for H04: There is no
significant influence of intellectual
stimulation on job satisfaction
among the employees in
commercial banks in Kenya
Linear regression:
Y =β0 + β4X4+ ∑
Accept if p<.05 or otherwise
reject
Moderating
effect of Job
satisfaction
To test for H05: There is no
significant moderating effect of job
security between transformational
leadership and job satisfaction
among employees in commercial
banks in Kenya
Multiple linear regression:
Y =β0 + β1X1 + β2X2 + β3X3 +
β4X4+ β5Z + ∑
Accept if p<.05 or otherwise
reject
3.9 Chapter Summary
This chapter has discussed the research methodology, the research philosophy, the
research design, the sampling design, the data collection methods, research procedures
and data analysis methods used in the study. It has also outlined the descriptive and
inferential statistics that the study adopted for the analysis and presentation of results and
findings. Chapter four presents the results and findings of data analysis.
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CHAPTER FOUR
4.0 RESULTS AND FINDINGS
4.1 Introduction
This chapter presents the results and findings of the study. The presentation of the results
is done sequentially according to the research questions. Demographic and general
information is presented first followed by the descriptive and inferential statistics of
idealized influence, individualized consideration, inspirational motivation, intellectual
stimulation and job satisfaction, and lastly the moderating effect of job security between
transformational leadership and job satisfaction.
A total of 424 questionnaires were distributed, 347 questionnaires were returned and
analyzed representing an 82% response rate.
4.2 General Information
This section presents the demographic and general information. Descriptive statistics
were used to analyze the demographic information in form of percentage, mean and
standard deviation. The information analyzed included gender, age, education, duration of
working in the bank and tiers of the banks and the results are presented below.
4.2.1 Gender
Out of the 347 respondents, 52% were male and 48% who were female as indicated in the
figure 4.1.
Male52%
Female48%
Figure 4.1: Gender of Respondents
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4.2.2 Age of Respondents
Figure 4.2 shows the age distribution of the respondents. The results revealed that 49%
were aged 30-39; 35% were aged 21-29 years, 13% were aged 40-49 years, 3% were aged
50-59 years while those who were aged over 60 years were less than 1%.
35.20%
48.50%
13.10%
2.90%0.30%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
21-29 30-39 40-49 50-59 Over 60
Figure 4.2: Age of Respondents
4.2.3 Education of Respondents
Figure 4.3 shows the distribution of respondents based on education qualification. The
results revealed that majority of the respondents (about 59%) had a Bachelor’s degree.
This was followed by approximately 33% who were Master’s degree holders. A few of
the respondents (about 1%) were certificate holders.
1.20%5.80%
58.50%
32.90%
1.70%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
Certificate Diploma Bachelor's Master's PhD
Figure 4.3: Education Qualification
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4.2.4 Duration of Working
Figure 4.4 shows results on the duration of work in the bank. There was clear pattern on
the duration of working; majority of respondents had worked for fewer years and fewer of
the respondents had worked for more years in the banking sector. Those who had worked
for between 0-5 years were about 37% followed by those who had worked for 6-10 years
who were about 34%. Only about 6% of the respondents had worked for more than 20
years. This showed that fewer people opted to remain in the banking sector as they grew
older.
37.30%
34.10%
19.10%
4.00%
5.50%
0-5
6-10
11-15
16-20
over 20
Figure 4.4: Duration of Working
4.2.3 Tiers of the Banks
Figure 4.5 presents results on the tiers of the banks. In Kenya, banks are classified into
three different tiers; thus, tiers; 1, 2 and 3. The respondents were asked to indicate the tier
of their bank; 49% indicated they worked for banks classified as tier 1, 34% worked for
banks classified as tier 2 and lastly 17% worked for banks classified as tier 3.
Tier 149%
Tier 234%
Tier 317%
Figure 4.5: Tier of the Banks
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4.3 Influence of Idealized Influence on Job Satisfaction
The first objective was to determine the influence of idealized influence on job
satisfaction. This was guided by the independent variable questions on idealized influence
and dependent variable questions on job satisfaction. The independent variable questions
were: my leader has charismatic attributes; my leader demonstrates trust in my abilities;
and my leader is ethical in the workplace. The dependent variable questions on job
satisfaction were: I am committed to the organization because of my leader’s charismatic
attributes; I am present at work because my leader demonstrates trust in my abilities; and
I have no intentions of leaving my job because my leader is ethical in the workplace. The
results and findings of both descriptive and inferential statistics are presented below.
4.3.1 Factor Analysis
Factor analysis was used to evaluate the variability among the observed correlated
variables to ensure the questions in the research instrument relate to the construct of
measure. Questions that did not relate to the construct were extracted from the analysis.
Factor analysis was conducted on three questions for the dependent variable ‘job
satisfaction’ and the three questions for independent variable ‘idealized influence’ as
presented below.
4.3.1.1 Factor Analysis on Idealized Influence
The independent variable in the study was idealized influence. As indicated in table 4.1a,
only one factor was derived with Kaiser-Meyer result of 0.721. The Bartlett’s test of
Sphericity was significant at X2 (3, N=347) = 462.905, p<.05. The factor was adequate for
extraction of component since Kaiser-Meyer-Olkin Measure was greater than 0.6 and the
Bartlett’s test was significant (p<.05). Table 4.1a shows the results.
Table 4.1a: KMO and Bartlett's Test on Idealized Influence
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .721
Bartlett's Test of Sphericity Approx. Chi-square 462.905
Df 3
Sig. .000
* Significant at p<0.05 level
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Using the principal component analysis, the total variance explained on the extraction
showed that the extracted values presented 78% of the first component. Only one
component was extracted ‘idealized influence’. Further, average value principle was used
to obtain the measure of the extracted independent variable by transformation. Table 4.1b
shows the results of the variance explained.
Table 4.1b: Total Variance Explained for Idealized Influence
Component
Initial Eigenvalues Extraction Sums of Squared Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance Cumulative %
1 2.327 77.554 77.554 2.327 77.554 77.554
2 .396 13.216 90.770
3 .277 9.230 100.000
Extraction Method: Principal Component Analysis.
One component for idealized influence had an Eigen value that was greater than one
which was in line with the results for total variance explained for idealized influence as
shown in Figure 4.6.
Figure 4.6: Scree Plot for Idealized Influence
The variables of the extracted components were indicated on the component matrix Table
4.1c. Only one factor was extracted representing ‘idealized influence’. The variables
103
extracted and values were; my leader has charismatic attributes (.875), my leader
demonstrates trust in my abilities (.905) and my leader is ethical in the workplace (.861).
All the variables and components measured under the factor loading were greater than
.60. Further, using the average of the components, the transformed data had a stronger
component of .880 which was greater than .60. All the components were stronger and
were included as variables of analysis in the model ‘idealized influence’ since the values
were greater than .60.
Table 4.1c: Component Matrix on Idealized Influence
Idealized Influence
Component
1
My leader has charismatic attributes .875
My leader demonstrates trust in my abilities .905
My leader is ethical in the workplace .861
Extraction Method: Principal Component Analysis.
a. 1 component extracted.
4.3.1.2 Factor Analysis of Idealized Influence on Job Satisfaction
The dependent variable in the study was idealized influence on job satisfaction. As
indicated in Table 4.2a, only one factor was derived with Kaiser-Meyer Olkin result of
0.739. The Bartlett’s test of Sphericity was significant at X2 (3, N=347) = 497.434, p<.05.
The factor was adequate for extraction of the component since Kaiser-Meyer Olkin
Measure was greater than 0.6 and the Bartlett’s test was significant (p<.05).
Table 4.2a: KMO and Bartlett’s Test on Idealized Influence on Job Satisfaction
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .739
Bartlett's Test of Sphericity Approx. Chi-square 497.434
Df 3
Sig. .000
* Significant at p<0.05 level
104
Using the principal component analysis, the total variance explained on the extraction
shows the extracted values presented 79% of the component. Only one component was
extracted ‘idealized influence on job satisfaction’. Further, average value principle was
used to obtain the measure of the extracted independent variable named ‘idealized
influence on job satisfaction’ by transformation. Table 4.2b shows the results of the total
variance explained on idealized influence.
Table 4.2b: Total Variance Explained on Idealized Influence
Component
Initial Eigenvalues
Extraction Sums of Squared
Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
%
1 2.370 79.010 79.010 2.370 79.010 79.010
2 .326 10.871 89.880
3 .304 10.120 100.000
Extraction Method: Principal Component Analysis
The variables of the extracted components are indicated on the component matrix Table
4.2c. Only one factor was extracted representing ‘idealized influence on Job satisfaction’.
The variables and values extracted were: ‘I am committed to the organization because of
my leader’s charismatic attributes’ and ‘I have no intentions of leaving my job because
my leader is ethical in the workplace’ had similar component matrix value of .891 while
‘I am present at work because my leader demonstrates trust in my abilities’ had
component matrix value of .884. This shows the variables and components measured
under the factor loading were greater than .60. Further, using the average of the
components, the transformed data had a stronger component of .889 which was greater
than .60. The components of the dependent variables were included as variables of
analysis in the model as ‘idealized influence on job satisfaction’ since the values were
greater than .60. Table 4.2c shows the component matrix of idealized influence on job
satisfaction.
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Table 4.2c: Component Matrix of Idealized Influence on Job Satisfaction
Idealized Influence on Job Satisfaction Component
1
I am committed to the organization because of my leader has
charismatic attributes .891
I am hardly absent from work because my leader demonstrates
trust in my abilities .884
I have no intentions of leaving my job because my leader is
ethical in the workplace .891
Extraction Method: Principal Component Analysis.
a. 1 component extracted.
4.3.2 Descriptive Statistics for Idealized Influence
On idealized influence, majority of the respondents agreed on the attribute ‘my leader is
ethical in the workplace’ (M= 4.23, SD = 0.84) and also ‘my leader demonstrates trust in
my abilities’ (M= 4.08, SD = 0.88). This clearly shows the difference; with the decrease
in mean, the standard deviation increased indicating responses were varied. Table 4.3
shows the results of the descriptive statistics of idealized influence. On job satisfaction,
majority of the respondents agreed on the attribute ‘I am hardly absent from work because
my leader demonstrates trust in my abilities’ (M= 3.42, SD = 1.21) followed by ‘I am
committed to the organization because of my leader’s charismatic attributes’ (M= 3.25,
SD = 1.14). The trend of the mean and standard deviation varied depicting varied
responses as indicated in Table 4.3.
106
Table 4.3: Mean and Standard Deviation of Idealized Influence
Idealized Influence M SD Skewness Std Error
My leader has charismatic attribute 3.89 0.97 -1.03 0.13
My leader demonstrates trust in my abilities 4.08 0.88 -1.05 0.13
My leader is ethical in the workplace 4.23 0.84 -1.28 0.13
Effect of Idealized Influence on Job Satisfaction
I am committed to the organization because of
my leader has charismatic attributes 3.25 1.14 -0.23 0.13
I am hardly absent from work because my
leader demonstrates trust in my abilities 3.42 1.21 -0.44 0.13
I have no intentions of leaving my job
because my leader is ethical in the workplace 2.91 1.27 0.04 0.13
4.3.3 Chi-square Test of Idealized Influence and Job Satisfaction
The Chi-square test was used to determine whether there was a significant association
between idealized influence and job satisfaction. The chi-square test results showed that
there was a significant association between idealized influence and job satisfaction X2
(132, N = 346) = 302.886, p<.05). The results are presented in Table 4.4.
Table 4.4: Chi-square Test of Idealized Influence and Job Satisfaction
Idealized Influence Value df Asymp. Sig. (2-sided)
Pearson Chi-square 302.886a 132 .000
Likelihood Ratio 260.451 132 .000
Linear-by-Linear Association 84.977 1 .000
N of Valid Cases 346
a. 134 cells (85.9%) have expected count less than 5. The minimum expected count is .01.
* Significant at p<0.05 level
107
4.3.4 Correlation Analysis between Idealized Influence and Job Satisfaction
Correlation analysis was used to test the relationship between idealized influence
variables and job satisfaction. As shown in Table 4.5a, all the variables were highly
correlated. The first variable under idealized influence ‘my leader has charismatic
attributes’ was positively correlated with job satisfaction r (345) =.563, p<.05; ‘my leader
demonstrates trust in my abilities’ was positively correlated with job satisfaction r (346)
=.596, p<.05; and ‘my leader is ethical in the workplace’ was positively correlated with
job satisfaction r (343) =.564, p<.05.
Table 4.5a: Correlation Analysis between Idealized Influence Variables and Job
Satisfaction
Idealized Influence Pearson Correlation Job Satisfaction
My leader has charismatic attribute. Pearson Correlation .563**
Sig. (2-tailed) .000
N 345
My leader demonstrates trust in my
abilities.
Pearson Correlation .596**
Sig. (2-tailed) .000
N 346
My leader is ethical in the workplace. Pearson Correlation .564**
Sig. (2-tailed) .000
N 343
* Significant at p<0.05 level
Further, correlation analysis was used to test the relationship between idealized influence
and job satisfaction. The results showed that there was a strong and positive correlation
between idealized influence and job satisfaction r (346) =.496, p<.05. The results are
presented in Table 4.5b.
Table 4.5b: Correlation Analysis between Idealized Influence and Job Satisfaction
Job Satisfaction
Idealized influence Pearson Correlation .496**
Sig. (2-tailed) .000
N 346
* Significant at p<0.05 level
108
4.3.5 One-way ANOVA on Idealized Influence
The One-way ANOVA test was performed to test the mean differences between idealized
influence and the demographic information of respondents; gender, age, education level,
duration of working at the bank and the tier of the bank. Table 4.6a shows the results
which indicate that there was no significant difference between the mean values of all the
respondents’ demographic information of gender, age, education level, duration of
working, tier of the bank and idealized influence.
Table 4.6a: One-way ANOVA on Idealized Influence
Sum of
Squares df
Mean
Square F Sig.
Gender Between Groups 3.773 11 .343 1.388 .177
Within Groups 82.041 332 .247
Total 85.814 343
Age Between Groups 9.847 11 .895 1.514 .124
Within Groups 195.652 331 .591
Total 205.499 342
Education Between Groups 4.900 11 .445 1.144 .326
Within Groups 129.259 332 .389
Total 134.160 343
How long
have you
worked
Between Groups 13.850 11 1.259 1.031 .418
Within Groups 406.747 333 1.221
Total 420.597 344
Tier of your
bank
Between Groups 10.262 11 .933 1.686 .075
Within Groups 184.767 334 .553
Total 195.029 345
* Significant at p<0.05 level
The One-way ANOVA test was also performed to test the mean differences between job
satisfaction and the demographic factors of gender, age, education, duration of working at
the bank and tier of the bank. Table 4.6b shows the results which indicate that there was
109
no significant difference between the mean values of majority of the demographic
variables and job satisfaction. However, the means for job satisfaction were significantly
different across the demographic variable of the number of years worked in the
organization.
Table 4.6b: One-way ANOVA on Idealized Influence on Job Satisfaction
Sum of
Squares
df Mean
Square
F Sig.
Gender
Between Groups 2.103 12 .175 .693 .758
Within Groups 83.711 331 .253
Total 85.814 343
Age
Between Groups 7.701 12 .642 1.071 .384
Within Groups 197.798 330 .599
Total 205.499 342
Education
Between Groups 4.325 12 .360 .919 .528
Within Groups 129.835 331 .392
Total 134.160 343
How long have
you worked
Between Groups 30.497 12 2.541 2.163 .013
Within Groups 390.100 332 1.175
Total 420.597 344
Tier of your
bank
Between Groups 4.647 12 .387 .677 .773
Within Groups 190.382 333 .572
Total 195.029 345
* Significant at p<0.05 level
4.3.6 Regression Analysis and Hypothesis Testing
This section presents the regression analysis, the model used for hypothesis testing in the
study and the assumptions of regression. Regression analysis was done to determine the
relationship, magnitude of the effect and projection of the influence of idealized influence
on job satisfaction among employees in commercial banks in Kenya.
110
4.3.6.1 Assumptions for Regression Analysis on Idealized Influence
Before running the regression analysis, assumptions for regression were tested. The
following tests were conducted: normality test, linearity test, homoscedasticity test and
multicollinearity tests as presented hereunder.
4.3.6.1.1 Normality Test on Idealized Influence
Using one sample Kolmogorov-Smirnov Test, the test of normality was conducted to
determine the distribution of data depicting either a normal or skewed curve. This was
determined by the statistical significance of the dependent and the independent variable
(p<.05). The normal parameters test indicated difference on mean: idealized influence
had (M= 4.07, SD = .788) compared to Job satisfaction (M= 3.20, SD = 1.07). The
variance on the mean was low compared to the standard deviation variance which was
high. Further, the results showed the variance on the most extreme differences was
minimal and the variables were significant to each other (p<.05) indicating a high level of
relationship hence the data was not normally distributed (p<.05). Table 4.7a indicates the
results of the normality test.
Table 4.7a: One-Sample Kolmogorov-Smirnov Test on Idealized Influence
Idealized_ influence Job_ satisfaction
N 346 346
Normal Parametersa,b Mean 4.0655 3.1965
Std. Deviation .78771 1.07253
Most Extreme Differences Absolute .184 .103
Positive .118 .084
Negative -.184 -.103
Test Statistic .184 .103
Asymp. Sig. (2-tailed) .000c .000c
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.
* Significant at p<0.05 level
111
4.3.6.1.2 Linearity Test on Idealized Influence
The analysis of variance (ANOVA) was used to determine linearity. The linearity test was
conducted to determine whether the nature of the relationship between idealized influence
and job satisfaction was linear or not. As indicated in Table 4.7b, there was a significant
relationship between idealized influence and job satisfaction on the combined and
linearity tests (p<.05). However, the deviation from linearity was not significant. Hence
the relationship between idealized influence and job satisfaction was linear and passed the
test of linearity.
Table 4.7b: Linearity Test on Idealized Influence
Sum of
Squares df
Mean
Square F Sig.
Idealized
influence * Job
satisfaction
Between
Groups
(Combined) 62.420 12 5.202 11.422 .000
Linearity 52.728 1 52.728 115.782 .000
Deviation from
Linearity 9.692 11 .820 1.988 .071
Within Groups 151.651 333 .455
Total 214.071 345
* Significant at p<0.05 level
4.3.6.1.3 Multicollinearity Test on Idealized Influence
Multicollinearity test was performed to determine if the values of idealized influence and
job satisfaction had high similarity. The test of multicollinearity was using the Variance
Inflation Factor (VIF). Statistically, there is no multicollinearity when the value of VIF
between 1 and 10. As indicated in Table 4.7c, the VIF value was 1.860 which shows there
was no multicollinearity between idealized influence and job satisfaction.
112
Table 4.7c: Multicollinearity Test on Idealized Influence
Model
Unstandardized
Coefficients
Standardized
Coefficients
T Sig.
Collinearity
Statistics
B
Std.
Error Beta Tolerance VIF
1 (Constant) .449 .264 1.702 .090
Idealized
Influence .676 .064 .496 10.603 .003 1.860 1.860
4.3.6.1.4 Homoscedasticity Test on Idealized influence
Homoscedasticity test was carried out to determine if idealized influence of the bank
employees had similar variance to job satisfaction on the regression values. As indicated
on Table 4.7d, the results indicate that the value of the Levene Statistic, F (10, 334) =
1.69, p = .08 was above the study’s level of significance (p <.05) indicating the data was
homogenous.
Table 4.7d: Homoscedasticity Test on Idealized Influence
Levene Statistic df1 df2 Sig.
1.688 10 334 .082
* Significant at p<0.05 level
4.3.6.2 Regression and Hypothesis Testing
Regression analysis was carried out to determine the extent to which idealized influence
influenced job satisfaction among employees in commercial banks in Kenya. Multiple
linear regression was used to predict job satisfaction of employees in commercial banks
in Kenya from idealized influence. The hypothesis tested was:
H01: There is no significant influence of idealized influence on job satisfaction among
employees in commercial banks in Kenyan.
The regression results for the hypothesis testing were presented in the form of the model
summary, regression ANOVA and regression coefficient.
113
4.3.6.2.1 Regression Model Summary
The model summary results presented in Table 4.8 indicate that idealized influence
explained 25% of job satisfaction among employees in commercial banks in Kenya (R2) =
.246.
Table 4.8: Model Summary of Idealized Influence and Job Satisfaction
Model R
R
Square
Adjusted
R
Square
Std.
Error of
the
Estimate
Change Statistics
R
Square
Change
F
Change df1 df2
Sig. F
Change
1 .496a .246 .244 .93247 .246 112.421 1 344 .000
a. Predictors: (Constant), Idealized Influence
* Significant at p<0.05 level
4.3.6.2.1 Regression ANOVA
The regression ANOVA showed that idealized influence had a significant influence on
job satisfaction F(1, 97.750) = 112.421, p<.05) as indicated Table 4.9. This means that
the regression model was suitable for predicting the outcome variable on how idealized
influence influenced job satisfaction among employees in commercial banks in Kenya.
Table 4.9: Regression ANOVA of Idealized Influence on Job Satisfaction
Model
Sum of
Squares Df Mean Square F Sig.
1 Regression 97.750 1 97.750 112.421 .000b
Residual 299.108 344 .869
Total 396.858 345
a. Dependent Variable: Job satisfaction
b. Predictors: (Constant), idealized influence
* Significant at p<0.05 level
4.3.6.2.3 Regression Coefficient on Idealized Influence
Table 4.10 shows the results of the regression coefficient. In the regression coefficients
model, the analysis showed that idealized influence statistically predicted job satisfaction
114
(β = .676, (.449) t = 10.603, p<.05). The beta weight gauges the importance of
explanatory variable across the model and was positive on idealized influence, Beta of
.449 and statistically significant at p<.05. This means, one unit of increase in idealized
influence increased the unit of job satisfaction by .449.
Table 4.10: Coefficients of Idealized Influence on Job Satisfaction
Model
Unstandardized
Coefficients
Standardized
Coefficients
T Sig. B Std. Error Beta
1 (Constant) .449 .264 1.702 .090
Idealized Influence .676 .064 .496 10.603 .003
a. Dependent Variable: Job satisfaction
* Significant at p<0.05 level
From the coefficient table, the values of the regression model were derived:
The general form of the regression model used was:
= Constant; = idealized influence and = Error term.
From the coefficient table, idealized influence influenced job satisfaction among
employees in commercial banks in Kenya.
Y= 0.449 + .676X + .064
Multiple linear regression analysis was used to test if idealized influence significantly
predicted job satisfaction among employees in commercial banks in Kenya. The results
revealed that idealized influence explained 25% of job satisfaction (R2 = .246, F (1,
97.750) = 112.421, p<.05) while the remaining 75% of job satisfaction were explained by
other factors. Further, idealized influence significantly predicted job satisfaction (β =
.676, (.449) t = 10.603, p<.05). Therefore, the study rejected the null hypothesis H01:
There is no significant influence of idealized influence on job satisfaction among
employees in commercial banks in Kenya and accepted the alternate hypothesis, H11:
115
There is a significant influence of idealized influence on job satisfaction among
employees in commercial banks in Kenya.
4.4 Influence of Individualized Consideration on Job Satisfaction
The second objective was to determine the influence of individualized consideration on
job satisfaction. This was guided by the independent variable questions on individualized
consideration and dependent variable questions on job satisfaction. The independent
variable questions were: my leader delegates work to me; my leader mentors me in the
workplace; and my leader supports me in my work. The dependent variable questions on
job satisfactions were: I have no intentions of leaving my job because my leader delegates
work to me; I am committed to the organization because my leader mentors me in the
workplace; and I am hardly absent from work because my leader supports me in my
work. The results and findings of both the descriptive and inferential statistics are
presented below.
4.4.1 Factor Analysis
Factor analysis was used to evaluate the variability among the observed correlated
variables to ensure the questions in the research instrument relate to the construct of
measure. Questions that did not relate to construct were extracted from the analysis.
Factor analysis was conducted on three questions for dependent variable ‘job satisfaction’
and three questions for independent variable ‘individualized consideration’ as presented
below.
4.4.1.1 Factor Analysis on Individualized Consideration
The independent variable in the study was individualized consideration. As indicated in
Table 4.11a, only one factor was derived with Kaiser-Meyer Olkin result of .654. The
Bartlett’s test of sphericity was significant at X2 (3, N=347) = 309.573, p<.05. The factor
was adequate for extraction of component since Kaiser-Meyer-Olkin Measure was greater
than .60 and the Bartlett’s test was significant (p<.05).
116
Table 4.11a: KMO and Bartlett's Test on Individualized Consideration.
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .654
Bartlett's Test of Sphericity Approx. Chi-square 309.573
df 3
Sig. .000
* Significant at p<0.05 level
Using the Principal component analysis, the total variance explained on the extraction
showed the extracted values presented 69% of the first component. Only one component
was extracted ‘individualized consideration’. The average value principle was used to
obtain the measure of the extracted independent variable by transformation. Table 4.11b
shows the results of the variance explained.
Table 4.11b: Total Variance Explained for Individualized Consideration
Component
Initial Eigenvalues
Extraction Sums of Squared
Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
%
1 2.069 68.980 68.980 2.069 68.980 68.980
2 .606 20.217 89.196
3 .324 10.804 100.000
Extraction Method: Principal Component Analysis.
One component for individualized consideration had an Eigen value that was greater than
one which was in line with the results for total variance explained for individualized
consideration as shown in Figure 4.7.
117
Figure 4.7: Scree Plot for Individualized Consideration
The variables of the extracted components were indicated on the component matrix Table
4.11c. Only one factor was extracted representing ‘individualized consideration’. The
variables extracted and values were; my leader mentors me in the workplace (.847), my
leader supports me in my work (.885) and my leader delegates work to me (.754). All the
variables and components analyzed under the factor loading were greater than .60.
Further, using the average of the components, the transformed data had a stronger
component of .829 which was greater than .60. All the components were included as
variables of analysis in the model ‘individualized consideration’ since the values were
greater than .60. Table 4.11c shows the component matrix on individualized
consideration.
Table 4.11c: Component Matrix on Individualized Consideration
Individualized consideration
Component
1
My leader mentors me in the workplace .847
My leader supports me in my work .885
My leader delegates work to me .754
Extraction Method: Principal Component Analysis.
a. 1 component extracted.
118
4.4.1.2 Factor Analysis of Individualized Consideration on Job Satisfaction
The dependent variable in the study was individualized consideration on job satisfaction.
As indicated in Table 4.12a, only one factor was derived with Kaiser-Meyer Olkin result
of .730. The Bartlett’s test of sphericity was significant at X2 (3, N=347) = 590.668,
p<.05. The factor was adequate for extraction of the component since Kaiser-Meyer-
Olkin Measure was greater than .60 and the Bartlett’s test was significant (p<.05).
Table 4.12a: KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .730
Bartlett's Test of Sphericity Approx. Chi-square 590.668
df 3
Sig. .000
* Significant at p<0.05 level
Using the Principal component analysis, the total variance explained on the extraction
showed the extracted values presented 81% of the component. Only one component was
extracted ‘individualized consideration on job satisfaction’. Further, average value
principle was used to obtain the measure of the extracted independent variable named
‘individualized consideration on job satisfaction’ by transformation. Table 4.12b shows
the results of the variance explained.
Table 4.12b: Total Variance Explained for Individualized Consideration
Component
Initial Eigenvalues
Extraction Sums of Squared
Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance Cumulative %
1 2.439 81.315 81.315 2.439 81.315 81.315
2 .350 11.669 92.984
3 .210 7.016 100.000
Extraction Method: Principal Component Analysis.
The variables of the extracted components are indicated on the component matrix table.
Only one factor was extracted representing ‘individualized consideration on job
119
satisfaction’. The variables extracted and values were: ‘I am committed to the
organization because my leader mentors me in the workplace’ had a component matrix
value of .909; ‘I am hardly absent from work because my leader supports me in my work’
had a component matrix value of .923 and lastly, ‘I have no intentions of leaving my job
because my leader delegates work to me’ had a component matrix value of .873. All the
variables and component measure under the factor loading were greater than .60. Further,
using the average of the components, the transformed data had a stronger component of
.902 which was greater than .60. All the components of dependent variables were
included as variable of analysis in the model as ‘individualized consideration on job
satisfaction’ since the values were greater than .60. Table 4.12c shows the component
matrix for individualized consideration.
Table 4.12c: Component Matrix of Individualized Consideration on Job Satisfaction
Individualized Consideration
Component
1
I am committed to the organization because my leader mentors me in the
workplace .909
I am hardly absent from work because my leader supports me in my work .923
I have no intentions of leaving my job because my leader delegates work to
me .873
Extraction Method: Principal Component Analysis.
a. 1 component extracted.
4.4.2 Descriptive Statistics for Individualized Consideration
On individualized consideration, majority of the respondents agreed on attribute ‘my
leader delegates work to me’ (M= 4.2, SD = .774) followed by ‘my leader supports me in
my work’ (M= 4.0, SD = .900). This clearly showed the difference, with the decrease in
mean, the standard deviation increased which means there were varied responses. Table
4.13 shows the results of the descriptive statistics of individualized consideration. On job
satisfaction, majority of the respondents agreed on the attribute, ‘I am committed to the
organization because my leader mentors me in the workplace’ (M= 3.29, SD = 1.19). This
was followed by ‘I am hardly absent from work because my leader supports me in my
work’ (M= 3.27, SD = 1.14). The trend of the mean and standard deviation was on the
opposite direction indicating varied responses as indicated in Table 4.13.
120
Table 4.13: Mean and Standard Deviation of Individualized Consideration
Individualized Consideration M SD Skewness Std
Error
My leader mentors me in the workplace 3.7637 1.07873 -.824 .131
My leader supports me in my work 4.0202 .90096 -1.137 .131
My leader delegates work to me 4.1902 .77431 -1.282 .131
Influence of Individualized Consideration on Job Satisfaction
I am committed to the organization because my
leader mentors me in the workplace
3.2911 1.18712 -.287 .131
I am hardly absent from work because my leader
supports me in my work
3.2795 1.14786 -.344 .131
I have no intentions of leaving my job because my
leader delegates work to me
2.9308 1.20972 -.005 .131
4.4.3 Chi-square Test on Individualized Consideration and Job Satisfaction
The Chi-square test was used to determine whether there was a significant association
between individualized consideration and job satisfaction. The chi-square test results
showed that there was a significant association between individualized consideration and
job satisfaction X2 (132, N = 347) = 385.123, p<.05) as shown in Table 4.14.
Table 4.14: Chi-square Test on Individualized Consideration and Job Satisfaction
Individualized consideration Value df Asymp. Sig. (2-sided)
Pearson Chi-square 385.123a 132 .000
Likelihood Ratio 296.020 132 .000
Linear-by-Linear Association 122.398 1 .000
N of Valid Cases 347
a. 136 cells (87.2%) have expected count less than 5. The minimum expected count is
.01.
* Significant at p<0.05 level
4.4.4 Correlation Analysis between Individualized Consideration and Job
Satisfaction
Correlation analysis was used to test the relationship between the individualized
consideration variables and job satisfaction. As shown in Table 4.15a, all the variables
121
were highly correlated. The first variable under idealized influence ‘my leader mentors
me in the workplace’ was positively correlated with job satisfaction r (347) =.872, p<.05;
‘my leader supports me in my work’ was positively correlated with job satisfaction r
(347) =.876, p<.05; and ‘my leader delegates work to me’ was positively correlated with
job satisfaction r (347) =.734, p<.05.
Table 4.15a: Correlation Analysis between Individualized Consideration Variables
and Job Satisfaction
Individualized Consideration Pearson Correlation Job Satisfaction
My leader mentors me in the
workplace
Pearson Correlation .872**
Sig. (2-tailed) .000
N 347
My leader supports me in my work Pearson Correlation .876**
Sig. (2-tailed) .000
N 347
My leader delegates work to me Pearson Correlation .734**
Sig. (2-tailed) .000
N 347
* Significant at p<0.05 level
Further, correlation analysis was used to test the relationship between individualized
consideration and job satisfaction. The results showed that there was strong and positive
correlation between individualized consideration and job satisfaction r (347) =.595,
p<.05. The results are shown in Table 4.15b.
Table 4.15b: Correlation Analysis between Individualized Consideration and Job
Satisfaction
Job Satisfaction
Individualized
Consideration
Pearson Correlation .595**
Sig. (2-tailed) .000
N 347
* Significant at p<0.05 level
122
4.4.5 One-Way ANOVA on Individualized Consideration
The One-way ANOVA test was performed to test the mean difference between
individualized consideration and the demographic information of respondents; gender,
age, education level, duration of working at the bank and the tier of the bank. Table 4.16a
shows the results which indicate there was no significant difference between the mean
values of all the respondents’ demographic information and individualized consideration.
Table 4.16a: One-way ANOVA on Individualized Consideration
Sum of
Squares df
Mean
Square F Sig.
Gender Between Groups 4.020 11 .365 1.484 .136
Within Groups 82.021 333 .246
Total 86.041 344
Age Between Groups 3.713 11 .338 .552 .867
Within Groups 203.122 332 .612
Total 206.834 343
Education Between Groups 6.285 11 .571 1.469 .142
Within Groups 129.558 333 .389
Total 135.843 344
How long
have you
worked
Between Groups 17.074 11 1.552 1.285 .232
Within Groups 403.528 334 1.208
Total 420.601 345
Tier of your
bank
Between Groups 5.789 11 .526 .929 .512
Within Groups 189.704 335 .566
Total 195.493 346
* Significant at p<0.05 level
The One-way ANOVA test was also performed to test the mean differences between job
satisfaction and the demographic factors of gender, age, education, duration of working at
the bank and tier of the bank. Table 4.16b shows the results which indicate that there was
123
no significant difference between the mean values of the demographic variables of gender
and tier of the bank with job satisfaction. However, the means for job satisfaction were
significantly different across the age, education and number of years worked.
Table 4.16b: One-way ANOVA of Individualized Consideration on Job Satisfaction
Sum of
Squares
df Mean
Square
F Sig.
Gender
Between Groups 2.796 12 .233 .929 .518
Within Groups 83.245 332 .251
Total 86.041 344
Age
Between Groups 13.382 12 1.115 1.908 .033
Within Groups 193.452 331 .584
Total 206.834 343
Education
Between Groups 8.682 12 .723 1.889 .035
Within Groups 127.162 332 .383
Total 135.843 344
How long
have you
worked
Between Groups 28.751 12 2.396 2.036 .021
Within Groups 391.850 333 1.177
Total 420.601 345
Tier of
your bank
Between Groups 5.702 12 .475 .836 .613
Within Groups 189.791 334 .568
Total 195.493 346
* Significant at p<0.05 level
4.4.6 Regression Analysis and Hypothesis Testing
This section presents the regression analysis, the model used for hypothesis testing in the
study and the assumptions for the regression. The regression analysis was done to
determine the relationship, magnitude of the influence and projection of the effect of
individualized consideration on job satisfaction among employees in commercial banks in
Kenya.
124
4.4.6.1 Assumptions for Regression Analysis on Individualized Consideration
Before running the regression analysis, assumptions for regression were tested. The
following tests were conducted: normality test, linearity test, homoscedasticity test and
multicollinearity tests as presented hereunder.
4.4.6.1.1 Normality Test on Individualized Consideration
Using one sample Kolmogorov-Smirnov Test, the test of normality was conducted to
determine the distribution of data depicting either a normal or skewed curve. This was
determined by the statistical significance of the dependent and the independent variable
(p<.05). The normal parameters test indicated difference on mean: individualized
consideration had (M= 3.99, SD = .766) compared to Job satisfaction (M= 3.18, SD =
1.06). The variance on the mean was low compared to the standard deviation variance
which was high. Further, the output showed the variance on the most extreme differences
was minimal and the variables were significant to each other (p<.05) indicating high level
of relationship hence the data was not normally distributed (p<.05). Table 4.17a indicates
the results of normality test.
Table 4.17a: One-Sample Kolmogorov-Smirnov Test on Individualized
Consideration
Individualized
concentration
Individualized
concentration on Job
satisfaction
N 347 347
Normal Parametersa,b Mean 3.9914 3.1671
Std. Deviation .76592 1.06481
Most Extreme Differences Absolute .173 .115
Positive .101 .083
Negative -.173 -.115
Test Statistic .173 .115
Asymp. Sig. (2-tailed) .000c .000c
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.
* Significant at p<0.05 level
125
4.4.6.1.2 Linearity Test on Individualized Consideration
The analysis of variance (ANOVA) was used to determine linearity. The linearity test was
conducted to determine whether the nature of the relationship between individualized
consideration and job satisfaction was linear or not. As indicated in Table 4.17b, the
output indicated a significant relationship between individualized concentration and job
satisfaction on the combined and linearity tests (p<.05). However, the deviation from
linearity was not significant. Hence individualized concentration and job satisfaction were
linear and passed the test of linearity.
Table 4.17b: Linearity Test on Individualized Concentration
Sum of
Squares df
Mean
Square F Sig.
Job
Satisfaction *
Individualized
concentration
Between
Groups
(Combined) 144.353 11 13.123 17.730 .000
Linearity 138.779 1 138.779 187.500 .000
Deviation
from Linearity 5.575 10 .557 .753 .674
Within Groups 247.952 335 .740
Total 392.305 346
* Significant at p<0.05 level
4.4.6.1.3 Multicollinearity Test on Individualized Consideration
Multicollinearity test was performed to determine if the values of individualized
consideration and job satisfaction had high similarity. The test of multicollinearity was
analyzed by the variance inflation factor (VIF); statistically, there was no
multicollinearity when the value of VIF between 1 and 10. As indicated in Table 4.17c,
the VIF value was 1.210 shows there was no multicollinearity between individualized
consideration and job satisfaction.
126
Table 4.17c: Multicollinearity Test on Individualized Consideration
Model
Unstandardized
Coefficients
Standardized
Coefficients
T Sig.
Collinearity
Statistics
B
Std.
Error Beta Tolerance VIF
1 (Constant) 2.627 .110 23.957 .000
Job Satisfaction .426 .032 .577 13.127 .000 1.210 1.210
4.4.6.1.4 Homoscedasticity Test on Individualized Consideration
Homoscedasticity test was carried out to determine if individualized consideration of the
bank employees had similar variance to job satisfaction on the regression values. As
indicated on Table 4.17d, the results indicate that the value of the Levene Statistic, F(10,
335) = 1.84, p = .053 was above the study’s level of significance (p ≤ .05) indicating the
data was homogenous.
Table 4.17d: Homoscedasticity Test on Individualized Consideration
Levene Statistic df1 df2 Sig.
1.837 10 335 .053
* Significant at p<0.05 level
4.4.6.2 Regression and Hypothesis Testing on Individualized Consideration
Regression analysis was carried out to determine the extent to which individualized
consideration influenced job satisfaction among employees in commercial banks in
Kenya. Multiple linear regression was used to predict job satisfaction among employees
in commercial banks in Kenya from individualized consideration. The hypothesis tested
was:
H02: There is no significant influence of individualized consideration on job satisfaction
among employees in commercial banks in Kenya
The regression results for the hypothesis testing were presented in form of the model
summary, regression ANOVA and regression coefficient.
127
4.4.6.2.1 Regression Model Summary
The model summary results presented in Table 4.18 indicate that individualized
consideration explained 35% of job satisfaction among employees in commercial banks
in Kenya (R2) = .354.
Table 4.18: Model Summary of Individualized Consideration on Job Satisfaction
Model R
R
Square
Adjusted
R Square
Std.
Error of
the
Estimate
Change Statistics
R Square
Change
F
Change df1 df2
Sig. F
Change
1 .595a .354 .352 .85724 .354 188.851 1 345 .000
a. Predictors: (Constant), Individualized Consideration
* Significant at p<0.05 level
4.4.6.2.2 Regression ANOVA
The regression ANOVA showed that idealized influence had a significant influence on
job satisfaction F(1, 97.750) = 112.421, p<.05) as indicated Table 4.19.
The regression ANOVA revealed that individualized consideration had a significant
influence on job satisfaction F(1, 138.779) = 188.851, p<.05) as indicated in Table 4.19.
This means that the regression model constructed was suitable for predicting the outcome
variable on how individualized consideration influenced job satisfaction among
employees in commercial banks in Kenya.
Table 4.19: Regression ANOVA of Individualized Consideration on Job Satisfaction
Model Sum of Squares df Mean Square F Sig.
1 Regression 138.779 1 138.779 188.851 .000b
Residual 253.527 345 .735
Total 392.305 346
a. Dependent Variable: Job Satisfaction
b. Predictors: (Constant), Individualized Consideration
* Significant at p<0.05 level
128
4.4.6.2.3 Regression Coefficient of Individualized Consideration
Table 4.20 shows the output of the regression coefficient. In the regression coefficient
model, the analysis showed that individualized consideration statistically predicted job
satisfaction (β = .827, (-.545) t = 13.742, p<.05). The beta weight gauges the importance
of the explanatory variable across the model and was positive on the individualized
consideration, Beta of .827 and statistically significant at p<.05. This means a unit
increase in individualized consideration increases the unit of job satisfaction by .827.
Table 4.20: Coefficients of Individualized Consideration on Job Satisfaction
Model
Unstandardized
Coefficients
Standardized
Coefficients
T Sig. B Std. Error Beta
1 (Constant) -.133 .245 -.545 .586
Individualized
Concentration .827 .060 .595 13.742 .000
a. Dependent Variable: Job Satisfaction
* Significant at p<0.05 level
From the coefficient table, the values of the regression model were derived:
The general form of the regression model used was:
= Constant; = individualized consideration and = Error term.
From the coefficient table, individualized consideration influences job satisfaction among
employees in commercial banks in Kenya.
Y= -.133 + .827X + .060
The multiple linear regression analysis was used to test if individualized consideration
significantly predicted job satisfaction among employees in commercial banks in Kenya.
The results revealed individualized consideration explained 35% of job satisfaction (R2 =
.354, F(1, 138.779) = 188.851, p<.05) while the remaining 65% of job satisfaction was
explained by other factors. Further, individualized consideration significantly predicted
job satisfaction (β = .827, (-.545) t = 13.742, p<.05). Therefore, the study rejected the null
129
hypothesis H02: There is no significant influence of individualized consideration on job
satisfaction among employees in commercial banks in Kenya and accepted the alternate
hypothesis, H12: There is a significant influence of individualized consideration on job
satisfaction among employees in commercial banks in Kenya.
4.5 Influence of Inspirational Motivation on Job Satisfaction
The third objective in this research was to determine the influence of inspirational
motivation on job satisfaction. This was guided by the independent variable questions on
inspirational motivation and dependent variable questions on job satisfaction. The
independent variable questions were: my leader encourages two-way communication; my
leader promotes teamwork among employees; and my leader’s behavior motivates me at
work. The dependent variable questions on job satisfaction were: I am committed to the
organization because my leader encourages two-way communication, I am hardly absent
from work because my leader promotes teamwork among employees and lastly, I have no
intentions of leaving my job because my leader’s behavior motivates me at work, the
findings are presented as shown below.
4.5.1 Factor Analysis
Factor analysis was used to evaluate the variability among the observed correlated
variables to ensure the questions in the research instrument relate to the construct of
measure. Questions that did not relate to construct were extracted from the analysis.
Factor analysis was conducted on three questions for dependent variable ‘job satisfaction’
and three questions for independent variable ‘inspirational motivation’ presented
separately as follow.
4.5.1.1 Factor Analysis on Inspiration Motivation
The independent variable in this study was inspirational motivation. As indicated in Table
4.21a, only one factor was derived with Kaiser-Meyer Olkin result of .747. The Bartlett’s
test of sphericity was significant at X2 (3, N=347) = 608.536, p<.05. The factor was
adequate for extraction of component since Kaiser-Meyer-Olkin Measure was greater
than .60 and the Bartlett’s test was significant (p<.05).
130
Table 4.21a: KMO and Bartlett's Test on Inspirational Motivation
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .747
Bartlett's Test of Sphericity Approx. Chi-square 608.536
df 3
Sig. .000
* Significant at p<0.05 level
Using the Principal component analysis, the total variance explained on the extraction
showed the extracted values presented 83% of the first component. Only one component
was extracted ‘inspiration motivation’. Further, average value principle was used to
obtain the measure of the extracted independent variable by transformation. Table 4.21b
shows the results of the variance explained.
Table 4.21b: Total Variance Explained for Inspirational Motivation
Componen
t
Initial Eigenvalues
Extraction Sums of Squared
Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
%
1 2.477 82.559 82.559 2.477 82.559 82.559
2 .293 9.753 92.312
3 .231 7.688 100.000
Extraction Method: Principal Component Analysis.
One component for inspirational motivation had an Eigen value that was greater than one
which was in line with the results for total variance explained for inspirational motivation
as shown in Figure 4.8.
131
Figure 4.8: Scree Plot for Inspirational Motivation
The variables of the extracted components are indicated on the component matrix Table
4.21c. Only one factor was extracted representing ‘inspirational motivation’. The
variables extracted and values were: my leader encourages two-way communication
(.897), my leader promotes teamwork among employees (.919), and my leader’s behavior
motivates me at work (.909). All the variables and component measure under the factor
loading were greater than .60. Further, using the average of the components, the
transformed data had a stronger component of .908 which was greater than .60. All the
components were included as variables of analysis in the model ‘inspirational motivation’
since the values were greater than .60.
Table 4.21c: Component Matrix on Inspirational Motivation
Inspirational Motivation
Component
1
My leader encourages two-way communication .897
My leader promotes teamwork among employees .919
My leader’s behavior motivates me at work .909
Extraction Method: Principal Component Analysis.
a. 1 component extracted.
132
4.5.1.2 Factor Analysis on Inspirational Motivation and Job Satisfaction
The dependent variable in the study was influence of inspirational motivation on job
satisfaction. As indicated in Table 4.22a, only one factor was derived with Kaiser-Meyer
Olkin result of .75. The Bartlett’s test of sphericity was significant at X2 (3, N=347) =
685.906, p<.05. The factor was adequate for extraction of the component since Kaiser-
Meyer-Olkin Measure was greater than .60 and the Bartlett’s test was significant (p<.05).
Table 4.22a: KMO and Bartlett's Test Inspirational Motivation and Job Satisfaction
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .750
Bartlett's Test of Sphericity Approx. Chi-square 685.906
df 3
Sig. .000
* Significant at p<0.05 level
Using the Principal component analysis, the total variance explained on the extraction
showed the extracted values presented 84% of the component. Only one component was
extracted ‘inspirational motivation on job satisfaction’. Further, the average value
principle was used to obtain the measure of the extracted independent variable named
‘inspirational motivation on job satisfaction’ by transformation. Table 4.22b shows the
results of the variance explained.
Table 4.22b: Total Variance Explained for Inspirational motivation on Job
Satisfaction
Component
Initial Eigenvalues
Extraction Sums of Squared
Loadings
Total
% of
Variance Cumulative % Total
% of
Variance
Cumulative
%
1 2.529 84.313 84.313 2.529 84.313 84.313
2 .274 9.128 93.441
3 .197 6.559 100.000
Extraction Method: Principal Component Analysis.
133
The variables of the extracted components were indicated on the component matrix table.
Only one factor was extracted representing ‘inspirational motivation on job satisfaction’.
The variables extracted and values were; I am committed to the organization because my
leader encourages two-way communication had a component matrix value of .918; I am
hardly absent from work because my leader promotes teamwork among employees had a
component matrix value of. 932 and lastly; I have no intentions of leaving my job because
my leader’s behavior motivates me at work had a component matrix value of .905. All the
variables and component measure under the factor loading were greater than .60. Further,
using the average of the components, the transformed data has a stronger component of
.918 which is greater than .60. This means all the components of the independent variable
were included as variables of analysis in the model as ‘inspirational motivation on job
satisfaction’ since the values were greater than .60. Table 4.22c shows the component
matrix of inspirational motivation on job satisfaction.
Table 4.22c: Component Matrix on Inspirational Motivation and Job Satisfaction
Inspirational Motivation on Job Satisfaction
Component
1
I am committed to the organization because my leader encourages
two-way communication .918
I am hardly absent from work because my leader promotes
teamwork among employees .932
I have no intentions of leaving my job because my leader’s behavior
motivates me at work .905
Extraction Method: Principal Component Analysis.
a. 1 components extracted.
4.5.2 Descriptive Statistics for Inspirational Motivation
On inspirational motivation, majority of the respondents agreed on the attribute ‘my
leader promotes teamwork among employees’ (M= 4.12, SD = .92), followed by ‘my
leader encourages two-way communication’ (M= 4.08, SD = .92). This clearly shows the
difference; with decrease in mean, the standard deviation increased indicating varied
responses. Table 4.23 indicates the results of the descriptive statistics of inspirational
motivation. On job satisfaction, majority of the respondents agreed that ‘I am committed
to the organization because my leader encourages two-way communication’ (M= 3.41,
SD = 1.10). This was followed by ‘I am hardly absent from work because my leader
134
promotes teamwork among employees’ (M= 3.23, SD = 1.09. The trend of the mean and
standard deviation varied depicting varied responses as indicated in Table 4.23.
Table 4.23: Mean and Standard Deviation of Inspirational Motivation
Inspirational Motivation M SD Skewness Std Err
My leader encourages two-way communication 4.0807 .91825 -1.219 .131
My leader promotes teamwork among
employees 4.1210 .92323 -1.262 .131
My leader’s behavior motivates me at work 3.8542 1.05230 -.917 .132
Inspirational Motivations on Job
Satisfaction
I am committed to the organization because my
leader encourages two-way communication 3.4150 1.10992 -.467 .131
I am always present at work because my leader
promotes teamwork among employees 3.2305 1.09063 -.240 .131
I have no intentions of leaving my job because
my leader’s behavior motivates me at work 3.0490 1.16570 -.063 .131
4.5.3 Chi-square Test: Inspirational Motivation and Job Satisfaction
The Chi-square test was used to determine whether there was a significant association
between inspirational motivation and job satisfaction. The chi-square test results showed
that there was as significant association between inspirational motivation and job
satisfaction X2 (156, N = 347) = 445.180, p<.05). The results are presented in Table 4.24.
Table 4.24: Chi-square Test on Inspirational Motivation and Job Satisfaction
Inspirational Motivation Value df Asymp. Sig. (2-sided)
Pearson Chi-square 445.180a 156 .000
Likelihood Ratio 312.954 156 .000
Linear-by-Linear Association 119.052 1 .000
N of Valid Cases 347
a. 163 cells (89.6%) have expected count less than 5. The minimum expected count is .02.
* Significant at p<0.05 level
135
4.5.4 Correlation Analysis between Inspirational Motivation and Job Satisfaction
Correlation analysis was used to test the relationship between the inspirational motivation
variables and job satisfaction. As shown in Table 4.25a, all the variables were highly
correlated. The first variable under inspirational motivation ‘my leader encourages two-
way communication’ was positively correlated with job satisfaction r (347) =.893, p<.05;
‘my leader promotes teamwork among employees’ was positively correlated with job
satisfaction r (347) =.915, p<.05; and ‘my leader’s behavior motivates me at work’ was
positively correlated with job satisfaction r (347) =.917, p<.05.
Table 4.25a: Correlation Analysis between Inspirational Motivation Variables and
Job Satisfaction
Inspirational Motivation Pearson Correlation Job Satisfaction
My leader encourages two-way
communication
Pearson Correlation .893**
Sig. (2-tailed) .000
N 347
My leader promotes teamwork among
employees
Pearson Correlation .915**
Sig. (2-tailed) .000
N 347
My leader’s behavior motivates me at
work
Pearson Correlation .917**
Sig. (2-tailed) .000
N 347
* Significant at p<0.05 level
Further, correlation analysis was used to test the relationship between inspirational
motivation and job satisfaction. The results show that there was a strong and positive
correlation between inspirational motivation and job satisfaction r (347) =.587, p<.05.
The results are as shown in Table 4.25b.
Table 4.25b: Correlation Analysis between Inspirational Motivation and Job
Satisfaction
Job Satisfaction
Inspirational Motivation Pearson Correlation .587**
Sig. (2-tailed) .000
N 347
* Significant at p<0.05 level
136
4.5.5 One-Way ANOVA on Inspirational Motivation
The One-way ANOVA test was performed to test the mean difference between
inspirational motivation and the demographic information of respondents; gender, age,
education level, duration of working at the bank and the tier of the bank. Table 4.26a
shows the results which indicate that there was no significant difference between the
mean values of all the respondents’ demographic information and inspirational
motivation.
Table 4.26a: One-way ANOVA on Inspirational Motivation
Sum of
Squares df Mean Square F Sig.
Gender Between Groups 4.328 13 .333 1.349 .183
Within Groups 81.712 331 .247
Total 86.041 344
Age Between Groups 4.501 13 .346 .565 .881
Within Groups 202.333 330 .613
Total 206.834 343
Education Between Groups 4.072 13 .313 .787 .674
Within Groups 131.771 331 .398
Total 135.843 344
How long
have you
worked
Between Groups 15.776 13 1.214 .995 .455
Within Groups 404.825 332 1.219
Total 420.601 345
Tier of your
bank
Between Groups 11.005 13 .847 1.528 .105
Within Groups 184.488 333 .554
Total 195.493 346
* Significant at p<0.05 level
137
The One-way ANOVA test was also performed to test the mean differences between job
satisfaction and the demographic factors of gender, age, education, duration of working at
the bank and tier of the bank. Table 4.26b shows the results which indicate that there was
no significant difference between the mean values of the demographic variables on
inspirational motivation and job satisfaction.
Table 4.26b: One-way ANOVA of Inspirational Motivation on Job Satisfaction
Sum of
Squares
df Mean
Square
F Sig.
Gender
Between
Groups 2.985 12 .249 .994 .454
Within
Groups 83.055 332 .250
Total 86.041 344
Age
Between
Groups 7.091 12 .591 .979 .468
Within
Groups 199.743 331 .603
Total 206.834 343
Education
Between
Groups 6.501 12 .542 1.391 .168
Within
Groups 129.343 332 .390
Total 135.843 344
How long have you
worked
Between
Groups 18.449 12 1.537 1.273 .233
Within
Groups 402.152 333 1.208
Total 420.601 345
Tier of your bank
Between
Groups 4.348 12 .362 .633 .814
Within
Groups 191.145 334 .572
Total 195.493 346
* Significant at p<0.05 level
4.5.6 Regression Analysis and Hypothesis Testing
This section presents the regression analysis, the model used for hypothesis testing in the
study and the assumptions for the regression. The regression analysis was done to
determine the relationship, magnitude of the effect and projection of the effect of
inspirational motivation on job satisfaction among employees in commercial banks in
Kenya.
138
4.5.6.1 Assumptions for Regression Analysis on Inspirational Motivation
Before running the regression analysis, assumptions for regression were tested. The
following tests were conducted: normality test, linearity test, homoscedasticity test and
multicollinearity tests as presented below.
4.5.6.1.1 Normality Test on Inspirational Motivation
Using one sample Kolmogorov-Smirnov Test, the test of normality was conducted to
determine the distribution of data depicting either normal or skewed curve. This was
determined by statistical significance of the dependent and the independent variable
(p<.05). The normal parameters test indicated a difference on mean: inspirational
motivation had (M= 4.02, SD = .876) compared to Job satisfaction (M= 3.23, SD = 1.03).
The variance on the mean was low compared to the standard deviation variance which
was high. Further, the output showed the variance on the most extreme differences was
minimal and the variables were significant to each other (p<.05) indicating high level of
relationship hence the data was not normally distributed (p<.05). Table 4.27a shows the
output of the normality test.
Table 4.27a: One-Sample Kolmogorov-Smirnov Test on Inspirational Motivation
Inspirational
motivation
Inspirational
motivation on
Job Satisfaction
N 347 347
Normal Parametersa,b Mean 4.0216 3.2315
Std. Deviation .87640 1.03000
Most Extreme Differences Absolute .185 .126
Positive .132 .075
Negative -.185 -.126
Test Statistic .185 .126
Asymp. Sig. (2-tailed) .000c .000c
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.
* Significant at p<0.05 level
139
4.5.6.1.2 Linearity Test on Inspirational Motivation
The analysis of variance (ANOVA) was used to determine linearity. The linearity test was
conducted to determine the nature of the relationship between inspirational motivation
and job satisfaction whether linear or not. As indicated in Table 4.27b, there was a
significant relationship between inspirational motivation and job satisfaction on the
combined and linearity tests (p<.05). However, the deviation from linearity was not
significant. Hence inspirational motivation and job satisfaction were linear and passed the
test of linearity.
Table 4.27b: Linearity Test on Inspirational Motivation
Sum of
Squares Df
Mean
Square F Sig.
Inspirational
motivation on
Job Satisfaction
* Inspirational
motivation
Between
Groups
(Combined) 134.195 13 10.323 14.761 .000
Linearity 126.302 1 126.302 180.606 .000
Deviation
from Linearity 7.893 12 .658 .941 .506
Within Groups 232.874 333 .699
Total 367.069 346
* Significant at p<0.05 level
4.5.6.1.3 Multicollinearity Test on Inspirational Motivation
Multicollinearity test was performed to determine if the values of inspirational motivation
and job satisfaction had higher similarity. The test of multicollinearity was tested using
the variance inflation factor (VIF); statistically, there was no multicollinearity when the
value of VIF between 1 and 10. As indicated in Table 4.27c, the VIF value was 2.260
which showed that there was no multicollinearity between inspirational motivation and
job satisfaction.
140
Table 4.27c: Multicollinearity Test on Inspirational Motivation
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
Collinearity
Statistics
B
Std.
Error Beta Tolerance VIF
1 (Constant) .459 .211 2.177 .030
Inspirational
motivation .689 .051 .587 13.453 .000 2.260 2.260
4.5.6.1.4 Homoscedasticity Test on Inspirational Motivation
Homoscedasticity test was carried out to determine if inspirational motivation of the bank
employees had similar variance to job satisfaction on the regression values. As indicated
on Table 4.27d, results indicate that the value of the Levene Statistic, F(12, 333) = 3.25,
p = .00 was above the study’s level of significance (p ≤ .05) indicating the data was not
homogenous.
Table 4.27d: Homoscedasticity Test on Inspirational Motivation
Levene Statistic df1 df2 Sig.
3.248 12 333 .000
* Significant at p<0.05 level
4.5.6.2 Regression and Hypothesis Testing on Inspirational Motivation
Regression analysis was carried out to determine the extent to which inspirational
motivation influenced job satisfaction among employees in commercial banks in Kenya.
Multiple linear regression was used to predict job satisfaction among employees in
commercial banks in Kenya from inspirational motivation. The hypothesis tested was:
H03: There is no significant influence of inspirational motivation on job satisfaction
among employees in commercial banks in Kenya
The regression results for the hypothesis testing were presented in the form of the model
summary, regression ANOVA and regression coefficient.
141
4.5.6.2.1 Regression Model Summary
The model summary results presented in Table 4.28 indicate that inspirational motivation
explained 34% of job satisfaction of employees in commercial banks in Kenya (R2) =
.344.
Table 4.28: Model Summary on Inspirational Motivation and Job Satisfaction
Model R
R
Square
Adjusted
R
Square
Std.
Error of
the
Estimate
Change Statistics
R
Square
Change
F
Change df1 df2
Sig. F
Change
1 .587a .344 .342 .83539 .344 180.980 1 345 .000
a. Predictors: (Constant), Inspirational motivation
* Significant at p<0.05 level
4.5.6.2.2 Regression ANOVA
The regression ANOVA showed that inspirational motivation had a significant influence
on job satisfaction F(1, 126.302) = 180.980, p<.05) as indicated in Table 4.29. This
showed the regression model constructed was suitable in predicting the outcome variable
on how inspirational motivation influenced job satisfaction among employees in
commercial banks in Kenya.
Table 4.29: ANOVA for Inspirational Motivation and Job Satisfaction
Model
Sum of
Squares df Mean Square F Sig.
1 Regression 126.302 1 126.302 180.980 .000b
Residual 240.767 345 .698
Total 367.069 346
a. Dependent Variable: Inspirational motivation on Job Satisfaction
b. Predictors: (Constant), Inspirational motivation
* Significant at p<0.05 level
4.5.6.2.3 Regression Coefficient of Inspirational Motivation
Table 4.30 shows the results of the regression coefficient. In the regression coefficient
model, the analysis showed inspirational motivation statistically predicted job satisfaction
142
(β = .689, (2.117) t = 13.453, p<.05). The beta weight gauges the importance of
explanatory variable across the model and was positive on the inspirational motivation,
Beta of .689 and statistically significant at p<.05. This means, one unit of increase in
inspirational motivation increased the unit of satisfaction by .689.
Table 4.30: Coefficients of Inspirational Motivation on Job Satisfaction
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig. B Std. Error Beta
1 (Constant) .459 .211 2.177 .030
Inspirational
motivation .689 .051 .587 13.453 .000
a. Dependent Variable: Inspirational motivation on Job Satisfaction
* Significant at p<0.05 level
From the coefficient table, the values of the regression model were derived:
The general form of the regression model used was:
= Constant; = Inspirational Motivation and = Error term.
From the coefficient table, inspirational motivation influenced job satisfaction among
employees in commercial banks in Kenya.
Y= 0.459 + .689X +.051
Multiple linear regression analysis was used to test if inspirational motivation
significantly predicted job satisfaction among employees in commercial banks in Kenya.
The results revealed that inspirational motivation explained 34% of the job satisfaction
(R2 = .344, F(1, 126.302) = 180.980, p<.05) while the remaining 66% of job satisfaction
was explained by other factors. Further, inspirational motivation significantly predicted
job satisfaction (β = .689, (2.117) t = 13.453, p<.05). Therefore, the study rejected the
null hypothesis H03: There is no significant influence of inspirational motivation on job
satisfaction among employees in commercial banks in Kenya and accepted the alternate
hypothesis, H12: There is a significant influence of inspirational motivation on job
satisfaction among employees in commercial banks in Kenya.
143
4.6 Influence of Intellectual Stimulation on Job Satisfaction
The fourth objective in this study was to determine the influence of intellectual
stimulation on job satisfaction. This was guided by the independent variable questions on
intellectual stimulation and dependent variable questions on job satisfaction. The
independent variable questions were: my leader encourages knowledge sharing among
employees; my leader permits me to be creative in my job and; my leader allows me to
take risks in my job. The dependent variable questions were: I am committed to the
organization because my leader encourages knowledge sharing among employees; I am
hardly absent from work because my leader permits me to be creative in my job; and I
have no intentions of leaving my job because my leader allows me to take risks in my job.
The findings are presented as follows.
4.6.1 Factor Analysis
Factor analysis was used to evaluate the variability among the observed correlated
variables to ensure the questions in the research instrument relate to the construct of
measure. Questions that did not relate to construct were extracted from the analysis.
Factor analysis was conducted on three questions for dependent variable ‘intellectual
stimulation’ and three questions on independent variable ‘intellectual stimulation’
presented separately as shown below.
4.6.1.1 Factor Analysis on Intellectual Stimulation
The independent variable in study was intellectual stimulation. As indicated in Table
4.31a, only one factor was derived with Kaiser-Meyer Olkin result of .712. The Bartlett’s
test of sphericity was significant at X2 (3, N=347) = 460.533, p<.05. The factor was
adequate for extraction of component since Kaiser-Meyer-Olkin Measure was greater
than .60 and the Bartlett’s test was significant (p<.05).
Table 4.31a: KMO and Bartlett's Test on Intellectual Stimulation
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .712
Bartlett's Test of Sphericity Approx. Chi-square 460.533
df 3
Sig. .000
* Significant at p<0.05 level
144
Using the Principal component analysis, the total variance explained on the extraction
showed that the extracted values presented 77% of the first component. Only one
component was extracted ‘intellectual stimulation’. Further, the average value principle
was used to obtain the measure of the extracted independent variable by transformation.
Table 4.31b shows the results of the variance explained.
Table 4.31b: Total Variance Explained for Intellectual Stimulation
Component
Initial Eigen values
Extraction Sums of Squared
Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
%
1 2.310 77.010 77.010 2.310 77.010 77.010
2 .418 13.938 90.948
3 .272 9.052 100.000
Extraction Method: Principal Component Analysis
The variables of the extracted components are indicated on the component matrix table.
Only one factor was extracted representing ‘intellectual stimulation’. The variables and
values extracted were: ‘my leader encourages knowledge sharing among employees’
(.859), ‘my leader permits me to be creative in my job’ (.908); and ‘my leader allows me
to take risks in my job’ (.864). All variables and component measure under the factor
loading were greater than .60. Further, using the average of the components, the
transformed data had a stronger component of .877 which is greater than .60. All the
components were included as variables of analysis in the model ‘intellectual stimulation’
since the values were greater than .60. Table 4.31c shows the component matrix for
intellectual stimulation.
Table 4.31c: Component Matrix on Intellectual Stimulation
Intellectual stimulation Component
1
My leader encourages knowledge sharing among employees .859
My leader permits me to be creative in my job .908
My leader allows me to take risks in my job .864
Extraction Method: Principal Component Analysis.
a. 1 component extracted.
145
4.6.1.2 Factor Analysis on Intellectual Stimulation on Job Satisfaction
The dependent variable in the study was intellectual stimulation on job satisfaction. As
indicated in Table 4.32a, only one factor was derived with Kaiser-Meyer Olkin result of
.733. The Bartlett’s test of sphericity was significant at X2 (3, N=347) = 600.174, p<.05.
This indicated the factor was adequate for extraction of component since Kaiser-Meyer-
Olkin Measure was greater than .60 and the Bartlett’s test was significant (p<.05).
Table 4.32a: KMO and Bartlett's Test on Intellectual Stimulation on Job
Satisfaction
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .733
Bartlett's Test of Sphericity Approx. Chi-square 600.174
df 3
Sig. .000
* Significant at p<0.05 level
Using the Principal component analysis, the total variance explained on the extraction
showed the extracted values presented 82% of the component. Only one component was
extracted ‘intellectual stimulation on job satisfaction’. Further, the average value principle
was used to obtain the measure of the extracted independent variable named ‘intellectual
stimulation on job satisfaction’ by transformation. Table 4.32b shows the results of the
variance explained.
Table 4.32b: Total Variance Explained for Intellectual Stimulation
Component
Initial Eigenvalues
Extraction Sums of Squared
Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
%
1 2.454 81.786 81.786 2.454 81.786 81.786
2 .331 11.046 92.832
3 .215 7.168 100.000
Extraction Method: Principal Component Analysis
146
One component for intellectual stimulation had an Eigen value that was greater than one
which was in line with the results for total variance explained for intellectual stimulation
as shown in Figure 4.9.
Figure 4.9: Scree Plot for Intellectual Stimulation
The variables of the extracted components are indicated on the component matrix table.
Only one factor was extracted representing ‘intellectual stimulation on job satisfaction’.
The variables and values were: ‘I am committed to the organization because my leader
encourages knowledge sharing among employees’ had a component matrix value of .897;
‘I am hardly absent from work because my leader permits me to be creative in my job’
had a component matrix value of. 927 and lastly; ‘I have no intentions of leaving my job
because my leader allows me to take risks in my job’ had a component matrix value of
.889.
All the variables and component measure under the factor loading were greater than .60.
Further, using the average of the components, the transformed data had a stronger
component of .904 which was greater than .60. All the components were included as
variables of analysis in the model as ‘intellectual stimulation’. Table 4.32c shows the
component matrix for intellectual stimulation on job satisfaction.
147
Table 4.32c: Component Matrix on Intellectual Stimulation and Job Satisfaction
Intellectual stimulation on job satisfaction Component
1
I am committed to the organization because my leader encourages
knowledge sharing among employees .897
I am hardly absent from work because my leader permits me to be
creative in my job .927
I have no intentions of leaving my job because my leader allows
me to take risks in my job .889
Extraction Method: Principal Component Analysis.
a. 1 component extracted.
4.6.2 Descriptive Statistics on Intellectual Stimulation
On intellectual stimulation, majority of the respondents agreed on the attribute ‘my leader
encourages knowledge sharing among employees’ (M= 4.13, SD = .86) followed by ‘my
leader permits me to be creative in my job’ (M= 4.0, SD = .94). This clearly showed the
difference; with decrease in mean, the standard deviation increased indicating varied
responses. Table 4.33 shows the results of the descriptive statistics of intellectual
stimulation.
On job satisfaction, majority of the respondents agreed on the attribute ‘I am committed
to the organization because my leader encourages knowledge sharing among employees’
(M= 3.48, SD = 1.11). This was followed by ‘I am hardly absent from work because my
leader permits me to be creative in my job’ (M= 3.31, SD = 1.12). The trend of the mean
and standard deviation indicates variance in responses as presented in Table 4.33.
148
Table 4.33: Mean and Standard Deviation of Intellectual Stimulations
Intellectual Stimulation M SD Skewness Std. Err
My leader encourages knowledge sharing
among employees 4.1326 .86000 -1.273 .131
My leader permits me to be creative in my
job 4.0086 .93884 -1.050 .131
My leader allows me to take risks in my
job 3.5850 1.04555 -.433 .131
Influence of Intellectual Stimulation on Job Satisfaction
I am committed to the organization
because my leader encourages knowledge
sharing among employees
3.4784 1.11297 -.445 .131
I am always present at work because my
leader permits me to be creative in my job 3.3112 1.12305 -.267 .131
I have no intentions of leaving my job
because my leader allows me to take risks
in my job
2.9193 1.16517 .070 .131
4.6.3 Chi-square Test on Intellectual Stimulation and Job Satisfaction
The Chi-square test was used to determine whether there was a significant association
between intellectual stimulation and job satisfaction. The chi-square test showed that
there was a significant association between intellectual stimulation and job satisfaction X2
(144, N = 347) = 426.404, p<.05). The results are presented in Table 4.34.
Table 4.34: Chi-square Test on Intellectual Stimulation and Job Satisfaction
Intellectual Stimulation Value df Asymp. Sig. (2-sided)
Pearson Chi-square 426.404a 144 .000
Likelihood Ratio 314.315 144 .000
Linear-by-Linear Association 101.155 1 .000
N of Valid Cases 347
a. 147 cells (87.0%) have expected count less than 5. The minimum expected count is
.03.
* Significant at p<0.05 level
149
4.6.4 Correlation Analysis between Intellectual Stimulation and Job Satisfaction
Correlation analysis was used to test the relationship between the intellectual stimulation
variables and job satisfaction. As shown in Table 4.35a, all the variables were highly
correlated. The first variable under intellectual stimulation ‘my leader encourages
knowledge sharing among employees’ was positively correlated with job satisfaction r
(347) =.638, p<.05; ‘my leader permits me to be creative in my job’ was positively
correlated with job satisfaction r (347) =.547, p<.05; and ‘my leader allows me to take
risks in my job’ was positively correlated with job satisfaction r (347) =.550, p<.05.
Table 4.35a: Correlation Analysis between Intellectual Stimulation Variables and
Job Satisfaction
Intellectual Stimulation Pearson Correlation Job Satisfaction
My leader encourages knowledge
sharing among employees
Pearson Correlation .638**
Sig. (2-tailed) .000
N 347
My leader permits me to be creative in
my job
Pearson Correlation .547**
Sig. (2-tailed) .000
N 347
My leader allows me to take risks in my
job
Pearson Correlation .550**
Sig. (2-tailed) .000
N 347
* Significant at p<0.05 level
Further, correlation analysis was used to test the relationship between intellectual
stimulation and job satisfaction. The results show there was strong and positive
correlation between intellectual stimulation and job satisfaction r (347) =.541, p<.05. The
results are outlined in Table 4.35b.
Table 4.35b: Correlation Analysis between Intellectual Stimulation and Job
Satisfaction
Job Satisfaction
Intellectual Stimulation Pearson Correlation .541**
Sig. (2-tailed) .000
N 347
* Significant at p<0.05 level
150
4.6.5 One-way ANOVA on Intellectual Stimulation
The One-way ANOVA test was performed to test the mean differences between
intellectual stimulation and the demographic information of respondents; gender, age,
education level, duration of working at the bank and lastly the tier of the bank. Table
4.36a shows the results which indicate there was no significant difference between the
mean values of all the respondents’ demographic information and intellectual stimulation.
Table 4.36a: One-way ANOVA on Intellectual stimulation
Sum of
Squares Df
Mean
Square F Sig.
Gender Between Groups 3.659 12 .305 1.229 .261
Within Groups 82.381 332 .248
Total 86.041 344
Age Between Groups 3.507 12 .292 .476 .928
Within Groups 203.327 331 .614
Total 206.834 343
Education Between Groups 6.618 12 .551 1.417 .156
Within Groups 129.226 332 .389
Total 135.843 344
How long
have you
worked
Between Groups 15.730 12 1.311 1.078 .378
Within Groups 404.871 333 1.216
Total 420.601 345
Tier of
your bank
Between Groups 7.987 12 .666 1.186 .292
Within Groups 187.506 334 .561
Total 195.493 346
* Significant at p<0.05 level
The One-way ANOVA test was also performed to test the mean differences between job
satisfaction and the demographic factors of gender, age, education, duration of working at
the bank and tier of the bank. Table 4.36b shows the results which indicate that there was
151
no significant difference between the mean values of the demographic variables on
intellectual stimulation and job satisfaction.
Table 4.36b: One-way ANOVA on Intellectual stimulation on Job Satisfaction
Sum of
Squares
df Mean
Square
F Sig.
Gender
Between
Groups 2.909 12 .242 .968 .479
Within
Groups 83.132 332 .250
Total 86.041 344
Age
Between
Groups 7.890 12 .658 1.094 .364
Within
Groups 198.944 331 .601
Total 206.834 343
Education
Between
Groups 5.453 12 .454 1.157 .313
Within
Groups 130.390 332 .393
Total 135.843 344
How long have you
worked
Between
Groups 21.948 12 1.829 1.528 .112
Within
Groups 398.653 333 1.197
Total 420.601 345
Tier of your bank
Between
Groups 5.570 12 .464 .816 .634
Within
Groups 189.923 334 .569
Total 195.493 346
* Significant at p<0.05 level
4.6.6 Regression Analysis and Hypothesis Testing
This section presents the regression analysis, the model used for hypothesis testing in the
study and the assumptions for the regression. The regression analysis was done to
determine the relationship, magnitude of the effect and projection of the effect of
152
intellectual stimulation on job satisfaction among employees in commercial banks in
Kenya.
4.6.6.1 Assumptions for Regression Analysis on Intellectual Stimulation
Before running the regression analysis, assumptions for regression were tested. The
following tests were conducted: normality test, linearity test, homoscedasticity test and
multicollinearity tests as presented below.
4.6.6.1.1 Normality Test on Intellectual Stimulation
Using one sample Kolmogorov-Smirnov Test, the test of normality was conducted to
determine the distribution of data depicting either normal or skewed curve. This was
determined by statistical significance of the dependent and the independent variable
(p<.05). The normal parameters test indicated a difference on mean: intellectual
stimulation had (M= 3.91, SD = 0.832) compared to Job satisfaction (M= 3.24, SD =
1.02). The variance on the mean was low compared to the standard deviation variance
which was high. Further, the output showed the variance on the most extreme differences
was minimal and the variables were significant to each other (p<.05) indicating a high
level of relationship hence the data was not normally distributed (p<.05). Table 4.37a
indicates the results of the normality test.
Table 4.37a: One-Sample Kolmogorov-Smirnov Test on Intellectual Stimulation
Intellectual
Stimulation Job Satisfaction
N 347 347
Normal Parametersa,b Mean 3.9087 3.2363
Std. Deviation .83227 1.02499
Most Extreme Differences Absolute .146 .112
Positive .105 .085
Negative -.146 -.112
Test Statistic .146 .112
Asymp. Sig. (2-tailed) .000c .000c
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.
* Significant at p<0.05 level
153
4.6.6.1.2 Linearity Test on Intellectual Stimulation
The analysis of variance (ANOVA) was used to determine linearity. The linearity test was
conducted to determine whether the nature of the relationship between intellectual
stimulation and job satisfaction was linear or not. As indicated in table 4.37b, there was
significant relationship between intellectual stimulation and job satisfaction on the
combined and linearity tests (p<.05). However, the deviation from linearity was not
significant. Hence intellectual stimulation and job satisfaction were linear and passed the
test of linearity.
Table 4.37b: Linearity Test on Intellectual Stimulation
Sum of
Squares df
Mean
Square F Sig.
Job
Satisfaction
* Intellectual
Stimulation
Between
Groups
(Combined) 114.587 12 9.549 12.813 .000
Linearity 106.274 1 106.274 142.596 .000
Deviation
from Linearity 8.313 11 .756 1.014 .433
Within Groups 248.924 334 .745
Total 363.511 346
* Significant at p<0.05 level
4.6.6.1.3 Multicollinearity Test on Intellectual Stimulation
Multicollinearity test was performed to determine if the values of intellectual stimulation
and job satisfaction had higher similarity. The test of multicollinearity was tested by the
Variance Inflation Factor (VIF); statistically, there was no multicollinearity when the
value of VIF between 1 and 10. As indicated in Table 4.37c, the VIF value was 1.801
hence it indicated there was no multicollinearity between intellectual stimulation and job
satisfaction.
154
Table 4.37c: Multicollinearity Test on Intellectual Stimulation.
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
Collinearity
Statistics
B
Std.
Error Beta Tolerance VIF
1 (Constant) .633 .223 2.842 .005
Intellectual
Stimulation .666 .056 .541 11.939 .000 1.801 1.801
4.6.6.1.4 Homoscedasticity Test on Intellectual Stimulation
Homoscedasticity test was carried out to determine if intellectual stimulation of the bank
employees gives similar variance to job satisfaction on the regression values. As indicated
on Table 4.37d, the results indicate that the value of the Levene Statistic, F(12, 334) =
2.26, p = .01 was below the study’s level of significance (p ≤ .05) indicating the data was
not homogenous.
Table 4.37d: Homoscedasticity Test on Intellectual Stimulation
Levene Statistic df1 df2 Sig.
2.259 12 334 .009
* Significant at p<0.05 level
4.6.6.2 Regression and Hypothesis Testing on Intellectual Stimulation
Regression analysis was carried out to determine the extent to which intellectual
stimulation influenced job satisfaction among employees in commercial banks in Kenya.
Multiple linear regression was used to predict job satisfaction of employees in
commercial banks in Kenya from intellectual stimulation. The hypothesis tested was:
H04: There is no significant influence of intellectual stimulation on job satisfaction among
the employees in commercial banks in Kenya.
The regression results for the hypothesis testing were presented in the form of the model
summary, regression ANOVA and regression coefficient.
155
4.6.6.2.1 Regression Model Summary
The model summary results presented in Table 4.38 indicate that intellectual stimulation
explained 29% of job satisfaction of employees in commercial banks in Kenya (R2) =
.292.
Table 4.38: Model Summary on Intellectual Stimulation on Job Satisfaction
Model R
R
Square
Adjusted
R
Square
Std. Error
of the
Estimate
Change Statistics
R
Square
Change
F
Change df df2
Sig. F
Change
1 .541a .292 .290 .86349 .292 142.533 1 345 .000
a. Predictors: (Constant), Intellectual Stimulation
b. Dependent Variable: Job Satisfaction
* Significant at p<0.05 level
4.6.6.2.2 Regression ANOVA
The regression ANOVA showed that intellectual stimulation had a significant influence
on job satisfaction F(1, 106.274) = 142.533, p<.05) as indicated in Table 4.39. This
means that the regression model was suitable for predicting the outcome variable on how
intellectual stimulation influenced job satisfaction among employees in commercial banks
in Kenya.
Table 4.39: ANOVA of Intellectual Stimulation on job satisfaction
Model Sum of Squares df Mean Square F Sig.
1 Regression 106.274 1 106.274 142.533 .000b
Residual 257.237 345 .746
Total 363.511 346
a. Dependent Variable: Job Satisfaction
b. Predictors: (Constant), Intellectual Stimulation
* Significant at p<0.05 level
156
4.6.6.2.3 Regression Coefficient of Intellectual Stimulation
Table 4.40 shows the results of the regression coefficient. In the regression coefficient
model, the analysis showed that intellectual stimulation statistically predicted job
satisfaction (β = .666, (2.842) t = 11.939, p<.05). The beta weight gauges the importance
of explanatory variable across the model and was positive on intellectual stimulation,
Beta of .666 and statistically significant at p<.05. This means, one unit of increase in
intellectual stimulation increased the unit of job satisfaction by .666.
Table 4.40: Coefficients of Intellectual Stimulation on job satisfaction
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
Collinearity
Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) .633 .223 2.842 .005
Intellectual
Stimulation .666 .056 .541 11.939 .000 1.000 1.000
a. Dependent Variable: Job Satisfaction
* Significant at p<0.05 level
From the coefficient table, the values of the regression model were derived:
The general form of the regression model used was:
= Constant; = Intellectual Stimulation and = Error term.
From the coefficient table, intellectual stimulation influences job satisfaction in the
Kenyan banking sector.
Y= 0.633 + .666X +.056
The multiple linear regression analysis was used to test if intellectual stimulation
significantly predicted job satisfaction among employees in commercial banks in Kenya.
The results revealed that intellectual stimulation explained 29% of the job satisfaction (R2
= .292, F(1, 106.274) = 142.533, p<.05) while the remaining 71% of job satisfaction was
explained by other factors. Further, intellectual stimulation significantly predicted job
satisfaction (β = .666, (2.842) t = 11.939, p<.05). Therefore, the study rejected the null
hypothesis H04: There is no significant influence of intellectual stimulation on job
157
satisfaction among the employees in commercial banks in Kenya and accepted the
alternate hypothesis, H14: There is a significant influence of intellectual stimulation on job
satisfaction among the employees in commercial banks in Kenya.
4.7 Moderating Effect of Job Security on the Influence of Transformational
Leadership on Job Satisfaction
The last objective in this study was to determine the moderating effect of ‘job security’ on
the influence of transformational leadership on job satisfaction. The moderating effect of
job security questions were: my leader encourages fair treatment to everyone; my leader’s
behavior does not cause me stress; and my leader does not leave room for anxiety. The
dependent variable questions were: I am committed to the organization because my leader
encourages fair treatment to everyone; I am hardly absent from work because my leader’s
behavior does not cause me stresses; and I have no intentions of leaving my job because
my leader does not leave room for anxiety. All the responses were measured on a five
point Likert scale. The results and findings of both the descriptive and inferential statistics
are presented below.
4.7.1 Factor Analysis
Factor analysis was used to evaluate the variability among the observed correlated
variables to ensure the questions in the research instrument relate to the construct of
measure. Questions that did not relate to construct were extracted from the analysis.
Factor analysis was conducted on three questions for dependent variable ‘job satisfaction’
and three questions for moderating variable ‘job security’ presented below.
4.7.1.1 Factor Analysis on ‘Job Security’ as Moderating Variable
The dependent and moderating variables had three questions each. As indicated in Table
4.41a, only one factor was derived with Kaiser-Meyer Olkin result of .733. The Bartlett’s
test of sphericity was significant at X2 (3, N=347) = 563.351, p<.05. The factor was
adequate for extraction of components since Kaiser-Meyer-Olkin Measure was greater
than .60 and the Bartlett’s test was significant (p<.05).
158
Table 4.41a: KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .733
Bartlett's Test of Sphericity Approx. Chi-square 563.351
df 3
Sig. .000
* Significant at p<0.05 level
Using the Principal component analysis, the total variance explained on the extraction
showed the extracted values presented 81% of the first component. Only one component
was extracted ‘Job security as moderating effect’. Further, average value principle was
used to obtain the measure of the extracted independent variable by transformation. Table
4.41b shows the results of the variance explained.
Table 4.41b: Total Variance Explained for Job Security as Moderating Variable
Component
Initial Eigenvalues
Extraction Sums of Squared
Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
%
1 2.424 80.798 80.798 2.424 80.798 80.798
2 .350 11.665 92.462
3 .226 7.538 100.000
Extraction Method: Principal Component Analysis.
The variables of the extracted components are indicated on the component matrix table.
Only one factor was extracted representing the ‘moderating effect’. The variables and
values were: ‘my leader encourages fair treatment to everyone’ with component matrix of
.872; ‘my leader’s behavior does not cause me stress’ with component matrix of .913; and
‘my leader does not leave room for anxiety’ with component matrix of .911. All variables
and component measure under the factor loading were greater than .60. Further, using the
average of the components, the transformed data had a stronger component of .899 which
was greater than .60. All the components were included as variables of analysis in the
model. Table 4.41c shows the component matrix for the moderating effect of job security.
159
Table 4.41c: Component Matrix on Job Security as Moderating Effect
Job security as moderating effect
Component
1
My leader encourages fair treatment to everyone .872
My leader’s behavior does not cause me stress .913
My leader does not leave room for anxiety .911
Extraction Method: Principal Component Analysis.
a. 1 component extracted.
4.7.1.2 Factor Analysis on Job Security as Moderating Variable on Job Satisfaction
Job security was the moderating variable in this study. As indicated in Table 4.42a, only
one factor was derived with Kaiser-Meyer Olkin result of .729. The Bartlett’s test of
sphericity was significant at X2 (3, N=347) = 601.909, p<.05. This indicated the factor as
adequate for extraction of component since Kaiser-Meyer-Olkin Measure is greater than
.60 and the Bartlett’s test is significant (p<.05).
Table 4.42a: KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .729
Bartlett's Test of Sphericity Approx. Chi-square 601.909
df 3
Sig. .000
* Significant at p<0.05 level
Using the Principal component analysis, the total variance explained on the extraction
shows the extracted values present 82% of the component. Only one component was
extracted ‘moderating effect on job satisfaction’. Further, average value principle was
used to obtain the measure of the extracted independent variable named ‘moderating
effect on job satisfaction’ by transformation. Table 4.42b shows the results of the
variance explained.
160
Table 4.42b: Total Variance Explained for Job Security as Moderating Variable
Component
Initial Eigenvalues Extraction Sums of Squared Loadings
Total
% of
Variance Cumulative % Total % of Variance Cumulative %
1 2.453 81.769 81.769 2.453 81.769 81.769
2 .338 11.283 93.051
3 .208 6.949 100.000
Extraction Method: Principal Component Analysis.
One component for job security had an Eigen value that was greater than one which was
in line with the results for total variance explained for job security as shown in Figure
4.10.
Figure 4.10: Scree Plot for Job Security
The details on the extracted component forming the dependent variable ‘Moderating
effect’ were indicated in the Table 4.42c. The component extraction of each of variable
showed ‘I am committed to the organization because my leader encourages fair treatment
to everyone’ had a component matrix value of .897; ‘I am hardly absent from work
because my leader’s behavior does not cause me stress’ had a component matrix value of.
161
929 and lastly; ‘I have no intentions of leaving my job because my leader does not leave
room for anxiety’ had a component matrix value of .886. This showed the variables and
component measure under the factor loading were greater than .60. Further, using the
average of the components, the transformed data had a stronger component of .904 which
was greater than .60. All the components of dependent variables were included as
variable of analysis. Table 4.42c indicates the component matrix measure of ‘job security’
as moderating effect on job satisfaction.
Table 4.42c: Component Matrix on Job Security as Moderating Variable on Job
Satisfaction
Job security on job satisfaction
Component
1
I am committed to the organization because my leader encourages fair treatment to
everyone .897
I am hardly absent from work because my leader’s behavior does not cause me
stress .929
I have no intentions of leaving my job because my leader does not leave room for
anxiety .886
Extraction Method: Principal Component Analysis.
a. 1 Component extracted.
4.7.2 Descriptive Statistics for Moderating Variable
The mean and standard deviation of the moderating variable were analyzed using
descriptive statistics. Majority of the respondents agreed on the attribute ‘my leader
encourages fair treatment to everyone’ (M= 3.92, SD = 1.06) and also ‘my leader’s
behavior does not cause me stress’ (M= 3.66, SD = 1.08). Other results are also presented
in the table. This clearly showed the difference, with the decrease in mean, the standard
deviation increased indicating varied responses. Table 4.43 shows the results of the
descriptive statistics of the moderating effect of job security.
162
Table 4.43: Distribution of Job Security as Moderating Variable
Job Security M SD Skewness Std Err
My leader encourages fair treatment to
everyone 3.9164 1.06247 -1.069 .131
My leader’s behavior does not cause
me stress 3.6599 1.08574 -.559 .131
My leader does not leave room for
anxiety 3.5116 1.05249 -.325 .131
Moderating Effect of Job Security on Job Satisfaction
I am committed to the organization
because my leader encourages fair
treatment to everyone
3.4162 1.16478 -.449 .131
I am hardly absent from work because
my leader’s behavior does not cause
me stress
3.2594 1.13873 -.250 .131
I have no intentions of leaving my job
because my leader does not leave room
for anxiety
2.9366 1.16128 .068 .131
4.7.3 Chi-square Test of Job Security as Moderating variable and Job Satisfaction
The Chi-square test was used to determine whether there was a significant association
between job security and job satisfaction. The chi-square test showed that there was a
significant association between job security as the moderating effect variable and job
satisfaction X2 (144, N = 347) = 664.814, p<.05). The results are presented in Table 4.44.
Table 4.44: Chi-square Test of Job Security and Job Satisfaction
Job security as moderating
variable
Value df Asymp. Sig. (2-
sided)
Pearson Chi-square 664.814a 144 .000
Likelihood Ratio 431.895 144 .000
Linear-by-Linear Association 168.179 1 .000
N of Valid Cases 347
a. 153 cells (90.5%) have expected count less than 5. The minimum expected count is .02.
* Significant at p<0.05 level
163
4.7.4 Correlation Analysis between Job Security and job satisfaction
Correlation analysis was used to test the relationship between job security variables and
job satisfaction. All the variables were highly correlated. The first variable under job
security ‘My leader encourages fair treatment to everyone was positively correlated with
job satisfaction r (347) =.593, p<.05; ‘My leader’s behavior does not cause me stress r
(347) =.628, p<.05; and ‘My leader does not leave room for anxiety’ r (347) =.660,
p<.05. The results of the correlation test are presented in Table 4.45.
Table 4.45a: Correlation Analysis between Job Security Variables and Job
Satisfaction
Moderating effect of Job Security Pearson Correlation Job Satisfaction
My leader encourages fair treatment to
everyone
Pearson Correlation .593**
Sig. (2-tailed) .000
N 347
My leader’s behavior does not cause me
stress
Pearson Correlation .628**
Sig. (2-tailed) .000
N 347
My leader does not leave room for anxiety Pearson Correlation .660**
Sig. (2-tailed) .000
N 347
* Significant at p<0.05 level
Further, correlation analysis was used to test the relationship between job security and job
satisfaction. The results showed that there was strong and positive correlation between
job security and job satisfaction r (347) =.697, p<.05. The results are as shown in Table
4.45b.
Table 4.45b: Correlation Analysis between Job Security and Job Satisfaction
Job security on job satisfaction Job Satisfaction
Job security as
moderating variable
Pearson Correlation .697**
Sig. (2-tailed) .000
N 347
* Significant at p<0.05 level
164
4.7.5 One-Way ANOVA on Job Security
The One-way ANOVA test was conducted to test the mean difference between job
security and the demographic information of respondents; gender, age, education level,
duration of working at the bank and lastly the tier of the bank. Table 4.46a shows the
results which indicate there was no significant difference between the mean values of all
the respondents’ demographic information and job security.
Table 4.46a: One-way ANOVA on Job Security
Sum of Squares Df Mean Square F Sig.
Gender Between Groups 1.803 12 .150 .592 .848
Within Groups 84.237 332 .254
Total 86.041 344
Age Between Groups 4.520 12 .377 .616 .828
Within Groups 202.314 331 .611
Total 206.834 343
Education Between Groups 5.554 12 .463 1.179 .296
Within Groups 130.289 332 .392
Total 135.843 344
How long
have you
worked
Between Groups 13.483 12 1.124 .919 .528
Within Groups 407.118 333 1.223
Total 420.601 345
Tier of your
bank
Between Groups 4.102 12 .342 .596 .845
Within Groups 191.391 334 .573
Total 195.493 346
* Significant at p<0.05 level
The One-way ANOVA test was also performed to test the mean differences between job
satisfaction and the demographic factors of gender, age, education, duration of working at
the bank and tier of the bank. Table 4.46b shows the results which indicate that there was
no significant difference between the mean values of the demographic variables on job
security and job satisfaction.
165
Table 4.46b: One-way ANOVA on Job Security on Job Satisfaction
Sum of Squares df Mean Square F Sig.
Gender
Between Groups 3.149 12 .262 1.051 .402
Within Groups 82.892 332 .250
Total 86.041 344
Age
Between Groups 5.977 12 .498 .821 .629
Within Groups 200.857 331 .607
Total 206.834 343
Education
Between Groups 5.268 12 .439 1.116 .346
Within Groups 130.575 332 .393
Total 135.843 344
How long
have you
worked
Between Groups 13.417 12 1.118 .914 .533
Within Groups 407.184 333 1.223
Total 420.601 345
Tier of
your bank
Between Groups 4.520 12 .377 .659 .791
Within Groups 190.973 334 .572
Total 195.493 346
* Significant at p<0.05 level
4.7.6 Regression Analysis and Hypothesis Testing
This section presents the regression analysis, the model used for hypothesis testing in the
study and the assumptions for the regression. Regression analysis was done to determine
the relationship, magnitude of the effect and projection of the moderating effect job
security between transformational leadership and job satisfaction among employees in
commercial banks in Kenya.
4.7.6.1 Assumptions for Regression Analysis on the Moderating Variable
Before running the regression analysis, assumptions for regression were tested. The
following tests were conducted: normality test, linearity test, homoscedasticity test and
multicollinearity tests as presented below.
166
4.7.6.1.1 Normality Test on Job Security
Using one sample Kolmogorov-Smirnov Test, the test of normality was conducted to
determine the distribution of data depicting either a normal or skewed curve. This was
determined by the statistical significance of the dependent and the independent variable
(p<.05). The normal parameters test indicates the difference on mean in all the dependent,
independent and moderating effect variables. The results showed the mean and standard
deviation were as follows: Idealized influence (M = 4.07, SD =.79) followed by
Inspirational motivation (M =4.02, SD=.88), Individualized consideration (M = 4.0, SD=
.77), Intellectual stimulation (M= 3.90, SD = .83), Moderating effect of job security (M =
3.7, SD= .96) and lastly, the job satisfaction (M = 3.2, SD= .95). The results of the mean
showed the difference in mean and variance in responses. The variance on the most
extreme differences was minimal and the variables were significant to each other (p<.05)
indicating a high level of relationship hence the data was not normally distributed. Table
4.47a shows the results of the normality test.
Table 4.47a: One-Sample Kolmogorov-Smirnov Test
Job
Sati
sfact
ion
Idea
lize
d
infl
uen
ce
Ind
ivid
uali
zed
Con
sid
erati
on
Insp
irati
on
al
moti
vati
on
Inte
llec
tual
Sti
mu
lati
on
Mod
erati
ng
Eff
ect
N 347 346 347 347 347 347
Normal
Parametersa,b
Mean 3.2077 4.0655 3.9914 4.0216 3.9087 3.6964
SD .94919 .78771 .76592 .87640 .83227 .96073
Most Extreme
Differences
Absolute .055 .184 .173 .185 .146 .142
Positive .040 .118 .101 .132 .105 .094
Negative -.055 -.184 -.173 -.185 -.146 -.142
Test Statistic .055 .184 .173 .185 .146 .142
Asymp. Sig. (2-tailed) .014c .000c .000c .000c .000c .000c
a. Test distribution is Normal.
b. Calculated from data.
c. Lilliefors Significance Correction.
* Significant at p<0.05 level
167
4.7.6.1.2 Linearity Test on Job Security
The analysis of variance (ANOVA) was used to determine linearity. The linearity test was
conducted to determine if the relationship between transformational leadership and job
satisfaction was linear or not. As indicated in Table 4.47b, there was a significant
relationship between transformational leadership variables (collapsed value of
independent variable) and job satisfaction p<.05. Similarly, the linearity between the
transformational leadership variables and job satisfaction was significant p<.05.
However, the deviation from linearity was not significant. Hence the relationship between
transformational leadership and job satisfaction was linear and passed the test of linearity.
Table 4.47b: Linearity Test on Job Security
Sum of
Squares Df
Mean
Square F Sig.
Job Satisfaction Between
Groups
(Combined) 168.274 79 2.130 3.964 .000
Linearity 129.561 1 129.561 241.139 .000
Deviation
from Linearity 38.713 78 .496 .924 .655
Within Groups 143.456 267 .537
Total 311.731 346
* Significant at p<0.05 level
4.7.6.1.3 Multicollinearity Test on Job Security
Multicollinearity test was performed to determine if the values of transformational
leadership, moderating effect of job security and job satisfaction had higher similarity.
The test of multicollearity was tested using the Variance Inflation Factor (VIF);
statistically, there is no multicollinearity when the value of the VIF is between 1 and 10.
As indicated in Table 4.47c, Idealized influence had a VIF of 2.425; individualized
consideration had VIF of 2.313; Inspirational motivation had VIF of 3.207; Intellectual
stimulation had VIF of 2.113; and moderating effect variable had a VIF of 2.577, no
multicollinearity.
168
Table 4.47c: Multicollinearity Test on Job Security
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.
Collinearity
Statistics
B
Std.
Error Beta Tolerance VIF
1 (Constant) .142 .229 .622 .534
Idealized Influence -.039 .076 -.032 -.511 .610 .412 2.425
Individualized
Consideration .219 .076 .177 2.880 .004 .432 2.313
Inspirational
Motivation .190 .078 .175 2.427 .016 .312 3.207
Intellectual
Stimulation .042 .067 .036 .621 .535 .473 2.113
Moderating Variable .384 .064 .389 6.011 .000 .388 2.577
a. Dependent Variable: Job Satisfaction
4.7.6.1.4 Homoscedasticity Test on Job Security
Homoscedasticity test was carried out to determine if the moderating effect of job
security of the bank employees gave similar a variance to job satisfaction on the
regression values. As indicated in Table 4.47d, the results indicate that the value of the
Levene Statistic, F(12, 334) = 3.62, p = .00 was below the study’s level of significance (p
≤ .05) indicating the data was not homogenous.
Table 4.47d: Homoscedasticity Test on Job Security
Levene Statistic df1 df2 Sig.
3.620 12 334 .000
* Significant at p<0.05 level
4.7.6.2 Regression and Hypothesis Testing
Regression analysis was carried out to determine the extent to which job security
moderated the relationship between transformational leadership and job satisfaction
among employees in commercial banks in Kenya. Multiple linear regression analysis was
used to predict the moderating effect of job security on the influence of transformational
169
leadership on job satisfaction among employees in commercial banks in Kenya. The
hypothesis tested was:
H05: There is no significant moderating effect of job security between transformational
leadership and job satisfaction among employees in commercial banks in Kenya.
The regression results for the hypothesis testing were presented in the form of the model
summary, regression ANOVA and regression coefficient.
4.7.6.2.1 Regression Model Summary
The model summary results presented in Table 4.48 indicate that the moderating effect of
job security between transformational leadership and job satisfaction explained 44% of
job satisfaction of employees in commercial banks in Kenya (R2) = .446.
Table 4.48: Model Summary of the Moderating Effect of Job Security between
Transformational Leadership and Job Satisfaction
Model R
R
Square
Adjusted
R
Square
Std.
Error of
the
Estimate
Change Statistics
R
Square
Change
F
Change df1 df2
Sig. F
Change
1 .668e .446 .438 .71187 .059 36.126 1 340 .000
e. Predictors: (Constant), Idealized Influence, Individualized Consideration, Inspirational
Motivation, Intellectual Stimulation, Moderating variable,
f. Dependent Variable: Job Satisfaction
* Significant at p<0.05 level
4.7.6.2.2 Regression ANOVA
The regression ANOVA showed that job security had a significant moderating effect
between transformational leadership and job satisfaction F(5, 27.760) = 54.780, p<.05) as
indicated Table 4.49.
170
Table 4.49: ANOVA Transformational Leadership and Moderating Variable on Job
Satisfaction
Model Sum of Squares df Mean Square F Sig.
1 Regression 138.802 5 27.760 54.780 .000f
Residual 172.299 340 .507
Total 311.101 345
f. Predictors: (Constant), Idealized Influence, Individualized Consideration, Inspirational
Motivation, Intellectual Stimulation, Moderating Variable Effect
* Significant at p<0.05 level
4.7.6.2.3 Regression Coefficient of Job Security
Table 4.50 shows the results of the regression coefficient. In the regression coefficient
model, the analysis showed that ‘idealized influence’ and ‘intellectual stimulation’ were
not statistically significant hence dropped from the equation and that ‘individualized
consideration’ statistically predicted job satisfaction (β = .219, t (.622) = 2.880, p<.05).
The beta weight gauges the importance of the explanatory variable across the model and
was positive on ‘individualized consideration’ and was statistically significant. This
meant that one unit of increase in ‘individualized consideration’ increased the unit of job
satisfaction by .219 with the inclusion of moderating variable. The variable ‘inspiration
motivation’ also statistically predicted job satisfaction (β = .190, t (.622) = 2.427, p<.05).
The beta weight gauges the importance of the explanatory variable across the model and
was positive on ‘inspiration motivation’ and statistically significant indicating one unit of
increase in ‘inspiration motivation’ increased the unit of job satisfaction by .190. Lastly,
the moderating variable statistically predicted job satisfaction (β = .384, t (.622) = 6.011,
p<.05). The beta weight gauges the importance of moderating variable across the model
and was statistically significant (p<.05). This meant, one unit of increase in ‘moderating
variable’ increased the unit of job satisfaction by .384 without the influence of
moderating variable.
171
Table 4.50: Coefficients of Independent Variables and Moderating Effect on Job
Satisfaction
Model
Unstandardized
Coefficients
Standardized
Coefficients
T Sig. B Std. Error Beta
1 (Constant) .142 .229 .622 .534
Idealized Influence -.039 .076 -.032 -.511 .610
Individualized
Consideration .219 .076 .177 2.880 .004
Inspirational
Motivation .190 .078 .175 2.427 .016
Intellectual Stimulation .042 .067 .036 .621 .535
Moderating Variable .384 .064 .389 6.011 .000
a. Dependent Variable: Job Satisfaction
* Significant at p<0.05 level
The general form of the multiple linear regression model used was:
Job Satisfaction = β0 + β1 x Idealized influence + β2 x Individualized consideration + β3 x
Inspirational motivation + β4 x intellectual stimulation + β5 x Job security + ∑
X1 = Idealized influence
X2 = Individualized consideration
X3 = Inspirational motivation
X4 = Intellectual stimulation
X5 = Moderating Variable
∑ = Error term
Idealized influence and intellectual stimulation were not statistically significant hence
dropped from the model equation which was comprised of individualized consideration,
inspirational motivation and job security.
Job Satisfaction = β0 + β2 X2 + β3 X
3 + β4 X4 + β5 X
5 + ∑
Y= 0.142 + .219X2 + .190X3 + .384X5 + .229
172
Multiple linear regression analysis was used to test if there was a significant moderating
effect of job security between transformational leadership and job satisfaction among
employees in commercial banks in Kenya. The results revealed that job security had a
significant moderating effect between transformational leadership and job satisfaction (R2
= .446, F(5, 27.760) = 54.780, p<.05) . Individualized consideration statistically predicted
job satisfaction with inclusion of the moderating variables (β = .219, t (.622) = 2.880,
p<.05): the beta weight decreased from .258 to .219 with the inclusion of moderating
variable reducing its influence on job satisfaction. Inspirational motivation variable
statistically predicted job satisfaction with the inclusion of the moderating variable, (β =
.190, t (.622) = 2.427, p<.05), the beta weight also decreased from .338 to .190 reducing
its effect on job satisfaction. However, both idealized influence and intellectual
stimulation were not significant. Lastly, the moderating variable significantly predicted
job satisfaction (β = .384, t (.622) = 6.011, p<.05).
This showed that with the moderating effect of job security, transformational leadership
significantly predicted job satisfaction. Therefore, the study rejects the null hypothesis
H05: There is no significant moderating effect of job security between transformational
leadership and job satisfaction among employees in commercial banks in Kenya and
accepts the alternate hypothesis, H15: There is a significant moderating effect of job
security between transformational leadership and job satisfaction among employees in
commercial banks in Kenya.
4.8 Chapter Summary
This chapter has presented the findings of the study. The demographic presentation
covered the characteristics of the respondents working in the banking industry; age,
gender, education level, working duration and the tiers of the bank. This was followed by
the presentation of the results based on each research question. The items presented were;
factor analysis, descriptive statistics, Chi-square test, correlation analysis and regression
analysis.
On the first research question, the results revealed that there was a significant correlation
between idealized influence and job satisfaction among employees in commercial banks
in Kenya r (346) =.496, p<.05. Chi-square test revealed a significant association between
idealized influence and job satisfaction X2 (132, N = 346) = 302.886, p<.05). The One-
173
way ANOVA test showed there was no significant difference on the mean values of the
respondents’ demographic information on idealized influence and job satisfaction except
for number of years worked in the organization. The multiple linear regression analysis
results revealed that idealized influence explained 25% of job satisfaction (R2 = .246, F(1,
97.750) = 112.421, p<.05) and significantly predicted job satisfaction (β = .676, (.449) t =
10.603, p<.05). Therefore, the null hypothesis that there is no significant influence of
idealized influence on job satisfaction among employees in commercial banks in Kenya
was rejected.
On the second research question, the results revealed that there was a significant
correlation between individualized consideration and job satisfaction among employees in
commercial banks in Kenya r (347) =.595, p<.05. Chi-square test revealed a significant
association between individualized consideration and job satisfaction X2 (132, N = 347) =
385.123, p<.05). The One-way ANOVA test showed that there was no significant
difference on the mean values of the respondents’ demographic information on
individualized consideration and job satisfaction except for age, education and number of
years worked in the organization. The multiple linear regression results revealed that
individualized consideration explained 35% of job satisfaction (R2 = .354, F(1, 138.779)
= 188.851, p<.05) and significantly predicted job satisfaction (β = .827, (-.545) t =
13.742, p<.05). Therefore, the null hypothesis that there is no significant influence of
individualized consideration on job satisfaction among employees in commercial banks in
Kenya was rejected.
On the third research question, the results revealed that there was a significant correlation
between inspirational motivation and job satisfaction among employees in commercial
banks in Kenya r (347) =.587, p<.05. The Chi-square test showed a significant
association between inspirational motivation and job satisfaction X2 (156, N = 347) =
445.180, p<.05). The One-way ANOVA test revealed there was no significant difference
on the mean values of the respondents’ demographic information on inspirational
motivation and job satisfaction. The multiple linear regression results revealed that
inspirational motivation explained 34% of job satisfaction (R2 = .344, F(1, 126.302) =
180.980, p<.05) and significantly predicted job satisfaction (β = .689, (2.117) t = 13.453,
p<.05). Therefore, the null hypothesis that there is no significant influence of
174
inspirational motivation on job satisfaction among employees in commercial banks in
Kenya was rejected.
On the fourth research question, the results revealed that there was a significant
correlation between the intellectual stimulation and job satisfaction among employees in
commercial banks in Kenya r (347) =.541, p<.05. The Chi-square test revealed a
significant association between intellectual stimulation and job satisfaction X2 (144, N =
347) = 426.404, p<.05). The One-way ANOVA test showed there was no significant
difference on the mean values of the respondents’ demographic information on
intellectual stimulation and job satisfaction. The multiple linear regression results
revealed that intellectual stimulation explained 29% of job satisfaction (R2 = .292, F(1,
106.274) = 142.533, p<.05) and significantly predicted job satisfaction (β = .666, (2.842)
t = 11.939, p<.05). Therefore, the null hypothesis that there is no significant influence of
intellectual stimulation on job satisfaction among employees in commercial banks in
Kenya was rejected.
On the last research question, the results revealed that there was a significant correlation
between the moderating effect of job security and job satisfaction among employees in
commercial banks in Kenya r (347) =.697, p<.05. The Chi-square test revealed a
significant association between job security as moderating effect variable and job
satisfaction X2 (144, N = 347) = 664.814, p<.05). The One-way ANOVA test showed
there was no significant difference on the mean values of the respondents’ demographic
information on job security and job satisfaction. The multiple linear regression results
revealed that transformational leadership explained 44% of job satisfaction when
moderated by job security (R2 = .446, F(5, 27.760) = 54.780, p<.05). Job security had a
significant moderating effect between transformational leadership and job satisfaction (β
= .384, (.622) t = 6.011, p<.05). Therefore, the null hypothesis that there is no significant
moderating effect of job security between transformational leadership and job satisfaction
among employees in commercial banks in Kenya was rejected.
The next chapter presents a summary of the findings, discussions of the findings,
conclusions and recommendations based on the findings of the study.
175
CHAPTER FIVE
5.0. SUMMARY, DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS
5.1 Introduction
This chapter presents the summary, discussion, conclusions and recommendations of the
study. The summary, discussions and conclusions are presented based on the research
questions. Recommendations are made based on the findings of the study. The study also
gives suggestions for future research.
5.2 Summary of the Study
The purpose of this study was to examine the influence of transformational leadership
style on job satisfaction among employees in commercial banks in Kenya. This study was
guided by the following research questions: To what extent does idealized influence
influence job satisfaction among employees in commercial banks in Kenya? To what
extent does individualized consideration influence job satisfaction among employees in
commercial banks in Kenya? To what extent does inspirational motivation influence job
satisfaction among employees in commercial banks in Kenya? To what extent does
intellectual stimulation influence job satisfaction among employees in commercial banks
in Kenya? To what extent does job security moderate the relationship between
transformational leadership and job satisfaction among employees in commercial banks in
Kenya?
The study was based on the positivism research philosophy. The study adopted the
descriptive correlation research design. The target population was 10,310 managerial
employees in the commercial banks in Kenya. Stratified random sampling technique was
used to select a sample of 424 managers in commercials banks in Kenya who participated
in the study. A response rate of 82% was obtained. The study used a structured
questionnaire to collect data from the managerial employees. Data analysis was done
using both descriptive and inferential statistics; descriptive statistics tests performed were
percentage, mean and standard deviation. The inferential statistical tests carried out were
chi-square test, correlation analysis, ANOVA, and regression analysis to obtain the
relationship between the variables of the study. Statistical Package for the Social Sciences
(SPSS) was used to analyze the data.
176
The first research question sought to examine the extent to which idealized influence
influenced job satisfaction among employees in commercial banks in Kenya. The results
revealed that there was a significant correlation between idealized influence and job
satisfaction among employees in commercial banks in Kenya r (346) =.496, p<.05. Chi-
square test revealed that there was a significant association between idealized influence
and job satisfaction X2 (132, N = 346) = 302.886, p<.05). The One-way ANOVA test
showed that there was no significant difference on the mean values of the respondents’
demographic information on idealized influence and job satisfaction except for number of
years worked in the organization at (p<.05). The multiple linear regression analysis
results revealed that idealized influence explained 25% of job satisfaction (R2 = .246, F(1,
97.750) = 112.421, p<.05) and significantly predicted job satisfaction (β = .676, (.449) t =
10.603, p<.05). Therefore, the study rejected the null hypothesis, H01: There is no
significant influence of idealized influence on job satisfaction among employees in
commercial banks in Kenya.
The second research question sought to examine the extent to which individualized
consideration influenced job satisfaction among employees in commercial banks in
Kenya. The results revealed that there was a significant correlation between
individualized consideration and job satisfaction among employees in commercial banks
in Kenya r (347) =.595, p<.05. Chi-square test revealed that there was a significant
association between individualized consideration and job satisfaction X2 (132, N = 347) =
385.123, p<.05). The One-way ANOVA test showed that there was no significant
difference on the mean values of the respondents’ demographic information on
individualized consideration and job satisfaction except for age, education and number of
years worked in the organization at (p<.05). The multiple linear regression results
revealed that individualized consideration explained 35% of job satisfaction (R2 = .354,
F(1, 138.779) = 188.851, p<.05) and significantly predicted job satisfaction (β = .827, (-
.545) t = 13.742, p<.05). Therefore, the study rejected the null hypothesis, H02: There is
no significant influence of individualized consideration on job satisfaction among
employees in commercial banks in Kenya.
The third research question sought to examine the extent to which inspirational
motivation influenced job satisfaction among employees in commercial banks in Kenya.
The results revealed that there was a significant correlation between inspirational
177
motivation and job satisfaction among employees in commercial banks in Kenya r (347)
=.587, p<.05. The Chi-square test revealed that there was a significant association
between inspirational motivation and job satisfaction X2 (156, N = 347) = 445.180,
p<.05). The One-way ANOVA test showed that there was no significant difference on the
mean values based on the respondents’ demographic information on inspirational
motivation and job satisfaction (p<.05). The multiple linear regression results revealed
that inspirational motivation explained 34% of job satisfaction (R2 = .344, F(1, 126.302)
= 180.980, p<.05) and significantly predicted job satisfaction (β = .689, (2.117) t =
13.453, p<.05). Therefore, the study rejected the null hypothesis, H03: There is no
significant influence of inspirational motivation on job satisfaction among employees in
commercial banks in Kenya.
The fourth research question sought to examine the extent to which intellectual
stimulation influenced job satisfaction among employees in commercial banks in Kenya.
The results revealed that there was a significant correlation between intellectual
stimulation and job satisfaction among employees in commercial banks in Kenya r (347)
=.541, p<.05. The Chi-square test revealed there was a significant association between
intellectual stimulation and job satisfaction X2 (144, N = 347) = 426.404, p<.05). The
One-way ANOVA test showed that there was no significant difference on the mean
values based on the respondents’ demographic information on intellectual stimulation and
job satisfaction (p<.05). The multiple linear regression results revealed that intellectual
stimulation explained 29% of job satisfaction (R2 = .292, F(1, 106.274) = 142.533,
p<.05) and significantly predicted job satisfaction (β = .666, (2.842) t = 11.939, p<.05).
Therefore, the study rejected the null hypothesis, H04: There is no significant influence of
intellectual stimulation on job satisfaction among employees in commercial banks in
Kenya.
The fifth research question sought to examine the extent to which job security moderated
the relationship between transformational leadership and job satisfaction among
employees in commercial banks in Kenya. The results revealed that there was a
significant correlation between the moderating effect of job security and job satisfaction
among employees in commercial banks in Kenya r (347) =.697, p<.05. The Chi-square
test revealed that there was a significant association between job security as moderating
variable and job satisfaction X2 (144, N = 347) = 664.814, p<.05). The One-way ANOVA
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test showed there was no significant difference on the mean values of the respondents’
demographic information on job security and job satisfaction. The multiple linear
regression results revealed that transformational leadership explained 44% of job
satisfaction when moderated by job security (R2 = .446, F(5, 27.760) = 54.780, p<.05).
Job security had a statistically significant moderating effect between transformational
leadership and job satisfaction (β = .384, t (.622) = 6.011, p<.05). This showed that job
security had a significant moderating effect between transformational leadership and job
satisfaction. Therefore, the study rejected the null hypothesis, H05: There is no significant
moderating effect of job security between transformational leadership and job satisfaction
among employees in commercial banks in Kenya.
5.3 Discussion of Results
This section presents the discussion of results which is presented in line with the research
questions. Correlation analysis, Chi-square, One-way ANOVA and Multiple linear
regression results are discussed in this section.
5.3.1 Influence of Idealized Influence on Job Satisfaction
The first research question sought to examine the extent to which idealized influence
influenced job satisfaction among employees in commercial banks in Kenya. The results
of correlation analysis revealed a positive correlation between idealized influence
variables and job satisfaction; charismatic attributes (r (345) =.563, p<.05), trust (r (346)
=.596, p<.05), and ethical (r (343) =.564, p<.05). This showed idealized influence had a
positive and strong correlation with job satisfaction. The findings were similar to Hwang
et al. (2005) study which showed there was correlation between commitment and
performance which are mainly a function of satisfaction. Huang et al. (2005) in their
study dubbed ‘fitting in organizational values’ sought to investigate whether CEO
charismatic leadership had a positive effect on employees. The findings demonstrated that
charisma had significant effects on employee outcomes of extra effort, job satisfaction
and organizational commitment. Ahmed et al. (2012) sought to establish the relationship
between organizational ethics and job satisfaction in employees of banks in Pakistan and
found that benevolent ethical climate and top management support for ethical behavior
were positively correlated to job satisfaction.
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However, there are studies that have found no correlation between idealized influence and
job satisfaction. Hanaysha et al. (2012) study in Malaysia among administrative and
clerical staff involved in graduate and postgraduate affairs in three universities found a
positive relationship between charisma and job satisfaction which was statistically
insignificant. Ahmed et al. (2012) sought to establish the relationship between
organizational ethics and job satisfaction in employees of banks in Pakistan and found out
that egoistic ethical climate was negatively related to job satisfaction. Further, principled
ethical climate had no relationship with job satisfaction. These findings necessitate more
research in the area since majority of the studies indicate a positive correlation between
charisma and job satisfaction with statistical significance. However, there are very few
studies with a negative relationship hence most agree that idealized influence is positively
correlated with job satisfaction.
The chi-square test was used to establish the strength of association between idealized
influence and job satisfaction. The results showed that there was a significant association
between idealized influence and job satisfaction X2 (132, N = 346) = 302.886, p<.05). The
idealized influence variables were trust, charisma and ethics. Research indicates that
people who are in high trust environments live longer, enjoy greater wellness and job
satisfaction. In contrast, a low trust environment sucks energy, results into stress and
reduced wellness which has the possibility of destroying performance. Lack of trust also
suppresses expressions which may lead to a lot of dysfunctions in the organization hence
the need to cultivate a trust culture which is a precursor to job satisfaction and
performance (Jameson, 2010).
Bacha (2010) in a study on the relationships among organizational performance,
environmental uncertainty and employee’s perceptions of CEOs found that CEOs who are
found to be increasingly energetic have an impact on organizational performance as
opposed to model CEOs who have no significant impact on organizational performance.
This shows that the environment that creates ethics or trust between employees is
determined by the individual characteristics. Khuong and Hoang (2015) further affirmed
this when they found that as much as compensation and fringe benefits matter, the
leader’s personality and characteristics are more important as they affect the motivational
work environment for the staff which in turn yields positive job attitudes. This shows that
ethics, trust and charisma are determined by a leader. Lastly, a good ethical environment
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has the potential to boost an employee’s job satisfaction level while the consequences of
ethical misgivings are detrimental to the organization (Yang & Islam, 2012; Avolio &
Bass, 2002; Khuong & Hoang, 2015). All these studies found out that idealized influence
factors; trust, charisma and ethics are determined by individual leaders which has a
significant impact on the job satisfaction.
The One-way ANOVA test results showed that there was no significant difference on the
mean values of all the respondents’ demographic information on idealized influence and
job satisfaction except on the number of years worked in the organization (p<.05). This
shows that idealized influence is not determined by an individual’s background but by
other factors as outlined by researcher. According to Nikoloski (2015), the ethics of
charismatic leaders refers to how they use their power, and in what. Charismatic leaders
who are high on ethics have better workplace environments with less interpersonal and
workplace deviance. These leaders act as role models and their behavior more often than
not cascades through the organization. Khuong and Hoang (2015) also stated that a leader
who possesses charisma, trust and ethics is able to influence his followers because
followers identify with him; this in turn boosts the employee’s job satisfaction. This
supports the findings that idealized influence on an individual is not determined by the
background. Further, an ethical climate refers to individual beliefs about the
organizational practices, procedures, standards and ethical values and not the individuals
background (Ahmed et al., 2012). Sarker et al. (2003) found that the overall job
satisfaction indicated that job satisfaction rises in the tenure of service in majority of the
age groups except those below twenty five years old. Therefore, job satisfaction among
hotel employees was significantly dependent on the tenure of service in the organization.
The results of multiple linear regression indicated that idealized influence significantly
influenced job satisfaction (R2 = .246, F (1, 97.750) = 112.421, p<.05). The analysis
revealed that idealized influence statistically predicted job satisfaction (B = .676, (.449) t
= 10.603, p<.05). Different studies support this including Gitoho et al. (2016) who
studied the influence of idealized influence on employee satisfaction amongst listed
companies in Nairobi securities exchange and found out that idealized influence affects
job satisfaction. Emu and Umeh (2014) empirically examined the relationship between
leadership style and job satisfaction among customer relationship officers in Nigerian
banks. The results indicated that idealized influence explained 25% of job satisfaction.
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The low degree of influence (25%) was similar to what Long et al. (2014) found in their
study ‘impact of transformational leadership on job satisfaction in Malaysia’. The results
of the study revealed a positive but non-significant relationship between idealized
influence and job satisfaction. The research findings were in line with existing findings
that idealized influence significantly influenced job satisfaction.
5.3.2 Influence of Individualized Consideration on Job Satisfaction
The second research question sought to examine the extent to which individualized
consideration influenced job satisfaction among employees in commercial banks in
Kenya. The results of correlation analysis showed a positive significant relationship
between individualized consideration and job satisfaction: mentorship at the workplace (r
(347) =.872, p<.05), support in and outside work place (r (347) =.876, p<.05) and work
delegation (r (347) =.734, p<.05). Miao and Kim (2010) investigated the influence of
perceived organizational support and job satisfaction as positive correlations of employee
performance in China. The results indicated that organizational citizenship behavior
increased with more favorable perception of organizational support and job satisfaction.
Long et al. (2014) carried out a study on the impact of transformational leadership style
on job satisfaction and found that only the aspect of individualized consideration and
more so the support a leader offers to his employees had a significant impact on job
satisfaction. Social support also predicts job involvement and job satisfaction because it
acts as a buffer to stressors that arise from the work or interaction with colleagues
(Salami, 2010). Research that supports the correlation between individualized
consideration and job satisfaction includes but is not limited to management support
among other factors like recognition and job security (Mosadeghrad & Ferdosi, 2013).
Emmanuel and Hassan (2015) carried out a study to establish the effect of
transformational leadership on job satisfaction in four and five star hotels in Kuala
Lumpur. The results of this study revealed a positive and significant correlation between
individualized consideration and job satisfaction. It has also been established that
employees who are entrusted with decision making and receive support from their
supervisors and colleagues are more satisfied with their jobs (Musenze et al., 2014).
Conversely, there is research that has found a negative correlation between individualized
consideration and job satisfaction. In a study by Weng at al. (2010), there was no
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significant relationship between psychosocial mentoring and three aspects of employee
job satisfaction which were; co-workers, the job itself and promotion.
Further, Arzi and Farahbod (2014) in their study on the impact of leadership on job
satisfaction in Iranian hotels found that supportive leadership had a significant impact on
job satisfaction but recognition did not affect job satisfaction. Additionally, Riisgaard et
al. (2016) in a review paper with the aim of establishing the relations between task
delegation and job satisfaction in general practice found that nurses had negative attitudes
and experiences towards task delegation especially due to an increased workload.
However, majority were generally satisfied with their jobs and the various tasks they
performed which were delegated to them by the general physicians. They attributed this
satisfaction to the autonomy which they enjoyed. The results revealed that contrary to
most of the studies in this thematic area, the effect of delegation of authority and
responsibility was not significant on job satisfaction but empowerment had a significant
impact on job satisfaction.
The chi-square test was used to determine the strength of association between
individualized consideration and job satisfaction. The results revealed that there was a
significant association between individualized consideration and job satisfaction X2 (132,
N = 347) = 385.123, p<.05). The individualized consideration variables were mentoring,
support and delegation. The results show that mentorship, support and delegation
influence job satisfaction. Belias and Koustelios (2014) stated that individualized
consideration fosters the provision of support, encouragement, coaching, feedback
mechanisms and delegation which play a big role in the follower’s personal development
which in turn positively impacts job satisfaction. Further, Bass and Avolio (1994) noted
that a leader demonstrates individualized consideration when providing the followers with
support. The study went on to note that the improvement of individualized consideration
around supportive and developmental leadership is likely to have a transformational
impact (Long et al., 2014). Individualized consideration refers to the personal attention
the leaders have towards the needs of the followers which makes the followers to feel
valued; this explains the significant relationship between individualized consideration
with job satisfaction. However, some studies show that bank jobs are characterized by
long working hours, pressure from the job itself, poor treatment, non-conducive working
environment, minimal promotion opportunities and unfairness (Sattar & Ali, 2014). These
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studies show there is no significant relationship between individualized consideration and
job satisfaction especially when the working environment is poor.
The One-way ANOVA test results showed that there was no significant difference on the
mean values of all the respondents’ demographic information on individualized
consideration and job satisfaction. However, the means for job satisfaction were
significantly different across the age, education and number of years worked (p<.05).
Hoboubi et al. (2017) found that there were significant differences in job satisfaction
mean scores among three age groups of young, middle age and older people. Job
satisfaction was found to be higher for older employees and the young employees but
lower for the middle aged employees. They attributed this to young employees being
motivated and older ones settling in their lives whereas the middle aged employees would
be unhappy with repetitiveness of roles. They also found that the education level affected
job satisfaction indicating that people who had good educational qualifications were more
satisfied. Olorunsola (2012) found that age significantly influenced job satisfaction of
administrative staff in Nigeria Universities. They attributed this to the values and
expectations of the staff at the different ages.
Research by Alkahtani (2016) noted that the leader’s ability to create a supportive
environment by listening, coaching and mentoring speaks volumes to the followers about
how their leaders consider their needs by ensuring that as the organization grows the
employees also grow in their areas of interest. The leaders also help the employees to get
through their personal challenges because they are concerned not only about the work but
also their followers well-being. Ahmad et al. (2014) stated that leaders train the followers
on how to achieve the set goals and objectives. The accomplishment results in aspects of
recognition which are key drivers of job satisfaction. Further, Muenjohn (2010) found out
that encouragement from the leaders allows the followers to express themselves freely
and also to implement their ideas.
The results of multiple linear regression showed that individualized consideration
significantly influenced job satisfaction (R2 = .354, F (1, 138.779) = 188.851, p<.05).
The analysis showed that individualized consideration statistically predicted job
satisfaction (B = .827, (-.545) t = 13.742, p<.05). These results were similar to Mustafa
and Lines (2014) who found out that supportive leadership has a positive impact on job
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satisfaction which reaffirms that a leader’s characteristics and behaviors play an
important role in boosting job satisfaction, ultimately leading to positive outcomes in the
workplace. Kombo et al. (2014) found that delegation had a strong relationship with job
satisfaction and performance through raised enthusiasm for the employees. Additionally,
delegation was not only rewarding for the employees but it also raised the employees’
sense of accomplishment and self-esteem.
Horner (2017) carried out a study to establish whether mentoring based on Watson’s
caring model positively influenced nurses’ job satisfaction. All the participants reported
that mentor experience or relationship positively influenced job satisfaction. Additionally,
job satisfaction was associated with reduced turnover of staff and improved patient
retention. Hanaysha et al. (2012) conducted a study in Malaysia among administrative
and clerical staff involved in graduate and postgraduate affairs in three universities. The
findings revealed that individualized consideration was negatively related to job
satisfaction which contradicts most research. It is however attributed to the fact that
perhaps employees could not meet their leaders due to their busy schedules.
5.3.3 Influence of Inspirational Motivation on Job Satisfaction
The third research question sought to examine the extent to which inspirational
motivation influenced job satisfaction among employees in commercial banks in Kenya.
The results of correlation analysis of inspirational motivation and job satisfaction showed
a positive correlation on all the variables with job satisfaction: communication (r (347)
=.893, p<.05), teamwork (r (347) =.915, p<.05); and motivation (r (347) =.917, p<.05).
Other studies have found a positive correlation between inspirational motivation and job
satisfaction. Kakakhel et al. (2015) carried out a study on the impact of organizational
communication on organizational commitment and job satisfaction in Pakistan. The
findings of the study indicated that organizational communication had a positive effect on
job satisfaction. Monga et al. (2015) who studied job satisfaction of employees of ICICI
bank found that among other factors like communication, attitudes of supervisors, job
security and team work had an important role in determining employee job satisfaction.
Rizwan et al. (2012) conducted an empirical study of employee job satisfaction and aimed
to establish the crucial problems faced by employees and to find ways to enhance
employee loyalty. Findings revealed a strong and positive relationship between team
work and job satisfaction.
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The chi-square test was used to determine the strength of association between
inspirational motivation and job satisfaction. The results showed that there was a
significant association between inspirational motivation and job satisfaction X2 (156, N =
347) = 445.180, p<.05). The variables of inspirational motivation are communication,
teamwork and support which have a significant association with job satisfaction.
Research indicates that effective communication, teamwork and motivation influence job
satisfaction. A study found that communication whether horizontal or vertical, formal or
informal in any environment was an important factor that influenced the organization’s
success which is a factor of satisfaction (Epure et al., 2013). Another study goes on to
note that if employees receive proper communication about their roles, responsibilities
and performance expectations, their satisfaction increases. Thus, the supervisor’s role on
inspirational motivation cannot be overemphasized because of the significant impact it
has on job satisfaction (Kakakhel et al., 2015).
Leaders need to ensure they promote job satisfaction and commitment yielding policies
and practices. Employee commitment is beyond being passively loyal to being actively
involved and being ready to transcend personal gain for organizational gain. This explains
why inspirational motivation factors like teamwork, communication and motivation are
individual based and have a significant association with job satisfaction. However, E.O
Darko and T.O Darko (2015) research in Ghana noted that as a result of high competition
in the banking industry, employees are expected to work harder to ensure they retain and
attract new business regardless of the carder of the Bank. Such competition affects
personal motivation at work which in turn affects the job satisfaction (Thirulogasundaram
& Sahu, 2014). This greatly affects motivation and commitment and as stated by Yucel
and Bektas (2012), the level of commitment can greatly influence the quality of service
rendered to customers and influences job satisfaction. This research shows that the bank’s
working environment can contribute to negative association between inspirational
motivation and job satisfaction.
The One-way ANOVA test results showed that there was no significant difference on the
mean value of all the respondents’ demographic information on inspirational motivation
and job satisfaction (p<.05). The results revealed that personal individual background
does not influence or relate to inspirational motivation. Teamwork as a factor that
influences inspiration motivation is determined by personal individual skills, mutual
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accountability and complements to each other. In order to create effective teamwork,
there must be clear goals, relevant skills, mutual trust, commitment, effective
communication, negotiation skills and good leadership with both internal and external
support (Benrazavi & Silong, 2013; Musriha, 2013). Additionally, attributes of
inspirational motivation enable a leader to instill pride in the followers and induces the
follower’s interests beyond personal interests for the good of the organization (Guay,
2013). A leader’s optimistic talk about the future also helps to build hope in the followers
because the leader provides an exciting image of organization’s future (Guay, 2013; Rao
& Abdul, 2015; Bass, 1985). This supports the research finding that individual
background does not influence inspirational motivation variables.
The results of multiple linear regression revealed that inspirational motivation
significantly influenced job satisfaction (R2 = .344, F(1, 126.302) = 180.980, p<.05). The
analysis showed inspirational motivation statistically predicted job satisfaction (B = .689,
(2.117) t = 13.453, p<.05). Akpinar et al. (2013) stated that job satisfaction was a result of
organizational commitment and not organizational communication. Additionally, results
indicated that there was a positive relationship between employee’s perception of
organizational communication and organizational commitment. However, unlike many
studies, the results indicated communication to a greater extent predicted organizational
commitment as opposed to job satisfaction. Shujaat et al. (2014) conducted a research to
establish the impact of team work on employee job satisfaction. The results of the study
revealed that there was a significant impact of team work on job satisfaction. This
indicates that it is important for organizational leaders to build a team work culture, build
team skills and hold it in high regard because of its significant effect on job satisfaction
and achieving organizational goals. Rana (2015) sought to determine the job satisfaction
factors affecting employees in the Bangladesh banking sector. The results indicated that
there was a significant and positive relationship between human resource management
practices like team work, job autonomy and leadership behavior on job satisfaction;
however, team work was the most important factor affecting job satisfaction
5.3.4 Influence of Intellectual Stimulation on Job Satisfaction
The fourth research question sought to examine the extent to which intellectual
stimulation influenced job satisfaction among employees in commercial banks in Kenya.
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The results of correlation analysis test on intellectual stimulation and job satisfaction
showed a positive correlation on all the variables: knowledge sharing (r (347) =.638,
p<.05), creativity (r (347) =.547, p<.05) and risk taking (r (347) =.550, p<.05). Cheung
and Wong (2011) examined the link between transformational leadership and employee
creativity in Hong Kong. The results of the study revealed a positive and significant
relationship between transformational leadership and employee creativity which in turn
boosts employee job satisfaction. Raisi and Forutan (2017) conducted a study on the
relationship between a knowledge sharing culture and job satisfaction in the context of
Bank Sepah Branches in Shriraz, Iran. Results revealed a positive and significant
relationship between a knowledge sharing culture and components of job satisfaction.
Habib et al. (2014) sought to establish the impact of organizational culture on job
satisfaction, employee commitment and turnover intention. The results of the study
revealed that organization culture, specifically, innovation and risk taking highly
influenced employee commitment, job satisfaction and retention. However, the study
found that intellectual stimulation was positively correlated to job satisfaction because
leaders foster inspiration through stimulation which in turn creates excitement
The chi-square test was used to determine the strength of association between intellectual
stimulation and job satisfaction. The results showed that there was a significant
association between intellectual stimulation and job satisfaction X2 (144, N = 347) =
426.404, p<.05). The variables under intellectual stimulation are knowledge sharing,
creativity and risk-taking. Different researchers have noted the importance of intellectual
stimulation variables that lead to job satisfaction. Chen et al. (2009) found that
organizations need to provide a supportive process and environment for employees to be
creative. Additionally, the organizations should provide challenges, involvement of staff
and trust because these motivate employees to make contributions. An environment that
allows creativity is catalyzed by some room for ambiguity, freedom and some room for
risk taking (Chen et al., 2009). Iqbal et al. (2013) and Raju (2017) support the need for
intellectual stimulation; an ethical organizational climate is a key enabler for creativity
among employees in the organizations. Employees were more associated with
organizations which encouraged creativity and provided a platform for freedom of
expression. This shows how a work environment that encourages creativity, risk taking
and knowledge sharing contributes to job satisfaction.
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The One-way ANOVA test results showed that there was no significant difference in the
mean values of all the respondents’ demographic information on intellectual stimulation
and job satisfaction (p<.05). The results indicate that organizations that encourage
innovation and provide a supportive climate are likely to experience growth and retention
of talent. This is attributed to the organizational leadership which provides employees
with a conducive and supportive environment to enable them to be creative and
innovative whilst allowing room for implementation of their innovations (Farrukh et al.,
2014). The research conducted by Raisi and Forutan (2017) on a knowledge sharing
culture and job satisfaction in the context of Bank Sepah Branches in Shriraz, Iran also
showed a positive relationship between a knowledge sharing culture and intellectual
stimulation. This shows that the culture of the organization influences intellectual
stimulation variables and not individual background.
The results of the multiple linear regression revealed that intellectual stimulation
significantly influenced job satisfaction (R2 = .292, F (1, 106.274) = 142.533, p<.05). The
analysis showed that intellectual stimulation statistically predicted job satisfaction (B =
.666 (2.842) t = 11.939, p<.05). Yee et al. (2014) conducted a study on the effect of a
psychological climate for creativity on job satisfaction and work performance. The
findings showed that a creative climate is a key predictor of job satisfaction and work
performance among electrical engineers. In this regard, leaders need to create a culture
and an environment which promotes creativity in their organizations since it is a predictor
of job satisfaction. Kianto et al. (2016) sought to establish if knowledge management
could be used to nurture job satisfaction and also examined how it could be used to
increase individual employee job satisfaction. The results revealed that knowledge
sharing was a key component of the knowledge management process which was found to
have a positive correlation with job satisfaction. The overall study concludes that having
knowledge management processes in place is linked to high job satisfaction. Abbaspour
and Noghreh (2015) examined the relationship between organizational culture and job
satisfaction of Tourism Bank employees in Iran. The results revealed that there was a
relationship between organizational culture factors like risk taking and job satisfaction.
Specifically, there was a relationship between risk-taking and job satisfaction which was
not statistically significant.
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5.3.5 Moderating Effect of Job Security on the Influence Transformational
Leadership on Job Satisfaction
The fifth research question sought to examine the extent to which job security moderated
the relationship between transformational leadership and job satisfaction among
employees in commercial banks in Kenya. The results of the correlation analysis test
revealed that there was a positive correlation on the moderating effect of job security and
job satisfaction: ‘My leader encourages fair treatment to everyone’ was positively
correlated with job satisfaction r (347) =.593, p<.05; ‘My leader’s behavior does not
cause me stress’ was positively correlated with job satisfaction r (347) =.628, p<.05; and
‘My leader does not leave room for anxiety’ was positively correlated with job
satisfaction r (347) =.660, p<.05. Anxiety manifests itself through future concerns and the
inability to predict that future employment and career concerns all which have the
possibility of affecting the employee’s judgments, perceptions, satisfaction and
productivity. Studies have found these elements to be strong predictors of job satisfaction
and thus a leader should endeavor to reassure employees through effective and accurate
communication to dispel any anxieties for there to be job satisfaction (Kler et al., 2015).
Nadinloyi et al. (2013) sought to examine the relationship between job satisfaction and
mental health. The findings based on their hypothesis indicate there was a relatively weak
but significant correlation between anxiety and job satisfaction meaning leaders need to
ensure there is minimum or no anxiety for job satisfaction to grow. However, according
to Agarwal (2015) who measured the relationship of job stress and job satisfaction in the
Indian IT Sector, there is no relationship between job stresses to job satisfaction. The
discussion shows the results on the correlation differ though most studies indicate that
stress is negatively correlated to job satisfaction as found in this study.
The chi-square test was used to determine the strength of association between job security
as the moderating variable and job satisfaction. The results showed that there was a
significant association between job security as the moderating variable and job
satisfaction X2 (144, N = 347) = 664.814, p<.05). The job security variables were anxiety,
fairness and stress. These results showed that anxiety, fairness and stress are job security
variables which affect job satisfaction. Darko E.O and Darko (2015), in Ghana noted that
as a result of high competition in the banking industry, employees are now expected to
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work harder to ensure they retain and attract new business which affects their job
security. This emanates from the fact that organizations depend on people to achieve their
objectives and when there is no job satisfaction then the employees are faced with choices
of whether to quit or remain on the job. This negatively affects the organizational
effectiveness (Tetteh & Brenyah, 2016).
According to Islam and Rahman (2016), the banking industry has been curbed by
problems like extended working hours, pressure, non-conducive working environments,
lack of fairness, reducing career growth opportunities and poor treatment. All these have
a significant impact on the level of organizational commitment and job satisfaction.
Thorsteinsson et al. (2014) examined the association between stress, organizational
support and staff health which incorporated anxiety, depression and fatigue together with
work outcomes like turnover intentions, organizational commitment and job satisfaction.
The findings indicate that high work stress was associated with worse staff health like
anxiety, depression and fatigue all of which lead to negative work outcomes like low job
satisfaction, high turnover intentions and less organizational commitment. These results
are generalizable to the banking sector where job security affects job satisfaction.
The One-way ANOVA test results showed that there was no significant difference
between the mean values of the entire respondent’s demographic data on job security and
job satisfaction. The demographic information included; gender, age, education level,
duration of working at the bank. Different researchers have found out that job satisfaction
is not determined by an individual’s characteristics but by other factors. Umair et al.
(2016) investigated the employee’s perception of fairness in the performance appraisal
system and the effect this had on job satisfaction of the employees. They found that the
perception of fairness consisted of distributive justice, procedural justice and interactional
justice which had an impact on job satisfaction. Lin et al. (2014) conducted a study on
role stress and job satisfaction among bank employees in Sabah, Malaysia. The results
indicate that there was a significant role of stress attributed to bank characteristics of
extended working hours, pressure, non-conducive working environments, lack of fairness,
reducing career growth opportunities and poor treatment (Islam & Rahman, 2016). These
discussions can be summarized by Yousef (1998) who found out that the importance of
job security comes from its influence on work related outcomes for example employee
health, turnover and job satisfaction.
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The results of multiple linear regression revealed that job security had a significant
moderating effect between transformational leadership and job satisfaction (R2 = .446,
F(5, 27.760) = 54.780, p<.05). Additionally, the analysis revealed that the regression
coefficient for job security was statistically significant (β = .384, t (.622) = 6.011, p<.05).
This showed that with the moderating effect of job security, transformational leadership
predicted job satisfaction. Thus, job security is a key factor in determining job
satisfaction. Studies have revealed that lack of job security has consequences among them
turnover intentions which consequently affect the job satisfaction. This also affects the
quality of service rendered to customers, productivity and ultimately the overall
organizational success. Knowledge of this and a vision of the bigger picture of the
consequences of turnover and job satisfaction should spur leaders into providing the best
environments to obviate the lack of job security (Joarder & Ashraf, 2012).
Allan et al. (2016) conducted a research on meaningful work and mental health with job
satisfaction as a moderator. The study found that having meaningful work was associated
with better mental health meaning lower rates of depression, anxiety and stress.
Meaningful work predicted lower depression but did not significantly predict anxiety or
stress. Thus, meaningful work contributes to the level of job satisfaction. Khan et al.
(2013) conducted a research to establish whether job satisfaction of operational staff in
Islamic banks was determined through organizational climate, occupational stress, age
and gender. The results revealed that organizational climate and occupational stress have
a significant impact on the level of job satisfaction. These research findings support the
results of this study which indicate that job security influences job satisfaction.
5.4 Conclusions
This section presents the conclusions based on the findings of the study. The presentation
is done according to the research questions.
5.4.1 Influence of Idealized Influence on Job Satisfaction
The multiple linear regression test results revealed that idealized influence had a
significant influence on job satisfaction (R2 = .246, F(1, 97.750) = 112.421, p<.05). As a
result, the null hypothesis that there was no significant influence of idealized influence on
job satisfaction among employees in commercial banks in Kenya was rejected. The study
concluded that idealized influence significantly influenced job satisfaction among
employees in commercial banks in Kenya.
192
5.4.2 Influence of Individualized Consideration on Job Satisfaction
The multiple linear regression test results revealed that individualized consideration had a
significant influence on job satisfaction (R2 = .354, F(1, 138.779) = 188.851, p<.05). As a
result, the null hypothesis that there was no significant influence of individualized
consideration on job satisfaction among employees in commercial banks in Kenya was
rejected. The study concluded that individualized consideration significantly influenced
job satisfaction among employees in commercial banks in Kenya.
5.4.3 Influence of Inspirational Motivation on Job Satisfaction
The multiple linear regression test results revealed that inspirational motivation had a
significant influence on job satisfaction (R2 = .344, F(1, 126.302) = 180.980, p<.05). As a
result, the null hypothesis that there was no significant influence of inspirational
motivation on job satisfaction among employees in commercial banks in Kenya was
rejected. The study concluded that inspirational motivation significantly influenced job
satisfaction among employees in commercial banks in Kenya.
5.4.4 Influence of Intellectual Stimulation on Job Satisfaction
The multiple linear regression test results revealed that intellectual stimulation
significantly influenced job satisfaction (R2 = .292, F(1, 106.274) = 142.533, p<.05). As a
result, the null hypothesis that there was no significant influence of intellectual
stimulation on job satisfaction among employees in commercial banks in Kenya was
rejected. The study concluded that intellectual stimulation significantly influenced job
satisfaction among employees in commercial banks in Kenya.
5.4.5 Moderating effect of Job Security on the Influence of Transformational
Leadership on Job Satisfaction
The multiple linear regression test revealed that job security had a significant moderating
effect between transformational leadership and job satisfaction (R2 = .446, F(5, 27.760) =
54.780, p <.05). As a result, the null hypothesis that there was no significant moderating
effect of job security between transformational leadership and job satisfaction among
employees in commercial banks in Kenya was rejected. The study concluded that job
security has a significant moderating effect on the influence of transformational
leadership and job satisfaction among employees in commercial banks in Kenya.
193
5.5 Recommendations
This section presents suggestions for improvement based on the findings of the study and
also presents suggestions for further research.
5.5.1 Suggestions for Improvement
5.5.1.1 Influence of Idealized Influence on Job Satisfaction
The study established that idealized influence significantly influenced job satisfaction
among employees in commercial banks in Kenya. Based on the finding, the leaders of
banks should leverage on idealized influence to enhance job satisfaction among the
employees. To achieve this, they can demonstrate or model how the employees should
behave through charisma. Additionally, being trustworthy and ethical will help to
enhance job satisfaction among the employees.
5.5.1.2 Influence of Individualized Consideration on Job Satisfaction
The study established that individualized consideration significantly influenced job
satisfaction among employees in commercial banks in Kenya. Based on the finding,
leaders in the commercial banks should leverage on individualized consideration to drive
job satisfaction among the employees. This can be achieved through mentorship, support
and delegation. These aspects demonstrate concern and care for the employees needs.
This helps in boosting the job satisfaction among the employees.
5.5.1.3 Influence of Inspirational Motivation on Job Satisfaction
The study established that inspirational motivation significantly influenced job
satisfaction among employees in commercial banks in Kenya. As a result, the leaders in
the commercial banks should use inspirational motivation elements to drive and sustain
job satisfaction. Motivation can be achieved through communication, encouraging
teamwork and providing motivational elements in the workplace which promote job
satisfaction among the employees.
5.5.1.4 Influence of Intellectual Stimulation on Job Satisfaction
The study established that intellectual stimulation significantly influenced job satisfaction
among employees in commercial banks in Kenya. Therefore, leaders in commercial banks
194
need to stimulate their employees in order to enhance and sustain their job satisfaction.
This can be achieved through knowledge sharing and allowing creativity among the
employees. As much as some of the jobs in commercial banks can be routine, the
leadership needs to develop ways of stimulating the intellect of the employees. This will
in turn drive job satisfaction among the employees.
5.5.1.5 Moderating Effect of Job Security on the Influence of Transformational
Leadership on Job Satisfaction
The study established that job security significantly moderated the relationship between
transformational leadership and job satisfaction among employees in commercial banks in
Kenya. It is therefore important that leaders in commercial banks ensure employees have
job security which positively influences job satisfaction significantly. The lack of job
security negatively influences job satisfaction. Job security can be provided by ensuring
there is fairness, effective communication to reduce anxiety, no stress and that the work
environment is habitable. Aspects of lack of fairness, factors leading to anxiety and stress
should be eliminated in order to enhance job security among the employees.
5.5.2 Suggestions for Further Research
This study sought to establish the influence of transformational leadership on job
satisfaction among employees in commercial banks in Kenya. This was a cross-sectional
study carried out when commercial banks in Kenya were going through a lot of
turbulence due to new legislation which capped the interest rates. As a result, this led to a
reduction in the profitability of the commercial banks. Additionally, the country was
going through an electioneering period which resulted in reduced business for the
commercial banks. Based on this, most banks had to review their strategies to cut on costs
and most chose to leverage on electronic platforms and reduce investments in brick and
motor. As a result, most banks were downsizing through staff lay-offs and early
retirement programs which caused a lot of anxiety among the employees in the industry
due to lack of job security. This situation could have influenced the lack of job
satisfaction among the employees in the banking sector at the particular time this study
was carried out. Therefore, future research should carry out a study on the influence of
transformational leadership on job satisfaction among employees in other sectors such as
the microfinance institutions in Kenya at a time when the industry will have stabilized.
195
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APPENDICES
Appendix I: Cover Letter
4th August, 2017
Dear Respondent,
I am a Doctoral candidate in the Business Administration program at United States
International University of Africa (USIU – Africa). As part of my doctoral degree
requirement, I am expected to successfully conduct Applied Research on a relevant topic
in my area of concentration which is Leadership and Change Management.
This study will focus on The Influence of Transformational Leadership on Job
Satisfaction among employees in Kenyan Banks.
I would like to humbly request that you spend some time (10-15 minutes) to complete this
questionnaire to the best of your knowledge. Thank you in advance for accepting to be a
positive contributor to our society. I assure you that your responses will be treated with
utmost confidentiality.
To maintain anonymity, I request that you do not write your name on the questionnaire.
The findings of this study will go help bank managers institute the effective leadership
style which will positively influence job satisfaction among employees in the banking
sector.
Yours Sincerely,
Andrew Njiraini Njiinu (Doctoral Candidate)
For more information, please contact me on:
Cell: 0723 869 792
Email: [email protected]
225
Appendix II: Questionnaire
This questionnaire has five sections which will cover general and demographic data,
influence of idealized influence on job satisfaction, influence of individualized
consideration on job satisfaction, influence of inspirational motivation on job satisfaction,
influence of intellectual stimulation on job satisfaction and the moderating effect of job
security on the influence of transformational leadership on job satisfaction.
Instructions: Please tick in the appropriate box. You are requested to complete this
questionnaire as honestly and objectively as possible.
SECTION A: DEMOGRAPHIC AND GENERAL INFORMATION
Please tick (√) appropriately within the box provided
1. What is your gender?
Male [ ] Female [ ]
2. What is your age bracket?
21-29 years [ ] 30-39 years [ ] 40-49 years [ ] 50-59 years [ ] Over 60 years [ ]
3. What is your highest level of education?
Certificate [ ] Diploma [ ] Bachelor’s Degree [ ] Master’s Degree [ ] PhD [ ]
4. How long have you worked in the Bank?
0-5 years [ ] 6-10 years [ ] 11-15 years [ ] 16-20 years [ ] Over 20 years [ ]
5. What is the Tier of your bank?
Tier I [ ] Tier II [ ] Tier III [ ]
226
SECTION B: INFLUENCE OF IDEALIZED INFLUENCE ON JOB
SATISFACTION
This section focuses on the influence of idealized influence on job satisfaction.
Idealized influence is the capability to exert influence by serving as a role model. It brings
out positive emotions from employees and makes them desire to emulate the leader who
is a role model. It is achieved through charisma, trust and ethics. Job satisfaction is an
emotional state or a pleasurable experience of an employee from the expectations of the
job and the reality of the job situation.
Using a scale of 1-5, where one 1 = Strongly Disagree (SD), 2 = Disagree (D), 3 =
Neutral (N), 4 = Agree (A) and 5 = Strongly Agree (SA), indicate the extent to which you
agree or disagree with the following statements by ticking the box that best represents
your opinion on each statement.
Idealized Influence 1 2 3 4 5
SD D N A SA
My leader has charismatic attributes
My leader demonstrates trust in my abilities
My leader is ethical in the workplace
Influence of Idealized Influence on Job Satisfaction
I am committed to the organization because my leader
has charismatic attributes
I am hardly absent from work because my leader
demonstrates trust in my abilities
I have no intentions of leaving my job because my
leader is ethical in the workplace
227
SECTION C: INFLUENCE OF INDIVIDUALIZED CONSIDERATION ON JOB
SATISFACTION
This section focuses on the influence of individualized consideration on job satisfaction.
Individualized consideration is the degree to which the leader attends to the needs of the
employees by displaying attention to their developmental needs. It involves leaders
offering mentorship, coaching and support to the needs of the employees. Job satisfaction
is an emotional state or a pleasurable experience of an employee from the expectations of
the job and the reality of the job situation.
Using a scale of 1-5, where one 1 = Strongly Disagree (SD), 2 = Disagree (D), 3 =
Neutral (N), 4 = Agree (A) and 5 = Strongly Agree (SA), indicate the extent to which you
agree or disagree with the following statements by ticking the box that best represents
your opinion on each statement.
Individualized Consideration 1 2 3 4 5
SD D N A SA
My leader mentors me in the workplace
My leader supports me in my work
My leader delegates work to me
Influence of Individualized Consideration on Job Satisfaction
I am committed to the organization because my leader mentors
me in the workplace
I am hardly absent from work because my leader supports me in
my work
I have no intentions of leaving my job because my leader
delegates work to me
228
SECTION D: INFLUENCE OF INSPIRATIONAL MOTIVATION ON JOB
SATISFACTION
This section focuses on the influence of inspirational motivation on job satisfaction.
Inspirational motivation is the ability of a leader to behave in a way that inspires,
motivates and generates enthusiasm from employees. It is achieved through
communication, teamwork and motivation. Job satisfaction is an emotional state or a
pleasurable experience of an employee from the expectations of the job and the reality of
the job situation.
Using a scale of 1-5, where one 1 = Strongly Disagree (SD), 2 = Disagree (D), 3 =
Neutral (N), 4 = Agree (A) and 5 = Strongly Agree (SA), indicate the extent to which you
agree or disagree with the following statements by ticking the box that best represents
your opinion on each statement.
Inspirational Motivation 1 2 3 4 5
SD D N A SA
My leader encourages two-way communication
My leader promotes teamwork among employees
My leader’s behavior motivates me at work
Influence of Inspirational Motivation on Job Satisfaction
I am committed to the organization because my leader
encourages two-way communication
I am hardly absent from work because my leader promotes
teamwork among employees
I have no intentions of leaving my job because my leader’s
behavior motivates me at work
229
SECTION E: INFLUENCE OF INTELLECTUAL STIMULATION ON JOB
SATISFACTION
This section focuses on the influence of intellectual stimulation on job satisfaction.
Intellectual stimulation refers to the leader’s actions which persuade the employees to use
their sense of logic to analyze situations using their creative thinking to find solutions. It
involves creativity and innovation, risk taking and knowledge sharing. Job satisfaction is
an emotional state or a pleasurable experience of an employee from the expectations of
the job and the reality of the job situation.
Using a scale of 1-5, where one 1 = Strongly Disagree (SD), 2 = Disagree (D), 3 =
Neutral (N), 4 = Agree (A) and 5 = Strongly Agree (SA), indicate the extent to which you
agree or disagree with the following statements by ticking the box that best represents
your opinion on each statement.
Intellectual Stimulation 1 2 3 4 5
SD D N A SA
My leader encourages knowledge sharing among employees
My leader permits me to be creative in my job
My leader allows me to take risks in my job
Influence of Intellectual Stimulation on Job Satisfaction
I am committed to the organization because my leader
encourages knowledge sharing among employees
I am hardly absent from work because my leader permits me
to be creative in my job
I have no intentions of leaving my job because my leader
allows me to take risks in my job
230
SECTION F: MODERATING EFFECT OF JOB SECURITY ON THE
INFLUENCE OF TRANSFORMATIONAL LEADERSHIP ON JOB
SATISFACTION
This section focuses on the moderating effect of job security on the influence of
transformational leadership on job satisfaction.
Job security refers to expectations regarding the continuity of a job situation and goes
over and above the loss or retention of a job to the continuation or loss of certain
desirable job features such as promotion opportunities and favorable working condition. It
is influenced by anxiety, fairness and stress. Job satisfaction is an emotional state or a
pleasurable experience of an employee from the expectations of the job and the reality of
the job situation.
Using a scale of 1-5, where one 1 = Strongly Disagree (SD), 2 = Disagree (D), 3 =
Neutral (N), 4 = Agree (A) and 5 = Strongly Agree (SA), indicate the extent to which you
agree or disagree with the following statements by ticking the box that best represents
your opinion on each statement.
Job Security 1 2 3 4 5
SD D N A SA
My leader encourages fair treatment to everyone
My leader’s behavior does not cause me stress
My leader does not leave room for anxiety
Influence of Job Security on Job Satisfaction
I am committed to the organization because my leader
encourages fair treatment to everyone
I am hardly absent from work because my leader’s behavior
does not cause me stress
I have no intentions of leaving my job because my leader
does not leave room for anxiety
231
Appendix III: USIU Research Introduction Letter
232
Appendix IV: NACOSTI Research Permit
233
Appendix V: Classification of Banks in Tiers
Tier One Banks
No Bank Name
1 Kenya Commercial Bank
2 Standard Chartered Bank Kenya Limited
3 Barclays Bank of Kenya Limited
4 Commercial Bank of Africa Limited
5 Co-operative Bank of Kenya Limited
6 Diamond Trust Bank Limited
7 Equity Bank Limited
Tier Two Banks
No Bank Name
1 National Bank of Kenya Limited
2 Citibank N A
3 Bank of Africa Kenya Limited
4 Chase Bank Limited
5 Stanbic Bank Kenya Limited
6 NIC Bank Limited
7 ECO Bank Limited
8 I&M Bank Limited
9 Housing Finance Bank
10 Family Bank Ltd
11 Bank of India
12 Bank of Baroda (Kenya Limited)
13 Prime Bank Limited
14 Imperial Bank Limited
234
Tier Three Banks
No Bank Name
1 Habib Bank Limited
2 M-Oriental Bank Limited
3 Habib Bank A G Zurich
4 Middle East Bank Kenya Limited
5 Consolidated Bank of Kenya Limited
6 Credit Bank Limited
7 Trans-National Bank Limited
8 African Banking Corp. Bank Ltd
9 Giro Commercial Bank Limited
10 Spire Bank Ltd
11 Paramount Universal Bank Limited
12 Jamii Bora Bank
13 Guaranty Trust Bank ( Kenya) Ltd.
14 Victoria Commercial Bank Limited
15 Guardian Bank Limited
16 Development Bank of Kenya Limited
17 Fidelity Commercial Bank Limited
18 Sidian Bank Limited
19 Gulf African Bank Ltd
20 First Community Bank
21 UBA Kenya Bank Ltd
22 Dubai Bank of Kenya Ltd