các nhân tố tác động lên lòng trung thành người lao động tại điện lực Hải Dương

Shu - Te University
College of Management
Graduate School of Business Administration
Master
An Influence Factors Study on Job Satisfaction of Employees at
Hai Duong Power Company, Hai Duong Province, Vietnam
Student: Pham Tuan Ngoc
ID: s99733421
Advisor: Dr. Wang Jau Shyong
Co-Advisor: Dr. Sheng Jung Li
Dr. Nguyen Danh Nguyen
September, 2013

Shu-TeUniversity
GraduateSchoolof
BusinessAdministrationThesis
AnInfluenceFactorsStudyonJobSatisfactionof
EmployeesatHaiDuongPowerCompany,HaiDuong
Province,VietnamongPowerCompany,HaiDuong
Province,Vietnam
PhamTuanNgocSeptember,2013

An Influence Factors Study on Job Satisfaction of Employees at Hai
Duong Power Company, Hai Duong Province, Vietnam
ID: s99733421
Advisor: Dr. Wang Jau Shyong
Co-Advisor: Dr. Sheng Jung Li
A Thesis
Submitted to the
College of Management
Shu-Te University
In Partial Fulfillment of the Requirements
For the Degree of
Master of Science in
Business Administration
September, 2013

Shu-Te University
An Influence Factors Study on Job Satisfaction of Employees at Hai Duong
Power Company, Hai Duong Province, Vietnam
Advisor: Dr. Wang Jau Shyong Co-Advisor: Dr. Sheng Jung Li
Abstract
The main purpose of the study is to test the relationship between variables in JDI
model with general job satisfaction. The research results are obtained from actual
survey at Hai Duong Power Company with 200 employees. The research method in this
study is quantitative method with statistical techniques such as: testing by Cronbach
Alpha coefficient, explore factor analysis, correlation analysis and regression analysis.
The research results show that there are four in five factors in JDI model affecting job
satisfaction including: (1) work, (2) promotion opportunities; (3) co-workers, and (4)
supervisors. In demographic variables, the factor “age” has impact on the satisfaction
with job of employees. The study also suggests some solutions and recommendations
for company’s managers to improve job satisfaction of employees. And in the last, the
study points out limitations and directions for further researches in the same research
fields.
Key words: job satisfaction, JDI, power.
i

Acknowledgements
During the time of conducting this thesis, I have received many helps from many
people. Without these helps, I have probably not finished my dissertation, so I would
like to express my thanks to all of you.
I know that this project was not my individual achievement, but the result of many
people to whom I will be forever grateful. Of those, I would like to express my sincere
gratitude to my wife, who has been my cheer leader since high school. Her unwavering
support through this process could never be fully articulated. Her role was fundamental
in the mailing and scoring of the survey materials, and she contributed countless hours
to the completion of this project. She is, and always will be my rock.
Special thanks to Dr. Jau- Shyong Wang who has stuck with me from the
beginning of this journey, and always been there to share his expertise and guidance. I
would also like to thank the other members of my committee and my classmates. Each
of you has assisted in the development and review of this project, and I am thankful to
you all.
I would also like to thank my supervisor Dr. Nguyen for their on-going support
and for being flexible with my work schedule while I attended classes.
Finally, I want to say thanks very much for Dr. Jau-Shyong Wang, Dr. Sheng-
Jung Li, and Dr. Nguyen Danh Nguyen again with their advises and supported.
Special thanks for your help
ii

Table of Contents
Abstract..............................................................................................................................i
Acknowledgements...........................................................................................................ii
Table of Contents.............................................................................................................iii
List of Tables....................................................................................................................vi
List of Figures.................................................................................................................vii
Chapter 1 Introduction.......................................................................................................1
1.1 Research Background..........................................................................................1
1.2 Research Motivations. ........................................................................................4
1.3 Research Purposes...............................................................................................4
1.4 Research Procedure ............................................................................................5
Chapter 2 Literature Review.............................................................................................7
2.1 Definition of job satisfaction...............................................................................7
2.2 Theories of job satisfaction.................................................................................7
2.2.1Maslow's hierarchy of needs.....................................................................8
2.2.2McClelland's achievement motivation theory...........................................9
2.2.3Vroom’s Expectancy theory....................................................................10
2.2.4Motivation theory ...................................................................................10
2.3 Advantages of employee satisfaction................................................................11
2.4 Factors affecting job satisfaction.......................................................................12
2.4.1 Work itself.............................................................................................12
2.4.2 Promotion opportunities.........................................................................12
2.4.3 Supervisors.............................................................................................13
2.4.4 Co-workers.............................................................................................13
2.4.5 Salary / Pay.............................................................................................14
2.5 The effects of job satisfaction............................................................................14
2.5.1 Overall Performance...............................................................................14
2.5.2 Quitting the job.......................................................................................15
2.5.3 Absence of work.....................................................................................15
iii

Chapter 3 Research Methodology...................................................................................17
3.1 The population and research sample.................................................................17
3.2 Measurements....................................................................................................18
3.2.1 The reliability of JDI..............................................................................18
3.2.2 The validity of JDI..................................................................................19
3.2.3 Reasons for selecting JDI......................................................................19
3.3 Research model and hypotheses.......................................................................20
3.4 Scales for research variables and design of questionnaire ...............................23
3.5 Data analysis......................................................................................................26
3.5.1. Descriptive statistics..............................................................................26
3.5.2. Scale verification...................................................................................26
3.5.3. Explore factor analysis..........................................................................26
3.5.4 Building regression function..................................................................27
3.5.5 Testing research hypotheses...................................................................27
Chapter 4 Research Results.............................................................................................29
4.1 Descriptive statistics .........................................................................................29
4.1.1 Gender...................................................................................................29
4.1.2 Age.........................................................................................................29
4.1.3 Education level.......................................................................................30
4.1.4 Work experience.....................................................................................31
4.2 Results from questionnaire................................................................................31
4.3 Testing the reliability of scales and observed variables in the model...............32
4.3.1 Testing scales for factor “work”............................................................33
4.3.2 Testing scales for factor “promotion opportunities”.............................33
4.3.3 Testing the scales for factor “salary”.....................................................34
4.3.4 Testing scales for factor “supervisors”..................................................34
4.3.5 Testing scales for factor “co-workers”..................................................35
4.3.6 Testing scales for the dependent variable “job satisfaction”.................35
4.4 Explore factor analysis......................................................................................36
4.4.1 Explore factor analysis with independent variables..............................36
iv

4.4.2 Explore factor analysis with the dependent variable “job satisfaction”39
4.5 Building regression function and testing research hypotheses .........................39
4.5.1 Estimating regression function from data set .......................................40
4.5.2 Testing research hypotheses..................................................................41
4.6 Testing the differences between different groups of employees by demographic
variables ..................................................................................................................42
4.6.1 Testing differences between variables by gender..................................43
4.6.2 Testing differences between variables by age.......................................46
4.6.3 Testing differences between groups by education level........................49
4.6.4 Testing differences between groups by work experience......................50
4.7 Discussion..........................................................................................................51
Chapter 5 Conclusions and Recommendations ..............................................................53
5.1 Conclusions.......................................................................................................53
5.2 Recommendations from research results...........................................................53
5.3 The importance of the study..............................................................................54
5.4 Limitations of the study.....................................................................................54
5.5 Directions for future researches.........................................................................54
References.......................................................................................................................55
Appendix.........................................................................................................................58
v

List of Tables
Table 1. Results of business targets in 2012......................................................................3
Table 2. The results from questionnaires.......................................................................31
Table 3. Results from testing scales for factor “work”...................................................33
Table 4. Results from testing the scales for factor “promotion opportunities”...............34
Table 5. Results from testing scales for factor “salary”..................................................34
Table 6. Results from testing scales for factor “supervisors”.........................................35
Table 7. Results from testing scales for factor “co-workers”..........................................35
Table 8. Results from testing scales for the dependent variable “job satisfaction”........36
Table 9. KMO and Bartlett's Test with independent variables........................................36
Table 10. Total variance extracted of independent variables..........................................37
Table 11. Rotated Component Matrix of independent variables.....................................37
Table 12. KMO and Bartlett's Test with the dependent variable....................................39
Table 13. Total Variance Explained with the dependent variable...................................39
Table 14. Component Matrixa.........................................................................................39
Table 15. Model Summaryb............................................................................................40
Table 16. ANOVAa.........................................................................................................40
Table 17. Coefficientsa....................................................................................................40
Table 18. Statistics by gender group...............................................................................43
Table 19. Independent Samples Test.............................................................................43
Table 20. Variance analysis by age................................................................................46
Table 21. Result from analysis of multi groups by Tukey value.....................................47
Table 22. Variance analysis by education level..............................................................49
Table 23. Variance analysis by work year.......................................................................50
vi

List of Figures
Figure 1. Research Structure.............................................................................................5
Figure 2. Maslow’s Model................................................................................................8
Figure 3. The Porter and Lawler Model..........................................................................11
Figure 4. The research model..........................................................................................21
Figure 5. Sample structure by Gender.............................................................................29
Figure 6. Sample structure by Age..................................................................................30
Figure 7. Sample structure by Education Level..............................................................30
Figure 8. Sample structure by year experience...............................................................31
vii

Chapter 1 Introduction
This chapter will introduce the research background, research motivations,
research purposes and research procedures. The contents in detail are as follows:
1.1 Research Background
The trend of regionalization and globalization put more stress on competition
among businesses. To sustain and develop in a market, all business are required to
obtain a unique strengthen to have advantage over other businesses in any competition
and affirm its position. Changes in business sector have to accept that the only
advantage as well the most sustainable advantage is human.
Any changes in business sector increase more stress, pressure on companies,
requiring them to change, take initiative in creation, utilizing advanced techniques,
creating new products and new services to meet the increasing need of customers.
Meanwhile, it also requires that Company to attract more qualified employee, maintain
and improve their human resources.
One of the leading criterions for assessing quality of investment environment is
labor resources. It is impossible for a business to make a breakthrough step if their
employees are unqualified or dishonest. The organization of their employees must be
proficient to maximize their strength.
According to human resources experts, assessment job satisfaction of a staff is a
key task for a business to develop human resource sustainably. Of course, this task must
be implemented upon some criterions for different position and must be carried out
periodically in-person discussion basis. There is no good if an employee is recruited
without a job description. Because without a job description, the candidates cannot
imagine his/her tasks to express him/her during the interview and then when he/she is
recruited, it is very hard for this person to work. In many cases, they are afraid of being
unfair treated. The bonus – punish regime must be fair and transparency, so does the
employee appraisal. Besides that, in appointing a position, the leader must consider the
characteristics of an employee to make the most suitable coordination between different

people with different characteristic to make a good team (of which everybody can fulfill
the other).
In the context of present direct competition, there are various reasons for a staff to
quit his/her job, such as feeling unsatisfied with material interests, no respect, no
sharing from supervisors, no motivation, no promotion, no training, unclear policy,
strict supervise, no coordination from colleagues, unfairness, bad working environment,
no democracy, etc. If the human resource is not planned efficiently, the business will
face damaged troubles if anything wrong happen.
In Vietnam, the study of satisfaction of employees (if any) shall only be
conducted internally by the HR department is responsible. This is still pretty much
limited as much experience not to influence errors, expensive cost and time investment,
no concrete results with the goal of what to do, not the Human Resources department
creates enough influence to convince operating successful.
Black & Porter (2000) showed that all activities within an organization can be
traced to human involvement and capabilities. The factors determining job satisfaction
has been extensively researched in many developed countries in the world (Cranny et al.
1992).
Similarly, Ting (1997) states that empirical evidence consistently indicates that
job characteristics such as pay satisfaction, opportunities for promotion, task clarity and
relationships with co-workers and supervisors have significant effects on job
satisfaction of employees. In support, a study conducted by Ellickson and Logsdon
(2002) reflected that job satisfaction of employees was significantly influenced by
perceptions of employee satisfaction in terms of pay, promotional opportunities,
relationships with supervisors, employees performance management systems and fringe
benefits.
Some information about Hai Duong Power Company (HDPC)
Company’s name: Hai Duong MTV Power Co., Ltd - North Power Corporation.
Date of establishment: 08-4-1969.
Headquarter: No. 33 Ho Chi Minh Avenue - Hai Duong City - Hai Duong
Province

Pursuant to the Charter of organization and operation of Hai Duong MTV Power
Co., Ltd, which is approved by Chairman of the company, the production model of Hai
Duong Power Company is arranged as follows:
Hai Duong MTV Power Co., Ltd has 1.300 staffs with following classification of
education level:
Male employees: 839 persons (74,45 %); female employees: 288 persons
(25,55%).
Employees above university-level: 20 persons (1,54 %)
Employees at university-level: 601 persons (46,23 %)
Employees at college-level: 147 persons (11,31 %)
Employees at intermediate-level, and workers: 532 persons (40,92%)
Company leaders including President as well as Director; 01 Comptroller; 04
Deputy Directors; 01 Union president and Vice Secretary of the Party Committee
Advisory unit: include 13 division departments
Production unit: 12 powers; 1 factory;
Auxiliary Unit: 01 Power testing factory; 01 facility repairing factory, 01 power
installation factor, 01 design consultancy factory, and 01 Project Management
department.
Table 1. Results of business targets in 2012
No Targets Unit Assigned tasks Performance
Comparing
ratio
1 The loss of electricity kWh 3.184.738.738
2 Commercial power kWh 2.683.000.000 2.687.259.908 1,00
3
The electricity loss
percentage
% 6.30 6.14 -0,16
4
Average electricity
price
VND/kwh 1240,10 1.244,71 4,61
5 Total revenue millions 3.327.188,30 3.352.220,56 1,01
6
Total number of
clients
contract 481.263

1.2 Research Motivations.
In this thesis, the main motives that promote author to research are:
 Hai Duong Power Company is facing up with the challenges and difficulties,
most of which is human resource management.
 There is in the company lack of qualified and skilled staffs; working condition
with high risks, and the pay and appraisal systems is not good and does not motivate
employees.
 Many staffs feel dissatisfied when they have to travel far to work.
 No research on the job satisfaction of the staff at Hai Duong Power Company
before.
In addition, Development of a research program on employees’ satisfaction in
power companies in Vietnam in this period is very important. After many years of
working, the managers as well the employees tried to run and develop a Company.
However, recently, while the managers tried to promote the business, they faced
troubles with human resources. During the last 3 years, number of staff who left the
Company is high. There are many reasons for this problem and this fact affect badly on
Company’s income and image.
1.3 Research Purposes
 To find out what factors affect job satisfaction among HDPC employees and to
investigate job satisfaction in HDPC.
 Assessment the difference in Job satisfaction between staffs to identify
dimensions that influence to Job satisfaction, such as: Gender, Work position,
Education level, working experience years.
 To propose solutions to acquire higher job satisfaction in Hai Duong Power
Company.

1.4 Research Procedure
The procedures of this study are shown in figure 1
Figure 1. Research Structure
Step 1: Defining research objectives: At this step, the author identifies research
issues and objectives of the study, in details here is evaluating the satisfaction with job
of employees at Hai Duong Power Company. The purpose is to evaluate factors
affecting job satisfaction of employees and how demographic factors influence job
satisfaction; as well as the impact intensity of each factor on general satisfaction level.
Step 2: Writing chapter 1: At this step, the author does based on instructions from
STU on necessary contents for the part of introduction including: research background,
research motivations, research methodology, and research procedure.

Step 3: Writing chapter 2: This is the step at which the author collects results
from previous studies on job satisfaction, about definitions, theories of job satisfaction,
factors affecting job satisfaction, and the effect of job satisfaction with research units.
Step 4: Writing chapter 3: Based on theoretical basics, model and results from
other researches, the author will build an appropriate research model to select as an
official theoretical model for the study. In detail in this study, the author selects JDI
model and other necessary methods to achieve posed research purposes.
Step 5: Designing questionnaire: Questionnaire will be designed and trial done to
get comment and opinions from research objects. After that, they will be adjusted to get
the final official research for actual survey.
Step 6: Collecting data: After completing questionnaire for actual survey,
questionnaire will be distributed to employees to get actual data for analysis. Obtained
data will be cleaned and analyzed.
Step 7: Analyzing data: Data after cleaned will be analyzed with the support of
SPSS software by such as: testing the reliability of scales, explore factor analysis,
regression analysis, and variance analysis to get answers for questions posed in the part
of research purposes.
Step 8: Conclusions and recommendations: This is the last step of the study.
Based on the results from data set, the author will summarize main results and propose
solutions as well as directions for further researches. At the same time, the author also
generally rechecks all parts and completes the thesis.

Chapter 2 Literature Review
This chapter will present contents of theories on job satisfaction, advantages of
creating job satisfaction, factors affecting job satisfaction, and effects of job satisfaction
on employees. The contents in detail are as follows:
2.1 Definition of job satisfaction
Job satisfaction is not a unified concept because it comes from different
perspectives of other researchers. Kusku (2003) supposes that job satisfaction reflects
needs, desires and perceived feelings of employees about their job. This definition
comes from the theory of Maslow's hierarchy of needs (1943) which supposes that
employees feel satisfied if their needs are met from low to high level. Wright and Kim
(2004) also suppose that job satisfaction is the appropriateness between what employees
want from job and what they feel about job. Some other researchers consider job
satisfaction as positive feeling state of employees with job and it is expressed through
their behavior and belief (Vroom, 1964; Locke, 1976; Quinn and Staines, 1979; Weiss
et al, 1967).
Some researchers suppose that job satisfaction is the satisfaction with aspects of
job. The level of satisfaction with each aspect of job will affect attitudes and awareness
of employees. This is clearly proven in the research on Job Descriptive Index (JDI) of
Smith et al (1969 quoted from Luddy, 2005). In the research of Smith et al, job
satisfaction is expressed in five main factors including: (1) work, (2) promotion
opportunities, (3) supervisors, (4) co-workers, and (5) salary. These aspects of job from
Smith’s study are also recognized by many researchers in different researches (Spector,
1997; Tran Kim Dung, 2005; Luddy, 2005).
In general, there are two ways to define job satisfaction including (1) considering
job satisfaction as a general variable that brings emotional nature (positive and negative)
of employees with job affecting their belief and attitudes; (2) considering job in
different separate aspects of job. In this study, job satisfaction is mentioned both in
aspects of job and general satisfaction of employees.
2.2 Theories of job satisfaction

2.2.1 Maslow's hierarchy of needs
According to Maslow, there are numerous levels of human satisfaction in
order from bottom to top. Accordingly, people all have five types of need as
follows (figure):
Figure 2. Maslow’s Model
In which:
Level 1: Basic needs or biological needs including needs to ensure human
existence such as eating, drinking, wearing, surviving, developing race and other
needs of the body.
Level 2: Needs for security and safety: needs for protection from elements,
security, order, law, limits, stability, etc.
Level 3: Social needs or needs for linking and acceptance: needs for love,
for friends, for being accepted, etc.
Level 4: Esteem needs: needs for self-respect, for others respect, for having
a status, etc.
Level 5: Needs for self-actualization or self-mobilization: needs for truth,
goodness, beauty, self-reliance, creativity, humor, etc.
These five levels of need are divided into two groups including low need
level (level 1 and 2), and high need level (level 3, 4, and 5). The differences

between these two groups are that: The low needs are endogenous needs
(physiological, safety needs, etc.) which are born from the inside demand of
people; and high needs or exogenous needs (communication, respect and self-
improvement needs, etc.) which are social need arising from external demands.
Maslow’s hierarchy of needs is widely recognized and applied in practice during
the 1960s and 1970s (Robins et al, 2002). The weakness of the theory of Maslow
is not to provide empirical evidences for the theory and some researches to
confirm its value also failed (Robins et al, 2002)
2.2.2 McClelland's achievement motivation theory
David Mc. Clelland (cited by Robbins et al, 2008) suggests that humans
have three basic needs: need for achievement, need for affiliation, and need for
power. In which:
(1) The need for achievement
People with high need for achievement are always trying to realize their
works better. They want to overcome difficulties and obstacles. They consider that
their successes or failures result from their actions. It means that they prefer
challenging tasks. This is the kind of people who work better when they are
motivated. Common characteristics of people with high need of achievement are:
- Desire to carry out personal responsibilities
- Tendency to set high goals for themselves
- High demand for specific and immediate responses
Mastering quickly and early their work
(2) The need for the affiliation
Similar to Maslow social needs, it is the need to be accepted such as needs
for love, need for friends. Employees have strong need for affiliation will work
well in the friendly and social working environment.
(3) The need for power
This is the need to control and influence others in their work environment.
Researchers point out that people with strong needs for power and for
achievement tend to become managers. Some also assume that successful

executives have the strongest need for powerful, followed by the need for
achievement and finally the need for affiliation.
2.2.3 Vroom’s Expectancy theory
Vroom (1964) suggests people are motivated at work to reach goals if they
believe in valence of those goals, and they can see the work they do can help them
to reach the goals. Vroom’s theory asserts that motivation at work is defined by
valence they put in their efforts’ outcome and multiplied by the belief they have.
In other words, Vroom’s theory indicates motivation is the product of expected
valence that people put in goals and opportunities they see to accomplish the
goals:
Motivational Force (MF) = Expectancy x Instrumentality x Valence.
When a person is indifferent of achieving goals, then his/ her passion is
considered equal to zero; and the passion will be below zero when that person
rejects reaching the goal; the results of the two situations are not motivation
created. Similarly, a person may have no motivation to reach the goal if
expectancy is zero or negative:
2.2.4 Motivation theory
E. Lawler (1974 cited from Robins et al 2002) developed a more complete
version of motivation depending upon expectancy theory built a more perfect
motivation model and mostly base on Expectancy theory (Figure 3).
As the model mentioned, all effort or strength of motivation depend on the
value of the reward and the probability or possibility of getting that reward. Next,
task performance is determined by motivation, ability to work of people
(knowledge and skills) and the perception of the tasks required. So performance is
the responsible factor that leads to intrinsic as well as extrinsic rewards. These
rewards, along with the equity of individual lead to satisfaction. Hence,
satisfaction of the individual depends upon the fairness of the reward.

Figure 3. The Porter and Lawler Model
This model is more appropriate to describe the system of motivation. The model
shows that motivation is not a simple cause and effect problem.
2.3 Advantages of employee satisfaction
Human resource is the decisive factor in the development of the organization
(Wheeland, 2002). To create loyalty and attachment to the organization, it is needed to
create employee satisfaction with the job they are doing. Creating job satisfaction and
loyalty helps organizations reduce the cost of recruitment, training and reduce errors in
the process of working down from the new employee. The staffs who are highly skilled
and experienced usually complete work in a short time compared to the new staffs
lacking of work experience.
The experts on quality in U.S. such as Deming or Juran said that job satisfaction
will lead to productivity and performance of the company. The expert on quality in
Japan as Ishikawa (1985) always stressed the importance of the "human element" to
create an environment of high quality work. Ishikawa supposed that effective quality
control should be based on people management. The research of Saari and Judge (2004)
Perceived
effort reward
probability
Perceived
Equitable reward
Perception of
task required
Ability to do
specific task
Value of rewards
Extrinsic
rewards
Intrinsic
reward
Performance
Accomplishm
ent
Satisfa
ction
Effo
rt

also showed that job satisfaction affects job performance of employees. In general,
research shows that job satisfaction will make employees more loyal, or strike down
state or increased union activity (Saari and Judge, 2004).
2.4 Factors affecting job satisfaction
Factors that affect job satisfaction of employees are described by JDI. These
factors include: work, promotion opportunities, supervisors, co-worker, and salary:
2.4.1 Work itself
The job satisfaction depends on the satisfaction with the work components,
such as the nature of job (Loke, 1995 cited from Luddy, 2005). The relevance of
the work to workers is expressed through many aspects of the nature of work: use
of different skills, employees' understanding the work process, and certain
importance of the work for the organization. In addition, the work must be in
accordance with workers' capacity. Many different studies tested relationship
between “work itself” and job satisfaction of employees (Luddy, 2005; Ha Nam
Khanh Giao, 2011; Chau Van Toan, 2009).
2.4.2 Promotion opportunities
Some researchers supposed that promotion opportunities closely link with
the job satisfaction of employees (Pergamit & Veum in 1999; Peterson et al, 2003;
Sclafane, 1999 cited from Luddy, 2005). This view is supported by research by
Ellickson and Logsdon (2002) which shows that advancement opportunities are
believed to have a positive influence job satisfaction. However Kreitner and
Kinicki (2001) supposed that positive relationships between development
opportunities and job satisfaction depend on fairness perceptions of employees. In
Vietnam, the studies of Tran Kim Dung (2005), Chau Van Toan (2009) with staffs
working in the office in Ho Chi Minh City also show that promotion opportunities
have positive impact on job satisfaction. The study of Ha Nam Khanh Giao (2011)
with employees working in the field of manufacture of beverages (Tan Hiep Phat
Corporation) also shows that the factor “promotion opportunities” has influence
on job satisfaction of employees.

In some studies in Vietnam (such as Tran Kim Dung, 2005; Ha Nam Khanh
Giao, 2011), the factor “promotion opportunities” is considered in aspects such as:
Fully professional trained, opportunities to improve the professional skills, create
opportunities for those who can afford, chance for individual developments, and
training and promotion policies are clear.
2.4.3 Supervisors
“Supervisor” is understood as the direct manager of employees. Supervisor
makes employees satisfied through their communication, their attention and care
for their subordinates, or their act of protecting employees when it is necessary,
and through demonstrating their leadership ability and professional capacity in
front of their staff (Robins et al, 2002).
In addition, employees feel satisfied with their supervisor thanks to their fair
treatment, or sincere recognition of employees' contribution. According to
Ramsey (1997, cited from Luddy, 2005), leadership affects working morale high
or low. Attitudes and behaviors of leaders for employees could also be factors
affecting the behavior or uncooperative co-workers. The leadership style
democracy creates more sympathy from employees. It can promote learning and
reduce the frustration in work when employees are motivated on time. Many
actual researches also show positive relationship between the factor “supervisors”
and job satisfaction (Koustelios, 2001; Peterson, Puia & Suess, 2003 cited from
Luddy, 2005; Tran Kim Dung, 2005; Ha Nam Khanh Giao, 2011).
2.4.4 Co-workers
C-workers are people working together in the organization or the people
working in the same department. Friendly co-worker relation will increase the
satisfaction with job of employees (Johns, 1996; Kreitner & Kinicki in 2001 cited
from Luddy, 2005). The factor “co-workers” is considered good is in the
organization, employees are always willing to help each other, work together
effectively, treat well, working environment is friendly, and employees have
reliable relations. The relationship between factor “co-workers” and “job
satisfaction” is tested in many different studies. The study of Madison (2000 cited

from Luddy, 2005) with 21.000 women showed that for works that require
rigorous without the support of colleagues, the ability of dissatisfaction with job
of employees will be higher. Many actual researches also showed positive
relationship between co-worker’s supports and the job satisfaction (Luddy, 2005;
Chau Van Toan, 2009; Ha Nam Khanh Giao, 2011; Pham Van Manh, 2012).
2.4.5 Salary / Pay
The salary is the amount the employee earned while completing the job.
Some studies suggest that there is little empirical evidence that wages affect job
satisfaction. Workers may have high-income but they still do not feel satisfied
with job if it does not fit their capacity and skills or they do not fit in with work
(Bassett, 1994 cited from Luddy, 2005). However, the study of Oshagbemi (2000)
showed the relationship between salary and job satisfaction by statistical analysis.
The factor “salary” in this study is considered in some aspects such as: the
mismatch between salary and employee's contribution, employees can live on
their salary, or the reward and allowances policies are fair. In addition, the author
also compares salary of employees at the company with other units. We can see
that in the conditions of Vietnam, salary or income is still an important factor
affecting job satisfaction (Tran Kim Dung, 2005; Pham Van Manh, 2012).
JDI becomes more popularly to evaluate the satisfaction level with job. In
this study, the author tests the effects of factors in JDI model on general job
satisfaction. Details here are five main factors including (1) work itself, (2)
promotion opportunities, (3) supervisor, (4) co-worker, and (5) pay and measure
how they have impact on the satisfaction with job of employees in Hai Duong
Power Company.
2.5 The effects of job satisfaction
Luddy (2005) summarized some effects of job satisfaction on productivity, the
leave and absence of work:
2.5.1 Overall Performance
The research results show that the relationship between job satisfaction and
performance is positive, but small and inappropriate (Johns, 1996).

According to Luthans (1989), although some relations between satisfying
employees with job and their productivity exist, but the relationship between these
variables is not strong. Authors suppose that employees who feel much satisfied
with job may be not effectively working staffs.
At the private companies, there may be no significant relationship between
job satisfaction and performance, but in some organizations, a close relationship
exists between job satisfaction and performance (Robbins et al 2003).
2.5.2 Quitting the job
Some studies agree with the viewpoint supposing that “job quit” has
negative impact with job satisfaction (Griffon, Meglino & Mobley (1979) and
Price (1977) cited in Robbins et al, 2003).
According to French (2003), the ratio of job quit of employees often
happens in an environment where the employees feel dissatisfied. Greenberg and
Baron (1995) supposed that employees have tendency to quit their job as a way to
express their dissatisfaction. By not reporting or resigning to seek a new job
prospects, employees can express their dissatisfaction or try to escape the
unpleasant aspects that they can meet. Phillips and Phillips (2001) agree that job
quit of employees is the most important factor.
The study of Steel and Ovalle (1984) established a very close relationship
between job satisfaction and job quit. It showed that employees with
dissatisfaction with job may tend to leave their job. According to Lee and
Mowday (1987) cited in Luthans (1989), there is a relationship existing between
job satisfaction and job quit.
The researchers also admitted that making employees feel satisfaction with
job does not mean to reduce trend of job quit from employees, but it supports in
maintaining a low rate of quitting.
2.5.3 Absence of work
The study shows that the level of job satisfaction has impact on the absence
of work (Hellriegel, Slocum & Woodman, 1989).

Nel et al. (2004) said that "absence “ is considered as a withdrawn behavior
when it is used as a way to get rid of a working environment that is not desirable".
According to Luthans (1989), many studies are done based on a negative
relationship between job satisfaction and job absence. Hence, if the satisfaction is
low, absence tends to become higher. Contrary to this, the study of John (1996)
showed a moderate relationship between job satisfaction and job absence.
Robbins (1993) agreed with above conclusion of John (1996). According to
Robbins et al. (2003), the moderate relationship between these variables may
come from the fact that employees can be free absent if they feel sick. This reason
may reduce the correlation coefficient between job satisfaction and absence.

Chapter 3 Research Methodology
This chapter will present research methods used to investigate relations between
employees of the company and their managers at Hai Duong Power Company on job
satisfaction. Selection of samples, measurement tools, methods of data collection and
other statistical techniques are also mentioned in this chapter.
3.1 The population and research sample
The purpose of this study is to evaluate the job satisfaction level of employees at
Hai Duong Power Company. So, the research objects of the study include all employees
working at the company. The selection of the study plays an important role in defining
the overall of study because it will help the author establish sample size and objects,
which are highly representative for the population (Nguyen Cao Van, 2009).
To ensure the reliability of the study, selecting an appropriate sample size is
necessary. General principle for selection of sample size is that the bigger sample size
is, the higher accuracy of research results will be. However, if the sample size is too big,
it will affect time and cost to do the research. Therefore, researchers often recommend
selecting a sample size that is appropriate with the ability of study and ensures
necessary reliability (for example: Suanders et al, 2007; Nguyen Dinh Tho, 2011). The
principle for defining necessary sample size depends on the overall of study as well as
analysis methods. Methods of sample selection often bases on the principle of sampling
principle in two times. At the first time, taking random samples of 100 to 200, and next
according to the standard deviation and statistical inferences to determine the
appropriate sample size (Nguyen Cao Van, 2009). Some other researchers make
experience rules for sampling by methods of explore factor analysis or regression
analysis method. For example Lee and Comrey (1992 quoted from Maccalum et al,
1999) gave the sample size for the respective views as follows: 100 = bad, 200 = pretty,
300 = good, 500 = very good, 1000 or more = excellent. In general, rules of experience
sampling have inconsistencies between different researchers. In the scope of this study,

because of limitation on research resources, the sample size will base on minimum
principle to ensure the necessary reliability. Thus, the sample size is defined = 200
according to the principle of Lee and Comrey (1992). It is a good sample size and
satisfies many other sampling principles.
After defining sample size, questionnaires will be completed and distributed to
employees working at Hai Duong Power Company. The time for collecting data will
last from February to April, 2013.
Data collection method: To collect research data, after building final questionnaire
(see more in 3.4), the author will start distributing questionnaire to employees working
in Hai Duong Power Company. Questionnaires will be sent to managers of departments
along with answering instruction to ensure that employees understand right about the
content of questions. After employees fill in information in answer sheets,
questionnaires will be collected by leaders and sent to the author to summarize and
analyze research results.
3.2 Measurements
JDI model is used in this study to design questionnaire and to collect actual data.
3.2.1 The reliability of JDI
Anastasi (1990, quoted from Luddy, 2005) supposed that the reliability is
the consistency of the evaluation values obtained by the same person when
examining in different tests. In other words, the reliability of scales for factor or
for a research model is evaluated based on its other repeated researches which also
ensure the reliability. To test the reliability of each research definition, we use
many different methods such as: Split – half technique; item analysis and popular
is using Cronbach Alpha coefficient.
Researches using JDI show that definitions in JDI are reliable definitions.
According to Smuker et al (2003 quoted from Luddy, 2005) there are 78 survey
with female sports reporter by using JDI model and they all show that factors in
JDI model ensure their high reliability with Cronbach Alpha coefficient greater
than 0.7. Other researches in the United States provide evidences of the reliability
of factor in this model. For example, the study of Futrell (1979) Alpha

coefficients of factors are from 0.67 to 0.96, in the study of Nagy (2002), Alpha
coefficient are from 0.83 to 0.9 (quoted from Luddy, 2005). In Vietnam, recent
researches of Tran Thi Kim Dung (2005), Chau Van Toan (2009) or Pham Van
Manh (2012) also proved that using definitions in JDI model is appropriate
because they ensure the reliability with Cronbach Alpha coefficients greater than
0.6. In conclusion, we can see that JDI is a reliable index to be used for researches
on job satisfaction.
3.2.2 The validity of JDI
JDI becomes more popular in many researches on measuring job
satisfaction level of many other researchers. Nagy (2002 quoted from Luddy,
2005) supposed that there are 400 studies and documents proving the validity of
JDI. Different researches point out the relations between factors of Job in JDI and
job satisfaction. For example, the study of Luddy (2005), study of Chau Van Toan
(2009) proved that factors in JDI reach distinction value. This is also tested in the
study of Kincki et al (2002) which shows that JDI achieve consistency, reliability,
and convergence value and distinction value. Through that the validity of JDI is
confirmed.
3.2.3 Reasons for selecting JDI
Using JDI becomes more and more popular in measuring job satisfaction in
many researches. According to Kerr (1997 quoted from Ha Nam Khanh Giao,
2011), JDI has basic and reliable research definitions. Luddy summarizes some
comments of other researches about the reason why they selected JDI to measure
job satisfaction as follows:
 Smith (1969) quoted from Spector (1997) supposes that JDI is a valuable
and reliable method which is used to measure job satisfaction;
 Vorster (1992) quoted from Cockcroft (2001) concluded that JDI has been
standardized and found to be consistent with the conditions in the different
studies;

 JDI is considered as a careful design and the most popular tool to measure
job satisfaction (Vroom, 1964 quoted from Schneider & Vaught, 1993). There are
more than 50% world's leading articles published on management from year 1970
to 1978 related mention the use of JDI on survey on job satisfaction (Yeager,
1981 quoted from Schneider & Vaught, 1993);
 JDI was already used in before surveys in the region to measure job
satisfaction level of employees (Schneider & Vaught, 1993).
 JDI is easy to use and does not require reading ability to complete
(Heneman, Schwab, Fossum and Dyer, 1983).
3.3 Research model and hypotheses
In the scope of this study, JDI associated with the factor “general job satisfaction”
is referenced from Spector (1995) and from other studies in Vietnam using JDI model in
measuring job satisfaction (for example: Tran Kim Dung, 2005; Chau Van Toan, 2009;
Ha Nam Khanh Giao, 2011; Pham Van Manh, 2012). Different with other researches
(for example the study of Luddy (2005) using 72 questions from JDI model of Smith et al
(1969 cited from Luddy, 2005), this study established many adjusted questions with
different levels than yes – no questions and still used five original factors in JDI model.
The research model will include 5 factors from JDI as follows:

Figure 4. The research model
Then the research hypotheses are:
The factor “work itself” reflects the appropriate level of the job with the capacity,
and desire of workers. An appropriate job is expressed in some aspects such as: the
appropriateness with capacity, professional skill, ability to clearly understand job,
opportunity to use personal capacities of employees and comfortable feeling to realize
job assignments (Luddy, 2005). Various studies have proven the link between the "work
itself" factor and job satisfaction of employees. The relationship between them is a
positive relation (Luddy, 2005; Chau Van Toan, 2009; Ha Nam Khanh Giao, 2011).
Therefore, in this study, the first hypothesis is:
H1: The factor “work itself” positively affects job satisfaction.
Promotion opportunities: This factor expresses staff’s awareness about their
opportunities to be trained, to develop personal capacity and to advance within the
organization. Training and promotion opportunities can be seen as motivation factors in
Herzberg's two-factor theory, improving these factors will increase the job satisfaction
level of employees. Employees will feel satisfied with the job, which gives them
opportunities to be trained on personal skills and to advance in their career. This is
proven through studies of many researchers (Tran Kim Dung, 2005; Ha Nam Khanh
Giao, 2011; Pham Văn Manh, 2012). Hence, the second hypothesis of this study is:
H2: The factor “promotion opportunities” positively affects job satisfaction.
"Salary" reflects employee perception on the fairness (inside and outside) in
salary. Salary is the remuneration that the employees earn for their work in the

organization. According to Maslow's theory of needs, the need for pay is equivalent to
the basic needs, physiological needs. It is endogenous and must be satisfied. In general,
at the same level of work the employees will feel more satisfied when their income is
higher. In a developing country like Vietnam, “salary” is still an important factor
affecting the satisfaction with job (Tran Kim Dung, 2005; Pham Van Manh, 2012). So
this gives out following hypothesis:
H3: The factor “salary” positively affects job satisfaction.
"Supervisors" is related to the relationship between employees and their direct
supervisors, the support of their superiors, leadership style and leadership abilities to
perform administrative functions of managers within the organization. Supervisor is a
direct manager who manages activities of employees (Robins et al, 2002). Supervisor's
caring for employees is a good way to motivate them, to reduce their dissatisfaction at
work. In other works, "Supervisors" factor has a positive impact on employee
satisfaction at work. This has been proven through studies of numerous researchers
(Luddy, 2005; Tran Kim Dung, 2005; Ha Nam Khanh Giao, 2011). Therefore, this
study proposes hypotheses as follows:
H4: The factor “supervisors” positively affects job satisfaction.
"Co-workers": indicates colleague behaviors, co-worker relations in the
workplace. Co-workers are people who work together at the same place with similar
work content. Relationships between co-workers are competitive and supportive.
Employees will feel satisfied with their job if they get good support from their co-
workers; their co-workers are friendly and help each other at work as well as rewards

and promotion policies in the organization are fair. In other words, employees will feel
more satisfied at work when they have good relationships with their co-workers. Many
researches showed the positive relationship between the factor “co-workers” with job
satisfaction (Luddy, 2005; Chau Van Toan, 2009; Ha Nam Khanh Giao, 2011; Pham
Van Manh, 2012). Thus, this study hypothesizes that:
H5: The factor “co-workers” positively affects job satisfaction
3.4 Scales for research variables and design of questionnaire
This study uses the basic theoretical JDI which is developed by Smith et al (1969)
with five main factors including independent variables and the dependent variable “job
satisfaction”. The value and reliability of JDI model are proven, however initial
researches still use Yes – No questions. According to Nguyen Dinh Tho (2011),
nowadays with the development of scale building, scales with many assessment levels
will be more appropriate and reliable than others. In many scales (Stapel, Likert),
Likert is the most popular scale in sociological studies. In recent studies (for example:
Tran Kim Dung, 2005; Chau Van Toan, 2009, Pham Van Manh, 2012, etc), the authors
also used Likert scale to measure factors in the research model which use JDI model
instead of Yes- No questions. Therefore, in this study, the author also use five-point
Likert scale to measure observed variables.
Observed variables are built based on basic theoretical JDI model, and at the same
time the author also references some other researches in Vietnam such as the study of
Tran Kim Dung (2005), study of Chau Van Toan (2009), Pham Van Mạnh (2012). And
these observed variable are also adjusted to suit Vietnamese research conditions through
trial interviews with employees to test if they understand right the contents of questions
in the questionnaire or not. In detail, factors are measured through observed items as
follows:
For the factor “work”: This factor is measured by six different observed items
referenced from the theory of Smith et al (1969), research of Tran Kim Dung (2005),

Chau Van Toan (2009) and adjusted to suit new research condition. In detail, observed
items for factor “work” are:
(1) The work suits the capacity and professional knowledge.
(2) Clear understanding of the work
(3) The work allows chance for development of individual ability.
(4) There is motivation for creative work
(5) The work is interesting and challenging
(6) Work assignments are reasonable.
For the factor “promotion opportunities”, an important factor for employee:
Promotion often brings much more income as well as recognition of capability. In this
study, the factor “promotion opportunities” is built by five observed items based on
inherits from JDI model. Questions are referenced from studies of Tran Kim Dung
(2005), Chau Van Toan (2009) for office employees in Vietnam. The contents of
questions are as follows:
(1) Fully professional trained
(2) Opportunities to improve the professional skills
(3) Create opportunities for those who can afford
(4) Chance for individual developments
(5) Training and promotion policies are clear.
For the factor “salary”: This factor is measured by five different observed items
which are inherited from the studies of Tran Kim Dung (2005), Pham Van Manh (2012)
and adjusted to suit the research unit’s conditions. They include:
(1) Salary is in accordance with the capabilities and contributions.
(2) Fair rewards for effective work
(3) Equitable distribution of salaries, bonuses and allowances for the
contributions.
(4) Can live on current income
(5) Salary is equal to other units
For the factor “supervisors”: This is measured by four observed items. These
items are referenced from JDI model of Smith et al (1969) and Tran Kim Dung (2005)

as well as from studies of Tran Van Manh (2012), and Chau Van Toan (2009). They are
also adjusted through trial interviews with employees. The contents of observed items
are as follows:
(1) Supervisors take care of subordinates
(2) Employees obtain supports from supervisors
(3) Supervisors fairly treated every employees
(4) Supervisors has good performance, vision as well as leadership skill
For the factor “co-workers”: In this study, the factor “co-workers” is measured by
observed questions based on studies of Tran Kim Dung (2005) and Chau Van Toan
(2009). At the same time, observed items are also adjusted to suit new research
conditions but still have initial meaning. For this factor, there are following four
observed items:
(1) Co-workers are ready to help each other
(2) Co-workers coordinate to work well
(3) Co-workers are very friendly
(4) co-workers are very trustworthy
A weakness of JDI model is that there are no scales for general satisfaction level
(Spector, 1997 quoted from Vo Thi Thien Hai and Pham Duc Ky, 2010). Therefore,
using traditional JDI just evaluate the satisfaction with aspects of job not general
satisfaction level. To overcome this, Spector propose to measure general satisfaction by
three observed items including (1) In general, I feel satisfied with your job, (2) In
general, I like my job, and (3) In general, I like to work here. Studies in Vietnam (for
example: studies of Tran Kim Dung, 2005) consider the satisfaction with job as is
comfortable, stick with the job and respect the work. In the scope of this study which is
referenced by study of Tran Kim Dung (2005), there are some adjusts and add of three
new observed items to measure the factor “general satisfaction” including:
(1) Feel satisfied working here
(2) Feel happy when be chosen to work here
(3) Consider the company as the second home

After developing scales for each factor in the research model, the author continues
building questionnaire for actual survey. In principle, questionnaire needs to be built
simply and conveniently for answers of employees as well as analysis of data set later.
Based on the consultation of colleagues and employees, the questionnaire is designed
including three following parts:
(1) Personal information of asked people
(2) Contents of main questions (observed variables in the model)
(3) Open comments of employees
(See Appendix 01)
3.5 Data analysis
Collected data is analyzed by using statistical analysis techniques such as:
descriptive statistics, testing scale reliability, exploratory factor analysis, correlation
analysis, multiple regression analysis, testing hypothesis by statistics. The cycle of
research analysis is described as follows. Including:
3.5.1. Descriptive statistics
Obtained samples will be statistically classified based on the criteria for
classification such as: gender, age, education level, work position and income. At
the same time, the author also calculates the Mean value (average value),
maximum value, minimum value and standard deviation of answers from data set.
3.5.2. Scale verification
Factors are tested by Cronbach`s Alpha coefficient and the total correlation
coefficient (Item-total correlation). Observed items not ensuring the reliability
will be removed from the scale and not appear in the step of factor analysis. In
this study, Cronbach`s Alpha must be at least 0.6 (Hair et al, 1998). The Item-total
correlation which is greater than 0.3 will be considered as a spam item and then
removed from scale (Nunally and Burstein, 1994)
3.5.3. Explore factor analysis
Definitions (factors) after by Cronbach`s Alpha tested will be processed by
Explore factor analysis (EFA). Explore Factor Analysis will help the author
reduce the observed variables into fewer latent variables and they will be more

meaningful in explaining the research model. Some standards applied when
testing by EFA are as follows:
 Testing the appropriateness of exploratory factor analysis with sample data
through statistical value of Kaiser-Meyer-Olkin (KMO): Accordingly, if the value
of KMO is higher than 0.5, the exploratory factor analysis will be appropriate
(Garson, 2002), whereas if the KMO value is less than 0.5, using exploratory
factor analysis method will not be suitable for existing data.
 Number of factors: The numbers of factors are determined based on the
eigenvalue index, which represents the variance explained by each factor.
According to Kaiser’ standards, the factors with eigenvalue less than 1 will be
excluded from the research model (Garson, 2003).
 Variance explained: Total variance explained must be greater than 50% (Hair
et al, 1998).
 Convergence criterion: To make the scale convergent, the correlation
coefficients between the variables and the coefficients of a factor loading must be
greater than or equal to 0.5 (Gerbing & Anderson, 1988).
 Principal component analysis with Varimax rotation: This must be done to
ensure that the number of factors is minimum (Trong and Ngoc 2008).
3.5.4 Building regression function
Scales for factors after tested will be processed Linear Regression by the
method of Ordinary Least Squares (OLS) through two tools of Enter and
Stepwise. Through the regression function, the author will find out the
relationship between the independent variable and dependent variable in the
model.
3.5.5 Testing research hypotheses
Research hypotheses will be tested through actual data from the regression
function. Standards here base on corresponding t-test and p-value (Sig.). The
reliability coefficient is 95%, and p-value will be directly compared with 0.05 to
conclude if the hypothesis accepted or rejected. For testing differences between

sub-total in the study, we use T-test and variance analysis (ANOVA), and also
compare corresponding p-value. To test the appropriation of data and of the
model, we use R-square, t-test and F-test. To evaluate the importance of factors,
we consider corresponding Beta coefficient in the regression function.
3.5.6 Variance analysis
For different tests between subtotals in the study, we use T-test and variance
analysis (ANOVA). This test is also used to directly compare corresponding p-
value. To test the differences between groups of variables, we use Post Hoc Test
with Tukey value to evaluate.

Chapter 4 Research Results
This chapter will present main research results from analysis of actual data with
the support of SPSS 20 software. The analysis contents include: descriptive statistics,
testing the reliability of scales, explore factor analysis, regression analysis, and variance
analysis. The contents in details are as follows:
4.1 Descriptive statistics
From 200 questionnaires which were distributed to employees of Hai Duong
Power Company, the author collected 132 male workers (equivalent to 68%), 62 answer
sheets from female workers (equivalent to 32%). The sample size of 194 questionnaires
ensures the minimum sample size. And the sample structure is based on following
criteria:
4.1.1 Gender
In 194 valid questionnaires, we get 132 male employees (equivalent to
68%), 62 female employees (equivalent to 32%). This exactly reflects the
employee structure of the company as well as characteristics of the industry with
the employee rate between male and female of 70:30.
Figure 5. Sample structure by Gender
4.1.2 Age
From 194 valid questionnaires, if by age classified, the group of employees
at the age from 31 to 35 has largest proportion, accounting for a total of 33% (63

persons), the group at the age from 25 to 30 makes up 22% (43 persons) and the
group at the age from 36 to 40 makes up 21% (41 persons). Other two groups less
than 24 years old and more than 40 years old have proportion of 14% (27 persons)
and 10% (20 persons).
Figure 6. Sample structure by Age
4.1.3 Education level
The results from 194 valid questionnaires show that there are 158 persons at
the university level (equivalent to 81%), 27 persons at college and intermediate
level (equivalent to 14%), and 9 other people are at master level (equivalent to
5%).
Figure 7. Sample structure by Education Level

4.1.4 Work experience
Results from 194 valid questionnaires show that there are 23 employees
working at the company less than 1 year (12%), 62 persons working for the
company less than 5 years with the proportion of 32%, 50 people working for the
company from 5 to 15 years (equivalent to 26%), and 59 persons working for the
company more than 15 years (equivalent to 30%).
Figure 8. Sample structure by year experience
4.2 Results from questionnaire
The research results from questionnaire show that the answer mostly at the level
3 and level 4 in the five point Likert scale. The Mean values are more than 3 and some
questions have Mean value of 5, and the standard deviation is quite small (less than 1).
Therefore, we can initially conclude that the satisfaction level of employees at Hai
Duong Power Company with their job is quite good.
Table 2. The results from questionnaires
N Minimum Maximum Mean Std. D
WO1 194 2.00 5.00 3.3608 .88377
WO2 194 2.00 5.00 3.8402 .81453
WO3 194 2.00 5.00 3.8196 .76411
WO4 194 2.00 5.00 3.8402 .76871
WO5 194 2.00 5.00 3.8093 .78833
WO6 194 2.00 5.00 3.7990 .81806

OP1 194 2.00 5.00 3.7165 .78657
OP2 194 2.00 5.00 3.5567 .76136
OP3 194 2.00 5.00 3.4845 .72145
OP4 194 2.00 5.00 3.9691 .76115
OP5 194 2.00 5.00 3.7732 .70535
SA1 194 2.00 5.00 3.5567 .93818
SA2 194 2.00 5.00 3.5567 .93264
SA3 194 2.00 5.00 3.5412 .93899
SA4 194 2.00 5.00 3.5464 .93322
SA5 194 2.00 5.00 3.6031 .90605
SU1 194 2.00 5.00 3.4845 .72859
SU2 194 1.00 5.00 3.4691 .74914
SU3 194 2.00 5.00 3.5000 .70711
SU4 194 2.00 5.00 3.4330 .67382
CO1 194 2.00 5.00 3.7062 .79589
CO2 194 1.00 5.00 3.7371 .80024
CO3 194 1.00 5.00 3.8144 .76626
CO4 194 2.00 5.00 3.4948 .74977
JS1 194 2.00 5.00 3.5670 .79385
JS2 194 1.00 5.00 3.5773 .84357
JS3 194 1.00 5.00 3.3814 .74727
4.3 Testing the reliability of scales and observed variables in the model
Observed variables in the model are built from 3 to 6 different observed items
for one factor. To test the reliability of scales for factors, we use Cronbach Alpha
coefficient, a popular coefficient used to evaluate the reliability of a research definition
(Suander et al, 2007; Hair et al, 2006). As presented in chapter 3, the standards here
include: Cronbach`s Alpha coefficient must be at least 0.6, the total correlation
coefficient must be at least 0.3. Observed items if have the total correlation coefficient
less than 0.3 will be removed from scales for factor and no appear in next analysis step.
The results from testing the reliability of scales for each factor are as follows:

4.3.1 Testing scales for factor “work”
The factor “work” is built by six observed variables items from WO1 to
WO6. Form actual data, we see that the item WO1 has total correlation coefficient
= 0.0490 less than 0.3. It means the item WO1 is not a scales for factor “work”.
So, we will remove this item from scales for the factor “work”. The results after
item WO1 deleted show Cronbach Alpha coefficient = 0.933 greater than 0.6 and
the total correlation coefficients of observed items are greater than 0.3. Thus, we
can conclude that scales for factor “work” measured by five items from WO2 to
WO6 are reliable and appropriate (table 3).
Table 3. Results from testing scales for factor “work”
Code
Cronbach Alpha,
N
Corrected Item-
Total Correlation
Cronbach's Alpha
if Item Deleted
WO1(removed)
α = 0.933, N = 5
0.049 0.933
WO2 0.807 0.791
WO3 0.832 0.789
WO4 0.824 0.791
WO5 0.724 0.809
WO6 0.754 0.802
Note: α is Cronbach Alpha coefficient, N is the number of appropriate items for
factor
4.3.2 Testing scales for factor “promotion opportunities”
The factor “promotion opportunities” is measured by five observed items
from OP1 to OP5. The results from actual data show and the total correlation
coefficients are greater than 0.3 (table 4). So we can conclude that the scales for
factor “promotion opportunities” measured by five observed items from OP1 to
OP5 are reliable and appropriate.

Table 4. Results from testing the scales for factor “promotion opportunities”
Code
Cronbach Alpha,
N
Corrected Item-Total
Correlation
Cronbach's Alpha
if Item Deleted
OP1
α = 0.811, N = 5
.703 .740
OP2 .630 .764
OP3 .618 .769
OP4 .476 .811
OP5 .573 .782
factor
4.3.3 Testing the scales for factor “salary”
The factor “salary” is built from five observed items from SA1 to SA5. The
results from actual data show that Cronbach Alpha coefficient equals to 0.909
>0.6 and the total correlation coefficients are greater than 0.3 (table 5). It proves
that scales for factor “salary” measured by five observed items from SA1 to SA5
are reliable and appropriate.
Table 5. Results from testing scales for factor “salary”
Code Cronbach Alpha, N
Correlation
Cronbach's Alpha if
Item Deleted
SA1
α = 0.909, N = 5
.773 .888
SA2 .739 .895
SA3 .813 .880
SA4 .729 .897
SA5 .796 .883
factor
4.3.4 Testing scales for factor “supervisors”
The factor “supervisors” is built by four observed items from SU1 to Su4.
Results from actual data show that Cronbach Alpha coefficient is 0.924 > 0.6, and
the total correlation coefficients of items are greater than 0.3 (table 6). So we can

conclude here that scales for factor “supervisors” measured by four observed
items from SU1 to SU4 are reliable and appropriate.
Table 6. Results from testing scales for factor “supervisors”
Correlation
Cronbach's Alpha if
Item Deleted
SU1
α = 0.924, N = 4
.851 .891
SU2 .864 .887
SU3 .830 .898
SU4 .751 .924
factor
4.3.5 Testing scales for factor “co-workers”
The factor “co-workers” is built by four observed items from CO1 to CO4.
Results from actual data show that Cronbach Alpha coefficient is 0.816 > 0.6, the
total correlation coefficients of items are greater than 0.3 (table 7). Therefore we
can conclude that scales for the factor “co-workers” measured by four observed
items from CO1 to CO4 are reliable and appropriate.
Table 7. Results from testing scales for factor “co-workers”
Correlation
Cronbach's Alpha if
Item Deleted
CO1
0.816, N = 4
.668 .754
CO2 .715 .731
CO3 .585 .793
CO4 .581 .794
factor
4.3.6 Testing scales for the dependent variable “job satisfaction”
The dependent variable “job satisfaction” is measured by three observed
items from JS1 to JS3. Results from data analysis show that Cronbach Alpha
coefficient is 0.793, and the total correlation coefficients of items are greater than
0.3 (table 8). So we conclude that scales for the dependent variable “job
satisfaction” measured by items from JS1 to JS3 are reliable and appropriate.

Table 8. Results from testing scales for the dependent variable “job satisfaction”
Correlation
Cronbach's Alpha if
Item Deleted
JS1
α = 0.793, N = 3
.613 .742
JS2 .659 .695
JS3 .639 .718
factor
In conclusion, after testing scales for all factors in the model, we see that
there is only one observed item (WO1) in the variable “work” is inappropriate and
removed from factor analysis. Observed variables with Cronbach Alpha
coefficient greater than 0.7 have high reliability level.
4.4 Explore factor analysis
After testing scales for factor by Cronbach`s Alpha coefficient, scales will be
tested by the method of explore factor analysis (EFA). The method of EFA is used to
find the interdependence between the variables. This method will help the author collect
a set of fewer implicit variables (factors) from the data set of observed variables (Hair et
al, 2006). For this study, Explore factor analysis will be done particularly for
independent variables and the dependent variable. Factor extraction method used is
Principal component with Varimax rotation to extract the smallest number of factors
(Hoang Trong and Chu Nguyen Mong Ngoc, 2008). The analysis standards are factor
loading coefficient must be at least 0.5 in one factor, eigen-value equals or greater than
1, variance extracted must be at least 50%, KMO is at least 0.5, Bartlett-test has p-value
less than 0.05. Results from data analysis are as follows:
4.4.1 Explore factor analysis with independent variables
From the data set, item WO1 is consider as a “spam” item and not measures
for the factor “work” (see more in 4.3.1). So doing explore factor analysis with
independent variables, we get following results:
Table 9. KMO and Bartlett's Test with independent variables
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .865

Bartlett's Test of Sphericity
Approx. Chi-Square 3042.888
df 253
Sig. .000
Table 10. Total variance extracted of independent variables
Component Initial Eigenvalues Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 7.319 31.823 31.823 3.991 17.351 17.351
2 3.912 17.009 48.833 3.782 16.444 33.795
3 2.214 9.627 58.460 3.284 14.277 48.071
4 2.039 8.866 67.326 2.854 12.409 60.480
5 1.115 4.848 72.174 2.689 11.693 72.174
6 .942 4.094 76.268
7 .618 2.685 78.952
8 .584 2.540 81.493
9 .536 2.330 83.823
10 .442 1.920 85.743
11 .414 1.801 87.543
12 .397 1.728 89.271
13 .339 1.476 90.747
14 .322 1.400 92.146
15 .291 1.265 93.412
16 .280 1.216 94.628
17 .258 1.121 95.749
18 .225 .980 96.730
19 .192 .836 97.566
20 .181 .785 98.351
21 .138 .598 98.949
22 .125 .543 99.493
23 .117 .507 100.000
Extraction Method: Principal Component Analysis.
Table 11. Rotated Component Matrix of independent variables

Component
1 2 3 4 5
WO4 .885
WO3 .874
WO2 .855
WO6 .805
WO5 .800
SA3 .873
SA5 .873
SA1 .861
SA2 .831
SA4 .807
SU2 .901
SU3 .866
SU1 .863
SU4 .833
OP1 .739
OP5 .735
OP2 .722
OP4 .632
OP3 .623
CO1 .791
CO2 .779
CO4 .662
CO3 .653
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
The results show that KMO = 0.865 > 0.5, Bartlett-test has p-value = 0.000
< 0.05 (table 9), the variance extracted = 72.174% greater than 50%, eigenvalue =
1.115 after extracting to5 factors (table 10), and observed items form five
different factors (table 11). So, using the method of explore factor analysis is
appropriate to the research data.

4.4.2 Explore factor analysis with the dependent variable “job satisfaction”
From actual data, we do explore factor analysis with the dependent variable
“job satisfaction” and get following results:
Table 12. KMO and Bartlett's Test with the dependent variable
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .706
Bartlett's Test of Sphericity
Approx. Chi-Square 173.493
df 3
Sig. .000
Table 13. Total Variance Explained with the dependent variable
Component Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 2.126 70.860 70.860 2.126 70.860 70.860
2 .472 15.743 86.603
3 .402 13.397 100.000
Table 14. Component Matrixa
Component
1
JS2 .856
JS3 .843
JS1 .826
The analysis results show that KMO = 0.706 greater than 0.5, Bartlett-test
has p-value = 0.000 less than 0.05 (table 12), eigenvalue equals to 2.126 > 1, the
variance extracted = 70.860% > 50% (table 13), three observed items form only
one factor (table 14). Thus, using method of factor analysis here is appropriate,
and scales for the dependent variable “job satisfaction” are unidirectional scales.
4.5 Building regression function and testing research hypotheses

4.5.1 Estimating regression function from data set
To test research hypotheses, we use method of regression analysis, in which
the factor JS_job satisfaction is a dependent variable and other variables
WO_work, OP_promotion opportunities, SA_salary, SU_supervisors, and CO_co-
worker are independent variables. Variables for regression analysis are
standardized variables using factor score from results of testing explore factor
analysis in the part 4.3. Results from data analysis with SPSS software are as
follows:
Table 15. Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
Durbin-Watson
1 .785a
.616 .606 .62786456 2.060
a. Predictors: (Constant), CO, SU, SA, OP, WO
b. Dependent Variable: JS
Table 16. ANOVAa
Model Sum of
Squares
df Mean
Square
F Sig.
1
Regression 118.888 5 23.778 60.316 .000b
Residual 74.112 188 .394
Total 193.000 193
a. Dependent Variable: JS
b. Predictors: (Constant), CO, SU, SA, OP, WO
Table 17. Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig. Collinearity
Statistics
B Std. Error Beta Tolerance VIF
1
(Constant) -1.227E-016 .045 .000 1.000
WO .230 .045 .230 5.085 .000 1.000 1.000
OP .412 .045 .412 9.109 .000 1.000 1.000
SA -.056 .045 -.056 -1.233 .219 1.000 1.000
SU .117 .045 .117 2.599 .010 1.000 1.000
CO .614 .045 .614 13.582 .000 1.000 1.000
a. Dependent Variable: JS

The regression function is defined as follows: JS = 0.230WO + 0.412OP –
0.056SA + 0.117SU + 0.614CO. Variance analysis shows that F-test has p-value
= 0.000 (table 16), it means there is at least one independent variable having Beta
coefficient differ 0. Adjusted R square = 0.606 (table 15) proves that independent
variables explain 60.6% of the variability of the dependent variable JS-job
satisfaction. Because this study used standardized variables, the estimated model
does not violate the assumptions of the method OLS.
4.5.2 Testing research hypotheses
Testing hypothesis H1: Factor “work itself” positively affects job
satisfaction. From actual data, we see that Beta coefficient of the item WO is β =
0.230 > 0, p-value = 0.000 < 0.05 (table 17). So with the reliability coefficient =
95%, we can suppose that the factor “work” has positive impact on job
satisfaction. In other words, we accept the hypothesis H1. This result shows that
the factor “work itself” is a factor affecting general feeling of employees with job.
If the company finds out solutions to increase satisfaction level with job 1 unit,
the satisfaction level of employees will increase to 0.230 unit.
Testing hypothesis H2: Factor “promotion opportunities” positively affects
job satisfaction. From actual data, we see that Beta coefficient of the item OP is β
= 0.412 > 0, p – value = 0.000 < 0.05 (table 17). So with the reliability coefficient
= 95%, we can suppose that the factor “promotion opportunities” has positive
impact on job satisfaction. In other words, we accept the hypothesis H2. Thi result
once again proves the positive relationship between “promotion opportunities”
and “job satisfaction”. If the chance for promotion is high, the satisfaction level
with job will also become higher. Thus, if the company improves the factor
“promotion opportunities” 1 unit, the satisfaction level with job of employees will
increase to 0.412 unit.
Testing hypothesis H3: Factor “salary” positively affects job satisfaction.
From actual data, we see that the corresponding t-test of the item SA has p – value
= 0.219 > 0.05 (table 17). So with the reliability coefficient = 95%, we can

suppose that the factor “salary” has no impact on job satisfaction. In other words,
we reject the hypothesis H3. At this time, the salary of employees in the field of
electric power in Vietnam and also in Hai Duong is quite good. In comparison
with other fields, the income from this field is much higher than others. The
employees can easily compare in a same request level of working skill, and work
intensity with other companies. So the expectations about salary are not high. We
can consider it as a factor which met expectations of employees already, so it is
not a factor inspiring their satisfaction with job.
Testing hypothesis H4: Factor “supervisors” positively affects job
satisfaction. From actual data, we see that Beta coefficient of the item SU is β =
0.117 > 0, p –value = 0.010 < 0.05 (table 17). So with the reliability coefficient =
95%, we can suppose that the factor “supervisors” has positive impact on job
satisfaction. In other words, we accept the hypothesis H4. This showed that if the
company improves the feeling of employees with the factor “supervisors” (change
leader style, improve the relationship between supervisors and employees) 1 unit,
the satisfaction level of employees with job will increase to 0.117 unit.
Testing hypothesis H5: Factor “co-workers” positively affects job
satisfaction. From actual data, we see that Beta coefficient of the item CO is β =
0.614 > 0, p-value = 0.000 < 0.05 (table 17). So with the reliability coefficient =
95%, we can suppose that the factor “co-workers” has positive impact on job
satisfaction. In other words, we accept the hypothesis H5. This result showed that
the factor “co-workers” has impact on the satisfaction level with job of
employees. If the employees feel satisfied with co-worker relations (for example:
building organizational culture), they will have tendency of becoming more
satisfied with general job. According to this result, if we improve the factor “co-
workers” 1 unit, the job satisfaction level will increase to 0.612 unit.
4.6 Testing the differences between different groups of employees by
demographic variables
To test the differences between employee groups based on demographic variables,
we use analysis methods of T-test and ANOVA. However the variables in the regression

analysis are standardized variables using factor score, so they will not appropriate to be
analyzed by T-test and ANOVA, because standardized variables have equal Variance
and Mean. Therefore, those variables will be encoded according to the rules of taking a
simple average as follows:
ReWO = Mean(WO2,WO3,WO4,WO5,WO6) (variable “work”)
ReOP = Mean(OP1, OP2,OP3,OP4,OP5) (variable “promotion opportunities”)
ReSA = Mean(SA1, SA2, SA3, SA4, SA5) (variable “salary”)
ReSU = Mean(SU1, SU2, SU3, SU4) (variable “supervisors”)
ReCO = Mean(CO1, CO2, CO3, CO4) (variable “co-workers”)
ReJS = Mean(JS1, JS2, JS3) (variable “job satisfaction”).
Results from testing the differences between variables are as follows (here we do
not consider the analysis with observed variable ReSA, because the factor “salary” has
no impact on dependent variable):
4.6.1 Testing differences between variables by gender
To test differences between groups of male and female employees, we use
analysis by Independent T-test, and Levene-test to check the covariance. The
results from analysis of data set are as follows:
Table 18. Statistics by gender group
Gender N Mean Std. Deviation Std. Error Mean
ReWO
Male 132 3.7773 .70922 .06173
Female 62 3.9161 .68477 .08697
ReOP
Male 132 3.7061 .55172 .04802
Female 62 3.6871 .59464 .07552
ReSU
Male 132 3.4716 .61054 .05314
Female 62 3.4718 .71875 .09128
ReCO
Male 132 3.6932 .62821 .05468
Female 62 3.6774 .62297 .07912
ReJS
Male 132 3.5000 .65835 .05730
Female 62 3.5269 .69751 .08858
Table 19. Independent Samples Test

Levene's Test for
Equality of Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
ReWO
Equal variances
assumed
.577 .448 -1.286 192 .200 -.13886
Equal variances
not assumed
-1.302 123.369 .195 -.13886
ReOP
Equal variances
assumed
1.022 .313 .218 192 .828 .01896
Equal variances
not assumed
.212 111.790 .833 .01896
ReSU
Equal variances
assumed
4.112 .044 -.002 192 .999 -.00018
Equal variances
not assumed
-.002 103.801 .999 -.00018
ReCO
Equal variances
assumed
.108 .743 .163 192 .870 .01576
Equal variances
not assumed
.164 120.398 .870 .01576
ReJS
Equal variances
assumed
.529 .468 -.260 192 .795 -.02688
Equal variances
not assumed
-.255 113.478 .799 -.02688
The results show that:
For the variable “work” (ReWO), Levene-test has p-value = 0.448 > 0.05
(table 19), it means the variances between group of male and group of female
employees on the variable “work” are same. Thus, we will use results from “Equal
variances assumed” that shows T-test has p-value = 0.200 > 0.05. It also proves
that there are no significant differences between these two groups on the factor
“work”. The results of the average value also show a very small difference
between them.

For the variable “promotion opportunities” (ReOP), Levene-test has p-value
= 0.313 > 0.05 (table 19), it means the variances between group of male and group
of female employees on the variable “work” are same. Thus, we will use results
from “Equal variances assumed” that shows T-test has p-value = 0.828 > 0.05. It
also proves that there are no significant differences between these two groups on
the factor “promotion opportunities”. The results also show very small average
values of these groups with different gender.
For the variable “supervisors” (ReSU), Levene-test has p-value = 0.044 <
0.05 (table 19), it means the variances between group of male and group of female
employees on the variable “supervisors” are different. Thus, we will use results
from “Equal variances assumed” that shows T-test has p-value = 0.999 > 0.05. It
also proves that there are no significant differences between these two groups on
the factor “supervisors”. The results of the average value also show a very small
difference between them.
For the variable “co-workers” (ReCO), Levene-test has p-value = 0.743 >
0.05 (table 19), it means the variances between group of male and group of female
employees on the variable “supervisors” are same. Thus, we will use results from
“Equal variances assumed” that shows T-test has p-value = 0.870 > 0.05. It also
proves that there are no significant differences between these two groups on the
factor “co-workers”. The results of the average value also show a very small
difference between them.
For the dependent variable “job satisfaction” (ReJS), Levene-test has p-
value = 0.468 < 0.05 (table 19), it means the variances between group of male and
group of female employees on the variable “supervisors” are different. Thus, we
will use results from “Equal variances assumed” that shows T-test has p-value =
0.795 > 0.05. It also proves that there are no significant differences between these
two groups on the factor “job satisfaction”. The results of the average value also
show a very small difference between them.

4.6.2 Testing differences between variables by age
To test differences between groups of different age, we use variance
analysis method (ANOVA). If there are differences between these groups, we
continue using deep analysis method (Post Hoc Test) with Tukey value to test in
which group the differences are. The results from data set are as follows:
Table 20. Variance analysis by age
Sum of
Squares
df Mean
Square
F Sig.
ReWO
Between
Groups
5.258 4 1.314 2.759 .029
Within Groups 90.052 189 .476
Total 95.309 193
ReOP
Between
Groups
2.408 4 .602 1.927 .108
Total 61.460 193
ReSU
Between
Groups
3.808 4 .952 2.351 .056
Total 80.344 193
ReCO
Between
Groups
5.496 4 1.374 3.716 .006
Total 75.383 193
ReJS
Between
Groups
4.801 4 1.200 2.777 .028
Total 86.486 193
The analysis results show that:
For the variable “work”, F-test between groups has p-value = 0.029 < 0.05
(table 20). So, there are differences between groups of different age on the factor
“work”. Results from testing by Tukey value also show differences between group
of employees below 24 years old and group of employees at the age from 25 to 30

and the group at the age from 36 to 40. In details, the group under 24 years old has
tendency of higher satisfaction with job (table 21).
For the variable “co-workers”, F-test between groups has p-value = 0.006 <
0.05 (table 20). It proves that there are differences between groups of different age
on the factor “co-workers”. Results from testing by Tukey value also show
differences between the group of employees under 24 years old and other groups.
In details, the group below 24 years old has tendency of higher satisfaction with
co-workers than others (table 21).
For the variable “job satisfaction”, F-test between groups has p-value =
0.028 < 0.05 (table 20). It proves that there are differences between groups of
different age on the factor “general job satisfaction”. Results from testing by
Tukey value also show differences between the group of employees below 24
years old and and group of employees at the age from 31 to 35 and the group at
the age from 36 to 40. In details, the group under 24 years old has tendency of
higher satisfaction with the factor “job satisfaction” than others (table 21).
For other variables including “promotion opportunities” and “supervisors”,
variance analysis shows that F-test between groups has p-value greater than 0.05,
it means there are no differences between groups of different age on these two
factors.
Table 21. Result from analysis of multi groups by Tukey value
Dependent
Variable
(I) IP2 (J) IP2 Mean
Difference (I-
J)
Std. Error Sig. 95% Confidence Interval
Lower
Bound
Upper Bound
ReWO
Below 24
25 – 30 .50508*
.16949 .027 .0383 .9719
31- 35 .37249 .15878 .135 -.0648 .8098
36 – 40 .49033*
.17108 .037 .0191 .9615
Higher 40 .47741 .20364 .136 -.0835 1.0383
25 - 30 Below 24 -.50508*
.16949 .027 -.9719 -.0383
31- 35 -.13260 .13654 .868 -.5087 .2435
36 – 40 -.01475 .15067 1.000 -.4297 .4002

Higher 40 -.02767 .18683 1.000 -.5422 .4869
31- 35
Below 24 -.37249 .15878 .135 -.8098 .0648
25 – 30 .13260 .13654 .868 -.2435 .5087
36 – 40 .11785 .13851 .914 -.2636 .4993
Higher 40 .10492 .17716 .976 -.3830 .5929
36 - 40
Below 24 -.49033*
.17108 .037 -.9615 -.0191
25 – 30 .01475 .15067 1.000 -.4002 .4297
31- 35 -.11785 .13851 .914 -.4993 .2636
Higher 40 -.01293 .18827 1.000 -.5315 .5056
Higher 40
Below 24 -.47741 .20364 .136 -1.0383 .0835
25 – 30 .02767 .18683 1.000 -.4869 .5422
31- 35 -.10492 .17716 .976 -.5929 .3830
36 – 40 .01293 .18827 1.000 -.5056 .5315
ReCO
Below 24
25 – 30 .44035*
.14931 .029 .0291 .8516
31- 35 .37169 .13987 .064 -.0136 .7569
36 – 40 .54359*
.15071 .004 .1285 .9587
Higher 40 .51157*
.17940 .038 .0175 1.0057
25 - 30
Below 24 -.44035*
.14931 .029 -.8516 -.0291
31- 35 -.06866 .12029 .979 -.4000 .2626
36 – 40 .10323 .13273 .937 -.2624 .4688
Higher 40 .07122 .16458 .993 -.3821 .5245
31- 35
Below 24 -.37169 .13987 .064 -.7569 .0136
25 – 30 .06866 .12029 .979 -.2626 .4000
36 – 40 .17189 .12202 .623 -.1642 .5080
Higher 40 .13988 .15607 .898 -.2900 .5697
36 - 40
Below 24 -.54359*
.15071 .004 -.9587 -.1285
25 – 30 -.10323 .13273 .937 -.4688 .2624
31- 35 -.17189 .12202 .623 -.5080 .1642
Higher 40 -.03201 .16585 1.000 -.4888 .4248
Higher 40
Below 24 -.51157*
.17940 .038 -1.0057 -.0175
25 – 30 -.07122 .16458 .993 -.5245 .3821
31- 35 -.13988 .15607 .898 -.5697 .2900
36 – 40 .03201 .16585 1.000 -.4248 .4888
ReJS Below 24 25 – 30 .35716 .16143 .180 -.0874 .8018
31- 35 .43739*
.15122 .034 .0209 .8539
36 – 40 .51069*
.16294 .017 .0619 .9595
Higher 40 .37654 .19395 .299 -.1577 .9107

25 - 30
Below 24 -.35716 .16143 .180 -.8018 .0874
31- 35 .08023 .13004 .972 -.2780 .4384
36 – 40 .15353 .14350 .822 -.2417 .5488
Higher 40 .01938 .17793 1.000 -.4707 .5095
31- 35
Below 24 -.43739*
.15122 .034 -.8539 -.0209
25 – 30 -.08023 .13004 .972 -.4384 .2780
36 – 40 .07330 .13191 .981 -.2900 .4366
Higher 40 -.06085 .16873 .996 -.5256 .4039
36 - 40
Below 24 -.51069*
.16294 .017 -.9595 -.0619
25 – 30 -.15353 .14350 .822 -.5488 .2417
31- 35 -.07330 .13191 .981 -.4366 .2900
Higher 40 -.13415 .17931 .945 -.6280 .3597
Higher 40
Below 24 -.37654 .19395 .299 -.9107 .1577
25 – 30 -.01938 .17793 1.000 -.5095 .4707
31- 35 .06085 .16873 .996 -.4039 .5256
36 – 40 .13415 .17931 .945 -.3597 .6280
*. The mean difference is significant at the 0.05 level.
4.6.3 Testing differences between groups by education level
To test differences between groups of different education level, we use
variance analysis method and get following results:
Table 22. Variance analysis by education level
Sum of
Squares
df Mean
Square
F Sig.
ReWO
Between Groups .116 2 .058 .116 .891
Total 95.309 193
ReOP
Between Groups .664 2 .332 1.043 .354
Total 61.460 193
ReSU
Between Groups 1.185 2 .592 1.429 .242
Total 80.344 193
ReCO
Between Groups .098 2 .049 .124 .883
Total 75.383 193

ReJS
Between Groups 1.131 2 .566 1.266 .284
Total 86.486 193
The analysis results show that F-test between groups on every variables has
p-value greater than 0.05 (minimum with the variable ReSU = 0.242). It proves
that there are no differences between employee groups of different education
level.
4.6.4 Testing differences between groups by work experience
To test the differences between groups based on the number of work year of
employees, we use variance analysis method and get following results:
Table 23. Variance analysis by work year
Sum of
Squares
df Mean
Square
F Sig.
ReWO
Between Groups .413 3 .138 .276 .843
Total 95.309 193
ReOP
Between Groups 1.369 3 .456 1.443 .232
Total 61.460 193
ReSU
Between Groups .665 3 .222 .528 .663
Total 80.344 193
ReCO
Between Groups 2.297 3 .766 1.991 .117
Total 75.383 193
ReJS
Between Groups 2.983 3 .994 2.262 .083
Total 86.486 193
The analysis results show that F-test between groups for all variables has p-
value greater than 0.05 (minimum for the variable ReJS which has p –value =
0.083). So, we can suppose that there are no meaningful differences between
groups of different work year on every variables in the model.

4.7 Discussion
The research results show a close relation between factors in JDI model (except
the factor “salary”) and the dependent variable “general job satisfaction”. In this study,
the factor “co-workers” has biggest impact intensity. This result is similar with
conclusions from the research of Madison (2000 quoted from Luddy, 2005) which also
show the factor “co-workers” is one of factors most strongly affecting job satisfaction of
employees. However it is different from research results of Ha Nam Khanh Giao (2011)
in the field of drinking water production (Tan Hiep Phat Corporation). The study of Ha
Nam Khanh Giao proves that the factor “co-workers” has no statistical meaning when
testing its impact on job satisfaction. When comparing characteristics of these two
research units, there are significant differences between the study of Ha Nam Khanh
Giao and this study. The study of Ha Nam Khanh Giao is done in an enterprise with
private capital. For production workers, their job bases on the production line with a
specific assignment. Therefore, relations between co-workers on professional are
mandatory and considered as must-have feature. In this study, Hai Duong Power
Company is an enterprise with state capital, and the sharing of work between co-
workers is limited, so employees care more about factor “co-workers”. This will affect
the satisfaction of employees with job. The second important factor is “promotion
opportunities”. This result is also same with results from some other studies (Ha Nam
Khanh Giao, 2011; Chau Van Toan, 2009; Luddy, 2005; Ellickson and Logsdon, 2002).
This once again confirms the relationship between the organization and job satisfaction.
The third important factor is “work”. This result is similar with expected relationship
between variables in the model. It proves positive relationship between nature of work
and general job satisfaction. And the last important factor is “supervisors”. The research
results also show that job satisfaction is affected by this factor. It is also similar with
results from studies of Robbin et al (2002), Luddy (2005), Tran Kim Dung (2005), Chau
Van Toan (2009) which show positive relationship between job satisfaction and the
factor “supervisors”. In this study, the factor “salary” has no impact on job satisfaction
of employees. It proves results from Bassett (1999 quoted from Luddy, 2005) supposing

that factor salary or income has no significant influence on the satisfaction of employees
with job.
For demographic variables affecting job satisfaction of employees, the research
results show that:
For the variable “gender”, all variables in the model show no differences between
groups of male and female employees on general job satisfaction. This also proves that
perceptiveness levels of male and female employees on job satisfaction are quite same.
The reason may come from the fact that recently, Hai Duong Power Company has good
modes and policies for employees, and there is no phenomenon of discrimination
against male and female workers.
For the variable “age”, the research results show that about the variables “job
satisfaction”, “promotion opportunities”, and “supervisors”, feeling of employees
between groups of different age is quite similar with each other. However, for the factor
“work” and “co-workers”, there are differences between group of employees under 24
years old and others. This group has tendency of higher satisfaction level. The reason
comes from the fact that young employees often tend to integrate more quickly to new
environments, and working environment for staffs is quite friendly so they tend to be
more satisfied than with the factor “co-workers”. Besides, young employees now still
tend to work in state enterprises, particularly at the present when the economic has
many difficulties. So, working in appropriate work places such as Hai Duong Power
Company will make employees feel more satisfied with old people.
For the variable “education level”, the results also significant differences between
groups of different education level on all research factors. Because the education level
of employees resemble each other. Employees at the company are mostly at college and
university level. For In contrast, for the factor working year, the results show no
differences between employee groups having different working year.

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