undergraduate thesis proposal - industrial gas company

7/29/2019 Undergraduate thesis proposal - industrial gas company

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Petra Christian University

1. INTRODUCTION

1.1.Research BackgroundHR in gas company in general.

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2009 (persentase)

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HR is the asset of companies

1.1.1. Description of Internship

While the writers are doing the research, the writers are doing internships

in one of the biggest industrial gas company in Indonesia. The company is the

first industrial gas company in Indonesia. The core business of the company is to

supply industrial gases such as Oxygen, Nitrogen, and many other gases and

related services to almost any industry such as metal works, metallurgy, chemical

processes and petrochemical industry, electronic and electrical industry, medical

and pharmaceutical industry, food and beverage industry, drinking water

treatment, waste water treatment, agribusiness, etc.

Furthermore, the writers are having internship period of January 16 th, 2012

until May 16th, 2012, which means that the internship is conducted for about four

months. The writers were put in different departments of the company, which is

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one of the writers is put in Export-Import Department. Meanwhile, the other

writer is put in Human Resource Management.

Next, the writer who is put in Export-Import department learns a lot during

the internship period. With the help of the supervisors and other co-workers, the

writer could learn about the export-import documents, the procedure of importing

or exporting products to or from Indonesia, creating documents that are needed to

conduct the export-import business, and creating a good database of hardcopy and

softcopy for the documentation of the export-import activities of the company.

Moreover, the writer who is put in Human Resource department also

learns a lot during the internship period.

Finally, the writers feel really blessed and grateful that the writers could

have internship opportunity in one of the biggest industrial gas company in

Indonesia. The writers could learn a lot through the help of employees of the

company and in finishing the Final Research Report.

1.1.2. Justification for the Research

Analyzing the relationship between job satisfaction and organizational

commitment is particularly crucial nowadays, as people often do not work at the

same company or job throughout their lifetime. It is also sometimes hard to find

suitable people for certain positions. So, once an ideal candidate is chosen,

companies are more likely willing to make a great effort to retain those employees.

If two employees exhibit different levels of job satisfaction and that job

satisfaction can be proven to lead to organizational commitment, the employer

will likely hire the employee with the higher level of job satisfaction. This isbecause the employer can expect the more satisfied individual to stay with the

company.

Next, the main interest ofthe writers research is to investigate whether an

employees job satisfaction will affect his or her level of commitment in the

company. It is important to study the relationship between job satisfaction and

organizational commitment in the company, because it will help the writers to

understand how employees work and their organizational behaviours in the


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company. Also, this is of particular interest for the company, because the costs of

hiring and training new employees are high. Therefore, the company should try to

keep a constant workforce, which also helps to reduce the risks of deterioration in

services offered to its customers. Generally, it is expected that employees are

more likely to stay with the company and be highly committed when they can see

a strong linkage between the companys performance and their work.

Furthermore, according to Aamodt (2010), when employees experience

low job satisfaction and organizational commitment, it can be costly since the

company has to spend money for advertisement of the vacant position, and

training and development cost. Absenteeism may also be a very costly issue

because it can result in reduced productivity when lowly committed employees do

not see any link between the tasks they do and the companys profitability.

Moreover, at times, employees may not leave the company even when

they are dissatisfied or do not feel committed to the company. This condition

makes studying the two variables serve an even greater importance. When

workers are dissatisfied, this may create counterproductive behavior and lack of

organizational citizenship behaviors, which can lead to a lower level of

organizational commitment. In turn, this may result in severe consequences such

as labour strikes. Another reason why the writers are interested in studying

whether job satisfaction would lead to organizational commitment is because this

may increase productivity. With an improvement in productivity, the company

will operate better and have higher growth, which is an important goal for the

company. Thus, it is critical to investigate the employees level of satisfaction and

their organizational commitment.

Finally, if the research shows that job satisfaction and organizationalcommitment are related, it would be beneficial for the company, since it would

only need to increase one variable (job satisfaction) to achieve the positive effect

of the other (organizational commitment). For example, the company could

reward workers with job advancement opportunities or change a facet of the job in

a desirable way, which will increase job satisfaction and ultimately lead to a

higher level of organizational commitment.

Turnover 13%


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1.1.3. Statement of Research Problem

Does pay become the significant facet of job satisfaction that influences

the affective commitment of the employees of the company?

Does promotion become the significant facet of job satisfaction that

influences the affective commitment of the employees of the company?

Does supervision become the significant facet of job satisfaction that


Does fringe benefit become the significant facet of job satisfaction that


Does contingent reward become the significant facet of job satisfaction

that influences the affective commitment of the employees of the

company?

Does operating procedure become the significant facet of job

satisfaction that influences the affective commitment of the employees

of the company?

Does co-worker become the significant facet of job satisfaction that


Does nature of work become the significant facet of job satisfaction that


Does communication become the significant facet of job satisfaction


company?

1.2. Research Objectives

To know whether pay becomes the significant facet of job satisfaction


company or not.

To know whether promotion becomes the significant facet of job


of the company or not.


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To know whether supervision becomes the significant facet of job



To know whether fringe benefits becomes the significant facet of job



To know whether contingent reward becomes the significant facet of

job satisfaction that influences the affective commitment of the

employees of the company or not.

To know whether operating procedure becomes the significant facet of

job satisfaction that influences the affective commitment of the

employees of the company or not.

To know whether co-worker becomes the significant facet of job



To know whether nature of work becomes the significant facet of job



To know whether communication becomes the significant facet of job



1.3. Research Benefit

1.3.1. For the Company

1. To be able to determine the level of the job satisfaction and the

affective commitment of the employees.

2. To be able to determine the significant attributes of nine facets of job

satisfaction that could boost the affective commitment.

3. To be able to gain information for use in better human resource

management in the future.

1.3.2. For the University


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1. Completing the information related with the effect of job satisfaction

towards the organizational commitment.

2. Developing further networking with the company and the department.

3. Providing feedback for prior similar research and serving as a stepping

stone for further research in the future.

1.3.3. For the Student

1. Applying the knowledge and theories that the writer got from

academicals and theoretical to the real business world.

2. Gaining real-time research experience to develop research skill.

3. Contributing to the company as appreciation for the opportunity given

to the writer.


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2. THEORETICAL BACKGROUND

2.1. Concepts and Definitions

2.1.1. Human Resource Management

2.1.2. Organizational Behavior

According to Newstrom & Davis (1997, p5), organizational

behavior is the study and application of knowledge about how

people as individuals and as groups act within organizations.

Also, Newstrom & Davis states that organizational behavior is an

applied science, which consists of the information about effective

practices in one organization is being extended to many others.

Newstrom & Davis also states that organizational behavior as a

science share four goals. The first objective is to describe,

systematically, how people behave under a variety of conditions.

Achieving this goal allows employees to communicate about human

behavior at work using a common language. A second goal is to

understand why people behave as they do. Next, the third goal is

predicting, which means to predict the employee behavior in the

future. Then, the fourth goal is to control and manage the employees

activity at work.

According to Robbins & Judge (2011, p ), organizational behavior

isa field study that investigates the impact that individuals, groups,

and structure have on behavior within organizations, for the purposeof applying such knowledge toward improving an organizations

effectiveness. Also, Robbins and Judge try to elaborate more on

the organizational behavior as a field study, which means that it is a

distinct area of expertise with a common body of knowledge, and it

studies three determinants of behavior in organizations, which are

individuals, groups, and structure. Therefore, organizational

behavior applies the knowledge gained about individuals, groups,


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and the effect of structure on behavior in order to make

organizations work more effectively.

Furthermore, Robbins and Judge sum up their definition of

organizational behavior as the study of what people do in an

organization and how their behavior affects the organizations

performance. Therefore, organizational behavior concerns

specifically with employment-related situations, such as jobs, work,

absenteeism, employment turnover, productivity, human

performance, and management.

2.1.3. Job Satisfaction

According to Robbins & Judge (2011, p ), Job satisfaction is a

positive feeling about a job resulting from an evaluation of its

characteristics.

Two Factor Theory

Herzberg, Mausner, and Synderman (1959) proposed the

motivator-hygiene theory, or as it more commonly known, two

factor-theory. Two factortheory assumes that everyone has two

types of needs, which are hygiene needs and motivator needs.

Hygiene needs include factors extrinsic to the work itself, such as

the work environment, supervision, and pay. Motivator needs

include intrinsic factors, such as achievement, recognition, and

work activities.

According to Herzberg, when hygiene needs are not fulfilled, the

worker is dissatisfied. When hygiene needs are fulfilled, the workeris not dissatisfied. The fulfillment of the hygiene needs are fulfilled,

the worker is not dissatisfied. The fulfillment of the hygiene needs

does not produce a state of satisfaction, but rather a state of

neutrality. For example, if your garbage is not collected, you will

undoubtedly become dissatisfied. However, the fact that your

garbage is collected will not make you happy. Our attitude toward


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garbage collection is probably best described as a neutral state that

is disrupted only by the absence of garbage collection.

When motivator needs are fulfilled, the worker is satisfied; when

they are not fulfilled, the worker is not satisfied. However, the state

of being not satisfied is not equivalent to being dissatisfied

(similar to hygiene needs). For example, when workers obtain a

sense of achievement and responsibility from their jobs, they are

satisfied. However, if they do not obtain achievement and

responsibility at work, they do not feel satisfied, which is different

from being dissatisfied. Two-factor theory even implies that a

worker can be simultaneously satisfied and dissatisfied because

satisfaction and dissatisfaction are separate states.

However, according to Dipboye, Smith and Howell (1994), two-

factor theory is primarily a descriptive theory. That is, it attempts

only to describe the conditions under which workers are influenced

to feel satisfied or dissatisfied.

Comparison Theory

Comparison theory is such one class of cognitive, process-oriented

theory of job satisfaction (Dipboye, Smith and Howell, 1994,

p.149). Comparison theory asks workers to consider how much of

some characteristic they have in their present job and how much of

this characteristic they would like to have in their present jobs. The

characteristic on question is typically framed in terms of different

type of comparisons, such as need, value, or special comparisons.

For example, you might be asked to consider how muchopportunity for social interaction you have in your present job and

how much you would prefer to have.

Lawler (1973) incorporated the concept of attained versus desire-

needs in his model of facet of satisfaction. It is a facet satisfaction

model because satisfaction with various components or facets of

the job, such as supervision, pay, or the work itself, is considered.

Lawlers model specifies that workers compare what their jobs


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should provide in terms of job facets, such as promotions and pay,

to what they currently receive from their jobs. However, simple

need comparison theory is extended by also weighing the influence

of certain worker characteristic (such as skill, training, and age)

and job characteristics (such as degree of responsibility and

difficulty).

An example, will clarify the relationship implied by Lawlers

model. In determining him/her level of job satisfaction, a worker

might consider that he/she brings an MBA and ten years of

business experience to a responsible managerial job. A coworker,

him/her referent other, has only a bachelors degree and eight years

of experience. The coworkers job is also a managerial position,

but with less responsibility and a slightly higher salary.

Consequently, the worker, after weighing the various inputs,

outcomes, and amounts received, feels dissatisfied with him/her

pay.

However, this theory is difficult to apply, especially in finding

out the part of referent to others.


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Figure Lawlers (1973) model of facet of satisfaction

Source: Lawler, E.E. (1973).Motivation in Work Organizations. Monterey, CA:

Brooks/Cole.

According to Spector, (1997, p ), job satisfaction is an

attitudinal variable that reflects how people feel about their jobs

overall as well as about various aspects of them. In simple terms,

job satisfaction is the extent to which people like their jobs; job

dissatisfaction is the extent to which they dislike them.

According to Spector, there have been two approaches to the study

of job satisfaction, which are the global approach and the facet

approach. The global approach treats job satisfaction as a single,

overall feeling toward the job. Meanwhile, the alternative approach

is to focus on job facets, or different aspect of the job, such as

rewards (pay or fringe benefits), other people on the job

(supervisors or co-workers), job conditions, and the nature of the

work itself.


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Furthermore, Spector sees the facet approach permits a more

complete picture of job satisfaction. He thinks that an individual

typically has different levels of satisfaction with the various facets.

For example, an employee might be very dissatisfied with pay and

fringe benefits, but at the same time be very satisfied with the

nature of work and supervisors.

For the purposes of the research conducted, nine facets of job satisfaction

were identified , namely: pay, promotion, supervision, benefits, contingent

rewards, operating procedures, co-workers, nature of the work and

communication (Spector 1997).

Table

Facet Description

Pay Satisfaction with pay and pay raises

Promotion Satisfaction with promotion opportunities

Supervision Satisfaction with persons immediate supervision

Fringe Benefits Satisfaction with monetary and non-monetary benefits

Contingent Rewards Satisfaction with appreciation, recognition, and rewards for good work

Operating Procedures Satisfaction with operating policies and procedures

Co-workers Satisfaction with co-workers

Nature of Work Satisfaction with type of work done

Communication Satisfaction with communication within the organization

Source: Spector, P. (1997).Job Satisfaction: Application, Assessment, Causes and

Consequences. California: Sage.

Pay

Pay is associated with global satisfaction and even more closely with the

facet of pay satisfaction. Although money is important to individuals, research has

shown that individuals who earn more are not necessarily more satisfied in their

jobs (Spector 2008).


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Promotion

Job satisfaction is likely to be experienced by individuals who perceive

promotional opportunities to be fair (Robbins 1993; Spector 1997). Promotions

provide opportunities for personal growth, more responsibilities and increased

social status (Robbins 1993).

Supervision

An immediate supervisors behaviour is also a determinant of job

satisfaction (Spector 1997). Employee satisfaction increases when the immediate

supervisor is understanding, friendly, offers praise for good performance, listens

to employees opinions and shows personal interest in them (Robbins 1993).

Fringe Benefits

Spector (1997) divides fringe benefits into monetary and non-monetary

benefits. Increasing intrinsic and extrinsic fringe benefits that attract an

employees attention may subsequently increase their performance and induce

higher levels of organisational commitment

Contingent Rewards

According to Spector (1997), examples of contingent rewards are

appreciation, recognition and rewards for good work. Employee dissatisfaction

may result if an employee perceives that their efforts are not recognised or that

their rewards are not equitable, tied to their performance or tailored to their needs

(Robbins 1993). Contingent rewards support the reinforcement theory of

motivation, in terms of which performance-relevant behaviours will increase infrequency if rewarded (Spector 2008).

Operating Procedures

Specific job characteristics lead to positive psychological states such as

experiencing the meaningfulness of work, feelings of responsibility and

knowledge about the products of work, which in turn lead to satisfaction with the

job (Judge, Bono & Locke 2000; Spector 1997). Autonomy gives rise to feelings


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of responsibility. Knowledge about the products of work is gained through job

feedback. When these characteristics are combined, the scope and complexity of a

job is defined. High scope results in high levels of job satisfaction, while low

scope leads to boredom and dissatisfaction. Aspects of the job and the

organisational environment relate to job satisfaction, and as a result some

situations produce positive job satisfaction, while others produce job

dissatisfaction (Spector 2008).

Co-workers

Perceptions of fairness are important determinants of peoples behaviour

and reactions to work (Spector 2008). According to Martins and Coetzee (2007),

employee motivation and organisational culture are affected by how an

employees needs and objectives are integrated with the needs and objectives of

the organisation, worklife balance practices and physical work environment.

Work fulfils an individuals social factor need. Therefore, having friendly and

supportive co-workers leads to increased job satisfaction (Robbins 1993).

According to Ghazzawi (2008), an employees coworkers, the groups they belong

to, and the culture to which an individual is exposed all have the potential to

influence job satisfaction.

Nature of Work

The nature of the workmay be influenced by the supervisors behaviour.

The nature of work satisfaction is defined as the employees satisfaction with the

type of work they do (Spector 1997). Employees prefer work that is mentally

challenging in that it provides them with opportunities to use their skills andabilities and offers a variety of tasks, freedom and feedback on how well they are

doing (Robbins 1993).

Communication

The formation of specific goals, feedback on progress towards these goals,

and reinforcement of desired behaviour all stimulate motivation and require

communication. The fewer distortions, ambiguities and incongruities that occur in


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communication within organisations, the more satisfied employees will feel with

regard to their work (Robbins 1993).

2.1.4. Organizational Commitment

According to Dipboye, Smith and Howell (1994, p),

organizational commitment is defined as a workers identification

with and involvement in a particular organization. Although, like

job satisfaction, organizational commitment refers to ones affect

toward his or her employing organization, organizational

commitment is thought to be more global and enduring than job

satisfaction. Specifically, organizational commitment refers to

employee attitude about the whole organization and therefore is

probably less influenced by daily events (e.g., a disagreement with

the supervisor).

The concept of organisational commitment has attracted considerable

interest in an attempt to understand and clarify the intensity and stability of an

employees dedication to the organisation (Lumley 2010). In the context of the

present study, organisational commitment is regarded as an attitude, as it relates to

individuals mindsets about the organisation (Meyer & Allen 1991).

Mathieu and Zajac (1990) believe that developing a better perception of

the progression associated with organisational commitment has an effect on

employees, organisations and the world in general. The level of employees

organisational commitment will possibly ensure that they are better suited toreceiving both extrinsic rewards (which include remuneration and benefits) and

psychological rewards (which include job satisfaction and associations with

fellow employees) related to associations. Organisational commitment is

generally assumed to reduce adandonment behaviours, which include tardiness

and turnover. In addition, employees who are committed to their organisation may

be more willing to participate in extra-role activities, such as being creative or


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innovative, which frequently guarantee an organisations competitiveness in the

market (Katz & Kahn 1978).

Organisational commitment is viewed as a psychological connection that

individuals have with their organisation, characterised by strong identification

with the organisation and a desire to contribute to the accomplishment of

organisational goals (Meyer & Allen 1997). Meyer and Allens (1991) three -

component model of organisational commitment is therefore of relevance to this

research. Meyer and Allen (1991) conceive of organisational commitment as

reflecting three core themes, namely affective, continuance and normative

commitment. Also, according to Meyer and Allen (1991) affective, continuance,

and normative commitment are distinguishablecomponents of commitment.

Commitment can be seen as an affective point of reference towards the

organisation (affective commitment), acknowledgement of the consequences of

leaving the organisation (continuance commitment), and an ethical responsibility

to stay with the organisations (normative commitment) (Meyer & Allen 1991).

Affective Commitment

Affective commitment is the extent to which an employee wants to remain

with the organization, cares about the organization, and is willing to exert effort

on its behalf. It is the individuals psychological or emotional connection to,

identification with and participation in the organisation (Meyer & Allen 1997).

Employees who are affectively committed to the organisation will probably carry

on working for it because they want to (Meyer & Allen 1991). Individuals whoare dedicated at an emotional level usually remain with the organisation because

they see their individual employment relationship as being in harmony with the

goals andvalues of the organisation for which they are currently working.

For example, an employee of the Red Cross might like her coworkers and

her boss, share the altruistic goals of the organization, and realize that her efforts

will result in better organizational performance.


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Continuance Commitment

Continuance commitment is the extent to which an employee believes

he/she must remain with the organization due to the time, expense, and effort that

he/she has already put into it or the difficulty she would have in finding another

job (Meyer & Allen 1997). Continuance commitment is also regarded as an

awareness of the costs associated with leaving the organisation (Meyer & Allen

1997). Because of the individuals awareness or consideration of expenses and

threats linked to leaving the organisation, continuance commitment is considered

to be calculative (Meyer & Allen 1997). Individuals with continuance

commitment remain with a specific organisation because of the money they as

employees earn as a result of the time spent in the organisation, and not because

they want to. This differs from affective commitment, where individuals remain

with an organisation because they want to and because they are familiar with the

organisation and its principles.

For example, a chamber of commerce director who spent ten years making

business contacts, getting funding for a new building, and earning the trust of the

local city council. Though he/she could take a new job with a chamber in a

different city, she would need to spend another ten years with that chamber just to

make the gains she has already made. As another example, an employee might

hate her job and want to leave, but realizes that no other organization would hire

her or give her the salary she desires.

Normative Commitment

Normative commitment is the extent to which an employee feels obligated

to the organization and, as a result of this obligation, must remain with theorganization (Meyer & Allen 1997). Normative commitment also can be

explained as a sense of responsibility to continue employment with a specific

organisation because he/she believes that he/she owes the organisation (Meyer &

Allen 1997). The internalised idea of responsibility and commitment allows

employees continued membership that is appreciated by a specific organisation

(Meyer & Allen 1991).


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A good example of normative commitment would be an employee who

was given him/her first job by an organization, was mentored by him/her manager,

and was trained at great cost to the organization. The employee may feel that she

is ethically obligated to remain with the organization because of its extensive

investment in him/her.

Moreover, Meyer et al. (1993) discuss the nature and origins of the three

components of commitment. Figure . shows the major influences on each

commitment. Also, different factors are involved in each component. Affective

commitment arises from job conditions and met expectations, that is, whether the

job provided the rewards the employee expected. Meanwhile, continuance

commitment is produced by the benefits accrued from working for the

organization and by the lack of available alternative jobs. Finally, normative

commitment comes from the employees performance values and from the

obligations the person feels toward the employer. These obligations derive from

favors that the organization has done, such as paying the persons school expenses.


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Figure

Source: Meyer, J.P., Allen, N.J. (1993). Commitment to organizations and

occupations: Extension and test of a three-component-conceptualization.

Journal of Applied Psychology, 78, 538-551.

2.2. Relationship Between Concepts

Strong positive relationships have been observed between organisational

commitment and desirable work outcomes such as performance, adaptability and

job satisfaction (Angle & Perry 1981; Hunt, Chonko & Wood 1985; Mowday,

Porter & Dubin 1974). Research results indicate that satisfied employees tend to

be committed to an organisation, and employees who are satisfied and committed


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Employees prefer to stay in their company and work hard for a return. If

employees feel that the company treats them fairly or well, the workers will feel

that they are responsible to keep working hard for their companies. Also, in order

to maintain their current satisfied jobs, employees will perform well and work

effectively, which is beneficial for the company. Therefore, in order to increase

the employees level of commitment, the manager can try to increase their

employees level of job satisfaction.

https://kucampus.kaplan.edu/documentstore/docs09/pdf/picj/vol3/issue1/Job_

Satisfaction_and_Organizational_Commitment_Among_Probation_and_Parole_O

fficers_Vol3_1.pdf

Title: Job Satisfaction and Organizational Commitment Among

Probation and Parole Officers: A Case Study

Author: Seble Getahun, Barbara Sims, and Don Hummer

Numerous studies have focused on job satisfaction and organizational

commitment of police officers and correctional personnel, but few have examined

these concepts within community corrections agencies. This study draws on prior

research into job satisfaction of criminal system actors and looks at the

explanatory power of these concepts for probation and parole officers from one

county in a northeastern state. Results indicate that employees are most satisfied

when their occupational tasks are meaningful experiences into which they have

input and are collaborative efforts with supervisors. Background characteristics of

officers had no influence on job satisfaction, indicating that organizational cultureand management style are the more important factors in explaining employee

satisfaction and, possibly, retention.

http://ccsenet.org/journal/index.php/ijbm/article/viewFile/5204/4901..

Title: Job Satisfaction and Organizational Commitment of University

Teachers in Public Sector of Pakistan
http://ccsenet.org/journal/index.php/ijbm/article/viewFile/5204/4901http://ccsenet.org/journal/index.php/ijbm/article/viewFile/5204/4901http://ccsenet.org/journal/index.php/ijbm/article/viewFile/5204/4901


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Author: Prof. Dr. Muhammad Ehsan Malik, Dr. Samina Nawab, Basharat Naeem,

Rizwan Qaiser Danish

Study Objectives: The purpose of this investigation was to determine the impact of

teachers satisfaction with job dimensions on perceived organizational

commitment in public sector universities of Pakistan. In addition, the study aimed

at exploring to what extent these teachers are committed to their universities and

satisfied with different dimensions to their job.

Research Design/Methodology: A survey-based descriptive research design was

used. The study was carried on teaching faculty working in two public sector

universities of Pakistan. About 650 survey questionnaires were distributed in

October, 2009 by employing diverse modes of communication such as email, in

person and post. Multiple follow ups yielded 331 statistically usable

questionnaires. Stepwise regression analysis and one sample t-tests were used to

confirming the research hypotheses.

Results: The findings of the study indicated that the satisfaction with work-itself,

quality of supervision and pay satisfaction had significant positive influence on

organizational commitment of faculty members. They had high degree of

organizational commitment and satisfaction with work-itself, supervision, salary,

coworkers and opportunities for promotion.

Research limitations/implications: The focus of the study was teachers working at

public sectors universities in Pakistan only. Self-reported measures were used to

measure job satisfaction and organizational commitment. Since respondents were

from two public sector universities only so the findings cannot be generalized to

faculty members of public sector universities in Pakistan.

Practical implications: Considering the importance of university teachersorganizational commitment and their effects on effectiveness of the universities,

policy makers and academic administrators should take necessary measures for

the optimal provision of intrinsic and extrinsic job rewards to make their core

workforce highly satisfied and committed.

Originality/value: The relevant literature shows that university teachers

commitment and job satisfaction is under-researched area particularly in the

public sector institutions of higher learning in Pakistan. So, the current


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investigation has contributed to improve the understanding on significant issue.

Besides, the study findings are discussed in perspective of practical implications

in public sector universities.

The study intended not only to ascertain the influence of job facets satisfaction on

organizational commitment of public sector university faculty in Pakistan but to

determine their degree of commitment and satisfaction also.

Based on the findings, it is concluded that nature of work, salary satisfaction and

quality supervision are significant predictors of organizational commitment of the

Pakistani public sector university faculty. It was also found out that they were

highly satisfied with their supervisor, coworkers, compensation, work-itself and

opportunities of advancement in their universities. Common sense confirms that

higher education is not immune to the problem of teachers low level of job

satisfaction and organizational commitment which could result into unfavorable

economic and non economic outcomes such as high exit turnover, reduced

teaching effectiveness and intellectual development of the students. So policy

makers and academic administrators should take necessary measures for the

optimal provision of intrinsic and extrinsic job rewards to make their core

workforce highly satisfied and committed to reap the benefits of improved

motivation, performance and organizational citizenship behaviors.


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2.4. Framework of the Report

Figure Framework of the report


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2.5. Hypothesis

The writers are assuming several possible results depending on the condition.

Those are:

Hypothesis 1

H0: It is presumed that the employees of the company are not having high

affective commitment.

H1: It is presumed that the employees of the company are having high

affective commitment.

Hypothesis 2


continuance commitment.


continuance commitment.

Hypothesis 3


normative commitment.

H1: It is presumed that the employees of the company are having highnormative commitment.

Hypothesis 4


organizational commitment.


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organizational commitment.

Hypothesis 5

H0: It is presumed that there is no significant relationship between the

variables of nine facets of job satisfaction with the affective commitment

of the employees of the company.

H1: It is presumed that there is significant relationship between the

variables of nine facets of job satisfaction with the affective commitment


Hypothesis 6


variables of nine facets of job satisfaction with the continuance

commitment of the employees of the company.


variables of nine facets of job satisfaction with the continuance


Hypothesis 7


variables of nine facets of job satisfaction with the normative



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variables of nine facets of job satisfaction with the normative


Hypothesis 8


variables of nine facets of job satisfaction with the organizational



variables of nine facets of job satisfaction with the organizational


Hypothesis 9

H0: Pay/ Promotion/ Supervision/ Fringe Benefits/ Contingent Rewards/

Operating Procedures/ Co-workers/ Nature of Work/ Communication are

not the most significant factor that influences the affective commitment




the most significant factor that influences the affective commitment of theemployees of the company.

Hypothesis 10




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not the most significant factor that influences the continuance




the most significant factor that influences the continuance commitment of

the employees of the company.

Hypothesis 11



not the most significant factor that influences the normative commitment




the most significant factor that influences the normative commitment of

the employees of the company.

Hypothesis 12


Operating Procedures/ Co-workers/ Nature of Work/ Communication arenot the most significant factor that influences the organizational




the most significant factor that influences the organizational commitment



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3. RESEARCH METHOD

3.1. Type of Research Method

In this step we need to design the research in a way that the requisite data can

be gathered and analyzed to arrive at a solution and to answer the previous

problem statements.

Different with Cooper and Schindler who categorize research method into

three types, which are exploratory, descriptive and causal research methods,

Sekaran and Boogie (2010) defines that there are four purposes of the research,

namely exploratory, descriptive, hypothesis testing, and case study, depends on

the stage to which knowledge about the research topic has advanced.

The first purpose of the research is exploratory study, which is undertaken

when not much is known about the situation at hand, or no information is

available on how similar problems or research issues have been solved in the past.

In essence, exploratory studies are undertaken to better comprehend the nature of

the problem, since very few studies might have been conducted in that area. Some

qualitative studies where data are collected through observation, interviews, or

focus groups are exploratory in nature. However, exploratory studies are also

necessary when some facts are known, but more information is needed for

developing a viable theoretical framework. In sum, exploratory studies are

important for obtaining a good grasp of the phenomenon of interest and advancing

knowledge through subsequent theory building and hypothesis testing.

The second purpose of a research is descriptive study, which is undertaken in

order to ascertain and be able to describe the characteristics of the variables of

interest in a situation. In addition, descriptive studies are undertaken inorganizations to learn about and describe the characteristics of a group of

employees, as for example, the age, education level, job status, and length of

service. The goal of the descriptive study is to offer a profile or to describe

relevant aspects of the phenomena of interest to the researcher from an individual,

organizational, industryoriented, or other perspective.

The third purpose of a research is actually hypotheses testing, which is a

study that usually explains the nature of certain relationships, or establishes the


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differences among groups or the independence of two or more factors in a

situation. Hypotheses testing is undertaken to explain the variance in the

dependent variable or to predict organizational outcomes.

Last but not least is the case study research that involves in-depth, contextual

analyses of matters relating to similar situations in other organization. Case

studies, as a problem solving technique, are not frequently resorted to in

organizations because findings the same type of problem in another comparable

setting is difficult due to the reluctance of the companies to reveal their problems.

Case studies that are qualitative in nature are, however, useful in applying

solutions to current problems based on past problem-solving experiences. Also,

case studies are useful in understanding certain phenomena, and generating further

theories for empirical testing.

Based on those explanations, in this research, the writer conducts

exploratory study as well as causal study to answer the statement of research

problems and corresponding research objectives. Through exploratory study,

the writer will be able to understand what factors are influencing the

effectiveness of employee training and development through the components.

It is expected that exploratory study helps the writer, the company, and the

industry to better understand this research topic because there is no specific

research topic in the consulting industry.

Furthermore, in this research, the writer also uses descriptive study to

have information on the respondents profile and their opinion about

training and development. The writer conducts frequencies and cross-

tabulations analysis as parts of descriptive study.

3.2. Description of Variables

The variable used in this research can be classified into two, dependent and

independent, approached by Sekaran and Boogie (2009). Dependent variable is

the variable of primary interest to the researcher, which is the employee

performance. On the other side, independent variable is the variable that

influences the dependent variable in either a positive or negative way. The


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components of training and development are the independent variables, while the

results or the outcomes are the dependent variables.

3.2.1. Dependent Variable

Dependent variable is the variable of primary interest to the researcher. The

researchers goal is to understand and describe the dependent variable, or to

explain its variability, or predict it. In other words, it is the main variable that

lends itself for investigation as a viable factor (Sekaran and Bougie, 2009, p. 70).

Furthermore, the dependent variable that the writers would like to use in this

research is the organizational commitment by Allen & Meyer (1993).

3.2.1.1. Dimension 1: Affective Commitment

Element 1: Job conditions

Element 2: Met expectations

3.2.1.2. Dimension 2: Continuance Commitment

Element 3: Benefits accrued

Element 4: Jobs available

3.2.1.3. Dimension 3: Normative Commitment

Element 5: Personal values

Element 6: Felt obligations

3.2.2. Independent Variable

Independent variable is one that influences the dependent variable in either

a positive or negative way. That is, when the independent variable is present, the

dependent variable is also present, and with each unit of increase in the

independent variable, there is an increase or decrease in the dependent variable

(Sekaran and Bougie, 2009, p.70).

Also, according to Sekaran and Bougie, to establish that a change in the

independent variable causes a change in the dependent variable, all four of the

following condition should be met:


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1. The independent and the dependent should covary: in other words, a

change in the dependent variable should be associated with a change

in the independent variable.

2. The independent variable (the pressunmed causal factor) should

precede the dependent variable. In other words, there must be a time

sequence in which the two occur: the cause must eccour before the

effect.

3. No other factor should be a possible cause of the change in the

dependent variable. Hence, the researcher should control for the

effect of other variables.

4. A logical explanation (a theory) is needed about why the

independent variable affects the dependent variable.

Furthermore, the independent variables that the writers would like to use in

this research are the nine facets of job satisfaction by Spector (1997).

3.2.2.1. Dimension 1: Pay

Element 1: Satisfaction with pay and pay raises

3.2.2.2. Dimension 2: Promotion

Element 2: Satisfaction with promotion opportunities

3.2.2.3. Dimension 3: Supervision

Element 3: Satisfaction with persons immediate supervision

3.2.2.4. Dimension 4: Fringe Benefits

Element 4: Satisfaction with monetary and non-monetary benefits

3.2.2.5. Dimension 5: Contingent Rewards

Element 5: Satisfaction with appreciation, recognition, and rewards for good

work


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3.2.2.6. Dimension 6: Operating Procedures

Element 6: Satisfaction with operating policies and procedures

3.2.2.7. Dimension 7: Co-workers

Element 7: Satisfaction with co-workers

3.2.2.8. Dimension 8:Nature of Work

Element 8: Satisfaction with type of work done

3.2.2.9. Dimension 9: Communication

Element 9: Satisfaction with communication within the organization

3.3. Description of Data

The description of data will cover three main things, which are type of data,

source of data, and sampling method.

3.3.1. Type of Data

Based on the scales developed, there are four possible data types, which

are using nominal, ordinal, interval, and ratio scales data. (Sekaran and Bougie,

2009)

Nominal Scale

A nominal scale is one that allows the researcher to assign subjects to certain

categories or groups (such as male & female for example). Nominal scales

categorize individuals or objects into mutually exclusive and collectively

exhaustive groups. The information that can be generated from nominalscaling is limited to calculate the percentage (or frequency).

Ordinal Scale

An ordinal scale rank orders the categories in some meaningful way (not only

categorizes the variables to denote differences among the various categories).

In an ordinal scale, the categories are to be ordered according to some

preferences.

Interval Scale


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An interval scale allows the researcher to perform certain arithmetical

operations on the data collected from the respondents. Also, interval scale

allows to measure the distance between any two points on the scale .This

helps researcher to compute the means & the standard deviations of the

responses on the variables.

Ratio Scale

The ratio scale overcomes the deficiency of the arbitrary origin point of the

interval scale, in that it has an absolute (in contrast to an arbitrary) zero point

which is a meaningful measurement point. The ratio scale not only measures

the magnitude of the differences between points in the scale but also taps the

proportions in the differences. It is considered as the most powerful of the

four scales because it has a unique zero origin and subsumes all properties of

the other three scales to calculate the ratio of the weights of two individuals.

Table 3.1. Differentiators between Four Types of Scale

No Scale Difference Order Distance Unique

Origin

Example Tests of significance

1 Nominal Yes No No No Gender

(Male/Female)

X

2 Ordinal Yes Yes No No Doneness of meat

(well, medium well,

medium rare, rare)

Rank-order

correlations

3 Interval Yes Yes Yes No Temperature in

degrees

t-test, F-test

4 Ratio Yes Yes Yes Yes Weighing balance t-test, F-test

Source: Adapted from Sekaran and Bougie (2009, p. 146)In addition to the types of scales mentioned above, Sekaran and Bougie

(2009, p. 149) mentions ten rating scales that are often used in organizational

research, which are:

Dichotomous scale

Category scale

Semantic differential scale

Numerical scale


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Itemized rating scale

Likert scale

Fixed or constant sum rating scale

Stapel scale

Graphic rating scale

Consensus scale

Out of the four possible data types (nominal, ordinal, interval, and

ratio), the writer collects numerical variables from respondents using three

types of the data, which are nominal, ordinal, and interval data categories.

Nominal data covers the questions on respondents profile, such as

gender, age through multiple choice single-response questions in all four

kinds of questionnaires being distributed. Those questions are using

dichotomous scale and category scale.

Ordinal data covers the questions asking for the surveyed item by

using Likert Scales. In this rating method, there are 5 representative

numbers, which are 1 represents Strongly Disagree (SDA), 2 represents

Disagree (DA), 3 represents Neutral (N), 4 represents Agree (A), and 5

represents Strongly Agree (SA).

Interval data covers the questions on employee development

evaluation questionnaire, related to CheckPoint 360. Unlike the Likert scale,

the scale in CheckPoint 360 will be summed for each dimension, thus it is an

interval data. In this system, 0 represents Not Applicable (not averaged into

scores), 1 represents Never demonstrates this skill, 2 represents Seldom

demonstrates this skill, 3 represents Sometimes demonstrates this skill, 4

represents Usually demonstrates this skill, and 5 represents Always

demonstrates this skill.

Furthermore, within this research, the ratio data will include the data of age

of the respondents. Meanwhile, nominal data will include the respondents profile

asked in the questionnaire, comprises of gender, occupation, level of income and

amount of gallons of water purchase per month. On the other hand, ordinal data

shows an indication of order in its characteristics. Furthermore, the ordinal data


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will be shown in the questionnaire through Likert Scale. The Likert scale is

designed to examine how strongly subjects agree or disagree with statements on a

five-point scale with the following anchors: strongly disagree, disagree, neither

agree nor disagree, agree, and strongly disagree (Sekaran and Bougie, 2009, p.

152).

Strongly

Disagree Disagree Neither Agree Nor Disagree Agree

Strongly

Agree

1 2 3 4 5

Table 3.1 Likert Scale

3.3.2. Source of Data

The data used to complete the research can be classified into primary and

secondary data. Based on Sekaran and Bougie (2009, p.180), primary data is the

information obtained first-hand by the researcher on the variables of interest for

the specific purpose of the study, while secondary data is the information gathered

from sources that already exist or someone other than the researcher.

In this research, the primary data is obtained from the questionnaires

developed by the researchers and were distributed to the targeted respondents that

will be explained deeper in sampling section. There are 4 (four) types of

questionnaires developed by the researchers (attached in Appendix). First,

the researchers distributed the questionnaire to measure the evaluation of

four training components from the previous training that has been attended

by the respondents, in this case are the employees, right after they joined the

training program. Secondly, the researchers distributed the questionnaire to

measure the evaluation of employee performance after attending a specific

training program, filled by the employees as their self-assessment and also by

the supervisor to get more objective information. Third, the researchers also

distributed the questionnaire to measure the evaluation of six development

program components from the on-going development process that has been

implemented to the respondents, in this case are the employees. Fourthly, the

researchers then distributed the questionnaire to measure the evaluation of


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employee performance after being developed through an employee

development program, filled by the employees as their self-assessment and

also by the people around them to get more objective information, such as

supervisor and peers, in accordance with Checkpoint 360o Feedback theory

mentioned in chapter 2.

Nevertheless, the data used in the research background, justification for the

research, and summary of relevant research are classified into secondary data,

because those were generated from the available data from existing sources, such

as text books, published journals, and websites.

3.3.3. Sampling Method

According to Sekaran and Bougie (2009), sampling process is the process

of selecting a sufficient number of the right elements from the population, so that

a study of the sample and an understanding of its properties or characteristics

make it possible for the writer to generalize such properties or characteristics to

the population elements.

In learning how representative data can be collected, according to Sekaran

and Bougie, a few terms, as described further, have first to be understood. First is

population. The population refers to the entire group of people, events, or things

of interest that the researcher wishes to investigate. It is the group of people,

events, or things of interest for which the researcher wants to make inferences

(based on sample statistics).

The second term is element. An element is a single member of the

population.

The third term is the sample. Sample is a subset of the population. Itcomprises some members selected from it. In other words, some, but not all,

elements of the population form the sample. According to Hair et al (2006),

minimum sample size is counted as five observations for each estimated

parameter.

The fourth term is sampling unit. The sampling unit is the element or set

of elements that is available for selection in some stage of the sampling process.


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The fifth term is subject. A subject is a single member of the sample, just

as an element is a single member of the population.

Moreover, there are two major types of sampling designs (Sekaran and

Bougie, 2009), they are probability and nonprobability sampling. When elements

in the population have a known chance of being chosen as subjects in the sample,

the writers resort to a probability sampling design. Probability sampling can be

either unrestricted (simple random sampling) or restricted (complex probability

sampling) in nature. Meanwhile, in nonprobability sampling, the elements do not

have a known or predetermined chance of being selected as subjects.

The first probability sampling type is the unrestricted or simple random

sampling. In the unrestricted probability sampling design, more commonly known

as simple random sampling, every element in the population has a known and

equal chance of being selected as a subject. Say, there are 1000 elements in the

population with a sample of 100. Suppose we were to drop pieces of paper in a

box, each containing the name of one of the elements, and draw 100 of those from

the box with eyes closed. We know that the first piece drawn will have a 1/1000

chance of being drawn, the next one a 1/999 chance of being drawn, and so on. In

other words, we know that the probability of any one of them being chosen is 1 in

the number of the population, and we also know that each single element in the

box has the same or equal probability of being chosen. When we thus draw the

elements from the population, it is most likely that the distribution patterns of the

characteristics we are interested in investigating in the population are also

likewise distributed in the subjects we draw for our sample. This sampling design,known as simple random sampling, has the least bias and offers the most

generalizability. However, this sampling process could become cumbersome and

expensive; in addition an entirely updated listing of the population may not

always be available. For these and other reasons, other probability sampling

designs are often chosen instead.

The second probability sampling type is the restricted or complex

probability sampling. As an alternative to the simple random sampling design,


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several complex probability sampling (restricted probability) designs can be used.

These probability sampling procedures offer a viable, and sometimes more

efficient, alternative to the unrestricted design we just discussed. Efficiency is

improved in that more information can be obtained for a given sample size using

some of the complex probability sampling procedures than the simple random

sampling design. The five most common complex probability sampling designs

systematic sampling, stratified random sampling, cluster sampling, area sampling,

and double sampling.

For conclusion, in this paper, the writers have decided that the population

is

3.4. Analytical Method

This research will mainly utilize the Ordinal Logistic Regression, which is a

general term for several specific computational techniques. In assisting with the

statistical calculation of Ordinal Logistic Regression, this research will use PASW

Statistics 18 program.

3.4.1. Validity

According to Sekaran and Bougie (2009, p.157), it is important to make

sure that the instrument that is being developed to measure a particular concept is

indeed accurately measuring the variable, as well as the concept that we set out to

measure. Therefore to measure the goodness of the data, the reliability and

validity of the measures are then established.

Validity test is a test on how well an instrument that is developedmeasures the particular concept it is intended to measure, which is concerned with

whether the right concept is being measured. Validity test is tested by using

Cronbachs Alpha after the item deleted bigger than the original Cronbachs

Alpha if item deleted. Therefore, if the Cronbachs Alpha after the item deleted

bigger than the original Cronbachs Alpha, it means that the data is not valid.

3.4.2. Reliability


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On the other hand, Sekaran and Bougie (2009) states that reliability test

is a test of how consistently a measuring instruent measures whatever concept it is

measuring, which concerns about stability and consistency of measurement.

Cronbachs Alpha is the reliability coefficient that indicates how well the items in

a set are positively correlated to one another. The closer the Cronbachs Alpha is

to 1, the higher the internal consistency reliability. In general, Cronbachs Alpha

less than 0.60 are considered to be poor, those in the 0.70 range are considered

acceptable, and those over 0.80 are good. Therefore, the Cronbachs Alpha must

be higher than 0.60 which means the questionnaire is reliable.

Table 3.. Cronbachs Alpha Meaning

Cronbachs Alpha Meaning

0.8 Good

Source: Adapted from Sekaran and Bougie (2009)

3.4.3. Descriptive Statistics Model

The writer will use descriptive statistics model to find a picture of the

center, spread, and shape of distributions as it is explained by Cooper and

Schindler (2009). Basically, it is a simple model that the writer does not have

to find the relationship between others. It is only showing the explicit

meaning.

Meanwhile, Bougie and Sekaran states that descriptive study statistics

is undertaken in order to ascertain and be able to describe the characteristics

of the variables of interest in a situation (Bougie and Sekaran, 2009). The

goal of a descriptive study is to offer to the researcher a profile or to describe

relevant aspects of the phenomenon of interest from an individual,

organizational, industry-oriented, or other perspective.


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Especially in the research, the writer uses the model to analyze the

respondent profile and customer loyalty level. Most of the time, the writer

will only use graph and descriptive statistics to explain the questions.

According to Jonathan Sarwono (2005), descriptive is used to know the

minimum, maximum, mean, standard deviation and the sum value. Then, the

writer will test the first hypothesis using mean value of customer loyalty. So,

if the customer loyalty level mostly lays above 2.5, it means that the customer

loyalty of Pureit through Andalan is high.

3.4.4. Normality

Normality test is one of the regression assumptions that requires the error

around the line of regression is normally distributed at each value of X. The test is

used to test whether in the regression model, the residuals is normally distributed.

In the t-test and F-test, it is a basic assumption that residual value is normally

distributed. There are two options to check the normality of the distribution which

are using the normal probability plot and histogram.

Normal probability plot compares the observed values with those expected

from a normal distribution. If the distribution is normal, the points on this plot

should fall close to the diagonal line (Cooper and Schindler, 2008, p.479). The

other option is to use histogram which is commonly used to represent data

graphically. If the data is normally distributed, then the histogram will be

described as bell-shaped.

3.4.5. Homoscedasticity

According to Hoffman (2010), homoscedasticity test is used to know

whether the regression model has consistence (same) variance of the residuals in

one observation to another or not. This consistence of variance is called as

homoscedasticity while if the variance is not consistent, it will be called as

heteroscedasticity. Good regression model is the one who has homoscedasticity.

To do homoscedasticity test, the writer can see from the scatterplot that is

provided in SPSS analysis. If the data is randomly well spread below zero (0) and


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above zero (0) in Y-Axis, it shows that regression has no heteroscedasticity

situation.

3.4.6. Autocorrelation

Autocorrelation test is used to test the independence of errors which is

one of the basic assumptions of regression model. In order to do the test, Durbin-

Watson test is used, which measures the correlation between each residual and the

residual for the time period immediately preceding the one of interest.

To use the Durbin-Watson test, first compute the d value and then

compare it to the values from a special table of d values available in many

regression textbooks and on the internet. Some statistical programs provide values

from these tables as part of their output. The values in the table include an upper

limit and a lower limit based on the number of coefficients (explanatory variables

+ 1 or {k + 1} and the sample size (n). The following rules-of-thumb apply to the

use of the d values from a linear regression model:

Table 3.4. Durbin-Watson Value Meaning

D value Meaning

dmodel < dlower positive autocorrelation is present

dmodel > dupper no positive autocorrelation

dupper < dmodel < dlower the test is inconclusive

Source: Linear Regression Analysis : Applications and Assumptions (John

Hoffmann, 2010)

In other words, there is a positive autocorrelation when Durbin-Watson

value is equal to zero, while there is less likely that the model is affected by

autocorrelation if Durbin-Watson value is closer to 2.

3.4.7. Multicollinearity


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One important problem in the application of multiple regression analysis

involves the possible collinearity of the exploratory variables. This condition

refers to situations in which one or more of the explanatory variables are highly

correlated with each other. In such situations, collinear variables do not provide

new information, and it becomes difficult to separate the effect of such variables

on the dependent variable.

One of the methods of assessing multicollinearity is the Variance

Inflationary Factors (VIF) for each explanatory variable which is computed by the

following formula:

If a set of explanatory variables is uncorrelated, each VIFj is equal to 1.

If the set is highly intercorrelated, then the VIFj might even exceed 10. Hoffmann

(2010) suggested that if VIFj is greater than 10, there is too much correlation

between variable Xj and the other explanatory variables and it indicates

multicollinearity happens. A multiple regression model that has one or more large

VIF values should be used with extreme caution. The model may be used to

predict values of dependent variable only in the case where the values of the

independent variables to be used in the prediction are consistent with the values

observed in the data set.

3.4.8. Multiple RegressionAnalysis

According to Sekaran and Bougie (2009), multiple regression analysis is

used when more than one independent variable to explain variance in the

dependent variable. As the descriptive tool, multiple regression is often used inthree situations. First of all, it is used to develop a self-weighting estimating

equation by which to predict values for a criterion variable (DV) from the values

for several predictor variables (IVs). Second, it is used to control the confounding

variables to better evaluate the contribution of other variables. Last of all, it is

used to test and explain causal theory. However, as the inference tool, multiple

regression is used to test hypotheses and estimate population values.


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In this research, since the researchers want to know the influence of

components to the outcome, multiple regression analysis will be used. So, the

equation for the multiple regression for the effect of job satisfaction to the

employee commitment framework will be:

Y1= 0+ 1X1+ 2X2+ 3X3+ 4X4+ 5X5 + 6X6 + 7X7 + 8X8 + 9X9 +

Where:

Y1 = Employee Organizational Commitment

0 = Y intercept (the value of Y when all X equals to zero)

1- 5 = Regression coefficient associated with each Xi

X1 = Pay

X2 = Promotion

X3 = Supervision

X4 = Fringe Benefits

X5 = Contingent Rewards

X6 = Operating Procedures

X7 = Co-workers

X8 = Nature of Work

X9 = Communication

= Random error in Y for observation i

Furthermore, the writers would like to use 95% of confidence level.

There is a reason behind the usage of 95 % of confidence level. It is because

one of the relevant researches, which is the research by Siew, Taiwo, Salim,Downe (2011), is actually using 99% of confidence. However, in this research,

the writer would like to use rather pessimistic approach rather than the

research of Siew, Taiwo, Salim, Downe (2011) in examining the impacts of

reliability, responsiveness, assurance, empathy, and tangible aspects on

customer loyalty. Therefore, the writers use 95% confidence level for this

research.


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Moreover, the outcome of the multiple regression analysis can be shown in

ANOVA table, which includes:

3.4.8.1. The Coefficients of Multiple Determination (Adjusted R Square)

The test is used to know the goodness of fit of the regression model.

Usually in the past, many researchers used R square value to analyze how far the

dependent variable can be explained by the independent variables. However, the R

square value has disadvantage of bias to total number of independent variable

inserted to the model (Ghozali, 2006, p. 83). For every addition of one

independent variable, the R square must be increased, no matter that independent

variable significantly affects the dependent variable or not. Therefore, nowadays,

many researchers switch to use adjusted R square, because unlike R square,

adjusted R square can be increased or decreased if one independent variable is

inserted into the model. Finally, the higher value means that the higher

independent variables capability to explain the dependent variable. Cooper and

Schindler mentioned that the closer it is resulted to 100 %, the better it is (Cooper

and Schindler, 2008, p. 548).

3.4.8.2. F-Test

F-test, or also called as Fisher Test, is used to know whether the

regression model is appropriate to be used for research. If the significant value is

less than 0.05, then it shows that the regression model is appropriate to be used in

explaining the dependent variable or employee outcome in this research. In other

words, the independent variables are affecting simultaneously the dependent

variable if the significance-F value is less than 0.05.

Table 3.5. F-Test Result

F-Test Result Meaning

F-value < 5% The set of independent variables has significant

relationship with the dependent variable.

Therefore, the H0 is rejected.

F-value > 5% The set of independent variable does not have


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significant relationship with the dependent

variable. Therefore, the H0 is accepted.

Source: Draper and Smith (1998, p. 38)

Therefore, if the significant value of total variable is below 0.05, the

researchers will reject the H0, which mentions that training elements has negative

influence toward employee training outcomes and development elements has

negative influence toward employee development outcomes.

3.4.8.3. T-Test

T-test determines the relationship between each independent variable

with the dependent variable, using the predetermined confidence level. P-value of

an independent variable, produced by t-test has two meanings, explained by table

3.6.

Table 3.6. T-Test Result

T-Test Result Meaning

P-value < 5% There is significant relationship between that

particular independent variable with the dependent

variable. Therefore, the H0 is rejected.

P-value > 5% There is no significant relationship between that

particular independent variable with the dependent

variable. Therefore, the H0 is not rejected.

Source: Draper and Smith (1998, p. 37)

4. ANALYSIS AND RESULTS

4.1. Description of Analysis Procedure

4.1.1. Validity and Reliability of the Data


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5. SUMMARY AND RECOMMENDATION

5.1. Summary and Conclusions

5.2. Recommendations

5.3. Limitations of the Research

5.4. Suggestion for Further Research


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