IMPACT OF KARASEK JOB DEMAND CONTROL MODEL ON THE JOB SATISFACTION OF THE EMPLOYEES OF NADRA

IMPACT OF KARASEK JOB DEMAND CONTROL MODEL ON
THE JOB SATISFACTION OF THE EMPLOYEES OF NADRA

Nehal hussain
Muhammad Ali Jinnah University Islamabad Pakistan
E-mail: nehalhussain81@gmail.com
Tel: +92-333-5711764

Kanwal Khalid
Muhammad Ali Jinnah University Islamabad Pakistan
E-mail: kanwalkk@gmail.com

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ABSTRACT

In this study, Karasek JDC model has been applied to check the impact in the employees of NADRA. As
NADRA is one of the organizations that is running successfully in this era of recession, the study focused
on the factors of the employee Job Satisfaction. Questionnaire has been used as the data collecting
instrument. The sample of 200 employees was given the questionnaire which was divided into four sub-
groups: Job-Demand, Job-Control, Social-Support and Job Dissatisfaction. Job Demand was calculated on
Qualitative Demand, Employee Demand, Workload Demand and Conflict Demand. Similarly, Job Control
was measured through Qualitative Control, Employee Control, Workload Control and Conflict Control.
Linear Regression and Correlation was the statistical tolls that measured the data by using SPSS and MS
Excel. According to the results, low demand, low control and low social support are the factors for Job
satisfaction among the employees of NADRA The unusual response from the study may be a platform for
future research to be carried out in this respect.

Key Words: Job-Demand, Job-Control, Social-Support, Job Dissatisfaction Linear Regression and
Correlation

1. INTRODUCTION:

The ultimate end of education is happiness or a good human life, a life enriched by the possession
of every kind of good, by the enjoyment of every type of satisfaction. The relation between life
satisfaction and job satisfaction was firstly searched by Wilensky at 1960's. Satisfaction in one domain
of individual's life extends into other areas. The relationship between job satisfaction and performance
has so many issues. This is a long debate whether good performance of the employee leads to
employee’s job satisfaction or job satisfaction leads to employee’s good performance. But the end
result is employee’s good performance leads to good organizational productivity.

The term Job Satisfaction means satisfaction of the employee from the product of different aspects
affecting the job. The organization is consists of the number of employees. It is the organization’s duty
to provide facilities and benefits to employees so that their employees become Satisfy from the job.
Job satisfaction of the employee helps the organization to perform well, because the happy and satisfy
employee work better than the depressed and dissatisfied employee. It is believed and proved through
various researches that the productivity of an organization is directly associated with the satisfied
employees. If the employees of the organization are satisfied from their jobs, they will have positive
feelings for the organization and they will perform well. If the employee is dissatisfied from the job, it
leads to the stress.

Among the numerous problems employees face due to job stress, the most significant one relate to
job dissatisfaction and low (marginal) job performance. Karasek worked on a model and gave three
dimensions of job satisfaction. Job demands that leads to stressors, job control and social support. Job
stress is the state of mind that impede anyone's routine activities and situation appears threatening due
to factors like Job pressure, Job Control, Conflict at work, Employment opportunity and Company
environment. The relationship between job stress and employee productivity is of inverted U shape. It
shows that initially increase in job stress positively affects the employee's productivity but later on,
higher levels of job stress or even lower stress levels prevailing for longer time frames decreases the
productivity of employees.

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Ms. Santha Subbulaxmi. S, Programmer, Lions Aravind Institute of Community Ophthalmology,
Madurai
According to Karasek’s JDC Model Stress is caused by strain. Karasak and Theorell, (1990) described
strain as the result of comparing demands that the job has on the employee to the control the employee
has over the job. Plotted on a Matrix, the job types are 4.
The ‘high-strain jobs’ result in the highest job performance. Karasak’s demand/ control model of
determining stress is highly credible, but it lacks certain variables; which gave evolved over time, as he
did his initial work in late 1960’s. Since then, many factors have been added to the work environment
such as improving quality and productivity, improving people’s skills, managing workforce diversity,
responding to Globalization, empowering people, stimulating innovation and change, dealing with
“Temporariness”, decreasing employee loyalty and improving ethical behaviour etc.

This research is undertaken to study the impact of Karasek model of Job Demand-Control on the Job
Satisfaction of the employees of NADRA.
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1.1 OPERATIONAL DEFINITIONS

1.1.1 Job Satisfaction
Different authors gave various definitions of job satisfaction. Some of them are taken from the
book of D.M. Pestonjee “Motivation and Job Satisfaction” which are given below:
According to Weiss, Job satisfaction is defined as a pleasurable, emotional, state resulting from
appraisal of one’s job. An effective reaction to one’s job.
Blum and Naylor also defined Job satisfaction as general attitude, which is the result of many
specific attitudes in three areas namely:
• Specific job factors
• Individual characteristics
• Group relationship outside the job

According to Glimmer, Job satisfaction is defined, as it is result of various attitudes the person
hold towards the job, towards the related factors and towards the life in general. Job satisfaction is
defined as “any contribution, psychological, physical, and environmental circumstances that cause
a person truthfully say, ‘I am satisfied with my job.”
Locke defined Job satisfaction as a pleasurable or positive state of mind resulting from appraisal
of one’s job or job experiences.

1.1.2 Job demand
Karasek, notified job demands as a division of all potential work stressors, particularly
“psychological stressors involved in accomplishing the work load, stressors related to unexpected tasks
and stressors of job-related personal conflict”. Furthermore, job demands refer to the amount of
workload or responsibilities or perquisites placed on an individual to work under these.

1.1.3 Job Control
Basically, job control refers to the extent to which an individual has a capability to exercise
authority over one or all potential and actual stressors of job. Job control and how individual or group
of workers are completing are another factors closely associated to the development of stress (Kompier
& Levi, 1993). Job control includes the worker’s abilities and skills for coping with demands and the
latitude to decide how a specific task should be accomplished.

1.1.4 Social Support
Job support, the last measurement of the Karasek’s (1979) model, looks at the level and nature of backing
given by the management or the supervisors or colleagues or subordinates to the employee.

1.2 Models of job satisfaction

1.2.1 Affect Theory
The most famous job satisfaction model is given by Edwin A. Locke which is known as Affect
theory. The main point of this model is determined by what you expect from the job and what you are
getting from the job. This theory also states the factors affecting the work and the level of satisfaction
or dissatisfaction about the particular factor. Further, the theory states that how much one values a
given facet of work (e.g. the degree of autonomy in a position) moderates how satisfied/dissatisfied
one becomes when expectations are/aren’t met. When a person values a particular facet of a job, his
satisfaction is more greatly impacted both positively (when expectations are met) and negatively (when
expectations are not met), compared to one who doesn’t value that facet. To illustrate, if Employee A
values autonomy in the workplace and Employee B is indifferent about autonomy, then Employee A
would be more satisfied in a position that offers a high degree of autonomy and less satisfied in a
position with little or no autonomy compared to Employee B. This theory also states that too much of a
particular facet will produce stronger feelings of dissatisfaction the more a worker values that facet.

1.2.2 Dispositional Theory

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Another well-known job satisfaction theory is the Dispositional Theory Template: Jackson April
2007. It is a very general theory that suggests that people have inborn nature that source them to have
trend toward a certain level of satisfaction, regardless of one’s job. This approach became a prominent
explanation of job satisfaction in light of evidence that job satisfaction tends to be stable over time and
across careers and jobs. Research also indicates that identical twins have similar levels of job
satisfaction. A significant model that narrowed the scope of the Dispositional Theory was the Core
Self-evaluations Model, proposed by Timothy A. Judge in 1998. Judge argued that there are four Core
Self-evaluations that determine one’s disposition towards job satisfaction: self-esteem, general self-
efficacy, locus of control, and neuroticism. This model states that higher levels of self-esteem (the
value one places on his/her self) and general self-efficacy (the belief in one’s own competence) lead to
higher work satisfaction. Having an internal locus of control (believing one has control over herhis
own life, as opposed to outside forces having control) leads to higher job satisfaction. Finally, lower
levels of neuroticism lead to higher job satisfaction.

1.2.3 Two-Factor Theory (Motivator-Hygiene Theory)
Frederick Herzberg’s Two factor theory (also known as Motivator Hygiene Theory) attempts to
explain satisfaction and motivation in the workplace. This theory states that satisfaction and
dissatisfaction are driven by different factors – motivation and hygiene factors, respectively. An
employee’s motivation to work is continually related to job satisfaction of a subordinate. Motivation
can be seen as an inner force that drives individuals to attain personal and organizational goals
(Hoskinson, Porter, & Wrench, p.133). Motivating factors are those aspects of the job that make people
want to perform, and provide people with satisfaction, for example achievement in work, recognition,
promotion opportunities. These motivating factors are considered to be intrinsic to the job, or the work
carried out. Hygiene factors include aspects of the working environment such as pay, company
policies, supervisory practices, and other working conditions. While Hertzberg's model has stimulated
much research, researchers have been unable to reliably empirically prove the model, with Hackman &
Oldham suggesting that Hertzberg's original formulation of the model may have been a methodological
artifact. Furthermore, the theory does not consider individual differences, conversely predicting all
employees will react in an identical manner to changes in motivating/hygiene factors. Finally, the
model has been criticized in that it does not specify how motivating/hygiene factors are to be
measured.

1.2.4 Job Characteristics Model
Hackman & Oldham proposed the Job Characteristics Model, which is widely used as a
framework to study how particular job characteristics impact on job outcomes, including job
satisfaction. The model states that there are five core job characteristics (skill variety, task identity,
task significance, autonomy, and feedback) which impact three critical psychological states
(experienced meaningfulness, experienced responsibility for outcomes, and knowledge of the actual
results), in turn influencing work outcomes (job satisfaction, absenteeism, work motivation, etc.). The
five core job characteristics can be combined to form a motivating potential score (MPS) for a job,
which can be used as an index of how likely a job is to affect an employee's attitudes and behaviors. A
meta-analysis of studies that assess the framework of the model provides some support for the validity
of the JCM.

1.3 Our Organization:
NADRA is one of the largest organizations in the country. NADRA is an organization working for the
issuance of NIC to the citizens of Pakistan. NADRA employs a highly skilled workforce of more than
11,000 technical and management personnel having more than 400 domestic offices and five
international offices.

National Database & Registration Authority (NADRA) has gained international recognition for its
success in providing solutions for identification, e-governance and secure documents that deliver
multi-pronged goals of mitigating identity theft, safe-guarding the interests of our clients, and

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facilitating the public. In-depth Research and Development efforts have enabled NADRA to become
the trailblazer in the area of Software Integration, Data Warehousing, Network Infrastructure
Development and Project Management.

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1.3.1 Organizational Chart

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1.3.2 Achievements:
• NADRA has been placed amongst the Top 50 e-Passport Technology Suppliers for 5 consecutive years
in ID World Magazine, for 2005, 2006, 2007, 2008 and 2009 published by Wise Media, Italy. NADRA
is amongst the 3 companies selected from Asia and Africa on the list. NADRA was honored with the
“Outstanding Achievement Award” at CARDEX Middle East in Cairo, Egypt in May, 2007.
• NADRA has been awarded The Merit Exporter Award by Federation of Pakistan Chambers of
Commerce & Industry (FPCCI) in 2006 for achieving export of homeland security solutions in the
international market.
• NADRA’s Chief Technology Officer was awarded the “ID Talent Award” in November, 2007 at the
ID World International Congress held in Milan, Italy. He was recently awarded Tamgah-e-Imtiaz in
2009 for his services rendered to the state.
• Deputy Chairman NADRA was awarded ID Outstanding Achievement Award on November 3, 2009 in
Milan at an exclusive ceremony during the eighths ID WORLD International Congress, the Global
Summit on Automatic Identification.

The objective behind selecting this organization was, in 2011 most of the organizations are not
performing well due to certain reasons including political influences and worldwide recession. But
NADRA was one of the organizations who have maintained their position which showed the good
performance of their employees.

1.4 Statement of the Problem

It was commonly believed that in Pakistan most of the organizations were not performing well due to
certain reasons including political influences and worldwide recession. But NADRA was one of the
organizations which had maintained its position.

After exploring the above mentioned problem through interviews, literature review of NADRA and
pilot study the researcher intends:

To investigate the impact of Karasek’s Job Demand-Control Model on Job Satisfaction among the
employees of NADRA.

In the current study, a number of variables were critical that have been taken into account in the study.
These comprised Job Demand, Job Control and Social & Colleague Support.

1.5 Objective of the study
1. To study the impact of Karasek JDC model on Job satisfaction of the employees of NADRA.
2. To explore the factors of Job satisfaction
3. To find out the relationship between job demand and job satisfaction
4. To examine the impact of job control on job satisfaction
5. To determine whether job control and social support moderate the relationship between job
demands and job dissatisfaction

1.6 Significance of the study

Job satisfaction is frequently studied concept in the disciplines of management sciences,
psychology, sociology and economics. This is mainly due to the fact that job satisfaction leads to
influence the performance of the organization. No doubt, this is much debated issue but researchers
have related it to current liquidity crunch in financial sector. The Economic slump has created high
uncertainty among the people especially employees. This study was crucial to scrutinize the relation of
job satisfaction with respect to the demand and control over the job.
The results of the study facilitate supervisor to analyze possible reasons for change in employee
productivity. It further helped them to improve work environment conditions, create a better job
description, create innovative ways of assigning tasks to employees, and manage a flexible work
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environment to facilitate employees to create a balance between personal and professional life. The
study further help managers to better match the task demands to the employees' capabilities and work
load.
The study also helps future researchers to suggest and further develop mechanisms and tools to
help managers cope with the issue of declining employee productivity. The study can also help future
researchers to undertake a comparative study and analyze the role of these variables and their relation
with respect to the future better economic conditions of the market. Most importantly this study gave
guidelines to NADRA, and other organizations similar to NADRA, how to enhance the productivity of
the organization by improving the work environment and gives proper support in respect of mentor and
sub ordinate and peer to peer.

1.7 Hypothesis

According to the objectives of our study researcher predicted the following six hypotheses:
H1-Job Demands are positively associated with Job Dissatisfaction;
H2-Job Control is negatively associated with Job Dissatisfaction;
H3-Social Support is negatively related to Job Dissatisfaction;

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1.8 Research Design

Qualitative Demands
Employee’s Demands Total Demands
Workload Demands
Conflict Demands

Qualitative Control
Employee’s Control Total Control Job Dissatisfaction
Workload Control
Conflict Control

Colleagues Support
Social Support
Supervisor Support

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2. LITERATURE REVIEW

2.1 Job satisfaction and Job Performance:

Karasek’s Job Demand-Control model has a vast literature to work on. In this research, the
researcher tends to find out the influence of demand and control of job along with social support on job
satisfaction which ultimately leads to life satisfaction. The relation between life satisfaction and job
satisfaction was firstly searched by Wilensky at 1960's. (Dolan and Gosselin, 2000; Smulders, 1983, 285).
Satisfaction in one domain of individual's life extends into other areas. (Loscocco and Roschelle, 1991;
Elizur, 1991, 313; Iverson and Maguire, 2000; O'Driscoll, 1996, 281; Greenhaus and Beutell 1985, 76-88).
The relationship between job satisfaction and performance has so many issues. This is a long debate
whether good performance of the employee leads to employee’s job satisfaction or job satisfaction leads to
employees’ good performance (Kadence Buchanan). But the end result is employee’s good performance
leads to good organizational productivity.

Hawthorne studies have a strong connection between employee attitudes and performance. These
studies (1924-1933), mainly recognized to Elton Mayo of the Harvard Business School, were introduced to
find the relationship between different factors on the employee productivity. This connection was studied
and seriously considered in 1930’s (Roethlisberger, 1941). According to Hawthorne study human relations
movement deepens the interest in the relationship. After these studies Brayfield and Crockett (1955) has
studied the same relationship between job satisfaction and job performance, and also these studies shows
the relationship with other behavioral outcomes (accidents, absence and turnover).

2.2 Job Satisfaction:

Hoppock (1935) has coined a term job satisfaction by reviewing 35 studies on satisfaction. These
studies were carried out to observe the job satisfaction which shows that job satisfaction is the mixture of
different condition like environmental, mental and the functions of growth and development. But the nature
of job cannot be measured through the number of different variables that directly effecting the satisfaction
of the individual. This finding provided strong evidence that people work for purposes other than pay,
which paved the way for researchers to investigate other factors in job satisfaction. Khan (2006) reveals in
his study that Hoppock (1935) brought Job satisfaction to lime light. He observed job satisfaction in the
combination of psychological and environmental circumstances that cause person to fully say, “I am
satisfied with my job”.

In the field of job satisfaction, some studies suggest that employees are satisfied when they get good
remuneration. This suggestion is very helpful for the organizations and they implement different wage
payments system along with other incentives, allowances and non-monetary benefits (Aswathappa, 2003).
According to him, he explained three theories of remuneration

1. Reinforcement and expectancy theory

2. Equity theory

3. Agency theory

When we talk about Job Satisfaction, it diverts the attention towards the organizational psychology because
job satisfaction is the end result in most of the studies. This is one of the affective finding in anyone’s job.

2.3 Job Demand-Control model:

The Job Demands-Control model dates back to the late 1970’s, when Karasek a North America scholar
with a background in industrial sociology (1979), presented a job strain model according to which mental
stress and strain result from the interaction of job demands and job control. This model predicts that mental
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strain and job dissatisfaction are the combination of high job demands with low job control. Therefore, four
types of jobs predicts through this model which might result from different combinations of job demands
and job control: passive jobs (low demands and low job control), low strain jobs (low demands and high
job control), high strain jobs (high job demands and low job control), and active jobs (both high demands
and high job control).

Job Demand Control (JDC) model was given by a scholar of industrial sociology named Karasek in
1979. This model is mainly focused on the stress that employees face in their occupation. Stress is one of
the most serious work hazards of the Present times (Darley & Parfitt, 1996; Jamal 7 Baba 1992). The effect
of work-related stress on employees is severe with 50-80% of all diseases having a stress related nature
(Dotard & Wine field, 1996; Jamal & Badawi, 1993). Among the numerous problems employees face due
to job stress, the most significant ones relate to job dissatisfaction, burn out, high absenteeism, high
turnover, low organizational commitment, and low (marginal) job performance (Jamal 1984; Jamal 1985;
Jamal and Baba 1997; Jamal Badawi 1995; Westman & Eden 1996). Matterson and Ivancevich (1987)
estimated that stress cause 50% of absenteeism, 40% of turnover and 5% of total lost productivity due to
preventable job stress.

Organizations have begun to realize that the job stress of their employees is costing the organization. This
realization has fueled research into the cause and effects of stress. Stress is caused by strain (Karasak
1990). Karasak and Theorell, (1990) described strain as the result of comparing demands that the job has on
the employee to the control the employee has over the job. Plotted on a Matrix, the job types are 4. (Lu
1999)

The ‘high-strain jobs’ result in the highest job result (Karasak & Theorell, 1990). Karasak’s demand/
control model of determining stress is highly credible, but it lacks certain variables; which gave evolved
over time. (Lu 1999) Karasak did his initial work in late 1960’s. Since then, many factors have been added
to the work environment such as improving quality and productivity, improving people’s skills, managing
workforce diversity, responding to Globalization, empowering people, stimulating innovation and change,
dealing with “Temporariness”, decreasing employee loyalty and improving ethical behavior etc. (Edwards
1979; Robbins 1993). Karasek et al.’s (1982) has worked on to investigate the connection among job
demands, job control and support. Therefore, this research and several more recent studies adopting a
similar approach (Carrere et al., 1991; Kawakami et al., 1997; Unden, 1996). Strong support comes from
just two studies (Landsbergis et al., 1992; Parkes et al., 1994), with diverse findings in two others.

Job stress can be viewed as an individual’s reaction to work environment characteristics that approach
threatening. It generally indicates a poor fit between the individual and work abilities and work
environment. (Jamal, 1999)

Another model of understanding job stress is the P-E fit model given by Caplan, Cobb, French, Harrison, &
Pinneau, 1982 and Jamal and Ahmad, 1985. This model describes that stress results from a poor fit between
an individual’s abilities and the work environment. Either the environment may make regular, excessive
demands on the individual or the individual’s abilities may fall short of the environment’s requirements.
The types of stress identified are 1) Chronic Stress and 2) Acute Stress. Dwyer and Ganster (1991) made
difference between psychological demands of job (e.g., vigilance and precision requirements) and physical
demands of job (e.g., muscular exertion, exposure to job hazards), in the areas of manufacturing
organizations.

2.4 Job Demand-Control-Support Model:

The model which has three variables is known as three-way interactive model. It is evolved from
two way interaction of demand control then social support was added to make it three-way interaction
model. Mainly, the model showed the fair effects of control on the demand-strain relationship will be found
only when support is high. When we talk about three-way interaction model, researchers have found that

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the addition of support is an important expansion of two-way model (Johnson, and Hall, 1988; Winnubst,
and Schabracq, 1996).

Johnson & Hall (1988) tells us that social support plays a vital role in the interaction between job
demand and job control. Wong et al. (2007) mentioned that negative strain should be very low when job
demands and role clarity is high because every employee knows what to and how to do the tasks which
effects in strain which is negative in type. On the other hand when the employees don’t know how to do the
task and they are expected to do all the tasks then it results in strain which is high in nature. So it can be
derived that the link between role clarity and demand depends on condition where role clarity moderates
the demand-strain relationship.

Karasek gave another form to his model by adding supervisory support where supervisory support
has a influence on his or her well-being, then many researches have taken place to study the level of
supervisory support within a group. Some studies show the relationship between supervisory support and
occupational stress (Leather, Lawrence, and Dickson, 1998; Winnubst, and Schabracq, 1996), while Carl
Andrew et al. (2000) gave the other approach. According to them high job demands and role clarity is
effective in the case where employee is also the member of supportive leaders because the link with support
is more significant than the interactive effect of job control. Johnson and Hall (1988) found that there is
lack of social support that can beat the buffering effects of job control.

Karasek’s model basically found the relationship between job demand and job control on strain.
Bradley (2004) attempted to produce findings from the studies published between 1979 and 2003 and he
identified that many studies supported that job control buffers the job demands-strain relationship. The test
which he used to validate his studies is ANOVA.

This is for sure that the interaction between job demands and job control leaves a physiological,
affective and behavioral strain. Van der Doef and Maes (1999) found that the outcome of the “job control
buffering” was physiological well-being, job satisfaction or job related well-being. Social support did not
fluctuate significantly by sample characteristics in many studies (de Jonge, Dollard, Dormann, & Houtman,
2000).

Vermeulen and Mustard (2000) interviewed thousands of workers regarding effect of job factors
on strain. The results were stronger for males. Warr (1990) and Wall et al. (1996) found the impact of job
demands and job control on physiological features among different samples of 1000 workers. Warr
suggested these interactions as non-significant whereas Wall et al., (1996) recommended them as
significant. Strain hypothesis has been approved but not the buffer hypothesis (e.g. Pelfrene, Vlerick,
Kittel, Mak, Kornitzer & de Backer, 2002; Rafferty, Friend & Landsbergis, 2001; Van der Doef et al.,
2000; Verhoeven, Maes, Kraaij & Joekes, 2003).

De Jonge, Reuvers, et al. (2000) concluded on the factors that involved in the interaction of three
variables among 1739 employees that absenteeism is not included in the combination with other skill
related variables. De Jonge et al. (1996) observed that support, but not job control, predicted emotional
exhaustion. Mitchell and some others studied the relationship of job demand and support and they found
that the interaction is true for only some sort of stressors, types of support and strain outcomes. Some
researcher Morrison et al. (2001) suggested that job satisfaction can be gained when they analyze the data
individually exclusive of the work environment factor and they do not predict the general health scores.

Pomaki and Anagnostopoulou’s (2001) studies and prepared a report on Greek teachers and
concluded that social support does not support the strain outcome measured and job control has no
additional effect. Tetrick and La Rocco (1987) figured out that the relationship between role stressors and
job satisfaction was moderated by job control, but job control did not moderate the relationship between
stressors and psychological state of happiness. Chay (1993) studied JDC model and concluded that when
one of the two job factors was present, the other was unnecessary. Bromet et al. (1988) found that job
demands and job control interacted to predict alcohol problems and physical symptoms. He used
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longitudinal data which he obtained from medical interviews. Buffering effects of social support on strain
are measured by Repetti (1993) and he suggested that the effect is weak and unconvincing. Buunk and
Peeters (1994) suggested that these effects are rarely found more than expected by chance. On the other
hand to above views, Dollard and Winefield (1995) found that social support did not have a moderating
effect upon general mental health status, whereas Greller et al. (1992) reported that this effect was
significant in predicting psychosomatic complaints in police officers. The reason behind is that Dollard and
Winefield job controlled for negative affectivity, whereas Greller at al. did not do so. Rau et al. (2001)
found that the interaction of job control and colleague support predicted several measures of heart rate, but
not of blood pressure.

LaRocco et al. (1980) found that role of social support is the outcome of relationship among demand and
such signs of strain and it does not have any significant response on demand and satisfaction association.
On the other hand, Beehr (1985) gave a line that different types of support have differential effects.
Exclusively, active support have a reasonable effect upon strain by minimizing the harmful response of job
stressors, whereas emotional support was thought to have two effects - it directly reduces strain as well as
moderating the demand-strain linkage at workplace. These conflicting investigations are due to
involvement of many numbers of variables. Some researchers (e.g., Daniels & Guppy, 1994; Fusilier,
Ganster, & Mayes, 1987; Lefcourt et al., 1984; Rodriguez et al., 2001) said that the impact of social support
is different for different measures if internal control. Social support is given on the basis of other variables
as well. Cohen and Wills (1985) suggested that social support varies on the basis of person interaction
within social group. Conversely, the moderating effect of social support is proposed to fulfill the
requirements of stressed employees (Beehr et al., 2003, and Winnubst & Schabracq, 1996). The moderating
impact of social support on stress is not direct. According to stress matching theory, there are some
complications. To resolve this complex mechanism, Bradley, (2004) drawn a conclusion from the vast body
of research.

2.5 JDC Model and Social Support

Collective proves on this model testing implies that social support at work may either have a direct effect
on the level of job strains independent of the level of job stressors (Payne, and Jones, 1987;Loscocco, and
Spitze, 1990; Parasuraman, Greenhaus, and Granrose, 1992; Roxburgh, 1996 ; Andries et al., 1996;). The
job strain buffering hypothesis assumes social support (by all sides) are effectively mobilized to counteract
job stress so that negative consequences of job stress are reduced (Gore, 1985). Based on this analysis and
in accordance with the JDCS model of Johnson and Hall (1988), it is anticipated that low support combined
with high job strain conditions (i.e. high job demands and low job control) will have negative effects on
mental health, as compare to either low support and low strain environment or high support and high strain
environment. Unfortunately, cross-sectional as well as longitudinal studies on the JDCS model have not
been unanimous in their results.

Researches on the Karasek’s original JDC model, predicted results are obtained particularly with
cardiovascular disease (Johnson, 1986; Astrand, Hanson, and Isacson, 1989; Johnson, and Hall, 1988;

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Johnson et al., 1989), whereas for somatic complaints and psychological strain, results are contradictory.
Andries et al. (1996) claimed to support the JDCS model, they merely compared different combinations of
the three variables and did not specifically test the 3-way multiplicative interaction relationship.
Nevertheless, the stress moderating role of social support at workplace was not found in other studies
(Melamed et al, 1991; Fahtera et al., 1996). On the other side of picture the results of the study by Parkes et
al. (1994) were mixed; the models `worked’ for somatic symptoms but not for job satisfaction or improve
productivity.

Landsbergis et al. (1992) established a important interaction between job demands, job control and social
support but did not reproduce the expected stress moderating effect of social support. The results of their
study showed that in active jobs that are characterized by high job demands and high job control, poor
social support was related to job dissatisfaction. Similar results were found by Schaubroeck, and Fink
(1998), who suggested that workers facing high demanding job situations coupled with high job control and
low support, or low job control and high support will tend to experience difficulties in coping because one
key ingredient for successful coping is required the equality of job control and social support.

3. METHODOLOGIES

3.1 Population

For the purpose of the research, all the employees of NADRA Head quarters, Islamabad, Pakistan were
considered as population. NADRA employs a highly skilled workforce of more than 11,000 technical and
management personnel.

3.2 Sample

In order to carry out the research, a sample of 200 employees was chosen from NADRA.
Questionnaires were personally distributed among them. 163 male and 37 female were included in the
sample.

Distributed Complete Received
Male Female Total Male Female Total
09-11 55 7 62 12 5 17
12-16 42 20 62 23 11 34
17-20 66 10 76 50 5 55
163 37 200 85 21 106

3.3 Instrument:

Questionnaire has been used for the purpose of data collection by keeping following advantages in
mind.

• In Questionnaires the responses are gathered in a standardized way, that why questionnaires
are more objective than interviews.
• Generally it is relatively quick to collect information using a questionnaire. However in some
situations they can take a long time not only to design but also to apply and analyze.
• Potentially information can be collected from a large portion of a group. This potential is not
often realized, as returns from questionnaires are usually low. However return rates can be
dramatically improved if the questionnaire is delivered and responded to in bounded time.

15

3.3.1 Designing Questionnaire:

In order to qualitatively analyze the relationship between the factors under study, researchers made the use
of structured questionnaire, which comprised 51 questions. Further, the questionnaire was divided into 5
parts according to the variables. For the first variable, Job Demand, 16 questions were asked based on the 5
point likert scale ranging from 1= “Completely False” to 5= “Strongly True”. Same number of questions
were asked for the Job Control variable by using 5 point liker scale ranging from 1= “Virtually No Control”
to 5= “Complete Control”. Then 11 questions were asked for the Job Dissatisfaction variable on the basis
of 5 point likert scale ranging from 1= “Strongly Disagree” to 5= “Strongly Agree”. Then 8 questions were
for Social Support. Same 5 point likert scale was used ranging from 1= “Not at All” to 5= “Very Much”.
Questionnaire attached at Annex ‘A’.

3.3.2 Job Demand:

Job Demands (JD) refers to the amount of workload or responsibilities or perquisites placed on an
individual to work under these. It was measured by taking Job Content Survey. The variable has four
facets: Qualitative Demands, Employee Demands, Workload Demands and Conflict Demands. Job
Demand was taken as first variable and it was grouped in first part namely “A”. It consisted of 16 questions
measured on 5 point likert scale. Q1, Q7, Q11 and Q13 were asked for Qualitative Demands (QD). Q4,
Q14, Q15 and Q16 were asked to measure Employee demands (ED). Furthermore; Q2, Q3, Q6 and Q12
were measured for Workload Demands (WD) and lastly, Q5, Q8, Q9 and Q10 were asked for Conflict
Demands (CD).

3.3.3 Job Control:

Basically, Job Control (JC) refers to the extent to which an individual has a capability to exercise authority
over one or all potential and actual stressors of job. It was second part in questionnaire represented by “B”.
Researcher used Ganster’s (1989) validated measure of job control. Total 16 questions were asked on 5
point Likert scale. Job control was further divided into four main facets: Qualitative Control (QC),
Employee Control (EC), Workload Control (WC) and Conflict Control (CC). QC was measured through
Q1, Q7, Q11 and Q13 of part “B”. EC was measured through Q4, Q14, Q15 and Q16 of same part. Q2, Q3,
Q6 and Q12 of part “B” were taken to measure WC and CC was measured through Q5, Q8, Q9 and Q10.

3.3.4 Job Dissatisfaction:

Employee’s job satisfaction was measured by a four-item scale from Caplan et al. (1975), with some minor
changes in scale which ended up to 11 items. Each item was scored on a 5-point Likert scale. The particular
part was represented by “C”. All 11 questions were based on Employee Job Dissatisfaction (JDis).

3.3.5 Social Support:

Job support (JS), the last measurement of the Karasek’s (1979) model, looks at the level and nature of
backing given by the management or the supervisors or colleagues or subordinates to the employee. Social
Support was measured using Bradley, (2004), Caplan, Cobb, French, Van Harrison, and Pinneau's (1975)
Social Support Scale and revised social support scale. Because that measure includes two subscales: social
support from supervisor (Part D) and social support from work colleagues (Part E). Both parts had 4
questions each based on 5 point Likert Scale.

3.4 Data Collection:

16

The number of male respondents was 85 while female respondents were 21 (Table 3.1). Thus,
among the 200 questionnaires distributed, with one follow up, 106 completed questionnaires were returned,
yielding a response rate of 53 %. Rest 94 questionnaires were either incomplete or they did not respond
Those employees lied in the grade between BPS-09 to BPS 20. All other positions were excluded for the
purpose of research, because the content of questionnaire was not easily understandable to all of the
employees of NADRA. From BPS-09 to BPS-11, the researcher considers them low level employees.
Middle level employees were from BPS-12 to BPS-16 while top level or officers were from BPS-17 to
BPS-20.

The respondents who completed the questionnaires are 106. Among 106, 85 were male and 21
were female. From BPS-09 to BPS-11, 12 males responded and 5 females replied which means, total 17
employees responded from BPS-09 to BPS-11. From BPS-12 to BPS-16, 23 males responded and 11
females replied which means, total 34 employees responded from BPS-12 to BPS-16 and from last group
which was BPS-17 to BPS-20, total 55 employees responded, among 55, 50 were male and 5 were females.
The number of questionnaires returned incomplete or not replied was 96. 78 males and 16 females returned
incomplete questionnaires.

The Non probabilistic sampling technique was used. And sample was selected based on
convenient sampling. As the subject of the study were top, middle and low level employees, therefore, a
sample of 200 employees was fairly justifiable as the sample had homogenous characteristics and that it
was a true representative of the original population.

4. DATA ANALYSIS

Data analysis is a process of transforming the collected data into useful information. This is an
important phase of research process. There are two types of data; one is qualitative and other is
quantitative. It provides us to explore the data into textual, tabular and graphical form by using some
statistical tools.

This research was based on qualitative data. For the purpose of this research study, the researcher had
analyzed the data descriptively in which frequencies were shown for the independent variables i.e Job-
Demand, Job-Control and Social-Support and dependant Variable which was Job-Dissatisfaction. These
frequencies were shown in table 4.1, 4.2, 4.3 and 4.4 respectively. The graphical representation of these
variables was shown in the form of bar charts.

For the purpose of analysis, SPSS-17 was used. Linear Regression and correlation were analyzed
through this software. Some descriptive statistical tests and Correlation matrix were performed on MS
Excel as well.

17

Frequency Distribution
Job-Demand

Frequency Percent Frequency Percent

1.81 1 .9 3.56 9 8.5
2.19 2 1.9 3.63 8 7.5
2.56 1 .9 3.69 8 7.5
2.94 4 3.8 3.75 8 7.5
3.00 3 2.8 3.81 3 2.8
3.06 1 .9 3.88 1 .9
3.13 5 4.7 3.94 3 2.8
3.19 7 6.6 4.00 2 1.9
3.25 3 2.8 4.13 1 .9
3.31 4 3.8 4.19 1 .9
3.38 17 16.0 4.38 2 1.9
3.44 10 9.4 4.94 1 .9
3.50 1 .9
Table 4.1 shows the frequency distribution for the independent variable Job-Demand

Fig 4.1 Bar Chart for table 4.1

JobDemand

15

10

5

0
1.81 2.56 3.00 3.13 3.25 3.38 3.50 3.63 3.75 3.88 4.00 4.19 4.94
2.19 2.94 3.06 3.19 3.31 3.44 3.56 3.69 3.81 3.94 4.13 4.38

Frequency distribution:
Job-Control
18


2.63 3 2.8 3.50 5 4.7
2.69 1 .9 3.56 5 4.7
2.75 1 .9 3.63 7 6.6
2.81 2 1.9 3.69 4 3.8
2.94 2 1.9 3.75 2 1.9
3.00 2 1.9 3.81 4 3.8
3.06 6 5.7 3.88 2 1.9
3.13 14 13.2 3.94 2 1.9
3.19 11 10.4 4.00 4 3.8
3.25 5 4.7 4.06 2 1.9
3.31 6 5.7 4.13 1 .9
3.38 3 2.8 4.19 3 2.8
3.44 9 8.5
Table 4.2 shows the frequency distribution for the independent variable Job-Control

Fig 4.2 Bar-Chart for table 4.2 JobControl

14

12

10

8

6

4

2

0
2.63 2.75 2.94 3.06 3.19 3.31 3.44 3.56 3.69 3.81 3.94 4.06 4.19
2.69 2.81 3.00 3.13 3.25 3.38 3.50 3.63 3.75 3.88 4.00 4.13

19

Frequency distribution
Social-Support


2.25 2 1.9 3.38 10 9.4
2.38 2 1.9 3.50 15 14.2
2.50 3 2.8 3.63 13 12.3
2.63 3 2.8 3.75 10 9.4
2.75 1 .9 3.88 5 4.7
2.88 4 3.8 4.00 7 6.6
3.00 4 3.8 4.13 4 3.8
3.13 11 10.4 4.25 2 1.9
3.25 6 5.7 4.38 4 3.8
Table 4.3 shows the frequency distribution for the independent variable Social-Support

Fig 4.3 Bar Chart for Table 4.3
SocialSupport

15.0

12.5

10.0

7.5

5.0

2.5

0.0
2.25 2.50 2.75 3.00 3.25 3.50 3.75 4.00 4.25
2.38 2.63 2.88 3.13 3.38 3.63 3.88 4.13 4.38

20

Frequency Distribution
Job Dissatisfaction


2.64 1 .9 3.73 9 8.5
2.82 2 1.9 3.82 7 6.6
2.91 2 1.9 3.91 7 6.6
3.00 4 3.8 4.00 10 9.4
3.09 2 1.9 4.09 7 6.6
3.18 1 .9 4.18 9 8.5
3.27 1 .9 4.27 8 7.5
3.36 3 2.8 4.36 2 1.9
3.45 9 8.5 4.45 4 3.8
3.55 10 9.4 4.64 2 1.9
3.64 6 5.7
Table 4.4 shows the frequency distribution for the dependent variable Job-Dissatisfaction

Fig 4.4 Bar-Chart for table 4.4 JDis

10

8

6

4

2

0
2.64 2.91 3.09 3.27 3.45 3.64 3.82 4.00 4.18 4.36 4.64
2.82 3.00 3.18 3.36 3.55 3.73 3.91 4.09 4.27 4.45

21

For the purpose of data analysis, the researcher verified all hypotheses.

H1-Job demands are positively associated with job dissatisfaction;

To test the first hypothesis, the researcher needed to check the relationship between Job Demand and Job
Dissatisfaction. Job demand was calculated by taking the mean values of Qualitative Demand, Employee
Demand, Work Demand and Conflict Demand.

Descriptive Statistics

Mean Std. Deviation N
Job-Dissatisfaction 3.7839 .43089 106
Job-Demand 3.4570 .41533 106

Table 4.5 shows the Mean and Standard Deviation Value for

Job-Demand and Job-Dissatisfaction

Two statistical tests i-e correlation and regression were applied to find the relationship between job demand
and job dissatisfaction. The results indicated are as follows;

Correlations

Job-Dissatisfaction Job-Demand
Pearson
Job-Dissatisfaction 1.000 .078
Correlation
Job-Demand .078 1.000
Job-Dissatisfaction . .215
Sig. (1-tailed)
Job-Demand .215 .
Job-Dissatisfaction 106 106
N
Job-Demand 106 106

Table 4.6 shows the correlation between Job-Demand and Job-Dissatisfaction

This figure of correlation showed a positive relationship between Job Demand and Job Dissatisfaction.
Significance level of .000 means high significant relationship between both variables. Figure of Pearson
correlation indicated that 7.8% of variation in job dissatisfaction was caused by job demand and the impact
of job demand was positive on job dissatisfaction. It meant that demand is leading to increase in the
dissatisfaction of employees. Significance was 1-tailed because our hypotheses were strong in nature.

22

Regression:

Variables Entered/Removed(b)
Model Variables Variables Method
Entered Removed
1 Job-Demand(a) . Enter
a) All requested variables entered.
b ) Dependent Variable: Job-Dissatisfaction

Model Summary(b)
Model R R2 Adjusted R2 Std. Error of the
Estimate
1 .078(a) .006 -.004 .43165
a) Predictors: (Constant), Job-Demand
b) Dependent Variable: Job-Dissatisfaction

Table 4.7 shows the regression Analysis of Job-Demand and Job-Dissatisfaction

The value of R2 was showing the goodness of fit of a model. Value in this analysis was 0.006 which was
normally acceptable in qualitative data like the current study. Adjusted R2 was a modification of R2 that
adjusted for the number of explanatory terms in a model. Unlike R2, the adjusted R2 increases only if the
new term improves the model more than would be expected by chance. There is minute difference in this
study regarding R2 and Adjusted R2. It means there would be minor change in the results even if the
population was used instead of sample.

ANOVA (b)

Model Sum of df Mean Square F Sig.
Squares
1 Regression .117 1 .117 .629 .429(a)
Residual 19.378 104 .186
Total 19.495 105
a) Predictors: (Constant), Job-Demand

Table 4.8 shows the results of ANOVA

The ANOVA test was applied to see the explanatory power of model applied in this study. F value was
0.629 which was much lower than acceptable value. The significance level was also strong.

Coefficients (a)

Model Unstandardized Standardized t Sig.
Coefficients Coefficients
B Std. Error Beta
1 (Constant) 3.506 .353 9.928 .000
Job-Demand .080 .101 .078 .793 .429
a) Dependent Variable: Job-Dissatisfaction

23

Table 4.9 shows the t value and significance level

Standardized value of Beta showed the sensitivity of dependent variable i-e, Job Dissatisfaction due to Job
Demand. It again showed 7.8% positive variation which was caused by independent variables. t value
showed significant difference between 2 groups researchers were studying. It showed a highly significant
value of independent variable on dependent variable. So H1 was accepted that showed

“Job demands are positively associated with job dissatisfaction”

Residuals Statistics (a)

Minimum Maximum Mean Std. Deviation N
Predicted Value 3.6516 3.9030 3.7839 .03341 106
Std. Predicted Value -3.959 3.565 .000 1.000 106
Standard Error of Predicted .042 .172 .055 .023 106
Value
Adjusted Predicted Value 3.5344 4.0112 3.7839 .04382 106
Residual -1.07555 .81383 .00000 .42959 106
Std. Residual -2.492 1.885 .000 .995 106
Stud. Residual -2.561 1.907 .000 1.007 106
Deleted Residual -1.13648 .83229 .00000 .44039 106
Stud. Deleted Residual -2.633 1.932 -.002 1.016 106
Mahal. Distance .002 15.677 .991 2.388 106
Cook's Distance .000 .241 .013 .037 106
Centered Leverage Value .000 .149 .009 .023 106

Table 4.10 shows the difference between the sample and the estimated function value.

Histogram
Histogram:

Dependent Variable: JDis

20

15
Frequency

10

5

Mean =-4.93E-15
0 Std. Dev. =0.995
N =106
-3 -2 -1 0 1 2

Regression Standardized Residual

Histograms were used to represent the data in distributions.

Scatter Plot/Diagram:

24

Scatterplot


Regression Standardized Residual 2

0

-2

-2.5 0.0 2.5
Fig 4.6 Regression Standardized Predicted Value

Scatter Plots (also called scatter diagrams) were used to investigate the possible relationship between two
variables

H2-Job control is negatively associated with job dissatisfaction;

To test this hypothesis, the researcher needed to check the relationship between Job Control and Job
Dissatisfaction. Job Control was calculated by taking the mean of Qualitative Control, Employee Control,
Work Control and Conflict Control.


Job-Control 3.3945 .36651 106


Job-Control and Job-Dissatisfaction

Two statistical tests i-e correlation and regression were applied to find the relationship between Job Control
and Job Dissatisfaction. The results indicated were as follow;

Correlations

25

Job-Dissatisfaction Job-Control
Pearson Job-Dissatisfaction 1.000 .272
Correlation Job-Control .272 1.000
Job-Dissatisfaction
. .002
Sig. (1-tailed) Job-Control .002 .
N Job-Dissatisfaction 106 106
Job-Control 106 106

Table 4.12 shows the correlation between Job-Control and Job-Dissatisfaction

This figure of correlation showed a positive relationship between Job Control and Job Dissatisfaction.
correlation indicated that 27% of variation in job dissatisfaction was caused by job control and the impact
of Job Control was positive on Job Dissatisfaction. It meant that’s when there was increase in Job Control
there was an increase in the Dissatisfaction of employee as well. Significance was 1-tailed because our
hypotheses were strong in nature.

Regression:

Model Variables Entered Variables Removed Method
1 Job-Control(a) . Enter

Model Summary(b)
Estimate
1 .272(a) .074 .065 .41665
a) Predictors: (Constant), Job-Control

Table 4.13 shows the regression Analysis of Job-Control and Job-Dissatisfaction

normally acceptable in qualitative data like the current study. Adjusted R2 was a modification of R2 that
adjusted for the number of explanatory terms in a model. Unlike R2, the adjusted R2 increased only if the
new term improved the model more than would be expected by chance. There was minute difference in this
study regarding R2 and Adjusted R2. It means there was less change in the results even if the population was
used instead of sample.

ANOVA (b)

26

Model Sum of df Mean Square F Sig.
Squares
1 Regression 1.441 1 1.441 8.301 .005(a)
Residual 18.054 104 .174
Total 19.495 105
a) Predictors: (Constant), Job-Control


8.301. The significant level was very strong.

Coefficients (a)

Model Unstandardized Standardized t Sig.
B Std. Error Beta
1 (Constant) 2.699 .379 7.126 .000
Job-Control .320 .111 .272 2.881 .005


Standardized value of Beta showed the sensitivity of dependent variable i-e, Job Dissatisfaction was due to
Job Control. It again showed 27% positive variation which was caused by independent variables. t value
value of independent variable on dependent variable. So H2 was rejected which was;

“Job control is negatively associated with job dissatisfaction;”


Minimum Maximum Mean Std. N
Deviation
Predicted Value 3.5379 4.0374 3.7839 .11715 106
Value
Residual -.91952 .77880 .00000 .41466 106
Std. Residual -2.207 1.869 .000 .995 106
Stud. Residual -2.222 1.882 -.001 1.005 106
Deleted Residual -.95043 .78922 -.00066 .42262 106
Mahal. Distance .003 4.682 .991 1.264 106
Cook's Distance .000 .134 .010 .017 106

27



The residual of a sample was the difference between the sample and the estimated function value.
Histogram
Histogram


20

15
Frequency

10

5

Mean =-4.4E-15
0 Std. Dev. =0.995
N =106
-3 -2 -1 0 1 2
Fig 4.7 Regression Standardized Residual

Histograms were used to represent the data in distributions.

Scatter Plot/Diagram:

28

Scatterplot


2
Regression Standardized Residual

0

-2

-2.5 0.0 2.5
Fig 4.8 Regression Standardized Predicted Value

Scatter Plots (also called scatter diagrams) were used to investigate the possible relationship between two
variables

H3-Social Support is negatively related to Job Dissatisfaction;

To test the last hypothesis, the researcher needed to check the relationship between Social Support and Job
Dissatisfaction. Supervisor Support and Colleague Support were taken to calculate the Social Support by
taking their Mean values.


Social-Support 3.4481 .48699 106


Social-Support and Job-Dissatisfaction

Two statistical tests i-e correlation and regression were applied to find the relationship between Social
Support and Job Dissatisfaction. The results indicated were as follow;

Correlations

29

Job-Dissatisfaction Social-Support
Pearson Job-Dissatisfaction 1.000 .198
Correlation
Social-Support .198 1.000
Sig. (1-tailed) Job-Dissatisfaction . .021
N Social-Support .021 .
Job-Dissatisfaction 106 106
Social-Support 106 106

Table 4.18 shows the correlation between Social-Support and Job-Dissatisfaction

This figure of correlation showed a positive relationship between Social Support and Job Dissatisfaction.
correlation indicated that 19% of variation in Job Dissatisfaction was caused by Social Support and the
impact of Social Support was positive on Job Dissatisfaction. It means increase in Social Support increases
the Job Dissatisfaction. Significance was 1-tailed because our hypotheses were strong in nature.

Regression:

Model Variables Entered Variables Method
Removed
1 Social-Support (a) . Enter
b ) Dependent Variable: Job-Dissatisfaction

Model Summary(b)
Estimate
1 .198(a) .039 .030 .42436
a) Predictors: (Constant), Social-Support

Table 4.19 shows the regression Analysis of Social-Support and Job-Dissatisfaction

normally acceptable in qualitative data like the current study. Adjusted R 2 was a modification of R2 that
adjusted for the number of explanatory terms in a model. Unlike R2, the adjusted R2 increased only if the
new term improved the model more than would be expected by chance. There was minute difference in this
study regarding R2 and Adjusted R2. It meant that there was less change in the results even if the population
was used instead of sample.

ANOVA (b)

30

Model Sum of Squares df Mean Square F Sig.

1 Regression .766 1 .766 4.255 .042(a)
Residual 18.729 104 .180
Total 19.495 105
a) Predictors: (Constant), Social-Support


4.255 which was much lower than acceptable value of 20. The significant level was very strong.

Coefficients (a)

Model Unstandardized Standardized T Sig.
B Std. Beta
Error
1 (Constant) 3.179 .296 10.736 .000
Social-Support .175 .085 .198 2.063 .042


Standardized value of Beta showed the sensitivity of dependent variable i-e, Job Dissatisfaction due to
Social Support. It again showed 19% positive variation which was caused by independent variables. t value
value of independent variable on dependent variable. So H3 was rejected which was;

“Social Support is negatively related to Job Dissatisfaction;”


Minimum Maximum Mean Std. N
Deviation
Predicted Value 3.5737 3.9465 3.7839 .08542 106
Value
Residual -1.09083 .73375 .00000 .42234 106
Std. Residual -2.571 1.729 .000 .995 106
Stud. Residual -2.588 1.754 .000 1.007 106
Deleted Residual -1.10590 .75476 -.00024 .43249 106
Mahal. Distance .011 6.053 .991 1.378 106
Cook's Distance .000 .095 .012 .020 106

31



5. Conclusion:

This research was an attempt to find out the impact of Karasek’s (1979; Karasek & Theorell,
1990) models of job strain and work environment. The data was analyzed by Statistical Package for Social
Sciences (SPSS) 17. It showed that Job-Demand was positively associated with Job-Dissatisfaction and
Job-Control and Social-Support were negatively associated with Job-Dissatisfaction. According to
literature review, the researcher figured out that Job-Demands are positively associated with Job-
Dissatisfaction and Job-Control and Social-Support are negatively associated with Job-Dissatisfaction. The
first part is verified and other two are not. So

H1 Job demands are positively associated with job dissatisfaction Accepted
H2 Job control is negatively associated with job dissatisfaction Rejected
H3 Social support is negatively related to job dissatisfaction Rejected

In NADRA employee are very satisfied as their organization is performing quite well from past
years. The researcher concluded that low Job-Demands, low Job-Control and low Social Support gives
employees better satisfaction. According to Fox et al., the degree of control was mainly affected by the
individual properties like some people have less expectations from them and they don’t want to have much
power for decision plus some people are shy and they don’t want to interfere in someone’s else work so the
social support part is different for different people. The result showed that employees of NADRA were not
very authoritative that’s why they were satisfied and performed really well. Their mental approach and
authorities are stuck. S.S Wong et al., proved that the interdependencies of manager and employees
increase with the increase in demand. The results also showed that the employees of NADRA had less
demands and that’s why the relationships between employee and manager were weak.

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[2] Astrand, Hanson, & Isacsson, (1989). Job demands, job decision latitude, job supports, and social
network factors as predictors of mortality in a Swedish paper company. British Journal of
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[3] Barnett & Brennan, R. T. (1995). The relationship between job experiences and psychological
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[4] Beehr, T. A. (1985). The role of social support in coping with stress. Human stress and cognition
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[5] Beehr, T. A., Glaser, Canali, K. G., & Wallwey (2001). Back to basics: Re-examination of
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32

[7] Bradley, G. (2004). A Test of Demands-Control- Support Model. Job Strain and healthy work.
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[19] Daniels, K., & Guppy, A. (1997). Stressors, locus of control, and social support as consequences
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33

IMPACT OF KARASEK JOB DEMAND CONTROL MODEL ON THE JOB SATISFACTION OF THE EMPLOYEES OF NADRA

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