We prepared Total 35 questionnaires and distributed a twelve-item questionnaire to 100 employees, among whom 66 are men and 34 are women. Data received from all the responses were inputted into SPSS software for analysis. Moreover, some questionnaires were rejected due to lack of credibility and authenticity. Table 1 indicates the percentage of male and female, who responded to the questionnaire.
Table 1
Gender
|
Frequency
|
Percent
|
Cumulative (%)
|
Male
|
66
|
66
|
66
|
Female
|
34
|
34
|
100
|
Total
|
100
|
100
|
|
Table 2
Overall job satisfaction of employees of Nassa Super Garments Ltd
Satisfaction Level
|
Frequency
|
%
|
Cumulative (%)
|
Highly satisfied
|
18
|
18
|
18
|
Satisfied
|
35
|
35
|
53
|
Neutral
|
35
|
35
|
88
|
Dissatisfied
|
5
|
5
|
93
|
Highly Dissatisfied
|
7
|
7
|
100
|
Total
|
100
|
100
|
|
From Table 2, we see more than 50% respondents are satisfied with their job (18% are highly satisfied and 35% are satisfied). On the other hand, 35% respondents are neutral with their job. Finally, 12% are dissatisfied with their job. (7% are highly dissatisfied and 5% are dissatisfied)
Table 3
Descriptive Statistics for Independent and dependent variables
Variables
|
Mean
|
Std. Deviation
|
GENERAL MANAGER'S BEHAVIOUR
|
3.94
|
1.144
|
JOB SECURITY
|
4.56
|
0.902
|
WORKING CONDITION AND DECISION- MAKING PROCESS
|
4.48
|
0.785
|
UNAVAILABILITY OF LEAVES AND REST
|
2.32
|
1.197
|
PAY AND OTHER FINANCIAL INCENTIVES
|
4.26
|
0.981
|
JOB NATURE
|
3.88
|
1.343
|
WORKLOAD AND STRESS LEVEL
|
2.20
|
0.984
|
LACK OF EVALUATION OF PERSONAL INTEREST
|
2.24
|
1.360
|
INEFFICIENT CANTEEN FACILITY
|
2.02
|
0.937
|
MANAGEMENT POLICY
|
4.06
|
1.179
|
REWARDS AND RECOGNITION
|
4.80
|
0.402
|
OVERALL, JOB SATISFACTION
|
3.52
|
1.019
|
Table 3 elucidates the mean and Std. Deviation of 11 variables that have impact on job satisfaction. We see employees, who responded to the questionnaire, are satisfied with their job because overall job satisfaction is 3.52.(Satisfaction range represents from 3.1 to 4). In addition, Job satisfaction is below 3 in case of unavailability of leaves and rest, workload and stress level, lack of evaluation of personal interest and inefficient canteen facility, because these four variables have generally negative impact on job satisfaction.

Table 4 shows the correlation between dependent variable (job satisfaction) and independent variables at the 0.05 level of significance. In accordance with table 4, we see job security, working condition and decision-making process have high positive correlation with job satisfaction while rewards and recognition have moderate positive (0.619) correlation with job satisfaction. We also observe that inefficient canteen facility and workload and stress level have low (-0.436) and negligible (-0.231) negative correlation with job satisfaction. All the correlations are found statistically significant at 0.05 level.

General Manager’s Behavior (GMB), Job Security (JS), Working Condition and Decision-Making Process (WCADP), Unavailability of leaves and Rest (UOLAR), Pay and Other Financial Incentives (PAOFI), Job Nature (JN), Workload and Stress Level (WASL), Lack of Evaluation of Personal Interest (LOEOPI), Inefficient Canteen Facility (ICF), Management Policy (MP), Rewards and Recognition (RAR)
Table 5 indicates Pearson correlations among independent variables. We see rewards and recognition are highly correlated (0.624) with working condition and decision-making process. Moreover, there is a high and positive correlation (0.663) between job security and general manager’s behavior, as a general manager (GM) along with director and others responsible can decide whether employees continue their job or not. Job security is also reliant upon working condition & decision-making process because they are highly correlated (0.652). On the other hand, there is negligible negative correlation between inefficient canteen facility and rewards and recognition (-.034), because rewards and recognition can never depend on inefficient canteen facility. Correlation (-.054) between job security and workload and stress level is also negligible negative, as job security is not contingent upon workload and stress level. However, workers face unavailability of leaves and rest and lack of evaluation of personal interest for mainly management policy (correlation between management policy and unavailability of leaves and rest is 0.579 and lack of evaluation of personal interest is 0.463 respectively)

Table 6 indicates the range of Pearson’s correlation coefficient. Following the given range of correlation coefficient, we made remark on correlation between dependent and independent variables and correlations among independent variables.
But correlation can’t explain the relation between dependent and independent variables in the most emphatic way. Therefore, we have adapted regression model, which can analyze the relation between dependent variable and independent variables properly.
Table 7
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
1
|
.949a
|
.901
|
.888
|
.468
|
Predictors: (Constant), GENERAL MANAGER’S BEHAVIOR, JOB SECURITY, WORKING CONDITION AND DECISION- MAKING PROCESS, UNAVAILABILITY OF LEAVES AND REST, PAY AND OTHER FINANCIAL INCENTIVES, JOB NATURE, WORKLOAD AND STRESS LEVEL, LACK OF EVALUATION OF PERSONAL INTERESR, INEFFICIENT CANTEEN FACILITY, MANAGEMENT POLICY, REWARDS AND RECOGNITION
Table 7 shows regression model summary, in which R square plays an important role. Alphabet R indicates the strength of relation between what we predicted and what the result has been measured. However, in this model our main focus on R square, which accounts for particular amount of total variance in the dependent variable. We see the value of R square is .901 or 90.1%, meaning that 90.1% of the independent variables directly affect the dependent variable (overall job satisfaction). It also indicates that 90.1% of total variance in the dependent variable must be explained by independent variables and the remaining 9.9% are explained by other variables, which are not included in our research study.
Table 8
Model
|
Sum of Squares
|
Df
|
Mean Square
|
F
|
Sig.
|
1
|
Regression
|
174.202
|
11
|
15.837
|
72.439
|
.000b
|
Residual
|
19.238
|
88
|
0.219
|
|
|
Total
|
193.44
|
99
|
|
|
|
a. Dependent Variable: OVERALL JOB SATISFACTION
b. Predictors: (Constant), GENERAL MANAGER'S BEHAVIOR, JOB SECURITY, WORKING CONDITION AND DECISION-MAKING PROCESS, UNAVAILABILITY OF LEAVES AND REST, PAY AND OTHER FINANCIAL INCENTIVES, JOB NATURE, WORKLOAD AND STRESS LEVEL, LACK OF EVALUATION OF PERSONAL INTEREST, INEFFICIENT CANTEEN FACILITY, MANAGEMENT POLICY, REWARDS AND RECOGNITION
Table 8 ANOVA clarifies whether regression model is significant or not. We see the value of “sig” is 0.000. That means the model is significant and fit for further analysis. It also indicates that independent variables (job security, working condition and decision-making process, unavailability of leaves and rest, pay and other financial incentives, lack of evaluation of personal interest, inefficient canteen facility, rewards and recognition, general manager’s behavior, job security, workload and stress level and management policy) affect the dependent variable significantly. We have plotted next coefficients table to check the significance of each variable.

Based on table 9 we see that job security, working condition and decision-making process, unavailability of leaves and rest, pay and other financial incentives, lack of evaluation of personal interest, inefficient canteen facility and rewards and recognition have statistically significant relation with job satisfaction of employees of Nassa Super Garments Limited, because p value of these variables is lower than 0.05. So, we are able to reject Ho 2, Ho 3, Ho 4, Ho 5, Ho 8, Ho 9 and Ho 11 at 0.05 level of significance. On the other hand, general manager’s behavior, job security, workload and stress level and management policy have no significant relation with the job satisfaction of employees. (P value is larger than 0.05). None of them offers any significant amount of unique variance in explaining dependent variable (job satisfaction). They may have indirect effect on job satisfaction. Therefore, we fail to reject Ho 1, Ho 6, Ho 7 and Ho 10 at 0.05 level of significance. The relation between dependent variable and independent variables can be written by the following equation:
Overall job satisfaction = 1.423 + 0.010[General manager’s behavior] + 0.529[Job security] + 0.711[Working environment and decision-making process] + -0.316[Unavailability of leaves and rest] + 0.146[Pay and other financial incentives] + 0.027[Job nature] + -0.061[Workload and stress level] + -0.479[Lack of evaluation of personal interest] + -0.186[Inefficient canteen facility] + 0.082[Management policy] + 0.207[Rewards and recognition]
Coefficient table indicates that a unite increase in General manager’s behavior increases job satisfaction by 0.010, a unite increase in job security increases job satisfaction by 0.529, a unite increase in working environment and decision-making process increases job satisfaction by 0.711, a unit increase in unavailability of leaves and rest decreases job satisfaction by -0.316, a unit increase in pay and other financial incentives increases job satisfaction by 0.146, a unit increase in job nature increases job satisfaction by 0.027, a unit increase in workload and stress level decreases job satisfaction by -0.061, a unit increase in lack of evaluation of personal interest decreases job satisfaction by -0.479, a unit increase in inefficient canteen facility decreases job satisfaction by -0.186, a unit increase in management policy increases job satisfaction by 0.082 and finally a unit increase in rewards and recognition increases job satisfaction by 0.207.
We have already found that General manager’s behavior, Job nature, Workload and stress level and management policy are statistically insignificant predictors of overall job satisfaction. We also observe that the standardized coefficients (Beta) and unstandardized coefficients(B) of unavailability of leaves and rest, lack of evaluation of personal interest and inefficient canteen facility are negative, meaning that these three variables have negative relation with job satisfaction. But they are found as statistically significant predictor of dependent variable (overall job satisfaction). So, we can say that unavailability of leaves and rest, lack of evaluation of personal interest and inefficient canteen facility are significant negative predictors of job satisfaction. However, depending on P value (0.05), Ho 2, Ho 3, Ho 4, Ho 5, Ho 8, Ho 9 and Ho 11 have been rejected. That indicates they significantly influence the job satisfaction of employees of Nasa Super Garments Ltd. Moreover, Ho 1, Ho 6, Ho 7 and Ho 10 have been deemed to have less or indirect impact on employees’ job satisfaction. In the coefficients table the value of VIF plays a significant role in identifying multicollinearity problem. We see that the value of VIF of each variable is lower than 5. That means there is no multicollinearity issue in our calculation.