CHAPTER 04
RESEARCH FINDINGS
To determine the job satisfaction of female employees is the core aspires of this study. Survey was conducted to instigate this research comprehensively from scratch. Data that was collected is tabulated in following portions of this chapter.
4.1 Reliability and validity analysis:
In order to assess that how much the female employees are satisfied with their jobs questionnaires were distributed among the female staff of banks and telecommunication companies. For the questionnaire evaluation pilot study was conducted and the results of pilot testing shows that the Cronbach’s alpha coefficient value for all variables in the study revealed a value of coefficient at 0.897, which shows that the questionnaire was reliable enough for data collection. Moreover to trim down the further ambiguities in questionnaire factor loading of the items of variables was also calculated and got the following results:
| Variables | Factor loading | Reliability analysis |
| Pay Item 1 Item 2 Item 3 | 0.874 0.915 0.735 | 0.726 |
| OCB Item 1 Item 2 Item 3 Item 4 Item 5 Item 6 Item 7 | 0.684 0.541 0.772 0.659 0.413 0.475 0.702 | 0.669 |
| Innovative Culture Item 1 Item 2 Item 3 Item 4 Item 5 Item 6 Item 7 | 0.518 0.709 0.694 0.671 0.697 0.696 0.698 | 0.744 |
| Supervisor Item 1 Item 2 Item 3 Item 4 Item 5 | 0.611 0.687 0.750 0.736 0.690 | 0.640 |
| Org Commitment Item1 Item 2 Item 3 Item 4 Item 5 | 0.665 0.632 0.742 0.690 0.518 | 0.765 |
| Promotion Item 1 Item 2 Item 3 | 0.720 0.858 0.805 | 0.693 |
| Co workers Item 1 Item 2 Item 3 | 0.758 0.821 0.805 | 0.708 |
| Working conditions Item 1 Item 2 Item 3 Item 4 | 0.676 0.627 0.807 0.744 | 0.713 |
| Recognition Item 1 Item 2 Item 3 | 0.802 0.839 0.718 | 0.689 |
| Per_Emp_Performance Item 1 Item 2 Item 3 Item 4 | 0.633 0.820 0.836 0.762 | 0.670 |
| Job satisfaction Item1 Item 2 Item 3 Item 4 Item 5 Item 6 | 0.647 0.793 0.757 0.729 0.745 0.604 | 0.683 |
Table 4.1 shows the reliability analysis and factor loading of all item of the questionnaire. Factor loading help us to eliminate such questions which have minor contribution in the questionnaire.
Initially designed questionnaire consists of total 50 questions and after the pilot testing questionnaire consisting of 41 questions was distributed for actual data collection.
In this study findings are calculated by using:
1. Descriptive statistic technique
2. Linear regression
4.2 Descriptive statistics and analysis:
To analyze the responses descriptive statistics was used in which the mean and standard deviation of independent variables versus dependent variable was obtained. The findings are shown below in the table:
Table 4.2.1
Descriptive statistics
| Descriptive Statistics | |||
| | Mean | Std. Deviation | N |
| JOB_SATISFACTION | 3.2326 | .71950 | 364 |
| PAY | 3.3031 | .95282 | 364 |
| INNO_CULTURE | 3.4007 | .71829 | 364 |
| SUPERVISOR | 3.7231 | .71860 | 364 |
| PROMOTION | 3.3864 | .91191 | 364 |
| CO_WORKERS | 3.7564 | .82723 | 364 |
| WORK_CONDITIONS | 3.5982 | .73162 | 364 |
| RRECOGNITION | 3.5247 | .83631 | 364 |
| OCB | 3.5460 | .67860 | 365 |
| PER_EMP_PER ORG_COMMITMENT | 3.9726 3.4553 | .65931 .69052 | 365 365 |
| | | | |
(Predictors: (constant), pay, innovative culture, supervisor, promotion, coworkers, working conditions, recognition, organizational commitment, organizational citizenship behavior, perceived employee performance.
Dependent variable: Job Satisfaction)
This table shows the mean score and standard deviation of independent variables (pay, innovative culture, supervisor, promotion, coworkers, working conditions, recognition, organizational commitment, organizational citizenship behavior, perceived employee performance.) and dependent variable (job satisfaction). The responses were obtained using a 5 point likert scale in the questionnaire where 1= strongly disagree and 5= strongly agree.
The mean score of job satisfaction is 3.23 i.e. tendency toward mean which shows that female employees doesn’t consider their jobs a success story. The tendency of mean score of pay, innovative culture, promotion is also at mean i.e. 3 The following mean values indicating those areas where employees were most likely to be staisfied or dissatisfied.This can be interpreted as that some females are satisfied with their company’s pay structure and they thought that their salary is as per their efforts and skills and some are of opposite views. Some respondents thought that there is a factor of spontaneity, fun and ease (innovative culture) in their organization and they can easily put forth their ideas for consideration and review and vice versa is also true for other group of employees. Similarly, some employees are of the view that there are less advancement opportunities at their work place and some thought that they can’t easily move ahead of others in their organization.
While the mean score for other variables like supervisors, co workers, working conditions and recognition. OCB, organizational commitment and perceived employee performance is at 4 = AGREE which shows that female employees of both banking sector and telecommunication sector are satisfied with their supervisor’s behavior, they have good relations with their co workers, they have not to force themselves to go to their workplace means that they are satisfied with the working conditions and they are of the view they are regularly praised for their good work and everyone gets what he or she deserves (promotional opportunities). There are equal promotional opportunities in both sectors. All the female employees are committed towards their organization. They feel proud in themselves for being the part of this organization and they have no regret on their decision of working with this organization. Similarly the female staff has high degree of organizational citizenship behavior in themselves which mean that they are always willing to help others who are absent or have heavy workload and they are so much loyal towards their organization that they like to obey company’s rules and regulations even when no one is watching them at their workplace. Whatever the situations are the female employees are always willing to work hard and they perform their tasks effectively, means no external factors influence their performance of working.
4.3 Regression Analysis:
In regression reliance of one variable (that is random), upon the other variable (that is non-random or fixed), can be calculated. For finding the contribution of independent variable towards dependent variable, Linear Regression was used. This statistical method is used to determine the predicted effect of independent variable on the dependent variable. Various findings of this research are discussed below:
4.3.1 Working Conditions and Job Satisfaction:
To assess that whether adverse working conditions have substantial effect on job satisfaction or not linear regression analysis is used and results are discussed below:
Table 4.3.1.1
Working conditions and Job Satisfaction
| | ||||
| Model | R | R square | B | P |
| 1 | 0.350 | 0.122 | 0.350 | 0.000 |
| | ||||
R value 0.350, from the table, shows that there is weak relation between working conditions and job satisfaction. As the R value is always equalents to the correlation coefficients of dependent and independent. So, this figure 0.350 also indicates weak correlation between independent variable (working conditions) and dependent variable (job satisfaction). So, the findings from the data predict that there is weak correlation (0.350) between working conditions and job satisfaction; means working conditions have no direct effect on job satisfaction.
R Square value is fraction of variation in dependent variable that is accounted for independent variable. In the findings from above mentioned table, it is clearly stated that working conditions have not so much impact on the job satisfaction. The above table clearly suggests that 12.2% (.122) changes in job satisfaction are due to working conditions and, the remaining portion may be attributed to other sources/reasons. So there is weak dependency of job satisfaction on working conditions.
Last column of the Table reports the results of the significance tests for the coefficients. P-value is reported as .000, which in this case means that the actual p-value is less than .001 and is rounded off. So, it is concluded that null hypothesis is rejected i.e adverse working conditions have no effect on level of job satisfaction. Ultimately, alternative hypothesis H1 is proved which shows that adverse working conditions significantly decrease the level of job satisfaction.
4.3.2 Pay and Job Satisfaction:
The findings of the relationship between fairness in pay and job satisfaction is discussed below:
Table 4.3.2.1
Pay and Job Satisfaction
| | ||||
| Model | R | R square | B | P |
| 2 | 0.337 | 0.065 | 0.337 | 0.000 |
| | ||||
R value 0.337, from the table, shows that there is weak relation between fairness in pay and job satisfaction. So, the findings from the data predict that there is weak correlation (0.337) between pay and job satisfaction; means pay and job satisfaction are weakly correlated.
In the findings from above mentioned table R square is equal to 0.065, it is clearly stated that pay have weak impact on the job satisfaction. The above table clearly suggests that 6.5% (.065) changes in job satisfaction are due to pay and, the remaining portion may be attributed to other sources/reasons. So there is weak dependency of job satisfaction on pay.
P-value is reported as .000, which in this case means that the actual p-value is less than .001 and is rounded off. So, it is concluded that the null hypothesis H0 will be rejected i.e pay and job satisfaction are not positively related. Ultimately, the findings prove hypothesis H2 There exist positive relationship between fairness in pay and job satisfaction.
4.3.3 Reward, Recognition and Job Satisfaction:
The findings of the relationship between fairness in pay and job satisfaction is discussed below:
Table 4.3.3.1
Reward, Recognition and Job Satisfaction
| | ||||
| Model | R | R square | B | P |
| 3 | 0.337 | 0.113 | 0.337 | 0.000 |
| | ||||
R value 0.337, from the table, shows that there is weak relation between recognition and job satisfaction. As the R value is always equalent to the correlation coefficients of dependent and independent. So, this figure 0.337 also indicates weak correlation between independent variable (reward, recognition) and dependent variable (job satisfaction). So, the findings from the data predict that there is weak correlation (0.337) between reward, recognition and job satisfaction; means reward, recognition and job satisfaction are weakly correlated.
In the findings from above mentioned table R square is equal to 0.113, it is clearly stated that reward, recognition have weak impact on the job satisfaction. The above table clearly suggests that 11.3% (.065) changes in job satisfaction are due to reward, recognition and, the remaining portion may be attributed to other sources/reasons. So there is weak dependency of job satisfaction on reward, recognition.
Last value, P-value is reported as .000, which in this case means that the actual p-value is less than .001 and is rounded off. So, it is concluded that the null hypothesis H0 will be rejected or that Reward and recognition are not directly related to job satisfaction. Ultimately, the findings prove, alternate hypothesis H3 that Reward and recognition are directly related to job satisfaction.
4.3.4 Supervisor and Job Satisfaction:
The findings of the relationship between loyalty to supervisor and job satisfaction are discussed here under:
Table 4.3.4.1
Supervisor and Job Satisfaction
| | ||||
| Model | R | R square | B | P |
| 4 | 0.230 | 0.053 | 0.230 | 0.000 |
| | ||||
R value 0.230, from the table, shows that there is weak relation between loyalty to supervisor and job satisfaction. So, this figure 0.230 also indicates weak correlation between independent variable (supervisor) and dependent variable (job satisfaction). So, the findings from the data predict that there is weak correlation (0.230) between supervisor and job satisfaction; means supervisor and job satisfaction are weakly correlated.
In the findings from above mentioned table R square is equal to 0.053, it is clearly stated that supervisor have weak impact on the job satisfaction. The above table clearly suggests that 5.3% (.053) changes in job satisfaction are due to loyalty to supervisor and, the remaining portion may be attributed to other sources/reasons. So there is weak dependency of job satisfaction on loyalty to supervisor.
Last column of the Table reports that P-value is reported as .000, which in this case means that the actual p-value is less than .001 and is rounded off. So, it is concluded that the null hypothesis H0 will be rejected or Loyalty to supervisor has indirect relationship with job satisfaction.
Ultimately, the findings prove alternate hypothesis H4 that Loyalty to supervisor has direct relationship with job satisfaction.
4.3.5 Co workers and Job Satisfaction:
The findings of the relationship between happiness with co workers and job satisfaction are discussed here under:
Figure 4.3.5.1
Co workers and Job Satisfaction
| | ||||
| Model | R | R square | B | P |
| 5 | 0.135 | 0.018 | 0.135 | 0.10 |
| | ||||
R value 0.135, from the table, shows that there is weak relation between happiness with co workers and job satisfaction. This figure 0.135 also indicates weak correlation between independent variable (co workers) and dependent variable (job satisfaction). So, the findings from the data predict that there is weak correlation (0.135) between co workers and job satisfaction; means happiness with co workers and job satisfaction are weakly correlated.
In the findings from above mentioned table R square is equal to 0.018, it is clearly stated that co workers have weak impact on the job satisfaction. The above table clearly suggests that 1.8% (.018) changes in job satisfaction are due to happiness with co workers and, the remaining portion may be attributed to other sources/reasons. So there is weak dependency of job satisfaction on happiness with co workers.
Last column of the Table reports the results of the significance tests for the coefficients. P-value is reported as .010, which in this case means that the actual p-value is more than .001 and is rounded off. So, it is concluded that the null hypothesis H0 will be accepted or Female employees are not satisfied with their co workers. Ultimately, the findings reject our alternate hypothesis H5 that Female employees are satisfied with their co workers.
4.3.6 Promotional opportunities and Job Satisfaction:
The findings of the relationship between promotional opportunities and job satisfaction are discussed here under:
Table 4.3.6.1
Promotional opportunities and Job Satisfaction
| | ||||
| Model | R | R square | B | P |
| 6 | 0.386 | 0.149 | 0.386 | 0.000 |
| | ||||
R value 0.386, from the table, shows that there is weak relation between promotional opportunities and job satisfaction. As the R value is always equalent to the correlation coefficients of dependent and independent. So, this figure 0.386 also indicates weak correlation between independent variable (promotional opportunities) and dependent variable (job satisfaction). So, the findings from the data predict that there is weak correlation (0.386) between promotional opportunities and job satisfaction; means promotional opportunities and job satisfaction are weakly correlated.
In the findings from above mentioned table R square is equal to 0.149, it is clearly stated that promotional opportunities have weak impact on the job satisfaction. The above table clearly suggests that 1.5% (.149) changes in job satisfaction are due to promotional opportunities and, the remaining portion may be attributed to other sources/reasons. So there is weak dependency of job satisfaction on promotional opportunities.
P-value is reported as .000, which in this case means that the actual p-value is less than .005 and is rounded off. So, it is concluded that the null hypothesis H0 will be rejected or Promotional opportunities and employees satisfaction are insignificantly related. Ultimately, the findings prove alternate hypothesis H6 that Promotional opportunities and employees satisfaction are significantly related.
4.3.7 Innovative culture and Job Satisfaction:
The findings of the relationship between innovative culture and job satisfaction are discussed here under:
Figure 4.3.7.1
Innovative culture and Job Satisfaction
| | ||||
| Model | R | R square | B | P |
| 7 | 0.405. | 0.164 | 0.405 | 0.000 |
| | ||||
R value 0.405, from the table, shows that there is weak relation between innovative culture and job satisfaction. So, this figure 0.405 also indicates weak correlation between independent variable (innovative culture) and dependent variable (job satisfaction). So, the findings from the data predict that there is weak correlation (0.405) between innovative culture and job satisfaction; means innovative culture and job satisfaction are weakly correlated.
In the findings from above mentioned table R square is equal to 0.164 it is clearly stated that innovative culture have weak impact on the job satisfaction. The above table clearly suggests that 16.4% (.164) changes in job satisfaction are due to innovative culture of organization and, the remaining portion may be attributed to other sources/reasons. So there is weak dependency of job satisfaction on innovative culture.
Last column of the Table reports the results of the significance tests for the coefficients. P-value is reported as .000, which in this case means that the actual p-value is less than .001 and is rounded off. So, it is concluded that the null hypothesis H0 will be rejected or Innovative culture doesn’t increase the level of job satisfaction. Ultimately, the findings prove our alternate hypothesis H7 that Innovative culture increases the level of job satisfaction, means that workers are rewarded for their risk taking activities and they can easily participate in organizations day to day activities.
4.3.8 Job Satisfaction and organizational commitment:
The findings of the relationship between organizational commitment and job satisfaction are discussed below:
Table 4.3.8.1
Organizational commitment and Job Satisfaction
| | ||||
| Model | R | R square | B | P |
| 8 | 0.467 | 0.218 | 0.467 | 0.000 |
| | ||||
R value 0.467, from the table, shows that there is weak relation between organizational commitment and job satisfaction. As the R value is always equalent to the correlation coefficients of dependent and independent. So, this figure 0.467 also indicates weak correlation between independent variable (job satisfaction) and dependent variable (organizational commitment). So, the findings from the data predict that there is weak correlation (0.467) between job satisfaction and organizational commitment; means job satisfaction and organizational commitment is weakly correlated.
In the findings from above mentioned table R square is equal to 0.218, it is clearly stated that job satisfaction have weak impact on organizational commitment. The above table clearly suggests that 21.8% (0.218) changes in organizational commitment are due to job satisfaction and, the remaining portion may be attributed to other sources/reasons. So there is weak dependency of organizational commitment on job satisfaction.
Last column of the Table reports the results of the significance tests for the coefficients. P-value is reported as .000, which in this case means that the actual p-value is less than .001 and is rounded off. So, it is concluded that the null hypothesis H0 will be rejected or Job satisfaction is insignificantly related to Organizational commitment.
Ultimately, the findings prove our alternate hypothesis H8 that Job satisfaction is significantly related to Organizational commitment.
4.3.9 Job Satisfaction and organizational citizenship behavior:
The findings of the relationship between organizational citizenship behavior and job satisfaction are discussed below:
Table 4.3.9.1
Organizational citizenship behavior and Job Satisfaction
| | ||||
| Model | R | R square | B | P |
| 9 | 0.309 | 0.095 | 0.309 | 0.000 |
| | ||||
R value 0.309, from the table, shows that there is weak relation between organizational citizenship behavior and job satisfaction. As the R value is always equalent to the correlation coefficients of dependent and independent. So, this figure 0.309 also indicates weak correlation between independent variable (job satisfaction) and dependent variable (organizational citizenship behavior). So, the findings from the data predict that there is weak correlation (0.309) between job satisfaction and organizational citizenship behavior; means job satisfaction and organizational citizenship behavior is weakly correlated.
In the findings from above mentioned table R square is equal to 0.095, it is clearly stated that job satisfaction have weak impact on organizational citizenship behavior. The above table clearly suggests that 9.5% (0.095) changes in organizational citizenship behavior are due to job satisfaction and, the remaining portion may be attributed to other sources/reasons. So there is weak dependency of organizational citizenship behavior on job satisfaction.
P-value is reported as .000, which in this case means that the actual p-value is less than .001 and is rounded off. So, it is concluded that the null hypothesis H0 will be rejected or Job satisfaction is negatively correlated with organizational citizenship behavior. Ultimately, the findings prove alternate hypothesis H9 that Job satisfaction is positively correlated with organizational citizenship behavior.
4.3.10 Job Satisfaction and perceived employee performance
The findings of the relationship between perceived employee performance and job satisfaction are discussed below:
Table 4.3.10.1
Perceived employee performance and Job Satisfaction
| | ||||
| Model | R | R square | B | P |
| 10 | 0.225 | 0.050 | 0.225 | 0.000 |
| | ||||
R value 0.225, from the table, shows that there is weak relation between perceived employee performance and job satisfaction. As the R value is always equalent to the correlation coefficients of dependent and independent. So, this figure 0.225 also indicates weak correlation between independent variable (job satisfaction) and dependent variable (perceived employee performance). So, the findings from the data predict that there is weak correlation (0.225) between job satisfaction and perceived employee performance; means job satisfaction and perceived employee performance is weakly correlated.
In the findings from above mentioned table R square is equal to 0.050, it is clearly stated that job satisfaction have weak impact on perceived employee performance. The above table clearly suggests that 5% (0.050) changes in perceived employee performance are due to job satisfaction and, the remaining portion may be attributed to other sources/reasons. So there is weak dependency of perceived employee performance on job satisfaction.
Last column of the Table reports the results of the significance tests for the coefficients. P-value is reported as .000, which in this case means that the actual p-value is less than .001 and is rounded off. So, it is concluded that the null hypothesis H0 will be rejected or: Job satisfaction is indirectly correlated with perceived employee performance ultimately, the findings prove our alternate hypothesis H10 that Job satisfaction is directly correlated with perceived employee performance.
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