4.2.1 Age
Age distribution was categorized into four subsections. According to the data, majority of the employees fall in to the age category of 26-35 which is nearly 51%. On the other hand, age categories of 18-25 and 35-45 comparatively have lesser number of employees and percentage wise 30% and 13% respectively. The least number of employees belong to the age category of 46 and above and a percentage wise 6% out of the total sample population.
Age Category (Years) No of Employees
18-25 24
26-35 41
35-45 10
46 & above 5
Table 4.1 - Age Distribution
32
Figure 4.1 - Age Distribution
4.2.2 Gender
The pie chart below shows the distribution of male and female employees at ABC Company. Out of the 80 respondents who have faced the questionnaire, 60% are female and 40% are male,
Figure 4.2. - Gender Distribution 4.2.3 Marital Status
30%
51%
13%
6%
AGE
18-25 26-35 36-45 46 or above
Male 60%
Female 40%
Gender
Male Female
33
According to the data that has been generated by the researcher and it is presented in the above graph, it is clear that the majority of the sample of employees was unmarried which contains 58%
and married employees are 42%.
4.3 Figure- Marital Status Distribution
4.2.4 Independent Variable – Employee Assistance Program
Correlations
Employee_Pe rformance
Employee_Assist ance_Programes Employee_Pe
rformance
Pearson Correlation 1 .589**
Sig. (2-tailed) .000
N 74 74
Employee_As sistance_Prog rames
Pearson Correlation .589** 1
Sig. (2-tailed) .000
N 74 74
**. Correlation is significant at the 0.01 level (2-tailed).
4.2. Correlation Table – Employee Assistance Programs
42%
58%
Marital Status
Married Unmarried
34
According to the correlation matrix, employee assistance programs are strongly associated with Employee performance. Both correlation coefficients of employee performance and Employee Assistance Programs shows positive relationship. And, Employee Assistance Programs are statistically significant at the 0.01 level (2-tailed).
The strongest positive significant association shows in between employee assistance programs and Employee Performance and its coefficient of correlation is 0.589 at a 0.01 significant level.
Regression
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .311a .097 .083 .72730
a. Predictors: (Constant), Employee_Assistance_Programes
Table 4.3-Regression Model Summary: Employee Assistance Programs and employee performance
Regression statistics R – 0.311
R Square - 0.097
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 3.579 1 3.579 6.767 .012b
Residual 33.325 72 .529
Total 36.905 73
a. Dependent Variable: Employee_Performance
b. Predictors: (Constant), Employee_Assistance_Programes
ANOVA Table 4.4: Employee Assistance Programs and Employee Performance
35 Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 2.027 .606 3.347 .001
Employee_Assistance_Progr ames
.428 .165 .311 2.601 .012
a. Dependent Variable: Employee_Performance
Coefficient Table 4.5: Employee Assistance Programs and employee performance
According to the model summary of the regression analysis on Employee Assistance Programs and Employee performance, R is 0.311 which indicates that the model is successful in predicting elements. R2 is the proportion of variance in the dependent variable which can be explained by the independent variable. In the current study, R2 is 0.097. Correlation is significant at 0.01 level.
4.2.5 Independent variable- Working Environment
Correlations
Correlations
Employee_
Performanc e
Working_En vironment
Employee_Performance Pearson Correlation 1 .780**
Sig. (2-tailed) .000
N 74 74
Working_Environment Pearson Correlation .780** 1
Sig. (2-tailed) .000
N 74 74
4.6 Correlation Table – Working Environment
The correlation between Employee Performance (Dependent Variable) and working environment (Independent Variable) is represented by the Pearson’s correlation coefficient value. (0.780) it shows that there is a moderate degree of positive correlation.
36 Regression
Model Summary
Model R R Square Adjusted R
Square
Std. Error of the Estimate
1 .780a .609 .603 .64807
Table 4.7-Regression Model Summary: Working Environment and employee performance
Regression statistics R Square – 0.780
Adjusted R Square - - 0.609
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 44.444 1 44.444 105.820 .000b
Residual 28.560 72 .420
Total 73.004 69
ANOVA Table 4.8: Working Environment and Employee Performance
Coefficientsa
37
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .086 .311 .278 .782
Working_Environment 1.033 .100 .780 10.287 .000
Coefficient Table 4.9: Working Environment and employee performance
According to the model summary of the regression analysis on working environment and Employee performance, R is 0.780 which indicates that the model is successful in predicting elements. R2 is the proportion of variance in the dependent variable which can be explained by the independent variable. In the current study, R2 is 0.609. According to the coefficient table, the regression coefficients of working environment is statistically significant. In this analysis, the regression coefficient is 0. 240. Correlation is significant at 0.01 level.
4.3.6 Independent variable- Technology Advancement
Correlations
Employee_
Performanc e
Technology_
Advancement
Employee_Performanc e
Pearson Correlation 1 .670**
Sig. (2-tailed) .000
N 74 74
Technology_Advanceme nt
Pearson Correlation .670** 1
Sig. (2-tailed) .000
N 74 74
**. Correlation is significant at the 0.01 level (2-tailed).
Correlation Table 4.10- Technology Advancement
38
According to the table of correlation between Technology advancemet and employee performance gives a positive value. Therefore, it is a strong positive relationship between Technology advancement and employee performance which means they are statistically correlated..
The correlation coefficient value of the coefficient table (0.670) indicates a strong positive relationship.
Model Summary
Model R R Square Adjusted R
Square
Std. Error of the Estimate
1 .670a .449 .441 .76887
a. Predictors: (Constant), Technology_Advancement
Table 4.11-Regression Model Summary: Technology Advancement and employee performance
R Square (R2)will show the percentage of regression between the independent variable and the dependent variable.
Regression statistics R – 0.670
R Square - 0.449
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 32.805 1 32.805 55.491 .000b
Residual 40.199 68 .591
39
Total 73.004 69
a. Dependent Variable: Employee_Performance b. Predictors: (Constant), Technology_Advancement
ANOVA Table 4.12: Technology Advancement and Employee Performance According to the tables Anova table and Coefficients table, it is identified that the relationship between Technology Advancement and employee performance was significant at 0.000 which is less than in the significance level of 1% (0.01).
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .297 .398 .746 .458
Technology_Advancement .932 .125 .670 7.449 .000
a. Dependent Variable: Employee_Performance
Coefficient Table 4.13: Technology Advancement and employee performance
According to the model summary of the regression analysis on technology advancement and Employee performance, R is 0.670 which indicates that the model is successful in predicting elements. R2 is the proportion of variance in the dependent variable which can be explained by the independent variable. In the current study, R2 is 0.449.
According to the coefficient table, the regression coefficients of technology advancement is statistically significant. In this analysis, the regression coefficient is 0. 932.
40
4.2.7 Independent variable- Workplace Stress
Correlations
Workplace_St ress
Employee_Pe rformance
Workplace_Stress Pearson Correlation 1 .352**
Sig. (2-tailed) .002
N 74 74
Employee_Performance Pearson Correlation .352** 1
Sig. (2-tailed) .002
N 74 74
**. Correlation is significant at the 0.01 level (2-tailed).
Correlation Table 4.14- Workplace Stress
According to the table of correlation between workplace stress and employee performance gives a moderate value. Therefore, it is moderate relationship between workplace stress and employee performance which means they are statistically correlated.
The correlation coefficient value of the coefficient table (0.352) indicates a moderate relationship.
Regression
Model Summary
Model R R Square Adjusted R
Square
Std. Error of the Estimate
1 .352a .124 .112 .56066
a. Predictors: (Constant), Workplace_Stress
Table 4.15- Regression Model Summary: Workplace Stress and Employee performance
Regression statistics R – 0.352
R Square - 0.124
41 ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 3.195 1 3.195 10.163 .002b
Residual 22.633 72 .314
Total 25.827 73
a. Dependent Variable: Employee_Performance b. Predictors: (Constant), Workplace_Stress
ANOVA Table 4.16 – Workplace Stress and Employee performance
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 1.332 .267 4.992 .000
Workplace_Stress .240 .075 .352 3.188 .002
a. Dependent Variable: Employee_Performance
Table 4.17: Workplace Stress and Employee performance
According to the model summary of the regression analysis on Employee Assistance Programs and Employee performance, R is 0.124 which indicates that the model is successful in predicting elements. R2 is the proportion of variance in the dependent variable which can be explained by the independent variable. In the current study, R2 is 0.352.
According to the coefficient table, the regression coefficients of Employee Assistance Programs is statistically significant. In this analysis, the regression coefficient is 0. 352 at a 0.01 significant level.
42 4.2.8 Hypotheses Testing
Hypotheses Status
Hypothesis 1
H01: There is no impact of the employee assistant programs on Employee Performance.
Rejected
Ha1: There is an impact of the employee assistant programs on Employee Performance.
Accepted
Hypothesis 2
H02: There is no impact of the working environment
between on Employee Performance. Rejected
Ha2: There is an impact of the working environment
on Employee Performance. Accepted
Hypothesis 3
H03: There is no impact of the technology advancement on Employee Performance.
Rejected
Ha3: There is an impact of the technology
advancement on Employee Performance. Accepted
Hypothesis 4
Rejected
43 H04: There is no impact of the workplace stress on Employee Performance.
Ha4: There is an impact of the workplace stress on
Employee Performance. Accepted
Table 4.18: Hypotheses Testing