Quantitaive Method Assignment Sample
(Source: SPSS)
Reliability analysis
Cronbach’s Alpha | N of Items |
.776 | 32 |
(Source: SPSS)
Correlation analysis
Confidence1 | Confidence2 | Confidence3 | Confidence4 | Hope1 | Hope2 | Hope3 | Hope4 | ||
Confidence1 | Pearson Correlation | 1 | .574** | .553** | .460** | .587** | .353** | .557** | .499** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 490.791 | 354.501 | 362.126 | 263.117 | 296.665 | 229.493 | 266.539 | 282.573 | |
Covariance | 1.410 | 1.019 | 1.041 | .756 | .852 | .659 | .766 | .812 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Confidence2 | Pearson Correlation | .574** | 1 | .772** | .731** | .535** | .426** | .466** | .548** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 354.501 | 777.140 | 636.355 | 526.513 | 340.146 | 348.298 | 280.791 | 390.160 | |
Covariance | 1.019 | 2.233 | 1.829 | 1.513 | .977 | 1.001 | .807 | 1.121 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Confidence3 | Pearson Correlation | .553** | .772** | 1 | .739** | .491** | .426** | .516** | .530** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 362.126 | 636.355 | 873.266 | 564.135 | 330.860 | 369.223 | 329.593 | 400.120 | |
Covariance | 1.041 | 1.829 | 2.509 | 1.621 | .951 | 1.061 | .947 | 1.150 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Confidence4 | Pearson Correlation | .460** | .731** | .739** | 1 | .424** | .453** | .424** | .570** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 263.117 | 526.513 | 564.135 | 668.057 | 249.983 | 343.436 | 236.848 | 376.158 | |
Covariance | .756 | 1.513 | 1.621 | 1.920 | .718 | .987 | .681 | 1.081 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Hope1 | Pearson Correlation | .587** | .535** | .491** | .424** | 1 | .392** | .649** | .497** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 296.665 | 340.146 | 330.860 | 249.983 | 519.805 | 262.269 | 319.946 | 289.453 | |
Covariance | .852 | .977 | .951 | .718 | 1.494 | .754 | .919 | .832 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Hope2 | Pearson Correlation | .353** | .426** | .426** | .453** | .392** | 1 | .442** | .641** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 229.493 | 348.298 | 369.223 | 343.436 | 262.269 | 860.510 | 280.046 | 480.198 | |
Covariance | .659 | 1.001 | 1.061 | .987 | .754 | 2.473 | .805 | 1.380 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Hope3 | Pearson Correlation | .557** | .466** | .516** | .424** | .649** | .442** | 1 | .519** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 266.539 | 280.791 | 329.593 | 236.848 | 319.946 | 280.046 | 467.352 | 286.332 | |
Covariance | .766 | .807 | .947 | .681 | .919 | .805 | 1.343 | .823 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Hope4 | Pearson Correlation | .499** | .548** | .530** | .570** | .497** | .641** | .519** | 1 |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 282.573 | 390.160 | 400.120 | 376.158 | 289.453 | 480.198 | 286.332 | 652.183 | |
Covariance | .812 | 1.121 | 1.150 | 1.081 | .832 | 1.380 | .823 | 1.874 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Resilience1 | Resilience2 | Resilience3 | Resilience4 | Hope1 | Hope2 | Hope3 | Hope4 | ||
Resilience1 | Pearson Correlation | 1 | .611** | .740** | .630** | .606** | .370** | .593** | .490** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 376.779 | 319.172 | 332.421 | 284.582 | 267.997 | 210.739 | 248.808 | 242.860 | |
Covariance | 1.083 | .917 | .955 | .818 | .770 | .606 | .715 | .698 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Resilience2 | Pearson Correlation | .611** | 1 | .730** | .672** | .558** | .362** | .487** | .523** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 319.172 | 724.567 | 454.490 | 420.819 | 342.691 | 285.840 | 283.266 | 359.837 | |
Covariance | .917 | 2.082 | 1.306 | 1.209 | .985 | .821 | .814 | 1.034 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Resilience3 | Pearson Correlation | .740** | .730** | 1 | .693** | .629** | .412** | .584** | .515** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 332.421 | 454.490 | 535.650 | 372.708 | 331.642 | 279.407 | 292.003 | 304.450 | |
Covariance | .955 | 1.306 | 1.539 | 1.071 | .953 | .803 | .839 | .875 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Resilience4 | Pearson Correlation | .630** | .672** | .693** | 1 | .576** | .354** | .509** | .526** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 284.582 | 420.819 | 372.708 | 540.739 | 305.553 | 241.324 | 256.052 | 312.097 | |
Covariance | .818 | 1.209 | 1.071 | 1.554 | .878 | .693 | .736 | .897 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Hope1 | Pearson Correlation | .606** | .558** | .629** | .576** | 1 | .392** | .649** | .497** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 267.997 | 342.691 | 331.642 | 305.553 | 519.805 | 262.269 | 319.946 | 289.453 | |
Covariance | .770 | .985 | .953 | .878 | 1.494 | .754 | .919 | .832 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Hope2 | Pearson Correlation | .370** | .362** | .412** | .354** | .392** | 1 | .442** | .641** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 210.739 | 285.840 | 279.407 | 241.324 | 262.269 | 860.510 | 280.046 | 480.198 | |
Covariance | .606 | .821 | .803 | .693 | .754 | 2.473 | .805 | 1.380 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Hope3 | Pearson Correlation | .593** | .487** | .584** | .509** | .649** | .442** | 1 | .519** |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 248.808 | 283.266 | 292.003 | 256.052 | 319.946 | 280.046 | 467.352 | 286.332 | |
Covariance | .715 | .814 | .839 | .736 | .919 | .805 | 1.343 | .823 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Hope4 | Pearson Correlation | .490** | .523** | .515** | .526** | .497** | .641** | .519** | 1 |
Sig. (2-tailed) | .000 | .000 | .000 | .000 | .000 | .000 | .000 | ||
Sum of Squares and Cross-products | 242.860 | 359.837 | 304.450 | 312.097 | 289.453 | 480.198 | 286.332 | 652.183 | |
Covariance | .698 | 1.034 | .875 | .897 | .832 | 1.380 | .823 | 1.874 | |
N | 349 | 349 | 349 | 349 | 349 | 349 | 349 | 349 | |
Table 3: Correlation analysis
(Source: SPSS)
Regression analysis
ANOVA | ||||||||||||||||||||||||||
Model | Sum of Squares | df | Mean Square | F | Sig. | |||||||||||||||||||||
1 | Regression | 211.099 | 4 | 52.775 | 58.808 | .000b | ||||||||||||||||||||
Residual | 308.706 | 344 | .897 | |||||||||||||||||||||||
Total | 519.805 | 348 | ||||||||||||||||||||||||
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Table 4: Regression analysis
(Source: SPSS) |
Data analysis
Descriptive analysis
Based on the mean value for most of the questions is 1 and the maximum value of most of the questions is 7. The mean value generally indicates the lower responses and on the other hand, maximum value indicates higher responses from respondents (Sonmez Cakir and Adiguzel, 2020). Mean and maximum value indicates how respondents give responses regarding psychological capital of employees that impact employees’ behavior and attitude that gives positive working outcomes. The mean value of the first 4 questions is 5.26, 5.27, 5.2, 4.95, and 5.32 which indicates respondents agree that the psychological stability of employees increases self-confidence and gives better working output. The standard deviation of these questions is also 1.188, 1.494, 1.584, and 1.386 therefore, it can be said that responses are well distributed over the responses given by responders in this survey.
The mean value of questions 5th, 6th, 7th, and 8th are 5.30, 4.64, 5.35, and 4.88, indicating that respondents agree that management needs to focus on employee’s hope to make them satisfied and develop their psychological state within the organization. The standard deviation of 5th and 6th questions is 1.494, 2.473, hence it can be said that most of the responses from responders are well distributed. The mean value of all the questions regarding employee resilience is more than 4.78 and less than 5.39, Therefore respondents strongly agree that good psychological capital indicates better employee resilience and positive outcomes in working performance.
Based on the descriptive analysis it has been found that the mean value of the 13th, 14th, 15th, and 16th questions are 4.25, 4.70, 4.62, and 4.52, indicating respondents strongly agree that good psychological health of employees increase working performance and reduce organizational cost-effectively. The standard deviation rate of these questions is 2.061, 2.073, 2.380, and 1.727. Therefore, it can be understood that all responses are well distributed over the responses given by responders (Ahmad et al. 2019). The mean value of 17th number question is 4.51 therefore it can be understood that survey participants strongly agree that good psychological capital one employees bring innovation. The standard deviation of this question is 2.170 which indicates responses are well distributed over the given responses by responders in their survey. The mean value of job satisfaction-related questions is 4.71-5.14. It indicates that job satisfaction increases the working performance of employees and respondents strongly agree with that. The standard deviation rate of 21st, 22nd, and 23rd number questions are 2.349, 1.744, and 1.763, Therefore from this data, it can be said that responses are well distributed over the responses collected from the responder.
Reliability analysis
Based on the above table in this SPSS analysis, the value of Cronbach’s Alpha is .776 that indicates, all items have good reliability with the given topic in this present research. As per the views of Astivia and Zumbo (2019), values of alpha ranging from 0.6-0.7, indicate moderate reliability and on the other hand range between 0.7-0.8, indicating good reliability, as well as, values above 0.8 shows excellent reliability of items with the research scenario. All research items are mostly related to the employee’s psychological capital that impacts employee’s attitude and behaviours. Research members found suitable information regarding job satisfaction and self-confidence that directly affects employees’ effectiveness and working performance.
Correlational analysis
The correlation value of confidence-1 with hope-1, hope-2, hope-3 is .587, .353, .557, .499 that indicates that all variables are highly significant at 0.01 level. On the other hand, it has been seen that the correlation value between confidence-2 and hope-1, hope-2 and hope-3 is .535, .426, .466, .548. It also indicates that confidence-2 is highly significant with an employee’s hope. Therefore, correlational analysis helps to find out the significance level between two variables such as hope and confidence in this research (Guo and Hou, 2021). Based on the above table, it has been found that confidence-3 and confidence-4 are also well connected and highly significant with hope-1, hope-2, and hope-3.
Regression analysis
Based on the above table of regression analysis it has been found that the value of R is .491 and the value of R square is .241. Based on the Anova analysis it has been found that the total sum of squares is 860.510, where the value of the mean square of regression is 51.904. The regression analysis also helps to measure the relationship between research variables and research modules to get desired research outcomes effectively (Kafle, 2019).
Discussion
Based on the above table it has been found, that respondents strongly agree that psychological capital of employees directly impacts self-confidence of employees (Mishra et al. 2019). Therefore it can be said that organizations need to develop mental stability for reducing psychological stress to enhance working performance. Employee attitude, behaviors can be affected by an employee’s psychological capacity within an organization (Hu, 2020). The mean value of hope is 5.30 that indicate that employee’s hope plays an important role to improve working efficiency and get better working performance from employees within an organization. Based on the above analysis it has been seen that most of the respondents stated that employee resilience depends on their psychological capital (Luthans et al. 2019). Good psychological capital and psychological capacity of each employee plays important roles to increase performance and working ability.
Based on the mean value of descriptive analysis respondents strongly agree that employee’s hope is an important factor in maintaining their psychological capacity effectively (Novitasari et al. 2020). Management needs to focus on employee’s hope to make them satisfied and encourage them to get better working output. The mean value of employees resilience is 5.39 with standard error 0.56. It can be said from the above data statistics that maintaining employee resilience depends on their behaviors, attitude, and psychological capacity (Wang et al. 2018). Based on the correlation analysis it has been seen that relation between two variables such as confidence and hope is highly significant. It can be said that an employee’s confidence level is effectively connected with the employee’s hope. Therefore, management needs to focus on maintaining employee confidence to make them satisfied and fulfill their hope within the organization (Burhanuddin et al. 2019). The variable of confidence-4 is highly significant with hope-1, hope-2 and hope-3.
The standard deviation value of each variable such as confidence, job satisfaction, hope, resilience indicates that responses are well distributed over the responses provided by respondents in the research. High correlation values between employee confidence and employee’s hope are effectively interconnected. As cited by Nolzen (2018), management needs to increase employee confidence level to manage their hopes and needs within an organization. It has been seen that all the variables have positive mean values and it indicates all respondents strongly agree for each response in this research. The mean value of job satisfaction is 4.71, indicating that the psychological state of an employee helps to get satisfaction in a job within an organization. Good job satisfaction level helps to increase the working ability as well as performance of employees (Sameer, 2018). Through this analysis, the relation between employee satisfactions, hope, and confidence with organizational performance has been discussed in an effective manner.
Conclusion
Based on the SPSS analysis it has been seen that most of the responses are well distributed over the responses given by the responders in this survey. Respondents strongly agree that psychological capital increases self-confidence, hope, job satisfaction, and innovation within an organization. The analysis of mean, median value through SPSS helps to understand how respondents agree, disagree, and strongly agree with each variable in this present research. Through the regression analysis, correlational analysis researchers found the value of R and R-square to understand the relation between waxing variables. The positive mean value indicates, respondents agree that employee’s behavior, attitude, job satisfaction, and hope is dependent on the psychological capital effectively. Therefore, SPSS analysis helps to understand the survey responses and measure the relationship between each research variable for achieving desired research outputs.
References
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Novitasari, D., Siswanto, E., Purwanto, A. and Fahmi, K., 2020. Authentic Leadership and Innovation: What is the Role of Psychological Capital?. International Journal of Social and Management Studies, 1(1), pp.1-21.
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