Today, many organizations are experiencing various effects related to employee stress. Though the effects can be either negative or positive, the most experienced one, according to the available data, is the negative stress, which has gone to an extent of debilitating the employees hence costly to the employers. Managers are forced to identify those employees suffering from negative stress and implement programs as a defense against the effects on the employee performance. This study, therefore, determines the negative effects of employees stress on the employee performance and how such effects can be managed.
How does employee stress affect their organizational performance and how can the effects be managed?
Job related stress.
Individual related stress and organizational related stress.
Moderating: Other factors affecting employee performance such age, gender, work experience, and education
With the identified problem, research question and the objectives the following hypotheses were formed:
H0: There is no relationship between employees' performance and job, organizational, and individual-related stress.
H1: Job, individual, and organizational related stress have a significant effect on the employees' performance.
Data Analysis Techniques
For this study, the data collected would be used to test the relationship between the set of a variable with the statistical objective being to determine the effects of the other variables on the dependent variable. The dependent variable is the employee performance and the independent variables are the job-related stress, organizational related stress, and individual-related stress. The test is expected to either approve or disapprove the hypothesis. If the null hypothesis is rejected and the alternative one accepted, then the study concludes that there is a significant relationship between the dependent and the independent variables.
From the set of the data, there are just two possible outcomes of the hypothesis, either rejecting or failing to reject the null hypothesis. Therefore, the data is considered binomial. One outcome confirms the significant effect of the independent variables on the dependent variable. Since the control variables are obvious determinants of employees' performance, they are used to compare the effects of the two set of independent variables. The type of data evaluated in this case is continuous data. The data was collected by means of structured questionnaires which are issued to the respondents to obtain the target sample using convenient sampling technique.
To get the desired results, various methods of analyses would be applied; reliability tests, Pearson's correlation test and regression test. The reliabilities of both the dependent variable and independent variable are expected to indicate either a negative or positive relationship between the two variables. In this case, the output of the reliabilities test shows a significantly negative correlational relationship between job stress and job performance. The output from the test for a correlation coefficient as expected produces a negative value of beta, implying that for every one percent increase in job-related stress, there will be a corresponding effect of the beta value on the job performance which is negatively correlated to job stress (Learntech, 2018). The regression analysis would then show the relationship between job stress and job performance which is proved by the value of R Square (Laerd Statistics, 2013).
The main purpose of the study was to determine the relationship between the job stress and job performance of employees. As per the hypothesis, job stress has a negative relationship to job performance implying that when stress occurs, it affects the employees' performance negatively. Management support would help reduce or increase employee stress, apparent organizational assistance; management support would work as a cushion which positively decreases work-related stress in employees. The choice of Pearson's Correlation Coefficient and multiple regression methods was because they both show a linear correlation between the variables can easily run by a statistical program; SPSS or Excel in this case. The two methods are certainly the best applicable to realize the desired result answering the research question.
Data Analysis - Pearson's Correlation Coefficient. (2018). Retrieved from http://learntech.uwe.ac.uk/da/Default.aspx?pageid=1442
How to perform a Multiple Regression Analysis in SPSS Statistics | Laerd Statistics. (2013). Retrieved from https://statistics.laerd.com/spss-tutorials/multiple-regression-using-spss-statistics.php
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