The relationship between job stress and job satisfaction among employees at Kuching Port Authority, Sarawak / Nurul Nabila Jol

Jol, Nurul Nabila (2018) The relationship between job stress and job satisfaction among employees at Kuching Port Authority, Sarawak / Nurul Nabila Jol. [Student Project] (Unpublished)

Abstract

This study was conducted to investigate the relationship between job stress and employees’ job satisfaction at the Kuching Port Authority, Sarawak. There were three objectives for this study which were to identify the relationship between workload and employees’ job satisfaction, to identify the relationship between role conflict and employees’ job satisfaction, and to identify the relationship between the physical environment and employee’ job satisfaction. The conceptual framework was adapted to complete the literature review. The instrument of the questionnaire was used for the data collection purposes. Meanwhile, the correlational survey research design was adapted using quantitative methods. The simple census sampling technique was used to select the
staff department and the questionnaires were distributed to 100 respondents at Kuching Port Authority, Sarawak. The data analysis involved frequencies and inferential statistics, such as correlations and the coefficient of determination. Based on data findings there are relationships between job stress and employees’ job satisfaction at Kuching Port Authority, Sarawak, which are the physical environment (r=.0550**), role conflict (0.470**), and workload (r=0.326**) . From these findings, it showed that the three elements for this study, workload, role conflict, and physical environment, are the factors that lead to job stress and job satisfaction at Kuching Port Authority, Sarawak. The study recommendation that the organisation should provide more a friendly or
comfortable environment to employees so that the employees can be more productive and away from job stress which may affect their job satisfaction. The future researchers may also increase the sample size to more than 100, so that the data will become more accurate and relevant.

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