Author
Listed:
- Rogozińska-Pawełczyk, Anna
- Olbryś, Joanna
Abstract
Job satisfaction and its relationship with other variables determining organizational successes and failures continues to be an important field of research because the role of job satisfaction and its impacts have not been yet sufficiently explained. The issue of job satisfaction is particularly important for countries or regions that are transitioning from emerging to developed status, to a free market system and towards a knowledge-based economies. Despite the topicality of the topic, there is still limited research on the formation of job satisfaction of employees in the emerging Central and Eastern European countries. To properly measure job satisfaction, adapted methods that show adequate validity evidence for the desired context might be used. This study aims to investigate employees’ overall level of job satisfaction using a novel multivariate Bayesian Network (BN). Several discrete variables that affect job satisfaction are incorporated into the model. The graphical representation of the model is supplemented by numeric information about probability based on the questionnaire. The simulations reveal that there is a considerable potential to improve employees’ satisfaction within the Polish companies investigated in this research. The obtained results also have an implication for managers in emerging economies, seeking to improve productivity as it may help them to devise an effective Human Resource Management (HRM) system toward job satisfaction for their employees. This research is valuable in terms of recognizing the best employer strategies to increase the level of employees’ job satisfaction in Polish companies. In the light of the existing literature, the proposed BN approach is quite innovative, and it is an universal one since it can be easily adapted for other economies.
Suggested Citation
Rogozińska-Pawełczyk, Anna & Olbryś, Joanna, 2023.
"What are the most important factors affecting job satisfaction? Evidence for Poland from the Bayesian Network model,"
Journal of East European Management Studies, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 28(3), pages 442-478.
Handle:
RePEc:nms:joeems:10.5771/0949-6181-2023-3-442
DOI: 10.5771/0949-6181-2023-3-442
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