Abstract
The digitalization has changed the way people accomplish their daily tasks, communicate with each other, and work. There are many benefits like greater flexibility in terms of place and time, and increase of speed the tasks can be performed. At the same time, technology-based communication can limit social relationships within the company. These changes require company leaders to be cautious about their employee wellbeing and satisfaction. It is not an easy task, and there is little research on how new technologies are affecting employees. The purpose of this research is to create an algorithm to predict the behavior of employees. Dataset of 102 people was used for the analysis. An algorithm was designed to help employers discover in which areas and ways the company should improve their work. The algorithm can predict which employees are likely to leave the company and for which reasons. At the same time, it can be used as a guide for technology developers to improve the quality of their communication technologies.
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Support for effective participation of Vidzeme University of Applied Sciences within the international scientific circles (ViA-Int), project number 1.1.1.5/18/I/005.
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Pratt, M., Boudhane, M., Cakula, S. (2021). Predictive Data Analysis Model for Employee Satisfaction Using ML Algorithms. In: Saeed, F., Al-Hadhrami, T., Mohammed, F., Mohammed, E. (eds) Advances on Smart and Soft Computing. Advances in Intelligent Systems and Computing, vol 1188. Springer, Singapore. https://doi.org/10.1007/978-981-15-6048-4_13
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