Importance of Employee Motivation and Satisfaction in the Workplace based on BiLSTM and ANN Approach

Abstract

The aging of Europe’s population is reflected in the rising share of retirees in the labor force. This proposed approach to summarize the significance of employee motivation and satisfaction at work across generations in Slovenian companies. The system’s goal is to determine if and how older workers’ motivation and contentment in the job change over time. Feature selection, preprocessing, and model training are all parts of the proposed strategy. Fuzzy set theory was established in the field of preprocessing as a means of assigning numerical value to ineffable concepts like thought, logic, and the subjective understanding of events. During feature selection, correlation is used as a criterion. Once the characteristics have been gathered, BiLSTM-ANN is utilized to train the models. The proposed method excels in comparison to stateof-the-art algorithms like LSTM and ANN. This strategy has a 0.97 percent chance of succeeding.