A DCGNET based Novel Approach for Employee Engagement Mediated Progressive Work Practices on Logistics Organization

Abstract

The purpose of the research was to ascertain what aspects of a dynamic workplace were most influential in shaping levels of participation, commitment, and inspiration among workers. This study focuses on IT firms in Chennai, India, and uses a qualitative and descriptive approach. Academic studies on subjects including higher productivity, enhanced communication, a more collaborative work culture, and the eradication of human error and bias were reviewed to determine the impact of a progressive work environment on employee engagement. The suggested strategy makes use of preprocessing, feature extraction, and model training. The raw data requires a preprocessing procedure to organize it. We use word embeddings and term frequencies for feature extraction. The models are trained using DCGNet once the features have been retrieved. CNN and GRU, two of the most popular alternatives, are beaten by the proposed strategy