Decoding the Workplace & EOR: An Employee Survey Analysis by Data Science Techniques and Visualization
September 28, 2023 Β· Declared Dead Β· π arXiv.org
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Authors
Kishankumar Bhimani, Khushbu Saradva
arXiv ID
2309.16329
Category
cs.IR: Information Retrieval
Cross-listed
cs.HC,
math.NA
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
This research study explores the new dynamics of employee-organi-zation relationships (EOR) [6] using advanced data science methodologies and presents findings through accessible visualizations. Leveraging a dataset pro-cured from a comprehensive nationwide big employee survey, this study employs innovative strategy for theoretical researcher by using our state-of-the-art visual-ization. The results present insightful visualizations encapsulating demographic analysis, workforce satisfaction, work environment scrutiny, and the employee's view via word cloud interpretations and burnout predictions. The study underscores the profound implications of data science across various management sectors, enhancing understanding of workplace dynamics and pro-moting mutual growth and satisfaction. This multifaceted approach caters to a diverse array of readers, from researchers in sociology and management to firms seeking detailed understanding of their workforce's satisfaction, emphasizing on practicality and interpretability. The research encourages proactive measures to improve workplace environ-ments, boost employee satisfaction, and foster healthier, more productive organ-izations. It serves as a resourceful tool for those committed to these objectives, manifesting the transformative potential of data science in driving insightful nar-ratives about workplace dynamics and employee-organization relationships. In essence, this research unearths valuable insights to aid management, HR profes-sionals, and companies
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