A Fuzzy-based Decision Making for Organizational Performance and Transformational Leadership: A Contemporary Management Viewpoint

Companies must focus on organizational performance and transformational leadership (TL) in human resource management (HRM) to adapt to environmental shifts. This expertise allows huge-scale firms to sustain their position in a growing marketplace by improving managerial capability. TL is critical to company growth in the current rapid digital economy. TL is a critical concept that may possess a significant effect on a organizational performance in today's constantly shifting digital landscape. Utilizing a fuzzy-logic based decision-making system for recognizing suitable leaders allows for the development of key skills via ongoing training and practical education throughout their professional life. Evaluating complicated big data utilizing modern artificial intelligence (AI) algorithms may facilitate the development of novel and efficient methods to finding leadership prospects. In this study, a prediction system for an HRM employment management strategy utilizing machine learning (ML) methods was built for Indian IT sectors (IIT) and evaluated to identify possible leadership prospects through examining big data from 5000 staff. The SVM, GB, RF, and KNN models all attained accuracy of 42%, 92%, 74%, and 97% respectively. The research outcomes show that big data and ML methods may be used for modeling successful promotional decisions in broad and embedded organizations, indicating substantial possibilities for organizational performance and TL growth in the companies.

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