• Annu Mishra
• Prof. Sunil Kant Mishra

MNCs currently use knowledge management (KM) as a key strategic management tool to boost innovation, operational effectiveness, and competitive advantage in the global marketplace. By examining the knowledge collection, sharing, storing, and utilisation methods of a few multinational corporations (MNCs) operating in India, this study demonstrates the efficacy of KM practices in these companies. This study examines a number of knowledge management models, such as the SECI model and knowledge spiral, and assesses the contribution of technology-driven KM solutions including cloud computing, big data analytics, and artificial intelligence. The study uses case studies and empirical analysis to determine key performance indicators (KPIs) to gauge how well knowledge management (KM) methods are working. It also looks at how organisational culture, leadership, and digital transformation affect MNCs' adoption of KM. The results show the advantages and difficulties MNCs encounter when putting KM methods into practice, such as structural impediments, technology constraints, and opposition to knowledge sharing. The study ends with suggestions for enhancing knowledge management procedures to promote corporate innovation and long-term expansion in multinational corporations.

Knowledge Management Practices, Multinational Corporations (MNCs), Knowledge Sharing, Organizational Learning, Digital Transformation, Knowledge Retention.

"Assessing the Effectiveness of Knowledge Management Practices in Multinational Corporations", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.h252-h258, May-2025, Available :http://www.jetir.org/papers/JETIR2505823.pdf

"Assessing the Effectiveness of Knowledge Management Practices in Multinational Corporations", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. pph252-h258, May-2025, Available at : http://www.jetir.org/papers/JETIR2505823.pdf