Journal of applied mathematics & informatics

The Korean Society for Computational and Applied Mathematics (한국전산응용수학회)
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STATISTICAL MODELLING USING DATA MINING TOOLS IN MERGERS AND ACQUISITION WITH REGARDS TO MANUFACTURE & SERVICE SECTOR

  • KALAIVANI, S. (Department of Mathematics, Sathyabama Institute of Science and Technology) ;
  • SIVAKUMAR, K. (Department of Mathematics, Saveetha Institute of Medical and Technical Sciences) ;
  • VIJAYARANGAM, J. (Department of Applied Mathematics, Sri Venkateshwara College of Engineering)
  • Received : 2021.12.13
  • Accepted : 2022.03.03
  • Published : 2022.05.30
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Abstract

Many organizations seek statistical modelling facilitated by data analytics technologies for determining the prediction models associated with M&A (Merger and Acquisition). By combining these data analytics tool alongside with data collection approaches aids organizations towards M&A decision making, followed by achieving profitable insights as well. It promotes for better visibility, overall improvements and effective negotiation strategies for post-M&A integration. This paper explores on the impact of pre and post integration of M&A in a standard organizational setting via devising a suitable statistical model via employing techniques such as Naïve Bayes, K-nearest neighbour (KNN), and Decision Tree & Support Vector Machine (SVM).

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