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S. Kalaivani,K. Sivakumar,J. Vijayarangam 한국전산응용수학회 2022 Journal of applied mathematics & informatics Vol.40 No.3
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).