Strategic Decision Models Cross-Validation by Use of Decision Reports Information Extraction

Authors

  • Lucian Hancu 1. "Babes-Bolyai" University of Cluj-Napoca Romania, Cluj-Napoca, 1 M. Kogalniceanu, and 2. SoftProEuro Ltd. Cluj-Napoca Romania, 400614 Cluj-Napoca, 1 Lacul Rosu

Keywords:

Mergers and Acquisitions, Quantitative Models, Cross-Verification, Boosting Algorithm, Growth Crisis, Business Survival

Abstract

From all the events in the life of a business entity, the Mergers and Acquisitions transactions are one of the most challenging ones, as they drastically affect the life of the involved entities, but also their business stakeholders (like clients or suppliers). The Merger transaction can be seen as a growth crisis in the life of the buyer entity and a strive for survival in the life of the acquired company. Studying such transactions are being a constant preoccupation for both academia and practitioners, modeling mergers in order to predict them - one of the most ambitious task. In this paper, we present our technique of cross-validating the results of our model and use several boosting methods for improving the computed decisions scores.

Author Biography

Lucian Hancu, 1. "Babes-Bolyai" University of Cluj-Napoca Romania, Cluj-Napoca, 1 M. Kogalniceanu, and 2. SoftProEuro Ltd. Cluj-Napoca Romania, 400614 Cluj-Napoca, 1 Lacul Rosu

Department of Mathematics and Computer Science

References

D. Angwin, Mergers and Acquisitions, Blackwell Publishing, 2007, pg. 21.

H. K. Baker, T. O. Miller, B. J. Ramsperger, A Typology of Mergers Motives, in Akron Business and Law Review, 12(4), 1981, 24-29, reprinted in J. A. Krug, Mergers and Acquisitions, SAGE, 2008, pp. 67-76.

G.K. Deans, F. Kroeger, S. Zeisel, Winning the Merger Endgame, A playbook for Profiting from Industry Consolidation, A.T. Kearney, 2003, pp. 22-95.

L. Hancu, Data-Mining Techniques for Supporting Merging Decisions, in International Journal of Computers, Communications and Control, Suppl. Issue, 2008, pp. 322-326.

L. Hancu, Pruning Decision Trees for Easing Complex Strategic Decisions, in Annals of the Tiberiu Popoviciu Seminar, Volume 6, 2008, pp. 194-203.

L. Hancu, Mining Strategic Decisions Information Systems for Predicting Future Market Concentrations, in Proceedings of the International IADIS Information Systems Conference, March 2012, Berlin, Germany.

KPMG, 20 anni di M&A - Fusioni e acquisizioni in Italia dal 1988 al 2010 (20 years of M&As- Mergers and Acquisitions in Italy from 1988 to 2010), EGEA, 2010.

F. Kroeger, A. Vizjak, M. Moriarty, Beating the Global Consolidation Endgame, A. T. Kearney, 2008.

Published

2014-09-13

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