Data-Mining Techniques for Supporting Merging Decisions

Abstract: The Mergers and Acquisitions transactions have increased during the last years, as business entities face multiple threats caused by globalization and are unable to exploit the opportunities offered by the global market. These transactions come as a solution for consolidating the position of one entity on the local, national or global market, but usually surprise the competition, which does not have any prepared strategy for surviving the rise of a stronger competitor. In order to help the entities decide to which company should merge, or to be aware of the fact that a competitor could merge in the near future, we have built a technique for supporting merging decisions, based on the financial statements analysis and the Web usage logs extracted from our multi-server search application. The model suggests the merge with an entity which share the same activity code with the initial entity, or has a related activity code, according to the Business Dependency Map (derived from the Web search logs)