A Business Merger and Acquisition Knowledge Management System Using Artificial Intelligence Techniques

Abstract

Knowledge is recognized as a strategic resource, with major key drivers being the need to cut time to market and gain the business opportunities in a global market with new products and services. This chapter presents a knowledge management system known as guidance for business merger and acquisition (GBMA) process. This application uses a hybrid knowledge-based system to place bidding on the target company, formulating a strategy, and modification of the initial strategy if necessary, for the business acquisition processes. Legal knowledge for GBMA is represented in two forms, as rules and cases. Besides distinguishing the two different forms of knowledge representation, the chapter outlines the actual use of these forms in a computational architecture that is designed to generate a suitable solution, for a given new business scenario, using different reasoning mechanisms (e.g., rule-based reasoning, case-based reasoning). Business scenarios are used to show the functionalities of the presented architecture.