Data Mining in the Research of Corporate Acquisition Performance

Abstract

With a descriptive and predictive ability, data mining can discover the hidden patterns of data from a large-scale data warehouse by precise mathematical means, which is valuable for decision making, especially for corporate top management. With a regression analysis based on a large survey data, this paper examines an important issue concerned to corporate acquisition. It is found that acquisition performance is positively influenced by organizational adjustment, top management turnover, buyers’ experience, target firm’s performance, and business relevance, and negatively influenced by region distance, shareholding ratio, state-owned shares of buyers, and relative size. The founding can have some theoretical value for corporate decision on the process of acquisitions and how to enhance acquisition performance and also indicate the practical value of data mining technology.