NDLI: A study on the factors influencing post-merger performance of China's listed firms based on data mining

Content Provider	IEEE Xplore Digital Library
Author	Chuanrui Fu
Copyright Year	2010
Description	Author affiliation: School of Management Fuzhou University Fuzhou, P.R. China (Chuanrui Fu)
Abstract	Based on a sample of Mergers and Acquisitions of China's A-share listed companies during 2003–2005, this paper adopts multivariate adaptive regression splines model which is a newly developed data mining technique to analyze the nonlinear relationship between post-merger operating performance and M&A characteristics such as corporate free cash flow, holding proportion of large shareholders, State-owned share ratio, M&A premium, relative target size and industry relatedness of target and merger. The result demonstrates that corporate free cash flow per share has a nonlinear threshold effect on the first-year performance of merger subsequent to the M&A transaction. For the second year following M&A transaction, corporate free cash flow per share significantly negatively impacts the performance. However, there are no significant evidence that the M&A characteristics affect the performance of merger for the third year after M&A transaction and the year of M&A. The explanational powers of our regression models for the first two years following M&A transaction are obviously higher than that of previous research, which suggests that our regression models adequately reflect the nonlinear relationship between M&A characteristics and post-merger performance.
Starting Page	422
Ending Page	427
File Size	476213
Page Count	6
File Format	PDF
ISBN	9781424452637
DOI	10.1109/ICIME.2010.5478130
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Costs Corporate acquisitions Industrial relations Merging mergers and acquisitions Data mining factor analysis Investments Economies of scale multivariate adaptive regression splines model nonlinear relationship Performance analysis Mining industry Energy management
Content Type	Text
Resource Type	Article

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