Text mining to gain technical intelligence for acquired target selection: A case study for China's computer numerical control machine tools industry

•A method to extract technical intelligence to facilitate M&A target selection.•To blend text mining techniques and expert knowledge.•Both technical and strategic aspects are involved.•A case study on China's Computer Numerical Control Machine Tools industry.

Technology strategy plays an increasingly important role in today's Mergers and Acquisitions (M&A) activities. Informing that strategy with empirical intelligence offers great potential value to R&D managers and technology policy makers. This paper proposes a methodology, based on patent analysis, to extract technical intelligence to identify M&A target technologies and evaluate relevant target companies to facilitate M&A target selection. We apply the term clumping process and a trend analysis together with policy and market information to profile present R&D status and capture future development signals and trends in order to grasp a range of significant domain-based technologies. Furthermore, a comparison between a selected acquirer and leading players is used to identify significant technologies and sub-technologies for specific strategy-oriented technology M&A activities. Finally, aiming to recommend appropriate M&A target companies, we set up an index-based system to evaluate the acquired target candidates from both firms-side perspective and target firm-side perspective and differentially weigh for specific M&A situations. We provide an empirical study in the field of computer numerical control machine tools (CNCMT) in China to identify technology M&A targets for an emerging Chinese CNCMT company — Estun Automation under different M&A strategies.