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• W1936792324 abstract "ABSTRACT Mergers and acquisitions (M&A) play increasingly important roles for contemporary business, especially in high‐tech industries that conduct M&As to pursue complementarity from other companies and thereby preserve or extend their competitive advantages. The appropriate selection (prediction) of M&A targets for a given bidder company constitutes a critical first step for an effective technology M&A activity. Yet existing studies only employ financial and managerial indicators when constructing M&A prediction models, and select candidate target companies without considering the profile of the bidder company or its technological compatibility with candidate target companies. Such limitations greatly restrict the applicability of existing studies to supporting technology M&A predictions. To address these limitations, we propose a technology M&A prediction technique that encompasses technological indicators as independent variables and accounts for the technological profiles of both bidder and candidate target companies. Forty‐three technological indicators are derived from patent documents and an ensemble learning method is developed for our proposed technology M&A prediction technique. Our evaluation results, on the basis of the M&A cases between January 1997 and May 2008 that involve companies in Japan and Taiwan, confirm the viability and applicability of the proposed technology M&A prediction technique. In addition, our evaluation also suggests that the incorporation of the technological profiles and compatibility of both bidder and candidate target companies as predictors significantly improves the effectiveness of relevant predictions." @default.
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• W1936792324 date "2014-01-29" @default.
• W1936792324 modified "2023-10-18" @default.
• W1936792324 title "Exploiting Technological Indicators for Effective Technology Merger and Acquisition (M&A) Predictions" @default.
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• W1936792324 doi "https://doi.org/10.1111/deci.12062" @default.
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