Discovering business diversification opportunities using patent information and open innovation cases
This paper proposes a method to identify business diversification opportunities for a company. In particular, the method uses M&A cases related to business diversifications to identify atypical diversification opportunities. The underlying idea of the method is that industrial sectors of compani...
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Veröffentlicht in: | Technological forecasting & social change 2019-02, Vol.139, p.144-154 |
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Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | This paper proposes a method to identify business diversification opportunities for a company. In particular, the method uses M&A cases related to business diversifications to identify atypical diversification opportunities. The underlying idea of the method is that industrial sectors of companies acquired by acquiring companies having similar characteristics with the focal company can be business diversification directions for the company. Industrial sectors of companies are identified by using IPC(International Patent Classification)-ISIC(International Standard Industrial Classification) concordance, and we updated the previous concordance to reflect the recent technological and business environments. For verification of the method, we used a successful M&A case related to business diversification and tested that the method can identify same industrial sector with the case as top priority. The results show that the method identified the same industrial sector as top ranking and other uncommon industrial sectors as recommended opportunities.
•The proposed method identifies business diversification opportunities by using M&A and patent data.•M&A cases on business diversification are used as the key information to link a company to uncommon business sectors.•We updated the existing IPC-ISIC concordance to reflect recent technological and business environments.•The empirical analysis shows that the method well identifies atypical business diversification opportunities. |
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ISSN: | 0040-1625 1873-5509 |
DOI: | 10.1016/j.techfore.2018.11.006 |