Measuring technology complementarity between enterprises with an hlda topic model

Xuefeng Wang*, Yali Qiao, Yujia Hou, Shuo Zhang, Xiaotong Han

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    10 Citations (Scopus)

    Abstract

    When considering a joint venture or merger, it is essential for firms to explore innovators with complementary technology to compensate for any internal limitations inR&Dresources. In this article, we provide a framework for exploring the technology complementarity between enterprises in a quantitative manner based on text-mining patent data. A hierarchical latent Dirichlet allocation topic model identifies the technology topics hidden in patent documents along with the hierarchical structure of those topics. The technology complementarity between broad classes of technology and their subclassifications across enterprises is then measured with an improved formulation. An empirical study on three-dimensional printing illustrates the validity, reliability, and practicality of this method and the measurement formula used, endorsed by technical experts. This method can be used to identify R&D opportunities, to find appropriate acquisition targets and potential collaborators, and to support managerial decision-making with quantified information on technology complementarity.

    Original languageEnglish
    Article number08937531
    Pages (from-to)1309-1320
    Number of pages12
    JournalIEEE Transactions on Engineering Management
    Volume68
    Issue number5
    DOIs
    Publication statusPublished - 1 Oct 2021

    Keywords

    • Hierarchical latent Dirichlet allocation (hLDA) topic model
    • Quantitative
    • Technology complementarity
    • Text mining
    • Three-dimensional (3-D) printing technology

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