Tech Mining Approach for Identifying Potentially Disruptive Technologies: From the Perspective of Technological Alternatives

Yali Qiao*, Xuefeng Wang*, Ying Huang, Shuo Zhang, Xuemei Yang

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Identifying potentially disruptive technologies is challenging but important for innovators. The existing research based on the tech mining approach pays much attention to technological change but less attention to characterizing its disruptive process and effects. In this article, we suggest a novel perspective to help understand and identify potentially disruptive technology that displaces the mainstream technology (termed 'alternative disruption') by modeling it as a process in which alternative technologies compete against incumbent technology. Accordingly, we propose a systematic framework to identify this type of technological disruptors by quantitatively characterizing its disruptive process and effects. To illustrate the alternative features, uniquely, the framework is solutions focused that answer the same technological problem as the mainstream one in which subject-action-object semantic analysis and community detection algorithm are used to mine and cluster the found solutions into groups as candidate technologies, including mainstream technologies and potentially alternative ones. Incorporating disruptive characteristics of technological advance, technology applicability, and market niche, the alternative one with a highest comprehensively competitive position against mainstream technologies remains as the most disruptive potential. Finally, the case of cancer treatments verifies the feasibility and effectiveness of this framework. Also, this proposed framework can provide quantitative information for decision making in promising technologies deployment and resource allocation.

    Original languageEnglish
    Pages (from-to)5921-5938
    Number of pages18
    JournalIEEE Transactions on Engineering Management
    Volume71
    DOIs
    Publication statusPublished - 2024

    Keywords

    • Competitiveness measurement
    • disruptive technology
    • subject-action-object (SAO) semantic analysis
    • technological alternatives
    • text mining

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