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

透视图(图形) 颠覆性技术 数据科学 工程类 计算机科学 制造工程 人工智能
作者
Yali Qiao,Xuefeng Wang,Ying Huang,Shuo Zhang,Xuemei Yang
出处
期刊:IEEE Transactions on Engineering Management [Institute of Electrical and Electronics Engineers]
卷期号:71: 5921-5938 被引量:1
标识
DOI:10.1109/tem.2024.3369756
摘要

Identifying potentially disruptive technologies is challenging but important for innovators. Existing research based on tech mining approach pays much attention to technological change, but less attention to characterizing its disruptive process and effects. This research suggested a novel perspective to help understand and identify potentially disruptive technology that displace the mainstream technology (termed as "alternative disruption") by modelling it as a process in which alternative technologies compete against incumbent technology. Accordingly, we proposed 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 a same technological problem with the mainstream one, in which Subject-action-object (SAO) 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.

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