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

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 nove...

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Veröffentlicht in:IEEE transactions on engineering management Jg. 71; S. 5921 - 5938
Hauptverfasser: Qiao, Yali, Wang, Xuefeng, Huang, Ying, Zhang, Shuo, Yang, Xuemei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Alternative technology
Competitiveness measurement
Data mining
Disruptive innovation
Disruptive technologies
disruptive technology
Document handling
Manuals
Monitoring
Niche marketing
Niche markets
Resource allocation
Semantic analysis
Semantics
subject–action–object (SAO) semantic analysis
technological alternatives
Technology
Text mining
ISSN:0018-9391, 1558-0040
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Zusammenfassung: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.
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ISSN:0018-9391
1558-0040
DOI:10.1109/TEM.2024.3369756