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Patent analysis based technology innovation assessment with the lens of disruptive innovation theory: A case of blockchain technological trajectories

Priyanka C. Bhatt, Kuei-Kuei Lai, Vinayak A. Drave, Tzu-Chuen Lu and Vimal Kumar

Technological Forecasting and Social Change, 2023, vol. 196, issue C

Abstract: The technological innovation period has reduced drastically in the current era giving rise to constantly new disruptive technologies, which may seem discreet; however, their evolution is also derived from the previous technological path. This study aims to identify the technology trajectory and evolution phases of disruptive technology, Blockchain, with respect to its predecessor technologies. Within the context of disruptive innovation theory, patent citation analysis employing the key-route main path method was utilized for this study. The data collection was based on keywords and IPC codes to retrieve US patents from the webpat database. The data obtained included 10,919 initial patents and 6206 final patents after simple family merge. The results acquired ranged from the year 1974 to 2021. The study identified five significant technology clusters based on the key-route main path analysis and framed the evolution path of the technology. The findings reveal the technological path dependence and knowledge flow of technological innovation. The novelty of this study lies in its approach to mapping DI theory characteristics with patent analysis to identify the path dependence of disruptive innovations, which aids researchers and decision-makers in understanding and assessing their innovation strategies.

Keywords: Disruptive innovation theory; Knowledge flow; Key-route analysis; Main path analysis; Technological trajectory; Blockchain technology (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:196:y:2023:i:c:s0040162523005498

DOI: 10.1016/j.techfore.2023.122864

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