Anticipation and analysis of industry convergence using patent-level indicators.

Autor/inn/en	Ashouri, Sajad; Mention, Anne-Laure; Smyrnios, Kosmas X.
Titel	Anticipation and analysis of industry convergence using patent-level indicators.
Quelle	In: Scientometrics, (2021) 7, S.5727-5758 PDF als Volltext Verfügbarkeit
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0138-9130
DOI	10.1007/s11192-021-04025-7
Schlagwörter	Industry convergence; Patent; Knowledge combination; Technology forecasting; Innovation
Abstract	Abstract This study tackles the initiation of industry convergence to develop a patent-level framework aiming to anticipate convergence. Despite the vast amount of studies in the convergence literature, much remains to be understood about the dynamics of convergence, from the outset at the technology level to further development at the industry level. The evaluation of technical domain combinations facilitates the identification of industry convergence at early stages. This study analyzes patent data to measure the continuity in the combination of technical knowledge domains, which drives convergence. We also identified the patent indicators which promote the formation of the influential combinations that drive industry convergence. The present findings revealed that only a few unprecedented combinations in technical domains developed in future technologies, which implies the significance of distinguishing the combinations that may be expanding rapidly in subsequent years. The results also reported that the influential combinations need to be identifiable for future inventors, useful and practical for future technologies, and compatible with a variety of technical domains. This research provides insights for studies in innovation and technology management as well as implications for inventors, managers, and policymakers toward technology road-mapping.
Erfasst von	OLC
Update	2023/2/05