Exploring paper characteristics that facilitate the knowledge flow from science to technology

Cherng G. Ding, Wen-Chi Hung, Meng-Che Lee and Hung-Jui Wang

Journal of Informetrics, 2017, vol. 11, issue 1, 244-256

Abstract: In this study, we explore paper characteristics that facilitate the knowledge flow from science to technology by using the patent-to-paper citation data. The linear growth trajectory of the number of patent citations to a scientific paper over time is used to measure the dynamism of its utilization for technology applications. The citation data used were obtained from the USPTO database based on two 5-year citation windows, 2001–2005 and 2009–2013. The former included patent citations to the publications in the Thomson Reuters Web of Science in 1998, and the latter included those in 2006. Only the publications in the top ten most frequently cited subject categories in the Web of Science were selected. By using growth modeling, we have found that the mean slope of the trajectory is significant. Moreover, the paper citation count, the ranking factor of the journal in which the paper was published, whether the paper is an industrial publication, and whether it is a review article have been identified to exert significant effects on the growth of the citation of scientific literature by patented inventions. Some policy implications are discussed.

Keywords: Growth modeling; Paper characteristics; Patent-to-paper citation; Ranking factor; Research impact (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:11:y:2017:i:1:p:244-256

DOI: 10.1016/j.joi.2016.12.004

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