Purpose Following the typical features of the grey-rhino event as predictability and profound influence, we attempt to find a special pattern called the grey-rhino in eminent technologies via patent analysis. Design/methodology/approach We propose to combine triadic patent families and technology life cycle to define the grey-rhino model. Firstly, we design the indicator rhino-index Rh = ST/SP and descriptor sequence {Rh}, where ST and SP are the accumulative number of triadic patent families and all patent families respectively for a specific technology. Secondly, according to the two typical features of the grey-rhino event, a grey-rhino is defined as a technology that meets both qualitative and quantitative conditions. Qualitatively, this technology has a profound influence. Quantitatively, in the emerging stage, Rh ≥ Rae, where Rae is the average level of the proportion of triadic patent families. Finally, this model is verified in three datasets, namely Encyclopedia Britannica's list for the greatest inventions (EB technologies for short), MIT breakthrough technologies (MIT technologies) and Derwent Manual Code technologies (MAN technologies). Findings The result shows that there are 64.71% EB technologies and 50.00% MIT technologies meeting the quantitative standard of the grey-rhino model, but only 14.71% MAN technologies fit the quantitative standard. This falling trend indicates the quantitative standard of the grey-rhino model is reasonable. EB technologies and MIT technologies have profound influence on society, which means they satisfy the qualitative standard of the grey-rhino model. Hence, 64.71% EB technologies and 50.00% MIT technologies are grey-rhinos. In 14.71% MAN technologies meeting the quantitative standard, we make some qualitative judgments and deem U11-A01A, U12-A01A1A, and W01-A01A as grey-rhino technologies. In addition, grey-rhinos and non-grey-rhinos have some differences. Rh values of grey-rhinos have a downward trend, while Rh values of non-grey-rhinos have a contrary trend. Rh values of grey-rhinos are scattered relatively in the early stage and centralize gradually, but non-grey-rhinos do not have this feature. Research limitations There are four main limitations. First, if a technology satisfies the quantitative standard of the model, it is likely to be a grey-rhino but expert judgments are necessary. Second, we don't know why it will be eminent, which involves technical contents. Thirdly, we did not consider the China National Intellectual Property Administration (CNIPA) and the German Patent and Trademark Office (DPMA) which also play important roles in worldwide patents, so we hope to expand our study to the CNIPA and the DPMA. Furthermore, we did not compare the rhino-index with other patent indicators. Practical implications If a technology meets the quantitative standard, this can be seen as early warning signals and the technology may become a grey-rhino in the future, which can catch people's attention in the emerging stage and make people seize the technical opportunity early. Originality/value We define and verify a new pattern called the grey-rhino model in eminent technologies.
Purpose We attempt to find out whether OA or TA really affects the dissemination of scientific discoveries. Design/methodology/approach We design the indicators, hot-degree, and R-index to indicate a topic OA or TA advantages. First, according to the OA classification of the Web of Science (WoS), we collect data from the WoS by downloading OA and TA articles, letters, and reviews published in Nature and Science during 2010–2019. These papers are divided into three broad disciplines, namely biomedicine, physics, and others. Then, taking a discipline in a journal and using the classical Latent Dirichlet Allocation (LDA) to cluster 100 topics of OA and TA papers respectively, we apply the Pearson correlation coefficient to match the topics of OA and TA, and calculate the hot-degree and R-index of every OA-TA topic pair. Finally, characteristics of the discipline can be presented. In qualitative comparison, we choose some high-quality papers which belong to Nature remarkable papers or Science breakthroughs, and analyze the relations between OA/TA and citation numbers. Findings The result shows that OA hot-degree in biomedicine is significantly greater than that of TA, but significantly less than that of TA in physics. Based on the R-index, it is found that OA advantages exist in biomedicine and TA advantages do in physics. Therefore, the dissemination of average scientific discoveries in all fields is not necessarily affected by OA or TA. However, OA promotes the spread of important scientific discoveries in high-quality papers. Research limitations We lost some citations by ignoring other open sources such as arXiv and bioArxiv. Another limitation came from that Nature employs some strong measures for access-promoting subscription-based articles, on which the boundary between OA and TA became fuzzy. Practical implications It is useful to select hot topics in a set of publications by the hot-degree index. The finding comprehensively reflects the differences of OA and TA in different disciplines, which is a useful reference when researchers choose the publishing way as OA or TA. Originality/value We propose a new method, including two indicators, to explore and measure OA or TA advantages.
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