Measuring tech emergence: A contest
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DOI: 10.1016/j.techfore.2020.120176
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Cited by:
- Min, Chao & Bu, Yi & Sun, Jianjun, 2021. "Predicting scientific breakthroughs based on knowledge structure variations," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
- Riad Shams, S.M. & Vrontis, Demetris & Chaudhuri, Ranjan & Chavan, Gitesh & Czinkota, Michael R., 2020. "Stakeholder engagement for innovation management and entrepreneurial development: A meta-analysis," Journal of Business Research, Elsevier, vol. 119(C), pages 67-86.
- Li, Xin & Wen, Yang & Jiang, Jiaojiao & Daim, Tugrul & Huang, Lucheng, 2022. "Identifying potential breakthrough research: A machine learning method using scientific papers and Twitter data," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
- Wooseok Jang & Yongtae Park & Hyeonju Seol, 2021. "Identifying emerging technologies using expert opinions on the future: A topic modeling and fuzzy clustering approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6505-6532, August.
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Keywords
R&D assessment; R&D emergence; Research indicators; Predicting research topics; Technology emergence indicators; Emerging technology;All these keywords.
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