This work is licensed under the Creative Commons Attribution 4.0 International License.
Abercrombie R. K., Udoeyop A. W., & Schlicher, B. G. (2013). A study of scientometric methods to identify emerging technologies via modeling of milestones. Scientometrics, 91(2), 327–342.AbercrombieR. K.UdoeyopA. W.SchlicherB. G.2013A study of scientometric methods to identify emerging technologies via modeling of milestones91232734210.1007/s11192-011-0614-4Search in Google Scholar
Adams, J. (1990). Fundamental stocks of knowledge and productivity growth. Journal of Political Economy, 98(4), 673–702.AdamsJ.1990Fundamental stocks of knowledge and productivity growth98467370210.1086/261702Search in Google Scholar
Adamuthe, A. C., & Thampi, G. T. (2019). Technology forecasting: a case study of computational technologies. Technological Forecasting and Social Change, 143, 181–189.AdamutheA. C.ThampiG. T.2019Technology forecasting: a case study of computational technologies14318118910.1016/j.techfore.2019.03.002Search in Google Scholar
Ahuja, G., & Lampert, C.M. (2001). Entrepreneurship in the large corporation: A longitudinal study of how established firms create breakthrough inventions. Strategic Management Journal, 22(6–7), 521–543.AhujaG.LampertC.M.2001Entrepreneurship in the large corporation: A longitudinal study of how established firms create breakthrough inventions226–752154310.1002/smj.176Search in Google Scholar
Andersen, B. (1999). The hunt for S-shaped growth paths in technological innovation: A patent study. Journal of Evolutionary Economics, 9(4), 487–526.AndersenB.1999The hunt for S-shaped growth paths in technological innovation: A patent study9448752610.1007/s001910050093Search in Google Scholar
Ardito, L., D’Adda, D., & Petruzzelli, A. M. (2018). Mapping innovation dynamics in the Internet of Things domain: Evidence from patent analysis. Technological Forecasting and Social Change, 136, 317–330.ArditoL.D’AddaD.PetruzzelliA. M.2018Mapping innovation dynamics in the Internet of Things domain: Evidence from patent analysis13631733010.1016/j.techfore.2017.04.022Search in Google Scholar
Arts, S., & Veugelers, R. (2015). Technology familiarity, recombinant novelty, and breakthrough invention. Industrial and Corporate Change, 24(6), 1215–1246.ArtsS.VeugelersR.2015Technology familiarity, recombinant novelty, and breakthrough invention2461215124610.1093/icc/dtu029Search in Google Scholar
Asid, R., & Khalifah, N. A. (2016). The effects of foreign R&D and triadic patent propensity on developing economies efficiency and convergence. Journal Ekonomi Malaysia, 50(2), 107–124.AsidR.KhalifahN. A.2016The effects of foreign R&D and triadic patent propensity on developing economies efficiency and convergence502107124Search in Google Scholar
Baudry, M., & Dumont, B. (2004). Comparing firms’ triadic patent applications across countries: Is there a gap in terms of R&D effort or a gap in terms of performances? Research Policy, 35(2), 324–342.BaudryM.DumontB.2004Comparing firms’ triadic patent applications across countries: Is there a gap in terms of R&D effort or a gap in terms of performances?35232434210.1016/j.respol.2005.12.004Search in Google Scholar
Briggs, K., & Buehler, D. L. (2019). An analysis of technologically radical innovation and breakthrough patents. International Journal of the Economics of Business, 25(3), 341–365.BriggsK.BuehlerD. L.2019An analysis of technologically radical innovation and breakthrough patents25334136510.1080/13571516.2018.1438873Search in Google Scholar
Bush, V. (1945). Science: The endless frontier. Washington, DC: Government Printing Office.BushV.1945Washington, DCGovernment Printing OfficeSearch in Google Scholar
Chen, D. Z., Huang, W. T., & Huang, M. H. (2014). Analyzing Taiwan's patenting performance: Comparing US patents and triadic patent families. Malaysian Journal of Library and Information Science, 19(1), 51–70.ChenD. Z.HuangW. T.HuangM. H.2014Analyzing Taiwan's patenting performance: Comparing US patents and triadic patent families1915170Search in Google Scholar
Chen, S., Huang, F. W., & Lin, J. H. (2022). Effects of Cap-and-Trade Mechanism and Financial Gray Rhino Threats on Insurer Performance. Energies, 15(15), 5506.ChenS.HuangF. W.LinJ. H.2022Effects of Cap-and-Trade Mechanism and Financial Gray Rhino Threats on Insurer Performance1515550610.3390/en15155506Search in Google Scholar
Cheng, Y., Huang, L., Ramlogan, R., & Li, X. (2017). Forecasting of potential impacts of disruptive technology in promising technological areas: Elaborating the SIRS epidemic model in RFID technology. Technological Forecasting and Social Change, 117, 170–183.ChengY.HuangL.RamloganR.LiX.2017Forecasting of potential impacts of disruptive technology in promising technological areas: Elaborating the SIRS epidemic model in RFID technology11717018310.1016/j.techfore.2016.12.003Search in Google Scholar
Christensen, C. M. (2006). The ongoing process of building a theory of disruption. Journal of Product Innovation Management, 23(1), 39–55.ChristensenC. M.2006The ongoing process of building a theory of disruption231395510.1111/j.1540-5885.2005.00180.xSearch in Google Scholar
Cleverdon, C. W. (1972). On the inverse relationship of recall and precision. Journal of documentation, 28(3), 195–201.CleverdonC. W.1972On the inverse relationship of recall and precision28319520110.1108/eb026538Search in Google Scholar
Criscuolo, P. (2006). The ‘home advantage’ effect and patent families. A comparison of OECD triadic patents, the USPTO and the EPO. Scientometrics, 66(1), 23–41.CriscuoloP.2006The ‘home advantage’ effect and patent families. A comparison of OECD triadic patents, the USPTO and the EPO661234110.1007/s11192-006-0003-6Search in Google Scholar
Dahlin, K. B, & Behrens, D. M. (2005). When is an invention really radical? Defining and measuring technological radicalness. Research Policy, 34(5), 717–737.DahlinK. BBehrensD. M.2005When is an invention really radical? Defining and measuring technological radicalness34571773710.1016/j.respol.2005.03.009Search in Google Scholar
Dehghanimadvar, M., Shirmohammadi, R., Sadeghzadeh, M., Aslani, A., & Ghasempour, R. (2020) Hydrogen production technologies: Attractiveness and future perspective. International Journal of Energy Research, 44(11), 8233–8254.DehghanimadvarM.ShirmohammadiR.SadeghzadehM.AslaniA.GhasempourR.2020Hydrogen production technologies: Attractiveness and future perspective44118233825410.1002/er.5508Search in Google Scholar
de Rassenfosse, G., Dernis, H., Guellec, D., Picci, L., & de la Potterie, B. V. (2013). The worldwide count of priority patents: A new indicator of inventive activity. Research Policy, 42(3), 720–737.de RassenfosseG.DernisH.GuellecD.PicciL.de la PotterieB. V.2013The worldwide count of priority patents: A new indicator of inventive activity42372073710.1016/j.respol.2012.11.002Search in Google Scholar
Dernis, H., & Khan, M. (2004). Triadic patent families methodology. OECD Science, Technology and Industry Working Papers, 02.DernisH.KhanM.2004Triadic patent families methodologyTechnology and Industry Working Papers, 02.Search in Google Scholar
Dupuis, R. D., & Krames, M. R. (2008). History, development, and applications of high-brightness visible light-emitting diodes. Journal of Lightwave Technology, 26(9), 1154–1171.DupuisR. D.KramesM. R.2008History, development, and applications of high-brightness visible light-emitting diodes2691154117110.1109/JLT.2008.923628Search in Google Scholar
EDinformatrics. (n.d.). The Encyclopedia Britannica's list for the Greatest Inventions of all times. https://www.edinformatics.com/inventions_inventors/EDinformatrics(n.d.)https://www.edinformatics.com/inventions_inventors/Search in Google Scholar
Ernst, H. (1997). The use of patent data for technological forecasting: The diffusion of CNC-technology in the machine tool industry. Small Business Economics, 9(4), 361–381.ErnstH.1997The use of patent data for technological forecasting: The diffusion of CNC-technology in the machine tool industry9436138110.1023/A:1007921808138Search in Google Scholar
Fischer, T., & Ringler, P. (2015). The coincidence of patent thickets-A comparative analysis. Technovation, 38, 42–49.FischerT.RinglerP.2015The coincidence of patent thickets-A comparative analysis38424910.1016/j.technovation.2014.11.004Search in Google Scholar
Fleming, L. (2001). Recombinant uncertainty in technological search. Management Science, 47(1), 117–132.FlemingL.2001Recombinant uncertainty in technological search47111713210.1287/mnsc.47.1.117.10671Search in Google Scholar
Gao, L. D., Porter, A. L., Wang, J., Fang, S., Zhang, X., Ma, T. T., Wang, W. P., & Huang, L. (2013). Technology life cycle analysis method based on patent documents. Technological Forecasting and Social Change, 80(3), 398–407.GaoL. D.PorterA. L.WangJ.FangS.ZhangX.MaT. T.WangW. P.HuangL.2013Technology life cycle analysis method based on patent documents80339840710.1016/j.techfore.2012.10.003Search in Google Scholar
Geum, Y., Jeon, J., & Seol, H. (2013). Identifying technological opportunities using the novelty detection technique: a case of laser technology in semiconductor manufacturing. Technology Analysis & Strategic Management, 25(1), 1–22.GeumY.JeonJ.SeolH.2013Identifying technological opportunities using the novelty detection technique: a case of laser technology in semiconductor manufacturing25112210.1080/09537325.2012.748892Search in Google Scholar
Giovanis, E., & Ozdamar, O. (2015). Determinants of total factor productivity: Evidence from US compustat firms and triadic patent families. International Journal of Economics and Business Research, 10(3), 258–272.GiovanisE.OzdamarO.2015Determinants of total factor productivity: Evidence from US compustat firms and triadic patent families10325827210.1504/IJEBR.2015.071845Search in Google Scholar
Graham, S. J. H., Marco, A. C., & Myers, A. F. (2018). Patent transactions in the marketplace: Lessons from the USPTO Patent Assignment Dataset. Journal of Economics & Management Strategy, 27(3), 343–371.GrahamS. J. H.MarcoA. C.MyersA. F.2018Patent transactions in the marketplace: Lessons from the USPTO Patent Assignment Dataset27334337110.1111/jems.12262Search in Google Scholar
Guo, J., Xiang, P. C., & Lee, Y. L. (2022). Analyzing and controlling construction engineering project gray rhino risks with innovative mcdm methods: interference fuzzy analytical network process and decision-making trial and evaluation laboratory. Applied Sciences-Basel, 12(11), 5693.GuoJ.XiangP. C.LeeY. L.2022Analyzing and controlling construction engineering project gray rhino risks with innovative mcdm methods: interference fuzzy analytical network process and decision-making trial and evaluation laboratory1211569310.3390/app12115693Search in Google Scholar
Haupt, R., Kloyer, M., & Lange, M. (2007). Patent indicators for the technology life cycle development. Research Policy, 36(3), 387–398.HauptR.KloyerM.LangeM.2007Patent indicators for the technology life cycle development36338739810.1016/j.respol.2006.12.004Search in Google Scholar
Higham, K., Contisciani, M., & De Bacco, C. (2022). Multilayer patent citation networks: A comprehensive analytical framework for studying explicit technological relationships. Technological Forecasting and Social Change, 179, 121628.HighamK.ContiscianiM.De BaccoC.2022Multilayer patent citation networks: A comprehensive analytical framework for studying explicit technological relationships17912162810.1016/j.techfore.2022.121628Search in Google Scholar
Huang, C., & Jacob, J. (2014). Determinants of quadic patenting: Market access, imitative threat, competition and strength of intellectual property rights. Technological Forecasting and Social Change, 85, 4–16.HuangC.JacobJ.2014Determinants of quadic patenting: Market access, imitative threat, competition and strength of intellectual property rights8541610.1016/j.techfore.2013.04.004Search in Google Scholar
Huang, F. W. (2020). A simple model of financial grey rhino under insurer capital regulation. Applied Economics, 52(46), 5088–5097.HuangF. W.2020A simple model of financial grey rhino under insurer capital regulation52465088509710.1080/00036846.2020.1752905Search in Google Scholar
Jia, W. F., Xie, Y. P., Zhao, Y. N., Yao, K., Shi, H., & Chong, D. Z. (2021). Research on disruptive technology recognition of China's electronic information and communication industry based on patent influence. Journal of Global Information Management, 29(2), 148–165.JiaW. F.XieY. P.ZhaoY. N.YaoK.ShiH.ChongD. Z.2021Research on disruptive technology recognition of China's electronic information and communication industry based on patent influence29214816510.4018/JGIM.2021030108Search in Google Scholar
Jung, H. J. (2020). Recombination sources and breakthrough inventions: University-developed technology versus firm-developed technology. Journal of Technology Transfer, 45(4), 1121–1166.JungH. J.2020Recombination sources and breakthrough inventions: University-developed technology versus firm-developed technology4541121116610.1007/s10961-019-09741-0Search in Google Scholar
Kim, D., Cerigo, D. B., Jeong, H., & Youn, H. (2016). Technological novelty profile and invention's future impact. EPJ Data Science, 5, 8.KimD.CerigoD. B.JeongH.YounH.2016Technological novelty profile and invention's future impact5810.1140/epjds/s13688-016-0069-1Search in Google Scholar
Kim, G., & Bae, J. (2017). A novel approach to forecast promising technology through patent analysis. Technological Forecasting and Social Change, 117, 228–237.KimG.BaeJ.2017A novel approach to forecast promising technology through patent analysis11722823710.1016/j.techfore.2016.11.023Search in Google Scholar
Laurens, P., Le Bas, C., & Schoen, A. (2019). Worldwide IP coverage of patented inventions in large pharma firms: to what extent do the internationalisation of R&D and firm strategy matter? International Journal of Technology Management, 80(3–4), 177–211.LaurensP.Le BasC.SchoenA.2019Worldwide IP coverage of patented inventions in large pharma firms: to what extent do the internationalisation of R&D and firm strategy matter?803–417721110.1504/IJTM.2019.100283Search in Google Scholar
Lee, C., Kang, B., & Shin, J. (2015a). Novelty-focused patent mapping for technology opportunity analysis. Technological Forecasting and Social Change, 90, 355–365.LeeC.KangB.ShinJ.2015aNovelty-focused patent mapping for technology opportunity analysis9035536510.1016/j.techfore.2014.05.010Search in Google Scholar
Lee, C., Kim, J., Kwon, O., & Woo, H. G. (2016). Stochastic technology life cycle analysis using multiple patent indicators. Technological Forecasting and Social Change, 106, 53–64.LeeC.KimJ.KwonO.WooH. G.2016Stochastic technology life cycle analysis using multiple patent indicators106536410.1016/j.techfore.2016.01.024Search in Google Scholar
Lee, W. S., Han, E. J., & Sohn, S. Y. (2015b). Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents. Technology Analysis & Strategic Management, 100, 317–329.LeeW. S.HanE. J.SohnS. Y.2015bPredicting the pattern of technology convergence using big-data technology on large-scale triadic patents10031732910.1016/j.techfore.2015.07.022Search in Google Scholar
Lezama-Nicolas, R., Rodriguez-Salvador, M., Rio-Belver, R., & Bildosola, I. (2018). A bibliometric method for assessing technological maturity: The case of additive manufacturing. Scientometrics, 117(3), 1425–1452.Lezama-NicolasR.Rodriguez-SalvadorM.Rio-BelverR.BildosolaI.2018A bibliometric method for assessing technological maturity: The case of additive manufacturing11731425145210.1007/s11192-018-2941-1626724730546169Search in Google Scholar
Lin, D. M., Liu, W. B., Guo, Y. X., & Meyer, M. (2021a). Using technological entropy to identify technology life cycle. Journal of Informetrics, 15(2), 101137.LinD. M.LiuW. B.GuoY. X.MeyerM.2021aUsing technological entropy to identify technology life cycle15210113710.1016/j.joi.2021.101137Search in Google Scholar
Lin, J. H., Chang, C. P., & Chen, S. (2021b). A simple model of financial grey rhino under insurer capital regulation: an extension. Applied Economics Letters, 28(21), 1872–1876.LinJ. H.ChangC. P.ChenS.2021bA simple model of financial grey rhino under insurer capital regulation: an extension28211872187610.1080/13504851.2020.1854655Search in Google Scholar
Lin, M., & Patel, P. C. (2019). Distant search, technological diversity, and branding focus: Incremental and radical innovation in small- and medium-sized consignees. IEEE Transactions on Engineering Management, 66(2), 170–179.LinM.PatelP. C.2019Distant search, technological diversity, and branding focus: Incremental and radical innovation in small- and medium-sized consignees66217017910.1109/TEM.2018.2836179Search in Google Scholar
Liu, C. Y., & Wang, J. C. (2010). Forecasting the development of the biped robot walking technique in Japan through S-curve model analysis. Scientometrics, 82(1), 21–36.LiuC. Y.WangJ. C.2010Forecasting the development of the biped robot walking technique in Japan through S-curve model analysis821213610.1007/s11192-009-0055-5Search in Google Scholar
Liu, W., Tan, R. H., Li, Z. B., Cao, G. Z., & Yu, F. (2021). A patent-based method for monitoring the development of technological innovations based on knowledge diffusion. Journal of Knowledge Management, 25(2), 380–401.LiuW.TanR. H.LiZ. B.CaoG. Z.YuF.2021A patent-based method for monitoring the development of technological innovations based on knowledge diffusion25238040110.1108/JKM-09-2019-0502Search in Google Scholar
Liu, X. W., Wang, X. Z., Lyu, L., & Wang, Y. P. (2022). Identifying disruptive technologies by integrating multi-source data. Scientometrics, 127(9), 5325–5351.LiuX. W.WangX. Z.LyuL.WangY. P.2022Identifying disruptive technologies by integrating multi-source data12795325535110.1007/s11192-022-04283-zSearch in Google Scholar
Madvar, M. D., Ahmadi, F., Shirmohammadi, R., Aslani, A. (2019a). Forecasting of wind energy technology domains based on the technology life cycle approach. Energy Reports, 5, 1236–1248.MadvarM. D.AhmadiF.ShirmohammadiR.AslaniA.2019aForecasting of wind energy technology domains based on the technology life cycle approach51236124810.1016/j.egyr.2019.08.069Search in Google Scholar
Madvar, M. D., Aslani, A., Ahmadi, M. H., & Ghomi, N. S. K. (2019b). Current status and future forecasting of biofuels technology development. International Journal of Energy Research, 43(3), 1142–1160.MadvarM. D.AslaniA.AhmadiM. H.GhomiN. S. K.2019bCurrent status and future forecasting of biofuels technology development4331142116010.1002/er.4344Search in Google Scholar
Magee, C. L., Kleyn, P. W., Monks, B. M., Betz, U., & Basnet, S. (2018). Pre-existing technological core and roots for the CRISPR breakthrough. PLoS ONE, 13(9), e0198541.MageeC. L.KleynP. W.MonksB. M.BetzU.BasnetS.2018Pre-existing technological core and roots for the CRISPR breakthrough139e019854110.1371/journal.pone.0198541614552730231020Search in Google Scholar
Mattos, L. H. S., & Speziali, M. G. (2017). Patent landscape: Technology development behind science in the flavor and fragrances (F&F) area. World Patent Information, 51, 57–65.MattosL. H. S.SpezialiM. G.2017Patent landscape: Technology development behind science in the flavor and fragrances (F&F) area51576510.1016/j.wpi.2017.11.006Search in Google Scholar
Messinis, G. (2011). Triadic citations, country biases and patent value: The case of pharmaceuticals. Scientometrics, 89(3), 813–833.MessinisG.2011Triadic citations, country biases and patent value: The case of pharmaceuticals89381383310.1007/s11192-011-0473-zSearch in Google Scholar
Meyer, P. S., Yung, J. W., & Ausubel, J. H. (1999). A primer on logistic growth and substitution - The mathematics of the Loglet Lab software. Technological Forecasting and Social Change, 61(3), 247–271.MeyerP. S.YungJ. W.AusubelJ. H.1999A primer on logistic growth and substitution - The mathematics of the Loglet Lab software61324727110.1016/S0040-1625(99)00021-9Search in Google Scholar
Milanez, D. H., de Faria, L. I. L., do Amaral, R. M., Leiva, D. R., & Gregolin, J. A. R. (2014). Patents in nanotechnology: An analysis using macro-indicators and forecasting curves. Scientometrics, 101(2), 1097–1112.MilanezD. H.de FariaL. I. L.do AmaralR. M.LeivaD. R.GregolinJ. A. R.2014Patents in nanotechnology: An analysis using macro-indicators and forecasting curves10121097111210.1007/s11192-014-1244-4Search in Google Scholar
MIT Technology Review. (2003, February 1). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2003/MIT Technology Review2003February1https://www.technologyreview.com/10-breakthrough-technologies/2003/Search in Google Scholar
MIT Technology Review. (2004, February 1). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2004/MIT Technology Review2004February1https://www.technologyreview.com/10-breakthrough-technologies/2004/Search in Google Scholar
MIT Technology Review. (2005, May 1). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2005/MIT Technology Review2005May1https://www.technologyreview.com/10-breakthrough-technologies/2005/Search in Google Scholar
MIT Technology Review. (2006, March 1). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2006/MIT Technology Review2006March1https://www.technologyreview.com/10-breakthrough-technologies/2006/Search in Google Scholar
MIT Technology Review. (2007, March 1). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2007/MIT Technology Review2007March1https://www.technologyreview.com/10-breakthrough-technologies/2007/Search in Google Scholar
MIT Technology Review. (2007, February 19). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2008/MIT Technology Review2007February19https://www.technologyreview.com/10-breakthrough-technologies/2008/Search in Google Scholar
MIT Technology Review. (2009, February 24). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2009/MIT Technology Review2009February24https://www.technologyreview.com/10-breakthrough-technologies/2009/Search in Google Scholar
MIT Technology Review. (2010, April 20). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2010/MIT Technology Review2010April20https://www.technologyreview.com/10-breakthrough-technologies/2010/Search in Google Scholar
MIT Technology Review. (2011, April 19). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2011/MIT Technology Review2011April19https://www.technologyreview.com/10-breakthrough-technologies/2011/Search in Google Scholar
MIT Technology Review. (2012, April 25). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2012/MIT Technology Review2012April25https://www.technologyreview.com/10-breakthrough-technologies/2012/Search in Google Scholar
MIT Technology Review. (2013, April 23). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2013/MIT Technology Review2013April23https://www.technologyreview.com/10-breakthrough-technologies/2013/Search in Google Scholar
MIT Technology Review. (2014, April 23). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2014/MIT Technology Review2014April23https://www.technologyreview.com/10-breakthrough-technologies/2014/Search in Google Scholar
MIT Technology Review. (2015, February 18). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2015/MIT Technology Review2015February18https://www.technologyreview.com/10-breakthrough-technologies/2015/Search in Google Scholar
MIT Technology Review. (2016, February 23). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2016/MIT Technology Review2016February23https://www.technologyreview.com/10-breakthrough-technologies/2016/Search in Google Scholar
MIT Technology Review. (2017, February 22). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2017/MIT Technology Review2017February22https://www.technologyreview.com/10-breakthrough-technologies/2017/Search in Google Scholar
MIT Technology Review. (2018, February 21). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2018/MIT Technology Review2018February21https://www.technologyreview.com/10-breakthrough-technologies/2018/Search in Google Scholar
MIT Technology Review. (2019, February 27). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2019/MIT Technology Review2019February27https://www.technologyreview.com/10-breakthrough-technologies/2019/Search in Google Scholar
Momeni, A., & Rost, K. (2016). Identification and monitoring of possible disruptive technologies by patent-development paths and topic modeling. Technological Forecasting and Social Change, 104, 16–29.MomeniA.RostK.2016Identification and monitoring of possible disruptive technologies by patent-development paths and topic modeling104162910.1016/j.techfore.2015.12.003Search in Google Scholar
Phene, A., Fladmoe-Lindquist, K., & Marsh, L. (2006). Breakthrough innovations in the US biotechnology industry: The effects of technological space and geographic origin. Strategic Management Journal, 27(4), 369–388.PheneA.Fladmoe-LindquistK.MarshL.2006Breakthrough innovations in the US biotechnology industry: The effects of technological space and geographic origin27436938810.1002/smj.522Search in Google Scholar
Parameswar, N., Chaubey, A., & Dhir, S. (2021). Black swan: bibliometric analysis and development of research agenda. Benchmarking-An International Journal, 28(7), 2259–2279.ParameswarN.ChaubeyA.DhirS.2021Black swan: bibliometric analysis and development of research agenda2872259227910.1108/BIJ-08-2020-0443Search in Google Scholar
Rizzo, U., Barbieri, N., Ramaciotti, L., & Iannantuono, D. (2020). The division of labour between academia and industry for the generation of radical inventions. The Journal of Technology Transfer, 45(2), 393–413.RizzoU.BarbieriN.RamaciottiL.IannantuonoD.2020The division of labour between academia and industry for the generation of radical inventions45239341310.1007/s10961-018-9688-ySearch in Google Scholar
Rosenberg, N. (1974). Science, invention and economic growth. Economic Journal, 84(333), 90–108.RosenbergN.1974Science, invention and economic growth843339010810.1017/CBO9780511561313.016Search in Google Scholar
Shane, S. (2001). Technological opportunities and new firm creation. Management Science, 47(2), 205–220.ShaneS.2001Technological opportunities and new firm creation47220522010.1287/mnsc.47.2.205.9837Search in Google Scholar
Shen, Y. C., Chang, S. H., Lin, G. T. R., & Yu, H. C. (2010). A hybrid selection model for emerging technology. Technological Forecasting and Social Change, 77(1), 151–166.ShenY. C.ChangS. H.LinG. T. R.YuH. C.2010A hybrid selection model for emerging technology77115116610.1016/j.techfore.2009.05.001Search in Google Scholar
Sternitzke, C. (2009). Defining triadic patent families as a measure of technological strength. Scientometrics, 81(1), 91–109.SternitzkeC.2009Defining triadic patent families as a measure of technological strength8119110910.1007/s11192-009-1836-6Search in Google Scholar
Stoffels, M. A., Klauck, F. J. R., Hamadi, T., Glorius, F., & Leker, J. (2020). Technology trends of catalysts in hydrogenation reactions: A patent landscape analysis. Advanced Synthesis & Catalysis, 362(2), 1258–1274.StoffelsM. A.KlauckF. J. R.HamadiT.GloriusF.LekerJ.2020Technology trends of catalysts in hydrogenation reactions: A patent landscape analysis36221258127410.1002/adsc.201901292716191432322184Search in Google Scholar
Strumsky, D., & Lobo, J. (2015). Identifying the sources of technological novelty in the process of invention. Research Policy, 44(8), 1445–1461.StrumskyD.LoboJ.2015Identifying the sources of technological novelty in the process of invention4481445146110.1016/j.respol.2015.05.008Search in Google Scholar
Sun, B. X., Kolesnikov, S., Goldstein, A., & Chan, G. (2021). A dynamic approach for identifying technological breakthroughs with an application in solar photovoltaics. Technological Forecasting and Social Change, 165, 120534.SunB. X.KolesnikovS.GoldsteinA.ChanG.2021A dynamic approach for identifying technological breakthroughs with an application in solar photovoltaics16512053410.1016/j.techfore.2020.120534Search in Google Scholar
Tahmooresnejad, L., & Beaudry, C. (2019). Capturing the economic value of triadic patents. Scientometrics, 118(1), 127–157.TahmooresnejadL.BeaudryC.2019Capturing the economic value of triadic patents118112715710.1007/s11192-018-2959-4Search in Google Scholar
Taleb, N. N. (2007). Black swans: The impact of the highly improbable. New York: Random House.TalebN. N.2007New YorkRandom HouseSearch in Google Scholar
van der Pol, J., & Rameshkoumar, J. P. (2018). The co-evolution of knowledge and collaboration networks: the role of the technology life-cycle. Scientometrics, 114(1), 307–323.van der PolJ.RameshkoumarJ. P.2018The co-evolution of knowledge and collaboration networks: the role of the technology life-cycle114130732310.1007/s11192-017-2579-4Search in Google Scholar
Verhoeven, D., Bakker, J., & Veugelers, R. (2016). Measuring technological novelty with patent-based indicators. Research Policy, 45(3), 707–723.VerhoevenD.BakkerJ.VeugelersR.2016Measuring technological novelty with patent-based indicators45370772310.1016/j.respol.2015.11.010Search in Google Scholar
Wang, J., & Chen, Y. J. (2019). A novelty detection patent mining approach for analyzing technological opportunities. Advanced Engineering Informatics, 42, 100941.WangJ.ChenY. J.2019A novelty detection patent mining approach for analyzing technological opportunities4210094110.1016/j.aei.2019.100941Search in Google Scholar
Winnink, J. J., & Tijssen, R. J. W. (2015). Early stage identification of breakthroughs at the interface of science and technology: Lessons drawn from a landmark publication. Scientometrics, 102(1), 113–134.WinninkJ. J.TijssenR. J. W.2015Early stage identification of breakthroughs at the interface of science and technology: Lessons drawn from a landmark publication102111313410.1007/s11192-014-1451-zSearch in Google Scholar
Wu, L. F., Wang, D. S., & Evans, J. A. (2019). Large teams develop and small teams disrupt science and technology. Nature, 566(7744), 378–382.WuL. F.WangD. S.EvansJ. A.2019Large teams develop and small teams disrupt science and technology566774437838210.1038/s41586-019-0941-930760923Search in Google Scholar
Wucker, M. (2016). The grey-rhino: How to recognize and act on the obvious dangers we ignore. London: St. Martin's Press.WuckerM.2016LondonSt. Martin's PressSearch in Google Scholar
Yeh, H. Y., Huang, M. H., & Chen, D. Z. (2015). The longitudinal study of highly-impact-technology enterprises in the ICT industry: A social network perspective. Journal of Global Information Management, 22(4), 54–74.YehH. Y.HuangM. H.ChenD. Z.2015The longitudinal study of highly-impact-technology enterprises in the ICT industry: A social network perspective224547410.4018/jgim.2014100104Search in Google Scholar
Yoon, B., & Park, Y. (2007). Development of new technology forecasting algorithm: Hybrid approach for morphology analysis and conjoint analysis of patent information. IEEE Transactions on Engineering Management, 54(3), 588–599.YoonB.ParkY.2007Development of new technology forecasting algorithm: Hybrid approach for morphology analysis and conjoint analysis of patent information54358859910.1109/TEM.2007.900796Search in Google Scholar
Yoon, J., Park, Y., Kim, M., Lee, J., & Lee, D. (2014). Tracing evolving trends in printed electronics using patent information. Journal of Nanoparticle Research, 16(7), 1–15.YoonJ.ParkY.KimM.LeeJ.LeeD.2014Tracing evolving trends in printed electronics using patent information16711510.1007/s11051-014-2471-6Search in Google Scholar
Yung, J. W., Meyer, P. S., & Ausubel, J. H. (1999). The Loglet Lab software: A tutorial. Technological Forecasting and Social Change, 61(3), 273–295. (http://phe.rockefeller.edu/LogletLab/)YungJ. W.MeyerP. S.AusubelJ. H.1999The Loglet Lab software: A tutorial613273295(http://phe.rockefeller.edu/LogletLab/)10.1016/S0040-1625(99)00023-2Search in Google Scholar
Zeng, C. J., Qi, E. P., Li, S. S., Stanley, H. E., & Ye, F. Y. (2017). Statistical characteristics of breakthrough discoveries in science using the metaphor of black and white swans. Physica A, 487, 40–46.ZengC. J.QiE. P.LiS. S.StanleyH. E.YeF. Y.2017Statistical characteristics of breakthrough discoveries in science using the metaphor of black and white swans487404610.1016/j.physa.2017.05.041Search in Google Scholar
Zhang, B., Yu, X., & Zhang, R. Z. (2022). Emerging technology identification based on a dynamic framework: A lifecycle evolution perspective. Technology Analysis & Strategic Management, DOI: 10.1080/09537325.2022.2034779.ZhangB.YuX.ZhangR. Z.2022Emerging technology identification based on a dynamic framework: A lifecycle evolution perspective10.1080/09537325.2022.2034779Open DOISearch in Google Scholar
Zhang, H. H., Zuccala, A. A., & Ye, F. Y. (2019). Tracing the ‘swan-groups’ of physics and economics in the key publications of Nobel laureates. Scientometrics, 119(1), 425–436.ZhangH. H.ZuccalaA. A.YeF. Y.2019Tracing the ‘swan-groups’ of physics and economics in the key publications of Nobel laureates119142543610.1007/s11192-019-03036-9Search in Google Scholar
Zhang, H. H., & Ye, F. Y. (2020). Identifying ‘associated-sleeping-beauties’ in ‘swan-groups’ based on small qualified datasets of physics and economics. Scientometrics, 122(3), 1525–1537.ZhangH. H.YeF. Y.2020Identifying ‘associated-sleeping-beauties’ in ‘swan-groups’ based on small qualified datasets of physics and economics12231525153710.1007/s11192-020-03359-ySearch in Google Scholar