Cite

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. 2013 A study of scientometric methods to identify emerging technologies via modeling of milestones Scientometrics 91 2 327 342 10.1007/s11192-011-0614-4 Search in Google Scholar

Adams, J. (1990). Fundamental stocks of knowledge and productivity growth. Journal of Political Economy, 98(4), 673–702. AdamsJ. 1990 Fundamental stocks of knowledge and productivity growth Journal of Political Economy 98 4 673 702 10.1086/261702 Search 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. 2019 Technology forecasting: a case study of computational technologies Technological Forecasting and Social Change 143 181 189 10.1016/j.techfore.2019.03.002 Search 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. 2001 Entrepreneurship in the large corporation: A longitudinal study of how established firms create breakthrough inventions Strategic Management Journal 22 6–7 521 543 10.1002/smj.176 Search 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. 1999 The hunt for S-shaped growth paths in technological innovation: A patent study Journal of Evolutionary Economics 9 4 487 526 10.1007/s001910050093 Search 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. 2018 Mapping innovation dynamics in the Internet of Things domain: Evidence from patent analysis Technological Forecasting and Social Change 136 317 330 10.1016/j.techfore.2017.04.022 Search 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. 2015 Technology familiarity, recombinant novelty, and breakthrough invention Industrial and Corporate Change 24 6 1215 1246 10.1093/icc/dtu029 Search 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. 2016 The effects of foreign R&D and triadic patent propensity on developing economies efficiency and convergence Journal Ekonomi Malaysia 50 2 107 124 Search 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. 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 10.1016/j.respol.2005.12.004 Search 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. 2019 An analysis of technologically radical innovation and breakthrough patents International Journal of the Economics of Business 25 3 341 365 10.1080/13571516.2018.1438873 Search in Google Scholar

Bush, V. (1945). Science: The endless frontier. Washington, DC: Government Printing Office. BushV. 1945 Science: The endless frontier Washington, DC Government Printing Office Search 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. 2014 Analyzing Taiwan's patenting performance: Comparing US patents and triadic patent families Malaysian Journal of Library and Information Science 19 1 51 70 Search 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. 2022 Effects of Cap-and-Trade Mechanism and Financial Gray Rhino Threats on Insurer Performance Energies 15 15 5506 10.3390/en15155506 Search 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. 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 10.1016/j.techfore.2016.12.003 Search 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. 2006 The ongoing process of building a theory of disruption Journal of Product Innovation Management 23 1 39 55 10.1111/j.1540-5885.2005.00180.x Search in Google Scholar

Cleverdon, C. W. (1972). On the inverse relationship of recall and precision. Journal of documentation, 28(3), 195–201. CleverdonC. W. 1972 On the inverse relationship of recall and precision Journal of documentation 28 3 195 201 10.1108/eb026538 Search 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. 2006 The ‘home advantage’ effect and patent families. A comparison of OECD triadic patents, the USPTO and the EPO Scientometrics 66 1 23 41 10.1007/s11192-006-0003-6 Search 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. B BehrensD. M. 2005 When is an invention really radical? Defining and measuring technological radicalness Research Policy 34 5 717 737 10.1016/j.respol.2005.03.009 Search 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. 2020 Hydrogen production technologies: Attractiveness and future perspective International Journal of Energy Research 44 11 8233 8254 10.1002/er.5508 Search 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. 2013 The worldwide count of priority patents: A new indicator of inventive activity Research Policy 42 3 720 737 10.1016/j.respol.2012.11.002 Search in Google Scholar

Dernis, H., & Khan, M. (2004). Triadic patent families methodology. OECD Science, Technology and Industry Working Papers, 02. DernisH. KhanM. 2004 Triadic patent families methodology OECD Science Technology 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. 2008 History, development, and applications of high-brightness visible light-emitting diodes Journal of Lightwave Technology 26 9 1154 1171 10.1109/JLT.2008.923628 Search 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.) The Encyclopedia Britannica's list for the Greatest Inventions of all times 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. 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 10.1023/A:1007921808138 Search in Google Scholar

Fischer, T., & Ringler, P. (2015). The coincidence of patent thickets-A comparative analysis. Technovation, 38, 42–49. FischerT. RinglerP. 2015 The coincidence of patent thickets-A comparative analysis Technovation 38 42 49 10.1016/j.technovation.2014.11.004 Search in Google Scholar

Fleming, L. (2001). Recombinant uncertainty in technological search. Management Science, 47(1), 117–132. FlemingL. 2001 Recombinant uncertainty in technological search Management Science 47 1 117 132 10.1287/mnsc.47.1.117.10671 Search 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. 2013 Technology life cycle analysis method based on patent documents Technological Forecasting and Social Change 80 3 398 407 10.1016/j.techfore.2012.10.003 Search 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. 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 10.1080/09537325.2012.748892 Search 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. 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 10.1504/IJEBR.2015.071845 Search 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. 2018 Patent transactions in the marketplace: Lessons from the USPTO Patent Assignment Dataset Journal of Economics & Management Strategy 27 3 343 371 10.1111/jems.12262 Search 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. 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 10.3390/app12115693 Search 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. 2007 Patent indicators for the technology life cycle development Research Policy 36 3 387 398 10.1016/j.respol.2006.12.004 Search 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. 2022 Multilayer patent citation networks: A comprehensive analytical framework for studying explicit technological relationships Technological Forecasting and Social Change 179 121628 10.1016/j.techfore.2022.121628 Search 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. 2014 Determinants of quadic patenting: Market access, imitative threat, competition and strength of intellectual property rights Technological Forecasting and Social Change 85 4 16 10.1016/j.techfore.2013.04.004 Search 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. 2020 A simple model of financial grey rhino under insurer capital regulation Applied Economics 52 46 5088 5097 10.1080/00036846.2020.1752905 Search 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. 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 10.4018/JGIM.2021030108 Search 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. 2020 Recombination sources and breakthrough inventions: University-developed technology versus firm-developed technology Journal of Technology Transfer 45 4 1121 1166 10.1007/s10961-019-09741-0 Search 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. 2016 Technological novelty profile and invention's future impact EPJ Data Science 5 8 10.1140/epjds/s13688-016-0069-1 Search 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. 2017 A novel approach to forecast promising technology through patent analysis Technological Forecasting and Social Change 117 228 237 10.1016/j.techfore.2016.11.023 Search 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. 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 10.1504/IJTM.2019.100283 Search 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. 2015a Novelty-focused patent mapping for technology opportunity analysis Technological Forecasting and Social Change 90 355 365 10.1016/j.techfore.2014.05.010 Search 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. 2016 Stochastic technology life cycle analysis using multiple patent indicators Technological Forecasting and Social Change 106 53 64 10.1016/j.techfore.2016.01.024 Search 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. 2015b Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents Technology Analysis & Strategic Management 100 317 329 10.1016/j.techfore.2015.07.022 Search 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. 2018 A bibliometric method for assessing technological maturity: The case of additive manufacturing Scientometrics 117 3 1425 1452 10.1007/s11192-018-2941-1626724730546169 Search 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. 2021a Using technological entropy to identify technology life cycle Journal of Informetrics 15 2 101137 10.1016/j.joi.2021.101137 Search 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. 2021b A simple model of financial grey rhino under insurer capital regulation: an extension Applied Economics Letters 28 21 1872 1876 10.1080/13504851.2020.1854655 Search 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. 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 10.1109/TEM.2018.2836179 Search 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. 2010 Forecasting the development of the biped robot walking technique in Japan through S-curve model analysis Scientometrics 82 1 21 36 10.1007/s11192-009-0055-5 Search 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. 2021 A patent-based method for monitoring the development of technological innovations based on knowledge diffusion Journal of Knowledge Management 25 2 380 401 10.1108/JKM-09-2019-0502 Search 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. 2022 Identifying disruptive technologies by integrating multi-source data Scientometrics 127 9 5325 5351 10.1007/s11192-022-04283-z Search 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. 2019a Forecasting of wind energy technology domains based on the technology life cycle approach Energy Reports 5 1236 1248 10.1016/j.egyr.2019.08.069 Search 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. 2019b Current status and future forecasting of biofuels technology development International Journal of Energy Research 43 3 1142 1160 10.1002/er.4344 Search 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. 2018 Pre-existing technological core and roots for the CRISPR breakthrough PLoS ONE 13 9 e0198541 10.1371/journal.pone.0198541614552730231020 Search 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. 2017 Patent landscape: Technology development behind science in the flavor and fragrances (F&F) area World Patent Information 51 57 65 10.1016/j.wpi.2017.11.006 Search in Google Scholar

Messinis, G. (2011). Triadic citations, country biases and patent value: The case of pharmaceuticals. Scientometrics, 89(3), 813–833. MessinisG. 2011 Triadic citations, country biases and patent value: The case of pharmaceuticals Scientometrics 89 3 813 833 10.1007/s11192-011-0473-z Search 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. 1999 A primer on logistic growth and substitution - The mathematics of the Loglet Lab software Technological Forecasting and Social Change 61 3 247 271 10.1016/S0040-1625(99)00021-9 Search 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. 2014 Patents in nanotechnology: An analysis using macro-indicators and forecasting curves Scientometrics 101 2 1097 1112 10.1007/s11192-014-1244-4 Search in Google Scholar

MIT Technology Review. (2003, February 1). 10 breakthrough technologies. https://www.technologyreview.com/10-breakthrough-technologies/2003/ MIT Technology Review 2003 February 1 10 breakthrough technologies https://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 Review 2004 February 1 10 breakthrough technologies https://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 Review 2005 May 1 10 breakthrough technologies https://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 Review 2006 March 1 10 breakthrough technologies https://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 Review 2007 March 1 10 breakthrough technologies https://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 Review 2007 February 19 10 breakthrough technologies https://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 Review 2009 February 24 10 breakthrough technologies https://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 Review 2010 April 20 10 breakthrough technologies https://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 Review 2011 April 19 10 breakthrough technologies https://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 Review 2012 April 25 10 breakthrough technologies https://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 Review 2013 April 23 10 breakthrough technologies https://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 Review 2014 April 23 10 breakthrough technologies https://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 Review 2015 February 18 10 breakthrough technologies https://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 Review 2016 February 23 10 breakthrough technologies https://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 Review 2017 February 22 10 breakthrough technologies https://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 Review 2018 February 21 10 breakthrough technologies https://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 Review 2019 February 27 10 breakthrough technologies https://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. 2016 Identification and monitoring of possible disruptive technologies by patent-development paths and topic modeling Technological Forecasting and Social Change 104 16 29 10.1016/j.techfore.2015.12.003 Search 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. 2006 Breakthrough innovations in the US biotechnology industry: The effects of technological space and geographic origin Strategic Management Journal 27 4 369 388 10.1002/smj.522 Search 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. 2021 Black swan: bibliometric analysis and development of research agenda Benchmarking-An International Journal 28 7 2259 2279 10.1108/BIJ-08-2020-0443 Search 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. 2020 The division of labour between academia and industry for the generation of radical inventions The Journal of Technology Transfer 45 2 393 413 10.1007/s10961-018-9688-y Search in Google Scholar

Rosenberg, N. (1974). Science, invention and economic growth. Economic Journal, 84(333), 90–108. RosenbergN. 1974 Science, invention and economic growth Economic Journal 84 333 90 108 10.1017/CBO9780511561313.016 Search in Google Scholar

Shane, S. (2001). Technological opportunities and new firm creation. Management Science, 47(2), 205–220. ShaneS. 2001 Technological opportunities and new firm creation Management Science 47 2 205 220 10.1287/mnsc.47.2.205.9837 Search 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. 2010 A hybrid selection model for emerging technology Technological Forecasting and Social Change 77 1 151 166 10.1016/j.techfore.2009.05.001 Search in Google Scholar

Sternitzke, C. (2009). Defining triadic patent families as a measure of technological strength. Scientometrics, 81(1), 91–109. SternitzkeC. 2009 Defining triadic patent families as a measure of technological strength Scientometrics 81 1 91 109 10.1007/s11192-009-1836-6 Search 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. 2020 Technology trends of catalysts in hydrogenation reactions: A patent landscape analysis Advanced Synthesis & Catalysis 362 2 1258 1274 10.1002/adsc.201901292716191432322184 Search 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. 2015 Identifying the sources of technological novelty in the process of invention Research Policy 44 8 1445 1461 10.1016/j.respol.2015.05.008 Search 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. 2021 A dynamic approach for identifying technological breakthroughs with an application in solar photovoltaics Technological Forecasting and Social Change 165 120534 10.1016/j.techfore.2020.120534 Search in Google Scholar

Tahmooresnejad, L., & Beaudry, C. (2019). Capturing the economic value of triadic patents. Scientometrics, 118(1), 127–157. TahmooresnejadL. BeaudryC. 2019 Capturing the economic value of triadic patents Scientometrics 118 1 127 157 10.1007/s11192-018-2959-4 Search in Google Scholar

Taleb, N. N. (2007). Black swans: The impact of the highly improbable. New York: Random House. TalebN. N. 2007 Black swans: The impact of the highly improbable New York Random House Search 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. 2018 The co-evolution of knowledge and collaboration networks: the role of the technology life-cycle Scientometrics 114 1 307 323 10.1007/s11192-017-2579-4 Search 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. 2016 Measuring technological novelty with patent-based indicators Research Policy 45 3 707 723 10.1016/j.respol.2015.11.010 Search 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. 2019 A novelty detection patent mining approach for analyzing technological opportunities Advanced Engineering Informatics 42 100941 10.1016/j.aei.2019.100941 Search 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. 2015 Early stage identification of breakthroughs at the interface of science and technology: Lessons drawn from a landmark publication Scientometrics 102 1 113 134 10.1007/s11192-014-1451-z Search 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. 2019 Large teams develop and small teams disrupt science and technology Nature 566 7744 378 382 10.1038/s41586-019-0941-930760923 Search 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. 2016 The grey-rhino: How to recognize and act on the obvious dangers we ignore London St. Martin's Press Search 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. 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 10.4018/jgim.2014100104 Search 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. 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 10.1109/TEM.2007.900796 Search 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. 2014 Tracing evolving trends in printed electronics using patent information Journal of Nanoparticle Research 16 7 1 15 10.1007/s11051-014-2471-6 Search 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. 1999 The Loglet Lab software: A tutorial Technological Forecasting and Social Change 61 3 273 295 (http://phe.rockefeller.edu/LogletLab/) 10.1016/S0040-1625(99)00023-2 Search 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. 2017 Statistical characteristics of breakthrough discoveries in science using the metaphor of black and white swans Physica A 487 40 46 10.1016/j.physa.2017.05.041 Search 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. 2022 Emerging technology identification based on a dynamic framework: A lifecycle evolution perspective Technology Analysis & Strategic Management 10.1080/09537325.2022.2034779 Open 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. 2019 Tracing the ‘swan-groups’ of physics and economics in the key publications of Nobel laureates Scientometrics 119 1 425 436 10.1007/s11192-019-03036-9 Search 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. 2020 Identifying ‘associated-sleeping-beauties’ in ‘swan-groups’ based on small qualified datasets of physics and economics Scientometrics 122 3 1525 1537 10.1007/s11192-020-03359-y Search in Google Scholar

eISSN:
2543-683X
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Information Technology, Project Management, Databases and Data Mining