Anticipation and analysis of industry convergence using patent-level indicators
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DOI: 10.1007/s11192-021-04025-7
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- Yoon, Janghyeok & Park, Hyunseok & Seo, Wonchul & Lee, Jae-Min & Coh, Byoung-youl & Kim, Jonghwa, 2015. "Technology opportunity discovery (TOD) from existing technologies and products: A function-based TOD framework," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 153-167.
- Péter Érdi & Kinga Makovi & Zoltán Somogyvári & Katherine Strandburg & Jan Tobochnik & Péter Volf & László Zalányi, 2013. "Prediction of emerging technologies based on analysis of the US patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 225-242, April.
- Guan, Jian Cheng & Yan, Yan, 2016. "Technological proximity and recombinative innovation in the alternative energy field," Research Policy, Elsevier, vol. 45(7), pages 1460-1473.
- Heo, Pil Sun & Lee, Duk Hee, 2019. "Evolution patterns and network structural characteristics of industry convergence," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 405-426.
- Geum, Youngjung & Kim, Moon-Soo & Lee, Sungjoo, 2016. "How industrial convergence happens: A taxonomical approach based on empirical evidences," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 112-120.
- Karvonen, Matti & Kässi, Tuomo, 2013. "Patent citations as a tool for analysing the early stages of convergence," Technological Forecasting and Social Change, Elsevier, vol. 80(6), pages 1094-1107.
- Changyong Lee & Suckwon Hong & Juram Kim, 2021. "Anticipating multi-technology convergence: a machine learning approach using patent information," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 1867-1896, March.
- Dahlin, Kristina B. & Behrens, Dean M., 2005. "When is an invention really radical?: Defining and measuring technological radicalness," Research Policy, Elsevier, vol. 34(5), pages 717-737, June.
- Manuel Trajtenberg, 1990. "A Penny for Your Quotes: Patent Citations and the Value of Innovations," RAND Journal of Economics, The RAND Corporation, vol. 21(1), pages 172-187, Spring.
- Kim, Tae San & Sohn, So Young, 2020. "Machine-learning-based deep semantic analysis approach for forecasting new technology convergence," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
- Gauch, Stephan & Blind, Knut, 2015. "Technological convergence and the absorptive capacity of standardisation," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 236-249.
- Robert Swinney & Gérard P. Cachon & Serguei Netessine, 2011. "Capacity Investment Timing by Start-ups and Established Firms in New Markets," Management Science, INFORMS, vol. 57(4), pages 763-777, April.
- Kim, Yee Kyoung & Oh, Jun Byoung, 2017. "Examination workloads, grant decision bias and examination quality of patent office," Research Policy, Elsevier, vol. 46(5), pages 1005-1019.
- Nooteboom, Bart & Van Haverbeke, Wim & Duysters, Geert & Gilsing, Victor & van den Oord, Ad, 2007.
"Optimal cognitive distance and absorptive capacity,"
Research Policy, Elsevier, vol. 36(7), pages 1016-1034, September.
- Nooteboom, B. & Vanheverbeke, W.P.M. & Duysters, G.M. & Gilsing, V.A. & Oord van den, A.J., 2005. "Optimal cognitive distance and absorptive capacity," Working Papers 05.05, Eindhoven Center for Innovation Studies.
- Nooteboom, B. & Vanhaverbeke, W.P.M. & Duijsters, G.M. & Gilsing, V.A. & Oord, A., 2006. "Optimal Cognitive Distance and Absorptive Capacity," Other publications TiSEM eb5155cb-c888-4301-a667-9, Tilburg University, School of Economics and Management.
- Nooteboom, B. & Vanhaverbeke, W.P.M. & Duijsters, G.M. & Gilsing, V.A. & Oord, A., 2006. "Optimal Cognitive Distance and Absorptive Capacity," Discussion Paper 2006-33, Tilburg University, Center for Economic Research.
- Rajagopal, 2014. "Organizations and Innovation," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 3, pages 58-86, Palgrave Macmillan.
- Schoenmakers, Wilfred & Duysters, Geert, 2010. "The technological origins of radical inventions," Research Policy, Elsevier, vol. 39(8), pages 1051-1059, October.
- Verhoeven, Dennis & Bakker, Jurriën & Veugelers, Reinhilde, 2016.
"Measuring technological novelty with patent-based indicators,"
Research Policy, Elsevier, vol. 45(3), pages 707-723.
- Dennis Verhoeven & Jurriën Bakker & Reinhilde Veugelers, 2015. "Measuring technological novelty with patent-based indicators," Working Papers of Department of Management, Strategy and Innovation, Leuven 501835, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
- Seongkyoon Jeong & Jong-Chan Kim & Jae Young Choi, 2015. "Technology convergence: What developmental stage are we in?," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 841-871, September.
- Hanlin You & Mengjun Li & Keith W. Hipel & Jiang Jiang & Bingfeng Ge & Hante Duan, 2017. "Development trend forecasting for coherent light generator technology based on patent citation network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 297-315, April.
- Su, Hsin-Ning & Moaniba, Igam M., 2017. "Investigating the dynamics of interdisciplinary evolution in technology developments," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 12-23.
- Fredrik Hacklin & Martin W. Wallin, 2013. "Convergence and interdisciplinarity in innovation management: a review, critique, and future directions," The Service Industries Journal, Taylor & Francis Journals, vol. 33(7-8), pages 774-788, May.
- Arts, Sam & Hou, Jianan & Gomez, Juan Carlos, 2021. "Natural language processing to identify the creation and impact of new technologies in patent text: Code, data, and new measures," Research Policy, Elsevier, vol. 50(2).
- Sam Arts & Reinhilde Veugelers, 2020.
"Taste for science, academic boundary spanning, and inventive performance of scientists and engineers in industry,"
Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 29(4), pages 917-933.
- Veugelers, Reinhilde & Arts, Sam, 2018. "Taste for Science, Academic Boundary Spanning and Inventive Performance of Scientists and Engineers in Industry," CEPR Discussion Papers 12704, C.E.P.R. Discussion Papers.
- Kim, Namil & Lee, Hyeokseong & Kim, Wonjoon & Lee, Hyunjong & Suh, Jong Hwan, 2015. "Dynamic patterns of industry convergence: Evidence from a large amount of unstructured data," Research Policy, Elsevier, vol. 44(9), pages 1734-1748.
- Sick, Nathalie & Preschitschek, Nina & Leker, Jens & Bröring, Stefanie, 2019. "A new framework to assess industry convergence in high technology environments," Technovation, Elsevier, vol. 84, pages 48-58.
- Cheng, Yu & Huang, Lucheng & Ramlogan, Ronnie & Li, Xin, 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, Elsevier, vol. 117(C), pages 170-183.
- Hagedoorn, John & Cloodt, Myriam, 2003. "Measuring innovative performance: is there an advantage in using multiple indicators?," Research Policy, Elsevier, vol. 32(8), pages 1365-1379, September.
- Righi, Cesare & Simcoe, Timothy, 2019. "Patent examiner specialization," Research Policy, Elsevier, vol. 48(1), pages 137-148.
- Lee, Won Sang & Han, Eun Jin & Sohn, So Young, 2015. "Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 317-329.
- Kristina Dahlin & Deans M. Behrens, 2005. "When is an invention really radical? Defining and measuring technological radicalness," Post-Print hal-00480416, HAL.
- Lee, Changyong & Cho, Yangrae & Seol, Hyeonju & Park, Yongtae, 2012. "A stochastic patent citation analysis approach to assessing future technological impacts," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 16-29.
- Euiseok Kim & Yongrae Cho & Wonjoon Kim, 2014. "Dynamic patterns of technological convergence in printed electronics technologies: patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 975-998, February.
- Sam Arts & Lee Fleming, 2018. "Paradise of Novelty—Or Loss of Human Capital? Exploring New Fields and Inventive Output," Organization Science, INFORMS, vol. 29(6), pages 1074-1092, December.
- Scott D. Bass & Lukasz A. Kurgan, 2010. "Discovery of factors influencing patent value based on machine learning in patents in the field of nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 217-241, February.
- Sasaki, Hajime & Sakata, Ichiro, 2021. "Identifying potential technological spin-offs using hierarchical information in international patent classification," Technovation, Elsevier, vol. 100(C).
- Strumsky, Deborah & Lobo, José, 2015. "Identifying the sources of technological novelty in the process of invention," Research Policy, Elsevier, vol. 44(8), pages 1445-1461.
- Song, Kisik & Kim, Kyuwoong & Lee, Sungjoo, 2018. "Identifying promising technologies using patents: A retrospective feature analysis and a prospective needs analysis on outlier patents," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 118-132.
- J. Scott Long & Jeremy Freese, 2006. "Regression Models for Categorical Dependent Variables using Stata, 2nd Edition," Stata Press books, StataCorp LP, edition 2, number long2, March.
- Yu-Shan Chen & Chun-Yu Shih & Ching-Hsun Chang, 2013. "Patents and market value in the U.S. pharmaceutical industry: new evidence from panel threshold regression," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 161-176, November.
- Caviggioli, Federico, 2016. "Technology fusion: Identification and analysis of the drivers of technology convergence using patent data," Technovation, Elsevier, vol. 55, pages 22-32.
- Jeeeun Kim & Sungjoo Lee, 2017. "Forecasting and identifying multi-technology convergence based on patent data: the case of IT and BT industries in 2020," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 47-65, April.
- Sai Yayavaram & Wei-Ru Chen, 2015. "Changes in firm knowledge couplings and firm innovation performance: The moderating role of technological complexity," Strategic Management Journal, Wiley Blackwell, vol. 36(3), pages 377-396, March.
- Song, Chie Hoon & Elvers, David & Leker, Jens, 2017. "Anticipation of converging technology areas — A refined approach for the identification of attractive fields of innovation," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 98-115.
- Junbyoung Oh & Yee Kyoung Kim, 2017. "Examination workloads, grant decision bias and examination quality of patent office," Inha University IBER Working Paper Series 2017-3, Inha University, Institute of Business and Economic Research, revised Apr 2017.
- Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
- Arun Kumaraswamy & Raghu Garud & Shahzad (Shaz) Ansari, 2018. "Perspectives on Disruptive Innovations," Journal of Management Studies, Wiley Blackwell, vol. 55(7), pages 1025-1042, November.
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- Ghaffari, Mohsen & Aliahmadi, Alireza & Khalkhali, Abolfazl & Zakery, Amir & Daim, Tugrul U. & Yalcin, Haydar, 2023. "Topic-based technology mapping using patent data analysis: A case study of vehicle tires," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
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More about this item
Keywords
Industry convergence; Patent; Knowledge combination; Technology forecasting; Innovation;All these keywords.
JEL classification:
- O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
- O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
- O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
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