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Identification of Patent Collaboration Partners in A Science-based Industry |
Yang Xi1,Liu Xin2 |
(1.Center for Studies of Intellectual Property Rights, Zhongnan University of Economics and Law, Wuhan 430073, China;2.School of Public Administration, Southwest Jiaotong University, Chengdu 610031, China) |
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Abstract The development of science-based industry has become the focus of global science and technology as well as industrial competition. Science-based industry has the characteristics of open innovation. The innovation subject in the industry is committed to finding partners to make full use of external resources, so as to obtain patent collaboration opportunities and competitive advantages. For how to choose partners, domestic and foreign scholars mainly analyze the evaluation factors and research motivation of partners through qualitative research methods such as expert knowledge. Thus, the research results are greatly affected by subjective factors and lack certain objectivity. Patent information covers rich technical, legal and economic information. Patent information is an important information resource for innovation subjects to find partners and carry out innovation collaboration. However, there is a lack of in-depth research on science-based industrial innovation and development by using patent information, and the research on exploring patent partners in science-based industry from a predictive perspective is still blank. #br# Aiming at exploring patent collaboration opportunities and competitive advantages in science-based industry, this study introduces actor-network theory to the research field of science-based industry, employs patent technological portfolio and social network analysis, and proposes a new method of patent partner identification. Taking graphene, a typical science-based industry, as an example, this study proves the effectiveness of the method. After looking through related literature and consulting technical experts' advice, 67 835 graphene technology patents from 2011 to 2019were obtained downloaded from Derwent Innovation Index. This method combines the technology level with the patentee level from a predictive perspective, and deeply discusses the logical translation process of identification for potential domestic and foreign patent partners. The actor-network theory divides the translation of patent partners' identification into four processes: problematization, interessement, mobilization and enrollment. It also selects appropriate patent indicators to measure the process of interessement, mobilization and enrollment. The process of problematization aims to extract the research problems in line with the common interests of all actors according to the current situation of industrial innovation and development. This study focuses on how to find potential patent partners in science-based industries. In the process of interessement, starting from the common interests among actors, it looks for potential actors to join the network. Based on patent analysis the study identifies the technology hotspots and fronts in the science-based industry from the technology level which shows the common innovation opportunities of patentees in the industrial competition;it also verifies the patentees with competitive advantages in the science-based industry from the patentee level which indicates the potential important actors in the interactive network. The process of mobilization is designed to provide a strategy for connecting with other actors. This paper constructs the technology association network of the patentee in key technology fields, combines the technology level with the patentee level, and digs out technical focus among important patentees. Based on the common technical focus among patentees, this paper further constructs the strategy of identifying potential patent partners in the science-based industry. In the process of enrollment, this paper adopts the strategies in the mobilization process and forms an interactive network between actors. Based on the index of technical similarity, this paper constructs patent partner identification networks, identifies China's potential domestic and foreign patent partners, and explores patent collaboration opportunities and competitive advantages. #br# The results show that the most potential domestic patent partners in the field of graphene include Zhejiang University, Harbin Institute of Technology, Chengdu New Keli Chemical Technology Co., Ltd., Tsinghua University and Central South University; the most potential foreign patent partners in the field of graphene include Samsung Electronics Co., Ltd, LG Chem Ltd., Nanotek Instruments Inc, LEE Y T, Sungkyunkwan University, and Korea Advanced Institute of Science and Technology; the key technology areas with the most collaboration potential at home and abroad are E05-U05C(Nanofilm), L03-H05(Vehicles), L03-A02B(Nonmetal conductors-carbon and graphite), A08-S02(Solvents; swelling agents) and A10-E05B(Chemical modification by carbonization). #br# The contributions of this paper are threefold. First this paper uses patent information to provide a useful supplement for the quantitative analysis of innovation and development in the science-based industries. Second it expands the existing theoretical system of science-based industry research by proposing a new methodology of patent partner identification. Lastly from the predictive perspective, this paper combines these two levels through patent technological portfolio and social network analysis, and identifies the potential domestic and foreign patent partners of the innovation subjects in China's graphene industry.#br#
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Received: 26 September 2021
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[1] 胥和平, 雷家骕. 前瞻布局基于科学的产业创新,培育先发优势的引领性发展[N].科技日报,2021-04-09.[2] MEYER-KRAHMER F, SCHMOCH U.Science-based technologies: university-industry interactions in four fields[J].Research Policy,1998,27(8): 835-851.[3] GIBBONS M, JOHNSTON R. The roles of science in technological innovation[J]. Research Policy, 1974, 3(3): 220-242.[4] 张艺,陈凯华,朱桂龙.产学研合作与后发国家创新主体能力演变——以中国高铁产业为例[J].科学学研究,2018,36(10):1896-1913.[5] 栾春娟.能源产业前沿探索:基于科学创新视角[J].中国科技论坛,2018, 34(7):74-80.[6] CHESBROUGH H W. Open innovation: the new imperative for creating and profiting from technology [M]. Boston: Harvard Business School Press, 2003: 43-62.[7] BIERLY III P E, GALLAGHEER S. Explaining alliance partner selection: fit, trust and strategic expediency[J]. Long Range Planning, 2007,40(2):134-153.[8] SANDNER P G, BLOCK J. The market value of R&D, patents and trademarks[J]. Research Policy, 2011, 40(7): 969-985.[9] 何怀文,陈如文.专利共有制度的博弈分析[J].清华知识产权评论, 2015,1(1): 103-127.[10] NOVOSELOV K S,GEIM A K,MOROZOV S V,et al. Electric field effect in atomically thin carbon films[J]. Science,2004,306(5696): 666-669.[11] KWON S,POETER A,YOUTIE J. Navigating the innovation trajectories of technology by combining specialization score analyses for publications and patents:graphene and nano-enabled drug delivery[J]. Scientometrics,2016,106(3): 1057-1071.[12] LI M. A novel three-dimension perspective to explore technology evolution[J]. Scientometrics,2015,105(3): 1679-1697.[13] 杨仲基,王宏起,王珊珊,等.基于动态网络方法的产业专利合作态势研究——以中国石墨烯产业为例[J].科技进步与对策,2018,35(9):59-65.[14] FREEMAN C. The economics of industrial innovation[M]. Hermondsworth: Penguin, 1974.[15] YI W J, ZOU L L, GUO J, et al. How can China reach its CO intensity reduction targets by 2020? a regional-location based on equity and development[J].Energy Policy,2011,39(5):2407-2415.[16] CORIAT B, ORSI F, WEINSTEIN O. Does biotech reflect a new science-based innovation regime[J].Industry and Innovation, 2003, 10(3): 231-253.[17] NELSON R R, WINTER S G. An evolutionary theory of economic change[M]. Cambridge: Harvard University Press, 1982.[18] 巴萨拉·乔.技术发展简史[M].上海:复旦大学出版社,2000.[19] ARORA A, NANDKUMAR A.Insecure advantage? markets for technology and the value of resources for entrepreneurial ventures[J]. Strategic Management Journal, 2012,33(3): 231-251.[20] DUTRENIT G.Building technological capabilities in latecomer firms: a review essay[J]. Science, Technology and Society,2004,9(2):209-241.[21] DE PAULO A, RIBEIRO E, PORTO G. Mapping countries cooperation networks in photovoltaic technology development based on patent analysis[J]. Scientometrics, 2018, 117(2): 667-686.[22] YANG W,YU X,ZHANG B,et al. Mapping the landscape of international technology diffusion (1994-2017): network analysis of transnational patents[J]. The Journal of Technology Transfer, 2021, 46(1): 138-171.[23] WANG X, `LI R, HUANG Y, et al. Identifying R&D partners for dye-sensitized solar cells: a multi-level patent portfolio-based approach[J]. Technology Analysis & Strategic Management, 2019, 31(3): 356-370.[24] HA S,LIU W,CHO H,et al. Technological advances in the fuel cell vehicle: patent portfolio management[J]. Technological Forecasting and Social Change,2015,100: 277-289.[25] LEYDESDORFF L, KOGLER D F, YAN B. Mapping patent classifications: portfolio and statistical analysis,and the comparison of strengths and weaknesses[J]. Scientometrics,2017, 112(3): 1573-1591.[26] 栾春娟, 侯剑华, 王贤文,等. 全球竞争对手的技术网络绘制与共性技术识别——以波音与空客为例[J].科技进步与对策, 2014, 31(2): 71-78.[27] LIU W,TAO Y,YANG Z,et al. Exploring and visualizing the patent collaboration network: a case study of smart grid field in China[J]. Sustainability,2019,11(2): 465-482.[28] EVERETT M G, BORGATTI S P. The dual-projection approach for two-mode networks[J]. Social Networks, 2013, 35(2):204-210.[29] 瑟乔·西斯蒙多. 科学技术学导论[M]. 许为民等, 译. 上海: 上海世纪出版集团, 2007.[30] 王春梅.基于行动者网络理论的区域创新体系进路研究——以南京为例[J].科技进步与对策,2012,29(24):52-55.[31] LATOUR B, WOOLGAR S. Laboratory life: the social construction of scientific facts [M]. Beverly Hills London: Sage, 1979: 154.[32] 王一鸣,曾国屏.行动者网络理论视角下的技术预见模型演进与展望[J].科技进步与对策,2013,30(9):156-160.[33] GAO P. Using actor-network theory to analyse strategy formulation[J]. Information System Journal, 2005, 15(3): 255-275.[34] SHIM Y, SHIN D H. Analyzing China′s fintech industry from the perspective of actor-network theory[J]. Telecommunications Policy, 2016, 40(2-3):168-181.[35] SHIM Y,SHIN D.Smartness in techno-nationalism? combining actor-network theory and institutionalization to assess Chinese smart TV development[J]. Technological Forecasting & Social Change, 2019, 139: 87-98.[36] 车尧,李雪梦.基于德温特手工代码的专利技术分析——以风能为例[J].情报科学,2015,33(4):132-138. |
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