为更好制定人工智能领域发展政策,通过构建人工智能领域的技术融合网络,分析该领域技术融合机理。基于人工智能领域2010~2019年的专利数据,结合技术维度和组织维度,从技术特征、组织的技术特征、组织的关系特征3个层面进行实证研究。结果表明:人工智能领域组织合作稀疏、融合技术相对分散、组织和技术具有明显的核心-边缘结构特征;技术特征层面,相似技术更易融合,已发生融合的技术会促进新融合发生;组织的技术特征层面,组织拥有的共性技术会抑制与其他技术融合的发生;组织的关系特征层面,组织间合作关系对技术融合作用与领域发展阶段密切相关,“伙伴圈”会抑制技术融合。
In order to better formulate policies for the development of artificial intelligence, this paper analyzes the technology convergence mechanism in the field of artificial intelligence by constructing the technology convergence network model. Based on the patent data from 2010—2019 of artificial intelligence field, combined with technology and organization dimension, this paper tries to analyzes from three aspects of technical characteristics, organization technical characteristics and organization relationship characteristics. The results show that: In the field of artificial intelligence, organization cooperation is sparse, fusion technology is relatively scattered, organization and technology have obvious core-edge structure characteristics. On the level of technical characteristics, similar technologies are easier to be converged, and technologies that have already been converged will promote new convergence; On the level of organizational technical characteristics, the common technologies owned by the orgnization will negatively affect the occurrence of convergence with other technologies; On the level of organizational relationship characteristics, the effect of cooperation between organizations on technological convergence is closely related to the development stage of the field, and the "circle of buddies" inhibits technology convergence.
[1] 王友发, 张茗源, 罗建强, 等. 专利视角下人工智能领域技术机会分析[J]. 科技进步与对策, 2020,37(4):19-26.
WANG Y F, ZHANG M Y, LUO J Q, et al. Research on the technological opportunity of artificial intelligence technology based on patent information[J]. Science & Technology Progress and Policy, 2020,37(4):19-26.
[2] ROSENBERG N. Technological change in the machine tool industry[J]. Journal of Economic History, 1963,23(4):414-443.
[3] KIM E, CHO Y, KIM W. Dynamic patterns of technological convergence in printed electronics technologies: patent citation network[J]. Scientometrics, 2014,98(2):975-998.
[4] 毛荐其, 李新秀, 刘娜. 技术会聚对创新绩效的作用机制研究[J]. 科技进步与对策, 2018,35(20):9-14.
MAO J Q, Li X X, LIU N. The mechanism of technological convergence on innovation performance[J]. Science & Technology Progress and Policy, 2018,35(20):9-14.
[5] JIANG F, JIANG Y, ZHI H, et al. Artificial intelligence in healthcare: past, present and future[J]. Stroke and Vascular Neurology, 2017,2(4):230-243.
[6] 陈燕红. 人工智能技术发展背景下智能金融的法律风险及应对[J]. 人民论坛·学术前沿, 2020(15):124-127.
CHEN Y H. Legal risks of intelligent finance in the AI technology context and responses[J]. People's Forum · Academic Frontiers, 2020(15):124-127.
[7] 苗红, 赵润博, 黄鲁成, 等. 基于LMDI分解模型的技术融合驱动因素研究[J]. 科技进步与对策, 2019,36(3):11-18.
MIAO H, ZHAO R B, HUANG L C, et al. Research on driving factors of technology convergence based on LMDI decomposition model[J]. Science & Technology Progress and Policy, 2019,36(3):11-18.
[8] 冯科, 曾德明. 技术融合距离的聚类特征与影响因素:基于大规模专利数据的实证研究[J]. 管理评论, 2019,31(8):97-109.
FENG K, ZENG D M. Clustering characteristics and influencing factors of technology convergence distance: an empirical study based on large-scale patent data[J]. Business Review, 2019,31(8):97-109.
[9] CAVIGGIOLI F. Technology fusion: Identification and analysis of the drivers of technology convergence using patent data[J]. Technovation, 2016,55-56:22-32.
[10] CHOI J, JEONG S, KIM K. A study on diffusion pattern of technology convergence: patent analysis for Korea[J]. Sustainability, 2015,7(9):11546-11569.
[11] LIM S, KWON O, LEE D H. Technology convergence in the Internet of Things (IoT) startup ecosystem: a network analysis[J]. Telematics and Informatics, 2018,35(7):1887-1899.
[12] KIM K. Impact of firms' cooperative innovation strategy on technological convergence performance: the case of korea's ICT Industry[J]. Sustainability, 2017,9(9):1601.
[13] 周建平, 刘程军, 徐维祥, 等. 电子商务背景下快递企业物流网络结构及自组织效应——以中通快递为例[J]. 经济地理, 2021,41(2):103-112.
ZHOU J P, LIU C J, XU W X, et al. Logistics network structure and self-organizing effect of express delivery enterprises under the background of e-commerce: a case study of ZTO Express[J]. Economic Geography, 2021,41(2):103-112.
[14] 吕一博, 韦明, 林歌歌. 基于专利计量的技术融合研究:判定、现状与趋势:以物联网与人工智能领域为例[J]. 科学学与科学技术管理, 2019,40(4):16-31.
LÜ Y B, WIE M, LIN G G. Research on technology fusion based on patentometrics: judge, status and trends-take the field of internet of things and artificial intelligence as an example[J]. Science of Science and Management of S.& T., 2019,40(4):16-31.
[15] 高霞, 陈凯华. 合作创新网络结构演化特征的复杂网络分析[J]. 科研管理, 2015,36(6):28-36.
GAO X, CHEN K H. Complex network analysis of the structural evolution characteristics of cooperative innovation networks[J]. Science Research Management, 2015,36(6):28-36.
[16] 宋昱晓, 苗红. 基于专利的技术融合趋势的驱动因素研究[J]. 情报杂志, 2017,36(12):98-105.
SONG Y X, MIAO H. Research on the driving factors of technology convergence trend based on patent[J]. Journal of Information, 2017,36(12):98-105.
[17] 翟东升, 张京先. 基于专利技术共现网络的无人驾驶汽车技术融合演化研究[J]. 情报杂志, 2020,39(4):60-66.
ZHAI D S, ZHANG J X. Research on technology convergence evolution of autonomous vehicle based on patent technology co-occurrence network[J]. Journal of Information, 2020,39(4):60-66.
[18] WANG P, RBOINS G, PATTISON P, et al. Exponential random graph models for multilevel networks[J]. Social Networks, 2013,35(1):96-115.
[19] 熊勇清, 白云, 陈晓红. 战略性新兴产业共性技术开发的合作企业评价:双维两阶段筛选模型的构建与应用[J]. 科研管理, 2014,35(8):68-74.
XIONG Y Q, BAI Y, CHEN X H. Evaluation of cooperative enterprises for generic technology development of strategic emerging industries: construction and application of dual-dimensional and two-stage screening model[J]. Science Research Management, 2014,35(8):68-74.