基于加权超图的产学研合作申请专利超网络——以上海ICT产业为例
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摘要
本文对产学研合作情况进行超网络描述,以产、学、研作为节点,以专利作为超边,以每条超边中组织机构合作专利的次数作为超边的权重,构建基于加权超图的产学研合作申请专利超网络拓扑结构。以国家知识产权局专利检索数据库为数据来源,采用超网络方法分析了上海2015年ICT产业产学研申请发明专利的合作关系。实证显示,超网络中节点的度、超度、超强度累计概率分布均服从幂律分布,说明网络结构中的节点具有异质性。最后构建了基于加权超图的超网络演化模型,对模型进行模拟仿真,理论值与模拟值相符合。通过分析发现,上海ICT产业内各技术领域创新格局不平衡,应该进一步加强产学研合作,并加强与其它地区的合作。本文的拓扑指标能够较好地反映合作网络所具有的特点,该方法也适用于实证分析其它合作网络。
This paper describes the Industry-University-Research(I-U-R)cooperation as a hypernetwork,in which a industry,university and research institute is expressed as a node,apatent is expressed as a hyperedge,and the number of the cooperative patents is expressed as the hyperedge weight.It constructs I-U-R cooperation hypernetwork topology model for applying patent based on weighted hypergraph.This paper takes the patent retrieval database from the State Intellectual Property Office(SIPO)of China as the sources of data.It analyzes the I-U-R cooperative relationship of ICT industry for applying invention patent in Shanghai in 2015 with hypernetwork method.The results obtained through empirical analysis affirm that the cumulative probability distribution of node degree,hyperdegree,and hyperstrength follow the power-law distribution,indicating that the nodes are heterogeneous in the network structure.Finally,the evolving hypernetwork model based on weighted hypergraph is examined and simulated.The results of simulations are consistent with the theoretical analysis.The technology innovation pattern of the ICT industry is unbalanced.The ICT industry should further strengthen the I-U-R cooperation,and the cooperation with other areas.The topological indexes of this paper can well reflect the characteristics of cooperative networks,and these approaches proposed in this paper can also be utilized to investigate other cooperation networks as well.
This paper describes the Industry-University-Research(I-U-R)cooperation as a hypernetwork,in which a industry,university and research institute is expressed as a node,apatent is expressed as a hyperedge,and the number of the cooperative patents is expressed as the hyperedge weight.It constructs I-U-R cooperation hypernetwork topology model for applying patent based on weighted hypergraph.This paper takes the patent retrieval database from the State Intellectual Property Office(SIPO)of China as the sources of data.It analyzes the I-U-R cooperative relationship of ICT industry for applying invention patent in Shanghai in 2015 with hypernetwork method.The results obtained through empirical analysis affirm that the cumulative probability distribution of node degree,hyperdegree,and hyperstrength follow the power-law distribution,indicating that the nodes are heterogeneous in the network structure.Finally,the evolving hypernetwork model based on weighted hypergraph is examined and simulated.The results of simulations are consistent with the theoretical analysis.The technology innovation pattern of the ICT industry is unbalanced.The ICT industry should further strengthen the I-U-R cooperation,and the cooperation with other areas.The topological indexes of this paper can well reflect the characteristics of cooperative networks,and these approaches proposed in this paper can also be utilized to investigate other cooperation networks as well.
引文
[1]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.
[2]曹霞,刘国巍.产学研合作创新网络规模、连接机制与创新绩效的关系研究——基于多主体仿真和动态系统论视角[J].运筹与管理,2015,(4):246~254.
[3]其格其,高霞,曹洁琼.我国ICT产业产学研合作创新网络结构对企业创新绩效的影响[J].科研管理,2016,(4):110~115.
[4]刘国巍.产学研合作创新网络时空演化模型及实证研究——基于广西2000-2013年的专利数据分析[J].科学学与科学技术管理,2015,36(4):64~74.
[5]陈伟等.产学研合作创新网络结构和风险研究——以海洋能产业为例[J].科学学与科学技术管理,2014,35(9):59~66.
[6]张艺等.中国科学院产学研合作网络特征与影响[J].科学学研究,2016,34(3):404~417.
[7]曹霞,刘国巍.基于社会资本的产学研合作创新超网络分析[J].管理评论,2013,25(4):115~124.
[8]Rothwell R.Successfulindustrial innovation:Critical factors for the 1990’s[J].R&D Management,1992,22(3):221~240.
[9]Tanimoto J.Coevulutionary,coexiting learning and teaching agents model for prisoner’s dilemma games enhancing cooperation with assortative heterogeneous networks[J].Physica A,2013,392(12):2955~2964.
[10]Krtke S.Regionalknowledge networks:A network analysis approach to the interlinking of knowledge resources[J].European Urban&Regional Studies,2010,17(1):83~97.
[11]Graf H,Henning T.Publicresearch in regional networks of innovators:A comparative study of four east german regions[J].Regional Studies,2009,43(10):1349~1368.
[12]Peters L D,et al.Collaboration andcollective learning:Networks as learning organisations[J].Journal of Business&Industrial Marketing,2010,25(6):478~484.
[13]Cantner U,Graf H.Thenetwork of innovators in jena:An application of social network analysis[J].Research Policy,2006,35(4):463~480.
[14]王众托.关于超网络的一点思考[J].上海理工大学学报,2011,33(3):229~237.
[15]王众托,王志平.超网络初探[J].管理学报,2008,5(1):1~8.
[16]Xiao Q.Amethod for measuring node importance in hypernetwork model[J].Research Journal of Applied Sciences,Engineering and Technology,2013,5(2):568~573.
[17]Liu J G,Yang G Y,Hu Z L.Aknowledge generation model via the hypernetwork[J].Plos One,2014,9(3):e89746.
[18]Yang G Y,Hu Z L,Liu J G.Knowledgediffusion in the collaboration hypernetwork[J].Physica A,2015,419:429~436.
[19]李勇建等.基于超图的非常规突发事件链网络模型研究[J].管理评论,2015,27(12):192~201.
[20]Pan X W,et al.Howusers employ various popular tags to annotate resources in social tagging:An empirical study[J].Journal of the Association for Information Science&Technology,2016,67(5):1121~1137.
[21]Guo J L,et al.Non-uniformevolving hypergraphs and weighted evolving hypergraphs[J].Scientific Reports,2016,(6):36648.
[22]Berge C.Graphs and hypergraphs[M].New York:Elsevier,1973.
[23]Chiang I J.Agglomerativealgorithm to discover semantics from unstructured big data[C]//IEEE International Conference on Big Data,2015.
[24]Estrada E,et al.Subgraphcentrality in complex networks[J].Physical Review E,2005,71(5):056103.
[25]Ghoshal G,et al.Random hypergraphs and their applications[J].Physical Review E,2009,79(6):066118.
[26]刘和东,钱丹.产学研合作绩效的提升路径研究——以高新技术企业为对象的实证分析[J].科学学研究,2016,34(5):704~712.
[27]潘旭伟,傅青苗.基于超网络的社会化标注行为[J].系统工程,2015,33(3):78~83.
[28]胡枫,赵海兴,马秀娟.一种超网络演化模型构建及特性分析[J].中国科学,2013,43(1):16~22.
[29]史定华.网络度分布理论[M].北京:高等教育出版社,2011:85~120.
[30]胡枫.一种超网络演化模型构建及特性分析[J].中国科学,2013,43(1):16~22.
[31]郭进利.非均齐超网络中标度律的涌现——富者愈富导致幂律分布吗[J].物理学报,2014,63(20):208901.
[32]王秋玉,曾刚,吕国庆.中国装备制造业产学研合作创新网络初探[J].地理学报,2016(2):251~264.
[33]OECD.Information technology outlook[Z].Paris:OECD,2010.
[34]高霞等.基于SIPO专利的产学研合作模式及其合作网络结构演化研究——以ICT产业为例[J].科学学与科学技术管理,2016,37(11):34~43.
[35]刘凤朝等.我国ICT产业专利申请趋势——关联分析[J].研究与发展管理,2010,22(2):40~47.
[36]马涛等.基于超网络的企业科技创新团队知识共享机制研究[J].情报科学,2017,35(12):120~128.
[37]Freeman L C.Centrality in social networks:Conceptual clarification[J].Social Network,1979,(1):215~239.
[38]Kapoor K,Sharma D,Srivastava J.Weighted node degree centrality for hypergraphs[C]//Network Science Workshop.IEEE,2013:152~155.
[39]索琪等.电视节目竞争关系的超网络分析[J].复杂系统与复杂性科学,2016,13(3):33~39.
[40]高霞.基于专利的我国ICT产业产学研合作创新实证研究[J].中国管理科学,2013,(11):715~719.
[41]郭进利.复杂网络和人类行为动力学[M].北京:科学出版社,2013:75~89.
[42]Barabási A L,Albert R,Jeong H.Mean-field theory for scale-free random networks[J].Physica A,2000,272(1~2):173~187.
[2]曹霞,刘国巍.产学研合作创新网络规模、连接机制与创新绩效的关系研究——基于多主体仿真和动态系统论视角[J].运筹与管理,2015,(4):246~254.
[3]其格其,高霞,曹洁琼.我国ICT产业产学研合作创新网络结构对企业创新绩效的影响[J].科研管理,2016,(4):110~115.
[4]刘国巍.产学研合作创新网络时空演化模型及实证研究——基于广西2000-2013年的专利数据分析[J].科学学与科学技术管理,2015,36(4):64~74.
[5]陈伟等.产学研合作创新网络结构和风险研究——以海洋能产业为例[J].科学学与科学技术管理,2014,35(9):59~66.
[6]张艺等.中国科学院产学研合作网络特征与影响[J].科学学研究,2016,34(3):404~417.
[7]曹霞,刘国巍.基于社会资本的产学研合作创新超网络分析[J].管理评论,2013,25(4):115~124.
[8]Rothwell R.Successfulindustrial innovation:Critical factors for the 1990’s[J].R&D Management,1992,22(3):221~240.
[9]Tanimoto J.Coevulutionary,coexiting learning and teaching agents model for prisoner’s dilemma games enhancing cooperation with assortative heterogeneous networks[J].Physica A,2013,392(12):2955~2964.
[10]Krtke S.Regionalknowledge networks:A network analysis approach to the interlinking of knowledge resources[J].European Urban&Regional Studies,2010,17(1):83~97.
[11]Graf H,Henning T.Publicresearch in regional networks of innovators:A comparative study of four east german regions[J].Regional Studies,2009,43(10):1349~1368.
[12]Peters L D,et al.Collaboration andcollective learning:Networks as learning organisations[J].Journal of Business&Industrial Marketing,2010,25(6):478~484.
[13]Cantner U,Graf H.Thenetwork of innovators in jena:An application of social network analysis[J].Research Policy,2006,35(4):463~480.
[14]王众托.关于超网络的一点思考[J].上海理工大学学报,2011,33(3):229~237.
[15]王众托,王志平.超网络初探[J].管理学报,2008,5(1):1~8.
[16]Xiao Q.Amethod for measuring node importance in hypernetwork model[J].Research Journal of Applied Sciences,Engineering and Technology,2013,5(2):568~573.
[17]Liu J G,Yang G Y,Hu Z L.Aknowledge generation model via the hypernetwork[J].Plos One,2014,9(3):e89746.
[18]Yang G Y,Hu Z L,Liu J G.Knowledgediffusion in the collaboration hypernetwork[J].Physica A,2015,419:429~436.
[19]李勇建等.基于超图的非常规突发事件链网络模型研究[J].管理评论,2015,27(12):192~201.
[20]Pan X W,et al.Howusers employ various popular tags to annotate resources in social tagging:An empirical study[J].Journal of the Association for Information Science&Technology,2016,67(5):1121~1137.
[21]Guo J L,et al.Non-uniformevolving hypergraphs and weighted evolving hypergraphs[J].Scientific Reports,2016,(6):36648.
[22]Berge C.Graphs and hypergraphs[M].New York:Elsevier,1973.
[23]Chiang I J.Agglomerativealgorithm to discover semantics from unstructured big data[C]//IEEE International Conference on Big Data,2015.
[24]Estrada E,et al.Subgraphcentrality in complex networks[J].Physical Review E,2005,71(5):056103.
[25]Ghoshal G,et al.Random hypergraphs and their applications[J].Physical Review E,2009,79(6):066118.
[26]刘和东,钱丹.产学研合作绩效的提升路径研究——以高新技术企业为对象的实证分析[J].科学学研究,2016,34(5):704~712.
[27]潘旭伟,傅青苗.基于超网络的社会化标注行为[J].系统工程,2015,33(3):78~83.
[28]胡枫,赵海兴,马秀娟.一种超网络演化模型构建及特性分析[J].中国科学,2013,43(1):16~22.
[29]史定华.网络度分布理论[M].北京:高等教育出版社,2011:85~120.
[30]胡枫.一种超网络演化模型构建及特性分析[J].中国科学,2013,43(1):16~22.
[31]郭进利.非均齐超网络中标度律的涌现——富者愈富导致幂律分布吗[J].物理学报,2014,63(20):208901.
[32]王秋玉,曾刚,吕国庆.中国装备制造业产学研合作创新网络初探[J].地理学报,2016(2):251~264.
[33]OECD.Information technology outlook[Z].Paris:OECD,2010.
[34]高霞等.基于SIPO专利的产学研合作模式及其合作网络结构演化研究——以ICT产业为例[J].科学学与科学技术管理,2016,37(11):34~43.
[35]刘凤朝等.我国ICT产业专利申请趋势——关联分析[J].研究与发展管理,2010,22(2):40~47.
[36]马涛等.基于超网络的企业科技创新团队知识共享机制研究[J].情报科学,2017,35(12):120~128.
[37]Freeman L C.Centrality in social networks:Conceptual clarification[J].Social Network,1979,(1):215~239.
[38]Kapoor K,Sharma D,Srivastava J.Weighted node degree centrality for hypergraphs[C]//Network Science Workshop.IEEE,2013:152~155.
[39]索琪等.电视节目竞争关系的超网络分析[J].复杂系统与复杂性科学,2016,13(3):33~39.
[40]高霞.基于专利的我国ICT产业产学研合作创新实证研究[J].中国管理科学,2013,(11):715~719.
[41]郭进利.复杂网络和人类行为动力学[M].北京:科学出版社,2013:75~89.
[42]Barabási A L,Albert R,Jeong H.Mean-field theory for scale-free random networks[J].Physica A,2000,272(1~2):173~187.