基于ERGM的科技主体间专利技术交易机会实证研究
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摘要
本文构建科技主体间专利技术交易网络,从网络内生结构、科技主体间关系属性、科技主体个体属性等多维度提出影响专利交易的假设变量,建立复杂网络指数随机图模型(ERGM),预测科技主体间专利技术交易机会。通过2012-2016年新能源领域专利技术的实证研究,并将ERGM预测精度与传统链接预测方法对比,验证了ERGM在预测方面的优势和可行性。该研究一方面为技术交易网络中主体间交易机会预测提供有效方法,另一方面为专利技术交易推荐与主体对接提供决策。
To improve the efficiency of patent technology transfer and solve the problem of insufficient application of the effective supply of scientific and technological innovation,we construct the patent transaction network among the body of technology,propose the hypothesis variables of effecting patent transaction considering the multi-dimensional properties e. g. the endogenous structure of network,the relationship properties between body of technology and the individual attributes,then a complex network model is established based on exponential random graph model(ERGM) to predict opportunities of patent technology transactions and recommend the patent technology for supply and demand body. The advantages and feasibility of ERGM are verified in prediction by empirical study of patent technology in the new energy field in 2012-2016 and comparison the prediction accuracy of ERGM with the traditional method of link prediction.This study provides an effective method for the opportunities prediction of technology transaction between the body in technology transaction network and decision support for the patent recommendation of supply and demand and partners matching.
To improve the efficiency of patent technology transfer and solve the problem of insufficient application of the effective supply of scientific and technological innovation,we construct the patent transaction network among the body of technology,propose the hypothesis variables of effecting patent transaction considering the multi-dimensional properties e. g. the endogenous structure of network,the relationship properties between body of technology and the individual attributes,then a complex network model is established based on exponential random graph model(ERGM) to predict opportunities of patent technology transactions and recommend the patent technology for supply and demand body. The advantages and feasibility of ERGM are verified in prediction by empirical study of patent technology in the new energy field in 2012-2016 and comparison the prediction accuracy of ERGM with the traditional method of link prediction.This study provides an effective method for the opportunities prediction of technology transaction between the body in technology transaction network and decision support for the patent recommendation of supply and demand and partners matching.
引文
[1]赵志耘.以科技创新引领供给侧结构性改革[J].中国软科学,2016(9):1-6.
[2]吴卫红,董诚,彭洁,等.美国促进科技成果转化的制度体系解析[J].科技管理研究,2015(14):16-20.
[3]余绍山,贺正楚,张蜜,等.再生有色金属产业技术专利状况及发展对策研究[J].中国软科学,2015(3):41-55.
[4]孙玉涛,栾倩.专利质量测度“三阶段-两维度”模型及实证研究—以C9联盟高校为例[J].科学学与科学技术管理,2016,37(6):23-32.
[5]张宇青.我国“专利沉睡”之困与治理研究[J].科学管理研究,2013,31(4):50-53.
[6]薛伟贤,田鹏,孙姝羽.战略性新兴产业技术供需协同研究:以陕西为例[J].科研管理,2016,37(4):507-516.
[7]王瑞敏,腾青,卢斐斐.影响高校专利转化的因素分析和对策研究[J].科研管理,2013,34(3):137-144.
[8]唐要家,孙路.专利转化中“专利沉睡”及其治理分析[J].中国软科学,2006(8):73-78.
[9]樊霞,赵丹萍,何悦.企业产学研合作的创新效率及其影响因素研究[J].科研管理,2012,33(2):33-39.
[10]熊捷,孙道银.企业社会资本、技术知识获取与产品创新绩效关系研究[J].管理评论,2017,29(5):23-39.
[11]杨颖,李宇啸.研发协同的影响因素和绩效评价:文献综述[J].科研管理,2017,38(S1):543-549.
[12]陈晓峰.关系资源对集群企业间合作绩效的影响研究[J].科研管理,2017,38(6):59-66.
[13]叶春霞.企业专利合作网络演化的形成影响因素研究[D].武汉:华中科技大学,2014.
[14]吴梦蝶,唐雁.基于主题模型的有向社交网络链接预测方法[J].西南大学学报,2014,36(1):152-158.
[15]HE Yu Lin,LIU J N K,HU Yan Xing,et al.OWA operator based link prediction ensemble for social network[J].Expert Systems with Applications,2015,42(1):21-50.
[16]BLISS C A,FRANK M R,DANFORTH C M,et al.An evolutionary algorithm approach to link prediction in dynamic social networks[J].Journal of Computational Science,2014,5(5):750-764.
[17]PATTISON D P,WASSERMAN S.Logit models and logistic regressions for social networks:II.Multivariate relations[J].British Journal of Mathematical and Statistical Psychology,1999,61(2):401-425.
[18]LUSHER D,KOSKINEN J,ROBINS G.Exponential random graph models for social networks:Theory,methods and applications[M].Cambridge:Cambridge University Press,2012.
[19]李玉华,肖海岭,李栋才,等.基于链接重要性的动态链接预测方法研究[J].计算机研究与发展,2011,48(S3):40-46.
[20]SHIBATA N,KAJIKAWA Y,SAKATA I.Link prediction in citation networks[J].Journal of the American Society for Information Science and Technology,2012,63(1):78-85.
[21]ZHANG Chuang,ZHAI Bing Yu,WU Ming.Link prediction of community in Microblog based on exponential random graph model[C].//16th International Symposium on Wireless Personal Multimedia Communications(WPMC).Atlantic:IEEE PRESS,2013,6983(6):1-6.
[22]杨东辉.基于情感相似度的社会化推荐系统研究[D].哈尔滨:哈尔滨工业大学,2014.
[23]ROBBINS B,WELSER H T,GRIGORYEVA M,et al.Power-use in cooperative competition:A power-dependence model and an empirical test of network structure and geographic mobility[J].Social Science Research,2014,45:131-151.
[24]RELUN A,GROSBOIS V,ALEXANDROV T,et al.Prediction of pig trade movements in different European production systems using exponential random graph models[J].Frontiers in Veterinary Science,2017,4:1-12.
[25]CHROBOT-MASON D,GERBASI A,CULLEN-LESTER K L.Predicting leadership relationships:The importance of collective identity[J].Leadership Quarterly,2016,27(2):298-311.
[26]SCOTT T A.Analyzing policy networks using valued exponential random graph models:Do government-sponsored collaborative groups enhance organizational networks?[J].Policy Studies Journal,2015,44(2):215-244.
[27]HUNTER D R,GOODREAU S M,HANDCOCK M S.ERGM.userterms:A template package for extending statnet[J].Journal of Statistical Software,2013,52(2):1-25.
[28]刘宏鲲,吕琳媛,周涛.利用链路预测推断网络演化机制[J].中国科学:物理学力学天文学,2011,41(7):816-823.
[29]刘颖琦,王静宇,ARI K.产业联盟中知识转移、技术创新对中国新能源汽车产业发展的影响[J].中国软科学,2016(5):1-11.
[30]顾志恒.清华大学美国专利分析与高校海外专利推进策略[J].科研管理,2017,38(1):137-143.
[31]杨尚洪,李斌,王然,等.美国国防领域知识产权管理与技术转移的做法与启示[J].中国科技论坛,2017(4):186-192.
[2]吴卫红,董诚,彭洁,等.美国促进科技成果转化的制度体系解析[J].科技管理研究,2015(14):16-20.
[3]余绍山,贺正楚,张蜜,等.再生有色金属产业技术专利状况及发展对策研究[J].中国软科学,2015(3):41-55.
[4]孙玉涛,栾倩.专利质量测度“三阶段-两维度”模型及实证研究—以C9联盟高校为例[J].科学学与科学技术管理,2016,37(6):23-32.
[5]张宇青.我国“专利沉睡”之困与治理研究[J].科学管理研究,2013,31(4):50-53.
[6]薛伟贤,田鹏,孙姝羽.战略性新兴产业技术供需协同研究:以陕西为例[J].科研管理,2016,37(4):507-516.
[7]王瑞敏,腾青,卢斐斐.影响高校专利转化的因素分析和对策研究[J].科研管理,2013,34(3):137-144.
[8]唐要家,孙路.专利转化中“专利沉睡”及其治理分析[J].中国软科学,2006(8):73-78.
[9]樊霞,赵丹萍,何悦.企业产学研合作的创新效率及其影响因素研究[J].科研管理,2012,33(2):33-39.
[10]熊捷,孙道银.企业社会资本、技术知识获取与产品创新绩效关系研究[J].管理评论,2017,29(5):23-39.
[11]杨颖,李宇啸.研发协同的影响因素和绩效评价:文献综述[J].科研管理,2017,38(S1):543-549.
[12]陈晓峰.关系资源对集群企业间合作绩效的影响研究[J].科研管理,2017,38(6):59-66.
[13]叶春霞.企业专利合作网络演化的形成影响因素研究[D].武汉:华中科技大学,2014.
[14]吴梦蝶,唐雁.基于主题模型的有向社交网络链接预测方法[J].西南大学学报,2014,36(1):152-158.
[15]HE Yu Lin,LIU J N K,HU Yan Xing,et al.OWA operator based link prediction ensemble for social network[J].Expert Systems with Applications,2015,42(1):21-50.
[16]BLISS C A,FRANK M R,DANFORTH C M,et al.An evolutionary algorithm approach to link prediction in dynamic social networks[J].Journal of Computational Science,2014,5(5):750-764.
[17]PATTISON D P,WASSERMAN S.Logit models and logistic regressions for social networks:II.Multivariate relations[J].British Journal of Mathematical and Statistical Psychology,1999,61(2):401-425.
[18]LUSHER D,KOSKINEN J,ROBINS G.Exponential random graph models for social networks:Theory,methods and applications[M].Cambridge:Cambridge University Press,2012.
[19]李玉华,肖海岭,李栋才,等.基于链接重要性的动态链接预测方法研究[J].计算机研究与发展,2011,48(S3):40-46.
[20]SHIBATA N,KAJIKAWA Y,SAKATA I.Link prediction in citation networks[J].Journal of the American Society for Information Science and Technology,2012,63(1):78-85.
[21]ZHANG Chuang,ZHAI Bing Yu,WU Ming.Link prediction of community in Microblog based on exponential random graph model[C].//16th International Symposium on Wireless Personal Multimedia Communications(WPMC).Atlantic:IEEE PRESS,2013,6983(6):1-6.
[22]杨东辉.基于情感相似度的社会化推荐系统研究[D].哈尔滨:哈尔滨工业大学,2014.
[23]ROBBINS B,WELSER H T,GRIGORYEVA M,et al.Power-use in cooperative competition:A power-dependence model and an empirical test of network structure and geographic mobility[J].Social Science Research,2014,45:131-151.
[24]RELUN A,GROSBOIS V,ALEXANDROV T,et al.Prediction of pig trade movements in different European production systems using exponential random graph models[J].Frontiers in Veterinary Science,2017,4:1-12.
[25]CHROBOT-MASON D,GERBASI A,CULLEN-LESTER K L.Predicting leadership relationships:The importance of collective identity[J].Leadership Quarterly,2016,27(2):298-311.
[26]SCOTT T A.Analyzing policy networks using valued exponential random graph models:Do government-sponsored collaborative groups enhance organizational networks?[J].Policy Studies Journal,2015,44(2):215-244.
[27]HUNTER D R,GOODREAU S M,HANDCOCK M S.ERGM.userterms:A template package for extending statnet[J].Journal of Statistical Software,2013,52(2):1-25.
[28]刘宏鲲,吕琳媛,周涛.利用链路预测推断网络演化机制[J].中国科学:物理学力学天文学,2011,41(7):816-823.
[29]刘颖琦,王静宇,ARI K.产业联盟中知识转移、技术创新对中国新能源汽车产业发展的影响[J].中国软科学,2016(5):1-11.
[30]顾志恒.清华大学美国专利分析与高校海外专利推进策略[J].科研管理,2017,38(1):137-143.
[31]杨尚洪,李斌,王然,等.美国国防领域知识产权管理与技术转移的做法与启示[J].中国科技论坛,2017(4):186-192.