多维邻近性对跨界联盟协同创新的影响研究——基于人工智能合作专利的数据分析

Research on the Impact of Multi-dimensional Proximities on Collaborative Innovation Ability of Cross-border Alliances:Empirical Analysis Based on Cooperative Patent Data of Artificial Intelligence

当前环境下,跨界创新已成为一种重要的创新形式。跨界联盟能够突破原有边界束缚,协同不同领域资源,产生具有重大价值的创新成果。联盟主体间组织关系、地理距离和技术禀赋等多种邻近因素对跨界联盟协同创新活动具有重要影响。通过分析人工智能领域2000—2018年间的专利申请数据,划分出技术创新生命周期的3个阶段,分别运用有序多分类Logisitic回归和负二项回归方法对不同阶段的合作专利数据进行分析,挖掘跨界联盟多维邻近性与联盟创新能力的关联关系,并进一步研究网络特征对多维邻近性的调节作用。结果表明:在产业技术发展的过程中,组织关系邻近对联盟的协同创新始终具有正向的驱动作用;地理邻近在技术导入期对联盟的跨界创新有促进作用,但在技术成长期和成熟期对联盟创新的影响不大;技术邻近性对联盟创新的影响主要在技术成长期和成熟期得以显现,在技术成长期,技术邻近性的影响程度先增强后减弱,而在技术成熟期,技术邻近性对联盟的协同创新具有正向促进作用。此外,跨界联盟的网络特征对组织关系及地理邻近与联盟创新的关系具有一定的调节作用,联盟节点间较为密切的合作关系一方面能够增强组织关系邻近对联盟创新的促进作用,另一方面还能够替代地理邻近推动联盟的协同创新。

In the era of digital economy,more and more traditional enterprises use the power of new generation information technology such as big data and artificial intelligence to integrate heterogeneous resources and carry out collaborative innovation through cross-border alliances.Cross-border innovation is not only an important factor for enterprises to maintain sustainable competitive advantages,but also accelerates industrial integration.It has become an important way of innovation driven development strategy in China.The heterogeneity of members is the most significant and key feature of cross-border alliance.And it is also an important factor that can affect the collaborative innovation among alliance members.Therefore,from a multi-dimensional perspective,the quantitative analysis of the degree of difference between alliance members is an important basis for the selection of alliance partners,and it is also an effective method and way to measure the effect of collaborative innovation.Drawing on the resource-based view,technology life cycle theory and social identity theory,this study constructs a conceptual model of the impact of multi-dimensional proximity on the collaborative innovation of cross-border alliances based on the existing viewpoints of multi-dimensional proximity,social networks and cross-industry innovation.This study takes the patent data in the field of artificial intelligence from 2000 to 2018 in the national intellectual property database as the research sample and looks up the relevant information in the national enterprise credit information publicity system.According to the change law of the number of patent applications and patent applicants,this study divides the technological innovation life cycle into three stages.Furthermore,according to the characteristics of the cooperative patent data at different stages,an ordered multi-class logistic regression model and a negative binomial regression model were used to analyze the degree of proximity in cross-border alliances in terms of geography,technology,and organizational relationships.The models also analyze the influence of the network attributes of the alliance on the innovation ability,and further studies the moderating effect of the network characteristics on this relationship.The study results show that:In the process of industrial technology development,the proximity of organizational relationships always has a positive driving force for the collaborative innovation of alliances;Geographical proximity promotes the cross-border innovation during the technology introduction period,but has little effect on the alliance innovation during the technology growth and maturity period;The impact of technology proximity on alliance innovation is mainly manifested in the period of technology growth and maturity.In the period of technology growth,the influence of technology proximity first increases and then decreases,while in the period of technology maturity,technology proximity has a positive role in promoting collaborative innovation;In addition,the network characteristics of cross-border alliances have a certain moderating effect between organizational relationship proximity,geographic proximity and alliance innovation.On the one hand,the closer cooperation among alliance members can enhance the promotion of organizational proximity to alliance innovation,on the other hand,it can replace geographical proximity to promote collaborative innovation.From the perspective of multi-dimensional proximity,this study focuses on cross-border degree of cooperative innovation among alliance members,provides a decision-making reference for the cooperation strategies of alliance innovative members at different stages of technological development in the field of artificial intelligence.According to the research results,when establishing cross-border alliances and selecting partners,it is necessary not only to expand the scope of technology cross-border search,but also to evaluate the current technological development stage,especially after entering the technological growth and maturity stage,it should pay attention to the technological characteristics among alliance innovative members.At the same time,the alliance should give full play to the driving effect of relationship capital on collaborative innovation.Alliance managers can formulate corresponding policies to strengthen the cooperation among alliance members,help eliminate cognitive barriers,overcome geographical distance,make full use of the aggregation effect and scale effect of network,innovate service mode,and improve the collaborative innovation efficiency of alliance.Future research will continue to closely track the development of the field of artificial intelligence,and further reveal the influence of multi-dimensional proximity on collaborative innovation capabilities.