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学术视界 | 发明者网络社群动态配置及对创新能力的影响

刘娜等 数字经济与商业模式 2023-03-28

发明者网络社群动态配置及对创新能力的影响

刘娜1,嵇金星1,毛荐其1,王霄飞1,官建成2

(1.山东工商学院工商管理学院,山东 烟台264005;

2.中国科学院大学经济与管理学院,北京100190)

摘要鉴于发明者在创新活动中的“抱团”研发现象,采用GN算法,识别可再生能源行业发明者合作创新网络的社群结构,根据社群内部成员和社群经纪人网络位点的不同,通过相邻期社群动态追踪,划分社群结构动态配置,实证社群配置与社群创新能力间的关系。结果表明:发明者合作创新网络存在明显的社群划分,不同类型的社群动态配置对社群发明者创新影响显著不同。总体为,动态与静态相协调的社群配置优于双动或双静的社群配置,具体为,“动荡”社群创新能力最弱,“纽带”社群创新能力最强,“独立”及“固化”社群介于两者间。以促进发明者创新,政策应该有利于创新网络动态及稳定的折中。

关键词:创新网络;网络社群;社群经纪人;网络动态;社群配置;稳定性;创新绩效

主要研究结论:本研究采用GN算法,识别了可再生能源领域发明者合作创新网络的社群结构,根据社群内成员和社群经纪人网络位点的差异,通过社群动态追踪,定义了四种社群动态配置,并探究了社群配置对社群创新能力的影响,得出以下结论:(1)可再生能源领域的发明者合作创新网络呈现显著的网络社群结构,揭示发明者“抱团”行为是技术研发过程中普遍存在的创新模式;(2)网络社群和社群经纪人随时间不断演变,并呈现不同的社群结构动态配置,即“纽带”社群、“独立”社群、“固化”社群和“动荡”社群;(3)不同的社群配置对社群发明者创新能力影响不同,动态和静态相协调的社群配置相对而言是有效的社群配置结构,优于双动或双静的社群配置,即“纽带”社群和“独立”社群创新能力强,“动荡”社群和“固化”社群创新能力弱。


The dynamic configuration of inventors′ network community and its influence on innovation capacity

Liu Na1, Ji Jinxing1, Mao Jianqi1, Wang Xiaofei1, Guan Jiancheng2

(1. School of Business Administration, Shandong Technology and Business University, Yantai 264005, Shandong, China; 

2. School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

Abstract:In innovation activities, inventors have shown a phenomenon of "hugging together", which leads to the clustering of collaborative innovation networks and forms network communities. The network community of inventors is an aggregated structural group in collaborative networks. Inventors within the same community are frequently and closely linked with each other. Community brokers locate on the periphery of a community and have a position advantage of crossing the boundaries of different communities, which are critical to transfer knowledge from outside the community into a form that can be absorbed by inventors within the community. 

There is a lack of research on how the dynamic and stable structure configuration of different network loci influences innovation. Solving this problem is helpful to provide theoretical guidance for improving innovation capacity and decision supports for innovation network management. Thus, this study aims to explore how network community structure and its dynamic configuration in inventors′ collaborative innovation network influence their innovation capacity in the field of renewable energy. We stress the roles of the overall dynamic of the community and the dynamic of community brokers. Firstly, inventors′ collaborative networks are constructed based on co-inventing relationship in renewable energy patents. Then, inventors′ network communities are identified by adopting GN algorithm. Community dynamic configuration is defined through tracking communities in adjacent phases based on the dynamic difference of network loci between members within communities and community brokers. Four types of community dynamic configuration are defined, and there are independent community, rigid community, volatile community and broking community, respectively. We hypothesize that among the four types of communities, broking communities have the strongest innovation capacity, while volatile communities have the weakest innovation capacity. OLS regression analyses are used to empirically test our hypotheses and the robustness tests are carried out by using nonparametric bootstrap method. 

Through this study, we aim to break through the limitations of studies on the functional mechanism of innovation networks from the static network perspective and integrate the advantages of static and dynamic networks. We contribute to the study of innovation network structure and network dynamics, enriches studies on the functional mechanism of innovation network, and expect to provide guidance and suggestions for improving inventors′ innovation capacities.

The results of GN algorithm show that there are obvious community structures in inventors′ collaborative innovation network in the renewable energy field, and network communities and communities′ brokers evolve over time and they present different dynamic configurations. Moreover, the results of OLS regressions and robustness tests show that different dynamic configuration of community has a significantly different impact on community innovation capacity. Overall, the dynamic and static harmonious community configuration is better than the dual dynamic or static community configuration. Specifically, the innovation capacity of the volatile community is weak and that of broking community is strong and that of independent community and rigid community are somewhere in between. This study emphasizes the effect of heterogeneity of community dynamic configuration on innovation of community inventors, and the policy should be conducive to the compromise of dynamic and stable structure of innovation networks, so as to promote innovation of inventors.

Key words:innovation network; network community; community broker; network dynamic; community configuration; stability; innovation performance

引用本文:刘娜,嵇金星,毛荐其,王霄飞,官建成.发明者网络社群动态配置及对创新能力的影响[J].科研管理,2021,42(9):44-51.

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