个体在线知识分享行为的惯性效应分析
发布时间：2018-11-06 14:30
【摘要】：在线知识社群是大数据时代组织学习、协同创新、知识与信息交流与转移的重要方式。针对这种在线知识网络的分析、预测和管控,是大数据对经济社会实现数据服务和决策咨询功能的重要环节。以CMKT咨询俱乐部2群QQ群为例,搜集分析该群在2016年3月份所有的专业交流、讨论和分享记录,并基于这些实时数据建构CMKT动态知识网络,分析了在线动态知识网络中个体知识分享行为的策略性选择,最终验证了动态知识网络中个体分享行为的惯性效应。基于这一惯性效应,在大数据技术的支撑下,政府、高校或科研机构以及大型企业可以对其所构建的跨组织学习知识网络的动态演化趋势进行有效的分析和预测,并适时地选择干预或管控手段以引导知识网络更好地发挥在协同创新、知识转移、跨组织学习等方面的作用。
[Abstract]:Online knowledge community is an important way to organize learning, collaborative innovation, knowledge and information exchange and transfer in big data's time. The analysis, prediction and control of this online knowledge network is an important link for big data to realize the function of data service and decision-making consultation to the economy and society. Taking CMKT Consulting Club Group 2 as an example, this paper collects and analyzes all the professional exchanges, discussions and records of this group in March 2016, and constructs a CMKT dynamic knowledge network based on these real-time data. The strategic choice of individual knowledge sharing behavior in online dynamic knowledge network is analyzed and the inertia effect of individual sharing behavior in dynamic knowledge network is verified. Based on this inertia effect, under the support of big data technology, the government, universities or scientific research institutions and large enterprises can effectively analyze and predict the dynamic evolution trend of cross-organizational learning knowledge network. And timely choice of intervention or control means to guide the knowledge network to play a better role in collaborative innovation, knowledge transfer, cross-organizational learning and so on.
【作者单位】： 广州市社会科学院产业经济与企业管理研究所;北京市长城企业战略研究所;
【基金】：广州市社会科学院青年课题
【分类号】：C913.4
本文编号：2314555
[Abstract]:Online knowledge community is an important way to organize learning, collaborative innovation, knowledge and information exchange and transfer in big data's time. The analysis, prediction and control of this online knowledge network is an important link for big data to realize the function of data service and decision-making consultation to the economy and society. Taking CMKT Consulting Club Group 2 as an example, this paper collects and analyzes all the professional exchanges, discussions and records of this group in March 2016, and constructs a CMKT dynamic knowledge network based on these real-time data. The strategic choice of individual knowledge sharing behavior in online dynamic knowledge network is analyzed and the inertia effect of individual sharing behavior in dynamic knowledge network is verified. Based on this inertia effect, under the support of big data technology, the government, universities or scientific research institutions and large enterprises can effectively analyze and predict the dynamic evolution trend of cross-organizational learning knowledge network. And timely choice of intervention or control means to guide the knowledge network to play a better role in collaborative innovation, knowledge transfer, cross-organizational learning and so on.
【作者单位】： 广州市社会科学院产业经济与企业管理研究所;北京市长城企业战略研究所;
【基金】：广州市社会科学院青年课题
【分类号】：C913.4
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