【摘要】：在線知識社群是大數(shù)據(jù)時代組織學習、協(xié)同創(chuàng)新、知識與信息交流與轉移的重要方式。針對這種在線知識網絡的分析、預測和管控,是大數(shù)據(jù)對經濟社會實現(xiàn)數(shù)據(jù)服務和決策咨詢功能的重要環(huán)節(jié)。以CMKT咨詢俱樂部2群QQ群為例,搜集分析該群在2016年3月份所有的專業(yè)交流、討論和分享記錄,并基于這些實時數(shù)據(jù)建構CMKT動態(tài)知識網絡,分析了在線動態(tài)知識網絡中個體知識分享行為的策略性選擇,最終驗證了動態(tài)知識網絡中個體分享行為的慣性效應。基于這一慣性效應,在大數(shù)據(jù)技術的支撐下,政府、高校或科研機構以及大型企業(yè)可以對其所構建的跨組織學習知識網絡的動態(tài)演化趨勢進行有效的分析和預測,并適時地選擇干預或管控手段以引導知識網絡更好地發(fā)揮在協(xié)同創(chuàng)新、知識轉移、跨組織學習等方面的作用。
[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.
【作者單位】： 廣州市社會科學院產業(yè)經濟與企業(yè)管理研究所;北京市長城企業(yè)戰(zhàn)略研究所;
【基金】：廣州市社會科學院青年課題
【分類號】：C913.4

【相似文獻】

相關期刊論文 前1條

1 陳婷;王麗;;不作為慣性效應[J];經濟研究導刊;2010年36期

，

本文編號：2314555