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Transactive Memory System and Knowledge Transfer Within Teams: a Virtual Experiment Approach

Author: ZhongZuo
Tutor: LiuYong
School: South China University of Technology
Course: Management decision-making and system theory
Keywords: Transactive Memory System Knowledge Transfer Virtual Experiment TeamKnowledge Management
CLC: TP391.9
Type: Master's thesis
Year: 2013
Downloads: 20
Quote: 0
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Abstract


Knowledge transfer is an important content of the knowledge management research, aswell as an important means of work teams to make full use of existing knowledge to achieveobjects. Previous researches indicates that transactive memory system(TMS) has significantimpact on team performance, however, how TMS influence team knowledge transferactivities, and how this influence differs under different external conditions is stay unclear. Toremedy this gap, we launched a virtual experiment research based on multi-agent simulationmethod. The virtual experiment research can on one hand reflect dynamic interact processwithin teams, and on the other hand simulate various experimental environment base onflexible settings. We designed the computer simulation scheme base on classic transactivememory system theory, and developed the simulation platform using the Repast-javaframework. Besides, we designed specific experiments for each of the external factors in thisresearch. Before the actual experiments, we launched a verification experiment to test thereliability of the model in this research. The virtual experimental results indicate that thedevelopment of transactive memory system presents a nonlinear first quick back slow trend.At the same time, as the transactive memory system grow, teams can achieve higher andhigher knowledge transfer efficiency, however, this trend was significantly influenced byexternal factors, such as team size, knowledge heterogeneity and task complexity.Firstly, team size will affect the generate speed of TMS in teams and also affect theimpact of TMS to knowledge transfer. Small-scale teams can build TMS faster thanlarge-scale teams; however large-scale teams can achieve higher knowledge transferefficiency. Secondly, the knowledge background differences between team members canspeed up the construction of TMS, and at the same time help teams achieve higher knowledgetransfer efficiency. Finally, task complexity slows down the construction speed of TMS withinteams, and seriously affects knowledge transfer efficiency.Base on the experiments results, we concluded several management implications andadvices on team knowledge management. These implications and advices are mainly aboutteam building, specialization and cooperation mechanisms, team atmosphere and knowledgesharing mechanisms. At the end of this paper, we summed up the full text, as well as theexperiment conclusions, besides, we pointed out shortcomings of the study andrecommendations for future research.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Computer simulation
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