The Effect of Network Relational Structure on Knowledge Diffusion Learning: An Empirical Study

Zhang Renping, Zheng ShiYong, Qiu Ming, Rizwan Ali, Ubaldo Comite

Abstract


As social media has been popularized, users have shifted from the receiver of knowledge to the creator and communicator of knowledge. Besides, the relationship between users has become more sophisticated. In two-way and one-way networks, different network relationship structures formed be-tween users have different impacts on the knowledge learning of infor-mation recipients. Some studies highlighted that knowledge, according to the different forms of knowledge generation and expression, can be split in-to explicit and tacit knowledge. Thus, in the network structure with differ-ent levels of relationship intensity, which type of knowledge can be spread and learned better? To answer this question, this study first uses second-hand data analysis. As revealed from the results of empirical research, under Weibo and WeChat, i.e., two different network structures, a variety of knowledge dissemination learning will have different effects. Then, by ana-lyzing questionnaire data, the phenomenon and its internal mechanism are explained in accordance with the theory of regulatory focus.

Keywords


network relational structure;explicit knowledge;tacit knowledge;regulato-ry focus theory

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Copyright (c) 2021 Zhang Renping, Zheng ShiYong, Qiu Ming, Rizwan Ali, Ubaldo Comite


International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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