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Social network analysis: A tool for evaluating and predicting future knowledge flows from an insurance organization

机译:社交网络分析:一种评估和预测保险机构未来知识流的工具

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The paper aims to identify the individuals who influence the knowledge sharing processes from an internal social network and to forecast the future knowledge flows that may cross it. Exploratory research is employed, and a four-phase methodology is developed which combines a social network analysis with structural modeling. This is applied to the internal enterprise social network used by a British insurance company. The main results emphasize the most influential groups, their relationships, future knowledge flows, and the connection between the network's heterogeneity and structure, and employees' future knowledge sharing intention. These findings have both theoretical and practical implications. The theory is extended by proving that a social network analysis can be used as a tool for evaluating and predicting future knowledge flows. At the same time, a solution is offered to decision-makers so they will be able to: (i) identify the potential knowledge loss; (ii) determine leaders; (iii) establish who is going to act as a knowledge diffuser, by sharing what they know with their coworkers, and who is going to act as a knowledge repository, by focusing on acquiring increasingly more knowledge; (iv) identify the elements that influence employees' future knowledge sharing intention. (C) 2016 Elsevier Inc. All rights reserved.
机译:本文旨在确定影响内部社交网络知识共享过程的个人,并预测可能跨越其的知识流。采用了探索性研究,并开发了一个将社会网络分析与结构建模相结合的四阶段方法。这适用于英国保险公司使用的内部企业社交网络。主要结果强调了最具影响力的群体,他们之间的关系,未来的知识流以及网络的异质性和结构之间的联系,以及员工未来的知识共享意图。这些发现具有理论和实践意义。通过证明社交网络分析可以用作评估和预测未来知识流的工具来扩展该理论。同时,为决策者提供了一种解决方案,使他们能够:(i)确定潜在的知识损失; (ii)确定领导人; (iii)通过与同事共享他们所知道的知识来确定谁将充当知识传播者,并通过专注于获取越来越多的知识来确定谁将充当知识仓库; (iv)确定影响员工未来知识共享意图的要素。 (C)2016 Elsevier Inc.保留所有权利。

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