Dynamic analysis of the association between network structures and the performance of knowledge workers using information technologies

学者和实践者都相信，一个演员在一个组织内的社会网络中的嵌入性会影响他或她的表现。然而，研究这种关系的研究结果是相互矛盾的。因此，只有少数工具可以支持管理者根据组织中的社交网络进行决策。该项目的主要目标是为决策者提供一套有效管理组织内社交网络的工具，以提高生产力。为了实现这一目标，必须澄清相互矛盾的研究结果。特别是，一些相互矛盾的结果可能归因于数据收集的方法和时间效应的忽视。我们的目标是避免一些传统的数据收集方法的缺点（如社会期望偏差，记忆效应或山楂效应），通过采用现代信息技术。此外，我们考虑时间效应，采用最近开发的模型测试，允许因果关系的声明时，使用纵向网络数据的统计方法。使用这些方法，我们还考虑了社会网络和嵌入式演员的性能的相互依赖。所取得的成果将作为一个决策支持系统，以便将来能够有效地管理组织内的社交网络。

Scholars and practitioners alike are convinced that an actor's embeddedness in a social network within an organization influences his or her performance. However, the results of studies that examine this relationship are conflicting. Consequently, there are only a few tools available that can support managers' decision making according to social networks in organizations. The main goal of this project is to equip decision makers with a tool set for an effective management of social networks within organizations in order to enhance productivity. To achieve this goal, the conflicting study results have to be clarified. Particularly, some of the conflicting results might be attributed to the method of data collection and the neglect of temporal effects. We aim to avoid some of the shortcomings of conventional data collection methods (e.g. social desirability bias, memory effects or the Hawthorn effect) by employing modern information technologies. Furthermore, we consider temporal effects by employing recently developed statistical methods for model tests that allow for causality statements when using longitudinal network data. Using these methods we also consider the mutual dependence of social network and performance of the embedded actors. The results gained will be prepared as a Decision Support System, so that in the future it will be possible to effectively manage social networks within organizations.