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Modeling And Analysis Of Project Team Formation Factors In A Project-oriented Virtual Organization (provo)

机译:面向项目的虚拟组织(项目)中项目团队形成因素的建模与分析

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In this era of rapid changes in the project-oriented R&D organization's environment, some are actively pursuing joint research to gain a leading edge over other R&D organizations. The condition for joint research is the knowledge that an organization needs from other organizations and the capability of collaboration. This study presents a ProVO model using the concept of virtual organization and project team formation based on knowledge and collaboration. In this model, VO is represented by the capability of carrying out a project and the cost of employment. Capability consists of knowledge competence (KC) and collaboration competence (CC). KC, in turn, consists of individual knowledge and collective knowledge from social network, while CC consists of density, degree centrality, and closeness centrality. To verify the presented model, we conducted a case study on a research institute. The analysis results show that all five project team formation factors of KC and CC are statistically significant. A prototype was also developed for selecting project team members using the binary logistics regression model. The proposed ProVO model can assist quantitative decision making on the selection of project team members by a project-oriented R&D organization from the aspects of knowledge and collaboration.
机译:在这个以项目为导向的研发组织的环境瞬息万变的时代,一些组织正在积极寻求联合研究以取得领先于其他研发组织的领先优势。联合研究的条件是一个组织需要其他组织的知识以及协作能力。本研究使用基于知识和协作的虚拟组织和项目团队组成的概念,提出了一个ProVO模型。在此模型中,VO由执行项目的能力和雇用成本表示。能力包括知识能力(KC)和协作能力(CC)。反过来,KC由来自社交网络的个人知识和集体知识组成,而CC由密度,学位中心和亲密关系组成。为了验证所提出的模型,我们在一家研究所进行了案例研究。分析结果表明,KC和CC的所有五个项目团队组成因素均具有统计学意义。还开发了一个原型,用于使用二元物流回归模型选择项目团队成员。所提出的ProVO模型可以帮助一个面向项目的研发组织从知识和协作方面对项目团队成员的选择进行定量决策。

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