基于信任和核心团队的产品开发项目组织集群

Na Yang, Qing Yang, Tao Yao
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引用次数: 2

摘要

新产品开发(PD)项目是一个复杂的通信网络,涉及团队之间的信任关系。信任突出,间接影响团队位置和组织绩效。为了管理项目协同的复杂性,本文建立了团队之间的相互信任模型,并进一步确定核心团队,优化项目开发组织网络结构。首先,我们确定了影响PD组织网络中纽带强度传递行为的技术相互依赖和情感亲密。然后,我们研究了组织网络中共同第三方的存在如何影响相互依赖团队之间的信任可转移性。基于信任可转移性对结构相似性进行建模。为了识别在组织网络中通常具有高重要性和多样化知识的核心团队,我们改进了与共同接受者/来源相关的信任可转移性的LeaderRank中心性,以评估团队的重要性并呈现团队属性(即专业知识)多样性。为了围绕核心团队构建群组,我们使用核心团队作为K-means聚类算法的输入参数(即初始聚类种子)。聚类结果强化了工业实例中的若干管理实践,包括信任可转移性如何影响最优组织网络结构以及如何构建基于核心团队的组织网络结构。
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Clustering product development project organization based on trust and core teams
The new product development (PD) project is a complex network of communications involving trust relationships among teams. Trust is prominent, influencing the team positions and organizational performance indirectly. To manage the coordination complexity in PD projects, in this paper, we build a model of mutual trust among teams and further identify core teams to optimize the PD organizational network structure. First, we identified the technical interdependency and emotional closeness that influence the transmission behavior of the tie strength in the PD organizational network. Then, we examined how the presence of a common third party in the organizational network affects the trust transferability between interdependent teams. We modelled the structural similarity based on the trust transferability. To identify the core teams, which typically have high importance as well as diverse knowledge in the organizational network, we improved the LeaderRank centrality with trust transferability related to common recipients/sources to evaluate the importance of teams and present the team attributes (i.e. expertise) diversity. To build the group around core teams, we used the core teams as the input parameter (i.e. the initial clustering seeds) of the K-means clustering algorithms. The clustering results reinforce several managerial practices in an industrial example, including how trust transferability impacts the optimal organizational network structure and how to build an organizational network structure based on core teams.
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