Innopod Solutions Kft, Budapest, Hungary.
MTA-PE Budapest Ranking Research Group (BRRG), University of Pannonia, Veszprém, Hungary.
Sci Rep. 2019 Mar 1;9(1):3322. doi: 10.1038/s41598-019-39705-1.
Network analysis can be applied to understand organizations based on patterns of communication, knowledge flows, trust, and the proximity of employees. A multidimensional organizational network was designed, and association rule mining of the edge labels applied to reveal how relationships, motivations, and perceptions determine each other in different scopes of activities and types of organizations. Frequent itemset-based similarity analysis of the nodes provides the opportunity to characterize typical roles in organizations and clusters of co-workers. A survey was designed to define 15 layers of the organizational network and demonstrate the applicability of the method in three companies. The novelty of our approach resides in the evaluation of people in organizations as frequent multidimensional patterns of multilayer networks. The results illustrate that the overlapping edges of the proposed multilayer network can be used to highlight the motivation and managerial capabilities of the leaders and to find similarly perceived key persons.
网络分析可用于根据沟通模式、知识流、信任和员工的接近程度来理解组织。设计了一个多维组织网络，并对边标签进行关联规则挖掘，以揭示在不同活动范围和组织类型中，关系、动机和感知如何相互影响。节点的基于频繁项集的相似性分析提供了在组织中刻画典型角色和同事群体的机会。设计了一项调查来定义组织网络的 15 个层次，并在三家公司中展示该方法的适用性。我们方法的新颖之处在于将组织中的人员评估为频繁的多维多层网络模式。结果表明，可以利用所提出的多层网络的重叠边来突出领导者的动机和管理能力，并找到具有相似感知的关键人员。
