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Dynamic network analysis-based communication network evolution and shared situation awareness estimation in the network organization.

机译:网络组织中基于动态网络分析的通信网络演进和共享态势感知估计。

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摘要

As the network organization proliferates over traditional hierarchical forms, the requirement to describe, estimate and predict the dynamic structure as well as the need to measure performance in network-organizations has become critical (Carley, 2002b; 2003). Traditional, static organizational line charts no longer produce viable explanations of organizational behavior. As a network, the members are constantly reorganizing to the environment and therefore are rapidly changing the organizational structure (Graham, Schneider, Gonzalez, 2004). These rapid shifts in organizational structure have implications for organizational performance and measurement. Measures of organizational performance include situation model (Entin & Entin, 1999), mental model congruence (Entin & Serfaty, 2000; Graham, Schneider, Bauer, Bessiere, & Gonzalez, 2004), transactive memory (Carley & Ren, 2001), shared mental model (Salas et al., 1995) and shared situation awareness (Endsley & Jones, 2001; 2002). Each of these measures have, as a common characteristic, the ability to describes how 'in-sync' the organizational membership is at a given point of time. Organizations operating in a fast-paced environment which are 'in-sync', tend to have higher levels of performance than those that are not (Salas et al., 1999; Arquilla & Ronfeldt, 2002). To understand and describe rapid network change in terms of Shared Situation Awareness, I use a combined approach consisting of experimentation and simulation. I conduct multiple, large-scale experiments on military command and control network-organization structure in a pseudo-laboratory environment. Using dynamic network analysis techniques, I identify and characterize the factors that contribute to the change in structure of the organization. Network change factors found significant are homophilly, physical distance, communication network distance, and organizational structure. These empirically based factors are instantiated in new implementation of the proximity matrix in the ORA & DyNet models (Carley et al., 2003).
机译:随着网络组织以传统的分层形式激增,描述,估计和预测动态结构的要求以及衡量网络组织绩效的需求已变得至关重要(Carley,2002b; 2003)。传统的静态组织折线图不再产生对组织行为的可行解释。作为一个网络,成员正在不断地向环境进行重组,因此正在迅速改变组织结构(Graham,Schneider,Gonzalez,2004)。组织结构的这些快速变化对组织绩效和衡量具有影响。组织绩效的度量包括情境模型(Entin和Entin,1999年),心理模型的一致性(Entin和Serfaty,2000年; Graham,Schneider,Bauer,Bessiere和Gonzalez,2004年),互动式记忆(Carley和Ren,2001年)心理模型(Salas等,1995)和共享态势感知(Endsley&Jones,2001; 2002)。作为一项共同的特征,所有这些措施都具有描述组织成员在给定时间点的“同步”能力。在“同步”的快节奏环境中运行的组织往往具有比非同步组织更高的绩效水平(Salas等,1999; Arquilla&Ronfeldt,2002)。为了理解和描述基于共享态势感知的快速网络变化,我使用了一种由实验和模拟组成的组合方法。我在伪实验室环境中对军事指挥与控制网络的组织结构进行了多个大规模实验。通过使用动态网络分析技术,我可以识别和表征促成组织结构变化的因素。发现重要的网络变化因素是同质性,物理距离,通信网络距离和组织结构。这些基于经验的因素在ORA和DyNet模型中新实现的邻近矩阵中得以实例化(Carley等,2003)。

著录项

  • 作者

    Graham, John M.;

  • 作者单位

    Carnegie Mellon University.;

  • 授予单位 Carnegie Mellon University.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2005
  • 页码 127 p.
  • 总页数 127
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 TP;
  • 关键词

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