Wiltshire Travis J, Butner Jonathan E, Pirtle Zachary
University of Southern Denmark.
University of Utah.
Nonlinear Dynamics Psychol Life Sci. 2017 Jul;21(3):335-358.
In complex work domains and organizations, understanding schedule-ing dynamics can ensure objectives are reached and delays are mitigated. In the current paper, we examine the scheduling dynamics for NASA's Exploration Flight Test 1 (EFT-1) activities. For this examination, we specifically modeled simultaneous change in percent complete and estimated duration for a given project as they were included in monthly reports over time. In short, we utilized latent change score mixture modeling to extract the attractor dynamics within the scheduling data. We found three primarily patterns: an attractor at low duration, low percent complete; a saddle that was attractive toward full completion and repelled duration away from five months, and an attractor at full completion and high duration. We replicated these three patterns using multilevel modeling. Then, we examined how task dependencies, in terms of the number of predecessors and successors, affected the probability of exhibiting a given pattern over time. Thus, we offer a flexible method for understanding the patterns that can characterize scheduling dynamics as well as other dynamical systems. Several recommendations for future directions are discussed.
在复杂的工作领域和组织中,理解调度动态可以确保目标得以实现,并减少延误。在本文中,我们研究了美国国家航空航天局(NASA)探索飞行测试1(EFT - 1)活动的调度动态。对于此次研究,我们专门对给定项目随时间包含在月度报告中的完成百分比和估计持续时间的同步变化进行了建模。简而言之,我们利用潜在变化分数混合建模来提取调度数据中的吸引子动态。我们发现了三种主要模式:一种是低持续时间且低完成百分比的吸引子;一种是对完全完成具有吸引力且将持续时间从五个月排斥开的鞍点;以及一种是完全完成且高持续时间的吸引子。我们使用多层建模复制了这三种模式。然后,我们研究了任务依赖关系,就前驱任务和后继任务的数量而言,如何随时间影响呈现给定模式的概率。因此,我们提供了一种灵活的方法来理解能够表征调度动态以及其他动态系统的模式。文中还讨论了对未来方向的一些建议。