RAPID: Network Improvisation in Emergency Response: An Application to Debris Removal Operations

这项快速反应研究补助金(RAPID)将调查在纽约州进行飓风桑迪飓风后碎片清除行动的紧急多组织网络内的决策过程。预计这项研究将有助于扩大关于组织如何即兴发挥作用的研究主体：即他们如何在时间限制下采取创造性和有用的行动，几乎不可能取消以前的行动。这项工作将发现和审查组织即兴发挥程度与组织整体业绩之间的关系，特别侧重于效率、效力和外地碎片清除小组努力分配之间的权衡。将从(使用现有计算机系统收集的)负载记录中提取详细的性能数据，并辅之以问卷调查数据和费用估计数。这项工作将采用和推广从排队网络研究中汲取的方法来分析碎片清除活动，并辅之以统计和模拟方法来描述这些网络中个人和群体的行为。这项工作将包括就这项研究的方法和结果向执业专业人员进行外联。它将产生经过验证的数据集，用于解决复杂排队网络中的即兴行为，以及将通过出版物和学术和实践者场所的演示广泛传播的结果。最后，这项工作预计将有助于提高社会规划和应对大规模灾害的能力，特别是通过增进对碎片清除绩效决定因素的了解。

This Rapid Response Research Grant (RAPID) will investigate decision making processes within the emergent multi-organizational network that is undertaking post-Hurricane Sandy debris removal operations in the State of New York. The research is expected to contribute to an expanding body of research on how organizations improvise: that is, how they take creative and useful action under time constraint, with little or no possibility of undoing previous actions. This work will discover and examine relationships between degree of organizational improvisation and overall organizational performance, focusing specifically on tradeoffs between efficiency, effectiveness and distribution of effort by debris removal teams in the field. Detailed performance data will be extracted from records of loads hauled (as collected using existing computer-based systems), supplemented with questionaire data and cost estimates. The work will employ and extend methods drawn from research on queueing networks to analyze debris removal activities, supplemented by statistical- and simulation-based methods for characterizing the behaviors of individuals and groups within these networks. This work will include outreach to practicing professionals concerning the methods and results of this research. It will produce validated data sets for addressing improvised behavior within complex queueing networks, along with results that will be broadly disseminated through publications and presentations in academic and practitioner venues. Finally, this work is expected to contribute to society's ability to plan for and respond to large-scale disasters, particularly by improving understanding of the determinants of debris removal performance.