DRU: Inter-organizational Decision Making and Organization Design for Improved ICT Coordination in Disaster Relief

高度复杂的决策涉及多个组织，这些组织既有共同的利益，也有私人的利益，这给救灾这一关键领域以及组织学者带来了许多挑战。特别是，很难理解多组织协调体的结构、决策权的分配和治理如何影响决策过程和结果。此外，系统地评估改进决策对相关活动的影响，例如在供应链中提供货物，提出了一个重大挑战。这项研究将在人道主义救济的信息和通信技术协调决策的背景下处理这些问题，卡特里娜飓风救济工作中的通信故障就是一个例子，需要对这一领域给予高度重视。这个多学科的研究项目将基于软件的智能代理对信息共享和决策的研究与影响信息共享的组织设计的研究相结合，并对改进决策所带来的行业级绩效改进进行分析评估。将参与这项研究的协调机构是紧急情况能力建设国际工作组（IWG ECB），由最大的国际人道主义救济机构的代表组成，包括援外社、乐施会和救助儿童会等，以及主要由较小机构组成的人道网（HumaniNet）。使用定性方法从这些组织收集的数据，然后将用于修改基于代理的架构，以执行这些设计对决策的影响的敏感性分析，生成改进设计的建议。随后，模拟的输出将用于分析模型，以预测决策改进对救灾供应链绩效的影响。总之，我们在决策方面的研究将为救灾这一关键领域提供急需的知识，同时为组织科学、人工智能和物流理论提供根本性的进步。

Highly complex decision making involving multiple organizations, which have both shared and private interests, pose many challenges in the critical area of disaster relief as well as for organizational scholars. In particular, it is difficult to understand how the structure, distribution of decision rights, and governance of a multi-organization coordination body influences decision making processes and outcomes. Also, systematic assessment of the effects of improved decision making for related activities, such as the provision of goods in a supply chain, presents a significant challenge. This research will address these problems in the context of decision making for information and communication technology (ICT) coordination in humanitarian relief, an area which, as exemplified by the communication failures in the relief effort for hurricane Katrina, requires significant attention.This multi-disciplinary research project integrates software-based intelligent agent research on information sharing and decision making with a study of organization designs that influence information sharing, and analytic assessments of the industry-level performance improvements resulting from improved decision making. The coordination bodies who will participate in this study are the International Working Group for Emergency Capacity Building (IWG ECB), consisting of representatives from the largest international humanitarian relief agencies, including CARE, Oxfam and Save the Children, among others, and HumaniNet, consisting of primarily smaller agencies. Data gathered from these organizations using qualitative methods, will then be used to modify an agent-based architecture to perform sensitivity analyses of the effects of these designs on decision making, generating recommendations for improved designs. Subsequently, the outputs of the simulation will be used in analytic models to predict the effects of decision making improvements on disaster relief supply chain performance. Together, our research on decision making will contribute badly needed knowledge in the critical area of disaster relief, while making fundamental advancements to theories of organization science, artificial intelligence and logistics.