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

涉及多个组织的高度复杂的决策，既有共同的利益，也有私人的利益，这给救灾的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机构的结构、决策权分配和治理如何影响决策过程和结果。此外，对供应链中货物供应等相关活动改进决策的效果进行系统评估也是一项重大挑战。这项研究将在人道主义救援中信息和通信技术(ICT)协调的决策背景下解决这些问题，这一领域需要给予极大的关注，卡特里娜飓风救援工作中的通信故障就是例证。这一多学科研究项目将基于软件的信息共享和决策智能代理研究与影响信息共享的组织设计研究相结合，并对改进决策所产生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应急能力建设国际工作组(IWG ECB)，它由最大的国际人道主义救济机构的代表组成，其中包括CARE、乐施会和救助儿童会等机构，以及HumaniNet，主要由较小的机构组成。然后，使用定性方法从这些组织收集的数据将用于修改基于代理的架构，以对这些设计对决策的影响进行敏感性分析，从而为改进的设计提出建议。随后，模拟的结果将被用于分析模型，以预测决策改进对救灾供应链绩效的影响。总之，我们对决策的研究将在救灾的关键领域贡献急需的知识，同时在组织科学、人工智能和物流理论方面取得根本性进展。

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.