An Episode as a Trace of Resilient Performance in Large-Scale Incident Management Systems
An Episode as a Trace of Resilient Performance in Large-Scale Incident Management Systems
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DOI：
10.1177/1541931218621178
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发表时间：
2018-09
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影响因子：
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通讯作者：
Changwon Son;F. Sasangohar;S. Peres;S. Mannan;Mary Kay O’Connor
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作者：
Changwon Son;F. Sasangohar;S. Peres;S. Mannan;Mary Kay O’Connor
灾难揭示了事件管理系统在准备、响应和从破坏性事件中恢复方面面临的持续挑战。这些挑战反映在最近的自然灾害、工业事故和恐怖袭击等灾难性事件中。为了应对这些挑战，人们越来越认识到需要事件管理系统的弹性（Comfort, Boin, & Demchak, 2010）。弹性被定义为系统在扰动之前、期间和之后调整其性能的能力（Hollnagel, Woods, & Leveson, 2007）。从联合认知系统（JCS）的理论来看，弹性绩效是通过JCS三要素之间的相互作用来实现的：人类操作员、技术工件和来自世界的需求（Hollnagel & Woods, 2005; Woods & Hollnagel, 2006）。因此，本研究旨在通过调查JCS三元组之间的相互作用，确定事件管理系统（例如事件管理团队（IMT））的弹性性能。研究小组在高保真紧急演习设施进行了两次自然观察，并收集了参与者的音频和视频记录。然后将这些录音编织在一起，以方便对相互作用进行分析。为了表现人类与应对事件需求的技术工具之间的相互作用，开发了交互式事件分析（IEA）并将其应用于收集的数据。IEA旨在捕捉互动的三个C：语境（Context）、内容（Content）和特征（Characteristics）。上下文指的是交互的发起者、接收者和所使用的技术。内容表示操作人员和技术工具之间发生的操作和通信。特征是指交互的频率和持续时间。为了确定IMT应对事件需求的表现，在给IMT注入（一段模拟信息输入）后构建了一个情节。利用国际能源署，提取了两个事件作为初步结果。我们观察到信息管理模式的相似和不同。首先，这两个事件表明IMT遵循一个共同的信息流：收集事件数据（例如，实地报告），记录数据，并将数据传播给IMT的其他成员。在这两种情况下，参与者倾向于使用类似的技术来完成特定的信息管理任务。例如，电话用于收集事件数据，影印机（即打印机和复印机）用于记录文件，纸质表格用于传播。另一方面，捕捉到了不同的模式。在第二集中，I/I Unit的成员努力寻找一种更喜欢的交流方式（例如，纸和电子邮件），成员们与第一集中没有出现的老师进行了互动。因此，第二集的时间几乎是第一集的两倍。目前的研究结果虽然是初步的，但表明应急操作员、技术工具和事件需求之间存在非线性和动态的相互作用。正如Woods（2006）所指出的那样，系统的弹性可能在系统面临破坏性事件之前是不可见的。在这方面，IEA将作为一个工具，代表系统在工作需求后的弹性性能。此外，IEA还有望成为一种诊断工具，用于检查JCT三要素之间的相互作用。为了收集更多的证据来支持初步分析的结果，未来的研究将侧重于从收集到的数据中提取更多的事件，并确定IMT弹性表现的新模式。
Disasters have revealed persistent challenges for incident management systems in preparing for, responding to, and recovering from disruptive events. Such challenges have been reflected in recent catastrophic events such as natural disasters, industrial accidents, and terrorist attacks. To address the challenges, a need for resilience of incident management systems has been increasingly recognized (Comfort, Boin, & Demchak, 2010). Resilience is defined as a system’s capacity to adjust its performance before, during and after a disturbance (Hollnagel, Woods, & Leveson, 2007). From the theory of Joint Cognitive System (JCS), resilient performance is rendered through an interplay among the JCS triad: human operators, technological artifacts, and demands from the world (Hollnagel & Woods, 2005; Woods & Hollnagel, 2006). Hence, this study aims to identify resilient performance of an incident management system (e.g., Incident Management Team (IMT)) by investigating interac-tions among the JCS triad. The research team conducted two naturalistic observations at a high-fidelity emergency exercise facility and collected audio and video recordings from participants. These recordings were then weaved together to facilitate the analysis of interactions. To represent the interactions among humans and technological tools that cope with demands from an incident, an Interactive Episode Analysis (IEA) was developed and applied to the collected data. The IEA was designed to capture three C’s of an interaction: Context, Content and Characteristics. Context refers to an initiator, a receiver of the interaction, and a technology used. Content indicates actions and communications that occur between human operators and technical tools. Characteristics refer to frequency and time duration of the interaction. To identify the IMT’s performance to cope with incident demands, an episode was constructed after an inject (a piece of simulated information input) was given to the IMT. Using the IEA, two episodes were extracted as preliminary results. Both similar and different patterns of information management were observed. First, both episodes suggest that the IMT follows a common information flow: collecting incident data (e.g., field report), documenting the data, and disseminating the data to other members of the IMT. In both episodes, participants tended to use similar technologies for a certain information management task. For example, a telephone was used for collection of incident data, a photocopying machine (i.e., printer and photocopier) for documentation, and a paper form for dissemination. On the other hand, dissimilar patterns were captured. As members of I/I Unit in the second episode struggled to find out a preferred method of communication (e.g., paper vs. email), the members interacted with instructors that were not seen in the first episode. As such, the second episode took almost twice the duration of the first episode. The findings from the current study, albeit preliminary, suggest non-linear and dynamic interactions among emergency operators, technical tools, and demands from an incident. As Woods (2006) noted, resilience of a system may not be visible until the system faces disruptive events. In such regards, the IEA would serve as a tool to represent the system’s resilient performance after a work demand. In addition, the IEA showed promise as a diagnostic tool that examines the interactions among the JCT triad. To gather more evidence to support findings in the preliminary analysis, future research will focus on extracting more episodes from the collected data and identifying emerging patterns of resilient performance of the IMT.