Towards a System‐Oriented Framework for Analysing and Evaluating Emergency Response

Information can be provided by studying and evaluating past emergencies and the response in connection to them. This information would then be useful in efforts directed at preventing, mitigating and/or preparing for future emergencies. However, the analysis and evaluation of emergency response operations is not an easy task, especially when the operation involves several cooperating actors (e.g. the fire and rescue services, the police, the emergency medical services, etc.). Here, we identify and discuss four aspects of this challenge: (1) issues related to the values governing the evaluation, (2) issues related to the complexity of the systems involved, (3) issues related to the validity of the information on which the analysis and evaluation is based and (4) issues related to the limiting conditions under which the emergency response system operated. An outline of a framework for such an analysis and evaluation, influenced by systems theory, accident investigation theories and programme evaluation theories dealing with the above aspects, is introduced, discussed and exemplified using empirical results from a case study. We conclude that the proposed framework may provide a better understanding of how an emergency response system functioned during a specific operation, and help to identify the potential events and/or circumstances that could significantly affect the performance of the emergency response system, either negatively or positively. The insights gained from using the framework may allow the actors involved in the response operation to gain a better understanding of how the emergency response system functioned as a whole, as well as how the actors performed as individual components of the system. Furthermore, the information can also be useful for actors preparing for future emergencies.     

Effective organizational improvisation in information systems development: Insights from the Tencent messaging system development

Organizational improvisation has been increasingly observed in information systems development (ISD), which leads to both positive and negative results. Extant studies have examined how to conduct effective improvisation, but findings are mainly based on variance-based models; a process model is missing. Our study fills this gap by conducting an in-depth case study of the Tencent messaging system development. Our study identifies a four-phase process model featuring, a continuous iteration between improvisational search and build. Our findings make important contributions to organizational improvisation literature in ISD and general management and provide a step-by-step guide for ISD managers to conduct effective improvisation.     

Governments' Ability to Assist Nationals in Disasters Abroad: What Do We Know about Consular Emergency Management?

This review draws attention to the need for consolidated inquiry into large‐scale consular emergency management. Occurring outside national borders, these low‐probability but high‐impact events affect a large number of national citizens. They challenge governments' crisis management systems, and direct public and government attention to a sector that has been largely overlooked in public administration literature – consular affairs. This review brings together the relevant literature on consular assistance and looks further afield to find analysis of emergency responses in case studies of three major consular emergencies. Three underlying themes emerge, central to a more nuanced understanding of the government response to large‐scale emergencies affecting citizens abroad.     

Business processes in the agile organisation: a socio-technical perspective

This paper takes a cross-disciplinary view of the ontology of “business process”: how the concept is treated in the IS research literature and how related concepts (with stronger human behavioural orientation) from organisation and management sciences can potentially inform this IS perspective. In particular, is there room for socio-technical concepts such as technology affordance, derived from the constructivist tradition, in improving our understanding of operational business processes, particularly human-centric business processes? The paper presents a theoretical framework for understanding the role of business processes in organisational agility that distinguishes between the process-as-designed and the process-as-practiced. How this practice aspect of business processes also leads to the improvisation of various information technology enablers, is explored using a socio-technical lens. The posited theoretical framework is illustrated and validated with data drawn from an interpretive empirical case study of a large IT services company. The research suggests that processes within the organisation evolve both by top-down design and by the bottom-up routinisation of practice and that the tension between these is driven by the need for flexibility.     

Parallel Planning: A New Motion Planning Framework for Autonomous Driving

Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to deal with emergency situations, a new motion planning framework called as "parallel planning" is proposed in this paper. In order to generate sufficient and various training samples, artificial traffic scenes are firstly constructed based on the knowledge from the reality. A deep planning model which combines a convolutional neural network (CNN) with the Long Short-Term Memory module (LSTM) is developed to make planning decisions in an end-toend mode. This model can learn from both real and artificial traffic scenes and imitate the driving style of human drivers. Moreover, a parallel deep reinforcement learning approach is also presented to improve the robustness of planning model and reduce the error rate. To handle emergency situations, a hybrid generative model including a variational auto-encoder (VAE) and a generative adversarial network (GAN) is utilized to learn from virtual emergencies generated in artificial traffic scenes. While an autonomous vehicle is moving, the hybrid generative model generates multiple video clips in parallel, which correspond to different potential emergency scenarios. Simultaneously, the deep planning model makes planning decisions for both virtual and current real scenes. The final planning decision is determined by analysis of real observations. Leveraging the parallel planning approach, the planner is able to make rational decisions without heavy calculation burden when an emergency occurs.      

Real-Time Decision Support for Emergency Management: An Integration of Advanced Computer and Communications Technology

Responses to emergencies are typically based on contingency plans. However, unexpected events can occur during the operation that affect safety and/or effectiveness of the activated response plan. Latest advances in communications and information technology can collect and transfer a large amount of data to the on-scene commander in real-time. The commander can then assess the potential impact of such events and decide if and how to revise the planned course of action to maintain safety and efficiency of the operation. This paper proposes a new paradigm for real-time decision support for emergency response - operational risk management. Emergency response is modelled as a large-scale operational system, including a human-machine real-time controller. The decision model is based on a topological graph structure, where the nodes are decisions and the arcs the activities. The attributes of the activities are expressed as ordinal preference values. The optimal course of action is the sequence of activities with the highest preference for resolving the emergency situation. The implementation of the decision model into a prototype decision support system is discussed.     

突发事件下的医院应急资源冗余配置优化模型

突发事件发生前,医院需要保持一定的应急资源冗余量。针对突发事件下医院应急资源冗余的配置优化问题,首先,基于效用理论,通过分析医院应急资源冗余的效用体现来对应急资源冗余进行定义和分类,确定了符合边际规律的效用函数;其次,建立了总效用最大化的医院应急资源冗余配置模型,并给出应急资源储存量的上限及应急合理度的下限作为模型的约束条件;最后,把粒子群算法和序列二次规划法相结合进行寻优求解。通过案例分析,得出了医院四种应急资源冗余的优化方案,总结出了医院的应急水平对医院应急资源冗余的需求程度。研究表明,应急资源冗余配置优化模型能够帮助医院在突发事件下很好地进行应急救援,提高医院应急资源的利用效率。     

Resilience is not control: healthcare,crisis management,and ICT

Like other high hazard sectors, successful crisis response relies on a well-founded understanding of the work domain and the manner in which operators perceive and deal with obstacles to achieving goals. That understanding is essential to the development of information and communications technology (ICT) that are intended to support operator performance. While crises are uncommon in other high hazard sectors such as nuclear power generation and aviation, acute and ambulatory healthcare work encounters life-and-death crises daily. This makes healthcare a useful living laboratory to develop ICT in order to manage crises. This paper shows how healthcare organizations that continually deal with complex, uncertain, high-tempo operations can serve as a model to develop ICT that supports crisis management. We illustrate the results of using these methods through an example of cognitive systems engineering research that identifies ambulatory care risks to patients. We then describe multiple methods that can be used together to efficiently study complex, high hazard work settings. We conclude with an example of how it can support the development of a cognitive aid for diabetic care to support work in that setting.     

基于层次分析法的电网企业突发事件应急能力评估

为评估电网企业对突发事件的应急能力，本文提出了一种基于层次分析法的电网企业突发事件应急能力评价模型。该模型通过中国南方电网公司构建的电网企业应急管理能力指标体系，引入层次分析法来确定指标权重，通过各指标所发生的事件频率与各指标权重系数的加权计算，得到不同电网企业对于突发事件的应急能力评价结果。以贵州各市供电局为例，对其进行实例计算和评价。其评价结果表明，评价得出的各区域的应急能力值与实际情况相符，所建立的电网企业对于突发事件的应急能力评价模型是有效的。     

Participation Patterns and Reliability of Human Sensing in Crowd-Sourced Disaster Management

Over the last ten years, there has been a significant increase in crowd-sourcing applications for disaster management. Their success depends heavily on the behaviour of social media users, acting as human sensors during disaster monitoring and emergency response. Unlike their technological counterparts, human sensors are complex social entities, contributing in different ways to their collective task and creating varying participation patterns through social media. Failing to understand these participation patterns limits our capacity to evaluate the reliability of human sensing in different contexts. Based on an analysis of flood-related information contributed by Twitter users in Jakarta during the 2014/2015 and 2015/2016 monsoonal seasons, this study establishes four categories of human sensors and their respective levels of reliability for disaster management. The results have significant implications for how we frame expectations and develop reliance on the use of social media for disaster management. Importantly, the results will serve as a useful guide for understanding levels of incentive that may be required to motivate members of the different categories of social media users during emergencies and disasters.     

A mathematical model for the diffusion of emergency warning messages during CBRNe emergencies

Understanding the diffusion of warning messages is essential to adequately respond to emergency events and situations. This is especially true in urgent scenarios, that is situations where external events are happening at the same rate or faster than the diffusion process itself. In this paper, an information diffusion model (Bass model) is proposed to study the spread of warning messages during emergencies involving urgent diffusion dynamics, for example a CBRNe event. In the present study, the Bass model is applied to two hazardous materials transportation accidents reported in the literature: the Pittsburgh phosphorus oxychloride release and the precautionary evacuation occurred in Confluence due to toxic chemicals released after a train derailment. Warning data collected from the two accidents and reported in published literature studies were used in this work and fitted with the Bass model. The diffusion of emergency warning messages is modelled as a two‐component system, where the spread of information is characterized by (a) a “broadcast process” that disseminates the emergency warning vertically (in the sense that many people are alerted simultaneously) and (b) a horizontal “contagion process” whereby people first hear of the event and then sequentially tell others (social media, word‐of‐mouth and peer‐to‐peer communication). The Bass model provided an excellent fit of the warning diffusion times related to both accidents suggesting that the very first phase of the warning process is sustained by a “broadcast” information diffusion process. However, after less than 1 hr from the beginning of the warning process the efficacy of its diffusion is dominated by the “contagion” component, that is the effectiveness of a robust social network between individuals. In conclusion, the Bass model proved to be a handy tool to assess epidemics spreading of information from the people who adopted the information. Our results suggest that the general Bass model applied to diffusion of emergency warning has the potential to provide key information in the management of emergencies. This approach can be applied right away by professional communicators, advisors and decision‐makers in case of a CBRNe event.     

Fast and learnable behavioral and cognitive modeling for virtual character animation

Behavioral and cognitive modeling for virtual characters is a promising field. It significantly reduces the workload on the animator, allowing characters to act autonomously in a believable fashion. It also makes interactivity between humans and virtual characters more practical than ever before. In this paper we present a novel technique where an artificial neural network is used to approximate a cognitive model. This allows us to execute the model much more quickly, making cognitively empowered characters more practical for interactive applications. Through this approach, we can animate several thousand intelligent characters in real time on a PC. We also present a novel technique for how a virtual character, instead of using an explicit model supplied by the user, can automatically learn an unknown behavioral/cognitive model by itself through reinforcement learning. The ability to learn without an explicit model appears promising for helping behavioral and cognitive modeling become more broadly accepted and used in the computer graphics community, as it can further reduce the workload on the animator. Further, it provides solutions for problems that cannot easily be modeled explicitly. Copyright © 2004 John Wiley & Sons, Ltd.     

Resilience and vulnerability of small flexible crisis response teams: implications for training and preparation

Following the Asian Tsunami of 2004 and during the Israel–Lebanon Crisis of 2006, Sweden sent small crisis response teams to support civilians. The small size of the teams, combined with situations that did not always play out according to expectations and plans, presented a challenge to their resilience—their ability to adapt to circumstances outside of plans made in advance. In this paper, we analyze the experiences of 14 members of Swedish field teams involved in the crises response, based on focus group discussions. We describe a cycle of preparing for role improvisation, of taking improvised roles, of working in them, and of getting out of them when they are no longer a benefit. The discussions revealed that although role improvisation was seen as necessary to get the work done, they also saw a need to manage negative side effects and vulnerabilities of role improvisation in various ways. We discuss training goals based on their experiences, to address perceived strengths and vulnerabilities of role improvisation. We also discuss factors affecting role improvisation, such as a resilience climate of shared attitudes. Our results can be useful for organizations that have or that plan to adopt flexible crisis response teams. Our results can also be of interests to a more general audience with an interest in how practices necessary for resilience can bring negative side effects, for instance, resilience loss in the organization after an initial adaptive stage.     

Cognitive process modelling of controllers in en route air traffic control

In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes. PRACTITIONER SUMMARY: This research focuses on an experimental study to gain a better understanding of controllers' cognitive processes in air traffic control. We conducted ethnographic observations and then analysed the data to develop a model of controllers' cognitive process. This analysis revealed that strategic routines are applicable to decision making.     

应急配送车辆调度优化研究综述与展望

应急配送车辆调度优化是物流配送领域近年来的一个新兴的研究方向,它的研究可大大减少自然灾害和公共卫生事件等突发灾难所带来的损失,对最大程度保护人民生命和财产安全、推进应急物流管理的完善和发展具有非常重要的意义和广阔的应用前景。对近年来国内相关学者在应急配送车辆调度优化研究中的成果进行了系统整理,并从模型、算法、研究方法等多个方面进行了述评,同时讨论了存在的一些问题,并展望了今后的研究方向。     

EDUCATION AND TRAINING

To make strategic use of the information resource, IS managers must learn how to keep abreast of strategic opportunities for their organization, the information that could enhance their strategic position, how to obtain and manage that information, and how information technology can assist this process. Such organizational learning requires education and training as well as a support infrastructure and the leadership of senior management in creating the appropriate education, training, and support programs in information management. IS managers have the opportunity-and the obligation- to see that senior management understands the importance of these programs.     

Knowledge-based models for emergency management systems

This paper proposes the use of advanced knowledge models to support environmental emergency management as an adequate response to the current needs and technology. A generic architecture embodying the knowledge pieces required to manage emergencies in different kinds of problem scenarios is described. Simulation models of the physical system, integrated as part of the knowledge architecture, are also claimed to be adequate, both from the point of view of the knowledge model calibration and the training of the emergency personnel as well. The feasibility of the approach has been demonstrated with the application of the generic model to a particular real world problem: the management of flood emergencies in the Jucar river basin area (Spain). This work was developed in the framework of ARTEMIS, a European Commission research project.     

Software intervention in the process of improvisation

This paper provides a rationale for the possible development of software interfaces, the purpose of which is to provide opportunities for an improvising musician to construct a performance which, on the one hand allows them to engage with sonic and visual material produced by generative algorithms and on the other challenges the conscious and subconscious cognitive processes which govern their normal performance practice. Both cognitive psychology and communication theory offer great insight into the evolution of human cognisance and provide pointers to models with which the activity of musical improvisation could be interpreted. In the course of this paper I have tried to relate academic concepts and theories to material gleaned from improvising musicians, giving credence to their opinions and drawing inference from their experiences.     

Applying information technology to the presentation of emergency operating procedures: implications for usability criteria

As a result of their increasing complexity, modern industrial systems have come to rely on written procedures for dealing with various emergencies that might be encountered. Despite the significant effort invested in developing emergency operating procedures, traditional hard-copy procedures have been found inadequate in presenting complex instructions, handling cross-references, tracing suspended or incomplete steps, and in general, monitoring user progress. Developments in information technology have presented new opportunities for resolving these problems in using and adapting procedures. This article reviews current developments and problems with computer-based procedures and proposes a framework for specifying usability aspects of their use. The usability framework addresses critical cognitive activities involved in managing system emergencies and draws upon empirical studies of 'official' and 'selective' uses of procedures in actual practice. Finally, information technology applications are considered within the wider organizational context, such as compliance with procedures, crew communication, and retention of skills.     

A storyteller's guide to problem‐based learning for information systems management education

More than a decade ago, evidence‐based recommendations emerged regarding what students of information systems (IS) management education should learn and how should they learn it. Although these recommendations for how IS management should be taught remain valid, they need to be updated to account for recent advances in technologies that enable multimedia learning. Promoters of such technologies promise enhanced cognitive and behavioural outcomes, but this promise remains unreached, reflecting the underdeveloped multimedia‐enabled learning literature. To help attain this promise and rejuvenate the literature of multimedia learning, we offer a roadmap for new areas of research that would inform the design and use of a novel form of multimedia materials: narrative animated videos (NAVs). NAVs represent a form of self‐determined learning that features immersive, story‐based content. We argue that their use will intrinsically motivate users to process the materials to completion, thereby enhancing cognitive and behavioural outcomes, and thus catalysing the effectiveness of the team‐based learning and self‐regulated learning modes for problem‐based learning (PBL) delivery of IS management education. This compelling roadmap corresponds to meaningful IS research because it centres on a topic that the IS literature has long examined—the role of user motivation—and because its theoretical contributions invite specific paths of research for informing the design of the PBL delivery of IS management education within an information systems artefact.