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Effective Emergency Response Management (ERM) system evaluation is vital to the process of continual improvement within emergency response organizations. The purpose of this paper is to investigate if an entire ERM system can be captured and encoded within a standardized framework.

Employing an exploratory approach the authors apply a mixed methods case study design and inductive reasoning to analyse documentary evidence provided during the inquest into the London Bombings 2005. The authors use content analysis to investigate the nature of ERM system data availability and apply principals of Network Theory to iteratively develop a framework within which data can be encoded.

The authors find that complex ERM system data can be captured and stored within a standardized framework. The authors present a conceptual framework and multi-stage mixed methods process, the Standardized Emergency Response Incident Evaluation System (SERIES) model, to support data collection, storage and interpretation. The findings demonstrate that ERM system evaluation can benefit from the adoption of a standardized mixed-methods approach employing data transformation and triangulation. The authors also demonstrate the potential of the proposed standardized model, by integrating qualitative and quantitative data, to support interpretation and reporting through the use of appropriate data visualization.

The SERIES model provides a practical tool and procedural guidelines to capture and share vital ERM system data and information across all emergency services. It also presents an opportunity to develop a large comprehensive multi-incident dataset to support academic inquiry and partnership between academics and practitioners.

The purpose of this paper is to provide an analytical model to decide between cash-based and in-kind distributions during emergency responses considering the needs of beneficiaries and market conditions. To allow the switch between modalities, a preparedness framework for humanitarian organizations (HOs) is provided.

A mathematical model is proposed to help humanitarian responders make quantitative decisions on the type of programs to implement in emergency responses. The model was applied to a field response by an international HO during the COVID-19 emergency in Colombia.

Cash-based and in-kind distributions are not mutually exclusive response modalities during emergencies, and the real needs of beneficiaries and market effects should be included in the modality selection decision to improve program effectiveness.

The research is focused on short-term immediate response to emergencies; the proposed model assumes favorable market conditions and limits the aid options to direct in-kind and multipurpose cash assistance, excluding other types of cash transfers.

The research outlines practical preconditions to operationalize switching between programs during an emergency. The study provides evidence that HOs should consider dynamics decision tools to select aid modalities and evaluate their response depending on market conditions.

Considering aid modality as a dynamic decision and including the needs from beneficiaries in the choice can have profound impact in the dignifying of humanitarian response to emergencies.

The quantitative model to decide between aid modalities is a novel approach to include beneficiaries' needs and market dynamics into humanitarian supply chain research. The preparedness framework closes the gap between the emergency preparedness literature and the operational constraints that organizations face for fast program implementation.

The intensifying effects of climate change and the growing concentration of population in hazardous locations mean that, for many communities, disasters are increasingly becoming not only foreseeable, but inevitable. While much attention is, and should be, focused on what these foreseeable disasters require in terms of disaster planning and mitigation, attention should also be focused on a related and equally pressing phenomena: mismanagement of disaster response, particularly as climate proves an increasing stressor. Like disasters themselves, disaster mismanagement – while not entirely predictable – may exhibit some predictable patterns. This chapter explores past disaster management failures, considers how climate change may alter or exacerbate certain response pathologies, and evaluates some potential remedies that might mitigate these challenges.

There have been plenty of emergencies occurred in tourism all over the world in recent years. These events and disasters have brought the tourists and relevant organizations enormous loss of life and property. The main reasons are the lack of holistic coordination among different departments and response for social responsibility. In the process of prevention and response of tourism emergency, the local governments need to take synergic action. Meanwhile, the positive participation in the tourism emergency rescue is one of the ways to share social responsibility. This paper aims to examine the early-warning management of regional tourism emergencies, in order to minimize the loss on both tourists' life and money, from the perspective of systematic thinking.

The paper establishes a regional tourism emergency response model based on holistic assessment approach and Bayesian network technology. It analyzes most critical factors of regional tourism emergency and the mutual influence among them. Thereafter, it employs the Bayesian network technology to assess the influence of several factors on the final magnitude of casualties holistically. Based on this, the paper proposes the response principle and the response process to regional tourism emergency.

This paper constructs the “FRES” principle about the holistic response to regional tourism emergency, including “fulfillment of social responsibility”, “rapid action”, “experience accumulation” and “synergic response”. Based on this principle, the paper suggests a general process on the holistic response to regional tourism emergency. Finally, the paper takes the mudslides emergency in Taiwan on October 23, 2010 as an example to conduct an empirical analysis. The paper gives an optimal holistic solution to the responding process of this event in the light of the “FRES” principle.

This paper explains the social responsibility related to the regional tourism emergencies and employs the Bayesian network technology to analyze the systematical responding process to tourism emergency. It proposes originally a “FRES” principle and a general process on the response to regional tourism emergency which are proven to be effective in systematical response to regional tourism events. The research results can facilitate the various local governments to jointly fulfill their social responsibilities and optimize the management of regional tourism emergencies in a holistic way.

Pertinent information sharing across various government agencies, as well as non‐governmental and private organizations, is essential to assess the incident situation, identify the needed resources for emergency response and generate response plans. However, each agency may have incident management systems of its choice with valuable information in its own format, posing difficulty in effective information sharing. Application‐to‐application sharing cross agency boundaries will significantly reduce human efforts and delay in emergency response. Information sharing from disparate systems and organizations, however, requires solving of the interoperability issue. The purpose of this paper is to present the UICDS™‐based resource sharing framework as a step toward addressing the afore‐mentioned challenges.

A prototype middleware system is developed using a standards‐based information sharing infrastructure called UICDS™ (Unified Incident Command and Decision Support™), an initiative led by the Department of Homeland Security (DHS) Science and Technology division. This standards‐based middleware, resource management plug‐in utilizes the ontology of organizational structure, workflow activities and resources, and the inference rules to discover and share resource information and interoperability from different incident management applications.

The middleware prototype implementation shows that the UICDS™‐based interoperability between heterogeneous incident management applications is feasible. Specifically, the paper shows that the resource data stored in the Resource Directory Database (RDDB) of the NJ Office of Emergency Management (NJOEM), Hippocrates of the New Jersey Department of Health and Senior Services (NJDHSS) can be discovered and shared with other incident management systems using the ontology and inference rules.

This study illustrates the possible solutions to the application to application interoperability problem using the DHS initiated interoperability platform called UICDS™.

The resource discovery and emergency response planning can be automated using the incident domain ontology and inference rules to dynamically generate the location‐based incident response workflows.

The purpose of this paper is to contribute an analysis of how crisis communication can make a difference in terms of the impact of an emergency on society.

The attitude of the response organisations with respect to communities is reflected in the planning model they adopt. Two ideal-typical planning models are distinguished in the literature. In order to analyse what role both planning models play in the dynamics of crisis communications, the authors selected two Dutch cases for a comparative case analysis on message contents and media responses to the crisis communication.

The content analysis revealed different crisis communication styles used by the emergency response organisation. The crisis communication in the first case focused primarily on denotative meaning-making while the crisis communication in the second case focused primarily on connotative meaning-making.

The authors argue that, in crisis communication, more attention should be paid to the way in which a response organisation approaches the situation, and to the dynamics of the interaction with the affected community.

More attention should be paid to the fact that emergency response and the affected community mutually shape each other; large-scale operations need to be moved out of their exclusivity and integrated into society.

Crises have a significant societal impact and do not occur in isolation from the broader social environment. The way in which people within society interpret the information from the authorities is important for the emergency response organisation in order that it can adapt to ongoing developments and match its communication more effectively to the affected communities.

The lack of studies about the response time of emergency medical service during the coronavirus disease 2019 (COVID-19) pandemic in a dense city of a developing country has triggered this study to explore the factors contributing to a high response time of ambulance service to reach patients in need. An evaluation of contributing factors to the response time is necessary to guide decision-makers in keeping a high service level of emergency medical service.

This research employed an agent-based modeling approach with input parameters from interviews with emergency medical service staff in Bandung city, Indonesia. The agent-based model is established to evaluate the relevant contribution of the factors to response time reduction using several scenarios.

According to agent-based simulation, four factors contribute to the response time: the process of preparing crew and ambulance during the pandemic, coverage area, traffic density and crew responsiveness. Among these factors, the preparation process during the pandemic and coverage area significantly contributed to the response time, while the traffic density and crew responsiveness were less significant. The preparation process is closely related to the safety procedure in handling patients during the COVID-19 pandemic and normal time. The recommended coverage area for maintaining a low response time is 5 km, equivalent to six local subdistricts.

This study has explored the factors contributing to emergency medical response time. The insignificant contribution of the traffic density showed that citizens, in general, have high awareness and compliance to traffic priority regulation, so crew responsiveness in handling ambulances is an irrelevant factor. This study might have different contributing factors for less dense population areas and focuses on public emergency medical services provided by the local government.

The local government must provide additional funding to cover additional investment for ambulance, crew and administration for the new emergency service deployment point. Exercising an efficient process in ambulance and crew preparation is mandatory for each emergency deployment point.

This study evaluates the contributing factors of emergency medical response time in the pandemic and normal situation by qualitative analysis and agent-based simulation. The performance comparison in terms of medical response time before and after COVID-19 through agent-based simulation is valuable for decision-makers to reduce the impact of COVID-19.

This study aims to answer the question: What dynamic capabilities do diverse humanitarian organizations have?

We examine this question through the lens of dynamic capabilities with sensing, seizing and reconfiguring capacities. The research team interviewed 15 individuals from 12 humanitarian organizations that had (a) different geographic scopes (global versus local) and (b) different missions (emergency response versus long-term development aid). We also gathered data from secondary sources, including standard operating procedures, company websites, and news databases (Factiva, Reuters and Bloomberg).

The findings identify the operational and dynamic capabilities of global and local humanitarian organizations while distinguishing between their mission to provide long-term development aid or emergency relief. (1) The global organizations, with their beneficiary responsiveness, reconfigured their sensing and seizing capacities throughout the COVID-19 pandemic by pivoting quickly to local procurement or regional supply chains. The long-term development organizations pivoted to multi-year supplier agreements with fixed pricing to counter price uncertainty and accessed social capital with government bodies. In contrast, emergency response organizations developed end-to-end supply chain visibility to sense changes in supply and demand. (2) Local humanitarian organizations developed the capacity to sense demand and supply changes to reconfigure based on their experiential learning working with the local community. The long-term-development local organizations used un-owned and scalable relief infrastructure to seize opportunities to rebuild affected areas. In contrast, emergency response organizations developed their capacity to seize opportunities to provide aid stemming from their decentralized decision-making, a lack of structured procedures, and the authority for increased expenditure.

We propose a theoretical framework to identify humanitarian organizations' operational and dynamic capabilities, distinguishing between global and local organizations and their emergency response and long-term aid missions.

Under uncertain circumstances, digital technologies are taken as digital transformation enablers and driving forces to integrate with medical, healthcare and emergency management research for effective epidemic prevention and control. This study aims to adapt complex systems in emergency management. Thus, a digital transformation-driven and systematic circulation framework is proposed in this study that can utilize the advantages of digital technologies to generate innovative and systematic governance.

Aiming at adapting complex systems in emergency management, a systematic circulation framework based on the interpretive research is proposed in this study that can utilize the advantages of digital technologies to generate innovative and systematic governance. The framework consists of four phases: (1) analysis of emergency management stages, (2) risk identification in the emergency management stages, (3) digital-enabled response model design for emergency management, and (4) strategy generation for digital emergency governance. A case study in China was illustrated in this study.

This paper examines the role those digital technologies can play in responding to pandemics and outlines a framework based on four phases of digital technologies for pandemic responses. After the phase-by-phase analysis, a digital technology-enabled emergency management framework, titled “Expected digital-enabled emergency management framework (EDEM framework)” was adapted and proposed. Moreover, the social risks of emergency management phases are identified. Then, three strategies for emergency governance and digital governance from the three perspectives, namely “Strengthening weaknesses for emergency response,” “Enhancing integration for collaborative governance,” and “Engaging foundations for emergency management” that the government can adopt them in the future, fight for public health emergency events.

The novel digital transformation-driven systematic circulation framework for public health risk response and governance was proposed. Meanwhile, an “Expected digital-enabled emergency management framework (EDEM model)” was also proposed to achieve a more effective empirical response for public health risk response and governance and contribute to studies about the government facing the COVID-19 pandemic effectively.

The purpose of this paper is to discuss the challenges inherent in planning and responding to disaster events in a multi-agency context where numerous governmental and non-governmental actors and agencies are involved in the planning and response phases. In particular, the authors examine a situation where a lead agency has recently been delegated the responsibility for emergency relief logistics and how it might determine and implement best practice.

Adopting an iterative inductive approach, the authors gather data and insights from academic literature, emergency management policies, frameworks and documents and exploratory in-depth interviews with 12 key informants who have considerable experience with the challenges of logistic preparation and response to disasters in a developed country context. The data and context are limited to developed counties, especially the state of Queensland, Australia.

The authors discuss the challenge of achieving coordinated supply chain management where mandated/lead response agencies are required to meet stakeholder and local community expectations and outcomes. From these findings, the authors offer 11 practical recommendations to assist the delivery of best practice in emergency logistics.

Humanitarian logistics is usually examined from a low/middle-income country perspective, yet an efficient and effective disaster response is no less important for developed economies. In this respect, the authors offer a fresh examination of the challenges of delivering best practice for emergency logistics in order to achieve expected community outcomes.