Tiered Approach to Resilience Assessment

Managing business continuity in the Arctic: Experiences from mining

This article presents a model for business continuity capacity, which shows how organizations can analyze possible gaps in their business continuity capability and thereby increase their capacity to recover value-adding critical activities. Using an example of a flooded mine on Svalbard, the study investigated how the mining company Store Norske Spitsbergen Coal Company (SNSK), with considerable experience with similar events and an excellent safety record, could fail to manage a well-known event and reduce recovery times of its critical activities. The analysis explored how experience in safety and incident management does not necessarily mean that these abilities are transferable to a new but similar event. The study sought to answer the research question: To what extent does SNSK's systematic work with safety, and experience with flooding events, improve business continuity capacity? In the Arctic, emergency response can take hours or days to arrive after the event. A structured recovery system can support pre-existing platforms aimed at safety, to include the critical activities needed to ensure an organization's overall survival. Systematic work can improve performance and make the organization engage in a virtuous cycle by implementing management structures, risk identification systems, competency development, and processes for the in situ evaluation of hazards. However, as seen here, the organization needs to pay attention to changes that could affect risk assessments and threat levels well-known events. These insights can be utilized by other organizations seeking synergy when strengthening their safety and business continuity performance.

Linking coastal environmental and health observations for human wellbeing

Coastal areas have long been attractive places to live, work, and recreate and remain so even in the face of growing threats from global environmental change. At any moment, a significant portion of the human population is exposed to both positive and negative health effects associated with coastal locations. Some locations may be "hotspots" of concern for human health due to ongoing climatic and other changes, accentuating the need for better understanding of coastal environment-human health linkages. This paper describes how environmental and health data could be combined to create a coastal environmental and human health observing system. While largely based on information from the US and Europe, the concept should be relevant to almost any coastal area. If implemented, a coastal health observing system would connect a variety of human health data and environmental observations for individuals and communities, and where possible cohorts. Health data would be derived from questionnaires and other personal sources, clinical examinations, electronic health records, wearable devices, and syndromic surveillance, plus information on vulnerability and health-relevant community characteristics, and social media observations. Environmental data sources would include weather and climate, beach and coastal conditions, sentinel species, occurrences of harmful organisms and substances, seafood safety advisories, and distribution, proximity, and characteristics of health-promoting green and blue spaces. Where available, information on supporting resources could be added. Establishment of a linked network of coastal health observatories could provide powerful tools for understanding the positive and negative health effects of coastal living, lead to better health protections and enhanced wellbeing, and provide significant benefits to coastal residents, including the historically disadvantaged, as well as the military, hospitals and emergency departments, academic medical, public health, and environmental health programs, and others. Early networks could provide best practices and lessons learned to assist later entries.

Cascading failures and resilience optimization of hospital infrastructure systems against the COVID-19

The outbreak of the Coronavirus Disease 2019 (COVID-19) has put the resilience of a country's healthcare infrastructure to the most severe test. The challenge of taking emergency measures to optimize the supply of medical resources and effectively meet the medical needs of residents is an important issue that needs to be resolved urgently in the prevention and control of public health emergencies. This paper analyzes cascading failures and optimization of the resilience of the hospital infrastructure system (HIS) with the presence of the COVID-19. It proposes a propagation model to describe the COVID-19 infectious process and establishes a cascading failure model of a HIS to analyze its failure mechanism. It also proposes a method for optimizing the resilience of HIS. Then the supplies and demands in maintaining the operations of HIS are studied, and a restoration strategy is obtained. Finally, simulation analysis of the spread of the COVID-19 is carried out to illustrate the applicability of the proposed method.

Analyzing organizational barriers towards building postpandemic supply chain resilience in Indian MSMEs: a grey-DEMATEL approach

Purpose

This study aims to identify the barriers to building supply chain resilience and assess the contextual relationship between them in the Indian micro, small and medium enterprise (MSME) sector for the post COVID-19 era.

Design/methodology/approach

Barriers to supply chain resilience were extracted from the extant literature and were evaluated using the grey sets and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach from strategic, tactical and operational business perspectives. The responses from experts on the identified barriers were collected through a structured questionnaire. The prominence-net effect results obtained after the DEMATEL application helped identify the most prominent barriers, their net cause and effect, and their correlation with each other.

Findings

A total of 16 barriers to resilience, identified from the literature, were considered for analysis. The findings of the study revealed that the lack of flexibility is the most critical causal barrier to building a resilient supply chain. Lack of planned resource management was also found to be an influential barrier. The study also identified the supply chain design, need for collaboration and technological capability as important factors for the MSME sector to focus on.

Research limitations/implications

The study is limited to assessing barriers to the supply chain resilience of MSMEs in India. More extensive research may be needed to reveal the global trend.

Practical implications

The study is significantly important for the MSMEs looking to establish resilient supply chains. Managers can use the findings to identify the weak links in the supply chain for strategic and tactical planning and can take corrective actions.

Originality/value

The study pinpoints the key linkages between barriers that impede MSMEs to make their supply chains resilient and robust to mitigate the impact of future disruptions and adversities. The work may be used by practitioners to further their attention on the significant challenges.

Prioritization of Resilience Initiatives for Climate-Related Disasters in the Metropolitan City of Venice

Increases in the magnitude and frequency of climate and other disruptive factors are placing environmental, economic, and social stresses on coastal systems. This is further exacerbated by land use transformations, urbanization, over-tourism, sociopolitical tensions, technological innovations, among others. A scenario-informed multicriteria decision analysis (MCDA) was applied in the Metropolitan City of Venice integrating qualitative (i.e., local stakeholder preferences) and quantitative information (i.e., climate-change projections) with the aim of enhancing system resilience to multiple climate-related threats. As part of this analysis, different groups of local stakeholders (e.g., local authorities, civil protection agencies, SMEs, NGOs) were asked to identify critical functions that needs to be sustained. Various policy initiatives were considered to support these critical functions. The MCDA was used to rank the initiatives across several scenarios describing main climate threats (e.g., storm surges, floods, heatwaves, drought). We found that many climate change scenarios were considered to be disruptive to stakeholders and influence alternative ranking. The management alternatives acting on physical domain generally enhance resilience across just a few scenarios while cognitive and informative initiatives provided resilience enhancement across most scenarios considered. With uncertainty of multiple stressors along with projected climate variability, a portfolio of cognitive and physical initiatives is recommended to enhance resilience.

An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection

The formalization and solution of supplier selection problems (SSPs) based on sustainable (economic, environmental, and social) indicators have become a fundamental tool to perform a strategic analysis of the whole supply chain process and maximize the competitive advantage of firms. Over the last decade, sustainability issues have been often considered in combination with resilient indexes leading to the study of sustainable-resilient supplier selection problems (SRSSPs). The current research on sustainable development, particularly concerned with the strong impact that the recent COVID-19 pandemic has had on supply chains, has been paying increasing attention to the resilience concept and its role within SSPs. This study proposes a hybrid fuzzy multi-criteria decision making (MCDM) method to solve SRSSPs. The fuzzy best-worst method is used first to determine the importance weights of the selection criteria. A combined grey relational analysis and the technique for order of preference by similarity to ideal solution (TOPSIS) method is used next to evaluate the suppliers in a fuzzy environment. Triangular fuzzy numbers (TFNs) are used to express the weights of criteria and alternatives to account for the ambiguity and uncertainty inherent to subjective evaluations. However, the proposed method can be easily extended to other fuzzy settings depending on the uncertainty facing managers and decision-makers. A real-life application is presented to demonstrate the applicability and efficacy of the proposed model. Sixteen evaluation criteria are identified and classified as economic, environmental, social, or resilient. The results obtained through the case study show that "pollution control," "environmental management system," and "risk awareness" are the most influential criteria when studying SRSSPs related to the manufacturing industry. Finally, three different sensitivity analysis methods are applied to validate the robustness of the proposed framework, namely, changing the weights of the criteria, comparing the results with those of other common fuzzy MCDM methods, and changing the components of the principal decision matrix.

Decision support architectures for the recovery of interdependent infrastructure with large-scale damage and socially vulnerable populations

Infrastructure damage has household-level consequences after a major disaster. Losses are experienced due to factors such as unavailable services and impaired mobility. Socially vulnerable residents, in particular, have few resources with which to adapt. Decision support tools for making justifiable, transparent, repeatable decisions that center the needs of users during recovery are currently nonexistent. In part, this is because infrastructure recovery is a complex process, often involving the coordination of multiple entities. The recovery problem can be rendered more tractable by applying tools suitable for modeling complex systems and processes. System theoretic process analysis (STPA) can be used for goalsetting in a complex, dynamic system such as community civil infrastructure. STPA is used here to devise a decision support tool architecture suitable for coordinated multiagency recovery efforts. The example application is a long-term recovery process with widespread infrastructure damage, population displacement, and other disruptions in system use due to a major disaster. In the example, losses and hazards are defined to reflect recovery challenges commonly faced by vulnerable populations experiencing partial or total displacement. This extension of STPA then reverses these hazards, starting with the most hazardous system states and progressing sequentially to less hazardous states until recovery is complete.

Organizational Resilience to Disruption Risks: Developing Metrics and Testing Effectiveness of Operational Strategies

This study draws from the system resilience literature to propose three different metrics for evaluating the resilience performance of organizations against disruptions: the initial loss due to the disruption, the maximum loss, and the total loss over time. In order to show the usefulness of the developed metrics in practice, we deploy these metrics to study the effectiveness of two resilience strategies: maintaining operational slack and broadening operational scope, by empirically analyzing the performance of manufacturing firms that experienced a disruption during the period from 2005 to the end of 2014. The results show that maintaining certain aspects of operational slack and broadening business scope and geographic scope can affect these different metrics in different ways. Our results help decisionmakers in risk management to gain a better understanding of the conditions under which the recommended strategies actually improve organizations' resilience, as well as the ways in which they may do so.

A case study of complex disasters within the resilience framework in Zagreb, Croatia: Two earthquakes in one pandemic

This paper is an analysis of complex crisis management and the importance of resilience on the example of co-occurring disasters. A resilience framework model was analyzed based on epidemiologic data and the interplay of several disasters; the COVID-19 pandemic and two 2020 Zagreb, Croatia earthquakes. A dose-response principle may be applied to a complex crisis scenario, within a resilience-vulnerability framework. The available data present the concept of balance between vulnerability and resilience of the population affected by complex crises as well as possible adaptation mechanisms. Multiple disasters that last for a prolonged period reduce the populations' resilience and increase the risk of the next crisis becoming a disaster as well. Such complex disasters should not be approached by multiple risk management protocols, but rather by a single, multilayered protocol. Health policies that predict the possible effects of complex disasters on health risk management need to provide measures to maintain and promote resilience instead of collapse. These is a clear need to adopt green environmental policies, reduce socioeconomic inequality, train volunteer managers during crises, introduce timely evidence-informed policies and transfer new research and innovations in society rapidly.

The Influence of Residents' Resilience on the Recovery in the Torrential Rain in Western Japan in 2018

In 2018 torrential rain caused serious human suffering and damage to property in western Japan. Following such disasters, the investigation of residents' subsequent recovery process is important to determine the support required in affected areas and disaster risk management. This study examines the effects of psychological resilience on residents' life recovery following the torrential rain. We conducted a web survey with 1,000 residents in 13 districts of Hiroshima prefecture and 6 districts of Okayama prefecture that suffered the most damage caused by the torrential rain. The survey used the "recovery calendar" approach to assess residents' life recovery from the disaster. Results indicated that residents who had suffered relatively little damage began to recover during the "disaster utopia" phase up to 2 months after the disaster. However, residents who had suffered serious damage began to recover during the "reentry to everyday life" phase up to 6 months after the disaster. Moreover, older residents or residents with strong psychological resilience who suffered serious damage were likely to recover sooner than those with weaker psychological resilience. Therefore, this study indicates the importance of an approach to disaster recovery according to the level of damage, phased time period, and psychological resilience.

How to tackle complexity in urban climate resilience? Negotiating climate science, adaptation and multi-level governance in India

As the world’s population is expected to be over 2/3^rd urban by 2050, climate action in cities is a growing area of interest in the inter-disciplines of development policy, disaster mitigation and environmental governance. The climate impacts are expected to be quite severe in the developing world, given its urban societies are densely packed, vastly exposed to natural elements while possessing limited capabilities. There is a notable ambiguity and complexity that inhibits a methodical approach in identifying urban resilience measures. The complexity is due to intersection of large number of distinct variables in climate geoscience (precipitation and temperature anomalies at different locations, RCPs, timeline), adaptation alternatives (approach, priority, intervention level) and urban governance (functional mandate, institutional capacity, and plans & policies). This research examines how disparate and complex knowledge and information in these inter-disciplines can be processed for systematic ‘negotiation’ to situate, ground and operationalize resilience in cities. With India as a case, we test this by simulating mid-term and long-run climate scenarios (2050 & 2080) to map regional climate impacts that shows escalation in the intensity of climate events like heat waves, urban flooding, landslides and sea level rise. We draw on suitable adaptation measures for five key urban sectors- water, infrastructure (including energy), building, urban planning, health and conclude a sleuth of climate resilience building measures for policy application through national/ state policies, local urban plans and preparation of city resilience strategy, as well as advance the research on ‘negotiated resilience’ in urban areas

Reviewing qualitative research approaches in the context of critical infrastructure resilience

Modern societies are increasingly dependent on the proper functioning of critical infrastructures (CIs). CIs produce and distribute essential goods or services, as for power transmission systems, water treatment and distribution infrastructures, transportation systems, communication networks, nuclear power plants, and information technologies. Being resilient becomes a key property for CIs, which are constantly exposed to threats that can undermine safety, security, and business continuity. Nowadays, a variety of approaches exist in the context of CIs' resilience research. This paper provides a state-of-the-art review on the approaches that have a complete qualitative dimension, or that can be used as entry points for semi-quantitative analyses. The study aims to uncover the usage of qualitative research methods through a systematic review based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The paper identifies four principal dimensions of resilience referred to CIs (i.e., techno-centric, organisational, community, and urban) and discusses the related qualitative methods. Besides many studies being focused on energy and transportation systems, the literature review allows to observe that interviews and questionnaires are most frequently used to gather qualitative data, besides a high percentage of mixed-method research. The article aims to provide a synthesis of literature on qualitative methods used for resilience research in the domain of CIs, detailing lessons learned from such approaches to shed lights on best practices and identify possible future research directions.

An IoE and Big Multimedia Data Approach for Urban Transport System Resilience Management in Smart Cities

Today, the complexity of urban systems combined with existing and emerging threats constrains administrations to consider smart technologies and related huge amounts of data generated as a means to take timely and informed decisions. The smart city needs to be prepared for both expected and unexpected situations, and the possibility to mitigate the effect of the uncertainty behind the causes of disruptions through the analysis of all the possible data generated by the city open new possibility for resilience operationalization. This article aims at introducing a new conceptualization for resilience and presenting an innovative full stack solution to exploit Internet of Everything (IoE) and big multimedia data in smart cities to manage resilience of urban transport systems (UTS), which is one of the most critical infrastructures of the city. The approach is based on a novel data driven approach to resilience engineering and functional resonance analysis method (FRAM), to understand and model an UTS in the context of smart cities and to support evidence driven decision making. The paper proposes an architecture taking into account: (a) different kinds of available data generated in the smart city, (b) big data collection and semantic aggregation and enrichment; (c) data sense-making process composed by analytics of different data sources like social media, communication networks, IoT, user behavior; (d) tools for knowledge driven decisions able to combine different information generated by analytics, experience, and structural information of the city into a comprehensive and evidence driven decision model. The solution has been applied in Florence metropolitan city in the context of RESOLUTE H2020 research project of the European Commission.

Globalization and global risk: How risk analysis needs to be enhanced to be effective in confronting current threats

In the last 20-30 years, technological innovation has enabled the advancement of industry at a global scale, giving rise to a truly global society, resting on an interdependent web of transnational technical, economic and social systems. These systems are exposed to scenarios of cascading outbreaks, whose impacts can ripple to very large scales through their strong interdependencies, as recently shown by the pandemic spreading of the Coronavirus. Considerable work has been conducted in recent years to develop frameworks to support the assessment, communication, management and governance of this type of risk, building on concepts like systemic risks, complexity theory, deep uncertainties, resilience engineering, adaptive management and black swans. Yet contemporary risk analysis struggles to provide authoritative societal guidance for adequately handling these types of risks, as clearly illustrated by the Coronavirus case. In this paper, we reflect on this situation. We aim to identify critical challenges in current frameworks of risk assessment and management and point to ways to strengthen these, to be better able to confront threats like the Coronavirus in the future. A set of principles and theses are established, which have the potential to support a common foundation for the many different scientific perspectives and 'schools' currently dealing with risk handling issues.

Monitoring of transport infrastructure exposed to multiple hazards: a roadmap for building resilience

Monitoring-enhanced resilience in transport management is emerging together with the new technologies and digital data, however have not been fully explored yet. Digital technologies have the potential to provide rapid resilience assessments in a quantifiable and engineered manner for transport infrastructure, which is exposed to multiple natural and human-induced hazards and diverse loads throughout their life-cycle. Physical damage and disruption of networks and interdependent systems may cause tremendous socioeconomic impact, affecting world economies and societies. Nowadays, transport infrastructure stakeholders have shifted the requirements in risk and resilience assessment. The expectation is that risk is estimated efficiently, almost in real-time with high accuracy, aiming at maximising the functionality and minimising losses. Nevertheless, no integrated framework exists for quantifying resilience to diverse hazards, based on structural and functionality monitoring (SHFM) data, and this is the main capability gap that this paper envisages filling. Monitoring systems have been used widely in transport infrastructure and have been studied extensively in the literature. Data can facilitate prognosis of the asset condition and the functionality of the network, informing computer-based asset and traffic models, which can assist in defining actionable performance indicators, for diagnosis and for defining risk and loss expediently and accurately. Evidence exists that SHFM is an enabler of resilience. However, strategies are absent in support of monitoring-based resilience assessment in transport infrastructure management. In response to the above challenge, this paper puts forward for the first time in the international literature, a roadmap for monitoring-based quantification of resilience for transport infrastructure, based on a comprehensive review of the current state-of-the-art. It is a holistic asset management roadmap, which identifies the interactions among the design, monitoring, risk assessment and quantification of resilience to multiple hazards. Monitoring is embraced as a vital component, providing expedient feedback for recovery measures, accelerating decision-making for adaptation of changing ecosystems and built environments, utilising emerging technologies, to continuously deliver safer and resilient transport infrastructure.

A Resilience-Based Approach to Risk Assessments-Building Resilient Organizations under Arctic Conditions

Reliability and higher levels of safety are thought to be achieved by using systematic approaches to managing risks. The assessment of risks has produced a range of different approaches to assessing these uncertainties, presenting models for how risks affect individuals or organizations. Contemporary risk assessment tools based on this approach have proven difficult for practitioners to use as tools for tactical and operational decision making. This article presents an alternative to these assessments by utilizing a resilience perspective, arguing that complex systems are inclined to variety and uncertainty regarding the results they produce and are therefore prone to systemic failures. A continuous improvement approach is a source of reliability when managing complex systems and is necessary to manage varieties and uncertainties. For an organization to understand how risk events occur, it is necessary to define what is believed to be the equilibrium of the system in time and space. By applying a resilience engineering (RE) perspective to risk assessment, it is possible to manage this complexity by assessing the ability to respond, monitor, learn, and anticipate risks, and in so doing to move away from the flawed frequency and consequences approach. Using a research station network in the Arctic as an example illustrates how an RE approach qualifies assessments by bridging risk assessments with value-creation processes. The article concludes by arguing that a resilience-based risk assessment can improve on current practice, including for organizations located outside the Arctic region.

Benefits, barriers, and incentives for improved resilience to disruption in university teaching

Pandemics, earthquakes, fire, war, and other disasters place universities at risk. Disasters can disrupt learning and teaching (L&T) for weeks to months or longer. Some institutions have developed business continuity plans to protect key organisational services and structures, allowing L&T to continue. However, little research touches on how academics, learners, and communities of practice might respond before, during, and after disasters and how their resilience to disruption can be fostered to reduce impacts on L&T. In this research, we investigated academics' perceptions of building resilience to major L&T disruptions in the New Zealand context. Specifically, we explored how academics characterise a resilient academic and institution, and identified the benefits, barriers, and incentives to building resilience. We used a pragmatic theoretical approach with a mixed methods methodology, to categorise the results within three distinct levels (individual, school/department, and institution), supporting the design and implementation of resilience-building strategies for academics and institutional leaders. We found that support, community, leadership, and planning at universities are critical in building and inhibiting resilience. Participants reported several 'high impact' incentives, addressing multiple barriers, that could be used to kick-start resilience. Online and flexible learning are key opportunities for resilience-building, but universities should not underestimate the importance of face-to-face interactions between staff and learners. Our results provide a strong starting point for practitioners and researchers aiming to understand how universities can foster resilience to major disruptions and disasters on university teaching.

Measuring the resilience of criminogenic ecosystems to global disruption: A case-study of COVID-19 in China

This paper uses resilience as a lens through which to analyse disasters and other major threats to patterns of criminal behaviour. A set of indicators and mathematical models are introduced that aim to quantitatively describe changes in crime levels in comparison to what could otherwise be expected, and what might be expected by way of adaptation and subsequent resumption of those patterns. The validity of the proposed resilience assessment tool is demonstrated using commercial theft data from the COVID-19 pandemic period. A 64 per cent reduction in crime was found in the studied city (China) during an 83-day period, before daily crime levels bounced back to higher than expected values. The proposed resilience indicators are recommended as benchmarking instruments for evaluating and comparing the global impact of COVID-19 policies on crime and public safety.

Measuring the resilience of criminogenic ecosystems to global disruption: A case-study of COVID-19 in China

This paper uses resilience as a lens through which to analyse disasters and other major threats to patterns of criminal behaviour. A set of indicators and mathematical models are introduced that aim to quantitatively describe changes in crime levels in comparison to what could otherwise be expected, and what might be expected by way of adaptation and subsequent resumption of those patterns. The validity of the proposed resilience assessment tool is demonstrated using commercial theft data from the COVID-19 pandemic period. A 64 per cent reduction in crime was found in the studied city (China) during an 83-day period, before daily crime levels bounced back to higher than expected values. The proposed resilience indicators are recommended as benchmarking instruments for evaluating and comparing the global impact of COVID-19 policies on crime and public safety.

Advancements to the Multi-System Model of Resilience: updates from empirical evidence

In this paper, we discuss further advancements to the Multi-System Model of Resilience through examining empirical factor structures of the Multi-System Model of Resilience Inventory along with other measures of resilience. Evidence from multiple sampled populations provided support for the three-systems organization of the model and highlight its similarities and differences in relation to other measures of resilience. The MSMR conceptualizes resilience as a capacity that enables functioning across a continuum from vulnerability to resilience, whereby internal and external resources interface with dynamic coping processes in response to varying needs and goals. Meaningful applications of this model and future steps in model and measurement developments are discussed.

MCDA Index Tool: an interactive software to develop indices and rankings

A web-based software, called MCDA Index Tool (https://www.mcdaindex.net/), is presented in this paper. It allows developing indices and ranking alternatives, based on multiple combinations of normalization methods and aggregation functions. Given the steadily increasing importance of accounting for multiple preferences of the decision-makers and assessing the robustness of the decision recommendations, this tool is a timely instrument that can be used primarily by non-multiple criteria decision analysis (MCDA) experts to dynamically shape and evaluate their indices. The MCDA Index Tool allows the user to (i) input a dataset directly from spreadsheets with alternatives and indicators performance, (ii) build multiple indices by choosing several normalization methods and aggregation functions, and (iii) visualize and compare the indices' scores and rankings to assess the robustness of the results. A novel perspective on uncertainty and sensitivity analysis of preference models offers operational solutions to assess the influence of different strategies to develop indices and visualize their results. A case study for the assessment of the energy security and sustainability implications of different global energy scenarios is used to illustrate the application of the MCDA Index Tool. Analysts have now access to an index development tool that supports constructive and dynamic evaluation of the stability of rankings driven by a single score while including multiple decision-makers' and stakeholders' preferences.

MCDA Index Tool: an interactive software to develop indices and rankings

A web-based software, called MCDA Index Tool (https://www.mcdaindex.net/), is presented in this paper. It allows developing indices and ranking alternatives, based on multiple combinations of normalization methods and aggregation functions. Given the steadily increasing importance of accounting for multiple preferences of the decision-makers and assessing the robustness of the decision recommendations, this tool is a timely instrument that can be used primarily by non-multiple criteria decision analysis (MCDA) experts to dynamically shape and evaluate their indices. The MCDA Index Tool allows the user to (i) input a dataset directly from spreadsheets with alternatives and indicators performance, (ii) build multiple indices by choosing several normalization methods and aggregation functions, and (iii) visualize and compare the indices' scores and rankings to assess the robustness of the results. A novel perspective on uncertainty and sensitivity analysis of preference models offers operational solutions to assess the influence of different strategies to develop indices and visualize their results. A case study for the assessment of the energy security and sustainability implications of different global energy scenarios is used to illustrate the application of the MCDA Index Tool. Analysts have now access to an index development tool that supports constructive and dynamic evaluation of the stability of rankings driven by a single score while including multiple decision-makers' and stakeholders' preferences.

The case for value chain resilience

Purpose

Value chain analyses that help businesses build competitive advantage must include considerations of unpredictable shocks and stressors that can create costly business disruptions. Enriching value chain analysis with considerations of system resilience, meaning the ability to recover and adapt after adverse events, can reduce the imposed costs of such disruptions.

Design/methodology/approach

The paper provides a perspective on resilience as both an expansion and complement of risk analysis. It examines applications of both concepts within current value chain literature and within supply chain literature that may inform potential directions or pitfalls for future value chain investigations. Established frameworks from the broader field of resilience research are proposed for value chain resilience analysis and practice.

Findings

The synthesis reveals a need to expand value chain resilience analysis to incorporate phases of system disruption. Current explorations in the literature lack an explicit acknowledgement and understanding of system-level effects related to interconnectedness. The quantification methods proposed for value chain resilience analysis address these gaps.

Originality/value

Using broader resilience conceptualizations, this paper introduces the resilience matrix and three-tiered resilience assessment that can be applied within value chain analyses to better safeguard long-term business feasibility despite a context of increasing threats.

Assessing resilience of healthcare infrastructure exposed to COVID-19: emerging risks, resilience indicators, interdependencies and international standards

In the moment of preparation of this paper, the world is still globally in grip of the Corona (COVID-19) crisis, and the need to understand the broader overall framework of the crisis increases. As in similar cases in the past, also with this one, the main interest is on the “first response”. Fully appreciating the efforts of those risking their lives facing pandemics, this paper tries to identify the main elements of the larger, possibly global, framework, supported by international standards, needed to deal with new (emerging) risks resulting from threats like Corona and assess the resilience of systems affected. The paper proposes that future solutions should include a number of new elements, related to both risk and resilience. That should include broadening the scope of attention, currently focused onto preparation and response phases, to the phases of “understanding risks”, including emerging risks, and transformation and adaptation. The paper suggests to use resilience indicators in this process. The proposed approach has been applied in different cases involving critical infrastructures in Europe (energy supply, water supply, transportation, etc., exposed to various threats), including the health system in Austria. The detailed, indicator-based, resilience analysis included mapping resilience, resilience stress-testing, visualization, etc., showing, already before the COVID-19, the resilience (stress-testing) limits of the infrastructures. A simpler (57 indicator based) analysis has, then been done for 11 countries (including Austria). The paper links these results with the options available in the area of policies, standards, guidelines and tools (such as the RiskRadar), with focus on interdependencies and global standards—especially the new ISO 31,050, linking emerging risks and resilience.

A multi-hazards earth science perspective on the COVID-19 pandemic: the potential for concurrent and cascading crises

Meteorological and geophysical hazards will concur and interact with coronavirus disease (COVID-19) impacts in many regions on Earth. These interactions will challenge the resilience of societies and systems. A comparison of plausible COVID-19 epidemic trajectories with multi-hazard time-series curves enables delineation of multi-hazard scenarios for selected countries (United States, China, Australia, Bangladesh) and regions (Texas). In multi-hazard crises, governments and other responding agents may be required to make complex, highly compromised, hierarchical decisions aimed to balance COVID-19 risks and protocols with disaster response and recovery operations. Contemporary socioeconomic changes (e.g. reducing risk mitigation measures, lowering restrictions on human activity to stimulate economic recovery) may alter COVID-19 epidemiological dynamics and increase future risks relating to natural hazards and COVID-19 interactions. For example, the aggregation of evacuees into communal environments and increased demand on medical, economic, and infrastructural capacity associated with natural hazard impacts may increase COVID-19 exposure risks and vulnerabilities. COVID-19 epidemiologic conditions at the time of a natural hazard event might also influence the characteristics of emergency and humanitarian responses (e.g. evacuation and sheltering procedures, resource availability, implementation modalities, and assistance types). A simple epidemic phenomenological model with a concurrent disaster event predicts a greater infection rate following events during the pre-infection rate peak period compared with post-peak events, highlighting the need for enacting COVID-19 counter measures in advance of seasonal increases in natural hazards. Inclusion of natural hazard inputs into COVID-19 epidemiological models could enhance the evidence base for informing contemporary policy across diverse multi-hazard scenarios, defining and addressing gaps in disaster preparedness strategies and resourcing, and implementing a future-planning systems approach into contemporary COVID-19 mitigation strategies. Our recommendations may assist governments and their advisors to develop risk reduction strategies for natural and cascading hazards during the COVID-19 pandemic.

COVID, resilience, and the built environment

This article provides a perspective on the reciprocal relationships between public and private sector resilience planning activities and the ongoing COVID responses in the U.S. Through the lens of the built environment, this article provides selected insights into how various disaster, organizational, and engineering resilience activities have likely positively shaped COVID responses within the healthcare sector. These positive influences are contextualized within extensive efforts within public health and healthcare management to calibrate community resilience frameworks and practices for utilization in everything from advancing community health to the continuity of facilities operations. Thereafter, the article shifts focus to speculate on how ongoing experiences under COVID might yield positive impacts for future resilience designs, plans and policies within housing and the built environment. Through this perspective, the article hopes to explore those often overlooked aspects of the physical and social parameters of the built environment that may be understood as providing opportunities to inform future disaster, public health, and climate change preparations and responses.

Constructing a comprehensive disaster resilience index: The case of Italy

Measuring disaster resilience is a key component of successful disaster risk management and climate change adaptation. Quantitative, indicator-based assessments are typically applied to evaluate resilience by combining various indicators of performance into a single composite index. Building upon extensive research on social vulnerability and coping/adaptive capacity, we first develop an original, comprehensive disaster resilience index (CDRI) at municipal level across Italy, to support the implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030. As next, we perform extensive sensitivity and robustness analysis to assess how various methodological choices, especially the normalisation and aggregation methods applied, influence the ensuing rankings. The results show patterns of social vulnerability and resilience with sizeable variability across the northern and southern regions. We propose several statistical methods to allow decision makers to explore the territorial, social and economic disparities, and choose aggregation methods best suitable for the various policy purposes. These methods are based on linear and non-liner normalization approaches combining the OWA and LSP aggregators. Robust resilience rankings are determined by relative dominance across multiple methods. The dominance measures can be used as a decision-making benchmark for climate change adaptation and disaster risk management strategies and plans.

Network Reconfiguration for Increasing Transportation System Resilience Under Extreme Events

Evacuating residents out of affected areas is an important strategy for mitigating the impact of natural disasters. However, the resulting abrupt increase in the travel demand during evacuation causes severe congestions across the transportation system, which thereby interrupts other commuters' regular activities. In this article, a bilevel mathematical optimization model is formulated to address this issue, and our research objective is to maximize the transportation system resilience and restore its performance through two network reconfiguration schemes: contraflow (also referred to as lane reversal) and crossing elimination at intersections. Mathematical models are developed to represent the two reconfiguration schemes and characterize the interactions between traffic operators and passengers. Specifically, traffic operators act as leaders to determine the optimal system reconfiguration to minimize the total travel time for all the users (both evacuees and regular commuters), while passengers act as followers by freely choosing the path with the minimum travel time, which eventually converges to a user equilibrium state. For each given network reconfiguration, the lower-level problem is formulated as a traffic assignment problem (TAP) where each user tries to minimize his/her own travel time. To tackle the lower-level optimization problem, a gradient projection method is leveraged to shift the flow from other nonshortest paths to the shortest path between each origin-destination pair, eventually converging to the user equilibrium traffic assignment. The upper-level problem is formulated as a constrained discrete optimization problem, and a probabilistic solution discovery algorithm is used to obtain the near-optimal solution. Two numerical examples are used to demonstrate the effectiveness of the proposed method in restoring the traffic system performance.

Decision-Making Analytics Using Plural Resilience Parameters for Adaptive Management of Complex Systems

It is critical for complex systems to effectively recover, adapt, and reorganize after system disruptions. Common approaches for evaluating system resilience typically study single measures of performance at one time, such as with a single resilience curve. However, multiple measures of performance are needed for complex systems that involve many components, functions, and noncommensurate valuations of performance. Hence, this article presents a framework for: (1) modeling resilience for complex systems with competing measures of performance, and (2) modeling decision making for investing in these systems using multiple stakeholder perspectives and multicriteria decision analysis. This resilience framework, which is described and demonstrated in this article via a real-world case study, will be of interest to managers of complex systems, such as supply chains and large-scale infrastructure networks.

A multicountry comparative survey about organizational resilience in anaesthesia

RATIONALE, AIMS, AND OBJECTIVES

The application of resilience in health care requires the shift from a cause-effect approach to a systemic approach, yet few tools have been developed to measure resilience potential in this specific context. This study tests a resilience assessment grid (RAG) questionnaire to measure the resilience of anaesthesiologists, with a cross-country survey.

METHOD

A study was conducted with an analytic hierarchy process (AHP) questionnaire containing 57 detailed questions; 16 nations and 172 respondents were involved in the study. The data were statistically analysed to identify insights from the questionnaire, main improvements for further assessment, and confirmation of the design of the questionnaire. The questionnaire reliability was assessed by Cronbach analysis. Weak items were identified by a detailed correlations analysis and through a weight-polarization matrix. Construct validity was confirmed by principal component analysis (PCA) and factor analysis (FA).

RESULTS

The α level of Cronbach analysis is 0.910. PCA and FA confirmed the absence of underlying unexpected factors, with less than 8% from the first factor and a total of just 54% of variability explained by 17 factors. Suggestions for revising the questionnaire ensue from the analysis, with improvements for the questionnaire's significance.

CONCLUSION

The questionnaire shows the potential to assess proxy measures of resilience, even confirming the relevance of a structured weighting approach based on the AHP. The exemplar statistical cross-country analyses encourage the widespread use of a centralized resilience questionnaire to support standardized analyses and the diffusion of best practices among organizations.