Search results

Recent changes in climate, rainfall patterns, snow melt and rising sea levels coupled with an increase in urban development have increased the threat of flooding. To curb these threats and mitigate these damages, property-level approaches to improving resilience are now being encouraged as part of an integrated approach to flood risk management. This raises questions such as, what are the flood resilient attributes within individual properties, what is their importance and how can these be quantified. This research sought to develop a quantitative approach for the measurement of property-level flood resilience.

A synthesis of literature was undertaken to establish the main resilient attributes and their relevant sub-attributes. This process led to the development of a new method, named the Composite Flood Resilient Index (CFRI) to weight the attributes and sub-attributes of flood resilience based on their importance. The approach adopts the use of the fuzzy-analytic hierarchy process (F-AHP) approach to quantify flood resilience.

The implications of the proposed methodology in determining the flood resilience of individual property, including the potential use in retrofitting activities, and the benefits to a range of stakeholders are considered.

The methodology offers the potential to support the measurement of flood resilience of individual properties, allowing the identification and prioritisation of specific interventions to improve the resilience of a property.

Whereas previous attempts to quantify flood resilience have adopted qualitative approaches with some level of subjectivity, this proposed methodology represents an important advancement in developing a scientific and quantitative approach.

Despite the proliferation of supply chain risk management (SCRM) studies, a theoretically supported and empirically validated study on justifying the antecedents and measurement dimensions of supply chain resilience (SCRE) is rare. Therefore, drawing on extensive literature review, this study aims to explore and validate the antecedents and the measurement dimensions of SCRE.

This study uses positivist paradigm using quantitative method. However, it also uses qualitative approach in the form of field study to contextualize the research model. The quantitative study is conducted by operationalising a survey research. Partial least square-based structural equation modelling has been used to analyze the data.

Study results suggest that the psychometric properties of the SCRE dimensions, supply chain readiness, response and recovery, are reliable and valid. It also affirms that supply chain orientation (SCO), learning and development and supply chain risk management culture (SCRMC) significantly influence the SCRE. Further, SCRMC mediates the relationship between SCO and SCRE.

The findings of this study will assist the supply chain managers in taking decision on readiness capability development and reducing the decisional uncertainty during response and recovery.

Drawing on extensive extant literature on crisis management and supply chain management, this study develops and validates the measurement dimensions of SCRE in terms of readiness, response and recovery, as well as justifies the antecedent factors of SCRE, which is a novel attempt in SCRM literature.

The current study aims to identify and classify the financial resilience measurement indices using the intuitive fuzzy approach.

The present study aims to identify and classify firms' indices of financial resilience measurement using the Fuzzy–Delphi combined method and the intuitive fuzzy DEMATEL technique with interval values. For the study and the literature review, 29 financial resilience indices were identified, and 12 were finalised after screening and localisation. Next, the selected indices were classified into two groups of influencing and being influenced, and the significant range of each one was determined. Finally, the executive and research suggestions were presented based on the obtained results.

The study results indicate a higher significance level of redundancy and visibility in financial resilience.

The present study is the pioneer study to assess, identify and classify the contributing indices to financial resilience.

Conceptual interpretations of sustainability and resilience are widening with discursive use and altering the relationship and understanding of both concepts. By using three city case studies in the USA, this paper aims to consider which conceptual interpretations are operational and what is being measured in the context of city policy, municipal planning and built environment practice. With increasing pressures of urbanisation, it is imperative to consider which conceptual interpretations of resilience and sustainability are being measured in frameworks for the built environment if Risk-Informed Sustainable Development across multiple sectors is to be delivered.

Three case studies with semi-structured interviews have been thematically analysed to explore how sustainability and resilience have been operationalised at policy, planning and practice levels.

City policies, municipal planning and practitioners are working with different interpretations. Collectively Risk Informed Sustainable Development is not formally recognised. Policies recognise GHG reductions and natural hazard events; planning guidance stipulates Environmental Impact Assessments based on legal requirements; and practitioners consider passive-survivability and systematic thinking. Across the sectors, the Leadership in Environmental and Energy Assessment Method provides a common foundation but is used with varying requirements.

Decision-makers should incorporate risk-informed sustainable development, update codes of practice and legal requirements leading to exemplary practice becoming normalised.

Passive-survivability should be affordable and adopt risk-informed sustainable development principles.

Three US city case studies with data collected from interviews have been analysed simultaneously at policy, planning and practice levels. Interrelated implications have been outlined on how to improve decision-making of sustainability and resilience across sectors.

Flood resilience is emerging as a major component of an integrated strategic approach to flood risk management. This approach recognizes that some flooding is inevitable and aligns with the concept of “living with water.” Resilience measurement is a key in making business case for investments in resilient retrofits/adaptations, and could potentially be used to inform the design of new developments in flood prone areas. The literature is, however, sparse on frameworks for measuring flood resilience. The purpose of this paper is to describe the development of a fuzzy logic (FL)-based resilience measuring model, drawing on a synthesis of extant flood resilience and FL literature.

An abstraction of the flood resilience system followed by identification and characterization of systems’ variables and parameters were carried out. The resulting model was transformed into a fuzzy inference system (FIS) using three input factors: inherent resilience, supportive facilities (SF) and resident capacity.

The resulting FIS generates resilience index for households with a wide range of techno-economic and socio-environmental features.

It is concluded that the FL-based model provides a veritable tool for the measurement of flood resilience at the level of the individual property, and with the potential to be further developed for larger scale applications, i.e. at the community or regional levels.

Resilience has become a priority of most agendas for disaster risk reduction at different scales leading to an increase demand for measurement of resilience. However, resilience is mostly defined, assessed and measured by outsider experts rather than by those primarily concerned – local people. This article presents the development of people-centred indicators of resilience in New Zealand. It details both the process and outcomes of these indicators.

The study draws from participatory methods to develop a six-step tool kit for people-centred indicators of resilience. The people-centred indicators were implemented with four communities in New Zealand in 2019 and 2020.

The paper highlights that people are capable at defining and assessing their own resilience. The indicators enabled people identify and measure areas of low resilience and foster dialogue between locals and practitioners to strengthen it.

People-centred indicators also have limitations and pose challenges. Their development requires strong facilitation skills; it limitedly enables comparison across communities and implies downward accountability.

The findings should stimulate discussions about who should measure resilience and for whom such measurement is it for. It provides a tool kit that can be used by practitioners and policy makers to measure and strengthen community resilience.

Most resilience indicators is outsider-driven and limitedly involves local people. This study uses a radically different approach placing people at the centre of resilience measurement.

Enterprises often face a wide variety of adverse events. Adverse events can have negative effects on organizations like failures of resources. In case resources fail, they are not available and cannot perform the assigned work. Enterprises are therefore especially interested in how resilient processes and workflows are in case adverse events occur and resources may fail. For this purpose, process resilience measurement approaches are needed.

To measure the resilience of processes and workflows, a life cycle and five quantitative metrics have been developed. The metrics have been validated using five real-world production and logistics cases to show their applicability on process models and paths. Furthermore, workshops have been conducted with professionals to get additional feedback on the contributions.

Based on the results obtained from applying the metrics to five real-world cases, view-based resilience improvements can be derived. Overall, only one of the five real-world cases can be considered as completely resilient. Furthermore, the metrics and life cycle have been especially valued by professionals with respect to transparency, independency, comparability as well as the ability to determine critical process paths.

Several authors have dealt with different aspects related to the measurement of business processes, resilience or a combination thereof. However, a life cycle or metrics to quantitatively measure the resilience of processes by considering resources has not been found yet. The life cycle and metrics are therefore novel. As a future research direction, they can be applied in different domains for further validation purposes.

The purpose of this paper is to present a framework for evaluation and ranking of potential surrogates to select the optimum surrogates and test it for five selected social resilience indicators in a disaster context. Innovative resilience assessment approaches are required to capture key facets of resilience indicators to deepen the understanding of social resilience. Surrogates can adequately represent the target indicator that is difficult to measure, as surrogates are defined as key facets of a target indicator.

To optimize the selection of surrogates, five key evaluation criteria were used. Disaster management experts completed an online survey questionnaire and evaluated three potential surrogate options. Surrogates were then ranked using PROMETHEE, a multi-experts multi-criteria group decision analysis technique.

A framework was devised to evaluate and rank potential surrogates to assess social resilience in a disaster context. The findings revealed that the first ranked surrogate can be the most critical facet of a resilience indicator of measure. In most instances, highly experienced cohort of practitioners and policy makers have aligned their preferences of surrogates with the overall ranking of surrogates obtained in this study.

The surrogate approach can also be tested in different disaster and geographic contexts. The resilience indicators used in this study to explore surrogates are largely applicable in all contexts. However, the preference of surrogates may also vary in different contexts.

Once the surrogate is selected through an evaluation process proposed in this paper, the resilience status can be updated regularly with the help of the selected surrogate. The first ranked surrogate for each of the social resilience indicator can be applied, since the findings revealed that the first ranked surrogate can be the most critical facet in the context of the social resilience indicator being measured.

The framework and the selection of optimal surrogates will assist to overcome the conceptual and methodical challenges of social resilience assessment. The applicability of selected surrogates by practitioners and policymakers in disaster management will play a vital role in resilience investment decision-making at the community level.

The surrogate approach has been used in the fields of ecology and clinical medicine to overcome the challenges in measuring difficult to measure indicators. The use of surrogates in this study to measure social resilience indicators in a disaster context is innovative, which was not yet explored in resilience measurement in disaster management.

Decision-makers, practitioners and community members have a need to assess the disaster resilience of their communities and to understand their own capacities in disaster situations. There is a lack of consensus among researchers as to what resilience means and how it can be measured. This paper proposes a novel technique to achieve consensus among stakeholders on definitions, objectives and indicators for measuring a key dimension of community disaster resilience (CDR), physical infrastructure (PI).

This study uses a five-step approach utilizing Q-methods to contextualize a resilience index for PI. Interviews, focus groups and Q-sorting workshops were conducted to develop a tool that ranked measures according to stakeholder preference. A total of 84 participants took part in the workshops across four countries (United Kingdom, Malaysia, Pakistan and Sri Lanka).

The initial set of 317 measures was reduced to 128 and divided into the three community capacities of anticipatory, absorptive and restorative. The physical infrastructure capacity assessment tool (PI-CAT) was then finalized to have 38 indicators that were also ranked in order of importance by the participants.

The PI-CAT can be useful for local governments and communities to measure their own resilience. The tool allows stakeholders to be confident that the metrics being used are ones that are relevant, important and meet their requirements.

The Q-method approach helps stakeholders to develop and use a community capacity assessment tool that is appropriate for their context. The PI-CAT can be used to identify effective investments that will enhance CDR.

Growth in a number of the supply chain (SC) disruptions threatens the enterprises globally. Earlier studies and reports say that many organizations go out of businesses within two or three years after they experience a major disruption. Therefore, companies in today’s volatile business arena need to possess the necessary resilience level to combat supply china disruptions. This is even more important for organizations of developing nations, which are constantly struggling to gain the advantages of globalization and to grab the new opportunities. Thus, this paper aims to help organizations understand their SC resilience level through a framework.

The methodology comprises integrated Delphi – fuzzy logic approach in identifying formative elements of SC resilience from a diverse resilience related body of knowledge and distinguish key obstacles of SC resilience based on their performance level.

Findings reveal that SC flexibility components such as sourcing, manufacturing and logistic flexibility are the major contributors of SC resilience index of case organization. Similarly, lack of risk management culture, inter-organizational relationships, information sharing and integration of SC stakeholders are the major inhibitors of resilience. Thus, the organization needs to overcome these identified obstacles to enhance their SC resilience level.

Present study offers a novel focus of research on SC resilience measurement that is significant for understanding the level of immunity enterprises possess to unanticipated SC interruptions, and the ability to bounce back after an unforeseen event.

This paper proposes an integrated Delphi – fuzzy logic framework for measuring SC resilience. In doing so, the study identifies key potential inhibitors of SC resilience of the case company under study.