Development of a multi-risk index for Italy: a tool for supporting informed decision making on disaster risk reduction prioritisation

Effective disaster-risk management decision making relies on holistic multi-risk quantification approaches. Such approaches should capture the effects of multiple (natural) hazards, facilitating the development and implementation of appropriate preparedness and mitigation strategies. They should also account for social vulnerability factors, which may significantly influence how different communities respond to and cope with hazardous events. We propose a straightforward multi-risk index that integrates both of these crucial considerations. The index appropriately accounts for uncertainties, relying on probabilistic distributions of hazard inputs, physical and social vulnerability indices, and population exposure for each individual risk of interest. The resulting individual risk scores are combined through suitable weights that explicitly reflect variable stakeholder perspectives in related policymaking. We demonstrate the index for earthquake and flood risk across the entire country of Italy (at the resolution of municipalities) using easily accessible data. The proposed metric identifies hotspots across the Italian territory that should be prioritised for actions that promote disaster risk reduction. Sensitivity analyses of metric weights reveal how these hotspots can change as a function of stakeholder preferences and/or variations in the emphasis placed on different types of hazards, ultimately underlining the importance of accounting for accurate stakeholder feedback and adopting a holistic view of risk in disaster-related decision making. A prominent advantage of the proposed index is that it is relatively simple and could be easily adopted for practical multi-risk decision support across any other national or transnational context of interest

EXPERIENCES WITH TRADITIONAL COMPENSATORY FINANCE SCHEMES AND LESSONS FROM FLEX

This paper describes some policy instruments set up by the IMF and the European Union in order to provide financial assistance to developing countries whose economies are affected by exogenous shocks from exports side. After briefly reviewing the IMF’s CFF and the EU’s STABEX, the paper presents the operational rules of FLEX and comments on how it functioned from 2000 to 2007. The analysis shows that the FLEX facility suffered from there being inadequate finance allocated to ACPs and from delays in the financing procedure. While these constraints greatly limited the impact of FLEX in the application years 2000-2006, the 2008 FLEX revision eased them and, now, FLEX can guarantee financial support more rapidly than in the past and may more satisfactorily cover the financial requirements of ACPs coping with export earnings instability.Developing Countries, Export Earnings Instability, Budget Support

Enablers of post-COVID-19 customer demand resilience: Evidence from fast-fashion MSMEs

This study aims to analyse the resilience of customer demand management in post-coronavirus disease (COVID) 2019, using fast fashion as an example. The paper provides insights for potential applications to micro, small, and medium enterprises (MSMEs). Based on the qualitative analysis and an integrated PDCA-DEMATEL-fuzzy technique for order of preference by similarity to the ideal solution (TOPSIS) methodology of fuzzy multi-criteria decision-making, we explored and prioritised the enablers of resilience management for fast-fashion MSMEs. The results reveal that the highest priority enabler is maintaining customer loyalty. Other enablers are associated with e-commerce endorsement, a customer-focused assortment of items, and flexible store operations. The study findings will enable fast-fashion MSMEs to develop effective actions and priorities in operations efforts to promote post-pandemic recovery. Despite the importance of the resilience project and the changing fast-fashion customer patterns, only a handful of studies have explored how resilience can be managed in this field. Thus, the findings can contribute to closing this gap in the context of operations resilience research as well as MSME operations

FlowSort-GDSS:a novel group multi-criteria decision support system for sorting problems with application to FMEA

Failure mode and effects analysis (FMEA) is a well-known approach for correlating the failure modes of a system to their effects, with the objective of assessing their criticality. The criticality of a failure mode is traditionally established by its risk priority number (RPN), which is the product of the scores assigned to the three risk factors, which are likeness of occurrence, the chance of being undetected and the severity of the effects. Taking a simple "unweighted" product has major shortcomings. One of them is to provide just a number, which does not sort failures modes into priority classes. Moreover, to make the decision more robust, the FMEA is better tackled by multiple decision-makers. Unfortunately, the literature lacks group decision support systems (GDSS) for sorting failures in the field of the FMEA. In this paper, a novel multi-criteria decision making (MCDM) method named FlowSort-GDSS is proposed to sort the failure modes into priority classes by involving multiple decision-makers. The essence of this method lies in the pair-wise comparison between the failure modes and the reference profiles established by the decision-makers on the risk factors. Finally a case study is presented to illustrate the advantages of this new robust method in sorting failures

Structuring composite local governance indicators

The importance of good governance is praised by many academics and practitioners. The prominence of the subject suggests that measurement is important. However, setting out to measure the quality of governance empirically is controversial. Doubts regarding the feasibility and meaningfulness of this undertaking are widespread in the literature. Recognizing the potential caveats, the current article discusses a set of guidelines for structuring a theoretically-sound local governance assessment tool based on the Decision Analysis and Operational Research literatures. The authors argue that using a multi-criteria model which employs several objective (quantitative and qualitative) indicators and relies on a participatory method to aggregate them is a suitable way of developing sensible Local Governance Indicators. The purpose here is to provide a detailed roadmap for any country (or region, or locality) willing to engage in the assessment of the qualityof local governance. The real-world implementation of a model developed according to these guidelines could help raise awareness, promote good practices, and increase the ‘governance literacy’ of citizens. By operationalizing good governance, analysts may also be able to further investigate the relationships between local governance practices and several socio-economic factors

Safe and sustainable by design chemicals and materials. Framework for the definition of criteria and evaluation procedure for chemicals and materials

The EU CSS action plan foresees the development of a framework to define safe and sustainable by design (SSbD) criteria for chemicals and materials. The SSbD is an approach to support the design, development, production and use of chemicals and materials that focuses on providing a desirable function (or service), while avoiding or minimising harmful impacts to human health and the environment. The SSbD concept integrates aspects for the domain of safety, circularity and functionality of chemicals and materials, with sustainability consideration throughout their lifecycle, minimising their environmental footprint. SSbD aims at facilitating the industrial transition towards a safe, zero pollution, climate-neutral and resource-efficient economy, addressing adverse effects on humans, ecosystems and biodiversity from a lifecycle perspective. To fulfil these ambitions, there is the need to develop a new framework for the definition of safe and sustainable by design criteria for chemicals and materials. To do so, several frameworks were reviewed including initiatives from research, industry, governmental agencies and NGOs. Capitalising on this information, a framework was developed and is presented in this report including a methodology for the definition of possible SSbD criteria and implementation mechanisms

How should we be using biomarkers in trials of disease modification in Parkinson’s disease?

The recent validation of the alpha synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson’s disease has formed the backbone for a proposed staging system for incorporation in Parkinson’s disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson’s disease patients into trials (as distinct from patients with non- Parkinson’s disease parkinsonism or non- Parkinson’s disease tremors). There remain however further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson’s disease, namely: optimising the distinction between different alpha synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; as sensitive means of confirming target engagement; and in the early prediction of longer-term clinical benefit. For example; levels of cerebrospinal fluid proteins such as the lysosomal enzyme ß-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer disease like pathology (detectable through cerebrospinal fluid levels of Amyloid Beta-42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline of Parkinson’s disease even in its later stages. The exploitation of additional biomarkers to the alpha synuclein seed amplification assay will therefore greatly add to our ability to plan trials and assess disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson’s disease. However, correlation with clinical progression does not necessarily equate to causation and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson’s disease