Historic areas (HAs) are highly vulnerable to natural hazards, including earthquakes, that can cause severe damage, if not total destruction. This paper proposes methods that can be implemented through a geographical information system to assess earthquake-induced physical damages and the resulting impacts on the functions of HAs and to monitor their resilience. For the assessment of damages, making reference to the universally recognised procedure of convoluting hazard, exposure, and vulnerability, this paper proposes (a) a framework for assessing hazard maps of both real and end-user defined earthquakes; (b) a classification of the exposed elements of the built environment; and (c) an index-based seismic vulnerability assessment method for heritage buildings. Moving towards the continuous monitoring of resilience, an index-based assessment method is proposed to quantify how the functions of HAs recover over time. The implementation of the proposed methods in an ad hoc customized WebGIS Decision Support System, referred to as ARCH DSS, is demonstrated in this paper with reference to the historic area of Camerino-San Severino (Italy). Our conclusions show how ARCH DSS can inform and contribute to increasing awareness of the vulnerabilities of HAs and of the severity of the potential impacts, thus supporting effective decision making on mitigation strategies, post-disaster response, and build back better.

Risks related to climate change and natural hazards increasingly affect urban areas such as historic towns, old urban quarters, villages, and hamlets. These, as well as historic landscapes, make up a significant part of an urban area’s identity and cannot just be rebuilt or significantly changed without taking into account the historic value, cultural background, and prescribed regulations. Systematic resilience building for historic areas is becoming essential, and research supporting it will be in the spotlight. However, questions still exist concerning how to best transfer research results into practice at the community level. Standardization of resilience-enhancing methods and tools deriving from research projects is one option, chosen, e.g., for the EU-Horizon 2020 project ARCH. Within the project, a disaster risk management (DRM) framework has been composed and then transferred into a standard, supported by a co-creation approach involving relevant stakeholders. This article outlines the project’s different standardization steps and its impact on the development of the ARCH DRM Framework. It highlights the systematic inclusion of project-external stakeholders who actively contribute to the validation and enhancement of the ARCH DRM framework to guarantee maximum applicability in historic areas, supporting them in their fight against the impacts of climate change and natural hazards.

A high organizational complexity above the cognitive limits of employees and management can contribute to a business performing sub-standardly in comparison to its competitors. As businesses can grow over time into a state of high complexity, an active approach to complexity management has to be taken. This paper presents the NES classification method, aimed at facilitating the modeling and assessment of organizational complexity. Here, any system is classified as belonging to one of three classes: class N natural, class E engineered, or class S slipped systems. Operationalizing NES by applying the Tree Attribute Matrix modeling method, this paper describes exemplary observations made as part of consulting projects that demonstrated typical underperformance situations resulting from their organizations “slipping” into structures of high complexity, and includes management measures to reduce complexity and thereby improve performance.

Simulation Notes Europe SNE 22(2), 2012, 61-68DOI: 10.11128/sne.22.tn.10121