Abstract: Scenarios are frequently used in Emergency Planning and Preparedness. These scenarios are developed based on the hypothesis of occurrence or not of significant events. This is a complex process because of the interrelations between events. This fact, along with the uncertainty about the occurrence or non-occurrence of the events, makes the scenario generation process a challenging issue for emergency managers. In this work a new step-by-step model for clustering scenarios via cross-impact is proposed. The authors. proposal adds tools for detecting critical events and graphical representation to the previous scenario-generation methods based on Cross-Impact Analysis. Moreover, it allows working with large sets of events without using great computational infrastructures. These contributions are expected to be useful for supporting the analysis of critical events and risk assessment tasks in Emergency Planning and Preparedness. Operational issues and practical implications of the model are discussed by means of an example.

Abstract: In recent years Cross-Impact Analysis (CIA) has resurged as a powerful tool for forecasting the occurrence or not of a set of interrelated events in complex situations, such as emergencies. In this sense, CIA can be used for creating working models out of significant events and crisis scenarios. CIA has been combined with other methodological approaches in order to increase its functionality and improve its final outcome. This is the case of the merger of CIA and the technique called Interpretive Structural Modeling (ISM). The CIA-ISM approach aims at contributing to CIA with tools for detecting critical events and supporting graphical representation of scenarios. In this paper, major extensions to CIA-ISM are presented. These extensions are based on the inclusion of initial condition events and outcome events as two new event types that make CIA-ISM much richer in its potential span of application areas. The practical implications of these major extensions to CIA-ISM are illustrated with an example. The usefulness of this contribution to researchers and practitioners concerned with emergency planning and preparedness is also discussed.

Abstract: Companies work increasingly more on projects as a means of executing organizational decisions. However, too many enterprise projects result in failure. Hence, firms should follow a risk management method that drives their projects toward success. Nevertheless, project managers often deal with risks intuitively. This is partly because they lack the proper means to correctly manage the underlying risks which affect the entire cycle of their projects. Therefore, one purpose is to identify the critical events that managers may encounter before the beginning of the project and during its development. In addition, we propose CIA-ISM to represent existing relationships between the unforeseen events in the project?s lifetime and their key performance indicators. This also predicts the influence of risks on project performance over time by means of scenarios. The tool proposed would thus help practitioners to manage enterprise projects risks in a more effective and proactive way. We have validated the predictive capability of the CIA-ISM model with 22 real projects. The results show a high level of predictive capability in terms of risk analysis and key performance indicators.