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Crises are becoming more and more frequent. Whether natural disasters, economic crises, political events, or a pandemic - the right action mitigates the impact. The PAIRS project plans to minimize the surprise effect of these and to recommend appropriate actions based on data using artificial intelligence (AI). This paper conceptualizes a cascading model based on scenario technique, which acts as the basic approach in the project. The long-term discipline of scenario technique is integrated into the discipline of crisis management to enable short-term and continuous crises management in an automated manner. For this purpose, a practical crisis definition is given and interpreted as a process. Then, a cascading model is derived in which crises are continuously thought through using the scenario technique and three types of observations are classified: Incidents, disturbances, and crises. The presented model is exemplified within a non-technical application of a use case in the context of humanitarian logistics and the COVID-19 pandemic. Furthermore, first technical insights from the field of AI are given in the form of a semantic description composing a knowledge graph. In summary, a conceptual model is presented to enable situation-based crisis management with automated scenario generation by combining the two disciplines of crisis management with scenario technique.
Crises pose significant short and long-term threats to companies. The research project PAIRS aims to strengthen the resilience of actors in the supply-chain, en-ergy, and healthcare sectors in crisis situations. The basis for this is the newly created potential in data exchange, which is leveraged by combining internal with external (company-)data, e.g. in the GAIA-X network. AI is then the key to iden-tifying the time of the crisis and deriving appropriate actions to deal with it. Therefore, crisis scenarios are generated, and risks are assessed. In this paper, the project fundamentals are discussed. This includes the development of a project definition of the term "crisis", which is based on literature research of various scientific disciplines (e.g. economics or political science), as well as interviews with professional and academic experts from different fields. Moreover, a specif-ic example from the supply-chain domain is introduced to illustrate the process of requirement identification.