Disruption and Disaster Management

Abstract

Abstract Disruption and disaster management (DM) are inseparable concepts with reciprocal influence. While DM’s objective is to achieve resiliency, disruption level is a key determinant. However, the disruption might not be foreseeable and strike on short notice. Thus, having knowledge to effectively respond to it is crucial, and learning from best practices is envisaged as the most feasible way to deal with it. However, it is important to have a representative mechanism to allow learning to happen. This is approached by advocating a DM knowledge analysis framework, an agent-based modelling framework rooted in agent-oriented software engineering that can represent social-technical attributes of DM activities. The framework also has the ability to well-knit formal and local knowledge for a more complete one, facilitating a better decision-making mechanism in DM. This chapter shows the efficacy and effectiveness of the framework in various real case studies, as well as limitations and future research directions.