Information sharing for coordinated self-organisation in disasters

Abstract

Fostering disaster resilience depends on effective coordination between diverse groups. At the same time, the volatile conditions of a disaster require different actors to self-organize in a decentralized way. While information sharing has been described as central to both coordination and self-organization, effective information management remains challenging during disasters, given shifting organizational patterns, evolving roles, changing information needs, and the high information load caused by volatility. This thesis addresses these challenges by analyzing coordinated self-organization through effective inter-group information exchange between communities and professional responders during disasters (1).

This thesis puts forward a way to systematically study disaster information sharing from an actor-centered perspective through a combination agent-based modeling and empirical case study research. It does so by developing a methodology to create Agent-Based Models (ABMs) for studying disaster information sharing through qualitative inquiry (2). This approach is chosen given the challenges of gathering quantitative data about disaster response (e.g., through surveys and disaster simulation exercises).

The methodology was applied to the case of Jakarta to develop an empirical descriptive ABM. Findings from case study research and simulations with this ABM show that, when actors are unaware of the information they need (i.e., their needs are latent), delivering information on time to them becomes particularly challenging. Further, the results show that communities tend to address a higher portion of their information needs compared to professional responders (3,2). Communities’ highly localized situational awareness needs to be combined with a more global perspective concerning a disaster and its development to foster effective coordination. To achieve this, a two-way communication between professional response organizations and communities is essential.

The empirical ABM was then extended and abstracted from the Jakarta case to develop a theoretical ABM to study the emergence of Informational Boundary Spanners (IBSs); i.e. of actors that facilitate inter-group information exchange. Findings from simulations with this ABM suggest that individually learning who provides high-quality information is a mechanism that fosters the emergence of IBSs (4). This collectively intelligent behavior is contingent on stable information sources and a high number of trusted inter-group connections among communities and professional response organizations, especially at high levels of volatility (4).

The methodology proposed in this thesis provided the means to systematically study actor-centered disaster information sharing. First, the methodology was found to be rigorous in translating qualitative data into ABMs, and to provide a way to balance cross-case comparability with the flexibility to capture the nuances of specific cases (1,2). Second, the methodology was found to be versatile in developing both empirical and theoretical ABMs to study actor centered disaster information sharing, including mechanisms leading to the emergence of intergroup information exchange during disasters (2,4).

Future research will focus on exploring synergies among coordinated self-organization, collective intelligence, and resilience beyond the context of disaster response, concentrating on how collective learning, sensing, and remembering can foster adaptive, transformative, and absorptive resilience capacities in both the short and long term.