Information use by multi-agency teams in time constrained, uncertain and complex environments

This research investigates information practices issues in a time constrained, uncertain and complex environment with a focus on emergency management. During a major incident, commanders from the multi-agency emergency services such as from the police, fire and rescue, and ambulance need to come together to manage the incident. Depending on the nature of the incident, commanders involved in emergency management vary; hence they meet on an ad-hoc basis. The literature states that information should be shared among members of a team for coordination. It is thus necessary to understand issues underlying information sharing. Also, one of the major tasks in emergency management is to make decisions. From an information science perspective, it is imperative to understand how information is used by decision makers to make decisions. Thus, two research questions of interest are (1) the issues which impact information sharing and (2) how information is used for making decisions. This research takes an interpretive approach in which activity theory is used as a methodological and analytical framework to address these research questions. Investigating the first research question, it was found that different components impact information sharing. These components are grouped into six dimensions providing more holistic understanding of the context, which is advocated in information practices research. A model (the POSSTT model) is proposed as a framework to study information sharing of such ad-hoc multi-agency groups. Addressing the second research question, contributions are made to the ongoing debate on types of decision making. In theory, type 2 (analytical) decision making is promoted by many researchers; however, in practice it was found that in a time constrained environment, decision makers may use a combination of type 1 (intuitive) and type 2 (albeit not deliberative) decision making. A model for how experienced people use information to make decision is proposed. In addition, a need is realised for sub-dividing the experienced decision making model into an "experienced decision maker" model, and, an "experienced and confident decision maker" model. These contributions have practical implication for policy making and system design