A Knowledge Elicitation Approach to Improving Security Management Systems in the Humanitarian Sector

Abstract

Many humanitarian organisations adopt top-down systems to keep staff safe, which seek to quantify risk and avoid this by controlling the way staff operate. This limits the role of knowledge from experienced humanitarian workers, which weakens systems by providing training that is generic and procedures which do not match the reality of the ground. Knowledge management theory provides a solution and recommendations to effectively convert and share knowledge.
This thesis explores top-down knowledge and bottom-up knowledge to understand how they are similar and how they are different. The research focuses on identifying effective methods at eliciting different types of knowledge requirement. As security is a sensitive domain, it also discusses methods of accessing participants and eliciting information from those who may not
want to provide it. The methods used as evaluated against how well they elicited knowledge, their practical application, the feasibility to be conducted by others and how well they accessed the sensitive domain.
The primary research was split into two parts. Stage 1 collected top-down knowledge requirements and Stage 2 collected bottom-up knowledge requirements. Participants were selected on their domain expertise from groups representing security experts and field workers. A critical comparison of the knowledge collected showed that knowledge between security experts and experienced field workers had more similarity than difference, contradicting what
was stated in the literature. Two methods used are noteworthy because of their novel application- a systematic document analysis, combining both systematic review and document analysis and scenario-based discussions which use three specialist knowledge elicitation methods: Limited Task Analysis, Process Mapping and Critical-Decision Method. Both were effective at eliciting knowledge and produced usable findings.
The thesis contributes a new hypothesis to research: that a gap exists with the knowledge in novice workers, which the SECI model can fill. The synthesis of the requirements list from the two stages resulted in a combined list of 9 top-down/bottom-up, expert elicited requirements inventory. Recommendations are made on how this can be applied by humanitarian organisations. Two novel research methods have also been trialled and deemed effective for knowledge elicitation in sensitive domains.

Date of Award	Sept 2018
Original language	English
Awarding Institution	Coventry University