Eliciting experts’ knowledge in emergency response organizations

Okoli, Justin, Weller, Gordon ORCID: https://orcid.org/0000-0002-7495-489X and Watt, John ORCID: https://orcid.org/0000-0002-9771-4442 (2014) Eliciting experts’ knowledge in emergency response organizations. International Journal of Emergency Services, 3 (2) . pp. 118-130. ISSN 2047-0894 [Article] (doi:10.1108/IJES-06-2014-0009)

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Purpose: Experienced fire ground commanders are known to make decisions in time-pressured and dynamic environments. The purpose of this paper is to report some of the tacit knowledge and skills expert firefighters use in performing complex fire ground tasks.
Design/Methodology/Approach: This study utilized a structured knowledge elicitation tool, known as the critical decision method (CDM), to elicit expert knowledge. Seventeen experienced fire-fighters were interviewed indepth using a semi-structured CDM interview protocol. The CDM protocol was analyzed using the emergent themes analysis (ETA) approach
Findings: Findings from the CDM protocol reveal both the salient cues sought, which we termed critical cue inventory (CCI), and the goals pursued by the fire ground commanders at each decision point. The CCI is categorized into five classes based on the type of information each cue generates to the incident commanders
Practical Implications: Since the critical decision method is a useful tool for identifying training needs, this study discussed the practical implications for transferring experts’ knowledge to novice firefighters
Originality/Value: Although many authors recognize that experts perform exceptionally well in their domains of practice, the difficulty still lies in getting a structured method for unmasking experts’ tacit knowledge. This paper is therefore relevant as it presents useful findings following a naturalistic knowledge elicitation study that was conducted across different fire stations in the UK and Nigeria.

Item Type: Article
Research Areas: A. > School of Science and Technology > Centre for Decision Analysis and Risk Management (DARM)
Item ID: 24199
Useful Links:
Depositing User: John Watt
Date Deposited: 01 May 2018 15:44
Last Modified: 10 Jun 2021 02:59
URI: https://eprints.mdx.ac.uk/id/eprint/24199

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