Knowledge elicitation techniques in a knowledge management context

被引:67
|
作者
Gavrilova, Tatiana [1 ]
Andreeva, Tatiana [2 ]
机构
[1] St Petersburg Univ, Grad Sch Management, Dept Informat Technol Management, St Petersburg, Russia
[2] St Petersburg Univ, Grad Sch Management, Dept Org Behav & Human Resource Management, St Petersburg, Russia
关键词
Knowledge management; Knowledge elicitation techniques; Knowledge engineering; EXPERTS; FIRM;
D O I
10.1108/13673271211246112
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
Purpose - A significant part of knowledge and experience in an organization belongs not to the organization itself, but to the individuals it employs. Therefore, knowledge management (KM) tasks should include eliciting knowledge from knowledgeable individuals. The paper aims to argue that the current palette of methods proposed for this in KM discourse is limited by idealistic assumptions about the behavior of knowledge owners. This paper also aims to enrich the repertoire of methods that can be used in an organization to extract knowledge (both tacit and explicit) from its employees by bridging KM and knowledge engineering and its accomplishments in the knowledge elicitation field. Design/methodology/approach - This paper is based on extensive literature review and 20 years of experience of one of the authors in applying various knowledge elicitation techniques in multiple companies and contexts. Findings - The paper proposes that the special agent (analyst) might be needed to elicit knowledge from individuals (experts) in order to allow further knowledge sharing and knowledge creation. Based on this idea, the paper proposes a new classification of the knowledge elicitation techniques that highlights the role of analyst in the knowledge elicitation process. Practical implications - The paper contributes to managerial practice by describing a systemic variety of knowledge elicitation techniques with direct recommendations of their feasibility in the KM context. Originality/value - The paper contributes to a wider use of knowledge engineering methodologies and technologies by KM researchers and practitioners in organizations.
引用
收藏
页码:523 / 537
页数:15
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