Minrata Supanitchaisiri, Onjaree Natakuatoong, S. Sinthupinyo
{"title":"The innovative model for extracting tacit knowledge in organisations","authors":"Minrata Supanitchaisiri, Onjaree Natakuatoong, S. Sinthupinyo","doi":"10.1504/IJKMS.2018.10017945","DOIUrl":null,"url":null,"abstract":"This research aimed to examine the obstacles of classical practices for extracting tacit knowledge, and to propose a new method of self-extracting tacit knowledge in organisations. This study opted for an exploratory study using the mixed methods research covering both qualitative and quantitative studies. The focus group interview was used to obtain qualitative information from 24 executives and experts in knowledge management, in five organisations. ATLAS.ti was used to analyse focus group data. The quantitative data was gained from a survey of 26 executives and KM experts who participated in the KM seminar. The result from the analysis was then used to develop a model of tacit knowledge extraction. The key finding is that major challenges of extracting tacit knowledge are lack of certainty of corporate policy, lack of motivation, lack of continuity in knowledge management activities, lack of a support system for the learning environment, lack of participation, non-supportive culture and behaviour, lack of preparation for interviewing, discontinuity in interviews during extraction of tacit knowledge, misinterpreted questioning, and inexperienced interviewers has a lack of experience. Web-based applications were the key source for the questions, which were comprised of both primary and secondary questions.","PeriodicalId":39285,"journal":{"name":"International Journal of Knowledge Management Studies","volume":"1 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Knowledge Management Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJKMS.2018.10017945","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 3
Abstract
This research aimed to examine the obstacles of classical practices for extracting tacit knowledge, and to propose a new method of self-extracting tacit knowledge in organisations. This study opted for an exploratory study using the mixed methods research covering both qualitative and quantitative studies. The focus group interview was used to obtain qualitative information from 24 executives and experts in knowledge management, in five organisations. ATLAS.ti was used to analyse focus group data. The quantitative data was gained from a survey of 26 executives and KM experts who participated in the KM seminar. The result from the analysis was then used to develop a model of tacit knowledge extraction. The key finding is that major challenges of extracting tacit knowledge are lack of certainty of corporate policy, lack of motivation, lack of continuity in knowledge management activities, lack of a support system for the learning environment, lack of participation, non-supportive culture and behaviour, lack of preparation for interviewing, discontinuity in interviews during extraction of tacit knowledge, misinterpreted questioning, and inexperienced interviewers has a lack of experience. Web-based applications were the key source for the questions, which were comprised of both primary and secondary questions.
期刊介绍:
“Knowledge as a key resource will contribute to improved organisational performance if it is properly leveraged and harnessed." IJKMS is a refereed and authoritative source of information in the field of knowledge management and related aspects. Topics covered include: -Knowledge creation, acquisition, codification, classification, organisation -Knowledge sharing, transfer, application, protection, retention -KM design and development -KM management and implementation -Measurement of knowledge management performance and benefits -Techniques and methods for managing knowledge -Technological tools for knowledge management, e.g. -knowledge bases, collaborative tools -expert/intelligent systems, knowledge mining/extraction -content/document management -portals, search and retrieval -e-learning, virtual reality, business intelligence, etc. -Human, organisational, strategic, behavioural, socio-cultural aspects -Public policy, economics, education policy, intellectual capital, ethics -Other related aspects of KM