Tacit knowledge for business intelligence framework using cognitive-based approach
Tacit knowledge becoming a key issue in business intelligence approach to knowledge systems. Capturing the tacit knowledge is not a straightforward task, since it consists of unstructured data and related to a variety of information that is not always accessible through traditional means. This work...
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my.uum.etd.102132023-01-11T00:34:01Z https://etd.uum.edu.my/10213/ Tacit knowledge for business intelligence framework using cognitive-based approach Surbakti, Herison T58.6-58.62 Management information systems HF5001-6182 Business Tacit knowledge becoming a key issue in business intelligence approach to knowledge systems. Capturing the tacit knowledge is not a straightforward task, since it consists of unstructured data and related to a variety of information that is not always accessible through traditional means. This work presents a systematic approach for capturing tacit knowledge to be used in a business intelligence framework. The approach is based on the theory of systematic functional linguistics, developed into interview protocols to be asked to tacit knowledge owners. The data transformed into cognitive maps to supply the data warehouse. The framework was tested on 23 librarians from several university libraries in West Java and Yogyakarta, Indonesia. The algorithm starts with a content targeted interview to identify the list of problems faced by librarians. The problems were then converted into a questionnaire to identify qualities of the problems such as frequency, urgency, severity, and importance. From the questionnaire results, the best tacit knowledge performers were identified. They are respondents who can solve the problems, while the majority of the respondents are unable to solve them. The best performers were then subjected to grammar targeted interview to collect the solutions they made to the problems. The transcription of the interview results is then converted into cognitive maps that visualize the solutions. These cognitive maps are then stored in a data warehouse and ready to collect anytime for analytics purposes. The framework is validated through Power BI and reviewed by seven experts. Its applicability to other domains is justified as long as the domain, e.g., manufacturing, have experienced problems related to technical, managerial, and empirical problems faced by employees at work. This research contributes to the methods of capturing tacit knowledge using a cognitive-based approach, which important to ensure the continuity of business in various domains. 2022 Thesis NonPeerReviewed text en https://etd.uum.edu.my/10213/1/s900835_01.pdf text en https://etd.uum.edu.my/10213/2/s900835_02.pdf Surbakti, Herison (2022) Tacit knowledge for business intelligence framework using cognitive-based approach. Doctoral thesis, Universiti Utara Malaysia. |
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T58.6-58.62 Management information systems HF5001-6182 Business Surbakti, Herison Tacit knowledge for business intelligence framework using cognitive-based approach |
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Tacit knowledge becoming a key issue in business intelligence approach to knowledge systems. Capturing the tacit knowledge is not a straightforward task, since it consists of unstructured data and related to a variety of information that is not always accessible through traditional means. This work presents a systematic approach for capturing tacit knowledge to be used in a business intelligence framework. The approach is based on the theory of systematic functional linguistics, developed into interview protocols to be asked to tacit knowledge owners. The data transformed into cognitive maps to supply the data warehouse. The framework was tested on 23 librarians from several university libraries in West Java and Yogyakarta, Indonesia. The algorithm starts with a content targeted interview to identify the list of problems faced by librarians. The problems were then converted into a questionnaire to identify qualities of the problems such as frequency, urgency, severity, and importance. From the questionnaire results, the best tacit knowledge performers were identified. They are respondents who can solve the problems, while the majority of the respondents are unable to solve them. The best performers were then subjected to grammar targeted interview to collect the solutions they made to the problems. The transcription of the interview results is then converted into cognitive maps that visualize the solutions. These cognitive maps are then stored in a data warehouse and ready to collect anytime for analytics purposes. The framework is validated through Power BI and reviewed by seven experts. Its applicability to other domains is justified as long as the domain, e.g., manufacturing, have experienced problems related to technical, managerial, and empirical problems faced by employees at work. This research contributes to the methods of capturing tacit knowledge using a cognitive-based approach, which important to ensure the continuity of business in various domains. |
format |
Thesis |
author |
Surbakti, Herison |
author_facet |
Surbakti, Herison |
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Surbakti, Herison |
title |
Tacit knowledge for business intelligence framework using cognitive-based approach |
title_short |
Tacit knowledge for business intelligence framework using cognitive-based approach |
title_full |
Tacit knowledge for business intelligence framework using cognitive-based approach |
title_fullStr |
Tacit knowledge for business intelligence framework using cognitive-based approach |
title_full_unstemmed |
Tacit knowledge for business intelligence framework using cognitive-based approach |
title_sort |
tacit knowledge for business intelligence framework using cognitive-based approach |
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2022 |
url |
https://etd.uum.edu.my/10213/1/s900835_01.pdf https://etd.uum.edu.my/10213/2/s900835_02.pdf https://etd.uum.edu.my/10213/ |
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13.209306 |