Knowledge engineering technique for cluster development

After the concept of industry cluster was tangibly applied in many countries, SMEs trended to link to each other to maintain their competitiveness in the market. The major key success factors of the cluster are knowledge sharing and collaboration between partners. This knowledge is collected in form...

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Main Authors: Pradorn Sureephong, Nopasit Chakpitak, Yacine Ouzroute, Gilles Neubert, Abdelaziz Bouras
Format: Book Series
Published: 2018
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/60977
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-609772018-09-10T04:06:47Z Knowledge engineering technique for cluster development Pradorn Sureephong Nopasit Chakpitak Yacine Ouzroute Gilles Neubert Abdelaziz Bouras Computer Science Mathematics After the concept of industry cluster was tangibly applied in many countries, SMEs trended to link to each other to maintain their competitiveness in the market. The major key success factors of the cluster are knowledge sharing and collaboration between partners. This knowledge is collected in form of tacit and explicit knowledge from experts and institutions within the cluster. The objective of this study is about enhancing the industry cluster with knowledge management by using knowledge engineering which is one of the most important method for managing knowledge. This work analyzed three well known knowledge engineering methods, i.e. MOKA, SPEDE and CommonKADS, and compare the capability to be implemented in the cluster context. Then, we selected one method and proposed die adapted methodology. At the end of this paper, we validated and demonstrated the proposed methodology with some primary result by using case study of handicraft cluster in Thailand. © Springer-Verlag Berlin Heidelberg 2007. 2018-09-10T04:02:21Z 2018-09-10T04:02:21Z 2007-12-01 Book Series 16113349 03029743 2-s2.0-38149052256 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=38149052256&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/60977
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
Mathematics
spellingShingle Computer Science
Mathematics
Pradorn Sureephong
Nopasit Chakpitak
Yacine Ouzroute
Gilles Neubert
Abdelaziz Bouras
Knowledge engineering technique for cluster development
description After the concept of industry cluster was tangibly applied in many countries, SMEs trended to link to each other to maintain their competitiveness in the market. The major key success factors of the cluster are knowledge sharing and collaboration between partners. This knowledge is collected in form of tacit and explicit knowledge from experts and institutions within the cluster. The objective of this study is about enhancing the industry cluster with knowledge management by using knowledge engineering which is one of the most important method for managing knowledge. This work analyzed three well known knowledge engineering methods, i.e. MOKA, SPEDE and CommonKADS, and compare the capability to be implemented in the cluster context. Then, we selected one method and proposed die adapted methodology. At the end of this paper, we validated and demonstrated the proposed methodology with some primary result by using case study of handicraft cluster in Thailand. © Springer-Verlag Berlin Heidelberg 2007.
format Book Series
author Pradorn Sureephong
Nopasit Chakpitak
Yacine Ouzroute
Gilles Neubert
Abdelaziz Bouras
author_facet Pradorn Sureephong
Nopasit Chakpitak
Yacine Ouzroute
Gilles Neubert
Abdelaziz Bouras
author_sort Pradorn Sureephong
title Knowledge engineering technique for cluster development
title_short Knowledge engineering technique for cluster development
title_full Knowledge engineering technique for cluster development
title_fullStr Knowledge engineering technique for cluster development
title_full_unstemmed Knowledge engineering technique for cluster development
title_sort knowledge engineering technique for cluster development
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=38149052256&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/60977
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