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Knowledge Engineering Technique for Cluster Development

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  • Pradorn Sureephong

    (LIESP - Laboratoire d'Informatique pour l'Entreprise et les Systèmes de Production - UL2 - Université Lumière - Lyon 2 - ECL - École Centrale de Lyon - Université de Lyon - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - INSA Lyon - Institut National des Sciences Appliquées de Lyon - Université de Lyon - INSA - Institut National des Sciences Appliquées, CAMT - College of Arts, Media and Technology - CMU - Chiang Mai University)

  • Nopasit Chakpitak

    (CAMT - College of Arts, Media and Technology - CMU - Chiang Mai University)

  • Yacine Ouzrout

    (LIESP - Laboratoire d'Informatique pour l'Entreprise et les Systèmes de Production - UL2 - Université Lumière - Lyon 2 - ECL - École Centrale de Lyon - Université de Lyon - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - INSA Lyon - Institut National des Sciences Appliquées de Lyon - Université de Lyon - INSA - Institut National des Sciences Appliquées)

  • Gilles Neubert

    (LIESP - Laboratoire d'Informatique pour l'Entreprise et les Systèmes de Production - UL2 - Université Lumière - Lyon 2 - ECL - École Centrale de Lyon - Université de Lyon - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - INSA Lyon - Institut National des Sciences Appliquées de Lyon - Université de Lyon - INSA - Institut National des Sciences Appliquées)

  • Abdelaziz Bouras

    (LIESP - Laboratoire d'Informatique pour l'Entreprise et les Systèmes de Production - UL2 - Université Lumière - Lyon 2 - ECL - École Centrale de Lyon - Université de Lyon - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - INSA Lyon - Institut National des Sciences Appliquées de Lyon - Université de Lyon - INSA - Institut National des Sciences Appliquées)

Abstract

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 compares the capability to be implemented in the cluster context. Then, we selected one method and proposed the 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.

Suggested Citation

  • Pradorn Sureephong & Nopasit Chakpitak & Yacine Ouzrout & Gilles Neubert & Abdelaziz Bouras, 2007. "Knowledge Engineering Technique for Cluster Development," Post-Print hal-00196472, HAL.
    • Handle: RePEc:hal:journl:hal-00196472
    Note: View the original document on HAL open archive server: https://hal.science/hal-00196472
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    References listed on IDEAS

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    1. Anders Malmberg & Dominic Power, 2005. "(How) Do (Firms in) Clusters Create Knowledge?," Industry and Innovation, Taylor & Francis Journals, vol. 12(4), pages 409-431.
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    Keywords

    Knowledge Engineering; Industry Cluster; CommonKADS; Knowledge Management System;
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