Knowledge Engineering Technique for Cluster Development

TL;DR

This paper compares knowledge engineering methods for enhancing industry clusters and proposes an adapted methodology validated through a case study of a Thai handicraft cluster.

Contribution

It analyzes and compares MOKA, SPEDE, and CommonKADS methods, selecting and adapting one for cluster knowledge management.

Findings

The adapted methodology is effective in a real cluster setting.

Knowledge sharing improves cluster competitiveness.

Case study demonstrates practical applicability.

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.