相似係數於皮革工業上之應用：以印尼為例

Abstract

As the fast growing of leather industry in Indonesia, it is urgent to figure out the strategies for successful cluster of leather industries. In this work, we apply quantitative methods with the idea of grouping technology and introduce the similarity coefficient for clusters of leather industry. Similarity coefficient is the quantified degree of similarity to compare a cluster to the benchmark of successful clusters. Benchmarks are selected first as the best cluster. Then clusters are compared to the benchmark pairwisely. Critical successful clusters are caught as a string and weighted by their importance levels. For a pair cluster, similarity coefficient is composed of weighted merger distance between two strings. We then collect similarity coefficients of successful clusters as fingerprints in building new clusters of leather industry. As a case study, clusters of leather industry in Indonesia are examined. It gives recommendation to related government and sheds light on the road of success.

As the fast growing of leather industry in Indonesia, it is urgent to figure out the strategies for successful cluster of leather industries. In this work, we apply quantitative methods with the idea of grouping technology and introduce the similarity coefficient for clusters of leather industry. Similarity coefficient is the quantified degree of similarity to compare a cluster to the benchmark of successful clusters. Benchmarks are selected first as the best cluster. Then clusters are compared to the benchmark pairwisely. Critical successful clusters are caught as a string and weighted by their importance levels. For a pair cluster, similarity coefficient is composed of weighted merger distance between two strings. We then collect similarity coefficients of successful clusters as fingerprints in building new clusters of leather industry. As a case study, clusters of leather industry in Indonesia are examined. It gives recommendation to related government and sheds light on the road of success.