期刊論文
| 學年 | 102 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2013-12-01 |
| 作品名稱 | Mining business knowledge for developing integrated key performance indicators on an optical mould firm |
| 作品名稱（其他語言） | |
| 著者 | Liao, Shu-Hsien; Hsiao, Pei-Yuan |
| 單位 | 淡江大學管理科學學系 |
| 出版者 | Abingdon: Taylor & Francis |
| 著錄名稱、卷期、頁數 | International Journal of Computer Integrated Manufacturing 26(8), pp.703-719 |
| 摘要 | The supply chain for Taiwanese optical components accounts for 39.7% of the total supply chain of the optical mould industry. However, some critical elements of the optical mould industry are difficult to predict; these include personnel, mechanical equipment, material, environmental and complex management factors. Therefore, these enterprises need flexibility to fine-tune their organisational structure, so that the main functions of various departments operate with the best processes. Beside case firm database, this study collects subjective data by designing a questionnaire with nominal scale question to investigate employees’ potential attitude and behaviour in relation to the case firm's key perfomance indicators KPIs. A total of 250 questionnaires were sent and 220 questionnaires were returned, including 207 effective questionnaires. All data source are designed on a entity relationships ER model and constructed on a relational database. In addition, this study applies a data mining approach using association rules, an Apriori algorithm, and cluster analysis to develop the integrated KPIs for a Taiwanese optical mould company. This study investigates the data mining process and considers how the development of the integrated KPIs for this company might serve as a business intelligence example for other firms and industries. |
| 關鍵字 | data mining; association rules; cluster analysis; optical mould firm; key performance index \(KPI\); business intelligence |
| 語言 | en_US |
| ISSN | 0951-192X |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | GBR |
| 公開徵稿 | |
| 出版型式 | ,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/91984 ) |