教師資料查詢 | 類別: 期刊論文 | 教師: 廖述賢 LIAO SHU-HSIEN (瀏覽個人網頁)

標題:Mining business knowledge for developing integrated key performance indicators on an optical mould firm
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
語言英文(美國)
ISSN0951-192X
期刊性質國外
收錄於SCI;
產學合作
通訊作者
審稿制度
國別英國
公開徵稿
出版型式,紙本
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