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題名 | 半導體產業經營績效之研究--以國內上市櫃公司為例=A Study of Operating Performance of Semiconductor Industry: The Case of Publicly Listed Companies in Taiwan |
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作者 | 黃玉美; | 書刊名 | 德明學報 |
卷期 | 20 2002.12[民91.12] |
頁次 | 頁1-16 |
分類號 | 494.7 |
關鍵詞 | 半導體產業; 經營績效; 財務比率; Semiconductor industry; Operating performance; Financial ratio; |
語文 | 中文(Chinese) |
中文摘要 | 本研究係以半導體產業上市櫃公司為研究對象,使用民國八十五年至八十九年的 二十八項財務比率來建立經營績效之評估模式,並以民國九十年的財務資料為預測樣本,該 模式可作為投資人、銀行授信與公司管理當局評估經營績效的一項參考依據。實證結果顯示 :一、經由因素分析可萃取出三個評估基準來衡量公司之經營績效,此評估基準分別為獲利 能力因素、資產結構因素及經營成長能力因素,三個因素總解釋變異能力達 86.423%。二、 利用因素分析萃取出的三個評估基準,依解釋變異能力的不同,賦予不同的權重,並根據經 營績效強度分數予以排名,另依平均水準劃分為高低兩績效群,各群在獲利能力因素、資產 結構因素、經營成長能力因素上均有顯著差異。三、建立經營績效之區別模式,該模式包括 三項變數,其原始資料正確區別率為 97.3%,預測樣本正確區別率為 88.57%。 |
英文摘要 | This research objects are publicly listed semiconductor industry companies. The model of operating performance to evaluate publicly listed semiconductor industry companies were set up based on the twenty-eight financial ratios from 1996 to 2000. A predicted result was derived from 2001 financial information. This model can be used as a survey reference for investors, bankers and company's management teams. A brief summary of the major findings are given below: 1.Three evaluative criteria can be extracted via factor analysis to evaluate operating performance of companies. The basis of evaluative criteria is capability of earning profit, criterion of asset structure, and capability of operating growth. These three criteria can explain 86.423% of total variance. 2.Above three evaluative criteria obtained from factor analysis extraction can give different degree of weight in accordance with their individual explaining ability. A ranking list can be derived from each company's operating performance. Based on the ranking list, publicly listed semiconductor industry companies can be divided into two clusters: high operating performance and low operating performance. There is a significant difference in every criterion among clusters. 3.The discriminate model of operating performance evaluation was set up and included three variables. 97.3% raw data can be exactly discriminated by this model, and also 88.57% predicted result could be exactly discriminated too. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。