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題名 | 直覺模糊尺度應用於衡量商店形象之比較研究=A Comparative Study Applying Intuitionistic Fuzzy Scales to Measure Store Image |
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作者姓名(中文) | 陳亭羽; 黃聖芬; 王曉斌; | 書刊名 | 企業管理學報 |
卷期 | 84 2010.03[民99.03] |
頁次 | 頁71-106 |
分類號 | 498 |
關鍵詞 | 商店形象; 直覺模糊集合; 評估函數; 多屬性決策; 連結性與非連結性關係; Store image; Intuitionistic fuzzy set; Evaluation function; Multiple attribute decision making; Conjunctive and disjunctive relationship; |
語文 | 中文(Chinese) |
中文摘要 | 擁有良好的商店形象是業者維持其市場地位重要的利器,倘若我們能正確衡量顧客所認知的商店形象,就能立即提出因應對策。以往的研究常使用具有順序且等距性的李克特尺度或語意差別尺度來量測商店形象,然而事實上每個人對尺度間差距的認知不完全相等,同時人類的思考模式總是充滿著複雜性及不確定性。傳統衡量方式可能無法充分測得受訪者內心真實的想法。因此本研究以直覺模糊集合與評估函數為基礎,發展三個商店形象評估方法,同時發放傳統李克特問卷與直覺模糊問卷,並以一個百貨公司的多屬性決策問題為例,計算其商店形象分數與方案排序。研究結果發現利用評估方法獲得的商店形象排序比起傳統李克特尺度以統計方法計算的排序,較貼近受訪者內心真正的排序,而且還能妥善處理屬性間的連結性關係與非連結性關係。 |
英文摘要 | Possessing a splendid store image is an essential efficient instrument to maintain the market position. If being capable of measuring customers' cognitive store image accurately, we can propose a corresponding strategy immediately. Plenty of studies have being using the Likert scale or semantic differential scale which is characterized as ordinal and interval concept to measure store image; however, the interval distance elicited by human beings is not equivalent. Besides, the human thinking model is full of complex and uncertainty. Because the traditional measurement is unable to entirely capture subjects' inner thoughts, this study bases on the intuitionistic fuzzy set and evaluation function to develop three evaluation measures for store image. A multiple attribute decision making problem concerning the department store image was taken for an instance. The Likert scale and the intuitionistic fuzzy questionnaires were used simultaneously. The scores of the store image are calculated by the traditional statistical skill and the evaluation measures. The results show that the ranking of the store image generated by the evaluation measures is more consistent with the subject's ranking than by the statistical method. Besides, the evaluation measures also can deal with the conjunctive and disjunctive relationship between attributes. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。