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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/65709

    Title: 策略群組規劃方法之評比;Comparison on Grouping Methods of Strategy Factors
    Authors: 張中和;Chang,Chung-ho
    Contributors: 資訊管理學系
    Keywords: SWOT分析;TF-IDF;資源分類程序;資訊檢索;網路分群法;SWOT analysis;TF-IDF;Resource Classification Process;Information Retrieval;Network Clustering
    Date: 2014-07-24
    Issue Date: 2014-10-15 17:08:40 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 在進行策略規劃時,最常用之方法為SWOT分析。然而,此種作法先天上將多元策略因子搭配之可能性捨棄,限制了創造力,恐造成決策的偏狹。
    成功運用資訊檢索技術發展出策略因子關係指數矩陣,加入時間因素之考量,讓策略因子關係之判斷能夠更為全面,順利運用於網路分群法中。群組結果相較於SWOT分析具備多元策略因子搭配之可能性,因而能有效擴展決策視野;利用文件資料庫作為補助工具,能夠超越SWOT分析加諸於個人主觀之認知,因此增進了創造力;並在分群結果中發掘出新的策略組合。;When conducting strategy planning, the most popular way is SWOT analysis. However, SWOT method abandons the possibility of grouping multiple strategy factors in advance, limits creativity of strategy forming, and narrows the vision of decision.
    Hence, based on many mathematical methods, i.e. information retrieval tech-nologies and network clustering methods, new grouping methods of strategy factors are going to be developed and be compared to SWOT analysis on performance by using the existing interacting matrices for demonstration.
    The strategy factor index matrix has been successfully built. Time is taken as an element into account, makes the evaluation of relationship of strategy factors more comprehensively, and is applied to network clustering methods smoothly. The results of strategy factors grouping have a potential of multi-factor assembling compared to SWOT analysis and a capability that can help expanding vision of decision. The utilizing of document database as assistance of forming the matrix makes the clustering methods transcend SWOT analysis on the classification of strategy factors relied on personal cognition. Therefore, it enhances the creativity. And, it is found that in the strategy factor groups, there are some new combinations when using those new methods.
    Appears in Collections:[資訊管理研究所] 博碩士論文

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