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整合資料包絡分析法及二維模糊語意演算法分析女子網球職業選手比賽績效-由管理面觀點

Combining Data Envelopment Analysis and a Two-tuple Fuzzy Linguistic Computing Algorithm to Analyze the Tournament Performance of WTA Players: A Managerial Perspective

摘要


本研究旨在整合資料包絡分析及二維模糊語意演算評估方法,並且由管理面觀點出發,以客觀式與主觀式之二向度觀點評估暨分析女子網球職業選手的比賽績效,期能獲得具有相輔相成之效的分析結果,據以提供給受評選手參考。在二向度評估方法中,主觀式評估方法以12位教練組成專家群,並分別利用模糊語意變數及德爾菲法表達與整合其評判意見,以獲得高質量的共識及信度,再以二維模糊語意演算法快速計算受評選手的比賽績效;另外,客觀式評估方法乃採用知名之資料包絡分析法。六項評估指標被引用,50位選手接受二向度之評估與分析。二向度評估方法所得相輔相成之效有二,其一具有相互支持與驗證之效:共同發現(一)「三盤比賽的勝率」為最重要的評估指標、(二)兩位優異選手可做為無效率選手的學習典範、(三)主觀式評判與客觀式評判之間顯著存在一個線性迴歸模式及(四)41位受評選手的比賽績效獲得一致性的評判;其二具有相互彌補之效:透過相互比較演算結果後,發現其中九位受評選手的比賽績效應該接受重新檢視與評估,而此發現如非經不同面向之綜合分析與比較,恐無法獲得。由分析結果顯示,本研究藉由二向度評估方法達成相輔相成之效的初念,已粗淺獲得應證,值得持續推廣,以獲取更多應用實例之支持。

並列摘要


The purpose of this study was to combine the use of a two-tuple fuzzy linguistic computing algorithm and data envelopment analysis to evaluate and analyze tournament performances of tennis players from the Women’s Tennis Association (WTA) from two perspectives. Fuzzy linguistic variables and the Delphi method were used for conducting a subjective analysis of player performance. An expert group of 12 members were used to collect a full set of information and gain consensus on expert opinions. A two-tuple fuzzy linguistic computing algorithm was used to evaluate tournament performance. The performance of 50 WTA players was also objectively evaluated using data envelopment analysis with six evaluation measures. The result of this study was twofold. First, the findings of the subjective and objective analyses supported and validated each other: (1) the ”three-set win rate” was the most important measure; (2) two excellent players could become role-models for other players; (3) a significant linear regression model existed between the two results; and (4) 41 players received consistent evaluation on their performances. Second, the findings were complementary. When comparing the results, nine players received different performance evaluations. This discovery could not have been made without a comprehensive analysis and comparison of the results. This complementary method was able to validate data preliminarily and achieve a research objective. The method of using two-dimensional evaluation algorithms can be used in other fields of research to obtain supporting information.

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