Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/36174
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dc.contributor.advisor李文福<br>王媛慧zh_TW
dc.contributor.author卓筱婷zh_TW
dc.contributor.authorCho, Hsiao-Tingen_US
dc.creator卓筱婷zh_TW
dc.creatorCho, Hsiao-Tingen_US
dc.date2004en_US
dc.date.accessioned2009-09-18T09:23:11Z-
dc.date.available2009-09-18T09:23:11Z-
dc.date.issued2009-09-18T09:23:11Z-
dc.identifierG0922580361en_US
dc.identifier.urihttps://nccur.lib.nccu.edu.tw/handle/140.119/36174-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description經濟研究所zh_TW
dc.description92258036zh_TW
dc.description93zh_TW
dc.description.abstract傳統DEA效率分析假設產業具單一生產過程,直到2000年,Färe and Grosskopf 提出Network DEA,闡明產業生產過程應分屬多階段性質。本研究應用其架構,假設職棒產業生產過程為兩個階段,並特別以Sexton and Lewis (2003) 增加中間產出的Two-Stage DEA 法,即第一階段的產出作為第二階段的投入,進行1992年至2004年「中華職業棒球聯盟」,共71個DMUs的實證分析。\r\nTwo-Stage DEA的第一階段是指花錢聘雇球員,而球團有效花錢聘雇球員的程度稱為「前置效率」,效率平均值為0.994;第二階段效率是指球隊正式比賽時,球員是否充分發揮技術潛能贏球,稱為「臨場效率」,效率平均值為0.969;而包含第一、二階段的整體球團運作效率則為「組織效率」,效率平均值為0.798。透過與傳統DEA的BCC模型之比較,發現Two-Stage DEA提供較豐富的組織運作過程資訊,俾管理者找出球團之無效率階段。\r\n 復以Tobit截斷迴歸模型,探討影響球團「前置效率」、「臨場效率」與「組織效率」之變數為何。結果指出,球隊對戰觀眾數、聯盟變革與現場直播對「前置效率」有顯著影響,「臨場效率」則受到臨時性獎勵制度與投手平均年齡的影響,而對戰觀眾數、聯盟變革、總教練的更動頻率與常設性獎勵制度,則是造成球隊「組織效率」差異的主因。\r\n\r\n關鍵字:Network DEA、中間產出、Two-Stage DEA、職業棒球、效率zh_TW
dc.description.abstractTraditional DEA gauges efficiencies with only one production process, while in this study we apply Network DEA initiated by Färe and Grosskopf (2000), and in particular follow the Two-Stage DEA model incorporating the intermediate products, outputs from the first stage becomes inputs to the second stage, by Sexton and Lewis (2003) to evaluate the production efficiency of 71 DMUs of the Chinese professional Baseball League (CPBL ) from 1992 to 2004.\r\nHow fair are the ball teams paying the players is called ”front office efficiency”, arithmetic mean is 0.994, in the first stage, how potentially successful are the teams playing the games is called “on-field efficiency”, arithmetic mean is 0.969, in the second stage, and how potentially successful are the teams playing the games if with perfect front office efficiency of the teams is called “organization efficiency”, arithmetic mean is 0.798. Comparing Two-Stage DEA model with BCC model of traditional DEA, we find that the former model provides more information of organizational operations for managers to understand and better the performance of the teams.\r\nTobit regression analysis shows that (1) the front office efficiency is significantly positively influenced by spectators, variation of the league and television live, and (2) the on-field efficiency is significantly positively influenced by extemporaneous bonus and pitcher’s age. (3) The organization efficiency is significantly positively influenced by the spectators, variation of the league and fixed bonus, but the organization efficiency is significantly negatively influenced by change of coaches.\r\n\r\n\r\nKeyword:Network DEA, Intermediate products, Two-Stage DEA , Efficiency, Professional baseballen_US
dc.description.tableofcontents第一章 緒論\r\n1.1 研究背景與動機\r\n1.2 研究目的與方法\r\n1.3 本文架構\r\n第二章 台灣職棒概述與文獻回顧\r\n2.1 台灣職棒產業概述.\r\n2.2 台灣職棒發展歷程與經營現況\r\n2.3 效率文獻回顧\r\n2.3.1 國外文獻\r\n2.3.2 國內文獻\r\n第三章 理論模型\r\n3.1 生產函數與效率\r\n3.2 傳統DEA\r\n3.3 Two-Stage DEA\r\n3.4 Tobit迴歸分析模型\r\n第四章 實證結果與分析\r\n4.1 投入產出變數選取說明\r\n4.2 傳統DEA實證分析\r\n4.3 Two-Stage DEA 實證分析\r\n4.3.1 模型假設說明\r\n4.3.2 兩模型效率值分析\r\n4.3.3 兩模型規模報酬分析\r\n4.3.4 兩模型參考集合分析\r\n4.3.5 Two-Stage DEA產出差額分析\r\n4.3.6 聯盟變革前後之兩模型效率分析\r\n4.3.7 Two-Stage DEA球隊別組織效率分析\r\n4.4 Tobit 迴歸分析\r\n4.4.1 兩模型組織效率Tobit迴歸分析\r\n4.4.2 前置效率Tobit迴歸分析\r\n4.4.3 臨場效率Tobit迴歸分析\r\n第五章 結論\r\n5.1 結論\r\n5.2 研究限制與未來研究方向\r\n參考文獻\r\n附表 中華職棒球團變遷zh_TW
dc.language.isoen_US-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0922580361en_US
dc.subject中間產出zh_TW
dc.subject職業棒球zh_TW
dc.subject效率zh_TW
dc.subjectNetwork DEAen_US
dc.subjectintermediate productsen_US
dc.subjectTwo-Stage DEAen_US
dc.subjectprofessional baseballen_US
dc.subjectefficiencyen_US
dc.title中華職棒聯盟球隊生產效率分析:考量中間產出之DEA模型zh_TW
dc.typethesisen
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