多角化是否能提升銀行獲利與降低風險？本文採2000年至2007年21家本國銀行之年資料，獲利以調整呆帳費用後之資產報酬率作為評估基礎；風險以資產報酬率的標準差衡量，利用追蹤資料分析法，探討銀行多角化程度對獲利與風險之影響，並分析對於逾放比率不同之銀行，其獲利、風險之影響因素是否有所差異，實證結果顯示：一、依品質一致性原則調整呆帳後之資產報酬率，較財報公佈之資產報酬率具較佳之解釋能力與統計顯著性；二、營業收入多角化可提升獲利與降低風險；資產配置多角化不但無法提升獲利，甚使其面臨更高之風險；轉投資模式與風險具有負向關係；三、金融控股公司經營模式與獲利具有正向關係；資產規模與風險具有負向關係；權益資產比及用人費用率與獲利、風險具有負向關係；總體環境因素和風險具有正向關係；四、對於低逾放比率銀行，分散營業收入來源，擴充銀行規模及提高自有資金比例，對其獲利與風險皆有正面之助益；對於高逾放比率銀行，僅有營業收入多角化模式可同時提升獲利與降低風險，意謂此類銀行除可採取營業收入多角化策略彌補呆帳損失外，亦應確實監控授信資產品質，方能有效地改善獲利能力與降低風險。 / Does diversification indeed lead to increase profitability and reduce risk? We use a panel dataset of 21 banks in Taiwan for the period from 2000 to 2007, bad debt-adjusted ROA serves as the measure of profitability and the standard deviation of ROA serves as the measure of risk. This study investigate the effect of diversification on profitability and risk and hope to know how it works out under different non-performing loans ratio. Our main finding are as follows:(i)Compare with ROA in financial statement ,bad debt-adjusted ROA making better significance. (ii)Revenue diversification has positive relation to increase profitability and negative to reduce risk. Asset diversification has negative relation to reduce profitability and positive relation to increase risk. Equity investment has negative relation between risk. (iii) Banks operating as part of financial holding companies can improve profitability. Size has negative relation between risk. Equity to asset ratio and compensation to revenue ratio have negative relation to reduce both profitability and risk. Macroeconomic factor has positive relation to increase risk.(iv)For low non-performing loans ratio banks, revenue diversification, size and equity to asset ratio have positive relation to increase profitability and negative to reduce risk. For high non-performing loans ratio banks, revenue diversification is the only way to improve banks’ profitability and reduce risk. It draws a conclusion that banks monitor loan need strengthening in high non-performing loans ratio banks.

中小企業是台灣經濟貿易發展的命脈，過去以中小企業為主的出口貿易經濟體系，是創造台灣經濟奇蹟的主要動力。隨著2006年底新巴賽爾協定的正式實施，金融機構為符合新協定規範，亦需將中小企業信用評分程序，納入其徵、授信管理系統，以求信用風險評估皆可量化處理。故本研究將資料採礦技術應用於建置中小企業違約風險模型，針對內部評等法中的企業型暴險，根據新協定與金管會的準則，不僅以財務變數為主，也廣泛增加如企業基本特性及總體經濟因子等非財務變數，納入模型作為考慮變數，計算違約機率進而建置一信用評等系統，作為金融機構對於未來新授信戶之風險管理的參考依據。而本研究將以中小企業中製造傳統產業公司為主要的研究對象，建構企業違約風險模型及其信用評等系統，資料的觀察期間為2003至2005年。 本研究分別利用羅吉斯迴歸、類神經網路、和C&R Tree三種方法建立模型並加以評估比較其預測能力。研究結果發現，經評估確立以1:1精細抽樣比例下，使用羅吉斯迴歸技術建模的效果最佳，共選出六個變數作為企業違約機率模型之建模變數。經驗證後，此模型即使應用到不同期間或其他實際資料，仍具有一定的穩定性與預測效力，且符合新巴塞資本協定與金管會的各項規範，表示本研究之信用評等模型，確實能夠在銀行授信流程實務中加以應用。 / To track the development of Taiwan’s economy history, one very important factor that should never be ignored is the role of small enterprise businesses (the SMEs) which has always been played as a main driving force in the growth of Taiwan’s export trade economic system. With the formal implementation of Basel II in the end of 2006, there arises the need in the banking institutions to establish a credit scoring process for the SMEs into their credit evaluation systems in order to conform to the new accords and to quantify the credit risk assessment process. Consequently, in this research we apply data mining techniques to construct the default risk model for the SMEs in accordance to the new accords and the guidelines published by the FSC (the Financial Supervisory Commission). In addition we not only take the financial variables as the core variables but also increase the non- financial variables such as the enterprise basic characteristics and overall economic factors extensively into the default risk model in order to formulate the probability of credit default risk as well as to establish the credit rating system for the enterprise-based at risk for default in the IRB in the second pillars of the Basel II. The data which used in this research is taken from the traditional SMEs industry ranging from the year of 2003 to 2005. We use each of the following three methods, the Logistic Regression, the Neural Network and the C&R Tree, to build the model. Evaluation of the models is carried out using several statistics test results to compare the prediction accuracy of each model. Based on the result of this research under the 1:1 oversampling proportion, we are inclined to adopt the Logistic Regression techniques modeling as our chosen choice of model. There are six variables being selected from the dataset as the final significant variables in the default risk model. After multiple testing of the model, we believe that this model can withstand the testing for its capability of prediction even when applying in a different time frame or on other data set. More importantly this model is in conformity with the Basel II requirements published by the FSC which makes it even more practical in terms of evaluating credit risk default and credit rating system in the banking industry.

由於國際原油價格不斷攀升，加上節能、環保議題、休閒運動和樂活新興生活型態等各項因素的交互影響，使的自行車產業成為新一代的明星產業。為了順應此一趨勢，故本研究期望透過資料採礦的應用，配合SPSS Clementine 12.0軟體，冀望找出是否擁有自行車之影響變數，並以巨大捷安特以及愛地雅為個案分析對象，進行行銷組合策略分析與建議。 投入變數共分為三大部分：基本人口統計變數、生活型態變數以及自行車消費行為變數，進行模型建置，由於分類迴歸樹不論是在整體預測正確率或準確度，皆是高於羅吉斯迴歸和類神經網路，故最後選擇分類迴歸樹此一模型。 透過分類迴歸樹共獲得八項影響「是否擁有自行車」之相關變數，其中「月可支配所得」、「出生年次」、「性別」、「報紙接觸率」、「商品訴求-樂活」、「保健食品最近一年使用時間」、「親疏關係情人」、「商品訴求-排毒」，此八項變數對自行車擁有者具較大影響力，故本研究以此八項變數為巨大捷安特和愛地雅之行銷策略建議依據。 / Due to the interrelationship among the dramatic run-up in gasoline, advocacy for energy-saving issue and conservation of the earth, leisure activities, and LOHAS lifestyles, the bike industry turns out to be a leading and star industry in this era. In order to follow this trend, the study aims to discover the core factors of possessing bicycles through the application of SPSS Clementine 12.0 software. Three variables—demographics, lifestyles and the bicycle consumption behavior—were used to construct the model. Since Decision tree-CART is excellent in the forecast accuracy and validity as compared to Logistic regression and Artificial neural network, the Decision tree-CART was adopted in this research. Through using Decision tree-CART, this study identified eight factors that have greater impact on possessing bicycles and they are “ monthly income”, “year of the birth”, “sex (distinction)”, “The frequency of reading newspaper”, “product expectation—LOHAS”, “ The usage of health products within a year”, “the relationship with the opposite sex”, “product expectation—detoxification”. This research will chiefly use these eight factors to provide the marketing portfolio strategy recommendations for GIANT and IDEAL. Keywords: Cycling, Data Mining, Decision tree-CART, GIANT, IDEAL, Marketing Portfolio Strategy

自從企業社會責任（Corporate Social Responsibility，CSR）的概念被提出以來，至今已經受到全球廣泛地注視，更儼然成為一個所有社會中皆不可抹滅的重要課題。台灣伴隨著經濟的發展，對生活水準與環境品質的要求也隨之提升，因此人們開始注意到環境是需要被改善的，然而企業社會責任便是改善的作為之一，近年來企業社會責任在國內才開始逐漸地受到重視，而企業也開始逐漸地會去關注到這個面向。在國外存在不少探究企業社會責任表現對企業績效（銷售額、營業收入）影響的文獻，而其中大多數文獻所作的實證分析結果都顯示了企業社會責任的表現對企業本身的績效是會帶來正面幫助的，相較之下國內關於探討企業社會責任表現對企業績效影響的文獻卻是十分地稀少，因此本文研究想要藉由兩層級資料包絡分析法（Two-level DEA）的應用來探討國內企業的企業社會責任表現對企業本身績效的影響究竟為何？本文研究以台灣19家大型製造業為例，特別將企業社會責任表現納入企業產出的投入項之中，希望利用此方法的應用所得到的效率值差異，分析企業社會責任表現高低對企業產出效率的影響程度，而能進一步瞭解企業社會責任表現與企業績效的關係。

近年來，由於網路發展、知識水平的提升、社會大眾對網路使用習性的改變以及網路瀏覽速度的提升，網路影音播放已然相當普及；同時，Web2.0的概念廣為網路使用者接受，使YouTube 等Web2.0影音網站崛起。以YouTube為首的Web2.0影音網站，成為了人們參與網路社群以及與他人互動的管道；另一方面，全球化競爭，網路廣告的廣泛使用，讓Web2.0影音網站成為一項新穎的傳播媒介。 　　本研究於YouTube網站上抓取11,269筆「蘋果電腦Mac系列產品」相關資料，利用資料間的好友關係、訂閱／被訂閱關係，建構一社會網絡；並使用社會網絡分析中著重連結方向性的方法，辨識網絡上的傳播關鍵節點，包括廣為對外散佈意見的意見領袖、集中訂閱的參考節點，以及深度涉入特定影音類型的專家；同時本研究使用資料探勘中的關連規則分析，獲得傳播關鍵節點間的關連規則。其次，本研究使用人與人矩陣辨識使用者透過哪些影音類型會產生緊密連結；另利用資料探勘中的分群技術，將網絡上的節點作子網絡歸屬，透過分析子網絡的屬性，加上各子網絡適合行銷傳播的特性，探討在影音網站上行銷傳播之特性。 　　本研究發現，在YouTube網站上與Mac系列產品有關的使用者，多喜好觀賞音樂、娛樂類型的影音，且使用者透過觀看音樂和電影與動畫類型影音易產生緊密連結；九個分群子網絡關鍵傳播節點和關連規則數量都不一，且適合傳播的影音類型都不相同，將可視要傳播的理念或產品性質最接近的子網絡來操作傳播。 / Nowadays, web videos are put to use universally due to the development of Internet, arising of the multitude knowledge and the change of the Internet using behavior. Moreover, the concept of Web2.0 has accepted by the Internet users. The reasons mentioned above result the prosperity of Web2.0 video websites like YouTube. Several user interaction facts have made Web2.0 video websites channels which allow people to participate in web communities and to interact with each others. Furthermore, the Web2.0 video websites have become a new communication media on account of worldwide competition and the using of Internet advertisement. Therefore, the enterprises often interpenetrate target consumers by web videos through Web2.0 video websites. The research propose an analytic structure which is an effective method to recognize the critical properties of marketing communication on Web2.0 video websites by social network analysis, data mining and communication theories. The main purposes of the research are as following. 1. To present an analytic structure to realize the keys to marketing communicate on Web2.0 video websites. 2. Critical network problems analysis, positioning the network users and explaining the marketing communication meaning. 3. Verifying with YouTube-Mac network.

財政部於2006年底建置完成的電子發票整合服務平台，提供不同產業間之買賣雙方一個具有公信力的交易稽核平台。企業在此可利用電子發票向銀行進行貸款，完成融資服務，由於貸款跨越企業與銀行，而各個不同組織間，其流程中會有金、商流共同所需之資訊，但是彼此所需的資訊格式的不同，讓整個流程無法一氣喝成。 本研究提出一個以雲端運算為基礎的服務導向架構電子發票加值平台，透過此平台企業可將原本的發票融資，轉換成利用電子發票進行線上融資，再透過XML-based訊息轉換器將企業端電子發票XML格式轉換為處理帳務之XBRL格式，以及銀行端之金流訊息FXML格式，並利用雲端運算服務作為資料儲存與呈現的基礎，而服務導向架構提供了完成此跨組織金、商流活動所需的平台一個良好架構。 在電子發票加值平台中，處理電子發票加值服務時會運用發票上的金流與商流資訊，基於安全性的考量，所以不能將資料都儲存於雲端運算的資源中，本研究的資料中心利用分散式資料儲存方式，將機密的資料儲存於企業端，減少企業使用服務的疑慮，並透過分散式資料擷取/儲存機制對不同的資料庫存取服務所需之資料，讓企業可以更放心且便利的使用服務。 / Ministry of Finance, R.O.C builds a reliable E-Invoice platform in 2006, to provide buyers and sellers a credible audit platform. Through E-Invoice platform, companies could complete loan service. Because loan service crosses the banks and enterprises, they will need the same information in loan process. However the information to each other is different formats, so that the whole process can not complete straight through. This study proposed a Service-oriented architecture E-Invoice value-added platform which based on cloud computing services. Through this platform, companies can change invoice loan service into E-Invoice on-line loan service. In this platform, they not only can use a XML-based message converter to convert business XML format to financial information XBRL format and cash flow information FXML format but also can use cloud computing services to store and present data. However Service-oriented architecture can provide this cross-organizational activity a suitable architecture. In E-Invoice value-added platform, E-Invoice on-line loan service will handle the information of cash flow and business flow, but based on security considerations, we can not stored all the data in the cloud. However this study use decentralized data center to store confidential information in the enterprise client to solve this problem and use some mechanism to extract/store data from different data center. Therefore Companies can reduce their concerns of using services and use services conveniently.

在這篇文章裡我們採用了White所提出的真實檢驗法(Reality Check)來解決探勘資料偏誤(Data-snooping bias)的問題，結果顯示從1980年到2008年間，技術分析法則的確可以幫助投資人在日圓兌美元及英鎊兌美元這兩個外匯市場獲利；我們也發現在外匯市場最普遍的技術分析方式─移動平均法(moving average)表現不如其他的技術分析法則，而通道突破法(channel break-out)的表現則明顯優於其他技術分析法則。 除了檢驗技術分析方法的獲利性之外，我們也嘗試著探討技術分析方法的獲利性與央行干預之間的關係，追隨Szacmary與Mathur在1997年所發表的論文，我們把技術分析法則擴充為在真實檢驗法中所使用到的所有法則，並且盡可能加長分析的期間。結果顯示技術分析法則的獲利與央行干預並不存在任何特定的關係。 / In this paper we construct a huge universe of simple trading rules and apply White’s Reality Check to mitigate data-snooping bias then detect the profitability of technical trading rules. We find that technical analysis is useful no matter in the full sample time or each subsample period. The channel break-out method outperforms the other methods in our finding while the profitability of the most commonly used moving average method is worse than the others. Furthermore, we inspect the relationships between the returns of technical trading rules and central bank intervention. The results suggest that there’s no evident relationship between the return series of trading rules and central bank intervention and are not consistent with the view of our following previous study.

有鑑於我國與大陸方面是否應簽訂ECFA仍有許多疑慮，本研究欲就香港與大陸所簽訂之CEPA協定對香港銀行業經營效率有何影響加以探討，以便對台灣未來可能簽訂ECFA時提供台灣銀行業相關參考及對策。 本研究針對2000年至2007年的18家香港地區銀行以及30家台灣地區銀行，採用資料包絡分析(DEA)計算業者之經營效率，最後控制銀行業者本身之財務特性及總體經濟環境因素，應用Tobit迴歸比較分析實施CEPA對香港銀行業之影響及台灣與香港業者之差異。 研究結果顯示港銀行業之經營效率八年間均較台灣銀行業為佳，此外CEPA協定之採用整體而言對台灣以及香港銀行業均無顯著影響，雖然協定採用後之第三、四兩年，香港銀行業之效率顯著高於實施後之前兩年與台灣銀行業者，亦即CEPA之效益要到協議三及四之後才顯現出來。因此可知CEPA簽訂後，效益不會立即顯現，須有更多的開放例如CEPA三及四對營業額及資本額的放寬才有可能顯現直接之效益。此點應可作為台灣未來與大陸談判時應考慮之因素。 / Since Taiwan still disputes whether to sign Economic Cooperation Framework Agreement, (ECFA) with mainland China or not, this research tries to analyze the efficient change of Hong Kong banking industry before and after singing Closer Economic Partnership Agreement (CEPA) with mainland China. And hope to gain some understandings about the effect of singing CEPA, so that to provide some strategic references for singing EFCA in the future. The research data draw from 2000 to 2007 of the 18 regional banks from Hong Kong and 30 regional banks from Taiwan. The research applies data envelopment analysis (DEA) to evaluate the operating efficiency of the banks. After controlling banks’ financial characteristics and macro economics variables, the Tobit regression denotes the following suggestions. The efficient of Hong Kong banking industry showed a better efficiency than Taiwan banking industry. After signing CEPA for two years, Hong Kong banking industry finally revealed a significant improvement than first two years as well as Taiwan’s banking industry. The results suggest that signing CEPA does not immediately increase the efficiency of the industry; the agreement might need fewer restrictions, such as fewer amounts of sales restriction and less capital restriction in CPEA III and IV, in order to boost the performance of the industry. The results should provide a good strategic consideration about the future EFCA talk for Taiwan.

本研究以Rao(2006)的MMPI為基礎，在距離函數觀念下將MMPI進行拆解，分解成技術效率變動、技術變動、規模變動以及追趕項，再將追趕成份，進一步拆解為「技術追趕」(catch-up in technology, 簡稱CUT) 與「潛在技術變動」(potential technological change, PTC)，其中，CUT又可再分解為變動規模報酬之下的效率追趕(catch-up in efficiency, CUE)及規模追趕 (catch-up in scale, CUS)。實證上，利用1993-2007年間，15個歐洲國家的財務報表資料，運用DEA法分析西歐金融機構之經營效率，並進行生產力的推估與拆解，同時結合共同邊界的分析架構，從事群組國家間比較分析。 實證結果發現，MMPI表現突出的群組，主要來自於技術效率的進步，例如：北歐三國群組和奧地利；其次是規模效率的進步，例如：北歐三國與法國；最後才是技術變動，例如法國。而在十個國家群組中，除了義大利的MMPI退步以及奧地利的規模效率呈現持平外，其餘八個群組的MMPI與其三個構成項目，都呈現同升同降的相同趨勢，不同處僅在於變動幅度大小。例如MMPI都呈現進步的情形，其構成項目，分別表現出技術退步、技術效率進步以及規模效率進步。這樣的結果可能來自於歐洲單一市場的運作方式。 又依MMPI統計差異性檢定的結果，我們可以將原先依MMPI數值大小排序的十個國家群組，重新考慮群組間統計上差異及無差異的情形，合併為五個層次的生產力成長情形，第一層為北歐三國，MMPI成長最快，其次為奧地利、法國、比利時，再次為荷葡西英群組，第四層是盧森堡、瑞士，最末層則為德國、丹麥及義大利。

資訊發達的時代，資訊取得的方式與管道比起以前更方便而多元，但龐大資料量同時也造成了我們往往很難找到真正需要資料的問題，也因此資料的排名(ranking)問題就變得十分重要。本研究目的在於運用排名學習找出良好的排名，利用人對於某特定議題所給予的排名順序找出排名規則，並應用於資料探勘上，讓電腦可自動對資料做評分，產生正確的排序，將有助於資料的搜尋。 　　本研究分為兩部分，第一部份為排名演算法的設計，我們改良現有的排名方法(RankBoost)，設計出另一個新的演算法(RealRankBoost)，並且用LETOR benchmark實測，作為與其他方法的比較和效果提升的證明；第二部份為非對稱加權概念的提出，我們考量排名位置所造成的資料被檢視機率不同，而給予不同的權重，使排名結果能更貼近人類的角度。 / With the innovation in computer technology, we have easier ways to access information. But the huge amount of data also makes it hard for us to find what we really want. This is why ranking is important to us. The central issues of many applications are ranking, such as document retrieval, expert finding, and anti spam. The objective of this thesis is to discover a good ranking function according to specific ranking order of the human perceptions. We employ the learning-to-rank approach to automatically score and generate ranking order that helps data searching. This thesis is divided into two parts. Firstly, we design a new learning-to-rank algorithm named RealRankBoost based on an existing method (RankBoost). We investigate the efficacy of the proposed method by performing comparative analysis using the LETOR benchmark. Secondly, we propose to assign asymmetric weightings for ranking in the sense that incorrect placement of top-ranked items should yield higher penalty. Incorporation of the asymmetric weighting technique will further make our system to mimic human ranking strategy.