信用評等制度在美國已有百年以上歷史，而我國自民國80幾年開始發展評等制度，截至目前，僅有中華信用評等公司與台灣經濟新報社兩家公司提供評等服務，而台灣經濟新報社更將金融保險業排除於評等對象之外。站在穩定市場競爭、保障消費者權益、配合監理需求，以及輔助專案投標等方面來看，市場上的確需要一套能反映產險業行業特性之評等模式。 本文以美國接受A.M.Best評等之產險公司為研究對象，運用三種統計方法：多元區別分析(Multiple Discriminant Analysis，MDA)、羅吉斯迴歸(Unordered Logistic Regression，ULR)、順序性羅吉斯迴歸(Ordered Logistic Regression，OLR)，來建構產險公司之信用評等模式。樣本選擇方面：估計樣本，選取美國1993年到1996年接受A.M.Best評等之產險公司327家；保留樣本，為1997年78筆資料。 而本文預定達成目標如下： 一、建立等級預測模型：參考Ederington(1985)所作債券等級預測模型，以獲利能力、槓桿、流動性、投資風險、準備金適足性五類指標共38個財務比率，透過三種統計模型，建構等級預測模型。 二、藉由等級預測之建立，尋找能有效區別產險公司評等等級之財務指標，並分析其影響程度。 三、力求模型公信力：無論變數選擇或權數決定，皆由統計軟體按照樣本特性選取產生，減少人為主觀判斷。 在決定研究對象之初，因考慮到國內產險公司接受評等之家數不多，且年數又太短，資料數量無法據以建立評等模式，因而決定以美國的產險公司為對象，再以台灣樣本作為保留樣本，預測之等級結果僅供參考之用。 / Three possible models of the P-L Insurers rating process are estimated and compared：1. Muitiple Discriminant Model, 2. Unordered Logistic Model, 3. Ordered Logistic Model. Each model is estimated for a sample of 327 American P-L insurance companies using the same 38 independent variables. The three estimated models are then employed to predict ratings for a holdout sample of 78 companies. The study analyzes 1993 through 1997 data for a sample of P-L insurers that acquired A.M.Best Financial strength ratings between December 31,1993, and December 31, 1997. Empirical evidence suggests that even when models with the same basic structure were compared, differences in estimation procedures resulted in quite different coefficient estimates and classifications. The muitiple discriminant model clearly outperformed the regression model, while the unordered logistic model was clearly superior to the ordered logistic model.

過去都市的發展與道路規劃多以汽機車為主體，對於自行車的騎乘環境相對不夠友善，而隨著近年國內自行車使用率逐年攀升，據資料指出自行車發生事故的機率也有提高的趨勢，顯示自行車於道路上之安全性考量更需重視。故本研究將針對台北市自行車肇事資料進行深入探討，找出影響肇事嚴重度之因素，進而從規劃設計面研擬降低自行車事故之改善策略。 本研究係以民國98年至102年台北市自行車事故資料為分析對象，將肇事嚴重程度分為「死亡或頭部受傷」、「人員受傷」及「未受傷」三類，同時根據文獻回顧及實務上所能取得之資料，蒐集人、路、環境等24項研究變數。首先透過統計分析了解肇事資料之特性，而後再以多項式羅吉斯迴歸模型，分別針對整體事故以及不同空間及不同事故型態之自行車肇事資料，建構自行車肇事嚴重度模型，以釐清影響自行車事故之主要因素。 研究結果顯示，道路因素中事故位置為路口及路段對於自行車事故皆有顯著影響，其中路口造成死亡或受傷之機率更高；環境因素中，因彎道或建物造成視距不良對於增加自行車事故亦有顯著影響，而坡道則會降低事故發生之機率；在人的因素中，18歲以下和年齡越大、酒駕、直行或右轉，皆會增加因自行車事故致死或受傷之機率。最後依據實證之結果，謹從交通管理中的3E政策-交通工程（Engineering）、交通教育（Education）及交通執法（Enforcement）三面向之觀念及角度帶入都市設計層面，提出道路及環境改善措施，以提升都市街道之自行車騎乘環境，並透過教育宣導、推廣活動及相關法令規範等配套措施，藉以增加自行車之騎乘安全。

隨著氣候變遷與溫室效應影響日益明顯，台灣近年發生極端強降雨颱風的次數越來越頻繁，更造成流域地區嚴重災情，而從莫拉克風災經驗可體會到家戶風險溝通的重要性，也意識到我國實務與學術上相關研究的缺乏，故本研究探討家戶風險溝通機制中各項重要因素與調適行為間的關係，以及找出影響家戶調適行為決策之關鍵因素，進而提出家戶風險溝通策略之改善建議，以促進家戶採取調適行為。 本研究經由文獻回顧建立家戶調適行為之風險溝通概念架構，依循此架構研擬問卷，以高屏溪流域地區家戶為研究對象進行問卷調查，透過結構方程模式(SEM)驗證風險溝通架構，了解風險溝通機制各項因素與影響調適行為各因素之關係，後以面對災害回應之強烈將調適行為積極程度分為「消極或低度積極」、「中度積極」與「高度積極」，運用多項式羅吉斯迴歸模型建立家戶應變措施決策模型與調適措施決策模型，找出影響家戶調適行為決策之關鍵因素。 研究結果顯示，調適行為受到內在認知的影響，而內在認知同時受風險溝通機制與外在環境之影響，就風險溝通機制而言，親友鄰居、村里長與地方政府等社區網絡為重要管道。影響調適行為之關鍵因素以災害認知為主，其次為調適行為認知，居住村里次之，其中災害認知與調適行為認知越高，越有可能採取較積極之調適行為，此外，由於自然社會環境、風險溝通特性與社會經濟背景等因素交互影響下，各村里在調適行為決策上也有所差異。最後依據實證結果，與水患自主防災社區風險溝通現況，提出改善家戶風險溝通之策略建議，期望增進風險溝通機制的完備與促進家戶採取調適行為，以減緩極端氣候造成的衝擊。 / Along with the intensification of global climate change and greenhouse effect, typhoons with extreme rainfall strike Taiwan more and more frequently, which cause severe disasters in watershed area. From the experience of Typhoon Morakot in 2009, we realized the importance of risk communication with households and also the lack of related academic research. As a result, this study aims to discuss important factors in risk communication mechanism and their relationships with adaptive behaviors. It also find out key factors influencing decision-making of adaptive behaviors. Based on literature review, this study build a conceptual framework of risk communication process to describe how to trigger adaptive behaviors and encourage adaptive behaviors with risk communication. This study send out questionnaires to the households in Kaoping River Watershed and use structural equation modeling(SEM) to verify the conceptual framework. Then according to attitude of positive degree, adaptive behaviors are classified into“passive or low”,“medium” and “high” levels. By multinomial logistic regression, an empirical analysis was performed to analyze the key factors influencing decision-making of adaptive behaviors. The results show that adaptive behaviors are affected by internal cognition and at the same time internal cognition are affected by risk communication mechanism and external environment. As for risk communication mechanism, family, friends, neighbors and local governments are crucial communication channel. Key factors influencing decision-making of adaptive behaviors are cognition of disaster and adaptive behavior. People with higher cognition of disaster and adaptive behavior would more likely to take positive adaptive behaviors. Besides, community they lived in is also a key factor. Because the interaction of environments, risk communication patterns and socioeconomic attributes, people from different communities would take different adaptive behaviors. Based on empirical results, this study propose suggestions of risk communication strategies in order to better the risk communication mechanism and encourage households to take adaptive behaviors.

在我國正式加入WTO後，汽車產業面臨嚴重競爭，且相較於其他國家，台灣的汽車市場趨近於飽和現象，在供過於求情況下，製造與裝配過程附加價值低，附加價值存在於隨品牌所提供的產品服務。藉由商業智慧系統之建立，透過資料採礦、預測的功能，將不同消費習慣的客戶進行分類，達到準確的目標行銷。 　　本研究採用「決策樹C5.0」、「CART迴歸樹」與「羅吉斯迴歸」等方法建立模型於新車滿意度資料庫、車主購買滿意度資料庫及車主維修滿意度資料庫之資料。從三大資料庫中找出既有顧客群裡，較有可能會再次購買同品牌汽車的顧客特性，進一步整合行銷策略，提升顧客再次購買的機會。根據不同資料庫，本研究目的如下： 一、 分析於新車滿意度資料庫之資料，此資料包含2005年購買新車之車主資料，主要是建立客戶類型區隔模型及再購模型。 二、 分析於車主購買滿意度資料庫之資料，分別建立顧客是否會再次購買以及是否會向親朋好友推薦該品牌之模型。 三、 分析於車主維修滿意度資料庫之資料，分別建立顧客是否會再次購買、是否會推薦親朋好友以及是否會再次回廠維修之模型。

為了符合國際清算銀行在 2006 年通過的新巴賽爾資本協定，且有鑑於近年 來整體經濟環境欠佳，銀行業者面對外部的規定以及內部的需求，積極地尋求 信用風險模型的建置方法，希望將整個融資的評等過程系統化以提高對信用風 險的控管。 本研究希望利用 92 至94 年未上市上櫃中小企業之營造業的資料，依循新 巴賽爾資本協定之規定並配合資料採礦的技術，擬出一套信用風險模型建置與 評估的標準流程，其中包含企業違約機率模型以及信用評等系統的建置，前者 能預測出授信戶的違約情形以及違約機率；後者則是能利用前者的分析結果將 授信戶分成數個不同的等級，藉此區別授信戶是否屬於具有高度風險的違約授 信戶，期待能提供銀行業者作為因應新巴賽爾協定中內部評等法的建置，以及 中小企業的融資業務上內部風險管理的需求一個參考的依據。 研究結果共選出 5 個變數作為企業違約機率模型建立之依據，訓練資料以 及原始資料的AUC 分別為0.799 以及0.773，表示模型能有效的預測違約機率 並判別出違約授信戶以及非違約授信戶。接著，經過回顧測試與係數拔靴測試， 證實本研究的模型具有一定的穩定性。另外，透過信用評等系統將所有授信戶 分為8 個評等等級，並藉由等級同質性檢定以及敏感度分析的測試，可以驗證 出本研究之評等系統具有將不同違約程度的授信戶正確歸類之能力。最後，經 由轉移矩陣可以發現，整體而言，營造業在2003 年到2005 年間的表現有逐漸 好轉的趨勢，與營造業實際發展情形相互比較之下，也確實得到相互吻合的結 論。 / In order to conform to the New Basel Capital Accord passing in 2006 by the Bank for International Settlements and due to the slump faced by economies globally and the rise in the number of defaulters in the recent years, the banking industry has aggressively looked for ways to establish the reliable credit risk model that can accommodate required regulations set forth by the Accord as well as the internal banking procedure demands. The banking industry attempts to standardize the process of evaluating credit rating in regards to capital risk in the loan business to enhance the control of credit risks. The attempt of this research is to perform the process of the establishment and evaluation of the credit risk model which includes the default risk model of companies and the credit rating system within the framework of the New Basel Capital Accord using the statistical tool known as data mining. The data adopted in this study is taken from the construction industry of the SMEs from 2003 to 2005. The default risk model assesses the probability whether a company is at risk of being defaulted. In addition the credit rating system assigns credit scores to a company in question based on the application result from the default risk model to differentiate those who have high risk of being defaulted. More importantly this research provides banking industry of varying degrees of complexity to monitor its risk assessment as well as becoming a reference basis of the loan business in the SMEs. Based on the result of this study, five variables are selected as the default probability model basis. The AUC for the training data is 0.799 and for the raw data is 0.773 which represents the accuracy and reliability of the model in predicting the probability of default risk and determining the likelihood of the companies to default. After series of testing, our model stability plays a key role in determining whether the algorithm produces an optimal model in this study. The credit rating system formulates credit scores of the companies into 8 credit ratings. Applying homogeneity test and sensitive analysis, this study is able to verify the validity and accuracy of the rating system to correctly classify different levels of credit risk that could have jeopardized the companies to default. Finally, through the transformation matrix, there has been an improvement trend of performance in the construction industry from 2003 to 2005 which coincides with the result of this study.

2008年，美國華爾街危機影響全球金融市場，即使美國擬出許多救市計畫，全球股市依舊暴跌。在此危機衝擊下，各大金融機構不但利潤下滑，且資產減記和信貸損失也愈來愈嚴重。造成此一現象的主因即是次級房貸的影響，次級房貸主要是針對收入低、信用不佳卻需要貸款購屋的民眾，這類客戶通常借貸不易，倘若銀行內部沒有完善的評等機制那放款則需承受較大的違約風險。為因應此趨勢，本研究以台灣未上市中小企業為實例，資料的觀察期間為2003至2005年，透過資料採礦流程，建構企業違約風險模型及其信用評等系統。 本研究分別利用羅吉斯迴歸、類神經網路、和分類迴歸樹三種方法建立模型並加以評估比較其預測能力。發現羅吉斯迴歸模型對於違約戶的預測能力及有效性皆優於其他兩者，並選定為本研究之最終模型，並對選定之模型作評估及驗證，發現模型的預測能力表現尚屬穩定，確實能夠在銀行授信流程實務中加以應用。 / In 2008, the financial crisis on Wall Street had severe impacted the global economy. Although the US government has drawn up regulatory policies in an attempt to save the stock market, the value of global stock market has shrunk drastically. As such, the profits of many financial institutes’ have not only plunged, their value of assets have decreased while loss related to mortgage became more severe. The main cause behind this global phenomenon can be attributed to the effect of subprime mortgages. Subprime mortgages are mainly aimed at consumers who have low income and poor credit history but wish to purchase homes through the means of mortgage. These consumers usually find it difficult to obtain mortgage loans. If banks do not have a well structured evaluation system, they would have to bear more risks in the case of a default. To better understand this trend, this research chooses middle and small private enterprises as its samples. The period of observation is 2003 to 2005. Using the data mining process, this research builds a model that shows the risk associated with contract failure and credit score system. The research builds a model based on logistic regression, Neural Network, and cart to compare and contrast each of the three model’s ability to predict. The result shows that logistic regression is better at predicting defaults and is more effective than the other two models. The research, therefore, concludes logistic regression model as the research’s final model to study and evaluate. In process, the research result demonstrates that the logistic regression model makes more precise prediction and its prediction is fairly stable. Logistic regression model is capable for banks to employ in performing credit check.

近年來隨著台灣人口日漸少子化，「養兒防老」的傳統觀念已不符時勢所趨，面對高齡化社會所帶來龐大的財政負擔及老年人口安養等社會問題。過去研究結果提供了一可能的解決方案－「逆向房屋抵押貸款（Reverse Mortgage, RM）」，然而，對於此種新型貸款在台灣推行之完整可行性分析，相關研究尚付之闕如。是故，本研究從承貸雙方角度出發，旨在深入探討未來逆向房屋抵押貸款在台推行之可行性。 首先，對於申貸者而言，本研究以30至60歲且名下擁有不動產之家戶為研究單位，並用問卷調查台灣中年房屋持有者申請逆向房屋抵押貸款之意願程度。針對調查結果，再以「羅吉斯迴歸（Logistic Regression）」分析影響申請意願之顯著因子，據以探討申請意願與受訪者特性兩者之關係。 其次，從承貸者角度建立一貸款定價模型，模擬分析於損益兩平條件下，貸款機構有無貸款保險，以及於不同貸款給付方案中，其可提供逆向房屋抵押貸款之最高可貸款成數（Loan to Value, LTV）。再者，進一步結合台灣各主要都會區房價資料，研究顯示所得替代率（Income Replacement Ratio, IRR-RM）符合多數申貸者之基本需求。 本研究預期「逆向房屋抵押貸款」除了有效解決人口老化所衍生之社會問題外，亦兼具政府「就地老化（Aging in Place）」政策效益，提升了老年生活品質，維護老年人口的尊嚴。 / With the continuously declining fertility rates and the increasing life expectancy, Taiwan has become one of the aging societies in the world. To release the financial strain of the government, a great number of literature has suggested an alternative option, Reverse Mortgage (RM), to improve the retiring life quality of the elders. However, little attention has been given specifically to the feasibility of the application of RM and the pricing model in individual countries. This study thus conducted the questionnaire and collected the data in Taiwan for analysis in order to show the implementation feasibility of RM in aging society for both the aspects of both lenders and borrowers. First of all, to find out the factors affecting the willingness in applying for RM and the characteristic of the middle-aged homeowners, we designed a survey and a quantitative analysis of the questionnaire through Logistic Regression Analysis. Second, under a break-even hypothesis, we analyzed the ratio of Loan to Value (LTV) a reverse mortgage lender would offer through the simulation model. Furthermore, the housing data from different metropolises of Taiwan is integrated into the study in order to determine whether if the Income Replacement Ratio of RM (IRR-RM) could meet the basic needs of Taiwanese. Results found in this paper suggest that RM could satisfy the general need of people in Taiwan. Procedures conducted in this study may also provide precious insight for other aging countries. This paper suggests that reverse mortgage could not only solve the society issues, but also secure the retiring lives of the elders and preserve their living qualities.

假設二元反應曲線為簡單線性羅吉斯迴歸模型(Simple Linear Logistic Regression Model)，在樣本數為偶數的前題下，所謂的最佳D型設計(D-Optimal Design)是直接將半數的樣本點配置在第17.6個百分位數，而另一半則配置在第82.4個百分位數。很遺憾的是，這兩個位置在參數未知的情況下是無法決定的，因此逐次實驗設計法(Sequential Experimental Designs)在應用上就有其必要性。在大樣本的情況下，本文所探討的逐次實驗設計法在理論上具有良好的漸近最佳D型性質(Asymptotic D-Optimality)。尤其重要的是，這些特性並不會因為起始階段的配置不盡理想而消失，影響的只是收斂的快慢而已。但是在實際應用上，這些大樣本的理想性質卻不是我們關注的焦點。實驗步驟收斂速度的快慢，在小樣本的考慮下有決定性的重要性。基於這樣的考量，本文將提出三種起始階段設計的方法並透過模擬比較它們之間的優劣性。 / The D-optimal design is well known to be a two-point design for the simple linear logistic regression function model. Specif-ically , one half of the design points are allocated at the 17.6- th percentile, and the other half at the 82.4-th percentile. Since the locations of the two design points depend on the unknown parameters, the actual 2-locations can not be obtained. In order to dilemma, a sequential design is somehow necessary in practice. Sequential designs disscused in this context have some good properties that would not disappear even the initial stgae is not good enough under large sample size. The speed of converges of the sequential designs is influenced by the initial stage imposed under small sample size. Based on this, three initial stages will be provided in this study and will be compared through simulation conducted by C++ language.

IPCC於第四次報告書中，模擬氣候持續暖化預測未來海平面上升之情形，而海平面上升對於人口集中的台北都會區將產生莫大之衝擊，同時亦會造成土地利用變遷。本研究目的在於探討海平面上升對台北都會區土地利用變遷之影響，以及受淹沒地區之人口未來可能之遷移區位，主要係從社會經濟發展層面進行分析。運用二元羅吉斯迴歸模式並結合土地利用轉換與影響模型（CLUE-s），以四種不同情境模擬土地利用變遷之情況，其情境分別為海平面上升59公分管制農林地與不管制，以及海平面上升100公分管制農林地與不管制。 　　研究結果顯示，海平面上升之情形越嚴重，未來的都市建地發展會越趨向擴張的形式，對農林地產生變遷之壓力；而於同一海平面上升水平下，針對農林地進行管制，其建地之發展會較為集中於都市計畫地區範圍內，且多數人口亦將遷移至此，容易形成人口壓力。此外，土地利用變遷模擬所得之新增建地部分，於情境A、C下足以容納受影響之人口，但情境B、D則不足以容納，皆會對台北都會區產生容受力之問題，產生累計人口超過計畫人口之現象。因此，建議未來政府於都市發展上，可調整都市計畫內之土地使用強度或都市範圍，也可利用都市更新之方式減少新的土地開發；此外，從國家層級分析，未來的國土計畫法於立法上，亦可將更多氣候變遷相關影響因子納入四大功能分區，透過適宜性分析進行分類分級，以做為未來土地利用發展之引導。 / The 4th IPCC report simulated climate warming and predicted future sea-level rise scenarios. A sea level rise will have a great impact on the population of the Taipei metropolitan area, and it will also produce land-use changes. The purpose of this study is to research the impact of sea level change on land use changes and population migration in Taipei metropolitan, and the areas that will be immigrated by the flooded areas. The method used includes binary logistic regression model combined with Conversion of Land Use and its Effects Model (CLUE-s). Setting the sea-level rise and regulating agricultural land, forest land of the four simulated situations. The results show that the higher sea level rises, the more transformation towards urban development in the future, and the higher sea level will also pressure agriculture and forestry changes. As a result of population pressure on Taipei metropolitan area, the same level of sea-level rise for the regulation of agriculture and forestry land, the development of building sites and population migration will be more concentrated on urban planning areas. In addition, the simulation of land use change generated new building sites, sufficient enough to accommodate the affected population under A and C simulated situations, but B and D couldn’t generate such results. Instead, it will generate a carrying capacity issue. Therefore, this thesis suggests that the government adjust the intensity of land use in urban development, urban areas and urban renewal of urban planning. In addition, the analysis from the national level, the future legislation of Land Planning Act should include the relation of climate change impact factors as a consideration of future land use development.

基於累積殘差的廣義線性模型檢查方法，由Su和Wei(1991)所提出。在本次研究中利用蒙地卡羅模擬的方式探討，在各種模型下該檢定方法的成效，當中包含：卜瓦松迴歸模型、羅吉斯迴歸模型及負二項迴歸模型。由於負二項分配相較於卜瓦松分配及二項分配多了一個參數r，其中負二項分配之隨機變數定義為：直到第r次成功之失敗次數。因此，亦探討了在不同參數r下，基於累積殘差的廣義線性模型檢查方法是否有成效上的差異。結果發現，當r較小時，該模型檢查方法，需要較多的樣本數；而當參數r過大時，由於參數r的估計結果與實際值差異過大，便會導致檢定結果成效不佳。另一部分，亦將基於累積殘差的廣義線性模型檢查方法輔以傳統的迴歸模型參數T檢定，使得模型的適合度檢定流程趨於完善。