近來，臺灣教育部為招收更多國際學生而實行新政策。本研究分析政策實行的效果、學生來臺原因及在臺學生的滿意度。研究一以時間序列分析1954至2008年的國際學生人數，ARIMA模式的預測效果良好(RER=0.83%)，未來三年內國際學生人數將突破二萬人。研究二以問卷調查分析學生選擇留學國家及學校的選擇因素，同時分析學生來臺動機、所遇困難及在臺滿意度間的關係 (N=210)。結果顯示容易的簽證程序及臺灣的學術聲望影響學生來臺讀書；此外，財務、後勤及生活條件影響學生選擇留學學校。學生因臺學術聲望來臺且無食物適應困難者，願意再次來臺念書；學生因具吸引力課程及方便生活環境來臺且無硬體設備及學習適應方面困難者，願意建議他人來臺留學。根據研究結果，政府應加強國內教學品質，並協助提升學校學術聲望；增加赴海外任教教師，以教學專業提升我國國際形象。有興趣吸引國際學生的學校應可從健全學校行政體制著手，並聚焦於完善學生招生、入學諮詢輔導工作及協助生活適應。 / Recently, the Taiwanese Ministry of Education has implemented a new policy to recruit more international students. This study analyzes the policy’s effects and the reasons motivating students to study in Taiwan. The number of international students in Taiwan from 1954 to 2008 was used to generate a time series model to estimate the number of international students before and after the policy implementation. This ARIMA model (RER=0.83%) demonstrated a dramatic increase in the number of international students over the years. Using a questionnaire designed to examine determinants that affect international students’ decisions for choosing Taiwan and their respective schools (N=210), this study then study the relationship between the students’ motivations, the challenges they faced, and their degree of satisfaction with their experiences. Results demonstrated that an easy visa application process and Taiwan’s acclaimed academic reputation attracted students. Furthermore, financial, logistical, and living reasons affected the students’ choices in schools. Students who found living and educational conditions favorable and who felt intellectually stimulated would choose again to study in Taiwan and would recommend others to do so. Based on these results, the government should strengthen the quality of instruction and further promote Taiwan’s universities abroad. Schools interested in attracting international students should develop structured administrative systems focused on recruiting students and helping them transition into a new environment.

住宅為兼具消費及投資之雙重功能財貨，因此若從購屋動機劃分購屋族群，可以分為自住者及投資者，近年來受到國內房市呈現生氣蓬勃之景象及利率持續走低等總體經濟因素影響之下，出現越來越多以投資為主要目的之投資型購屋者，對於金融機構之購屋貸款業務來說，投資者之還款行為相較於自住者是比較不穩定的。故本文之研究目的即藉由探討自住者及投資者之購屋特徵異同，建立投資者之機率預測模型，預測某購屋者成為投資者之機率，提供一較為客觀之機率預測模型，供作金融機構放貸參考準則。接著進一步探討在不同機率界限（cutoff point）下之預測準確率，找出預測準確率最高之機率界限值，提高本模型之預測準確度；並探討金融機構在不同經營方針下之較適機率界限值。 / 本文使用台灣住宅需求動向季報之已購屋者問卷，建立二元羅吉特模型。研究結果顯示，區位在中心都市、高單價、小面積產品及大面積產品、預售屋及拍賣屋市場屬於投資型產品，而搜尋時間短、搜尋間數少、年齡較長、男性、無固定職業及家庭平均月收入較高者成為投資者之機率較高。接著，運用貝氏定理計算出預測準確率最高之機率界限值，結果當機率界限值為0.70時預測準確率最高，投資者達72.22%，自住者達80.07%。此外，並使用2007Q4的資料作樣本外驗證，投資者命中率為65.52%，自住者命中率為84.51%。最後，為提供金融機構運用，本文模擬兩種預測誤差在不同權重下對於金融機構所造成的損失，找出損失最少的機率界限值，結果皆是以0.70為最適機率界限值。 / Housing is dual function goods, consumption and investment, so if we separate the home buyers by their motives, they can be defined as two groups, owner-occupiers and investors. Recently, because the housing market is vigorous inland and the rates are fairly low, there are more and more home buyers buying houses for investment. To financial institutions, their payment behaviors are more instable, compare to owner-occupiers. So this article is aim to build a probability predictive model of housing investors by discussing the different home buying characters between owner-occupiers and investors. Therefore we can provide financing institutions a more objective method evaluating if they should lend money to the home buyers. Then we discuss the predictive accuracy with different cutoff points, finding the cutoff point with highest predictive accuracy, therefore we can elevate the model`s predictive accuracy. Besides, we also discuss the most optimal cutoff point for financial institutions under different administration principles. / This article builds binary logit model by the data of “Housing Demand Survey in Taiwan”. Our results suggests that if the houses in downtown、high unit price、big and small acreage、presale and court auction housing market belong to investing houses. And short search duration、few search items、older、male、non-constant job、higher income are getting higher probability to be housing investors. Then, we use Bayesian Theorem to figure out the cutoff point with highest predictive accuracy, and Our results suggests that 0.70 cutoff point with highest predictive accuracy , at that time, investor predictive accuracy is 72.22%, owner-occupier is 80.07%. Besides, we also do the out-sample test by the 2007Q4 data, the investor`s hit-rate is65.52%, the owner-occupier`s hit-rate is 84.51%. At the end, in order to provide financial institution to use, we give two predictive deviation different weights, to find the smallest loss cutoff point, the result all suggest that 0.70 is the most optimal cutoff point.

We estimate the willingness to pay for electricity generated from renewable energy in the Czech Republic. Discrete choice experiment is used to elicit preferences for various attributes of renewable electricity support scheme (PM emission, GHG emission, size of RE power plant, revenue distribution, and costs). Original survey is carried with 404 respondents living in two regions - Ustecky (polluted area) and Southern Bohemia (cleaner area). We find that respondents prefer decentralized renewable electricity sources over centralized, local air quality improvements over reduction in greenhouse gas emissions. Estimated marginal willingness to pay for 1% reduction in emission of particulate matter equals to 49 CZK, respectively 3.7 % of average monthly electricity bill. In total, WTP for green electricity is larger than current compulsory contributions to renewable energy support scheme. Powered by TCPDF (www.tcpdf.org)

På livsmedelsmarknaden finns det olika produkter som konsumenten kan välja mellan. Valensom görs inom dagligvaruhandeln kan påverka individen och samhället på olika sätt, dåprodukter har olika näringsinnehåll och de har producerats under olika förutsättningar. För attkonsumenten ska veta hur olika produkter påverkar individen och samhället finns det olikamärkningar såsom Fairtrade och KRAV. Ekologiska produkter marknadsförs som hälsosammasamtidigt som de ska vara bättre för miljön än icke ekologiska produkter. Den ekologiskamarknaden har ökat de senaste 5 åren. Av den anledningen finner vi det intressant att analyseravem som väljer att konsumera ekologiska produkter och varför.Syftet med studien är att analysera vilka faktorer som påverkar konsumenternas val attkonsumera ekologiska produkter. För att kunna analysera de olika faktorerna användskvantitativa ansatser. Data samlas in genom en enkätundersökning och analyseras medekonometriska tekniker. Resultatet analyseras även med hjälp av ekonomiska teorier.Enkätundersökningen genomförs på den svenska marknaden, i de två kommunerna Norrköpingoch Ockelbo.Studiens resultat indikerar att utbildning, kön, upplevd kunskap om ekologiska märkningar,upplevd mediepåverkan, härkomst och kommun är signifikanta variabler för att förklaraekologisk konsumtion. Resultatet indikerar även att de två viktigaste argumenten för attkonsumera ekologiska produkter är ur hälso- och miljösynpunkt. / The consumer can choose between different products at the market of groceries. These choicescan affect the human being and society in different ways, because products do not have thesame nutritional value and they may not have been produced in the same way. Therefore, it isimportant for the consumer to have knowledge about brands like Fairtrade and KRAV. InSweden, the products that are marketed as healthy and environmentally friendly alternatives arecalled ecological products. In the last 5 years, the market of ecological products has increased,because the market shows that the demand of ecological alternatives has increased. For thisreason, we think it is interesting to analyze who the typical consumer of ecological products isand why.The purpose of this study is to analyze which factors that affects the consumer’s choice ofecological products. To analyze the different factors the study is using quantitative methods.The data will be collected from surveys and then analyzed by using econometrical techniques,and the results will be analyzed and examined using economic theories. The survey is beingperformed on the Swedish market, where the municipalities Norrköping and Ockelbo has beenchosen. Norrköping has a substantially larger population than Ockelbo, which we consider is abenefit for the study.The results of the study shows us that education, gender, perceived knowledge about ecologicalbrands, experienced influence from media, a Nordic heritage and municipality are significantvariables to explain ecological consumption. The results also indicate the two most importantarguments for consuming ecological products are those of health and environmentalperspectives.

Contemporary research indicates that the era of autonomous vehicles (AVs) is not only inevitable but may be reached sooner than expected; however, not enough research has been done to address road infrastructure readiness for supporting AV operations. Highway agencies at all levels of governments seek to identify the needed infrastructure changes to facilitate the successful integration of AVs into the existing roadway system. Given multiple sources of uncertainty particularly the market penetration of AVs, agencies find it difficult to justify the substantial investments needed to make these infrastructure changes using traditional value engineering approaches. It is needed to account for these uncertainties by doing a phased retrofitting of road infrastructure to keep up with the AV market penetration. This way, the agency can expand, defer, or scale back the investments at a future time. This dissertation develops a real options analysis (ROA) framework to address these issues while capturing the monetary value of investment timing flexibility. Using key stakeholder feedback, an extensive literature review, and discussions with experts, the needed AV-motivated changes in road infrastructure were identified across two stages of AV operations; the transition phase and the fully-autonomous phase. For a project-level case study of a 66-mile stretch of Indiana’s four-six lane Interstate corridor, two potential scenarios of infrastructure retrofitting were established and evaluated using the net present value (NPV) and ROA approaches. The results show that the NPV approach can lead to decisions at the start of the evaluation period but does not address the uncertainty associated with AV market penetration. In contrast, ROA was found to address uncertainty by incorporating investment timing flexibility and capturing its monetary value. Using the dissertation’s framework, agencies can identify and analyze a wide range of possible scenarios of AV-oriented infrastructure retrofitting to enhance readiness, at both the project and network levels.

The Water Framework Directive requires reduced environmental impacts from human activities and for the assessment of the non-market benefits of pollution remediation schemes. This policy shift has exacerbated the research problems surrounding the physical, social and economic consequences of the relationship between land use and water quality. This research seeks to quantify the major socio-economic and environmental benefits for people which may arise as riverine pollution is reduced. To achieve these aims this research integrates primary data analyses combining choice experiment techniques with geographical information system based analyses of secondary data concerning the spatial distributions of riverine pollution. Current knowledge on the microbial quality of river water, measured by faecal indicator organism (FIO) concentrations and assessed at catchment scale, is inadequate. This research develops generic regression models to predict base- and high-flow faecal coliform (FC) and enterococci (EN) concentrations, using land cover and population (human and livestock) variables. The resulting models are then used both to predict FIO concentrations in unmonitored watercourses and to evaluate the likely impacts of different land use scenarios, enabling insights into the optimal locations and cost-effective mix of implementation strategies. Valuation experiments frequently conflate respondents’ preferences for different aspects of water quality. This analysis uses stated preference techniques to disaggregate the values of recreation and ecological attributes of water quality, thereby allowing decision makers to better understand the consequences of adopting alternative investment strategies which favour either ecological, recreational or a mix of benefits. The results reveal heterogeneous preferences across society; specifically, latent class analysis identifies three distinct groups, holding significantly different preferences for water quality. From a methodological perspective this research greatly enhances the ongoing synthesis of geographic and economic social sciences and addresses important policy questions which are of interest to a variety of stakeholders, including government departments and the water industry.

企業發生財務危機，不僅使其經營陷入生死關頭之掙扎，更影響眾多投資人、債權人的利益，對於整個經濟環境亦造成一定的衝擊。因此，如何提早察覺企業之危機，以減少社會成本，實值得我們深入研究。 本研究主要目的為評估現金流量表揭露之資訊，於預測企業財務危機的有用性。本研究欲探討現金流量資訊是否為預測企業財務危機的良好指標，於建構企業財務危機預警模式之際，加入現金流量的財務指標是否會比僅以傳統財務比率建立之預警模式，更具預測能力。 本研究採用配對樣本設計，在我國上市公司中共選取了35家危機公司與68家正常公司。並利用Logit迴歸分析分別建立現金流量模式、應計財務模式與綜合模式，得到以下結論： 一、在財務危機發生之前一至三年，本研究所使用的應計基礎財務比率並非皆適合用來區分危機公司與正常公司。 二、除了營業活動現金流量相關比率具有顯著的區別能力外，部分投資與融資活動現金流量相關比率亦提供額外的財務危機警訊。 三、現金流量比率預警模式之預測力表現不遜於應計基礎比率模式；但在應計基礎比率中加入現金流量比率，並未顯著提高模式的預測能力。 / The objective of this study is to assess the usefulness of cash flow disclosures in the prediction of financial distress. This study also determines whether cash flow ratios are good indicator of financial distress and whether adding cash flow ratios in prediction model can improve the predictive ability of the model employing conventional accrual-based ratios. Using a matched pair design, this study examines a sample of 35 distress firms along with 68 non-distress firms. Also, a logistic regression analysis is used to establish the financial distress model with and without cash flow variables respectively, in order to test the hypotheses developed by this study and to derive the conclusion. The findings of this study are as follows. 1. During the period between 3 years to 1 year before financial distress, the accrual-based ratios used in this study aren't all good predictor in financial distress model. 2. The discriminate ability of operating cash flow data is significant. Also, the investing and financing cash flow data provide additional information in the prediction of business distress. 3. Cash flow ratios provide a superior measure for the prediction of financial distress over accrual-based ratios. However, no significant evidence shows that using cash flow ratios in conjunction with accrual-based ratios can improve the overall predictive power of accrual-based ratios alone.

租稅天堂係一相對的概念，故其定義則因國而異。在企業國際化之後，租稅天堂的運用日趨頻繁，而方式則不一而足。其操作的原則不外乎透過移轉計價，即收入與費用的調整，將集團的利潤儘量集中在租稅天堂基地公司，以享受租稅遞延─甚至透過第二次隱藏的措施以圖謀中期或長期遞延利益。 　　我國自民國七十六年放寬外匯管制、七十八年放寬投資範圍及財務標準以來，對外投資的金額與件數激增。為瞭解我國廠商之成立控股公司與從事移轉計價之行為，乃就對外投資事業進行因素分析與Logit模型的檢定，分別尋求兩者行為的共同因素及具有影響力的動機。 　　雖然根據迴歸的結果顯示，企業乃是基於許多商業上的理由而使用租稅天堂；然而，其正當性的前提為所有的交易必須是純粹基於商業上的理由而非人為的策略。故從稅務機關的立場而言，它也有理由來關心交易是否按常規的價格或者利潤是否被不當地移轉。所以，合理的稅制乃必須兼顧廠商的商務上的需要與政府維持稅制公平、中立的職責。 　　惟觀乎我國目前對涉外交易之租稅規定，似較偏向於對外來投資之獎勵及規範，對於我國企業對外投資之相關稅負問題則規定甚少。緣此，本文乃就各國對於反租稅天堂措施中常用的一般性與特別性的立法規定，作一比較性的歸納，然後針對美國1993年的修正案作一說明。最後，對於假華僑案與重複課稅之減緩予以檢討，期能從中尋求出一個較為完善的稅制。

海岸為海洋與陸地交界之處，風、浪與潮流等自然營力長期於此不斷的侵蝕與堆積交互演替。近年來，隨著人口快速增加，人類對於海岸地區土地利用與開發的需求急遽擴張，使得影響海岸地形的變因日益複雜且變化迅速。宜蘭特殊的沙丘性海岸因抗蝕性弱，易受到外力影響而改變地形，海岸後方的沿海平原為人口與產業集中的地區，因此自然營力與人為因素對宜蘭平原海岸地形與環境的影響，備受關注。因衛星影像具多時期與大尺度的空間特性，可提供土地覆蓋變遷分析之有效資訊，故本文使用2003年、2006年與2009年宜蘭平原沿海地區SPOT 5衛星影像，利用階層式分類程序將研究試區分為水體、建成與交通用地、沙地、農地與林地等五種土地覆蓋類別，透過土地覆蓋分類之結果，比較三個時期土地覆蓋型面積的變化；建立馬可夫轉移矩陣，了解各土地覆蓋型轉移的情況；其次，量化地景指標以了解整體土地覆蓋型區塊在空間結構上的情況，並利用Shannon多樣性指標t檢定測驗兩時期間整體地景是否有明顯的變遷。進一步，利用二項式Logit迴歸分析2003至2006年與2006年至2009年間土地覆蓋型的變化與沙丘海岸變遷的關係以及參考前人宜蘭海岸變遷之研究，選擇可能影響此區海岸變遷的自然與人為環境因子，建立二項式Logit迴歸模式，探討各項因子對於沙丘性海岸的影響，並利用海岸沙丘空間分佈預測機率圖，最後以2006年與2009年沙地主題圖作為驗證資料，探討模式的可行性。本研究透過不同的空間計量方法，了解本區土地覆蓋型的變化，期本研究成果對於此區海岸保護與管理政策制定者有一參考的依據。 / Coastal zone is at the junction of ocean and land. The area constantly experiences interchanging succession of erosion and accumulation due to natural forces such as wind, wave, and tidal currents. In recent years, associated with fast population increase, the demand of lands expanded rapidly such that the effects on topography of coastal zone became more complex and changed quickly. Coastal sand dunes are dynamic and fragile terrain often regarded as environmentally sensitive areas. Sand dunes are vulnerable to erosion by natural process and human activity. The objective of this research was to examine the effects of environmental factors and land-use changes on coastal sand dunes in I-Lan County. Satellite imageries are characterized by multi-temporal and large-scale, therefore they are ideal for providing necessary information to facilitate analysis of regional land-cover changes. In this research, three SPOT 5 images acquired in 2003, 2006 and 2009 were used to analyze land-cover changes in I-Lan coastal zone. Firstly, a hierarchical classification procedure was applied to classify the image data to five land-cover types and the land-cover changes were compared. Secondly, based on the classification results, a Markov transitional probability matrix was constructed to understand the transition among different land-cover types, and the Fragstats software was used to quantify the landscape structure of three different periods. By analyzing the spatial distributions of land-cover types in different time periods, we were able to examine to the temporal and spatial changes of land-cover in the I-Lan coastal zone. In addition, a t-test based on Shannon diversity index was used to evaluate the changes of the whole landscape in the study area. Thirdly, by selecting possible natural and man-made factors that are likely to affect coastal environment based on various prior studies, the mathematical models such as Markov chain and binomial logit regression analysis were applied to predict the future overall landscape structure and to simulate the spatial distribution of the sandy coastal zone. Thematic maps derived from satellite images obtained in 2006 and 2009 were used to verify and assess the feasibility of the models. This study integrated several spatial statistical methods to understand the patterns of land-cover changes in the study area. It is expected that the results of this study may offer a valuable reference for the policy-makers of coastal protection and management.

住宅選擇是每一個家戶都會面臨到的問題，過去文獻發現購屋者先選擇租屋或購屋，若決定購屋，則先決定於何區位購屋，然後再決定購買何種房屋類型之房屋，然而卻未曾提及購屋者於不同市場類型住宅間之選擇。預售屋、新成屋以及中古屋等不同市場類型之住宅，各自隱含不同的效用及風險，影響著購屋者之選擇，因此本研究試圖討論購屋者於不同市場類型住宅間之選擇與偏好。 本研究採用內政部營建署「住宅需求動向調查」資料，利用混合多項羅吉特模型探討不同限制條件下，預售屋、新成屋與中古屋之個體選擇行為。實證結果顯示，投資者較偏好於購買知覺風險較高之預售屋，期待以高知覺風險換取高的報酬；教育程度較高者，因對居住品質要求愈高，因此傾向於選擇設備新穎之預售屋與新成屋；家戶平均月所得較高之購屋者，負擔能力較高，因此選擇總價較高之預售屋機率較高，其次為新成屋。此外，搜尋頻率愈高者，選擇預售屋之機率愈高，因預售屋無實體存在，預售屋購屋者為降低其知覺風險，將花費更高之搜尋成本。在價格彈性分析部分，實證結果顯示預售屋之競爭力最高，但預售屋之受衝擊力亦最高，而中古屋之競爭力於三種市場類型中居次，但中古屋衝擊力最小，因此，當單價屬性發生變動時，較不影響中古屋購屋者之選擇，但卻大幅影響預售屋購屋者之選擇機率。 / Every household would face housing choice, the past housing choice study founded that households decided tenure choice first, if they decides to buy a house, they first decided on what location, and then decided what type of housing to buy, but it has not been mentioned the housing choice among different residential market types. Pre-sale houses, newly constructed houses and existing houses implied different effectiveness and risks, affecting the choice of homebuyers. This article tried to discuss homeowners’ choice among different residential market types. This study use Construction and Planning Agency, "Housing Demand Survey of 2009" data, use mixed multinomial logit model, investigated under different constraints, housing choice behavior among pre-sale houses, newly constructed houses and existing houses. The empirical results showed that investors prefer higher perceived risk in buying pre-sale housing, looking for a high perceived risk and high rewards; higher education level, due to the higher quality requirements for living, so they preferred pre-sale houses and newly constructed houses. Homebuyers which have higher average monthly household income, have more affordable ability, so the probability of choosing pre-sale houses are much higher, followed by the newly constructed houses. In addition, the higher search frequency were more likely to choose pre-sale houses because pre-sale houses for sale no physical presence, pre-sale housing homebuyers in order to reduce their perceived risk, would spend more search costs. In the price elasticity analysis, empirical results showed that the pre-sale houses had the highest competitiveness, but the impact force was also the highest, while the existing houses market, the competitiveness of the third types was the second place, and the competitiveness of the existing houses was the smallest. Thus, when a change in unit price attribute, does not affect existing houses homebuyers, but significantly affected the choice probability of pre-sale houses homebuyers.