全球金融危機之後，在許多國家嚴重赤字之下，各界皆相當關心財政整頓效果。本文參考 Lin(2016) 的三階段方法估計動態追蹤資料分量迴歸，並使用敘事法 (narrative approach) 所建構的財政整頓衝擊變數，分析 17 個 OECD 國家 1978-2007 年跨國追蹤資料，探討財政整頓對經濟成長的影響效果。實證結果顯示財政整頓對經濟成長為負向影響，實施財政整頓會抑制產出，對一國經濟造成損害，且在經濟情勢不佳時，該負向效果更明顯。

There were many technical events held in 2017, like 2017 COMPUTEX, Google I/O, Microsoft Design Forum…etc., and Artificial intelligence (AI) is one of the most concerned and hottest topics in these events. There is no doubt that in the next few years, AI technology and its further developments will be the major focus in the science and technology industry. As AI technology brings in a lot of new applications and develops commercial values, for the server industry and corresponding supply chain, it will lead to a new wave and benefit the whole ecosystem. Although the growth rate of desktop and laptop computer slows down and smartphone market starts to saturate, the demand for data processing and computing continues to grow. Large datacenter, server hardware and cloud applications supported at the back-end could still keep their momentum of growth. Taiwan-based original design manufacturers (ODMs) maintain a stable growth rate in 90% of the worldwide server manufacturing and many new business models evolved in order to fulfill the demands brought by artificial intelligence (AI). The aim of this study is to analyze the positive and negative impacts of AI technology on server industry, and will focus on four major groups in the industry: datacenter customers, OEM, ODM and component suppliers.

近年來，在資通訊快速發展與公民意識崛起的環境下，開放資料開始成為各國關注的議題之一。運用開放資料致力於資訊透明、達至公眾參與與協同合作的三個目標，不但將政府資訊透明化、節省資訊流通成本，同時能夠藉由開放資料提供民眾更便捷的生活，並運用於經濟發展。 本研究運用公私協作模型，探討台灣在開放資料的發展過程中，政府、企業與公民間的互動關係，並藉此檢驗三方之間是否平衡運作。研究過程，透過相關文獻的檢閱分析三方的協作分析過程，並以運用開放資料進行商業開發的「公車通」、「KNY台灣天氣」、「觀天氣」與「天氣風險管理開發」作為本研究的個案，補足公私協作上的企業方的實務觀點。並先以企業的角度探討企業成功運用開放資料進行商業開放的關鍵因素，及現階段運用開放資料進行商業開發的發展情況。再將這企業個案放置於公私協作架構中，探討政府、企業與公民三方之間的互動關係。 本研究發現，先進者優勢、因開發者背景所取得之資源，以及對於政府開放資料的依賴程度為企業成功運用開放資料進行商業開發的關鍵因素。另外，政府、企業與公民在公私協作上，並非單向而為雙向的互動關係，且「政府」為公私民協作是否能夠平衡運作的關鍵角色。並經由此研究分析給予建議：1.企業若降低對政府開放資料的依賴程度，並運用組織人才及其關鍵資源，將能夠增加商業模式的差異性。2.政府不應干涉企業與民間於運用開放資料進行商業發展的市場。3.政府須提出完備的獎勵機制，亦或黑客公務員的加入，突破政府的穀倉效應。 / With the rise of civic consciousness, and the rapid development of information and communication technologies, open data become the important issue around the world. The purpose of the study uses the Public-Private-People-Partnership theory to investigate the interactional relationship within government, enterprises and citizen in the process of promoting open data in Taiwan. In addition, using the business model to investigate the key factors in developing business with open data successfully from the perspective of enterprises. The research adopts case study and in-depth interviews as the research tools to investigate. Furthermore, this research finds out that first-mover advantage, the resources enterprises have and the degree of dependence on open government data are the key factors in business development. In addition, the interactions within government, enterprises and citizen are not only unidirectional but bidirectional. And the operation of government will be the key factor to the balance in Public-Private-People-Partnership model. This study suggests that (a) If enterprise reduce the dependence on the open government data and use resources properly, it will increase the difference in its business model. (b) The government in Taiwan should not interfere the market in the business development with open data. (c) The government in Taiwan should set the performance incentives completely, and let more hacker civil servants join into public sector to break through silo effect.

網路盛行下，取得資訊的成本大幅降低，人們在旅遊決策前會先使用網路查詢相關的資訊，本研究目的在於探討線上的旅遊景點資訊搜尋對於景點以及對於到訪該景點之旅客有什麼樣的影響，利用景點的Google搜尋熱度、景點的燈光資料及景點旅客人數的資料，使用固定效果模型分析，證實景點的線上的旅遊景點資訊會使其景點變得熱鬧，尤其會影響到秘境、高學歷旅客及年輕人喜歡前往的景點。 另外本研究也發現，線上搜尋會使得旅客想要找旅伴一同出遊，且會使去其景點的遊客平均年齡降低，以及使遊客去其景點採取自由行的比例上升，讓旅客的旅遊模式變得多元化。 / With the borderless online communication becoming more widespread, obtaining information has significantly become faster and easier. Nowadays, people will do the research from the internet to gain the tourists information in advance. The purpose of this study is to explore how the online search of tourist attractions affects the attractions visitors. This study uses the Google trends, Nighttime Lights on Taiwan attractions and the number of tourist attractions from 2004 to 2013. This study used the fixed effects model to confirm that the online search of tourist attraction will make that attraction become more popular.

台灣是一個追求高等教育的理想學習地點，本研究藉由文獻整理歸納出以下幾點： 一、台灣提供優質的學術環境; 二、擁有豐富的文化遺產; 三、合理的學費; 四、多樣的獎學金申請機會; 五、優良以及安全的生活環境; 六、實惠且可靠的醫療系統; 七、良好的華語學習環境; 八、在台灣留學有助於未來的學習規劃以及工作機會。 本研究探討影響國際學生選擇來台灣就讀的因素，並運用追蹤資料(Panel data) 分析2006~2015年共10年的數據來了解台灣地區社會經濟的環境因素如何影響國際學生選擇學習目的地城市的決策指標，進一步分析出哪些因素特質影響了一個城市區域對於國際學生的吸引力。 結果顯示，國際學生總數在學院數量，失業率，高等教育比例，教育支出比例，醫療機構數量和犯罪率等方面都有達到統計顯著性。另外，分析顯示，國際學位生與非學位學生之間有不同的統計顯著性。 / Taiwan is an ideal study destination for several reasons. According to the literature reviewed in this research, the reasons are the following: Taiwan provides a high-quality academic environment, rich cultural heritage, reasonable tuition, generous scholarships, excellent living environment with a high level of safety, an affordable and reliable medical system, a good environment to learn Mandarin Chinese, and studying in Taiwan is helpful for both further study and future careers. This research was conducted in order to find out what factors influence international students' immigration to Taiwan to study. In this research, the investigation is carried out to find out how the environment affects international students' decision-making process and conducting with panel data analysis to find out from 2006~2015 what factors determine a students' destination city to study in Taiwan. The results indicate that the total number of the international students have statistical significance on the categories of Number of Colleges and Universities, Unemployment Rate, Higher Education Ratio, Education Expenditures Ratio, Number of Medical Care Institutions and General Crime Rate. The analysis indicated that there are different statistically significant results between the degree students and the non-degree students.

臺灣隨著戰後嬰兒潮步入高齡，加上生育率為世界最低國家之一，刻正面臨嚴重的少子化及高齡化問題，除提升生育率、減少本國勞動力外流、並爭取海外留學生、僑民回國就業外，補充外籍勞動力，以減緩工作世代壓力，實為我國的當務之急。 為了解外國勞動力在臺工作縣市分布的影響因素，不同於以往的研究，本文從縣市別角度出發，採用2006年至2015年臺灣21個縣市的追蹤調查資料，以外籍專業人員、外籍勞工、全部外籍勞動力為被解釋變數建立3個模型，並分別以最小平方法、固定效果模型以及隨機效果模型進行迴歸分析，結果顯示，影響外國專業人才來臺工作縣市分布之重要因素為產業因素與教育資源因素，而失業率、產業因素以及教育資源因素則為外籍勞工與全部外籍勞動力的重要影響因素。 / Taiwan, with the post-war baby boom turning into the elderly boom by time, coupled with being one of the lowest birth rate in the world, is currently facing serious population aging problems. In order to deal with this situation, Taiwan government needs to encourage fertility, reduce domestic workforce outflows, and attract overseas students and nationals to return home. In addition, it is also urgent to recruit foreign workforce to ease the pressure of domestic working generation. Different from the previous studies, this study attempted to understand the influencing factors of foreign workforce’s distribution in Taiwan by adopting a new perspective of observing each city and county respectively. This study used the data of 21 cities and counties in Taiwan from year 2006 to 2015, choosing the data of foreign workforce, foreign professionals and foreign labors as the dependent variables. Afterwards, the OLS model, the fixed effect model and the random effect model were conducted to estimate those variables separately. The results indicated that the industrial factors and educational resources factors were the main important factors influencing the distribution of foreign professionals in Taiwan, while the unemployment rate, industrial factors and educational resources factors were the important factors influencing the distribution of foreign labors and all the foreign workforce.

在今日，實施綠色供應鏈管理不僅是遵守法規規範，更積極的是實施綠色供應鏈管理可為企業帶來更多競爭優勢，因此綠色供應鏈管理對企業而言越來越是值得探討與重視的議題。 目前綠色供應鏈管理平台的建立普遍是依賴政府或是第三方機構建立資料交換的機制，或是串接供應鏈上各個企業不同的企業系統達到資料交換的目的，然而這樣的做法有其風險。因為物料資料對企業來說是敏感且有價值的，企業須對提供儲存、資料交換服務的平台有高度信任度，且整個系統亦有中央集權式系統架構之缺陷。運用區塊鏈技術的特性可以解決這樣的問題，區塊鏈技術提供資料永久保存、不可篡改的分散式系統解決方案。本研究更近一步將區塊鏈技術結合加解密機制，讓資料僅有提供者本身以及其同意之查詢者能讀取，如此一來使得區塊鏈系統更具資料隱私之特性，並透過區塊鏈外部儲存系統的設計使儲存空間更易規模化，使得綠色供應鏈中大量、有價值物料資料之儲存、交換且須高度信賴物料資料不被篡改以及綠色認證不被篡改、偽造的這些議題能被解決。 / Nowadays, the implementation of green supply chain management system can bring more competitive advantages for enterprises. This issue is increasingly worthy of discussion. Until now, the establishment of green supply chain management platform generally depends on the government or third parties building the mechanism of exchanging the information, and connecting the various enterprises of different enterprises on supply chain to achieve the purpose of data exchange. However, the approach has risks. The features of blockchain technology can provide permanent preservation and tamper-proof system through the decentralized system solutions. Moreover, this study combines with data-privacy design and off-blockchain storage design to solve the problems of storaging and exchanging the valuable data and ensure material information and green certifications are tamper-proof.

隨著大數據時代來臨，機器學習方法已然成為熱門學習的主題，主要分為監督式學習與非監督式學習，亦即分類與分群。本研究以羅吉斯迴歸配適結果加權距離矩陣，以資料雲幾何樹分群法為主，在含有類別變數的紅酒資料中，透過先分群再分類的方式，判斷是否可以得到更佳的預測結果。並比較監督式學習下各種機器學習方法預測表現，及非監督式學習下後再透過分類器方法的預測表現。在內容的排序上，首先介紹常見的分類與分群演算方法，並分析其優缺點與假設限制，接著將介紹資料雲幾何樹演算法，並詳述執行步驟。最後再引入加權資料雲幾何樹演算法，將權重的觀點應用在資料雲幾何樹演算法中，透過紅酒資料，比較各種分類與分群方法的預測準確率。 / Machine learning has become a popular topic since the coming of big data era. Machine learning algorithms are often categorized as being supervised or unsupervised, namely classification or clustering methods. In this study, first, we introduced the advantages, disadvantages, and limits of traditional classification and clustering algorithms. Next, we introduced DCG-tree and WDCG algorithms. We extended the idea of WDCG to the cases with label size=3. The distance matrix was modified by the fitted results of logistic regression. Lastly, by using a real wine dataset, we then compared the performance of WDCG with the performance of traditional classification methodologies. The study showed that using unsupervised learning algorithm with logistic regression as a classifier performs better than using only the traditional classification methods.

閱讀是吸收知識的途徑，不同的閱讀模式所帶來的閱讀成效也會不同。如何透過機器學習的方式，從凝視點找出閱讀行為的關聯性，將是本研究的目標。實驗選擇低成本眼動儀紀錄讀者閱讀過程中的眼動資料，採用dispersion-based演算法找出凝視點，以計算凝視點特徵，包含凝視時間、凝視距離、凝視位置以及凝視方向。 本研究將閱讀模式分成五種類別，包含快讀、慢讀、精讀、跳讀與關鍵字識別，透過不同文章的呈現，引導30位測試者遵循其內容進行閱讀，藉此收集不同行為模式的眼動資料。實驗流程中所有的眼動資料會隨機被分成為兩份，依序建立不同維度的訓練資料，由交叉驗證的分類結果找出理想之特徵與維度。以每次挑選6位測試者的眼動數據為測試資料進行5次分類驗證，其平均正確率為78.24%、74.19%、93.75%、87.96%以及96.20%，均達到不錯的分類結果。 / Reading is one of the paths to acquire knowledge. The efficiency is different when different reading patterns are involved. It is the objective of this research to classify reading patterns from fixation data using machine learning techniques. In our experiment, a low-cost eye tracker is employed to record the eye movements during the reading process. A dispersion-based algorithm is implemented to identify fixation from the recorded data. Features pertaining to fixation including duration, path length, landing position and fixation direction are extracted for classification purposes. Five categories of reading pattern are defined and investigated in this study, namely, speed reading, slow reading, in-depth reading, skim-and-skip, and keyword spotting. We have recruited thirty subjects to participate in our experiment. The participants are instructed to read different articles using specific styles designated by the experimenter in order to assign label to the collected data. Feature selection is achieved by analyzing the predictive results of cross-validation from the training data obtained from all subjects. The average classification accuracies in five-fold cross-validation are 78.24%, 74.19%, 93.75%, 87.96% and 96.20% using the eye movements of the six randomly selected subjects as test data.

觀光旅遊業已成為二十一世紀的明星產業，根據觀光局統計2015年來臺觀光旅客已達到1,043萬人次，觀光外匯收入更達到4,528億元。觀光旅遊業的迅速發展，不僅可藉由吸引外來觀光客增加外匯收入、創造就業機會，政府亦能以創新思維，推動整合性政策及各縣市行銷策略來振興經濟，藉此提升國民的生活品質。若能找出臺灣觀光發展特色並永續經營，必讓臺灣成為新的區域中心點、成為亞太新觀光中心。 基於上述研究動機，本研究主要探討2014年來臺觀光旅客所參與活動的特性。以交通部觀光局所提供之問卷，進行資料整理並使用決策樹分析，找出來臺旅客所參與各項活動之特徵，進而瞭解來臺旅客旅遊動機、消費情形及休憩滿意度，以供政府及民間相關單位研擬國際觀光宣傳與行銷策略、提昇國內觀光服務品質與國際旅遊觀光競爭力之參考，並持續提升臺灣觀光品質形象，更努力建構質量並進的觀光環境，希望能奠定觀光產業從量變到質變的基礎，達到擴大觀光服務輸出的目的。 / Tourism has become a major industry in Taiwan in the 21st century. According to the Tourism Bureau, Taiwan received over 10 million international visitors in 2015, which generates over 4.5 billion New Taiwan dollars in revenue. With the industry fast booming, tourism revenue is increased and new jobs are created. The government is thus able to boost the economy through innovation in all comprehensive policies and collaboration between cities and counties on marketing strategies, which in turn raises the living standards of Taiwanese citizens. If the industry is developed efficiently and sustainably, Taiwan has the potential to be the next focal point of Asian-Pacific tourism. With the information mentioned above in mind, this study aims to analyze international visitors to Taiwan and activities they engaged in in the year 2014. Based on surveys provided by the Tourism Bureau, it utilizes decision tree analysis to identify the characteristics of visitors and their activities. It further explores their purpose of visit, spending during and overall satisfaction with their stay. In doing so, it could make a positive contribution when the government and tourism-related industries intend to devise future marketing strategies, improve service performance, and build a global image to attract more tourists. All in all, more emphasis should be laid on quality than quantity in order for the tourism industry to expand efficiently and sustainably.