一國的政策產出常是受到該國政治、經濟、社會因素等的影響，而在巴西，由於其境內的「地球綠肺」亞馬遜雨林攸關人類之永續生存，故特別引起國際重視，也因此巴西的環境決策除了受到國內政治、經濟、社會因素影響以外，國際面的衝擊對之也深具撼動力。本文分別探討巴西軍政府時期與文人政府時期的國際情勢(外部環境)如何與其國內政治、經濟、社會因素(伊斯頓政治分析模型中的輸入項)相互作用，進而影響巴西軍政府與文人政府時期的環境政策，特別是亞馬遜政策。 巴西軍政府時期由於抱持「依賴」理論的世界觀，加以政治民族主義強烈，人民又乏管道表達反對意見﹔全國上下一味不惜犧牲亞馬遜以追求高經濟成長﹔社會上的環境運動發展雖始萌芽，但尚未成熟﹔國際間對於環境保護的共識亦尚處於模糊階段，故造就出一面倒向「大力開發亞馬遜」的政策決議。相較於政治與經濟因素的強烈開發動機，社會與國際因素的制衡力量根本不足以阻止亞馬遜流域的慘遭破壞與不永續發展。 文人政府時期的巴西受到全球化風潮的影響，受國際影響程度日漸增大，政治上亦開始走向民主，然而其政治特色一大部分係延續傳統的巴西政治文化，其政治現實上的限制一定程度地阻礙了巴西環境政策的落實；經濟方面，雖然巴西在卡爾多索的領導下擺脫了高通膨的惡夢，但對外部門脆弱的問題使得巴西政府的目標仍然是刺激經濟增長，故巴西經濟好轉對於亞馬遜政策是幸抑或是不幸，吾人仍持保留的態度。不過若以文人政府時期的社會面來看，則亞馬遜的前景便樂觀許多。雖然巴西目前有眾多非政府環境組織規模都不大，資源也不夠充裕，政府也不見得重視，但此時期中產階級與群眾運動開始結合運作，使得環境運動力量大增，即便目前其對政治的直接影響有限，但透過環保文化與價值的深耕，必可對未來的世代產生長遠的影響，政客們也會因選民的傾向而漸漸加強其環保的訴求，最後再輔以國際力量的支持，相信巴西人對於自己的環境會有越來越多的深思與關懷。

No description available.

美國亞馬遜公司以零售業起家，發展至今許多服務產品領導技術，已然被歸類為科技創新公司。本研究由亞馬遜公司的發展歷史、各項產品、服務內容、競爭對象等角度切入，進而探討其在發展過程形成的產品生態系統與產業生態系統，以及面臨的困境。 Kindle（電子閱讀器，後來也發展出平板電腦版本）的推出可以說是亞馬遜公司在數位產業中的重要產品，連結了其強大零售網絡與數位科技內容，例如數位影音，對於未來發展方向的扮演重要角色，也在此特別加以闡述說明。 本研究同時也對於亞馬遜與其他科技創新公司，例如蘋果、谷歌、微軟等，彼此之間既競爭又合作的關係進行分析與比較，期能對於這個既熟悉又陌生的國際品牌得以進一步了解。 / Amazon was once best known by its e-commerce and was indexed in category of retail sale in many stastistcs study. However in recent year development, Amazon is groupped in Technology Innovation category as well. The objective of thi thesis is mainly to provide an overview on the development of Amazon through introducing to all about its company history, essential products, services and important competitors. Furthermore, the thesis would like to look into its product ecosystem and industry ecosystem that are formed because the new developed products and competition, as well as the trouble it is facing or will encounter in the future. Among the products, Kindle, an E-reading device and later in tablet version as well, is one of the most import products in Amazon history. Kindle, serves as the channel between Amazon’s biggest and strongest E-commerce networks and modern digital technology products, such as streaming music and videos, it plays an significant role and worths a chapter to elaborate. The thesis also examines the relationships between Amazon’s main competitors, like Apple, Google and Microsoft. The relationships can be described as cooperative and competitive at the same time. A chapter on this topic should be very interesting and hope by doing so we can know more about this global company that almost every body in Taiwan knows but does not understand it well enough.

電子書興起，改變了讀者的閱讀方式，紙本書不再是唯一的選擇。電子書的供應鏈由上而下可分為：作者、出版社、DRM業者、網路通路平台、電信業者、硬體載具製造商。隨著科技創新，新的供應鏈創造了參與者新的競合模式，各參與者的商業模式也隨之創新，相較於過去的紙本書市場出版商擁有較大的議價能力之情況，在新的競合模式中，掌握客源的網路平台通路商對於上游的出版商之議價能力大幅提升。另一方面，越來越多作者跳過出版社，直接將電子書的版權賣給網路平台通路商，導致出版商原有的掌握版權之優勢減弱，長期下可能會致使出版社在電子書供應鏈中的議價能力進一步降低。未來隨著科技進步，彩色電子書閱器與結合其他功能的設備將是發展趨勢，但光靠硬體端難以建立他人無法輕易突破的進入障礙，而許多參與者在供應鏈上並非具單一角色，像是Amazon與Apple兼具網路平台通路商與硬體載具供應商之角色，亦即「平台+硬體載具」的雙重獲利模式，而這兩間公司皆掌握了主要的「客源」，是其重要優勢。而Amazon更是透過支援的應用程式，讓非自家載具之消費者也能至自己的電子書店下載電子書，像是iPad、iPhone、藍莓機等等。因此以未來電子書成長後議價能力與賺取現金流之能力的消長預期來看，相較於其他參與者，Amazon與Apple會是較佳的長期投資標的。 / The emergence of e-books changes the reading habit, and the paper-book is not the only one medium of reading anymore. The supply chain of e-books comprises diversified industries, including authors, publishers, DRM providers, online retailers who operate digital bookstores and manage accounts of customers, telecommunications, technology-side players. When technology advances, the new supply chain creates new co-competition model, the business models of players begins to innovate. Compared to paper-book market in which the publishers have stronger bargaining power, in new co-competition models, the online retailers have a huge customer base and therefore have stronger bargaining power over publishers. Furthermore, there are more and more authors who skip publishers and sell the digital right to online retailers directly. That is, the content resources controlled by publishers reduce, and the bargaining power of publishers deteriorates. In the future, producing colorful e-readers will not be a difficulty anymore, but the technology-side players will have difficulty in establishing entrance barrier. However, some participants play various roles across the supply chain, such as Amazon and Apple. Both of two companies play the roles of online retailers and technology-side players, and have double sales resources from plate form and hardware. Beside, both of these companies have large customer base, and it is the critical competitive advantage of Amazon and Apple. Especially, Amazon supports some hardware tools like iPad, iPhone, and Blackberry. As long as the customers download the application programs, the customers can purchase e-books on Amazon.com. From the aspects of potential of growing bargaining power and future discounted cashflows, Amazon and Apple would be better choices for long-term investors.

資料的快速增長與變化以及分析工具日新月異，增加資料分析的挑戰，本研究希望透過一個完整機器學習流程，提供學術或企業在導入大數據分析時的參考藍圖。我們以Spark作為大數據分析的計算框架，利用MLlib的Spark.ml與Spark.mllib兩個套件建構機器學習模型，解決傳統資料分析時可能會遇到的問題。在資料分析過程中會比較Spark不同分析模組的適用性情境，首先使用本地端叢集進行開發，最後提交至Amazon雲端叢集加快建模與分析的效能。大數據資料分析流程將以微博為實驗範例，並使用香港大學新聞與傳媒研究中心提供的2012年大陸微博資料集，我們採用RDD、Spark SQL與GraphX萃取微博使用者貼文資料的特增值，並以隨機森林建構預測模型，來預測使用者是否具有官方認證的二元分類。 / The rapid growth of data volume and advanced data analytics tools dramatically increase the challenge of big data analytics services adoption. This paper presents a big data analytics pipeline referenced blueprint for academic and company when they consider importing the associated services. We propose to use Apache Spark as a big data computing framework, which Spark MLlib contains two packages Spark.ml and Spark.mllib, on building a machine learning model. This resolves the traditional data analytics problem. In this big data analytics pipeline, we address a situation for adopting suitable Spark modules. We first use local cluster to develop our data analytics project following the jobs submitted to AWS EC2 clusters to accelerate analytic performance. We demonstrate the proposed big data analytics blueprint by using 2012 Weibo datasets. Finally, we use Spark SQL and GraphX to extract information features from large amount of the Weibo users’ posts. The official certification prediction model is constructed for Weibo users through Random Forest algorithm.