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網路外部性與競爭規範--微軟之反托拉斯案件研究 / Network Externality and Competition Regulation---A Research on the Antitrust Case of Microsoft楊佳憲, Yang, Jia-Shiang Unknown Date (has links)
Red-Hat Linux之CEO,Robert Yang曾對微軟行為作如此論述:「微軟很壞,但壞的很成功!」本文內容可分為三部分。首先在於釐清微軟成功之原因,針對形成微軟獨佔個人電腦作業系統之原因,做一有系統之經濟觀點分析:將軟體產業特殊之競爭策略層面考量與相關網路外部性理論經濟模型推論、驗證過程透過本文架構重新整合,發展出不同於一般管理文獻論述之方式以建立微軟獨佔地位之經濟理論基礎。第二部份針對微軟破壞競爭規範等違法行為作研究,主要針對微軟1998年對網景之反托拉斯此案,以美國司法部公布之事實認定書與休曼法為基礎,加以延申並做詳盡之探討。第三部分則針對微軟被宣判違反反托拉斯法後,政府在網際網路時代下執行反托拉斯法以回復競爭規範之角色、補救原則、措施做一探討並與AT&T案例比較;最後並提出兩種分割方式經濟模型分析與最適分割條件之政策性建議。 / The CEO of Red-Hat Linux, Robert Yang, has made such comments on the behavior of Microsoft that:” Microsoft is very bad, but very successful.” This thesis mainly focuses on three parts. The first part is to clarify the reasons why Microsoft is so successful and analyze its monopolistic position on personal computer operating system market in light of a systematic、economic method combining strategic competitive characteristics of software industry with economic theories of network externalities, making its foundations of monopoly and distinguish from general managerial arguments through the framework of this thesis. The second part primarily focuses on the antitrust case of Microsoft’s behavior against Netscape proposed by DOJ in 1998. Basing on the DOJ’s findings of fact and the antitrust law of Sherman act, we made explorative research on the case. The third part is to explore the role、principles and methods of antitrust remedy enforcements by government under the era of networks and Internet and compare with the AT&T case in 1982. Finally, we compare between two different ways that divide Microsoft into two companies in light of economic analysis and propose policy recommendation about condition that will optimize upon exploiting such remedy method.
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優步公司訂價演算法關於價格聯合行為爭議之研究─以美國休曼法為中心 / A Study on Price-Fixing Controversies over Uber's Pricing Algorithm Focusing on U.S. Jurisprudence of Sherman Act劉穎蓁 Unknown Date (has links)
近來共享經濟商業模式崛起,對各國既有相關市場皆造成不少之衝擊,當中,優步公司用以計算車資之「訂價演算法」,於美國實務亦引起許多爭議。美國司法案例中其中一個重要爭議即為優步公司單方制定之「訂價演算法」與其採行之「高峰動態訂價法」究否構成價格聯合行為。於美國實務近來2起與價格聯合行為相關之案例,即包含Meyer v. Kalanick案與Chamber of Commerce & RASIER, LLC v. City of Seattle案(以下簡稱「City of Seattle案」)中,皆可見Uber企圖正當化其價格聯合行為,以免於競爭法審查下有違法之嫌。而美國對於價格聯合行為之規範,載明於休曼法第1條;依據休曼法第1條規定,若原告擬主張被告行為違反卡特爾行為,則應證明系爭卡特爾行為符合合意主體要件、具合意或共謀行為,與造成限制性之競爭效果等三項要件。由於上述二案皆仍於訴訟前階段,判決尚未出爐,因此,此議題值得吾等分析之。本文擬以美國實務判決為基準,彙整相關爭議,進而探討Uber所採訂價演算法是否構成價格聯合行為。
本文發現,雖然此等訂價演算法究否構成價格聯合行為尚未有定論,然由於訂價演算法中之高峰動態訂價法可提高駕駛於尖峰時段中提供載客服務之誘因,將有助於調節市場機制與促進競爭。此外,Uber亦可利用其訂價演算法與設置平台所奠立之優勢,使其得以潛在破壞市場秩序之形式,創造競爭優勢。據此,Uber除可克服既有行政管制下市場進入之劣勢外,亦得使相關市場交易效率大幅提升、市場更加競爭。因此,於探討Uber價格聯合行為合法與否時,亦應將此等因素納入考量。 / The rapid expansion of sharing economy enterprises around the world has led to many challenges. And among these enterprises, one of the most disruptive examples is Uber because of its algorithm. In the United States, the lawsuits regarding Uber's algorithm has also gained massive attention. One of the controversial issues of the complaints relies upon whether Uber's algorithm which set by Uber, and “surge pricing” model do constitute an illegal price-fixing in violation of Section 1 of the Sherman Act. In 2 recent high-profile cases, Meyer v. Kalanick & Chamber of Commerce & RASIER, LLC v. City of Seattle, Uber has tried to justify its price fixing to avoid antitrust scrutiny. There are three specific facts that the Plaintiff must prove to establish its antitrust claim in Section 1 of the Sherman Act: 2 or more entities entering into an agreement, conspiracy, and unreasonably restrains competition. Analysis regarding Uber's algorithm is significant because the trials are ongoing. Therefore, the thesis examines whether Uber's algorithm do constitute an illegal price-fixing in violation of Section 1 of the Sherman Act by exploring the potential problems with regard to the elements based on U.S. judicial decisions.
The thesis believes that Uber's algorithm can enhance the efficiency of transaction and has pro-competitive effects, leading to the impact of Uber's surge pricing on providing the incentives for drivers during peak hours. Establishing platform and Uber's algorithm create Uber's strengths and advantages. By having disrupted the existing industry, Uber's algorithm serves pro-competitive purposes.
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