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Tellabs Inc. v. Makor Issues & Rights, 551 U.S. 308 (2007), was a United States Supreme Court case in which the Court ruled on the interpretation of the Private Securities Litigation Reform Act of 1995's requirement of scienter in a civil action in apply to Tellabs and Makor Issues & Rights. [1]
Tellabs, Inc. is a global network technology company that provides networking and communications solutions to both private and governmental agencies. [2] The company offers a range of products and services, including optical transport systems, access systems, managed access solutions, and network management software.
The Court's decision in Padilla v. Kentucky, holding that the Sixth Amendment requires defense attorneys to inform criminal defendants of the deportation risks of guilty pleas, does not apply retroactively to cases already final on direct review (that is, non-habeas appeals). Marx v. General Revenue Corp. 11-1175: 2013-02-26
The United States Supreme Court issued a decision that clarified what was to be understood as a "strong inference." In Tellabs, Inc. v. Makor Issues & Rights, LTD (21 June 2007) , an 8–1 ruling of the Court defined the standard that the plaintiff had to meet to proceed with a securities fraud litigation.
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In this example a company should prefer product B's risk and payoffs under realistic risk preference coefficients. Multiple-criteria decision-making (MCDM) or multiple-criteria decision analysis (MCDA) is a sub-discipline of operations research that explicitly evaluates multiple conflicting criteria in decision making (both in daily life and in settings such as business, government and medicine).
The decision-making paradox is a phenomenon related to decision-making and the quest for determining reliable decision-making methods. It was first described by Triantaphyllou, and has been recognized in the related literature as a fundamental paradox in multi-criteria decision analysis (MCDA), multi-criteria decision making (MCDM) and decision analysis since then.
The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which was originally developed by Ching-Lai Hwang and Yoon in 1981 [1] with further developments by Yoon in 1987, [2] and Hwang, Lai and Liu in 1993. [3]