This book constructs a model of the knowledge value chain in the university and analyzes the university knowledge value-added mechanism in the process of Industry-University Collaborative Innovation. The efficiency of university knowledge value-added of Provinces in China is measured. The book illustrates the operating mechanism between enterprise subsystems and college subsystems in the collaborative innovation system, and establishes a Data Envelopment Analysis (DEA) model with parallel decision making units to assess the performance of Industry-University Collaboration Innovation in China by considering the complex internal structure of the collaborative innovation system. The book also addresses various behaviors of knowledge agents in the knowledge sharing process. The research findings of this book will provide some policy implications to help policy makers to establish a more effective collaborative and interactive innovation system. The focus on China offers a unique contribution, because the form that university-industry collaborations take differs widely from country to country. The United States, the United Kingdom, Japan, and China differ vastly in the way that they implement their respective R&D policies. Some of these differences stem from national culture, others from the historical evolution of the institutions that support innovation efforts, and some from the extent of available resources.

This book constructs a model of the knowledge value chain in the university and analyzes the university knowledge value-added mechanism in the process of Industry-University Collaborative Innovation. The efficiency of university knowledge value-added of Provinces in China is measured. The book illustrates the operating mechanism between enterprise subsystems and college subsystems in the collaborative innovation system, and establishes a Data Envelopment Analysis (DEA) model with parallel decision making units to assess the performance of Industry-University Collaboration Innovation in China by considering the complex internal structure of the collaborative innovation system. The book also addresses various behaviors of knowledge agents in the knowledge sharing process. The research findings of this book will provide some policy implications to help policy makers to establish a more effective collaborative and interactive innovation system. The focus on China offers a unique contribution, because the form that university-industry collaborations take differs widely from country to country. The United States, the United Kingdom, Japan, and China differ vastly in the way that they implement their respective R&D policies. Some of these differences stem from national culture, others from the historical evolution of the institutions that support innovation efforts, and some from the extent of available resources.

This book offers new transparent views and step-by-step methods for performance evaluation of a set of units using Data Envelopment Analysis (DEA). The book has twelve practical chapters. Elementary concepts and definitions are gradually built in Chapters 1-6 based upon four examples of one input and one output factors, two input factors, two output factors, and four input and three output factors. Simultaneously, the mathematical foundations using linear programming are also introduced without any prerequisites. A reader with basic knowledge of mathematics and computers is able to understand the contents of the book. In addition, to prevent pre-judgment about the available concepts and definitions in the DEA literature, some new phrases are introduced and, after elucidating each phrase in detail in Chapters 1-6, they are reintroduced for industry-wide accuracy in Chapter 7. After that, some of the more advanced DEA topics are illustrated in Chapters 8-12, such as: production-planning problems, output-input ratio analysis, efficiency over different time periods, Malmquist efficiency indexes, and a delta neighborhood model. A clear overview of many of the elementary and advanced concepts of DEA is provided, including Technical Efficiency, Relative Efficiency, Cost/Revenue/Profit Efficiency, Price/Overall Efficiency, the DEA axioms, the mathematical background to measure technical efficiency and overall efficiency, the multiplier/envelopment form of basic DEA models in input/output-orientation, the multiplier/envelopment of Additive DEA model, the multiplier/envelopment of slacks-based models, and others. The book also covers a variety of DEA techniques, input-output ratio analysis, the natural relationships between DEA frontier and the ratio of output to input factors, production-planning problems, planning ideas with a centralized decision-making unit, context-dependent DEA, Malmquist efficiency index, efficiency over different time periods, and others. End-of-chapter exercises are provided for each chapter.

This book offers new transparent views and step-by-step methods for performance evaluation of a set of units using Data Envelopment Analysis (DEA). The book has twelve practical chapters. Elementary concepts and definitions are gradually built in Chapters 1-6 based upon four examples of one input and one output factors, two input factors, two output factors, and four input and three output factors. Simultaneously, the mathematical foundations using linear programming are also introduced without any prerequisites. A reader with basic knowledge of mathematics and computers is able to understand the contents of the book. In addition, to prevent pre-judgment about the available concepts and definitions in the DEA literature, some new phrases are introduced and, after elucidating each phrase in detail in Chapters 1-6, they are reintroduced for industry-wide accuracy in Chapter 7. After that, some of the more advanced DEA topics are illustrated in Chapters 8-12, such as: production-planning problems, output-input ratio analysis, efficiency over different time periods, Malmquist efficiency indexes, and a delta neighborhood model. A clear overview of many of the elementary and advanced concepts of DEA is provided, including Technical Efficiency, Relative Efficiency, Cost/Revenue/Profit Efficiency, Price/Overall Efficiency, the DEA axioms, the mathematical background to measure technical efficiency and overall efficiency, the multiplier/envelopment form of basic DEA models in input/output-orientation, the multiplier/envelopment of Additive DEA model, the multiplier/envelopment of slacks-based models, and others. The book also covers a variety of DEA techniques, input-output ratio analysis, the natural relationships between DEA frontier and the ratio of output to input factors, production-planning problems, planning ideas with a centralized decision-making unit, context-dependent DEA, Malmquist efficiency index, efficiency over different time periods, and others. End-of-chapter exercises are provided for each chapter.

Studienarbeit aus dem Jahr 2009 im Fachbereich BWL - Rechnungswesen, Bilanzierung, Steuern, Note: 1,0, Universitat zu Koln (Seminar fur Allgemeine Betriebswirtschaftslehre und Bankbetriebslehre), Sprache: Deutsch, Abstract: Als die Kreditzusagen und der Commercial Paper Markt in den letzten Jahrzehnten in den USA verstarkt an Bedeutung gewonnen haben, hat sich auch die entsprechende Literatur in diesem Bereich schnell entwickelt. In Anbetracht der historischen Entwicklung des Commercial Paper Marktes ist das Ziel dieser Seminararbeit, einen Uberblick uber die Rolle der Banken auf dem Commercial Paper Markt zu geben, wobei der Fokus auf einem theoretischen Paper von Gatev & Strahan (2006) "Banks' Advantage in Hedging Liquidity Risk: Theory and Evidence from the Commercial Paper Market" liegt. In der Arbeit wird nach einer Einfuhrung die bisherigen Arbeiten uber Kreditzusagen, insbesondere uber Commercial Paper Backup Lines, dargestellt. Danach wird das Paper von Gatev & Strahan prasentiert, welches den Vorteil der Banken gegenuber Nichtbanken- Finanzintermediaren bei der Liquiditatsbereitstellung via Kreditzusagen untersucht. Hierbei werden sowohl die grundlegende Argumentation als auch die empirische Belegung und die angewendeten statistischen Methoden vorgestellt. Ausgehend von diesem Paper werden auch einige Punkte fur Diskussionen geschildert.

Studienarbeit aus dem Jahr 2009 im Fachbereich BWL - Wirtschaftspolitik, Note: 1,0, Universitat zu Koln (Staatswissenschaftliches Seminar), Veranstaltung: Monetare Aussenwirtschaft, Sprache: Deutsch, Abstract: Die hohe Aufmerksamkeit, die den Wahrungskrisen in den letzten Jahren sowohl aus der Wissenschaft als auch aus der Offentlichkeit widerfahrt, kann als ein Beweis fur die grosse Bedeutung dieses Themas fur das internationale Finanzsystem gesehen werden. Auch vor dem Hintergrund der heutigen Finanzkrise sind Warnungen bezuglich der Stabilitat einiger fixierter, aber auch flexibler, Wahrungen, sowie Bemuhungen der jeweiligen Regierungen zur Verteidigung ihrer heimischen Wahrungen zu finden. Ziel dieser Seminararbeit ist es, einen Uberblick uber die Konzepte der drei Wahrungskrisenmodellgenerationen zu geben, wobei der Schwerpunkt auf den ersten beiden Generationen liegt. Im Kapitel 2 werden wichtige Wahrungskrisen seit dem Zusammenbruch des Bretton Woods Systems sowie die parallele theoretische Entwicklung der Generationen der Wahrungskrisenmodelle dargestellt. Danach wird die erste Modellgeneration im Kapitel 3 anhand des Beispiels von Flood und Garber (1984) naher beschrieben. Das Kapitel 4 widmet sich der Erlauterung der zweiten Modellgeneration mit Hilfe des Modells von Obstfeld (1996). Anschliessend wird die akademische Debatte zwischen den Vertretern der beiden Generationen uber den richtigen Erklarungsansatz im Kapitel 5 geschilde