Suchergebnis: Katalogdaten im Frühjahrssemester 2017
|Management, Technologie und Ökonomie Master|
|363-0404-00L||Industry and Competitive Analysis |
Due to didactic reasons originating from the group-work based approach, the number of participants is limited to 30. First come first served by order of enrollment in myStudies.
Experience in statistical analysis with tools such as SPSS or equivalents is an advantage.
|W||3 KP||2G||V. He|
|Kurzbeschreibung||Industry and Competitive Analysis (ICA) is a part of any strategy development. It contains a very practical set of methods to quickly obtain a good grasp of an industry. The purpose of ICA is to understand factors that impact on the financial performance of the industry, and as well the financial performance of firms within the industry.|
|Lernziel||Students develop an understanding of how the structure of industries impact on firm and industry-level performance.|
Students get familiar with, and obtain practical skills in analyzing industries and firms within them.
Students develop in-depth knowledge of one industry.
|Inhalt||Industry and competitive analysis (ICA) is a part of any strategy development in firms and other organizations. It contains a very practical set of methods to quickly obtain a good grasp of an industry, be it pharmaceuticals, information and communication technology, aluminum, or even the beer industry. The purpose of ICA is to understand factors that impact on the performance of the industry, and as well the performance of firms within the industry. Firms in an industry can be categorized in so called “strategic groups” based on the strategies they are pursuing. Each strategic group is associated with a certain level of performance, and the firms' “membership” in such groups can be used to predict their moves within the industry. Moreover, managers use ICA to allocate resources, reach strategic goals such as market share or profitability, and help their firms improve their position within the industry.|
|Literatur||Session 1: Introduction to competitive strategy|
Chapter 2 of Porter (2004)
Porter, M.E. 1996. What is strategy. Harvard Business Review. 74 (6): 61-78.
Reeves, M., Love, C., & Tillmanns, P. (2012). Your strategy needs a strategy. Harvard Business Review, 90(9), 76-83.
Session 2: Understanding industry analysis
Chapter 1 & 3 of Porter (2004)
Porter, M.E. 2008. The five competitive forces that shape strategy. Harvard Business Review. 86 (1): 78-93.
Session 3: Understanding strategic groups and firm membership
Chapter 7 of Porter (2004)
Short, J. C., David J. K., Timothy B. P., and Tomas M. H. 2007. Firm, strategic group, and industry influences on performance. Strategic Management Journal, 28: 147-167.
Harrigan, K. R. (1985). An application of clustering for strategic group analysis. Strategic Management Journal, 6(1), 55-73.
Session 4: Strategic position of the firm
Chapter 15 of Porter (2004)
Coyne, K. P., & Horn, J. (2009). Predicting your competitor's reaction. Harvard Business Review, 87(4), 90-97.
McNamara, G., Deephouse, D. L., & Luce, R. A. (2003). Competitive positioning within and across a strategic group structure: the performance of core, secondary, and solitary firms. Strategic Management Journal, 24(2), 161-181.
Session 5: Global industry and firm strategy
Chapter 13 of Porter (2004)
Makhija, M. V., Kim, K., & Williamson, S. D. (1997). Measuring globalization of industries using a national industry approach: Empirical evidence across five countries and over time. Journal of international business studies, 679-710.
Spencer, J. W. (2003). Firms' knowledge-sharing strategies in the global innovation system: empirical evidence from the flat panel display industry. Strategic Management Journal, 24(3), 217-233.
Session 6: ICA and entrepreneurial opportunities
Hitt, M. A., Ireland, R. D., Sirmon, D. G., & Trahms, C. A. (2011). Strategic entrepreneurship: creating value for individuals, organizations, and society. The Academy of Management Perspectives, 25(2), 57-75.
Alvarez, S. A., Barney, J. B., & Anderson, P. (2013). Forming and exploiting opportunities: The implications of discovery and creation processes for entrepreneurial and organizational research. Organization Science, 24(1), 301-317.
|Voraussetzungen / Besonderes||Due to didactic reasons originating from the group-work based approach, the number of participants is limited to 30. First come first served by order of enrollment in myStudies. Exchange students may register by sending an e-mail to Christian Wedl (firstname.lastname@example.org), should they face problems with registration at myStudies. Note that emails should be sent individually, no group registration is welcome. E-mails that are sent before the starting date of registration at myStudies will not be accepted.|
- There is no exam in this course. The students are graded on an industry report, and a mandatory presentation of the industry analysis to an expert panel. This presentation takes place during the last session of the course.
- Knowledge of SPSS or similar statistical packages is an advantage.
- This is an interactive class and class participation is important. Students should judge if full commitment can be made to attending the lectures before registration.
|363-0448-00L||Global Operations Strategy||W||3 KP||3G||T. Netland, R. Binkert, P. Schönsleben|
|Kurzbeschreibung||This course provides students who aim to work in globally operating companies a theoretical fundament on strategic configuration and coordination of global production networks.|
|Lernziel||This course focuses on global operations strategy. Students get familiar with designing, managing, and improving global factory networks. It covers topics such as corporate lean programs, capacity management, factory planning, network design, outsourcing, and offshoring.|
|Inhalt||This course covers factory- and network design, managing global operations, and corporate improvement programs.|
|Skript||To be announced|
|Literatur||To be announced|
|Voraussetzungen / Besonderes||Requirements: Preferably the course 363-0445-00L Production and Operations Management|
|363-0452-00L||Purchasing and Supply Management||W||3 KP||2G||S. Wagner|
|Kurzbeschreibung||Based on up to date purchasing and supplier management theories and practices, the course familiarizes students with the design and implementation of purchasing strategies, processes, structures and systems, as well as the structure and management of supplier portfolios and buyer-supplier relationships.|
|Lernziel||Students will acquire skills and tools which are valuable for designing and implementing purchasing and supplier strategies.|
|Inhalt||The value sourced from suppliers and the innovation stemming from the supply base has increased substantially in recent years. As a consequence, suppliers and the purchasing function have become critically important for firms in many manufacturing and service industries. Purchasing and supply management is on the agenda of top-management today. This course will familiarize students with modern purchasing and supplier management theory and practice. They will learn how to design and implement purchasing strategies, processes, structures and systems, and how to structure and manage supplier portfolios and buyer-supplier relationships to meet firms’ supply needs.|
|Skript||Will be available for download from the homepage of the Chair of Logistics Management (www.scm.ethz.ch).|
|Literatur||The following textbook is recommended:|
Cousins, Paul/Lamming, Richard/Lawson, Benn/Squire, Brian (2008): Strategic supply management: Principles, theories and practice, Harlow, UK: Financial Times Prentice Hall (ISBN: 0273651005).
The following textbooks are supplementary:
van Weele, Arjan J. (2014): Purchasing and supply chain management: Analysis, strategy, planning and practice, 6th ed., Andover: Cengage Learning (ISBN: 9781408088463).
Benton, W.C. (2010): Purchasing and supply chain management, 2nd ed., New York: McGraw-Hill (ISBN: 0073525146).
|Voraussetzungen / Besonderes||The final course grade will be a weighted average of the following:|
Written test: 70%
Case studies (during the semester): 30%
Class participation: Up to 10% extra credit.
|363-0514-00L||Energy Economics and Policy|
It is recommended for students to have taken a course in introductory microeconomics. If not, they should be familiar with microeconomics as in, for example,"Microeconomics" by Mankiw & Taylor and the appendices 4 and 7 of the book "Microeconomics" by Pindyck & Rubinfeld.
|W||3 KP||2G||M. Filippini|
|Kurzbeschreibung||An introduction to principles of energy economics and applications using energy policies: demand analysis, economic analysis of energy investments and cost analysis, economics of fossil fuels, economics of electricity, economics of renewable energy, market failures and energy policy, market-based and non-market based instruments, demand side management and regulation of energy industries.|
|Lernziel||The students will develop the understanding of economic principles and tools necessary to analyze energy issues and to formulate energy policy instruments. Emphasis will be put on empirical analysis of energy demand and supply, market failures, energy policy instruments, investments in power plants and in energy efficiency technologies and the reform of the electric power sector.|
|Inhalt||The course provides an introduction to energy economics principles and policy applications. The core topics are|
-Economic analysis of energy investments and cost analysis
-Economics of fossil fuels
-Economics of electricity
-Economics of renewable energies
-Market failures and energy policy
-Market oriented and non-market oriented instruments
-Demand side management
-Regulation of energy industries
|Literatur||- Joanne Evans (Editor) and Lester C. Hunt (Editor), 2009, International Handbook on the Economics of Energy, Edward Elgar Publishing.|
- Bhattacharyya, Subhes C., Energy Economics, 2011, Energy Economics Concepts, Issues, Markets and Governance, 1st Edition, Springer.
|Voraussetzungen / Besonderes||It is recommended for students to have taken a course in introductory microeconomics. If not, they should be familiar with microeconomics as in, for example, "Microeconomics" by Mankiw & Taylor and the appendices 4 and 7 of the book "Microeconomics" by Pindyck & Rubinfeld.|
|363-0543-00L||Agent-Based Modelling of Social Systems |
Findet dieses Semester nicht statt.
|W||3 KP||2V + 1U||F. Schweitzer|
|Kurzbeschreibung||Agent-based modelling is introduced as a bottom-up approach to understand the dynamics of complex social systems. The course focuses on agents as the fundamental constituents of a system and their theoretical formalisation and on quantitative analysis of a wide range of social phenomena-cooperation and competition, opinion dynamics, spatial interactions and behaviour in online social networks.|
|Lernziel||A successful participant of this course is able to|
- understand the rationale of agent-centered models of social systems
- understand the relation between rules implemented at the individual level and the emerging behaviour at the global level
- learn to choose appropriate model classes to characterise different social systems
- grasp the influence of agent heterogeneity on the model output
- efficiently implement agent-based models using Python and visualise the output
|Inhalt||Agent-based modelling (ABM) provides a bottom-up approach to understand the complex dynamics of social systems. In ABM, agents are the basic constituents of any social system. Depending on the granularity of the analysis, an agent could represent a single individual, a household, a firm, a country, etc. Agents have internal states or degrees of freedom opinions, strategies, etc.), the ability to perceive and change their environment, and the ability to interact with other agents. Their individual (microscopic) actions and interactions with other agents, result in macroscopic (collective, system) dynamics with emergent properties. As more and more accurate individual-level data about online and offline social systems become available, our formal, quantitative understanding of the collective dynamics of these systems needs to progress in the same manner. |
We focus on a minimalistic description of the agents' behaviour which relates individual interaction rules to the dynamics on the collective level and complements engineering and machine learning approaches.
The course is structured in three main parts. The first two parts introduce two main agent concepts - Boolean agents and Brownian agents, which differ in how the internal dynamics of agents is represented. Boolean agents are characterized by binary internal states, e.g. yes/no opinion, while Brownian agents can have a continuous spectrum of internal states, e.g. preferences and attitudes. The last part introduces models in which agents interact in physical space, e.g. migrate or move collectively.
Throughout the course, we will discuss a wide variety of application areas, such as:
- opinion dynamics and social influence,
- cooperation and competition,
- online social networks,
- systemic risk
- emotional influence and communication
- swarming behavior
- spatial competition
While the lectures focus on the theoretical foundations of agent-based modelling, weekly exercise classes provide practical skills. Using the Python programming language, the participants implement agent-based models in guided and autonomous projects, which they present and jointly discuss.
|Skript||The lecture slides will be available on the Moodle platform, for registered students only.|
|Literatur||See handouts. Specific literature is provided for download, for registered students only.|
|Voraussetzungen / Besonderes||Participants of the course should have some background in mathematics and an interest in formal modelling and computer simulations, and should be motivated to learn about social systems from a quantitative perspective.|
Prior knowledge of Python is not necessary.
Self-study tasks are provided as home work for small teams (2-4 members).
Weekly exercises (45 min) are used to discuss the solutions and guide the student.
During the second half of the semester, teams need to complete a course project in which they will implement and discuss an agent-based model to characterise a system chosen jointly with the course organisers. This project will be evaluated, and its grade will count as 25% of the final grade.
|363-0552-00L||Economic Growth and Resource Use||W||3 KP||2G||A. Schäfer|
|Kurzbeschreibung||The lecture focuses on the economics of non-renewable resources and deals with the main economic issues regarding such commodities.|
|Lernziel||The objective of the lecture is to make students familiar with the main topics in the economics of non-renewable natural resources so that they become able to autonomously read much of the academic literature on the issue. The economics of natural resources adds an intertemporal dimension to the classical static theory. The analyses provided in the lecture will use basic dynamic optimization tools; students are also expected to develop or consolidate their related technical skills.|
|Inhalt||The lecture focuses on the economics of non-renewable resources and deals with the main economic issues regarding such commodities. Two peculiarities of natural resources make them interesting economic objects. The intertemporal dimension of resource exploitation is absent in standard static treatments of classical economic theory. The non-renewability of natural resources further implies long-term supply limitations, unlike conventional goods that are indefinitely reproducible. Because of those peculiarities, many well-known economic results do not apply to the case of resources.|
As it is appropriate in most chapters, priority will be given to a synthetic partial equilibrium setting. Elementary knowledge of microeconomics (like what is provided by H. Varian, Intermediate Microeconomics) is considered as a prerequisite. Moreover, an introduction to standard partial equilibrium analysis will be provided at the beginning of the lecture. General equilibrium effects should be introduced as they become crucial, as will be the case in the chapters on the interplay between economic growth and resource depletion.
The questions addressed in the lecture will be the following ones:
The intertemporal theory of non-renewable resource supply; the dynamic market equilibrium allocation; the exploration and development of exploitable reserves; the heterogenous quality of resource deposits; pollution and other externalities arising from the use of fossil fuels; the exercise of market power by resource suppliers and market structures; socially optimum extraction patterns and sustainability; the taxation of non-renewable resources; the international strategic dimension of resource taxation; the uncertainty about future reserves and market conditions; economic growth, resource limitations, and the innovation process...
|Skript||Lecture Notes of the course will be sent by email to officially subscribed students.|
|Literatur||The main reference of the course is the set of lecture notes; students will also be encouraged to read some influential academic articles dealing with the issues under study.|
|Voraussetzungen / Besonderes||Elementary knowledge of microeconomics (like what is provided by H. Varian, Intermediate Microeconomics) is considered as a prerequisite.|
|363-0558-00L||Strategic and Cooperative Thinking|
Vorgängiger Besuch der Lerneinheit 363-0503-00L Principles of Microeconomics wird empfohlen.
|W||3 KP||2G||O. Tejada Pinyol|
|Kurzbeschreibung||Noncooperative and Cooperative Game Theory, concepts and applications|
|Lernziel||The goal of the lecture is to learn how to think strategically or cooperatively and to apply the concepts |
of game theory to economic, social, political and business situations.
|Inhalt||Part 1: Strategic Thinking (Noncooperative Game Theory)|
Thinking in static and dynamic games with complete and incomplete information
Part 2: Cooperative Thinking (Cooperative Game Theory)
Thinking in repeated and cooperative games.
|Skript||For inquiries and questions regarding the course organization please send an email to Dr. Oriol Tejada (email@example.com).|
|Literatur||Davis (1997): Game Theory: A Nontechnical Introduction. Courier Dover Publications|
Dixit and Nalebuff (1991): Thinking Strategically. W.W. Norton & Company
Fudenberg and Tirole (1991): Game Theory. MIT Press
Gibbons (1992): Game Theory for applied economists. Princeton University Press
Mas-Collel et al. (1995): Microeconomic Theory. Oxford University Press
Myerson (1992): Game Theory: Analysis of Conflict. Havard University Press
Osborne (2003): An Introduction to Game Theory. Oxford University Press
Watson (2002): Strategy: An Introduction in Game Theory. W.W. Norton & Company
|Voraussetzungen / Besonderes||The lecture will be in English.|
|363-0564-00L||Entrepreneurial Risks||W||3 KP||2G||D. Sornette|
|Kurzbeschreibung||-General introduction to the different dimensions of risks with|
emphasis on entrepreneurial, financial and social risks.
-Development of the concepts and tools to understand these risks,
control and master them.
-Decision making and risks; human cooperation and risks
|Lernziel||We live a in complex world with many nonlinear|
negative and positive feedbacks. Entrepreneurship is one of
the leading human activity based on innovation to create
new wealth and new social developments. This course will
analyze the risks (upside and downside) associated with
entrepreneurship and more generally human activity
in the firms, in social networks and in society.
The goal is to present what we believe are the key concepts
and the quantitative tools to understand and manage risks.
An emphasis will be on large and extreme risks, known
to control many systems, and which require novel ways
of thinking and of managing. We will examine the questions
of (i) how much one can manage and control these risks,
(ii) how these actions may feedback positively or negatively
and (iii) how to foster human cooperation for the creation
of wealth and social well-being.
Depending on the number of students and of the interest, the exam
will consist in a project, one for each student or in small groups,
focused on the application of the concepts and tools developed in this
class to problems of practical use to the students in their varied fields.
The choice of the subjects will be jointly decided by the
students and the professor.
|Inhalt||This content is not final and is subjected to change|
and adaptation during the development of the course
in order to take into account feedbacks from the
students and participants to the course.
1- Risks in the firm and in entrepreneurship
-What is risk? The four levels.
-Conceptual and technical tools
-Introduction to three different concepts of probability
-Useful notions of probability theory
(Frequentist versus Bayesian approach,
the central limit theorem and its generalizations, extreme value theory)
-Where are the risks for firms? Downside and upside
-Diversification and market risks
2-The world of power law risks
-power laws and beyond
-scale invariance, fractal and multifractals
-mechanisms for power laws
-Examples in the corporate, financial and social worlds
3-Risks emerging from collective self-organization
-concept of bottom-up self-organization
-bifurcations, theory of catastrophes, phase transitions
-the hierarchical approach to understanding self-organization
4-Measures of risks
-coherent and consistent measures of risks
-origin of risks
-dependence structure of risks
-measures of dependence and of extreme dependences
-introduction to copulas
5-Conceptual and mathematical models of risk processes
-self-excited point processes of economic and financial shocks
-agent-based models applied to collective emergent behavior
in organization of firms and societies and their risks
6-Endogenous versus exogenous origins of crises
-mild crises versus wild catastrophes: black swans and kings
-the dynamics of commercial sales
-the dynamics of Youtube views and internet downloads
-the dynamics of risks in the financial markets
-strategic management and extreme risks
7-Why do markets burst and crash?
-collective behavior, imitation and herding
-humans as social animals and consequence of risks
-bubbles and crashes in human affairs, innovation, new technologies
8-Limits of predictability, of control and of management
-the phenomenon of ``illusion of control''
-the world is a whole: irreducible risks from lack of diversification
-intrinsic limits of predictability
-the concept of pockets of predictability
-political, financial, economics, natural risks
-elements on theories of decision making
-Human cooperation and its lack thereof, mechanisms and design
|Skript||The lecture notes will be distributed a the beginning of |
|Literatur||I will use elements taken from my books |
Critical Phenomena in Natural Sciences,
Chaos, Fractals, Self-organization and Disorder: Concepts and Tools,
2nd ed. (Springer Series in Synergetics, Heidelberg, 2004)
-Y. Malevergne and D. Sornette
Extreme Financial Risks (From Dependence to Risk Management)
(Springer, Heidelberg, 2006).
Why Stock Markets Crash
(Critical Events in Complex Financial Systems),
(Princeton University Press, 2003)
as well as from a variety of other sources, which will be
indicated to the students during each lecture.
|Voraussetzungen / Besonderes||-A deep curiosity and interest in asking questions and in attempting to |
understand and manage the complexity of the corporate, financial
and social world
-quantitative skills in mathematical analysis and algebra
for the modeling part.
|363-0584-00L||International Monetary Economics||W||3 KP||2V||J.‑E. Sturm, J. Kingeski Galimberti|
|Kurzbeschreibung||What determines the foreign exchange rate in the short- and long-term? What are the effects of monetary and fiscal policy in an open economy? What drives a country's choice of the foreign exchange rate regime and why are some countries more prone to financial crises than others? A number of simple theoretical frameworks will be developed that allow us to discuss recent economic policy issues.|
|Lernziel||The core objective of the course is to develop simple macroeconomic models of open economies that can be usefully applied to international economic phenomena ranging from global financial imbalances, the Chinese exchange rate regime, the European Monetary Union, reform proposals for the international financial architecture, to global financial crises.|
|Skript||Lecture notes will be made available via Moodle.|
|Literatur||Krugman, Paul, Maurice Obstfeld and Marc Melitz (2014), International Economics, Theory and Policy, 10th Global Edition, Pearson Addison Wesley.|
|363-0586-00L||International Economics: Theory of New Trade and Multinational Firms||W||3 KP||2V||P. Egger, B. M. M. Zoller-Rydzek|
|Kurzbeschreibung||The primary goal of the course is to familiarize students with recent work in international economics.|
|Lernziel||The primary goal of the course is to familiarize students with recent work in international economics. While traditional text books are largely concerned with models where production cost differences between countries (through differences in factor productivity or in relative factor endowments) are the main source of gains from trade, I will assume that students are familiar with these concepts and only briefly touch on them. The focus will be on models where the main reason for trade are consumer preferences and their love of variety and its major impediments are transport costs. Covering models of trade only, of trade and multinational firms, and of factor mobility and agglomeration, students will get a good overview of key contributions in international economics within the last quarter of a century.|
|Literatur||Copies of the original articles and relevant chapters of books will be made available to participants of the course.|
|363-0588-00L||Complex Networks||W||4 KP||2V + 1U||I. Scholtes|
|Kurzbeschreibung||The course provides an overview of the methods and abstractions used in (i) the quantitative study of complex networks, (ii) empirical network analysis, (iii) the study of dynamical processes in networked systems, (iv) the analysis of robustness of networked systems, (v) the study of network evolution, and (vi) data mining techniques for networked data sets.|
|Lernziel||* the network approach to complex systems, where actors are represented as nodes and interactions are represented as links|
* learn about structural properties of classes of networks
* learn about feedback mechanism in the formation of networks
* learn about statistical inference and data mining techniques for data on networked systems
* learn methods and abstractions used in the growing literature on complex networks
|Inhalt||Networks matter! This holds for social and economic systems, for technical infrastructures as well as for information systems. Increasingly, these networked systems are outside the control of a centralized authority but rather evolve in a distributed and self-organized way. How can we understand their evolution and what are the local processes that shape their global features? How does their topology influence dynamical processes like diffusion? And how can we characterize the importance of specific nodes? |
This course provides a systematic answer to such questions, by developing methods and tools which can be applied to networks in diverse areas like infrastructure, communication, information systems, biology or (online) social networks. In a network approach, agents in such systems (like e.g. humans, computers, documents, power plants, biological or financial entities) are represented as nodes, whereas their interactions are represented as links.
The first part of the course, "Introduction to networks: basic and advanced metrics", describes how networks can be represented mathematically and how the properties of their link structures can be quantified empirically.
In a second part "Stochastic Models of Complex Networks" we address how analytical statements about crucial properties like connectedness or robustness can be made based on simple macroscopic stochastic models without knowing the details of a topology.
In the third part we address "Dynamical processes on complex networks". We show how a simple model for a random walk in networks can give insights into the authority of nodes, the efficiency of diffusion processes as well as the existence of community structures.
A fourth part "Network Optimisation and Inference" introduces models for the emergence of complex topological features which are due to stochastic optimization processes, as well as statistical methods to detect patterns in large data sets on networks.
In a fifth part, we address "Network Dynamics", introducing models for the emergence of complex features that are due to (i) feedback phenomena in simple network growth processes or (iii) order correlations in systems with highly dynamic links.
A final part "Research Trends" introduces recent research on the application of data mining and machine learning techniques to relational data.
|Skript||The lecture slides are provided as handouts - including notes and literature sources - to registered students only. |
All material is to be found on Moodle at the following URL: https://moodle-app2.let.ethz.ch/course/view.php?id=2678
|Literatur||See handouts. Specific literature is provided for download - for registered students, only.|
|Voraussetzungen / Besonderes||There are no pre-requisites for this course. Self-study tasks (to be solved analytically and by means of computer simulations) are provided as home work. Weekly exercises (45 min) are used to discuss selected solutions. Active participation in the exercises is strongly suggested for a successful completion of the final exam.|
|363-0792-00L||Knowledge Management||W||1 KP||2G||P. Wolf|
|Kurzbeschreibung||The course introduces theoretical concepts of Knowledge Management from the perspective of two different social sciences: Organization Studies/Management and Sociology. Common Knowledge Management approaches, methods and tools will be presented, and the participants will have the opportunity to test some of them.|
|Lernziel||The efficient management of knowledge as a resource of an organization is considered to be a major source of competitive advantage. The course aims at |
- introducing participants to the most common knowledge management theories,
- raising their awareness on opportunities and barriers to attempts of managing knowledge in organizations
- drawing a realistic picture of what can be achieved by managers in the frame of knowledge management initatives by what means and approaches.
|Inhalt||The course is building on a systemic-constructionist perspective of knowledge. From this perspective, knowledge is understood as co-constructed by people in interactions. Such a theoretic perspective looks at systemic (organizational) structures and the interplay between individuals and these structures in processes of knowledge generation and transformation. |
Next to an introduction into knowledge management theories, the course will also present participants with knowledge management approaches and tools.
|Skript||None. Participants will be provided with slides before the course.|
|Literatur||Relevant literature (3-5 articles) will be send to the students at least four weeks before the course.|
|Voraussetzungen / Besonderes||There will be a term work assignment - reports to be handed in in the second half of May. Students will work on an own KM case study.|
|363-0887-00L||Management Research |
Participation to both sessions are mandatory to receive the credit, there will be no exceptions.
If a student can't take part in one of the sessions, the course has to be taken the following semester.
The course is mandatory for MSc. students and recommended for MAS students who write their Master Thesis at the Chair of Strategic Management and Innovation.
|W||1 KP||1S||N. Geilinger|
|Kurzbeschreibung||This course teaches students about the basic principles of scientific work in the field of social sciences.|
|Lernziel||This course teaches students about the basic principles of scientific work in the field of social sciences.|
|Inhalt||This course teaches students about the basic principles of scientific work in the field of social sciences. It is an introduction into the fascinating field of research. The course shows the power of theory and literature, helps formulating intriguing research questions, provides an overview of scientific methods and data analysis, and gives hints on how to derive insightful conclusions out of results. The goal is to motivate students to find and read research papers relevant to their field, develop an own thesis design and write scientific articles.|
|Voraussetzungen / Besonderes||· The course is mandatory for MSc students and recommended for MAS students who write their thesis at the Chair of Strategic Management and Innovation (SMI). |
· The course is given once every semester and takes place during two separate days. Attendance on both days is required to successfully complete the course.
Findet dieses Semester nicht statt.
|W||3 KP||2V||A. Bommier|
|Kurzbeschreibung||This is a theoretical course on the economics of financial decision making, at the crossroads between Microeconomics and Finance. It discusses portfolio choice theory, risk sharing, market equilibrium and asset pricing.|
|Lernziel||The objective is to make students familiar with the economics of financial decision making and develop their intuition regarding the determination of asset prices, the notions of optimal risk sharing. However this is not a practical formation for traders. Moreover, the lecture doesn't cover topics such as market irrationality or systemic risk.|
|Inhalt||The following topics will be discussed:|
Introduction to finance and investment planning; Option valuation; Arbitrage; Choice under uncertainty; Portfolio Choice; Risk sharing and insurance; Market equilibrium under symmetric information.
|Literatur||Suggesting readings: |
1) "Investments", by Z. Bodie, A. Kane and A. Marcus, for the
introductory part of the course (see chapters 20 and 21 in
2) "Finance and the Economics of Uncertainty" by G. Demange and G. Laroque, Blackwell, 2006.
3) "The Economics of Risk and Time", by C. Gollier, and
- "Intermediate Financial Theory" by J.-P. Danthine and J.B. Donaldson.
- Ingersoll, J., E., Theory of Financial Decision Making, Rowman and Littlefield Publishers.
- Leroy S and J. Werner, Principles of Financial Economics, Cambridge University Press, 2001
|Voraussetzungen / Besonderes||Basic mathematical skills needed (calculus, linear algebra, convex analysis). Students must be able to solve simple optimization problems (e.g. Lagrangian methods). Some knowledge in microeconomics would help but is not compulsory. The bases will be covered in class.|
|363-1017-00L||Risk and Insurance Economics||W||4 KP||3V||W. Mimra|
|Kurzbeschreibung||The course covers economics of risk and insurance. Topics covered are fundamentals of insurance, risk measures and risk management, demand and supply of insurance and asymmetric information in insurance markets.|
|Lernziel||The goal is to introduce students to basic concepts of risk, risk management and economics of insurance.|
|Inhalt||- fundamentals of insurance|
- what is the rationale for corporate risk management?
- measures of risk and methods of risk management
- demand for insurance
- supply of insurance
- information problems in insurance markets: moral hazard, adverse selection, fraud
|Literatur||- Peter Zweifel and Roland Eisen (2012), Insurance Economics, Springer. |
- S. Hun Seog (2010), The Economics of Risk and Insurance, Wiley-Blackwell.
- Ray Rees and Achim Wambach (2008), The Microeconomics of Insurance, Foundations and Trends in Microeconomics: Vol. 4: No 1-2.
- Eeckhoudt/Gollier/Schlesinger (2007), Economic and Financial Decisions under Risk, Princeton University Press.
- introductory background reading: Harrington/Niehaus (2003), Risk Management and Insurance, McGraw Hill.
|363-1031-00L||Quantitative Methods in Energy and Environmental Economics||W||4 KP||3G||S. Rausch, A. L. Martinez Cruz|
|Kurzbeschreibung||The course provides an introduction to quantitative methods used to analyze problems in energy and environmental economics. Emphasis will be put on partial equilibrium models, static and dynamic general equilibrium models, climate economic models and integrated assessment models, regression models to estimate demand functions, econometric techniques for policy evaluations, and panel data methods.|
|Lernziel||The objectives of the course are twofold. First, the course is intended to provide an introduction to the economic assessment of energy and environmental policy. To this end, the course provides students with an overview of state-of-the-art tools to economic modeling and econometric approaches. Second, the course is intended to familiarize master (and doctoral students) with the computer software necessary to implement these quantitative methods to initiate their own research in energy and environmental economics. |
Ancillary objectives of the course include an introduction to environmental implications of energy use and the role of economic analysis in designing policies which address issues of energy security, climate change and related environmental externalities.
|Literatur||Lecture notes, exercises and reference material will be made available to students during the semester.|
|Voraussetzungen / Besonderes||Basic knowledge of microeconomics and calculus. Knowledge from the course Energy Economics and Policy (363-0514-00L) is helpful but not required.|
|363-1060-00L||Strategies for Sustainable Business |
Limited number of participants
Registration will only be effective once confirmed by email from the organizers.
|W||2 KP||2S||A. Brophy, J. Hoppmann, J. Meuer|
|Kurzbeschreibung||In this course, students will learn to critique strategies for sustainable business through exploring case studies on three main questions: 1. What is sustainability in business? 2. How do I design a sustainability strategy? 3. How do I implement a sustainability strategy?|
|Lernziel||After the course, students should be able to:|
Understand and explain sustainability challenges facing companies;
Critique sustainability and related strategies;
Evaluate decisions taken by managers;
Suggest alternative approaches;
Develop action plans;
Critique and reflect on strategies for sustainability in their own organisations.
Students will also learn to apply a range of strategy concepts to sustainability challenges, including reputation, leadership, organisational change and culture.
|Inhalt||Although many companies now report on their sustainability actions, few successfully integrate sustainability into their business operations. In this seminar, we will cover three main questions that will help students to critique and to develop strategies for sustainable business: |
1. What is sustainability in business?
2. How do I design a sustainability strategy?
3. How do I implement a sustainability strategy?
The course will be taught using case studies. The case studies will allow us to explore from multiple perspectives the many tensions involved in developing strategies for sustainable business. Case study materials will be distributed before the sessions, as well as guidelines on how best to efficiently and effectively prepare for case study discussions. Students will be required to read the materials and to submit short assignments before each class. The sessions will be interactive and will include large and small group discussions.
For each of the three guiding questions, we will explore sustainability problems faced by a range of different companies. For example, we will look at the challenges Fairphone faces in combining both social and economic goals. We step into the shoes of RWE's CEO Peter Terium as he grapples with ensuring a profitable and sustainable future for the German utility. And we try to encourage as many of our colleagues as possible to adopt a sustainability initiative using a change management simulation.
Our case discussions will help each of you to apply strategy concepts to real-world sustainability problems and will also serve as a basis for thinking about sustainability in your own organisations.
|Literatur||Case study materials and guidelines for analysing cases will be provided to participants by email several weeks before the seminar.|
|363-1091-00L||Social Data Science||W||3 KP||2V + 1U||D. Garcia Becerra|
|Kurzbeschreibung||Social Data Science is introduced as a set of techniques to analyze human behavior and social interaction through digital traces.|
The course focuses both on the fundamentals and applications of Data Science in the Social Sciences, including technologies for data retrieval, processing, and analysis with the aim to derive insights that are interpretable from a wider theoretical perspective.
|Lernziel||A successful participant of this course is able to|
- understand a wide variety of techniques to retrieve digital trace data from online data sources
- store, process, and summarize online data for quantitative analysis
- perform statistical analyses to test hypotheses, derive insights, and formulate predictions
- implement streamlined software that integrates data retrieval, processing, statistical analysis, and visualization
- interpret the results of data analysis with respect to theoretical and testable principles of human behavior
- understand the limitations of observational data analysis with respect to data volume, statistical power, and external validity
|Inhalt||Social Data Science (SDS) provides a broad approach to the quantitative analysis of human behavior through digital trace data.|
SDS integrates the implementation of data retrieval and processing, the application of statistical analysis methods, and the interpretation of results to derive insights of human behavior at high resolutions and large scales.
The motivation of SDS stems from theories in the Social Sciences, which are addressed with respect to societal phenomena and formulated as principles that can be tested against empirical data.
Data retrieval in SDS is performed in an automated manner, accessing online databases and programming interfaces that capture the digital traces of human behavior.
Data processing is computerized with calibrated methods that quantify human behavior, for example constructing social networks or measuring emotional expression.
These quantities are used in statistical analyses to both test hypotheses and explore new aspects on human behavior.
The course is structured in three main parts. First, collective behavior is analyzed with respect to time trends, distributions, and information sharing. The second part focuses on the processing and analysis of text, applying and validating sentiment analysis methods. The third part covers empirical social network analysis based on online social network data, covering both topological and dynamic aspects of social networks.
The course will cover various examples of the application of SDS:
- Search trends to measure information seeking
- Popularity signals and social influence
- Microblogging data to measure mood
- Digital markets and cryptocurrencies
- Sentiment analysis across various online media
- Twitter network analysis
The lectures include theoretical foundations of the application of digital trace data in the Social Sciences, as well as practical examples of data retrieval, processing, and analysis cases in the R statistical language from a literate programming perspective. Weekly exercise classes provide practical skills and discuss the solutions to exercises that build on the concepts and methods presented in the previous lectures.
|Skript||The lecture slides will be available on the Moodle platform, for registered students only.|
|Literatur||See handouts. Specific literature is provided for download, for registered students only.|
|Voraussetzungen / Besonderes||Participants of the course should have some basic background in statistics and programming, and an interest to learn about human behavior from a quantitative perspective.|
Prior knowledge of R, information retrieval, or information systems is not necessary.
Self-study tasks are provided as home work and build on technical and theoretical content explained in the lectures.
Weekly exercises (45 min) are used to discuss the solutions and guide the student.
- Seite 1 von 1