Search result: Catalogue data in Autumn Semester 2017
Agroecosystem Sciences Master  | ||||||
 Master Studies (Programme Regulations 2011) | ||||||
| Majors | ||||||
| Major in Food and Resource Use Economics | ||||||
| Disciplinary Competences | ||||||
| Decision Making in Food Value Chains | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|---|
| 752-2122-00L | Food and Consumer Behaviour | W+ | 2 credits | 2V | M. Siegrist, C. Hartmann | |
| Abstract | This course focuses on food consumer behavior, consumer's decision-making processes and consumer's attitudes towards food products. | |||||
| Learning objective | The course provides an overview about the following topics: Factors influencing consumer's food choice, food and health, attitudes towards new foods and food technologies, labeling and food policy issues | |||||
| 751-2205-00L | Advanced Management in the Agri-Food-Chain | W+ | 2 credits | 2G | M. Weber | |
| Abstract | Advanced Management in the Agri-Food-Chain (Vorlesung wird in deutscher Sprache abgehalten.) | |||||
| Learning objective | After the lecture the students ... ... know the characteristics and consequences of complexity in the organizational world, ... know and can apply selected comprehensive models for managing in complex situations, ... know possible practical applications and examples of the treated contents to organizations in the Agri-Food Chain and ... are able to deepen the relevant topics in an autonomous way. | |||||
| Content | In the lecture the following contents will be treated: - State, reasons and effects of complexity in the organizational world. - A basic framework for shaping and governing intelligent organizations. - Selected contemporary models for managing in the complex organizational world. - Transfer and adaption of the models to organizations in the Agri-Food Chain. | |||||
| Lecture notes | Reader with selected contents. | |||||
| Prerequisites / Notice | - Vorlesung "Management in the Agri-Food Chain" in D-USYS | |||||
| 363-0403-00L | Introduction to Marketing | W+ | 3 credits | 2G | F. von Wangenheim | |
| Abstract | The course is designed to convey a profound understanding of marketing's role in modern firms, its interactions and interfaces with other disciplines, its main instruments and recent trends. Particular attention is given to emerging marketing concepts and instruments, and the role of marketing in technology firms. | |||||
| Learning objective | After taking the lecture, students should have knowledge about 1) The definition and role of marketing (marketing basics) 2) Creating marketing insights - understanding customer behavior - Theoretical concepts in customer behavior (customer behavior) - Analytical means to extend knowledge on customer behavior (marketing research) - Strategic tools to quantify customer behavior (CLV, CE) 3) Strategic marketing - translating marketing insights into actionable marketing strategies - Segmentation, Targeting, and Positioning - Attracting customers (marketing mix, 4Ps) - Maintaining profitable customer relations (CRM) | |||||
| Content | The course is designed to convey a profound understanding of marketing's role in modern firms, its interactions and interfaces with other disciplines, its main instruments and recent trends. Particular attention is given to emerging marketing concepts and instruments, and the role of marketing in technology firms. The lecture features tutorial sessions that are held at irregularly spaced intervals throughout the semester (approximately every third week). The tutorial sessions take place at the same time and location as the main lecture. It serves to illustrate theoretical and methodological concepts from the lecture by walking students through the analysis of real-world data from the telecommunications industry. The case data will be provided so that students practice and apply the concepts of the lecture on their own. The tutorial is held jointly by two Teaching Assistants (Zhiying Cui and Jana Gross) and the professor (Prof. F. von Wangenheim). | |||||
| Literature | Kotler, P./Armstrong, G.: Principles of Marketing, 17th edition, Pearson 2017. Weekly readings, distributed in class (via Moodle) | |||||
| Environmental and Resource Use Economics | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
| 701-1651-00L | Environmental Governance  Number of participants limited to 30. | W+ | 3 credits | 2G | E. Lieberherr, G. de Buren, R. Schweizer | |
| Abstract | The course addresses environmental policies, focusing on new steering approaches, which are generally summarized as environmental governance. The course also provides students with tools to analyze environmental policy processes and assesses the key features of environmental governance by examining various practical environmental policy examples. | |||||
| Learning objective | To understand how an environmental problem may (not) become a policy and explain political processes, using basic concepts and techniques from political science. To analyze the evolution as well as the key elements of environmental governance. To be able to identify the main challenges and opportunities for environmental governance and to critically discuss them with reference to various practical policy examples. | |||||
| Content | Improvements in environmental quality and sustainable management of natural resources cannot be achieved through technical solutions alone. The quality of the environment and the achievement of sustainable development strongly depend on human behavior and specifically the human uses of nature. To influence human behavior, we rely on public policies and other societal rules, which aim to steer the way humans use natural resources and their effects on the environment. Such steering can take place through government intervention alone. However, this often also involves governance, which includes the interplay between governmental and non-governmental actors, the use of diverse tools such as emission standards or financial incentives to steer actors' behavior and can occur at the local, regional, national or international level. In this course, we will address both the practical aspects of as well as the scientific debate on environmental governance. The course gives future environmental experts a strong basis to position themselves in the governance debate, which does not preclude government but rather involves a spectrum from government to governance. Key questions that this course seeks to answer: What are the core characteristics of environmental challenges from a policy perspective? What are key elements of 'environmental governance' and how legitimate and effective are these approaches in addressing persistent environmental challenges? | |||||
| Lecture notes | Lecture slides and additional course material will be provided on Moodle. | |||||
| Literature | We will mostly work with readings from the following books: - Carter, N. (2007). The politics of the environment: Ideas, activism, policy (2nd ed.). Cambridge: Cambridge University Press. - Hogl, K., Kvarda, E., Nordbeck, R., Pregernig, M. (Eds) (2012): Environmental Governance: The Challenge of Legitimacy and Effectiveness. Cheltenham: Edward Elgar Publishing Limited. | |||||
| Prerequisites / Notice | A detailed course schedule will be made available at the beginning of the semester. During the lecture we will work with Moodle. We ask that all students register themselves on this platform before the lecture and to bring a laptop, tablet or smartphone to class, so that you can complete exercises using Moodle. We recommend that students have (a) three-years BSc education of a (technical) university; (b) successfully completed Bachelor introductory course to environmental policy (Entwicklungen nationaler Umweltpolitik (or equivalent)) and (c) familiarity with key issues in environmental policy and some fundamental knowledge of one social science or humanities discipline (political science, economics, sociology, history, psychology, philosophy) | |||||
| 751-2103-00L | Socioeconomics of Agriculture | W+ | 2 credits | 2V | S. Mann | |
| Abstract | The main part of this lecture will examine constellations where hierarchies, markets or cooperation have been observed and described in the agricultural sector. On a more aggregated level, different agricultural systems will be evaluated in terms of main socioeconomic parameters like social capital or perceptions. | |||||
| Learning objective | Students should be able to describe the dynamics of hierarchies, markets and cooperation in an agricultural context. | |||||
| Content | Introduction to Sociology Introduction to Socioeconomics Agricultural Administration: Path dependencies and efficiency issues Power in the Chain The farming family Occupational Choices Consumption Choices Locational Choices Common Resource Management in Alpine Farming Agricultural Cooperatives Societal perceptions of agriculture Perceptions of farming from within Varieties of agricultural systems and policies | |||||
| Lecture notes | Link | |||||
| Literature | see script | |||||
| Prerequisites / Notice | Basic economic knowledge is expected. | |||||
| 860-0023-00L | International Environmental Politics Particularly suitable for students of D-ITET, D-USYS | W | 3 credits | 2V | T. Bernauer | |
| Abstract | This course focuses on the conditions under which cooperation in international environmental politics emerges and the conditions under which such cooperation and the respective public policies are effective and/or efficient. | |||||
| Learning objective | The objectives of this course are to (1) gain an overview of relevant questions in the area of international environmental politics from a social sciences viewpoint; (2) learn how to identify interesting/innovative questions concerning this policy area and how to answer them in a methodologically sophisticated way; (3) gain an overview of important global and regional environmental problems. | |||||
| Content | This course deals with how and why international cooperation in environmental politics emerges, and under what circumstances such cooperation is effective and efficient. Based on theories of international political economy and theories of government regulation various examples of international environmental politics are discussed: the management of international water resources, the problem of unsafe nuclear power plants in eastern Europe, political responses to global warming, the protection of the stratospheric ozone layer, the reduction of long-range transboundary air pollution in Europe, the prevention of pollution of the oceans, etc. The course is open to all ETH students. Participation does not require previous coursework in the social sciences. After passing an end-of-semester test (requirement: grade 4.0 or higher) students will receive 3 ECTS credit points. The workload is around 90 hours (meetings, reading assignments, preparation of test). Visiting students (e.g., from the University of Zurich) are subject to the same conditions. Registration of visiting students in the web-based system of ETH is compulsory. | |||||
| Lecture notes | Assigned reading materials and slides will be available at http://www.ib.ethz.ch/teaching.html (select link 'Registered students, please click here for course materials' at top of that page). Log in with your nethz name and password. Questions concerning access to course materials can be addressed to Dennis Atzenhofer at dennis.atzenhofer@ir.gess.ethz.ch). All assigned papers must be read ahead of the respective meeting. Following the course on the basis of on-line slides and papers alone is not sufficient. Physical presence in the classroom is essential. Many books and journals covering international environmental policy issues can be found at the D-GESS library at the IFW building, Haldeneggsteig 4, B-floor, or in the library of D-USYS. | |||||
| Literature | Assigned reading materials and slides will be available at http://www.ib.ethz.ch/teaching.html (select link -Registered students, please click here for course materials- at top of that page). Log in with your nethz name and password. Questions concerning access to course materials can be addressed to dennis.atzenhofer@ir.gess.ethz.ch). | |||||
| Prerequisites / Notice | None | |||||
| Agricultural Trade and Policies | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
| 751-2903-00L | Evaluation of Agricultural Policies | W+ | 3 credits | 2G | M. Stolze, S. Mann | |
| Abstract | The course focuses on agricultural eeconomic research with particular focus on policy evaluation. We impart insights in the issue of policy evaluation as part of agricultural economics research. | |||||
| Learning objective | Focus: Policy Evaluation ------------------------------------------- The students are to... - have a critical look at different angles of agri-economic research - study scientific literature of the focus theme - consider strengths, weaknesses and the application of research approaches - apply knowledge gained from other courses with respect to the focus theme - get insights in agricultural economic research of the national research institutions by visiting Agroscope and the Research Institute of Organic Agriculture (FiBL) - be capable to conduct evaluations and critically reflect evaluation results | |||||
| Content | Unit: Subject ---------------------------------------------------------------------- 01: Introduction 02: The normative frame for policy evaluation 03: Excursion to Frick 04: Public Politics for Evaluation 05: Application of Evaluations 06: Quantitive Methods 07: Excursion to Tänikon 08: Qualitative Methods 09: Case Study 10: Examination | |||||
| Lecture notes | Handouts (power point presentations) | |||||
| Literature | 1) Bussmann Werner, Klöti Ulrich und Knoepfel Peter, 2004 (Hrsg). Einführung in die Politikevaluation. Helbling&Lichtenhahn. In German language. Will be privided by the lectures in unit 01. 2) Vedung Evert, 2000. Public Policy and Program Evaluation. ISBN 0-7658-0687-8. | |||||
| Prerequisites / Notice | Unit 03: 1 day course at FiBL in 5070 Frick, www.fibl.org Unit 09: 1 day course at Agroscope in Tänikon, 8356 Ettenhausen, www.agroscope.admin.ch | |||||
| 851-0626-01L | International Aid and Development Number of participants limited to 40 Prerequisites: Basic knowledge of economics | W | 2 credits | 2V | I. Günther | |
| Abstract | The course gives economic and empirical foundations for a sound understanding of the instruments, prospects and limitations of international development aid. | |||||
| Learning objective | Students have a theoretically and empirically sound understanding of the prospects and limitations of international development aid. Students are able to critically discuss the various aid instruments of bi-and multilateral donors and NGOs. | |||||
| Content | Introduction to the Determinants of Underdevelopment; History of Aid; Aid and Development: Theories and Empirics; Political Economy of Aid; Experience and Impact of Aid; New Instruments of Aid: e.g. Micro-Finance, Budget-Support; Fair-Trade. | |||||
| Literature | Articles and book abstracts will be uploaded to a course website. | |||||
| Methodology Competences | ||||||
| Methods in Food and Resource Use Economics | ||||||
| Number | Title | Type | ECTS | Hours | Lecturers | |
| 751-3801-00L | Experimental Design and Applied Statistics in Agroecosystem Science | W+ | 3 credits | 2G | A. Hund, W. Eugster, C. Grieder, R. Kölliker | |
| Abstract | In this course, different experimental designs will be discussed and various statistical tools will be applied to research questions in agroecosystem sciences. Both manipulative (field and laboratory) experiments and surveys are addressed and students work with a selection of basic techniques and methods to analyse data using a hands-on approach. Methods range from simple t-tests to multi-factoria | |||||
| Learning objective | Students will know various statistical analyses and their application to science problems in their study area as well as a wide range of experimental design options used in environmental and agricultural sciences. They will practice to use statistical software packages (R), understand pros and cons of various designs and statistics, and be able to statistically evaluate their own results as well as those of published studies. | |||||
| Content | The course program uses a learning-by-doing approach ("hands-on minds-on"). New topics are introduced in the lecture hall, but most of the work is done in the computer lab to allow for the different speeds of progress of the student while working with data and analyzing results. In addition to contact hours exercises must be finalized and handed in for grading. The credit points will be given based on successful assessments of selected exercises. The tentative schedule containst the following topics: Introduction To Experimental Design and Applied Statistics Introduction to 'R' / Revival of 'R' Skills Designs of Field and Growth Chamber Experiments Nonlinear Regression Fits Multivariate Techniques: Principle Component Analysis, Canonical Correpondence Analysis (CCA), Cluster Analysis ANOVA using linear and mixed effect models Error Analysis, Error Propagation and Error Estimation Introduction to autoregression and autocorrelations in temporal and spatial data and how to consider them in ANOVA-type analysis This course does not provide the mathematical background that students are expected to bring along when signing up to this course. Alternatively, students can consider some aspects of this course as a first exposure to solutions in experimental design and applied statistics and then deepen their understanding in follow-up statistical courses. | |||||
| Lecture notes | Handouts will be available (in English) | |||||
| Literature | A selection of suggested additional literature, especially for German speaking students will be presented in the introductory lecture. | |||||
| Prerequisites / Notice | This course is based on the course Mathematik IV: Statistik, passed in the 2nd year and the Bachelor's course "Wissenschaftliche Datenauswertung und Datenpräsentation" (751-0441-00L) | |||||
| 363-0541-00L | Systems Dynamics and Complexity | W+ | 3 credits | 3G | F. Schweitzer, G. Casiraghi, V. Nanumyan | |
| Abstract | Finding solutions: what is complexity, problem solving cycle. Implementing solutions: project management, critical path method, quality control feedback loop. Controlling solutions: Vensim software, feedback cycles, control parameters, instabilities, chaos, oscillations and cycles, supply and demand, production functions, investment and consumption | |||||
| Learning objective | A successful participant of the course is able to: - understand why most real problems are not simple, but require solution methods that go beyond algorithmic and mathematical approaches - apply the problem solving cycle as a systematic approach to identify problems and their solutions - calculate project schedules according to the critical path method - setup and run systems dynamics models by means of the Vensim software - identify feedback cycles and reasons for unintended systems behavior - analyse the stability of nonlinear dynamical systems and apply this to macroeconomic dynamics | |||||
| Content | Why are problems not simple? Why do some systems behave in an unintended way? How can we model and control their dynamics? The course provides answers to these questions by using a broad range of methods encompassing systems oriented management, classical systems dynamics, nonlinear dynamics and macroeconomic modeling. The course is structured along three main tasks: 1. Finding solutions 2. Implementing solutions 3. Controlling solutions PART 1 introduces complexity as a system immanent property that cannot be simplified. It introduces the problem solving cycle, used in systems oriented management, as an approach to structure problems and to find solutions. PART 2 discusses selected problems of project management when implementing solutions. Methods for identifying the critical path of subtasks in a project and for calculating the allocation of resources are provided. The role of quality control as an additional feedback loop and the consequences of small changes are discussed. PART 3, by far the largest part of the course, provides more insight into the dynamics of existing systems. Examples come from biology (population dynamics), management (inventory modeling, technology adoption, production systems) and economics (supply and demand, investment and consumption). For systems dynamics models, the software program VENSIM is used to evaluate the dynamics. For economic models analytical approaches, also used in nonlinear dynamics and control theory, are applied. These together provide a systematic understanding of the role of feedback loops and instabilities in the dynamics of systems. Emphasis is on oscillating phenomena, such as business cycles and other life cycles. Weekly self-study tasks are used to apply the concepts introduced in the lectures and to come to grips with the software program VENSIM. | |||||
| Lecture notes | The lecture slides are provided as handouts - including notes and literature sources - to registered students only. All material is to be found on the Moodle platform. More details during the first lecture | |||||
| Prerequisites / Notice | Self-study tasks (discussion exercises, Vensim exercises) are provided as home work. Weekly exercise sessions (45 min) are used to discuss selected solutions. Regular participation in the exercises is an efficient way to understand the concepts relevant for the final exam. | |||||
| 401-0647-00L | Introduction to Mathematical Optimization | W+ | 5 credits | 2V + 1U | D. Adjiashvili | |
| Abstract | Introduction to basic techniques and problems in mathematical optimization, and their applications to a variety of problems in engineering. | |||||
| Learning objective | The goal of the course is to obtain a good understanding of some of the most fundamental mathematical optimization techniques used to solve linear programs and basic combinatorial optimization problems. The students will also practice applying the learned models to problems in engineering. | |||||
| Content | Topics covered in this course include: - Linear programming (simplex method, duality theory, shadow prices, ...). - Basic combinatorial optimization problems (spanning trees, shortest paths, network flows, ...). - Modelling with mathematical optimization: applications of mathematical programming in engineering. | |||||
| Literature | Information about relevant literature will be given in the lecture. | |||||
| Prerequisites / Notice | This course is meant for students who did not already attend the course "Mathematical Optimization", which is a more advance lecture covering similar topics. Compared to "Mathematical Optimization", this course has a stronger focus on modeling and applications. | |||||
| 751-0423-00L | Risk Analysis and Risk Management in Agriculture | W+ | 3 credits | 2G | R. Finger | |
| Abstract | Agricultural production is exposed to various risks which are important for decisions taken by farmers and other actors in the agri-food sector. Moreover, risk management is indispensable for all actors. This course introduces modern concepts on decision making under risk and recent developments in risk management. The focus of this course in on agriculture applications. | |||||
| Learning objective | -to develop a better understanding of decision making under uncertainty and risk; -to gain experience in different approaches to analyze risky decisions; -to develop an understanding for different sources of risk in agricultural production; -to understand the crucial role of subjective perceptions and preferences for risk management decisions; -to get an overview on risk management in the agricultural sector, with a particular focus on insurance solutions | |||||
| Content | - Quantification and measurement of risk - Risk preferences, expected utility theory and alternative models of risk behavior - Concepts on the decision making under risk - Production, investment and diversification decisions under risk - Risk management in agriculture | |||||
| Lecture notes | Handouts will be distributed in the lecture and available on the moodle. | |||||
| Prerequisites / Notice | knowledge of basic concepts of probability theory and microeconomics | |||||
| 751-1573-00L | Dynamic Simulation in Agricultural and Regional Economics | W | 2 credits | 2V | B. Kopainsky | |
| Abstract | In this class, students learn the basics of system dynamics and its application to agricultural and regional economic questions. In the second half of the class, students develop their own simulation model, with which they evaluate potential interventions for improving the economic as well as the ecological sustainability of food systems. | |||||
| Learning objective | - Students learn the basic theory and practice of dynamic simulation - Students can develop, analyze and extend a dynamic simulation model and interpret its results. - By applying the developed simulation model, students gain insights into food system issues. They also learn to recognize the benefits and pitfalls of dynamic simulation, both from a theoretical and an applied perspective. | |||||
| Lecture notes | slides (will be provided during the class) | |||||
| Literature | articles and papers (will be provided during the class) | |||||
| 751-1575-00L | Applied Optimization in Agricultural Economics Does not take place this semester. | W | 2 credits | 1V | ||
| Abstract | ||||||
| Learning objective | ||||||
| 363-0305-00L | Empirical Methods in Management | W+ | 3 credits | 2G | F. von Wangenheim | |
| Abstract | Evidence-based management requires valid empirical research. In this course, students will learn the basics of research design, fundamentals of data collection and statistical methods to analyze the data acquired in social science research. Students are expected to apply their knowledge in class discussions and out-of-class assignments. | |||||
| Learning objective | - Ability to formulate research questions and designing an appropriate study - Ability to collect and analyze data using a variety of methods - Ability to critically assess the quality of empirical research in management - Applied knowledge of empirical methods through out-of-class assignments | |||||
| Content | 1) Introduction to empirical management research 2) Research designs: exploratory, descriptive, experimental 3) Measurement and scaling 4) Data collection and sampling 5) Data analysis methods 6) Reporting and presenting empirical research | |||||
| Prerequisites / Notice | Assignments and projects: This course includes out-of-class assignments and projects to give students some hands-on experience in conducting empirical research in management. Projects will focus on one particular aspect of empirical research, like the formulation of a research question or the design of a study. Students will have at least one week to work on each assignment. Students are expected to work on these assignments individually. Duplicate answers will receive no credit and will be subject to a disciplinary review. Assignments will be graded and need to be turned-in on time. Class participation: Class participation is encouraged and can greatly improve students' learning in this class. In this spirit, students are expected to attend class regularly and come to class prepared. | |||||
| 363-0585-00L | Intermediate Econometrics | W+ | 3 credits | 2V | M. Kesina | |
| Abstract | The idea of this course is to familiarize students with instrumental variables estimation of linear regression models and the estimation of models with limited dependent variables as well as of nonlinear regression models. While most of the material covered will pertain to cross-sectional data, we will also work on selected issues with panel data. | |||||
| Learning objective | I will provide STATA programs and show the execution thereof. After having participated in this course, students will be able to carry out simple research projects and understand the basics of intermediate econometrics. In particular, they will be able to write simple programs in STATA and to qualify their own and others' regression output relating to problems covered. | |||||
| Literature | Jeffrey M. Wooldridge: Introductory Econometrics; Jeffrey M. Wooldridge: Econometric Analysis of Cross Section and Panel Data; A. Colin Cameron and Pravin K. Trivedi. Microeconometrics: Methods and Applications. | |||||
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