Suchergebnis: Katalogdaten im Frühjahrssemester 2021

Management, Technologie und Ökonomie Master Information
Kernfächer
Unternehmens- und Personalführung
NummerTitelTypECTSUmfangDozierende
363-0302-00LHuman Resource Management: Leading Teams Information W+3 KP2GG. Grote
KurzbeschreibungThe basic processes of human resource management are discussed (selection, reward systems, performance evaluation, career development) and embedded in the broader context of leadership in teams. Leadership concepts and group processes are presented. Practical instruments supporting leadership functions are introduced and applied in business settings through student projects.
Lernziel• Understand basic HRM functions and their relationship to leadership
• Know instruments for selection, performance appraisal, compensation, and development
• Understand leadership requirements and success factors in leadership
• Know fundamental processes in teams
• Apply and expand theoretical knowledge on a specific topic in self-guided learning
• Manage team processes and diversity
InhaltHuman Resource Management (HRM) concerns the policies, practices, and systems that influence employees' behavior, attitudes, and performance. HRM aims at applying human resources within organizations such that people succeed and organizational performance improves. HRM is of high strategic relevance as evidenced by strong links between good HRM practices and business outcomes.

In the course, concepts and instruments for employee selection, performance management, and personnel development are presented. Some instruments are also practically applied in small groups. Fundamentals of effective leadership and dynamics in teams are discussed, in particular in view of the increasing demands for balancing stability and flexibility in fast-changing organizations.

The course is taught from the perspective of team members' and team leaders' role in HRM, not from the perspective of HR managers. Thereby, students can directly relate their own experience to the HRM practices discussed. This applies to prior work experience, but also to any other teamwork experience, be it as a student or in a private role, for instance in sports clubs. Selecting the right team members, discussing and improving individual and team performance, managing task and relational conflicts, and sharing and building on each other's knowledge to solve problems are ubiquituous challenges that the course addresses.

As part of the course, students also apply HRM instruments in company contexts in a group semester project. Topics for these projects are determined prior to the course and in the past have concerned leadership assessment, performance-based pay, and working in virtual teams. Students are provided with background literature and specific tools to conduct the project and are accompanied by a project advisor who provides additional support.
SkriptThere is no script.
LiteraturA reading list and the respective documents are provided via moodle.
363-1039-00LIntroduction to NegotiationW+3 KP2GM. Ambühl
KurzbeschreibungThe course introduces students to the concepts, theories, and strategies of negotiation and is enriched with an extensive exploration of real-life case-study examples.
LernzielThe objective of the course is to teach students to recognize, understand, and approach different negotiation situations, by relying on a range of primarily quantitative and some qualitative analytical tools.
InhaltWe all negotiate on a daily basis – on a personal level with friends, family, and service providers, on a professional level with employers and clients, among others. Additionally, negotiations are constantly unfolding across various issues at the political level, from solving armed conflicts to negotiating trade and market access deals.

The course aims to provide students with a toolbox of analytical methods that can be used to identify and disentangle negotiation situations, as well as serve as a reference point to guide action in practice. The applicability of these analytical methods is illustrated through examples of negotiation situations from international politics and business.

The theoretical part of the course covers diverse perspectives on negotiation: with a key focus on game theory, but also covering Harvard principles of negotiation, as well as the negotiation engineering approach developed by Prof. Ambühl at ETH Zurich. The course also dedicates some time to focus on conflict management as a specific category of negotiation situations and briefly introduces students to the social aspects of negotiation, based on the insights from psychology and behavioral economics.

The empirical part of the course draws on case-studies from the realm of international politics and business, including examples from Prof. Ambühl’s work as a career diplomat. Every year, the course also hosts two guest lecturers – representatives from politics or business leaders, who share practical experience on negotiations from their careers.
LiteraturThe list of relevant references will be distributed in the beginning of the course.
Strategie, Märkte und Technologie
NummerTitelTypECTSUmfangDozierende
363-1077-00LEntrepreneurship Information W+3 KP2GB. Clarysse
KurzbeschreibungThis course introduces the various elements important to start an innovative business. These are: insights into how technology as a context shapes opportunities to start a business, assessing opportunities, protecting one's idea and technology, market testing and feedback, how to form a team, raising investment and deal evaluation, use of novel financing sources, development of term sheets.
LernzielThis course enables to understand:
How technologies develop from science to commercial products
What kind of entrepreneurial opportunities emerge from this cycle
How assumptions are tested in the market and evolve into business plans
What the importance is of founding teams and how they are fit together
How to raise money from various sources such as crowd funding, ICO, business angels and venture capitalists
How to develop a business case
How to negotiate and structure a funding deal
InhaltThe course consists of 7 sessions of 4 hours, every other week. The first 2 hours typically cover the content of the session, while in the last 2 hours students work in teams to apply the content in specific case settings.

The course is structured as follows:

In session 1, we discuss how science develops into technologies that are eventually commercialized into products ...We discuss how technology entrepreneurs can create ventures based upon the technology they work on, the demand they see in their environment or just through the mere aspiration of creating a company. We specifically focus on how these companies can create value in the absence of clear customer revenues and what the eventual outcome is of such a venture.

In Session 2, we look at how entrepreneurs do market research and how different types of market research help them to develop their business. In addition, you will get an overview of various forms of prototyping, and of how the use of such prototyping can help you test the market and incorporate market feedback into your product or service.

In Session 3, we introduce the concept of "appropriability". For entrepreneurs, especially in a technology environment, it is very important to think about how they can appropriate value from the ideas they develop and the products they introduce in the market. Such appropriation can be enabled through legal mechanisms such as IP or might be facilitated through the way in which the company is set up. We also discuss how value can be delivered in an industry, how negotiation power can be assessed, what different actors need to be taken into consideration when determining the value flow in a network and, eventually, how to think of a business model annex business plan.

Session 4 touches upon a number of HR questions and managerial challenges for the budding entrepreneur: Is it better to go alone or in a team? Are there more or less successful compositions of an entrepreneurial team and if so, where to find the right co-conspirators? We also introduce the basic elements of making a financial plan.

Session 5 introduces you in the world of raising capital. You get an overview of the various sources of capital including business angels, accelerators, crowd funding, venture capital and corporate capital. Guest speakers from the financing industry will answer your questions with regards to getting finance.

Session 6 deals with the legal side of making a deal between an investor and a company. We also explain how to make an elevator pitch and how to pitch for money (including business plan competitions)

Session 7 includes a negotiation game. The negotiation game allows you to go through the different conditions of a term sheet including the valuation of a start-up, the lock-in of the management team, the liquidation options and the division of power. The aim is to learn how to use each of these terms in a practical setting and be able to write a term sheet with an investor.

Each of the sessions includes a mix of theory (usually 2 hours), case study/exercise work and occasional guest presentations (usually 1 hour). The course is an excellent introduction to 'do it yourself courses' such as the Deep Science Sprint, the Digital Entrepreneurship Course,..
SkriptPowerpoint slides are provided ahead of each session and provide together with Clarysse and Kiefer (2011) the core course material.

In addition to the slides and handbook, most sessions have case material (uploaded ahead of the course and to be read BEFORE the lecture in which the case will be discussed). Video material is part of the core syllabus.
LiteraturClarysse, B. & S. Kiefer The Smart Entrepreneur (Elliott & Thompson, 2011) is used as core reading material.

In addition, each session also has "advanced reading" papers, which are useful to deepen your knowledge about the specific subject under discussion. It is sufficient to read the introduction and the conclusions of the papers to get the core idea.

The papers are uploaded through Moodle, the book is available for sale at Amazon.com or can be ordered from any book store.
Voraussetzungen / BesonderesNo special background is needed.
363-0392-00LStrategic Management Information Belegung eingeschränkt - Details anzeigen
Number of participants limited to 80.

If you have any questions please contact the teaching assistant Krishna Vaibhav: Link.
W+3 KP2GS. Herting
KurzbeschreibungThis courses conveys concepts and methods in strategic management, with a focus on competitive strategy. Competitive strategy aims at improving and establishing position of firms within an industry.
LernzielThe lecture "strategic management" is designed to teach relevant competences in strategic planning and -implementation, for both professional work-life and further scientific development. The course provides an overview of the basics of “strategy” and the most prevalent concepts and methods in strategic management. The course is given as a combination of lectures about concepts/methods, and case studies where the students asked to solve strategic issues of the case companies. In two sessions, the students will also be addressing real-time strategic issues of firms that are represented by executives.
InhaltContents:
a. Strategy concepts
b. Industry dynamics I: Industry analysis
c. Industry dynamics II: Analysis of technology and innovation
d. The resource-based theory of the firm
e. The knowledge-based theory of the firm

Strategic Management offers a combination of lectures about concepts/methods, and case studies where the students solve strategic issues of the involved companies. This aims at offering students a profound theoretical understanding of important and current topics and also offer an opportunity to present these concepts in front of an audience.
This course conveys concepts and methods in strategic management, with a focus on competitive strategy. Competitive strategy aims at analyzing and establishing position of firms within an industry, securing firm performance. Thus, the course focuses on a number of important topics, such as the evolution of industry, industry structure, the analysis of a firm's resources- and knowledge, and innovation.
In addition, student groups will hold presentations on the four main topics of this class, to further develop concepts and enhance understanding. The presentations will cover Industry Dynamics I, Industry Dynamics II, Resource Based View of the Firm, Knowledge Based View of the Firm. For all presentations, selected Harvard Business Cases will be used as a common ground for students to start from.
Students are also expected to read and understand the required readings (approx. 15 items) that cover the most important papers and articles from the past 30 years in management and strategy research.
To underline the relevance of Strategic Management in firms, decision makers from companies in Switzerland will be holding guest lectures and give their take on strategy in practice and give insight on current topics in the field.
Voraussetzungen / BesonderesSession #0: (tbd) Introduction & How to solve a case
Session #1: (tbd) Introduction to Strategy
Session #2: (tbd) Industry Dynamics I
Session #3: (tbd) Industry Dynamics II
Session #4: (tbd) Resource-Based Theory
Session #5: (tbd) Guest Lecture I
Session #6: (tbd) Knowledge-based Theory
Session #7: (tbd) Guest Lecture II

Please NOTE: The dates of the guest lectures subject to change due to availability of the guest lecturers. The final schedule will be provided in the first session.
Quantitative und Qualitative Methoden zur Lösung komplexer Probleme
NummerTitelTypECTSUmfangDozierende
363-0570-00LPrinciples of Econometrics
Prerequisites: previous knowledge in economics.
W+3 KP2GJ.‑E. Sturm, A. Beerli
KurzbeschreibungThis course introduces the fundamentals of econometrics. We cover simple and multiple regression analysis using different data formats. An emphasis is on hypothesis testing, interpretation of regression results, and understanding threats to the causal interpretation of relationships in the data.
LernzielThe course targets both the theoretical understanding as well as the application of basic econometric methods to real world problems.

The educational objective of this course is that, after completion, students should be able to:
1. understand different forms of data (cross-sectional, panel, time-series) and their strengths and weaknesses for answering different research questions.
2. understand how to translate questions about economic policy issues and human behaviour into research hypotheses that can be tested with data.
3. apply their theoretical knowledge about econometrics to concrete examples based on the knowledge they acquired in tutorial sessions using the statistical software package STATA and interpret estimation results.
4. name and identify potential threats for causal interpretations of relationships in the data and explain whether (and how) they can be addressed.
InhaltThe term “econometrics” stands for the application of specific statistical methods to the field of economics. Econometrics aims at providing empirical evidence using observational data that can be used to learn about the real-world existence of specific relationships postulated in economic theories. Typical research questions that economists analyse by using econometric methods include for instance: Do minimum wages reduce employment? Does a gender wage gap exist and how large is it? Does foreign aid affect economic growth? How do interest rate changes influence exports? Is there an effect of economic outcomes on politicians’ chances to get re-elected?

Starting from simple regression analysis, the course introduces the statistical framework that is used in econometrics to answer such empirical research questions. A major focus is on understanding and mastering methods of hypothesis testing using multiple regressions.
The lecture discusses different issues regarding assumptions, interpretation, and inference in multiple linear regression models. Among others, the course addresses the following questions: How well or badly does the applied model fit the observed facts? How large is the estimate of the effects of one variable on another and how reliable is the estimate? Can the model be used to predict the specific variable of interest and how precise is that prediction? What are the crucial assumptions of the estimation strategy used, (how) can they be tested, and does the estimated relationship represent a causal effect?

The course lectures introduce the methods and computer tutorials give the students the opportunity to apply and deepen their knowledge using the software package STATA.
LiteraturWooldridge, Jeffrey M. (2018) Introductory Econometrics : A Modern Approach. Seventh ed. ISBN: 978-1-337-55886-0 [access to relevant chapters will be provided]
Voraussetzungen / BesonderesThis course is intended for students interested in econometrics who have already taken an introductory course in economics (e.g., the course "Principles of Macroeconomics"). Knowledge of the statistical software STATA is no prerequisite and will be acquired during the course.
Mikro- und Makroökonomie
NummerTitelTypECTSUmfangDozierende
363-0515-00LDecisions and MarketsW+3 KP2VA. Bommier
KurzbeschreibungThis course provides an introduction to microeconomics. The course emphasizes the conceptual foundations of microeconomics and contains concrete examples of their application.
LernzielThe purpose of this course is to provide master students with an introduction to graduate-level microeconomics, particularly for students considering further graduate work in economics, business administration or management science. The course provides the fundamental concepts and tools for graduate courses in economics offered at ETH and UZH.

After completing this course:
- Students will be able to understand and use existing models to make predictions of consumer and firm behavior.
- Students understand the fundamental welfare theorems and will be able to analyze equilibria of markets with perfect and imperfect competition.
- Students will be able to analyze under which conditions market allocations are not efficient (market failure).
InhaltMicroeconomics is the branch of economics which studies the decision-making by an individual, household, firm, industry or level of government. The economic equilibrium is the result of agents' interactions. Microeconomics is an element of nearly every subfield in economic analysis today. This course introduces the fundamental frameworks which form the basis of many economic models.

Theory of the consumer:
- Consumer preferences and utility
- Budget sets and optimal choice
- Demand functions
- Labor supply and intertemporal choice
- Welfare economics

Theory of the producer:
- Technological constraints and the production function
- Cost minimization
- Profit maximization

Market structure:
- Perfectly competitive markets
- Monopoly behavior
- Duopoly behavior

General equilibrium analysis:
- Market equilibrium in an exchange economy
SkriptThe lecture will be based on lecture slides, which will be made available on Moodle.
LiteraturThe course is mostly based on the textbook by R. Serrano and A. Feldman: "A Short Course in Intermediate Microeconomics with Calculus" (Cambridge University Press, 2013). Another textbook of interest is "Intermediate Microeconomics: A Modern Approach" by H. Varian (Norton, 2014).
Exercises are available in the textbook by R. Serrano and A. Feldman ("A Short Course in Intermediate Microeconomics with Calculus", Cambridge University Press, 2013). More exercises can be found in the book "Workouts in Intermediate Microeconomics" by T. Bergstrom and H. Varian (Norton, 2010).
Voraussetzungen / BesonderesThe course is open to students who have completed an undergraduate course in economics principles and an undergraduate course in multivariate calculus.
363-0575-00LEconomic Growth, Cycles and PolicyW+3 KP2GH. Gersbach
KurzbeschreibungThis intermediate course focuses on the core thinking devices and foundations in macroeconomics and monetary economics, and uses these devices to understand economic growth, business cycles, crises as well as how to conduct monetary and fiscal policies and policies to foster the stability of financial and economic systems.
Lernziel- Fundamental knowledge about the drivers of economic growth in the short and long run, key macroeconomic variables and observed patterns in developed countries

- Comprehensive understanding of core macroeconomic frameworks and thinking devices
InhaltThis intermediate course focuses on the core thinking devices and foundations in macroeconomics and monetary economics, and uses these devices to understand economic growth, business cycles, crises as well as how to conduct monetary and fiscal policies and policies to foster the stability of financial and economic systems. The course is structured in the following way:

Part I: Basics
- Introduction
- IS-LM Model in Closed Economy (Repetition)
- Schools of Thought
- Consumption and Investment
- The Solow Growth Model

Part II: Special Themes
- Money Holding, Inflation, and Monetary Policy
- Crises in Market Economies
- IS-LM Model and Open Economy
- Theories of exchange rate determination
- Technical Appendix
SkriptCopies of the slides will be made available.
LiteraturChapters in
Manfred Gärtner (2009), Macroeconomics, Third Edition, Prentice Hall.
and selected chapters in other books and/or papers
Voraussetzungen / BesonderesIt is required that participants have attended the lecture "Principles of Macroeconomics" (363-0565-00L).
Finanzielle Führung
NummerTitelTypECTSUmfangDozierende
363-0560-00LFinancial Management Information W+3 KP2VJ.‑P. Chardonnens
KurzbeschreibungThis course introduces students to the concept and principles of financial management that are of primary concern to corporate managers, and all the consideration needed to make financial decision. It involves investment and financing decisions through the application of financial analysis.
LernzielBy attending this course, students will be able to:
- increase the overall value of firms and improve their profitability.
- ensure sufficient availability of funds to satisfy maturing short-term debt.
- improve the management of working capital and short-term financing.
- make capital budgeting decisions under both certainty and uncertainty.
- discuss the capital structure theory.
- understand the different sources of finance.
- describe the main motives and implications of mergers and acquisitions.
InhaltThe course Financial Management follows the course Accounting for Managers. The principles of financial management are illustrated with different cases. The course is divided into six main sections:

1. The first section discusses the financial goals of the firm, value-based management, and the objectives of liquidity and profitability.

2. The second chapter explains the tools and methods of financial analysis and forecasting needed by managers in order to make appropriate investing and financing decisions.

3. The third division demonstrates the importance of the management of working capital, cash planning, current asset management, short term financing, and the cash flow statement.

4. The fourth module introduces the static and dynamic methods of capital budgeting in order to improve the profitability of the organisation and achieve the main objectives.

5. The fifth part relates to the financing of the company, the capital structure theory, the cost of capital, the different sources of equity and debt financing.

6. The last section of the course illustrates special topics of financial management, such as mezzanine finance, corporate restructuring, mergers & acquisitions, and the valuation of shares.
Voraussetzungen / BesonderesRequirement : Good knowledge of financial accounting (Accounting for Managers)
Wahlfächer
NummerTitelTypECTSUmfangDozierende
363-0543-00LAgent-Based Modelling of Social Systems Information W3 KP2V + 1UF. Schweitzer, G. Vaccario
KurzbeschreibungAgent-based modeling is introduced as a bottom-up approach to understand the complex dynamics of social systems. The course is based on formal models of agents and their interactions. Computer simulations using Python allow the quantitative analysis of a wide range of social phenomena, e.g. cooperation and competition, opinion dynamics, spatial interactions and behaviour in social networks.
LernzielA successful participant of this course is able to
- understand the rationale of agent-based models of social systems
- understand the relation between rules implemented at the individual level and the emerging behavior at the global level
- learn to choose appropriate model classes to characterize different social systems
- grasp the influence of agent heterogeneity on the model output
- efficiently implement agent-based models using Python and visualize the output
InhaltThis full-featured course on agent-based modeling (ABM) allows participants with no prior expertise to understand concepts, methods and tools of ABM, to apply them in their master or doctoral thesis. We focus on a formal description of agents and their interactions, to allow for a suitable implementation in computer simulations. Given certain rules for the agents, we are interested to model their collective dynamics on the systemic level.

Agent-based modeling is introduced as a bottom-up approach to understand the complex dynamics of social systems.
Agents represent the basic constituents of such systems. The are described by 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, which we want to understand and to analyze.

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 modeling, weekly exercise classes provide practical skills. Using the Python programming language, the participants implement agent-based models in guided and in self-chosen projects, which they present and jointly discuss.
SkriptThe lecture slides will be available on the Moodle platform, for registered students only.
LiteraturSee handouts. Specific literature is provided for download, for registered students only.
Voraussetzungen / BesonderesParticipants of the course should have some background in mathematics and an interest in formal modeling and in 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 students.

The examination will account for 70% of the grade and will be conducted electronically. The "closed book" rule applies: no books, no summaries, no lecture materials. The exam questions and answers will be only in English. The use of a paper-based dictionary is permitted.
The group project to be handed in at the beginning of July will count 30% to the final grade.
363-1098-00LBusiness Analytics
Students from the MAS MTEC are not applicable for this course and are kindly asked to enroll in the course "AI for Executives (365-1120-00L)" instead.
W3 KP1GS. Feuerriegel
KurzbeschreibungIn this course, students learn to plan, implement and evaluate analytics in applied settings in order to generate value from data for society, corporations and individuals. This serves the pressing need of firms to improve their efficiency – such as customer satisfaction, competitive advantage –by leveraging the growing amounts of structured and unstructured data.
LernzielOverall learning goal

By the end of the course, students will be able to plan, implement and evaluate analytics in applied settings in order to generate value from data for society, corporations and individuals. This serves the pressing need of firms to improve their efficiency – such as customer satisfaction, competitive advantage –by leveraging the growing amounts of structured and unstructured data.

Detailed breakdown by objective

To achieve this overall goal, students should after participation being able to:

Objective 1 (Managerial aspects): Understand the processes and challenges of analytics-related projects
• Identify applications for analytics in corporations and organizations that create value
• List implications for management when undertaking a project involving business analytics
• Apply the data mining process CRISP-DM to their actual setting

Objective 2 (Methodological challenges): Understand common methods for performing business analytics
• Translate use cases of business analytics into a mathematical model formulation
• Name common methods for business analytics, as well as their underlying concepts
• Compare the properties of these models

Objective 3 (Practical implementation): Performing actual evaluations of business analytics based on real-word datasets
• Preprocess data in order to transform it into relational structures
• Apply statistical software (e.g. “R” or Python) to perform business analytics in practice
• Evaluate the results in order to choose the best-performing method
InhaltWith the emergence of ubiquitous computing technology, company decisions nowadays rely strongly on computer-aided “Business Analytics”.

Business analytics refers to technologies that target how business information (or sometimes information in general) is collected, analyzed and presented. Combining these features results in software serving the purpose of providing better decision support for individuals, businesses and organizations.

This course will teach what distinguishes the varying capabilities across business analytics – namely the underlying methods. Participants will learn different strategies for data collection, data analysis, and data visualization. Sample approaches include dimension reduction of big data, data visualization, model selection, clustering and forecasting.
In particular, the course will teach the following themes:
• Forecasting: How can historical values be used to make predictions of future developments ahead of time? How can firms utilize unstructured data to facilitate the predictive performance? What are metrics to evaluate the performance of predictions?
• Data analysis: How can one derive explanatory power in order to study the response to an input?
• Clustering: How can businesses group consumers into distinct categories according to their purchase behavior?
• Dimension reduction: How can businesses simplify a large amount of indicators into a smaller subset with similar characteristics?
During the exercise, individual assignments will consist of a specific problem from business analytics. Each participant will be provided with a dataset to which a certain method should be applied to using the statistics software R.

Note: the course is a block course teaching the theoretical elements. This provides then the basis for a project work where individual students or groups implement analytics to a business-relevant datasets. This project underlies eventually the grading.
SkriptContent:
1. Motivation and terminology
2. Business and data understanding
a. Data management and strategy
b. Data mining processes
3. Data preparation for big data
a. Software and tools
b. Knowledge representation and storage
c. Information preprocessing
4. Explanatory modeling
5. Predictive modeling
a. Classification
b. Variable selection
c. Handling non-linearities
d. Ensemble learning
e. Unsupervised learning
f. Working with unstructured data
6. Managerial implications
LiteraturJames, Witten, Hastie & Tibshirani (2013): An Introduction to Statistical Learning: With Applications in R. Springer.
Sharda, Delen & Turban (2014): Business Intelligence: A Managerial Perspective on Analytics. Pearson.
Voraussetzungen / BesonderesPlease note that we expect simple scripting skills (e.g. in Python), as students will apply their theoretical knowledge by implementing a machine learning application with given open-source packages.
363-1132-00LBusiness Models for a Circular Economy Belegung eingeschränkt - Details anzeigen W3 KP1.5GC. Bening-Bach, N. U. Blum
KurzbeschreibungThis course leads students through the process of re-thinking an existing product in a circular way. At the end of the course students will come up with new, circular business models for their products. The course consists of an overview of circular economy principles, research, diverse workshop formats and team work.
Lernziel1) Students familiarize themselves with the principles of a circular economy
2) Students critically reflect on the limits of a circular economy
3) Students experience a re-thinking process of an existing product along circular economy principles
InhaltThis course is aimed at people with a keen interest to understand and solve societal and environmental problems employing the principles of a circular economy.

The seminar consists of a mix of lectures, workshops, individual working sessions, and team work. Critical reflection is an integrative part of the process.

The course tackles a topic that in the light of climate change, resource scarcity and decreasing biodiversity, gains traction in industry, policy and academia: Circular economy. A circular economy is a regnerative system that uses as little resources as possible in the most efficient way. The implementation of a circular economy offers different ways to do so, e.g. by re-design, re-use, re-cycling. Along these different "cycles" new business models arise.

In this course students evaluate different products on their potential for a circular economy by considering - among others -the product's technical, economic, and legal environment. Once they strengthened their knowledge on the product and oh circular economy principles, they will develop solutions and business models in teams. The course ends with a pitching event, where the teams will present their solutions and business ideas.
363-1116-00LClimate FinanceW3 KP2GV. Stolbova
KurzbeschreibungThe course focuses on understanding the impact of climate change on the financial system and the impact of the financial system on climate change. It addresses how firms, banks, governments, insurances and pension funds invest in climate-related financial assets, what are the risks and returns associated with them, and how climate policies impact financial assets and financial stability.
LernzielThe objectives of this course are threefold. First, it aims to provide participants with an overview of the state-of-the-art situation in matters of the impact of climate on finance and the impact of finance on the environment. Second, it introduces current challenges in the fields of sustainable finance, environmental finance and climate finance, and familiarizes participants with existing methods to solve these challenges. Third, it equips participants with knowledge and tools in climate-finance data analysis which could be applied to the real-world cases by calculating climate-related risks and gains for specific market players.
InhaltIt consists of three parts:
The first part gives an overview of the relation between finance and climate. It starts with an introduction of the nature of climate change phenomenon and its financial implications. Several types of climate-related financial risks are considered including physical risks of climate change (financial risks associated with natural disasters), and transition risks (associated with the transition to a low-carbon economy, climate policies and regulations, stranded assets). In addition, risks and opportunities associated with the transition to a low-carbon economy are discussed for institutional sectors (banks, investment funds, pension funds and insurance sector), individual market players, and the real economy.
The second part allows the participants to acquire knowledge of existing methods and tools in financial climate-related risk assessment including both state-of-the-art academic research methods and current industry practices. It also discusses instruments available to market players for financing the transition to a low-carbon economy (e.g. green bonds, climate funds, concessional loans) and existing measures of assessing the environmental impact of investments. Participants of the course receive an opportunity to apply these methods to real-case portfolios of selected market players.
The third part addresses the economic and financial effects of climate policies and environmental regulations. It starts with an overview of implemented and widely debated climate policies. Then, it discusses existing models for the development of economic sectors considering various climate policies and greenhouse gas (GHG) emissions targets. Finally, the course addresses the impact of climate policies on financial institutions, the real economy, individual investors, and provides main arguments on the heated debate on “winners and losers” on the way to decarbonization.
LiteraturThe main reference of the course is the set of lecture notes; students will also be encouraged to read some influential books and academic articles dealing with the issues under study:

[1] “Environmental finance: A guide to Environmental Risk Assessment and financial products”, Labatt, S. and White, R. 2002

[2] “Carbon Finance: the financial implications of climate change”, Labatt, S. and White, R., 2007
[3] “Handbook of environmental and sustainable finance”, Ramiah, V. and Gregoriou, G., 2015

[4] “Greening Economy, Graying Society”, Bretschger, L., CER-ETH Press, Zurich, 2018, 2nd edition
[5] “Natural Resource & Environmental Economics”, Perman, R., Ma, Y., McGilvray, J, Maddison, D., and Common, M., 4th edition, Longman, Essex, 2011

Additional literature:
[6] “Breaking the tragedy of the Horizon - climate change and financial stability”, Carney, M., 2015. Speech given at Lloyd's of London by the Governor of the Bank of England.

[7] “A climate stress-test of the financial system“, Battiston, S., Mandel, A., Monasterolo, I., Schutze, F., Visentin, G., 2017, Nature Clim. Change 7 (4), 283–288.

[8] “Vulnerable yet relevant: the two dimensions of climate-related financial disclosure”, Monasterolo, I., Battiston, S., Janetos, A., Zheng, Z., 2017, Clim. Chang. 145 (3-4), 495–507.

[9] “Rolling the “DICE”: an optimal transition path for controlling greenhouse gases”, Nordhaus, W.D., 1993. Resour. Energy Econ. 15 (1), 27–50

[10] “A Financial Macro-Network Approach to Climate Policy Evaluation”, Stolbova, V., Monasterolo, I., Battiston, S., Ecological Economics, 149, 2018, 239–253
363-1095-00LCommercializing Science and Technology Belegung eingeschränkt - Details anzeigen
Findet dieses Semester nicht statt.
W3 KP2G
KurzbeschreibungThis course is designed for ETH students from all departments and levels to develop their knowledge and competencies on how to turn science and technology into new business opportunities. A key element of this course is the practical application of knowledge to a field project in which students develop a business proposal for an early-stage technology.
LernzielPrimary Course Goals:
1 - To understand key trajectories of how science-based and technological inventions can be transformed into new business opportunities
2 - To understand and compare different commercialization options and appropriate strategies to seize such options
3 - To understand key resourcing challenges for technology-based ventures and how to address them
4 - To conceptualize and develop convincing narratives for presenting a compelling business case for a technology-based venture
5 - To foster an entrepreneurial spirit

The knowledge you will acquire in this course will be useful for different career options: either founding or becoming an employee in a technology start-up, but also if you aim for a career in managing technology in an established firm or within a public or private research lab.
InhaltThis course combines theoretical knowledge with practice. Students will form small teams (3 - 4 members) and work on a technology (preferably from the ETH context) to build a roadmap of how to turn this technology into a value-creating business. Each course meeting will also include a more theory-focused discussion to help students making important decisions as they develop their business case.

In so doing, the course puts a major emphasis on key strategic decisions in high-tech start-ups:

First, one of the most important tasks for technology entrepreneurs is to understand the range of potential applications and the conditions of value creation in the respective industry setting and making early decisions about the core commercial strategy for their technology. This forms the starting point for your field project. The class discussion will prepare you for evaluating the potential of your technology and making a selection of which path to follow.

Second, successful technology commercialization then also requires understanding Intellectual Property Rights, different options for designing technology business models and how to structure market entry strategies such that they allow moving along the technology learning curve and facilitating the adoption of innovative products. In your field project, you will make use of your newly acquired knowledge to develop a market strategy and a potential business model for the successful commercialization of your technology.

Finally, acquiring and mobilizing resources (financial as well as human) is a key task and not easy due to the inherent uncertainty around the value potential of your idea. During the course, we will discuss important aspects of resource mobilization, which will help you develop an appropriate resourcing strategy geared to move your field project forward in the future. You will present your final business case in front of a small jury, consisting mainly of ETH stakeholders.

Key topics we will cover in this course:
1 - Origins of entrepreneurial opportunities and sources of value: problem-solution spaces
2 - Entrepreneurial thinking and business logic: competitive advantage, strategic positioning and value capture
3 - Entrepreneurial business case development: crafting compelling strategies for opportunity exploitation and mobilizing resources

ETHZ offers a lot of support infrastructure for technology start-ups, so the most promising projects from this course will find ample opportunities to continue further development, either through additional courses, through direct coaching and mentoring from entrepreneurs in residence, or acceleration programs, like the ETH Pioneer Fellowship program.
SkriptAll course materials (syllabus, coursebook, slides, and worksheets) will be made available to inscribed course participants through Moodle.

The course materials will consist of short summary notes by the lecturer that will incl. links to blog posts, videos, and relevant academic articles for further independent study. These course materials will form the point of departure for class discussion and work on the projects.
Voraussetzungen / BesonderesThis course is open to ETH students at all levels and from all departments, including PhD students. No prior knowledge of business or economics is required to successfully complete this course.

Note that active participation in the course sessions will form part of your course grade. Likewise, you should be prepared to spend enough time on the field project during the semester.
363-0588-00LComplex Networks Information W4 KP2V + 1UF. Schweitzer
KurzbeschreibungThe 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
InhaltNetworks 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.
SkriptThe 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: Link
LiteraturSee handouts. Specific literature is provided for download - for registered students, only.
Voraussetzungen / BesonderesThere 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.
363-1070-00LCyber SecurityW3 KP2GS. Frei
KurzbeschreibungThis course provides a solid understanding of the fundamental mechanics and limitations of cyber security to provide guidance for future leaders as well as individuals constituting our society.
Introduction to the concepts, developments, and the current state of affairs in the cyber security domain. We look at the topic from the attackers, defenders and societies perspective.
LernzielUpon completion of this course students understand the essential developments, principles, challenges as well as the the limitations and the state of practice in cyber security from the technological, economic, legal, and social perspective.
The course provides an interdisciplinary overview, guidance, and understanding of the dynamics in cyber security to guide decision making in business and society. Students understand the topics from the attackers, defenders, and societies perspective.
InhaltIntroduction
- Brief history of the rise of the Internet from the attackers, defenders, commercial and society perspective
- Learning points from past and current assumptions, approaches, successes, failures, and surprises

Internet Infrastructure
- Establish a high level understanding of the fundamental design principals and functional blocks of the Internet infrastructure
- Understand strengths and weaknesses of present design choices from security perspective
- High level understanding of relevant networking concepts, protocols, software applications, policies, processes & organizations in order to assess these topics
- Establish a functional, high level understanding of relevant aspects of cryptography

Cyber Security & Risk
- Recognize cyber security as an interdisciplinary, highly dynamic, complex and adaptive system where increased interaction and dependencies between physical, communication, and social layers brings fundamentally different (and unpredictable) threats
- Core security assets such as: confidentiality, integrity, availability, authenticity, accountability, non repudiation, privacy
- Dominant players, protocols, and technologies
- Different threat actors along the dimensions attacker goals, resources, approach, and threat

Economics of Cyber Security
Understand security challenges and limitations from an economic, rather than technological perspective
- From security perspective: incentives of industry vs. users, security as a negative externality, zero marginal cost of software, network effect, time to market, lock-in, switching cost, economics of usability, security as a trade-off
- Social and psychological aspects of security

Attacker Capabilities
- Attacker capabilities and the offensive use from technical, economic, organizational, and operational perspective
- Understand common and novel attack and evasion techniques, proliferation of expertise and tools, optimal timing to use zero-day attacks
- Attack types and malware development lifecycle and detection evasion techniques
- Botnets, exploit markets, plausible deniability, distributed denial of service (DDoS)
- Processes and dynamics in the (in)security community, cyber-underground

Defense Options and Limitations
- Functional principles, capabilities, and limitations of diverse protection and detection technologies
- Security effectiveness and evaluation/testing of security technologies
- Trade-off between efficiency and resilience against structurally novel attacks
- Effectiveness baseline security measures
- Know cyber information sources and frameworks

Cyber Security Challenges
- Increasing software complexity and vulnerabilities, the illusion of secure software
- Full disclosure debate, economics of bug bounty programs
- Internet of things, Industry control systems (SCADA/ICS)
- Security and integrity of the supply chain (IoT, Smart-X)
- Social media and mass protests
- Erosion of privacy

Legal Aspects
- Legal aspects of cyber security, compliance, and policies
- Know the fundamental national and international legal and regulatory requirements in connection with cyber security on a cross-sector and sector-specific level
- Understanding of legal risks and measures for risk mitigation

Guest Talks:
- Pascal Gujer - Digital Forensics Expert Kapo Zurich (Cantonal Police Departement Zurich)
- Maxim Salomon - Previously at Roche now with Google as Technical Program Manager for Security of Mergers & Acquisitions "The safety vs. security of cyber physical systems"
- Marc Ruef - Security Expert, "Navigating the Cyber Underground"
- Roger Halbheer - Executive Security Advisor for Microsoft in EMEA
SkriptLecture slides will be available on the site of the lecture:

Link

Collaboradom: Cyber Security Course 2021

To get access ask Link for the registration code once the course has begun
LiteraturPaper reading provided during the lectures
Voraussetzungen / Besonderesnone
363-1066-00LDesigning Effective Projects for Promoting Health@Work Belegung eingeschränkt - Details anzeigen
Number of participants limited to 30.
W3 KP2GG. Bauer, R. Brauchli, G. J. Jenny
KurzbeschreibungThe fast-changing high-performance economy is highly dependent on healthy employees – and at the same time is putting their health at risk. Expectations of employees regarding health@work are rising. In a workshop format, students learn how to develop effective, exemplary projects to promote good working conditions, work-life balance or healthy lifestyles in companies.
LernzielAfter active participation in the course, students will
• Know the key individual, team-level, and organizational factors influencing health@work
• Be familiar with health-related challenges and opportunities of a changing world of work
• Know intervention strategies for improving working conditions, work-life balance and health behaviors in companies
• Be able to design an exemplary intervention project– based on key principles and a systematic planning cycle
InhaltThe globalization and the digital transformation of our economy leads to fast changes in organizations and of working conditions. Work becomes more flexible regarding time, location and employment contracts. Employees become more demanding regarding their autonomy, the quality of working life and their work-life balance. In this dynamic context, offering standardized health promotion programs in companies is not sufficient any more. Employers and employees need to jointly develop tailored approaches how to continuously assess and improve health@work. Thus, we want to enable you to support companies in this process.
The course consists of four parts. The first part with four sessions provides an introduction into approaches to promote health@work. The lectures will present and discuss these approaches using practical examples and discuss them with the students.
Session 1: Course overview; dynamic, challenging context of our economy; intervention approaches; core principles and planning steps of a project for promoting health@work
Session 2: Promoting Health @ Work: Improving working conditions
Session 3: Promoting Health @ Work: Lifestyle interventions at work
Session 4: Promoting Health @ Work: Work-Life-Balance and Leisure crafting interventions

The second part aims to identify and sharpen the project ideas developed by students in groups of two. We offer a short version of a design thinking workshop to help students generate innovative ideas. The pitch presentations help to focus on the essence of the own idea and to trigger constructive feedback for improving it.
Session 5: Design thinking workshop: Find your own project idea
Session 6: Pitch: Presentations of the project idea in plenary incl. feedback

The third part has a workshop format. We introduce all students how to practically plan a health@work project. Then the two-person project teams are assigned to four tutors. These tutors support the teams in their systematic, detailed planning of the own project idea. Particularly, students will consider the four principles of successful health promotion projects: systematic planning, participation of stakeholders, combined individual- and environmental-level actions, integration into company routines.
Session 7: Introduction to practical project planning in-a-nutshell
Sessions 8-11: Tutored workshop

In the fourth part, the two-person project teams present their project plan in the plenary, discuss it with all students, and obtain feedback by the course leader.
Sessions 12-13: Presentations & discussions of projects

Given the hands-on workshop character of this lecture, students are required to actively participate in all sessions. Besides raising knowledge on promoting health@work, the students generally improve their project development skills. Also, as the course has students from D-MTEC, D-HEST and D-USYS, it facilitates their transdisciplinary exchange. Transdisciplinary skills are increasingly needed for addressing complex needs in our society.
Voraussetzungen / BesonderesA course for students dedicated to applied learning through projects. As the whole course is designed as a hands-on workshop for the students, active participation in all lectures is required. Class size limited to 30 students.
363-1076-00LDiffusion of Clean TechnologiesW3 KP2GB. Girod, C. Knöri
KurzbeschreibungHow can the diffusion clean technologies be accelerated?
Participants learn to apply analytic tools to understand environmental and business potentials of clean technologies. Exercises that evaluate a clean technology selected by the student themselves deepen the theoretical knowledge gained. Students are trained to evaluate, explain and pitch a clean technology.
LernzielAfter completing this course: ...
1) Students are able to apply the theoretical concepts explaining the performance and diffusion of clean technologies*
2) Students can determine key drivers and barriers (economic, environmental, technological, regulatory) for the diffusion of clean technologies*
3) Students know how to quantitatively model key characteristics or dynamics of selected clean technologies*
4) Students are prepared to convincingly present a selected clean technology* to a business or policy audience

*In 2021 we will focus on sustainable negative emission technologies (NET), also known as 'carbon dioxide removal'. This includes all technologies that allow to remove CO2 from the atmosphere. For instance technologies to enable reforestation, carbon storage in soils, Biomass Energy and Carbon Capture and Storage (BECCS), Direct Air Capture (DAC) or use of wood in construction.
InhaltWe face a climate and sustainability crisis which requires a fundamental shift to a truly environmentally friendly economy. A key contribution stems from an accelerated development and application of clean technologies such as technologies harnessing renewable energies, enabling increasing energy efficiency or event resulting in negative emission.

Because of the increasing scientific consensus that we will need negative emission technologies (NET) to avoid dangerous climate change, we will focus on NET in 2021. This includes all technologies that allow to remove CO2 from the atmosphere (examples see above).

The goal of this course is to better understand how we can accelerate the diffusion of clean technologies. Students are enabled to answer critical questions such as: What are barriers hindering the diffusion of a certain clean technology? How can we overcome these barriers and drive the diffusion of clean technologies?

The lecture can be divided into four parts:
1. Input on a conceptual basis: Overview on key frameworks and theories for assessing the environmental and economic performance of clean technologies as well as their resulting diffusion. This part will be provided as input by the lecturers and discussed in class.

2. Assessment of selected clean technologies: Students select out of a long list of clean technologies a technology to assess in more detail. For this technology, the concepts learned in part 1 are applied. Assessments are peer-reviewed and discussed.

3. Modeling of diffusion: Students will develop a simplified model for the diffusion of selected clean technology to better understand the dynamics of diffusion and modeling technological behavior.

4. Presenting clean technologies: To conclude students will learn how to pitch their technology assessment to a business or policy audience since this is a crucial part for enabling technology diffusion. These inspiring presentations form the basis for a final class discussion on selected clean technologies and applied concepts.

The list of concepts, tools and techniques applied and discussed in this lecture includes: Analytical tools to assess the environmental performance of clean technologies (e.g. Life Cycle-Assessment); economic view on the diffusion of clean technologies; evolutionary perspective (e.g. technological learning); decision process of adopters (e.g. status-quo bias of consumers, rebound effect); relevant environmental policies (e.g. standards, labels, carbon pricing); modeling approaches for diffusion of clean technologies (e.g. agent-based modeling); techniques for convincing presentations (e.g. TED-style presentation).
SkriptHandout and exercises will be available on electronic platform.
LiteraturRelevant literature will be available on electronic platform.
Voraussetzungen / BesonderesInterest in sustainability and climate action.
363-1130-00LDigital Health Belegung eingeschränkt - Details anzeigen W3 KP2VT. Kowatsch
KurzbeschreibungToday, we face the challenge of chronic conditions. Personal coaching approaches are neither scalable nor financially sustainable. The question arises therefore to which degree Digital Health applications are appropriate to address this challenge. In this lecture, students will learn about the need, design and assessment of digital health interventions.
LernzielThe promise of more personalized, patient-centered, and outcomes-based healthcare is real, worthy, and within reach (Harvard Business Review, October 2019), NHS teams up with Amazon to bring Alexa to patients (The Guardian, July 2019), Apple Heart Study demonstrates the ability of wearable technology to detect atrial fibrillation (Stanford Medicine News, March 2019). In the midst of a global pandemic and a US recession, US digital health companies raised $5.4B in venture funding across the first six months of 2020. The sector is on track to have its largest funding year ever. (Rocket Health, 2020)

What are the rationale and implications behind the recent developments in the field of digital health?

Digital Health is the use of information and communication technology for the prevention and treatment of diseases in the everyday life of individuals. It is thus linked to topics such as digital health interventions, digital biomarker, digital coaches and healthcare chatbots, telemedicine, mobile and wearable computing, self-tracking, personalized medicine, connected health, smart homes or smart cars.

In the 20th century, healthcare systems specialized in acute care. In the 21st century, we now face the challenge of dealing with the specific characteristics of chronic conditions. These are now responsible for around 70% of all deaths worldwide and 85% of all deaths in Europe and are associated with an estimated economic loss of $7 trillion between 2011 and 2025. Chronic diseases are characterized in particular by the fact that they require an intervention paradigm that focuses on prevention and lifestyle change. Lifestyle (e.g., diet, physical activity, tobacco or alcohol consumption) can reduce the risk of suffering from a chronic condition or, if already present, can reduce its burden. A corresponding change in lifestyle is, however, only implemented by a fraction of those affected, partly because of missing or inadequate interventions or health literacy, partly due to socio-cultural influences. Individual personal coaching of these individuals is neither scalable nor financially sustainable.

Against this background, the question arises on how to develop evidence-based digital health interventions (DHIs) that allow medical doctors and other caregivers to scale and tailor long-term treatments to individuals in need at sustainable costs. At the intersection of health economics, information systems research, computer science, and behavioural medicine, this lecture has the objective to help students and upcoming healthcare executives interested in the multi-disciplinary field of digital health to better understand the need, design and assessment of DHIs.

After the course, students will be able to...

1. understand the importance of DHIs for the management of chronic conditions
2. understand the anatomy of DHIs
3. know frameworks for the design of DHIs
4. know evaluation criteria for DHIs
5. know technologies for DHIs
6. assess DHIs
7. discuss the advantages and disadvantages of DHIs
InhaltTo reach these learning objectives, the following topics are covered in the lecture and will be discussed based on concrete national and international examples including DHIs from the Center for Digital Health Interventions (Link), a joint initiative of the Department of Management, Technology and Economics at ETH Zurich and the Institute of Technology Management at the University of St.Gallen:

1. Motivation for Digital Health
- The rise of chronic diseases in developed countries
- The discrepancy of acute care and care of chronic diseases
- Lifestyle as medicine and prevention
- From excellence of care in healthcare institutions to excellence of care in everyday life

2. Anatomy of Digital Health Interventions
- Just-in-time adaptive interventions
- Digital biomarker for predicting states of vulnerability
- Digital biomarker for predicting states of receptivity
- Digital coaching and healthcare chatbots

3. Design & Evaluation of Digital Health Interventions
- Overview of design frameworks
- Preparation of DHIs
- Optimization of DHIs
- Evaluation of DHIs
- Implementation of DHIs

4. Digital Health Technologies
- Technologies for telemedicine
- Mobile medical devices
- Virtual, augmented and mixed reality applications incl. live demonstrations
- Privacy and regulatory considerations

The Digital Health lecture is structured in two parts and follows the concept of a hybrid therapy consisting of live sessions and complementary online lessons. In the first part, students will learn and discuss the topics of the four learning modules in weekly online sessions. Complementary learning material (e.g., video and audio clips), multiple-choice questions and exercises are provided online.

In the second part, students work in teams and will use their knowledge from the first part of the lecture to critically assess DHIs. Each team will then present and discuss the findings of the assessment with their fellow students who will provide peer-reviews. Additional online coaching sessions are offered to support the teams with the preparation of their presentations.
Literatur1. Cohen, A.B., Dorsey, E.R., Mathews, S.C. et al. (2020) A digital health industry cohort across the health continuum Nature Digital Medicine 3(68)
2. Collins, LM (2018) Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST) New York: Springer.
3. Corneta, VP, and Holden, RJ (2018) Systematic Review of Smartphone-Based Passive Sensing for Health and Wellbeing Journal of Biomedical Informatics (77:January), 120-132.
4. Coravos, A., Khozin, S., and K. D. Mandl (2019) Developing and Adopting Safe and Effective Digital Biomarkers to Improve Patient Outcomes Nature Digital Medicine 2 Paper 14.
5. Katz, D. L., E. P. Frates, J. P. Bonnet, S. K. Gupta, E. Vartiainen and R. H. Carmona (2018) Lifestyle as Medicine: The Case for a True Health Initiative American Journal of Health Promotion 32(6), 1452-1458.
6. Kvedar, JC, Fogel AL, Elenko E and Zohar D (2016) Digital medicine’s march on chronic disease Nature Biotechnology 34(3), 239-246
7. Kowatsch, T., L. Otto, S. Harperink, A. Cotti and H. Schlieter (2019) A Design and Evaluation Framework for Digital Health Interventions it ‐ Information Technology 61(5‐6), 253‐263.
8. Mathews, SC, McShea, MJ, Hanley, CL et al. (2019) Digital health: a path to validation. npj Digital Medicine 2(38)
9. Nahum-Shani, I, Smith SN, Spring BJ, Collins LM, Witkiewitz K, Tewari A and Murphy SA (2018) Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support Annals of Behavioral Medicine 52 (6), 446-462.
10. Powell AC, Torous JB, Firth J, Kaufman KR (2020) Generating value with mental health apps BJPsych Open 6(2):e16. Published 2020 Feb 5. doi:10.1192/bjo.2019.98
11. Safavi K, Mathews SC, Bates DW, Dorsey ER, Cohen AB (2019) Top-Funded Digital Health Companies And Their Impact On High-Burden, High-Cost Conditions Health Affairs 38(1):115-12
363-0552-00LEconomic Growth and Resource UseW3 KP2GC. Karydas
KurzbeschreibungThe course deals with the factors that contribute to economic development. Throughout the course theoretical economic modelling will be used to discuss the effects of factors – such as land, human/physical capital, technology, fossil energy resources, and climate change – on economic growth and to draw conclusions for the future.
LernzielThe general objective of the course is to provide students tools and intuition to:

i) think in a structured way – though economic modelling – about the factors that have lead to the different growth experiences among countries, and still shape our contemporary situation;
ii) assess and design policies on the basis of economic development;
iii) draw conclusions for the future of economic development, that take into account prevalent issues such as the scarcity of fossil energy resources and climate change.
InhaltWhy is economic growth worth studying? Which are the factors behind economic growth? What is the role of natural resources in shaping economic development? Is our finite planet able to support sustainable long-term economic growth? Economics aims at explaining human behaviour; how do we model it and how can we steer it for the better? How do you design an efficient economic policy for a sustainable future? What is sustainable anyway? These are some of the questions you will learn to answer in this course.

After spending the first lecture on overviewing the course, and the second lecture on building our mathematical and economic foundation, we begin with the three main modules that comprise this course.

The first module – called “Land and Economic Growth” – deals with the historical evolution of the factors behind economic development from the pre-industrial times to our modern growth experiences. By studying the history of economic growth, we understand change and how the society we live in came to be. In this module we will develop economic models that capture the transition from an era of miniscule economic growth that persisted for millennia before the industrial revolution – with land and human labour as the main inputs to economic activity, to our modern growth experience where the continuous improvement in technology and services is our status quo.

The second module – called “Non-Renewable Resources and Growth” – deals with the problem of optimal exploitation of non-renewable resources, as well as with the issue of “Resource Curse” – i.e., the observed negative relationship between economic development and resource abundance. Emerging in the 1970s due to two oil crises, the problem of the economy’s extreme dependence on fossil and depletable energy resources sparked a great deal of research to guide our way forward. Some important questions we will formally answer in this module are the following. How do we optimally exploit a given stock of a non-renewable resource? What affects the prices of non-renewable resources? If fossil energy sources – a (so far) important input to production – are getting ever depleted, is long-term growth possible? How do we explain the “Resource Curse” and what are the policies that allow a sustainable future in countries that suffer from such a curse?

The third module – called “Climate Change and Growth” – deals with the pressing problem of our changing climate. Greenhouse gas emissions – so far essential for economic activity – accumulate in the atmosphere and alter environmental patterns. This phenomenon – commonly known as climate change – is responsible for the increase in the frequency and the intensity of natural disasters, which damage our stocks of capital and put a drag on economic growth. To derive appropriate policies for a sustainable future, we will incorporate these aspects in workhorse models of the economics and finance literature. Students will learn how to derive and set the “correct” price on the use of polluting energy resources from the perspective of policy-makers. Additionally, pricing of climate change risks for financial markets is important, both for individual investors and central banks, as it is they who provide liquidity to firms to pursue their long-term growth targets. Accordingly, we will close the lecture with the pricing of climate change risks from an investor’s perspective.

After the last lecture of each of the three modules students will be handed out an exercise set which will be submitted by the beginning of the following week’s lecture. That lecture will be an exercise session where we will discuss the solutions in class. Each exercise set will be graded. The average grade from the best two exercise sets will account for 25% of the final grade; the rest 75% will be determined by a written exam.
SkriptLecture Notes of the course will be sent by email to officially subscribed students.
LiteraturThe 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 / BesonderesKnowledge of basic calculus (differentiation - integration) and basic statistics (e.g. what is an expectation; variance-covariance) is considered as a prerequisite. Elementary knowledge of dynamic systems analysis, optimal control theory and economic theory is a plus but not a prerequisite.
363-1125-00LEmpirical Environmental Economics
Findet dieses Semester nicht statt.
W3 KP2G
KurzbeschreibungThe course introduces students to the basics of empirical research in environmental economics. We will discuss various policy instruments and study empirical methods to evaluate the efficacy of key environmental policies in the real world. Students will have opportunities to work with data and replicate important empirical findings in the literature.
LernzielStudents will become familiar and well-versed with (1) an empirically-oriented approach to think about environmental problems and policy instruments, (2) empirical methods widely used to evaluate the effectiveness of environmental policies and (3) be able to discuss the efficacy of key environmental policies in the real world in a critical manner.
InhaltIn the first part of course, students will learn various empirical methods that are commonly used by empirical researchers. Once equipped with technical knowledge, in the second part of the course, we will discuss research papers that empirically identify environmental externalities. Topics include (1) the impact of temperature shocks on economic growth and productivity, (2) health impacts of air pollution, (3) and how environmental factors may affect other economic outcomes such as political stability, migration flows and labor market outcomes.

In the remaining part of the course, we will study environmental regulations designed to address such externalities. We will discuss papers that conduct ex-post empirical evaluations of key regulations around the world. We will see (1) how environmental regulation affects the competitiveness of industry, (2) how effective environmental polices are in inducing energy conservation from consumers, (3) firms' innovation activities in response to regulation, and finally (4) environmental regulation in the developing country context.
SkriptLecture slides will be provided electronically.
LiteraturFor the reading list for the course, please see the syllabus by clicking the link (Link).
Voraussetzungen / BesonderesKnowledge in econometrics is not required; Basic knowledge in economics helps.
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