Doctoral Course Program

Please note:

  • The registration for our doctoral courses is binding.
  • From the course program, all doctoral candidates who entered the list of doctoral candidates after January 1, 2014, have to complete at least four courses in Methods/Theory and one research skills seminar or five courses in Methods/Theory. Each doctoral course has to be on doctoral level and has to be equivalent to 4 ECTS and a minimum of 22.5 hours class time.
  • Doctoral candidates who would like to hand in their doctoral thesis must contact the Graduate Center in time (at least three months in advance) in order to request the approval form before submitting your dissertation to make sure your doctoral course program is completed. Please note that there are different approval forms according to the entry date to the list of doctoral candidates and the membership status in the Graduate School.
  • If not indicated differently, all doctoral courses are taught in English.

Summer Term 2022

  • Dynamic programming is an optimization approach that has been widely applied in operations management. In this course, the students will study the most recent and advanced models in dynamic programming.

     

    SyllabusAdvanced Dynamic Programming

    Registration: self registration in moodle

     

    Lecturer: Prof. Dr. Jingui Xie (TUM)

     

    Course dates: Kick-off April 28, 2022 via Zoom every Thursday morning. Dates could be coordinated with participants.

    If possible, the course will be held in person in TUM Campus Heilbronn; otherwise, via Zoom.

  • This seminar aims at teaching the basics of cognitive neuroscience and how it is applied more or less meaningfully in management and organisational research. We will specifically focus on non-invasive brain stimulation, electroencephalogram, and functional Magnetic Resonance Imaging. Graduate students will be enabled to understand these methods, successfully read respective papers and their method section, and to assess the potential as well as the pitfalls of neuroscientific methods in their fields of research.

     

    SyllabusBasic Neuroscience for Organisational Research and Economics

     

    Registration: e-mail to franziska.emmerling@tum.de

     

    Lecturer: Dr. Franziska Emmerling (TUM)

     

    Course dates: The seminar will include four sessions (first session a 4.5 hours, three further sessions a 6 hours).
    Session I: 09.06., 9:30-12:00 & 13:00-15:00, digital
    Session II: 07.09., 9:00-12:00 & 13:00-16:00, digital
    Session III: 08.09., 9:00-12:00 & 13:00-16:00, digital
    Session IV: 09.09., 9:00-12:00 & 13:00-16:00, digital

  • The advantages of a Bayesian approach to data analysis have been known for a long time (e.g., Edwards, Lindman, & Savage, 1963). Recent developments in computer science have made the practical application of these approaches accessible. Bayesian methods avoid many of the problems of frequentist methods—such as not being able to confirm the null hypothesis or that p-values depend on the goals during participant recruitment (e.g., Wagenmakers et al., 2017; Kruschke, 2014). In addition, Bayesian statistics is more intuitive than frequentist statistics, in that it evaluates a hypothesis given the data rather than the other way round. Bayesian approaches are therefore likely to eventually replace frequentist approaches in data analysis. The goal of this course is to introduce students to the logic and practice of Bayesian statistics as well as to provide an introduction to cognitive modeling.

     

    SyllabusBayesian data analysis and cognitive modeling

     

    Registration: e-mail to pachur@tum.de

     

    Lecturer: Prof. Dr. phil. Thorsten Pachur (TUM)

     

    Course dates: September 20 - 22, 2022; 9:00 am - 6:00 pm; Room: tbd

  • The course … (1) makes participants familiar with the problem of collecting massive data from Internet sources, (2) guides participants to evaluate the costs and benefits of automating data collection, (3) introduces participants to the structure of web sites, (4) reviews the most effective approaches for collecting data from web sources, (5) provides hands-on implementations using Python, and (6) outlines ethical and legal considerations.

     

    SyllabusCollecting Massive Internet Data

     

    Registration: Please send an email to Office.cdt@wi.tum.de with a registration request that includes your name (see below). Registration deadline: April 15, 2022.

     

    Lecturer: Prof. Dr. Jens Förderer (TUM)

     

    Course dates: Course will be held online via Zoom. Login details will be distributed after registration.
    04.08.2022, 09:00-18:00: Day 1
    05.08.2022, 09:00-18:00: Day 2
    19.08.2022: Q&A (9:00-13.30)

  • Econometric analysis aims at uncovering economic mechanisms, their causes and effects. Understanding the mechanisms behind a phenomenon is indispensable if one is to give advice to managers or policy makers, or to build theory. Simple regressions on cross-sectional data show associations, but not causality, so we need more sophisticated methods. This course shall convey econometric methods that allow causal inference, or at least to come closer to uncovering causal effects. The focus will be on applicable knowledge, less on details of the theory. The course is part of a series of econometrics courses at TUM School of Management that also comprises “Econometrics I: Research Design and Estimation Methods” by Professor Hottenrott and “Econometrics III: Advanced Econometrics and Machine Learning” by Professor Farbmacher.

    Topics comprise various methods to address selection issues and come close to causality:

    Randomized controlled trials and natural experiments Matching Regression discontinuity design Instrumental variables Panel data Differences-in-Differences Heckman selection models

     

    SyllabusEconometrics II: Causal Inference

     

    Registration: Until April 20, 2022, via Moodle.

     

    Lecturer: Prof. Dr. Joachim Henkel (TUM)

     

    Course dates: Kick-off Friday April 29, 2022, 2:00 pm – 4:30 pm in person (room will be announced). The course will be taught as a series of seven half-day seminars in June and July, either in the morning or on the afternoon. Dates will be coordinated with participants. The course is planned to be held in person.

  • The course covers a selection of state-of-the-art methods in econometrics and machine learning. It aims to provide students with a sound understanding of the methods discussed, such that they are able to do research using modern econometric techniques, as well as critically assess existing studies.

    In particular, the course will cover the following topics:

    Regression Shrinkage Methods (Ridge, Lasso, Elastic Net)
    Adaptive Lasso Regression
    Classifier-Lasso Regression
    Double Machine Learning

     

    SyllabusEconometrics III

     

    Registration: tbd

     

    Lecturer: Prof. Dr. Helmut Farbmacher (TUM)

     

    Course dates: March 21 - 25, 2022 (9 am to 4 pm); Z534/Z536

  • This seminar aims at teaching the theoretical and practical basics of eye tracking and how it is applied more or less meaningfully in management and organisational research. Graduate students will be enabled to understand eye tracking, successfully read respective papers and their method section, and to assess the potential as well as the pitfalls of eye tracking in their fields of research. Furthermore, graduate students will be familiarised with the complete research cycle of eye tracking studies (designing/developing, conducting and analysing eye tracking studies).

     

    SyllabusEye Tracking for Organisational Research and Economics

     

    Registration: Please send an e-mail to hannah.kunde@tum.de before September 15, 2022 – including a brief description of your prior experience with eye tracking and your TUM-ID.

     

    Lecturer: Hannah Kunde (TUM) and Dr. Franziska Emmerling (TUM)

     

    Course dates: Most sessions will take place online (the zoom-link will be send to participants before the first course day). Session III will take place in Munich (TUM main campus) – the final room will be announced during the first course days.

    29.09.2022, 9:00-12:00 & 13:00-15:00 (online)
    30.09.2022, 9:00-12:00 & 13:00-16:00 (online)
    06.10. or 07.10.2022, ~ 1 hour per group (online)
    13.10.2022, 9:00-12:00 & 13:00-16:00 (on campus, Munich)
    14.10.2022, 9:00-12:00 & 13:00-16:00 (online)

  • An introduction to basics of intellectual property (IP) and competition law in light of innovation in the global market. Topics covered are: Open and close strategies of useful information; obtaining, licensing and enforcing patents; copyrigth law basics and controversies; trade secrets protection and misapporation; data protection and use of big data; standardization; licensing standard essential patents to supply chains; pharmaaceutical patents; and sustainable IP strategies.

     

    SyllabusInnovation and Law

    Registration: Plese send an email to: sekretariat.jura@tum.de

     

    Lecturer: Prof. Yuko Kimijima (Keio University)

     

    Course dates: Every Monday and Tuesday in July from 9:00 to 12:00 am (July 4, July 5, July 11, July 12, July 18, July 19, July 25, and July 26, 2022)
    Room: 1355

  • This course is for researchers on the doctoral or post-doctoral levels who are beginners in economiclaboratory experiments. It will enable you to decide whether a laboratory experiment is appropriate to address some research question; find research questions in your area of interest that a laboratory experiment can address;
    develop an experimental design to address such a research question.

     

    In addition, the course will offer you hands-on training on how to bring experiments to the laboratory. It will cover common practical issues, such as which software to use, how to recruit participants, or how to conduct an experiment.

     

    The course will be most beneficial for you if you plan to run your own experiment soon. It will be particularly helpful for you if you consider using experimenTUM, TUM’s laboratory for experimental research in economics.

     

    SyllabusIntroduction to Experimental Economics

     

    Registration: Write to Andreas Ostermaier to sign up (ostermaier@sam.sdu.dk). Please state your primary research area and method. Mention also what motivates you to sign up for this course and whether you are planning to run an experiment.

     

    If you have a research question or idea for an experiment that you would like to see as an assignment, remember to include a very brief proposal in your application. If you have any introductory readings, feel free to suggest these, too.

     

    Please make sure you can attend the full course before signing up. From a pedagogical angle and out of fairness toward the other participants, you should not miss any part of the course for any reason, including the supervision of student exams.

     

    Lecturer: Dr. Andreas Ostermaier (University of Southern Denmark)

     

    Course dates: The seminar is scheduled to be held on July 25 – 27, 2022 in room 0505.Z1.534Z (https://portal.mytum.de/displayRoomMap?Z534@0505). If so mandated by TUM’s health and safety requirements, the seminar will be held online.

  • The course covers a selection of state-of-the-art methods in econometrics and machine learning with  applications in health economics. It aims to provide students with a sound understanding of the methods discussed, such that they are able to do research using modern econometric techniques, as well as critically assess existing studies.

     

    In particular, the course will likely cover the following topics:

    • Regression Shrinkage Methods (Ridge, Lasso, Elastic Net)
    • Decision Trees, Random/Causal Forests
    • Advanced Identification Strategies (e.g., Double Machine Learning)
    • Introduction to Neural Networks

     

    In the first meeting, we will discuss the econometric methods and/or machine learning techniques (including some applications to illustrate them). Students will then apply these methods and will replicate recent research papers in health economics. I will assign a (replication) project to each student, which (s)he will present at the second meeting. The presentation (roughly 15 minutes) together with a short report that summarizes the assigned paper (roughly 5 pages w/o figures, tables and references) will be relevant for the grading.

     

    SyllabusMachine Learning in Health Economics

     

    Registration:

     

    Lecturer: Prof. Dr. Helmut Farbmacher (TUM)

     

    Course dates: 1st meeting: August 1-2,2022; 2nd meeting: tba

    The course will be taught in-person.

  • The course (1) provides an overview of the peer-review process in international scientific journals 

    in business (i.e., submission procedures and requirements, editorial decisions, hierarchies), (2) provides guidance regarding how to write constructive reviews (i.e., generic template for a review, review expectancies for different outlets and different publication stages, serving as a discussant), (3) helps students analyzing reviews they received for their papers (i.e., identifying and aggregating received comments etc.), (4) to respond to reviews (i.e., writing a response note). The course provides practical examples from real peer review processes. The course starts with an introductory presentation by the instructor. Then, participants write peer reviews for the papers of other participants. After receiving reviews for their papers, students respond to the received reviews by writing response letters. Students will present their responses to the class.

     

    SyllabusMastering the Review Process: Writing of and Responding to Peer-Reviews

     

    Registration: Please send an email to office.cdt@wi.tum.de with a short registration request that includes your name and the title of your paper. Registration deadline: April 18, 2022.

     

    Formally, each participant requires a written paper draft. This paper will be reviewed by one other course participant. The paper should be a working paper and not be published.

     

    FAQ: Which paper should I submit for the course?

    • You should be interested in developing your paper. This is given if your paper is part of your dissertation, or if you intend to publish it in a scientific journal or in the proceedings of a conference.
    • All types of papers are welcome—including literature reviews, theoretical papers, empirical papers.
    • It is not necessary that your paper is fully completed. Nevertheless, it must be at least 8,000 words long. Empirical papers must at least report some (early) findings.
    • There are no formatting requirements for the working paper.
    • It is not possible to submit your paper after the first course day. This is because your paper will be distributed on the first course day for peer-review.

     

    The course is limited to 15 participants (first come, first served). The course will be offered as part of the International Doctoral Network in Information Systems – IDIS.

     

    Lecturer: Prof. Dr. Jens Förderer (TUM)

     

    Course dates: Course will be held online via Zoom. Login details will be distributed after registration.

    25.04.2022: Course administration, presentation by instructor on writing reviews (13:00-16.00)
    30.05.2022: Q&A, presentation by instructor on responding to reviews (13:00-16.00)
    30.06.2022: Presentation day 1 (9:00-17.30)
    01.07.2022: Presentation day 2 (9.00-17.30)

  • The study of networks has become crucial for the understanding of organization. In this class, we di

    scuss research on social networks and examine how it informs our understanding of organizations – informing a variety of topics such as strategy, innovation, or entrepreneurship.

    The goal of the class is to understand the theory as well as the methods underlying research on social networks.

     

    SyllabusNetworks and Organizations

     

    Registration: Self-registration via Moodle until June 13, 2022. The number of participants is not limited.

     

    Lecturer: Prof. Henning Piezunka, Ph.D. (INSEAD)

     

    Course dates: 20 – 24 June, 2022. The course will be taught in-person unless announced otherwise.

  • The purpose of this course is to give students a grounding in theoretical and empirical research in 

    strategic management research. During an in-class week in June, the focus will be on theoretical foundations of strategy. Moreover, workshops related to developing ideas and navigating the publication process will be provided.

     

    SyllabusSeminar on Strategic Management

     

    Registration: self-registration in Moodle

     

    Maximum number of participants: 15

     

    Lecturer: Professor Jeffrey J. Reuer, PhD (University of Colorado)

     

    Course dates: The course will be held in presence (seminar room 0514):
    06.06.2022: 09:00 – 12.30
    07.06.2022: 09:00 – 12:00 and 14:00 – 17:00
    08.06.2022: 14:00 – 17:00
    09.06.2022: 09:00 – 12:30
    10.06.2022: 09:00 – 12.30 and 14:00 – 17:00

  • The purpose of this course is to give doctoral candidates a grounding in theoretical and empirical r

    esearch in strategic management research. During the online week in July, particular attention will be devoted to empirical research. As this course builds on the content of the PhD Seminar on Strategic Management (I): “Theoretical Foundations of Strategy” which is held in presence in the week from June 6 to June 10, 2022, only students who attended this first course should take part in the second course “Empirical Research in Strategic Management”.

     

    SyllabusSeminar on Strategic Management

     

    Registration: self-registration in Moodle (https://www.moodle.tum.de/course/view.php?id=77170)

     

    Maximum number of participants: 15

     

    Lecturer: Professor Jeffrey J. Reuer, PhD (University of Colorado)

     

    Course dates: The course will be held online (via Zoom):
    04.07.2022: 15:00 – 18.30
    05.07.2022: 15:00 – 18:00 and 18:30 – 21:30
    06.07.2022: 15:00 – 18:00 and 18.30 – 21:30
    07.07.2022: 15:00 – 18:30
    08.07.2022: 15:00 – 18.30

  • Qualitative research has gone through a renaissance in many social sciences over the past two decade

    s. Albeit operating in a mainly quantitative field, agricultural and applied economists have found themselves using qualitative research approaches, especially in dealing with wicked problems, such as sustainability, and small numbers of cases, such as in agribusiness contexts or institutional economics issues. Often perceived as exploratory research, qualitative approaches offer much more than initial data for framing a quantitative project when used in a rigorous and skilled manner. This course provides an introduction to qualitative research paradigm(s), qualitative research methods (e.g., in-depth interviews, (participant) observation, focus group discussions, and action research), issues in qualitative research (e.g., the researcher as the research instrument, reflexivity), qualitative data analysis, and the development of theory based on qualitative (and quantitative) data.

     

    SyllabusQualitative Research and Developing Grounded Theory in Social Sciences

     

    Registration: Registration via the Doctoral Certificate Program in Agricultural Economics. Please register and apply via the program. No costs for participation in the program apply.

     

    Lecturer: Prof. Dr. Vera Bitsch (TUM)

     

    Course dates: 04.-08.07.2022
    Course will be held online via Zoom.

  • What this course is It is a readings course in which we critically discuss recent working papers or 

    What this course is
    It is a readings course in which we critically discuss recent working papers or published papers in empirical financial and sustainability accounting.

    What this course is not
    This course is not an introduction to accounting and/or econometrics. It is not a lecture but an interactive class with controversial discussions.

     

    SyllabusReadings In Empirical Accounting Research

     

    Registration: Please write an e-mail to benedikt.downar@tum.de by April 29, 2022 at the latest.

     

    Lecturer: Prof. Dr. Jürgen Ernstberger (TUM)

     

    Course dates: The kick-off meeting is on May 2, 2022 at 4:00 p.m. This first session provides an overview of important criteria for assessing the quality of empirical accounting research papers. In the following sessions, we discuss overview papers, seminal papers on specific topics, or state-of-the-art papers. Students can make suggestions for suitable papers which are related to their dissertation topics. In the following sessions, we discuss current working papers which are presented in research seminars and we participate in these seminars to learn how to present and discuss a paper.

  • Through reading materials, course discussions, guest lectures, and group work, students will gain in

    sight into the fundamental aspects of private equity investing, the perspective of fund managers and investors, those who transact with such funds, and those who regulate the fund industry. The course will provide a unique South African perspective, especially now that South Africa has adopted a Twin Peaks Regulatory Framework, like Australia and the United Kingdom. The course will start with an introduction to private equity and specifically third-party private equity funds, which represents the dominant organisational form. In addition, the course will discuss private equity in relation to finance, legal practice, tax, types of private equity, fund structuring, latest trends, as well as the key principles of fiduciary law related thereto.

     

    SyllabusThe Fundamentals of Private Equity Funds and Investing

     

    Registration: Plese send an email to: sekretariat.jura@tum.de

     

    Lecturer: Prof. Richard Stevens, LL.M. (University of Stellenbosch)

     

    Course dates: The course consists of a total of 24 hours of direct class interaction, which will be split over six(6) classes of four(4) hours each.

     

    The dates of the six(6) classes will be:

     

    • Lecture 1: June 13, 2022
    • Lecture 2: June 14, 2022
    • Lecture 3: June 15, 2022
    • Lecture 4: July 6, 2022
    • Lecture 5: July 7, 2022
    • Lecture 6: July 8, 2022


    Each class session will be from 9:00 am to 1:00 pm on the above days.

Summer School 2022

  • The goal of the doctoral course Empirical Sustainability Analytics is to promote an openminded discussion forum for all doctoral students who are interested in more details about the techniques and perspectives of providing, using, and processing sustainability data. The focus lies on the managerial and investor evaluation of environmental, societal, and (corporate) governance characteristics (ESG characteristics) and their role as corporate performance and cost drivers. Following completion of the course, the participants are able to successfully analyze empirical research questions in the broad field of corporate sustainability.

     

    Syllabus: Empirical Sustainability Analytics

     

    Registration: The course is limited to 15 participants. If there are more expressions of interests than places available, the participation decisions are assigned by lot.
    Please register via the portal of the TUM School of Management PhD Summer Academy 2022. The registration deadline is July 1, 2022.

     

    Lecturer: Prof. Dr. Michael Stich (TUM)

     

    Course dates: September 12 to 16, 2022; The course will be taught in-person at Campus Heilbronn.

  • This course aims to provide PhD students at the School of Management with a practical introduction to conducting field experiments, with a particular focus on field experiments in economics. Rather than focusing on the (econometric) theory of experiments, we will provide students with hands-on advice on how to solve concrete challenges related to planning, conducting, analyzing, and presenting the results of experimental field studies.

     

    SyllabusField Experiments: Start to finish

     

    Registration: Apply via Email to the instructor until July 1, 2022.

     

    Lecturer: Prof. Philipp Lergetporer, PhD (TUM)

     

    Course dates: September 19 - 23, 2022 (9:00 am to 4:00 pm); The course will be taught in-person at Campus Heilbronn.

  • Doctoral students need to publish their work eventually. In management research, the publication procedure is quite structured with a peer-review process. Experts read and comment on submitted papers during this review process and may demand specific improvements. The editors may invite the submitting authors to revise and resubmit their work. This sequence repeats until a paper eventually converges and is accepted for publication (or rejected). At the end of this course, students will be familiar with the different paths an article can take until submission. The focus of this course is on publishing in journals in the UT Dallas list, essentially a subset of the best Financial Times 50 listed journals. We will also use examples of non-FT-50 listed journals to discuss differences in the process.

     

    Syllabus: Reviewing and Revising

     

    Registration: There is a limit of 15 students maximum for this course. Please use the official procedure for the TUM SoM Ph.D. Summer School. The application deadline is July 1.

     

    Lecturer: Prof. Dr. David Wuttke (TUM)

     

    Course dates: The course takes place in the first week of the TUM SoM Ph.D. Summer School from September 12 to September 16, 2022. We will meet in person each morning/noon. Students will review key concepts in the afternoon sessions, read papers and reviews, and prepare for the next day’s session.

     

  • This is a research-oriented doctoral seminar on the field of information systems. This course shall provide a primer on the core but also most current research questions of interest in the economics of information systems field. This field is concerned with understanding the implications that information technology has for firms’ value creation, market structures, and competition. The references contain a list of exemplary papers from this field.


    The primary goal of this seminar is to familiarize participants with the current topics concerning the management and economics of the digitalization, in particular:
    - Principles of information good (cost of production, bundling, versioning, network effects)
    - Impact of IT on market structures
    - Platforms
    - Privacy
    - Copyright
    - Artificial Intelligence
    - Blockchains
    - Piracy

    To become familiar with these topics, students will be assigned a set of papers to present and evaluate. All participants will discuss the papers. The course starts with an introductory presentation by the instructor. The remainder of the course is based on group work and presentations by the participants.

     

    Syllabus: The Economics of the Digitalization and Information Systems

     

    Registration: There is a limit of 15 students maximum for this course. To apply, please use the official application procedure for the TUM SoM PhD Summer School. The application deadline is July 1, 2022.

     

    Lecturer: Prof. Dr. Jens Förderer (TUM)

     

    Course dates: The course takes place in the second week of the TUM SoM PhD Summer School from September 19 to September 23, 2022. We will meet in person on Campus Heilbronn.