Doctoral Course Program

The course will introduce choice modelling techniques for consumer and marketing analysis. Starting with the theory of consumer choice, the course will discuss different data types available for choice analysis. It will then focus on the specifics of choice experiments, discussing advantages and disadvantages of various experimental designs and data collection procedures. Participants will be familiarized with data handling and analysis considering multinomial logit, random parameters logit, and latent class analysis. To obtain an overview of the literature, participants will present papers from the relevant field.

Syllabus: Applied Choice Analysis

Registration: This course is offered as part of the Promotionskolleg Agrarökonomie. Registration occurs via https://www.agraroekonomik.de/

Lecturer: Prof. Dr. Jutta Roosen (TUM), Dr. Matthias Staudigel (TUM)

Course dates: September 15 – 19, 2025, Mo 13-16, Tu-Th 9-12, 13-16, Fr 9-12

Location: The course is offered in Freising-Weihenstephan. Lecture is in person, attendance required.

This doctoral course aims at giving doctoral students at the School of Management an overview of the essentials quantitative methods. We will not focus on the econometrics, but aim at developing the students’ understanding of what the methods are all about and how they work in practice.

Syllabus: Econometrics I: Research Design and Estimation Methods

Registration: Apply via Email to the instructor until March 20^th 2025.

Lecturer: Prof. Hanna Hottenrott (TUM)

Course dates: 8.4.2025, 9.4.2025 (plus three more days to be announced)

Location: Campus Munich, Seminar room 0505.2566

Knowledge Objectives:

• Doctoral candidates will have a good understanding of academic writing and the structure of the different chapters in a scientific paper.
• Doctoral candidates will know efficient publication strategies

Skills Objectives:

• Doctoral candidates will have improved their skills in research as well as in writing their dissertations or papers.
• Doctoral candidates will have a solid draft of one of their dissertation paper.
• Doctoral candidates will have utilized the processes of revision by positive, constructive peer reviews of the documents by fellow doctoral candidates on their writing and by revising their documents.

Learning Objectives:

• Doctoral candidates will have learned about how to start and finish writing a scientific paper in the context of writing a doctoral thesis.
• Doctoral candidates will have identified standard elements of research papers and used this knowledge to work on their dissertations or papers.

Syllabus: Efficient Academic Writing for Empirical Research

Registration: Please apply until 28th February 2025 to Theresa Treffers, theresa.treffers@tum.de, via email containing:

• Your CV with contact information (email and mobile) and chair of your dissertation
• Dissertation topic (1 sentence)
• Problem statement (3 sentences)
• Data description (3 sentences)
• Target journal (possibly call for papers) and/or conference with deadline

Lecturer: Dr. Fabian Ahrens (TUM), PD Dr. Theresa Treffers (TUM), Prof. Dr. Isabell Welpe (TUM)

Course dates: 14.03.2025, 25.03.2025, 26.03.2025, 01.04.2025, 08.04.2025, 15.04.2025, 22.04.2025, 29.04.2025, 06.05.2025, 13.05.2025, 20.05.2025, 27.05.2025, 03.06.2025, 10.06.2025

Location: Online

South Africa is Africa’s largest economy and probably most developed. It therefore provides an ideal opportunity for various investment forms, including in private equity transactions. Through reading materials, course discussions, and group work, students will gain insight 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 the South African regulatory environment in respect of 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. At the conclusion of the course it will be clear that South Africa provides sufficient opportunities and protection to international funds which may want to invest in South Africa.

Syllabus: Financial Market Regulation in South Africa as Gateway to Investment in Africa: The Fundamentals of Private Equity Funds and Investing in South Africa

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

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

Course dates: The course will commence on Monday 16 June 2025. It consists of a total of 24 hours of direct class interaction, which will be split over six classes. 

Location: Campus Munich (0503.01.355)

The course is aimed at doctoral students. The course is designed to equip doctoral students with foundational knowledge and practical insights into the role of generative artificial intelligence (AI) within social science research, with a particular focus on quantitative marketing research. Based on the current literature body, course participants evaluate and discuss current applications related to generative AI in marketing.

Syllabus: Generative AI for Social Science Research

Registration: Please send an email to contact.dm@mgt.tum.de to register for this course.

Lecturer: Prof. Dr. Jochen Hartmann (TUM)

Course dates:
09/05/2025 09:30 – 13:30 Kick-off
22/05/2025 15:30 – 17:30 GenAI Lab Seminar Series
26/06/2025 15:30 – 17:30 GenAI Lab Seminar Series
10/07/2025 12:30 – 15:30 Paper Discussion
10/07/2025 15:30 – 17:30 GenAI Lab Seminar Series
18/07/2025 09:30 – 17:30 Presentation of Research Ideas

Location: Online (MS Teams)

This course will give doctoral students a broad overview of state-of-the-art technologies and methods (e.g., virtual reality, virtual humans, vocal transformation, AI) used in management research, specifically in leadership and social science related research. At the end of this course, participants will be familiar with the different methods and tools available for conducting research in management and will develop a concrete research project. We will discuss the benefits of using technologies, and the potential technical difficulties and drawbacks that might be encountered along the way, and how to solve them.

In this course, you will learn about existing methods and develop and work on a concrete research project involving an innovative technology. To this end, students will be asked to develop a final presentation showcasing a research project based on the concepts learned in the course.

Syllabus: Innovative Technologies in Management Research

Registration: By email to anely.bekbergenova@tum.de (Dr. Anely Bekbergenova) before August 11th. Participants will be admitted on a first come, first served basis.

Lecturer: Dr. Anely Bekbergenova and Prof. Dr. Claudia Peus (TUM)

Course dates:
Monday, 11.08.2025 – 23:59 – Registration deadline
Tuesday, 09.09.2025 – 9:00 – 17:00 – Presentation by instructor
Wednesday, 10.09.2025 – 9:00 – 17:00 – Presentation by instructor & group/individual work
Tuesday, 16.09.2025 – 9:00 – 17:00 – Presentation by participants & feedback
Tuesday, 23.09.2025 – 23:59 – Research proposal deadline

Location: The course will be held in person at the TUM main campus in Munich (Arcisstr. 21, Building 0505, Room Z577)

This course is for researchers on the doctoral or post-doctoral levels who are beginners in economic laboratory 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.

Syllabus: Introduction to Experimental Economics

Registration: Write to Andreas Ostermaier no later than July 25, 2025 to sign up (andreas.ostermaier@zu.de). 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: Prof. Dr. Andreas Ostermaier (Zeppelin University)

Course dates: The course will extend over three days. The tentative schedule is as follows.

First day:

• Visit to experimenTUM (interactive);
• The ultimatum game (lecture & discussion);
• Standard designs (first assignment, interactive).

Second day:

• Standard designs cont’d (first assignment, interactive);
• Common design choices (lecture & discussion);
• Designing your own experiment (second assignment, interactive).

Third day:

• Designing your own experiment, cont’d (second assignment, interactive);
• Benefits and pitfalls of lab experiments (lecture & discussion);
• Discussion of participants’ projects.

The course will typically at 9 a.m. in the morning and end no later than 5 p.m. in the afternoon. The afternoons of the first and second days are partly reserved for working on your assignments. I will always be around to assist you, commuting between the teams.

Location: Campus Munich

The course is aimed at doctoral candidates with an interest in Econometric Methods. The goal of this course is to introduce the concepts of Influence Functions, Local Robustness/Neyman Orthogonality and Machine Learning. The course will combine both general theory and applications (among others) to

• Two step estimation procedures
• Machine Learning Causal Inference
• Inequality of Opportunity
• Empirical Welfare Maximization

After the course students should be more familiar with how to use Machine Learning in economic applications with desired statistical guarantees.

Syllabus: Local Robustness and Machine Learning

Registration: Until 10th of June by email.

Lecturer: Joël Terschuur

Course dates: June 16-20, 2025 from 10:00-12:00 and 14:00-17:00

Location: Campus Munich

This doctoral course aims at giving doctoral students at the School of Management an overview of the essentials quantitative methods. We will not focus on the econometrics, but aim at developing the students’ understanding of what the methods are all about and how they work in practice.

Syllabus: Econometrics I: Research Design and Estimation Methods

Registration: Apply via Email to the instructor until March 20^th 2025.

Lecturer: Prof. Hanna Hottenrott (TUM)

Course dates: 24.3.2025, 25.3.2025, 26.3.2025, 8.4.2025, 9.4.2025

Location: Campus Munich, Seminar room 0505.2566

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 Prof. Dr. Hanna Hottenrott and “Econometrics II: Causal Inference” by Prof. Dr. Joachim Henkel.

The course covers a selection of state-of-the-art methods in econometrics. 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:

• Generalized Methods of Moments (GMM) Estimation
• Potential Outcomes and Treatment Effects
• Panel Data Estimation
• Regression Shrinkage Methods (Ridge, Lasso, Elastic Net)
• Advanced Identification Strategies (e.g. Double Machine Learning and Causal Forests)

In the morning, we will briefly discuss the econometric methods (including some applications to illustrate them). Students will then apply these methods and will replicate recent research papers in economics.
I will also assign a (replication) project to each student. You can also come up with an own application and/or dataset you are interested in.

Syllabus: Econometrics III: Advanced Econometrics & Statistical Learning (only PhD)

Registration: Until end of February, via email.

Lecturer: Prof. Dr. Helmut Farbmacher (TUM)

Course dates: March 24-28, 2025 (10am to 5pm, room 2544)

Location: Campus Munich

Knowledge Objectives
• Doctoral candidates will have a good understanding of academic writing and the structure of the different chapters in a scientific paper.
• Doctoral candidates will know efficient publication strategies
 

Skills Objectives
• Doctoral candidates will have improved their skills in research as well as in writing their dissertations or papers.
• Doctoral candidates will have a solid draft of one of their dissertation paper.
• Doctoral candidates will have utilized the processes of revision by positive, constructive peer reviews of the documents by fellow doctoral candidates on their writing and by revising their documents.

Learning Objectives
• Doctoral candidates will have learned about how to start and finish writing a scientific paper in the context of writing a dissertation.
• Doctoral candidates will have identified standard elements of research papers and used this knowledge to work on their dissertations or papers.

Syllabus: Efficient Academic Writing for Empirical Research

Registration: Please apply until 30th September 2024 to Theresa Treffers, theresa.treffers@tum.de, via email containing:
• Your CV with contact information and chair of your dissertation
• Dissertation topic (1 sentence)
• Problem statement (3 sentences)
• Data description (3 sentences)
• Target journal (possibly call for papers) and/or conference with deadline

Lecturer: Theresa Treffers

Course dates: 04.10.2024, 24.10.2024, 29.10.2024, 05.11.2024, 12.11.2024, 19.11.2024, 26.11.2024, 03.12.2024, 10.12.2024, 17.12.2024, 07.01.2025, 14.01.2025 and 28.01.2025

Location: Campus Munich and virtual

This course aims to provide doctoral canidates at the School of Management with a practicalintroduction 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.

Syllabus: Field Experiments: Start to Finish

Registration: Please send an email to Prof. Philipp Lergetporer (philipp.lergetporer@tum.de) to register for this course.

Lecturer: Prof. Philipp Lergetporer, PhD

Course dates: Each day (07.10.2024 - 11.10.2024), the lecture starts at 9 am and ends at 4 pm. There will be a lunch break and coffee breaks.

Location: The course will mainly take place at TUM Campus Munich. 

2566 (0505.02.566)

07.10.2024 - 9 am - 5 pm
08.10.2024 - 9 am - 5 pm
09.10.2024 - 2 pm - 5 pm

Z538 (0505.Z1.538Z)

10.10.2024 - 1:30 pm - 5 pm
11.10.2024 - 1:30 pm - 5 pm

The course is aimed at doctoral students. The course is designed to equip doctoral students with foundational knowledge and practical insights into the role of generative artificial intelligence (AI) within social science research, with a particular focus on quantitative marketing research. Based on the current literature body, course participants evaluate and discuss current applications related to generative AI in marketing.

Syllabus: Generative AI for Social Science Research

Registration: Please send an email to contact.dm@mgt.tum.de to register for this course.

Lecturer: Prof. Dr. Jochen Hartmann (TUM)

Course dates: 26.09.2024, 14.11.2024, 12.12.2024, 24.01.2025 and 25.02.2025

Location: Online (MS Teams)

This course will give doctoral students a broad overview of the state-of-the-art technologies and methods (e.g., virtual reality, virtual humans, vocal transformation, AI) used in management research. At the end of this course, participants will be familiar with the different methods and tools available for conducting research, and will develop a concrete research project. We will discuss the benefits of using technologies, and the potential technical difficulties and drawbacks that might be encountered along the way, and how to solve them.

In this course, you will learn about existing methods and develop and work on a concrete research project involving an innovative technology. To this end, students will be asked to develop a final presentation showcasing a research project based on the concepts learned in the course.

Syllabus: Innovative Technologies in Management Research

Registration: By email to anely.bekbergenova@tum.de (Dr. Anely Bekbergenova) before December 16th. Participants will be admitted on a first come, first served basis.

In your email please include (1) your doctoral research topics, (2) a research question you would like to explore using innovative technology (e.g., virtual reality, artificial intelligence, robotics).

Lecturer: Prof. Dr. Claudia Peus (TUM) and Dr. Anely Bekbergenova (TUM)

Course dates: The course will be held in person at the TUM main campus in Munich (Arcisstr. 21, Building 0505, Room Z577)

Monday, 16.12.2024 – 23:59 – Registration deadline
Tuesday, 18.02.2025 – 9:00 – 17:00 – Presentation by instructor
Wednesday, 19.02.2025 – 9:00 – 17:00 – Presentation by instructor & group/individual work
Wednesday, 26.02.2025 – 9:00 – 17:00 – Presentation by participants & feedback
Wednesday, 19.03.2025 – 23:59 – Research proposal deadline5

Location: Z577, Building 0505, TUM Main Campus Munich

The aim of this course is to provide participants with a broad overview of both content and process issues central to entrepreneurship research. The course is interactive in nature and demands participants’ preparation and active engagement during and between class sessions.

Syllabus: Introduction to Entrepreneurship Research

Registration: Please send an email to Prof. Siddharth Vedula (siddharth.vedula@tum.de) before 15 August 2024 to register for this course.

Lecturer: Prof. Siddharth Vedula

Course dates: 16.09.2024 - 25.09.2024, the seminar starts at 9 am and ends at 6 pm. 

Location: The course will take place in the Entrepreneurship Research Institute building in Garching (room TBD).

This course aims to provide scholars with developmental feedback on their current research papers in
the field of management. It aims to improve management research quality by providing quality feedback
and bringing new scholars into the field.

Syllabus: Paper and Proposal Development in Strategic Management: Meet the Editors at HEC Paris

Registration: Please send an email to Prof. Joachim Henkel (henkel@wi.tum.de) or Prof. Chengguang Li (chengguang.li@tum.de) by 7 October 2024 to register for this course. 

Lecturer: Prof. Joachim Henkel and Prof. Chengguang Li

Course dates: 14 October - 12 December 2004

Location: Campus Munich/Campus Heilbronn and/or online/hybrid; HEC Paris

This course gives doctoral candidates an introduction to the psychological theories and concepts that have been most influential for management research and practice. At the end of the course, participants will be familiar with the key concepts, respective empirical findings, and their application to management practice. To this end, each participant will be asked to present in class recent research pertaining to the theory s/he chooses, and to conduct an interactive exercise to facilitate a more comprehensive understanding of the theory’s relevance for management research and practice.

Syllabus: Psychological Theories

Registration: By email to regina.hagl@tum.de (Dr. Regina Hagl) until February 15, 2025. Participants will be admitted on a first come, first served basis.

Lecturer: Prof. Dr. Claudia Peus (TUM) and Dr. Regina Hagl (TUM)

Course dates: 

Monday, 17 February 2025, 9.00 am to 2:00 pm
Monday, 03 March 2025, 9.00 am to 2:30 pm, online (Group Feedback)
Monday, 24 March 2025, 9.00 am to 2:30 pm (Presentation Day 1)
Tuesday, 25 March 2025, 9.00 am to 2:30 pm (Presentation Day 2)
Wednesday, 26 March 2025, 9.00 am to 2:30 pm (Presentation Day 3)

Location: Campus Munich
Course will be held in person at the TUM main campus (Arcisstr. 21, Building 0505, Room Z577).

This course aims to provide scholars with developmental feedback on their current research papers in the field of management. It aims to improve management research quality by providing quality feedback and bringing new scholars into the field.

Syllabus: Readings Empirical Accounting Research

Registration: Please write an e-mail to carolin.gahr@tum.de by October 9th, 2024 at the latest.

Lecturer: Prof. Dr. Jürgen Ernstberger

Course dates: The kick-off meeting is on October 15^th, 2024 at 4 p.m.

Location: Campus Munich/hybrid

The goal of this course is to present and discuss current state-of-the-art research in finance. Therefore, renowned researchers from various European universities will present their latest research in the fields of asset pricing, corporate finance, and financial intermediation. Extensive discussion in class is encouraged. Thereby, students will learn to know and discuss critically current topics in finance. They will also learn more about state-of-the-art research methodologies.

Syllabus: Topics in Finance Research

Registration: Please send an email to aida.cehajic@tum.de by October 10, 2024. In your email, please state your department and specify the topic and state of your dissertation or research area (post-docs).

Lecturer: Dr. Aida Cehajic

Course dates: See https://www.fa.mgt.tum.de/fm/research-seminar/

Location: Campus Munich