Course program

Winter term 2024/2025

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

Summer term 2024

Participants will be assessed based on their seminar presentation (60%), homework assignments (20%), and oral contributions to the course (20%).
- Seminar presentations will be held by groups of two. Each group will present one method of addressing the problem of causal inference (e.g., RDD). The presentation of 120 min to 150 min shall introduce and explain the respective method as well as applications. Presenters will suggest an article in which this method is applied. The group will bring a dataset with which participants will apply the respective method during the course. The lecturer will meet with each group beforehand to aid in the preparation.
- Homework assignment. For some of the methods that we discuss in the course participants will do a homework assignment that consists of applying the method to a dataset, presenting the results, and providing an interpretation (in writing).
- Oral contributions. It is expected that participants prepare the readings for each session and are able to reflect on them. In addition, they shall actively take part in the discussion of the seminar presentations.
The course is pass/fail, not graded. In order to pass the course, participants must take part in all classes. In case of excused absence due to illness they need to hand in a written assignment about the content of the class they have missed.

Syllabus: Econometrics II: Causal Inference

Registration: Until April 17, 2024, via Moodle.

Lecturer: Prof. Dr. Joachim Henkel (TUM)

Course dates: Kick-off Friday April 19, 2024, 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.

Location: Campus Munich - The course is planned to be held in person (room will be announced).
The course aims to highlight three(3) key areas of private equity investing, namely:

1. The formation and structure of private equity funds and the key characteristics related thereto within the South African regulatory environment;
2. The importance of corporate governance and fiduciary law as it pertains to the private equity business model; and
3. Current trends and policy considerations that impacts private equity industry.

At the end of the module students should be able to understand the South African Financial Regulation environment and also where private equity fits into this system. Students should also be able to understand which legal forms are ideal to structure funds as well as the duties on fund managers in South Africa.

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

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

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

Course dates:

- The course will commence on Tuesday 11 June 2024.
- The course consists of a total of 24 hours of direct class interaction, which will be split over six (6) classes.
- The dates of the six(6) classes will be:
- Lecture 1: 11 June 2024 (9h00 – 13h00)
- Lecture 2: 12 June 2024 (9h00 – 13h00)
- Lecture 3: 13 June 2024 (9h00 – 13h00)
- Lecture 4: 2 July 2024 (9h00 – 13h00)
- Lecture 5: 3 July 2024 (9h00 – 13h00)
- Lecture 6: 4 July 2024 (9h00 – 13h00)
Location: Campus Munich (0503.01.355) - The course is planned to be held in person.
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. 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 have the opportunity to not only to develop an understanding of existing methods, but also to develop and work on a concrete research project involving an innovative technology. To this end, students will be asked to develop a short research proposal and a final presentation showcasing their work on the project.

Syllabus: Innovative Technologies in Management Research

Registration: By email to anely.bekbergenova@tum.de (Dr. Anely Bekbergenova) until April 1st. Participants will be admitted on a first come, first served basis.
In your email please include (1) your doctoral research topics, (2) a potential research question you would like to explore using innovative technology.

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

Course dates:

Monday, 01.04.2024 – 23:59 – Registration deadline
Wednesday, 10.04.2024 – 9:00 – 17:00 – Presentation by instructor
Thursday, 10.04.2024 – 9:00 – 17:00 – Presentation by instructor & group/individual work
Wednesday, 17.04.2024 – 9:00 – 17:00 - Presentation Day by participants & feedback
Wednesday, 1.05.2024 – 23:59 – Research proposal deadline

Location: Campus Munich - 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 19, 2024 to sign up (ostermaier@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 22–24, 2024 in room 0505.03.539 (https://portal.mytum.de/displayRoomMap?3539@0505).

Location: Campus Munich - The course is planned to be held in person.
The course is offered for doctoral candidates and post-docs at TUM, who conduct research in the field of business, economics, psychology, political science, sociology, or adjacent fields. Participants of other universities can be accepted for the course if capacity permits.

Each participant requires a working paper for participation, which will be peer-reviewed by another course participant.

Syllabus: Mastering the Review Process: Writing and Responding to Peer-Reviews

Registration: Application deadline: April 3, 2024
- Please send an e-mail to the above email address with a registration request that (1) includes your name, (2) the title of your paper (see Assessment), and (3) your TUM-eMail-Address.
- No late enrollment: Registration after the deadline is not possible.
Lecturer: Prof. Dr. Jens Förderer (TUM)

Course dates:

03.04.2024, 23:59:59: Registration deadline
10.04.2024, 09:00-16:00: Presentation by instructor
23.05.2024, 09:00-16:30: Presentation day 1
24.05.2024, 09:00-16:30: Presentation day 2

Location: Course will be held online-only via Zoom. Login details will be distributed after registration.
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 July 8, 2024. Participants will be admitted on a first come, first served basis.

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

Course dates:

Tuesday, 9 July 2024, 9.00 am to 5.00 pm
Tuesday, 23 July 2024, 9.00 am to 1 pm, online (Group Feedback)
Thursday, 1 August 2024, 9.00 am to 5.00 pm (Presentation Day 1)
Wednesday, 31 July 2024, 9.00 am to 5.00 pm (Presentation Day 2)

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

A structured introduction to learning methodological approaches for successful research in stochastic models and data-driven optimization in logistics and supply chain management at the beginning of the PhD program.

What this course is not

A listen and repeat lecture.

Syllabus: Research on Stochastic Modeling and Data-driven Optimization

Registration: Apply until March 31, 2024 by sending an email to: stefan.minner@tum.de.

Lecturer: Prof. Dr. Stefan Minner(TUM)

Course dates:

Kickoff-Meeting on April 15, 2-4 pm in room 1577.

Weekly sessions (April 15 - July 15) on Mondays, 2-4 pm in room 1577

Location: Campus Munich - The course is planned to be held in person.
This course has three goals: (1) it will help doctoral candidates develop a better understanding of how managers make decisions; (2) it will provide them with conceptual tools to navigate their own professional careers; and (3) it will introduce them to a fascinating field of research in which much is left to be explored and discovered.

Syllabus: Smart Management

Registration: By email to tomas.lejarraga@uib.eu until June 15, 2024. Participants will be admitted on a first come, first served basis.

Lecturer: Prof. Dr. Tomás Lejarraga (Universitat de les Illes Balears)

Course dates: The course will be held in person at the TUM main campus in Munich between June 18 to 20.

Location: TUM main campus in Munich
This course will build upon the earlier course of “Theoretical Foundations in Strategy.” In this class, we will go deeper into the theories we covered and give particular attention to empirical design issues and the development and testing of hypotheses. We will begin by examining the implications of firm heterogeneity for empirical research as well as the implications of “fit” (e.g., between organizations and their environments, between organizational forms and attributes of transactions, etc.) for empirical testing. We will also focus on firm survival and exit, and in later sessions cover modeling choices suitable for testing the theories we have covered in the first course. As part of our sessions, we will consider some award-winning strategy dissertations so you can identify what makes for a good dissertation. We will also have a workshop on developing your own research ideas based on what we are learning in the course.

Syllabus: Strategic Management (II): Empirical Research in Strategic Management

Registration: Please register for the course via self-registration in Moodle (https://www.moodle.tum.de/course/view.php?id=98016)

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

Course dates:

Empirical Research in Strategic Management (week of July 1, 2024; Zoom Login details tba).
1. Firm Heterogeneity and Fit (Monday, 13:00-16:30)
2. Survival and Exit (Tuesday, 13:00-16:00 and 16:30-18:30)
3. Transaction Cost Economics (Wednesday, 13:00-16:30 and 17:00-19:00)
4. Information Economics (Thursday, 13:00-16:30)
5. Implications of Strategic Decisions (Friday, 13:00-16:30)

Location: Course will be held online-only via Zoom. Login details will be distributed after registration.
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 methodological considerations.

Syllabus: Web Scraping for Scientists: An Introduction with Python

Registration: Registration deadline: 03.04.2024

Please send an email to the above stated address with a registration request that includes your name (see below) and your TUM eMail-address. Please do not sign up using your private email address. No registration is possible after the deadline.

Lecturer: Prof. Dr. Jens Förderer (TUM)

Course dates:

03.04.2024, 23:59:59: Registration Deadline
11.04.2024, 09:00-17:30: Day 1 (Fundamentals, HTML, Crawling, Fetching, Parsing)
12.04.2024, 09:00-17:30: Day 2 (Advanced Scraping, Methodological and Ethical Issues)
17.04.2024, 11:00-15:00: Q&A (Questions by Participants, Individual Consultation)
26.04.2024, 23:59:59: Submission Deadline for the Group Exercise

Location: Course will be held online-only via Zoom. Login details will be distributed after registration.

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Doctoral Course Program

Summer term 2025

Efficient Academic Writing for Empirical Research

Generative AI for Social Science Research

Winter term 2024/2025

Econometrics I: Research Design and Estimation Methods

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

Efficient Academic Writing for Empirical Research

Field Experiments: Start to finish

Generative AI for Social Science Research

Innovative Technologies in Management Research

Introduction to Entrepreneurship Research

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

Psychological Theories

Readings Empirical Accounting Research

Topics in Finance Research

Summer term 2024

Econometrics II: Causal Inference

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

Innovative Technologies in Management Research

Introduction to Experimental Economics

Mastering the Review Process: Writing and Responding to Peer-Reviews

Psychological Theories

Research on Stochastic Modeling and Data-driven Optimization

Smart Management

Strategic Management (II): Empirical Research in Strategic Management

Web Scraping for Scientists: An Introduction with Python