Doctoral Course Program

Find all doctoral courses of the Graduate Center of TUM School of Management as well as further information on doctoral course requirements in general and the process of recognizing courses from other institutions here.

  • All doctoral candidates who entered the list of doctoral candidates after January 1, 2014, have to successfully complete 10 SWS (weekly semester hours) of doctoral courses in methods and/or theory of their field. Courses offered by the Graduate Center of TUM School of Management are on doctoral level, comprise at least 2 SWS (21 hours class time) and minimum 3 ECTS workload per course. As a result, all doctoral candidates have to complete at least 5 courses.
    The recognition of external courses that do not differ significantly from those of the Graduate Center of Management with regard to the level of competence and workload is possible upon application to the Graduate Center. If you plan to take an external course, please make sure to contact us well in advance.
  • The registration for our doctoral courses is binding. Please deregister if you are unable to participate after all.
  • If not indicated differently, all doctoral courses are taught in English.
  • After successful completion of a course, please enter the course and all necessary details in DocGS.
  • If you have any suggestions for the course program of the Graduate Center of the TUM School of Management, we would be pleased to receive an email from you.

Doctoral Summer School 2023
at TUM Campus Heilbronn

TUM School of Management invites you to the second Doctoral Summer School at TUM Campus Heilbronn from September 18-29, 2023.

 

Week 1 (Sept 18 - Sept 22, 2023)

Course 1: Prof. Dr. Christoph Ann: Technology protection for Doctoral candidates Canceled due to illness.

Course 2: Prof. Dr. Paul Momtaz: Blockchain Technology and Digital Assets

 

Week 2 (Sept 25 - Sept 29, 2023)

Course 3: Prof. Dr. Jochen Hartmann: Machine Learning Lab

Course 4: Prof. Fehmi Tanrisever (Bilkent University): Emerging Topics in Operations Management

 

For more information please read this digital flyer. Please read it thoroughly before registering for the Doctoral Summer School.

 

Registration period ended and applicants received acceptance by email. Places will be distributed on a first come - first served basis. Registration is only possible for doctoral candidates of TUM School of Management.

Winter term 2023 / 2024

  • 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.

    The target audience are doctoral candidates and post-docs in finance. A requisite for participation is a specialization in finance and/or accounting.

     

    Syllabus: Advanced Topics in Finance Research (Methods/Theory)

     

    Registration: Please send an email to aida.cehajic@tum.de by October 10, 2023. In your email, please state your department and specify the topic and state of your dissertation or research area (post-docs).
    Strict preference will be given to individuals with a specialization in finance and/or accounting.

     

    Lecturer: Dr. Aida Cehajic (TUM)

     

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

     

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

     

  • The goal of the seminar is to foster a vibrant academic environment where doctoral candidates engage in stimulating discussions with peers and senior researchers (professors) that would help advancing their research. Focused on the advances in energy economics, the seminar is designed for doctoral candidates and postdoctoral researchers with an interest in related fields..

     

    Syllabus: Advances in Energy Economics

     

    Registration: To register for the course please email cem@wi.tum.de by Sep 15th, 2023. Spaces limited to 10 participants.

     

    Lecturer: Prof. Svetlana Ikonnikova (TUM) & Prof. Sebastian Schwennen (TUM)

     

    Course dates: From Oct 15 2023 to Mar 2024 (14 sessions, 2 SWS)

     

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

  • This course is designed to help (in particular) junior scholars in the field of management gain exposure and experience with techniques on the written communication of academic work, specifically, how to write interesting and important introductions. The course requires reading and the discussion of readings, but it is fundamentally a “learning-by-doing” course. I hope to have you undergo an iterative process where you a) communicate your research, b) receive feedback, c) revise your communication, and then cycle through this process again in your own journey. The goal of this course is to start you on the path of being a great communicator of your research and increase the odds of publishing in a top journal. Here, top journal implies primarily the “Top 6” (AMJ, AMR, ASQ, ManSci, OrgSci, SMJ), the leading journals in other disciplines (e.g., AJS, ASR, MISQ, Nature, Science…), and also, though to a lesser degree, top field journals that are often part of the “FT 50” – a list of 50 strong management journals listed by the Financial Times. The central question for publishing in these top journals is, usually, how can I make a “theoretical contribution?” Therefore, this course aims to help you clarify your core ideas and craft the introduction so that you articulate the contribution.

     

    Syllabus: Communicating Management Research: (Re)writing Introductions

     

    Registration: Please sign up for the course via email to amy.zhaoding@tum.de by January 8, 2024, with your up-to-date academic resume and a paragraph introducing your research interest and stage of the paper we will discuss during the course. Also email me if you have any questions regarding the course.

     

    Lecturer: Prof. Amy Zhao-Ding, Ph.D. (TUM)

     

    Course dates:

    All courses take place online (changes subject to the number of students enrolled). Below are the dates and topics for the sessions, please see “Course Outline” for details on each session’s content and required preparations.

    middle of January - What makes good theory? The clarification of ideas
    tba - How to make a contribution? The craft of introduction: I
    tba - How to make a contribution? The craft of introduction: II

     

    Location: online

  • 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 December 20th 2023.

     

    Lecturer: Prof. Hanna Hottenrott (TUM)

     

    Course dates: 09.01.2024, 10.01.2024, 11.01.2024, 17.01.2024 and 18.01.2024

    The first session in a day will start at approx. 9am and last to about noon, after a short lunch break it will continue from about 1pm to 2:30pm. The second session in a day will last from 2:45pm to about 4pm.

     

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

  • 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

     

    Registration: Until end of February, via email.

     

    Lecturer: Prof. Dr. Helmut Farbmacher (TUM)

     

    Course dates: March 11-15, 2024 (10am to 5pm, room 2544)

     

    Location: The course will mainly take place at TUM Campus Munich (room 2544).

  • This course aims to provide doctoral canidates at the School of Management with a practical introduction to conducting field experiments, with a particular focus on field experiments in economics.

     

    Syllabus: Field Experiments: Start to Finish

     

    Registration: Doctoral candidates send an email to Prof. Lergetporer philipp.lergetporer@tum.de 

     

    Lecturer: Prof. Philipp Lergetporer, PhD

     

    Course dates: Each day (09.10.2023-13.10.2023), 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 Heilbronn.

  • 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.


    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 you 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, and empirical papers.
    • It is not necessary to submit a fully complete paper. Nevertheless, it must be at least 5,000 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.

     

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

     

    Registration: Application deadline: October 6, 2023

    • 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: Course will be held online-only via Zoom. Login details will be distributed after registration.
    06.10.2023, 23:59:59: Registration deadline
    12.10.2023, 09:00-16:00: Presentation by instructor
    30.11.2023, 09:00-16:30: Presentation day 1
    01.12.2023, 09:00-16:30: Presentation day 2

     

    Location: The course will take place online.

  • This course gives doctoral students 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 martin.fladerer@tum.de (Dr. Martin Fladerer) until December 1, 2023. Participants will be admitted on a first come, first served basis.

     

    Lecturer: Prof. Dr. Claudia Peus (TUM) and Dr. Martin Fladerer (TUM)

     

    Course dates: Course will be held in person at the TUM main campus in Munich (Arcisstr. 21, Building 0505, Room Z577) – except for the Group Feedback, which is online.

    Friday, 15 December 2023, 9.00 am to 5.00 pm

    Friday, 9 February 2024, 1.00 pm to 5.00 pm, online (Group Feedback)

    Thursday, 22 February 2024, 9.00 am to 5.00 pm (Presentation Day 1)

    Friday, 23 February 2024, 9.00 am to 5.00 pm (Presentation Day 2)

     

    Location: Campus Munich, room Z577

  • Doctoral candidates in accounting will be familiarized with recent research in empirical financial and sustainability accounting.

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

     

    Syllabus: Readings in Empirical Accounting Research

     

    Registration: Please write an e-mail to Mario.keiling@tum.de by October 9th, 2023 at the latest.

     

    Lecturer: Prof. Dr. Jürgen Ernstberger (TUM)

     

    Course dates: The kick-off meeting is on October, 17th at 4 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.

     

    Location: Campus Munich, room 3546 + excursions

  • This seminar is open for all doctoral candidates at TUM School of Management who are interested in learning more about how to read, analyze, comprehend, and evaluate published studies systematically.

     

    Syllabus: Seminal Research in Operations and Supply Chain Management

     

    Registration: Please write an email to michela.carraro@tum.de until 15 October

     

    Lecturer: Michela Carraro (TUM)

     

    Course dates: The course will be held hybrid. The preliminary course dates for the WS 23/24 are

    Thursday, 26 October 2023, 9.00 am to 6.00 pm
    Thursday, 2 November 2023, 9.00 am to 6.00 pm
    Thursday, 9 November 2023, 9.00 am to 6.00 pm
    Thursday, 16 November 2023, 9.00 am to 6.00 pm
    Thursday, 23 November 2023, 9.00 am to 6.00 pm
    Thursday, 30 November 2023, 9.00 am to 6.00 pm
    Thursday, 7 December 2023, 9.00 am to 6.00 pm

  • The course is offered for doctoral candidates and post-docs at TUM. Participants of any research field are welcome.


    Participants of other universities are accepted only if capacity permits.
     

    Syllabus: Web Scraping for Scientists: An Introduction with Python

     

    Registration: 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.

    Registration deadline: 12.10.2023

     

    Lecturer: Prof. Dr. Jens Förderer (TUM)

     

    Course dates: Course will be held online-only via Zoom. Login details will be distributed after registration.
    12.10.2023, 23:59:59: Registration Deadline
    19.10.2023, 09:00-17:00: Day 1 (Fundamentals, HTML, Crawling, Fetching, Parsing)
    20.10.2023, 09:00-17:00: Day 2 (Advanced Scraping, Methodological and Ethical Issues)
    27.10.2023, 09:00-14:00: Q&A (Questions by Participants, Individual Consultation)
    09.11.2023, 23:59:59: Submission Deadline for the Group Exercise

     

    Location: The course will take place online.

  • Doctoral candidates and post-docs in business/management with particular interest in Sustainable Finance including ESG investing, green finance, and impact investing.

     

    Syllabus: Workshop on Current Research Trends in Sustainable Finance

     

    Registration: Doctoral candidates and post-docs may apply using a registration form 

    Registration will open on 1 July 2023.
    Deadline for registration is the 15 September 2023.


    The course is limited to 12 participants (first come, first served).

     

    Lecturer: Prof. Dr. Sebastian Müller (TUM) & Dr. Karoline Bax (TUM)

     

    Course dates: The presentation day will take place via Zoom approximately two weeks after the workshop. Login details will be  distributed after registration.

    The schedule of the 15 November 2023:

    9.30-10.00 Opening and administration
    10.00-11.30 Literature review part 1
    11.30-13.00 Literature review part 2
    13.30-16.30 Empirical analysis of prominent issues in sustainable finance
    16.30-18.00 Presentation of results and possible discussion on future research directions

    The schedule of the 16 -17 November 2023:
    09.00 – 17.30 Presentations and Panel Discussions

     

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

Summer Term 2023

  • The course covers basic and advanced panel data estimation methods and related topics like difference in-difference or synthetic control methods.

    In particular, the course will cover the following topics:
    • Static Panel Data Methods (FE vs RE, Inference, Time Effects)
    • Dynamic Panel Data Methods (GMM Estimation, Nickell Bias, Bias-Correction)
    • Large-T Panels
    • Difference-in-Difference and Synthetic Control Methods

     

    Syllabus: Advanced Panel Data Econometrics

     

    Registration: Until March 20, 2023, via email to farbmacher@tum.de

     

    Lecturer: Prof. Arturas Juodis (University of Amsterdam)

     

    Course dates: March 27-30, 2023 (in person) (9am to 4pm, room tba)

     

    Location: Campus Munich - March 27: 2566 (building 0505) and March 28-30: Z534/Z536 (building 0505)

  • The course will introduce doctoral students to 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 different 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: Students are asked to register via the Doctoral Certificate Program in Agricultural Economics (https://www.agraroekonomik.de/registration.html).

     

    Lecturer: Prof. Jutta Roosen, Corinna Hempel, Malte Oehlmann (TUM)

     

    Course dates:

    July 3, 2023, 14-17 hours
    July 4-July 6, 2023, 9-12 hours and 13-16 hours
    July 7, 2023, 9-12 hours

     

    Location: Campus Weihenstephan

  • 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.

     

    Syllabus: Bayesian data analysis and cognitive modeling

     

    Registration: Please apply to Prof. Pachur directly via email: pachur@tum.de.

     

    Lecturer: Prof. Dr. Thorsten Pachur (TUM)

     

    Course dates: 5.-7. September 2023, 9am - 6pm

     

    Location: Campus Munich - Room tbd

  • 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.

     

    Syllabus: Basic Neuroscience for Organisational Research and Economics

     

    Registration: e-mail to leidy.cubillos-pinilla@tum.de

     

    Lecturer: Dr. Leidy Y. Cubillos Pinilla (TUM)

     

    Course dates:

    Session I: 31.07., 9:30-12:00 & 13:00-15:00, Seminarraum Z577, TUM School of Management. Corner Luissenstraße and Arcisstraße, Arcisstraße 21, 80333 München
    Session II: 07.08., 9:00-12:00 & 13:00-16:00, Seminarraum Z577, TUM School of Management. Corner Luissenstraße and Arcisstraße, Arcisstraße 21, 80333 München
    Session III: 08.08., 9:00-12:00 & 13:00-16:00, Seminarraum Z577, TUM School of Management. Corner Luissenstraße and Arcisstraße, Arcisstraße 21, 80333 München
    Session IV: 14.08., 9:00-12:00 & 13:00-16:00, Seminarraum Z577, TUM School of Management. Corner Luissenstraße and Arcisstraße, Arcisstraße 21, 80333 München

     

    Location: Campus Munich - Z577 (building 0505)

  • This course offers an introduction into causal inference with directed acyclic graphs (DAGs). DAGs combine mathematical graph theory with statistical probability concepts and provide a powerful approach for causal modeling. Originally developed in the computer science and artificial intelligence field, they recently gained increasing traction also in other scientific disciplines (such as economics, political science, sociology, health sciences, and philosophy). DAGs allow to check the validity of causal statements based on intuitive graphical criteria, that do not require algebra. In addition, they open the possibility to completely automatize the causal inference task with the help of special identification algorithms. As an encompassing framework for causal reasoning, DAGs are becoming an essential tool for everyone interested in data science and machine learning.

     

    Syllabus: Causal Inference and Data Fusion in Management and Economics Research

     

    Registration: Please register for the course directly with the instructor via email.

     

    Lecturer: Prof. Dr. Paul Hünermund (Copenhagen Business School)

     

    Course dates: The course consists of a total of ten sessions with two sessions daily and a lunch break in-between, as well as a coffee break during the periods that take place in the afternoon. April 24-28, 2023 (10am to 4pm)

     

    Location: Campus Munich - Room tba.

  • 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:
    1. Randomized controlled trials and natural experiments
    2. Matching
    3. Regression discontinuity design
    4. Instrumental variables
    5. Panel data
    6. Differences-in-Differences
    7. Heckman selection models

     

    Syllabus: Econometrics II: Causal Inference

     

    Registration: Until April 19, 2023, via Moodle.

     

    Lecturer: Prof. Dr. Joachim Henkel (TUM)

     

    Course dates: Kick-off Friday April 21, 2023, 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 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, “Econometrics II: Causal Inference” by Prof. Dr. Joachim Henkel and “Econometrics III: Advanced Econometrics” by me. Econometrics IV will be a block lecture but conceptualized as a seminar based on student presentations. 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 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 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 IV: Machine Learning

     

    Registration: Until September 11, 2023, via email.

     

    Lecturer: Prof. Dr. Helmut Farbmacher (TUM)

     

    Course dates: September 18-22, 2023 (10am to 4pm, room 2544)

     

    Location: Campus Munich - The course is planned to be held in person (room will be announced).

  • In this course, students will learn about interesting research in the three areas of empirical corporate finance. The intention is to devote each meeting to a different topic by covering several related papers. The goal is to not only understand the results of the paper but also the methodology and the way how the paper arrived at the result. Both the instructor and the students will present research papers in the class, which will then be critically discussed. Thus, this course is highly interactive, so students are expected to actively participate in classes.

     

    Syllabus: Empirical Corporate Finance

     

    Registration: Please register for the course by sending an e-mail to lisa.knauer@tum.de until May 14, 2023, at the latest.

     

    Lecturer:  Prof. Thomas Schmid (HKU)

     

    Course dates:

    • Mo, 22.05.2023, 14 bis 16 Uhr: Raum 2418 (Seminarraum Lst. Friedl)
    • Di, 13.06.2023, 9 bis 18 Uhr: Raum 2418 (Seminarraum Lst. Friedl)
    • Mi, 14.06.2023, 9 bis 17 Uhr: Raum 3539 (Seminarraum Lst. Kaserer)
    • Do, 15.06.2023, 9 bis 18 Uhr: Raum 3539 (Seminarraum Lst. Kaserer)

     

    Location: Campus Munich

  • The first key element of this course is experimental design. The ultimatum game serves as an example of a design that can be and has been used to address multiple research questions. In addition, we will work with other selected standard designs intensively.
    The second key element is to understand when a laboratory experiment is an appropriate method to address a research question or to find research questions in your area of interest that laboratory experiments can address. We will thus consider recent research. You can strongly influence the contents of the course by suggesting a research question or idea (see application process).
    The third key element is to understand how to conduct a laboratory experiment. Along with questions about software, recruitment of participants, or funding, a visit to the laboratory gives you a specific idea of the procedures.
    Along with these key contents, we will be touching on various other issues, including criticism of the experimental method, and what can be done about potential weaknesses.

     

    Syllabus: Introduction to Experimental Economics

     

    Registration: Write to Andreas Ostermaier no later than July 21, 2023 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: Prof. Dr. Andreas Ostermaier (University of Southern Denmark)

     

    Course dates: The seminar is scheduled to be held on July 24–26, 2023 in room 0505.03.539.

     

    Location: Campus Munich - Room 0505.03.539

  • Many real life systems are subject to uncertainty and should therefore be modelled with stochastic models. In this course we focus on the theory and the application of two different classes of stochastic models: Discrete Time Markov Chains and Continuous Time Markov Chains. The students should gain knowledge about these models such that they are able to construct these models and apply them to solve real life problems. For illustration we use among others, models of inventory systems, manufacturing systems, maintenance systems, and queuing systems. We show how formulas for performance measures can be derived, and how they can be computed. Further, the students learn numerical methods to obtain solutions, which have to be implemented.
    Knowledge about Markov Chains is necessary to understand Markov Decision processes.This course is covering the prior knowledge necessary for the course on Markov Decision Models, including basics about reinforcement learning, that is given in the next semester.

     

    Syllabus: Markov Chains and Queuing Models

     

    Registration: PhD Students interested in the course can send an e-mail to office.cdt@mgt.tum.de

     

    Lecturer: Prof. Dr. Gudrun Kiesmüller (TUM)

     

    Course dates:

    20.03.2023: 16.00-17.30: Kick of meeting online - During the kick-off meeting we will discuss the organization of the course and the schedule


    The following meetings can be organized hybrid
    27.03.2023: 9.30-11.00: Lecture, Discrete Time Markov Chains: Modelling issues
    27.03.2023: 11.00-12.30: Exercise, Discrete Time Markov Chains: Modelling issues
    27.03.2023: 13.00-15.00: Lecture, Discrete Time Markov Chains: Analysis
    27.03.2023: 15.00-17.00: Exercise, Discrete Time Markov Chains: Analysis

    03.04.2023: 9.30-11.00: Lecture, Continuous Time Markov Chains: Modelling issues
    03.04.2023: 11.00-12.30: Exercise, Continuous Time Markov Chains: Modelling issues
    03.04.2023: 13.00-15.00: Lecture, Continuous Time Markov Chains: Analysis
    03.04.2023: 15.00-17.00: Exercise, Continuous Time Markov Chains: Analysis

    08.05.2023: 10.00-17.00: Presentation of projects

     

    Location: online / can be organized hybrid

  • Many real life systems are subject to uncertainty and should therefore be modelled with stochastic models. In this course, we focus on the theory and the application of Markov Decision Processes and Semi Markov Decision Processes. The students should gain knowledge about these models such that they are able to construct these models and apply them to solve real life problems. For illustration, we use among others, models of inventory systems, manufacturing systems and maintenance systems. We practice to derive the Bellmann equation for these systems and show how an optimal solution can be computed numerically. Besides the traditional solution approaches, we also discuss approaches based on reinforcement learning.

     

    Syllabus: Markov Decision Processes and Reinforcement Learning

     

    Registration: PhD Students interested in the course can send an e-mail to office.cdt@mgt.tum.de

     

    Lecturer: Prof. Dr. Gudrun Kiesmüller (TUM)

     

    Course dates:

    The course will take place in September/October 2023
    Kick-off meeting 90 minutes
    1 days traditional solution methods for Markov Decision Processes
    1 days reinforcement learning approaches for Markov Decision Processes
    1 day project presentation and discussion

     

    Location: tbd

  • The course provides an overview of the peer-review process in international scientific journals in business (i.e., submission procedures and requirements, editorial decisions, hierarchies). It offers 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) and equips participants with tools and information how to analyze reviews which they received on their papers (i.e., identifying and aggregating received comments etc.). Finally, the course prepares participants with tools and information on how to respond to reviews (i.e., writing a response note). We will talk about strategies for answering reviewer comments, setting priorities, and getting into a constructive mindset. Various real-life examples illustrate the topics.

     

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

     

    Registration: Please send an e-mail to the email address with a short registration request that includes your name and the title of your paper (see Assessment). Application deadline: April 12, 2023

     

     

    Lecturer: Prof. Dr. Jens Foerderer (TUM)

     

    Course dates:

    20.4.2023: Course administration, presentation by instructor on writing reviews (09:00-15.00)
    17.5.2023: Q&A, presentation by instructor on responding to reviews (13:00-16.00)

    Two presentation days in June (dates will be coordinated with the participants).

     

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

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

     

    Syllabus: Networks and Organizations

     

    Registration: Until July 3, 2023, via Moodle.

     

    Lecturer: Prof. Henning Piezunka (INSEAD)

     

    Course dates: July 10th, 2023 – July 14th, 2023

     

    Location: Campus Munich - Rroom will be announced.

  • This course gives doctoral students 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.dutz@tum.de (Dr. Regina Dutz) until April 30, 2023. Participants will be admitted on a first come, first served basis.

     

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

     

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

    Tuesday, 9 May 2023, 9.00 am to 5.00 pm

    Tuesday, 20 June 2023, 9.00 am to 1 pm, online (Group Feedback)

    Tuesday, 4 July 2023, 9.00 am to 5.00 pm (Presentation Day 1)

    Friday, 7 July 2023, 9.00 am to 5.00 pm (Presentation Day 2

     

    Location: Campus Munich - Room Z577

  • The aim of this course is to improve academic writing skills and to support the participants in publishing papers at leading journals. Participants are expected to submit a piece of writing before the start of the seminar. The goal of the course is to revise the piece. At the end of the course, the initially submitted piece of writing should be re-submitted to the lecturer. In addition, the course trains to write cover letters and to respond to journal reviewers.

     

    Syllabus: Scientifc Writing for Doctoral Candidates

     

    Registration: Please sign up for the course via email to Bastian.Krieger@zew.de by June 12, 2023. If you have any questions regarding the course, please contact Mr. Krieger.

     

    Lecturer: Dr. Bastian Krieger (ZEW)

     

    Preliminary Course dates:

    19.06.2023, 10:00 – 12:30, Campus Heilbronn / Hybrid

    19.06.2023, 14:00 – 16:30, Campus Heilbronn / Hybrid

    20.06.2023, 10:00 – 12:30, Campus Heilbronn / Hybrid

    20.06.2023, 14:00 – 16:30, Campus Heilbronn / Hybrid

    03.07.2023, 09:30 – 12:30, Online

    03.07.2023, 14:00 – 16:30, Online

    17.07.2023, 09:30 – 12:30, Online

    17.07.2023, 14:00 – 16:30, Online

    31.07.2023, Submission of revision history

     

    Location: TUM Campus Heilbronn (room t.b.a.) and online

  • This course targets PhD students and Post Docs and offers guidance on how to write high quality papers, targeted at top journals (e.g., Operations Research, Management Science, POM, MSOM, Transportation Science, …) in the field of Operations Research and Management Science. Among others, we will discuss strategies and methodologies on how to structure and organize papers, how to use proactive writing to anticipate referee criticisms, as well as a diverse toolset on how to convey your research’s main findings. The course contains a mix of lectures and hands on exercises for which students are required to bring a (not necessarily finished) working paper to the first meeting. Ultimately, the course prepares students to convey their research findings in a profound and at the same time comprehensive manner that enables them to prepare publications that are submittable to top-level journals in the field.

     

    Syllabus: Scientific Writing in the fields of Operations Research & Management Science

     

    Registration: Please send an e-Mail with a short application request that includes your name and the title of a working paper that you will bring to the course. Application deadline is April 17th. Places are limited and will be assigned based on fit and in case of a tie by first-come first-serve.

     

    Lecturer: Prof. Dr. Maximilian Schiffer (TUM)

     

    Course dates: April 27th, May 15th, June 1st

     

    Location: TUM Campus Munich, room to be defined.

  • We will begin with the foundational issues in strategy and see how the field made substantial progress by relaxing and addressing head-on a number of restrictive assumptions in mainstream economics about information, decision-making, and behavior in organizations. We will start with the early progress made by using the theories and approaches of industrial organizational economics, in addition to a number of very important (and controversial) insights that strategic management provided. We will cover a family of theories that make up so-called “organizational economics” that address key questions related to the organizational and geographic scope of the firm, and we will cover a series of competence-based, evolutionary, and learning perspectives on competitive advantage and firm dynamics. Finally, some attention will also be given to theories that are newer and have been used less often in different streams of strategy research but hold considerable promise, including information economics and real options theory. By design and necessity, breadth will be prioritized over depth, but by the end of the course you will have familiarity with a considerable body of theoretical material that has provided the bedrock for strategic management research over the past few decades. Equally important to you, all of the theories we will cover are topical and provide the basis for scholars’ research programs today.

     

    Syllabus: Seminar on Strategic Management (I): Theoretical Foundations of Strategy

     

    Registration: Please register for the course via self-registration in Moodle (https://www.moodle.tum.de/course/view.php?id=88698)

     

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

     

    Course dates: Theoretical Foundations of Strategy (week of July 3, 2023; Zoom: https://cuboulder.zoom.us/j/5539784611)
    1. Foundational Issues in Strategy (Monday, 15:00-18:30)
    2. Industrial Organization Economics (Tuesday, 15:00-18:30)
    3. Resource-Based View (Wednesday, 15:00-18:00)
    4. Knowledge-Based View and Dynamic Capabilities (Wednesday, 18:30-21:30)
    5. Transaction Cost Economics (Thursday, 15:00-18:30)
    6. Information Economics (Friday, 15:00-18:00)
    7. Real Options Theory (Friday, 18:30-21:30)

     

    Location: Online (Zoom)

  • 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: Seminar on 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=88699)

     

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

     

    Course dates: Empirical Research in Strategic Management (week of July 17, 2023; Zoom: https://cuboulder.zoom.us/j/5539784611)
    6. Firm Heterogeneity and Fit (Monday, 15:00-18:30)
    7. Survival and Exit (Tuesday, 15:00-18:00 and 18:30-21:30)
    8. Transaction Cost Economics (Wednesday, 15:00-18:00 and 18:30-21:30)
    9. Information Economics (Thursday, 15:00-18:30)
    10. Implications of Strategic Decisions (Friday, 15:00-18:30)

     

    Location: Online (Zoom)

  • This course is an introduction to the statistical computing environment R. In this course, you will learn how to interact with, process, analyze and visualize data in R. The main objective of this course is to familiarize participants with R and to develop competencies to effectively work on their own research projects with R. This course is also helpful as a primer for other summer program courses such as Advanced Regression or Data Mining.

     

    Syllabus: Statistics with R – Bootcamp

     

    Registration: Please register for the course by Tuesday, August 22 by sending an email to contact.dm@mgt.tum.de.

     

    Lecturer: Prof. Dr. Christian Hildebrand (University of St. Gallen)

     

    Course dates: August 31, 2023, September 7, 2023, September 8, 2023

     

    Location: Campus Munich (1 day) and virtual (2 days), see “Preliminary schedule” below 
    Rooms: 2566

     

  • 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 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.

     

    Syllabus: The 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 will commence on Monday 26 June 2023.
    • The course consists of a total of 24 hours of direct class interaction, which will be split over five (5) classes.
    • The dates of the five (5) classes will be:
      o Lecture 1: 26 June 2023 (9h00 – 13h00; 14h00-15h00)
      o Lecture 2: 27 June 2023 (9h00 – 13h00; 14h00-15h00)
      o Lecture 3: 28 June 2023 (9h00 – 13h00; 14h00-15h00)
      o Lecture 4: 29 June 2023 (9h00 – 13h00; 14h00-15h00)
      o Lecture 5: 30 June 2023 (9h00 – 13h00)

     

    Location: Campus Munich - Room 1355

  • 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,
    (6) and outlines ethical and methodological considerations.

     

    Syllabus: Web Scraping for Scientists: An Introduction with Python

     

    Registration: Please send an email to the above stated address with a registration request that includes your name (see below) and your TUM eMail-address. Registration deadline: 21.04.2023

     

    Lecturer: Prof. Dr. Jens Foerderer (TUM)

     

    Course dates:

    27.04.2023, 09:00-17:00: Day 1 (Fundamentals, HTML, Crawling, Fetching, Parsing)
    28.04.2023, 09:00-17:00: Day 2 (Advanced Scraping, Methodological and Ethical Issues)

    One Q&A meeting in May (date will be coordinated with the participants)

     

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

  • What does it take to write a research paper that is published in one of the top management journals? Editors and reviewers at top journals seek papers that make important ‘contributions’ to the literature. But what is a contribution? How do you know when your paper is contributing? More importantly, how do you write your paper to make a contribution that editors and reviewers recognize such that they want to publish your paper?

     

    Syllabus: Workshop on “Contributing” to the Management Literature

     

    Registration: To apply, please send an email to o.alexy@tum.de, and copy hposen@wisc.edu on the email. In this email, please specify (a) where you are in your doctoral program, (b) what you currently expect to do once you finish your doctoral program, and (c) what you hope to get out of this class. On top of that, please (d) attach the current version of the working paper you hope will be improved as a result of this workshop and (e) paste the abstract of the working paper to the bottom of the email. TUM students will need to apply before Jan 15, 2023; they will of course be able to submit an updated version of their working paper at a later date.

     

    Lecturer: Prof. Hart E. Posen (University of Wisconsin-Madison)

     

    Course dates:

    April 17 (Monday): 9:00 – 12.00 and 14:00 – 17:00
    April 18 (Tuesday): 9:00 – 12.00 and 14:00 – 17:00
    April 19 (Wednesday): 9:00 – 12.00 and 14:00 – 17:00
    Zoom (3h; day& time TBA)  How to apply my key learnings in my Ph.D. studies at TUM (Prof. Alexy; mandatory for TUM participants, open to others)

     

    Location: To be announced (either at TUM’s Garching campus or downtown)

Winter term 2022 / 2023

  • 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 December 20th 2022.

     

    Lecturer: Prof. Hanna Hottenrott (TUM)

     

    Course dates: The course will be held in January 2023 during the week of January 9th 2023 (Mon-Fri from 9:30am to 4pm). The first session in a day will start at approx. 9am and last to about noon, after a short lunch break it will continue from about 1pm to 2:30pm. The second session in a day will last from 2:45pm to about 4pm.

     

    Location: 05.05 2518 (Campus Munich)

  • 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, “Econometrics II: Causal Inference” by Prof. Dr. Joachim Henkel and “Econometrics IV: Machine Learning” by me.

    Econometrics III will be a block lecture but conceptualized as a seminar based on student presentations. 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)
    • Double Machine Learning

     

     

    Syllabus: Econometrics III: Advanced Econometrics (only PhD)

     

    Registration: Until March 13, 2023, via email.

     

    Lecturer: Prof. Dr. Helmut Farbmacher (TUM)

     

    Course dates: 1st part in person: March 13-14, 2023 (9.30am to 4pm, room 2544)
    2nd part via Zoom: March 20, 2023 (individual sessions)
    3rd part in person: March 23-24, 2023 (9.30am to 4pm, room 2544)

     

    Location: Munich

  • The seminar “Economics of Aging” will cover several economic and sociological aspects of demographic change. A special focus will be given to the analysis of: 1) the consequences of aging for the sustainability of the social security systems; 2) the interactions between economic decisions and health outcomes and 3) the consequences of aging on labor, capital and goods markets.

     

    Solid knowledge of quantitative empirical research methods is essential. Successful prior completion of "Applied Econometrics" (Prof. Hottenrott) or comparable courses is required. Successful completion of "Advanced Econometrics: Causal Inference" (Prof. Henkel) or comparable courses is strongly recommended.

     

    Syllabus: Economics of Aging

     

    Registration by e-mail to kneip@mea.mpisoc.mpg.de until September 26, 2022

     

    Lecturer: Prof. Axel Börsch-Supan (Max Planck Institute for Social Law and Social Policy)

     

    Course dates:  Wednesdays, 10.30 to 12.00 a.m.

    The course takes place throughout the term (incl. lecture-free time). Students need to participate for a sufficient amount of presentation time (22.5 hours) to arrive at the full credit of 4 ETCS.

    Kick-Off: October 12

    Location: Munich Center for Economics of Aging, Max-Planck-Institut für Sozialrecht und Sozialpolitik, Room 313, Amalienstraße 33, 80799 München

  • The course is aimed at Ph.D. candidates who are currently in the process of writing their dissertations or papers. The focus will be the work-in-progress of each participant- perfecting a difficult chapter, preparing a journal article for publication, or contemplating a paper for an upcoming conference. It aims to teach effective scientific writing fundamentals and create a space for intensive writing sessions and discussions.

     

     

    Syllabus: Efficient Academic Writing

     

    Registration:

    Deadline for registering: 30.09.2022

    For applying please send your CV and a short cover letter to Chengguang Li (chengguang.li@tum.de)

     

    Lecturer: Prof. Dr. Chengguang Li (TUM)

     

    Course dates: The preliminary course dates are 24.10., 31.10., 7.11., 14.11., 21.11., 28.11., 5.12., from 2:30 to 5:30 pm.

     

    Location: tbd

  • The course provides an overview of the peer-review process in international scientific journals in business (i.e., submission procedures and requirements, editorial decisions, hierarchies). It offers 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) and equips participants with tools and information how to analyze reviews which they received on their papers (i.e., identifying and aggregating received comments etc.). Finally, the course prepares participants with tools and information on how to respond to reviews (i.e., writing a response note). We will talk about strategies for answering reviewer comments, setting priorities, and getting intro a constructive mindset. Various real-life examples illustrate the topics.

     

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

     

    Registration: Please send an e-mail to the email address (office.cdt@wi.tum.de) with a short registration request that includes your name and the title of your paper (see Assessment).

    Application deadline: November 1, 2022

     

    Lecturer: Prof. Dr. Jens Foerderer (TUM)

     

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

    18.11.2022: Course administration, presentation by instructor on writing reviews (08:30-15.30)

    09.12.2022: Q&A, presentation by instructor on responding to reviews (09:00-12.30)

    27.01.2023: Presentation day 1 (9:00-15.00)

    03.02.2023: Presentation day 2 (9.00-15.00)

     

    Location: online

  • The course is intended for Ph.D. students in Strategic Management, International Management, Innovation, and Entrepreneurship. The goal is to develop ideas and working manuscripts with the aim of later submission for review in top management journals.

     

     

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

     

    Registration: 

    Deadline for registering: 30.09.2022

    For applying please send your CV and a short cover letter to Chengguang Li (chengguang.li@tum.de). Please also submit an extended abstract (between 5 and 10 pages of text) of your project proposal. Submitted abstracts should describe the project, the intended theoretical contribution, the research design, the empirical approach, and the status of the project idea to date. Please note that submission of an abstract does not guarantee acceptance. The quality of the proposal will be taken into consideration.

     

    Lecturer: Prof. Dr. Chengguang Li (TUM)

     

    Course dates: The course will start at the beginning of the WS 22/23 (the exact kick-off date will be announced soon). It will end with a roundtable discussion on the 25th of November 2022 at the HEC in Paris.

     

    Location: HEC Paris

  • In this course, PhD students will be guided on how to communicate their research findings in research manuscripts and presentations. From an initial draft to a submitted manuscript, the different stages of the writing process will be covered based on the participant’s individual research projects in logistics and supply chain management.

     

    Syllabus: Paper writing and communication in logistics and supply chain management

     

    Registration: Email to logistics.log@mgt.tum.de until October 24, 2022

     

    Lecturer: Prof. Dr. Stefan Minner (TUM)

     

    Course dates:  Tuesdays, 1:30-3pm in room 1577, October 25-February 10.

     

    Location: 0505.01.577 (Campus Munich)

  • This course gives doctoral students 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 martin.fladerer@tum.de (Dr. Martin Fladerer) until December 9, 2022. Participants will be admitted on a first come, first served basis.

     

    Lecturer: Prof. Dr. Claudia Peus (TUM) and Dr. Martin Fladerer (TUM)

     

    Course dates: Course will be held in person at the TUM main campus (Arcisstr. 21, Building 0505, Room Z577).
    Friday, 16 December 2022, 9.00 am to 5.00 pm
    Friday, 3 February 2023, 9.00 am to 1 pm, online (Group Feedback)
    Thursday, 16 February 2023, 9.00 am to 5.00 pm (Presentation Day 1)
    Friday, 17 February 2023, 9.00 am to 5.00 pm (Presentation Day 2)

     

    Location: Munich

  • Qualitative research has become an established method of inquiry in human and social sciences, including management and related fields. Qualitative papers are published in leading management journals (e.g. Academy of Management Journal). In this seminar you will learn about: the notion of methodological fit; ontological and epistemological assumptions; qualitative research designs; research methods for qualitative data collection; and research methods for qualitative data analysis.

     

    Syllabus: Qualitative Research

     

    Registration: Since the doctoral seminar is interactive in nature, it is limited to 15 participants. If you are interested in it, send a short letter of motivation and CV to Prof. Dr. Frank-Martin Belz until October 31, 2022 (email: frank.belz@tum.de).

     

    Lecturer: Prof. Dr. Frank-Martin Belz (TUM)

     

    Course dates: 05.12.2022, 12.12.2022, 13.12.2022, 31.01.2023

     

    Location: Munich

  • A structured introduction to learning methodological approaches for successful research in stochastic models in logistics and supply chain management at the beginning of the PhD program. It is expected that all participants will prepare one core topic (including some implementation) and present this to the other participants.

     

    Syllabus: Research on Stochastic Modeling and Optimization

     

    Registration: Apply until November 30, 2022 by sending an email to: stefan.minner@tum.de

     

    Lecturer: Prof. Dr. Stefan Minner (TUM)

     

    Course dates: Kickoff-Meeting on December 5, 1pm in room 1577. 3 day block course on February 20 - 22, 2023

     

    Location: Munich

  • The seminar requires solid knowledge in advanced mathematics, especially the knowledge of linear algebra, probabilities and fundamental optimization, etc. Mathematical maturity and the ability to write down precise and rigorous arguments and proofs are also important. Computer programming skills are expected. Doctoral students are the target audience.

     

    Syllabus: Robust Optimization

     

    Registration: Self-registration in Moodle.

     

    Lecturer: Prof. Dr. Jingui Xie (TUM)

     

    Course dates: Kick-off meeting via Zoom by annoucement. The course will be taught as a series of seminars on Thursday morning from 9:00 am to 12:00 am weekly. Dates could be coordinated with participants. If possible, the course will be held in person; otherwise, via Zoom.

     

    Location: online

  • The goal of this course is to present and discuss current state-of-the-art research in finance. Therefore, renowned researchers from various international universities will present their latest asset pricing, corporate finance, and financial intermediation research. 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.

     

    The target audience is Ph.D. students and post-docs in finance. A requisite for participation is a specialization in finance and/or accounting.

     

    Syllabus: Topics in Finance Research

     

    Registration: Please send an email to matthias.hanauer@tum.de by October 10, 2022. In your email, please state your department and specify the topic and state of your Ph.D. thesis or research area (post-docs). Strict preference will be given to individuals with a specialization in finance and/or accounting.

     

    Lecturer: Dr. Matthias Hanauer (TUM)

     

    Course dates: See

    https://www.professors.wi.tum.de/fm/research-seminar/.

     

    Location: Munich

  • This course …

    (1) is a beginner’s course for web scraping

    (2) makes participants familiar with the problem of collecting massive data from Internet sources

    (3) guides participants in evaluating the costs and benefits of automating data collection

    (4) introduces participants to the structure of websites

    (5) reviews the most effective approaches for collecting data from web sources

    (6) provides hands-on implementations using Python

    (7) outlines ethical and legal considerations

     

    Syllabus: Web Scraping for Scientists: An Introduction with Python

     

    Registration: Please send an e-mail to the email address (office.cdt@wi.tum.de) with a registration request that includes your name (see below).

    Application deadline: November 1, 2022

     

    Lecturer: Prof. Dr. Jens Foerderer (TUM)

     

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

    12.01.2023, 08:30-17:30: Day 1

    13.01.2023, 08:30-17:30: Day 2

    26.01.2023: Q&A (9:00-13.30)

     

    Location: online