BE INSPIRED

"The CDSB core courses and especially the electives are very useful because they equip us with solid skills in our field of research as well as in related fields." Kirstin Becker, CDSB

Course Catalog

Spring 2020


Course Type: core course

Course Number: ACC / TAX 910

Course Content

The course focuses on current research topics in the field of accounting and taxation. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The presentations have workshop format and are similar in style to leading scientific conferences. For each presentation, a separate preparation session for the Ph.D. students is offered in advance by rotating faculty. Overall, the course deepens the students’ insights into a variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in accounting and taxation. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Form of assessment: Oral participation.


Seminar Dates are announced here.



Course Type: core course

Course Number: ACC / TAX 920

Course Content

The course is taught in a seminar-style format. Students present their own research ideas at different stages of the project (early ideas, preliminary results, and complete working papers). The presentations involve an interactive discussion between faculty and students about the project’s potential contribution, related literature, research design and interpretation of results.

Learning outcomes: Students will learn how to present and discuss their own research results in a scientific format. They will become acquainted with acting as a discussant for other topics. Students will gain insights into the assessment of contribution, research design, and interpretation of research papers. The development of these skills is also helpful for writing scientific referee reports.

Form of assessment: Class Participation


Coursedates will be announced via email to registered participants.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
12.02.20
27.05.20
Wednesday
13:45
17:00
O 048

Lecturer(s)


Course Type: core course

Course Number: ACC 903

Credits: 6

Course Content

This course provides a comprehensive overview of research topics and core methods in influential seminal as well as contemporaneous papers in the empirical accounting literature. In particular, we cover after an (1) introduction and a review of some “Accounting Classics”, the literatures on (2) Earnings Management, (3) Valuation (value relevance, earnings response coefficients (ERC)/event studies, accounting-based valuation), (4) Voluntary Disclosure, (5) Mandatory Disclosure, (6) International/-Institutional Accounting and IFRS, (7) Corporate Narratives, and (8) Bank Accounting. In each session, there is first an overview lecture introducing core methods in the corresponding field, and second a session in which we will jointly discuss in more depth selected empirical methods. Students are expected to prepare all readings and to lead selected class discussions about assigned papers in the second half of each lecture.

The lectures and student discussions are supplemented by exercise sessions in which we discuss broader related topics such as which fields are currently ‘en vogue’ in the journals, how to ‘stay informed’ and identify potentially relevant regulatory changes, how to know about topics influential researchers are currently working on, or discuss where students see their individual strength and how they can become competitive researchers in the future.

Learning outcomes: Students should know about the core issues of existing accounting research and established empirical research methodologies. They should also be able to place current research into the literature and to critically evaluate its relevance and technical rigor, and therefore to develop meaningful research ideas to extend current knowledge.

Form of assessment: Exam (90 minutes) 50 %, paper presentations and exercise sessions 50 %


Exam: April 21, 2020


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
18.02.20
31.03.20
Tuesday
10:00
13:00
O 254
10.03.20
Tuesday
09:00
11:45
O 254

Lecturer(s)


Course Type: core course

Course Number: ACC 904

Credits: 6

Course Content

The course provides PhD students with an introduction to current topics and methods in empirical accounting research.  The course aims to survey a wide variety of empirical research in in this field.  The course covers methodological issues, theoretical background, and selected empirical papers.  The assigned papers serve as examples to illustrate challenges of empirical research in accounting.

The course is structured around different identification approaches that are frequently used in recent accounting research.  This structure reflects the increasing importance of empirical strategies to address causality concerns in empirical accounting papers.  Since research in econ and finance took a lead on these questions, a number of examples from these fields will be integrated into the course.

Learning outcomes: Students are able to understand and evaluate research questions, contribution, and research methods of current research papers on accounting-related issues. Students are also able to develop new research questions based on their knowledge of the accounting literature.

Form of assessment: Exam (90 minutes) 50 %, presentation 50 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
10.02.20
Monday
12:00
13:30
O254
17.02.20
Monday
12:00
13:30
O254
21.02.20
Friday
13:45
15:15
O254
24.02.20
Monday
12:00
13:30
O254
02.03.20
Monday
12:00
13:30
O254
09.03.20
Monday
12:00
13:30
O254
16.03.20
Monday
12:00
13:30
O254
23.03.20
Monday
10:00
13:30
O254
20.04.20
Monday
10:00
13:30
O254

Lecturer(s)


Course Type: elective course

Credits: 3

Course Content

It serves to furnish the student with the basics of

- developing scientific writing and written communication skills, in particular

  •  developing a theoretical/empirical/experimental research topic
  •  writing it up in line with today’s mode of communicating scientific content
  •  selecting an appropriate journal
  •  reacting to referee reports
  •  writing a referee report

- developing presentation skills in necessary variation, in particular

  •  presenting a research topic in 30 seconds / 1 minute / 5 minutes
  •  presenting a paper in conference format (20 minutes)
  • presenting a paper within a full seminar format
  • o preparing a formal discussion
  •  reacting to a discussant’s comments
  •  chairing a discussion
  •  contributing to the discussion of somebody else’s paper
     

This is NOT a course in which English language skills are exercised ---although reference is given frequently to how to express matters in that language. Beyond this, it is geared to successfully develop and provide logically consistent scientific arguments in a way that attracts the relevant readership.
 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
28.02.20
Friday
09:00
18:00
L7, 3-5, P043
13.03.20
Friday
09:00
18:00
L7, 3-5, P043

Lecturer(s)


Course Type: elective course

Credits: 6

Prerequisites

Although this course will include a short introduction to R, students are encouraged to work through one or more R tutorials prior or during the first weeks of the course.


Course Content

This course provides an introduction to supervised statistical learning techniques such as decision trees, random forests and boosting and discusses
their potential application in the social sciences. These methods focus on predicting an outcome Y based on some learned function f(X) and therefore facilitate new research perspectives in comparison with traditional regression models, which primarily focus on causation. Predictive methods also provide a valuable extension to the empirical social scientists’ toolkit as new data sources become more prominent. In addition to introducing supervised learning methods, the course will include practical sessions to exemplify how to tune, evaluate and interpret prediction models using R.

Learning outcomes: At the completion of this course, students will have a profound understanding of tree-based prediction methods and the machine learning perspective on statistical modeling. Students will learn the computational skills to apply and evaluate these methods using R.

Form of assessment: Presentation and / or term paper


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
18.02.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
03.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
17.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
31.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
21.04.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
05.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
19.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211


Course Type: elective course

Course Number: ACC 921

Credits: 8

Course Content

This course is aimed at doctoral students in accounting and neighboring fields including economics, finance, political and operations management. The course seeks to provide an introduction to the role of accounting information in (a) measuring cost and profitability, (b) accounting-based managerial performance measures, (c) cost allocation and internal pricing in multi-divisional firms and (d) financial ratios and firm valuation.

  • The main topics covered in this course include:
  • Measures of Product Cost and Relevant Costs
  • Measures of Profitability
  • Managerial Performance Evaluation
  • Internal Pricing
  • Accounting-based Equity Valuation and Financial Ratios

Learning outcomes: The primary objective of the course is to introduce students to current research paradigms on these topics and to identify promising avenues for future research. The course readings include recent theoretical and empirical papers.

Form of assessment: Homework Assignments (30%), Class Participation (15%), Paper Presentation (15%), Final Examination (40%)

Course Dates: tba


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
24.04.20
05.06.20
Friday
13:45
17:00
O 048

Lecturer(s)


Course Type: elective course

Course Number: RES

Credits: 5

Course Content

This course will introduce student to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS.

The course consists of four core building blocks:

1. Kick-Off & Introductory Session: What is interdisciplinary research.

After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by me, each participant will shortly (max 10 min, 3 slides per person) present the core idea of an interdisciplinary paper that involves her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is.

2. GESS Research Day

The GESS research day - kindly co-organized by your student representatives - consists of presentations by PhD students from all three centers and discussion panels with senior experts. Participation at the GESS Research Day is mandatory for all course participants. You will give  presentation on a current working paper or research project of yours and you will  discuss a paper/presentation from one of your fellow students from another field (15-20 min presentation, 5 min discussion, 5 min Q&A). Additionally, you will participate in one discussion panel. The idea of the discussion panels is to bring together students from different centers to discuss core topics of societal relevance. Within these panels, the students should talk about how their own field might contribute to the discussion of a specific topic and ideally come up with some joint interdisciplinary research ideas.

3. Science Speed Dating

The science speed dating event - also organized by your student representatives - involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a students from another field.

4. Project Presentations & Writeups

The proposals will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. These teams will also prepare a write-up of their proposal (max. 5 pages, incl. References) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in one week after the presentation.

Learning Outcomes: Upon successful completion of this course, students will

  • have gotten in touch with a variety of disciplinary research methods and perspectives from different fields
  • critically evaluate the strengths and weaknesses of these research methods
  • identify and develop an interdisciplinary research proposal and communicate their ideas clearly in both, a presentation and in writing.
  • have practiced to present their work to a critical, interdisciplinary audience and to discuss other students work in a format closely resembling that of most academic conferences.

Form of assessment:

This is a Pass/Fail course. To successfully pass the course, each student has to:

  • Give a short paper presentation in the introductory session.
  • Present, discuss, and participate in one discussion panel at the GESS Research Day. An extended abstract and the set of slides that will be used for the presentation or (preferably) a working paper draft needs to be provided by each presenting student to the assigned discussant two weeks before the research day.
  • Participate at the science speed dating event.
  • Present your interdisciplinary research proposal (group of two students) and subsequently hand in a the write-up
  • Full and active participation in all four building blocks is necessary to pass the course.
  • The best interdisciplinary proposal will win a price.

Please register by the registration deadline by sending title and abstract of the research project/topic you would like to present during the GESS research day to registration@gess.uni-mannheim.de. Please indicate in your e-mail your fields of interest and mention up to three broad other fields (e.g. Marketing, Macroeconomics, Social Psychology) you would like to collaborate with.

Please note that the course is limited to a maximum of 24 participants, and seats will be allocated on a first come first serve basis.


Course Dates:

March 11th, 2020, 10am-1pm, Kick-Off Meeting, Room 409 in L9, 1-2 (4. OG)        

April 23th, 2020, Deadline to send paper to discussant (and in cc: to gess@uni-mannheim.de)

April 30th, 2020, Research Day (whole day symposium)

May 4th, 2020, time TBA - Science Speed Dating Event

May 28th, 2020, Presentation of research proposal (half- to full day symposium)


Course Room: B6, 30-32, room 211


Lecturer(s)


Course Type: core course

Course Number: FIN 620

Credits: 6

Course Content

This course is for participants of FIN 901 only.

There is abundant evidence suggesting that the standard economic paradigm of rational investors does not adequately describe behavior in financial markets. Behavioral Finance examines how individuals' attitudes and behavior affect their financial decisions. This course reviews recent research on possible mispricing in financial markets due to the nature of psychological biases. Moreover the course deals with behavioral finance models explaining investor behavior or market anomalies when rational models provide no sufficient explanations. Topics will include among others overconfidence, prospect theory, heuristic driven biases and frame dependence.

Learning outcomes: Behavioral finance applies scientific research on human and social cognitive and emotionalbiases. After completing this course, students will be able to better understand economic decisions and how they affect market prices and returns. They will know how behavioral findings are integrated with neo-classical theory.

Form of assessment: Written exam (60 min.)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
20.02.20
02.04.20
Thursday
08:30
11:45
O 131
09.03.20
Monday
17:15
20:30
Exam
30.04.20
Thursday
08:30
10:00
SN 163
Tutorial
19.02.20
29.04.20
Wednesday
12:00
13:30
O 133

Lecturer(s)


Course Type: core course

Course Number: FIN 802

Credits: 8

Prerequisites

FIN 801 Discrete-Time Finance


Course Content

Itô calculus, stochastic differential equations, Black-Scholes theory, hedging and arbitrage pricing of European, American, and exotic options, complete and incomplete market models, consumption investment problems, term structure theory for volatility and interest rates, default risk

Learning outcomes: The course aims at providing the basic concepts and techniques for modelling and analysing financial price processes in continuous time.

Form of assessment: Term paper 90 %, participation 10 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
12.02.20
Wednesday
10:00
11:45
B 6, 30-32, room 211
12.02.20
Wednesday
13:45
18:00
B 6, 30-32, room 211
04.03.20
Wednesday
10:00
11:45
B 6, 30-32, room 211
04.03.20
Wednesday
13:45
18:00
B 6, 30-32, room 211
22.04.20
Wednesday
10:00
11:45
B 6, 30-32, room 211
22.04.20
Wednesday
13:45
18:00
B 6, 30-32, room 211

Lecturer(s)


Course Type: core course

Course Number: FIN 803

Credits: 6

Prerequisites

Formal: E 701, E 703, FIN 801

Recommended:

  • A first-year doctoral level course in microeconomics that covers game theory and information economics (signaling, adverse selection, equilibrium refinements)
  • A first-year doctoral level course in econometrics that covers estimation and testing theory.
  • Some familiarity with corporate finance and financial institutions at the level of a masters level course is also assumed, but not essential. If you have no prior knowledge of corporate finance, then some chapters in an MBA-level textbook (e.g. Brealey, Myers, and Allen, Principles of Corporate Finance, 11th edition, McGraw Hill 2013; Berk and DeMarzo, Corporate Finance, 3rd edition, Pearson 2013) would be useful.

Course Content

This course is intended to enable students to understand and conduct research in corporate finance. It is taught at a first-year doctoral level.

Learning outcomes: The course combines two objectives. Firstly, participants learn the classic contributions to the theory of modern corporate finance and understand the main contributions to the field. Secondly, the course also introduces some of the main empirical contributions to the field and studies the main econometric and statistical techniques used in corporate finance. At the end of the course participants should be familiar with the main empirical and theoretical tools used in corporate finance.

Form of assessment: Essay (take-home exam)

For actual course details please click here


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
28.02.20
Friday
08:30
12:30
L 9, 1-2, room 409
20.03.20
Friday
08:30
12:30
L 9, 1-2, room 409
03.04.20
Friday
08:30
12:30
L 9, 1-2, room 409
24.04.20
Friday
08:30
12:30
L 9, 1-2, room 409
08.05.20
Friday
08:30
12:30
L 9, 1-2, room 409
22.05.20
Friday
08:30
12:30
L 9, 1-2, room 409


Course Type: core course

Course Number: FIN 804

Credits: 6

Course Content

The course provides a refresher of several econometric concepts such as endogeneity, multicollinearity and selection bias. A focus will be on causal inference. We will discuss methods such as discrete choice modelling, instrumental variable regressions, regression discontinuity, difference-in-difference, matching, and panel econometrics. Empirical applications from finance will be critically discussed.

Learning outcomes: The course provides students with a knowledge of several econometric concepts and their applications in finance and contributes to students’ ability to plan and carry out independent empirical research.

Form of assessment: Written exam (90 minutes) 40 %, class participation 60 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
17.02.20
30.03.20
Monday
08:30
11:45
L 9, 1-2, room 409

Lecturer(s)


Course Type: core course

Course Number: FIN 901

Credits: 2

Course Content

FIN 901 is a continuative course of FIN 620. In this course students discuss and present current research topics in behavioral finance.

Learning outcomes: Students learn to critically discuss current research papers, i.e. data, methodology, and reasoning.

Form of assessment: Presentation


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
Kick-off
20.02.20
Thursday
11:45
13:00
O 131

Lecturer(s)


Course Type: core course

Course Number: FIN 910

Course Content

The course focuses on current research topics in the field of finance. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The presentations have workshop format and are similar in style to leading scientific conferences. The course introduces students to the variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in finance. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Form of assessment: Oral participation.


Seminar Dates are announced here.


Lecturer(s)


Course Type: elective course

Credits: 3

Course Content

It serves to furnish the student with the basics of

- developing scientific writing and written communication skills, in particular

  •  developing a theoretical/empirical/experimental research topic
  •  writing it up in line with today’s mode of communicating scientific content
  •  selecting an appropriate journal
  •  reacting to referee reports
  •  writing a referee report

- developing presentation skills in necessary variation, in particular

  •  presenting a research topic in 30 seconds / 1 minute / 5 minutes
  •  presenting a paper in conference format (20 minutes)
  • presenting a paper within a full seminar format
  • o preparing a formal discussion
  •  reacting to a discussant’s comments
  •  chairing a discussion
  •  contributing to the discussion of somebody else’s paper
     

This is NOT a course in which English language skills are exercised ---although reference is given frequently to how to express matters in that language. Beyond this, it is geared to successfully develop and provide logically consistent scientific arguments in a way that attracts the relevant readership.
 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
28.02.20
Friday
09:00
18:00
L7, 3-5, P043
13.03.20
Friday
09:00
18:00
L7, 3-5, P043

Lecturer(s)


Course Type: elective course

Credits: 6

Prerequisites

Although this course will include a short introduction to R, students are encouraged to work through one or more R tutorials prior or during the first weeks of the course.


Course Content

This course provides an introduction to supervised statistical learning techniques such as decision trees, random forests and boosting and discusses
their potential application in the social sciences. These methods focus on predicting an outcome Y based on some learned function f(X) and therefore facilitate new research perspectives in comparison with traditional regression models, which primarily focus on causation. Predictive methods also provide a valuable extension to the empirical social scientists’ toolkit as new data sources become more prominent. In addition to introducing supervised learning methods, the course will include practical sessions to exemplify how to tune, evaluate and interpret prediction models using R.

Learning outcomes: At the completion of this course, students will have a profound understanding of tree-based prediction methods and the machine learning perspective on statistical modeling. Students will learn the computational skills to apply and evaluate these methods using R.

Form of assessment: Presentation and / or term paper


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
18.02.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
03.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
17.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
31.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
21.04.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
05.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
19.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211


Course Type: elective course

Course Number: FIN 913

Credits: 4+4

Prerequisites

Recommended: The course requires some knowledge of probability theory and statistics. Furthermore, students should be familiar with the pricing of standard financial instruments including derivatives. 


Course Content

This course includes FIN 660 (4 ECTS), which covers tail risk measures, market and credit risk, risk aggregation as well as portfolio risk decomposition. The additional sessions for FIN 913 (4 ECTS) extend the material on selected topics such as the theoretical properties of modern tail risk measures, flexible parametric and semiparametric tail risk estimators, dynamic risk forecasting as well as backtesting. Furthermore, advanced topics in market and credit risk including credit derivatives will be covered.

Learning outcomes: Students understand modern tail risk measures and are able to discuss their strengths and weaknesses. They are familiar with advanced techniques for tail risk estimation including time-series methods, extreme-value theory and copulas. Students understand alternatives to the variance-covariance approach for market risk and are familiar with important extensions of basic credit risk models. In addition, they obtain an advanced understanding for the pricing of risky debt and credit derivatives.

Form of assessment: Written Exam (90 minutes) 80%, Solving a Case Study 10%, Class Participation 10%


Please note: FIN 913 course dates following the Kick-Off will be individually scheduled together with the participants.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
FIN 660
11.02.20
26.05.20
Tuesday
12:00
13:30
O 145
FIN 913 Kick-Off
13.02.20
Thursday
13:45
15:15
O 328

Lecturer(s)


Course Type: elective course

Course Number: RES

Credits: 5

Course Content

This course will introduce student to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS.

The course consists of four core building blocks:

1. Kick-Off & Introductory Session: What is interdisciplinary research.

After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by me, each participant will shortly (max 10 min, 3 slides per person) present the core idea of an interdisciplinary paper that involves her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is.

2. GESS Research Day

The GESS research day - kindly co-organized by your student representatives - consists of presentations by PhD students from all three centers and discussion panels with senior experts. Participation at the GESS Research Day is mandatory for all course participants. You will give  presentation on a current working paper or research project of yours and you will  discuss a paper/presentation from one of your fellow students from another field (15-20 min presentation, 5 min discussion, 5 min Q&A). Additionally, you will participate in one discussion panel. The idea of the discussion panels is to bring together students from different centers to discuss core topics of societal relevance. Within these panels, the students should talk about how their own field might contribute to the discussion of a specific topic and ideally come up with some joint interdisciplinary research ideas.

3. Science Speed Dating

The science speed dating event - also organized by your student representatives - involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a students from another field.

4. Project Presentations & Writeups

The proposals will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. These teams will also prepare a write-up of their proposal (max. 5 pages, incl. References) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in one week after the presentation.

Learning Outcomes: Upon successful completion of this course, students will

  • have gotten in touch with a variety of disciplinary research methods and perspectives from different fields
  • critically evaluate the strengths and weaknesses of these research methods
  • identify and develop an interdisciplinary research proposal and communicate their ideas clearly in both, a presentation and in writing.
  • have practiced to present their work to a critical, interdisciplinary audience and to discuss other students work in a format closely resembling that of most academic conferences.

Form of assessment:

This is a Pass/Fail course. To successfully pass the course, each student has to:

  • Give a short paper presentation in the introductory session.
  • Present, discuss, and participate in one discussion panel at the GESS Research Day. An extended abstract and the set of slides that will be used for the presentation or (preferably) a working paper draft needs to be provided by each presenting student to the assigned discussant two weeks before the research day.
  • Participate at the science speed dating event.
  • Present your interdisciplinary research proposal (group of two students) and subsequently hand in a the write-up
  • Full and active participation in all four building blocks is necessary to pass the course.
  • The best interdisciplinary proposal will win a price.

Please register by the registration deadline by sending title and abstract of the research project/topic you would like to present during the GESS research day to registration@gess.uni-mannheim.de. Please indicate in your e-mail your fields of interest and mention up to three broad other fields (e.g. Marketing, Macroeconomics, Social Psychology) you would like to collaborate with.

Please note that the course is limited to a maximum of 24 participants, and seats will be allocated on a first come first serve basis.


Course Dates:

March 11th, 2020, 10am-1pm, Kick-Off Meeting, Room 409 in L9, 1-2 (4. OG)        

April 23th, 2020, Deadline to send paper to discussant (and in cc: to gess@uni-mannheim.de)

April 30th, 2020, Research Day (whole day symposium)

May 4th, 2020, time TBA - Science Speed Dating Event

May 28th, 2020, Presentation of research proposal (half- to full day symposium)


Course Room: B6, 30-32, room 211


Lecturer(s)


Course Type: core course

Course Number: IS / OPM 910

Course Content

The course focuses on current research topics in the field of information systems and operations management. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The course introduces students to the variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in information systems and operations management. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Form of assessment: Oral participation.


Seminar Dates are announced here.



Lecturer(s)


Course Type: core course

Course Number: IS 807

Credits: 9

Course Content

This course provides an overview of qualitative research methods and their application in the field of Information Systems (IS). The course begins with an introduction to the basic principles and alternatives of conducting qualitative research. It then provides deeper insights into different types of qualitative research in terms of their epistemological, ontological, and methodological stance. For each stance, the underlying principles will be discussed with illustrative examples. The course is taught in a seminar style, requiring students to prepare readings before class and discuss them in class. Student presentations will help elicit the strengths and weaknesses of different qualitative methods in published research. Overall, the course is designed to be interactive. For a final paper, the students illustrate the application of particular methods to design their own qualitative research study.

Learning outcomes: After completing the course, students

  • have gained an overview of the common qualitative methods in IS research
  • know quality criteria and corresponding means to improve qualitative research designs
  • are able to prepare, plan, and execute own qualitative research endeavors.

Form of assessment: Term paper 50%, presentation 30 %, discussion 20 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
04.03.20
29.04.20
Wednesday
12:00
15:00
L 15, 1-6, room 714

Lecturer(s)


Course Type: elective course

Credits: 3

Course Content

It serves to furnish the student with the basics of

- developing scientific writing and written communication skills, in particular

  •  developing a theoretical/empirical/experimental research topic
  •  writing it up in line with today’s mode of communicating scientific content
  •  selecting an appropriate journal
  •  reacting to referee reports
  •  writing a referee report

- developing presentation skills in necessary variation, in particular

  •  presenting a research topic in 30 seconds / 1 minute / 5 minutes
  •  presenting a paper in conference format (20 minutes)
  • presenting a paper within a full seminar format
  • o preparing a formal discussion
  •  reacting to a discussant’s comments
  •  chairing a discussion
  •  contributing to the discussion of somebody else’s paper
     

This is NOT a course in which English language skills are exercised ---although reference is given frequently to how to express matters in that language. Beyond this, it is geared to successfully develop and provide logically consistent scientific arguments in a way that attracts the relevant readership.
 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
28.02.20
Friday
09:00
18:00
L7, 3-5, P043
13.03.20
Friday
09:00
18:00
L7, 3-5, P043

Lecturer(s)


Course Type: elective course

Credits: 6

Prerequisites

Although this course will include a short introduction to R, students are encouraged to work through one or more R tutorials prior or during the first weeks of the course.


Course Content

This course provides an introduction to supervised statistical learning techniques such as decision trees, random forests and boosting and discusses
their potential application in the social sciences. These methods focus on predicting an outcome Y based on some learned function f(X) and therefore facilitate new research perspectives in comparison with traditional regression models, which primarily focus on causation. Predictive methods also provide a valuable extension to the empirical social scientists’ toolkit as new data sources become more prominent. In addition to introducing supervised learning methods, the course will include practical sessions to exemplify how to tune, evaluate and interpret prediction models using R.

Learning outcomes: At the completion of this course, students will have a profound understanding of tree-based prediction methods and the machine learning perspective on statistical modeling. Students will learn the computational skills to apply and evaluate these methods using R.

Form of assessment: Presentation and / or term paper


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
18.02.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
03.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
17.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
31.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
21.04.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
05.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
19.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211

Lecturer(s)


Course Type: elective course

Course Number: IS 911

Credits: 8

Prerequisites

Fundamentals in computer science and programming


Course Content

This course covers principles and foundations of context-aware computing. Approaches to context acquisition, reasoning and management are presented and current trends in research are discussed.

Learning outcomes: Students will gain foundational knowledge about context-aware computing. They will learn about modelling and using context in computing systems. This includes context management and reasoning. After this module, students will know about the current state of the art in context-aware computing.

Form of assessment: Assignment 40 %, Discussion 40 %, Class Participation 20 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
18.02.20
26.05.20
Tuesday
13:45
15:15
L 15, 1-6, room 714/715

Lecturer(s)


Course Type: elective course

Course Number: RES

Credits: 5

Course Content

This course will introduce student to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS.

The course consists of four core building blocks:

1. Kick-Off & Introductory Session: What is interdisciplinary research.

After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by me, each participant will shortly (max 10 min, 3 slides per person) present the core idea of an interdisciplinary paper that involves her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is.

2. GESS Research Day

The GESS research day - kindly co-organized by your student representatives - consists of presentations by PhD students from all three centers and discussion panels with senior experts. Participation at the GESS Research Day is mandatory for all course participants. You will give  presentation on a current working paper or research project of yours and you will  discuss a paper/presentation from one of your fellow students from another field (15-20 min presentation, 5 min discussion, 5 min Q&A). Additionally, you will participate in one discussion panel. The idea of the discussion panels is to bring together students from different centers to discuss core topics of societal relevance. Within these panels, the students should talk about how their own field might contribute to the discussion of a specific topic and ideally come up with some joint interdisciplinary research ideas.

3. Science Speed Dating

The science speed dating event - also organized by your student representatives - involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a students from another field.

4. Project Presentations & Writeups

The proposals will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. These teams will also prepare a write-up of their proposal (max. 5 pages, incl. References) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in one week after the presentation.

Learning Outcomes: Upon successful completion of this course, students will

  • have gotten in touch with a variety of disciplinary research methods and perspectives from different fields
  • critically evaluate the strengths and weaknesses of these research methods
  • identify and develop an interdisciplinary research proposal and communicate their ideas clearly in both, a presentation and in writing.
  • have practiced to present their work to a critical, interdisciplinary audience and to discuss other students work in a format closely resembling that of most academic conferences.

Form of assessment:

This is a Pass/Fail course. To successfully pass the course, each student has to:

  • Give a short paper presentation in the introductory session.
  • Present, discuss, and participate in one discussion panel at the GESS Research Day. An extended abstract and the set of slides that will be used for the presentation or (preferably) a working paper draft needs to be provided by each presenting student to the assigned discussant two weeks before the research day.
  • Participate at the science speed dating event.
  • Present your interdisciplinary research proposal (group of two students) and subsequently hand in a the write-up
  • Full and active participation in all four building blocks is necessary to pass the course.
  • The best interdisciplinary proposal will win a price.

Please register by the registration deadline by sending title and abstract of the research project/topic you would like to present during the GESS research day to registration@gess.uni-mannheim.de. Please indicate in your e-mail your fields of interest and mention up to three broad other fields (e.g. Marketing, Macroeconomics, Social Psychology) you would like to collaborate with.

Please note that the course is limited to a maximum of 24 participants, and seats will be allocated on a first come first serve basis.


Course Dates:

March 11th, 2020, 10am-1pm, Kick-Off Meeting, Room 409 in L9, 1-2 (4. OG)        

April 23th, 2020, Deadline to send paper to discussant (and in cc: to gess@uni-mannheim.de)

April 30th, 2020, Research Day (whole day symposium)

May 4th, 2020, time TBA - Science Speed Dating Event

May 28th, 2020, Presentation of research proposal (half- to full day symposium)


Course Room: B6, 30-32, room 211


Lecturer(s)


Course Type: core course

Course Number: MAN 801

Credits: 6

Course Content

This seminar will expose participants to the rich ecology of theoretical perspectives flourishing in management and entrepreneurship research. Students are invited to develop and present creative research proposals worthwhile to be developed into a strong dissertation based upon well-grounded theoretical perspectives.

Learning outcomes: The course aims at enabling students to understand basic concepts in management and entrepreneurship research, identify appropriate theoretical concepts and lenses and apply them properly to their individual research topics.

Form of assessment: Essay 80 %, presentation 20 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
Kick-Off
25.02.20
Tuesday
16:00
18:00
L 9, 1-2, room 210

Lecturer(s)


Course Type: core course

Course Number: MAN 804

Credits: 6

Course Content

The seminar serves the purpose of familiarizing doctoral students with the most relevant research streams and trends in strategy research. We will read and discuss current state-of-the-art research with a special focus on the recent scholarly debate in the “Strategic Management Journal”, we will reflect the most prevalent theoretical lenses, key subject areas and phenomena as well as the empirical designs applied by scholars in this particular domain. Moreover, we will discuss the art of article writing for dedicated field journals.

Learning outcomes:

  • Develop an understanding of the most established as well as the latest emerging literature substreams in strategy research.
  • Gain an overview of the most prevalently studied phenomena and subject areas in these literature substreams.
  • Become familiar with the theoretical and methodological approaches used to address the different sets of research questions.

Form of assessment: Essay 60 %, presentation 40 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
26.02.20
Wednesday
09:00
18:30
L 9, 1-2, room 210
31.03.20
Tuesday
11:00
13:30
L 9, 1-2, room 210
01.04.20
Wednesday
09:00
18:30
L 9, 1-2, room 210


Course Type: core course

Course Number: MAN 807

Credits: 6

Course Content

Gary Loveman, former Chief Executive Officer and President of Caesars Entertainment Corporation: “There are three things that can get you fired from Caesars: Stealing, sexual harassment, and running an experiment without a control group.”

This course provides an introduction to the fundamental methodological issues that arise in experimental and quasi-experimental research. Illustrative examples are drawn from the behavioral sciences with a focus on the behavior of consumers and employees. Topics that are covered include: the development of research ideas; data collection and reliable measurement procedures; threats to validity; control procedures and experimental designs; and data analysis. Emphasis is placed on attaining a working knowledge of the use of regression and analysis of variance methods for experimental data.

Participants develop their own idea for an experimental study that will be presented, discussed, and developed in class. Participants write a short research paper summarizing the research idea, the methodological approach, as well as the expected contribution of the results.

Learning outcomes: Through participating the in course, participants will:

  • Train their scientific writing and presentation skills, and receive feedback concerning their research ideas;
  • Gain an understanding of methodological issues that arise in experimental and quasi-experimental research;
  • Attain the skills needed to plan and execute their own experiments and analyze the resulting data.

Form of assessment: Term paper (incl.final presentation)


Please note: students have the option to take the course also in summer at the Wittenberg Center for Global Ethics which includes group discussions in every session.

Coursdates in Wittenberg: June 2, June 3, June 4 and June 5, 2020.

Should you be interested please contact Prof. Edinger-Schons directly.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
10.02.20
Monday
10:15
11:45
17.02.20
Monday
10:15
11:45
24.02.20
Monday
10:15
11:45
02.03.20
Monday
10:15
11:45
09.03.20
Monday
10:15
11:45
16.03.20
Monday
10:15
11:45


Course Type: core course

Course Number: MAN 910

Course Content

The course focuses on current research topics in the field of management. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The course introduces students to the variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in management. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Form of assessment: Oral participation.


Seminar Dates are announced here.


Lecturer(s)


Course Type: elective course

Credits: 3

Course Content

It serves to furnish the student with the basics of

- developing scientific writing and written communication skills, in particular

  •  developing a theoretical/empirical/experimental research topic
  •  writing it up in line with today’s mode of communicating scientific content
  •  selecting an appropriate journal
  •  reacting to referee reports
  •  writing a referee report

- developing presentation skills in necessary variation, in particular

  •  presenting a research topic in 30 seconds / 1 minute / 5 minutes
  •  presenting a paper in conference format (20 minutes)
  • presenting a paper within a full seminar format
  • o preparing a formal discussion
  •  reacting to a discussant’s comments
  •  chairing a discussion
  •  contributing to the discussion of somebody else’s paper
     

This is NOT a course in which English language skills are exercised ---although reference is given frequently to how to express matters in that language. Beyond this, it is geared to successfully develop and provide logically consistent scientific arguments in a way that attracts the relevant readership.
 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
28.02.20
Friday
09:00
18:00
L7, 3-5, P043
13.03.20
Friday
09:00
18:00
L7, 3-5, P043

Lecturer(s)


Course Type: elective course

Credits: 6

Prerequisites

Although this course will include a short introduction to R, students are encouraged to work through one or more R tutorials prior or during the first weeks of the course.


Course Content

This course provides an introduction to supervised statistical learning techniques such as decision trees, random forests and boosting and discusses
their potential application in the social sciences. These methods focus on predicting an outcome Y based on some learned function f(X) and therefore facilitate new research perspectives in comparison with traditional regression models, which primarily focus on causation. Predictive methods also provide a valuable extension to the empirical social scientists’ toolkit as new data sources become more prominent. In addition to introducing supervised learning methods, the course will include practical sessions to exemplify how to tune, evaluate and interpret prediction models using R.

Learning outcomes: At the completion of this course, students will have a profound understanding of tree-based prediction methods and the machine learning perspective on statistical modeling. Students will learn the computational skills to apply and evaluate these methods using R.

Form of assessment: Presentation and / or term paper


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
18.02.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
03.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
17.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
31.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
21.04.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
05.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
19.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211


Course Type: elective course

Course Number: MAN 808

Credits: 6

Course Content

This course provides introductions into organization theories such as Max Weber’s Theory of Bureaucracy, Taylorism, Behavioral Theory, Theories of Organizational Evolution, Neoinstitutional Organization Theory, Network Theory, Interpretative Organizational Theories Theories, or Luhmann’s Organization Theory.

Learning outcomes: Students are able to evaluate the relevance of organization theories for the explanation of organizational phenomena. They are also able to apply organization theories in formulating research questions. They develop an understanding for the specific capabilities of organization theories.

Form of assessment: Presentation of a theory from the perspective of an interested newcomer (without grading); Paper which discusses the application of an organization theory to a self-chosen organizational problem 75%; Class Participation 25%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
11.02.20
Tuesday
09:00
12:00
27.03.20
Friday
09:00
19:00
27.04.20
Monday
09:00
19:00
28.04.20
Tuesday
09:00
16:00

Lecturer(s)


Course Type: elective course

Course Number: RES

Credits: 5

Course Content

This course will introduce student to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS.

The course consists of four core building blocks:

1. Kick-Off & Introductory Session: What is interdisciplinary research.

After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by me, each participant will shortly (max 10 min, 3 slides per person) present the core idea of an interdisciplinary paper that involves her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is.

2. GESS Research Day

The GESS research day - kindly co-organized by your student representatives - consists of presentations by PhD students from all three centers and discussion panels with senior experts. Participation at the GESS Research Day is mandatory for all course participants. You will give  presentation on a current working paper or research project of yours and you will  discuss a paper/presentation from one of your fellow students from another field (15-20 min presentation, 5 min discussion, 5 min Q&A). Additionally, you will participate in one discussion panel. The idea of the discussion panels is to bring together students from different centers to discuss core topics of societal relevance. Within these panels, the students should talk about how their own field might contribute to the discussion of a specific topic and ideally come up with some joint interdisciplinary research ideas.

3. Science Speed Dating

The science speed dating event - also organized by your student representatives - involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a students from another field.

4. Project Presentations & Writeups

The proposals will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. These teams will also prepare a write-up of their proposal (max. 5 pages, incl. References) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in one week after the presentation.

Learning Outcomes: Upon successful completion of this course, students will

  • have gotten in touch with a variety of disciplinary research methods and perspectives from different fields
  • critically evaluate the strengths and weaknesses of these research methods
  • identify and develop an interdisciplinary research proposal and communicate their ideas clearly in both, a presentation and in writing.
  • have practiced to present their work to a critical, interdisciplinary audience and to discuss other students work in a format closely resembling that of most academic conferences.

Form of assessment:

This is a Pass/Fail course. To successfully pass the course, each student has to:

  • Give a short paper presentation in the introductory session.
  • Present, discuss, and participate in one discussion panel at the GESS Research Day. An extended abstract and the set of slides that will be used for the presentation or (preferably) a working paper draft needs to be provided by each presenting student to the assigned discussant two weeks before the research day.
  • Participate at the science speed dating event.
  • Present your interdisciplinary research proposal (group of two students) and subsequently hand in a the write-up
  • Full and active participation in all four building blocks is necessary to pass the course.
  • The best interdisciplinary proposal will win a price.

Please register by the registration deadline by sending title and abstract of the research project/topic you would like to present during the GESS research day to registration@gess.uni-mannheim.de. Please indicate in your e-mail your fields of interest and mention up to three broad other fields (e.g. Marketing, Macroeconomics, Social Psychology) you would like to collaborate with.

Please note that the course is limited to a maximum of 24 participants, and seats will be allocated on a first come first serve basis.


Course Dates:

March 11th, 2020, 10am-1pm, Kick-Off Meeting, Room 409 in L9, 1-2 (4. OG)        

April 23th, 2020, Deadline to send paper to discussant (and in cc: to gess@uni-mannheim.de)

April 30th, 2020, Research Day (whole day symposium)

May 4th, 2020, time TBA - Science Speed Dating Event

May 28th, 2020, Presentation of research proposal (half- to full day symposium)


Course Room: B6, 30-32, room 211


Lecturer(s)


Course Type: core course

Course Number: MKT 804

Credits: 6

Course Content

This course teaches students how to develop and test theories in an applied and concrete way. We discuss and study a range of research approaches and methods, including structural equation modeling and experiments. This course provides students with an opportunity to develop and to fine-tune appropriate and specific theories for their own research.

Learning outcomes: Students come up and choose a specific topic of their interest in the beginning of the class and develop and present a theoretical framework suitable for their project. The latter part of the course is geared towards designing means to test the proposed theory. Another key learning outcome is to enhance students’ ability to conduct sound academic research and help them to derive hypotheses for their own research projects.

Form of assessment: Project (40%), presentation (60%)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
01.04.20
Wednesday
13:45
15:15
L 5, 1, room 009
22.04.20
Wednesday
13:45
15:15
L 5, 1, room 009
29.04.20
Wednesday
13:45
15:15
L 5, 1, room 009
06.05.20
Wednesday
13:45
15:15
L 5, 1, room 009
13.05.20
Wednesday
13:45
15:15
L 5, 1, room 009
20.05.20
Wednesday
13:45
15:15
L 5, 1, room 009
27.05.20
Wednesday
13:45
17:00
L 5, 1, room 009

Lecturer(s)


Course Type: core course

Course Number: MKT 910

Course Content

The course focuses on current research topics in the field of marketing. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The course introduces students to the variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in marketing. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Form of assessment: Oral participation.


Seminar Dates are announced here.


Lecturer(s)


Course Type: elective course

Credits: 3

Course Content

It serves to furnish the student with the basics of

- developing scientific writing and written communication skills, in particular

  •  developing a theoretical/empirical/experimental research topic
  •  writing it up in line with today’s mode of communicating scientific content
  •  selecting an appropriate journal
  •  reacting to referee reports
  •  writing a referee report

- developing presentation skills in necessary variation, in particular

  •  presenting a research topic in 30 seconds / 1 minute / 5 minutes
  •  presenting a paper in conference format (20 minutes)
  • presenting a paper within a full seminar format
  • o preparing a formal discussion
  •  reacting to a discussant’s comments
  •  chairing a discussion
  •  contributing to the discussion of somebody else’s paper
     

This is NOT a course in which English language skills are exercised ---although reference is given frequently to how to express matters in that language. Beyond this, it is geared to successfully develop and provide logically consistent scientific arguments in a way that attracts the relevant readership.
 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
28.02.20
Friday
09:00
18:00
L7, 3-5, P043
13.03.20
Friday
09:00
18:00
L7, 3-5, P043

Lecturer(s)


Course Type: elective course

Credits: 6

Prerequisites

Although this course will include a short introduction to R, students are encouraged to work through one or more R tutorials prior or during the first weeks of the course.


Course Content

This course provides an introduction to supervised statistical learning techniques such as decision trees, random forests and boosting and discusses
their potential application in the social sciences. These methods focus on predicting an outcome Y based on some learned function f(X) and therefore facilitate new research perspectives in comparison with traditional regression models, which primarily focus on causation. Predictive methods also provide a valuable extension to the empirical social scientists’ toolkit as new data sources become more prominent. In addition to introducing supervised learning methods, the course will include practical sessions to exemplify how to tune, evaluate and interpret prediction models using R.

Learning outcomes: At the completion of this course, students will have a profound understanding of tree-based prediction methods and the machine learning perspective on statistical modeling. Students will learn the computational skills to apply and evaluate these methods using R.

Form of assessment: Presentation and / or term paper


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
18.02.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
03.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
17.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
31.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
21.04.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
05.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
19.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211

Lecturer(s)


Course Type: elective course

Course Number: MKT 803

Credits: 8

Course Content

This course takes an 'information processing' perspective to examine consumer behavior. The key focus will be to examine how consumers process marketing stimuli and make decisions. This includes topics such as motivation, attention and comprehension, memory, attitudes and attitude change, and decision making models. Both classic and current papers on these topics will be discussed.

The goal of this seminar is to provide insights into research and content issues in Consumer Behavior. Students will read key research papers on important topics and critically evaluate the studies.

Learning outcomes: Students will gain insights into research and content issues in Consumer Behavior. Students will read key research papers on important topics and critically evaluate the studies. Students will be expected to read assigned articles prior to class and be prepared to discuss them.

Course evaluation: Essay (50 %), presentation (25 %), participation (25 %)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
12.05.20
Tuesday
14:00
17:00
L 5, 1, room 009
13.05.20
Wednesday
09:00
12:00
L 5, 1, room 009
20.05.20
Wednesday
09:00
12:00
L 5, 1, room 009
22.05.20
Friday
09:00
12:00
L 5, 1, room 009

Lecturer(s)


Course Type: elective course

Course Number: MKT 902

Credits: 6

Course Content

The primary goal of Advances in Marketing Research is to help students prepare to conduct research which is publishable in the leading research journals in their respective disciplines.  Hence, the feedback students receive will be consistent with that dispensed by the reviewers and editors of the most prestigious research journals in business (i.e., highly critical).  Even when a manuscript is accepted for publication at a leading journal, the authors typically receive mostly negative comments on their work.  It is important that students not take criticism of their research personally.  To do so would be extremely ego deflating and would interfere with their subsequent performance on other assignments.  Moreover, students need to develop the ability to accept and use criticism to be able to survive in the academic publishing world.

Learning outcomes: Advances in Marketing Research is designed to assist doctoral candidates in acquiring a deeper understanding of the research process and a knowledge of the research tools which they will need to design and execute scientific research on behavioral and organizational issues in marketing.  An effort is made to help the students develop research judgment as well as research skills so that they will be better able to assess when a proposed piece of research is likely to be fruitful and when it is not.

Form of assessment: Essay: 50%, presentation: 30%, discussion and simulation/statistical analysis: 20%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
14.02.20
29.05.20
Friday
15:30
17:00
L 5, 2, room 107

Lecturer(s)


Course Type: elective course

Course Number: RES

Credits: 5

Course Content

This course will introduce student to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS.

The course consists of four core building blocks:

1. Kick-Off & Introductory Session: What is interdisciplinary research.

After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by me, each participant will shortly (max 10 min, 3 slides per person) present the core idea of an interdisciplinary paper that involves her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is.

2. GESS Research Day

The GESS research day - kindly co-organized by your student representatives - consists of presentations by PhD students from all three centers and discussion panels with senior experts. Participation at the GESS Research Day is mandatory for all course participants. You will give  presentation on a current working paper or research project of yours and you will  discuss a paper/presentation from one of your fellow students from another field (15-20 min presentation, 5 min discussion, 5 min Q&A). Additionally, you will participate in one discussion panel. The idea of the discussion panels is to bring together students from different centers to discuss core topics of societal relevance. Within these panels, the students should talk about how their own field might contribute to the discussion of a specific topic and ideally come up with some joint interdisciplinary research ideas.

3. Science Speed Dating

The science speed dating event - also organized by your student representatives - involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a students from another field.

4. Project Presentations & Writeups

The proposals will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. These teams will also prepare a write-up of their proposal (max. 5 pages, incl. References) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in one week after the presentation.

Learning Outcomes: Upon successful completion of this course, students will

  • have gotten in touch with a variety of disciplinary research methods and perspectives from different fields
  • critically evaluate the strengths and weaknesses of these research methods
  • identify and develop an interdisciplinary research proposal and communicate their ideas clearly in both, a presentation and in writing.
  • have practiced to present their work to a critical, interdisciplinary audience and to discuss other students work in a format closely resembling that of most academic conferences.

Form of assessment:

This is a Pass/Fail course. To successfully pass the course, each student has to:

  • Give a short paper presentation in the introductory session.
  • Present, discuss, and participate in one discussion panel at the GESS Research Day. An extended abstract and the set of slides that will be used for the presentation or (preferably) a working paper draft needs to be provided by each presenting student to the assigned discussant two weeks before the research day.
  • Participate at the science speed dating event.
  • Present your interdisciplinary research proposal (group of two students) and subsequently hand in a the write-up
  • Full and active participation in all four building blocks is necessary to pass the course.
  • The best interdisciplinary proposal will win a price.

Please register by the registration deadline by sending title and abstract of the research project/topic you would like to present during the GESS research day to registration@gess.uni-mannheim.de. Please indicate in your e-mail your fields of interest and mention up to three broad other fields (e.g. Marketing, Macroeconomics, Social Psychology) you would like to collaborate with.

Please note that the course is limited to a maximum of 24 participants, and seats will be allocated on a first come first serve basis.


Course Dates:

March 11th, 2020, 10am-1pm, Kick-Off Meeting, Room 409 in L9, 1-2 (4. OG)        

April 23th, 2020, Deadline to send paper to discussant (and in cc: to gess@uni-mannheim.de)

April 30th, 2020, Research Day (whole day symposium)

May 4th, 2020, time TBA - Science Speed Dating Event

May 28th, 2020, Presentation of research proposal (half- to full day symposium)


Course Room: B6, 30-32, room 211


Lecturer(s)


Course Type: core course

Course Number: IS / OPM 910

Course Content

The course focuses on current research topics in the field of information systems and operations management. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The course introduces students to the variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in information systems and operations management. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Form of assessment: Oral participation.


Seminar Dates are announced here.



Lecturer(s)


Course Type: core course

Course Number: OPM 806

Credits: 8

Prerequisites

Recommended: Fundamentals of statistics


Course Content

A large part of research in operations management focusses on modeling and solving practical problems. In contrast to this “OR approach”, the objective of empirical research is to collect data about practical phenomena in order to describe, explain, or predict how those phenomena work. This module provides an overview of (mainly quantitative) empirical research approaches to investigate research questions in operations management and related fields. The focus in not on the comprehensive treatment of empirical research methods, but on how to proceed from having a basic research question to an appropriate research design and methodology. Hence, special emphasis will be placed on the importance of understanding the contingent relationship between the nature of the research question and the research design used to answer it. Topics covered include quantitative vs. qualitative empirical research, framing of research questions, engaging theory and grounding of hypotheses, measurement and operationalization, sampling, model specification, and mainstream research designs and methodologies. This will enable students to critically evaluate the quality of the majority of empirical research in operations management and to design convincing research of their own.

The course will be taught using an interactive seminar style and is based on the discussion of a selection of papers.

Learning outcomes: At the end of this course, students have gained the competence to initiate, design, implement, and evaluate empirical research in the social sciences as applied to operations management.

Form of assessment: Oral exam (30 minutes) 60%, presentation 40%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
03.04.20
Friday
08:30
13:30
SO 318
08.05.20
Friday
08:30
13:30
SO 318
15.05.20
Friday
08:30
13:30
SO 318
22.05.20
Friday
08:30
13:30
SO 318


Course Type: core course

Course Number: OPM 999

Credits: 9

Course Content

This course revolves around a research-oriented project that is carried out by the participants on an individual basis. Supported by their supervisors, participants will gain further experience in conducting research and will practice for the preparation of research proposals and own working papers. Topic and research question(s), project structure, and methodology are chosen independently by each student.

Learning outcomes: The main intended learning outcome is to learn and apply the competences for conducting high-quality research studies in operations management. In addition, participants will practice their skills in how to present research findings.

Form of assessment: Essay (70%), presentation (30%)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
Kick-Off
10.02.20
Monday
08:30
10:00
SO 322

Lecturer(s)


Course Type: elective course

Credits: 3

Course Content

It serves to furnish the student with the basics of

- developing scientific writing and written communication skills, in particular

  •  developing a theoretical/empirical/experimental research topic
  •  writing it up in line with today’s mode of communicating scientific content
  •  selecting an appropriate journal
  •  reacting to referee reports
  •  writing a referee report

- developing presentation skills in necessary variation, in particular

  •  presenting a research topic in 30 seconds / 1 minute / 5 minutes
  •  presenting a paper in conference format (20 minutes)
  • presenting a paper within a full seminar format
  • o preparing a formal discussion
  •  reacting to a discussant’s comments
  •  chairing a discussion
  •  contributing to the discussion of somebody else’s paper
     

This is NOT a course in which English language skills are exercised ---although reference is given frequently to how to express matters in that language. Beyond this, it is geared to successfully develop and provide logically consistent scientific arguments in a way that attracts the relevant readership.
 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
28.02.20
Friday
09:00
18:00
L7, 3-5, P043
13.03.20
Friday
09:00
18:00
L7, 3-5, P043

Lecturer(s)


Course Type: elective course

Credits: 6

Prerequisites

Although this course will include a short introduction to R, students are encouraged to work through one or more R tutorials prior or during the first weeks of the course.


Course Content

This course provides an introduction to supervised statistical learning techniques such as decision trees, random forests and boosting and discusses
their potential application in the social sciences. These methods focus on predicting an outcome Y based on some learned function f(X) and therefore facilitate new research perspectives in comparison with traditional regression models, which primarily focus on causation. Predictive methods also provide a valuable extension to the empirical social scientists’ toolkit as new data sources become more prominent. In addition to introducing supervised learning methods, the course will include practical sessions to exemplify how to tune, evaluate and interpret prediction models using R.

Learning outcomes: At the completion of this course, students will have a profound understanding of tree-based prediction methods and the machine learning perspective on statistical modeling. Students will learn the computational skills to apply and evaluate these methods using R.

Form of assessment: Presentation and / or term paper


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
18.02.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
03.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
17.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
31.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
21.04.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
05.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
19.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211

Lecturer(s)


Course Type: elective course

Course Number: OPM 918

Credits: 8

Course Content

This elective course aims at PhD students in Operations. The course is taught in a seminar-style format. Each student gives three presentations about one own research project based on a draft of a paper. The aim is to discuss and sharpen the contributions of that work. The presentations are structured similar to papers in that field:

1.     Models: Problem description, Model formulations, and contributions to scientific literature

2.     Methods: Analytical or algorithmic approaches

3.     Managerial Insights: Structured properties, data analysis, and numerical results

Students act as discussants to presentations of other students. At the end of the seminar students hand in a draft of the paper, which reflects the discussions to each single point.

Learning outcomes: Students will learn how to structure and discuss their own research results for a presentation and for a paper. They will become acquainted with acting as discussant for other topics. They will learn how to identify and sharpen the contributions of their own work. They learn how to present the analysis of data and how to design numerical studies.

Form of assessment: Presentations during the course (60%), active contribution to class discussion (15%), draft of paper (25%)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
11.02.20
26.05.20
Tuesday
08:30
11:45

Lecturer(s)


Course Type: elective course

Course Number: RES

Credits: 5

Course Content

This course will introduce student to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS.

The course consists of four core building blocks:

1. Kick-Off & Introductory Session: What is interdisciplinary research.

After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by me, each participant will shortly (max 10 min, 3 slides per person) present the core idea of an interdisciplinary paper that involves her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is.

2. GESS Research Day

The GESS research day - kindly co-organized by your student representatives - consists of presentations by PhD students from all three centers and discussion panels with senior experts. Participation at the GESS Research Day is mandatory for all course participants. You will give  presentation on a current working paper or research project of yours and you will  discuss a paper/presentation from one of your fellow students from another field (15-20 min presentation, 5 min discussion, 5 min Q&A). Additionally, you will participate in one discussion panel. The idea of the discussion panels is to bring together students from different centers to discuss core topics of societal relevance. Within these panels, the students should talk about how their own field might contribute to the discussion of a specific topic and ideally come up with some joint interdisciplinary research ideas.

3. Science Speed Dating

The science speed dating event - also organized by your student representatives - involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a students from another field.

4. Project Presentations & Writeups

The proposals will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. These teams will also prepare a write-up of their proposal (max. 5 pages, incl. References) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in one week after the presentation.

Learning Outcomes: Upon successful completion of this course, students will

  • have gotten in touch with a variety of disciplinary research methods and perspectives from different fields
  • critically evaluate the strengths and weaknesses of these research methods
  • identify and develop an interdisciplinary research proposal and communicate their ideas clearly in both, a presentation and in writing.
  • have practiced to present their work to a critical, interdisciplinary audience and to discuss other students work in a format closely resembling that of most academic conferences.

Form of assessment:

This is a Pass/Fail course. To successfully pass the course, each student has to:

  • Give a short paper presentation in the introductory session.
  • Present, discuss, and participate in one discussion panel at the GESS Research Day. An extended abstract and the set of slides that will be used for the presentation or (preferably) a working paper draft needs to be provided by each presenting student to the assigned discussant two weeks before the research day.
  • Participate at the science speed dating event.
  • Present your interdisciplinary research proposal (group of two students) and subsequently hand in a the write-up
  • Full and active participation in all four building blocks is necessary to pass the course.
  • The best interdisciplinary proposal will win a price.

Please register by the registration deadline by sending title and abstract of the research project/topic you would like to present during the GESS research day to registration@gess.uni-mannheim.de. Please indicate in your e-mail your fields of interest and mention up to three broad other fields (e.g. Marketing, Macroeconomics, Social Psychology) you would like to collaborate with.

Please note that the course is limited to a maximum of 24 participants, and seats will be allocated on a first come first serve basis.


Course Dates:

March 11th, 2020, 10am-1pm, Kick-Off Meeting, Room 409 in L9, 1-2 (4. OG)        

April 23th, 2020, Deadline to send paper to discussant (and in cc: to gess@uni-mannheim.de)

April 30th, 2020, Research Day (whole day symposium)

May 4th, 2020, time TBA - Science Speed Dating Event

May 28th, 2020, Presentation of research proposal (half- to full day symposium)


Course Room: B6, 30-32, room 211



Course Type: core course

Course Number: ACC / TAX 910

Course Content

The course focuses on current research topics in the field of accounting and taxation. Visiting researchers present their latest working papers and discuss their ideas with participating faculty and students. The presentations have workshop format and are similar in style to leading scientific conferences. For each presentation, a separate preparation session for the Ph.D. students is offered in advance by rotating faculty. Overall, the course deepens the students’ insights into a variety of research methods that are currently popular in empirical and theoretical research.

Learning outcomes: Students will learn to follow-up with and discuss about current research topics in accounting and taxation. The interaction with leading researchers will allow them to develop own research ideas and get insights into the design, execution and presentation of research projects.

Form of assessment: Oral participation.


Seminar Dates are announced here.



Course Type: core course

Course Number: ACC / TAX 920

Course Content

The course is taught in a seminar-style format. Students present their own research ideas at different stages of the project (early ideas, preliminary results, and complete working papers). The presentations involve an interactive discussion between faculty and students about the project’s potential contribution, related literature, research design and interpretation of results.

Learning outcomes: Students will learn how to present and discuss their own research results in a scientific format. They will become acquainted with acting as a discussant for other topics. Students will gain insights into the assessment of contribution, research design, and interpretation of research papers. The development of these skills is also helpful for writing scientific referee reports.

Form of assessment: Class Participation


Coursedates will be announced via email to registered participants.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
12.02.20
27.05.20
Wednesday
13:45
17:00
O 048

Lecturer(s)


Course Type: core course

Course Number: TAX 801

Credits: 8

Course Content

This course integrates tax law with national and international tax planning. The main topics include:

  1. Fundamentals of tax planning and tax neutrality
  2. The choice of the organizational Form
  3. Flat tax and dual income Tax
  4. International tax planning
  5. Effective tax rates

Learning outcomes: The course gives guidance to students who are interested in the impact of taxes on the decisions of firms. The focus is on investment and financing decisions as well as on location decisions both from a national and from an international perspective.

Form of assessment: Presentation 50%, class participation 50%


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
12.02.20
27.05.20
Wednesday
08:30
11:45
SO 133

Lecturer(s)


Course Type: elective course

Credits: 3

Course Content

It serves to furnish the student with the basics of

- developing scientific writing and written communication skills, in particular

  •  developing a theoretical/empirical/experimental research topic
  •  writing it up in line with today’s mode of communicating scientific content
  •  selecting an appropriate journal
  •  reacting to referee reports
  •  writing a referee report

- developing presentation skills in necessary variation, in particular

  •  presenting a research topic in 30 seconds / 1 minute / 5 minutes
  •  presenting a paper in conference format (20 minutes)
  • presenting a paper within a full seminar format
  • o preparing a formal discussion
  •  reacting to a discussant’s comments
  •  chairing a discussion
  •  contributing to the discussion of somebody else’s paper
     

This is NOT a course in which English language skills are exercised ---although reference is given frequently to how to express matters in that language. Beyond this, it is geared to successfully develop and provide logically consistent scientific arguments in a way that attracts the relevant readership.
 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Seminar
28.02.20
Friday
09:00
18:00
L7, 3-5, P043
13.03.20
Friday
09:00
18:00
L7, 3-5, P043

Lecturer(s)


Course Type: elective course

Credits: 6

Prerequisites

Although this course will include a short introduction to R, students are encouraged to work through one or more R tutorials prior or during the first weeks of the course.


Course Content

This course provides an introduction to supervised statistical learning techniques such as decision trees, random forests and boosting and discusses
their potential application in the social sciences. These methods focus on predicting an outcome Y based on some learned function f(X) and therefore facilitate new research perspectives in comparison with traditional regression models, which primarily focus on causation. Predictive methods also provide a valuable extension to the empirical social scientists’ toolkit as new data sources become more prominent. In addition to introducing supervised learning methods, the course will include practical sessions to exemplify how to tune, evaluate and interpret prediction models using R.

Learning outcomes: At the completion of this course, students will have a profound understanding of tree-based prediction methods and the machine learning perspective on statistical modeling. Students will learn the computational skills to apply and evaluate these methods using R.

Form of assessment: Presentation and / or term paper


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
18.02.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
03.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
17.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
31.03.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
21.04.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
05.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211
19.05.20
Tuesday
15:30
18:45
B 6, 30-32, room 211

Lecturer(s)


Course Type: elective course

Course Number: RES

Credits: 5

Course Content

This course will introduce student to interdisciplinary research and aims at initiating projects of an interdisciplinary nature, thereby fostering the interdisciplinary spirit of the graduate students at the GESS.

The course consists of four core building blocks:

1. Kick-Off & Introductory Session: What is interdisciplinary research.

After a short introduction on the nature and success of interdisciplinary research as well as the structure of the course by me, each participant will shortly (max 10 min, 3 slides per person) present the core idea of an interdisciplinary paper that involves her field. Please browse the recent issues of the most important journals in your field to find such a paper. Note that interdisciplinarity can have various aspects in this context (e.g., methods developed for a specific purpose in one field being used in another context, using a theoretical framework from one area to better understand a research question in another, using data generated in another context for a research project, ...). Your presentation should make clear, what the interdisciplinary innovation of the paper is.

2. GESS Research Day

The GESS research day - kindly co-organized by your student representatives - consists of presentations by PhD students from all three centers and discussion panels with senior experts. Participation at the GESS Research Day is mandatory for all course participants. You will give  presentation on a current working paper or research project of yours and you will  discuss a paper/presentation from one of your fellow students from another field (15-20 min presentation, 5 min discussion, 5 min Q&A). Additionally, you will participate in one discussion panel. The idea of the discussion panels is to bring together students from different centers to discuss core topics of societal relevance. Within these panels, the students should talk about how their own field might contribute to the discussion of a specific topic and ideally come up with some joint interdisciplinary research ideas.

3. Science Speed Dating

The science speed dating event - also organized by your student representatives - involves short bilateral talks between participants with the later possibility to match research interests. All course participants will participate in the speed dating event and are asked to develop at least one collaborative research proposal with a students from another field.

4. Project Presentations & Writeups

The proposals will be presented by groups of 2 (in exceptional cases 3) students in a final meeting about four weeks after the speed dating event. These teams will also prepare a write-up of their proposal (max. 5 pages, incl. References) explaining the intended contribution to the literature, the interdisciplinary aspects of the project and the proposed procedure how to implement the project to be handed in one week after the presentation.

Learning Outcomes: Upon successful completion of this course, students will

  • have gotten in touch with a variety of disciplinary research methods and perspectives from different fields
  • critically evaluate the strengths and weaknesses of these research methods
  • identify and develop an interdisciplinary research proposal and communicate their ideas clearly in both, a presentation and in writing.
  • have practiced to present their work to a critical, interdisciplinary audience and to discuss other students work in a format closely resembling that of most academic conferences.

Form of assessment:

This is a Pass/Fail course. To successfully pass the course, each student has to:

  • Give a short paper presentation in the introductory session.
  • Present, discuss, and participate in one discussion panel at the GESS Research Day. An extended abstract and the set of slides that will be used for the presentation or (preferably) a working paper draft needs to be provided by each presenting student to the assigned discussant two weeks before the research day.
  • Participate at the science speed dating event.
  • Present your interdisciplinary research proposal (group of two students) and subsequently hand in a the write-up
  • Full and active participation in all four building blocks is necessary to pass the course.
  • The best interdisciplinary proposal will win a price.

Please register by the registration deadline by sending title and abstract of the research project/topic you would like to present during the GESS research day to registration@gess.uni-mannheim.de. Please indicate in your e-mail your fields of interest and mention up to three broad other fields (e.g. Marketing, Macroeconomics, Social Psychology) you would like to collaborate with.

Please note that the course is limited to a maximum of 24 participants, and seats will be allocated on a first come first serve basis.


Course Dates:

March 11th, 2020, 10am-1pm, Kick-Off Meeting, Room 409 in L9, 1-2 (4. OG)        

April 23th, 2020, Deadline to send paper to discussant (and in cc: to gess@uni-mannheim.de)

April 30th, 2020, Research Day (whole day symposium)

May 4th, 2020, time TBA - Science Speed Dating Event

May 28th, 2020, Presentation of research proposal (half- to full day symposium)


Course Room: B6, 30-32, room 211



Course Type: elective course

Course Number: TAX 913

Credits: 10

Course Content

This course gives an introduction to the main subjects and methodologies of empirical taxation research. Important landmark papers as well as contributions from the current research frontier will be discussed. If the relevant data is available, students get the chance to understand the empirical approach in practice in the computer lab. Following topics may be included:

  • Tax incidence
  • Tax efficiency
  • Taxes in the context of mergers and acquisition
  • Taxation of multinationals
  • Tax avoidance and tax evasion
  • Capital taxation
  • Labor taxation

 

Learning outcomes: The course should enable participants to identify gaps in the existing literature and to evaluate the potential of new research ideas. As a primary objective, the course supports students in developing their empirical research projects.

Form of assessment: Essay and/or presentation


Please note: The course won't take place on Monday, February 24, 2020


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
10.02.20
25.05.20
Monday
13:45
17:00
SO 133
14.02.20
29.05.20
Friday
15:30
17:00
SO 133


Course Type: elective course

Course Number: TAX 922

Credits: 5

Course Content

The reading course is aimed at 2nd and higher year Ph.D. students to support them during their research phase.


The course provides a forum to discuss recent state-of-the art papers in taxation research (mostly applied empirical). All covered papers are recently published or in the working paper stage. In each class session, one student briefly presents a research paper before the paper is discussed in class. All students are expected to read the research paper to be discussed in preparation for the class and it is one main objectives of the course that papers are lively discussed among all class participants.

Students can choose papers which they wish to present or the responsible instructors provide a selection from which to pick. Students are encouraged to choose papers which are on the reading list for their thesis. The course could also serve as a forum for discussing paper drafts of peers or researchers within the network.

In addition to presenting a paper in class, students are expected to write a referee report for a research paper. This will teach how to evaluate a paper critically and how to write a referee report.

Learning outcomes:

  • Know your field and related fields: Learn about the literature, both in your own (sub-field) of interest and other fields.
  • Commit to a reading routine for your thesis
  • Community building: The reading group will spawn discussion and encourage community building
  • Ability to present and confidence building: Learn how to present well. (This is often easier with a paper that somebody else wrote – one is not as emotionally involved in the question/ approach/ results as with one’s own paper.)
  • Discussion competence: Learn how to be a good seminar participant: Behave well, ask clear questions, discuss in an appropriate manner etc.
  • Ability to understand: Learn how to read and approach research papers and learn to summarize the main message/points of the paper
  • Participation in scientific discourse
  • Learn how to evaluate a paper critically
  • Writing a referee report

Form of assessment: Paper (referee report) 40 %, Presentation 30 %, Class Participation 30 %


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
11.02.20
26.05.20
Tuesday
10:15
11:45
O 326/28

Register

Business Spring 2020

ACC / TAX 910
Area Seminar Accounting and Taxation
ACC / TAX 920
Brown Bag Seminar
ACC 903
Empirical Accounting Research I (Research Methods)
ACC 904
Empirical Accounting Research II (Causal Inference)
English Academic Writing for Economics and Business
Machine Learning
ACC 921
Topics in Analytical Accounting Research
RES
Interdisciplinary Work in the Economic and Social Sciences (Bridge Course)
FIN 620
Behavioral Finance
FIN 802
Continuous Time Finance
FIN 803
Corporate Finance
FIN 804
Econometrics of Financial Markets
FIN 901
Behavioral Finance
FIN 910
Area Seminar Finance
FIN 913
Advanced Quantitative Risk Management
IS / OPM 910
Area Seminar Information Systems and Operations Management
IS 807
Designing Qualitative Research Projects
IS 911
Context-Aware Computing
MAN 801
Advances in Entrepreneurship and Management Research
MAN 804
Advances in Strategic Managment
MAN 807
Experimental Research in Management
MAN 910
Area Seminar Management
MAN 808
Organization Theories
MKT 804
Theory Development and Model Building
MKT 910
Area Seminar Marketing
MKT 803
Consumer Behavior
MKT 902
Advances in Marketing Research
OPM 806
Empirical Research in Opeartions Management
OPM 999
Project Study Operations
OPM 918
Business Analytics: Models, Methods, Managerial Insights
TAX 801
Business Taxation
TAX 913
Empirical Taxation Research
TAX 922
Reading Course Taxation Research