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 2017

Lecturer(s)


Course Type: core course

Course Number: ACC 802

Credits: 6

Prerequisites

Recommended: Basics in agency-theory, decision theory and game theory


Course Content

This course considers the use of accounting information in firms. In particular, the focus is on the use of accounting information for decision making and stewardship. From a methodology perspective game-theoretic models covering the following fields are considered:

  1. Accounting
  2. Auditing
  3. Corporate Governance

Learning outcomes: Students are able to understand and discuss game-theoretic representations of accounting issues. Further, they are able to set up simple models on their own.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
14.02.17
30.05.17
Tuesday
17:15
18:45
14.02.17
30.05.17
Tuesday
17:15
18:45
O 226/28

Lecturer(s)


Course Type: core course

Course Number: ACC 903

Credits: 6

Course Content

This course provides a comprehensive overview of research topics and methodologies in influential classic and contemporaneous papers in the empirical accounting literature. In particular, we cover the literature on value relevance and earnings response coefficients/event studies, accounting-based valuation, earnings management, conservatism, voluntary and mandatory disclosures, other information channels, and international research. Students are expected to prepare all readings and to lead the class discussions about assigned papers in the second half of each lecture.

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.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
14.02.17
04.04.17
Tuesday
14:15
17:15
SO 133

Lecturer(s)


Course Type: core course

Course Number: ACC 904

Credits: 6

Prerequisites

Recommended: Empirical Accounting Research I, Advanced Econometrics I, Applied Econometrics


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.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
24.04.17
Monday
10:00
13:00
O 254
08.05.17
Monday
10:00
13:00
O 254
17.05.17
Wednesday
09:30
12:00
O 254
24.05.17
Wednesday
10:00
13:00
O 254
29.05.17
Monday
10:00
13:00
O 254
07.06.17
Wednesday
10:00
13:00
O 254


Course Type: elective course

Course Number: ACC 920/TAX 920

Credits: 6

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.

Form of assessment: Presentation (50%), Class Participation (50%)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
21.02.17
Tuesday
12:30
13:30
SO 133
28.02.17
Tuesday
12:30
13:30
SO 133
08.03.17
Wednesday
17:15
18:46
SO 318
28.03.17
Tuesday
12:00
13:30
SO 133
16.05.17
Tuesday
12:00
13:30
SO 133
23.05.17
Tuesday
12:00
13:45
SO 133
14.06.17
Wednesday
11:30
12:00
SO 133

Lecturer(s)


Course Type: core course

Course Number: FIN 802

Credits: 8

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 modeling and analyzing financial price processes in continuous time.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
22.02.17
Wednesday
10:30
18:00
L9, 1-2 room 409
22.03.17
Wednesday
10:30
18:00
L9, 1-2 room 409
03.05.17
Wednesday
10:30
18:00
L9, 1-2 room 409

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 participants to understand and conduct research in some selected areas of corporate finance. It is taught at a first-year doctoral level and combines two objectives. Firstly, participants learn some of the classic contributions to the theory of modern corporate finance and understand the main contributions in the respective area. 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.

 

For course details, click here.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
24.02.17
Friday
08:30
13:30
L9, 1-2 - room 409
10.03.17
Friday
08:30
13:30
L9, 1-2 - room 409
24.03.17
Friday
08:30
13:30
L9, 1-2 - room 409
07.04.17
Friday
08:30
13:30
L9, 1-2 - room 409
28.04.17
Friday
08:30
13:30
L9, 1-2 - room 409
05.05.17
Friday
08:30
13:30
L9, 1-2 - room 409

Lecturer(s)


Course Type: core course

Course Number: FIN 804

Credits: 6

Prerequisites

Basic knowledge in mathematics and statistics at the Bachelor level.

Recommended: Students should have successfully completed the 2-semester finance module of the Mannheim Bachelor program (or equivalent). It is recommended but not required that the students have participated in the Mathematics for Economists (E 700) and the Discrete Time Finance (FIN 801) courses.


Course Content

The first part of the course provides a brief refresher of several econometric concepts such as endogeneity, multicollinearity and selection bias. The second part of the course covers a number of topics and their applications in asset pricing, including the Fama-MacBeth regression approach and the GMM estimation methodology. The final part of the course is devoted to methodological questions in corporate finance with a focus on event studies, panel econometrics and discrete choice modelling.

Learning outcomes: The course provides students with a knowledge of several prevalent econometric concepts in finance and contributes to students’ ability to plan and carry out independent empirical research in the areas of empirical asset pricing and corporate finance.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
14.02.17
25.04.17
Tuesday
16:15
17:45
L9, 7 – room 308
Colloquium
23.05.17
30.05.17
Tuesday
15:30
19:30
L9, 7 – room 308

Lecturer(s)


Course Type: core course

Course Number: FIN 901

Credits: 6

Course Content

This course includes FIN620: 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. Behavioral finance applies scientific research on human and social cognitive and emotional biases. 

Learning outcomes:

Understanding the psychology of investors and potential biases in financial markets


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
Introductory session: compulsory
16.02.17
16.02.17
Thursday
11:45
12:00
0151
21.02.17
30.05.17
Tuesday
13:45
15:15
L5, 2 room: 107

Lecturer(s)


Course Type: elective course

Course Number: FIN 913

Credits: 8

Prerequisites

The course assumes some knowledge of probability theory and statistics and as well some knowledge of financial instruments and their valuation.

German language skills required.


Course Content

This course includes FIN660. Subject of the course are advanced concepts for measuring risk, quantitative methods for the management of market risks and credit risks and approaches to risk based performance management and capital allocation.

Literature: Albrecht/Huggenberger (2015): Finanzrisikomanagement, Stuttgart.


Competences acquired

After a successful completion of the course participants are familiar with the most important risk measures and their parametric/non-parametric estimation, with methods of calculating the value at risk of individual financial positions and portfolios of financial instruments, especially the delta-normal-method. They also have knowledge of the notion of credit value at risk and the most important credit risk models. Finally, they are familiar with the concept of return on risk adjusted capital (RORAC) and the fundamental approaches to capital allocation.

 

Course dates will depend on the availability of the participants. Please contact Mr. Huggenberger (huggenberger(at)bwl.uni-mannheim.de)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
Kick-off
14.02.17
Tuesday
12:00
13:30
O 328

Lecturer(s)


Course Type: core course

Course Number: IS 807

Credits: 9

Prerequisites

IS 801, IS 806, IS 901, IS 903

This course is open for students who write their disserttion proposal at a chair of the Information Systems department.


Course Content

This course is designed to facilitate the development of a MMBR Thesis / CDSB Dissertation Proposal.  Thus, it will take place in parallel to these activities. Participating students are required to

  • conduct a profound literature search for developing the respective theoretical / technological state-of-the-art in their respective field,
  • for identifying prospective avenues of substantial research in this field which includes the foundations for theoretical research model / technology architecture and solution design.

The process of a literature search and model / architecture definition will be accompanied by discussion between students and their respective instructors as well as by mutual student feedback.

Learning outcomes: Students are supposed to conduct a substantial literature review which provides the basis for designing novel research avenues. Furthermore, students are trained to achieve this goal in a continuous academic discourse with instructors and other students.


Lecturer(s)


Course Type: elective course

Course Number: IS 904

Credits: 6

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 three types of qualitative research, i.e. positivist variance-theoretic, interpretive (and/or grounded theory based), and process theoretic. For each of them, the underlying principles will be discussed with illustrative examples. The students are required to summarize and discuss particular research papers and to reflect on how the principles of conducting qualitative research were applied in the respective papers. For particular topics the students will be grouped into teams and will be required to prepare their group work and present it in class. Overall, the course is designed to be interactive. The students may also illustrate the application of particular methods based on their own paper and data, if they wish.
 
 
Grading:
 
The course will be graded based on three inputs:
20% Contributions of the students to class discussions during the sessions
30% Group presentation
50% Written research proposal, which has to be presented in form of a written research-in-progress paper after the course. In this paper, the students are required to elaborate a research proposal in which they show how a topic of their choice (e.g. their dissertation topic) could be examined (either entirely, partly, or complementarily) using (at least) one of the discussed qualitative research approaches. This paper is due July, 31, 2017. Details about the proposal, including an example, will be provided at the end of the course. The instructor will provide a 1-2 page feedback on each proposal. 

 
Readings for Class Discussion:
 
A collection of papers will be provided prior to the course in electronic form (see Schedule with Literature). The students are required to read the literature highlighted in BOLD prior to the sessions. The other readings (including the basic literature) are recommended but are not obligatory readings.
 


Basic readings:
 
Yin, Robert K. Case study research: design and methods, 4th Edition, 2009
Miles, M.B., and Huberman, M.A. Qualitative Data Analysis: An Expanded Sourcebook. Sage Publications, Thousand Oaks, CA, 1994.
Strauss, A. and J. Corbin. 1998. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. Thousand Oaks, CA: Sage Publications. 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
29.05.17
Monday
14:00
18:00
L 15, 1-6, room 422
30.05.17
Tuesday
09:00
12:15
L 15, 1-6, room 422
31.05.17
Wednesday
14:00
18:00
L 15, 1-6, room 422
01.06.17
THursday
09:00
12:15
L 15, 1-6, room 422

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 research. Students are invited to develop 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 research find appropriate theoretical concepts and lenses and apply them properly to their individual research topics.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
22.02.17
Wednesday
10:00
11:30
L9, 1-2 –Room 210
22.03.17
Wednesday
09:00
18:00
L9, 1-2 –Room 210
26.04.17
Wednesday
09:00
18:00
L9, 1-2 –Room 210

Lecturer(s)


Course Type: core course

Course Number: MAN 804

Credits: 6

Prerequisites

The seminar serves the purpose of familiarizing students with the most relevant research streams and trends in strategy research. Besides a review of the current state-of-the-art, we will engage in a discussion about the most prevalent theoretical lenses, key subject areas and phenomena as well as the empirical designs applied by scholars in these areas.

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

Capitalize on a critical reflection of the current state of the literature, to develop a research proposal


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
22.02.17
Wednesday
14:00
16:00
02.05.17
Tuesday
08:30
18:00
03.05.17
Wednesday
08:30
18:00

Lecturer(s)


Course Type: core course

Course Number: MKT 802

Credits: 6

Course Content

  • Explore the holistic process of development of marketing thought, theory construction, and theory testing using the structural equation modeling (SEM) framework.
  • Identify and explore potential substantive theoretical contributions to the marketing literature and present these in class.
  • Theory testing and construct validation (measurement properties) using the SEM framework.
  • Provide opportunity to exercise and extend scholarly analytical skills in order to facilitate students’ ability to conduct sound and rigorous academic research.

Seminar organization: The course will consist of assigned reading material, lectures, student presentations, and discussions. Lectures will be intended to elaborate points that might be difficult to glean from readings and to stimulate discussion. Generally, the course will be instructor guided but student run. That is, participants will be responsible for reading and analyzing course readings prior to class, presenting the assigned material, leading discussions on this material, and contributing additional relevant material on topics covered.The success of the course is heavily dependent on all participants having relatively equal levels of knowledge about each topic. It is critical, therefore, that all participants read the material in advance of each class session. There is a set of reading material distributed prior to class beginning and during the course.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
29.03.17
Wednesday
13:45
15:15
Roche Forum (L5, 1)
03.05.17
Wednesday
13:45
17:00
Roche Forum (L5, 1)
05.05.17
Friday
13:45
15:15
10.05.17
Wednesday
13:45
15:15
Roche Forum (L5, 1)
17.05.17
Wednesday
13:45
15:15
Roche Forum (L5, 1)
24.05.17
Wednesday
13:45
15:15
Roche Forum (L5, 1)
31.05.17
Wednesday
09:00
17:00
Roche Forum (L5, 1)

Lecturer(s)


Course Type: core course

Course Number: MKT 901

Credits: 6

Prerequisites

MKT 801


Course Content

In this course, students will develop their own marketing research projects (e.g., as parts of their own dissertation projects). In presentation sessions, students will present their research project to all participants of the class and to the instructor. Discussions among partici­pants as well as the instructor’s feedback aim at strengthening and refining the positioning and the contribution of the individual projects. Students in the first year of their Ph.D. studies can thus use this course to get important insights for the preparation and refinement of their disser­ta­tion proposal.

At the beginning of the course, objectives, general guidelines, and best practices for developing impactful research projects will be provided in a kick-off meeting. Furthermore, best practices how to get published in leading journals will be discussed. Then, students will start developing their projects. Students are not limited with respect to the choice of their individual research topic; however, it is made in accordance with the instructor.

Students will prepare the project by developing a presentation containing the positioning and research questions, a brief literature review, the theoretical foundations and research hypotheses, as well as an outlook on potential methodological approaches (such as obtaining and analyzing adequate data). Students will present their research projects. Based on the course participants’ and the instructor’s feedback, students can update and refine their research projects.

Learning outcomes:

  • Development of own marketing research project
  • presentation of own marketing research project
  • providing feedback on marketing research projects

This course aims at preparing students to formulate their own marketing research problems (e.g., as parts of their dissertation projects), to shape their contribution with respect to the existing literature, and to identify the necessary data and methods to conduct their research projects. As benchmark for the students’ research projects, the actual standards with respect to innovative­ness, relevance, and rigor of the leading international marketing journals will be applied. Furthermore, implications for practice have to be considered.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
21.02.17
Tuesday
14:00
16:00
Roche Forum in L5, 1
21.03.17
Tuesday
09:00
12:00
Roche Forum in L5, 1
22.03.17
Wednesday
09:00
12:00
Roche Forum in L5, 1
28.03.17
Tuesday
09:00
12:00
Roche Forum in L5, 1

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 and involvement, attention and comprehension, memory, attitudes and attitude change, and decision making models. In each session, the Professor will provide a brief overview of the topic. Then, both classic and current papers on these topics will be discussed. Students will be expected to read assigned articles prior to class and be prepared to discuss them.

Course schedule, topics, and reading assignments
1. May 5, 2017, 9.00h – 12.00h: Consumer Information Processing
Martin(2012), Raghunathan, Walker-Naylor, & Hoyer (2006)
2. May 8, 2017, 9.00h – 12.00h: Low Involvement/Unconscious Processing
Broniarczyk, Hoyer, & McAlister (1998), van Kerckhove, Geuens, & Vermeir (2015)
3. May 10, 2017, 9.00h- 12.00h: Information Search
Huang, Lurie, & Mitra (2009), Moore (2015)
4. May 12, 2017, 9.00h – 12.00h: Decision Making
Simonson & Sela (2011), Mehta, Hoegg, & Chakravarti (2010)

5. May 15, 2017, 9.00h – 12.00h: Attitudes and Persuasion
Shu & Carlson (2014), Dahl, Sengupta, & Vohs (2009)
6. May 17, 2017, 9.00h – 12.00h: Affect and Heuristics
Malaer, Krohmer, Hoyer, & Nyffenegger (2011), Mogilner, Aaker, & Kamvar (2012)
All sessions take place at the Roche Forum, L 5, 1, ground floor.
Students will get the articles by E-Mail after the registration for the course is finished.

Evaluation of articles and paper presentation
When reading each of the articles, you should think about and be prepared to discuss the following. Is important to identify both the strengths and weaknesses of the paper (i.e., this is not an exercise meant to just attack papers; rather, much can be learned by identifying what is good about a paper as well).
1. Do the authors motivate the topic adequately (i.e., why is it interesting and important)? What are the research gaps?
2. What are the theoretical foundations for hypotheses or arguments made? Is there strong support for the authors’ arguments?
3. Is there logic, internal consistency, and a strong linkage between theory and hypotheses or arguments?
4. Are the hypotheses interesting and testable or falsifiable (i.e., ability of design to eliminate alternative hypotheses or competing theoretical explanations)?
5. What is the originality of the contribution to the extant body of knowledge in discipline (i.e., what do we learn that is new?)?
6. Are the research methods employed to test hypotheses and measure key constructs strong in terms of internal and external validity?
7. Are the data analyzed and reported accurately?
8. What are the key implications of the findings for understanding consumer behavior and marketing?

Research Proposal
Each student is expected to write a research proposal within one of the major topic areas. The paper should be more than merely a literature review. It should develop an area in which research is needed and then proceed to develop a specific research topic including hypotheses, a proposed methodology, and an analysis plan. The paper should be a maximum of 20 double-spaced pages in length (including all exhibits and references) and has to be prepared by the end of the semester.

Course evaluation
Paper presentation (25%), class participation (25%), and the research proposal (50%).


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
05.05.17
Friday
09:00
12:00
Roche Forum (ground floor) in L5, 1
08.05.17
Monday
09:00
12:00
Roche Forum (ground floor) in L5, 1
10.05.17
Wednesday
09:00
12:00
Roche Forum (ground floor) in L5, 1
12.05.17
Friday
09:00
12:00
Roche Forum (ground floor) in L5, 1
15.05.17
Monday
09:00
12:00
Roche Forum (ground floor) in L5, 1
17.05.17
Wednesday
09:00
12:00
Roche Forum (ground floor) in L5, 1

Lecturer(s)


Course Type: elective course

Course Number: MKT 902

Credits: 6

Prerequisites

Recommended: MKT 801 Fundamentals of Marketing Research


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.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
17.02.17
09.06.17
Friday
10:15
13:30
L9, 1-2 – room 009

Lecturer(s)


Course Type: core course

Course Number: OPM 920

Credits: 8

Prerequisites

 

Profound knowledge in Operations Research

        A computer (preferably a notebook so you can learn and practice in and out of class) running any of Windows®, Mac®, or Linux®.

        We will use Python 3 and the open source Anaconda® platform that is available on Windows®, Mac®, and Linux®. In case of Windows®, you may need to have administrator rights for installing the software.

        If you don’t have Anaconda® installed we will install it at the beginning of the course.

        Basic experience with computers and programming: you are familiar with the concept of files and directories and are able to install software on your computer.


Course Content

 

The course examines new developments and current methods in operations research. Possible subject areas include e.g. nonlinear and integer optimization, queuing, stochastic programming, network theory, empirical methods, and specialized applications. A topic will be selected for thorough study.

The course offered in spring 2017 is a computer programming introductory course presenting the Python language elements, the concepts of structured programming, and includes a first view at object oriented programming. There are hands-on exercises throughout the course. In addition students learn algorithmic thinking. They implement and test optimization algorithms or heuristics. They learn how state of the art solver are embedded in Python.

It teaches

•        what computer programming is about

•        how to write programs in Python

•        how to understand existing Python code

•        how to solve programming problems on your own

•        where to look for more information

In addition to learning Python:

After completing the course, you will be able to learn any programming language a lot easier!

Some hints on similarities and differences compared to other languages such as C/C++, Java, PHP, and Fortran are included for participants who have some knowledge of another programming language.

Course language

The course is held in English. The course material will be provided in English.

Form of assessment: Assignment 70%, Presentation 30%

Schedule

Introduction phase: tba (4 h between 29.05. and 09.06.)

Block phase:

·         13.06. 13:45-18:45

·         14.06. 10:15-18:45

·         15.06. 10:15-13:30

Assignment discussion: tba (4 h between 26.06. and 24.07)

Registration: Please send your CV with transcripts to production@bwl.uni-mannheim.de

 


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
13.06.17
13.06.17
Tuesday
13:45
18:45
SO 318
14.06.17
14.06.17
Wednesday
10:15
18:45
SO 318
15.06.17
15.06.17
Thursday
10:15
13:30
SO 318


Course Type: elective course

Course Number: OPM 802

Credits: 8

Prerequisites

Recommended: Fundamentals in mathematics and statistics


Course Content

The course introduces some fundamental techniques for stochastic modelling and optimization, and it discusses their application in supply chain research. Key topics include:

  • Stochastic processes
  • Markov chains
  • Stochastic dynamic programming
  • Inventory theory
  • Revenue management

The course is taught in a seminar-style format.

Learning outcomes: The course aims to introduce the participants to fundamental stochastic modeling techniques. Upon completion of this course, participants should be able (i) to read and understand corresponding academic papers and (ii) to develop and analyze stochastic models for supply chain management issues.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
14.02.17
06.06.17
Tuesday
15:30
17:00
SO 318

Lecturer(s)


Course Type: elective 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.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
24.02.17
07.04.17
Friday
08:30
13:30

Lecturer(s)


Course Type: core course

Course Number: TAX 801

Credits: 8

Prerequisites

Recommended: Basic knowledge of national and international tax law


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.


Lecturer(s)


Course Type: core course

Course Number: TAX 801

Credits: 8

Course Content

Contents:

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.


Competences acquired

TAX 801


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
01.06.17
Thursday
08:30
18:45
02.06.17
Friday
08:30
18:45

Lecturer(s)


Course Type: core course

Course Number: TAX 913

Credits: 10

Prerequisites

Recommended: Advanced Econometrics I or Applied Econometrics I


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.


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
13.02.17
29.05.17
Monday
13:45
15:15
16.02.17
01.06.17
Thursday
10:15
11:45


Course Type: elective course

Credits: 4

Course Content

With this course we want to offer a special interest course covering highly research relevant topics on tax related R&D issues. The goal is to connect students with topics on the research frontier for R&D taxation with renowned scholars. To achieve this goal, we propose a unique interactive course designed as a workshop to grasp current research of both PhD students and renowned academics. The mutual exchange between participants from the University of Mannheim with other scholars will help to foster future state-of-the-art research conducted by GESS students and help them by providing networking opportunities.

Participants get valuable feedback for their conducted research. In addition, they get to know with other scholars working in this field and learn about their work. After completion of the workshop, participants should be able to critically evaluate research of their own and others to improve their work. In addition, young scholars are enable opportunities for future research collaborations.

The course will encompass two days. On the first day, renowned academics from leading universities will present novel research in lengthy seminar-style blocks. All participants will be given the opportunity to further discuss with the presenters. On the second day, PhD students will be given the opportunity to present their research projects. The presentations of PhD students will be more focused on receiving feedback to enhance and enrich their contribution.

To foster exchange between senior researchers and PhD students and provide networking opportunities for all participants, the summer school will include a dinner as well as several coffee breaks and lunches.

 

Learning Outcomes

Participants get valuable feedback for their conducted research. In addition, they get to know with other scholars working in this field and learn about their work. After completion of the workshop, participants should be able to critically evaluate research of their own and others to improve their work. In addition, young scholars are enable opportunities for future research collaborations.

 

Date

July 24-25, 2017

 

To register, please mail to: taxsummerschool@zew.de



Course Type: elective course

Course Number: ACC 920/TAX 920

Credits: 6

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.

Form of assessment: Presentation (50%), Class Participation (50%)


Schedule

Type
From
To
Weekday
From
To
Room
Material
Lecture
21.02.17
Tuesday
12:30
13:30
SO 133
28.02.17
Tuesday
12:30
13:30
SO 133
08.03.17
Wednesday
17:15
18:46
SO 318
28.03.17
Tuesday
12:00
13:30
SO 133
16.05.17
Tuesday
12:00
13:30
SO 133
23.05.17
Tuesday
12:00
13:45
SO 133
14.06.17
Wednesday
11:30
12:00
SO 133

Register

Business Spring 2017

ACC 802
Analytical Research in Accounting
ACC 903
Empirical Accounting Research I (Research Methods)
ACC 904
Empirical Accounting Research II (Causal Inference)
ACC 920/TAX 920
Brown Bag Seminar Accounting and Taxation
FIN 802
Continuous-Time Finance
FIN 803
Corporate Finance
FIN 804
Econometrics of Financial Markets
FIN 901
Behavioral Finance
FIN 913
Advanced Quantitative Risk Management
IS 807
Project Course
IS 904
Qualitative Research Methods in Information Systems
MAN 801
Advances in Entrepreneurship and Management Research
MAN 804
MAN 804 Advances in Strategic Management
MKT 802
Marketing Theories
MKT 901
Designing Marketing Research Projects
MKT 803
Consumer Behavior
MKT 902
Advances in Marketing Research
OPM 920
Contemporary Topics in Operations Research (Programming with Phyton)
OPM 802
Dynamic and Stochastic Models in Supply Chain Research
OPM 806
Empirical Research in Operations Management
TAX 801
Business Taxation
TAX 801
Business Taxation
TAX 913
Empirical Taxation Research
Summer School on Empirical Research in Taxation and R&D