The Doctoral Program –
Flexible and individual.
WHU awards the academic degree of Doctor of Business and Economics (Dr. rer. pol.) – the German equivalent to a Ph.D. – based on the submission of a scientific paper (dissertation) and its presentation (disputation). All doctoral projects are supervised by experienced and dedicated WHU faculty members, all of whom have made a name for themselves in the scientific community via a wealth of national and international publications and research projects.
In addition to writing and defending their dissertation, doctoral candidates will also have the opportunity to attend courses and guest lectures by eminent national and international professors, providing them with additional valuable insight, and illustrating WHU’s globalized network in the field of research.
The curriculum –
Learn more about the program structure.
The WHU Doctoral Program centers on candidates conducting independent research and writing a dissertation, with two advisors from the WHU faculty allocated to each student to support them as they work on academic papers in their field of choice.
The WHU Doctoral Program Regulations form the basis of the program and provide further details on the entire program of study.
Find out more about the key elements of the Doctoral Program:
Doctoral candidates will be asked to submit an exposé within a reasonable time after enrollment. The proposal will set out the scope of the doctoral project in terms of content and chosen methodology. The nature of the exposé will also determine the second dissertation advisor.
Doctoral candidates normally defend their doctoral projects within 18 months of admission to the program. The student will present the status of his research project to a panel, including the two advisors, and should clearly demonstrate that it is both suitable evidence of independent scientific work, and that it creates added value for the research community. The student must defend the results outlined in the dissertation and answer any questions.
Doctoral courses aim to provide students every opportunity to continue their academic education in the fields of business and economics, and enable them to acquire the necessary methodological and factual knowledge for their respective research projects. Each doctoral course is worth 3 ECTS and involves 75 to 90 hours of work. The number of courses that have to be completed depends on the particular doctoral process and on the conditions fulfilled when the student enrolled. The doctoral courses are selected in consultation with the student’s advisor.
Learn more about the doctoral courses on offer below.
The doctoral thesis must relate to a field of business or economics, and although it can also be interdisciplinary, it must be rooted in one of these two areas. The dissertation must be an independent piece of work demonstrating notable academic attainment, and contribute to advancing the fields of business and economics. Candidates must submit their dissertation either in a monographic or publication-based form.
The disputation sees the doctoral student presenting his or her dissertation and then discussing the subject matter. The student has to defend the results he or she has obtained and to answer questions.
The lecturers –
Top-notch international faculty.
Julia de Groote
Peter J. Jost
Franz W. Kellermans
The courses –
Sharing methodological and factual knowledge with the Doctoral students.
The doctoral courses are designed to provide every opportunity for students to continue their academic education in the fields of business and economics and to enable them to acquire methodological and factual knowledge for their research project. 3 ECTS credits are awarded for each course, and the work involved is approximately 75 to 90 hours. The number of courses that have to be completed depends on the particular doctoral process and on the conditions fulfilled when the student enrolled. The courses to be taken are selected in consultation with the first advisor of the dissertation.
The courses are typically divided into "Core Courses" which are offered regularly, once a year, and "Electives". Both types fulfil the requirements of courses of the doctoral program regulations. For more detailed information on the core courses and for information on current electives please see the Online Study Guide.
Discrete Choice Experiments (DCEs) are an essential evidence based research tool to better understand and predict individual and group decisions made by managers, organizations, and consumers. DCEs are suited to empirically study frequently asked research questions from many disciplines, such as, e.g., consumers’ trade-off between product characteristics and price in Marketing; households’ trade-off between interest rates and risk in Household Finance; and app-users’ trade-off between capabilities and privacy concerns in Information Systems. This PhD course will enable researchers to set up and apply their own discrete choice experiment to their research questions.
In this course, we will discuss the art of theory building in organizational behavioral research. Thereby, we focus on behavioral theories that are applied within the management arena, behavioral economics are NOT discussed in this course.
All research projects aim at making a theoretical contribution. However, several questions and challenges arise along the pathway of each research project, such as:
- What is a theoretical contribution?
- How do I know that I really have an innovative research idea?
- Do my methods match my aimed theoretical contribution?
- How do I write good theory?
- What do I have to consider when publishing theory?
Contract theory is the study of optimal incentive design in a principal-agent relationship. Such problems arise frequently in your PhD-thesis being it in management or economics.
This course is designed to introduce contract theory to those who will later think more rigorously about the strategic implications underlying adverse selection or moral hazard problems of their PhD-thesis.
We do so by emphasizing the exposition to management applications of the theory at least as much as the pure theory itself. For more information, see the syllabus on myWHUstudies.
Today’s business world is characterized by an unprecedented growth of data, by 2020 we will experience a 300-fold increase from 2005. This data comes in a broad variety of forms: 420 million wearable health monitors are currently in use, more than 4 billion hours of video are watched on YouTube each month and 30 billion pieces of content are shared on Facebook every month. A lot of the data is analyzed in real time: modern cars have about 100 sensors and the NYSE captures 1 TB of trade information during each trading session. However, 1 in 3 business leaders don’t trust the information they use to make decisions and about 27% of respondents in one survey were unsure of how much of their data was inaccurate. 4.4 million IT jobs have been created globally to support big data. AlphaGo has recently beaten the reigning (human) Go champion.
Game theory is the study of multi-person decision problems. Such problems arise frequently in your PhD-thesis being it in management or economics.
This course is designed to introduce game theory to those who will later think more rigorously about the strategic implications underlying the topic of their PhD-thesis. We do so by emphasizing the exposition to management applications of the theory at least as much as the pure theory itself.
For more information, see the syllabus on myWHUstudies.
This course examines a series of evidential, epistemological and methodological issues which arise in economic modelling and theorizing.
During the course, students will be trained to: clearly articulate persuasive and well-structured arguments for or against a given position; integrate heterogeneous bodies of empirical and theoretical information; adopt a self-directed and original approach to the examination of recent debates at the interface between the philosophy of economics and the philosophy of science.
By the end of the course, successful students will: demonstrate accurate knowledge of foundational issues in model construction and theory change in distinct decision sciences; master central terminological and conceptual distinctions concerning notions such as intertheoretic reduction and scientific revolution; acquire a detailed understanding of specific debates in the philosophy of science.
This course will provide participants with knowledge on a broad range of qualitative approaches in the field of business research, such as case studies, grounded theory, ethnography, or action research.
It further covers ways to bridge the divide between qualitative and quantitative research, such as mixed methods and qualitative comparative analysis (QCA).
The course is interactively designed in order to discuss benefits and challenges of conducting and publishing qualitative research.
Dynamic Programming (DP) is a powerful optimization technique in which complex problems are broken down into smaller, easier to solve sub-problems. In this class, we study DPs and their solution methods in the presence of randomness and apply the methods to practical areas (such as inventory theory, procurement, and optimal stopping).
This course covers the microeconometric, the macroeconometric, and the graph-theoretic approaches to causal inference.
The former two of these three categories reflect the type of empirical application in which causal inference tends to be applied in practice. For instance, in microeconometrics, causality is frequently looked at in regression discontinuity designs or via difference-indifference specifications while, in macro- or financial econometrics, the concept of causality is generally interwoven with those of exogeneity, structural breaks and structural vector autoregressions. As opposed to that, the graph-theoretic idea of causality originates in philosophy and computer science and implements a very different structural approach to causal inference; it has recently gained popularity in the social sciences.
The material will be presented in the lectures in a both qualitative and quantitative manner. Computer simulations, empirical illustrations as well as exercises will supplement informal discussions.