Category Archives: Research Design

VHB ProDok Kurse

Advanced Topics and Experimental Methods in Consumer Research

This course provides an overview of research methods and theories in consumer behavior. The topics covered in this seminar should be of interest to doctoral students studying Business, Psychology, Organization Behavior, and Marketing.

The course has two major goals:

To expose students to research in specific areas of consumer research and marketing and to familiarize them with findings in these areas. These broad areas are emotions, sustainable consumer behavior, and human-computer interactions.
To equip students with abilities to conceptualize, design and implement original consumer behavior research, particularly experimental research.

Students will read a set of core readings in order to gain knowledge of relevant theoretical foundations, methodological norms, and most recent findings. We will discuss papers published at top journals in consumer behavior, marketing, management, and psychology. One of the best ways for doctoral candidates to understand a research area is to critically review articles describing research in that area. The course will challenge students to adopt a critical stance when reading papers. This approach provides a deeper understanding of specific issues, a better appreciation of the research process, and training in research skills. During the discussion of the key articles on each topic, students will be challenged to review these articles. The class discussion will evaluate the articles and the reviews.

Students will learn to identify gaps in the literature or to apply a research problem to unexplored related phenomena.

Moreover, the second aim of this course is that students develop their own actionable research question and methodological plan. For this, they will be able to collect first data in the lab (BreLab) for their idea(s) (if physical course is possible), with the group and recruited students serving as participants in the respective experiments. If time-wise not possible, an online data collection will be done. Students will present their idea and potential results and give one another feedback on these ideas.

After completing this course, students will be able to define research questions in various domains of consumer behavior and in different empirical settings, they will know how to implement their research questions into an actionable experimental design, and they will be aware of potential problems and (dis)advantages in their research design.

Date:

25. – 27. September 2024 (Präsenz)

7. Oktober 2024 (Online)

Location:

Universität Bremen
WiWi2 F3290
Enrique-Schmidt-Str. 1
28359 Bremen

Language:

English

Lecturer:

Prof. Dr. Kristina Klein

University of Bremen

Registration:

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Registration Deadline: 25. August 2024

VHB ProDok Kurse

Choice-Based Optimization

Summary and study goals

Demand is an important quantity in many optimization problems such as revenue management and supply chain management. Demand usually depends on “supply” (price and availability of products, f. e.), which in turn is decided on in the optimization model. Hence, demand is endogenous to the optimization problem. Choice-based optimization (CBO) merges discrete choice models with math programs. Discrete choice models (DCM) have been applied by both practitioners and researchers for more than four decades in various fields. DCM describe the choice probabilities of individuals selecting an alternative from a set of available alternatives. CBO determines (i) the availability of the alternatives and/or (ii) the attributes of the alternatives, i.e., the decision variables determine the availability of alternatives and/or the shape of the attributes. We present CBO applications to location planning, supply chain management, assortment and revenue management.

Course Content

Students will learn how to develop and use predictive models (discrete choice models) in the software R and how to introduce such models in mathematical models for decision-making (i.e., mixed integer programs) to consider demand as an auxiliary variable. The models will be implemented in a modeling environment (GAMS). Case studies will be used for practicing purposes.

Date of Event

– 26. September 2024

Location

Universität Hamburg
Fakultät für Betriebswirtschaft
Moorweidenstraße 18
EG, Raum 0005.1
20148 Hamburg

Language:

English

Lecturer:

Univ.-Prof. Dr. habil. Knut Haase
Universität Hamburg
www.bwl.uni-hamburg.de/vw/personen/prof-knut-haase

Univ.-Prof. Dr. habil. Sven Müller
RWTH Aachen University
https://www.business-school.rwth-aachen.de/dozierende/prof-dr-sven-mueller/

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Registration Deadline: 25.08.2024

VHB ProDok Kurse

Endogeneity in Applied Empirical Research

Many empirical research projects in business and economics that use non-experimental data struggle with the proper identification of causal effects of independent variables (e.g., price, management decisions) on dependent variables (e.g., demand, firm performance). The reason is that the identification of a causal effect hinges on the untestable assumption that the error term of a model is uncorrelated with the independent variables. If this assumption is not met, a model is plagued by endogeneity.

The topic of endogeneity has received considerable attention, and it is probably the most frequently encountered troublemaker in a review process at an academic journal.

This course therefore has the goal of making students familiar with the problem of endogeneity and potential remedies. This implies that it will cover the opportunities and problems associated with traditional approaches (e.g., Instrumental Variable estimation, Matching, Difference-in-Difference) as well as more recent developments (e.g., Gaussian Copulas; Machine Learning and Causal Inference; Synthetic Control Methods; Directed Acyclical Graphs (DAG)). The course will also cover how the data structure (e.g., panel data) can be utilized to address the problem.

Because the literature on endogeneity is often quite technical, this course aims at providing an easily accessible approach to this topic. Special emphasis will also be given to understanding when endogeneity indeed poses a real problem as compared to settings in which endogeneity is less likely to be a real threat to the validity of the findings.

After completing this course, students will be able to define and describe endogeneity problems in different empirical settings, they will have a better understanding of whether and when causal identification is possible how to implement techniques that address endogeneity, and they will be aware of the (dis)advantages of different methods.

Date:

18.9.2024 online and 25.-27.9.2024 face-to-face

Location:

Online & University of Tübingen

Language:

Englisch

Lecturer:

Prof. Dr. Dominik Papies
Universität Tübingen

Registration:

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Participation fee:

Non-member: 650,00 Euro
VHB-member: 530,00 Euro

Registration deadline: August 18, 2024

Accomodation

The University of Tübingen Guest House has a limited number of rooms available that can be booked here: https://uni-tuebingen.de/en/12231.

VHB ProDok Kurse

Quantitative Empirical Accounting Research and Open Science Methods

This course focuses on quantitative empirical accounting research, covering theoretical, methodological and technical aspects of this research program. It also introduces students to the concepts of Open Science. In terms of applications, it concentrates on financial and non-financial reporting issues but also touches on some managerial and auditing topics. After this course, participants should

have a clear understanding about the theoretical foundations of quantitative empirical accounting research,
know the methodological approaches to and common pitfalls of empirical research designs,
have become familiar with a collaborative open science workflow using R/Python/Stata and Github,
know how to execute empirical archival studies, including the usability and inter-operability of different data sources
and, based on their own research proposal, have received constructive feedback on how to design and execute a viable study in the area of quantitative empirical financial accounting research.

Date:

Online: 03.09.24, 06.09.24, 10.09.24, 13.09.24, all slots 9am – noon.
Zoom: https://hu-berlin.zoom.us/j/69574538552

In person (FU Berlin): 18.09.24, 2pm – 20.09.24, noon

Location:

Online and in person

Course Language:

English

Lecturer:

Prof. Dr. Joachim Gassen (Humboldt-Universität zu Berlin, TRR 266 „Accounting for Transparency“)

http://www.wiwi.hu-berlin.de/professuren/bwl/rwuwp/staff/gassen

gassen@wiwi.hu-berlin.de

Registration:

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Participation fee:

Non-member: 610,00 Euro
VHB-member: 490,00 Euro

Registration Deadline: 4. August 2024

VHB ProDok Kurse

Ethnographic Research

The course is designed for doctorate students in business administration who want to learn about and conduct ethnographic research. The aim of the course is to provide students with methodological foundations and advanced knowledge on ethnographic research in business studies. After attending this course, participants should be able to

understand the methodological foundations of ethnographic research
differentiate between different approaches to ethnography and be able to assess their strengths and weaknesses
plan an ethnographic research design as well as be prepared for methodological challenges in their field research
understand ways of analyzing ethnographic data and judge ethnographic research according to quality criteria

The first workshop day will provide an overview of the history of ethnography as well as introduce the participants to different approaches in ethnographic research. The second workshop day focuses on research ethics, quality criteria and publishing ethnographic research. On the third workshop day, the process of doing ethnographic research in the field as well as the issues of access, roles and forms of engagement will be discussed. The fourth day looks at different strategies for analyzing ethnographic data. The session will be hands-on and offer participants the opportunity to gain practical experience with analyzing ethnographic data.

Date:

September 2 – 5, 2024

Location:

Kyffhäuser 21
Kyffhäuserstr. 21
10781 Berlin

Course Language:

English

Lecturers:

Prof. Dr. Jana Costas,
Europa-Universität Viadrina Frankfurt (Oder)

Jana Costas is Professor of Business Administration, in particular People, Work and Management at the European University Viadrina Frankfurt (Oder). She holds a PhD from the University of Cambridge, and has been awarded with the EU Marie Curie Fellowship. She conducted the fellowship at the Copenhagen Business School. Jana has also been Assistant Professor (Juniorprofessorin) for Qualitative Methods in Management Research at Freie Universität Berlin. Her research interests lie in the area of organization studies, in particular secrecy, creativity, control, identity, culture, leadership, tech lobbying, violence, and new work and organizational arrangements. She has published in and reviews for various journals, such as Organization Studies, Journal of Management Studies, Human Relations. Jana is Associate Editor of Organization and acts on the Editorial Board of Organization Theory. She has published the monograph Secrecy at Work: The Hidden Architecture of Organizational Life (with Chris Grey), Stanford University Press. Her ethnographic book Dramas of Dignity: Cleaners in the Corporate Underworld of Berlin published by Cambridge University Press won the EGOS book award 2023.

Prof. Blagoy Blagoev
Universität St.Gallen

Blagoy Blagoev is Professor of Organization Studies at University of St. Gallen (Switzerland). His research draws on a temporal lens to examine the interplay of people, organizations, and society in the context of current technological, ecological, and cultural transformations. His main research interests include (1) organizing and managing for sustainability, (2) emerging technologies and organizing, (3) new and decentralized forms of working and organizing, and (4) organizational change, innovation, and persistence. He draws on qualitative and historical research methods to examine a wide range of organizations such as multinational corporations, knowledge-intensive firms, museums, and coworking spaces. His work has appeared in leading international journals, such as Administrative Science Quarterly, Academy of Management Journal, Journal of Management Studies, Organization Studies, Organization and Scandinavian Journal of Management.

Prof. Dan Kärreman,
Copenhagen Business School

Dan Kärreman is Professor in Management and Organization Studies at Copenhagen Business School, and Professor in Business Administration at Lund University. His research interests include critical management studies, knowledge work, identity in organizations, leadership, organizational control and research methodology. He received his PhD, based on an organizational ethnography, in 1997, and has held position at Gothenburg University, Lund University, Copenhagen Business School and Royal Holloway, University of London. His contributions to organizational methodology includes articles and books on organizational discourse analysis, mystery as method, theory creation and critical inquiry. He has contributed to more than 40 journal articles in peer review publications and has published in most top ranked journals in organization studies.

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Registration Deadline: August 4, 2024

VHB ProDok Kurse

Advanced Topics in Organization Theory

This doctoral seminar exposes students to foundational and current research in organization theory. It is directed towards all business administration scholars interested in phenomena that involve organizations, which can be students of organization theory specifically, management and marketing more broadly, or even students of other areas of business research such as accounting, sustainability management or information systems for whom organizations, inter-organizational relationships and wider organizational and institutional fields might play a role in their research.

This course is not a basic course, however, but a course that focuses on current developments in organization theory. This does not necessarily mean that an in-depth prior knowledge of organization theory is required, but students should have a basic knowledge of the topic of organization and be familiar with some “classic“ organization theories such as the theory of bureaucracy, contingency theory or institutional theory.

After this course, participants will be able to:

Understand how classic organization theories have developed both theoretically and in terms of empirical research designs
Apply recent advances in organization theory to understand current organizational and interorganizational phenomena
Develop relevant research questions that promise theoretical contributions to current (inter-) organizational thought

Date of Event:

September 16-19, 2024

Location:

Harnack-Haus
Ihnestraße 16-20
14195 Berlin

Lecturer:

Univ.-Prof. Dr. Elke SchüßlerLeuphana Universität Lüneburg

Prof. Dr. Jörg Sydow
Freie Universität Berlin

Registration:

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Registration Deadline: July 21, 2024

VHB ProDok Kurse

Machine Learning

The course exposes participants to recent developments in the field of machine learning and discusses their ramifications for business and economics. Machine learning comprises theories, concepts, and algorithms to infer patterns from observational data. The prevalence of data (“big data”) has led to an increasing interest in the corresponding methodology to leverage existing data assets for improved decision-making and business process optimization. Concepts such as business analytics, data science, and artificial intelligence are omnipresent in decision-makers’ mindset and ground to a large extent on machine learning. Familiarizing course participants with these concepts and enabling them to purposefully apply cutting-edge methods to real-world decision problems in management, policy development, and research is the overarching objective of the course. Accordingly, the course targets Ph.D. students and young researchers with a general interest in algorithmic decision-making and/or concrete plan to employ machine learning in their research. A clear and approachable explanation of relevant methodologies and recent developments in machine learning paired with a batterie of practical exercises using contemporary software libraries of (deep) machine learning will ready participants for design-science or empirical-quantitative research projects.

Date:

17. – 20. September 2024

Location:

Harnack-Haus Tagungsstätte der Max-Planck-Gesellschaft
Ihnestr. 16-20
14195 Berlin

The course will be offered over a four-day period comprising lecture, tutorial, and discussion sessions.

Course Language:

English

Lecturer:

Prof. Dr. Stefan Lessmann

Humboldt-Universität zu Berlin

Registration:

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Registration Deadline: 18. August 2024

VHB ProDok Kurse

Meta Analysis

Abstract and Learning Objectives

Meta-analyses have become very popular in many fields of the social sciences incl. business and management research. The results of meta-analyses attract substantial interest by both scholars and practitioners, as indicated by high citation numbers and widespread dissemination of meta-analytic findings in the media.

By summarizing results drawn from a set of studies concerning a specific topic and by discovering consistencies and explaining inconsistencies in these results, meta-analysis is an essential step in the process of knowledge accumulation, theory building and theory testing in science, linking past research with future scientific endeavors.

The course targets researchers who are interested in understanding, conducting, and publishing meta-analytic research. Participants of this course will learn how to conduct and publish a high-quality meta-analysis in the area of management and business research. To this aim, the course follows a step-by-step procedure that covers the entire meta-analysis research process, including problem formulation and definition of a research question for a meta-analysis, literature search, study and effects coding, data preparation and analysis with different software tools, and reporting and publishing. Participants will further learn how to evaluate meta-analyses in the business and management literature and to follow the respective methodological discussion about meta-analyses in their field.

Date:

September 10 – 13, 2024

Location:

Harnack-Haus
Ihnestr. 16-20
14195 Berlin

Language:

English

Lecturer:

Prof. Dr. Martin Eisend

European University Viadriana

Registration:

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Registration Deadline: August, 11th, 2024

VHB ProDok Kurse

Machine Learning

Date:

23. – 26. April 2024

Location:

Harnack-Haus Tagungsstätte der Max-Planck-Gesellschaft
Ihnestr. 16-20
14195 Berlin

The course will be offered over a four-day period comprising lecture, tutorial, and discussion sessions.

Course Language:

English

Lecturer:

Prof. Dr. Stefan Lessmann
Humboldt-Universität zu Berlin

Registration:

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Registration Deadline: 24. März 2024

VHB ProDok Kurse

Design Science

Abstract and Learning Objectives

Design Science Research (DSR) is a promising research paradigm that intends to generate knowledge on the design of innovative solutions to real-world problems. As such, DSR is specifically useful in contributing to the solution of societally and practically relevant challenges. At the same time, matured methodological foundations are available today, specifically supporting publishing DSR research both at conferences and top-tier journals.

This course gives an introduction to Design Science Research (DSR). It focuses on planning and conducting design science research on Ph.D. level. It is intended to provide state-of-the art methodological competences for all Ph.D. students in business whose research is not solely descriptive/explanatory, but also comprises components where artefacts are purposefully designed and evaluated.

While Design Science Research is very common in Information Systems research, purposeful artefact design and evaluation are found in many other business research fields like, e.g., General Management, Operations Management/Management Science, Accounting/Controlling, Business Education, or Marketing. Although Design Science is often conducted implicitly, the methodological discourse in the Information Systems has led to a high level of reflection and to the availability of a large number of reference publications and cases, so that examples and cases will often originate from this domain. It should however be noted that Design Science as a paradigm is applicable and is used in nearly all fields of business research. As a consequence, this class is not only part of the Information Systems ProDok curriculum, but intentionally being positioned as cross-domain class.

The goal of the course is to provide Ph.D. students with insights and capabilities that enable them to plan and conduct independent Design Science research. To achieve this goal, students will engage in a number of activities in preparation and during this four-day course, including preparatory readings, lectures, presentations, project work, and in-class discussions. The course format offers an interactive learning experience and the unique opportunity to obtain individualized feedback from leading IS researchers as well as develop preliminary research designs for their own Ph.D. projects.

Date:

22. April bis 3. Mai 2024

Face to face time: Mo, Tue, Wed, Fr, Tue, Fr,

Location:

DIGITAL COURSE
offline: ca. ten days for reading, preparation, decentral group work between April 8 and
May 2, 2024

online: six half days between April 22 – May 3, 2024

Language:

English

Instructor:

Prof. Dr. Jan vom Brocke

University of Münster
www.janvombrocke.com
https://www.researchgate.net/profile/Jan_vom_Brocke

Prof. Dr. Robert Winter
University of St. Gallen
https://www.alexandria.unisg.ch/persons/621
https://www.researchgate.net/profile/Robert_Winter

Registration:

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As this course is offered as an digital course, the participation fee is reduced by 160 Euro.

Advanced Topics and Experimental Methods in Consumer Research

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Registration Deadline: 25. August 2024

Choice-Based Optimization

Summary and study goals

Course Content

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Registration Deadline: 25.08.2024

Endogeneity in Applied Empirical Research

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Participation fee:

Registration deadline: August 18, 2024

Accomodation

Quantitative Empirical Accounting Research and Open Science Methods

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Registration Deadline: 4. August 2024

Ethnographic Research

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Advanced Topics in Organization Theory

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Machine Learning

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Meta Analysis

Abstract and Learning Objectives

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Machine Learning

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Registration Deadline: 24. März 2024

Design Science

Abstract and Learning Objectives

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Registration Deadline: March 24, 2024