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

  1. – 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/

 

Registration:

Click for information on fees, payment and registration,
or email us: prodok@vhbonline.org.

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:

Click for information on fees, payment and registration,

or email us: prodok@vhbonline.org.

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:

Click for information on fees, payment and registration,
or email us: prodok@vhbonline.org.

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.

Registration:

Click for information on fees, payment and registration,

or email us: prodok@vhbonline.org.

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:

Click for information on fees, payment and registration,

or email us: prodok@vhbonline.org.

 

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:

Click for information on fees, payment and registration,

or email us: prodok@vhbonline.org.

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:

Click for information on fees, payment and registration,

or email us: prodok@vhbonline.org.

Registration Deadline: August, 11th, 2024

2 Starter Scholarships for Doctoral Candidates

CALL FOR APPLICATIONS – DOCTORAL CANDIDATES

Starter Scholarship

The scholarships are available from 1 April 2025 for the duration of one year.

We welcome applications from candidates aiming to write their doctoral thesis at the Bamberg Graduate School of Social Sciences. A scholarship will enable you to develop an excellent research proposal and submit it to appropriate funding bodies. The graduate school supports scholarship holders through personal mentoring, workshops, and support services.

The Bamberg Graduate School of Social Sciences is a multidisciplinary Graduate School funded by the Bavarian State. We are seeking to stimulate and guide cutting-edge doctoral research on some of the most crucial challenges modern knowledge-based societies are facing.

Specialised research agendas have been grouped into four thematic pillars:

PILLAR 1: Education, personal development and learning from early childhood to adulthood
PILLAR 2: Educational and social inequality across the entire life course
PILLAR 3: Changes in human capital, labour markets and demographic structures and their impact on social structures in modern societies
PILLAR 4: Governance, institutional change and political behaviour

A detailed list of topics that will be supervised by professors in our four pillars can be found here:
www.uni-bamberg.de/bagss/application/topics

// QUALIFICATION AND REQUIREMENTS:
We are inviting applications by highly qualified graduates from the fields of Sociology, Psychology, Educational Science, Political Science, Labour and Educational Economics, Demography and Statistics. Candidates must hold a Master‘s degree (or equivalent) in one of the aforementioned subjects or be very close to completion. International applications are encouraged but successful applicants will be required to take up their residence in Bamberg, a city noted for its high quality of life and great conditions for research and study. Starter scholarships amount to a monthly stipend of 1,568 EUR, plus other allowances according to the Graduate School’s guidelines. The Graduate School is committed to diversity, equal opportunities and the compatibility of family and career within its statutory obligations.

For further information about the Bamberg Graduate School of Social Sciences, the application process and the required documents, please visit our website at
https://www.uni-bamberg.de/en/bagss/application/starter-scholarships/

The deadline for the submission of your application is Sunday, 15 September 2024.

18th International Research Workshop – Methods for PhD (25 – 30 August 2024)

18th International Research Workshop – Methods for PhD
25 – 30 August 2024
Akademie Sankelmark, Flensburg (Germany)
https://www.phd-network.eu/irws/programme/

PROGRAMME

PARALLEL MORNING SESSION 1 (26 – 28 August 2024)

PARALLEL AFTERNOON SESSION 2 (26 – 28 August 2024)

PARALLEL SESSION 3 (29 August 2024)

WORKSHOP COMMITTEE

  • Dr Wenzel Matiaske, Helmut-Schmidt-University
  • Dr Simon Jebsen, University of Southern Denmark
  • Dr Heiko Stüber, University of Applied Labour Studies

FEES & CREDIT POINTS

599 Euro (with accommodation and meals)

It is possible to get a certificate on five credit points (according to the European Credit Transfer System).

WORKSHOP VENUE

The workshop will take place at the Akademie Sankelmark, Akademieweg 6, in Oeversee (near Flensburg), Germany.

CONTACT & REGISTRATION

Don’t hesitate to contact the workshop committee (irwsnetwork@gmail.com) for any questions.

Please register for the workshop here or on the workshop website.

ORGANIZERS

  • Helmut-Schmidt-University/University of the FAF Hamburg, Faculty of Economics and Social Sciences
  • Akademie Sankelmark im Deutschen Grenzverein e.V.

SUPPORTERS

  • Europa-Universität Flensburg
  • University of Hamburg, Faculty of Economics and Social Sciences
  • University of Hamburg, School of Business
  • Leuphana University Lüneburg, Faculty of Economics

Quantitative Text Analytics

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Assoc. Prof. Dr Fabian Hattke (University of Bergen)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: This course provides a basic introduction to the field of quantitative text analysis and natural language processing (NLP). It offers a theoretical introduction and hands-on exercises to explore the potential utility of different approaches to textual data (e.g., closed vs. open vocabulary text mining, sentiment analysis, topic detection, and data visualisation). The course teaches students to extract and process text from documents and to analyse the data by means of quantitative methods.

Software Installations: The course requires no coding or programming skills or prior experience with NLP tools. However, if students want to actively participate in the practical exercises and use their own datasets, they must install the following software on their personal laptops prior to the course.

  • Linguistic Inquiry and Word Count (LIWC) https://www.liwc.app/
    [the cheapest academic license is valid for 30 days and costs €18.95]
  • A generic statistics program like Stata, SPSS, or R.

Recommended literature:

  • Eichstaedt, J. C., Kern, M. L., Yaden, D. B., Schwartz, H. A., Giorgi, S., Park, G., … & Ungar, L. H. (2021). Closed-and open-vocabulary approaches to text analysis: A review, quantitative comparison, and recommendations. Psychological Methods, 26(4), 398-427.
  • Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis, 21(3), 267-297.
  • Hickman, L., Thapa, S., Tay, L., Cao, M., & Srinivasan, P. (2022). Text preprocessing for text mining in organizational research: Review and recommendations. Organizational Research Methods, 25(1), 114-146.
  • Indurkhya, N., & Damerau, F. J. (Eds.). (2010). Handbook of Natural Language Processing
    (Vol. 2). CRC Press Wilkerson, J., & Casas, A. (2017). Large-scale computerized text analysis in political science: Opportunities and challenges. Annual Review of Political Science, 20, 529-544.
  • Wilkerson, J., & Casas, A. (2017). Large-scale computerized text analysis in political science:
    Opportunities and challenges. Annual Review of Political Science, 20, 529-544.

You have to register for the International Research Workshop to participate in this course.