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VHB-ProDok: Kurs “Experimental Research and Behavioral Decision Making” an der HU Berlin

Vom 15. bis 18. Juli 2019 führt Professor Christian D. Schade (Humboldt-Universität zu Berlin) den bereits sehr erfolgreich stattgefundenen Kurs „Experimental Research and Behavioral Decision Making” an der Humboldt-Universität zu Berlin durch, zu dem wir Sie herzlich einladen.

Abstract and Learning Objectives
Various robust deviations from rational decision making have been reported such as loss aversion, probability weighting, status quo bias, overconfidence etc. Understanding those deviations leads to a more realistic modelling of the behavior of different economic actors and to an increased prediction success. In this course, participants will understand those and other important deviations from rationality as well as their theoretical explanations/modelling, e.g., prospect theory and mental accounting. Most theories have been developed implementing psychological and economic experiments. Whereas psychological experiments are mostly asking the respondents for hypothetical choices, real decisions with actual monetary payoffs are implemented in economic experiments. Half of the course will be concerned with a profound introduction to the several deviations from rationality that have been reported with real decision makers and with the theoretical treatment of those deviations. The other half of the course will deal with different types of experiments and different experimental designs as well as the matching of research question and type of empirical method to be used.

Anmeldung und weitere Infos
InteressentInnen können sich noch bis 16. Juni 2019 über das elektronische Anmeldeformular https://vhbonline.org/veranstaltungen/prodok/anmeldung/ oder per E-Mail an prodok@vhbonline.org anmelden. Unter dem Link finden Sie außerdem die Informationen zur Anmeldegebühr.

Hier erhalten Sie die Übersicht über das VHB-ProDok Kursangebot. Alle weiteren Informationen zu VHB-ProDok finden Sie unter http://prodok.org. Für Rückfragen steht Ihnen die Projektkoordinatorin Kathrin Schöps (kathrin.schoeps@vhbonline.org) von der Geschäftsstelle des VHB gerne zur Verfügung.

VHB-ProDok: Kurs “Theory and Theorizing in Information Systems Research” an der KLU Hamburg

Vom 16. bis 19. Juli 2019 führt Professor Benjamin Müller (Universität Lausanne) den in den letzten beiden Jahren sehr erfolgreichen und beliebten Kurs „Theory and Theorizing in Information Systems Research” an der Kühne Logistics University in Hamburg durch, zu dem wir Sie herzlich einladen.


The generation of knowledge can be seen as one of the key contributions of any science. Consequently, many scholars emphasize the centrality of theories for any scientific endeavor – a thought widely reflected in many disciplines from the natural to the social sciences. While a corresponding attention to theoretical work has been at the heart of the Information Systems (IS) discipline for a long time, the focus on theoretical debates and genuine conceptual contributions has been picking up recently. This is reflected by journal sections and conference tracks dedicated to advancing theory and theorizing in IS research, a number of workshops and special issues dedicated to the matter, as well as many authors’ experiences during the reviews processes of their work.

The course “Advanced Topics in Information Systems Theory” invites participants to join the ongoing discourse on theories and theorizing in the Business and Information Systems Engineering (BISE) and Information Systems (IS) research communities. It is designed to help participants build and extend their understanding of the nature and role of theory in BISE and IS research. Through discussions and analyses of current theoretical developments in the BISE and IS discipline and some of its main reference disciplines, participants will engage with theory and advance their skills of building their own theoretical contributions.

The course aims to achieve the following high-level learning objectives  1. Build a foundational understanding of what theory is and what role it plays in research  2. Develop basic theorizing skills and be familiar with extant theorizing strategies  3. Understand strategies to develop and publish own theoretical contributions

Overall, the course is designed to help students advance their understanding of theory and theorizing in the BISE / IS discipline and enhance their theorizing skills related to their own research and thesis work.

In terms of teaching formats, the course will be using a mixture of formats and approaches – from traditional lectures to interactive seminar sessions. To make this work, participants’ preparation before class is essential. Most of this preparation will involve reading a set of papers assigned to each participant that needs to be prepared for class. Through this preparation, a large portion of the workload for the course will occur in the weeks before the actual course date. Participants may also be asked to prepare other things as well, such as small presentations or posters, but these will come with less effort required. Specific instructions for all of the preparation necessary will be distributed in time before class.

Be advised that the course is not intended to be a comprehensive or normative prescription of how to engage with theory and theorizing in research. It is rather aimed at encouraging and empowering young scholars to carefully pay attention to their theoretical contribution and their engagement with the extant knowledge in the field. This explicitly includes a critical reflection on the current state of theory in the IS and BISE field in order to enable students to develop their own theoretical contributions as well as empower them to contribute to advancing the current debates on the nature and role of theory and theorizing in their own right.

Anmeldung und weitere Informationen

Interessierte können sich noch bis 2. Juni 2019 über das elektronische Anmeldeformular https://vhbonline.org/veranstaltungen/prodok/anmeldung/ oder per Email an prodok@vhbonline.org anmelden. Unter dem Link finden Sie außerdem die Informationen zur Anmeldegebühr.

Hier erhalten Sie außerdem die Übersicht über das VHB-ProDok Kursangebot. Alle weiteren Informationen zu VHB-ProDok finden Sie unter http://prodok.org. Für Rückfragen steht Ihnen die Projektkoordinatorin Kathrin Schöps (kathrin.schoeps@vhbonline.org) von der Geschäftsstelle des VHB gerne zur Verfügung.

Einladung zu Workshop und hochschulöffentlichem Roundtable “Hochschullehre in der Politischen Theorie und Ideengeschichte: Selbstverständnis, Praxis, Perspektiven” an der Universität Hamburg (10. und 11. Mai).

Am 10. und 11. Mai 2019 richten Alexander Weiß ( Helmut-Schmidt-Universität Hamburg ), Dannica Fleuß (Helmut-Schmidt-Universität Hamburg) und Andreas Busen (Universität Hamburg) an der Universität Hamburg einen Workshop zum Thema “Hochschullehre in der Politischen Theorie und Ideengeschichte: Selbstverständnis, Praxis, Perspektiven” aus.

Neben vielen Diskussionsbeiträgen wird es am 10. Mai von 17-18:30 Uhr auch einen (hochschul-)öffentlichen Roundtable geben, bei dem Dr. Svenja Ahlhaus (Universität Hamburg), Prof. Dr. Olaf Asbach (Universität Hamburg), Prof. Dr. Gary Schaal (Helmut-Schmidt-Universität Hamburg) und Dr. Frieder Vogelmann (Gastprofessor an der Goethe-Universität, Frankfurt a.M.) über Herausforderungen und Perspektiven der Lehre in Theorie und Ideengeschichte diskutieren werden.

Qualitative Comparative Analysis (QCA)

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Jonas Buche, Leibniz University Hannover

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Since the publication of the seminal work “The Comparative Method” by Charles Ragin in 1987, set-theoretic methods and especially Qualitative Comparative Analysis (QCA) have become a common research strategy in the social sciences. Set-theoretic methods analyse cases with regard to the identification of sufficient and necessary conditions and assume set relations to be equifinal, conjunctural and asymmetric. Not least since so-called fuzzy sets have been introduced to the method, there has been a rising interest in QCA as a welcome alternative to both small-n case studies and large-n statistical analyses. In short, QCA is recommended if ‘if…then’ hypotheses are analysed; if the goal is to derive sufficient and necessary conditions; if a comparison is planned; and if there is a mid-sized number of cases (between 10 and 60+).

The course offers a comprehensive introduction to QCA and is both conceptually and technically oriented. It starts off with an overview of the basics of set theory and demarcates QCA as a case-oriented method from both the quantitative and the interpretive-qualitative research paradigm. Through the notion of necessary and sufficient conditions and of truth tables, the single elements are built into the Truth Table Algorithm. However, this algorithm is not free of problems. Therefore, some pitfalls and strategies on how to overcome them are presented. On the third day, the software tool fsQCA will be introduced and applied to published studies.

Requirement of students: No prior knowledge is required. We will use the software fsQCA2.5 which can be downloaded at www.fsqca.com.

Recommended literature and pre-readings:

Buche, Jonas. 2017. “Assessing the Quality of Qualitative Comparative Analysis (QCA) – Evaluation, Improvement, Application”. Hannover: Leibniz Universität (https://www.researchgate.net/publication/323749578_Assessing_the_Quality_of_Qualitative_Comparative_Analysis_QCA_Evaluation_Improvement_Application)

Cebotari, Victor, and Maarten P. Vink (2013). “A Configurational Analysis of Ethnic Protest in Europe.” International Journal of Comparative Sociology, Vol. 54(4), 298-324.

Schneider, Carsten Q./Wagemann, Claudius, 2012. Set-Theoretic Methods for the Social Sciences. A Guide to Qualitative Comparative Analysis. Cambridge: Cambridge University Press.

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

Multi-level Modelling with R

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Daniel Lüdecke (UKE Hamburg)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: The course teaches how to fit multilevel regression models with the statistical programming language R. First, simple (generalized) linear regression models are introduced to show important basic principles of modelling, like simple regression, interaction terms, non-linear relationships between predictors and outcome (polynomial and spline terms). Later, the application of these principles in a multilevel framework are demonstrated. Furthermore, graphical representation of complex mixed models is covered that help communicate complicated models in a simple way even for a broad audience that is less familiar with such modelling techniques. Successful participation requires basic knowledge of regression modelling techniques. Students are encouraged to bring their own laptops with the free software R (www.r-project.org/) and RStudio (www.rstudio.com/) installed. All source code to run the examples is provided in preparation to the course.

Requirements: Basic knowledge of regression modelling (familiarity with terms like dependent and independent variables, linear and logistic regression, estimate, …)

Recommended readings:

Harrison, X. A., Donaldson, L., Correa-Cano, M. E., Evans, J., Fisher, D. N., Goodwin, C. E. D., … Inger, R. (2018). A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ, 6, e4794. https://doi.org/10.7717/peerj.4794

Bolker, B. M., Brooks, M. E., Clark, C. J., Geange, S. W., Poulsen, J. R., Stevens, M. H. H., & White, J.-S. S. (2009). Generalized linear mixed models: a practical guide for ecology and evolution. Trends in Ecology & Evolution, 24(3), 127–135. https://doi.org/10.1016/j.tree.2008.10.008

Required R packages:

  • Modelling: lme4, glmmTMB, GLMMadaptive
  • Visualization: ggeffects, sjPlot
  • Model Quality: performance
  • Data preparation: sjmisc, dplyr, tidyr

Run install.packages(c(“lme4”, “glmmTMB”, “performance”, “GLMMadaptive”, “ggeffects”, “sjPlot”, “sjmisc”, “dplyr”, “tidyr”), dependencies = TRUE) to install the relevant packages.

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

Analysing Panel and Spatial Data

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Assoc. Prof. Dr. Timo Friedel Mitze (University of Southern Denmark)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: The course is divided into two modules:

Part 1) Panel Data Analysis: The first module of the course is organized as a (basic!) introduction to the use of panel data in the different fields of business and social sciences. It is not meant as an expert course in advanced panel data modelling. The main goal is thus to provide insights into why and when applied researchers can benefit from working with panel data, i.e. the combination of cross-sectional and time-series data. The course provides course participants with an overview of the different types of (micro and macro) models that are available for panel data estimation and shows how to properly estimate these models with the help of the statistical software package STATA. Building on these basics, an outlook on more advanced panel data models will be given.

Part 2): Spatial Data Analysis: In the second module course participants will learn to use graphical and statistical tools to visualize and estimate models, in which spatial interaction places an important role. Besides presenting the general logic of spatial modeling approaches, a strong focus lies on illustrating the potential for applied work with these tools in the software package STATA. The module is structured as follows: After a brief introduction, different research settings in business and social sciences are outlined, which may call for the explicit use of spatial estimation techniques, for instance, in order to identify the importance of network and neighborhood effects. This is followed by some practical applications on how to measure and visualize the degree of spatial dependence in variables. The module then introduces course participants into the field of spatial econometrics and students can work with hands-on applications on the basis of different data sets. Finally, a link to spatial panel data models will be given to close the course.

Course Tools: Please bring your laptop computer. STATA can be installed in the beginning of the IRWS. Licenses will be provided. Datasets and STATA ado-files will be provided ahead of the course and should be installed on the participants’ computers. Introductory readings will be provided to registered participants approx. 4-6 weeks ahead of the course (see examples).

Basic requirements: Basic knowledge in econometrics; basic knowledge in STATA (e.g. online tutorial: https://www.youtube.com/watch?v=QaI_a_l2jqo)

Exemplary Readings

Baltagi, B. Econometric Analysis of Panel Data. 3 rd or higher edition, Wiley.

LeSage, J. Pace, K. Introduction to Spatial Econometrics. CRC Press.

Philosophies of Science

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Dr. Jaime Bonache (Universidad Carlos III de Madrid and Permanent Visiting Professor at ESADE Business School in Barcelona, Spain)

Date: see Workshop Programme

Max. number of participants: 15

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: By one widely held conception, Philosophy of Science is the attempt to understand the meaning, method, and logical structure of science by means of a logical and methodological analysis of the aims, methods, criteria, concepts, laws, and theories of science. It is thus an attempt to get a clear understanding of what science is and what is not. The major goal of this course is to provide students that understanding.

We would like to stress that this is an introductory course in Philosophy of Science. Our principles of selection of the topics included have been these: The selection should be intrinsically interesting. It should be relevant and comprehensible to a beginning student. It should serve to provoke discussion and criticism. We have also tried to relate the topics to current philosophical and methodological debates in the management area.

    a. The nature of management research
    b. (Two basic) Philosophical Positions in
    Management Research: Positivism and Interpretivism
    c. Positivism and Post-positivism
    d. Positivist research traditions in Management
    i. Theory Testing Research
    ii. Theory Building/Elaboration Research
    e. Evaluating Research Contributions in the Positivist tradition
    f. Some problems of positivism
    g. Phenomenology, Hermeneutics and its predecessors
    h. Comparing positivist and interpretive research contributions
    i. Evaluating research in the Interpretive Tradition
    j. Is interpretivism compatible with positivism?

The assigned readings are the following:

Bansal, P, Smith,W. and Vaara E. (2018): “New ways of seeing through qualitative research, Academy of Management Journal, Vol. 61 (4): 1189-1195.

Bonache. J and Zarraga, C. (2019): Compensating International Mobility in a Worker’s Cooperative: An interpretive study, Journal of World Business, in press

Lee, A. S. (1991). Integrating positivist and interpretive approaches to organizational research. Organization science, 2(4), 342-365.

Basic Bibliography:

Aguinis, H., & Solarino, A. M. 2019. Transparency and replicability in qualitative research: The case of interviews with elite informants. Strategic Management Journal. https://doi.org/10.1002/smj.3015

Alvesson, M., & Sandberg, J. (2011). Generating research questions through problematization. Academy of management review, 36(2), 247-27,1

Benton, T. (2001). Philosophy of social science: The philosophical foundations of social thought, McMilllan International.

Gibbert, M., Ruigrok, W., & Wicki, B. (2008). What passes as a rigorous case study?. Strategic management journal, 29(13), 1465-1474.

Kuhn, T. (1996): The Structure of Scientific Revolutions, 3rd Edition (First Edition 1962), The University of Chicago Press

Popper, K. (1963): “Science: Conjectures and Refutations.” From Conjectures and Refutations, pp. 33-41, 52-59. New York: Harper and Row

Rosenberg, A. (2011). Philosophy of science: A contemporary introduction. Routledge.

Sanders, P. (1982). Phenomenology: A new way of viewing organizational research. Academy of management review, 7(3), 353-360.

Sandberg, J. (2005). How do we justify knowledge produced within interpretive approaches?. Organizational research methods, 8(1), 41-68.

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

Introduction to Survival Analysis

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Andrea Schäfer (SOCIUM/Universität Bremen)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: The goal of this course is to introduce you to the topic of survival (or time to event) analysis and describes selected methods used for modelling and evaluating survival data. General statistical concepts and methods discussed in this course include survival and hazard functions, Kaplan-Meier estimator and graph and Cox proportional hazards model. Accordingly, we will explore the different types of censoring and truncation and, discover the properties of the survival and hazard function. You will learn the derivation and use of Kaplan-Meier (KM) non-parametric estimates and learn how to plot the KM and test for differences between groups. Further, we explore the motivation, strength and limits of Cox’s semi-parametric proportional hazard model and know how to fit the model. For our computer sessions we will be using a sample of the SOEP (Socio-economic Panel) data set. The course requires participants to use Stata to analyse survival analysis data.

In this course, you will learn about:

  • The goal, problem and strengths of survival analysis
  • Differences of survival analysis methods
  • Censoring and truncation (concepts and types)
  • The distribution of failure times (functions, rates and ratio, data layout, descriptive statistics)
  • Basics of non-parametric analysis (estimating Kaplan Meier estimator and comparing curves, graphing)
  • Basics of semi-parametric analysis (model definition and features, understanding and estimating Cox’s PH model)

Required: intermediate statistical knowledge, basic Stata skills

Recommended literature and pre-readings:

Allison, P. A. (2014): Event History and Survival Analysis. Quantitative Applications in the Social Sciences. Sage

Cleves, M.; W. Gould, R. G. Gutierrez, and Y. V. Marchenko (2010): An Introduction to Survival Analysis Using Stata, (3nd ed), Stata Press.

DTC Desktop Companion to the German Socio-Economic Panel (SOEP). This documentation is intended to give novice users a “jump start” in understanding the SOEP, its structure, depth, and research potential: http://companion.soep.de/Contents%20of%20SOEPcore/index.html

Goebel, J.; M. M. Grabka, S. Liebig, M. Kroh, D. Richter, C. Schröder and J. Schupp (2018): The German Socio-Economic Panel Study (SOEP) In: Jahrbücher für Nationalökonomie und Statistik / Journal of Economics and Statistics.

Kleinbaum, D. G. and M. Klein (2005): Survival analysis: a self-learning text (2nd ed), Springer.

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

13th International Research Workshop – Methods for PhD – 15–20 September 2019: Registration Open Now!

Akademie Sankelmark, Flensburg (Germany)


PARALLEL MORNING SESSION 1 (16 – 18 September 2019)

  • Data Analysis with Stata
    Tobias Gramlich, Hesse State Statistical Office
  • Qualitative Interviewing
    Dr. Sarah Potthoff, Ruhr-University Bochum
  • Grounded Theory
    Dr. Christine Moritz, Feldpartitur GmbH
  • Introduction to Survival Analysis
    Andrea Schaefer, University of Bremen
  • Writing your Literature Review
    Prof. Dr. Katharina Stornig, Justus-Liebig-University Gießen

PARALLEL AFTERNOON SESSION 2 (16 – 18 September 2019)

  • Data Analysis with R
    Dr. Marco Lehmann, UKE Hamburg
  • Analysing Panel and Spatial Data
    Prof. Dr. Timo Friedel Mitze, University of Southern Denmark
  • Qualitative Comparative Analysis (QCA)
    Dr. Jonas Buche, Leibniz University Hannover
  • Case Study Research
    Dr. Kamil Marcinkiewicz, University of Oldenbourg
  • Introduction to Data Mining and Quantitative Text Analysis with R
    Pascal Jürgens, Johannes Gutenberg-University Mainz

PARALLEL SESSION 3 (19 September 2019)

  • Philosophies of Sciences
    Prof. Dr. Jaime Bonache, Carlos III University of Madrid
  • Questionnaire Design
    Prof. Dr. Daniel Schnitzlein Leibniz University Hannover & DIW Berlin
  • Measuring Preferences using Conjoint Analytic Methods and Advanced Compositional Approaches
    Prof. Dr. Martin Meissner, University of Southern Denmark
  • Necessary Condition Analysis
    Prof. Dr. Sven Hauff, Helmut-Schmidt-University
  • Multi-level Modelling with R
    Dr. Daniel Lüdecke, UKE Hamburg


  • Wenzel Matiaske, Helmut-Schmidt-University
  • Simon Fietze, University of Southern Denmark
  • Heiko Stüber, Institute for Employment Research


499 Euro (with accommodation and meals)
299 Euro (without accommodation; lunch and dinner are included)

It is possible to get a certificate on 5 credit points (according to the European Credit Transfer System).


For any questions don’t hesitate to contact the workshop committee (irwsnetwork@gmail.com).
Please register for the workshop on the workshop website.


  • Helmut-Schmidt-University/University of the FAF Hamburg, Faculty of Economics and Social Sciences
  • Institute for Employment Research (IAB), The Research Institute of the Federal Employment Agency in Nuremberg
  • Akademie Sankelmark im Deutschen Grenzverein e.V.


  • Europa-Universität Flensburg
  • University of Hamburg, Faculty of Economics and Social Sciences
  • University of Hamburg, School of Business
  • Leuphana University Lüneburg, Faculty of Economics
  • Werkstatt für Personal- und Organisationsforschung e.V.

ReMaT – Research management training for early-stage researchers

A ReMaT workshop – Research management training for early-stage researchers – will take place in Hamburg on 18th and 19th November 2019. The workshop is designed for early-stage researchers in engineering and natural sciences, particularly PhD candidates from the 2nd year onwards. The idea of European networking is very much embedded in the concept, and we encourage participation from many different countries at the workshop.

ReMaT is an interactive, intensive workshop providing an introduction to research management. It involves two international trainers and is held in English. The modules of the workshop cover exploitation of knowledge and entrepreneurship, acquisition of grants, intellectual property rights and the management of interdisciplinary projects. They are delivered in such a way that it challenges participants to consider different perspectives on how they might use their PhD education in a variety of career paths, and convince others to hire them.

The organiser:
Tutech Innovation GmbH was founded in 1992 as the technology transfer institute for the Hamburg University of Technology. We are offering services regarding participation in EU funded programmes especially for publicly funded universities and SMEs. TUTECH ACADEMY workshops on technology transfer and innovation and research management equip participants from research and business with the right skill sets to do new work in their fields. Tutech Innovation GmbH has considerable experience in coaching researchers from a wide variety of backgrounds, disciplines and experience as well as nurturing those doing PhDs, participating in graduate schools or in the early stages of career development.

More information:
For further information please visit tutech.academy or send your enquiry to academy@tutech.de.