Category Archives: Network Courses

VHB ProDok Kurs “Choice-Based Optimization”

Choice-Based Optimization

Date: 19.07.-22.07.2021

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.


The course will be held online only. The lecturers will give presentations about the theoretical contents. Active participation is compulsory.


Univ.-Prof. Dr. habil. Knut Haase
Universität Hamburg

Univ.-Prof. Dr. habil. Sven Müller

Otto-von-Guericke-Universität Magdeburg


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Registration Deadline: 20. Juni 2021

VHB ProDok Kurs “Marketing Strategy Performance: Theory, Models, and Empirical Applications”

Marketing Strategy Performance: Theory, Models and Empirical Applications

Date: 05.-08.07.2021

Against the background of increasing pressure from the capital market and major corporate trends such as digitization, marketing managers are more and more forced to demonstrate the performance and value relevance of their decisions. Marketing scholars have responded to this development and produced numerous articles that relate marketing decisions with the creation of market-based assets (e.g. customer satisfaction), product-market performance (e.g., market share), accounting performance (e.g., return on assets), and financial-market performance (e.g., stock returns). The course aims at providing an overview of this literature, both from a conceptual/model-based perspective and from an empirical point of view. After having attended the course, students should be able to:

  • Understand central concepts of marketing strategy performance research and be able to establish links between these concepts;
  • Understand the basics of market response modeling and recognize the relevance of model specification for the validity of empirical estimation results;
  • Understand, categorize, and criticize high-quality (“A+”) articles within the research field;
  • Know key data analysis methods within the research field including their scope of application as well as their limitations and conduct first own analyses using standard software (R);
  • Develop relevant and interesting research questions with a potential for a high-quality publication.




Prof. Dr. Marc Fischer (Universität zu Köln)
Dr. Alexander Edeling (Universität zu Köln)
Prof. Dr. Simone Wies (Goethe Universität Frankfurt am Main)

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

Registration Deadline: June 6th, 2021

Tutech Innovation: How to prepare a competitive Horizon Europe proposal (21.04.2021)

The aim of the workshop is to provide guidance on how to develop proposals to
Horizon Europe that have a good chance of success and how to manage the
preparation process so that it comes to fruition on time in an efficient manner. We will start by looking at how proposals are evaluated and the new structure of the HEU template. Then we will focus on the novel notion of pathways to impact.

We will also look at the organisation of proposal preparation and how to develop a narrative. Real case examples will be used with the aim to make the workshop as hands-on’ as possible. There will be the opportunity to ask questions and on request, advice can be given after the workshop on specific cases.

Organiser: The workshop is provided by Tutech In-novation GmbH, a company owned jointly by Hamburg University of Technology (TUHH) and the Free and Hanseatic City of Hamburg whose mission is to promote effective transfer and exploitation of scientific and technical knowledge.

Trainer: Monica Schofield, CEng FIET currently heads the Business Unit Consultancy and Competence Development and is Director International Cooperation at Tutech Innovation.

Date: 21 April 2021 09:00 – 13:00 hrs

Place: online

Language of instruction: English

Registration: For additional information on workshop fees, conditions of registration and participation as well as the course programme, please click here.

Promotionsstudiengangskurse der Universität Hamburg / Fakultät für Wirtschafts- und Sozialwissenschaften / Graduate School

Promotionsstudiengangskurse im  Sommersemester 2021

Die Fakultät für Wirtschafts- und Sozialwissenschaften der Universität Hamburg bietet auch im kommenden Sommersemester 2021 wieder eine Vielzahl interessanter Kurse an. Nähere Details zu Kursen, Anmeldungen und Terminen entnehmen Sie bitte dem beigefügten Link.


HSU – Einführung in die quantitative Datenanalyse mit SPSS

Workshop zur Einführung in die quantitative Datenanalyse mit SPSS (Version 24/25)


Wie lassen sich erhobene Daten zielführend auswerten? In der Veranstaltung werden grundlegende Kenntnisse zu Statistiksoftware SPSS vermittelt. Im Vordergrund stehen dabei die Programmoberfläche und einfache Auswertungsverfahren der Deskriptiv- und Inferenzstatistik.

Die Veranstaltung ist so konzipiert, dass die Teilnehmerinnen und Teilnehmer am Ende des Kurses mit folgenden Inhalten sicher umgehen können:

  • Erstellung von Datenmasken und Dateneingabe
  • Uni- und bivariate deskriptive Statistik
  • Zusammenhangs- und Unterschiedsmessungen; Signifikanztests
  • Durchführung von Berechnungen; z.B. Erzeugung neuer Variablen, etwa Indizes
  • Verknüpfung von Dateien (Quer- und Längsschnitt)

Darüber hinaus können nach Absprache und zeitlichen Ressourcen gern weitere Themen mit der Dozentin behandelt bzw. individuelle Fragestellungen besprochen werden.


keine, von Vorteil wären jedoch Grundkenntnisse zu statistischen Kennziffern (etwa Mittelwerte, Streuungsmaße)



Dr. Elke Goltz, HSU


13.04.21 bis zum 16.04.21 – jeweils von 9:30 bis 14:30 Uhr


Online via MS Teams; Einloggdaten werden nach Schließung der TN-Liste verschickt.


maximal 10


Für Mitglieder der HSU erfolgt der direkte Kursbeitritt ab sofort unter diesem Link:


Wer nicht Angehöriger der Helmut-Schmidt-Universität ist, schickt bitte eine Mail an mit der Bitte um Teilnahme.

VHB ProDok Kurs Simulation Modelling für Business Research

Simulation Modelling for Business Research


March, 1.-11., 2021

face to face time: March, 1., 4., 8., 11.:


Business research increasingly considers wicked problems and complex dynamic systems. Analytical models of such problems and systems quickly become untraceable and unsolvable. Given increasing computational power, simulation models provide an alternative tool. They can fuel studies tracing the long-term evolution of systems and comparing the outcomes of alternative scenarios. However, successfully applying simulation modelling for business research requires expertise on applicable simulation paradigms, approaches to model validation and the analysis of stochastic results.



Course Language:



Prof. Dr. Catherine Cleophas, Christian-Albrechts-Universität zu Kiel


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Registration Deadline: 7. Februar 2021

VHB ProDok Kurs Stochastic Models

 Stochastic Models


Online-Course: 15.3.2021 – 1.4.2021

The course will be offered in electronic form. Participants get screencasts and exercises to study the different topics themselves. Additionally, virtual meetings are organized during the course to discuss the different topics and to support the participants.


Many real life system are subject to uncertainty and should therefore be modelled with stochastic models. In this course we focus on the theory and the application of three different classes of stochastic models:  Discrete Time Markov Chains,  Continuous Time Markov Chains, and Markov Decision Processes. The students should gain knowledge about these models such that they are able to construct these models and apply them to solve real life problems. For illustration we use among others models of inventory systems, manufacturing systems, maintenance systems and queuing systems. We show how formulas for performance measures can be derived and how they can be computed. Further, the students learn numerical methods to obtain solutions. Additionally, we discuss methods to  derive structural results and to obtain optimal policies.



Face to Face time:

The course starts with an introductory session on 15.3.2021 10.00-11.00

Regular virtual meetings take place at the following dates and times
17.3.2021, 16.00-18.00
19.3.2021 16.00-18.00
22.3.2021 16.00-18.00
24.3.2021 16.00-18.00
26.3.2021 16.00-18.00
29.3.2021 16.00-18.00

During the last meeting each student has to give a short presentation 1.4.2021, 10.00-18.00


Prof. Dr. Gudrun P Kiesmüller, TUM Campus Heilbronn, TU München


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Bitte beachten Sie, dass sich die Teilnahmegebühr für alle digitalen Kurse um 160 € reduziert und sich somit auf 410 € für VHB-Mitglieder bzw. 530 € für Externe beläuft.

Registration Deadline: February 14, 2021

PhD Course Econometrics


Block course


March 1st – March 3rd, 2021


Zoom (Link will be provided on the course website)

Course instructor:

Professor Martin Spindler (UHH)

Course value:

2 SWS or 4 LP

Course overview:

The main goal of this course is to give an introduction to causal inference, and if time allows to recent developments, in particular on the use of Machine Learning Methods for Causal Inference. Handouts of the slides will be provided during the course. The target audience are empirical researcher / PhD students who want to apply those methods for their research.


1) Introduction to Causal Inference / Basic Framework

2) Methods for Causal Inference (Diff-in-Diff, IV, Propensity Score Matching, Randomized Control Trials, …)

3) Recent Developments

Teaching language:


Student evaluation:

presentation of a recent paper in a blocked session (Summer Term2021) or presentation / written summary of a research project / idea


not required

VHB-ProDok Kurs Theoretical Perspectives On Corporate Social Responsibility (CSR)

Theoretical Perspectives on Corporate Social Responsibility (CSR)

Datum: 22.03. – 25.03.2021

Inhalt und Ziele:

Inhalt des 4-tägigen Workshops sind die Diskussion und das Entwickeln eines gemeinsamen Verständnisses über grundlegende theoretische Ansätze in der CSR-Forschung. Dies soll helfen, den Teilnehmern nicht nur ein fundiertes Verständnis der Forschung zu vermitteln, sondern auch, den State-of-the-Art der Literatur und aufkommende „hot topics“ mit relevanten Forschungsfragen zu verknüpfen. Der Workshop beinhaltet thematische Diskussionen zu verschiedenen Themenfeldern sowie themenübergreifende Inputs durch die Workshopleiter/in z.B. zum Publikationsprozess in der CSR Forschung, Karriereplanung, sowie Einbeziehung von Praktikern in die Forschung.

Der ProDok-Kurs CSR wendet sich in erster Linie an NachwuchswissenschaftlerInnen der Betriebswirtschaftslehre, die in ihrer Forschung einen Schwerpunkt auf die Bereiche CSR, unternehmerische Nachhaltigkeit sowie das grundlegende Verhältnis von Wirtschaft und Gesellschaft setzen.


22. bis 25. März 2021





Um einen Überblick über die Höhe der Teilnahmegebühr zu erhalten und um sich anzumelden, nutzen Sie bitte diesen Link: Anmeldung

Interessierte können sich per Email an anmelden.

Anmeldefrist: 21. Februar 2021

VHB ProDok Kurs Design Science

Design Science

Date: 22.02. – 05.03.2021

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.


22.2. bis 05.03.2021
face to face time: Tue, Thu, Mo, Wed, Fr


offline and online




Prof. Dr. Jan vom Brocke
University of Liechtenstein


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

Registration Deadline: January 24, 2021