VHB ProDok Kurs “Foundational Theories of Strategic Management Research”

Foundational Theories of Strategic Management Research

Date: 19.07.-22.07.2021
Abstract:

The main objective of the course is to familiarize doctoral students with the basic assumptions, concepts and theories underlying the field. In essence, we want to help doctoral students to become independent scholars who are knowledgeable on the major theories in the field of strategy.

We typically start with reading the seminal work on the topic, followed by examining several recent empirical applications of the theory. The course is comprehensive, encompassing the following domains: Overview of the field of Strategic Management, Industrial Organization Approaches to Strategy, Resource-based View Approaches to Strategy, Transaction Cost Economics and Vertical Integration, Real Options and Sequential Decision Making, Principal-Agent Theory and Corporate Governance, Top Executives and the Upper-Echelons Perspective, the Governance Performance Relationship.

Location:

Freie Universität Berlin

Course Language:

English

Lecturer:

Prof. Michael J. Leiblein, PhD,

Ohio State University

Prof. Dr. Thomas Mellewigt,

Freie Universität Berlin

Registration:

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

Registration Deadline: 20. Juni 2021

VHB ProDok Kurs “Choice-Based Optimization”

Choice-Based Optimization

Date: 19.07.-22.07.2021
Abstract:

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.

Location:

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

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

Otto-von-Guericke-Universität Magdeburg
https://www.om.ovgu.de/

Registration:

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

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
Abstract:

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.
Location:

ONLINE

Language:

English

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

Click for information on fees, payment and registration,

or email us: prodok@vhbonline.org.

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

Registration Deadline: June 6th, 2021

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 is 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 for 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, see
  • Summaries and Statistics: parameters, effectsize
  • Model Quality: performance
  • Data preparation: sjmisc, dplyr, tidyr

Run install.packages(c(“lme4”, “glmmTMB”, “parameters”, “performance”, “effectsize”, “see”, “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.

Data Analysis with R

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Marco Lehmann (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 introduces the programming language R used for statistical analyses. The beginning of each lecture comes with a demonstration of programming and statistical functions that will be elaborated on in the course of study. The students will then practice with many statistical examples. In addition to statistical functions, the course will introduce the definition of R as a programming language and its syntax rules. Students will further learn to use R’s scripting capabilities. Successful participation requires basic knowledge of descriptive and inferential statistics. The students are encouraged to bring their own laptops with the free software R (www.r-project.org/) and RStudio (www.rstudio.com/) installed.

A requirement of students: Basic knowledge in descriptive and inferential statistics is recommended.

Recommended literature and pre-readings:

  • Matloff, N. (2011). The Art of R Programming: A Tour of Statistical Software Design. No Starch Press.
  • Wollschläger, Daniel (2012). Grundlagen der Datenauswertung mit R (2. Aufl.). Berlin: Springer.

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

Case Study Research

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: PD Dr. Kamil Marcinkiewicz (University of 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: Case study research is frequently applied in the social sciences. It is particularly popular among political scientists, especially those specialising in area studies. The ubiquity of the case study research contrasts with the scarcity of theoretical reflection on its core methodological aspects. Also, the benefits of comparative analyses are often underestimated. In this course, participants will have an opportunity to learn more about what case study research is, what are its weakness and strengths and how should we go about the core question in designing a case study: a selection of cases. The course combines lectures with practical exercises and discussion of students’ projects.

A requirement of students: Please bring your laptop computer.

Recommended literature and pre-readings:

  • Gerring, J. (2007). Case Study Research: Principles and Practices (pp. 17-63). Cambridge: Cambridge University Press.
  • George, A. L., & Bennett, A. (2005). Case Studies and Theory Development in the Social Sciences (pp. 1-34). Cambridge, MA: MIT Press.
  • Rueschemeyer, D. (2003). Can One or a Few Cases Yield Theoretical Gains? In J. Mahoney and D. Rueschemeyer (Eds.), Comparative Historical Analysis in the Social Sciences (pp. 305-337) Cambridge: Cambridge University Press.
  • Hall, P.A. (2008). Systematic Process Analysis: When and How to Use it. European Political Science, 7(3), 304-317.

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

Call for Applications for the ARL International Summer School 2021

“Urban and Regional Infrastructures”
WED 29 September – SAT 2 October 2021 in Vienna

The ARL – Academy for Territorial Development in the Leibniz Association in cooperation with the University of Vienna is inviting applications for the ARL International Summer School 2021 on “Urban and Regional Infrastructures”, which will take place from Wed. 29 September to Sat. 2 October, 2021 in Vienna (the arrival is scheduled for 28 September 2021). Advanced master and doctoral students from all disciplines are invited to apply. The summer school will be held in English. The deadline for applications is 11th April 2021.

Please see the call for applications for further information on the event, the terms of participation, and information on the application process:

https://www.arl-net.de/en/projekte/arl-international-summer-school-2021

For further questions, please contact Dr. Lena Greinke (greinke@arl-net.de, +49 (0)511 34842 34).

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.

Promotionsstudiengang_SoSe_21

HSU – Einführung in die quantitative Datenanalyse mit SPSS

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

Inhalt:

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.

Voraussetzungen/Vorkenntnisse:

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

 

Tutorin:

Dr. Elke Goltz, HSU

Termine:

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

Ort:

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

Teilnehmer:

maximal 10

 

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

https://ilias.hsu-hh.de/goto.php?target=crs_341192_rcodemPqRdgLQkE&client_id=unibw

 

Wer nicht Angehöriger der Helmut-Schmidt-Universität ist, schickt bitte eine Mail an phd-network@hsu-hh.de mit der Bitte um Teilnahme.