Featured post

Promote your content on the PhD Network

Do you have any news (courses, call for papers, job announcements, etc.) that you would like to publish on the Ph.D. network website? You are welcome to write a post on our website and promote your content free of charge. Your relevant content will be promoted on our website, newsletter and social media.

We are currently accepting the following types of submissions:

  • Courses, Events, Conferences
  • Job Vacancies
  • Call for Papers

VHB ProDok Kurs

Marketing Strategy Performance: Theory, Models, and Empirical Applications

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.

Date:

July 11-14, 2022

Location:

Fritz Thyssen Stiftung, Apostelnkloster 13-15, 50672 Köln

Language:

English

Lecturer:

Prof. Dr. Marc Fischer (Universität zu Köln)

Prof. Dr. Simone Wies (Gotehe-Universität Frankfurt/M.)

Prof. Dr. Alexander Edeling (Universität zu Köln)

Registration:

Click for information on fees, payment and registration,

or email us: prodok@vhbonline.org.

 

Registration Deadline: June 12th, 2022

16th International Research Workshop – Methods for PhD (28 August – 2 September 2022)

16th International Research Workshop – Methods for PhD
28 August – 2 September 2022
Akademie Sankelmark, Flensburg (Germany)
http://www.phd-network.eu/irws/programme/

PROGRAMME

PARALLEL MORNING SESSION 1 (29 – 31 August 2022)

PARALLEL AFTERNOON SESSION 2 (29 – 31 August 2022)

PARALLEL SESSION 3 (1 September 2022)

WORKSHOP COMMITTEE:

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

FEES & CREDIT POINTS

539 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

For any questions, don’t hesitate to contact the workshop committee (irwsnetwork@gmail.com).

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
  • Institute for Employment Research (IAB), The Research Institute of the Federal Employment Agency in Nuremberg
  • 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

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 publishing 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 concerning identifying 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. The single elements are built into the Truth Table Algorithm through the notion of necessary and sufficient conditions and truth tables. However, this algorithm is not free of problems. Therefore, some pitfalls and strategies on how to overcome them are presented. The software tool fsQCA will be introduced and applied to published studies on the third day.

A 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:

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

Data Analysis with Stata

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Tobias Gramlich, Hesse State Statistical Office

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Stata is a statistical program package widely used (not only) in the social and economic sciences; it is used for data management, statistical graphics and analysis of quantitative data. Statistical concepts will not be part of the course, so participants should have some very basic knowledge of statistics. The course should enable participants to prepare their data for analysis, perform adequate analysis using a statistical computer program and document these tasks to keep them reproducible.

For Beginners with no or very little Stata knowledge!

Course topics cover:

  • “What You Type Is What You Get”: Basic Stata Command syntax
  • Getting (and Understanding) Help within Stata: Stata Built-in Help System
  • Basic Data Management: Load and Save Stata Datasets, Generate and Manipulate Variables, Describe and Label Data and Variables, Perform Basic uni- and bivariate Analyses, and Change the Structure of your Data.
  • Basic Stata Graphics: Scatterplot, Histogram, Bar Chart
  • Working with “Do-” and “Log-” Files

A requirement for students: Statistical concepts will not be part of the course, so participants should have some very basic knowledge of statistics.

Recommended literature and pre-readings: None.

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 the 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 for students: Basic knowledge of 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.

Writing Your Literature Review

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Sylvia Rohlfer (CUNEF University)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Regardless of discipline and the original research project, the literature review is a key part of a thesis or article. However, writing a literature review is the most daunting part of writing. Doctoral students often comment that the literature seems (and often is) massive. Hence, it might be helpful to be as systematic as possible when completing this task.

In this course, you will get practical insights and advice on how to write a literature review effectively. This will include tips, tricks and tools to improve your reading and sorting of the references, synthesizing the literature, summarizing existing debates and providing advice on presenting reviews effectively. We will also consider your writing habits. The sessions will be practical and require active involvement by students who will work in groups and get focused feedback on individual projects.

There are no pre-readings for the course, but participants will be required to complete smaller tasks outside the allotted workshop hours. Prior to the seminar, participants should send an extended abstract of their research project (two pages max. and in English/German/Spanish) to srohlfer@cunef.edu.

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

Academic English Writing

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Dr. Jonathan Mole (Europa-Universität Flensburg)

Date: see Workshop Programme

Max. number of participants: 20

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: Writing an academic text is a complex task. It requires knowledge of a range of accepted writing conventions and the ability to construct sentences that are not only idiomatically and grammatically correct but also suitably connected to one another. An awareness of the requirements and a degree of practice are necessary.

This workshop is primarily for people who are in the process of writing an academic text in English – a proposal, abstract, article, thesis etc. It provides the opportunity to obtain individual feedback on a text which you submit before the workshop. In the workshop, assistance will be given to enable you to self-correct any issues which have been highlighted (structure, understanding, logic, language etc.). In addition, an overview of the important characteristics of academic English writing will be discussed. If required, exercises will be available to highlight topics such as academic style (formality, impersonal and objective language, passive voice, caution, nominalisation); structure of a sentence, paragraph and document level; reporting verbs and their forms; coherence and cohesion; and citation and reference styles.

A requirement of students: Please supply a maximum of 2 pages of text at least two weeks before the workshop begins. English language skills at CEFR level B2/C1 are required.

Recommended literature and pre-reading: None.

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

Qualitative Research Methods

Institution: see Organisers & Supporters

Programme of study: International Research Workshop

Lecturer: Prof. Dr. Fabian Hattke (NHH Business School Bergen, Norway)

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 purpose of this course is to familiarize participants with the basic characteristics of qualitative research. The course introduces methodological and practical aspects of different forms of qualitative research like case studies, discourse analyses, interviews, observations, and qualitative meta-syntheses. The course covers various issues, including the philosophy of science, research designs, theory building, and sampling strategies. It also discusses practical challenges like developing research questions, the use of different coding approaches, technical tools, and ethical questions.

Recommended literature and pre-readings:

  • Adler, P. S., Forbes, L. C., & Willmott, H. (2007). Critical management studies. Academy of Management Annals, 1(1), 119-179.
  • Alvesson, M., & Karreman, D. (2000). Varieties of discourse: On the study of organizations through discourse analysis. Human Relations, 53(9), 1125-1149.
  • Corbin, J., & Strauss, A. (2014). Basics of qualitative research: Techniques and procedures for developing grounded theory. Sage publications.
  • Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532-550.
  • Flick, U., von Kardoff, E., & Steinke, I. (Eds.). (2004). A companion to qualitative research. Sage.
  • Hoon, C. (2013). Meta-synthesis of qualitative case studies: An approach to theory building. Organizational Research Methods, 16(4), 522-556.
  • Mayring, P. (2004). Qualitative content analysis. A companion to qualitative research. Forum: Qualitative Social Research, 1, 159-176.
  • Sandelowski, M., & Barroso, J. (2006). Handbook for synthesizing qualitative research. Springer Publishing.
  • Wodak, R., & Meyer, M. (Eds.). (2015). Methods of critical discourse studies. Sage.
  • Yin, R. K. (2017). Case study research and applications: Design and methods. Sage publications.

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 is demonstrated. Furthermore, graphical representation of complex mixed models is covered, which helps communicate complicated models 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.

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 weaknesses 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 discussions of students’ projects.

A requirement for 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.