Category Archives: Network Courses

Reminder Inside the Editor’s Head: Publizieren in internationalen Fachjournalen

Institution: Helmut-Schmidt-University Hamburg

Lecturer: Dr. Florian Kühn, Institute for International Politics, Helmut Schmidt University Hamburg

Date: 24.11.2016, 14:00-17:00

Place: Helmut-Schmidt-Universität, Holstenhofweg 85, 22043 Hamburg, Seminarraum 0105, Hauptgebäude H1

Language of instruction: Deutsch

Registration: Non-members of the Helmut-Schmidt-Universität may click here firstly to create an HSU-Ilias-account, and secondly here to join the course.

Contents:
Florian Kühn führt aus der Sicht eines Herausgebers einer internationalen Fachzeitschrift (Journal of Intervention and Statebuilding) in die Tücken, Fallstricke aber auch Praxis und Abläufe des Publishings ein. Wenn wir – womöglich zum ersten Mal? – vor der Frage stehen, wo und wie ein Aufsatz eingereicht werden kann und sollte, um angemessen berücksichtigt zu werden, aber auch eine Chance zu haben, einen Peer Review-Prozess zu überstehen, erscheint die Welt der Journal Publishings zunächst wie ein Buch mit sieben Siegeln. Dieser Workshop behandelt in drei Blöcken den Prozess einer Veröffentlichung (Welches Journal? Welcher Aufsatz? Wie präsentieren?). Aus der Sicht eines Herausgebers schildert Florian Kühn häufig gemacht Fehler und gibt Tipps, wie ein Aufsatz erfolgreich eingereicht werden kann, wie die Kommunikation zwischen Herausgebern und Einreichenden sowie zwischen Editorial Boards und Gutachtern verläuft, und wie sich die Chancen verbessern lassen, einen Aufsatz unterzubringen. Was kennzeichnet einen guten Aufsatz, wie präsentiere ich Forschungsergebnisse, welches Publikum spreche ich an, an welche bestehende Forschung knüpfe ich an (oder von welcher grenze ich meine Forschung ab), wie soll das Verhältnis zwischen Forschungsstand – Forschungsergebnissen – Desideraten sein, etc.? Je nach Interesse können Fragen zu Open Access, zu Indices, zu Zitationen und Impact-Berechnungen diskutiert werden.

Dr. Florian Kühn ist wissenschaftlicher Mitarbeiter am Institut für Internationale Politik an der HSU, hat Professuren an der Humboldt Universität zu Berlin und an der Otto-von-Guericke-Universität Magdeburg vertreten und ist seit 2013 Herausgeber von JISB.

JMP Intro & DOE/Kriging Workshop using JMP and R on 25th November at the HSU — CANCELED!

Dear Ladies and Gentlemen,

Due to unforeseen and unfortunate circumstances, the above-mentioned workshop on Kriging using JMP and R, scheduled for 25th November at the HSU, has to be canceled. We apologize for any inconvenience.

Kind regards
Volker Kraft, JMP Academic Ambassador, and Univ.-Prof. Dr. Sven Knoth, Chair of Computational Statistics, Helmut-Schmidt-Universität Hamburg

 

Paper course: Audit market research and publication strategies

Institution: Fakultät für Betriebswirtschaft, Universität Hamburg

Course instructor: Professor Nicole Ratzinger-Sakel (UHH)

Dates: Block course: February 2017 (3 days): 22 February, 2017 – 24 February, 2017.
Time: 9 a.m. – 5 p.m.

Location: tba

Course Value: 2 SWS or 4 LP

Course Overview:
The main objectives of this PhD course include:
Introduce students to the main areas of empirical audit market research and discuss the main statistical approaches/models used to examine these areas. In addition, the course will enhance students’ ability to critically review the quality of research papers and will introduce students to the publication process. To do so, students are expected to present and critically discuss papers that will be assigned to the students. Students will further see real reviewers’ comments given during the review process of double-blind reviewed journals as well as the authors’ implementation of these comments. Finally, students should present their (first ideas of) own research ideas during the course.

Teaching language: English

Student evaluation: Presentation and critical discussion of assigned papers (papers will be assigned to students after their application; each student is expected to present and critically discuss one paper)

Application: Please send a short letter of motivation that includes your research interests and a current CV

until January 14, 2017
to nicole.ratzinger-sakel@uni-hamburg.de.

 

Review Processes & Research Ethics

Institution: Fakultät für Betriebswirtschaft, Universität Hamburg

Lecturer: Prof. Dr. Michel Clement (Universität Hamburg)

Dates: block course: December 5th 2016 and January 10th 2017

Location: tba

Course Value: 1 SWS or 2 LP

Course Overview:
This course will give an introduction in review processes of journals specialized in the management and marketing area and/or media management and media economics. It also aims to teach how to review for journals and how to write response notes within a review process. The course also focuses on research ethics within review processes

Course Contents:
This course will focus on review processes. Topics include:

DAY 1:

1. The Author’s View: The submission process of various journals (Management Science, International Journal of Research in Marketing, Information Systems Research). Discussion of the submission steps:

a. Submission requirements
b. What to submit
c. Editor selection
d. Reviewer selection
e. Data requirements

2. The Editor’s View: Analysis of the submission systems and reviewer selection.

a. Reviewer selection
b. Decision making process
c. Reviewer evaluation

3. The Reviewer’s View: How the evaluate a paper. Guidelines on writing a review.

4. Ethical issues in the review process.

a. Cases of misconduct
b. Reviewer selection
c. Reviewer exclusion
d. Authorships
e. Conflict of Interest

5. Guidelines of how to write a review. Participants receive a paper that they are asked to review until the second part of the course. The reviews are then dis-cussed and the participants then receive the original reviews and the revision notes by the authors to learn how their assessment of the paper matches with the original review.

DAY 2:

6. Discussion of the reviews.

7. Guidelines of how to write revision notes.

8. Guidelines of how to write a response letter.

Individual (or two-person team, with permission) review assignments will be required. Own research questions and papers are very welcome to be discussed in the course.

Prerequisites:
Please also study the following texts / blog:

Albers, Sönke (2014): Preventing Unethical Publication Behavior of Quantitative Empirical Research by Changing Editorial Policies, Journal of Business Economics, 84 (9): 1151-1165.
Holbrook, Morris B. (1986): A Note on Sadomasochism in the Review Process: I Hate When That Happens, Journal of Marketing, Vol. 50, No. 3 (Jul., 1986), 104-108.
www.retractionwatch.com

Assessment: Assessment will be based on active participation and performance on assignments. Grading for students of University of Hamburg will be pass/fail.

Registration: Please e-mail Michel Clement: michel.clement@uni-hamburg.de until 01. November 2016 (Please remember that places will be allocated in order of received registrations)

 

Multivariate Analysis Methods

Institution: Fakultät für Betriebswirtschaft, Universität Hamburg

Lecturer: Tammo Bijmolt (University of Groningen, Faculty of Economics and Business)

Dates: 21st November 2016, 12th December 2016, 16th January 2017, 6th February 2017 (all sessions scheduled on Mondays)

Course Value: 3 SWS or 6 LP

Course Overview:
The PhD course deals with a variety of multivariate analysis methods. The main focus of the course is rather applied: students who have successfully finished the course should be able to apply multivariate analysis methods at an advanced level in scientific research in marketing (or more general, in business). A full-day lecture will be used to explain a particular method and to learn about conducting the analyses. There will be four topics, each with a lecture and an assignment (see below).
The course is open for students from outside Hamburg, from other departments within the Business School, and junior faculty members (max. 15-20 participants). In principle, participants could sign up for all sessions / the entire course, or cherry-pick the topic(-s) that they like.

Objectives:
After attending the course, students should have acquired:
a) State-of-the-art knowledge of potential application of these multivariate analysis methods
b) Understanding of the methodological underpinnings of the methods
c) Practical skills to perform the analyses

Assessment and Credits:
After the session, participants will have to work on an assignment (if the participant requires formal credits), using real data, and write a short report (about 10 pages; to be graded as pass/fail) about this. Participants who attend all sessions and pass the four assignments can attain 6 LP.

Potential topics:
Topics of the PhD course will be selected based on preferences of participants. Therefore, please indicate your preferred topic(s) out of the following methods when registering for the course. Four out of seven topics will be taught in the course.

# Topic

  1. Latent class analysis / mixture modelling
  2. Hierarchical models
  3. Hidden Markov models {assuming knowledge of 1}
  4. Moderation & mediation
  5. Meta-analysis
  6. Factor analysis & principal component analysis
  7. Duration models

Assessment and Credits: After the session, participants will have to work on an assignment (if the participant requires formal credits), using real data, and write a short report (about 10 pages; to be graded as pass/fail) about this. Participants who attend all sessions and pass the four assignments can attain 6 LP.

Registration: To register for this seminar please contact Marius Johnen (marius.johnen@uni-hamburg.de). Registration is open till 16th October 2016 and is on a first come, first serve basis.

Tammo H.A. Bijmolt is Professor of Marketing Research at the Department of Marketing. From March 2009 till November 2015, he has been Director of the research school SOM, Faculty of Economics and Business Administration, University of Groningen, The Netherlands. His research interests include conceptual and methodological issues such as consumer decision making, e-commerce, advertising, retailing, loyalty programs, and meta-analysis. His publications have appeared in international, prestigious journals, among others: Journal of Marketing Research, Journal of Marketing, Journal of Consumer Research, Marketing Science, International Journal of Research in Marketing, Psychometrika, and the Journal of the Royal Statistical Society (A). His articles have won best paper awards from International Journal of Research in Marketing (2007), Journal of Interactive Marketing (2011), and European Journal of Marketing (2015). He is member of the editorial board of International Journal of Research in Marketing and International Journal of Electronic Commerce. Tammo Bijmolt is vice-president of EIASM and lectures in the EDEN programs. He has lectured in a broad range of programs at the Bachelor, Master, PhD and executive MBA level. He has been involved in several research-based consultancy projects for a variety of companies including MetrixLab, GfK, Wehkamp, and Unilever. Finally, he served as expert in several legal cases involving market research projects.

 

 

Reminder/Update HSU-Doktorandenkurs: Combining Rigor and Relevance with Necessary Condition Analysis (NCA)

Institution: Helmut-Schmidt-University Hamburg

Lecturer: Jan Dul, Rotterdam School of Management, Erasmus University

Date: 20.10.2016 – 10 a.m. to 15 p.m.

Place: Helmut-Schmidt-Universität, Holstenhofweg 85, 22043 Hamburg

Room: Seminarraum 0105

Language of instruction: English

Registration: Please notify Dr. Sven Hauff via email (hauffs@hsu-hh.de)

Contents:
Necessary Condition Analysis (NCA) is a novel methodology, recently published in Organizational Research Methods (Dul, 2016). Reactions of editors and reviewers of papers that use NCA are very promising. For example, an editor of a 4-star journal said:
“From my perspective, [this NCA paper] is the most interesting paper I have handled at this journal, insofar as it really represents a new way to think about data analyses”.

How does NCA work?
NCA understands cause-effect relations in terms of “necessary but not sufficient”. It means that without the right level of the condition a certain effect cannot occur. This is independent of other causes, thus the necessary condition can be a bottleneck, critical factor, constraint, disqualifier, etc. In practice, the right level of necessary condition must be put and kept in place to avoid guaranteed failure. Other causes cannot compensate for this factor.

Whom is NCA for?
NCA is applicable to any discipline, and can provide strong results even when other analyses such as regression analysis show no or weak effects. By adding a different logic and data analysis approach, NCA adds both rigor and relevance to your theory, data analysis, and publications. NCA is a user-friendly method that requires no advanced statistical or methodological knowledge beforehand. It can be used in both quantitative research as well as in qualitative research. You can become one of the first users of NCA in your field, which makes your publication(s) extra attractive.

What will be discussed in the seminar?
The seminar consists of two parts:

  1. The first part (one hour) is open to anyone who is interested in NCA and its potential value. We will discuss the method and its applications in different management fields.
  2. Immediately afterwards, in the second part (1-3 hours depending on the number of participants) we will discuss the method in more detail. In particular we will focus on the participants’ research areas and datasets. If you are interested in a demonstration of the method on your dataset, please bring your dataset (scores of the variables) on a USB drive (e.g., excel.csv file). Normally, an NCA analysis takes less than 5 minutes to get the main results.

More information:

  • www.erim.nl/nca
  • Dul, J. (2016) Necessary Condition Analysis (NCA): Logic and methodology of “necessary but not sufficient” causality, Organizational Research Methods, 19(1), 10-52.

SDU Koldning: Social Network Analysis (13.-17.02.2017)

Institution: University of Southern Denmark (SDU), Department of Entrepreneurship and Relationship Management

Responsible/coordinator: Professor Thomas Schøtt, Dept. of Entrepreneurship and Relationship Management, University of Southern Denmark.

Lecturer: Prof. Thomas Schøtt.

Location: University of Southern Denmark, campus Kolding, near train station in Kolding, 6th floor Guest Café.

Time: 13-17 February 2017, Monday to Friday, 9:00-18:00 daily.

Teaching language: English.

Application: By 1 December 2016 to: tsc@sam.sdu.dk (early registration is recommended, as the course expectedly fills up).

Fee: 5500 DKK.

Purpose and content: Networks can be mapped as relations among actors. An actor may be a person, an organization, a nation, a region or some other entity that can engage in action. For example, we may examine – qualitatively and quantitatively – how networks constrain and enable actors’ thoughts and behaviors. Networks are analyzed in sociology, psychology, anthropology, political science, history, geography, communication, and studies of policy, administration and business. Introductions to principles of network analysis can be read via www.anaytictech.com The aim of the course is to empower the participants to analyze networks and to integrate theory and methodology in the analyses of social networks, specifically business networks.

The course will teach the general theoretical and methodological principles and apply them to business networks. The course has two goals. First, the participants will be exposed to, and discuss, a variety of conceptual and theoretical perspectives on the study of business networks, along with methods utilized in these theoretical frameworks. Second, the participants will learn to conduct quantitative analyses of networks. Training will be offered in analyses at the level of the whole system, at the level of subgroups, and at the level of individual actors.

The format combines lectures and discussion with training in analyses. We use SPSS and network analytic software such as UCINET and NETDRAW which each student will have to install. Data on some networks will be made available by the instructor (e.g. some data on interlocking directorates among enterprises in a city), but the participants are also welcome to bring some data on networks (if you have some data on networks, please email tsc@sam.sdu.dk prior to the course).

Literature

  • Analyzing Social Networks, Stephen Borgatti, Martin Everett (Sage 2013) (read this around the time you register for the course).
  • Doing Social Network Research, Garry Robins (Sage, 2015). (read this around the time you register for the course).
  • UCINET software package, that you buy from www.analytictech.com (40 $ for students).

Recommended:

  • Introduction to Social Network Methods. Robert Hanneman and Mark Riddle (2005)
    www.faculty.ucr.edu/~hanneman/nettext/
  • Social network analysis. John Scott (second edition is preferable)
  • Analysis of social networks. David Knoke et al. (second edition is preferable)
  • Applied network analysis. Ronald Burt et al.
  • Changing organizations: business networks. David Knoke
  • Social capital: theory and research. Nan Lin et al.
  • Achieving success through social capital. Wayne Baker
  • Networking smart. Wayne Baker
  • Networks in the global village. Barry Wellman
  • Social structures: a network approach (second edition). Barry Wellman et al.
  • Social network analysis. Stanley Wasserman et al.
  • Network models of the diffusion of innovations. Thomas Valente
  • Social Networks (journal), see at www.insna.org (click on Publications)
  • Connections (journal), see at www.insna.org (click on Publications)
  • Journal of Social Structure, published at www..cmu.edu/joss
  • “Network analysis” by Ronald Burt and “Network models” by Thomas Schøtt, in Structure Manual (236 pages) which can be downloaded from www.uchicago.edu/fac/ronald.burt/teaching/STRUCmanual.pdf

 

Participants: The course is intended for researchers and PhD students who are studying business networks and who wish to acquire this network analytic tool and the skill to map and analyze networks. The course does not presume any acquaintance with network analysis (although familiarity with quantitative research methods will be useful).

 

Credits/evaluation: 5 ECTS. Certificates of completion will be issued to those successfully completing all requirements of the course (including full attendance and submission of all required assignments). Requirement: A batch of training exercises and reading in December-January. The many training exercises will be assigned by 1 December 2016, and then solutions must be submitted weekly until meeting in the course. The purpose of the many training exercises is to train a basic understanding of ideas and techniques of network analysis.

Further information: Please contact Thomas Schøtt, tsc@sam.sdu.dk

JMP Intro & DOE / Kriging Workshop using JMP and R

Institution: Helmut-Schmidt-University Hamburg, hosted by Univ.-Prof. Dr. Sven Knoth, WiSo (sven.knoth@hsu-hh.de)

Presenter: Volker Kraft, JMP Academic Ambassador

Time: 25th November 2016, 10am – 5pm

Location: Helmut-Schmidt-Universität, Holstenhofweg 85, 22043, Hamburg,  WiSo Hörsaal 3 (or PC-Pool)

Registration: Please click here an fill out the form to register for the workshop.

Number of attendees: 25 max. (hands-on only)

Agenda:
10-12: Introduction to JMP, Design of Experiments and Predictive Modeling (live demo & discussion)
12-13: Lunch break – pizza session by JMP
13-17: Kriging Workshop – attendees should have JMP 13 pre-installed (see www.jmp.com/trial for 30 days trial license)

Target Group:
Morning: Anybody interested to see JMP 13, or to get ready for the afternoon hands-on workshop.
Afternoon: Anybody with applications that require to work with functions, often of many variables, that are costly to evaluate.
Knowledge of linear regression, statistical modeling, and stochastic processes is helpful but is not required for the workshop. Similarly, basic knowledge of R and/or JMP will be helpful for the hands-on lab component, but is not mandatory.

Content:
JMP is an easy-to-use, standalone statistics and graphics software from SAS Institute. It includes comprehensive capabilities for every academic field, and its interactive point-and-click interface and linked analyses and graphics make it ideal for research and for use in statistics courses, from the introductory to the advanced levels. JMP runs on Windows and Macintosh operating systems and also functions as an easy, point-and-click interface to SAS®, R, MATLAB and Excel.

The JMP INTRO SESSION introduces the interactive user interface of JMP. Sample applications will focus on Experimental Design and Data Modeling. Get to know about JMP academic resources and where to find help.

KRIGING (or Gaussian process regression) has proven to be of great interest when trying to approximate a costly to evaluate function in a closed form. The principle aim of the workshop is to show how to build useful surrogate models using this approach, and to make clear the assumptions that such models rely on. Furthermore, once it exists, we will show how a surrogate model can be used for optimization.

Lab sessions will use both R and JMP. The main aim of the lab is to quickly find optimal settings of a catapult numerical simulator that can fire the longest shot.

Workshop content and installation instructions for R (packages) and JMP will be shared mid of November.

 

Introduction to Regression Analysis

Institution: Fakultät für Betriebswirtschaft, Universität Hamburg

Course Instructor: Dr. Alexa Burmester (Universität Hamburg)

Dates, location: October 10. and 11. 2016; 09:15 – 13:45 h (block course), R. 4030/4031

Course Value: 1 SWS or 2 LP

Course Overview:
This course will give an introduction to regression analysis with Stata.
Course Contents: This course will focus on basic regression analysis. Topics include (1) Data preparation, (2) Summary statistics, (3) Model free evidence, (4) Regression analysis, (5) Check of model assumptions, (6) Nonlinear models & interaction effects, and (7) Panel data.
Individual (or two-person team, with permission) research assignments will be re-quired. Please schedule some time at Monday afternoon for the assignment. Own re-search questions and data are very welcome to be discussed in the course.

Software: Please bring a laptop with Stata 13 or newer. If applicable, you can bring your own data set of your research project.

Prerequisites:
Please also study the following text:
Backhaus, K., B. Erichson, W. Plinke und R. Weiber (2016): Multivariate Analysemethoden, 14. Auflage, Heidelberg (Kapitel 1: Regressionsanalyse)

Assessment: Assessment will be based on active participation and performance on assignments. Grading for students of University of Hamburg will be pass/fail.

Registration: Please e-mail Alexa Burmester: Alexa.Burmester@uni-hamburg.de until 06. October 2016. (Please remember that places will be allocated in order of received registrations.)

SYLLABUS
Day 1:

  • Data preparation
  • Summary statistics
  • Model free evidence
  • Regression analysis
  • Check of model assumptions

Day 2:

  • Presentation of assignment
  • Nonlinear models & interaction effects
  • Panel data
  • Summary

GIGA Hamburg: Introduction to Zotero (22.11.2016)

Institution: German Institute of Global and Area Studies (GIGA)

Lecturer: Dr. Birte Pfeiffer

Schedule: 22.11.2016

Place: GIGA, Neuer Jungfernstieg 21, 20534 Hamburg, Germany

Registration: Participants need to register online by filling in the registration form that is available on the website of the respective event (see below).

Course description:
Zotero is a free, open-source tool that helps you collect, organize, cite and share your research sources. This course will introduce the basics of Zotero such as: installation, adding sources to your library, organizing and managing your citations, creating a bibliography, and using the Mi-crosoft Word plug-in to easily insert citations from Zotero into your documents. Participants are encouraged to bring their personal computers so that they may download and interact with the program.

About the lecturer
Dr Birte Pfeiffer is Research Data Manager at the GIGA Information Centre.

Further information