Category Archives: University of Hamburg – BWL

Hamburg Business School: Doctoral study courses in winter semester 2017/18

The following doctoral study courses will be on offer at the Hamburg Business School in winter semester 2017/18:

  • Recent Developments in Causal Inference (Jan 31-Feb 2 2018)
    Martin Spindler (Information)
  • Microeconometrics (Nov 14-16 2017)
    Stefan Hoderlein (Information)
  • Writing skills, intellectual property rights and research integrity (Nov 17 2017)
    Andrea Sanchini (Information)
  • Project management and time/self-management skills (Dec 20 2017)
    Anette Hammerschmidt (Information)

See also https://www.bwl.uni-hamburg.de/en/forschung/promotion.html for further information on the doctoral studies program of the Hamburg Business School.

Universität Hamburg: Zwei wissenschaftliche Mitarbeiter/innen (Strategisches Management)

Fakultät/Fachbereich: Betriebswirtschaft
Seminar/Institut: Lehrstuhl für Strategisches Management (Prof. Dr. Nicola Berg)

Ab dem 01. Juli 2017 (oder nach Vereinbarung) sind zwei Stellen einer/eines wissenschaftlichen Mitarbeiterin/Mitarbeiters gemäß § 28 Abs. 1 HmbHG* zu besetzen.

Die Vergütung erfolgt nach der Entgeltgruppe 13 TV-L. Die wöchentliche Arbeitszeit entspricht 75% der regelmäßigen wöchentlichen Arbeitszeit.**

Die Befristung erfolgt auf der Grundlage von § 2 Wissenschaftszeitvertragsgesetz. Die Befris-tung ist vorgesehen für die Dauer von zunächst drei Jahren.

Die Universität strebt die Erhöhung des Anteils von Frauen am wissenschaftlichen Personal an und fordert deshalb qualifizierte Frauen nachdrücklich auf, sich zu bewerben. Frauen werden im Sinne des Hamburgischen Gleichstellungsgesetzes bei gleichwertiger Qualifikation vorrangig berücksichtigt.

Aufgaben:
Zu den Aufgaben einer wissenschaftlichen Mitarbeiterin/eines wissenschaftlichen Mitarbeiters gehören wissenschaftliche Dienstleistungen vorranging in der Forschung und der Lehre. Es besteht Gelegenheit zur wissenschaftlichen Weiterbildung, insbesondere zur Anfertigung einer Dissertation, hierfür steht mindestens ein Drittel der jeweiligen Arbeitszeit zur Verfügung.

Aufgabengebiet:
Das Aufgabengebiet dieser Stelle umfasst die Mitwirkung an Lehrveranstaltungen im Umfang von 3 Semesterwochenstunden bei 0,75% der regulären Arbeitszeit, die Planung und Durchführung von Forschungsprojekten, die Mitarbeit an Publikationen und die Kooperation mit Partnern aus der Wirtschaft. Geboten werden anspruchsvolle Forschungsarbeiten in einem engagierten Team sowie eine systematische Betreuung Ihres Dissertationsvorhabens.

Einstellungsvoraussetzungen:
Abschluss eines den Aufgaben entsprechenden Hochschulstudiums. Erwartet wird ein Hochschulstudium im Fach Betriebswirtschaftslehre mit einer Vertiefung in den Studienfächern Internationales Management, Strategisches Management oder Personalmanagement. Als Person weisen Sie Teamgeist, Internationalität, Praxiserfahrung und Erfahrungen in theoriegeleiteter-empirischer Forschung auf.

Schwerbehinderte haben Vorrang vor gesetzlich nicht bevorrechtigten Bewerberinnen/Bewerbern bei gleicher Eignung, Befähigung und fachlicher Leistung.

Für nähere Informationen wenden Sie sich bitte an Frau Prof. Dr. Nicola Berg (nicola.berg@uni-hamburg.de) oder schauen Sie im Internet unter http://www.bwl.uni-hamburg.de/de/stman nach.

Bitte senden Sie Ihre Bewerbung mit den üblichen Unterlagen (Bewerbungsschreiben, tabella-rischer Lebenslauf, Hochschulabschluss) bis Montag, 01. Oktober 2017 an:
Prof. Dr. Nicola Berg
Universität Hamburg
Fakultät für Betriebswirtschaft
Lehrstuhl für Strategisches Management
Von-Melle-Park 5
D-20146 Hamburg.

* Hamburgisches Hochschulgesetz
** die regelmäßige wöchentliche Arbeitszeit beträgt derzeit 39 Stunden

Weitere Informationen

Experimental Economics

Institution: Universität Hamburg, Fakultät für Betriebswirtschaft

Course instructor: Prof. Dr. Markus Nöth (Universität Hamburg)

Date: block course:

April 7 th, 2017: 8:15am-5:00pm (10*45min)
May 5th, 2017: 8:15am-1:00pm (6*45min)
June 2nd, 2017: 8:15am-5:00pm (10*45min)
June 21st, 2017: 6:00pm-7:30pm (2*45min)

Room: tbd (Moorweidenstraße 18, Von-Melle-Park 5 (ExpLab))

Course Value: 2 SWS or 4 LP

Teaching language: English

Registration: Send an email to markus.noeth@uni-hamburg.de until March 17th, 2017; please indicate if you prefer some specific topics to be covered.

Course Overview:
The main goal of this course is to give an introduction to the design and implementation of both laboratory and field experiments in various fields of Economics and Business Administration. PhD students who have some experience with or who consider to set up an experiment are welcome to participate in this course. First, we will identify different research questions for a laboratory or a field experiment. Second, based on a literature review (for some research fields that are proposed by the participants) an experimental design is developed and a pilot experiment will be set up and run in class. As part of this exercise, students will learn the basic requirements of a human subjects committee.

Topics:

  • Identify a suitable research question for an experiment
  • Ethical and scientific standards: historical and scientific reasons, consent requirements, human subjects committee, special requirements (children, elderly people, inmates, …), data collection and evaluation
  • Individual and group experiments in the laboratory
  • Surveys and internet experiments
  • Field experiments in cooperation with a company

General literature:

  • Kagel, John H., and Alvin E. Roth, 1995, The Handbook of Experimental Economics, Princeton University Press, Princeton/Oxford
  • Gerber, Alan S., and Donald P. Green, 2012, Field Experiments, W.W. Norton & Company, London/New York.
  • Kagel, John H., and Alvin E. Roth, 2015, The Handbook of Experimental Economics Volume 2, Princeton University Press, Princeton/Oxford

Assessment:

  • Paper presentation (May 5th)
  • experiment design presentation (extended summary on economic question, relevant literature, hypotheses, design: presentation with max. 10 slides or max. five pages extended abstract)
  • running a pilot experiment is optional

University of Hamburg: Introduction to Research in Closed-Loop Supply Chains

Institution: Universität Hamburg, Fakultät für Betriebswirtschaft

Course instructor: : Prof. Gilvan Souza (Kelley School of Business, Indiana University)

Date: June 16th 2017, 09:00-13:00 h  (block course)

Room: tba

Course Value: 1 LP

Teaching language: English

Registration: Please register via email to stefanie.nonnsen@uni-hamburg.de

Course Overview:
This course will provide an overview of research and tools used in closed-loop supply chain management research in operations management. A closed-loop supply chain is a supply chain with flows of products post-consumer use from consumers to retailers, manufacturers, and/or suppliers. Examples include consumer returns, and post-lease products. Emphasis will be given to strategic decision-making, such as product line extension, choice of product quality, and take-back legislation.

Course Contents:

  • An overview to closed-loop supply chains (CLSCs): types of product returns, and types of disposition decisions.
  • Examples of strategic, tactical and operational decisions in CLSCs
  • Strategic decision 1: Should an Original Equipment Manufacturer (OEM) offer a remanufactured product in its product line?
    • Monopoly pricing for a single product, and for a vertically differentiated product line under linear demand curves and constant marginal costs
    • The fundamental trade-off: Market expansion vs. cannibalization
    • Extension: non-linear demand curves
    • Competition between an OEM and a third-party remanufacturer
  • Strategic decision II: What is the optimal product quality when there is product recovery in the form of remanufacturing and/or recycling?
    • Introduction to classical quality choice models without product recovery (Mussa and Rosen, 1978)
    • Quality choice with product recovery: monopoly (Atasu and Souza 2013)
    • Quality choice with product recovery: competition between an OEM and a third-party remanufacturer (Orsdemir et al. 2014)
  • Strategic decision III: Design of optimal take-back legislation from a policy maker’s perspective, and an OEM’s response to it
    • The concept of welfare and its components: firms’ profits plus consumer surplus minus environmental impact
    • The model by Atasu and Van Wassenhove (2009)
  • Incentives and coordination in CLSCs
    • Reducing consumer returns through retailer effort (Ferguson, Guide, and Souza, 2006)
  • Overview of tactical decision making in CLSCs
    • Production planning for remanufactured products: product acquisition, grading, and disposition decisions
    • Hybrid inventory systems

Prerequisites: Background in Operations and Supply Chain Management is preferred but not absolutely necessary.

Assessment: Participation in discussion

University of Hamburg: HCHE Research Seminar and PhD Course 24 to 25 April 2017

Institution: Hamburg Center for Health Economics (HCHE)

Course instructor: Professor Mike Drummond, Professor of Health Economics and former Director of the Centre for Health Economics at the University of York

Date: 24-25 April 2017

Time:

  • 24 April: arrival of Prof. Mike Drummond, individual meetings (please ask for an appointment: andrea.buekow@uni-hamburg.de)
  • 24 April, 4:30 pm: HCHE Research Seminar Title: Where politics and economics collide: the case of orphan drugs
  • 25 April, 9:00 am – 5:00 pm: PhD Course Title: Methodological and Policy Issues in Economic Evaluation

Place: HCHE, Esplanade 36

  • HCHE Research Seminar: Rooms 4011/13
  • PhD Course: Rooms 4030/31

Credit Points: 1 SWS/2 LP (Universität Hamburg)

Teaching language: English

Registration for the PhD Course:  andrea.buekow@uni-hamburg.de, no later than 14 April 2017

University of Hamburg: Statistical Analysis of Big Data

Institution: Universität Hamburg, Fakultät für Betriebswirtschaft

Course instructor: Prof. Martin Spindler (UHH)

Date: Semester course, Time: T or W, 8-10am

Place: tba

Course value: 2 SWS or 4 LP

Course overview:
The main goal of this course is to give an introduction to statistical methods for the analysis of big data. Recently developed methods are discussed, in particular various methods of machine learning are presented and basic concepts for the analysis of big data are introduced. The course is based on the recent book by Efron and Hastie (2016).

Reference: Efron, B. and T. Hastie. Computer Age Statistical Inference. Cambridge University Press 2016.

Teaching language: English

Student evaluation: paper presentation/presentation of a chapter of the book

Registration: by email to martin.spindler@uni-hamburg.de

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.

 

 

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