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Nr. LV-Typ(en) LV-Titel
4623 PI SCSDT 2: Supply Chain Network Design (Group B) Präsenz-Modus
Anmeldung über LPIS
vom 01.02.2024 15:00 bis 08.02.2024 23:59
Abmeldung über LPIS
vom 01.02.2024 15:00 bis 07.05.2024 23:59

LV-Leiter/in Univ.Prof. Tina Wakolbinger, Ph.D.
Planpunkte Master Supply Chain Strategy and Digital Transformation - Course 2
Semesterstunden 2
Unterrichtssprache Englisch

Termine
Fr, 10.05.2024 09:00-12:30 Uhr TC.5.03 (Lageplan)
Di, 14.05.2024 12:00-15:30 Uhr TC.0.04 (Lageplan)
Fr, 24.05.2024 09:00-12:30 Uhr TC.5.03 (Lageplan)
Mi, 05.06.2024 09:00-12:30 Uhr TC.3.05 (Lageplan)
Fr, 14.06.2024 09:00-12:30 Uhr TC.5.03 (Lageplan)
Fr, 21.06.2024 09:00-12:30 Uhr TC.5.03 (Lageplan)
Fr, 28.06.2024 09:00-11:00 Uhr P TC.0.04 (Lageplan)
Termindownload (ical) | Termine abonnieren

Weitere Informationen https://learn.wu.ac.at/vvz/24s/4623

Kontakt:
tina.wakolbinger@wu.ac.at
Inhalte der LV:

The lecture is structured as follows:

1.) Introduction to Supply Chain Network Design

2.) Fundamentals of Supply Chain Modeling - Service Levels and Capacity

3.) Fixed and Variable Costs in Supply Chain Networks

4) Advanced Network Modeling

5.) Global Supply Chain Design and Risk Management

6.) Supply Chain Network Design in Practice

Lernergebnisse (Learning Outcomes):

After successful completion of the module, students should have acquired an understanding about the topics of supply chain network design. Students should have the skills and competence to evaluate the international environment and its implications for global supply chain design. Furthermore, students should be able to develop quantitative models that support decision-making in global supply chain networks.

Regelung zur Anwesenheit:

According to the examination regulation full attendance is intended for a PI. Absence in one unit is tolerated if a proper reason is given.

Lehr-/Lerndesign:

The course is based on lectures, discussion of assigned readings, cases, and application exercises. You are expected to have completed assignments, read the assigned material, and rework class exercises and demonstrations after each class session. If your expectations for the course are not being met or if you are concerned about your grade or other course related matters, please talk to your instructor as soon as possible during the semester.

PowerPoint lecture notes, grades, and other information related to the class will be posted throughout the semester in Canvas. Emails will besent to students’ university email accounts.

Leistung(en) für eine Beurteilung:
  • Homework assignments: 20% 
  • Case Study: 10 % 
  • In-class assignments: 20 %
  • Final Exam: 50 %

In order to pass the class, you need attend at least 60 % of all classes,  get more than 40 % on the final exam and more than 60 % overall. If you fulfill these criteria, the following grading scale will be applied:

  •     Excellent (1): 90% - 100.0%

  •     Good (2): 80% - <90%

  •     Satisfactory (3): 70% - <80%

  •     Sufficient (4): 60.0% - <70%

  •     Fail (5): <60.0% 

Prerequisite for passing the course: minimum performance of 40% in the final examination.

 

HOMEWORK:

 

An electronic version of the homework is due at the start of class on the day assigned. Any homework that is late will receive a score of zero. Cooperation with other students on homework assignments is encouraged. However, the final write-up must be done individually. ‘Duplicate’ homework write-ups are unacceptable and will receive a score of zero.

 

CASES:

 

You will work in teams of 4 students on one case study. Every member of your team will receive the same score, subject to controls for "free riding."

Teilnahmevoraussetzung(en):

Incoming students (exchange programs): At least 5 ECTS credits in Operations Research and/or Management Science (linear programming, decision analysis, decision trees).

Zuletzt bearbeitet: 22.11.2023 10:57

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