The objective of this course is to introduce students to several quantitative analysis techniques such as linear programming, integer programming, network models, and decision analysis that are commonly used in the field of logistics and supply chain management. Throughout the course students will gain experience with these techniques through in-class exercises, case studies, discussions, and practitioner presentations. On successful completion of the course students should be able to identify and understand a managerial decision making problem, formulate a quantitative model to represent it, solve the problem using the analytical techniques learned, interpret the results and perform sensitivity analysis, and be able to explain the underlying assumptions and the limitations of the techniques learned.
The objective of this course is to introduce students to the applied quantitative research in the field of logistics, operations and supply chain management. The students are expected to present and discuss papers from both classical and emerging literature, and to turn these presentations into learning experience for the participants via discussions. Through the presentations, discussions and term paper, the course aims (1) to enhance and reinforce the understanding of the data-driven, scientific decision making process, (2) to develop familiarity with the real-life applications of quantitative analysis and operations research tools, (3) to improve critical reading and presentation skills, (4) to advance the students in formulating a research problem that might potentially be extended to a master’s thesis.
The purpose of the course is to introduce students to the state-of-the-art research on closed-loop supply chains while improving their critical reading and presentation skills and to advance them in formulating a research problem that might potentially be extended to a publication. The students are expected to present and discuss papers from both classical and emerging literature on strategic, tactical and operational aspects of closed-loop supply chains and to turn these presentations into learning experience for the participants via discussions. Through presentations, discussions and a final assignment of short research paper, the course aims to develop familiarity with the current literature and improve modeling and presentation skills.
The objective of this course is to introduce students to a variety of tools that will improve their critical reasoning skills and ultimately the ability to make effective decisions. In the first part of the course, the students will learn (1) how to analyze arguments and identify when arguments are not supported by facts, (2) how to see through fallacies in arguments, (3) how to construct valid arguments based on true premises, and (4) how to present these arguments effectively to develop fact based decisions for their organizations. In the second part of the course, the student will be introduced to different approaches, analytical methods and support tools commonly used in scientific decision making. In particular, we will discuss (1) fact-based decision making process, (2) decision making under uncertainty, (3) decision trees, and (3) risk attitudes. Students will gain experience in the practice and process of critical reasoning and fact-based decision making through extensive in-class discussions, workshops and open-ended case studies.
Prof. Dr. Çerag Pinçe
Tel: +49 40 328707-251
Fax: +49 40 328707-209