Data-informed Decision Support when Order Fulfillment is at Risk

Focused on providing customers with punctual and complete deliveries of their requested products, order fulfillment is an important process within supply chain management under uncertainty. Late or insufficient deliveries create the risk of bad publicity, customer churn and lost sales. In a semiconductor B2B setting, we investigate customer complaints when orders deviate from the initially agreed commitment between both parties. Although a set of mitigation strategies to handle complaints is established, we find that the supplier would be better off it proactively managing order fulfillment at risk. In this vein, we examine possibilities for a predictive, behavior-aware and prescriptive decision support by empirically applying novel research methods in the operations management field.

Patrick Moder joined Kühne Logistics University in January 2021 as Ph.D. Candidate supervised by Prof. Dr. Kai Hoberg and Prof. Dr. Henrik Leopold. Patrick conducts his research on data-informed decision support when order fulfillment is at risk. He works in close collaboration with Infineon Technologies AG, where he will apply his theoretical results in the environment of a global semiconductor supply chain. Patrick received his Master of Science (Dipl.-Ing.) degree from the Technical University of Munich with a major in Mechanical Engineering and Management. In the course of his Master´s thesis, he applied semantic web technologies to detect changes in the semiconductor product lifecycle and to identify inconsistencies in change-related supply chain data. During the Master´s program, he spent a semester abroad in Sweden at Linköping University`s Institute of Technology. He received his Bachelor of Science degree from the Technical University of Munich, focusing on supply chain event management in the course of his Bachelor´s thesis.