Lab experiments have been widely used to obtain insights into human ordering behavior and the deviations from optimal order quantities. However, empirical work in real-world settings is still lacking. We fill this gap by examining approximately 180,000 order decisions of a material handling equipment manufacturer, where human planners place orders after receiving an order recommendation from a decision-support system (DSS). We focus specifically on the likelihood of deviations from a recommendation from the DSS and the direction of such deviations. We link such deviations to different item and demand characteristics, such as demand variability, lead time and supply uncertainty. Therefore, we develop two hierarchical generalized linear models (HGLMs) with three levels: the observation or order level, item level and planner level. We show that (i) planners adjust the recommendation when the item is important for production and the supply uncertainty and lead time are high, and (ii) planners adjust the recommendation in the direction that aligns with their incentives, i.e., upward when uncertainties increase and downward to reduce inventory value. Surprisingly, planners significantly decrease the order quantity relative to the order recommendation when supply uncertainty is high.

Prof. Dr. Kai Hoberg is Professor of Supply Chain and Operations Strategy and Head of Logistics Department at Kühne Logistics University in Hamburg, Germany. Before joining KLU, he was as assistant professor of supply chain management at the University of Cologne and project manager in the operations team at Booz & Company. Kai’s current research topics include supply chain analytics, role of technology in supply chains, inventory modeling, and the link between operations and finance.  His research findings have been published in academic journals like Journal of Operations Management, Production and Operations Management or European Journal of Operational Research.

https://www.wu.ac.at/en/scm/events/speaker-series/summer-semester-2019