Using Participatory Agent-Based Modeling to Teach Systems Thinking for Inventory Control

While systems thinking is critical to making good decisions in complex situations that frequently arise in supply chains, it is neither intuitive nor innate and must be trained explicitly. However, systems thinking and complexity are not formally taught in classrooms, and there is limited research on how to apply and assess approaches to teaching systems thinking in higher education. To address this gap, this research uses participatory agent-based modeling to improve learners' systems thinking skills and their ability to understand the consequences of complexity in supply networks when analyzing inventory control strategies. An agent-based model of a supply chain, in which agents represent suppliers and retail shops, was created using NetLogo. Students in an undergraduate course on production and inventory control were given a description of the supply chain and were asked to devise a suitable procurement and inventory control strategy for maximizing a retail shop's profit. The students then engaged with the model via HubNet, which allowed them to jointly participate in the simulation in the role of retail shops, making strategic, tactical, and operational inventory control decisions over the course of one simulated month. Student learning was assessed via sentiment analysis on reflection papers, with results indicating that engagement with the model helped students to better understand the role of production systems within a larger supply network, as well as increasing their understanding of the challenges associated with making good decisions in a complex and dynamic environment.