This thesis studies biases in offshoring decisions and proposes a tool to improve understanding of the value of lead-time. Recent research results show local responsive production reduces mismatch between supply and demand, but this aspect of the cost is often overlooked in offshoring decisions, leading to suboptimal decisions. The tradeoff between lower unit costs and mismatch cost under demand uncertainty as lead-time increases, and the benefits of a local portfolio of products with different demand volatility, make the offshoring decision complex and the optimal solution sometimes counterintuitive. Building on behavioral research, I designed software-based laboratory trials to explore patterns of decisions in an offshoring problem, and a simulation-game to help teach and communicate research insights. In the first paper, I find that participants facing an offshoring problem fail to apply the economically optimal strategy. In the second paper, I find that non-economic factors like peer influence play a role in offshoring decisions. These trials are exploratory in nature and do not provide generalizable results, rather, they are a step towards a better understanding of the fundamental research questions and the conception of experiments. In the third paper, I describe the development and use of a simulation-game to help students, managers and policy makers understand the value of lead-time and volatility portfolio through an active learning approach. My work contributes to the understanding of the impact of bounded rationality in offshoring decisions and proposes a teaching method adapted to the challenges posed by the concepts involved.