AbstractsEconomics

Early detection of emerald ash borer (EAB) infestation is problematic, with indicators not appearing until late during an infestation, and detection methods often requiring tradeoffs between information yielded and cost. Decision makers must determine which detection methods provide information matching their objectives within budget constraints. Notably, objectives of decision makers may vary, hence also their perceptions of different options' costs and benefits. This thesis presents a conceptual framework on the detection strategy problem, developing a simulation model to investigate when each detection method for EAB is most economical. The most effective and expensive methods are found to be more efficient when the likelihood of a mid-level infestation is high, while inexpensive methods are efficient when infestation is less likely or severe infestation is likely. Accuracy of a detection method is found to be more important for infestation cost reduction than the characteristics of the information the method provides.