Asteroids and other near-Earth objects pose a significant ongoing threat to our planet with the potential for catastrophic effects on human life, the environment, and the global economy. Advance warning would be necessary to deflect any object on a collision course with Earth, but detection and tracking technologies require substantial financial commitments. This paper presents a multiattribute utility framework to analyze whether and which detection technologies are worthwhile. This approach provides a rigorous and systematic understanding of the uncertainties, multiple objectives, and tradeoffs inherent in decisions involving low-probability, high-consequence events. The model shows that the detection technology investment decision is driven more by the abundant population of smaller (<140 meters in diameter) undiscovered near-Earth objects than by any other size category. In addition, we find that the preferred investment alternative varies substantially over a range of plausible value tradeoffs that a decision maker might assign to each human fatality, a well-studied economic measure used by governments and policymakers that is called the value of a statistical life. The model we present allows a decision maker to jointly examine the role of risk and ambiguity preferences in determining the best alternative, and we further extend the framework to consider how a decision maker might evaluate alternatives when the threat affects a larger group of people while the economic cost of investment is borne by a smaller subset of stakeholders. This paper was accepted by George Wu, behavioral economics and decision analysis. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2024.04948 .
Palley et al. (Wed,) studied this question.