Key points are not available for this paper at this time.
Cost-feasibility assessment remains a persistent challenge in the New Space economy, where early-stage missions must be evaluated under profound technological, operational, and financial uncertainty and where reliable historical cost data are often unavailable. Conventional parametric and regression-based cost models offer limited support in these settings, as critical architectural decisions are taken before technologies, interfaces, and operational concepts have stabilized. This study proposes a hybrid, expert-based framework for structuring early-stage cost-feasibility reasoning in frontier space missions by integrating systematic literature review, structured expert elicitation, and Partial Least Squares Structural Equation Modeling. The framework is demonstrated through a case study of lunar oxygen production via regolith sublimation. Implemented across three phases, the approach identifies and refines mission-relevant cost drivers through Delphi-based expert judgment and synthesizes these assessments into a coherent quantitative structure. The resulting model explains approximately 57% of the variance in expert cost assessments, indicating stable and interpretable patterns in expert judgment under conditions of high uncertainty. Within this structure, technological readiness and operational efficiency emerge as the most influential dimensions shaping perceptions of overall project magnitude. Rather than aiming to predict realized mission costs, the framework is designed to support relative comparison, early-stage architectural decision-making, and the disciplined organization of uncertainty. Anchored to an equipment-cost proxy and expert-derived driver weights, the framework produces an illustrative, order-of-magnitude project-scale estimate of approximately USD 30.7 billion for the reference mission configuration, consistent with expectations for large-scale space-resource initiatives. The principal contribution of the study lies in providing a transparent process for translating dispersed expert knowledge into structured cost-feasibility reasoning, with implications for early mission planning, derisking strategies, and stakeholder alignment in high-uncertainty space ventures.
Giulio Marano (Tue,) studied this question.