This paper proposes the Architecture-Aware Real Options Framework (AA-ROF), a systems-based model for valuing research data in multi-tier socio-technical infrastructures (Institutional Archive, Federated Mesh, AI Sandbox). AA-ROF treats architecture as an endogenous generator of exercise friction and defines the “Architecture Premium” as the gain in realizable option value; two of its three named effects are standard option properties applied to this endogenous strike, and the novelty lies in coupling that strike to the environmental penalty of compute-intensive architecture. The analysis yields two conditional implications: low friction can sharply compress value sensitivity to scientific uncertainty, and Tier-3 infrastructure can offset redundant-data-creation losses once cross-disciplinary reuse exceeds an illustrative threshold. Its central result is a symbolic total-cost boundary: the admissible Tier-3 environmental penalty equals the Tier-2 penalty plus the option-value gain minus annualized capital cost. Thus, the reported value of 60 is only a zero-capital-cost illustration, not a general adoption threshold; tier parameters follow literature ratios, not inverted from the model. A two-period extension reports opposing conditional feedback effects rather than an unconditional tier preference. AA-ROF thus offers a systems-level baseline for governing environmental burden and realizable option value in research data infrastructure.
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Ko et al. (2026) studied this question.
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