Institutionalizing Technological Foresight: A Multi-Domain Evaluation Model for Strategic Investment Decision Support

Reliable differentiation between hype-driven and structurally sustainable technologies remains a critical challenge in strategic investment environments, particularly within national security and high-responsibility domains. This study introduces the Technology Durability Score (TDS), a mathematically grounded evaluation model developed within the HAVELSAN framework. The model integrates four core dimensions-whitepaper/documentation depth, developer activity, protocol-level innovation, and problem-solution alignment-into a composite metric while accounting for adversarial robustness, temporal generalizability, and expert alignment. Empirical validation was conducted on 3000 synthetic projects and 300 real-world cases across dotcom, blockchain, and artificial intelligence domains. The model demonstrated high discriminative capacity, assigning scores $\geq 1.20$ to technically resilient projects such as Ethereum and ChatGPT, while assigning scores $\mathbf{\lt 0. 6 0}$ to hype-driven cases including Bitconnect and Tay. False positive rate against adversarial generated synthetic hype was limited to $12.2 \%$, and temporal accuracy loss remained under $9 \%$. Expert judgment alignment reached $84 \%$. These findings establish the TDS model as a reliable, explainable, and domain-adaptable tool for early-stage technology screening, enabling evidence-based investment decisions in complex innovative landscapes.