HELIOS Hybrid Evaluation of Lifecycle and Impact of Outstanding ScienceThe HELIOS Model (Hybrid Evaluation of Lifecycle and Impact of Outstanding Science) is a comprehensive framework designed to evaluate the maturity of emerging technologies by integrating multiple key indicators. The model combines data from R&D investment, scientific publications, patents, adoption levels, and regulatory frameworks to position each technology within its lifecycle phase. OverviewHELIOS [1] provides a composite index that simultaneously reflects both the state of scientific development (research impact) and technological advancement (diffusion and investment) of a technology. This hybrid approach draws inspiration from established frameworks such as NASA's Technology readiness level (TRL) and Rogers' adoption categories, which link technological evolution with user acceptance.[2] In the HELIOS framework, each variable indicates a complementary aspect of maturity: sustained growth in investment and publications typically precedes phases of technological expansion, while an elaborate regulatory environment points to a more consolidated technology. Mathematical formulationThe HELIOS index is calculated as a weighted average of five normalized variables (I, P, Pt, A, R) representing investment, publications, patents, adoption, and regulation, each scaled to the range [0,1]: Where the weights sum to 1. A typical weight distribution might be:
The resulting HELIOS value ranges from 0 (very early-stage technology) to 1 (high maturity). Scoring criteria and normalizationEach key variable is measured using standardized criteria and scales: Investment (R&D)Annual investment amount (public + private) in USD, normalized by dividing by the highest recorded level or sectoral target. Typical scoring ranges:
Scientific publicationsNumber of academic articles in the related discipline per year, normalized against historical maximum. Example ranges:
PatentsNumber of patent families published annually in the field. Similar normalization to publications:[3]
AdoptionDegree of technology implementation or usage, estimated as market penetration following the diffusion of innovations model:
RegulationMaturity level of legal frameworks and standards, qualitatively assessed:
Visual representationThe current state of the five variables can be represented graphically using a radar chart, where each dimension (investment, publications, patents, adoption, regulation) is measured from 0 to 1. The resulting surface reflects the technology maturity profile. Additionally, the typical Sigmoid function (S-Curve) illustrates the overall maturity trajectory: its maximum slope indicates the inflection point (rapid growth phase) and the final saturation level marks complete maturity. Variables and Scoring
Practical example: Quantum computingTo illustrate HELIOS, consider quantum computing with recent data:
Using suggested weights: A value of ~0.65 indicates an early growth stage, consistent with rapid expansion in patents and investment but limited adoption. This suggests quantum computing is still far from saturation, with the S-curve's increasing slope indicating that the mass adoption tipping point may be approaching. Applications and interpretationHELIOS values near 0.5–0.7 correspond to technologies in the development/early adoption phase, while indices close to 1 indicate maturity or stagnation. The model enables:
Enhanced HELIOS modelThe original HELIOS model was a linear evaluation tool, based on normalization and fixed weights, to assess the lifecycle and impact of scientific and technological developments. The enhanced version extends its scope with non-linear normalization (e.g., sigmoid functions), S-curve growth models for forecasting (investment, publications, patents, adoption, regulation), and dynamic weights across lifecycle phases. It also applies non-linear aggregation (e.g., Choquet integral, OWA operator) to capture synergies and redundancies, and integrates Uncertainty quantification methods such as Monte Carlo simulations. These upgrades turn HELIOS into a probabilistic forecasting framework, able to detect inflection points and support strategic planning, R&D investment, and policy-making in emerging technologies.[7] See also
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