This Hype Cycle uses the Norton-Bass Multigenerational Diffusion Model to calculate adoption curves for optical transceiver technologies. The model extends the classic Bass diffusion model to handle multiple generations of technology that compete and cannibalize each other.

Key Parameters:

• p (innovation coefficient) — Rate of adoption driven by external influence (marketing, industry events). Typically 0.01–0.05 for B2B networking equipment.
• q (imitation coefficient) — Rate of adoption driven by word-of-mouth and peer influence. Typically 0.3–0.5 for optical networking.
• m (market potential) — Total addressable market size, estimated from port shipment forecasts (LightCounting, Dell’Oro).
• τ (introduction time) — Year when the technology became commercially available.

Phase Classification: Technologies are classified into five phases based on their position on the adoption curve: Innovation Trigger (0–16%), Peak of Inflated Expectations (16–35%), Trough of Disillusionment (35–55%), Slope of Enlightenment (55–80%), and Plateau of Productivity (80–100%).

Composite Score: A weighted blend of adoption velocity (40%), market momentum from pricing data (30%), and ecosystem maturity from compatibility entries (30%). Score ranges from 0–100.

Data Sources: Adoption timing derived from IEEE/MSA standard ratification dates, market data from aggregated pricing across 60+ vendors, and compatibility data from 29,000+ verified switch-transceiver pairs.