Demand drivers
The simple engine (why EDM is demanded every day): On EDMA, protocol fees are paid at the moment proof clears, and exactly 50% of every protocol fee is burned in EDM in the same transaction:
Tokens: 4% per settle/retire → 2% of GMV burns in EDM.
Trade: 0.5% per paid milestone (per-tranche caps) → ~0.25% of released value burns in EDM (until caps bind).
The Router converts the burn half into EDM and destroys it on-chain; the burn cannot be discounted or deferred. That creates continuous, programmatic buy-pressure for EDM proportional to real usage.
1) Mechanical demand → EDM burned per dollar
Per unit formulas (copy/paste):
Tokens: EDM_burn = 0.02 × Tokens_GMV
Trade (≤ $10M per tranche): EDM_burn ≈ 0.0025 × Trade_GMV
Trade (> $10M per tranche): EDM_burn per tranche = $25,000 (cap / 2), i.e., 25k ÷ tranche_size
Monthly EDM Burn Formula:
Tokens GMV: Total gross market value of token settlements/retirements in the period.
Trade GMV ≤ $10M: Total gross market value of trade releases where each tranche is $10M or less.
For each trade tranche > $10M: Add $25,000 divided by the tranche size.
This formula translates platform activity (GMV by route and tranche size) into the actual monthly EDM burned, which is the core demand driver for the token.
That burn comes from required conversions into EDM at each event—no “optional staking,” no “future promises.”
2) Volume drivers (what pushes GMV through the rail)
Pilot → region rollout: more households, parks, and corporate buyers = more token settle/retire events (high burn coefficient: 2% of GMV).
Commodity lanes on Trade: each additional RFQ→Release path adds milestone releases (typical burn ~0.25% of released value per gate).
ESG mandates: registry mirrors + first-seen rules remove double-count/greenwashing risk, unlocking institutional retirements.
Compliance automation: one-click proof packs (PoV hash, mirror serials, burn hash) reduce buyer friction → higher order frequency.
Partner integrations: utilities/aggregators, ERPs, TMS/WMS/ESG connectors drive automatic usage.
Takeaway: Tokens GMV is the strongest direct driver (2% burn), while Trade GMV contributes steady, compounding burn (≈0.25% per gate) and expands the addressable base.
3) Mix & structure (how the same volume burns more or less)
Route mix: more Tokens vs Trade increases burn rate (2% vs ~0.25%).
Tranche sizing (Trade): tranches ≤ $10M preserve the ~0.25% effective burn; ultra-large tranches hit the $50k fee cap (burn=$25k) and lower effective burn.
Milestone cadence: more gates (e.g., On-Board, Customs, Arrival & QA) = more burn events; collapsing gates reduces total burn opportunities.
Market depth: adding high-frequency routes (e.g., hourly attributes with daily retirements) increases event count at the 2% burn coefficient.
Design lever: keep tranches practical (≤$10M) and gate definitions granular—but honest—to maximize truth-tied burn while preserving operational sanity.
4) Structural lockups (reduce circulating supply / increase stickiness)
veEDM staking (governance): locks EDM for 30/90/180/365 days; rewards come from treasury half, not burns.
Attestor bonds (where required): bonded roles escrow EDM; slashing risk aligns behavior and reduces float.
Paymaster / ops buffers: operational EDM held for gas sponsorship and router conversions.
Treasury policies: DAO can direct a portion of the treasury half to long-term programs (e.g., attestor rewards, grants), keeping working balances sticky.
None of these replace the burn engine; they reinforce holder incentives and lower effective float.
5) Flywheels that compound usage
Proof-first trust → bigger tickets: corporates buy more when claims are audit-ready; each larger retirement settles a 2% burn.
Attestor SLA leaderboard → better latency: faster passes reduce friction; more events complete; more burns.
Registry mirrors → eligibility expansion: once mirrored, tokens become compliant instruments in new markets, unlocking fresh retirements.
Integrations → automation: ERP/TMS/ESG webhooks convert manual transactions into programmatic flows (more frequent, smaller units → more burns on average).
DeFi rails (bounded, Phase 4+): Supplier Advance and Top-Up Bridge increase on-time releases (burn happens when they clear), without ever discounting burns.
6) Worked monthly scenarios
Scenario A — Early scale (pilot region): Tokens GMV = $25M; Trade GMV (≤$10M tranches) = $50M. EDM burned ≈ 0.02×25M + 0.0025×50M = $500k + $125k = $625k/month (in EDM value)
Scenario B — Two regions mid-scale: Tokens GMV = $70M; Trade GMV = $120M (10 tranches at $12M, rest ≤$10M). Trade burn ≈ 0.0025×(120M − 120M_from_capped) + capped tranches 10×25k = 250k (e.g., if $60M uncapped: 0.0025×60M = 150k; total trade burn ≈ $400k). Tokens burn = 0.02×70M = $1.4M. Total burn ≈ $1.8M/month
Scenario C — Tokens-heavy enterprise: Tokens GMV = $150M; Trade GMV = $60M (≤$10M tranches). Burn ≈ 0.02×150M + 0.0025×60M = $3.0M + $150k = $3.15M/month
(DAO dashboards should publish realized monthly burns alongside GMV by route and tranche distribution.)
7) What does not drive EDM demand (by design)
Gas: tiny, pass-through, never burned.
Mint / Convert / Mirror / Revoke: no protocol fee, no burn.
Rebates / staking rewards: come from the treasury half, not from the burn half.
Listings / drafts / holds: no fee until settle/release.
8) KPI links (to keep the engine honest)
Burn coverage = 100% of settle/release events (every receipt shows a burn hash).
Duplicate block rate > 99.9% (One-Claim) ensures no double-monetization.
EMT→Release p95 ≤ 15s keeps friction out of volume.
PoR daily 100% builds buyer confidence → repeat usage.
Plain recap
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