Cryptocurrencies primarily fall into three categories: stores of value, security tokens, and utility tokens. Universal stores of value can be evaluated using the equation of exchange because they possess independent monetary properties. Examples include Bitcoin, Bitcoin Cash, Zcash, Dash, Monero, and Decred. Some may disagree, but I also classify smart contract platforms like Ethereum, EOS, Dfinity, and Kadena in this category, as their native tokens have the potential to become independent stores of value if widely adopted.
Traditional securities are well-understood, so this article will not cover security tokens. While moving securities to blockchain offers advantages in settlement times and oversight, it doesn’t change their fundamental nature.
This article focuses on utility tokens.
Background
Most Initial Coin Offerings (ICOs) in 2016 and 2017 were utility tokens that doubled as proprietary payment currencies. High-profile examples include Filecoin, Golem, 0x, Civic, Raiden, and Basic Attention Token.
Each of these positioned itself as an independent monetary base, valuated using the equation of exchange: MV = PQ, which implies M = PQ/V. As discussed in my article "Understanding Token Velocity," the velocity (V) is a major challenge for proprietary payment tokens. High velocity often creates persistent downward pressure on token prices. I estimate velocity for such tokens could exceed 100, possibly reaching 1,000. For context, the M1 velocity of the U.S. dollar is approximately 5.5.
Below, I introduce two new token economic models designed to address the velocity problem for utility tokens. Both aim to achieve the following:
- Token price increases roughly linearly with network usage.
- Conversely, token price decreases if network usage declines or falls short of growth expectations.
Work Tokens
Augur pioneered the work token model, and Keep is another example.
In this model, service providers must stake (or "bond") the native token to earn the right to perform work on the network. This applies to "commodity-as-a-service" networks like Keep (off-chain privacy computation), Filecoin (distributed file storage), Livepeer (distributed video transcoding), Truebit (verifiable off-chain computation), and even decentralized labor platforms like Gems. The probability of a service provider being assigned a task is proportional to their staked tokens relative to the total staked tokens.
The beauty of this model is that increased network usage drives token price appreciation, even without speculators. As demand for services grows, providers earn more revenue. With a fixed token supply, providers rationally bid more per token to gain the right to earn this growing cash flow.
Most work token systems incorporate slashing mechanisms to penalize providers who fail to meet performance standards. For example, Filecoin providers commit to storing data for a period and must lock tokens as collateral. If they underperform, the protocol automatically slashes a portion of their stake.
Valuing work tokens is straightforward using net present value (NPV).
Compared to the "token-as-currency" model, work tokens fundamentally change valuation. Consider Filecoin’s target market of $110 billion by 2021. Under the traditional model, assuming a velocity between 30 and 100, Filecoin’s market cap would be $1.1–3.6 billion.
Under the work token model, assuming a 40% discount rate and 50% operating margin, Filecoin’s potential value is $110 billion × 50% / 40% = $137.5 billion—about 100 times higher.
Why? Because "token-as-currency" caps value at a fraction of transaction volume (M = PQ/V, V > 1), while work tokens represent a multiple of operating cash flows. As the network matures, risk decreases, further boosting value.
Work tokens only suit pure commodity services. If competition involves factors like marketing or customer service, another model is needed.
Burn-and-Mint Equilibrium (BME)
Factom pioneered the Burn-and-Mint Equilibrium model. To my knowledge, it’s the only token with substantial network value using this approach.
In BME, the token is a proprietary payment currency, but users burn tokens to access services instead of paying providers directly. The cost in USD terms is fixed—e.g., accessing Factom costs $0.001, regardless of token price.
Separately, the protocol mints new tokens each period, distributing them proportionally to providers based on their contribution to burned tokens. If total burned tokens are 50, and provider A burned 1, they receive 2% of newly minted tokens.
The minting rate (X) is not a function of burned tokens to avoid circular logic.
In equilibrium, linear growth in network usage drives token value appreciation. If burned tokens exceed minted tokens, supply decreases, pushing prices up. If minted tokens exceed burned tokens, supply increases, pressuring prices down.
This model assumes users and providers prefer holding stable currencies over the native token. It doesn’t require services to be commodities, allowing providers to compete on price and quality.
Choosing the Right Model
Work tokens capture more value, so teams should use them where possible. They suit decentralized cloud services like Filecoin, Keep, Truebit, and Livepeer, or human-powered services like Augur and Gems, where services are undifferentiated commodities.
BME fits services where providers compete on non-protocol factors—e.g., Civic (business development), 0x (user experience, API quality), or Basic Attention Token (content differentiation).
ICOs and Token Distribution
Work token systems don’t require broad token distribution to users. Service providers seeking profit will quickly adopt protocols that monetize underutilized hardware. Services like AwesomeMiner or 1protocol can dynamically allocate resources to the most profitable networks.
BME systems still need tokens distributed to millions of users to enable service access.
Pricing
In work token models, service prices are set at the network level. Providers cannot set individual prices, but competition occurs across networks (e.g., Filecoin vs. Amazon S3).
In BME models, each provider sets their own prices.
Governance
In traditional "token-as-currency" models, users rarely participate in governance due to high velocity—they don’t hold tokens long enough to vote.
Work tokens shift voting to suppliers (stakers), resembling decentralized equity where shareholders decide strategic directions.
For BME, it’s unclear how token-based voting is affected, as tokens still function as currency.
Network Effects
Neither model significantly alters network effects, which depend on protocol attributes, not token liquidity. For example, 0x’s network effect stems from global liquidity pools, not ETH-ZRX pairs. Similarly, Filecoin’s network effect grows logarithmically, regardless of the token model.
Scaling Work Token Networks
As work token networks grow, interesting dynamics emerge. If a provider holds 1% of tokens but lacks capacity to scale, they can sell tokens at appreciated prices or lend them via protocols like 1protocol, allowing others to expand network capacity.
Synthetic Tokens
Both models are compatible with cross-chain synthetic tokens, as discussed in "The Smart Contract Network Effect Fallacy."
Conclusion
Ethereum enables developers, providers, and consumers to transact with programmable money. Work tokens and BME are just two examples of this innovation. The design space is vast and largely unexplored.
As the crypto ecosystem matures, developers will experiment, refine, and invent new models to capture value for native tokens without sacrificing user experience.
Frequently Asked Questions
What is a utility token?
A utility token provides access to a product or service within a blockchain network. Unlike security tokens, they are not designed as investments. Examples include Filecoin for storage and Basic Attention Token for digital advertising.
How does the work token model control velocity?
By requiring service providers to stake tokens to earn work rights, the model reduces circulating supply. This creates buying pressure and lowers velocity, as tokens are locked rather than traded frequently.
Can the burn-and-mint model sustain long-term value?
Yes, if usage grows consistently. The equilibrium mechanism adjusts supply based on demand, promoting price stability. However, value depends on sustained network activity and adoption.
Which industries suit work tokens best?
Commodity-based services like cloud storage, computation, and bandwidth. Any service where performance is standardized and competition is purely on price fits this model.
How do synthetic tokens integrate with these models?
Synthetic tokens can represent staked or burned assets across blockchains. This enables interoperability, allowing users to participate in networks without holding the native token directly.
What are the risks of high token velocity?
High velocity indicates tokens are spent quickly rather than held, reducing scarcity and downward pressure on price. This makes it challenging for tokens to appreciate as networks grow.