Zou Chuanwei: Exploring Distributed Business Logic and Development Strategies with DeFi as an Example

There is a J-curve relationship between value creation and scale in distributed commerce, and distributed commerce can only create net value once scale exceeds a certain level.

Written by Chuanwei Zou, Chief Economist, Wanxiang Blockchain

In the great digital migration of human society, the impact of distributed commerce is growing. The world tends to be flattened, people tend to connect with each other in an anytime, anywhere and on-the-go manner, self-organization brings transformative power, and some centralized organizations are being disrupted. In the real economy, the sharing economy model is accelerating in the new crown epidemic. In the financial sector, FinTech has become an irreversible global trend.

The analysis of distributed commerce is generally based on the new institutional economics theory of the firm. Distributed commerce is essentially a market form. If some transactions are conducted through market mechanisms with lower transaction costs than through firms, it provides the ground for distributed commerce to develop. The analytical perspective of transaction costs, although profound, is difficult to support refined analysis because of the rich connotations of transaction costs.

DeFi is based on blockchain, a distributed technology, and the process of value creation and flow is very clear, and there is a clear correspondence between it and mainstream financial organizations, so a focused analysis of DeFi helps reveal the general logic of distributed commerce. For example, the volume of transactions on Uniswap is comparable to that of Coinbase for some time periods, and the business value created by both should be comparable as well; Coinbase creates business value in terms of profits and market value of shares, but where does Uniswap create business value? Is it the market value of Uni tokens? Is it possible to value the Uni token in comparison to the Coinbase stock?

This paper examines the distributed business logic by analyzing these new questions in the development of DeFi. The central conclusion is that there is a J-curve relationship between value creation and scale in distributed commerce. This conclusion helps to understand not only the growth strategy of distributed commerce and the competitive relationship with centralized commerce, but also some important mechanisms of distributed commerce, such as why DeFi cannot be separated from Staking, the value that governance tokens can capture.

This paper is divided into three parts. The first part is an introduction, the second part discusses the J-curve of distributed commerce, and the third part discusses distributed commerce development strategies and important mechanisms.

The J-Curve of Distributed Commerce
This section first discusses a simplified example of distributed commerce to introduce the basic concepts relevant to the analysis of this paper, then gives the J-curve, and finally compares it with centralized commerce to better understand distributed commerce.

A simplified example of distributed commerce
Suppose there exists a class of goods (e.g., apples) and two countries, country A and country B. Each inhabitant of country A is a producer of the good, labeled A_1, A_2, …, A_m. Each inhabitant of country B is a consumer of the good, labeled B_1, B_2, …, B_n.

Under a distributed commerce, any resident of country A can trade directly with any resident of country B. Thus, there are a total of m*n pairs of possible counterparties and the network of transactions is very dense. But this does not happen out of nowhere. Ideally, first, each commodity producer needs to know the preferences and purchasing power of each commodity consumer, and each commodity consumer needs to know the quality and price of each commodity producer; second, commodity producers and consumers need to find the most suitable counterparty through a set of search mechanisms; finally, matching commodity producers and consumers requires a set of mechanisms to guarantee the fulfillment of the transaction, the core of which is The core is the delivery of goods and payment of funds.

Suppose a commodity producer A_i and a consumer B_j are a pair of counterparties, and the highest price B_j is willing to pay for a unit of commodity is $10, while the lowest price A_i is willing to charge for a unit of commodity is $6. Suppose that the two negotiate and set the price for a unit of the good at $8. Then, this transaction yields a consumer surplus of $2 (= 10-8) and a producer surplus of $2 (= 8-6), for a total economic value of $4 (= consumer surplus + producer surplus). The negotiation of prices between producers and consumers of commodities can be considered as a transaction aggregation process.

Distributed commodities, despite their very dense trading network, face uncertainty in searching for counterparties, transaction aggregation, and transaction fulfillment, both for commodity producers and for commodity consumers. As a comparison, look next at the approach of centralized commerce.

Suppose that trade between countries A and B is conducted through an intermediary I. I promises to acquire the commodity from the commodity producer at $7 and sell it to the commodity consumer at $9. In this way, both producers and consumers of the good need only trust I, without having to know each other or search for counterparties, and both the trade is brokered and fulfilled only for I (with a total of m+n possible pairs of trading relationships), and the uncertainty they face is greatly reduced. However, the benefit distribution pattern will change significantly, as illustrated by A_i and B_j. Under centralized commerce, the consumer surplus is $1 (= 10-9), the producer profit is also $1 (= 7-6), and the intermediary earns $2 (= 9-7), leaving a total economic value of $4 (= consumer surplus + producer surplus + intermediary profit).

The establishment of the intermediary’s position consumes costs, such as acquiring relevant license qualifications, developing expertise in commodity evaluation, establishing supply chain and payment systems, and the need to tie up free funds during the time lag between acquiring and selling the commodity. Intermediaries bear the risk of not being able to sell or selling at a loss after acquiring the commodity. A portion of the intermediary’s profit is compensation for these costs and risks. Of course, if the intermediary is in a monopoly position in the trade, it can also make a profit from monopoly rents.

Centralized commerce can be valued if it has a clear scale of profitability and predictable cash flows. Distributed commerce is essentially a public good by providing a network of markets that facilitate direct transactions between participants. Public goods, despite their economic value, cannot be valued according to commercial principles. Figuratively speaking, in centralized commerce, economic value is deposited to some intermediaries in the flow, forming their profits and valuation; in distributed commerce, economic value is shared directly by participants, who of course need to make their own decisions and bear their own risks.

It should be noted that although the above example is for commodity trading, the logic holds for other types of distributed commerce as well. For example, in decentralized lending, Token lenders and borrowers can be matched directly; in decentralized exchanges, Token buyers and sellers can be matched directly.

In distributed commerce, participants can trade directly with each other, which generates two main benefits. First, the network effect, which can be portrayed by Metcalfe’s law, is proportional to the square of the number of participants. Second, when participants trade directly with each other, the value generated by the transaction is shared among them. Whereas, when participants trade through intermediaries, they must share part of the value generated by the transaction with the intermediaries.

There are prerequisites for direct trading between participants. First, there must be mutual trust between the participants. The integrity system has many manifestations. For example, trust generated by laws and regulations and ethical rules; trust generated in the real world through repetitive gaming; trust generated by blockchain, embodied in “code as law”; and trust generated in DeFi through Staking and collateral. Second, participants need to be able to find the right counterparty. This entails collecting and analyzing information, searching for counterparties, and transaction brokering. Third, participants need to secure trade fulfillment. All three of these prerequisites consume costs to secure, and the associated costs are proportional to the number of participants.

If the size of a distributed business is denoted by N (for example, N denotes the number of participants), then the economic value generated by a distributed business is equal to (all formulas in this article are for the convenience of reasoning)

Zou Chuanwei: Exploring Distributed Business Logic and Development Strategies with DeFi as an Example

where a denotes the conversion rate from network effect to economic value, which may vary greatly from network to network. b denotes the cost rate of building an integrity system, collecting and analyzing information, searching for counterparties, transaction brokering, and transaction fulfillment, etc. The relationship between value creation and scale in distributed commerce is shown in Figure 1, which is called the “J-curve effect” in this paper.

Zou Chuanwei: Exploring Distributed Business Logic and Development Strategies with DeFi as an Example

Figure 1: J-curve for distributed business

When the scale is not large enough, the network effect of distributed commerce does not come into play, and the economic value generated is lower than the construction cost, which is reflected in the front part of the J curve; only after the scale exceeds a certain level (i.e., the break-even point), the net value creation of distributed commerce turns positive.

Comparison with centralized commerce
Centralized commerce requires fixed costs, but the resulting license qualification, expertise, and infrastructure can be reused and can generate economies of scale. Again using N to denote the size of centralized commerce, the economic value generated by centralized commerce is equal to

Zou Chuanwei: Exploring Distributed Business Logic and Development Strategies with DeFi as an Example

where e portrays the efficiency of economies of scale of the centralized business and f portrays the fixed cost inputs of the centralized business. The relationship between value creation and scale of a centralized business is shown in Figure 2. centralized businesses also have break-even scale.

Zou Chuanwei: Exploring Distributed Business Logic and Development Strategies with DeFi as an Example

Figure 2: Value creation in a centralized business

The efficiency parameter e for economies of scale in centralized commerce has a very rich connotation. For example, in banking and insurance, a dollar of capital can support several dollars of assets (under Basel, banks are leveraged at 3%, meaning assets can be 33 times capital); in OTC derivatives trading, notional exposures can be many times the size of collateral; the notional principal amount of futures can be many times the margin; and a certain amount of liquidity can support several times the size of transactions through netting after rollover. A certain amount of liquidity can support several times the size of a transaction. The leverage of the financial system can be understood basically from this perspective, which reflects the advantages of centralized commerce in the financial field: 1. the scale advantage; 2. the risk diversification effect; 3. the liquidity savings from netting after rollover; 4. the leverage effect of derivatives. However, once a centralized financial intermediary encounters risk, it may create a shock to the financial system and even have spillover effects on society. This risk of ‘single point of failure’ is precisely why centralized financial intermediaries are strictly regulated.

Zou Chuanwei: Exploring Distributed Business Logic and Development Strategies with DeFi as an Example

Figure 3: Distributed versus centralized commerce

Figure 3 compares distributed versus centralized commerce. In terms of value creation alone, centralized commerce outperforms distributed commerce on a significant scale. The advantage of distributed commerce over centralized commerce can only be demonstrated once it exceeds a certain scale (called ‘critical scale’). This is a concrete manifestation of the boundary problem between market and business.

Distributed commerce development strategies and important mechanisms
To improve the value creation of distributed commerce, it is necessary to improve the conversion rate of network effects to economic value on the one hand, and to build an integrity system, collect and analyze information, search for counterparties, transaction matching, and transaction fulfillment at a lower cost on the other. But in the end, distributed commerce must make growth its first priority and reach critical mass as soon as possible to justify itself relative to centralized commerce. A few examples from the DeFi space follow to illustrate.

DeFi lending. Within the public chain is a de-trusted environment where direct transactions can be made between any two addresses, and smart contracts can be used to execute complex transactions. However, addresses cannot be used as credit subjects in the usual sense without being associated with an off-chain identity or reputation mechanism. For example, DeFi lending requires an overcollateralization of the borrowing address in order to secure future repayment. The overcollateralization mechanism is the integrity system in DeFi lending, which excludes the influence of widely varying credit qualifications at the individual level and greatly simplifies the work required to collect and analyze information. The cost of building this integrity system is reflected in the locked-in liquidity of the collateral, which grows linearly with the number of addresses, but allows DeFi lending to be done in a de-trusted manner, enabling effective network effects. The DeFi lending platform earns profits by setting the spread between the deposit and lending rates algorithmically, without the cost of evaluating the creditworthiness of the borrower and post-loan management as banks do, and with little or no risk to itself.

In AMM, liquidity pools also serve as a central counterparty function and are more efficient than order book transactions. Liquidity pools eliminate uncertainty for investors in terms of finding counterparties, transaction prices and volumes, and are an important commitment mechanism in a decentralized, de-trusted environment (see “General Theory of AMM” (Issue 31, 2021)). Regardless of how investors trade with the liquidity pool, the liquidity pool has to satisfy some constraints (e.g., constant product), so AMM can be considered as a cooperative on liquidity.

The above two examples also illustrate that in the general framework of distributed commerce, mechanisms with centralized overtones cannot be excluded at some points. For example, the de-trusted environment of public chains and overcollateralization, although eliminating the effect of individual heterogeneity, still face a lot of challenges in searching and matching between counterparties in a decentralized situation, and it is a good solution for liquidity pools to assume the central counterparty function, which also precipitates the economic value in the DeFi ecosystem. These mechanisms with centralized overtones are precisely the parts of distributed commerce that need to be designed well and are the most innovative.

Governance tokens. Based on the analysis above, the DeFi project’s governance token is weak in capturing value, primarily by attracting users to allow the DeFi project to reach critical scale quickly.

While the analysis of distributed commerce in this paper focuses on DeFi, the core logic holds true for federated chain-based distributed commerce as well. First, although a federated chain helps to build a trust network, a trading platform must be developed based on the trust network in order to realize as much economic value as possible, and a pure information platform has little economic value. Second, users have to be attracted through economic mechanisms in order to reach critical scale as soon as possible.

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