Token Design for aligning stakeholder interest with collective goal

Tokens are an integral part of any web 3.0 ecosystem, representing utility in various forms while also giving users an opportunity to grow within the ecosystem, making a stark difference between web 2.0 and web 3.0 businesses. Although basic token functionality is well understood, the real added value comes from a well-designed token’s power to incentivise users to behave in ways that are beneficial to the entire ecosystem and generate positive externalities.

This article covers some of the key points about Mechanism Design for purpose-driven tokenomics and some considerations for success in a world that is messy and irrational.

GAME THEORY — WHERE IT ALL BEGAN

To explore mechanism design, we need to first take a step back and understand the age old concept of Game Theory. Game theory explores how rational people make strategic decisions in different situations. The theory mathematically models the human behavioural paths within an interactive and dynamic environment. Put in another way, it is the science of strategy that maps out the best plan of action for agents to achieve a desired outcome or result.

One interesting concept to explore in Game Theory is the “Tragedy of the Commons”. When goods are permissionless, i.e. public, but they are rivalrous, ie, scarce, profit-maximising behaviour leads to something called Tragedy of the Commons as explained in the figure below.

In this scenario each agent has 2 options — use 100L (selfish) or use 50L (Collaborative). The more water a person uses, the higher is their “Happiness” (consider 3 levels of happiness — low and high.)

• If both consume 100L/day — short term profits are maximised, but the water runs out fast — resulting in ‘ low happiness’ for both
• If both consume 50L/day — short term profits are limited, but the water resource doesn’t deplete — resulting in ‘high happiness’ for both
• If 1 person consumes 100L/day and the other consumes 50L/day — the water runs out, but the person ‘over consuming’ has a “high happiness” and the person “under consuming” has a “low happiness”

Game Theory assumes that players will behave in a profit maximisation manner and players expect the other player also to behave in a profit maximisation manner, leading to both choosing the dominant strategy to consume 100L a day and both players receiving a payoff of “low happiness”. You can explore more examples of game theory here

The token economy also faces these issues, and the root of the problem is that maximisation of individual profits where users only focus on their own self-interests, behaving contrary to the common good by depleting a shared resource has negative ripple effects on the entire ecosystem. A well defined token economy should focus on aligning incentives with a common and collective goal.

MECHANISM DESIGN — A.K.A. REVERSE GAME THEORY

Unlike game theory, which focuses on how participants would behave given a set of rules, mechanism design sets desirable behavioural goals first and then focuses on establishing the game rules to accomplish those goals — hence, ‘Reverse Game Theory”. Mechanism design focuses on programming human behaviour through carefully designed incentives.

The underlying principle of mechanism design is that all humans work towards an objective. The path to achieving this objective is subdivided into multiple smaller steps or subgoals. Mechanisms must help humans achieve either their ultimate objective or a subgoal (such as earning money) which helps them achieve their final target. In most cases, money is a subgoal that motivates people to keep working and moving towards their goal. Hence a good mechanism would lead people to behave in a way that will generate money for themselves (personal incentives) while also creating a useful by-product (final objective).

Creating a mechanism is essentially an optimisation problem, where we maximise the objective function under certain constraints. Here are three simplified steps to design a game mechanism as described by Sam Williams from Arweave -

• Choose a goal — the main aim of the network.
  Eg: Maximise network security to avoid double spends
• Choose a reward mechanism — how you’re going to reward players in-game with an output that pushes them towards a goal (or a subgoal).
  Eg: Tokens are distributed relative to the security contribution of each miner
• Choose a function to match the reward mechanism — a function to apportion the rewards to players in a way that keeps players satisfied, while also achieving the goal of the network.
  Eg: proof of work and block production, acceptance, and fork avoidance.

In case you were wondering, the example given above is that of Bitcoin. You can watch the complete video to learn more about design mechanisms here.

THE RATIONALITY ASSUMPTION

The field of mechanism design in the context of crypto economics is still relatively new — so it still isn’t as all-encompassing as we might hope for it to be. Current crypto economics assumes rationality — that humans exhibit rational and selfish behaviour, consistent with their preferences and beliefs. But in reality human behaviour is much more complex, and we need to consider a whole suite of other factors.

This is captured well by Shermin Voshmigir in her article —

“Psychological, emotional, emotional, cultural, cognitive and social factors are also taken into account with the conclusion that people make over 90% of their decisions based on mental shortcuts or “rules of thumb.” Especially under pressure and in situations of high uncertainty humans tend to rely on anecdotal evidence and stereotypes to help them understand and respond to events more quickly. It is assumed that the rationality of individuals and institutions is “bounded” by time and cognitive limitations, and that good enough solutions are preferred over perfect solutions.”.

“The design of purpose-driven tokens uses game theory to model human reasoning into an automated steering mechanism formalised by the protocol or smart contract and should account for the behavioural complexities.”

To create more robust mechanisms, it is necessary to enlarge the current assumptions we use by borrowing concepts from behavioural economics, behavioural finance, behavioural game theory, and cognitive psychology.

A PEEK INTO AN IRRATIONAL WORLD — CONCEPTS FOR BETTER MECHANISMS

Prospect Theory or the Loss Aversion Theory

Prospect theory states that (most) people are inherently loss averse. It has been found that people value losses and gains differently, and a loss has a greater emotional impact on humans. Loss aversion also finds that the probability of a gain is perceived to be greater than that of a loss.

Endowment Effect or Divestiture Aversion

The endowment effect is an irrational bias that causes individuals to value an owned object higher than the market value. This is usually caused by 3 main reasons -

• Ownership — I own it, so it’s more valuable, duh!
• Loss Aversion — the perceived value of the good is greater than the current market value
• Emotional Significance — my favourite aunt gave me this!

The endowment effect can be used to promote an idea or sell products more easily by providing a sense of psychological ownership.

Cognitive Bias

Cognitive bias is a systematic error in thinking that affects decisions and judgment. This bias could be related to -

Memory — this is to do with how we remember things.

• The first information we receive is over-weighted — known as anchoring bias
• A greater value is placed on information that can be recalled quickly — known as the availability heuristic
• Post-event information interferes with event memory — known as misinformation

Attention — Humans are sometimes selectively attentive and overlook info that does not conform to existing beliefs which leads to a bias in opinion and judgment

Bounded Rationality

Bounded rationality is the theory that consumers are limited in their rational decision-making ability, driven by three main factors — cognitive ability, time constraint, and imperfect information. The theory states that the human decision-making process is an attempt to satisfice, rather than optimise, which results in decisions that are good enough, rather than the best possible decision. Bounded rationality addresses some of the key flaws in the original rational choice theory by highlighting the limitations of humans’ ability to make optimal decisions.

NUDGING

Nudging is the targeted small suggestions or formulations and positive reinforcements with the aim to influence consumer behaviour. Nudging entails designing an intervention meant to affect behaviour without changing the monetary incentives and without restricting anyone’s choice. Richard Thaler and Cass Sunstein (Nudge — Improving Decisions about Health, Wealth and Happiness (2008)) state that human decision making pattern is bounded by the cognitive boundaries, biases, and habits and such a behaviour can be influenced or “nudged” towards a better or more preferable direction by integrating insights about these boundaries, biases, and habits into the decision making process. More details and examples of nudging case studies here

Choice Architecture

Choice architecture is the design of different ways choices can be presented to decision-makers and the impact of that presentation on decision-making. Choice architecture capitalises on bounded rationality and instinctive ‘fast’ thinking by nudging customers into certain choices.

CONCLUSION

As explained in the article, human decision making combines both rational and irrational arguments to derive an outcome. While Token economics has come a long way in the past couple of years, there is still plenty of scope for research to answer some key questions that persist. Going forward Token ecosystems should take into account the role of behavioural economics to reliably model and forecast complex behaviours in the crypto context. It is paramount to develop a deeper understanding of how to apply macroeconomic policies to create more stable token ecosystems.

If you are in the process of building a Token based ecosystem and want to launch your token, here are some questions to help you get started:

• Economy Objectives — What is this ecosystem trying to achieve?
• Stakeholder Mapping — Who is going to be part of this ecosystem?
• Market Design — How do you get people to enter into this ecosystem?
• Mechanism Design — How are the token users compelled to behave?
• Monetary Policies — How are the tokens supply and distribution managed?
• Governance — Who takes the decisions in this ecosystem?

If you have any interesting points our ideas about Token Design and Behavioural Economics in the crypto context then don't hesitate to send us a message.

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