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Shiba Inu Unleashes “Transformative” Token Burn Model to Boost SHIB Value

Pancakeswap burn

The Shiba Inu team has introduced what it describes as a “transformative” token-burning mechanism to boost its ecosystem. This process is designed to reduce the SHIB token supply, potentially increasing the token’s value. 

As confirmed in the latest update, the new burning mechanics are tied to Shiba Inu’s layer-2 network, Shibarium. As more users transact on Shibarium, the Shiba Inu team will follow through on its commitment to collecting and burning a portion of network fees.

Shibarium’s roadmap requires that the team convert 70% of BONE tokens that users pay as network fees to SHIB, which is then removed from circulation. The other 30% of fees would be used for network maintenance efforts.

Shiba Inu Unpacks Stages of the Burn Mechanism

The burning mechanism revealed in Monday’s announcement involves two phases: manual phase and automated transition. The official Shiba Inu deployer wallet will manually manage the initial stage, allowing close monitoring and adjustments to ensure alignment with the network’s health and sustainability. Additionally, the team reckons that some necessary changes to the network will be coordinated with other validators and node operators.

Notably, the Shiba Inu team has already executed the first of its manual burn transactions. On Tuesday, the team burned 8.24 billion SHIB tokens (valued at around $71,000). Shiba Inu’s lead marketing strategist, Lucie, confirmed the burn event.

Meanwhile, Shiba Inu’s burn mechanism is set to evolve into an automated phase starting in January next year. This process will operate based on predetermined rules, making it more efficient and transparent. The Shiba Inu team disclosed plans for several upgrades to enhance the network’s efficiency ahead of the automated burn implementation.

At the time of writing, the price of SHIB has seen mild growth since the announcement of the new burn program. The token trades at $0.00000928, a 4% increase on the day, CoinStats data shows.