Navigating the digital foundations: A multi-criteria evaluation of layer-1 blockchains for web3 and the metaverse
Abstract
The rapidly expanding landscape of Web3 and the metaverse profoundly accentuates the escalating challenge of rigorously assessing and strategically selecting foundational Layer-1 digital blockchain platforms. Decision-makers frequently contend with the imperative of rational choice amidst a complex confluence of often conflicting technological attributes. This paper directly addresses this critical exigency by proposing a systematic framework for the comparative ranking of 10 prominent blockchain platforms. Employing a robust suite of five distinct Multi-Criteria Decision Making (MCDM) methods—TOPSIS, ARAS, RAPS, RAMS, and RATMI—a comprehensive evaluation is undertaken, scrutinizing performance across three pivotal criteria categories: performance/scalability, security, and economic/activity. The methodology incorporates a hybrid weighting strategy, assigning 50% of the total weight to the critical Hash Rate metric, with the remaining 50% distributed among other indicators using the objective Entropy Method. Based on the use of the entropy approach to determine weights based on randomness, the criteria weights were determined as follows: Speed 11%, Market Cap 6%, Time to Finality 11%, Total Transactions 10%, and Number of Nodes 12%. The empirical analysis consistently identifies Bitcoin as the top-ranking platform, securing the first position across all five MCDM methodologies. This finding validates its unparalleled robustness and security based on the defined criteria. Hyperliquid and Sui also emerged as exemplary performers, consistently exhibiting strong aggregate scores and securing the second and third positions, respectively. Conversely, other blockchains, such as BNB Chain, and Tron, demonstrated significant ranking volatility across the different evaluation methods. This observed variation is elucidated as a consequence of the extreme numerical scale of certain indicators, which introduces a high degree of sensitivity into the scoring process. Ultimately, this paper delivers a validated, data-driven empirical tool, offering stakeholders a transparent and adaptable framework for informed strategic decision-making within the rapidly evolving decentralized ecosystem. This contribution is pivotal for fostering the sustainable and resilient development of future digital infrastructures.