From throughput to value capture: scaling relationships and monetization structure in blockchain networks

OVERVIEW This working paper introduces a novel empirical framework for evaluating economic performance in blockchain networks. Rather than relying on transaction throughput or user counts as proxies for economic value—the dominant approach in both academic research and market analysis—this study distinguishes between the scale of on-chain activity and the efficiency with which that activity is monetized. The central contribution is the concept of a "monetization gap, " defined as the deviation between observed fee generation and the level predicted by a network's capital base and trading activity. By estimating a common scaling relationship across five major blockchain networks (Solana, Ethereum, BNB Chain, TRON, and Arbitrum) using four years of daily data, the analysis reveals systematic differences in how networks convert usage into economic value. KEY FINDINGS 1. TRADING ACTIVITY DOMINATES FEE GENERATIONThe analysis shows that decentralized exchange (DEX) trading volume is the primary driver of fee generation (β = 0. 329, p < 0. 001), while total value locked (TVL) —a measure of capital deployment—plays a secondary role (β = 0. 412, p < 0. 001). This challenges the conventional emphasis on TVL as the primary indicator of blockchain economic health. 2. SYSTEMATIC CROSS-NETWORK HETEROGENEITYConditional on capital and trading activity, networks exhibit large and persistent monetization gaps: • Solana: +0. 567 log points (higher-than-predicted fees) • TRON: +0. 596 log points (higher-than-predicted fees) • BNB Chain: +0. 261 log points (moderately positive) • Ethereum: −0. 228 log points (lower-than-predicted fees) • Arbitrum: −1. 222 log points (substantially lower fees) These gaps are statistically significant (p < 0. 001) and robust across multiple specifications. 3. TEMPORAL STABILITY AND REGIME ANALYSISThe monetization gaps are not artifacts of specific market conditions. When the 2022 crisis period (Terra/Luna collapse, FTX bankruptcy) is excluded, Solana's gap strengthens from +0. 567 to +0. 813—a 43% increase—indicating that the positive deviation reflects a durable structural characteristic rather than transitory market events. 4. IMPLICATIONS FOR HIGH-THROUGHPUT NETWORKSThe positive gaps for Solana and TRON are particularly notable given that both networks are designed for high throughput and low per-transaction costs—characteristics often associated with weak monetization. The findings challenge the conventional narrative that high-throughput architectures necessarily imply economically thin systems. METHODOLOGICAL CONTRIBUTIONS This paper advances blockchain valuation research in three ways: 1) EMPIRICAL FRAMEWORKThe monetization gap framework provides a reduced-form benchmark for comparing value capture efficiency across heterogeneous blockchain architectures. Unlike absolute metrics (total fees) or simple ratios (fees per transaction), the gap conditions on both capital deployment and economically meaningful activity, isolating network-specific monetization characteristics. 2) MULTI-DIMENSIONAL MEASUREMENTThe analysis demonstrates that conclusions about economic performance depend critically on how value capture is normalized. Networks that appear dominant under one metric (e. g. , Ethereum's total fees of 6. 9 billion) may exhibit weaker performance under alternative normalizations (Ethereum's negative monetization gap). 3) CROSS-NETWORK SCALING BENCHMARKBy estimating a common scaling relationship across multiple networks, the study establishes an empirical benchmark against which individual network performance can be evaluated. This approach accounts for the mechanical relationship between trading activity and fees while identifying systematic deviations that reflect differences in protocol design, fee market structure, and activity composition. DATA AND SAMPLE The analysis uses a daily panel dataset spanning April 20, 2022 to April 20, 2026, yielding 7, 278 network-day observations across five blockchain networks. All data are retrieved programmatically from the DefiLlama API to ensure consistency across networks and over time. Core variables: • Daily chain fees (proxy for value capture) • Total value locked / TVL (proxy for capital allocation) • Daily DEX volume (proxy for economically meaningful activity) The sample period includes multiple market regimes: the 2022 crisis year (Terra/Luna, FTX), the 2023 recovery, and the 2024-2026 expansion. Robustness checks confirm that results persist across these regimes. LIMITATIONS AND CAVEATS The study acknowledges several important limitations: MEV UNDERESTIMATIONOn-chain transaction fees do not capture maximal extractable value (MEV), which constitutes a substantial share of economic extraction in some networks. Fee-based measures should therefore be interpreted as lower-bound estimates of total value capture. ACTIVITY COMPOSITIONDEX volume may include wash trading and artificial activity, particularly in high-throughput environments. While the normalization approach partially mitigates this concern, measurement bias from activity composition differences cannot be fully eliminated. TEMPORAL REGIME EFFECTSSolana's positive gap may partially reflect the proliferation of memecoin launch platforms (e. g. , pump. fun) during the sample period, which generated unusually high fee-to-volume ratios. Disentangling structural monetization advantages from regime-specific effects remains an important direction for future research. L2 ARCHITECTUREFor Layer 2-centric networks (Ethereum, Arbitrum), observed L1 fees represent only a subset of total ecosystem value capture. Negative gaps may reflect architectural choices about value distribution across protocol layers rather than intrinsic monetization weakness. IMPLICATIONS FOR RESEARCHERSThe monetization gap framework provides a tractable empirical tool for evaluating economic performance in decentralized systems. The findings underscore the need to move beyond activity-based proxies and adopt multidimensional approaches that distinguish between usage intensity and value capture efficiency. FOR PRACTITIONERSInvestment and valuation analysis should not rely solely on transaction throughput or TVL metrics. Networks differ systematically in how they structure and monetize activity, and these differences have material implications for economic sustainability and competitive positioning. FOR PROTOCOL DESIGNERSThe results highlight the importance of fee market architecture in translating activity into economic value. Differences in congestion pricing, priority fee mechanisms, and transaction composition can lead to substantial variation in monetization outcomes even after controlling for capital and trading intensity. FUTURE RESEARCH DIRECTIONS This study opens several avenues for future investigation: • Incorporating MEV data to measure total value capture more comprehensively • Extending the temporal window to assess long-run stability of monetization patterns • Decomposing transaction types to isolate economically meaningful activity • Analyzing sub-period dynamics to separate structural from regime-specific effects • Developing theoretical models of how protocol design maps to monetization outcomes REPLICATION AND DATA AVAILABILITY All data used in this analysis are publicly available via the DefiLlama API. Replication code and detailed methodology are provided in the manuscript. The author welcomes feedback, questions, and suggestions for improvement. CITATION If you use this working paper in your research, please cite as: Santos, G. M. A. (2026). From Throughput to Value Capture: Scaling Relationships and Monetization Structure in Blockchain Networks. Working Paper. DOI: 10. 5281/zenodo. 19767077 CONTACT Gabrielle Mitoso Araujo SantosIndependent Researcher, MadridEmail: gabriellemitosoapplication@gmail. com Comments and suggestions are welcome. VERSION HISTORY v1. 0 (April 2026): Initial release - Full sample analysis (April 2022 - April 2026) - Robustness checks: crisis-period exclusion, lagged specifications - Cross-network comparison: 5 major blockchain networks