Decentralized physical infrastructure networks (DePIN) tokenomics

Abstract

Decentralized Physical Infrastructure Networks (DePIN) utilize crypto-economic incentives to orchestrate the crowdsourced deployment and operation of real-world infrastructure. The design and long-term viability of their tokenomic systems are central to their potential but represent a complex and rapidly evolving field. This scoping review provides a structured synthesis of DePIN tokenomics, moving beyond descriptive mapping to organize its core design primitives into a coherent analytical model. Following the Arksey and O’Malley framework and PRISMA-ScR guidelines, this review charts and synthesizes data thematically. Key findings reveal a prevailing “DePIN Flywheel” pattern grounded in a Burn-and-Mint Equilibrium, where demand is monetized through fiat-denominated usage credits created by burning the network’s native token. This mechanism, alongside governance-calibrated issuance and collateral requirements, forms the core of DePIN’s economic architecture. However, the literature consistently highlights significant challenges: the impact of token price volatility on provider economics, ensuring robust incentive alignment, generating sufficient non-speculative demand, and navigating regulatory uncertainty. We conclude with a research agenda prioritizing empirical event studies of governance changes, quality-adjusted reward measurement, and the development of valuation frameworks appropriate for these hybrid utility-governance assets.

1 Introduction

Public blockchains, popularized by Bitcoin (2008), extend a lineage of cryptographic timestamping that enables tamper-evident, append-only records (Haber and Stornetta, 1991; Nakamoto, 2008). This paper analyzes how these primitives coordinate real-world infrastructure via tokenized incentives—systems increasingly referred to as Decentralized Physical Infrastructure Networks (DePIN). The focus is economic: how DePIN verifies useful work, prices demand and keeps participants’ incentives aligned.

DePIN is a blockchain-mediated marketplace that performs three main functions (i) verifies contributions of useful physical work from resource suppliers (e.g., radio coverage, storage, GPU cycles, geospatial imagery), (ii) monetizes demand, often through prepaid, non-transferable credits priced in USD (e.g., Helium Data Credits; Render Credits; Hivemapper Map Credits) that are created via on-chain token burns, although other models such as direct payment in the native token (e.g., Filecoin) or stablecoins (e.g., Akash) are also utilized, and (iii) calibrates new token issuance, security deposits (pledge collateral), and verification rules via on-chain voting system known as chain governance—to manage the network’s economic rules, like token rewards and security deposit requirements.

This design is significant because it separates the stable price paid by users from the volatile token rewards received by suppliers. It ensures that real-world usage directly creates economic activity for the token, primarily through the burn mechanism. Conceptually, this structure is what economists call a ‘multi-sided platform,’ as it creates a marketplace between suppliers and users. Framing DePIN this way allows us to apply established economic models (like the Rochet–Tirole framework) to analyze how to best design fees and rewards for sustainable growth (Rochet and Tirole, 2003).

The emergence of DePIN represents a logical and significant evolution in the application of blockchain technology. Initial innovations, exemplified by Bitcoin, focused on creating decentralized monetary systems. The subsequent wave, often labeled Decentralized Finance (DeFi), replicated and re-engineered traditional financial services like lending and exchange on-chain. DePIN marks a third wave, moving beyond purely digital or financial applications to orchestrate real-world, non-financial activities. By integrating with the Internet of Things (IoT) and other cyber-physical systems, DePIN leverages tokenomics not merely to secure a ledger, but as a mechanism for mobilizing and managing distributed physical capital, a challenge that requires robust economic design to succeed where centralized models face limitations.

DePIN represents a fundamental departure from the centralized paradigms that historically required immense upfront capital investment (CapEx) by large corporations or government agencies, a model that created high barriers to entry and often resulted in monopolistic market structures. In contrast, DePIN utilizes a bottom-up approach, employing native tokens to incentivize a distributed network of providers to contribute physical resources—such as wireless hotspots, data storage, or GPU compute cycles—to a shared network. The economic significance of this model is rapidly growing, with analysts targeting traditional infrastructure markets valued in trillions of dollars and the aggregate market capitalization of DePIN-related tokens surging into the tens of billions across diverse global jurisdictions (Forbes Technology Council, 2024; Messari Research, 2025; Bane and Gala, 2025). As the sector has coalesced, scholars distinguish between Physical Resource Networks (PRNs), which deliver non-fungible, location-specific services (e.g., wireless connectivity), and Digital Resource Networks (DRNs), which supply fungible digital resources (e.g., compute, storage) (Lin et al., 2025). In simple terms, a PRN provides a resource that is unique to its location, like the signal from a specific Wi-Fi hotspot. A DRN provides a resource that is interchangeable, like a gigabyte of cloud storage, which is the same regardless of which computer it’s stored on.

The operational logic and economic viability of any DePIN project are inextricably linked to its tokenomics—the design of the economic system governing the network’s native token(s) (Cong et al., 2021; Jürjens et al., 2022; Malinova and Park, 2023). Within DePIN, tokenomics acts as the core coordination mechanism, orchestrating a self-reinforcing growth loop often termed the “DePIN Flywheel”. The engine of this flywheel has two key parts: it captures value from user payments through mechanisms like token burns, and then it directs that value to fund the rewards for infrastructure providers. Effectively, DePIN tokenomics represents a complex exercise in applied economic engineering, situated at the intersection of multi-sided platform economics (Rochet and Tirole, 2003), mechanism design, and contract theory.

Analysis of prominent projects reveals four recurring design primitives that constitute the DePIN economic architecture. These are not sequential stages but rather interlocking models that address distinct design challenges: (i) Verification of Physical Work (PoPW) where the network must have a reliable, automated way (protocol) to prove that contributors are actually providing the physical service they claim to be, such as validating wireless coverage or confirming data storage, this means useful, off-chain work has been performed. Examples include Filecoin’s Proof-of-Replication (PoRep) and Proof-of-Spacetime (PoSt) for storage (Protocol Labs, 2025; Fisch et al., 2018), and Helium’s Proof-of-Coverage (PoC) for wireless network validation (Helium Foundation, 2025b). (ii) Fiat-Denominated Pricing Rails, to insulate service consumers from token price volatility, many DePIN networks employ fiat-denominated pricing rails, where services are monetized through prepaid, non-transferable credits priced in a stable currency (e.g., USD). These credits—such as Helium Data Credits (Helium Foundation, 2025a) or Render Credits (Render Network Foundation, 2024)—are typically minted by burning the native protocol token. This mechanism not only shields users from fluctuations in token value but also creates a direct link between network usage and token value accrual. (iii) Governance-Calibrated Value Accrual: A Burn-and-Mint Equilibrium (BME) is often used, where tokens are burned to create usage credits and new tokens are minted to reward providers (Lin et al., 2023). This mechanism ties supply-side issuance to realized demand and allows on-chain governance to adjust economic parameters over time to maintain sustainability. (iv) To ensure service reliability and deter malicious behavior, providers are typically required to stake the network’s native token as collateral. This staked amount functions as a security deposit that can be partially or fully confiscated (“slashed”) in cases of poor performance, dishonest reporting, or other forms of misconduct, thereby creating a strong economic incentive for compliance and high-quality service provision.

The central challenge for DePIN lies in balancing these complex objectives in a dynamic environment. This economic balancing act is compounded by the novel challenges of decentralized governance via Decentralized Autonomous Organizations (DAOs) and a nascent, often ambiguous global regulatory landscape. High initial inflation required to bootstrap supply can depress long-term token value if not met with sufficient demand-linked value capture, while the inherent volatility of crypto markets profoundly impacts provider Return on Investment (ROI) and network stability (Chiu M. T. et al., 2024; Caprolu et al., 2025). Despite growing industry activity, academic literature remains sparse and methodologically diverse, lacking a systematic synthesis of these economic models. This fragmentation justifies a scoping review, a methodology explicitly designed to map key concepts, sources, and evidence in an emerging research area (Arksey and O’Malley, 2005; Peters et al., 2020).

This review makes several contributions to the nascent literature. First, to the best of our knowledge, the work provides one of the first systematic syntheses in DePIN tokenomics, organizing a fragmented body of knowledge into a coherent overview grounded in multi-sided platform theory. Second, it identifies and defines the core design primitives—such as Proof-of-Physical-Work (PoPW), fiat-denominated pricing rails, and Burn-and-Mint Equilibria—that constitute the sector’s dominant economic architecture. Third, it consolidates the key economic, governance, and regulatory challenges highlighted across academic and industry sources, assessing the risks to long-term sustainability. Finally, by delineating specific, actionable research gaps, it provides a clear agenda for future scholarly inquiry in finance and economics, emphasizing the need for rigorous empirical validation of these novel incentive systems.

The remainder of this paper is structured as follows: Section 2 details the scoping review methodology. Section 3 presents the results, including a synthesis of the core concepts, tokenomic models, and challenges identified. Section 4 discusses the key insights and implications and concludes by outlining the identified research gaps and future directions. Section 5 concludes the paper.

2 Methodology

2.1 Methodological framework

This study employs a scoping review methodology, appropriate for mapping concepts and evidence in emerging fields where comprehensive causal synthesis is premature (Petticrew and Roberts, 2006). The review adheres to the five-stage framework developed by Arksey and O’Malley (2005) and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist (Tricco et al., 2018). Methodological rigor was enhanced using the recommendations of Levac et al. (2010) and the iterative Population-Concept-Context (PCC) framework to define eligibility, as advised by Peters et al. (2020).

2.2 Search strategy

A comprehensive literature search was executed on 1 May 2025in two sources: Scopus and Google Scholar. Boolean operators and wildcards were used. The DePIN query included “Decentralized Physical Infrastructure Network*,” DePIN, “Token Incentivized Physical Infrastructure Network*,” TIPIN, “Proof of Physical Work,” PoPW, and MachineFi. After limiting to relevant subject areas and English, Scopus returned 42 records (Supplementary Appendix B). Google Scholar queries (Supplementary Appendix B) returned 19 records. Backward and forward citation chasing supplemented database searching. Backward and forward citation chasing supplemented database searching. Furthermore, to capture essential grey literature, 17 records were identified from targeted searches of industry websites and project repositories (see Figure 1).

2.3 Study selection and eligibility

The study selection was conducted in a two-stage process by the author. First, following deduplication of all retrieved records, titles and abstracts were screened against the predefined eligibility criteria. Second, the full texts of all potentially relevant records from the initial stage were retrieved and evaluated in detail. This process yielded a final sample of 46 sources. Recognizing that a substantial portion of the discourse in this nascent field occurs outside traditional academic publishing, the final sample deliberately included 24 academic articles (conferences, pre-prints, and articles) and 22 grey-literature sources (e.g., news articles, blog posts, white papers, reports), following Joanna Briggs Institute guidance on scoping-review evidence inclusion.

Studies were required to meet eligibility criteria defined by the PCC framework and publication type. The Population of interest was (DePIN), including specific projects, their protocols, or the sector as a whole. The Concept centered on tokenomics and crypto-economic phenomena within DePIN, such as economic models, token design, incentive mechanisms, and risk analyses. The Context was restricted to global literature published in English between 1 January 2021, and 1 May 2025. Included sources were peer-reviewed journal articles, conference proceedings, and substantive working papers or preprints. Conversely, studies were excluded if they were purely technical, focused on general blockchain or DeFi without a DePIN application, were brief market commentaries or promotional materials, were not in English, or fell outside the specified date range.

2.4 Data charting and synthesis

A standardized data-charting form was developed to extract relevant information from all included studies. Key data points extracted included: bibliographic details; the DePIN sector(s) and specific project(s) analyzed; described tokenomics frameworks and incentive mechanisms; token utilities, sustainability features, and governance arrangements; identified economic and financial risks; any quantitative metrics reported; and stated research gaps or directions for future research. The author completed the extraction for all studies no formal pilot of the charting form was conducted. Instead, the template was iteratively refined during early extraction, and all corrections were retro-applied to previously charted records to ensure consistency.

The extracted data were collated and summarized using a narrative approach (Popay et al., 2006) supplemented by descriptive statistics on study characteristics. A thematic analysis was then conducted (Thomas and Harden, 2008), which involved systematically coding the charted information, grouping codes into descriptive themes, and developing higher-order analytical themes that collectively map the DePIN tokenomics landscape. Consistent with Joanna Briggs Institute (JBI) guidance for scoping reviews, we did not undertake a formal risk-of-bias assessment; instead, we narratively reflected on methodological transparency and the depth of economic analysis to contextualize findings. Industry-funded and project-authored documents were flagged during charting; claims drawn from such sources were treated as contextual and triangulated with peer-reviewed evidence where possible and were not used to make inferential claims about effect sizes or performance.

2.5 Methodological limitations

This review is subject to several limitations. First, the restriction to English-language publications may have introduced a language bias, resulting in the exclusion of relevant research published in other languages. Second, the analysis is confined to publicly available data, meaning proprietary or unpublished performance metrics from DePIN projects were not captured. Third, the necessary inclusion of grey literature—while enhancing coverage in a nascent field—introduces risks of bias associated with non-peer-reviewed sources such as industry reports; we mitigated this by flagging funding and authorship, triangulating with peer-reviewed sources, and using such materials primarily for background and context. Finally, our use of Google Scholar was intentionally supplementary and limited to the top-ranked 100 results per query to enhance reproducibility; although this cap may miss lower-ranked items, evidence shows that Google Scholar is unsuitable as a sole source for systematic searching and is best paired with curated databases, which we did. Finally, the DePIN landscape is vast, with hundreds of active projects. The objective of this scoping review is to map the core concepts and dominant economic architectures documented in the accessible academic and substantive grey literature, not to conduct a comprehensive, quantitative comparison of all extant projects, which represents a distinct methodological undertaking beyond the scope of this review.

2.6 Characteristics of the included evidence base

The included literature (N = 46) displayed characteristics typical of an emerging field. A significant portion consisted of academic conference papers (n = 15), reflecting the rapid dissemination of ideas, while peer-reviewed journal articles (n = 5) and working papers/preprints (n = 6) provided more developed contributions. Grey literature (n = 22) offered timely industry perspectives. The publication dates were heavily skewed towards recent years (2023-early 2025), indicating accelerating research interest. While many sources adopted a global perspective, case studies frequently centered on prominent North American or European projects in the Wireless, Storage, and Compute sectors. The predominant methodological approaches in academic sources were conceptual analysis, descriptive case studies, and taxonomy development. Rigorous, quantitative empirical studies focusing specifically on the financial or economic outcomes of tokenomics designs were notably unavailable in the selected literature.

3 Results

The thematic analysis of the 46 included sources revealed four primary themes that characterize the DePIN tokenomics landscape: (1) the core conceptual frameworks used to define the sector, (2) a taxonomy of tokenomic models and incentive structures, (3) key mechanisms for achieving economic sustainability, and (4) the primary challenges and risks identified in the literature. These themes are detailed below.

3.1 Theme 1: the “DePIN flywheel” as a prevailing incentive framework in leading deployments

The DePIN flywheel emerges as a widely used, usage-driven feedback loop for bootstrapping and sustaining physical-infrastructure networks (Messari Research, 2025). Think of it like a heavy merry-go-round which requires a significant effort to start, but once it is spinning, its own momentum helps it continue with minimal force, the DePIN model applies this concept to network growth. This framework highlights how token incentives are designed to drive network growth and sustainability in DePINs. In what follows, the core mechanics, verification requirements, and recurrent challenges are synthesized.

The operational logic of the DePIN Flywheel is driven by a complex interdependency between three primary actors, whose roles, incentives, and value flows are systematically decomposed in the following table (see Table 1).

Actor category	Specific roles	Core function/Action	Value flow/Token mechanism	Economic outcome/Risk
I. Resource supplier (provider)	Miner, hotspot owner, data uploader, node operator	Deploys physical infrastructure. Performs useful physical work. Submits cryptographic proof-of-physical-work (PoPW). Stakes native token (T) as collateral	Receives newly issued tokens (rewards). Faces slashing (loss of S) for non-compliance or poor service	Faces high volatility risk due to tokenized rewards versus fiat costs (ROI uncertainty)
II. Demand-side user (consumer)	Enterprise client, developer, IoT device user, data buyer	Consumes the physical service (e.g., bandwidth, storage, compute). Pays the network for usage	Pays via fiat-denominated, non-transferable usage credits (CUSD). Triggers the token burn mechanism (T→CUSD)	Requires stable, predictable service pricing; drives non-speculative demand
III. Governance body (DAO)	Token holders, validators, core team/Foundation	Votes on economic parameters (e.g., emission rate, fee splits, slashing requirements). Manages protocol upgrades and treasury allocation	Calibrates new token issuance (I Our offer on Sallar Marketplace What is DePIN shop You have not selected any currency to display Latest posts What is DePIN? Read More » Niza Labs and PinGo Advance AI and DePIN Innovation on TON Blockchain Read More » SEC Staff Issues No-Action Letter for DePIN Token Distributions Read More » QWNR Launches Unified DePIN Orchestration Layer: Restructuring Cross-Network Resource Liquidity and Infrastructure Architecture Read More » Sui DePIN price today, SUIDEPIN to USD live price, marketcap and chart Read More »