Distributed Ledger Technology (DLT) has evolved beyond cryptocurrency applications and is now being explored in diverse financial scenarios, from payment systems to market infrastructure. This article examines the economic characteristics of DLT as an innovation, aiming to provide a practical understanding of its adoption challenges and opportunities while supporting strategic decision-making in both enterprise and policy contexts.
DLT introduces new technical and operational features that could reshape the organizational, operational, and regulatory structures of the financial system. As a result, central banks worldwide are actively monitoring, researching, and experimenting with this technology.
The real impact of DLT on finance will ultimately depend on the depth and breadth of its adoption—a process influenced not only by technological supply but also by fundamental economic principles.
The Economic Lens on DLT
Modern economic systems are evolving toward decentralized, peer-to-peer, and networked structures. DLT draws from cryptography, secure communication, trusted computing, peer-to-peer networking, and game theory to create a distributed, tamper-resistant, and adaptable computational architecture. It aims to meet the demands of a digital economy.
As a still-emerging innovation, DLT can be viewed as a combinatorial innovation—one that combines existing technologies in novel ways. Analyzing its application and diffusion through the lens of innovation economics offers valuable insights.
Information technology industries often exhibit network effects (or demand-side economies of scale), where the value of a product or service increases as more people use it. This has been observed in telecommunications, internet search, and digital payments.
Network effects are crucial for building and sustaining competitive advantage. They also pose unique challenges for public policy. In the context of DLT, discussions about network effects are common but often misunderstood, making clarity essential.
Proponents sometimes describe DLT as a "Internet of Value," suggesting it could enable open organizational forms much like the internet did for information. While it’s true that innovations in record-keeping can influence corporate governance and financial reporting, the broader implications for market structure deserve attention.
In financial markets, for example, DLT could streamline post-trade settlement processes, reduce reconciliation costs, and alter collateral requirements—potentially disrupting established players and business models.
According to economist Joseph Schumpeter, some innovations represent changes in techno-economic paradigms. These shifts involve clusters of innovations that collectively raise productivity across industries, spark new investment cycles, and redefine economic organization—as seen with the steam engine and electricity.
Some scholars suggest that DLT could enable new institutional forms between markets and firms, particularly through smart contracts that allow more flexible economic agreements.
Whether DLT constitutes a paradigm shift remains to be seen. Still, using this theoretical framework can generate useful hypotheses and guide industry and regulatory practices.
Innovation Diffusion and the "Darwinian Sea"
In recent years, the global financial industry has launched numerous DLT projects in areas such as cross-border payments, securities settlement, and trade finance.
These projects typically progress through stages like Proof-of-Technology (PoT) and Proof-of-Concept (PoC). Only after demonstrating incremental benefits do they move toward pilot testing in live environments.
Innovation economics breaks down technological innovation into several phases: Research, Development, Demonstration, and Deployment (together known as R&3D). The final stage is diffusion.
Each phase involves distinct risks. Research shows that two transition points are especially critical: the move from research to development, and from demonstration to deployment.
The first jump—from research to development—involves turning theoretical concepts into working prototypes. Although DLT was initially designed for decentralized payments, it may not naturally fit all financial use cases.
Development success depends on many factors beyond pure technology, including scalability, privacy mechanisms, consensus protocols, cost control, and clear demand alignment.
On the positive side, DLT is evolving rapidly. Innovation cycles are shortening over time, and modern programming languages, tools, and development environments have made combinatorial innovation faster and less costly than in the era of physical inventions.
Open-source communities and knowledge-sharing platforms also facilitate learning and reduce the cost of skill development—key advantages for DLT innovation.
However, the demonstration and deployment phases often entail greater risks. After a prototype is built, it must undergo real-world testing at or near full scale.
The demonstration phase validates the technology in realistic settings, while deployment involves adoption by early users followed by broader market penetration. Economists refer to this challenging transition as the "Darwinian Sea," where hidden technological and market risks can sink promising innovations.
Projects may fail due to high costs, lack of funding, or inability to operate reliably at scale. Even after successful demonstration, innovations can struggle in competitive markets if they are too costly or not sufficiently robust.
Additionally, innovators must navigate institutional inertia and resistance from incumbents. For instance, applying DLT in financial market infrastructure could redistribute profits and influence among participants, triggering pushback.
Network Effects in DLT
Network effects arise in industries where the value of a product or service grows as more users participate. This concept originated in network industries like utilities and telecommunications.
Economists distinguish between direct and indirect network effects. Direct network effects occur when a product becomes more valuable as its user base expands—as with telephones or social messaging apps.
Indirect network effects appear when increased usage of one product boosts the value of a complementary product. A classic example is an operating system and its applications.
In platform business models (e.g., e-commerce or ride-sharing), we see two-sided network effects, where growth in one user group attracts growth in another.
It’s important to clarify common misconceptions about network effects in DLT.
First, the network effects associated with a cryptocurrency token are not the same as those of the underlying DLT. While monetary and payment systems can exhibit network effects, most crypto-tokens are not designed as general-purpose currencies.
Tokens often function as access mechanisms or incentives within a public ledger—not as standalone networks.
Moreover, whether a ledger is public or permissioned does not inherently determine its network effects. What matters is the system’s functional design and positioning.
For example, Ethereum aims to be a “world computer” or an operating system for smart contracts. If successful, it could exhibit indirect network effects similar to those of software platforms.
However, the value of DLT nodes often stems from supply-side collaboration and economies of scale—not demand-side network effects.
Many hope DLT will deliver hyper-growth and user lock-in via network effects. But our analysis suggests that significant network effects are more likely to emerge at the application layer than the protocol layer.
This explains why public blockchain projects place such emphasis on decentralized application (DApp) ecosystems. Innovations like cross-chain interoperability could further enable network effects by linking different ledgers.
DLT as a Potential Paradigm Shift
If a technological innovation affects only a narrow range of industries, its diffusion may be relatively straightforward. However, innovations that represent a new techno-economic paradigm face greater adoption hurdles.
History offers many examples. Electric motors, for instance, were initially used as standalone showpieces before engineers integrated them into redes production workflows—eventually revolutionizing manufacturing productivity.
Similarly, many current DLT projects test isolated functionalities rather than offering end-to-end solutions. This approach can resemble “a solution looking for a problem.”
The Bank of Canada’s Jasper project—a DLT-based trial for a large-value payment system using a central bank digital currency—found that distributed systems could not yet match the efficiency of centralized ones. However, the experiment also highlighted DLT’s potential to improve efficiency if integrated more broadly across financial infrastructures.
Because of this promise, DLT has attracted significant attention—and speculative investment. This mismatch between expectations and realistic timelines often leads to a boom-and-bust cycle, similar to the Gartner Hype Curve.
As innovation scholar Carlota Perez described in Technological Revolutions and Financial Capital, new technologies often trigger financial bubbles driven by over-enthusiastic investment before eventually maturing into productive use.
Implications for Industry and Policy
Innovation economics and technological history both indicate that the diffusion of DLT will be a complex, dynamic process filled with challenges and uncertainties. Industry participants should prepare for a long adoption journey.
The "Darwinian Sea" between development and deployment justifies early public-sector involvement—especially for infrastructure-level innovations that generate positive externalities private actors may not fully capture.
Public support through demonstration projects and policy coordination can help overcome low-level Nash equilibria and achieve Pareto improvements.
Standard-setting is another area where public intervention can be valuable. Since network effects and competitive dynamics may prevent industry players from coalescing around common standards, public agencies can facilitate consensus-building.
Well-timed standardization can accelerate DLT adoption and enhance network effects. However, policymakers must avoid acting too early—which could distort markets and stifle innovation.
It is worth emphasizing that this analysis focuses on the economic aspects of DLT as a technological innovation. However, given its potential as a paradigm-shifting technology, DLT could profoundly affect business models and regulatory frameworks.
Financial regulators, in particular, must balance innovation encouragement with risk mitigation—especially as DLT is increasingly applied to core processes in the financial industry.
👉 Explore advanced insights on distributed systems
Frequently Asked Questions
What is Distributed Ledger Technology (DLT)?
DLT is a digital system that records transactions across multiple computers in a way that is secure, transparent, and decentralized. It underpins cryptocurrencies like Bitcoin but has broader applications in finance, supply chain, and identity management.
How does DLT differ from blockchain?
Blockchain is a type of DLT that structures data into blocks linked in a chain. While all blockchains are DLTs, not all DLTs use a blockchain structure—some employ different architectures like Directed Acyclic Graphs (DAGs).
Can DLT improve financial infrastructure?
Yes. DLT has the potential to reduce settlement times, lower counterparty risks, and increase transparency in financial transactions. Several central banks and financial institutions are experimenting with DLT for payments, clearing, and securities settlement.
What are the main barriers to DLT adoption?
Key challenges include scalability limitations, regulatory uncertainty, interoperability issues, and the complexity of integrating with legacy systems. Additionally, achieving consensus among stakeholders on standards and governance is difficult.
Are there risks associated with DLT?
Yes. Risks include technical vulnerabilities, privacy concerns, energy consumption (for some consensus mechanisms), and potential misuse for illicit activities. Proper design and regulation are essential to mitigate these risks.
How are central banks involved with DLT?
Many central banks are researching or piloting Central Bank Digital Currencies (CBDCs) using DLT. They are also monitoring private stablecoins and assessing the implications of DLT for monetary policy and financial stability.