Web3 is heralded as a new era, premised on broadly dispersed community ownership and governance within digital platforms. Use cases such as decentralized finance (DeFi) and nonfungible tokens (NFTs) are distinguished from predecessors by their decentralized and distributed structure. Developers and users of blockchain and distributed ledger (DL) platforms tend to view decentralization and distribution as intrinsic differentiators, and as an inherent good due to their efficiency and inclusivity properties. Yet, legal, and regulatory considerations raise concerns about how obligations can be upheld with no traditional corporate or management structure. For example, regulators may see authority dispersion as a reason not to act, as with former SEC official Bill Hinman’s proposal regarding “sufficiently decentralized” networks potentially falling outside the purview of securities regulation. The reality, however, is that we lack an accepted understanding and measurement of decentralization. Without a shared definition, decentralization cannot be ascertained in practice, or measured. The same is true of “distribution”, a related property that should be distinguished from decentralization (tentatively, we would define decentralization as the dispersion of information, and distribution as the dispersion of decision-making). Market participants cannot compare examples reliably, nor can policymakers rely on decentralization or distribution as objective properties. This research therefore is the first to systematically define and measure decentralisation and distribution, benefitting many stakeholders.

There is a persistent lack of funding, especially for SMEs.
Due to this situation’s problem, the factoring market appears to address delays in paying commercial invoices: sellers bring still-to-be-paid invoices to financial organizations (banks typically) that provide an advance payment. But:

– Why not proceed to a direct peer-to-peer payment “Bypassing” actors within the value chain?. Example: Put A owes to B and B ows to C. Why not accept a transfer directly to C in a reliable way thanks to DLT?: this would be more agile and avoid expenses and potentially a socially significant DeFi development.

Why not develop a distributed Automated Market Making where trading with invoices packages is available and open to the community. When commercialized, invoices are “bypassed” automatically: this would become an approach similar to factoring by banks today but open to the community and not centralized.

Blockchain is the proper technology to develop.

Our ByPay project is to research and analyze the technical foundations for a DeFi solution for invoice compensations without needing third parties but agreements among peers: to “ByPay” invoices, not only one-to-one but also many-to-many.

We propose to develop a DLT based living lab and a sandbox so that we might experiment and tune several of the approaches chosen and benchmark them with existing funding products like factoring or with theoretical optimal top-down solutions as seeds for the future social service.
Our ByPay is an improvement from banks’ prevailing schemes or the most recent mutual/peer-to-peer credit or virtual currency approaches.

Decentralized Finance (DeFi) has seen a tremendous increase in interest in the past years with many types of protocols, such as lending protocols or automated market-makers (AMMs) that fuel decentralized exchanges gaining significant traction, with billions in USD now locked in the most popular DeFi protocols such as Compound, Aave, Balancer, Uniswap, and the like. These protocols are typically controlled using on-chain governance, where tokenholders can vote to modify different parameters of the protocol. Up till now, however, choosing these parameters has been a manual process, typically done by the core team behind the protocol. In this work, we model these protocols, with a focus on their risk parameters, and propose an automatic parameter adjustment approach, whereas optimal parameters are computed given a maximum tolerated level of risk. Our system automatically generates interpretable governance proposals to adjust these parameters (that is, governance proposals can come with data-driven justifications), on which voting can occur using the regular voting process. This in effect leads to semi-automated governance, an approach that combines the optimality of deriving parameters through automated data-driven analysis with the assurance that major decisions will not be committed without human supervision.

Decentralized Autonomous Organizations have experienced a large boost in popularity and have seen a huge increase in real live in the recent month but have so far not been thoroughly scientifically studied even though DAOs are increasingly studied from an academic perspective. DAO research is missing the basic building blocks to perform scientific research such as but not limited to predicting fraud, as well as measuring and predicting the success of DAOs. There is a limited systematic understanding of the spectrum of organizational and structural characteristics, there is no synthesis of current knowledge of DAOs with regard to organizational design, governance, reward mechanisms and launch paths, and there is no systematic understanding of the performance of DAOs. With our work we aim to first create a taxonomy of DAOs using profound scientific methods to lay the basis for the second part of our study: the prediction of success of DAOs. This is important for anyone planning to found a DAO as the startup parameters of a DAO play an important role in its overall success. Furthermore, this work is important for scientist looking to do qualitative or quantitative studies on DAOs as a basic taxonomy is needed to perform further research.

Organizations have been the bases of society over centuries. Administration by humans results in the capture of the organization by the managers or governors. Broadly known as the agency problem, this affects the proper functioning of organizations through the mismatch of incentives between agents and participants. In addition, organizations suffer from a latency problem, and a lack of transparency. Years of development of this paradigm has created a robust Risk Management practice applied to the organization. The rise of decentralized organizations rooted in blockchains and smart contracts counters the agency problem through automation of governance and administration. Autonomous organizations are not without risk. Emergent risks in the autonomous model are caused by bugs in automation and unexpected behavior of code, exploited by bad actors. These risks are amplified by centralization and by continuous, ubiquitous and fast execution. Risk management in autonomous organizations is still in its infancy. Our view is that risk in autonomous organizations can only be managed by the automation of risk monitoring, measurement and mitigation. This paper examines these ideas in multiple dimensions and proposes metrics, including the measurement of security of such systems to improve trust and governance. We look at four organizing formations: enterprise ecosystems, decentralized finance projects, metaverses, and similar decentralized autonomous organizations. The research will be sourced from primary work uniting strategy, modeling and systems implementation experiences of the authors who are industry practitioners. The research will also use secondary sources such as research papers and interviews with experts.

Blockchain technology has emerged as one of the most revolutionary and disruptive innovations of the 21st century. However, Proof-of-Work (PoW)-based cryptocurrencies continue to be highly criticised for the immense greenhouse gas emissions resulting from energy-intensive PoW mining.

While sufficient scientific evidence for emission reductions through a switch from PoW to other consensus mechanisms and other applications of blockchain beyond cryptocurrency exists, this project seeks to investigate two mutually important aspects: how to decarbonize PoW mining as well as how to use bitcoin mining as a means to make efficient use of the volatile pattern of renewable energy generation.

Although indeed energy-intensive, the fact (and extent) that PoW mining could be based on low-carbon energy sources is generally overlooked. The portability of mining rigs and their technical characteristics provide mining with a price-elastic edge. This allows low-carbon energy companies to complement their renewable energy infrastructure with the cryptocurrency mining infrastructure. An energy rig can be turned on and off swiftly with variations in the hash rate and the energy supply relative to the demand. This can allow for the effective use and monetisation of excess and stranded energy without the need for government intervention, stabilise the decade-old problem of volatile renewable energy generation and increase the profitability of renewable energy enterprises.

This project shall fill the existing gap of empirical and quantitative data on the viability of this business model by researching the feasibility of using mining in particular to increase the profitability of an actual renewable energy production facility.