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More than 1000 distributed ledger technology (DLT) systems raising $600 billion in investment in 2016 feature the unprecedented and disruptive potential of blockchain technology. A systematic and data-driven analysis, comparison and rigorous evaluation of the different design choices of distributed ledgers and their implications is a challenge. The rapidly evolving nature of the blockchain landscape hinders reaching a common understanding of the techno-socio-economic design space of distributed ledgers and the cryptoeconomies they support. To fill this gap, this paper makes the following contributions: (i) A conceptual architecture of DLT systems with which (ii) a taxonomy is designed and (iii) a rigorous classification of DLT systems is made using real-world data and wisdom of the crowd. (iv) A DLT design guideline is the end result of applying machine learning methodologies on the classification data. Compared to related work and as defined in earlier taxonomy theory, the proposed taxonomy is highly comprehensive, robust, explanatory and extensible. The findings of this paper can provide new insights and better understanding of the key design choices evolving the modeling complexity of DLT systems, while identifying opportunities for new research contributions and business innovation.

This contribution develops the framework of a novel, socio-ecological finance system that enables the incentivization of environmentally friendly behavior, socially responsible production, resource recycling, sharing and more. We call this system Finance 4.0—where Finance 1.0 refers to a physical coin-based system, Finance 2.0 to a fiat currency system, Finance 3.0 to blockchain finance, while Finance 4.0 stands for a multi-dimensional, real-time feedback system that combines blockchain technology with the Internet of Things. Instead of “Finance 4.0,” we will also often use the abbreviation “FIN4.”In comparison with citizen scores such as the Chinese social credit score, the FIN4 approach is different in a variety of aspects: FIN4 is not aimed at punishment and control, but rather at helping to encourage, empower and coordinate sustainable and other favorable action. It is being built for local, temporary measurements and feedback, not for global surveillance and control. It seeks to protect the privacy of people rather than to keep information about everyone and every action forever. It is not focused on the individual in the sense of profiling and targeting, but on favorable interactions and our social and environmental goals. It offers a multi-dimensional choice of options instead of trying to determine every individual’s action through behavioral manipulation and control. It has a participatory opt-in nature, where people can co-create the incentive system in such a way that they can reach their goals more successfully. With multi-dimensional incentivization, it becomes possible to advance several goals simultaneously; thereby, many more people can benefit from the interactions they engage in, as multi-dimensional value exchange increases the solution space enormously.

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