An Algorithmic Blockchain Readiness Index †
Abstract
:1. Introduction
1.2. Summary of Contributions
- There is a lack of Blockchain knowledge in startups and/or individual investors on their decision-making with regards of which nations are blockchain-friendly to host their operations, and establish collaborations.
- Governmental authorities often fail to identify the most enabling conditions on deciding which actions need to be taken, in order to position their nation as a blockchain hub. Nations with a low score on specific indicators may use the results to initiate developments, which will exploit any areas of improvement.
- Socioeconomics. An analysis of how and to what extent local societies progress, after specific economic activities and/or operations take place [7].
- Legal management. An evaluation of the regulatory landscape of the assessed nations.
- Political economy. An examination of the relationship of blockchain production/output per nation with local government practices, and distribution of income [8].
- Managerial economics. An assessment of the challenges an organization and/or society is likely to face that affect decision making procedures [9].
2. Related Work
2.1. Overview of Current Status
2.1.1. The “Blockchain and Cryptocurrencies Regulation Index 2018”
2.1.2. Blockchain Related Indexes
2.1.3. Technology Related Indexes
3. Proposed Methodology
3.1. Indicators
3.1.1. Government Regulation Indicators
- (a) Legal Status of Cryptocurrencies
- Official recognition of cryptocurrencies: Cryptocurrencies are recognized differently among countries/regions. Most jurisdictions apply policies and rules, which are directly expressed for Bitcoin, while others refer to the treatment of cryptocurrencies in general by proposing a more general regulatory framework. Countries whose authorities have officially recognized Bitcoin or cryptocurrencies in general as financial instrument, property or commodity are favored.
- Prohibition of activities associated with cryptocurrencies: Various governmental bodies, and authorities have classified cryptocurrencies differently. In some countries, official authorities have explicitly allowed its use and trade, but others have banned or restricted it. Such bans and restrictions provide a negative signal for the index.
- Legal status remains a grey area: There are countries, which did not yet announce how cryptocurrencies or activities that relate with cryptocurrencies should be treated. The legality in this area is still undefined and questionable while these countries generally focus to the risks of cryptocurrencies (e.g., issues with financial stability). However, if no established regulation on cryptocurrencies exists, the use of them is still not illegal. Countries where Bitcoin and cryptocurrencies are regulatory placed within a grey area experience a neutral impact on the rankings.
- (b) Taxation of Cryptocurrency Income/Profits
- Transacting and/or trading with cryptocurrencies may require tax liabilities for the users. Regulatory bodies such as IRS and the European Court of Justice have issued guidance on the treatment of Bitcoin and other cryptocurrencies. Mining can also be considered in some occasions as an immediate income. Countries with established tax guidance are credited positively.
- (c) Government Intervention in Cryptocurrency activities
- Government measures to develop blockchain based strategies: Even though a limited number of nations have launched a blockchain/cryptocurrency regulatory framework, there are quite a few governmental authorities, which have created local taskforces and strategies, set to be implemented in the near future. Countries with an innovative character are credited positively in the proposed BRI.
- Government tight regulatory controls: Even in countries where cryptocurrencies are officially recognized and used by the public, tight regulations may still appear to slow down the growth of Blockchain startups. Such regulations may force exchanges to collect excess information to identify customers, impose additional trading fees, and acquire expensive licenses while in some cases the use of cryptocurrencies is even prohibited within some sectors. Our perspective is that countries with tight regulatory controls must be taken into consideration.
3.1.2. Research Indicators
- Research funding bodies: This indicator considers countries that actively seeking to become friendly for Academic Institutions, start-ups, and other initiatives that work on the fundamentals of the technology. Especially, countries that are funding such initiatives for research and development are considered positively.
- Related research output: The 100 most downloaded “Blockchain” related publications in SSRN eLibrary indicate engagement of authors and local research towards the concept. The area of residence and work of the authors is considered. This indicator is capturing data by using various keywords e.g., “Blockchain” to search for titles, abstracts and keywords in searching various academic libraries.
3.1.3. Technology Indicators
- Node Distribution: The estimation of the size of Bitcoin is calculated by finding all the reachable nodes within different regions. Even though nodes running older versions of the protocol may be hard to locate, the calculated percentage of nodes in each country is expected to be reliable. Besides Bitcoin nodes, Ethereum nodes are located and shall be included as a metric in the index, as these two decentralized networks are constantly the most widely used and developed networks since their Genesis block.
- Mining Facilities: This indicator considers statistics published by mining maps (as shown in [21]) that shows an estimate of the location of medium-to-large scale mining operations around the world. The origin of approximately half the bitcoin hash rate is captured, because some mining locations are kept secret.
- ICT Development Level: The ICT Development Index (IDI) is an index published by the United Nations International Telecommunication Union based on internationally agreed ICT indicators. Development on these areas indicates room for innovation towards Blockchain-specific activities. Iceland, Republic of Korea and Switzerland top these rankings.
- FinTech Engagement: FinTech ecosystem and infrastructure varies between countries. Demographics and the overall state of the economy are strongly related to FinTech engagement. The 2018 IFZ Global FinTech Rankings by The Institute for Financial Services Zug (IFZ) is a comprehensive research study identifying the regions with advanced FinTech ecosystems examining factors associated with driving entrepreneurship and innovation, as well as indicators related to financial technologies. As numerous entrepreneurs and start-ups are identified, Singapore and Switzerland are on the top of this list. We consider such data as an indicator to our BRI.
- Internet Access: Internet penetration rates indicate the likelihood of Blockchain adoption within regions. Internet users are defined as persons who accessed the internet in the last 12 months, from any device. According to World Bank Data (https://data.worldbank.org/), internet users are compared to the total population of a country to conclude on a certain percentage. This information may not directly be related to Blockchain adaptability but high internet penetration rate is still a positive sign, which shows room for development of the concept.
- Bitcoin ATMs launched: The number of Bitcoin ATMs serving the population. Bitcoin ATMs allow for an easy and convenient on-ramp into the Bitcoin ecosystem and installation rates indicate the rate at which a country or economy is accepting Bitcoin and how easy it is for the population to deposit and withdraw Bitcoin in exchange for cash. Data that relate to Bitcoin ATM installations are closely tracked by coinatmradar.com which our index considers.
3.1.4. Industry Indicators
- Prevalence of large Blockchain startups: The number of large Bitcoin and Blockchain companies within each country is useful as an indicator to show the prevalence and the engagement within an economy of Bitcoin and Blockchain as an industry. It also provides a welcome environment to innovate without distraction from regulation and prosecution. The top 100 most influential Blockchain companies are considered, as published by Richtopia (https://richtopia.com/).
- Venture Capital Investments: The amount of investment inflows into a country through private equity. Indicates the willingness of investors to make capital investments in risky but high growth potential Bitcoin and Blockchain companies and the acceptance of governments to allow for innovation within their borders. Data provided by sources e.g., the Crypto Fund Research (https://cryptofundresearch.com/) on investments are considered and updated regularly.
- Acceptance of Bitcoin by local companies: The number of companies within a country that accept Bitcoin in exchange for payments of goods and services indicates the acceptance of Bitcoin as a legitimate form of currency alongside local currency, and the ease of access to the general population this provides. Such data, are considered and from sources e.g., Coinmap.org.
3.1.5. User Engagement Indicators
- Community interest in Blockchain: The increase over time of the number of Web searches that include the term “Blockchain” indicates a trend within a country’s interest to the Blockchain technology.
- Community interest in Bitcoin: Similarly, as above, the increase over time of the number of Web searches that include the term “Bitcoin”. This indicates a trend within a country’s interest to Bitcoin as a concept and as a cryptocurrency.
- Bitcoin Core downloads: The total number of Bitcoin Core downloads as derived from Sourceforge.net, indicates local engagement and interest, as well as, a rough estimate of where most Bitcoin users are located. The data date range considered is from 2008-11-09 to today.
3.2. Challenges
4. Experiments and Evaluation Results
- Step 1: Normalization of data. As a pre-processing step, all indicators’ values were normalized as follows. First, all the non-already-normalized values (i.e., values coming from other indices) were normalized according to the population of the respective country. Second, all values were normalized according to a max-based scheme in order to fall into the [0, 1] interval.
- Step 2: Definition of a reference country. To the best of our knowledge, there is no analytical form (e.g., a mathematical formula) that enables the calculation of the target index taking as input the indicators’ values. For this purpose, we are introducing the concept of a “reference country” which stands as a virtual (i.e., non-existent) country exhibiting the best possible performance with respect to the considered indicators. This “ideal” country was generated as follows: for each indicator, we explored the available values of all countries and we retained the best performing one.
- Step 3. Computation of similarities. The similarities between each country and the reference/ideal country defined in Step 2 were computed. This was performed by vectoring the indicators’ values and calculating the cosine similarity between the respective vectors. Cosine similarity is computed using the following formula:
- Step 4. Ranking of countries. In this step, the underlying assumption is that a country exhibiting high BRI is expected to be similar with the reference/ideal country since the latter exhibits the best possible indicators. Under this hypothesis, the similarity scores computed in the previous step were used as BRI scores, while the countries were ranked in descending order.
5. Conclusions
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Country | BRI score |
---|---|
Singapore | 0.902 |
Canada | 0.854 |
Luxembourg | 0.839 |
Switzerland | 0.832 |
Malta | 0.830 |
USA | 0.824 |
Netherlands | 0.823 |
Slovenia | 0.816 |
Estonia | 0.816 |
Iceland | 0.810 |
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Vlachos, A.; Christodoulou, K.; Iosif, E. An Algorithmic Blockchain Readiness Index. Proceedings 2019, 28, 4. https://doi.org/10.3390/proceedings2019028004
Vlachos A, Christodoulou K, Iosif E. An Algorithmic Blockchain Readiness Index. Proceedings. 2019; 28(1):4. https://doi.org/10.3390/proceedings2019028004
Chicago/Turabian StyleVlachos, Andreas, Klitos Christodoulou, and Elias Iosif. 2019. "An Algorithmic Blockchain Readiness Index" Proceedings 28, no. 1: 4. https://doi.org/10.3390/proceedings2019028004
APA StyleVlachos, A., Christodoulou, K., & Iosif, E. (2019). An Algorithmic Blockchain Readiness Index. Proceedings, 28(1), 4. https://doi.org/10.3390/proceedings2019028004