List of topics
Defined topics | Keywords within the topics | Marginal topic distribution |
---|---|---|
The changing role of accountants | Organisation, accountant, literature, practise, role, governance, competency, decision, innovation, area, performance, knowledge, idea, profession, perspective, impact, industry, opportunity, theory, factor | 0.24 |
The new challenges for auditors | Audit, auditor, auditing, contract, procedure, client, assurance, statement, evidence, analytic, privacy, ecosystem, tool, profession, customer, volume, environment, adoption, firm, practice | 0.16 |
Opportunities and challenges of blockchain technology application | Block, ledger, peer, database, record, contract, design, node, entry, chain, access, function, solution, participant, problem, proof, hash, key, organisation, consensus | 0.11 |
Regulation of cryptoassets | Token, security, issuer, investor, ico, law, directive, regulation, project, right, capital, voucher, sale, regulator, issuance, holder, protection, consumer, rule, equity | 0.11 |
Cryptocurrencies and cryptoassets | Asset, currency, bitcoin, exchange, price, cryptocurrency, carbon, investment, coin, purpose, regulation, entity, trading, amount, money, statement, money_laundering, payment, income, sale | 0.09 |
Trading and uncertainty associated with blockchain and cryptocurrency | Volume, trading, investor, disclosure, return, firm, day, percent, measure, policy_uncertainty, news, readability, product, cryptocurrency, table, car, authority_news, evidence, word, stock | 0.08 |
FinTech in banking | Payment, bank, money, account, currency, cash, consumer, claim, banking, government, btc, choice, infrastructure, customer, state, sector, platform, intermediary, transfer, member | 0.065 |
New skills for teams | Analyst, team, forecast, member, diversity, effect, variable, accuracy, firm, experience, performance, sample, copy, size, column, table, panel, filing, industry, teamwork | 0.06 |
Ecosystems and supply chain | Supplier, supply_chain, buyer, traceability, access, certification, product, deforestation, food, premium, production, rent, contract, effort, sustainability, chain, standard, problem, decision, strategy | 0.045 |
Blockchain and taxation | Tax, taxation, wealth, vat, detection, topic, sale, table, invoice, taxis, rule, judgement, jurisdiction, revenue, good, entity, taxpayer, crime, treatment, authority | 0.04 |
Top 10 articles by number of citations
Authors, year | Title | Cites | Source | LDA topic the paper reflects |
---|---|---|---|---|
Toward an ontology-driven blockchain design for supply-chain provenance | 422 | Opportunities and challenges of blockchain technology application | ||
Blockchain and its coming impact on financial services | 302 | Opportunities and challenges of blockchain technology application | ||
Configuring blockchain architectures for transaction information in blockchain consortiums: The case of accounting and supply chain systems | 132 | Opportunities and challenges of blockchain technology application | ||
(2016) | Research ideas for artificial intelligence in auditing: The formalisation of audit and workforce supplementation | 131 | The new challenges for auditors | |
(2017) | Blockchain: Emergent industry adoption and implications for accounting | 112 | Opportunities and challenges of blockchain technology application | |
Can blockchains serve an accounting purpose? | 93 | Opportunities and challenges of blockchain technology application | ||
(2018) | Harmonising non-financial reporting regulation in Europe | 91 | The new challenges for auditors | |
The double spending problem and cryptocurrencies | 72 | SSRN | Opportunities and challenges of blockchain technology application | |
Designing confidentiality-preserving Blockchain-based transaction processing systems | 71 | Opportunities and challenges of blockchain technology application | ||
Disruption of financial intermediation by FinTech: a Review on crowdfunding and blockchain | 71 | Regulation of cryptoassets |
The top 10 articles by CPY
Authors, year | Title | CPY | Source | LDA topic the paper reflects |
---|---|---|---|---|
Toward an ontology-driven blockchain design for supply-chain provenance | 140.67 | Opportunities and challenges of blockchain technology application | ||
Blockchain and its coming impact on financial services | 60.4 | Opportunities and challenges of blockchain technology application | ||
Configuring blockchain architectures for transaction information in blockchain consortiums: The case of accounting and supply chain systems | 33 | Opportunities and challenges of blockchain technology application | ||
The role of internet-related technologies in shaping the work of accountants: New directions for accounting research | 32.5 | The changing role of accountants | ||
(2018) | Harmonising non-financial reporting regulation in Europe | 30.33 | The new challenges for auditors | |
(2017) | Blockchain: Emergent industry adoption and implications for accounting | 28 | Opportunities and challenges of blockchain technology application | |
Accounting and Auditing at the Time of Blockchain Technology: A research Agenda | 28 | The new challenges for auditors | ||
Implementation of blockchain technology in accounting sphere | 26.5 | The new challenges for auditors | ||
(2016) | Research ideas for artificial intelligence in auditing: The formalisation of audit and workforce supplementation | 26.2 | The new challenges for auditors | |
Auditing with smart contracts | 24 | The new challenges for auditors |
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Open Access
Peer-reviewed
Research Article
Roles Conceptualization, Data curation, Investigation, Methodology
Affiliation Groupe ALTEN, France
Contributed equally to this work with: Francesco Fontana, Elisa Ughetto
Roles Methodology, Writing – original draft, Writing – review & editing
* E-mail: [email protected]
Affiliation Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, Italy
Roles Conceptualization, Investigation, Methodology, Project administration, Supervision, Validation, Writing – original draft, Writing – review & editing
Affiliation Politecnico di Torino & Bureau of Entrepreneurial Finance, Corso Duca degli Abruzzi 24, Turin, Italy
In this paper, we use a Delphi approach to investigate whether, and to what extent, blockchain-based applications might affect firms’ organizations, innovations, and strategies by 2030, and, consequently, which societal areas may be mainly affected. We provide a deep understanding of how the adoption of this technology could lead to changes in Europe over multiple dimensions, ranging from business to culture and society, policy and regulation, economy, and technology. From the projections that reached a significant consensus and were given a high probability of occurrence by the experts, we derive four scenarios built around two main dimensions: the digitization of assets and the change in business models.
Citation: Levis D, Fontana F, Ughetto E (2021) A look into the future of blockchain technology. PLoS ONE 16(11): e0258995. https://doi.org/10.1371/journal.pone.0258995
Editor: Alessandro Margherita, University of Salento, ITALY
Received: June 1, 2021; Accepted: October 9, 2021; Published: November 17, 2021
Copyright: © 2021 Levis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper.
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Over the last few years, the hype and interest around blockchain technology have consistently increased. Practitioners from many industries and sectors have joined an open, yet mainly unstructured, discussion on the potential disruptive capabilities of this newly born technology [ 1 – 3 ]. In principle, the size of the phenomenon could be huge, with latest estimates predicting blockchain to store, by 2025, the 10 per cent of the world’s GDP (about $88tn in 2019) [ 4 ]. However, the complexity of the technology itself and the difficulties in assessing its impact across the different application fields have prevented the social, industrial and scientific communities to agree upon a shared vision of future blockchain-based scenarios. Very fundamental questions are still to be answered. Which blockchain-enabled applications will see the light in the next few years? Which industrial sectors will be mainly affected? How will companies react to potential industry-disruptors? How will the current societal paradigm shift? Which role will policy makers play in enhancing this new paradigm?
Despite the great and undoubted technological innovation linked to this technology, uncertainties and speculation on the potential scenarios still animate the industrial and scientific dialogue [ 5 ]. In particular, it is not yet clear which applications will see the light, and, eventually, what effects these changes will have at a societal level.
In this paper, we use a Delphi approach to investigate whether, and to what extent, blockchain-based applications will affect firms’ organizations, innovations and strategies by 2030, and, consequently, which societal areas will be mainly affected. With this methodology, we aim at reaching experts’ consensus to gain new insights and assess the likelihood about the future of the technology. This is a relevant issue, as blockchain technology applications cover a wide spectrum of areas. Blockchain can be applied vertically within an industry (e.g. disrupting its supply chain) or horizontally across different industries or within single companies (e.g. modifying the internal structures and the modus operandi of the different company functions). Given the number of potential applications and the complexity of the technology, stakeholders are divided into skeptics, who believe the technology is still too immature to become a paradigm in the near future, and enthusiasts, who instead believe that this radical innovation will disrupt many industries and completely change business models and people’s behaviors, like internet did during the 90s.
The literature on blockchain is also widely fragmented. Different works have investigated possible blockchain applications within specific domains, such as finance [ 6 – 8 ], logistics [ 9 ], healthcare [ 10 , 11 ] and education [ 12 ]. However, a holistic approach on possible blockchain-enabled future scenarios is still missing. To our knowledge, the only contribution in this direction is the one by White [ 13 ], who explores blockchain as a source of disruptive innovation exclusively with regard to the business field. We depart from his work to adopt a much wider perspective in this study. In fact, our aim is to obtain a deep understanding on how the adoption of this technology in Europe will lead to changes over multiple dimensions, ranging from business to culture and society, policy and regulation, economy and technology. Thus, our research aims at exploring if a convergence between the two divergent perspectives on blockchain can be found, bringing together experts currently working on blockchain projects to explore the possible changes that the technology will bring to the society by 2030.
Our study outlines an overall agreement among experts that the blockchain technology will have a deep impact on multiple dimensions. In the near future people will likely start using and exploit the blockchain technology potential, without really knowing how the technology behind works, in the same way as they send emails today, ignoring how the digital architecture that allows to exchange bytes of information works. Policy makers and governments will play a crucial role in this respect, by enabling productivity boosts and competitive gains from the companies operating under their jurisdictions. As such, a tight and cooperative relationship between industrial actors and regulatory bodies will be extremely important and auspicial. To this aim, it will be of key importance for all players to understand the real competitive advantage that blockchain can bring to their own industry and market.
This work aims at contributing to the raising blockchain literature by offering a holistic view on possible blockchain-enabled future scenarios in Europe, and to investigate which of the proposed scenarios is more likely to occur. As widely agreed by the academic literature, technological developments dictate the speed and pace at which societies change [ 14 ]. Under this assumption, technological forecasting appears to be a method of fundamental importance to understand “ex-ante” the potential development of technological changes, and their impact on different societal aspects [ 15 ]. Foreseeing future technological trends could help society in understanding possible future scenarios, thus contributing to a better knowledge of the new paradigms our society is heading towards. The work is structured as follows. Section 2 provides an overview on the main research streams upon which this work is based. Section 3 presents the methodology. Results are described in Section 4 and Section 5 concludes the work.
2.1 the blockchain technology.
As defined by Crosby et al. [ 3 ] a blockchain can be conceptualized as a shared and decentralized ledger of transactions. This chain grows as new blocks (i.e. read transactions or digital events) are appended to it continuously [ 16 , 17 ]. Each transaction in the ledger must be confirmed by the majority of the participants in the system [ 3 , 18 – 21 ]. This means for the community to verify the truthfulness of the new piece of information and to keep the blockchain copies synchronized between all the nodes (i.e. between all the participants to the network) in such a way that everybody agrees which is the chain of blocks to follow [ 19 ]. Thus, when a client executes a transaction (e.g. when it sends some value to another client), it broadcasts the transaction encrypted with a specific technique to the entire network, so that all users in the system receive a notification of the transaction in a few seconds. At that moment, the transaction is “unconfirmed”, since it has not yet been validated by the community. Once the users verify the transaction with a process called mining, a new block is added to the chain. Usually, the miner (i.e. the user participating to the verification process) receives a reward under the form of virtual coins, called cryptocurrencies. Examples of cryptocurrencies are Bitcoins, Ether, Stellar Lumens and many others. Virtual coins can then be used on the blockchain platform to transfer value between users [ 17 – 19 ].
Thanks to a combination of mathematics and cryptography, the transactions between users (i.e. exchange of data and value), once verified by the network and added to the chain, are “almost” unmodifiable and can be considered true with a reasonable level of confidence [ 17 , 19 , 22 ]. These attributes of the technology make it extremely efficient in transferring value between users, solving the problem of trust and thus potentially eliminating the need of a central authority (e.g. a bank) that authorizes and certifies the transactions [ 7 , 23 , 24 ].
The technology can be easily applied to form legally binding agreements among individuals. The digitalized asset, which is the underlying asset of the contract, is called token. A token can be a digitalized share of a company, as well as a real estate property or a car. Through the setting of smart contracts (i.e. digitalized contracts between two parties), the blockchain technology allows users to freely trade digital tokens, and consequently to trade their underling physical assets without the need of a central authority to certify the transaction (OECD, 2020).
The academic literature has investigated a wide range of possible blockchain applications within specific domains, such as finance [ 6 – 8 ], logistics [ 9 ], healthcare [ 10 , 11 ] and education [ 12 ].
As mentioned, one of the undoubted advantages of the blockchain technology is the possibility to overcome the problem of trust while transferring value [ 25 ]. Not surprisingly, the technology seems to find more applications in markets where intermediation is currently high, like the financial sector, and in particular the FinTech sector, that has recently experienced a consistent make-over thanks to the diffusion of digital technologies [ 7 , 26 , 27 ]. The implementation of the blockchain technology in the financial markets could provide investors and entrepreneurs with new tools to successfully exchange value and capitals without relying on central authorities, ideally solving the problem of trust. This is among the reasons why many observers believe that the blockchain would become a potential mainstream financial technology in the future [ 28 ]. Blockchain represents an innovation able to completely remodel our current financial system, breaking the old paradigm requiring trusted centralized parties [ 6 – 8 ]. With new blockchain-based automated forms of peer-to-peer lending, individuals having limited or no access to formal financial services could gain access to basic financial services previously reserved to individuals with certified financial records [ 29 ]. Indeed, blockchain technology can provide value across multiple dimensions, by decreasing information asymmetries and reducing related transactional costs [ 30 ]. Initial coin offerings (ICOs) represent one of the most successful blockchain-based applications for financing which has been currently developed. Virtual currencies like Bitcoins can disruptively change the way in which players active in the business of financing new ventures operate [ 7 , 30 – 33 ]. Through an ICO, a company in need of new capital offers digital stocks (named token) to the public. These digital tokens will then be used by investors to pay the future products developed by the financed company [ 30 , 34 , 35 ]. ICOs represents a disruptive tool: entrepreneurs can now finance their ventures without intermediaries and consequently lower the cost of the capital raised [ 31 , 36 ]. However, some threats coming from the technology adoption can also be identified, as blockchain can also lead to higher risks related to the lower level of control intrinsically connected to the technology, especially in the case of asymmetric information between the parties involved.
Disintermediation plays a key role in the healthcare sector as well, where blockchain has recently found numerous applications. Indeed, many players currently need to exchange a huge amount of information to effectively manage the whole sector: from hospitals, to physicians, to patients. The ability to trustfully exchange data and information becomes of undoubted value in this context [ 10 , 11 ]. It should not be difficult to envision blockchain applications in other fields as well. In every sector in which information, value, or goods are supposed to flow between parties, blockchain can enable a trustful connection between the players, with the need of a central body entrusting the transaction. Within supply chain, it can increase security and traceability of goods [ 9 , 37 ]. Within education, it can help in certifying students’ acquired skills, reducing, for example, degree fraud [ 12 ]. To conclude, a recent work from Lumineau et al. [ 38 ] highlights possible implications of the technology in the way collaborations are ruled and executed, shading light on new organizational paradigms. Indeed, the authors show how the intrinsically diverse nature of the technology could strongly affect organizational outcomes, heavily influencing and modifying (possibly improving) the way in which different entities cooperate and collaborate.
3.1 forecasting technique: the delphi method.
In the past decade, an increasing number of forecasting techniques has been employed in the academic literature to predict the potential developments induced by technological changes. In particular, the Delphi method, whose term derives from the Greek oracle Delphos, is a systematic and interactive method of prediction, which is based on a panel of experts and is carried out through a series of iterations, called rounds. Many academic works have adopted this method since its development [ 14 , 39 – 44 ]. As the core of the Delphi approach, experts are required to evaluate projections (representations of possible futures) and assess their societal impact and the likelihood that they will occur within a specific time horizon.
While the majority of forecasting methods does not account for the technological implications on the social, economic and political contexts, the Delphi technique allows subjective consideration of changes in interrelated contexts [ 45 ]. Many different variants of the Delphi methodology have been developed according to the needs and goals of each research. For the purpose of this research, we decided to follow the four-steps procedure suggested by Heiko and Darkow [ 46 ] ( Fig 1 ).
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The first step of the method requires to develop and envisage projections and possible scenarios that might arise through the adoption of the technology. These projections must be short, unequivocal, and concise [ 14 ]. This phase requires researchers to deeply understand the technology by analyzing the existing literature, attending courses and workshops and conducting a number of face-to-face interviews with experts ( Fig 2 ). Once the insights are gathered, the results are synthetized in future projections that will help develop the survey. The second step consists in presenting the study to the panel of selected experts who will take part in the first round of the survey. The main challenge during this phase is to select an appropriate panel of experts and maintain their commitment and response rate. The third step consists in a statistical and quantitative analysis of the answers received and in the selection of the second-round scenarios that experts will need to evaluate again. Through the analysis of the second round of answers, updated scenarios are developed adding to the projections the qualitative and quantitative insights provided by the research. The ultimate goal of this iterative process is to reach consensus among the experts on the scenarios that are most likely to happen in the future.
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The formulation of the projections represents a key aspect of the methodology and requires a particular attention and effort. In this phase, the projections that are later tested by the panel of experts are generated. Vagueness and inaccuracy might generate confusion in experts, leading to less meaningful results. To avoid this situation, we developed the projections by means of triangulation: literature review, interviews with experts and participation to workshops and conferences. The analysis of the literature on blockchain technology (and its benefits) allowed us to understand which industries and businesses will be mainly impacted by the technology.
We chose 2030 as a time horizon for the generation of the scenarios. This is a recommended time span for a Delphi study, since a superior period would have become unmanageable to provide relevant advice for strategic development. As reported in Table 1 , projections span among different areas. To the scope of the work, i.e. to grasp a holistic view of the most likely scenarios, it was necessary to investigate a number of multiple dimensions. Projections are related to socio-cultural, policy and regulations, economic, technological and business aspects. As it can be noticed, projections are all structured in the same way, to facilitate their understanding by experts.
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Twelve blockchain experts were interviewed among academics, startups’ founders and professionals working in consultancy firms, banks and legal institutions. The selection of the experts was made in order to get different points of view and a high level of expertise, as provided by the Delphi method guidelines. We conducted interviews that took between thirty and forty-five minutes on average, according to the interviewee’s availability. Each single interview was tailored for each participant by providing guidelines and reflection tips to encourage discussion. However, a certain degree of freedom was given to the expert to allow his/her spontaneous contribution and to gain some original insights that helped in the final design of the future scenarios. Some common aspects were discussed in all interviews generating redundancy and repetition of already emerged scenarios (e.g. ICOs, business model evolution, security and utility tokens, and legal issues). This is one of the reasons why twelve interviews were considered to be sufficient for the purposes of our research.
One of the authors attended three main events in order to strengthen the knowledge about blockchain and have a broader view of its implications in different fields and industries: one in Milan and two in Paris. Of particular notice, the Community Blockchain Week, a blockchain tech-focused initiative organized voluntarily by actors engaged into the technology and with the will and vision to spread the knowledge among citizens. Thanks to various workshops and speeches during the week, it was possible to dive deeper into many aspects of the technology, as well as to meet some knowledgeable experts of various fields, some of which agreed in participating to the research. The event was extremely useful not only to understand how the technology is evolving, but also to see how the community engages itself to spread the knowledge in order to generate more and more interest around it.
We performed desk research to formulate the initial set of projections. Through the survey of the literature, we gained a comprehensive view of all the potential scenarios of the technology. The analysis of consulting companies’ reports also offered a broader vision of future scenarios, thanks to their strategic rather than technical approach [ 1 , 2 ]. This process led to identify 76 projections that represented the basis for a reflection during the expert face-to-face interviews. After screening the relevant articles and reports, a first filtering of the identified 76 projections was made in order to dismiss redundant or incomplete projections, and to keep only the most complete and varied ones. This process reduced the number of projections to 33 and to 20 after the review of two experts.
The formulation of the projections represents the most sensitive part of the research since it influences the whole study. A detailed analysis was carried out in order to avoid mistakes and confusion. In order to facilitate the respondents filling the questionnaire and to avoid any kind of ambiguity, an introduction explaining the meaning of the terminology used in the questionnaire was presented before starting the survey. The developed scenarios were broken down into six macro categories (the same as proposed by Heiko and Darkow [ 46 ]) to guarantee a more complete and systemic view of how the blockchain ecosystem and community can change and shape the future. The choice of 20 projections to be evaluated by experts is in line with prior studies exploiting the Delphi method [ 46 , 47 ]. Parente and Anderson-Parente [ 47 ] have proposed to limit the number of Delphi questions (e.g. to 25 questions) in order to guarantee a high response rate and properly filled-in questionnaires, including only closed answers. We decided to add the possibility to comment the given answers in order to gather additional qualitative data to improve the quality of the results, in line with the methodology proposed by Heiko and Darkow [ 46 ].
As blockchain experts that took part to the survey, we selected individuals working in companies and institutions on the basis of their experience and knowledge of the field. Following Adler and Ziglio [ 48 ] and Heiko and Darkow [ 46 ] four requirements for “expertise” were considered:
A minimum panel size of 15–25 participants is often required to lead to consistent results. In our case, a panel of 35 experts was reached for the first round. For the reliability of the study the panelists were selected with different backgrounds and profiles. To be aligned with the European focus of the study, we considered experts working in twelve European countries, being France and Italy the ones with the highest number of respondents. The panel characteristics are reported in Figs 3 , 4 and 5 .
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In line with the methodology proposed by Heiko and Darkow [ 46 ], two rounds of surveys were executed. We decided to carry no more than two rounds because participating to a Delphi study requires a lot of effort and is a time-consuming task for panelists. By limiting the rounds to two, we reached a sufficient number of respondents that led to have valuable results and consistent conclusions. Moreover, since for each scenario the possibility to include a qualitative argumentation was included, the smaller number of iterations worked as a stimulus for the experts to explain the reasons of their quantitative answers.
The survey was carried out following the standards of the Internet-based Delphi, also called e-Delphi [ 39 , 40 ]. Giving the possibility to respondents to answer digitally allowed experts to be more flexible in responding to the survey, ensuring a greater participation. The way the questionnaire was structured was exactly as the e-Delphi website suggests, but for practical reasons we edited the survey using Google Form. Other standards, such as the real-time Delphi solution proposed by several studies [ 14 , 42 , 43 , 49 ] could have led to a better comparison among experts, but would have likely caused more withdraws to the survey.
In the first round of the survey, the experts assessed the expected probability and impact of the twenty outlined projections. Some Delphi studies [ 50 , 51 ] include a third factor that helps to assess the desirability of a scenario (i.e. how much an expert is in favour of the realization of a prediction). However, we decided not to include this last aspect to make the questionnaire lighter and faster to be filled in, and to reduce drop-outs ( Table 2 ).
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Impact, evaluated at the industry level, was measured on a five-point Likert scale [ 52 ]. Since there is not a general consensus among experts regarding the number of points the scale should have, and due to the general nature of the scenarios, we preferred to use a five-point Likert scale. The corresponding probabilities are: 0%, 25%, 50%, 75% and 100%. Gathering quantitative data allowed to perform a first set of analyses based on descriptive statistics (e.g. mean, median and interquartile range-IQR). We used qualitative data, instead, to build the final scenarios during the fourth step of the forecasting technique. Even though the literature regarding the Delphi method does not suggest a standardized way to analyze consensus, central tendency measures, such as median and mean values, are useful to grasp a first understanding and are frequently accepted and adopted ( Table 3 ). Scenarios with an IQR equal or lower than 1.5 were considered as having reached an acceptable degree of consensus. It should be noticed that most of the projections that achieved the highest probability, having a median value of 75% achieved also the consensus, i.e. IQR below 1.5. This was the case for projections 3, 4, 8, 9, 10, 13, 15, 19, 20.
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These results show that it was easier for experts to find a consensus over the projections that resulted as very likely to occur. Only projection number 18 achieved a high probability score but could not reach a consensus.
During the Delphi’s second round only the projections with an IQR above 1.5 (i.e. which did not reach consensus in the first round) were tested. In order to allow the respondents to easily understand the answers that the panel gave as a whole in round one, for each projection a quantitative report was provided. This report was made of a bar chart with the distribution of the first round’s answers and the correspondent qualitative details, i.e. some of the argumentations provided by some of the panelists. Experts were asked to reconsider the likelihood of occurrence of the projections number 1, 5, 7, 11, 12, 14 and 18. The second round was again structured using Google Form. Following the Delphi’s approach, we did not ask again to estimate the impact for each projection, since this would have presumably been not subject to any change. Moreover, we decided to leave the opportunity to offer again some qualitative comments in support of the answers for a better analysis of the results. The number of experts who successfully completed the second round of the survey dropped to 28, i.e. the 80% of the experts that completed Round 1 and 56% of the selected initial panel. Again, we evaluated the central tendency measures for the projections tested during the second round ( Table 4 ).
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In order to provide a more effective and structured analysis of the results, we first report the final summary table of the Delphi survey and then describe the insights obtained from the analysis. It has to be noticed that Table 5 reports quantitative data only, while during the survey qualitative data were collected as well. In presenting the results of this research, both quantitative and qualitative data are used to provide the best possible picture of what the blockchain-based future will look like. Alongside with standard statistics, we build on qualitative insights obtained during the interviews carried on with experts.
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Firstly, it is interesting to analyze which projections, out of the initial 20, reached a significant consensus (IQR <1.5 after the two rounds of the surveys) and were given a high probability of occurrence by the experts. We can summarize the findings in this domain around three major axes: efficiency, security, and innovation.
By 2030, it will be easier, faster and leaner to exchange value and data among users, institutions and countries. Efficiency will boost and uncover innovation potential within companies and societies if these latter will be able to exploit such a new opportunity. Policies will be a necessary pre-requisite for companies to be able to build a competitive edge globally. From this perspective, the capability of central governments to spur innovation with lean and flexible regulations will be a key driver in explaining the ex-post productivity differential among companies belonging to different countries. From the interview with an investment banker part of the BPCE French group (one of the largest banks in France), it emerged how efficiency is often hampered by the lack of an equally efficient regulation. To provide the reader with an interesting example, in 2018, Natixis, the international corporate and investment banking, asset management, insurance and financial services arm of BPCE, entered the Marco Polo consortium, an initiative born to provide a newly conceived trade and supply chain finance platform, leveraging Application Programming Interfaces (APIs) and blockchain technology. Many other leading banks joined the consortium as well. However, as highlighted by the investment banker, the main limiting factor of the consortium, strongly hampering its efficiency and ability to provide a competitive edge, was the “old-style” bureaucracy linked to it. Although transactions were in principle to be executed smoothly, a bulk of legal paperwork was required to approve them formally. In this case, it appears evident that technology often runs faster than policy, consistently lowering its potential. Interestingly, this view is also shared by regulatory bodies. An experienced lawyer and notary, also member of a panel of experts elected by the Italian government to define the national strategy on blockchain, highlighted that, sometimes, regulators working on blockchain-related policies are trying to adapt existing regulations to the new paradigm. Due to the intrinsically different nature of the technology, this could represent a wrong approach. At the same time, building a new set of policies from scratches could represent a challenging task. From this perspective, projections 4 and 5 confirm this insight: policy and technology should come hand in hand to synergically boost productivity. The three projections reached consensus after the two rounds and were assigned a high probability of occurrence. Overall, it is evident that regulatory aspects linked to the adoption of this new technology shall not be underestimated.
As previously mentioned, security, and specifically cybersecurity, is another dimension around which blockchain could bring consistent advantages, as projections 3, 10, 11 and 15 suggest. On this specific aspect, we interviewed a project leader of the World Economic Forum who previously worked for the United Nations for more than ten years. She dealt specifically with digital regulations, justice, and cybersecurity, and in the last three years before the interview, she specifically worked on blockchain implications and how the technology could be implemented in existing ecosystems. Thanks to her experience in the domain, she clearly explained how the blockchain represents a meaningful technology to avoid cyberattacks to sensitive data and digital files. In her opinion, the avoidance of a single point of failure is the main reason behind a possible blockchain adoption over the next years, since cyberattacks are becoming more frequent and dangerous and related costs for companies are exponentially increasing (e.g. 2020 has been a record year for cyber attacks). Consequently, companies will be increasingly investing in distributed ledgers as a form of contingency budget to lower the cybersecurity risk and its related cost. Given the centrality of data in today’s businesses, serious attacks and loss of data could represent a serious threat to business long-term sustainability.
The third relevant aspect on which blockchain will have a strong impact is, not surprisingly, innovation. Although regulation could represent a non-negligible limiting factor, experts foresee many sectors to be impacted by the technology adoption. For example, the financial sector could be heavily affected by this new paradigm. Particularly, companies’ capital structures and their strategic interlink with business models will drive a differential competitive power. Most likely, enterprises will have to rethink their business models to account for the possibility to digitize/tokenize their assets (Projections 8 and 18). The capability in flexibly adapting their service offerings to the new opportunity and the ability to raise, and re-invest, new capitals will shape the global competition landscape across different industrial sectors and geographies. From one side, blockchain will enable new strategic decisions, from the other side, it will be of fundamental importance to build technological capabilities to enable these decisions. The underlying technology behind transactions, equity offering and equity share transfers will most likely be the blockchain (Projections 13 and 16). Disintermediation and the ability to exchange value, information, and data trustfully without a central authority will enable a new way of funding and cooperation on open-source projects (Projection 19). Most likely, people will refer to blockchain systems as they now refer to browsers such as Chrome, Firefox or Internet Explorer. Many blockchains are already available and are constantly improved and developed, and it is foreseeable that this will remain the case in the future. Users will just need to know the characteristics that a blockchain provides to choose the most suitable one for their business and purposes. Blockchain-based systems will require new skills and knowledge that developers and engineers will need to develop. Big efforts will be needed to make the blockchain more and more user friendly and attractive for those who just want to benefit from the immutability, traceability, and security that it intrinsically brings. At the time of the writing and in line with the Abernathy and Utterback model [ 53 ] many players are currently investing and innovating on blockchain to provide services that will satisfy the new market needs.
The opportunity for people to deal freely will in fact generate opportunities that were unforeseeable before. Self-enforcing smart contracts (Projection 20) will let parties to buy and sell products or to rent them with pay-for-use schemes in an automated way, the digitization of shares and assets will allow companies to raise capital in new ways, without the need to rely on banks, venture capitals or traditional IPOs. Indeed, it is important to understand how the digitization of assets can challenge existing investments and the funding industry represented by traditional private equity firms and banks. Blockchain could allow the creation of platforms for the issuance of traditional financial products on a tokenized nature, making it easier, more transparent and cheaper to manage and access these tools for everyone, including both individual savers and SMEs. Two different types of companies can and will operate in the market: those which have blockchain at their core since their foundation, and those which have (or will have) to embark in a digital transformation process to reconvert themselves into blockchain-based enterprises. In both cases, companies are investing to get a competitive advantage over competitors, betting on the technology that is promising to reduce costs and increase efficiency. Once a dominant design in product and services will be achieved, companies that took a different path will likely exit the market, letting firms following the dominant design to gain market shares.
To conclude and to conceptualize the insights we obtained from both quantitative and qualitative data, we derived four scenarios that we organized in a matrix framework, reported in Table 6 . The framework was built around two main dimensions: on one hand the digitization of assets, and on the other hand the change in business models. The proposed framework leads to the identification of four quadrants: scenarios which envision both the digitization of assets and business model changes and scenarios which do not foresee neither of these two changes. These four main development scenarios were completed and analyzed in the light of the conducted interviews and of the quantitative and qualitative data gathered through the Delphi survey. Each quadrant was given a label: Internal Processes, Flow-less Coopetition, Suppliers Potential and Investment Opportunities. When discussing the quadrants, we try to highlight which of the three improvement areas previously identified (efficiency, security, and innovation) are exploited in the discussed scenario.
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To derive relevant insights from the framework, it is useful to start from the bottom left quadrant, Internal Processes. This name was chosen to highlight the absence of any particular evolution for the company at a strategic level through the blockchain adoption. In this case, it is conceivable to use the technology to incrementally improve firms’ operation performances. Blockchain’s main benefits are to increase traceability of transactions and guarantee their immutability. All these characteristics adopted on today’s processes will result in an automation of routine business functions, such as settlements and reconciliation, customs clearance, heavy payments, invoicing, and documentation, boosting operational efficiency and cost performance. In this scenario, security and efficiency will see a consistent improvement.
The top-left scenario shows instead a different perspective, by considering a broader adoption of blockchain that generates new cooperative business models among different stakeholders, potentially even among competitors. This is why it is called Flow-Less Coopetition. In this case, the benefits of blockchain will help at generating a more democratic ecosystem in terms of information. Those actors that base their business models on information asymmetry, having access to key information before others, will need to revisit their business models if they want to stay competitive. It is of interest to notice how big financial institutions, traditionally competing, are now exploring potential collaboration models in the light of this new technology (e.g. JP Morgan Chase, Morgan Stanley). This quadrant envisages an advance in all three blockchain-enabled dimensions: efficiency, security, and innovation.
The bottom-right scenario, called Suppliers Potential, highlights how, thanks to the digitization that blockchain allows, many actors could jump in the market providing solutions to those companies that would like to benefit from the advantages of digitizing their assets, but are lacking means and competences to internally develop them. Those companies would rather outsource the development of blockchain-based solutions. For this reason, the potential for the creation of a remunerative B2B market exists. Even though there are already protocols that are leaders in the market (Hyperledger Fabric and Ethereum), new solutions with different configurations will likely be needed to support different industries and use case solutions. As for the first scenario, also in this context efficiency and security will be mainly affected.
Finally, the last scenario (Investment Opportunities) focuses on the combination between the complete digitization of the assets of a company and the new business models that this major change could generate. As already mentioned in previous paragraphs, industries are experimenting many ways to facilitate the access to capital. Since the explosion of ICOs in 2017, new and easier ways to access capital have become possible and achievable. However, due to their unregulated nature, ICOs still present numerous potential threats (Projection 14 did not reach consensus). For this reason, other solutions, such as STOs (Security Token Offerings), are on the way of being tested. Bringing a higher degree of freedom to investments will allow companies to receive funds from diverse and non-traditional investors, and it will also boost investments by private individuals into early-stage companies. Efficiency and innovation will be at the core of this last scenario.
In this paper, we studied different blockchain-based projections and we assessed their likelihood and impact thanks to the participation of a pool of experts. We built our findings around three dimensions (efficiency, security, and innovation) and we derived four scenarios based on experts’ shared vision. Being the current literature widely fragmented, we believe this research represents a useful starting for conceptualizing blockchain potential and implications. While many research papers focus on blockchain specific applications or general reviews of the state of the art, we try to propose a unifying framework building on different typologies of insights and analyses. We merged quantitative observations derived from standard statistics with qualitative insights obtained directly from experts’ opinions.
Overall, we believe our research can constitute a useful tool for many practitioners involved in the innovation ecosystem and for managers of small, medium and large enterprises to look at future possible scenarios in a more rational and systematic way. From one side, a company’s management can use these forecasts as a starting point for the implementation of new strategies. As previously highlighted, blockchain offers endless possibilities. However, the ability to focus on activities and projects with a positive return on investment will be crucial. Firstly, managers will face the choice between insourcing or outsourcing the technological development of the platform. While the former choice ensures higher flexibility, it also generates high development and maintenance costs. Companies which will identify blockchain as their core service will be entitled to adopt this first strategy, while the majority of the enterprises will probably gain better competitive advantages adopting Blockchain as a Service (BaaS) solution. This latter approach will boost companies’ performances, by enhancing new service offerings as well as a new level of operational efficiency, without carrying the burden and costs of technological complexity.
As mentioned, we believe this research provides useful insights for policy makers as well. The adoption of blockchain represents a tremendous technological change bringing along interesting and tangible opportunities. However, different threats can be foreseen. Central authorities do not only solve the problem of trust in certifying value transactions. They also provide essential supervision on the process itself, for example ensuring that information asymmetry is kept at reasonable levels between parties engaging in any sort of contracts, especially in the financial world. Letting people directly exchange value between themselves or allowing companies to easily raise capitals can boost financial efficiency, but also provides room for frauds and ambiguous behaviours. Today, companies which are interested in raising capitals both through innovative tools such as crowdfunding or through traditional entities such as public financial markets, have the duty to disclose relevant information and usually go through a deep process of due diligence. Regulators should ensure the same level of control on companies that will raise money through Initial Coin Offerings or other sort of blockchain-enabled offerings. We believe that the first step towards a fair regulation of this newly born technology is the understanding of its foreseeable impact on the society in the near future. This work aims to be a precious enabler in this direction. As highlighted in the body of this research, it appears fundamental for policy makers, regulators and government to deeply understand the potential upsides and threats of this new technology, and to correctly navigate the different possible blockchain-enabled scenarios. The successful cooperation between companies’ management and regulators could enable significant productivity shifts in the economic tissue of many countries. Failing in efficiently grasping and enhancing these new paradigms from a regulatory perspective could result into a heavy deficit for the competitive edge and productivity of the industrial sectors of the governments’ respective countries, potentially leading to macroeconomic differentials in productivity.
To conclude, this research could be a useful reference for orienting into this complex and dynamic environment, reducing the perceived uncertainty associated to such a new technology. Thanks to the experts’ advice, it is now possible to have a clearer picture of the evolution of blockchain technologies and of the opportunities and threats that the technology will generate. Certain limitations and characteristics of this study must be considered to correctly and effectively take advantage of its results. The main objective of this work was to examine the most disrupting aspects that are likely to occur in Europe by 2030, with a particular focus on how the technology will facilitate financing, reduce costs, increase transparency and, in general, influence firms’ business models. From this point of view, the objectives and assumptions presented at the beginning of this paper can be considered as fully achieved, but further works exploring other industries and geographies are required to get an organic understanding of the new enhanced paradigms.
Our research only paves the way for a better understanding of what a blockchain-based future will look like, as the differences between industries are too large to be analyzed in a single work. Organizations and businesses in the financial world are consistently changing, but it will be necessary also for companies belonging to different sectors to completely rethink their core activities. From this perspective, we believe further works are needed in these directions. We hope researchers will use and explode our framework to further characterize and meticulously describe the new possible paradigms around the multiple dimensions examined in this work.
https://doi.org/10.1371/journal.pone.0258995.s001
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Bibliometrics & citations, view options, recommendations, a survey on blockchain for big data: approaches, opportunities, and future directions.
Big data has generated strong interest in various scientific and engineering domains over the last few years. Despite many advantages and applications, there are many challenges in big data to be tackled for better quality of service, ...
In the internet of things (IoT) and big data, the global information society is entering a new phase where consumers, networks, and perception devices work together more intimately. Software-defined networks (SDN) offer lower latency and massive ...
Recent research and experiments in the field of Internet of Things (IoT) security have found that these devices are vulnerable to various attacks, ranging from cyber-attacks to physical attacks on devices. Internet of Things (IoTs) have certain ...
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Recently, the spotlight has been cast on smart healthcare by many researchers to provide better facilities to patients. Improved services, such as reducing health hazards, monitoring patient health, tracking disease trends, and enhancing service quality, can be offered by smart healthcare. Despite its numerous potential benefits, smart healthcare is associated with some security challenges. These challenges can be mitigated by utilizing blockchain technology, which is characterized by decentralization, cryptography, consensus mechanisms, transparency and accountability, smart contracts, ownership of data, immutability, and distributed ledger. Therefore, the latest blockchain technology is focused in this article to address the security challenges of smart healthcare. In this article, attention is given to smart healthcare, smart cities for smart healthcare, smart and secure healthcare, and cutting-edge technologies for smart cities and smart healthcare.Please provide author biography and photo.
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Bhabani Sankar Samantray & K Hemant Kumar Reddy
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Samantray, B.S., Reddy, K.H.K. Blockchain enabled secured, smart healthcare system for smart cities: a systematic review on architecture, technology, and service management. Cluster Comput (2024). https://doi.org/10.1007/s10586-024-04661-7
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Blockchain has been receiving growing attention from both academia and practices. This paper aims to investigate the research status of blockchain-related studies and to analyze the development and evolution of this latest hot area via bibliometric analysis. We selected and explored 2451 papers published between 2013 and 2019 from the Web of Science Core Collection database. The analysis considers different dimensions, including annual publications and citation trends, author distribution, popular research themes, collaboration of countries (regions) and institutions, top papers, major publication journals (conferences), supportive funding agencies, and emerging research trends. The results show that the number of blockchain literature is still increasing, and the research priorities in blockchain-related research shift during the observation period from bitcoin, cryptocurrency, blockchain, smart contract, internet of thing, to the distributed ledger, and challenge and the inefficiency of blockchain. The findings of this research deliver a holistic picture of blockchain research, which illuminates the future direction of research, and provides implications for both academic research and enterprise practice.
With the era of bitcoin, digital cash denoted as BTC makes it possible to store and transmit value through the bitcoin network [ 1 ] . And therewith, blockchain, the technology underlying bitcoin, which adopts a peer-to-peer network to authenticate transactions, has been gaining growing attention from practices, especially Libra, a global currency and financial infrastructure launched by Facebook, and digital currency electronic payment. Currently, blockchain is also an increasingly important topic in the academic field. Blockchain research has considerably progressed, attracting attention from researchers, practitioners, and policy-makers [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ] .
Considering the huge potential benefits that blockchain would bring in various aspects of industries, for instance, finance and economy [ 10 , 11 , 12 ] , internet of things [ 13 , 14 , 15 ] , energy [ 16 , 17 ] , supply chain [ 18 , 19 ] , and other areas. It is often compared with the Internet and is even referred to as a new form of the Internet. As a result, the number of publications in the blockchain is growing rapidly. According to an initial search on the Web of Science Core Collection, over 2000 scientific papers published are related to blockchain.
Under the circumstances where the number of research publications in the blockchain is quickly increasing, although studies have tried to provide some insights into the blockchain research via literature reviews [ 20 , 21 , 22 , 23 , 24 ] . Comprehensive scientometric analysis of academic articles published in influential journals are beneficial to the further development of blockchain research. This research conducts a bibliometric visualization review and attempts to deliver an overview of the research in this fast-growing field.
The objectives of this research are as follows. First, we intend to build an overview of the distribution of blockchain-related research by time, authors, journals, institutions, countries (regions), and areas in the blockchain academic community. Second, we probe the key research topics of blockchain study, for which purpose, we conduct keyword co-occurrence analysis. Third, we picture the intellectual structure of blockchain study based on co-citation analysis of articles and author co-citation analysis. Finally, we identify the direction for the evolution of blockchain study. We adopt Citespace to detect and visualize emerging trends in blockchain study. To achieve these targets, we posed the following research questions:
Q1: What is the distribution pattern of blockchain publications and citations over recent years? Q2: Which are the main international contributing countries (regions) and institutions in blockchain research, and the collaboration network among them? Q3: What are the characteristics of the authorship distribution pattern? Q4: What are the key blockchain subjects based on the number of publications? Q5: Which are the major journals or conferences for blockchain-related research? Q6: Which are the most influential papers in blockchain research based on the number of citations? Q7: Who are the most influential authors in blockchain research according to the author co-citation network? Q8: What are the research trends in blockchain? Q9: What are the most supportive funding agencies for blockchain research?
Our intended contributions in this research are twofold. First, it is an attempt of adopting co-citation analysis to provide comprehensive and up-to-date developing trends in the lasted hot area, blockchain. Second, this study depicts a state-of-the-art blockchain research development and gives enlightenment on the evolution of blockchain. The findings of this research will be illuminating for both academic researchers, entrepreneurs, as well as policymakers.
The rest of the article is organized as follows. The literature review mainly summarizes related work. The “Data and methodology” section describes the data source and methodological process. The “Results” section presents the main results based on the bibliometric analysis as well as statistical analysis. “Conclusions and implications” conclude this research provides answers to the aforementioned research questions and poses directions for further work.
Scientometric analysis, also known as bibliometric network visualization analysis has been widely adopted in numerous areas to identify and visualize the trends in certain fields. For instance, Bonilla, et al. analyzed the development of academic research in economics in Latin America based on a scientometric analysis [ 25 ] . Li, et al. conducted research on emerging trends in the business model study using co-citation analysis [ 26 ] . Gaviriamarin, et al. applied bibliometric analysis to analyze the publications on the Journal of Knowledge Management [ 27 ] .
Since the birth of bitcoin, as the foundation of which, blockchain has gained an increasing amount of attention in academic research and among practices. The research papers focus on the blockchain are quite abundant and are continuing to emerge. Among a host of papers, a few studies investigate the research trend of blockchain-based on a bibliometric analysis [ 22 , 23 , 28 , 29 , 30 ] .
Table 1 presents a summary of these bibliometric studies that summarized some findings on blockchain research, yet very few investigated the co-citation network and the evolution of popular topics in a timeline view. The number of papers these articles analyzed is relatively small, which may be because they used simple retrieval formula in searching blockchain-related articles, and it could pose a threat to bibliometric analysis. Therefore, this research aims to conduct a comprehensive analysis of the status of blockchain research, which is beneficial to future research and practices.
An overview of existing bibliometric studies on blockchain research
ID | Year | First Author | Search Engine | Time Span | NP of analyzed | Main Findings |
---|---|---|---|---|---|---|
1 | 2019 | Dabbagh M | WOS | 2013–2018 | 995 | Blockchain papers are mainly in Computer Science, followed by Engineering, Telecommunications, and Business Economics. National Natural Science Foundation of China has made sound investments in Blockchain research. |
2 | 2018 | Zeng S | EI; CNKI | 2011–2017 | 473 (EI); 497 (CNKI) | Authors and institutes indexed by CNKI have higher productivity compared to EI. Researchers have shifted their attention from Bitcoin to the blockchain technology since 2017. |
3 | 2018 | Miau S | Scopus | 2008–2017 | 801 | There are three stages of blockchain research, namely, Bitcoin and cryptocurrencies, techniques of Blockchain and smart contract. |
4 | 2017 | Faming W | CNKI | 2015–2017 | 423 | Blockchain research system and the scientific research cooperation group of the author in China is yet to be formed. |
5 | 2017 | Mu-Nan L | WOS | 1986–2016 | 220 | Blockchains-related articles are highly correlated with Bitcoin’s, Proceedings Papers account for 72% of the whole blockchain literatures. |
Note: NP = number of publications; WOS = Web of Science Core Collection; CNKI = China National Knowledge Infrastructure Databases; EI = EI Compendex, an engineering bibliographic database published by Elsevier; Scopus = Elsevier’s abstract and citation database.
This section elaborates steps to conduct a comprehensive bibliometric-based analysis: 1) data collection, 2) methodological process. The overall approach and methodology are shown in Figure 1 , the details could be seen as follows.
Research methodology
As the leading database for science and literature, the Web of Science Core Collection has been widely used in bibliometrics analysis. It gives access to multidisciplinary information from over 18,000 high impact journals and over 180,000 conference proceedings, which allows for in-depth exploration of the complete network of citations in any field.
For the sake of acquiring enough articles that are relative to the blockchain, we select keywords from Wikipedia and industry information of blockchain, and some existing research literature [ 1 , 20 , 23 , 30 ] . Moreover, in consideration of that, there are a host of blockchain research papers in various fields, in fact, although some papers use keywords in abstract or the main body, blockchain is not the emphasis of the researches. Therefore, in order to get more accurate research results, we choose to conduct a title search instead of a topic search. Table 2 presents the retrieval results with different keywords in the titles, we find that among publications that are relative to the blockchain, the number of Proceeding Papers is the biggest, which is closely followed by articles, and a few reviews. Based on the comparison of five search results in Table 2 . In addition, for accuracy and comprehensiveness, we manually go through the abstract of all the papers form conducting a title search, and choose papers that are related to blockchain. Finally, a dataset with 2451 articles is used in the subsequent analysis.
The dataset we choose has good representativeness, although it may not completely cover all papers on the blockchain, it contains core papers, and in bibliometric analysis, core papers are enough to provide a holistic view for a comprehensive overview of blockchain research.
Blockchain research article characteristics by year from 2013 to 2019
ID | Retrieval Formula | Records | Document Type |
---|---|---|---|
1 | TI = (“blockchain*”) | 1,506 | P:793; A:683; R:40 |
2 | TI = (“bitcoin”) | 606 | P:333; A:272; R:5 |
3 | TI = (“blockchain*” OR “bitcoin”) | 2,064 | P:1,042; A:995; R:44 |
4 | (“blockchain*” OR “bitcoin” OR “ethereum*” OR “cryptocurrenc*” OR “smart contract*”) | 2,376 | P:1,175; A:1,172; R:47 |
5 | TI = (“blockchain*” OR “smart contract*” OR “smart- contract*” OR “distributed ledger” OR “hyperledger” OR “bitlicence” OR “chinaledger” OR “51% attack” OR “unspent transaction outputs” OR “segwit2x” OR “satoshi nakamoto” OR “dust transaction*” OR “cryptocurrenc*” OR “bitcoin*” OR “ethereum” OR “lite-coin” OR “monero” OR “zerocoin” OR “filecoin” OR “crypto currenc*” OR “crypto-currenc*” OR “cryptocurrenc*” OR “encrypted currenc*” OR “on-ledger currenc*” OR “off-ledger currenc*” OR “cryptonote” OR “altcoin” OR “crypto token” OR “crypto crash” OR “cryptokitties” OR “bitpay” OR “mtgox” OR “bitfinex” OR “bitstamp” OR “okex” OR “okcoin” OR “huobi” OR “bitmex” OR “binance” OR “negocie coins” OR “bitforex” OR “coinbase” OR “poloniex” OR “fcoin” OR “gate.io” OR “initial coin offering” OR “initial miner offering” OR “initial fork offering” OR “initial bounty offering*” OR “initial token offering” OR “security token offering” OR “initial cryptoasset offering” OR “crypto-wallets” OR “soft fork” OR “hard fork” OR “cold wallet” OR “hot wallet” OR “core wallet” OR “imtoken” OR “decentralized autonomous organization*” OR “decentralized autonomus corporation*” OR “decentralized autonomus campany*” OR “ASIC mining” OR “application-specific integrated circuit miner” OR “FPGA mining” OR “GPU mining” OR “bitmain” OR “canaan creative” OR OR “antpool” OR “SlushPool” OR “ViaBTC” OR “BTC.TOP” OR “F2Pool” OR “interplanetary file system”) | 2,451 | P:1,212; A:1,210; R:49 |
Note: Document type include: Article(A), Proceedings Paper(P), Review(R); Timespan = 2013 ∼ 2019, download in May 31, 2019; Indexes = SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, ESCI, CCR-EXPANDED, IC.
The bibliometric approach has received increasing attention in many research domains. In this study, the methodological process mainly includes three methods: 1) descriptive statistical analysis, 2) article co-citation, author co-citation, and cluster analysis on co-cited articles; 3) time-zone analysis on co-cited keywords.
Descriptive statistical analysis displays an overall status of the research development in the target field, which mainly presents an overview by publication years, document types, the research area of published journals, number of citations, and in terms of most cited paper, influential author, institutions and countries. Co-citation analysis helps to identify the frequency of co-cited papers and authors and provides crucial insights into the intellectual structure of certain research fields [ 31 ] . Time-zone analysis helps to understand the flow of information and research trends in the target area [ 32 ] .
Various visualization tools have been designed and developed as computer software such as Citespace and VOSviewer. In this study, we use Citespace for co-citation analysis and timezone analysis, VOSviewer is adopted for social network analysis and visualization, we also apply other tools such as Excel and Tableau for basic statistical analysis and the visualization of the bibliometric results. Notably, in Citespace, core nodes are displayed as “citation tree-rings”, which contain abundant information of an article, for instance, the color of a citation ring denotes the year of corresponding citations, and the rule of colors in Citespace is the oldest in dark blue and newest in light orange with a spectrum of colors in between, the thickness of a ring is proportional to the number of citations in a time slice [ 33 ] . Figure 2 illustrates the details of the citation tree-rings. In addition, Citespace adopts a time-slicing mechanism to produce a synthesized network visualization [ 34 ] .
Citation tree-rings [ 33 ]
Table 3 illustrates several characteristics of blockchain-related publications sorted by the year of publication. The annual number of articles and countries has been growing continuously since the proposing of Nakamoto’s paper in 2008 [ 1 ] , and the first blockchain research paper was published in 2013. By examining the published papers over time, there were only eight articles published in 2013. Afterward, with a continuous increase, a peak of 1,148 articles was published in 2018, and the number of publications is likely to grow ever since. Meanwhile, the annual number of countries taking part in blockchain research has also rapidly increased from 6 to 93 between 2013 and 2017, whereas the average number of Times Cited for single articles declined from 34.00 to 1.73 between 2013 and 2018. Over the observation period, 97 countries took part in the research on the blockchain with a sample of 44 in the H-index of our paper.
Statistical description of Blockchain research article from 2013 to 2019
Publication Year | NP (%) of 2451 Papers | No.CO | AV.TC | H-index |
---|---|---|---|---|
2013 | 8 (0.33%) | 6 | 34.00 | 4 |
2014 | 54 (2.20%) | 26 | 16.98 | 17 |
2015 | 101 (4.12%) | 37 | 14.88 | 19 |
2016 | 176 (7.18%) | 48 | 14.19 | 25 |
2017 | 569 (23.22%) | 65 | 5.00 | 26 |
2018 | 1,148 (46.84%) | 93 | 1.73 | 19 |
2019 | 395 (16.12%) | 72 | 0.29 | 4 |
Total | 2,451 (100.00%) | 97 | 4.12 | 44 |
Note: NP = number of publications; No.CO = number of countries; AV.TC = average number of Times Cited.
Figure 3 presents the cumulative numbers of published articles and citations from 2013 to 2019. There was a drastic increase in the number of papers published annually after 2016. As for the cumulative number of citations, there was no citation of blockchain literature before 2013, and 272 citations in 2013. By 2018, this number has grown over 10,000, which implies a widespread influence and attention of blockchain study in recent years.
Cumulative growth in blockchain publications and citations, 2013–2019
The exponential growth is a typical characteristic of the development of research fields [ 35 ] . The model can be expressed as:
where C is the cumulative number of articles or citations, Y is the publication or citation year, α , and β are parameters. In this study period, the cumulative articles and citations in the filed grow exponentially by R articles 2 = 0.9463 and R citations 2 = 0.8691 respectively. This shows that the research quantity curve of the blockchain is like an exponential function, which means the attention of academic circles on the blockchain has been increasing in recent years.
A total of 97 countries/areas have participated in blockchain research during the observation period. Table 4 shows the number of articles for each country (region) contributing to publications. Remarkably, an article may be written by several authors from different countries/areas, therefore, the sum of articles published by each country is large than the total number of articles. As can be seen from Table 4 , the USA and China play leading roles amongst all countries/areas observed, with publications of 532 (20.94%) and 489 (19.24%) articles respectively, followed by the UK, which published 214 (8.42%) articles.
Blockchain research country (region) ranked by number of articles (top 25)
Rank | Country (Region) | NP (%) of 2451 Papers | No.TC (%) | AV.TC | No.CA | H-index |
---|---|---|---|---|---|---|
1 | USA | 532 (20.94%) | 3,709 (36.57%) | 6.97 | 1,810 | 28 |
2 | China | 489 (19.24%) | 1,357 (13.38%) | 2.78 | 753 | 17 |
3 | UK | 214 (8.42%) | 1,211 (11.94%) | 5.66 | 658 | 17 |
4 | Germany | 121 (4.76%) | 589 (5.81%) | 4.87 | 437 | 13 |
5 | Italy | 120 (4.72%) | 430 (4.24%) | 3.58 | 335 | 11 |
6 | Australia | 118 (4.64%) | 509 (5.02%) | 4.31 | 372 | 13 |
7 | France | 105 (4.13%) | 550 (5.42%) | 5.24 | 376 | 13 |
8 | South Korea | 105 (4.13%) | 451 (4.45%) | 4.30 | 332 | 10 |
9 | India | 104 (4.09%) | 178 (1.76%) | 1.71 | 155 | 9 |
10 | Canada | 87 (3.42%) | 390 (3.85%) | 4.48 | 332 | 9 |
11 | Japan | 79 (3.11%) | 165 (1.63%) | 2.09 | 138 | 7 |
12 | Spain | 76 (2.99%) | 396 (3.90%) | 5.21 | 293 | 10 |
13 | Russia | 65 (2.56%) | 61 (0.60%) | 0.94 | 56 | 4 |
14 | Switzerland | 65 (2.56%) | 416 (4.10%) | 6.40 | 331 | 11 |
15 | Singapore | 55 (2.16%) | 394 (3.88%) | 7.16 | 313 | 11 |
16 | Netherlands | 47 (1.85%) | 69 (0.68%) | 1.47 | 66 | 4 |
17 | Austria | 43 (1.69%) | 320 (3.16%) | 7.44 | 280 | 8 |
18 | Greece | 42 (1.65%) | 181 (1.78%) | 4.31 | 171 | 5 |
19 | Taiwan, China | 39 (1.53%) | 95 (0.94%) | 2.44 | 78 | 6 |
20 | U Arab Emirates | 34 (1.34%) | 144 (1.42%) | 4.24 | 132 | 5 |
21 | Brazil | 32 (1.26%) | 40 (0.39%) | 1.25 | 39 | 4 |
22 | Norway | 31 (1.22%) | 214 (2.11%) | 6.90 | 172 | 7 |
23 | Malaysia | 30 (1.18%) | 29 (0.29%) | 0.97 | 27 | 4 |
24 | Romania | 27 (1.06%) | 54 (0.53%) | 2.00 | 52 | 3 |
25 | Turkey | 27 (1.06%) | 65 (0.64%) | 2.41 | 61 | 3 |
Note: NP = number of publications; No.TC = number of total Times Cited; AV.TC = average number of Times Cited; No.CA = number of Citing Articles.
From the perspective of citations, according to country/area distribution in Table 4 , we also find that USA-authored papers were cited by 1,810 papers with 3,709 (36.57%) citations, accounting for 36.57% of total citations. Meanwhile, articles from the USA also have a very high average number of citations per paper with a frequency of 6.97, which ranks third among the top 25 countries/ areas. Interestingly, the articles from Austria and Singapore appeared with the highest average number of citations per paper, with a frequency of 7.44 and 7.16 respectively, whereas the number of publications from these two countries was relatively low compared with the USA. The second was China, following the USA, papers were cited by 753 articles with 1,357 (13.38%) citations. Although the number of articles from China is close to the USA, the average number of citations per paper is lower with a frequency of 2.78. The subsequent countries include the UK, Germany, and Italy. The results indicate that the USA is the most influential country in blockchain.
International collaboration in science research is both a reality and a necessity [ 36 ] . A network consisting of nodes with the collaborating countries (regions) during the observation period is shown in Figure 4 . The network is created with the VOS viewer in which the thickness of the linking lines between two countries (regions) is directly proportional to their collaboration frequency. We can see from Figure 4 that the USA has the closest collaborative relationships with China, the UK, Australia, Germany, and Canada. China has the closest collaborative relationships with the USA, Australia, Singapore, UK, and South Korea. UK has the closest collaborative relationships with the USA, China, France, and Switzerland. Overall, based on the collaboration network, collaboration mainly emerges in highly productive countries (regions).
International collaboration network of the top 25 countries (territories), 2013–2019
A total of 2,190 institutions participated in blockchain-related research, and based on the number of publications, the top 25 of the most productive institutions are shown in Table 5 . Chinese Academy of Sciences had the highest number of publications with 43 papers, followed by the University of London with 42 papers, and Beijing University of Posts Telecommunications ranked third with 36 papers. The subsequent institutions included the University of California System and the Commonwealth Scientific Industrial Research Organization (CSIRO). In terms of the number of total Times Cited, Cornell University is cited most with 499 citations, and the average number of Times Cited is 20.79. Massachusetts Institute of Technology followed closely with 407 citations and with an average number of Times Cited of 22.61. The University of California System ranks third with 258 citations and an average number of Times Cited of 8.06. ETH Zurich ranked fourth with 257 citations and an average number of Times Cited of 10.28. It is notable that the National University of Singapore also had a high average number of Times Cited of 12.56. These results indicate that most of the influential institutions are mainly in the USA and Europe and Singapore. The number of publications from institutions in China is large, whereas few of the papers are highly recorded in average Times Cited. Papers from the National University of Defense Technology China took the highest of average Times Cited of 7.79.
Blockchain research country (territory) ranked by number of articles (top 25)
Rank | Institution | Country | NP (%) of 2451 Papers | No.TC | AV.TC | No.CA | H-index |
---|---|---|---|---|---|---|---|
1 | Chinese Academy of Sciences | China | 43 (1.75%) | 136 | 3.16 | 117 | 6 |
2 | University of London | UK | 42 (1.71%) | 132 | 3.14 | 123 | 7 |
3 | Beijing University of Posts Telecommunications | China | 36 (1.46%) | 56 | 1.94 | 70 | 5 |
4 | University of California System | USA | 32 (1.30%) | 258 | 8.06 | 233 | 8 |
5 | Commonwealth Scientific Industrial Research Organization | Australia | 28 (1.14%) | 229 | 8.18 | 172 | 9 |
6 | Beihang University | China | 26 (1.06%) | 43 | 1.65 | 38 | 4 |
7 | University of Texas System | USA | 26 (1.06%) | 62 | 2.38 | 51 | 4 |
8 | ETH Zurich | Switzerland | 25 (1.02%) | 257 | 10.28 | 208 | 9 |
9 | University of Paris-Saclay | France | 25 (1.02%) | 85 | 3.40 | 82 | 5 |
10 | Cornell University | USA | 24 (0.98%) | 499 | 20.79 | 387 | 10 |
11 | International Business Machines | USA | 24 (0.98%) | 110 | 4.58 | 97 | 7 |
12 | Peking University | China | 23 (0.94%) | 59 | 2.57 | 53 | 5 |
13 | University of New South Wales Sydney | Australia | 22 (0.89%) | 171 | 7.77 | 147 | 6 |
14 | University College London | UK | 21 (0.85%) | 87 | 4.14 | 82 | 5 |
15 | University of Electronic Science Technology of China | China | 20 (0.81%) | 106 | 5.30 | 92 | 5 |
16 | University of Sydney | Australia | 20 (0.81%) | 87 | 4.35 | 79 | 5 |
17 | National University of Defense Technology China | China | 19 (0.77%) | 148 | 7.79 | 130 | 4 |
18 | Shanghai Jiao Tong University | China | 19 (0.77%) | 46 | 2.42 | 42 | 3 |
19 | University of Cagliari | Italy | 19 (0.77%) | 107 | 5.63 | 89 | 5 |
20 | Massachusetts Institute of Technology | USA | 18 (0.73%) | 407 | 22.61 | 361 | 6 |
21 | Nanyang Technological University | Singapore | 18 (0.73%) | 123 | 6.83 | 103 | 6 |
22 | National University of Singapore | Singapore | 18 (0.73%) | 226 | 12.56 | 194 | 7 |
23 | University of Chinese Academy of Sciences | China | 18 (0.73%) | 21 | 1.17 | 19 | 3 |
24 | University of Texas At San Antonio | USA | 17 (0.69%) | 47 | 2.76 | 40 | 3 |
25 | Xidian University | USA | 17 (0.69%) | 39 | 2.29 | 35 | 4 |
To further explore data, the top 186 institutions with at least 5 articles each are chosen for collaboration network analysis. The collaboration network map is shown in Figure 5 , the thickness of linking lines between two institutions is directly proportional to their collaboration frequency. As seen from the cooperation network in the Chinese Academy of Sciences, Cornell University, Commonwealth Scientific Industrial Research Organization (CSIRO), University of Sydney, and ETH Zurich cooperated widely with other institutions. This shows that collaboration between institutions may boost the research of blockchain which echoes with extant research that proposes with-institution collaboration and international collaboration may all contribute to article quality [ 37 ] .
Collaboration network for institutions, 2013–2019
The total number of authors who contribute to the publications of blockchain is 5,862. Remarkably, an article may be written by several authors from different countries (regions) or institutions. Therefore, the total number of authors is bigger than the total number of articles. In fact, during the observation period, the average number of authors per paper is 2.4 articles. Reveals the distribution of the number of authors with different numbers of papers. As seen from the results, most of the authors had a tiny number of papers, i.e., among 5,862 authors, 4,808 authors have only one paper, 662 authors have two papers, and 213 authors have three papers.
According to the participation number of articles, the most productive author in the blockchain is Choo, Kim-Kwang Raymond from Univ Texas San Antonio, who took part in 14 articles in blockchain, followed by Marchesi, Michele from Univ of Cagliari, who took part in 13 articles related to blockchain. The third most productive author is Bouri, Elie from the Holy Spirit University of Kaslik, and David Roubaud from Montpellier Business School. Miller, Andrew, Shetty, Sachin, and Xu, Xiwei ranked fourth, who took part in 10 articles related to blockchain.
The distribution of number of author with different numbers of articles
No.AU | No.AR | Full Name | Institution |
---|---|---|---|
1 | 14 | Choo, Kim-Kwang Raymond | Univ Texas San Antonio |
1 | 13 | Marchesi, Michele | Univ of Cagliari |
2 | 11 | 1. Bouri, Elie; 2. David Roubaud | 1. Holy Spirit Univ Kaslik; 2. Montpellier Business School |
3 | 10 | 1. Miller, Andrew; 2. Shetty, Sachin; 3. Xu, Xiwei | 1. Univ of Illinois System; 2. Old Dominion Univ; 3. CSIRO |
5 | 9 | 1. Bonneau, Joseph; 2. Kiayias, Aggelos; 3. Njilla, Laurent; 4. Salah, Khaled; 5. Shi, Elaine | 1. New York Univ; 2. Univ of Edinburgh & IOHK; 3. US. Air Force Research Laboratory; 4. Khalifa Univ; 5. Cornell Univ |
9 | 8 | Du, Xiaojiang; Eyal, Ittay; Gupta, Rangan; Leung, Victor; Liang, Xueping; Moore, Tyler; Selmi, Refk; Tsai, Wei-Tek; Wang, Pengfei | - |
15 | 7 | - | - |
25 | 6 | - | - |
44 | 5 | - | - |
74 | 4 | - | - |
213 | 3 | - | - |
662 | 2 | - | - |
4,808 | 1 | - | - |
Note: No.AU = number of author; No.AR = number of articles.
Figure 6 displays the collaboration network for authors. The thickness of the linking lines between the two authors is directly proportional to their collaboration frequency. As we can see from Figure 6 , it indicates the most productive authors cooperate widely with others.
Collaboration network for authors, 2013–2019
Table 7 presents the top 25 blockchain categories ranked in terms of the number of articles published. As can be seen from Table 7 , among the top 10 categories, six are related to the Computer Science field, which indicates that blockchain-related researches are more abundant in the field of Computer Science compared with other research fields. Besides, there are also publications in the category of Business & Economics with 385 records.
The top 25 blockchain categories ranked by the number of publications
Rank | Web of Science Categories | Records | % of 2451 |
---|---|---|---|
1 | Computer Science | 1326 | 54.10% |
2 | Engineering | 724 | 29.54% |
3 | Engineering, Electrical & Electronic | 666 | 27.17% |
4 | Computer Science, Theory & Methods | 613 | 25.01% |
5 | Computer Science, Information Systems | 608 | 24.81% |
6 | Telecommunications | 410 | 16.73% |
7 | Business & Economics | 386 | 15.75% |
8 | Computer Science, Software Engineering | 219 | 8.94% |
9 | Computer Science, Interdisciplinary Applications | 196 | 8.00% |
10 | Computer Science, Hardware & Architecture | 184 | 7.51% |
11 | Economics | 175 | 7.14% |
12 | Business, Finance | 174 | 7.10% |
13 | Computer Science, Artificial Intelligence | 134 | 5.47% |
14 | Government & Law | 105 | 4.28% |
15 | Law | 94 | 3.84% |
16 | Science & Technology — Other Topics | 89 | 3.63% |
17 | Business | 58 | 2.37% |
18 | Multidisciplinary Sciences | 52 | 2.12% |
19 | Energy & Fuels | 51 | 2.08% |
20 | Automation & Control Systems | 44 | 1.80% |
21 | Management | 41 | 1.67% |
22 | Physics | 41 | 1.67% |
23 | Information Science & Library Science | 39 | 1.59% |
24 | Operations Research & Management Science | 36 | 1.47% |
25 | Green & Sustainable Science & Technology | 34 | 1.39% |
Figure 7 illustrates the betweenness centrality network of papers of the above categories by using Citespace after being simplified with Minimum Spanning Tree network scaling, which remains the most prominent connections. We can see from Figure 7 , the centrality of Computer Science, Engineering Electrical Electronic, Telecommunications, Engineering, and Business & Economics are notable.
Categories involved in blockchain, 2013–2019
The research of blockchain is published in 1,206 journals (conferences), the top 25 journals (conferences) are displayed in Table 8 . Blockchain research papers are concentrated in these top journals (conferences) and with a concentration ratio of nearly 20%. The major blockchain research journals include Lecture Notes in Computer Science, IEEE Access, Economics Letters, Future Generation Computer Systems, and Finance Research Letters, with more than 20 articles in each one. Meanwhile, the major blockchain research conferences include IEEE International Conference on Hot Information-Centric Networking, International Conference on Parallel and Distributed Systems Proceedings, International Conference on New Technologies Mobility, and Security, and Financial Cryptography and Data Security, with at least 14 articles published in each of these.
The top 25 blockchain publication journals (conferences)
Rank | Source Title | NP (%) of 2,451 | Country | No.TC |
---|---|---|---|---|
1 | Lecture Notes in Computer Science | 120 (4.89%) | Germany | 1253 |
2 | IEEE Access | 102 (4.16%) | USA | 639 |
3 | Economics Letters | 33 (1.35%) | Netherlands | 555 |
4 | Future Generation Computer Systems | 22 (0.90%) | Netherlands | 124 |
5 | Proceedings of 2018 1st IEEE International Conference on Hot Information Centric Networking HOTICN | 22 (0.90%) | - | 2 |
6 | Finance Research Letters | 21 (0.86%) | Netherlands | 307 |
7 | ERCIM News | 20 (0.82%) | - | 1 |
8 | Physica A: Statistical Mechanics and Its Applications | 20 (0.82%) | Netherlands | 101 |
9 | International Conference on Parallel and Distributed Systems Proceedings | 18 (0.73%) | - | 4 |
10 | Sensors | 17 (0.69%) | Switzerland | 66 |
11 | PLoS One | 16 (0.65%) | USA | 283 |
12 | Sustainability | 15 (0.61%) | Switzerland | 22 |
13 | 2018 9th IFIP International Conference on New Technologies Mobility and Security NTMS | 14 (0.57%) | - | 2 |
14 | Advances in Intelligent Systems and Computing | 14 (0.57%) | Germany | 29 |
15 | Financial Cryptography and Data Security FC 2016 | 14 (0.57%) | - | 141 |
16 | International Conference on New Technologies Mobility and Security | 14 (0.57%) | - | 2 |
17 | Financial Cryptography and Data Security Fc 2014 Workshops Bitcoin and WAHC 2014 | 13 (0.53%) | - | 142 |
18 | Journal of Medical Systems | 13 (0.53%) | USA | 127 |
19 | Proceedings 2018 IEEE 11th International Conference on Cloud Computing Cloud | 13 (0.53%) | - | 5 |
20 | 2018 IEEE 24th International Conference on Parallel and Distributed Systems ICPADS 2018 | 12 (0.49%) | - | 0 |
21 | Communications of the ACM | 12 (0.49%) | USA | 80 |
22 | International Journal of Advanced Computer Science and Applications | 12 (0.49%) | UK | 7 |
23 | Journal of Risk and Financial Management | 12 (0.49%) | - | 27 |
24 | Strategic Change Briefings in Entrepreneurial Finance | 12 (0.49%) | - | 52 |
25 | Computer Law Security Review | 11 (0.45%) | UK | 30 |
Note: NP = number of papers; No.TC = number of total Times Cited; Italic represents conference.
Since the notion of co-citation was introduced, there are a host of researchers have adopted the visualization of co-citation relationships. The work is followed by White and Griffith [ 38 ] , who identified the intellectual structure of science, researches then broaden the unit of analysis from articles to authors [ 39 , 40 ] . There are two major types of co-citation analysis, namely, article cocitation analysis and author co-citation analysis, which are commonly adopted to visualize the intellectual structure of the research field. In this study, we explore the intellectual structure of blockchain by using both article co-citation analysis and author co-citation analysis. We apply Citespace to analyze and visualize the intellectual structure [ 41 ] .
In this study, mining spanning trees was adopted to present the patterns in the author cocitation network, a visualization of the network of author co-citation is demonstrated in Figure 8 . In the visualization of the co-citation network, pivot points are highlighted with a purple ring, and landmark nodes are identified with a large radius. From Figure 8 , there are six pivot nodes and landmark nodes: Nakamoto S, Buterin V, Eyal I, Wood G, Swan M, Christidis K. These authors truly played crucial roles during the development of blockchain research. Table 9 shows the ranking of author citation counts, as well as their prominent publications.
Network of author co-citation, 2013–2019
The top 15 co-cited author ranked by citation counts
Rank | Citation Counts | First Author | Article Title, Publication Year |
---|---|---|---|
1 | 1202 | Nakamoto S ] | Bitcoin: A peer-to-peer electronic cash system, 2008. |
2 | 257 | Buterin V ] | A Next-generation smart contract and decentralized application platform, 2014. |
3 | 251 | Eyal I ] | Majority is not enough: Bitcoin mining is vulnerable, 2014. |
4 | 244 | Wood G ] | Ethereum: A secure decentralised generalised transaction ledger, 2014. |
5 | 235 | Swan M ] | Blockchain: Blueprint for a new economy. 2015. |
6 | 223 | Christidis K ] | Blockchains and smart contracts for the internet of things, 2016. |
7 | 182 | Bonneau J ] | Sok: Research perspectives and challenges for bitcoin and cryptocurrencies, 2015. |
8 | 176 | Szabo N ] | Formalizing and securing relationships on public networks, 1997. |
9 | 164 | Zyskind G ] | Decentralizing privacy: Using blockchain to protect personal data, 2015. |
10 | 154 | Castro M ] | Practical byzantine fault tolerance and proactive recovery, 2002. |
11 | 153 | Meiklejohn S ] | A fistful of bitcoins: Characterizing payments among men with no names, 2013. |
12 | 145 | Kosba A ] | Hawk: The blockchain model of cryptography and privacy-preserving smart contracts, 2016. |
13 | 144 | Reid F ] | An analysis of anonymity in the bitcoin system, 2013. |
14 | 143 | Luu L ] | A secure sharding protocol for open blockchains, 2016. |
15 | 140 | Ron D ] | Quantitative analysis of the full bitcoin transaction graph, 2013. |
Nakamoto S, as the creator of bitcoin, authored the bitcoin white paper, created and deployed bitcoin’s original reference implementation, is not surprised at the top of the co-citation count ranking, and has 1,202 citations in our dataset. Buterin V, a Russian-Canadian programmer, and writer primarily are known as a co-founder of ethereum and as a co-founder of Bitcoin Magazine, follows Nakamoto S, receives 257 citations. Eyal I, an assistant professor in technion, is a third of the ranking, with a representative article is “majority is not enough: Bitcoin mining is vulnerable”. Wood G, the ethereum founder, and free-trust technologist ranks fourth with 244 citations. The other core author with high citations includes Swan M, Christidis K, Bonneau J, Szabo N, Zyskind G, Castro M, and Meiklejohn S, with more than 150 citations of each person, and the typical publications of there are present in Table 9 .
To further investigate the features of the intellectual structure of blockchain research, we conducted an article co-citation analysis, using cluster mapping of co-citation articles networks to complete a visualization analysis of the evolution in the research field of blockchain. According to the article co-citation network, we adopted Citespace to divide the co-citation network into several clusters of co-cited articles. The visualization of clusters of co-cited articles is displayed in Figure 9 .
Clusters of co-cited articles, 2013–2019
As we mentioned earlier in the “Data and Methodology” section, the colors of citation rings and links are corresponding to the different time slices. Therefore, the deeper purple cluster (Cluster #1) is relatively old, and the prominent clusters (Cluster #0 and #2) are more recent. Cluster #0 is the youngest and Cluster #1 is the oldest. Cluster labels are identified based on burst terms extracted from titles, abstracts, keywords of bibliographic records [ 26 , 41 ] . Table 10 demonstrates six predominant clusters by the number of members in each cluster.
Results show that the research priorities of the clusters keep changing during the observation period. From the earlier time (Cluster # 1), bitcoin and bitcoin network are the major priorities of researchers, then some researchers changed the focuses onto cryptocurrency in blockchain research. Notably, more researchers are most interested in blockchain technology and public ledger recently.
According to the characteristics of pivot nodes and landmark nodes in the co-citation article network. The landmark and pivot nodes in co-citation articles are shown in Figure 10 , Five pivot nodes are Nakamoto S [ 1 ] , Wood G [ 44 ] , Kosba A [ 51 ] , Eyal I [ 12 ] and Maurer B [ 55 ] . The main landmark nodes are Christidis K [ 45 ] . Swan M [ 2 ] , Zyskind G [ 48 ] Nakamoto S [ 1 ] , Kosba A [ 51 ] , Notably, some nodes can be landmark and pivot at the same time.
Landmark and pivot nodes, 2013–2019
Summary of the largest 6 blockchain clusters
ID | Size | Label (LLR) | Label (TF*IDF) | Label (MI) | Mean Year |
---|---|---|---|---|---|
0 | 36 | blockchain technology; service system; open issue; structured literature review; early standardization; blockchain application; blockchain research framework; future trend; health care application; blockchain. | internet; things; vehicular network; public ledger; pharmaceutics; eagriculture; urban sustainability; nudge theory; cyber-security; smart contract. | public ledger; security infrastructure; online dispute resolution; public/private key; attention-driven investment; speculative bubble; iot applications; unconditional frequency domain analysis; measurement; distributed agreement; waldwolfowitz test. | 2016 |
1 | 34 | bitcoin p2p network; risk scoring; bitcoin transaction; bitcoin; anonymity; bitcoin network; extracting intelligence; alternative monetary exchange; digital economy; bitcoin transversal; digital currencies. | cryptocurrency; virtual currency; digital money; mining pool; cryptocurrencies; supply; cryptocurrencies; double spending; electronic money; authorization; exchange rate. | blockchain technology; bitcoin p2p network; using p2p network traffic; public/private key; attention-driven investment; speculative bubble; unconditional frequency domain analysis; measurement; shangai stock market; central bank regulation. | 2012 |
2 | 27 | cryptocurrency market; industrial average; dow jone; bitcoin market; financial asset; systematic analysis; semi-strong efficiency; dynamic relationship; other financial asset; bayesian neural network; bitcoin price; blockchain information. | cryptocurrency; Markov chain monte carlo; non-linear time series models; vector autoregression; fluctuation behavior; investor attention; exact local whittle; random walk hypothesis; bsgvar model; google search volume index; cryptocurrencies. | public ledger; security infrastructure; online dispute resolution; public/private key; attention-driven investment; speculative bubble; iot applications; unconditional frequency domain analysis; measurement; distributed agreement. | 2015 |
3 | 20 | digital currencies; technical survey; scalable blockchain protocol; research perspective; off-blockchain bitcoin transaction; cooperative game; theoretic analysis; bitcoin mining pool; blockchain; bitcoin. | smart contracts; payment channels; orchestration; blockchain games; mining pool; asymmetric information; service resistance; client puzzles; emerging market currency; cryptocurrencies; digital currencies; consensus. | blockchain technology; distributed agreement; sharding; outlier; secure and correct systems; business process; orchestration; markets; choreography; jointcloud; anomaly; trustless. | 2014 |
4 | 19 | alternative monetary exchange; digital economy; bitcoin transversal; bitcoin; money; cryptocurrency; digital money; cloud mining; profitability; digital currencies; cryptocurrency. | cryptocurrency; digital currency; technology adoption; electronic payment; information share; price discovery; profitability; to-peer network; pedagogy; online dispute resolution; cryptocurrencies; digital currencies; consensus; profitability. | online dispute resolution; cost of transaction; arbitration; enforcement; public ledger; security infrastructure; public/private key; attention-driven investment; speculative bubble; iot applications; unconditional frequency domain analysis. | 2013 |
5 | 11 | a systematic review; current research; blockchain technology; bitcoin; tutorial; distributed consensus; altcoins; survey; digital currencies; blockchain; cryptocurrencies. | cryptocurrency; emerging market currency; emerging market transactions; fraud detection; rating fraud; reputation systems; smart contracts; blind signatures; off-chain transactions; scalability; emerging technologies; to-peer network; digital money; financial services. | blockchain technology; service system; open issue; structured literature review; bitcoin; early standardization; blockchain application; blockchain; cryptocurrency market; industrial average. | 2014 |
Details of the largest cluster (Cluster #0, top10)
Counts | First Author | Year | Publication Title | Source Title |
---|---|---|---|---|
214 | Christidis K ] | 2016 | Blockchains and smart contracts for the internet of things | IEEE Access |
187 | Swan M ] | 2015 | Blockchain: Blueprint for a new economy | O’Reilly |
119 | Zyskind G ] | 2015 | Decentralizing privacy: Using blockchain to protect personal data | IEEE Security and Privacy Workshops |
112 | Kosba A ] | 2016 | Hawk: The blockchain model of cryptography and privacy-preserving smart contracts | IEEE Symposium on Security and Privacy |
99 | Tschorsch F ] | 2016 | Bitcoin and beyond: A technical survey on decentralized digital currencies | IEEE Communications Surveys and Tutorials |
85 | Wood G ] | 2014 | Ethereum: A secure decentralized generalized transaction ledger | Ethereum Secure Decentralized |
77 | Radziwill N ] | 2018 | Blockchain revolution: How the technology behind bitcoin is changing money, business, and the world | The Quality Management Journal |
75 | Azaria A ] | 2016 | MedVec: Using blockchain for medical data access and permission management | International Conference on Open and Big Data (OBD) |
72 | Yli-Huumo J ] | 2016 | Where is current research on blockchain technology? — A systematic review | PLoS One |
71 | Narayanan A ] | 2016 | Bitcoin and cryptocurrency technologies: A comprehensive introduction | Bitcoin Cryptocurrency |
Details of the largest cluster (Cluster #1, top10)
Counts | First Author | Year | Publication Title | Source Title |
---|---|---|---|---|
115 | Nakamoto S ] | 2008 | Bitcoin: A peer-to-peer electronic cash system | - |
91 | Ron D ] | 2013 | Quantitative analysis of the full bitcoin transaction graph | International Conference on Financial Cryptography and Data Security |
90 | Meiklejohn S ] | 2013 | A fistful of bitcoins: Characterizing payments among men with no names | Internet Measurement Conference |
73 | Reid F ] | 2013 | An analysis of anonymity in the bitcoin system | International Conference on Social Computing |
56 | Miers I ] | 2013 | Zerocoin: Anonymous distributed e-cash from bitcoin | IEEE Symposium on Security and Privacy |
23 | Ober M ] | 2013 | Structure and anonymity of the bitcoin transaction graph | Future Internet |
22 | Moore T ] | 2013 | Beware the middleman: Empirical analysis of bitcoin-exchange risk | International Conference on Financial Cryptography and Data Security |
21 | Androulaki E ] | 2013 | Evaluating user privacy in bitcoin | International Conference on Financial Cryptography and Data Security |
20 | Barber S ] | 2012 | Bitter to better—How to make bitcoin a better currency | International Conference on Financial Cryptography and Data Security |
Details of the largest cluster (Cluster #2, top10)
Counts | First Author | Year | Publication Title | Source Title |
---|---|---|---|---|
97 | Böhme R ] | 2015 | Bitcoin: Economics, technology, and governance | Journal of Economic Perspectives |
80 | Cheah E T ] | 2015 | Speculative bubbles in bitcoin markets? An empirical investigation into the fundamental value of bitcoin | Economics Letters |
78 | Urquhart A ] | 2016 | The inefficiency of bitcoin | Economics Letters |
64 | Dyhrberg A H ] | 2016 | Bitcoin, gold and the dollar — A GARCH volatility analysis | Finance Research Letters |
62 | Ciaian P ] | 2016 | The economics of bitcoin price formation | Applied Economics |
60 | Kristoufek L ] | 2013 | BitCoin Meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the internet era | Scientific Reports |
57 | Dwyer G P ] | 2015 | The economics of bitcoin and similar private digital currencies | Journal of Financial Stability |
52 | Nadarajah S ] | 2017 | On the inefficiency of bitcoin | Economics Letters |
51 | Katsiampa P ] | 2017 | Volatility estimation for bitcoin: A comparison of GARCH models | Economics Letters |
49 | Bouri E ] | 2017 | Does bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions | Finance Research Letters |
As seen from Table 10 , Cluster #0 is the largest cluster, containing 36 nodes, for the sake of obtaining more information about these clusters, we explored the details of the largest clusters. Table 11 illustrates the details of the Cluster 0#.
We also explored Cluster #1 and #2 in more detail. Table 12 and Table 13 present the details of Cluster #1 and Cluster #2 respectively, it is notable that the most active citation in Cluster #1 is “bitcoin: A peer-to-peer electronic cash system”, and the most active citation in Cluster #2 is “bitcoin: Economics, technology, and governance”. The core members of Cluster #1 and Cluster #2 deliver milestones of blockchain research related to the bitcoin system and cryptocurrency.
Table 14 lists the first 10 most cited blockchain research articles indexed by the Web of Science. These articles are ranked according to the total number of citations during the observation period. Among these articles, the publication of “blockchains and smart contracts for the internet of things” by Christidis is identified as the most cited paper of 266 citations. The paper also has the highest average number of citations per year.
The top 10 cited blockchain articles
Rank | Title | First Author | Source Title | Year |
---|---|---|---|---|
1 | Blockchains and smart contracts for the internet of things | Christidis K ] | IEEE Access | 2016 |
2 | Decentralizing privacy: Using blockchain to protect personal data | Zyskind G ] | IEEE Security and Privacy Work- shops | 2015 |
3 | Hawk: The blockchain model of cryptography and privacy-preserving smart contracts | Kosba A ] | IEEE Symposium on Security and Privacy | 2016 |
4 | Bitcoin: Economics, technology, and governance | Böhme R ] | Journal of Economic Perspectives | 2015 |
5 | Bitcoin and beyond: A technical survey on decentralized digital currencies | Tschorsch F ] | IEEE Communications Surveys and Tutorials | 2016 |
6 | Zerocoin: Anonymous distributed e-cash from bitcoin | Miers I ] | IEEE Symposium on Security and Privacy | 2013 |
7 | Zerocash: Decentralized anonymous payments from bitcoin | Sasson E B ] | IEEE Symposium on Security and Privacy | 2014 |
8 | Majority is not enough: Bitcoin mining is vulnerable | Eyal I ] | Financial Cryptography and Data Security | 2014 |
9 | Sok: Research perspectives and challenges for bitcoin and cryptocurrencies | Bonneau J ] | IEEE Symposium on Security and Privacy | 2015 |
10 | The bitcoin backbone protocol: Analysis and applications | Garay J ] | International Conference on the Theory and Applications of Cryptographic Techniques | 2015 |
According to Callon, et al. [ 77 ] co-word analysis is a useful way of examining the evolution of science. In our study, among 2,451 articles related to blockchain, we obtained 4,834 keywords, 594 keywords appeared 3 times, 315 keywords appeared 5 times, and 130 keywords appeared 10 times. Table 15 presents the most important keywords according to frequency. As seen, ‘blockchain’ ranks first with an occurrence frequency of 1,105, followed by ‘bitcoin’ of 606. The other high occurrence frequency keywords include: ‘cryptocurrency’, ‘smart contract’, and ‘iot’ (internet of thing).
The top 25 keywords ranked by frequency
Rank | Frequency | Keywords | Rank | Frequency | Keywords |
---|---|---|---|---|---|
1 | 1105 | blockchain | 14 | 49 | trust |
2 | 606 | bitcoin | 15 | 50 | distributed ledger |
3 | 288 | cryptocurrency | 16 | 44 | thing |
4 | 270 | smart contract | 17 | 44 | model |
5 | 82 | iot | 18 | 49 | inefficiency |
6 | 149 | security | 19 | 44 | economics |
7 | 117 | internet | 20 | 44 | management |
8 | 110 | ethereum | 21 | 42 | system |
9 | 89 | privacy | 22 | 42 | digital currency |
10 | 78 | internet of thing | 23 | 40 | authentication |
11 | 60 | technology | 24 | 38 | network |
12 | 51 | volatility | 25 | 34 | consensus |
13 | 51 | blockchain technology |
For the sake of further exploration of the relation amongst the major keywords in blockchain research papers, we adopted the top 315 keywords with a frequency no less than 5 times for co-occurrence network analysis. The keywords co-occurrence network is illustrated in Figure 11 . In a co-occurrence network, the size of the node represents the frequency of the keywords co-occurrence with other keywords. The higher the co-occurrence frequency of the two keywords, the closer the relationship between them.
The keywords co-occurrence network, 2013–2019
We can see from Figure 11 , the size of blockchain and bitcoin are the largest among all keywords. This means, in general, blockchain and bitcoin have more chances to co-occurrence with other keywords. Besides, blockchain is closer with a smart contract, iot, Ethereum, security, internet, and privacy, whereas bitcoin is closer with digital currency and cryptocurrency.
Figure 12 displays the time-zone view of co-cited keywords, which puts nodes in order from left to right according to their years being published. The left-sided nodes were published in the last five years, and on the right-hand side, they were published in recent two years. Correspondingly, some pivot nodes of keywords are listed in the boxes. We hope to show the evolution of blockchain in general and the changes of focuses in blockchain study.
The time-zone view of co-cited keywords, 2013–2019
The results suggest that, in 2013, when blockchain research begins to surface, bitcoin dominated the blockchain research field. Reasonably, the bitcoin is the first cryptocurrency based on blockchain technology, and the influential essays include quantitative analysis of the full bitcoin transaction graph [ 54 ] ; a fistful of bitcoins: Characterizing payments among men with no
names [ 50 ] ; and bitcoin meets google trends and Wikipedia: Quantifying the relationship between phenomena of the internet era [ 69 ] . Afterward, as various altcoins appeared, cryptocurrency and digital currency are widely discussed in blockchain-related research. The high-citation article is Zerocash: Decentralized anonymous payments from bitcoin [ 74 ] and privacy, which is the prominent characteristic of cryptocurrency. In 2015, blockchain and smart contract become a hotspot, the core publications include blockchain: A blueprint for a new economy [ 2 ] ; decentralizing privacy: Using blockchain to protect personal data [ 48 ] ; at the same time, some researchers also focus on the volatility and mining of cryptocurrency. In 2016, a growing number of researchers focus on the internet of things. The most popular article is blockchains and smart contracts for the internet of things [ 45 ] . In 2017, distributed ledger and blockchain technology become a research focus point. From 2018 onward, research focus on the challenge, and the inefficiency of blockchain appear.
Based on all 2451 funding sources we analyzed in this study, the National Natural Science Foundation of China (NSFC) has supported the biggest number of publications with 231 papers, followed by the National Key Research and Development Program of China, which supported the publication of 88 papers. Comparatively, the National Science Foundation of the USA has only supported 46 papers. It is remarkable that the “Ministry of Science and Technology Taiwan” supported 22 papers, which is more than the European Union. Table 16 illustrates the top 20 funding agencies for blockchain research ranked by the number of supported papers. The results indicate that China is one of the major investing countries in Blockchain research with the biggest number of supporting articles.
The top 20 funding agencies of blockchain-related research
Rank | Counts | Funding Agencies |
---|---|---|
1 | 231 | National Natural Science Foundation of China (NSFC) |
2 | 88 | National Key Research and Development Program of China |
3 | 46 | National Science Foundation (USA) |
4 | 26 | Fundamental Research Funds for the Central Universities (China) |
5 | 22 | “Ministry of Science and Technology Taiwan” |
6 | 14 | European Union |
7 | 10 | China Scholarship Council |
10 | 10 | JSPS KAKENHI (Japan) |
8 | 9 | China Postdoctoral Science Foundation |
9 | 8 | Beijing Natural Science Foundation |
11 | 6 | Young Elite Scientists Sponsorship Program by Tianjin |
12 | 6 | Natural Science Basic Research Plan in Shaanxi Province of China |
13 | 6 | Air Force Material Command (USA) |
14 | 5 | National Research Foundation of Korea (NRF) — Korea government (MSIP) |
15 | 4 | Students Foundation |
16 | 4 | Natural Science Foundation of Jiangsu Province |
17 | 4 | Guangdong Provincial Natural Science Foundation |
18 | 4 | Russian Science Foundation |
19 | 4 | Singapore MOE Tier 1 |
20 | 4 | Science and Technology Planning Project of Guangdong Province |
5.1 conclusions.
This research comprehensively investigates blockchain-related publications based on the Web of Science Core Collection and provides a quick overview of blockchain research. In this study, a coherent comprehensive bibliometric evaluation framework is adopted to investigate the hot and promising blockchain domain. We outline the core development landscape of blockchain, including the distribution of publications over time, by authors, journals, categories, institutions, countries (territories), intellectual structure, and research trends in the blockchain academic community. Combining the results of statistical analysis and co-cited articles, authors, and keywords, we formulate the answers to the following research questions:
RQ1 What is the distribution pattern of blockchain publications and citations over recent years?
The published blockchain papers significantly increased since 2013, when the first blockchain paper was published. An increasing number of articles were published since. In 2018, 1,148 articles were published at the peak, and the number of publications is likely to continuously grow. As for the cumulative number of citations, there were only 272 citations in 2013. By 2018 this number has grown to more than 10,000, which implies a widespread influence and attention attracted by blockchain study in recent years.
RQ2 Which are the main international contributing countries (regions) and institutions in blockchain research, as well as collaboration networks among them?
A total of 97 countries (regions) participated in blockchain research during the observation period. USA and China play the leading roles among all countries (regions), with publications of 532 (20.94%) and 489 (19.24%) articles respectively, followed by the UK, Germany, Italy, and Australia. From the aspect of citations, USA-authored papers were cited by 1,810 papers with 3,709 (36.57%) citations, accounting for 36.57% of total citations. Articles from the USA also have a very high average number of citations per paper with a frequency of 6.97. Although the number of articles from China is close to the USA, the average number of citations per paper is lower with a frequency of 2.78. The results indicate that the USA is the most influential country in the field of blockchain.
A total of 2,190 institutions participated in blockchain-related research. Among them, the Chinese Academy of Sciences has the highest number of publications with 43 papers, followed by the University of London, Beijing University of Posts Telecommunications, University of California System, Commonwealth Scientific Industrial Research Organization (CSIRO), Beihang University, University of Texas System, ETH Zurich. In respect of the number of total Times Cited and the average number of Times Cited, Cornell University is cited the most with 499 citations, and the average number of Times Cited is 20.79. followed by the Massachusetts Institute of Technology, University of California System, and ETH Zurich. The number of publications forms institutions in China is large, whereas few papers own high average Times Cited.
In terms of collaboration networks among different institutions, we found that the Chinese Academy of Sciences, Cornell University, Commonwealth Scientific Industrial Research Organization (CSIRO), University of Sydney, and ETH Zurich cooperated widely with other institutions.
RQ3 What are the characteristics of the authorship distribution?
The total number of authors who contribute to the publications of blockchain is 5,862. the average number of authors per paper is 2.4. Among 5,862 authors, 4,808 authors have only one paper, 662 authors have two papers, and 213 authors have three papers. Based on the number of participated papers, the most productive author in the field of blockchain is Choo, Kim-Kwang Raymond from Univ Texas San Antonio, who participated in 14 articles in the field of blockchain, followed by Marchesi M, Bouri E, David R, Miller A, Shetty S and Xu X.
RQ4 What are the core blockchain subjects and journals based on the number of publications?
Blockchain-related researches are more abundant in the field of Computer Science compared with other categories. Other major fields include Engineering, Business & Economics, Telecommunications, and Business & Economics.
RQ5 What are the major journals or conferences for blockchain-related research?
The research of blockchain is published in 1,206 journals (conferences), the major blockchain research journals include Lecture Notes In Computer Science, IEEE Access, Economics Letters, Future Generation Computer Systems, and Finance Research Letters. Meanwhile, the major blockchain research conferences include IEEE International Conference on Hot Information-Centric Networking, International Conference on Parallel and Distributed Systems Proceedings, International Conference on New Technologies Mobility and Security, and Financial Cryptography and Data Security.
RQ6 What are the most influential papers in blockchain research based on the number of citations?
Ranked by the total number of citations during the observation period, the publication: “blockchains and smart contracts for the internet of things” by Christidis and Devetsikiotis [ 45 ] is identified as the most cited paper with 266 citations, which also has a highest average number of citation per year, followed by decentralizing privacy: Using blockchain to protect personal data [ 48 ] with 169 citations and 33.80 average number of citations per year.
According to the number of times co-cited, the top five influential publications are as follows: Bitcoin: A peer-to-peer electronic cash system [ 1 ] , A next-generation smart contract and decentralized application platform [ 42 ] , Majority is not enough: Bitcoin mining is vulnerable [ 12 ] , Ethereum: A secure decentralised generalised transaction ledger [ 44 ] , Blockchain: Blueprint for a new economy [ 2 ] .
RQ7 Who are the most influential authors in blockchain research according to the author co-citation network?
Some authors played a crucial role during the development of blockchain research, Nakamoto S, as the creator of Bitcoin, and the author of the bitcoin white paper, created and deployed bitcoin’s original reference, therefore is not surprised at the top of the co-citation count ranking and got 1,202 citations in our dataset. Buterin V, a Russian-Canadian, programmer, and writer, primarily known as a co-founder of Ethereum and as a co-founder of Bitcoin Magazine who follows Nakamoto S and receives 257 citations. Other core authors with high citations include Eyal I, Wood G, Swan M, Christidis K, Bonneau J, Szabo N, Zyskind G, Castro M, and Meiklejohn S.
According to co-cited articles clusters, the research priorities in blockchain-related research keep changing during the observation period. Bitcoin and bitcoin network are the main priorities of researchers, then some researchers changed to focus on cryptocurrency in blockchain research.
RQ8 What are the research trends of blockchain?
The research priorities in blockchain-related research evolve during the observation period. As early as 2013, when the research on blockchain first appears, bitcoin dominated the blockchain research field. Then only one year later, as various altcoins begin to appear, cryptocurrency and digital currency are widely discussed in blockchain-related research. In 2015, blockchain and smart contracts become a hotspot till 2016 when a growing body of researches begin to focus on the internet of things. In 2017, distributed ledger and blockchain technology become the research focal point. From 2018 onward, research focus on the challenge and inefficiency of blockchain.
RQ9 What are the most supportive funding agencies of blockchain research?
The most supportive funding agency of blockchain research is the National Natural Science Foundation of China (NSFC) which has supported the publication of 231 papers. The results indicate that China is one of the major investing countries in Blockchain research with the biggest number of supporting articles.
Given the potential power of blockchain, it is noticeable that governments, enterprises, and researchers all pay increasing attention to this field. The application of blockchain in various industries, the supervision of cryptocurrencies, the newly rising central bank digital currency and Libra, are becoming the central issues of the whole society.
In our research, we conducted a comprehensive exploration of blockchain-related research via a bibliometrics analysis, our results provide guidance and implications for academic research and practices. First, the findings present a holistic view of research in the blockchain domain which benefits researchers and practitioners wanting to quickly obtain a visualized overview of blockchain research. Second, according to our findings of the evolution and trends in blockchain research, researchers could better understand the development and status of blockchain, which is helpful in choosing valuable research topics, the distributed ledger, the discussions on the inefficiency and challenges of blockchain technology, the supervision of cryptocurrencies, the central bank digital currency are emerging research topics, which deserve more attention from the academic community.
As with any research, the design employed incorporates limitations that open avenues for future research. First, this study is based on 2,451 articles retrieved from the Web of Science of Core Collection, although the Web of Science of Core Collection is truly a powerful database for bibliometric analysis, we can’t ignore the limitation brought by a unique data source. Future research can deal with this limitation by merging the publications from other sources, for instance, Scopus, CNKI, as well as patent database and investment data of blockchain, and it could help to validate the conclusion. Second, we mainly adopt the frequency indicator to outline the state-of-the art of blockchain research, although the frequency is most commonly used in the bibliometric analysis, and we also used H-index, citation to improve our analysis, some other valuable indicators are ignored, such as sigma and between centrality, therefore, it’s beneficial to combine those indicators in future research. Besides, it should be noted that, in co-citation analysis, a paper should be published for a certain period before it is cited by enough authors [ 26 ] , the newest published papers may not include in co-citation analysis, it’s also an intrinsic drawback of bibliometric methods.
Supported by the National Natural Science Foundation of China (71872171), and the Open Project of Key
Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences
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Iqbal earns runner-up in privacy tech award
A research paper by Umar Iqbal, an assistant professor of computer science and engineering in the McKelvey School of Engineering at Washington University in St. Louis, has been named runner-up for the Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies.
The award is presented annually to researchers who have made an outstanding contribution to the theory, design, implementation or deployment of privacy-enhancing technologies. It is awarded at the annual Privacy Enhancing Technologies Symposium.
Iqbal’s paper, “ Tracking, profiling, and ad targeting in the Amazon smart speaker ecosystem ,” was first presented at the ACM Internet Measurement Conference in Montreal in October, where it received the best paper award. The paper provided insight into what information is captured by smart speakers; how it is shared with other parties; and how it is used by such parties, allowing consumers to better understand the privacy risks of these devices and the impact of data sharing on people’s online experiences.
After the release of this research, Amazon updated its disclosure to include that it uses smart speaker interaction data to infer user interests for the purposes of ad targeting, which was initially not disclosed.
Originally published on the McKelvey Engineering website
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22 Pages Posted: 24 Jul 2024 Publication Status: Under Review
Shandong Academy of Medical Sciences
Objectives To analyzes global research trends in tricuspid regurgitation (TR) from 2010 to 2023 and explore hot topics in this field. Methods We reviewed the literature on TR from January 1, 2010 to December 31, 2023 using the Web of Science Core Collection (WoSCC) database, and the main type of literature was articles. Data on countries, organizations, authors, journals, etc., from which the literature originated were collected, processed and visualized using "bibliometrics" and VOSviewer software. Results From 2010 to 2023, we retrieved a total of 4,662 publications from the WOSCC database, and we found that a total of 100 countries, 4,572 affiliates, and 23,283 researchers were involved in this field of research. The countries with the most publications in this field is the United States, the most active institution is the Mayo Clinic, and the author who has made the most contributions is Bax JJ. TR related studies were most often published in the Journal of Thoracic and Cardiovascular Surgery. The keywords formed four clusters: (1) etiology of TR, (2) pathogenesis of secondary TR, (3) grading of TR severity, and (4) treatment of TR. Conclusions Using bibliometric analysis, this study summarized information on scientific publications on TR research from 2010 to 2023, providing global research trends in TR research.
Note: Funding declaration: This work was supported by the Natural Science Foundation of Shandong Province (ZR2022MH142). Conflict of Interests: The authors have no conflicts to disclose.
Keywords: valve disease, Bibliometric, Valve regurgitation, Tricuspid regurgitation, visualization
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If you're just starting out exploring blockchain-related topics for your dissertation, thesis or research project, you've come to the right place. In this post, we'll help kickstart your research by providing a hearty list of research topics and ideas related to blockchain and crypto, including examples from recent studies.. PS - This is just the start…
Abstract. Blockchain technology has emerged as a transformative force across various industries. This paper delves into the core concepts of blockchain, exploring its decentralized architecture ...
Blockchain-Empowered Fair Computational Resource Sharing System in the D2D Network. Zehua (David) Wang, Zhen Hong, Wei Cai. November 16, 2017. Read the Research Paper. Blockchain@UBC has published a number of research papers, through various academic partners and collobarative efforts. Explore more in detail through the list on this page.
In this session, we analyzed their published journals, research topics, citations, and so on, to depict the research status of blockchain in the field of business and economics more comprehensively. There are several review papers on blockchain. Each of these paper contains a summary of multiple research topics, instead of a single topic.
Blockchain technology research and application: a systematic literature review and future trends. iew and future trendsMin An, Graduate Student Member, IEEE, Qiyuan Fan, Hao Yu and Haiyang ZhaoAbst. act—Blockchain, as the basis for cryptocurrencies, has received extensive attentions recently. Blockchain serves as an immutable distributed ledger.
A bibliometric analysis is used to summarize large quantities of data to understand the intellectual landscape of a given field ("Subject and Course Guides: Bibliometric Analysis and Visualization: Bibliometrics," 2022). In this paper, the analysis will yield emerging trends in academic documents on blockchain-based payment systems.
Off-chain storage has the advantages of faster efficiency, lower cost, and higher privacy, but it is difficult for off-chain data to take advantage of the blockchain trust. A key research direction in the future is to closely integrate the on-chain and off-chain data so that the trust on the chain can be mapped to the off-chain data. 8.2.
This research provides an up-to-date and systematic understanding of blockchain's theoretical potential, pros, and cons for the real estate sector. The research aims to understand why and where to apply blockchain in real estate by conducting a systematic review that identified 296 relevant documents and performed a thematic content analysis.
Second, we probe the key research topics of blockchain study, for which purpose, we conduct keyword co-occurrence analysis. Third, we picture the intellectual structure of blockchain study based on co-citation analysis ... The research papers focus on the blockchain are quite abundant and are continuing to emerge. Among a host of papers, a few
Our research synthesizes and analyses extant articles that focus on blockchain-related perspectives which will potentially play an important role in sustainable development in the world. Blockchain applications and future directions always attract more attention.
The following 10 blockchain research topics could be helpful while pursuing your PhD studies: The effects of bitcoin regulation on the reduction of drug trafficking. Anti-money laundering legislations to prevent, detect and prosecute cryptocurrency-driven money laundering. The ease of tracing hacked bitcoins.
Even though, for most industries, blockchain is still a new and not yet well-established technology, the World Economic Forum estimates that, by 2025, at least 10% of global gross domestic product (GDP) will rely on blockchains. And, by 2030, blockchains will have created $3.1tn in business value ( Panetta, 2018 ).
In this paper, we use a Delphi approach to investigate whether, and to what extent, blockchain-based applications might affect firms' organizations, innovations, and strategies by 2030, and, consequently, which societal areas may be mainly affected. We provide a deep understanding of how the adoption of this technology could lead to changes in Europe over multiple dimensions, ranging from ...
Therefore, the research topics on Blockchain technology undertaken in 2022 may relate to the above-mentioned issues of improving cybersecurity techniques, possibly including combining Blockchain ...
In terms of technology, a blockchain is a list of records, each of which is formed into a block and contains information, a cryptographic hash, about the previous block. Blockchain Technology Importance and Advantages. The first source has a candid tone due to the presentation of unreserved and straightforward information on the use of ...
This paper's goal is to analyze the benefits of blockchain in big data as well as its drawbacks and identify potential future approaches. References [1] A. Adadi, ... Recent research and experiments in the field of Internet of Things (IoT) security have found that these devices are vulnerable to various attacks, ranging from cyber-attacks to ...
Numerous research articles employing blockchain technology have been published. Table 9 showcases a curated selection of blockchain articles specifically centered on healthcare. The authors' contributions, benefits of utilizing blockchain technology, research limitations, and the tools employed for conducting the research were deliberated upon.
The iPhone maker, citing a research paper by Yohan Beugin and Patrick McDaniel from University of Wisconsin-Madison, claims Topics aids digital fingerprinting that could be used by advertisers to ...
Blockchain has been receiving growing attention from both academia and practices. This paper aims to investigate the research status of blockchain-related studies and to analyze the development and evolution of this latest hot area via bibliometric analysis. We selected and explored 2451 papers published between 2013 and 2019 from the Web of Science Core Collection database.
The paper provided insight into what information is captured by smart speakers; how it is shared with other parties; and how it is used by such parties, allowing consumers to better understand the privacy risks of these devices and the impact of data sharing on people's online experiences.
The launch of NASA's James Webb Space Telescope (JWST) in 2021 kicked off an exciting new era for exoplanet research, especially for scientists looking at terrestrial planets orbiting stars other than our sun. But three years into the telescope's mission, some scientists have run into challenges that have slowed down progress.
Research and statistics. Reports, analysis and official statistics. Policy papers and consultations. Consultations and strategy. Transparency. Data, Freedom of Information releases and corporate ...
Abstract. Objectives To analyzes global research trends in tricuspid regurgitation (TR) from 2010 to 2023 and explore hot topics in this field. Methods We reviewed the literature on TR from January 1, 2010 to December 31, 2023 using the Web of Science Core Collection (WoSCC) database, and the main type of literature was articles.