A bibliometric review of cryptocurrencies: how have they grown?

Abstract and Figures

With the development of new technologies, some concepts become relevant in the economic area, as is the case with cryptocurrencies, in general, or Bitcoin and Ethereum, in particular. Due to the impact of these tools, a detailed bibliometric study that allows us to obtain all information about cryptocurrencies must be conducted. This study will help scientific production by specifying the development and lines of related research that have been followed and are currently being followed. We have used Tableau, R (Bibliometrix R Package), and VOSviewer software to analyze the information. These have been combined to create and review unified metadata from the Web of Science (WoS) and Scopus databases. The bibliometric analysis shows 771 articles on the WoS database and 648 articles on Scopus published between 2010 and early 2019. They present the most relevant articles, research areas, countries, institutions, authors, journals, and trends during the last few years. In conclusion, the number of publications has grown in the last 3 years. The analysis shows the evolution of blockchain technology used in this type of cryptocurrency. The review of this period marks a possible end to the historical part of cryptocurrencies, thereby opening the current topic to its multiple applications.
Content may be subject to copyright.
A bibliometric review ofcryptocurrencies:
howhave they grown?
Francisco Javier García‑Corral1* , José Antonio Cordero‑García2, Jaime de Pablo‑Valenciano3 and
Juan Uribe‑Toril3
In the last decade, secondary payment methods other than legal tender have been
developed to boost the market (Corrons 2017). Lietaer and Hallsmith (2006) defined
one of these payment mechanisms as an agreement to use more than just legal tender
as a means of exchange to link unused sources to unmet needs. In particular, a series
of complementary currencies incorporated into the economic world are mentioned.
Although these new supplementary payment methods are not listed in any global
database, more than 6000 types are presumed to exist. Among them, new electronic
payment methods have recently been incorporated, including virtual currencies or cryp-
tocurrencies. Although complementary currencies have been used for a longer period,
by historical amount and weight, the central focus of this study is the most innovative
With the development of new technologies, some concepts become relevant in
the economic area, as is the case with cryptocurrencies, in general, or Bitcoin and
Ethereum, in particular. Due to the impact of these tools, a detailed bibliometric study
that allows us to obtain all information about cryptocurrencies must be conducted.
This study will help scientific production by specifying the development and lines
of related research that have been followed and are currently being followed. We
have used Tableau, R (Bibliometrix R Package), and VOSviewer software to analyze the
information. These have been combined to create and review unified metadata from
the Web of Science (WoS) and Scopus databases. The bibliometric analysis shows 771
articles on the WoS database and 648 articles on Scopus published between 2010 and
early 2019. They present the most relevant articles, research areas, countries, institu‑
tions, authors, journals, and trends during the last few years. In conclusion, the number
of publications has grown in the last 3 years. The analysis shows the evolution of block‑
chain technology used in this type of cryptocurrency. The review of this period marks
a possible end to the historical part of cryptocurrencies, thereby opening the current
topic to its multiple applications.
Keywords: Cryptocurrency, Bitcoin, Ethereum, Bibliometric analysis, Business and
Open Access
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García‑Corraletal. Financial Innovation (2022) 8:2‑021‑00306‑5
Financial Innovation
1 Research Group: Almeria
Group of Applied Economy
(SEJ 147), University
of Almeria, Carretera
Sacramento s/n, 04120, La
Cañada de San Urbano,
Almería, Spain
Full list of author information
is available at the end of the
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García‑Corraletal. Financial Innovation (2022) 8:2
A broad spectrum of terminology are coined to differentiate between these crypto-
currencies, ranging from virtual complementary currency to electronic currency and its
derivative, cryptocurrency (Dai 1998). e first currency to become popular was Bitcoin,
which was founded in 2008 by Satoshi Nakamoto. Although previous attempts at virtual
currencies, such as E-gold in 1996 or Liberty Reverse in 2006, have been made, Bitcoin
was the first to exist in the global socio-economic sphere (Garcia etal. 2014).
During these cryptocurrencies’ short period of existence, they have been and are stud-
ied by a wide variety of disciplines, as they incorporate a number of innovative tech-
nologies, such as blockchain, cryptography, and smart contracts (Xu etal. 2019). Several
studies have characterized cryptocurrencies as having a volatile future (Urquhart 2016;
Katsiampa 2017; Chu etal. 2017; Conrad etal. 2018; Bouri etal. 2019) and initially pre-
sented them as non-perishable albeit secure. However, these promising technologies
have kept them (Zheng etal. 2018; Zulfiqar and Gulzar 2021). e globalization process
to which they are subjected, together with the lack of legal regulation, indicate that they
have been used in multiple forms as the primary component (Gomá-Garcés 2014; Zim-
mer 2017). ey are also the subject of much discussion and debate by entities, such as
the European Central Bank (2012) seeking to better define them as a means of exchange
and a unit of value accepted by a virtual community.
is article aims to contribute to the extant literature by conducting a bibliometric
analysis of the main currencies, as the number of publications on this subject is increas-
ing. erefore, a review of the materials published in this interdisciplinary area must
be incorporated. Moreover, this methodology is applied in multiple areas of knowledge
from the mapping analysis of bibliographic information obtained from high-impact
First, we will focus on Bitcoin and Ethereum as the main currencies and the concept
of cryptocurrency. e results obtained are intended to inform about a specific field of
study and its evolution and productivity. In addition, they help identify, analyze, and
organize the main elements of the search focus to show the evolution of trends in the
subject. Finally, the results seek to establish whether major changes occur in the lines of
research to determine whether the theoretical part is more irrelevant. In this case, the
new lines of research will be more practical, changing their orientation and making the
previous publications more historical-theoretical.
is method has been used in several studies with similar themes. However, unlike
previous studies (Table1), the present study considered three keywords, along with a
new temporal division in the discussion. Exclusively and to increase the importance of
this article, this study will include the results of “cryptocurrency, Bitcoin and Ethereum,
thus covering a broader index of results with economic topics from the Web of Science
(WoS) and Scopus databases. is differentiates it from the works related to blockchain
only as a concept that does not come into discussion, from those that analyze Bitcoin
only (e.g., Merediz-Sola etal. 2019; Orastean etal. 2019; Shen etal. 2020), or those that
only examine one database (Dabbagh etal. 2019).
is study begins with an introduction and a literature review on alternative forms
of payment and their different concepts and interpretations. en, it explains which
selected payment systems have the greatest impact. e methodology of the bibliomet-
ric analysis and the sources used to extract the data during the search process are then
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García‑Corraletal. Financial Innovation (2022) 8:2
presented. Subsequently, the results are presented independently, followed by a discus-
sion on the future of these tools with more up-to-date data until 2020. Finally, the last
section concludes with both definitive comments and potential research streams from
the data analysis.
The concept
Cryptocurrencies are a form of digital exchange that ensures that transactions are made
through a robust encryption process, which, in turn, controls the number of stocks (Luu
etal. 2016). is is a recent phenomenon gaining momentum in a volatile and fluctuat-
ing economic world (Ciaian etal. 2016) and has experienced significant growth, despite
not being considered an official form of debt cancellation (Dwyer 2015). Due to the
decentralized nature of cryptocurrencies, they cannot be used as a substitute for legal
currency (Nakamoto 2008) even if they were created to be used as such, thus making
them an unconventional currency. e creation and management of currencies are con-
trolled by non-governmental entities (Kim 2015); hence, although they are considered a
promising alternative for the future, they have various detractors who prefer to use them
as a form of speculation (Baur etal. 2018; Krugman 2018; Zhang etal. 2021). e decen-
tralized structure without regulated activity makes them a novel option to the traditional
financial system (Franco 2014). us, although they start from a totally negative configu-
ration, they have a series of advantages: cheaper transaction costs due to the absence of
Table 1 Comparison with previous studies
Source: Own compilation
Diferences This Paper A
of bitcoin
etal. (2019)
Bitcoin In
The Scientic
etal. (2019)
of Bitcoin:
a network
and concept
Shen etal.
The Evolution
of Blockchain:
a Bibliometric
Dabbagh etal.
Data base WoS * * * *
Scopus * *
Keywords Bitcoin * * * * *
Ethereum * *
rency * *
and citation
* * * * *
Research Area * * * * *
Country * * *
Institutions * *
Journals * * * *
Authors * * * *
Trends * * * *
Discussion * *
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García‑Corraletal. Financial Innovation (2022) 8:2
intermediaries; reduction of transaction times as these are carried out via the Internet;
the suppression of intermediaries as unnecessary financial agents in this series of trans-
actions; or their globality (Kostakis and Giotitsas 2014; Koblitz and Menezes 2016).
In addition, individuals have freedom to develop this type of currency; consequently,
multiple currencies have been created for specific purposes (Kondor etal. 2014) and
have become standard payment mechanisms (Fabian 2016). ey are used globally in
a society that views its transactions between direct parties and perceives them as being
more straightforward and negotiable because monetary conversion is not needed (Kris-
toufek 2013).
Privacy andsecurity
Originally, virtual currencies emerged as a means of digital exchange that guaranteed
their security, integrity, and balance due to a higher level of protection created by users.
In exchange for compensation, these individuals help with security work by processing
algorithms (Van Alstyne 2014; Urquhart 2018). at is, the security mechanisms of this
payment method arise from the users themselves who maintain and protect the base
fabric by providing computing power (Böhme etal. 2015). Mathematically speaking, the
security of an electronic currency or the blockchain can be compromised, but the cost
required to achieve this would be high, depending on the algorithm and its creation pro-
tocol (Xu 2016; Khan and Salah 2018; Zhang etal. 2019).
Transactions carried out with these currencies are direct between users and generally
anonymous (Miers etal. 2013), compared with those carried out with legal currency in
which payments are made through banking networks. erefore, anonymity has been
a key factor since their very inception (Ober etal. 2013). Although the development of
cryptocurrency has not always been equal and not all types of cryptocurrencies operate
the same, the complexity of violating anonymity is equal to the breach of their secu-
rity (Wang etal. 2018). Privacy and protection are mechanisms that, although consid-
ered strong, need to be improved to add new functionality as they progress in their use
because their standardization makes them attractive to hackers (Conti etal. 2018; Feng
etal. 2019).
Blockchain setup andmaintenance
Electronic currencies are created through mining, an incentive process in which trans-
actions are verified and new units are created and added to the core of existing ones
(Eyal and Sirer 2013). e miners are responsible for collecting the latest transactions
into blocks and finding a solution to the algorithm of each currency. As a reward, a
fixed amount of that currency is acquired by these miners (Böhme etal. 2015; Bonneah
etal. 2015). e solution to the algorithm changes continually and depends on previous
results to perform the next calculation in the sequence. is means that, as time goes by,
the difficulty in finding a solution will become greater, and its cost increases (Eyal and
Sirer 2013; Giungato etal. 2017). us, the process has been affected because the invest-
ment cost does not exceed the profits offered (Kristoufek 2015; Cocco and Marchesi
All the information related to the cryptocurrency is recorded on the blockchain, a
digital book shared on the network and responsible for collecting all the transactions
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García‑Corraletal. Financial Innovation (2022) 8:2
carried out with the cryptocurrency in two parts (i.e., input and output) (Franco 2014).
ese exchanges or transactions are called blocks and are encoded and linked with oth-
ers (Böhme etal. 2015). Blockchain information is stored on participating devices and is
open access (Zyskind etal. 2015), making the exchange process transparent and immune
to modifications (unalterable) (Brandvold etal. 2015). Once the data are verified, they
can no longer be edited without the community’s consent. is recent technology in
cryptocurrencies can be used for multiple purposes (Sikorski etal. 2017; Kuo etal. 2017;
Lee 2017) and is one of the most dynamic elements of the economy (Yin etal. 2017).
Due to the simplicity of use (Selgin 2013) and the lack of regulation, particularly con-
cerning taxation (Follador 2017), virtual currencies have been linked to numerous
unregulated activities, including criminal acts, and may contribute to further price
distortion (Barratt etal. 2013; Hardy and Norgaard 2016; Foley etal. 2019; Griffin and
Shams 2020). Another problem with these currencies is their high level of volatility,
losses, and a lack of widespread acceptance among the general public, which could indi-
cate their inefficiency (Nadarajah and Chu 2017; Klein etal. 2018). Although volatility
can mean both a risk and an opportunity (Brière etal. 2013), it is an intrinsic part of
the currency (Bariviera 2017) and virtually impossible to predict (Balcilar etal. 2017).
Recent studies have found that short-term bubbles limit the ability to profit from these
tools; however, investments in these currencies are not limited, leaving only conjectures
about obtaining economic benefits (Li etal. 2018). e continuous variations and col-
lapse in the exchange of distributed volume generate large fluctuations in prices (Navas-
Navarro 2015; Polaski etal. 2015) that denote the inefficiency of this market (Urquhart
2016; Zhang etal. 2018; Neslihanoglu 2021). It is an exchange mechanism whose real
value starts from zero (Van Alstyne 2014; Cheah and Fry 2015). Although their perma-
nence is currently being discussed as a matter of general interest, research has posited
that the life cycle of cryptocurrencies increases, as they stabilize (Bariviera etal. 2017).
The market andtheprotocols
Many virtual currencies have currently been given a relative value, based on different
variables, to the different legal tender currencies (Table2). All belong to a version of
Table 2 Digital Currency by market value (July 2021)
Source: Own compilation. Data collected from CoinMarketCap
Position Name Market cap Price Shares in circulation
1 Bitcoin $750,600,171,509 $39,959.72 18,770,200 BTC
2 Ethereum $271,733,293,394 $2,325.39 116,889,042 ETH
3 Tether $61,828,690,396 $1.00 61,796,971,748 USDT
4 Binance Coin $52,857,378,310 $314.44 168,137,036 BNB
5 Cardano $41,218,509,234 $1.29 32,065,792,346 ADA
6 XRP $32,843,217,941 $0.7071 46,312,443,360 XRP
7 USD Coin $27,363,663,734 $1.00 27,354,066,325 USDC
8 Dogecoin $26,668,380,056 $0.2044 130,639,341,482 DOGE
9 Polkadot $14,779,410,550 $15.10 979,197,585 DOT
10 Binance USD $12,228,250,268 $1.00 12,224,571,047 BUSD
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the protocol, depending on their application. us, we find that Bitcoin uses version
1.0 of the blockchain, whereas other alternatives, such as Ethereum, use version 2.0.
e latest version, called version 3.0, is part of an extension of the applications used.
Bitcoin and Ethereum have been chosen as the most relevant currencies based on
their original protocols, which share several characteristics, such as mining or their
structure; however, differences also exist between them (Table3).
Bitcoin is the pioneering platform of the blockchain concept based on a peer-to-
peer exchange that does not rely on traditional transaction schemes in which central
authorities or banks carry out transactions. Bitcoin can be defined as a form of cryp-
tocurrency or payment system based on cryptographic evidence whose unit is bitcoin
(Nakamoto 2008) and has unique characteristics that have defined the properties of
these currencies (Phillip etal. 2018). Having evolved from the Blockchain 1.0 proto-
col, Bitcoin is currently the most valuable and central axis of cryptocurrency studies
(Jang and Lee 2018). However, it has shared its weight with those of recent creation.
Meanwhile, Ethereum is an open-source, decentralized platforms whose purpose
is to create the most significant smart contract agreements (Luu etal. 2016). It is a
framework for the execution of contracts and useful automated computer applica-
tions (Bhargavan etal. 2016), without the need to trust third parties. It is currently
considered one of the most complex networks under review. We have chosen to ana-
lyze Ethereum in this study because it is one of the pioneering and most stable cryp-
tocurrencies 2.0.
Research methodology
e bibliometric analysis is responsible for reviewing different bibliographic material
to organize the relevant information on a specific topic. It is also a way of presenting
scientific publications that seek to assess the status of a given topic and the quality
and influence of authors and sources (Van Raan 2014).
Table 3 Comparison between Bitcoin and Ethereum
Source: Own compilation
Bitcoin Ethereum
Concept Bitcoin is both a currency and a digital pay‑
ment system The Ethereum network is based on distributed
ledger technology (DLT) or blockchain
Launch Date 31st of October 2008, date of publication of
White Paper December 2013
Form Cryptocurrency Cryptocurrency
Base Blockchain Blockchain
Ticker bitcoin (BTC) ether (ETH)
Purpose Payment System Allows execution of Smart contracts Contracts
and decentralized applications by means of
writing lines of code
Design Virtual Currency Token
Supply Mining
Recompense is based on validation of blocks Mining
Validation of blocks, transactions or contracts
In circulation 21 million bitcoin in total 18 million per year
Other Used like any other fiat currency Includes supplementary fees for “gas”
Only works within its own network
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For the elaboration of the present study, we have followed a series of systematic
stages. First, we established a list of research questions oriented for this study, which
helped delimit the most important words, the search pages, and the chosen period,
marking the direction of the work. Once the main theme had been structured and
created, the first results were filtered, delimiting the research toward a total number
of 1455 scientific articles distributed among the WoS and Scopus databases. With the
obtained metadata, we then proceeded creating our own database which has been
used for the present analysis.
Research questions
We formulate research questions that can help us identify the volume of articles to
predict future patterns and determine future lines of work to focus on. ese ques-
tionnaires will also make us easier to determine which papers and publication venues
to publicize our research. Lastly, these questions will help establish the relevance of
the field at a general level and help find possible new funding or coordinated research
avenues among the agents involved. We thus present the following research questions:
Q1: What is the distribution of publications on cryptocurrencies, especially Bitcoin
and Ethereum, in relation to their citations?
Q2: What areas of publications have the highest impact?
Q3: Which articles are the most influential in this technology according to the num-
ber of citations, and where are they located?
Q4: Which are the most relevant and related countries and institutions?
Data extraction
is study analyzed cryptocurrency, and the sources are the WoS and Scopus data-
bases that include the largest number of academic journals and publications. It also
analyzes the most frequently published authors, the most common or relevant topics,
the number of publications by country, and the language used for the largest number
of publications.
Two noteworthy sources have been chosen to solidify their documentary strength
(Manterola etal. 2005). is study’s validity study depends on whether the subject
area or the topic being researched is included in the sources of information. For many
years, WoS was the only database designed as an international and multidisciplinary
tool. Subsequently, Scopus was developed to compensate for the limitations of its pre-
decessor, and to date, it is a more extensive database.
Based on several assumptions, the analysis is structured as follows: First, the param-
eters of the study were chosen or defined to select the appropriate databases from
which to extract the data. Second, the corresponding search criteria were adjusted,
and the bibliographic information categories were compiled. Finally, the extracted
material was coded and used to create a combined database, and the extracted data
were analyzed and contrasted.
e words selected for the search were “cryptocurrency,” “Bitcoin,” or “Ethereum.
is selection covered both the generic concept of electronic currency and the two
types of pioneering and best-known currencies in the protocol’s respective version. e
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García‑Corraletal. Financial Innovation (2022) 8:2
period selected was from 2010, the date of the first publication, to 2018, using the years
2019–2021 to check whether the published articles influenced future research trends.
is is because, looking at all the data, we determine a turning point at which publica-
tions begin to double the number of the previous year (Fig.1). From the aforementioned
search criteria, we selected the filter for scientific articles as these were considered to be
the most representative.
Documents selection anddata analysis
We have used three different indicators for the selection of documents: quantity, qual-
ity, and the structural form and the relationship between publications. Quantity shows
the productivity index in terms of the number of publications. Meanwhile, quality shows
which publications have the greatest impact according to the total number of citations
received by a given text. Of the three, the two central ones of this text will be quantity
and quality. ese lead to the development and identification of successive rankings that
will be displayed in various tables.
After selecting the documents to be used, we created three databases, that is, an indi-
vidual one for each platform for comparison and a common unified one for specific
analyses. For this, we have used three software packages: Tableau, R (Bibliometrix R
Package), and VOSviewer.
e coding process was conducted by building a database using different variables that
store information about each article, thereby extracting the productivity related to this
research field.
Finally, after selecting the questions and extracting and preparing the data, we con-
ducted an analysis consisting of the number of publications and their incidence, a
selection of research areas, a distribution by country, institutions and journals, a more
detailed section dedicated to their authors, and a summary of the trends.
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Arcles WosArcles Scopus
Fig. 1 Annual scientific production. Source: Own compilation
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To achieve a global view of the productivity in this field of research, this study’s results
encompass the articles published during a given period and include information about
their respective languages, countries, institutions, journals, and authors. As we have
mentioned, the WoS and Scopus database search applies from 2010 to the end of 2018
because from 2019 onwards, the number of publications has multiplied, especially those
related to the term blockchain, which may mislead the results (Fig.2).
Initial approach
e following data show the evolutionary state of the cryptocurrencies up to the pre-
sent. As mentioned, the referenced sources are the WoS and Scopus databases, in which
WoS is considered the pivotal source because of its greater seniority.
e first section analyzes the sample. Applying the corresponding search filters, we
found 684 documents on the WoS database and 771 items on Scopus. Of these com-
bined results, 407 documents appeared in both databases. e search in the two data-
bases utilized the same period and began receiving content relevant to this study at
almost the same time. Although the search is delimited by years, we focus on the start-
ing year 2010 because of an anomalous result in Scopus in 1952 that coined the term
Ethereum in an investigation by Dr. H. Greiner in the area of medicine. After excluding
this search result, both bases coincide in the date of publication of articles, thus estab-
lishing this criterion equally.
Publications that included keywords, such as “Bitcoin,” “Ethereum,” or “Cryptocur-
rency,” appeared in 2011. ereafter, the number of publications that included these
keywords doubled annually. e recent creation of the aforementioned cryptocur-
rencies and their low impact indicate no related publications during the first years.
Since 2011, when a single publication appeared in both databases, the results have
Fig. 2 Most Cited articles in both databases. Source: Own compilation
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García‑Corraletal. Financial Innovation (2022) 8:2
increased exponentially. Figure2 highlights that the trajectory followed by both data-
bases is similar in terms of total publications, although with internal differences. If
the set of publications is analyzed, Scopus includes a larger number than WoS, except
for 2016, in which this trend is reversed.
e first publication included in WoS is “On Bitcoin and Red Balloons” (Babaioff
etal. 2012), which talks about getting a reward in a node “competition.” Meanwhile,
on Scopus, the first article is “Bitcoin: A bit too far?” (Jacobs 2011), which deals with
issues internal to the currency. Although both publications received a low number of
citations, the article “Bitcoin: A bit too far?” obtained a total of 10 citations compared
to the two citations received by the article on WoS.
In terms of citations on both platforms, the most significant articles practically
coincide, making it more relevant even with the creation of a common database that
combines both sources (Fig.2). In a separate analysis, both databases would show
concordance in two of the three articles. Moreover, both articles would be in WoS
and Scopus, although in different ranking positions. e article “Bitcoin: Economics,
Technology, and Governance” (Böhme etal. 2015) is ranked first in WoS with 139
citations, whereas in Scopus, it is ranked third with a total of 207 citations. e article
that ranked second on WoS is “Bitcoin and Beyond: A Technical Survey on Decentral-
ized Digital Currencies” (Tschorsch and Scheuermann 2016), with 133 citations; how-
ever, this article is ranked first in Scopus, with a total of 225 citations. Meanwhile, the
article “Where is current research on Blockchain technology?—A systematic review”
(Yli-Huumo etal. 2016) ranks second on Scopus, with a total of 210 mentions, but it
did not have any citations on WoS. Finally, the third-ranked article on WoS, that is,
“Speculative bubbles in Bitcoin markets? An empirical investigation into the funda-
mental value of Bitcoin” (Cheah and Fry 2015), has 109 citations.
Apart from the articles ranked first, the number of citations on Scopus is higher
than on WoS (Fig.3). The average number of citations per article is also higher, that
is, 19 on Scopus compared to 15 on WoS, even though WoS contains a larger num-
ber of documents on the topic. Although both databases commence with articles
Fig. 3 Comparison of citations. Source: Own compilation
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García‑Corraletal. Financial Innovation (2022) 8:2
without citations, the ends of the diagram show a greater number of atypical results
in Scopus.
As can be seen, the results are quite similar, both being in an equal position. The
country variable in both also shows a homogeneous growth and with similar results.
The most significant distinction can be found in the total number of citations if the
results are distributed over the years with a significantly higher number of citations
on WoS. This is because although the number of articles is lower, the variables of
authors and journals are higher (Table4).
Distribution byarea ofresearch
When comparing the databases, our search results show that the main areas of knowl-
edge are information technology and economics (Table5). Although WoS had 100 fewer
Table 4 General view
A = Articles, Au = Authors, C = Country, J = Journals, TC = Total cites. Source: Own compilation
Year A Au C J TC
WoS Sco WoS Sco Wo S Sco WoS Sco Wo S Sco
2011 1 1 4 1 1 1 1 1 2 9
2012 2 4 2 4 1 1 2 4 32 52
2013 8 10 9 18 9 6 8 9 253 296
2014 37 44 33 76 14 21 21 36 245 489
2015 52 62 97 117 22 25 48 54 863 782
2016 87 81 166 159 33 35 70 66 1102 1129
2017 132 148 288 159 37 39 101 105 1193 860
2018 365 421 892 160 65 69 212 159 1258 623
Table 5 Distribution by research area
RW = Research area WoS, RC = Research area Scopus, A = Articles. Source: Own compilation
Economics 156 Computer Science 269
Business finance 125 Economics, Econometrics and Finance 217
Computer science information systems 96 Social Sciences 188
Law 62 Engineering 166
Engineering electrical electronic 43 Business, Management and Accounting 133
Telecommunications 43 Mathematics 70
Computer science theory methods 42 Materials Science 39
Computer science software engineering 40 Decision Sciences 33
Multidisciplinary sciences 38 Biochemistry, Genetics and Molecular Biology 31
Computer science interdisciplinary applications 28 Arts and Humanities 29
Computer science hardware architecture 24 Physics and Astronomy 28
Business 22 Multidisciplinary 20
Physics multidisciplinary 20 Agricultural and Biological Sciences 16
Management 14 Energy 16
Remaining areas 209 Remaining areas 68
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results when the same number of research areas were considered, the wide range of clas-
sified thematic areas contained within WoS is greater than the classification in Scopus,
and thus the articles are distributed across a wider range of subjects.
Using WoS as a reference, we use areas of economic knowledge, such as economics
and business finance, in the ranking. e total sum of these articles is 282, which is simi-
lar to the second category in Scopus, which encompasses Economics, Econometrics, and
Finance. e remaining positions in the ranking are related to computer science, sys-
tems, and telecommunications, almost half of those included in the list. e remaining
articles are distributed among multiple categories, that is, a total of 76 different research
areas include the terms Bitcoin, Ethereum or Cryptocurrency, although only 14 of these
are specifically listed in the table. In contrast, Scopus directly links computer-related
articles and ranks them first. Next, the economic and social sciences are ranked second
and third with the remaining articles being linked, to a greater extent, to computer sci-
ences, such as engineering and mathematics; and the social sciences with business and
management. Once the threshold of the eighth theme is crossed, a greater diversity of
topics begins to be seen.
e results of both the databases and the many thematic areas denote the wide variety
of applications that technologies derived from electronic currencies have. Although the
keywords are based on economics, the standardized use of technologies born from cryp-
tocurrencies, most notably digital ledgers or blockchain, means that the distribution of
themes is very widespread. e blockchain shows a positive evolution in databases, such
as WoS, with a total of 692 results solely in articles in a period of just three years. e
term “blockchain” did not receive citations until 2015, the year in which its development
really took off. Hence, its importance is evident when compared to the origins in Bitcoin,
because it has managed to equal the same number of articles in half the number of years.
Fig. 4 Geographical distribution. Mercator projection Map. Landmasses appear larger the farther they
are from the poles. The projection, however, maintains constant bearings for navigation. Source: Own
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Distribution bycountry
In terms of geographical distribution, an apparent growing trend toward research on
this topic originates from the Asian continent, apart from the time factor (Figs.4 and 5).
at said, the principal language used is still English, and virtually all articles appear in
the two databases published in this language. Other articles were published in Russian,
Spanish, and Turkish in WoS, whereas the most used languages were Chinese, Russian,
and German in Scopus. Note that although both databases consider Russian to an influ-
ential language, as a geographical region, Russia is not featured as one of the most influ-
ential countries in terms of the number of publications.
Fig. 5 Grouping by country and year. Source: Own compilation
Table 6 Distribution by country
C = Country, R = Position in the Ranking, A = Articles, TC = Total cites, H = H‑Index. Source: Own compilation
WoS Sco WoS Sco WoS Sco WoS Sco
USA 1 1 182 161 1249 865 17 21
UK 2 3 84 91 1035 806 16 23
China 3 2 74 97 358 320 9 13
Germany 4 4 43 38 416 399 10 13
Australia 5 8 39 31 361 312 12 14
France 6 10 36 29 425 227 12 12
Italy 7 7 32 33 210 128 8 9
Switzerland 8 11 29 23 217 190 8 8
Russia 9 5 25 38 27 65 2 6
South Korea 10 9 23 31 136 175 7 8
Canada 11 12 22 19 70 79 5 8
Spain 12 13 22 19 350 235 8 10
India 13 6 17 33 105 63 5 7
Japan 14 15 15 16 51 42 4 5
Brazil 15 14 13 16 21 29 3 3
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In a more detailed comparison, both databases show similar results with respect to the
first four and the last two ranked countries (Table6). Both databases show the USA, UK
and China leading the ranking. ese countries also account for the largest number of
articles and citations together with the highest H-indexes. e databases also coincide
with respect to the countries ranked last, with the possible exception of India, which
in Scopus, is ranked sixth. Specifically, considering the ranking in terms of the number
of articles published, the results from both databases practically coincide, whereas the
results are more disparate in terms of the total number of citations. e discrepancy
mentioned earlier in India can only be highlighted in the number of articles. Regarding
the total number of citations, the rankings of Russia and Spain stand out for different
reasons. In the case of Russia, the total number of citations is much lower than expected
given the number of articles published. In contrast, Spain obtained a number of citations
that would place it in several higher positions compared to the number of published arti-
cles; the h-index is clearly higher than that obtained in the classification.
If we develop the content dealt with in each country in a more important way, taking
a total of 5 words as the focus of studies, we can see how the USA has always studied
bitcoin, deriving from it the concept of currency, blockchain, innovation, and economy
together with security. For its part, and also taking bitcoin as a central focus, England
has added the volatility of these currencies together with their technology, such as block-
chain, to its most relevant words. China is next, giving the same importance to bitcoin as
to the blockchain, deriving two lines of research from which the main concern of bitcoin
comes from its inefficiency and prices; however, the blockchain mentions security and
smart contracts. Germany and Australia are next on the list, but the main focus is on
bitcoin, but it is much shorter in terms of secondary issues, just mentioning economics
and blockchain. Meanwhile, Russia remains with bitcoin and cryptocurrencies in general
and, if the number of keywords is lowered as a concurrence, China appears as another
result, being the only ones to mention another place directly.
e most pivotal institution related to electronic currencies that focuses on Bitcoin and
Ethereum is the University of London with a total of 24 and 14 articles in WoS and Sco-
pus, respectively (Table7). is institution is followed by PDX Currency Corp in WoS,
with 17 published articles, although no citations are related to them. Again, in terms
of number of published articles, the next ranked institutions are the University Col-
lege London with 14 articles and Eidgenössische Technische Hochschule Zürich (ETH
Zurich) and the University of California System with 13 articles each. ey have also
attracted a large number of citations. Except for ETH Zurich, the aforementioned insti-
tutions are all English-speaking, which coincides with the high number of publications
in that language.
In contrast, Scopus shows a greater spatial distribution with respect to institutions.
Although the first result coincides with the aforementioned results from WoS, the insti-
tutions appearing next in the ranking are Montpellier Business School, Chinese Acad-
emy of Sciences, ETH Zurich and Holy Spirit Univ Kaslik located, respectively, in France,
China, Switzerland and Lebanon. e articles published by these institutions have a
higher number of references compared with more prominent institutions listed in WoS.
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Table 7 Institutions
Source: Own compilation
I = Institution, R = Position in the Ranking, A = Ar ticles, C = Country, TC = Total cites, AC = Average citation, H = H‑I ndex
WoS Sco WoS Sco Wo S Sco WoS Sco Wo S Sco
University of London 1 1 24 14 UK 162 73 6.75 5.21 7 6
PDX Currency Corp 2 17 USA 0 0 0
University College London 3 14 UK 74 5.29 4
ETH Zurich 4 4 13 9 Switzerland 147 158 11.31 17.6 4 5
University of California System 5 13 USA 105 8.08 4
Holy Spirit Univ Kaslik 5 9 Lebanon 117 13 8
Montpellier Business School 6 2 12 12 France 254 132 21.17 11 7 9
Beihang University 6 8 China 20 2.5 3
Languedoc Roussillon Universites Comue 7 11 France 251 22.82 7
University of Pretoria 7 8 South Africa 61 7.63 6
Chinese Academy of Sciences 8 3 10 11 China 49 158 4.9 14.36 5 6
Xidian University 8 8 China 17 2.13 3
University of Manchester 9 9 UK 117 13 4
Imperial College London 9 7 UK 28 4 4
Centre National de la Recherche Scientifique Cnrs 10 8 France 20 2.5 3
Ku Leuven 10 6 Belgium 63 10.5 4
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e results show that WoS has a greater concentration of English and American insti-
tutions as a central pillar, bringing together a core of English-speaking institutions that
makes up 40% of the total. In contrast, Scopus has a more varied distribution. e cen-
tral focus of the five institutions of each essential database has always been on issues
related to bitcoin as a core, with publications on its volatility, hedge, and economics
deriving from it. In a more minor way this time, the concept of the blockchain appears.
To conclude this section, we created a cluster map of institutions. As suggested by Fig.6
and given the recent development of the topic, the links and relationships between insti-
tutions are scarce, with only a suggestion of a rapprochement between Asian entities.
e journals with the highest number of publications in WoS and Scopus are Economics
Letters and IEEE Access with a total of 29 and 28 publications, respectively in the case
of Economic Letters and 26 and 30 in the case of IEEE Access. ey both clearly have
a high H-Index along with a large total number of accumulated citations. Two sources
appear in the third position of the ranking of both databases, albeit without any associ-
ated citations. ey are Digital Currency Challenge Shaping Online Payment Systems
through US Financial Regulations and Economist United Kingdom with 17 and 21 arti-
cles, respectively from USA and UK. is phenomenon of not receiving any citations is
repeated in the WoS ranking with the fourth ranked journal, Palgrave Pivot, and in Sco-
pus with the seventh ranked journal, Technology Review.
In the sample provided, only five journals are considered global publications in Table8
for both databases. is is evidence of the disparity between the two sources because,
aside from the two journals mentioned in the previous paragraph, Finance Research Let-
ters, PLOS One, and Physica A: Statistical Mechanics and its Applications are the only
journals listed in both sources. Although there are no other concurrences, the basic
scheme observed is remarkably similar because the coincident entities do so in almost
an equal number of the ranking, whereas the remaining journals coincide approximately
in the number of articles. e number of publications in these journals is always related
to economics, inefficiency, volatility, and gold, leaving blockchain and security as sec-
ondary topics.
Fig. 6 Cluster map of institutions. Source: Own compilation
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Table 8 Distribution by Journal
Source: Own compilation
J = Journal, R = Position in the Ranking, A = Articles, JCR = Journal Citation Reports, SJR = Scimago Journal Rank, C = Country, TC = Total cites, AC = Average citation, H = H‑Index
WoS Sco WoS Sco Wo S Sco WoS Sco Wo S Sco WoS Sco
Economics Letters 1 2 29 28 0.876 0.767 Switzerland 721 377 24.86 13.46 13 16
IEEE Access 2 1 26 30 4.098 0.609 USA 111 63 4.27 2.1 7 10
Digital Currency Challenge Shaping Online Payment
Systems through US Financial Regulations 3 – 17 – USA 0 – 0 0 –
Economist United Kingdom 3 21 0.100 UK 0 0 0
Palgrave Pivot 4 17 0 0 0
Finance Research Letters 5 4 14 14 1.709 0.770 USA 405 242 28.93 17.29 9 11
PLOS One 6 5 14 14 2.776 1.100 USA 219 319 15.64 22.79 7 10
Physica A: Statistical Mechanics and Its Applications 7 6 13 13 2.5 0.699 Netherland 113 61 8.69 4.69 4 7
Technology Review 7 9 0.117 USA 0 0 0
ERCIM News 8 8 1 0.13 1
Computer 8 8 0.498 USA 61 7.63 6
Journal of Risk and Financial Management 9 8 27 3.38 3
Royal Society Open Science 9 8 1.131 UK 25 3.13 2
Ledger 10 – 8 7 0.88 2
Computer Fraud and Security 10 7 0.177 36 5.14 3
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As a final comparison, Table9 shows the authors ordered according to the index of pub-
lications on the topic. e 17 articles by P.C. Mullan, which appear solely in WoS, can
be highlighted as an anomalous result, as they have received no citations. is can be
linked to the previous section on publications, as these articles are contained in a man-
ual. Regarding the rest of authors, E. Bouri and D. Roubaud stand out with nine articles
each, published in 2017 and 2018. Both authors have collaborated extensively and had
many citations, well above the average of other authors, although not in all articles.
Based solely on the total number of publications, and focusing on the most influen-
tial authors, the distribution of authors in both databases is quite similar. Regarding
Table 9 Distribution by author
Source: Own compilation
AU = Author, R = Position in the Ranking, A = Articles, TC = Total cites, AC = Average citation, H = H‑Index, FP = First
publication, LP = Last Publication
WoS Sco WoS Sco Wo S Sco WoS Sco Wo S Sco
Mullan, Pc 1 17 0 0 0 2014 2014
Bouri, E 2 1 9 9 223 117 24.78 13 7 8 2017 2018
Roubaud, D 3 2 9 9 242 131 26.89 14.56 7 8 2017 2018
Androulaki, E 4 7 29 4.14 1 2015 2016
Gupta, R 5 3 7 6 116 60 16.57 10 5 6 2017 2018
Luther, Wj 6 5 7 5 76 39 10.86 7.8 5 4 2016 2018
Wang, J 7 7 36 5.14 3 2018 2018
Bouoiyour, J 7 5 4 70 37 14 9.25 5 4 2015 2018
Karame, G 8 6 0 0 0 2016 2016
Corbet, S 8 4 27 6.75 3 2017 2018
Marchesi, M 9 4 6 6 41 22 6.83 3.67 4 4 2017 2018
Li, X 9 5 4 43 4 8.6 1 3 3 2017 2018
Selmi, R 10 6 6 5 71 37 11.83 7.4 5 4 2015 2018
Liu, J 10 4 4 1 2 2017 2018
Fig. 7 Author cluster on WoS. Source: Own compilation
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the field to which the authors belong, the most important ones come from Business
& Economics, Computer Science and Environmental Sciences & Ecology. However,
in a cluster analysis (Figs.7 and 8) and using the two databases as the basis for the
analysis, we determine that the relationship between them changes. In both cases,
the grouping has been generated using the same basic parameters that, together with
the greater distribution among the Scopus institutions, shows broader results with
six central nuclei versus the two mere nuclei in WoS.
Fig. 8 Author cluster on Scopus. Source: Own compilation
Fig. 9 Top authors’ production. Source: Own compilation
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Figure9 shows the evolution of the scientific production achieved by the most rel-
evant authors, taking WoS as a reference to observe their trajectory. The circles on
the cluster map represent the number of articles, and the color represents the inten-
sity of the citations received during the year. This would show how the most impor-
tant publications were produced in WoS during 2017, coinciding precisely with the
beginning of the increase in scientific publications.
Fig. 10 Keywords on WoS. Source: Own compilation
Fig. 11 Keywords on Scopus. Source: Own compilation
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Trend analysis
Based on the content of all the articles, we can identify the most common terms and
those with the greatest impact related to electronic currencies. Using the VOSviewer
software and R (Bibliometrix package), we compiled a series of large clusters indicat-
ing the frequency and evolution of the keywords (Figs.10 and 11), combined with a
three-field plot of top Keywords Plus, Sources, and Author Keywords (Fig.12). Nota-
bly, the wide variety of terms in Scopus is due to a higher index of publications, even
if some of them have not been followed up.
e results of both graphs show similarities in terms of key concepts that are
maintained over time. e secondary issues continue to have Bitcoin as the central
focus, drifting toward the concepts of blockchain, money, and security. Remarkably,
although the term Ethereum has been used as a study keyword, it does not appear
directly in the cluster figures, although the derivative terms, such as Smart contracts,
appear as the purpose of this type of currency.
Fig. 12 Three‑fields plot of top Keywords plus, sources, and Author keywords. Source: Own compilation
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e concept of security appears directly related to electronic currency, and hence,
the fact that it is not reflected in any type of legal regulation is conspicuous, given the
complexity of these payment mechanisms. If the latest publications and texts taken from
conferences are incorporated, changes are made to the graph that had not been previ-
ously considered, such as security becoming an impactful mainstay of the topic. is is
due to the standardization and greater acceptance of these types of currencies that had
even been temporarily banned in countries, such as China (2019), which is now one of
the largest producers of articles related to the subject, coming to appear in the keywords
of both databases, although the current situation in China is complex, as its uses have
recently been limited (China 2021).
Returning to the concept of security, we determine that the term crime appears close
due to the increase in publications related to criminal acts, such as money laundering
processes, darknet shops, or payment to ransomware, that in the last three years has
doubled the number of publications (Turner etal. 2019; Albrecht etal. 2019). is ter-
minology is related to the illicit and dark web keywords that evolve from the concept of
To finish with the new trends section, we compiled a Sankey diagram (Fig.12). e dia-
gram shows the relationship between sources (center), Keywords Plus (left), and Author
Keywords (right), which is especially useful for locating the topic in each of the journals
(Riehmann etal. 2005). e size of the nodes represents the frequency of the item and
the lines show the connections between them. e use of Keywords Plus and Authors’
keywords shows a difference to be considered, as Keywords Plus are more effective than
words given by authors in bibliometric analyses even if they are less representative of the
article’s content. (Zhang etal. 2016).
We can argue that Economics Letters relates its publications to a greater number of
terms, such as inefficiency, volatility, or market, covering more topics or characteristics
because of connector flows. ese are in turn closely related to the words “electronic
currencies, bitcoin and smart contracts” as the authors’ keywords. erefore, although
this first node mentions more topics, they are all related to the economic world, leaving
in the background the importance of applied technologies, such as blockchain. e pub-
lications of the second most influential node, IEEE Access, are closely related to the con-
cepts of “inefficiency, Bitcoin, and volatility,” with special interest in the authors’ words
“bitcoin, security, blockchain, smart contracts, privacy and privacy regulation.” ere-
fore, the authors of these publications can focus more on the financial applications that
arise from blockchain networks than on developing the currencies themselves. is per-
spective seems to be shared by four other sources (i.e., Computer Law & Security Review,
Journal of Risk and Financial Management, Banking Beyond Banks and Money, and
Royal Society Open Science), whereas Applied Economics and Finance Research Letters
follow the trend of the first node.
Using 2020 as a deadline, we can see that the aforementioned trends are the ones
that have finally concentrated on these publication types. e conceptual structure
map (Fig.13) of the MCA keyword plus method shows two main clusters in different
colors that coincide with the driving themes of these publications (Fig.14). is word
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clustering allows us to identify from today the groups with the same meaning and
their relationships. Porter’s derivation algorithm has been used to reduce the number
of words used in a root form, but this time, from the authors’ keywords with similar
results. In both cases, a maximum of 250 words per term has been applied. Both show
that regardless of the analysis used and keywords, the central topics are Bitcoin and
the blockchain network, which creates and supports the need for a separate biblio-
metric review of different areas to check the trends in them in the future. is situ-
ation is repeated in the different analyses conducted on the subject regardless of the
basis used, clearly showing a separation between technology and economy (Merediz-
Sola etal. 2019; Shen etal. 2020).
Figure15 shows a thematic division into four different periods. is is conducted
to clarify how the same area has been clearly divided into two distinct interconnected
branches since 2017–2018, creating the aforementioned economic-technological
division. Although the concern for cryptocurrencies is related to their value in the
market, technological evolution has opened up new lines of research thanks to its
multiple applications, such as machine learning.
At this point, some questions arise:
What should be the way forward for cryptocurrency research?
Cryptocurrencies will continue to be published, following the concepts of volatility,
decentralization, and efficiency as characteristics, along with the smart contract as an
application that initiated the 2.0 protocol. Especially in this context, the concept of
efficiency or inefficiency should be emphasized in a broader sense, given that the cost
of maintaining certain global networks based on peer-to-peer technology is start-
ing to cause survival problems and requires optimizations that were already foreseen
(Courtois etal. 2014). For example, Bitcoin power grid consumed approximately 2.55
GW of electricity in 2018, which is comparable to the consumption of countries, such
as Ireland and its 3.1 GW (de Vries 2018). e hash rate, or the computing power
Fig. 13 Conceptual structure map using MCA method. Source: Own compilation
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needed to keep the network stable and the technology moving forward, is its main
strength and weakness. e network will be more secure the higher the ratio is held,
but more complex to mine and more computational and energy intensive. For exam-
ple, some markets are currently affected by the COVID-19 pandemic, among other
reasons. Of these, and in direct relation to cryptocurrencies, we must highlight the
lack of stock and increase in computer components (mostly graphic cards) used for
mining algorithms (Allan 2021; Faulkner 2021). We have recently seen mining farms
using laptops in parallel due to their lower power consumption or companies, such as
Nvidia Corporation (2021), launching versions exclusively for these purposes. e use
of these technologies is promising but uncertain based on their overall cost alone (Li
etal. 2019).
Should these tools be separated generally from the technology created at the level of
future research?
Fig. 14 Thematic map using porter’s derivation algorithm method. Source: Own compilation
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As mentioned before, a constant relationship has both a technological and an eco-
nomic side. Undoubtedly, the impact of technology and its multiple applications will
keep them together, so this separation will not materialize. Although cryptocurrencies
have led the path, as shown in Fig.15, blockchain technology is the main topic that will
eventually leave Bitcoin and Ethereum as basic or niche topics, as Shen et al. (2020)
Can the technology created be applied to more business issues, and can they benefit
from it?
Above all, the Blockchain network is the pioneering technology that has appeared in a
number of publications on cryptocurrencies (Yli-Huumo etal. 2016). Since 2016, several
authors, such as Yu Zhang, Young-Sik Jeong, K.K.R. Choo or J.H. Park have established
this trend, with the highest number of mentions of blockchain appearing in late 2020.
Fig. 15 Topic evolution research (2010–2020). Source: Own compilation
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Blockchain is a disruptive technology that can be used in all subject areas. is mul-
tiplicity of uses made necessary a systematic review, with special attention to business
and economics (Xu etal. 2019). is suggests that we should take into account the appli-
cation of the base technology and its potential applications at the business level (Zhao
etal. 2016). Moreover, the cryptocurrency technology should be considered.
Based on the blockchain network analysis, this technology has great potential and
offers many opportunities for the business area (Xu etal. 2019). e blockchain encryp-
tion system allows, for example, conducting secure and reliable financial transactions
quickly, thanks to the distribution on independent nodes. e system also makes the
data more difficult to falsify since it must be exchanged from multiple nodes simultane-
ously and allows the realization of smart contracts. Furthermore, it keeps the informa-
tion more accessible because, as long as a node is still online, the information can be
accessed; it does not have a single source server (Felin and Lakhani 2018; Gatteschi etal.
2018; Tönniseen etal. 2018; Chang etal. 2019).
is study has reviewed an 8-year international search related to cryptocurrency due to
bibliometric analysis of the WoS and Scopus databases.
e results show the positive evolution both in terms of the number of articles pub-
lished and citations, with a growing number of publications and relevance in recent
years. Comparing the evolution of both databases, we determine that WoS contains a
greater number of citations received, whereas the Scopus database includes a greater
number of articles. e main topics or research areas that contain the concepts related
to cryptocurrencies are computer science and economics. If we delve further into the
number of research areas in both databases, limiting the criteria to articles only, the
enormous amount of categorical division seems to indicate that it is an interdisciplinary
branch. However, on closer inspection, this perception changes because the majority of
knowledge areas are related to the aforementioned sciences (i.e., computer science and
economics). e subsequent thematic areas are legal sciences, criminology, philosophy,
and physics.
e countries with the greatest number of publications are the USA, UK, and China,
with the latter appearing alongside Canada in analyzing the most relevant keywords. e
constant evolution of the regulatory framework regarding cryptocurrencies has gener-
ated various controversies at a global level. One notable case is in China, where after the
general ban on Bitcoin trading in 2017, the Hangzhou Internet Court recently granted
it a new status as a virtual asset. Hangzhou Internet Court was responsible for making
cryptocurrencies public and reversing the ban without being considered fiat money.
Meanwhile, the most used language for communications is English, coinciding with the
native language of two of the countries with the highest rate of published articles. In
contrast, although Chinese is not the language with the highest number of publications,
China is one of the most often recurrent keywords in the last three years, making it a
country showing the most interest in the subject. e authors’ cluster analysis also dem-
onstrates the high participation rate they acquire.
A more in-depth analysis confirms that the main journals and authors belonging to the
ranking also belong to the countries with the highest number of publications, to clarify
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any doubts that may arise from this new phenomenon. e number of outstanding jour-
nals and authors is increasing, but note that, especially when referring to authors, the
wide participation of the Asian continent is prevalent if Scopus references are taken into
account and even if the journals are English-speaking.
From the keywords obtained from the documents, the most frequent topics in the
world of cryptocurrencies can be linked and recognized. Although WoS mainly contains
words related to Bitcoin, Blockchain, and the volatility of these cryptocurrencies, Scopus
publications focus on Bitcoin, Blockchain, and the technological aspects derived from
them. Due to the importance of Blockchain technology, the publications on this topic
have doubled in the last two years. A basic analysis of the theme shows a total of 550 arti-
cles in 2018, whereas the figure exceeds 1100 2019 in WoS. Scopus in turn shows results
of approximately 650 and 1370. is is evidence of new lines of research among which
stand out, blockchain appearing on both platforms as noteworthy, and Smart Contracts
as an alternative to the conclusion of classic contracts that had been conducted.
At this point, and after starting to look at the reviews, especially of the most important
keywords or the evolution in the discussion, we can see how the theory and background
of cryptocurrencies has begun to conclude the publications on cryptocurrencies, leaving
practical research as a new line of research. is opens the way to other interdiscipli-
nary studies, especially after the controversy over the lack of regularization and harmo-
nization in matters, such as legislative issues. Internally, these currencies are constantly
revising and evolving to rectify the problems they previously had. us, the current
information about them will be transformed by version periods, closing the chapter on
version 1.0 and analyzing the modifications corresponding to version 2.0.
Finally, despite this study’s contribution, it also has some limitations. First, the field of
study is based solely on two of the most influential academic databases (WoS and Sco-
pus). Second, the type of document included in the analysis has been limited to arti-
cles. Given the recent creation of the topic and trying to cover the largest possible field
of study, expanding the results with Google Scholar as a third data source or using a
wide range of publication types could yield a larger document count, which in turn could
change the results, especially concerning the keywords used. If the subject were focused
on documents from Google Scholar, but the type of publication was not delimited, some
7750 total documents would be obtained. e following will be included in the top 10
publications: “Blockchain technology: Beyond bitcoin,” followed by “Zerocash: Decen-
tralized anonymous payments from bitcoin,” and “e inefficiency of Bitcoin.” Although
in different positions, all these articles are well placed in the two databases considered
in this study. However, if the document type were to be extended, the existing proce-
dural paper with the same time limitation as the articles in WoS amounts to 875, which,
together with 684 articles, would add up to a total of 1559 of the 1678 results obtained.
Scopus would yield a total of 1281 and 771, respectively, showing that 83.2% of the 2467
total results without applying filters are of both classes. In this way, an analysis of almost
all the elements could be conducted.
A: Articles; AC: Average citation; Au: Authors; BTC: Bitcoin; C: Country; ETH: Ether; FP: First publication; H: H‑Index; J: Jour‑
nals; JCR: Journal citation reports; LP: Last publication; R: Position in the ranking; RC: Research area scopus; RW: Research
area WoS; Sco: SCOPUS; SJR: Scimago Journal Rank; TC: Total cites; WoS: Web of Science.
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García‑Corraletal. Financial Innovation (2022) 8:2
Not applicable.
Authors’ contributions
FJGC contributed by retrieving literature, conducting data analysis and writing the paper. JdPV contributed by retrieving
literature and participated in its design and coordination. JUT contributed conducting data analysis and revised the
paper. JACG revised the paper and helped to write the manuscript. All authors read and approved the final manuscript.
No funding is declared.
Availability of data and materials
The datasets analyzed during the current study are available on the following websites: Price: https:// coinm arket cap.
com, Web of Science: http:// wos. fecyt. es/, Scopus: https:// www. scopus. com/
Competing interests
The authors declare that they have no competing interests.
Author details
1 Research Group: Almeria Group of Applied Economy (SEJ 147), University of Almeria, Carretera Sacramento s/n, 04120,
La Cañada de San Urbano, Almería, Spain. 2 Department of Law, Financial and Tax Law, University of Almeria, Carretera
Sacramento s/n, 04120, La Cañada de San Urbano, Almería, Spain. 3 Department of Business and Economics, Applied
Economic Area, University of Almería, Carretera Sacramento s/n, 04120, La Cañada de San Urbano, Almería, Spain.
Received: 6 August 2020 Accepted: 14 November 2021
Albrecht C, Duffin KM, Hawkins S, Rocha VMM (2019) The use of cryptocurrencies in the money laundering process 0. J
Money Laund Control 22(2):210–216. https:// doi. org/ 10. 1108/ JMLC‑ 12‑ 2017‑ 0074
Allan D (2021) Processor and graphics card stock woes could last into 2022, if chip shortage prediction is right. https://
www. techr adar. com/ news/ proce ssor‑ and‑ graph ics‑ card‑ stock‑ woes‑ could‑ last‑ into‑ 2022‑ if‑ chip‑ short age‑ predi
ction‑ is‑ right. Accessed 24 Feb 2021
Babaioff M, Dobzinski S, Oren S, Zohar A (2012) On bitcoin and red balloons. In: 13th ACM conference on electronic com‑
merce (EC ’12), Association for Computing Machinery, New York, NY, USA, pp 56–73
Balcilar M, Bouri E, Gupta R, Roubaud D (2017) Can volume predict Bitcoin returns and volatility? A quantiles‑based
approach. Econ Model 64:74–81
Bariviera AF, Basgall MJ, Hasperué W, Naiouf M (2017) Some stylized facts of the bitcoin market. Physica A 484:82–90.
https:// doi. org/ 10. 1016/j. physa. 2017. 04. 159
Bariviera AF (2017) The inefficiency of Bitcoin revisited: a dynamic approach. Econ Let 161(C):1–4.
Barratt MJ, Lenton S, Allen M (2013) Internet content regulation, public drug websites and the growth in hidden Internet
services. Drugs Educ Prevent Policy 20(3):195–202. https:// doi. org/ 10. 3109/ 09687 637. 2012. 745828
Baur DG, Hong K, Lee AD (2018) Bitcoin: Medium of exchange or speculative assets? J Int Finan Markets Inst Money
Bhargavan K, Delignat‑Lavaud A, Fournet C et al. (2016) Formal verification of smart contracts short paper. In: 2016 ACM
workshop on programming languages and analysis for security (PLAS’16), Vienna, Austria, Oct 2016, pp 91–96.
https:// doi. org/ 10. 1145/ 29936 00. 29936 11
Böhme R, Chirstin N, Edelman B (2015) Bitcoin: economics, technology, and governance. J Econ Perspect 29(2):213–238.
https:// doi. org/ 10. 1257/ jep. 29.2. 213
Bonneau J, Miller A, Clark J et al. (2015) Sok: research perspectives and challenges for bitcoin and cryptocurrencies. Secur
Privacy IEEE, pp 104–121.
Bouri E, Keung Marco Lau C, Lucey B, Roubaud D (2019) Trading volume and the predictability of return and volatility in
the cryptocurrency market. Financ Res Lett 29:340–346. https:// doi. org/ 10. 1016/j. frl. 2018. 08. 015
Brandvold M, Molnár P, Vagstad K, Andreas Valstad OC (2015) Price discovery on Bitcoin exchanges. J Int Finan Markets
Inst Money 36:18–35
Brière M, Oosterlinck K, Szafarz A (2013) Virtual currency, tangible return: port‑folio diversication with bitcoins, tangible
return: portfolio Diversication with Bitcoins. J Asset Manag 16(6):365–373. https:// doi. org/ 10. 1057/ jam. 2015.5
Chang SE, Chen Y, Lu M (2019) Supply chain re‑engineering using blockchain technology: a case of smart contract based
tracking process. Technol Forecast Soc Chang 144:1–11. https:// doi. org/ 10. 1016/j. techf ore. 2019. 03. 015
Cheah ET, Fry J (2015) Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of
Bitcoin. Econ Lett 130:32–36. https:// doi. org/ 10. 1016/j. econl et. 2015. 02. 029
China (2019) Bitcoin’s virtual property attributes recognized for the first time by the judiciary. http://m. caiji ng. com. cn/
api/ show? conte ntid= 46034 03. Accessed 10 Jan 2020
China (2021) Bitcoin tumbles below $30,000 on China crypto‑crackdown. https:// www. bbc. com/ news/ busin ess‑ 57549
543. Accessed 30 June 2021
Chu J, Chan S, Nadarajah S, Osterrieder J (2017) GARCH modelling of cryptocurrencies. J Risk Financ Manag 10:17. https://
doi. org/ 10. 3390/ jrfm1 00400 17
Page 29 of 31
García‑Corraletal. Financial Innovation (2022) 8:2
Ciaian P, Rajcaniova M, Kancs D (2016) The economics of Bitcoin price formation. Appl Econ 48(19):1799–1815. https://
doi. org/ 10. 1080/ 00036 846. 2015. 11090 38
Cocco L, Marchesi M (2016) Modeling and simulation of the economics of mining in the bitcoin market. PLoS ONE
Conrad C, Custovic A, Ghysels E (2018) Long‑ and short‑term cryptocurrency volatility components: a GARCH‑MIDAS
Analysis. J Risk Financ Manag 11:23. https:// doi. org/ 10. 3390/ jrfm1 10200 23
Conti M, Sandeep Kumar E, Lal C, Ruj S (2018) A survey on security and privacy issues of bitcoin. IEEE Commun Surv
Tutorials 20(4):3416–3452. https:// doi. org/ 10. 1109/ COMST. 2018. 28424 60
Corrons A (2017) Monedas complementarias: dinero con valores. RIO 18:109–34
Courtois NT, Grajek M, Naik R (2014) Optimizing SHA256 in bitcoin mining. Cryptography and security systems. In: CSS
2014. Communications in computer and information science, vol 448. https:// doi. org/ 10. 1007/ 978‑3‑ 662‑ 44893‑9_
Dabbagh M, Sookhak M, Safa NS (2019) The evolution of blockchain: a bibliometric study. IEEE Access 7:19212–19221.
https:// doi. org/ 10. 1109/ ACCESS. 2019. 28956 46
Dai W (1998) B‑money. Available via DIALOG. http:// www. weidai. com/ bmoney. txt. Accessed 20 Dec 2018
de Vries A (2018) Bitcoin’s growing energy problem. Joule 2(5):801–805. https:// doi. org/ 10. 1016/j. joule. 2018. 04. 016
Dwyer GP (2015) The economics of bitcoin and similar private digital currencies. J Financ Stab 17:81–91. https:// doi. org/
10. 1016/j. jfs. 2014. 11. 006
Eyal I, Sirer EG (2013) Majority is not enough: bitcoin mining is vulnerable. Comput Sci 8437:436–454
Fabian ML (2016) Analyzing the bitcoin network: the first four years. Future Internet. https:// doi. org/ 10. 3390/ fi801 0007
Faulkner C (2021) Nvidia made $5 billion during a GPU shortage and expects to do it again in Q1. https:// www. theve rge.
com/ 2021/2/ 24/ 22299 505/ nvidia‑ earni ngs‑ q4‑ 2021‑ quart erly‑ gpu‑ short age‑ reven ue. Accessed 24 Feb 2021
Felin T, Lakhani K (2018) What problems will you solve with Blockchain? MIT Sloan Manag Rev 60(1):32–3+.
Feng Q, He D, Zeadally S, Khurram Khan M, Kumar N (2019) A survey on privacy protection in blockchain system. J Netw
Comput Appl 126:45–58. https:// doi. org/ 10. 1016/j. jnca. 2018. 10. 020
Foley S, Karlsen J, Putnins T (2019) Sex, drugs, and bitcoin: how much illegal activity is financed through cryptocurren‑
cies? Rev Financ Stud 32(5):1798–1853. https:// doi. org/ 10. 1093/ rfs/ hhz015
Follador GB (2017) Criptomoedas e competência tributária. Revista brasileira de políticas públicas 7(3)
Franco P (2014) Understanding bitcoin: cryptography, engineering, and economics. Wiley, New York
Garcia D, Tessone CJ, Mavrodiev P, Perony N (2014) The digital traces of bubbles: feedback cycles between socio‑eco‑
nomic signals in the Bitcoin economy. J R Soc Interface 11(99)
Gatteschi V, Lamberti F, Demartini C, Pranteda C, Santamaría V (2018) To blockchain or not to blockchain: that is the ques‑
tion. IT Professional 20(2):62–74. https:// doi. org/ 10. 1109/ MITP. 2018. 02192 1652
Giungato P, Rana R, Tarabella A, Tricase C (2017) SoK: current trends in sustainability of bitcoins and related blockchain
technology. Sustainability 9(12):2214
Gomá‑Garcés I (2014) Bitcoin, una aproximación jurídica al fenómeno de la desmaterialización y privatización del dinero.
Available via DIALOG. https:// study lib. es/ doc/ 80301 53/ bitco in.‑ una‑ aprox imaci% C3% B3n‑ jur% C3% ADdica‑ al‑ fen%
C3% B3meno‑ de‑ la. Accessed 3 Feb 2019
Griffin J, Shams A (2020) Is bitcoin really untethered? J Financ 75(4):1913–1964
Hardy R, Norgaard J (2016) Reputation in the Internet black market: an empirical and theoretical analysis of the Deep
Web. J Inst Econ 12(3):515–539. https:// doi. org/ 10. 1017/ S1744 13741 50004 54
Jacobs E (2011) Bitcoin: a bit too far? J Internet Bank Commerce, 16
Jang H, Lee J (2018) An empirical study on modeling and prediction of Bitcoin prices with Bayesian neural networks
based on Blockchain information. IEEE Access 6:5427–5437. https:// doi. org/ 10. 1109/ ACCESS. 2017. 27791 81
Katsiampa P (2017) Volatility estimation for bitcoin: a comparison of GARCH models. Econ Lett 158:3–6. https:// doi. org/
10. 1016/j. econl et. 2017. 06. 023
Khan MA, Salah K (2018) IoT security: review, blockchain solutions, and open challenges. Future Gener Comput Syst Int J
Sci 82:395–411. https:// doi. org/ 10. 1016/j. future. 2017. 11. 022
Kim T (2015) The predecessors of bitcoin and their implications for the prospect of virtual currencies. PLoS ONE
10(4):e0123071. https:// doi. org/ 10. 1371/ journ al. pone. 01230 71
Klein T, Thu HP, Walther T (2018) Bitcoin is not the New Gold—a comparison of volatility, correlation, and portfolio perfor‑
mance. Int Rev Financ Anal 59:105–116. https:// doi. org/ 10. 1016/j. irfa. 2018. 07. 010
Koblitz N, Menezes AJ (2016) Cryptocash, cryptocurrencies, and cryptocontracts. Des Codes Crypt 78(1):87–102. https://
doi. org/ 10. 1007/ s10623‑ 015‑ 0148‑5
Kondor D, Pósfai M, Csabai I, Vattay G (2014) Do the rich get richer? An empirical analysis of the bitcoin transaction net‑
work. PLoS ONE 9(5):e97205. Corrected and republished from: Do the Rich Get Richer? An Empirical Analysis of the
Bitcoin Transaction Network. PLoS ONE 9(2):e86197
Kostakis V, Giotitsas C (2014) The (A)political economy of bitcoin. Triplec Comun Capit Crit 12(2):431–440
Kristoufek L (2013) BitCoin meets Google Trends and Wikipedia: quantifying the relationship between phenomena of the
Internet era. Sci Rep 3:3415
Kristoufek L (2015) What are the main drivers of the bitcoin price? Evidence from wavelet coherence analysis. PLoS ONE
10(4):e0123923. https:// doi. org/ 10. 1371/ journ al. pone. 01239 23
Krugman P (2018) Transaction costs and tethers: why I’m a crypto skeptic. In: NewYorkTimes. https:// www. nytim es. com/
2018/ 07/ 31/ opini on/ trans action‑ costs‑ and‑ tethe rs‑ why‑ im‑a‑ crypto‑ skept ic. html. Accessed 4 May 2019
Kuo T, Kim H, Ohno‑Machado L (2017) Blockchain distributed ledger technologies for biomedical and health care appli‑
cations. J Am Med Inform Assoc 24(6):1211–1220
Lee J (2017) BIDaaS: blockchain based ID as a service. IEEE Access 6:2274–2278
Li J, Li N, Peng J, Cui H, Wu Z (2019) Energy consumption of cryptocurrency mining: a study of electricity consumption in
mining cryptocurrencies. Energy 168:160–168. https:// doi. org/ 10. 1016/j. energy. 2018. 11. 046
Li T, Shin D, Wang B (2018) Cryptocurrency pump‑and‑dump schemes, unpublished manuscript, University of North
Carolina. SSRN: https:// ssrn. com/ abstr act= 32670 41 or doi. org/ 10. 2139/ ssrn. 32670 41
Page 30 of 31
García‑Corraletal. Financial Innovation (2022) 8:2
Lietaer BA, Hallsmith W (2006) Community currency guide. Available via DIALOG. http:// commu nity‑ curre ncy. info/ wp‑
conte nt/ uploa ds/ 2014/ 12/ lieta er‑ halls mith‑ commu nity‑ curre ncy‑ guide. pdf. Accessed 5 Nov 2018
Luu L, Chu DH, Olickel H, Saxena P, Hobor A (2016) Making smart contracts smarter. In: 2016 ACM SIGSAC conference on
computer and communications security, pp 254–269. https:// doi. org/ 10. 1145/ 29767 49. 29783 09
Manterola C, Pineda V, Vial M, Losada H (2005) ¿Es el factor de impacto un índice apropiado para determinar el grado de
evidencia de estudios sobre procedimientos terapéuticos en revistas quirúrgicas? Cir Esp 78(2):96–99
Merediz‑Solà I, Bariviera A (2019) A bibliometric analysis of bitcoin scientific production. Res Int Bus Financ 50:294–305.
https:// doi. org/ 10. 1016/j. ribaf. 2019. 06. 008
Miers, I, Garman C, Green M et al. (2013) Zerocoin: anonymous distributed e‑cash from bitcoin. In: 2012 IEEE symposium
on security and privacy, pp 397–411. https:// doi. org/ 10. 1109/ SP. 2013. 34
Nadarajah S, Chu J (2017) On the inefficiency of Bitcoin. Econ Let 150(C):6–9
Nakamoto S (2008) Bitcoin: a peer‑to‑peer electronic cash system. Available via DIALOG. http:// bitco in. org/ bitco in. pdf.
Accessed 30 Dec 2018
Navas‑Navarro S (2015) Un mercado financiero floreciente: el del dinero virtual no regulado (Especial atención a los
BITCOINS). Rev CESCO De Derecho De Consumo 13:79–115
Neslihanoglu S (2021) Linearity extensions of the market model: a case of the top 10 cryptocurrency prices during the
pre‑COVID‑19 and COVID‑19 periods. Financ Innov 7:38. https:// doi. org/ 10. 1186/ s40854‑ 021‑ 00247‑z
Nvidia Corporation (2021). https:// www. nvidia. com/ en‑ us/ cmp/. Accessed 24 Feb 2021
Ober M, Katzenbeisser S, Hamacher K (2013) Structure and anonymity of the bitcoin transaction graph. Future Internet
5(2):237–250. https:// doi. org/ 10. 3390/ fi502 0237
Orastean R, Silvia CM, Sava R (2019) Bitcoin in the scientific literature—a bibliometric study. Stud Bus Econ 14(3):160–174.
https:// doi. org/ 10. 2478/ sbe‑ 2019‑ 0051
Phillip A, Chan JSK, Peiris S (2018) A new look at cryptocurrencies. Econ Lett 163:6–9. https:// doi. org/ 10. 1016/j. econl et.
2017. 11. 020
Polasik M, Piotrowska AI, Wisniewski TP, Kotkowski R, Lightfoot J (2015) Price fluctuations and the use of bitcoin: an
empirical inquiry. Int J Electron Commer 20(1):9–49. https:// doi. org/ 10. 1080/ 10864 415. 2016. 10614 13
Van Raan AF (2014) Advances in bibliometric analysis: research performance assessment and science mapping. In: Block‑
mans W, Engwall L, Weaire D (eds) Bibliometrics. Use and abuse in the review of research performance. Wenner‑
Gren International Series, Portland Press, pp 17–28
Riehmann P, Hanfler M, Froehlich B (2005) Interactive Sankey diagrams. In: IEEE symposium on information visualization.
INFOVIS 2005. Minneapolis, MN, USA, 2005, pp 233–240.https:// doi. org/ 10. 1109/ INFVIS. 2005. 15321 52
European Central Bank (2012) Virtual Currency Schemes. DIALOG. https:// www. ecb. europa. eu/ pub/ pdf/ other/ virtu alcur
rency schem es201 210en. pdf. Accessed 9 Jan 2019
Selgin G (2013) Synthetic commodity money. In: SSRN https:// doi. org/ 10. 2139/ ssrn. 20001 18. Accessed 16 May 2019
Shen C, Chang LC, Su, TC (2020) Research development of Bitcoin: a network and concept linking analysis. Library Hi
Tech, vol ahead‑of‑print No. ahead‑of‑print. https:// doi. org/ 10. 1108/ LHT‑ 10‑ 2019‑ 0210
Sikorski J, Haughton J, Kraft M (2017) Blockchain technology in the chemical industry: machine‑to‑machine electricity
market. Appl Energy 195:234–246
Tönnissen S, Teuteberg F (2018) Using blockchain technology for business processes in purchasing—concept and case
study‑based evidence. In: Abramowicz W, Paschke A (eds) Business information systems. BIS 2018. Lecture notes in
business information processing 320. https:// doi. org/ 10. 1007/ 978‑3‑ 319‑ 93931‑5_ 18
Tschorsch F, Scheuermann N (2016) Bitcoin and beyond: a technical survey on decentralized digital currencies. IEEE Com‑
mun Surv Tutorials 18(3):2084–2123. https:// doi. org/ 10. 1109/ COMST. 2016. 25357 18
Turner AB, McCombie S, Uhlmann AJ (2019) A target‑centric intelligence approach to WannaCry 2.0. J Money Laund
Control 22(4):646–665. https:// doi. org/ 10. 1108/ JMLC‑ 01‑ 2019‑ 0005
Urquhart A (2016) The inefficiency of bitcoin. Econ Lett 148:80–82. https:// doi. org/ 10. 1016/j. econl et. 2016. 09. 019
Urquhart A (2018) What causes the attention of bitcoin? Econ Lett 166:40–44. https:// doi. org/ 10. 1016/j. econl et. 2018. 02
Van Alstyne M (2014) Why bitcoin has value. Commun ACM 57(5):30–32. https:// doi. org/ 10. 1145/ 25942 88
Wang Q, Li X, Yu Y (2018) Anonymity for bitcoin from secure escrow address. IEEE Access 6:12336–12341. https:// doi. org/
10. 1109/ ACCESS. 2017. 27875 63
Xu JJ (2016) Are blockchains immune to all malicious attacks? Financ Innov 2:25. https:// doi. org/ 10. 1186/
s40854‑ 016‑ 0046‑5
Xu M, Chen X, Kou G (2019) A systematic review of blockchain. Financ Innov 5:27. https:// doi. org/ 10. 1186/
s40854‑ 019‑ 0147‑z
Yin W, Wen Q, Li W, Huan Z, Jin Z (2017) An anti‑quantum transaction authentication approach in blockchain. IEEE Access
Yli‑Huumo J, Ko D, Choi S, Park S, Smolander K (2016) Where is current research on blockchain technology—a systematic
review. PLoS ONE 11(10):1–27
Zhang J, Yu Q, Zheng F, Long C, Lu Z, Duan Z (2016) Comparing keywords plus of WOS and author keywords: a case
study of patient adherence research. J Assoc Inf Sci Technol 67(4):967–972. https:// doi. org/ 10. 1002/ asi. 23437
Zhang W, Wang P, Li X, Shen D (2018) The inefficiency of cryptocurrency and its cross‑correlation with Dow Jones Indus‑
trial Average. Physica A 510:658–670. https:// doi. org/ 10. 1016/j. physa. 2018. 07. 032
Zhang R, Xue R, Li L (2019) Security and privacy on blockchain. ACM Comput Surv 52(3):51. https:// doi. org/ 10. 1145/
33164 81
Zhang X, Lu F, Tao R, Wang S (2021) The time‑varying causal relationship between the Bitcoin market and internet atten‑
tion. Financ Innov 7:66. https:// doi. org/ 10. 1186/ s40854‑ 021‑ 00275‑9
Zhao JL, Fan S, Yan J (2016) Overview of business innovations and research opportunities in blockchain and introduction
to the special issue. Financ Innov 2:28. https:// doi. org/ 10. 1186/ s40854‑ 016‑ 0049‑2
Zheng ZB, Xie SA, Dai HN, Chen XP, Wang HM (2018) Blockchain challenges and opportunities: a survey International. J
Web Grid Serv 14(4):352–375. https:// doi. org/ 10. 1504/ IJWGS. 2018. 095647
Page 31 of 31
García‑Corraletal. Financial Innovation (2022) 8:2
Zimmer Z (2017) Bitcoin and potosi silver historical perspectives on cryptocurrency. Technol Cult 58(2):307–334. https://
doi. org/ 10. 1353/ tech. 2017. 0038
Zulfiqar N, Gulzar S (2021) Implied volatility estimation of bitcoin options and the stylized facts of option pricing. Financ
Innov 7:67. https:// doi. org/ 10. 1186/ s40854‑ 021‑ 00280‑y
Zyskind G, Nathan O, Pentland A (2015) Decentralizing privacy: using blockchain to protect personal data. In: 2015 IEEE
security and privacy workshops, San Jose, CA, pp 180–184
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Conference Paper
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O conhecimento científico desenvolve-se a partir do trabalho construído e publicado por pesquisadores ao longo do tempo. Uma vez que trabalhos científicos já publicados são a base para o desenvolvimento de novas linhas de pesquisa, estudos bibliométricos se fazem importantes para a amplificação do conhecimento científico. Entretanto, muitas vezes os fluxos de pesquisa são volumosos, fragmentados e controversos. Portanto, para descomplicar o trabalho do pesquisador, o presente artigo tem por objetivo apresentar um tutorial para o uso do Bibliometrix: um pacote desenvolvido em linguagem R para mapeamento científico e estudos bibliométricos. O foco deste trabalho está nas etapas de coleta, análise e visualização de dados bibliométricos, e para isso, utilizou-se um exemplo mesclando dados obtidos das bases Scopus e Web of Science (WoS). Foram analisados 730 documentos da base Scopus e 814 da WoS na área de métodos de apoio multicritério à decisão (AMD) aplicados em problemas militares. Como resultado propõe-se um fluxograma detalhado dos processos de coleta, análise e visualização dos dados.
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The recently developed Bitcoin futures and options contracts in cryptocurrency derivatives exchanges mark the beginning of a new era in Bitcoin price risk hedging. The need for these tools dates back to the market crash of 1987, when investors needed better ways to protect their portfolios through option insurance. These tools provide greater flexibility to trade and hedge volatile swings in Bitcoin prices effectively. The violation of constant volatility and the log-normality assumption of the Black–Scholes option pricing model led to the discovery of the volatility smile, smirk, or skew in options markets. These stylized facts; that is, the volatility smile and implied volatilities implied by the option prices, are well documented in the option literature for almost all financial markets. These are expected to be true for Bitcoin options as well. The data sets for the study are based on short-dated Bitcoin options (14-day maturity) of two time periods traded on Deribit Bitcoin Futures and Options Exchange, a Netherlands-based cryptocurrency derivative exchange. The estimated results are compared with benchmark Black–Scholes implied volatility values for accuracy and efficiency analysis. This study has two aims: (1) to provide insights into the volatility smile in Bitcoin options and (2) to estimate the implied volatility of Bitcoin options through numerical approximation techniques, specifically the Newton Raphson and Bisection methods. The experimental results show that Bitcoin options belong to the commodity class of assets based on the presence of a volatility forward skew in Bitcoin option data. Moreover, the Newton Raphson and Bisection methods are effective in estimating the implied volatility of Bitcoin options. However, the Newton Raphson forecasting technique converges faster than does the Bisection method.
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The increasing attention on Bitcoin since 2013 prompts the issue of possible evidence for a causal relationship between the Bitcoin market and internet attention. Taking the Google search volume index as the measure of internet attention, time-varying Granger causality between the global Bitcoin market and internet attention is examined. Empirical results show a strong Granger causal relationship between internet attention and trading volume. Moreover, they indicate, beginning in early 2018, an even stronger impact of trading volume on internet attention, which is consistent with the rapid increase in Bitcoin users following the 2017 Bitcoin bubble. Although Bitcoin returns are found to strongly affect internet attention, internet attention only occasionally affects Bitcoin returns. Further investigation reveals that interactions between internet attention and returns can be amplified by extreme changes in prices, and internet attention is more likely to lead to returns during Bitcoin bubbles. These empirical findings shed light on cryptocurrency investor attention theory and imply trading strategy in Bitcoin markets.
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This research investigates the appropriateness of the linear specification of the market model for modeling and forecasting the cryptocurrency prices during the pre-COVID-19 and COVID-19 periods. Two extensions are offered to compare the performance of the linear specification of the market model (LMM), which allows for the measurement of the cryptocurrency price beta risk. The first is the generalized additive model, which permits flexibility in the rigid shape of the linearity of the LMM. The second is the time-varying linearity specification of the LMM (Tv-LMM), which is based on the state space model form via the Kalman filter, allowing for the measurement of the time-varying beta risk of the cryptocurrency price. The analysis is performed using daily data from both time periods on the top 10 cryptocurrencies by adjusted market capitalization, using the Crypto Currency Index 30 (CCI30) as a market proxy and 1-day and 7-day forward predictions. Such a comparison of cryptocurrency prices has yet to be undertaken in the literature. The empirical findings favor the Tv-LMM, which outperforms the others in terms of modeling and forecasting performance. This result suggests that the relationship between each cryptocurrency price and the CCI30 index should be locally instead of globally linear, especially during the COVID-19 period.
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Bitcoin (BTC) is a major virtual currency. Using weekly data over the 2010–2013 period, we analyze a BTC investment from the standpoint of a US investor with a diversified portfolio including both traditional assets (worldwide stocks, bonds, hard currencies) and alternative investments (commodities, hedge funds, real estate). Over the period under consideration, BTC investment had highly distinctive features, including exceptionally high average return and volatility. Its correlation with other assets was remarkably low. Spanning tests confirm that BTC investment offers significant diversification benefits. We show that the inclusion of even a small proportion of BTCs may dramatically improve the risk-return trade-off of well-diversified portfolios. Results should however be taken with caution as the data may reflect early-stage behavior that may not last in the medium or long run.
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This paper investigates whether Tether, a digital currency pegged to the U.S. dollar, influenced Bitcoin and other cryptocurrency prices during the 2017 boom. Using algorithms to analyze blockchain data, we find that purchases with Tether are timed following market downturns and result in sizable increases in Bitcoin prices. The flow is attributable to one entity, clusters below round prices, induces asymmetric autocorrelations in Bitcoin, and suggests insufficient Tether reserves before month‐ends. Rather than demand from cash investors, these patterns are most consistent with the supply‐based hypothesis of unbacked digital money inflating cryptocurrency prices.
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Since 2012, there has been growing interest in bitcoin scientific research from different fields, including computer science and engineering, economics, business and finance, law and regulatory. The purpose of this paper is to evaluate bitcoin literature based on the structures and networks of science, as a first step in the research of this new phenomenon. Analysing the growing scientific literature on bitcoin published between 2012 and 2019, we provided useful insights on academic research in this field regarding publication year, type and category, authors, journals and citations. The source of the 887 documents which support the study was Web of Science Core Collection. Using VOSviewer software we have designed bibliometric maps based on text and bibliographic data. Our study provides a knowledge area map that identifies and evaluates the links between authors and countries distribution, the conceptual structure of the field, the structure and connections of most cited papers and journals. Resuming our findings, we note a concentration of the interest on some keywords (bitcoin, cryptocurrency, blockchain) and on some influential authors (with more than 100 citations per article). As a pure expression of digital economy, the research on bitcoin as an economic concept counts only 33.5% from the total contributions in the field.
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Abstract Blockchain is considered by many to be a disruptive core technology. Although many researchers have realized the importance of blockchain, the research of blockchain is still in its infancy. Consequently, this study reviews the current academic research on blockchain, especially in the subject area of business and economics. Based on a systematic review of the literature retrieved from the Web of Science service, we explore the top-cited articles, most productive countries, and most common keywords. Additionally, we conduct a clustering analysis and identify the following five research themes: “economic benefit,” “blockchain technology,” “initial coin offerings,” “fintech revolution,” and “sharing economy.” Recommendations on future research directions and practical applications are also provided in this paper.
Purpose This study aims to provide researchers a holistic approach for comprehensive understanding of the Bitcoin-related research by discovering its trends, subjects, relations, keywords and concepts. Design/methodology/approach An integrated approach of bibliometric analysis, network analysis and concept linking analysis was proposed for exploring Bitcoin-related studies from 70 countries in the Scopus database. Findings The bibliometric analysis shows that electronic money and blockchain are the mainstream issues of Bitcoin, and the domain distribution of the literature is mainly in engineering-related fields. Through the network analysis of cocitations, co-occurrences and cowords, research clusters were discovered respectively from different perspectives. The authors also have mastered a multilevel concept linking diagram for six related major concepts. Originality/value The major contribution of this research is about providing an integrated and comprehensive approach to extract the mainstream issues that can help researchers conduct Bitcoin-relevant research. This study shows the development trend, context and clusters of Bitcoin-related studies from various perspectives networks and produces a visual concept linking diagram that will enable researchers to quickly understand the contextual relationship between Bitcoin keywords during literature analysis. In addition, the most crucial studies in the main topics are extracted to save the considerable time and labor that would be required to manually read all the literature and summarize the issues.
Purpose This paper aims to demonstrate the utility of a target-centric approach to intelligence collection and analysis in the prevention and investigation of ransomware attacks that involve cryptocurrencies. The paper uses the May 2017 WannaCry ransomware usage of the Bitcoin ecosystem as a case study. The approach proves particularly beneficial in facilitating information sharing and an integrated analysis across intelligence domains. Design/methodology/approach This study conducted data collection and analysis of the component Bitcoin elements of the WannaCry ransomware attack. A note of both technicalities of Bitcoin operations and current models for sharing cyber intelligence was made. Our analysis builds on and further develops current definitions and strategies for sharing cyber threat intelligence. It uses the problem definition model (PDM) and generic target network model (TNM) to create an analytic framework for the WannaCry ransomware attack scenario, allowing analysts the ability to test their hypotheses and integrate and share data for collaborative investigation. Findings Using a target-centric intelligence approach to WannaCry 2.0 shows that it is possible to model the intelligence problem of collecting and analysing data related to inflows and outflows of Bitcoin-related ransomware transactions. Bitcoin transactions form graph networks and allow to build a target network model for collecting, analysing and sharing intelligence with multiple stakeholders. Although attribution and anonymity prevail under cryptocurrency usage, there is a means for developing transaction walks using this method to target nefarious cryptocurrency exchanges where criminals are inclined to cash out their proceeds of crime. Originality/value The application of a target-centric intelligence approach to the cryptocurrency components of a ransomware attack provides a framework for intelligence units to break down the problem in the financial domain and model the network behaviour of illicit Bitcoin transactions relating to ransomware.
Blockchain offers an innovative approach to storing information, executing transactions, performing functions, and establishing trust in an open environment. Many consider blockchain as a technology breakthrough for cryptography and cybersecurity, with use cases ranging from globally deployed cryptocurrency systems like Bitcoin, to smart contracts, smart grids over the Internet of Things, and so forth. Although blockchain has received growing interests in both academia and industry in the recent years, the security and privacy of blockchains continue to be at the center of the debate when deploying blockchain in different applications. This article presents a comprehensive overview of the security and privacy of blockchain. To facilitate the discussion, we first introduce the notion of blockchains and its utility in the context of Bitcoin-like online transactions. Then, we describe the basic security properties that are supported as the essential requirements and building blocks for Bitcoin-like cryptocurrency systems, followed by presenting the additional security and privacy properties that are desired in many blockchain applications. Finally, we review the security and privacy techniques for achieving these security properties in blockchain-based systems, including representative consensus algorithms, hash chained storage, mixing protocols, anonymous signatures, non-interactive zero-knowledge proof, and so forth. We conjecture that this survey can help readers to gain an in-depth understanding of the security and privacy of blockchain with respect to concept, attributes, techniques, and systems.