E-ISSN:2250-0758
P-ISSN:2394-6962

Research Article

Cryptocurrency

International Journal of Engineering and Management Research

2026 Volume 16 Number 2 April
Publisherwww.vandanapublications.com

A Bibliometric Analysis on Cryptocurrency Taxation

Maurya A1*, Kaushal SK2
DOI:10.31033/IJEMR/16.2.2026.1893

1* Anubhav Maurya, Research Scholar, Department of Management, FMS, University of Lucknow, Lucknow, Uttar Pradesh, India.

2 Shailesh Kumar Kaushal, Associate Professor, Department of Management, FMS, University of Lucknow, Lucknow, Uttar Pradesh, India.

The primary purpose is to trace the progression of scholarly research on cryptocurrency taxation, uncovering prevailing patterns, influential contributors, yearly scientific output and citations, most relevant sources, thematic analysis and cooccurrence networks from 2010 to 2025.
Leveraging a systematic search on Scopus, our final dataset comprises 115 unique documents, with the majority of publications being highly recent (average age of 2.95 years) and exhibiting a robust annual growth rate of 18.65%. The analysis reveals that the field is highly collaborative (average of 2.7 co-authors per paper) and gaining significant scholarly attention, as evidenced by a promising average of 9.548 citations per document. The thematic structure of the literature, mapped through keyword co-occurrence and strategic diagrams, identifies "cryptocurrency," "blockchain," and "bitcoin" as the core, most central themes. The research is highly multidisciplinary, with a strong focus on regulatory, legal, and financial challenges surrounding taxation, anti-money laundering, and the classification of digital assets. While a dominant research source exists, the high dispersion of publications across 85 distinct sources suggests a fragmented but rapidly maturing field.

Keywords: Cryptocurrency, Bitcoin, Blockchain, Tax, Taxation, Digital Currency, Virtual Currency, Crypto Assets, Crypto

Corresponding Author How to Cite this Article To Browse
Anubhav Maurya, Research Scholar, Department of Management, FMS, University of Lucknow, Lucknow, Uttar Pradesh, India.
Email: 		Maurya A, Kaushal SK, A Bibliometric Analysis on Cryptocurrency Taxation. Int J Engg Mgmt Res. 2026;16(2):90-97.
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https://ijemr.vandanapublications.com/index.php/j/article/view/1893

Manuscript Received Review Round 1 Review Round 2 Review Round 3 Accepted
2026-03-03 2026-03-18 2026-04-04
Conflict of Interest Funding Ethical Approval Plagiarism X-checker Note
None Nil Yes 4.71

© 2026 by Maurya A, Kaushal SK and Published by Vandana Publications. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/ unported [CC BY 4.0].

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Download PDFBack To Article1. Introduction2. Research
Technique3. Limitations
of the Study4. ConclusionReferences
Maurya A, et al. A Bibliometric Analysis on Cryptocurrency Taxation

1. Introduction

The unprecedented rise of cryptocurrencies and their underlying blockchain technology has fundamentally altered the global financial landscape, presenting both opportunities and complex challenges for governments and tax authorities. Blockchain is a foundational technology that provides a decentralized and cryptographically secured distributed ledger. This unique structure allows for the immutable and transparent recording of transactions without relying on a central intermediary, thereby fostering trust in a trustless digital environment (Iansiti & Lakhani, 2017). Beyond its initial application, the core properties of blockchain offer transformative potential for various industries, including supply chain management, smart contracts, and digital identity verification (Iansiti & Lakhani, 2017). The first and most famous implementation of this technology was detailed in the original proposal for Bitcoin, which described a peer-to-peer electronic cash system (Nakamoto, 2008). Unlike traditional assets, the decentralized, borderless, and often pseudonymous nature of digital currencies like Bitcoin and Ethereum complicates their integration into conventional tax systems. Built upon Blockchain technology, cryptocurrencies are digital assets that function as a medium of exchange. Unlike traditional fiat currencies, they are decentralized and secured through cryptography, which verifies transactions and controls the creation of new units (Antonopoulos, 2017). This has created a global regulatory vacuum, prompting policymakers and tax agencies to grapple with fundamental questions about how to classify and tax these novel assets. As the market for digital assets expands, understanding the academic dialogue surrounding their fiscal treatment becomes crucial for policymakers, tax professionals, and academics alike.

A primary characteristic of major cryptocurrencies like Bitcoin is their extreme price volatility. This financial instability makes them a high-risk, speculative asset class and challenges their viability as a stable store of value compared to traditional currencies (Baur & Dimpfl, 2021).

The rise of digital assets has created significant challenges for tax authorities globally. In many countries, tax policy classifies cryptocurrencies as property rather than currency.

This crucial distinction means that when a cryptocurrency is sold, traded, or used for a purchase, the owner may realize a taxable capital gain or loss on the transaction (Hughes, 2018; Kaal, 2020).

This classification creates notable complexities for tax compliance. Users must track the cost basis for every asset across a high volume of transactions, a task further complicated by activities common in decentralized finance (DeFi), such as staking and liquidity mining (Sharfman, 2022). Formulating effective tax policy is further challenged by the pseudo-anonymous and borderless nature of cryptocurrencies, which hinders enforcement and creates jurisdictional ambiguity (Marian, 2015). The lack of international consensus on tax rules can lead to regulatory arbitrage, highlighting the need for global cooperation and frameworks like the OECD's Crypto-Asset Reporting Framework (CARF) to ensure consistent enforcement across borders (OECD, 2022).

Despite the growing importance of this topic, a holistic understanding of its intellectual structure and thematic evolution remains nascent. This paper addresses this gap by conducting a bibliometric analysis to systematically map the research landscape of cryptocurrency taxation. By employing a rigorous methodology that includes a comprehensive search strategy on leading academic database (Scopus) and a detailed data refinement process, this study offers a quantitative and qualitative overview of the field's key characteristics, influential themes, and future trajectories.

The research will specifically explore:

1. Scientific Production and Growth: We will analyze the annual publication trend from 2010 to 2025 to illustrate the field's rapid expansion and identify key growth periods.
2. Influential Authors and Sources: We will pinpoint the most productive authors and journals to identify the key contributors and platforms shaping the academic discourse.
3. Thematic Analysis: We will use thematic maps and co-occurrence networks to visualize the core research topics, identify emerging areas, and understand the relationships between different conceptual clusters (e.g., regulatory frameworks, financial crime, and asset classification).


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By providing this structured analysis, our study aims to serve as a foundational reference for researchers, offering a clear snapshot of a complex and rapidly evolving domain. The findings will be invaluable for identifying future research directions and informing policy debates on the appropriate fiscal treatment of digital currencies.

This research is highly relevant due to its interdisciplinary approach, which combines insights from economics, finance, business management and accounting. The growing importance of digital assets makes it essential to establish clear tax guidelines for activities like mining and trading. Currently, there is no consistent global approach to crypto taxation, which makes it hard to determine the value of these assets for tax purposes.

2. Research Technique

1. Keywords and Selection of Data

The foundation of this study's findings rests upon a rigorous and systematic review of existing academic literature on cryptocurrency taxation. To ensure the highest degree of credibility and scholarly validation, I developed a comprehensive search strategy in the most respected academic database: Scopus. The platform is indispensable for researchers, as it exclusively indexes high-quality, peer-reviewed publications, thereby guaranteeing that the sources included in this study meet stringent quality control standards. Furthermore, built-in tools for citation tracking and impact measurement were instrumental in identifying the most influential manuscripts in this specialized field.

Search was meticulously designed using a Boolean string to capture all relevant publications, including those using a wide range of terminologies. The search query—(“crypto” OR “cryptocurrency” OR “virtual currency” OR “digital currency”) AND (“tax” OR “taxation”)—was specifically crafted to retrieve articles addressing both direct and indirect taxation of cryptocurrencies. This broad approach was vital to ensure a comprehensive overview of the research landscape. The literature search was not limited to a single format; it included a wide range of academic publications such as journal articles, reviews, preprints, conference papers, and book chapters, all of which were required to be in English to maintain consistency and global accessibility. The data was extracted from Scopus on September 11, 2025, and the

analysis covers a significant period of industry growth, spanning from 2010 to 2025 for Scopus. Ultimately, this detailed process resulted in the identification of 115 research papers, which form the complete dataset for this study. The precise inclusion and exclusion criteria applied during this search are further detailed in Figure below.

PRISMA ANALYSIS

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2. Data Refinement and Relevance Assessment

Following the initial data collection from electronic databases, a multi-stage process of refinement and relevance assessment was undertaken to ensure the quality and focus of our analysis. The initial search, using the specified key terms and filters, yielded a total of 319 documents. A careful review of these results, based on the specific criteria outlined in the figure, led to the exclusion of documents that were not directly relevant to our research topic. Specifically, we filtered the results to include only articles in English, which reduced the number of documents from 319 to 285.

To guarantee that every included paper was aligned with our core objective—to analyze research on cryptocurrency taxation—we performed a detailed screening of the documents. Papers were meticulously evaluated to confirm they contained our key terms ("cryptocurrency" and "taxation") within a relevant context. This rigorous screening process resulted in a final selection of 175 papers, which were deemed relevant to our study.


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Subsequently, a more focused review of these 175 papers was conducted to select the most relevant articles for our in-depth analysis. This final relevance assessment narrowed the collection down to 115 highly relevant articles. This final set of papers formed the basis for our bibliographic study.

Exploratory Bibliographic Study

1) Main Information

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The data covers a 15-year period from 2010 to 2025, but with an average document age of only 2.95 years, indicating that the majority of research is very recent. The inclusion of 2025 suggests that the dataset may contain "articles in press" or pre-prints. With a total of 115 documents, the collection is considered small to medium-sized, hinting at either a highly specialized niche or a very new field of study. The field is expanding quickly, as shown by its robust annual growth rate of 18.65%. The research is published across a wide range of outlets, with 85 distinct sources for 115 documents, suggesting a high dispersion of publications rather than concentration in a few key journals. The document types are predominantly journal articles (77.4%), followed by book chapters (13%) and review articles (5.2%). The presence of review articles suggests the field is starting to consolidate its knowledge base. There are also a small number of conference papers (3.5%).The research is a highly collaborative effort, with 292 unique authors for 115 documents and an average of 2.7 co-authors per document. This indicates that most studies are conducted by teams rather than individuals. About a quarter of the documents are single-authored, showing there is still room for individual contributions. Approximately one-fifth of the documents (21.74%) involve international collaborations, pointing to a healthy level of global engagement. The average of 9.548 citations per document is considered promising, especially given the young age of the collection, and suggests the research is quickly gaining traction. The thematic content is rich and diverse, with 584 author-assigned keywords,

which is much higher than the number of automatically extracted keywords (207). This diversity suggests a complex or multidisciplinary research area with many distinct sub-themes.

2) Yearly Scientific Output and Citations

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Annual Scientific Production 📈

The first graph, titled Annual Scientific Production, displays the number of articles published each year from 2010 to 2024. The data shows a period of low, stable output from 2010 to 2013, followed by a gradual increase until a significant surge from 2018 to 2024. Production peaked in 2023 with approximately 28 articles. Following this peak, there was a sharp decline in 2024, with output dropping to about 12 articles. This could suggest a recent shift in research focus, a change in publication trends, or that data for 2024 is incomplete.

Average Citations per Year 📊

The second graph, titled Average Citations per Year, illustrates the average number of citations received by articles published in a given year. From 2010 to 2014, the average citations remained very low, barely above zero. The numbers began to climb in 2015, showing steady growth until a dramatic spike in 2020, where the average citations per article reached a high of about 7.5. This indicates that the articles published in 2020 were exceptionally impactful and widely referenced. After this peak, the average citations fell sharply in 2021 and continued to decline, dropping to less than 1 citation per article by 2024. This trend suggests that while recent years have seen an increase in article production, the impactfulness of those articles (as measured by citations) has not kept pace and has, in fact, decreased significantly since the 2020 peak.


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3) Most Relevant sources

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The data is presented in descending order, with the most productive source at the top and the least at the bottom.

  • The source at the top whose name is missing, is by far the most significant, having produced 12 documents. This is a considerable outlier compared to the other sources, which are all clustered at the lower end of the scale.
  • The next two sources below the most productive one each have 4 documents.
  • The remaining sources shown on the graph are all less productive, with each having either 2 or 3 documents.

The distribution of documents is highly skewed, with one source dominating the total output. This suggests that the research or information presented in the graph is heavily concentrated in a single publication or platform, with a long tail of other sources contributing a much smaller number of documents.

4) Most Relevant Authors

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All listed authors—including "BRUNO, HERNÁNDEZ JULIO," "ILLERA, DANIEL CAMARGO," "VAN DER GRAF, WILLEM A.," and other have the same No. of Documents, which is exactly 2. This suggests that all the authors shown are equally relevant, based on this metric, as they have each authored two documents. The chart is effectively a ranked list where all the top entries are tied.

5) Most Relevant Affiliations

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Top Affiliations: Four institutions—Universitas Sumatera Utara, Universitatea de Vest din Timișoara, University Malaya, and Universiti Utara Malaysia. Each have the highest count, with 8 articles.

Mid-Tier Contributors: RMIT University follows closely with 7 articles, while North-Caucasus Federal University and Universitas Pendidikan Nasional each contributed 6 articles.

Other Affiliations: Christ University and the "Not Reported" category both account for 5 articles, with Brawijaya University at the lowest represented, with 4 articles.

6) Thematic Analysis

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Research themes based on two key metrics: Relevance degree (Centrality) and Development degree (Density).

The diagram is divided into four quadrants, each representing a different type of research theme:

  • Motor Themes (Top Right): These are the most important and well-developed themes in the field. They have a high centrality, meaning they are well-connected to other themes, and high density, indicating they have a well-established body of literature. The themes here, such as cryptocurrency, bitcoin, and blockchain, are the core subjects driving the research field forward. Other motor themes include legislation, costs, and ecosystems, which are critical topics directly linked to the main subject.
  • Niche Themes (Top Left): These themes are well-developed (high density) but have low centrality, meaning they are specialized and less connected to the main research field. They represent specific, focused areas of study. The themes in this quadrant, like tax revenue, tax transaction, virtual payment instruments, CBDC (Central Bank Digital Currency), digital currencies, and tax policy, suggest a deep but isolated focus on the financial and regulatory aspects of the subject.
  • Emerging or Declining Themes (Bottom Left): These themes have both low centrality and low density, indicating they are either new topics that have not yet been fully developed or older topics that are no longer actively researched. The themes here are crypto assets, virtual asset service providers, government technology, and pollution tax. These topics may be on the rise, gaining attention but not yet central to the field, or they may be losing relevance.
  • Basic Themes (Bottom Right): These are broad, foundational themes with high centrality but low density. They are highly connected to other themes, but their own body of research is not very cohesive or well-defined. They often represent foundational knowledge. Themes like monetary policy, tax system, inflation tax, central bank, and digital currency fall into this category. They are essential concepts that underpin the entire research domain but are not the primary focus of cutting-edge research.

The large cluster of foundational themes in the bottom right, with the prominent motor themes of cryptocurrency, Bitcoin, and blockchain in the top right, indicates that the core research area is well-established and a central driver of a larger field, which itself is built on fundamental economic and financial concepts. The niche themes show that researchers are also exploring more specialized, granular topics within this field, while the themes in the bottom-left quadrant are either new or have limited research interest.

7) Co-occurance Keyword Network

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Core Topics: The network is centered on three main terms: cryptocurrency, bitcoin, and blockchain. These are the largest nodes, indicating they are the most frequent and central topics in the research. They are also highly interconnected, showing their close relationship.

Thematic Clusters: The network is divided into four main research clusters:

  • Purple Cluster: Focuses on the socio-legal and financial aspects of cryptocurrencies. This includes topics like taxes, legal regulation, accounting, and privacy, showing a concern for how digital assets fit into existing systems.
  • Blue Cluster: This is a major community centered on bitcoin. It highlights research on regulation, taxation, and financial crime like money laundering and tax evasion. It's a key bridge, connecting the core cryptocurrency concept to its real-world governance challenges.
  • Green Cluster: This cluster is built around blockchain It includes technical aspects like decentralization and mining, as well as policy-related topics like Central Bank Digital Currency (CBDC), showing that the technology is studied for applications beyond just private cryptocurrencies.

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  • Red Cluster: This smaller group focuses on how to classify digital assets within traditional financial categories, such as securities, currency, and commodity. This shows an ongoing effort to define and categorize these new assets.

The research field is multidisciplinary, blending technology, law, and finance. There's a strong and dominant focus on regulatory and fiscal challenges, especially concerning taxation and financial crime. Bitcoin is the primary case study for these real-world regulatory discussions. Blockchain is not just a technology for cryptocurrencies also it is also being researched for broader applications like CBDCs.

3. Limitations of the Study

The bibliometric analysis, while providing a quantitative overview, has several inherent limitations that must be considered when interpreting its findings.

  • Database and Language Bias: The study relies exclusively on the Scopus Core Collection, which may not capture all relevant publications, particularly those in non-English languages or those published in journals not indexed by Scopus. This could lead to the exclusion of significant research from specific regions or academic communities, potentially skewing the findings.
  • Keyword Dependency: The search strategy's effectiveness hinges on the Boolean string used ("crypto" OR "cryptocurrency" OR "virtual currency" OR "digital currency") AND ("tax" OR "taxation"). This reliance on keywords might miss relevant articles that use alternative terminology or more nuanced phrasing, thus potentially providing an incomplete picture of the research landscape.
  • Focus on Quantitative Metrics: Bibliometric analysis prioritizes quantitative data like publication counts and citations. While this provides a structured overview, it does not assess the qualitative impact or the scholarly value of individual papers. A highly cited article, for instance, may not necessarily be the most influential or high-quality one in the field.

4. Conclusion

The bibliometric analysis provides a comprehensive and data-driven overview of the nascent research field of cryptocurrency taxation. It systematically maps the field's intellectual structure, key themes, and evolution.

  • A Rapidly Evolving Field: The research demonstrates that cryptocurrency taxation is a rapidly expanding academic field, as evidenced by a robust annual growth rate of 18.65% and a low average document age of just 2.95 years. While scientific output has seen a significant surge, particularly from 2018 to 2023, the impactfulness, as measured by average citations, peaked in 2020 and has since declined. This suggests that while more papers are being published, the field is still finding its foundational, high-impact contributions.
  • Collaborative and Multidisciplinary: The field is highly collaborative, with an average of 2.7 co-authors per paper, and is gaining significant scholarly attention with an average of 9.548 citations per document. The research is highly multidisciplinary, drawing insights from economics, finance, business management, and accounting.
  • Core Thematic Structure: Thematic analysis reveals that "cryptocurrency," "blockchain," and "bitcoin" are the core, most central themes. The research is heavily focused on the regulatory, legal, and financial challenges surrounding taxation, anti-money laundering, and the classification of digital assets. The findings highlight a fragmented but rapidly maturing field, with a high dispersion of publications across 85 distinct sources, indicating that the research is not yet concentrated in a few dominant journals.

References

[1] Antonopoulos, A. M. (2017). Mastering bitcoin: Programming the open blockchain. (2nd ed.). O'Reilly Media, Inc.

[2] Baur, D. G., & Dimpfl, T. (2021). The volatility of Bitcoin and other cryptocurrencies. In D. G. Baur, & T. Dimpfl (Eds.), Handbook of Blockchain, Digital Finance, and Inclusion, Volume 2: ChinaTech, Mobile Security, and Distributed Ledger (pp. 119-145). Academic Press.


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[3] Hughes, S. J. (2018). Cryptocurrency regulation and taxation. (3), 670-680. https://doi.org/10.1108/JFC-07-2017-0068

[4] Iansiti, M., & Lakhani, K. R. (2017). The truth about blockchain. Harvard Business Review, 95(1), 118–127.

[5] Kaal, W. A. (2020). Crypto-taxation: A puzzle of inconsistent doctrinal analogies. Wake Forest Journal of Business and Intellectual Property Law, 20(2), 173–216.

[6] Marian, O. (2015). A conceptual framework for the regulation of cryptocurrencies. University of Chicago Law Review Dialogue, 82, pp. 53–72.

[7] Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.pdf

[8] Organisation for Economic Co-operation and Development (OECD). (2022). Crypto-asset reporting framework and amendments to the common reporting standard. OECD Publishing. https://doi.org/10.1787/492ba036-en

[9] Sharfman, B. S. (2022). The taxation of digitally-native property. Nebraska Law Review, 101(1), 1-46. Retrieved from https://digitalcommons.unl.edu/nlr/vol101/iss1/2

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