research paper topics on blockchain

Research Topics & Ideas

Blockchain & Cryptocurrency

If you’re just starting out exploring blockchain-related topics for your dissertation, thesis or research project, you’ve come to the right place. In this post, we’ll help kickstart your research by providing a hearty list of research topics and ideas related to blockchain and crypto, including examples from recent studies.

PS – This is just the start…

We know it’s exciting to run through a list of research topics, but please keep in mind that this list is just a starting point . These topic ideas provided here are intentionally broad and generic , so keep in mind that you will need to develop them further. Nevertheless, they should inspire some ideas for your project.

To develop a suitable research topic, you’ll need to identify a clear and convincing research gap , and a viable plan to fill that gap. If this sounds foreign to you, check out our free research topic webinar that explores how to find and refine a high-quality research topic, from scratch. Alternatively, consider our 1-on-1 coaching service .

Blockchain & Crypto-Related Research Topics

• The application of blockchain technology in securing electronic health records.
• Investigating the potential of smart contracts in automating insurance claims.
• The impact of blockchain on the traceability and transparency in supply chain management.
• Developing a blockchain-based voting system for enhancing electoral transparency.
• The role of blockchain in combating counterfeit goods in the luxury goods market.
• Assessing the security implications of quantum computing on cryptocurrency encryption.
• The use of blockchain for royalty distribution in the music industry.
• Investigating the scalability challenges of Ethereum and potential solutions.
• The impact of blockchain technology on cross-border remittances in developing countries.
• Developing a blockchain framework for real-time IoT device management.
• The application of tokenization in real estate asset management.
• Examining regulatory challenges for cryptocurrency exchanges in different jurisdictions.
• The potential of decentralized finance (DeFi) in disrupting traditional banking.
• Investigating the environmental impact of Bitcoin mining and potential sustainable alternatives.
• The role of blockchain in enhancing data security in cloud computing.
• Analysing the impact of Initial Coin Offerings (ICOs) on traditional venture capital funding.
• The use of blockchain for enhancing transparency in charitable organizations.
• Assessing the potential of blockchain in combating online identity theft and fraud.
• Investigating the use of cryptocurrency in illicit trade and its regulatory implications.
• The application of blockchain in automating and securing international trade finance.
• Analysing the efficiency of different consensus algorithms in blockchain networks.
• The potential of blockchain technology in managing intellectual property rights.
• Developing a decentralized platform for peer-to-peer energy trading using blockchain.
• Investigating the security vulnerabilities of various cryptocurrency wallets.
• The role of blockchain in revolutionizing the gaming industry through in-game assets.

Blockchain & Crypto Research Ideas (Continued)

• Assessing the impact of cryptocurrency adoption on monetary policy and banking systems.
• Investigating the integration of blockchain technology in the automotive industry for vehicle history tracking.
• The use of blockchain for secure and transparent public record keeping in government sectors.
• Analysing consumer adoption patterns and trust issues in cryptocurrency transactions.
• The application of blockchain in streamlining and securing online voting systems.
• Developing a blockchain-based platform for academic credential verification.
• Examining the impact of blockchain on enhancing privacy and security in social media platforms.
• The potential of blockchain in transforming the retail industry through supply chain transparency.
• Investigating the feasibility of central bank digital currencies (CBDCs).
• The use of blockchain in creating tamper-proof digital evidence systems for law enforcement.
• Analysing the role of cryptocurrency in financial inclusion in underbanked regions.
• Developing a blockchain solution for secure digital identity management.
• Investigating the use of blockchain in food safety and traceability.
• The potential of blockchain in streamlining and securing e-commerce transactions.
• Assessing the legal and ethical implications of smart contracts.
• The role of blockchain in the future of freelance and gig economy payments.
• Analysing the security and efficiency of cross-chain transactions in blockchain networks.
• The potential of blockchain for digital rights management in the media and entertainment industry.
• Investigating the impact of blockchain technology on the stock market and asset trading.
• Developing a blockchain framework for transparent and efficient public sector audits.
• The use of blockchain in ensuring the authenticity of luxury products.
• Analysing the challenges and opportunities of blockchain implementation in the healthcare sector.
• The potential of blockchain in transforming the logistics and transportation industry.
• Investigating the role of blockchain in mitigating risks in supply chain disruptions.
• The application of blockchain in enhancing transparency and accountability in non-profit organizations.

Recent Blockchain-Related Studies

While the ideas we’ve presented above are a decent starting point for finding a  research topic, they are fairly generic and non-specific. So, it helps to look at actual studies in the blockchain and cryptocurrency space to see how this all comes together in practice.

Below, we’ve included a selection of recent studies to help refine your thinking. These are actual studies,  so they can provide some useful insight as to what a research topic looks like in practice.

• A Novel Optimization for GPU Mining Using Overclocking and Undervolting (Shuaib et al., 2022).
• Systematic Review of Security Vulnerabilities in Ethereum Blockchain Smart Contract (Kushwaha et al., 2022).
• Blockchain for Modern Applications: A Survey (Krichen et al., 2022).
• The Role and Potential of Blockchain Technology in Islamic Finance (Truby et al., 2022).
• Analysis of the Security and Reliability of Cryptocurrency Systems Using Knowledge Discovery and Machine Learning Methods (Shahbazi & Byun, 2022).
• Blockchain technology used in medicine. A brief survey (Virgolici et al., 2022).
• On the Deployment of Blockchain in Edge Computing Wireless Networks (Jaafar et al., 2022).
• The Blockchains Technologies for Cryptocurrencies: A Review (Taha & Alanezi, 2022). Cryptocurrencies Advantages and Disadvantages: A Review (Qaroush et al., 2022).
• Blockchain Implementation in Financial Sector and Cyber Security System (Panduro-Ramirez et al., 2022).
• Secure Blockchain Interworking Using Extended Smart Contract (Fujimoto et al., 2022).
• Cryptocurrency: The Present and the Future Scenario (Kommuru et al., 2022).
• Preparation for Post-Quantum era: a survey about blockchain schemes from a post-quantum perspective (Ciulei et al., 2022).
• Cryptocurrency Blockchain Technology in the Digital Revolution Era (Astuti et al., 2022).
• D-RAM Distribution: A Popular Energy-Saving Memory Mining Blockchain Technology (Jing, 2022).
• A Survey on Blockchain for Bitcoin and Its Future Perspectives (Garg et al., 2022).
• Blockchain Security: A Survey of Techniques and Research Directions (Leng et al., 2022).
• The Importance and Use of Blockchain Technology in International Payment Methods (Erdoğdu & Ünüsan, 2023).
• Some Insights on Open Problems in Blockchains: Explorative Tracks for Tezos (Invited Talk) (Conchon, 2022).

As you can see, these research topics are a lot more focused than the generic topic ideas we presented earlier. So, in order for you to develop a high-quality research topic, you’ll need to get specific and laser-focused on a specific context with specific variables of interest.  In the video below, we explore some other important things you’ll need to consider when crafting your research topic.

Get 1-On-1 Help

If you’re still unsure about how to find a quality research topic, check out our Research Topic Kickstarter service, which is the perfect starting point for developing a unique, well-justified research topic.

You Might Also Like:

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

• Open access
• Published: 04 July 2019

A systematic review of blockchain

• Min Xu   ORCID: orcid.org/0000-0002-3929-7759 1 ,
• Xingtong Chen 1 &
• Gang Kou 1  

Financial Innovation volume  5 , Article number:  27 ( 2019 ) Cite this article

97k Accesses

309 Citations

14 Altmetric

Metrics details

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.

Introduction

The concepts of bitcoin and blockchain were first proposed in 2008 by someone using the pseudonym Satoshi Nakamoto, who described how cryptology and an open distributed ledger can be combined into a digital currency application (Nakamoto 2008 ). At first, the extremely high volatility of bitcoin and the attitudes of many countries toward its complexity restrained its development somewhat, but the advantages of blockchain—which is bitcoin’s underlying technology—attracted increasing attention. Some of the advantages of blockchain include its distributed ledger, decentralization, information transparency, tamper-proof construction, and openness. The evolution of blockchain has been a progressive process. Blockchain is currently delimited to Blockchain 1.0, 2.0, and 3.0, based on their applications. We provide more details on the three generations of blockchain in the Appendix . The application of blockchain technology has extended from digital currency and into finance, and it has even gradually extended into health care, supply chain management, market monitoring, smart energy, and copyright protection (Engelhardt 2017 ; Hyvarinen et al. 2017 ; Kim and Laskowski 2018 ; O'Dair and Beaven 2017 ; Radanovic and Likic 2018 ; Savelyev 2018 ).

Blockchain technology has been studied by a wide variety of academic disciplines. For example, some researchers have studied the underlying technology of blockchain, such as distributed storage, peer-to-peer networking, cryptography, smart contracts, and consensus algorithms (Christidis and Devetsikiotis 2016 ; Cruz et al. 2018 ; Kraft 2016 ). Meanwhile, legal researchers are interested in the regulations and laws governing blockchain-related technology (Kiviat 2015 ; Paech 2017 ). As the old saying goes: scholars in different disciplines have many different analytical perspectives and “speak many different languages.” This paper focuses on analyzing and combing papers in the field of business and economics. We aim to identify the key nodes (e.g., the most influential articles and journals) in the related research and to find the main research themes of blockchain in our discipline. In addition, we hope to offer some recommendations for future research and provide some suggestions for businesses that wish to apply blockchain in practice.

This study will conduct a systematic and objective review that is based on data statistics and analysis. We first describe the overall number and discipline distribution of blockchain-related papers. A total of 756 journal articles were retrieved. Subsequently, we refined the subject area to business and economics, and were able to add 119 articles to our further analysis. We then explored the influential countries, journals, articles, and most common keywords. On the basis of a scientific literature analysis tool, we were able to identify five research themes on blockchain. We believe that this data-driven literature review will be able to more objectively present the status of this research.

The rest of this paper is organized as follows. In the next section, we provided an overview of the existing articles in all of the disciplines. We holistically describe the number of papers related to blockchain and discipline distribution of the literature. We then conduct a further analysis in the subject field of business and economics, where we analyze the countries, publications, highly cited papers, and so on. We also point out the main research themes of this paper, based on CiteSpace. This is followed by recommendations for promising research directions and practical applications. In the last section, we discuss the conclusions and limitations.

Overview of the current research

In our research, we first conducted a search on Web of Science Core Collection (WOS), including four online databases: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Arts & Humanities Citation Index (A&HCI), and Emerging Sources Citation Index (ESCI). We chose WOS because the papers in these databases can typically reflect scholarly attention towards blockchain. When searching the term “blockchain” as a topic, we found a total of 925 records in these databases. After filtering out the less representative record types, we reduced these papers to 756 articles that were then used for further analysis. We extracted the full bibliographic record of the articles that we identified from WOS, including information on the title, author, keywords, abstract, journal, year, and other publication information. These records were then exported to CiteSpace for subsequent analysis. CiteSpace is a scientific literature analysis tool that enables us to visualize trends and patterns in the scientific literature (Chen 2004 ). In this paper, CiteSpace is used to visually represent complex structures for statistical analysis and to conduct cluster analysis.

Table  1 shows the number of academic papers published per year. We have listed the number of all of the publications in WOS, the number of articles in all of the disciplines, and the number of articles in business and economics subjects. It should be noted that we retrieved the literature on March 25, 2019. Therefore, the number of articles in 2019 is relatively small. The number of papers has continued to grow in recent years, which suggests that there is a growing interest in blockchain. All of the extracted papers in WOS were published after 2015, which is seven years after blockchain and bitcoin was first described by Nakamoto. In these initial seven years, many papers were published online or indexed by other databases. However, we have not discussed these papers here. We only chose WOS, representative high-level literature databases. This is the most common way of doing a literature review (Ipek 2019 ).

In the 756 articles that we managed to retrieve, the three most common keywords besides blockchain are bitcoin, smart contract, and cryptocurrency, with the frequency of 113 times, 72 times, and 61 times, respectively. This shows that the majority of the literature mentions the core technology of blockchain and its most widely known application—bitcoin.

In WOS, each article is assigned to one or more subject categories. Therefore, we use CiteSpace to visualize what research areas are involved in current research on blockchain. Figure  1 shows a network of such subject categories. The most common category is Computer Science, which has the largest circle, followed by Engineering and Telecommunications. Business and Economics is also a common subject area for blockchain. Consequently, in the following session, we will conduct further analysis in this field.

Disciplines in blockchain

Articles in business and economics

Given that the main objective of our research was to understand the research of blockchain in the area of economics and management, we conduct an in-depth analysis on the papers in this field. We refined the research area to Business and Economics, and we finally retrieved 119 articles from WOS. In this session, we analyzed their published journals, research topics, citations, and so on, to depict the research status of blockchain in the field of business and economics more comprehensively.

There are several review papers on blockchain. Each of these paper contains a summary of multiple research topics, instead of a single topic. We do not include these literature reviews in our paper. However, it is undeniable that these articles also play an important role on the study of blockchain. For instance, Wang et al. ( 2019 ) investigate the influence of blockchain on supply chain practices and policies. Zhao et al. ( 2016 ) suggest blockchain will widely adopted in finance and lead to many business innovations and research opportunities.

The United States, the United Kingdom, and Germany are the top three countries by the number of papers published on blockchain; the specific data are shown in Table  2 . The United States released more papers than the other countries and it produced more than one-third of the total articles. As of the time of data collection, China contributed 11 papers, ranking fourth. The 119 papers in total are drawn from 17 countries and regions. In contrast, we searched “big data” and “financial technology” in the same way, and found 286 papers on big data that came from 24 countries, while 779 papers on fintech came from 43 countries. This shows that blockchain is still an emerging research field, and it needs more countries and scholars to join in the research effort.

We counted the journals published in these papers and we found that 44 journals published related papers. Table  3 lists the top 11 journals to have published blockchain research. First is “Strategic Change: Briefings in Entrepreneurial Finance,” followed by “Financial Innovation” and “Asia Pacific Journal of Innovation and Entrepreneurship.” The majority of papers in the journal “Strategic Change” were published in 2017, except for one in 2018 and one in 2019. Papers in the journal “Financial Innovation” were generally published in 2016, with one published in 2017 and one in 2019. All five of the papers in the journal “Asia Pacific Journal of Innovation and Entrepreneurship” were published in 2017.

Cited references

Table  4 presents the top six cited publications, which were cited no less than five times. The list consists of three books and three journal articles. Some of these publications introduce blockchain from a technical perspective and some from an application perspective. Swan’s ( 2015 ) book illustrates the application scenarios of blockchain technology. In this book, the author describes that blockchain is essentially a public ledger with potential as a decentralized digital repository of all assets—not only tangible assets but also intangible assets such as votes, software, health data, and ideas. Tapscott and Tapscott’s ( 2016 ) book explains why blockchain technology will fundamentally change the world. Yermack ( 2017 ) points out that blockchain will have a huge impact and will present many challenges to corporate governance. Böhme et al. ( 2015 ) introduce bitcoin, the first and most famous application of blockchain. Narayanan et al. ( 2016 ) also focus on bitcoin and explain how bitcoin works at a technical level. Lansiti and Lakhani ( 2017 ) argue it will take years to truly transform the blockchain because it is a fundamental rather than destructive technology, which will not drive implementation, and companies will need other incentives to adopt blockchain.

Most influential articles

These 119 papers were cited 314 times in total, and 270 times without self-citations. The number of articles that they cited are 221, of which 197 are non-self-citations. The most influential articles with more than 10 citations are listed in Table  5 . The most popular article in our dataset is Lansiti and Lakhani ( 2017 ), with 49 citations in WOS. This suggests that this article has had a strong influence on the research of blockchain. This paper believes there is still a distance to the real application of the blockchain. The other articles describe how blockchain affects and works in various areas, such as financial services, organizational management, and health care. Since blockchain is an emerging technology, it is particularly necessary to explore how to combine blockchains with various industries and fields.

By comparing the journals in Tables 4 and 5 , we find that some journals appeared in both of the lists, such as Financial Innovation. In other words, papers on blockchain are more welcomed in these journals and the journal’s papers are highly recognized by other scholars. Meanwhile, although journals such as Harvard Business Review have only published a few papers related to blockchain, they are highly cited. Consequently, the journals in both of these lists are of great importance.

Research themes

Addressing research themes is crucial to understanding a research field and exploring future research directions. This paper explored the research topic based on keywords. Keywords are representative and concise descriptions of article content. First, we analyzed the most common keywords used by the papers. We find that the top five most frequently used keywords are “blockchain,” “bitcoin,” “cryptocurrency,” “fintech,” and “smart contract.” Although the potential for blockchain applications goes way beyond digital currencies, bitcoin and other cryptocurrencies—as an important blockchain application scenario in the finance industry—were widely discussed in these articles. Smart contracts allow firms to set up automated transactions in blockchains, thus playing a fundamentally supporting role in blockchain applications. Similar to the literature in all of the subject areas, studies in business and economics also frequently use bitcoin, cryptocurrency, and smart contract as their keywords. The difference is that many researchers have combined blockchain with finance, regarding it as an important financial technology.

After analyzing the frequency of keywords, we conducted a keywords clustering analysis to identify the research themes. As shown in Fig.  2 , five clusters were identified through the log-likelihood ratio (LLR) algorithm in Citespace, they are: cluster #0 “economic benefit,” cluster #1 “blockchain technology,” cluster #2 “initial coin offerings,” cluster #3 “fintech revolution,” and cluster #4 “sharing economy.”

Disciplines and topics

Many researchers have studied the economic benefits of blockchain. They suggest the application of blockchain technology to streamline transactions and settlement processes can effectively reduce the costs associated with manual operations. For instance, in the health care sector, blockchain can play an important role in centralizing research data, avoiding prescription drug fraud, and reducing administrative overheads (Engelhardt 2017 ). In the music industry, blockchain could improve the accuracy and availability of copyright data and significantly improve the transparency of the value chain (O'Dair and Beaven 2017 ). Swan ( 2017 ) expound the economic value of block chain through four typical applications, such as digital asset registries, leapfrog technology, long-tail personalized economic services, and payment channels and peer banking services.

The representative paper for cluster “blockchain technology” was published by Lansiti and Lakhani ( 2017 ), who analyze the inherent features of blockchain and pointed out that we still have a lot to do to apply blockchain extensively. Other researchers have explored the characteristics of blockchain technology from multiple perspectives. For example, Xu ( 2016 ) explores the types of fraud and malicious activities that blockchain technology can prevent and identifies attacks to which blockchain remains vulnerable. Meanwhile, Aune et al. ( 2017 ) propose a cryptographic approach to solve information leakage problems on a blockchain.

Initial coin offering (ICO) is also a research topic of great concern to scholars. Many researchers analyze the determinants of the success of initial coin offerings (Adhami et al. 2018 ; Ante et al. 2018 ). For example, Fisch ( 2019 ) assesses the determinants of the amount raised in ICOs and discusses the role of signaling ventures’ technological capabilities in ICOs. Deng et al. ( 2018 ) argue the outright ban on ICOs might hamper revolutionary technological development and they provided some regulatory reform suggestions on the current ICO ban in China.

Many researchers have explored blockchain’s support for various industries. The fintech revolution brought by the blockchain has received extensive attention (Yang and Li 2018 ). Researchers agree that this nascent technology may transform traditional trading methods and practice in financial industry (Ashta and Biot-Paquerot 2018 ; Chen et al. 2017 ; Kim and Sarin 2018 ). For instance, Gomber et al. ( 2018 ) discuss transformations in four areas of financial services: operations management, payments, lending, and deposit services. Dierksmeier and Seele ( 2018 ) address the impact of blockchain technology on the nature of financial transactions from a business ethics perspective.

Another cluster corresponds to the sharing economy. A handful of researchers have focused on this field and they have discussed the supporting role played by blockchain in the sharing economy. Pazaitis et al. ( 2017 ) describe a conceptual economic model of blockchain-based decentralized cooperation that might better support the dynamics of social sharing. Sun et al. ( 2016 ) discuss the contribution of emerging blockchain technologies to the three major factors of the sharing economy (i.e., human, technology, and organization). They also analyze how blockchain-based sharing services contribute to smart cities.

In this section, we will discuss the following issues: (1) What will be the future research directions for blockchain? (2) How can businesses benefit from blockchain? We hope that our discussions will be able to provide guidance for future academic development and social practice.

What will be the future research directions for blockchain?

In view of the five themes mentioned in this paper, we provide some recommendations for future research in this section.

The economic benefits of blockchain have been extensively studied in previous research. For individual businesses, it is important to understand the effects of blockchain applications on the organizational structure, mode of operation, and management model of the business. For the market as a whole, it is important to determine whether blockchain can resolve the market failures that are brought about by information asymmetry, and whether it can increase market efficiency and social welfare. However, understanding the mechanisms through which blockchain influences corporate and market efficiency will require further academic inquiry.

For researchers of blockchain technology, this paper suggests that we should pay more attention to privacy protection and security issues. Despite the fact that all of the blockchain transactions are anonymous and encrypted, there is still a risk of the data being hacked. In the security sector, there is a view that absolute security can never be guaranteed wherever physical contact exists. Consequently, the question of how to share transaction data while also protecting personal data privacy are particularly vital issues for both academic and social practice.

Initial coin offering and cryptocurrency markets have grown rapidly. They bring many interesting questions, such as how to manage digital currencies. Although the majority of the previous research has focused on the determinants of success of initial coin offerings, we believe that future research will discuss how to regulate cryptocurrency and the ICO market. The success of blockchain technology in digital currency applications prior to 2015 caught the attention of many traditional financial institutions. As blockchain has continued to reinvent itself, in 2019 it is now more than capable of meeting the needs of the finance industry. We believe that blockchain is able to achieve large-scale applications in many areas of finance, such as banking, capital markets, Internet finance, and related fields. The deep integration of blockchain technology and fintech will continue to be a promising research direction.

The sharing economy is often defined as a peer-to-peer based activity of sharing goods and services among individuals. In the future, sharing among enterprises may become an important part of the new sharing economy. Consequently, building the interconnection of blockchains may become a distinct trend. These interconnections will facilitate the linkages between processes of identity authentication, supply chain management, and payments in commercial operations. They will also allow for instantaneous information exchange and data coordination among enterprises and industries.

How can businesses benefit from blockchain?

Businesses can leverage blockchains in a variety of ways to gain an advantage over their competitors. They can streamline their core business, reduce transaction costs, and make intellectual property ownership and payments more transparent and automated (Felin and Lakhani 2018 ). Many researchers have discussed the application of blockchain in business. After analyzing these studies, we believe that enterprises can consider applying blockchain technology in the four aspects that follow.

Accounting settlement and crowdfunding

Bitcoin or another virtual currency supported by blockchain technology can help businesses to solve funding-related problems. For instance, cryptocurrencies support companies who wish to implement non-cash payments and accounting settlement. The automation of electronic transaction management accounting improves the level of control of monetary business execution, both internally and externally (Zadorozhnyi et al. 2018 ). In addition, blockchain technology represents an emerging source of venture capital crowdfunding (O'Dair and Owen 2019 ). Investors or founders of enterprises can obtain alternative entrepreneurial finance through token sales or initial coin offerings. Companies can handle financial-related issues more flexibly by holding, transferring, and issuing digital currencies that are based on blockchain technology.

Data storage and sharing

As the most valuable resource, data plays a vital role in every enterprise. Blockchain provide a reliable storage and efficient use of data (Novikov et al. 2018 ). As a decentralized and secure ledger, blockchain can be used to manage digital asset for many kinds of companies (Dutra et al. 2018 ). Decentralized data storage means you do not give the data to a centralized agency but give it instead to people around the world because no one can tamper with the data on the blockchain. Businesses can use blockchain to store data, improve the transparency and security of the data, and prevent the data from being tampered with. At the same time, blockchain also supports data sharing. For instance, all of the key parties in the accounting profession leverage an accountancy blockchain to aggregate and share instances of practitioner misconduct across the country on a nearly real-time basis (Sheldon 2018 ).

Supply chain management

Blockchain technology has the potential to significantly change supply chain management (SCM) (Treiblmaier 2018 ). Recent adoptions of the Internet of Things and blockchain technologies support better supply-chain provenance (Kim and Laskowski 2018 ). When the product goes from the manufacturer to the customer, important data are recorded in the blockchain. Companies can trace products and raw materials to effectively monitor product quality.

Smart trading

Businesses can build smart contracts on blockchain, which is widely used to implement business collaborations in general and inter-organizational business processes in particular. Enterprises can automate transactions based on smart contracts on block chains without manual confirmation. For instance, businesses can file taxes automatically under smart contracts (Vishnevsky and Chekina 2018 ).

Conclusions

This paper reviews 756 articles related to blockchain on the Web of Science Core Collection. It shows that the most common subject area is Computer Science, followed by Engineering, Telecommunications, and Business and Economics. In the research of Business and Economics, several key nodes are identified in the literature, such as the top-cited articles, most productive countries, and most common keywords. After a cluster analysis of the keywords, we identified the five most popular research themes: “economic benefit,” “blockchain technology,” “initial coin offerings,” “fintech revolution,” and “sharing economy.”

As an important emerging technology, blockchain will play a role in many fields. Therefore, we believe that the issues related to commercial applications of blockchain are critical for both academic and social practice. We propose several promising research directions. The first important research direction is understanding the mechanisms through which blockchain influences corporate and market efficiency. The second potential research direction is privacy protection and security issues. The third relates to how to manage digital currencies and how to regulate the cryptocurrency market. The fourth potential research direction is how to deeply integrate blockchain technology and fintech. The final topic is cross-chain technology—if each industry has its own blockchain system, then researchers and developers must discover new ways to exchange data. This is the key to achieving the Internet of Value. Thus, cross-chain technology will become an increasingly important topic as time goes on.

Businesses can benefit considerably from blockchain technology. Therefore, we suggest that the application of blockchain be taken into consideration when businesses have the following requirements: accounting settlement and crowdfunding, data storage and sharing, supply chain management, and smart trading.

Our study has recognized some limitations. First, this paper only analyzes the literature in Web of Science Core Collection databases (WOS), which may lead to the incompleteness of the relevant literature. Second, we filter our literature base on the subject category in WOS. In this process, we may have omitted some relevant research. Third, our recommendations have subjective limitations. We hope to initiate more research and discussions to address these points in the future.

Availability of data and materials

Data used in this paper were collected from Web of Science Core Collection.

Abbreviations

Initial coin offering

Web of Science Core Collection

Adhami S, Giudici G, Martinazzi S (2018) Why do businesses go crypto? An empirical analysis of initial coin offerings. J Econ Bus 100:64–75

Article   Google Scholar  

Ante L, Sandner P, Fiedler I (2018) Blockchain-based ICOs: pure hype or the Dawn of a new era of startup financing? J Risk Financ Manage 11(4):80

Ashta A, Biot-Paquerot G (2018) FinTech evolution: strategic value management issues in a fast changing industry. Strategic Change-Briefings in Entrepreneurial Finance 27(4):301–311

Google Scholar  

Aune RT, Krellenstein A, O'Hara M, Slama O (2017) Footprints on a Blockchain: trading and information leakage in distributed ledgers. J Trading 12(3):5–13

Böhme R, Christin N, Edelman B, Moore T (2015) Bitcoin: economics, technology, and governance. J Econ Perspect 29(2):213–238

Chen C (2004) Searching for intellectual turning points: progressive knowledge domain visualization. Proc Natl Acad Sci U S A 101(suppl:5303–5310

Chen Z, Li Y, Wu Y, Luo J (2017) The transition from traditional banking to mobile internet finance: an organizational innovation perspective - a comparative study of Citibank and ICBC. Financial Innovation 3(1):12

Christidis K, Devetsikiotis M (2016) Blockchains and smart contracts for the internet of things. Ieee Access 4:2292–2303

Crosby M, Pattanayak P, Verma S (2016) Blockchain technology: beyond bitcoin. Appl Innov 2:6–19

Cruz JP, Kaji Y, Yanai N (2018) RBAC-SC: role-based access control using smart contract. Ieee Access 6:12240–12251

Dai J, Vasarhelyi MA (2017) Toward Blockchain-based accounting and assurance. J Inf Syst 31(3):5–21

Deng H, Huang RH, Wu Q (2018) The regulation of initial coin offerings in China: problems, prognoses and prospects. Eur Bus Organ Law Rev 19(3):465–502

Dierksmeier C, Seele P (2018) Cryptocurrencies and business ethics. J Bus Ethics 152(1):1–14

Dutra A, Tumasjan A, Welpe IM (2018) Blockchain is changing how media and entertainment companies compete. MIT Sloan Manag Rev 60(1):39–3+

Engelhardt MA (2017) Hitching healthcare to the chain: an introduction to Blockchain Technology in the Healthcare Sector. Technol Innov Manage Rev 7(10):22–34

Fanning K, Centers DP (2016) Blockchain and its coming impact on financial services. J Corp Account Finance 27(5):53–57

Felin T, Lakhani K (2018) What problems will you solve with Blockchain? MIT Sloan Manag Rev 60(1):32–3+

Fisch C (2019) Initial coin offerings (ICOs) to finance new ventures. J Bus Ventur 34(1):1–22

Gomber P, Kauffman RJ, Parker C, Weber BW (2018) On the Fintech revolution: interpreting the forces of innovation, disruption, and transformation in financial services. J Manag Inf Syst 35(1):220–265

Green J, Newman P (2017) Citizen utilities: the emerging power paradigm. Energy Policy 105:283–293

Hyvarinen H, Risius M, Friis G (2017) A Blockchain-based approach towards overcoming financial fraud in public sector services. Bus Inf Syst Eng 59(6):441–456

Ipek I (2019) Organizational learning in exporting: a bibliometric analysis and critical review of the empirical research. Int Bus Rev 28(3):544–559

Kim HM, Laskowski M (2018) Toward an ontology-driven blockchain design for supply-chain provenance. Intell Syst Account Finance Manage 25(1):18–27

Kim S, Sarin A (2018) Distributed ledger and Blockchain technology: framework and use cases. J Invest Manage 16(3):90–101

Kiviat TI (2015) Beyond bitcoin: issues in regulating blockchain transactions. Duke Law J 65(3):569–608

Kraft D (2016) Difficulty control for blockchain-based consensus systems. Peer-to-Peer Networking and Applications 9(2):397–413

Lansiti M, Lakhani KR (2017) The truth about Blockchain. Harv Bus Rev 95(1):119–127

Mainelli M, Smith M (2015) Sharing ledgers for sharing economies: an exploration of mutual distributed ledgers (aka blockchain technology). J Financial Perspect 3(3):38-58

Nakamoto S (2008) Bitcoin: a peer-to-peer electronic cash system

Narayanan A, Bonneau J, Felten E, Miller A, Goldfeder S (2016). Bitcoin and cryptocurrency technologies: A Comprehensive Introduction. Princeton University Press: 336

Novikov SP, Mikheenko OV, Kulagina NA, Kazakov OD (2018) Digital registry of professional competences of the population drawing on distributed registries and smart contracts technologies. Biznes Informatika Business Inform 46(4):43–53

O'Dair M, Beaven Z (2017) The networked record industry: how blockchain technology could transform the record industry. Strateg Change Brief Entrep Finance 26(5):471–480

O'Dair M, Owen R (2019) Financing new creative enterprise through blockchain technology: opportunities and policy implications. Strateg Change Brief Entrep Finance 28(1):9–17

Paech P (2017) The governance of Blockchain financial networks. Mod Law Rev 80(6):1073–1110

Pazaitis A, De Filippi P, Kostakis V (2017) Blockchain and value systems in the sharing economy: the illustrative case of Backfeed. Technol Forecast Soc Chang 125:105–115

Pieroni A, Scarpato N, Di Nunzio L, Fallucchi F, Raso M (2018) Smarter city: smart energy grid based on blockchain technology. Int J Adv Sci Eng Inf Technol 8(1):298–306

Radanovic I, Likic R (2018) Opportunities for use of Blockchain Technology in Medicine. Appl Health Econ Health Policy 16(5):583–590

Savelyev A (2018) Copyright in the blockchain era: promises and challenges. Comput Law Secur Rev 34(3):550–561

Sheldon MD (2018) Using Blockchain to aggregate and share misconduct issues across the accounting profession. Curr Issues Audit 12(2):A27–A35

Sun J, Yan J, Zhang KZK (2016) Blockchain-based sharing services: what blockchain technology can contribute to smart cities. Financ Innov 2(1):26

Swan M (2015). Blockchain: Blueprint for a New Economy. O'Reilly Media: 152

Swan M (2017) Anticipating the economic benefits of Blockchain. Technol Innov Manage Rev 7(10):6–13

Tapscott D, Tapscott A (2016) Blockchain revolution: how the technology behind bitcoin is changing money, business, and the world. Portfolio: 368

Tapscott D, Tapscott A (2017) How Blockchain will change organizations. MIT Sloan Manag Rev 58(2):10–13

Treiblmaier H (2018) The impact of the blockchain on the supply chain: a theory-based research framework and a call for action. Supply Chain Manage Int J 23(6):545–559

Vishnevsky VP, Chekina VD (2018) Robot vs. tax inspector or how the fourth industrial revolution will change the tax system: a review of problems and solutions. J Tax Reform 4(1):6–26

Wang YL, Han JH, Beynon-Davies P (2019) Understanding blockchain technology for future supply chains: a systematic literature review and research agenda. Supply Chain Manage Int J 24(1):62–84

Xu JJ (2016) Are blockchains immune to all malicious attacks? Financ Innov 2(1):25

Yang D, Li M (2018) Evolutionary approaches and the construction of technology-driven regulations. Emerg Mark Financ Trade 54(14):3256–3271

Yermack D (2017) Corporate governance and Blockchains. Rev Finance 21(1):7–31

Zadorozhnyi ZMV, Murayskyi VV, Shevchuk OA (2018) Management accounting of electronic transactions with the use of cryptocurrencies. Financ Credit Activ Probl Theory Pract 3(26):169–177

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(1):28

Download references

Acknowledgements

Not applicable.

This research is supported by grants from National Natural Science Foundation of China (Nos. 71701168 and 71701034).

Author information

Authors and affiliations.

Southwestern University of Finance and Economics, Chengdu, China

Min Xu, Xingtong Chen & Gang Kou

You can also search for this author in PubMed   Google Scholar

Contributions

The first author contributed by retrieving literature and conducting data analysis. The second and third author contributed by writing the paper, especially the Discussion and Appendix . All authors read and approved the final manuscript.

Corresponding author

Correspondence to Min Xu .

Ethics declarations

Competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Three generations of blockchain

The scope of blockchain applications has increased from virtual currencies to financial applications to the entire social realm. Based on its applications, blockchain is delimited to Blockchain 1.0, 2.0, and 3.0.

Blockchain 1.0

Blockchain 1.0 was related to virtual currencies, such as bitcoin, which was not only the first and most widely used digital currency but it was also the first application of blockchain technology (Mainelli and Smith 2015 ). Digital currencies can reduce many of the costs associated with traditional physical currencies, such as the costs of circulation. Blockchain 1.0 produced a great many applications, one of which was Bitcoin. Most of these applications were digital currencies and tended to be used commercially for small-value payments, foreign exchange, gambling, and money laundering. At this stage, blockchain technology was generally used as a cryptocurrency and for payment systems that relied on cryptocurrency ecosystems.

Blockchain 2.0

Broadly speaking, Blockchain 2.0 includes Bitcoin 2.0, smart-contracts, smart-property, decentralized applications (Dapps), decentralized autonomous organizations (DAOs), and decentralized autonomous corporations (DACs) (Swan 2015 ). However, most people understand Blockchain 2.0 as applications in other areas of finance, where it is mainly used in securities trading, supply chain finance, banking instruments, payment clearing, anti-counterfeiting, establishing credit systems, and mutual insurance. The financial sector requires high levels of security and data integrity, and thus blockchain applications have some inherent advantages. The greatest contribution of Blockchain 2.0 was the idea of using smart-contracts to disrupt traditional currency and payment systems. Recently, the integration of blockchain and smart contract technology has become a popular research topic in problem resolution. For example, Ethereum, Codius, and Hyperledger have established programmable contract language and executable infrastructure to implement smart contracts.

Blockchain 3.0

In ‘Blockchain: Blueprint for a New Economy’, Blockchain 3.0 is described as the application of blockchain in areas other than currency and finance, such as in government, health, science, culture, and the arts (Swan 2015 ). Blockchain 3.0 aims to popularize the technology, and it focuses on the regulation and governance of its decentralization in society. The scope of this type of blockchain and its potential applications suggests that blockchain technology is a moving target (Crosby et al. 2016 ). Blockchain 3.0 envisions a more advanced form of “smart contracts” to establish a distributed organizational unit that makes and is subject to its own laws and which operates with a high degree of autonomy (Pieroni et al. 2018 ).

The integration of blockchain with tokens is an important combination of Blockchain 3.0. Tokens are proofs of digital rights, and blockchain tokens are widely recognized thanks to Ethereum and its ERC20 standard. Based on this standard, anyone can issue a custom token on Ethereum and this token can represent any right or value. Tokens refer to economic activities generated through the creation of encrypted tokens, which are principally but not exclusively based on the ERC20 standard. Tokens can serve as a form of validation of any right, including personal identity, academic diplomas, currency, receipts, keys, event tickets, rebate points, coupons, stocks, and bonds. Consequently, tokens can validate virtually any right that exists within a society. Blockchain is the back-end technology of the new era, while tokens are its front-end economic face. The combination of the two will bring about major societal transformation. Meanwhile, Blockchain 3.0 and its token economy continue to evolve.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Cite this article.

Xu, M., Chen, X. & Kou, G. A systematic review of blockchain. Financ Innov 5 , 27 (2019). https://doi.org/10.1186/s40854-019-0147-z

Download citation

Received : 01 May 2019

Accepted : 24 June 2019

Published : 04 July 2019

DOI : https://doi.org/10.1186/s40854-019-0147-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Systematic literature review
• Business and economics

• Reference Manager
• Simple TEXT file

People also looked at

Review article, toward more rigorous blockchain research: recommendations for writing blockchain case studies.

• Department of International Management, MODUL University Vienna, Vienna, Austria

About a decade ago the fundamental operating principle of the Blockchain was introduced. It took several years before the technology gained widespread recognition in industry and academic communities outside of the computer science sphere. Since then many academic communities have taken up the topic, but so far no well-defined research agenda has emerged: research topics are scattered and rigorous approaches are scarce. More often than not, use cases implemented by industry apply a trial and error approach and there exists a dearth of theory-based academic papers on the topic following robust methodologies. Being a nascent research topic, case studies on Blockchain applications are a suitable approach to systematically transfer industry experience into research agendas which benefit both theory development and testing as well as design science research. In this paper I offer guidelines and suggestions on how to design and structure Blockchain case studies to create value for academia and the industry. More specifically, I describe Blockchain characteristics and challenges, present existing Blockchain case studies, and discuss various types of case study research and how they can be useful for industry and academic research. I conclude with a framework and a checklist for Blockchain case study research.

Introduction

Within roughly a decade the Blockchain has shifted from a rather obscure and poorly understood topic into a phenomenon that has gained widespread mass media attention and attracts academics and practitioners alike. The growth in size of selected Blockchain networks, as measured by the number of unique addresses participating in daily activities, exhibits an exponential development following Metcalfe's law ( Alabi, 2017 ). In spite of a sharp drop in the prices of Bitcoin and other cryptocurrencies at the end of the year 2017, the general Blockchain market size is still estimated to grow from USD 242 million in 2016 to USD 7,684 million by 2022, at a compound annual growth rate of 79.6% ( MarketsandMarkets., 2017 ).

The emergence of Blockchain publications in leading academic journals has shown a substantial time lag in comparison to industry adoption. Outside of the computer science and cryptography communities, the first academic journal publications discussing Bitcoin appeared around 2012, followed by papers dealing with the Blockchain and DLT (Distributed Ledger Technology) around 2015. This delay has partly to do with lengthy review cycles of top-tier academic journals, but also with the complexity of the technology in combination with poorly understood and unclear use cases. This situation has changed with the emergence of publications targeting a broader audience, in which the authors speculate about potential application scenarios for the technology ( Swan, 2015 ; Tapscott and Tapscott, 2016 ; Iansiti and Lakhani, 2017 ). Many of the suggested use cases are far-reaching in terms of their potential implications and cover a wide range of industries and applications, including financial services, transportation and supply chain management, media and entertainment, education, tourism, public services, consumer services, voting, and academic peer reviews ( Yli-Huumo et al., 2016 ; Bahga and Madisetti, 2017 ; Lacity, 2018a ; Önder and Treiblmaier, 2018 ; Treiblmaier, 2018 ; Treiblmaier and Beck, 2019a , b ).

The relevance of the Blockchain for the Information Systems community is 2-fold. First, researchers with an interest in the implications of the technology may want to better understand the behavioral (on an individual, group, and organizational level) and economic impacts of the Blockchain as well as its antecedents. Second, design science researchers may want to focus on the application of Blockchain technology to design and implement novel and innovative artifacts, which also includes the potential transformation of software development and business processes ( Sillaber et al., 2018 ). While academia focuses largely on enhancing and refining existing frameworks and theories, as well as creating new ones, the industry needs advice and practical solutions.

The current lack of long-term experience with the Blockchain is aggravated by the fact that the technology is not yet mature, and therefore still under development. In their search for barriers to Blockchain adoption, Holotiuk et al. (2018) identified the lack of Blockchain use cases as a key challenge. A well-structured research agenda that encourages the systematic and comprehensive documentation of the findings of Blockchain case studies is therefore needed to ensure the cumulative compilation of knowledge and to provide guidance for the industry. Ideally, such a research agenda builds on previous research and allows for the comparability and straightforward integration of new findings. Given the flexibility and broad applicability of case studies ( Cavaye, 1996 ), they are well-suited for investigating nascent phenomena and structuring a research domain. They have the potential to bring together academic rigor and practical relevance, while simultaneously ensuring a substantial amount of methodological freedom ( Yin, 2014 ; Ridder, 2017 ).

Beck et al. (2017) suggest a list of Blockchain research topics for the IS community, including new business models, disruption, implementation types, sustainability issues, organizational implications, application development, Internet of Things (IoT) applications, challenges of implementing business logic, and limits of applications. Notably, all of these topics can be investigated with the help of carefully designed, executed and documented case studies. Existing Blockchain case studies are rare and are often published as anecdotes without a clearly defined structure, which makes it hard to critically evaluate them and to use them as a solid basis for further research or recommendations for the industry. It is therefore my goal to provide suggestions on how anecdotal evidence can be turned into systematic knowledge by considering the principles and guidelines of academic case study research.

In section Blockchain: Definitions, Characteristics and Challenges I present definitions, characteristics and challenges of the Blockchain, to lay a foundation for the remainder of this paper. In section Case Study Research and the Blockchain I differentiate between four types of theory-based case study research, each of which has its respective strengths and weaknesses, and provide an overview of existing Blockchain case studies, which cover one or more use cases, respectively. In section Designing and Reporting Blockchain Case Studies I present a generic framework for Blockchain case study research, followed by a proposed structure for systematic Blockchain case study papers. I end the paper with a brief conclusion in section Conclusion.

Blockchain: Definitions, Characteristics and Challenges

The Blockchain is a technology, or rather a combination of technologies ( Narayanan and Clark, 2017 ), that is still under development. In a recent white paper the IEEE states that the “Blockchain, as an industry, has entered its Cambrian phase” ( Peck, 2017 , p. 1), alluding to the rapid diversification of various life forms during that period.

The term Blockchain originates from the original description of Bitcoin by the mysterious author (or group of authors) identified as Satoshi Nakamoto (2008) . Nakamoto never actually uses the term “Blockchain” in his/her/their seminal paper, but instead describes how transactions, hashes, and nonces can be grouped together into a block-based data structure in which the single blocks are chained together by including the hash of a previous block. Since then, the term Blockchain has gained widespread public attention and is most commonly used to denote what can be more loosely described as “trustless systems,” indicating that the amount of trust required of individual actors is minimized. Most authors, however, do not care so much about a chain of blocks, but rather about the underlying characteristics of the technology which facilitate the creation of decentralized systems whose functioning does not necessitate specific trustworthy entities. It therefore makes sense to also consider the broader term “Distributed Ledger Technology” (DLT) in any paper dealing with the Blockchain in order to also include technologies that do not exhibit a chain-like structure, such as, for example, Tangle, a directed acyclic graph (DAG) used by IOTA, which entangles a stream of individual transactions. Another solution based on directed acyclic graphs is Hashgraph, a DLT with a consensus mechanism that does not rely on an energy-consuming proof-of-work mechanism. The major advantage of avoiding a linear block chain lies mainly in the faster throughput of the transactions ( Schueffel, 2017 ).

Table 1 lists several Blockchain and DLT definitions. The core of every Blockchain/DLT system is the distributed storage of data across multiple ledgers that can be spread across institutions and countries. While Meiklejohn et al. (2016) specifically refer to the Bitcoin Blockchain, all other definitions are more generic. The key characteristics include the distributed nature of the Blockchain, the immutability of the data, and the necessity of achieving consensus on which transactions are to be recorded. Each of these characteristics, and several others, are discussed in more detail in the following section. To date, no generally accepted definition of the Blockchain has emerged. It is therefore necessary to clearly describe the type of Blockchain/DLT being used in a specific case study and to outline the reasons for that particular choice.

Table 1 . Blockchain and DLT definitions.

The characteristics of the Blockchain, some of which might be only assumed or are currently under debate for technological, economic, business-related or legal reasons ( Hoelscher, 2018 ; Kim and Justl, 2018 ; Posadas, 2018 ), enable a wide variety of applications across multiple industries. Table 2 lists important characteristics of the Blockchain that emerged from a review of the literature as well as from interviews I personally conducted with 24 experts between January and February 2018. The interviews each lasted between 12 and 23 min. All interviews were recorded, transcribed and analyzed according to recognized standards for qualitative content analysis and grounded theory development ( Glaser and Strauss, 1967 ; Hsieh and Shannon, 2005 ). The experts were chosen from the member directory of a large Blockchain interest group in Austria and included representatives of organizations from various industries (e.g., finance, energy, transportation), interest groups, consulting agencies, governmental institutions and educational institutions. All of the interview partners had substantial previous experience with Blockchain technology, such as the implementation and evaluation of diverse use cases, industry consulting projects, or the mining of cryptocurrencies. More details can be found in Treiblmaier and Umlauff (2019) .

Table 2 . Blockchain characteristics.

The shown characteristics might not apply equally well to all types of Blockchain manifestations. A permissioned Blockchain run by members of a consortium, for example, represents a rather closed ecosystem with clearly defined participants and control structures that are (partly) centralized, which contrasts with permissionless Blockchains that offer free access for anyone. The inherent differences between these systems have repercussions regarding issues such as privacy, throughput, and the choice of consensus mechanisms.

Immutability is frequently mentioned as the central characteristic of the Blockchain, since it allows for the transformation of the “Internet of Information,” in which digital data can be copied without loss of accuracy, into the “Internet of Value,” in which units representing value can be transferred between peers and double spending can be prevented. Immutability is also highly desirable if transactions need to be tracked along the supply chain. However, this property comes at a cost. If data needs to be changed, which might be due to legal reasons ( Posadas, 2018 ), the Blockchain does not pose the most efficient data structure to do so. Furthermore, participation in public Blockchains is pseudonymous (or pseudo-anonymous), not anonymous, which raises privacy issues as it does not preclude identification ( Meiklejohn et al., 2016 ).

The transparency of Blockchains is achieved by allowing users read-only access to previous transactions and to inspect the content of smart contracts. This is especially important if products need to be tracked along the supply chain ( Kshetri, 2018 ). Again, it is crucial to differentiate between permissioned and permissionless Blockchains, with the former being run by members of a consortium and access thus restricted. In contrast, permissionless Blockchains, such as Bitcoin, allow for the inspection of blocks by everyone. While transparency and accountability are desirable in many instances, this might not hold true for all use cases. For example, private users might be concerned about sensitive personal data, and organizations might fear the leakage of confidential financial information.

The programmability of the Blockchain has rapidly improved in recent years. Bitcoin uses a basic scripting language, called Script, which intentionally avoids complex operations such as loops. In order to overcome this perceived limitation, the platform Ethereum ( Wood, 2014 ) introduced a Turing complete language called Solidity, which is currently the most popular language for the creation of so-called smart contracts ( Szabo, 1997 ): self-executing computer programs that execute in a deterministic and pre-defined way. However, this deterministic execution frequently lacks the flexibility needed in legal contracts and highlights the difficulties of reducing contractual relationships and the complexities of the real world into computer code ( Mik, 2017 ).

One of the most frequently cited characteristics of the Blockchain is its decentralized nature. This is not only true for the storage of data, but also for decision making and governance. Again, differences between Blockchain types exist, but in general no central authority is needed to validate transactions between peers. This leads to disintermediation, which, depending on the perspective, can be seen as both an advantage and a disadvantage. New governance structures can help to create more effective and efficient organizational structures and to reduce transaction costs. At the same time, disintermediation may be seen as a major threat for incumbents who hold strategic positions in existing supply chains and value networks ( Treiblmaier, 2018 ).

Decentralization is made possible by innovative consensus protocols across a network of nodes. Such protocols make sure that the task of compiling transactions and creating new blocks follows strict rules which do not favor one peer over another. The most widely known consensus algorithm, which is implemented in Bitcoin, is called proof-of-work (PoW) mining and is based on solving a mathematically demanding puzzle with dynamically adjustable complexities ( Yuan and Wang, 2018 ). During the evolution phase of Bitcoin, which saw a soaring exchange rate, miners invested more and more resources and PoW became notorious for its excessive use of energy. It is noteworthy, however, that PoW is only one out of a multitude of potential consensus algorithms used for permissionless networks, and various alternatives exist (e.g., proof-of-stake (PoS), which can be used in a hybrid form together with PoW; Byzantine fault tolerance-based consensus; crash fault tolerance-based consensus) ( Nguyen and Kim, 2018 ). Summarizing, the Blockchain can lead either to the consolidation of existing or the creation of new power structures.

Finally, the Blockchain enables the distribution of trust, such that it does not necessitate high levels of confidence in single authorities. Greiner and Wang (2015) introduced the notion of trust-free systems which use the Blockchain to create a verified, immutable, and available record of transactions that is governed by the system itself. However, as Hawlitschek et al. (2018) point out, the conceptualization of trust depends on the context, which is in their study the sharing industry, and will depend on creating trusted interfaces. However, the potential elimination of existing relationships and the emergence of an economy that is controlled by automatically executed processes is not without dispute, as the disappearance of personal relationships might lead to undesirable consequences.

I do not list all of the characteristics of the Blockchain mentioned in the (gray and academic) literature, such as the data being chronological, time-stamped, and cryptographically sealed ( Deloitte., 2017 ), since those are usually means to an end. However, such characteristics should also be discussed in case studies if they represent an important factor in the respective research project. I recommend that every case study contains some reflection on why the respective characteristics of that particular Blockchain configuration were chosen from among the alternatives, why they were important, how they were applied, and what (un)intended consequences arose from their application.

The substantial interest surrounding the Blockchain has been fueled by the great variety of possible use cases and its potential applicability in many industries ( Tapscott and Tapscott, 2016 ). However, actual implementations must be assimilated within existing complex social, economic, institutional, regulatory and physical systems ( Lacity and Willcocks, 2018 ), which can generate the numerous practical problems of implementation shown in Table 3 .

Table 3 . Blockchain challenges ( Swan, 2015 ; Lemieux, 2016 ; Kshetri, 2017 ; Lacity, 2018b ; Saad et al., 2019 ).

Swan (2015) lists various technical challenges, such as throughput, which determine the scalability of the Blockchain solution. This is mostly an issue for public Blockchains that depend on an elaborate consensus mechanism between peers. The Bitcoin network with a theoretical maximum of 7 transactions per second (tps) lags far behind the processing power of VISA (2,000 tps), Twitter (5,000 tps) and advertising networks (>100,000 tps). A performance analysis of Hyperledger Fabric and Ethereum, two popular Blockchain platforms, showed that the former consistently outperformed the latter, but the authors still conclude that “both platforms are still not competitive with current database systems in term of performances in high workload scenarios” ( Pongnumkul et al., 2017 , p. 1). Another related issue is latency, the processing time for a transaction in a network, which, in the case of Bitcoin, amounts to 10 min. This processing time has been chosen on purpose to avoid chain splits, and will not be reduced in the future. Furthermore, in order to increase security it is recommended to wait for several confirmed transactions, which further increases latency ( Swan, 2015 ). Again, the situation might look quite different for permissioned networks that are less prone to threats such as double-spending attacks due to deliberately chosen validators. Further challenges include the ever-increasing size of Blockchains, which consumes a considerable amount of bandwidth due to redundancies in data storage and transfer, and which constitutes a waste of resources, which is most obvious in the case of the PoW consensus mechanism that essentially trades energy for security. The proliferation of different Blockchains furthermore leads to an increasingly complex and hard to use infrastructure that hampers communication between chains and facilitates attacks on smaller chains.

Privacy and the Blockchain is a complex issue which arises mainly due to the immutability of data on the Blockchain. The situation is especially complex for personal data relating to an identified or identifiable natural person. The European Union's General Data Privacy Regulation (GDPR), which took effect on May 25, 2018, provides a set of regulations to ensure that individuals within the EU and those that conduct transactions within the EU can guarantee the protection of individual data. The GDPR, however, was written with a centralized entity in mind that has the power to control access rights, which is not case when Blockchain technology is used. It is thus unclear how Blockchain technology will comport with the GDPR ( Posadas, 2018 ). However, as Kshetri (2017) points out, the Blockchain also bears the potential to strengthen cybersecurity and privacy by deterring cybercriminals and unauthorized data manipulators. Additionally, it offers the possibility of allowing individuals to control their own private data. It does not, however, guarantee the reliability of information and has limitations as a solution for keeping trustworthy digital records ( Lemieux, 2016 ).

Lacity (2018b) lists various managerial challenges that include the specification of standards for access rights, data structures, and allowable transactions. Furthermore, she points out that current legislation lags behind technological developments, which creates insecurity on the side of organizations. A largely unexplored area is the need for new organizational structures that are able to cope with the idiosyncrasies of the Blockchain (see also Treiblmaier, 2018 ). Additionally, a major success factor of any technological solution is the attraction of a critical mass of adopters beyond the core originators, which is currently unclear for many Blockchain solutions that are still in an embryonic stage.

Finally, it must not be forgotten that the Blockchain is a potential target for manifold attacks. Just because the current cryptographic system and the chain of transactions in Bitcoin have so far withstood external attacks does not mean that Blockchain systems in general are resistant to all kinds of attacks. Saad et al. (2019) differentiate between three different attack areas, namely cryptographic constructs, the distributed architecture of the system, and the application context. They discuss a variety of potential attacks, including Blockchain forks, stale blocks and orphaned blocks, selfish mining, the 51% attack, DNS (domain name system) attacks, distributed denial of service attacks, consensus delays, Blockchain ingestion, double spending, and wallet theft.

A comparison between Tables 2 , 3 reveals various challenges (which might turn into serious problems during implementation or runtime) that are inextricably linked to the basic characteristics of the Blockchain. For example, conflicting goals such as creating publicly available solutions that guarantee security and privacy pose major technological, legal and organizational challenges. The same holds true if legal regulations demand the removal of data upon request, which contradicts immutability as a basic characteristic of the Blockchain. These are just some examples out of many potential areas of conflict that need to be carefully documented in case studies.

Case Study Research and the Blockchain

In his seminal book on case study research, Yin (2014) gives a 2- fold definition for case studies in which he differentiates between scope and features. More specifically, he defines a case study as “an empirical inquiry that investigates a contemporal phenomenon (the ‘case') in depth and within its real-world context, especially when the boundaries between phenomenon and context may not be clearly evident” (p. 16). Since the phenomenon and the context are sometimes hard to distinguish, the features of a case also need to be considered (p. 17): “a case study inquiry copes with the technically distinctive situation in which there will be many more variables of interest than data points, and as one result relies on multiple sources of evidence, with data needing to converge in a triangulating fashion, and as another result benefits from the prior development of theoretical propositions to guide data collection and analysis.” Yin explicitly differentiates between rigorous case studies and teaching cases, with the latter having less strict formal requirements.

Burns (2000 , p. 459) laments that “the case study has unfortunately been used as a ‘catch – all' category for anything that does not fit into experimental, survey, or historical methods.” Much too often, case study research is reduced to being exclusively exploratory without having a proper methodological foundation. As a potential solution, Ridder (2017) presents a comprehensive and differentiated perspective and introduces a portfolio approach in which he presents four case study research designs, each of which exhibits different strengths. These designs, labeled “no theory first”, “gaps and holes,” “social construction of theory” and “anomalies,” provide different contributions for building, developing and testing theory, and are discussed in more detail in the following section.

Case studies have a long tradition in IS. Benbasat et al. (1987) introduce case study research as a viable alternative to quantitative techniques that offers several advantages, such as independence from large samples sizes or distributional assumptions, as well as the potential of case studies to analyze a phenomenon within its context (i.e., an idiographic research strategy). Lee (1989) presents a scientific methodology for case studies and identifies four major problems, namely making controlled observations, making controlled deductions, allowing for replicability, and allowing for generalizability. He then describes how the alleged shortcomings of case studies can be overcome by using “natural controls” (e.g., by observing one person in varying, naturally occurring external situations), using logical reasoning for making deductions, adapting predictions while keeping the same theory and, finally, replicating case studies in different settings to ensure their generalizability. Lee furthermore suggests four considerations that can be used for a general assessment: (1) Does the case study consider any predictions through which the theory can be disproven?; (2) Are all the predictions internally consistent?; (3) Does the case study corroborate the theory through empirical testing?; and (4) Does the case study eliminate rival theories?

Cavaye (1996) investigates case study research in IS and concludes that “case study research can be used in the positivist and interpretivist traditions, for testing and building theory, with a single or multiple case study design, using qualitative or mixed methods” (p. 227). Dubé and Paré (2003) focused on rigor in information systems positivist case research by investigating contemporaneous practices. They identified and coded 183 case articles from seven major IS journals and concluded “that while modest progress has been made with respect to some specific attributes or criteria, the findings are somewhat disappointing and there are still significant areas for improvement” (p. 620). They especially lament the fact that descriptive case studies lag far behind explanatory and exploratory studies with respect to several attributes. The core of their paper comprises detailed recommendations on how to improve case study research designs, which include the use of clear research questions, a priori specification of constructions, discussion of theory and units of analysis, description of the study context and roles of investigators, elucidation of the data collection process, use of multiple data collection methods, data triangulation, clarification of the data analysis process, use of field notes, empirical testing, application of cross-case patterns, and a comparison with extant literature.

Wynn and Williams (2012) introduce principles for case study research from a critical realist perspective. They derive their principles directly from ontological (e.g., independent reality, open systems) and epistemological (e.g., mediated knowledge, unobservability of mechanisms) assumptions of critical realism and propose five methodological principles, namely the explication of events, explication of structure and content, retroduction, empirical corroboration, and triangulation, as well as the use of multiple methods.

A completely different approach is proposed by Avison et al. (2017) : the French New Novel tradition. They argue that this style presents the richness of the problem situation and leaves it up to the reader to discover meaning from the narrative. As such, their approach does not provide specific guidelines and the authors themselves state that “there is no consensus on the techniques required to develop a narrative of this genre” (p. 267). However, they also provide a detailed analysis as to how this approach can be simultaneously demanding as well as inspiring, and might provide an antidote to publications that blindly follow a “formula.” In a similar vein, my intention in this paper is not to favor a particular style or technique, but rather to illustrate the full range of available possibilities. Understanding different types of case studies thus presents an ideal starting point.

Typology of Academic Case Studies

As indicated in the previous section, case study research is a far wider-ranging and more powerful approach than many researchers might realize. Ridder (2017) presents a comprehensive typology that is based on the seminal work of four authors, namely Eisenhardt (1989) (no theory first, NTF), Yin (2014) (gaps and holes, GAH), Stake (1995) (social construction of reality, SCR), and Burawoy (2009) (anomalies, ANO). In Table 4 I highlight the main features of the respective approaches. A more detailed comparison can be found in Ridder (2017) .

Table 4 . Case study research designs and their theoretical contributions (cf. Ridder, 2017 ).

The general motivation for a specific case study distinguishes the four academic approaches. Whereas, an NTF study starts with a couple of preliminary variables and constructs, but no assumed relationships, the research question in GAH is based on existing theory and strives to answer “how and why” questions. The main driving force behind SCR is the researchers' curiosity to understand a particular phenomenon, while an ANO case study specifically investigates why a specific situation cannot be explained by existing theory. Data collection also differs based on the design. Purposive sampling, which is used in GAH as well as SCR, chooses members of a population for inclusion in a study based on the researchers' judgment. The sampling approach in GAH is highly dependent on the goal of the case study, which might suggest the selection of extreme or unusual cases as well as common or revelatory cases. In SCR the case is either of general interest or may help to better understand a theoretical issue. Theoretical sampling is a variation of purposive sampling with a stronger focus on identifying important theoretical constructs and their relationships ( Ridder, 2017 ).

As far as data analysis is concerned, the focus of NTF lies on the identification of emerging constructs within the case or between cases. GAH, in which a tentative theory exists, focuses on the correspondence between the researchers' framework or propositions and the data. The goal of SCR is to learn from the case and to come up with a categorical aggregation. Finally, data is also aggregated in an ANO study with a focus of theory reconstruction. In each study type, the methodological approach closely follows the intended research goal. In NTF, interviews, documents and observations can be used to discover relevant constructs and relationships. Similarly, a GAH approach relies on the confrontation of existing theory-based constructs and relationships with case descriptions resulting from interviews, documents and observations. In order to understand construct reality, a rich description of a particular case is completed in SCR, while an ANO approach relies on observation, interviews and dialogue between observer and participants to better understand why existing theoretical explanations have failed ( Ridder, 2017 ).

Eisenhardt and Graebner (2007) , p. 30 point out that “Theory building from case studies is an increasingly popular and relevant research strategy,” which is closest aligned with the NTF approach. Similarly, SCR strives to build theory from the rich descriptions gained during the analysis process, while the focus of GAH is more on developing and testing theory, and the goal of ANO is to test theory by emphasizing contradictions between existing theory and reality.

Case study researchers also have a substantial amount of freedom as far as the mode of argumentation is concerned. Dubois and Gadde (2002) highlight the different strengths of deductive, inductive and abductive approaches. Deduction works best for developing propositions from current theory and making them testable, induction strives to systematically generate theory from data, and abduction can be used for the discovery of new variables and relationships.

Blockchain Use Cases

It is a salient feature of the Blockchain that its characteristics allow for the creation of a multitude of (potential) use cases ( Tapscott and Tapscott, 2016 ; Dieterich et al., 2017 ; Morabito, 2017 ; White, 2017 ; Lacity, 2018a ; Leonard and Treiblmaier, 2019 ; Treiblmaier and Umlauff, 2019 ): cryptocurrencies, examples for smart contracts, crowdfunding, prediction markets, energy markets, smart property, settlements, processing, authenticity, traceability of products along the supply chain and visibility in data exchange, trade financing, international payments, know your customer (KYC), identity management, provenance, property, ownership, rights management, governance, digital certificates, digital identity, digital asset registry, escrow transfers, electronic voting, verified corporate due diligence, verified customer reviews, performance management systems, betting, tokenized incentive economies, digital rights, derivates markets, remittances, sustainability. This non-exhaustive list of use cases illustrates the potential of the Blockchain to transform organizations and their relationships. A comprehensive description of the respective use case is at the core of every case study and determines the methods being chosen.

Blockchain Case Studies in the Literature

In order to identify existing Blockchain case studies, I followed the guidelines for systematic literature reviews as suggested by Tranfield et al. (2003) and Watson (2015) and applied in Ngai et al. (2008) as well as ( Ngai and Gunasekaran, 2007 ). performed a database search using the terms “Blockchain” or “Distributed Ledger Technology (DLT),” in any combination with “case study,” “use case” or “case.” The databases I used were Business Source Premier from EBSCOhost and ScienceDirect as well as publicly available information on Google Scholar and ResearchGate. Furthermore, I screened the references of the selected publications to identify further papers of relevance. During the identification and selection process, it turned out that it was difficult to differentiate between full-fledged case studies and the documentation of single use cases, since many use cases were performed in close cooperation with the industry and embedded within more comprehensive projects. Furthermore, the term “case study” is frequently used for any kind of report in which project findings are reported, regardless of whether a rigorous approach was applied.

To select existing Blockchain cases studies, I decided to use as a relevant criterion the development or thorough discussion of (a) a prototype or an application, (b) a solution for a specific company, or (c) a solution for a particular industry. I did not include any white papers, which are frequently used by so-called ICOs (initial coin offerings) to promote their product and occasionally also refer to use cases. Table 5 lists the case studies that fulfill those selection criteria. I describe the methodological approach used in each case and the degree to which each study fulfills my recommendations for Blockchain case study research: the description of relevant Blockchain characteristics (cf. Table 2 ), the description of potential challenges that needed to be overcome (cf. Table 3 ), the research design with a focus on the underlying theoretical approach (cf. Table 4 ), and an evaluation of the outcome.

Table 5 . Blockchain case studies.

It turned out that Blockchain case studies are highly fragmented. Hardly any of them apply the suggested procedures for case studies that can be found in the academic literature. For example, I found only two case studies explicitly referring to theory. One is from Albrecht et al. (2018) , who apply Diffusion of Innovations theory, the Technology-Organization-Environment framework and institutional economics to investigate Blockchain use cases in the energy sector. The other one is from ( Pazaitis et al., 2017 ), who build their study about the Blockchain and value systems in the sharing economy on the theory of value. Nonetheless, all of the case studies provide some insight on topics of interest to the industry and from which some insights can be drawn.

Designing and Reporting Blockchain Case Studies

Figure 1 presents a framework illustrating how Blockchain use cases, case study research, the creation of artifacts and the creation, development and testing of theory are connected. The starting point is a specific phenomenon, most likely an envisioned Blockchain use case as listed above, embedded in its real-world context. In a first step, a careful preparation of the case is needed, in which it is crucial to outline the design of the study, including the motivation for applying Blockchain technology, data sources and the context. As is shown in this paper, case study research is a fairly flexible and multifaceted research approach that accommodates different methodological designs, but I still recommend to explicitly outline the basic structure and the goals of the project and how they influence the choice of methods. A crucial part of any Blockchain case study is the description of the relevant Blockchain characteristics (as shown in Table 2 ) and how they potentially contribute to the solution for a specific problem.

Figure 1 . A Framework for blockchain case study research.

Blockchain Case Study Framework

After outlining the justification for why a Blockchain-based approach is used, there are two basic streams of research, which can be differentiated by their goals of either focusing on theory or creating an artifact. Yin (2014) writes that “some theory development as part of the design phase is highly desired” (p. 37), but, as was shown above, alternative academic case study designs exist ( Ridder, 2017 ), or researchers may decide to create a teaching or industry case. If the focus is on the creation of theory, analytic generalization is applied, which is a two-step process that involves the illustration of how the findings of a case study bear upon a particular theory, theoretical construct, or theoretical sequence of events as well as the application of the same theory to implicate similar situations ( Yin, 2010 ). If the goal is the creation of an artifact, practical recommendations are needed which enable replication studies to track and trace the design, development and implementation process.

Theory-oriented research aims at theoretical implications for further use cases, but does not necessarily preclude the creation of a design science artifact. In a frequently cited case study, Markus (1983) reports on the implementation of a financial information system, but also applies and evaluates three different theories of resistance in the same study. She thus illustrates how a theoretical perspective can actually help in the solution of a practical problem. The generation of a design science artifact, which in the case of Blockchain might be a prototype, a full-fledged application or the implementation of a smart contract, has practical implications for the final evaluation of the use case. Either the original goal is achieved—(“success story”),—which calls for further replication studies in different scenarios, or the deviation from the originally specified project goals necessitates several modifications. Failures should therefore be documented, which is something that rarely happens in the industry, but should be a hallmark of academic research. It has to be noted, however, that design science research does not have to exclusively focus on design artifacts. As Baskerville et al. (2018) highlight, design theorizing is an expected norm in design science research, which implies that there is “some reflection on the advance in design knowledge that is being made” (p. 363).

A careful documentation of the deviations between initial expectations and concrete implementations is highly beneficial for future related studies. In the case of the Blockchain those experiences are especially important since, for example, the engineering process for smart contracts needs to be designed to account for the immutability of the Blockchain ( Sillaber et al., 2018 ). Other than in traditional software design, Blockchain-oriented design needs to prepare for all contingencies already during the conceptualization phase of a project. Currently there is a lack of research that evaluates the extent to which this is possible. The goal of the framework shown in Figure 1 is to give a rough overview of how case studies and their related methodological and epistemological approaches can be connected.

Blockchain Case Study Structure

The checklist in Table 6 , which is loosely based on recommendations for systematic reviews from Moher et al. (2009) , includes various sections (topics) to be included and discussed in a Blockchain case study. The actual structure clearly depends on the chosen design (e.g., research case, teaching case, industry case), but several principles might equally apply for different designs. As is the case in any academic paper, the abstract should highlight the major findings of the study in a nutshell, and will not be discussed any further herein.

Table 6 . Case study checklist.

In order to put a case study into context, researchers initially need to clearly outline the goal(s) of the project, as well as the justification for applying a Blockchain-based solution in this specific setting. Ideally, similar cases from the literature are considered. Defining and describing the type of Blockchain being evaluated and/or deployed (cf. Table 1 ) as well as the organizational context of the study is crucial to examining the fit between them. This includes all conditions and circumstances that are of relevance for the project, including internal and external driving forces as well as existing organizational structures and top management support. Numerous decision trees can be found in the literature that scrutinize the general applicability of the Blockchain. A recent white paper from the World Economic Forum (2018 , p. 6) summarizes decisive filter questions that help organizations to identify those scenarios in which a Blockchain application may not be appropriate. Most importantly, these scenarios include settings in which there are no intermediaries or brokers that need to be removed, no digital assets are used, and no permanent authoritative record of a digital asset can be created. For a comprehensive description of a Blockchain project at a conceptual stage, Feig (2018) recommends asking the following ten questions: (1) Who are the users?, (2) What data do users input?, (3) Are any inputs irreversible?, (4) Who are the peers?, (5) How do peers create blocks?, (6) What do peers validate?, (7) How do peers validate?, (8) How do peers reach consensus?, (9) Is the Blockchain immutable?, and (10) How are peers incentivized? In short, the first part of any Blockchain case study must lay the foundation for the rest of the paper by pinpointing the organizational setting as well as the technology and its intended purpose. Researchers especially need to document how they apply the respective characteristics of the Blockchain (cf. Table 2 ) and how they tackle the major challenges that arise during an implementation (cf. Table 3 ). Both industry and academia are at an early stage of Blockchain development and the careful description and documentation of case studies can help the industry to build on previous success stories and avoid pitfalls.

Subsequently, the methodology of the project needs to be introduced and explained, which differs significantly based on the role of theory. If the research is explicitly theory-focused, the four different designs shown in Table 4 —NTF, GAH, SCR, and ANO—need to be described in detail. The respective selection obviously impacts the choice of methods and data sources as well as the interpretation of the findings. If the focus is more on the creation of artifacts, the traceability and documentation of the case are paramount. However, this does not preclude theorizing, which can be done in an “interior mode” (i.e., producing theory for design and action) and an “exterior mode” (theorizing about artifacts in use) ( Baskerville et al., 2018 ). A comprehensive documentation of the data collection process is needed for all types of cases studies, while an in-depth description of the variables, which might include latent constructs, and their respective relationships is especially important for theory-related Blockchain studies. Independent of the type of case study, a certain amount of rigor is needed for the research design as well as for data collection and analysis processes ( Darke et al., 1998 ).

The presentation of the Blockchain results, again, heavily depends on the chosen design, but I recommend the inclusion of an additional discussion on how the characteristics of the Blockchain (cf. Table 2 ) were applied and how the Blockchain challenges (cf. Table 3 ) were overcome. Depending on the overall goal of the case study, it might be useful to detail various business processes or the development of smart contracts which deviate from previous software engineering approaches. Sillaber et al. (2018) suggest an elaborated engineering process which takes into account the immutability of smart contracts and is not based on the traditional waterfall model, but rather details the following phases: conceptualization, implementation, approval, submission, execution, and finalization. Elaborating on these stages helps readers of Blockchain case studies to reproduce the development and deployment of smart contracts.

The discussion summarizes the main findings and their relevance for major stakeholders. Additionally, a comparison with previous research is advisable, which especially includes the identification and description of “surprising” results. Lacity (2018a , p. 48) suggests structuring Blockchain applications around four major components: (1) the application interface or access point (e.g., digital asset exchange, digital wallet, bridge/gateway services, interfaces with existing systems, IoT devices), (2) use cases (e.g., track & trace, payments, voting), (3) code bases (e.g., Hyperledger Fabric, Ethereum, Corda, Multichain), and (4) Blockchain protocols (i.e., specific rules regarding access and how transactions are structured, addressed, transmitted, routed, validated, sequenced, secured, and added to the permanent record). Her framework provides a possible structure to systematically discuss the findings.

In order to provide a comprehensive quality assessment, Yin (2014) , p. 45) suggests an evaluation of construct validity, internal validity, external validity, and reliability. This is especially crucial for studies that build on previous research, develop and test theory, or strive to create a new research agenda. Given that the Blockchain is an evolving technology, a thorough analysis of limitations in light of the original research goals will help to critically shed light on its possibilities. As I have already noted above, the careful documentation and analysis of unsuccessful projects will also benefit future Blockchain endeavors. Carefully drafted conclusions and implications, which extend previous research, will further help to build a comprehensive Blockchain research agenda. Finally, if applicable, funding sources and the role of funders have to be specified.

In this paper I summarize key principles of various types of case study research and propose guidelines on how to design, conduct, and report Blockchain case studies. However, the structure I provide in this paper, along with suggestions on how to incorporate theory and ensure validity, is not meant as an exhaustive checklist to be used by reviewers in order to assess the overall quality of a publication. In other words, it should not be the case that the guidelines “become more important than the study” ( Holtkamp et al., 2019 ) or that the paper is “written according to a ‘formula”' ( Avison et al., 2017 , p. 271). Instead, I concur with Klein and Myers (1999) , p. 78) who write “while we believe that none of our principles should be left out arbitrarily, researchers need to work out themselves how (and which of) the principles apply in any particular situation.” I therefore believe that researchers will benefit most from this paper by consulting it prior to designing their study and selecting those parts that they deem useful for their specific research goals.

In a nutshell, I recommend that researchers

• provide a rationale for the use of Blockchain technology,

• define the type of Blockchain they use,

• describe the Blockchain characteristics that are relevant for their study and how they are implemented,

• discuss the Blockchain challenges encountered during the case study and how they influenced the outcome,

• justify the chosen case study type,

• outline the respective case study methodology,

• present and discuss the results appropriately for the specific case study type,

• provide a critical evaluation of their results,

• embed their results into a broader context, thus enabling incremental research.

Case study research provides a lot of freedom for academics and allows for the combination of various theoretical and practical approaches. By carefully designing their studies, researchers can ensure that they get the most out of this versatile approach. Blockchain technology is currently in its infancy and case study research provides many useful tools to systematically generate knowledge on which future research can build, be it theory-based or practically oriented. The recommendations I present in this paper are intended to enable such an incremental research agenda and I hope that many researchers will find them useful. Future research can easily adapt my recommendations to the investigation of other disruptive technologies.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Alabi, K. (2017). Digital blockchain networks appear to be following Metcalfe's Law. Electro. Commerce Res. Appli. 24, 23–29. doi: 10.1016/j.elerap.2017.06.003

CrossRef Full Text | Google Scholar

Albrecht, S., Reichert, S., Schmid, J., Strüker, J., Neumann, D., and Fridgen, G. (2018). “Dynamics of blockchain implementation—A case study from the energy sector,” in Proceedings of the 51 st Hawaii International Conference on System Sciences (Hawaii, USA).

Google Scholar

Angrish, A., Craver, B., Hasan, M., and Starly, B. (2018). A case study for Blockchain in manufacturing: “FabRec”: A prototype for peer-to-peer network of manufacturing nodes. Procedia Manufact. 26, 1180–1192. doi: 10.1016/j.promfg.2018.07.154

Auricchio, A., Fontela, B., Goel, A., He, Y., Jungmair, C., and Roa, A. (2017). Ryanair: Impact of Blockchain on the Organizational Design of Ryanair, Report . Available online at: https://de.slideshare.net/AntonioAuricchio/the-impact-of-blockchain-on-ryanairs-dynamic-prices (accessed July 14, 2018).

Avison, D., Malaurent, J., and Eynaud, P. (2017). A narrative approach to publishing information systems research: inspiration from the French New Novel tradition. Eur. J. Inform. Syst. 26, 260–273 doi: 10.1057/s41303-016-0022-1

Bahga, A., and Madisetti, V. K. (2017). Blockchain Applications: A Hands-On Approach . Berlin: VPT.

Baskerville, R., Baiyere, A., Gregor, S., Hevner, A., and Rossi, M. (2018). Design science research contributions: finding a balance between artifact and theory. J. Assoc. Inform. Syst. 19, 358–376. doi: 10.17705/1jais.00495

Beck, R., Avital, M., Rossi, M., and Thatcher, J. B. (2017). Blockchain technology in business and information systems research. Business Inform. Syst. Eng. 59, 381–384. doi: 10.1007/s12599-017-0505-1

Benbasat, I., Goldstein, D. K., and Mead, M. (1987). The case research strategy in studies of information systems. MIS Q. 11, 369–386. doi: 10.2307/248684

Biswas, K., Muthukkumarasamy, V., and Tan, W. L. (2017). “Blockchain based wine supply chain traceability system,” in Proceedings of the Future Technologies Conference (Vancouver).

Burawoy, M. (2009). The Extended Case Method. Four Countries, Four Decades, Four Great Transformations, and One Theoretical Tradition . Berkeley: University of California Press.

Burns, R. B. (2000). Introduction to Research Methods . London: SAGE publications.

Cavaye, A. L. M. (1996). Case study research: a multifaceted research approach for IS. Inform. Syst. J. 6, 227–242. doi: 10.1111/j.1365-2575.1996.tb00015.x

Darke, P., Shanks, G., and Broadbent, M. (1998). Successfully completing case study research: combining rigour, relevance and pragmatism. Inform. Syst. J. 8, 273–289. doi: 10.1046/j.1365-2575.1998.00040.x

Deloitte. (2017). Key Characteristics of the Blockchain. Deloitte Touche Tohmatsu India LLP. Avaialble online at: https://www2.deloitte.com/content/dam/Deloitte/in/Documents/industries/in-convergence-blockchain-key-characteristics-noexp.pdf (accessed October 1, 2018).

Dieterich, V., Ivanovic, M., Meier, T., Zäpfel, S., Utz, M., and Sandner, P. (2017). Application of Blockchain Technology in the Manufacturing Industry . Working Paper, Frankfurt School Blockchain Center.

Dubé, L., and Paré, G. (2003). Rigor in information systems positivist case research: current practices, trends, and recommendations. MIS Q. 27, 597–635. doi: 10.2307/30036550

Dubois, A., and Gadde, L. (2002). Systematic combining: an abductive approach to case research. J. Business Res. 55, 553–560. doi: 10.1016/S0148-2963(00)00195-8

Eisenhardt, K., and Graebner, M. E. (2007). Theory building from cases: Opportunities and challenges. Acad. Manage. J. 50, 25–32. doi: 10.5465/amj.2007.24160888

Eisenhardt, K. M. (1989). Building theories from case study research. Acad. Manag. Rev. 14, 532–550. doi: 10.5465/amr.1989.4308385

Feig, E. (2018). A Framework for Blockchain-Based Applications . Available online at: https://arxiv.org/abs/1803.00892

Glaser, B., and Strauss, A. L. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research . Chicago: Aldine Publishing Company.

Government Office for Science. (2016). Distributed Ledger Technology: Beyond Block Chain . A report by the UK government chief scientific advisor. London: Government Office for Science.

Gräther, W., Kolvenbach, S., Ruland, R., Schütte, J., Torres, C. F., and Wendland, F. (2018). “Blockchain for education: lifelong learning passport,” in Proceedings of the 1st ERCIM Blockchain Workshop 2018, Reports of the European Society for Socially Embedded Technologies , eds W. Prinz and P. Hoschka (Amsterdam), 1–8.

Greiner, M., and Wang, H. (2015). “Trust-free systems - a new research and design direction to handle trust issues in p2p systems: the case of bitcoin,” in Proceedings of the Americas Conference on Information Systems .

Hawlitschek, F., Notheisen, B., and Teubner, T. (2018). The limits of trust-free systems: a literature review on blockchain technology and trust in the sharing economy. Electro. Commer. Res. Appl. 29, 50–63. doi: 10.1016/j.elerap.2018.03.005

Hoelscher, J. (2018). Taking the lead on Blockchain: as the technology behind Bitcoin finds new uses, internal auditors must assess how the risks may impact the organization. Internal Audi. 75, 19–21

Holotiuk, F., Pisani, F., and Moormann, J. (2018).“Unveiling the key challenges to achieve the breakthrough of Blockchain: Insights from the payments industry,” in Proceedings of the 51 st Hawaii International Conference on System Sciences (Waikoloa), 3537–3546.

Holtkamp, P., Soliman, W., and Siponen, M. (2019).“Reconsidering the role of research method guidelines for qualitative, mixed-methods, and design science research,” in Proceedings of the 52nd Hawaii International Conference on System Sciences (Maui), 6280–6289.

Hsieh, H.-F., and Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualit. Health Res. 15, 1277–1288. doi: 10.1177/1049732305276687

PubMed Abstract | CrossRef Full Text | Google Scholar

Iansiti, M., and Lakhani, K. R. (2017). The truth about Blockchain, Harvard Busi. Rev. 95, 118–127.

Karamitsos, I., Papadaki, M., and Barghuthi, N. B. A. (2018). Design of the Blockchain smart contract: a use case for real estate. J. Inform. Secur. 9, 177–190. doi: 10.4236/jis.2018.93013

Khaqqi, K. N., Sikorski, J. J., Hadinoto, K., and Kraft, M. (2018). Incorporating seller/buyer reputation-based system in blockchain-enabled emission trading application. Appl. Energy 209, 8–19. doi: 10.1016/j.apenergy.2017.10.070

Kim, K., and Justl, J. M. (2018). Potential antitrust risks in the development and use of Blockchain. J. Tax. Regulat. Finan. Instit. 31, 5–16.

Klein, H. K., and Myers, M. D. (1999). A set of principles for conducting and evaluating interpretive field studies in information systems. MIS Q. 23, 67–94. doi: 10.2307/249410

Kshetri, N. (2017). Blockchain's roles in strengthening cybersecurity and protecting privacy. Telecommun. Policy 41, 1027–1038. doi: 10.1016/j.telpol.2017.09.003

Kshetri, N. (2018). Blockchain's roles in meeting key supply chain management objectives. Int. J. Inform. Manage. 39, 80–89. doi: 10.1016/j.ijinfomgt.2017.12.005

Lacity, M. (2018a). A Manager's Guide to Blockchain for Business: From Knowing What to Knowing How , Warwickshire, UK: SB Publishing.

Lacity, M. (2018b). Addressing key challenges to making enterprise Blockchain applications a reality, MIS Q. Execut. 17, 201–222.

Lacity, M. C., and Willcocks, L. P. (2018). Robotic Process and Cognitive Automation: The Next Phase , Steve Brooks Publishing.

Lee, A. S. (1989). A scientific methodology for MIS case studies. MIS Q. 13, 33–50. doi: 10.2307/248698

Lemieux, V. L. (2016). Trusting records: is blockchain technology the answer? Records Manag. J. 26, 110–139. doi: 10.1108/RMJ-12-2015-0042

Leonard, D., and Treiblmaier, H. (2019). “Can cryptocurrencies help to pave the way to a more sustainable economy? Questioning the economic growth paradigm,” in Business Transformation through Blockchain—Volume I , eds H. Treiblmaier and R. Beck (Cham: Palgrave Macmillan). doi: 10.1007/978-3-319-99058-3_7

Li, Z., Barenji, A. V., and Huang, G. Q. (2018). Toward a blockchain cloud manufacturing system as a peer to peer distributed network platform. Robot. Comput. Integ. Manufact. 54, 133–144. doi: 10.1016/j.rcim.2018.05.011

Lucena, P., Binotto, A. P. D., da Silva Momo, F., and Kim, H. (2018). “A case study for grain quality assurance tracking based on a Blockchain business network,” in Symposium on Foundations and Applications of Blockchain (FAB'18) (Los Angeles, USA).

MarketsandMarkets. (2017). Blockchain Market by Provider, Application (Payments, Exchanges, Smart Contracts, Documentation, Digital Identity, Supply Chain Management, and GRC Management), Organization size, Industry Vertical, and Region - Global Forecast to 2022. Market Report , MarketsandMarkets.com.

Markus, M. L. (1983). Power, politics, and MIS implementation. Commun. ACM 26, 430–444. doi: 10.1145/358141.358148

McConaghy, M., McMullen, G., Parry, G., McConaghy, T., and Holtzman, D. (2017). Visibility and digital art: blockchain as an ownership layer on the Internet. Strat. Change 26, 461–470. doi: 10.1002/jsc.2146

Meiklejohn, S., Pomarole, M., Jordan, G., Levchenko, K., McCoy, D., Voelker, G. M., et al. (2016). A fistful of Bitcoins: characterizing payments among men with no names. Commun. ACM 59, 86–93. doi: 10.1145/2896384

Mengelkamp, E., Gärttner, J., Rock, K., Kessler, S., Orsini, L., and Weinhardt, C. (2018). Designing microgrid energy markets. a case study: the brooklyn microgrid. Appl. Energy 210, 870–880. doi: 10.1016/j.apenergy.2017.06.054

Mik, E. (2017). Smart contracts: terminology, technical limitations and real world complexity. Law, Innovat. Technol. 9, 269–300. doi: 10.1080/17579961.2017.1378468

Moher, D., Liberati, A., Tetzlaff, J., and Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 6:e1000097. doi: 10.1371/journal.pmed1000097

Morabito, V. (2017). Business Innovation through Blockchain: The B3 Perspective . Cham: Springer.

Mougayar, W. (2016). The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology , Hoboken, NJ: Wiley.

Nakamoto, S. (2008). Bitcoin: a peer-to-peer electronic cash system. Self-Published paper , p. 1–9.

Narayanan, J., and Clark, J. (2017). Bitcoin's academic pedigree: the concept of cryptocurrencies is built from forgotten ideas in the research literature. ACM Queue 15, 1–30.

Ngai, E. W. T., and Gunasekaran (2007). A review for mobile commerce research and applications. Decis. Supp. Syst. 43, 3–15. doi: 10.1016/j.dss.2005.05.003

Ngai, E. W. T., Moon, K. K. L., Riggins, F. J., and Yi, C. Y. (2008). RFID research: an academic literature review (1995-2005) and future research directions. Int. J. Prod. Econ. 112, 510–520. doi: 10.1016/j.ijpe.2007.05.004

Nguyen, G.-T., and Kim, K. (2018). A survey about consensus algorithms used in Blockchain. J. Inform. Process. Syst. 14, 101–128. doi: 10.3745/JIPS.01.0024

O'Dair, M., and Beaven, Z. (2017). The networked record industry: How blockchain technology could transform the record industry. Strat. Change 26, 471–480. doi: 10.1002/jsc.2147

Olsen, R., Battiston, S., Caldarelli, G., Golub, A., Nikulin, M., and Ivliev, S. (2018). Case study of Lykke exchange: architecture and outlook. J. Risk Fina. 19, 26–38. doi: 10.1108/JRF-12-2016-0168

Önder, I., and Treiblmaier, H. (2018). Blockchain and tourism: three research propositions. Ann. Tour. Res. 72:5. doi: 10.1016/j.annals.2018.03.005

Pazaitis, A., De Filippi, P., and Kostakis, V. (2017). Blockchain and value systems in the sharing economy: the illustrative case of Backfeed. Technol. Forecast. Social Change 125, 105–115. doi: 10.1016/j.techfore.2017.05.025

Peck, M. (2017). Reinforcing the Links of the Blockchain . IEEE Future Directions Initiative White Paper.

Pongnumkul, S., Siripanpornchana, C., and Thajchayapong, S. (2017). “Performance analysis of private Blockchain platforms in varying workloads,” in 26 th International Conference on Computer Communication and Networks (ICCCN) (Vancouver).

Posadas, D. V. (2018). The internet of things: the GDPR and the Blockchain may be incompatible. J. Internet Law 21, 1–29.

Ridder, H.-G. (2017). The theory contribution of case study research designs. Business Res. 10, 281–305. doi: 10.1007/s40685-017-0045-z

Saad, M., Spaulding, J., Njilla, L., Kamhoua, C., Nyang, D.-H., and Mohaisen, A. (2019). “Overview of attack surfaces in Blockchain,” in Blockchain for Distributed System Security , eds S. S. Shetty, C. A. Kamhoua, and L. L. Njilla (Hoboken, NJ: Wiley-IEEE Press), 51–66.

Schueffel, P. (2017). Alternative distributed ledger technologies: blockchain vs. tangle vs. hashgraph - a high-level overview and comparison. SSRN Electro. J. 3144241, 1–8. doi: 10.2139/ssrn.3144241

Sikorski, J. J., Haughton, J., and Kraft, M. (2017). Blockchain technology in the chemical industry: machine-to-machine electricity market. Appl. Energy Elsevier 195, 234–246. doi: 10.1016/j.apenergy.2017.03.039

Sillaber, C., Gallersdörfer, U., Waltl, B., Felderer, M., and Treiblmaier, H. (2018). “Toward an integrated process model for smart contract engineering,”in Pre-ICIS Workshop on Blockchain and Smart Contract (San Francisco, USA), p. 82–86.

Stake, R. E. (1995). The Art of Case Study Research . Thousand Oaks: Sage Publications.

Strugar, D., Hussain, R., Mazzara, M., Rivera, V., Lee, J.-Y., and Mustafin, R. (2018). “On M2M micropayments: a case study of electric autonomous vehicles,” in IEEE International Conference on Blockchain (Blockchain-2018) (Halifax, NS).

Sullivan, C., and Burger, E. E. (2017). Residency and blockchain. Compu. Law Secur. Rev. 33, 470–481. doi: 10.1016/j.clsr.2017.03.016

Swan, M. (2015). Blockchain: Blueprint for a New Economy. Sebastopol , CA: O'Reilly Media.

Szabo, N. (1997). The Idea of Smart Contracts. Nick Szabo's papers and concise tutorials . Available online at: http://www.fon.hum.uva.nl/rob/Courses/InformationInSpeech/CDROM/Literature/LOTwinterschool2006/szabo.best.vwh.net/idea.html (accessed May 1, 2018).

Tapscott, D., and Tapscott, A. (2016). Blockchain Revolution: How the Technology behind Bitcoin is Changing Money, Business, and the World. New York, NY: Penguin.

Tranfield, D., Denyer, D., and Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br. J. Manage. 14, 207–222. doi: 10.1111/1467-8551.00375

Treiblmaier, H. (2018). The impact of the Blockchain on the supply chain: a theory-based research framework and a call for action. Supply Chain Manage. 23, 545–559. doi: 10.1108/SCM-01-2018-0029

Treiblmaier, H., and Beck, R. (2019a). Business Transformation Through Blockchain—Volume I . Cham: Palgrave Macmillan.

Treiblmaier, H., and Beck, R. (2019b). Business Transformation Through Blockchain – Volume II . Cham: Palgrave Macmillan.

Treiblmaier, H., and Umlauff, U. (2019). “Blockchain and the future of work: a self-determination theory approach,” in Blockchain Economics: Implications of Distributed Ledger Technology , eds M. Swan, J. Potts, S. Takagi, P. Tasca, and F. Witte (New Jersey, NJ), 105–124. doi: 10.1142/9781786346391_0006

Treiblmaier, H., and Zeinzinger, T. (2018). “Understanding the Blockchain through a gamified experience: a case study from Austria,” 25th European Conference on Information Systems (Portsmouth: UK).

Watson, R. T. (2015). Beyond being systematic in literature reviews in IS. J. Inform. Technol. 30, 185–187. doi: 10.1057/jit.2015.12

White, G. R. T. (2017). Future applications of blockchain in business and management: A Delphi Study. Strate. Change 26, 439–451. doi: 10.1002/jsc.2144

Wood, G. (2014). Ethereum: a secure decentralised generalised transaction ledger. Ethereum Project Yellow Paper , 1–32.

World Economic Forum (2018). Blockchain Beyond the Hype: A Practical Framework for Business Leaders, White Paper, World Economic Forum , Geneva: Switzerland.

Wynn, J. D., and Williams, C. K. (2012). Principles for conducting critical realist case study research in Information Systems. MIS Q. 36, 787–810. doi: 10.2307/41703481

Yin, R. (2010). “Analytic generalization,” in Encyclopedia of Case Study Research , eds J. Albert, G. Mills, and E. Wiebe (Thousand Oaks, CA: SAGE Publications, Inc.), 21–23.

Yin, R. K. (2014). Case Study Research: Design and Methods . Thousand Oaks: CA: Sage.

Ying, W., Jia, S., and Du, W. (2018). Digital enablement of Blockchain: Evidence from HNA group, Int. J. Inform. Manag. 39, 1–4. doi: 10.1016/j.ijinfomgt.2017.10.004

Yli-Huumo, J., Ko, D., Choi, S., Park, S., and Smolander, K. (2016). Where is current research on blockchain technology? A systematic review. PLoSONE 11:0163477. doi: 10.1371/journal.pone.0163477

Yuan, Y., and Wang, F.-Y. (2018). Blockchain and cryptocurrencies: model, techniques, and applications. IEEE Trans. Syst. Man Cyber. 48, 1421–1428. doi: 10.1109/TSMC.2018.2854904

Zhang, P., White, J., Schmidt, D. C., Lenz, G., and Rosenbloom, S. T. (2018). FHIRChain: applying Blockchain to securely and scalably share clinical data. Comput. Struct. Biotechnol. J. 16, 267–278. doi: 10.1016/j.csbj.2018.07.004

Keywords: blockchain, blockchain characteristics, distributed ledger technology, case study, use case, theory development, case study checklist, case study framework

Citation: Treiblmaier H (2019) Toward More Rigorous Blockchain Research: Recommendations for Writing Blockchain Case Studies. Front. Blockchain 2:3. doi: 10.3389/fbloc.2019.00003

Received: 06 February 2019; Accepted: 02 May 2019; Published: 16 May 2019.

Reviewed by:

Copyright © 2019 Treiblmaier. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Horst Treiblmaier, [email protected]

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

A look into the future of blockchain technology

Roles Conceptualization, Data curation, Investigation, Methodology

Affiliation Groupe ALTEN, France

Contributed equally to this work with: Francesco Fontana, Elisa Ughetto

Roles Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Politecnico di Torino, Corso Duca degli Abruzzi 24, Turin, Italy

Roles Conceptualization, Investigation, Methodology, Project administration, Supervision, Validation, Writing – original draft, Writing – review & editing

Affiliation Politecnico di Torino & Bureau of Entrepreneurial Finance, Corso Duca degli Abruzzi 24, Turin, Italy

• Daniel Levis, 
• Francesco Fontana, 
• Elisa Ughetto

• Published: November 17, 2021
• https://doi.org/10.1371/journal.pone.0258995
• Reader Comments

In this paper, we use a Delphi approach to investigate whether, and to what extent, blockchain-based applications might affect firms’ organizations, innovations, and strategies by 2030, and, consequently, which societal areas may be mainly affected. We provide a deep understanding of how the adoption of this technology could lead to changes in Europe over multiple dimensions, ranging from business to culture and society, policy and regulation, economy, and technology. From the projections that reached a significant consensus and were given a high probability of occurrence by the experts, we derive four scenarios built around two main dimensions: the digitization of assets and the change in business models.

Citation: Levis D, Fontana F, Ughetto E (2021) A look into the future of blockchain technology. PLoS ONE 16(11): e0258995. https://doi.org/10.1371/journal.pone.0258995

Editor: Alessandro Margherita, University of Salento, ITALY

Received: June 1, 2021; Accepted: October 9, 2021; Published: November 17, 2021

Copyright: © 2021 Levis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1 Introduction

Over the last few years, the hype and interest around blockchain technology have consistently increased. Practitioners from many industries and sectors have joined an open, yet mainly unstructured, discussion on the potential disruptive capabilities of this newly born technology [ 1 – 3 ]. In principle, the size of the phenomenon could be huge, with latest estimates predicting blockchain to store, by 2025, the 10 per cent of the world’s GDP (about $88tn in 2019) [ 4 ]. However, the complexity of the technology itself and the difficulties in assessing its impact across the different application fields have prevented the social, industrial and scientific communities to agree upon a shared vision of future blockchain-based scenarios. Very fundamental questions are still to be answered. Which blockchain-enabled applications will see the light in the next few years? Which industrial sectors will be mainly affected? How will companies react to potential industry-disruptors? How will the current societal paradigm shift? Which role will policy makers play in enhancing this new paradigm?

Despite the great and undoubted technological innovation linked to this technology, uncertainties and speculation on the potential scenarios still animate the industrial and scientific dialogue [ 5 ]. In particular, it is not yet clear which applications will see the light, and, eventually, what effects these changes will have at a societal level.

In this paper, we use a Delphi approach to investigate whether, and to what extent, blockchain-based applications will affect firms’ organizations, innovations and strategies by 2030, and, consequently, which societal areas will be mainly affected. With this methodology, we aim at reaching experts’ consensus to gain new insights and assess the likelihood about the future of the technology. This is a relevant issue, as blockchain technology applications cover a wide spectrum of areas. Blockchain can be applied vertically within an industry (e.g. disrupting its supply chain) or horizontally across different industries or within single companies (e.g. modifying the internal structures and the modus operandi of the different company functions). Given the number of potential applications and the complexity of the technology, stakeholders are divided into skeptics, who believe the technology is still too immature to become a paradigm in the near future, and enthusiasts, who instead believe that this radical innovation will disrupt many industries and completely change business models and people’s behaviors, like internet did during the 90s.

The literature on blockchain is also widely fragmented. Different works have investigated possible blockchain applications within specific domains, such as finance [ 6 – 8 ], logistics [ 9 ], healthcare [ 10 , 11 ] and education [ 12 ]. However, a holistic approach on possible blockchain-enabled future scenarios is still missing. To our knowledge, the only contribution in this direction is the one by White [ 13 ], who explores blockchain as a source of disruptive innovation exclusively with regard to the business field. We depart from his work to adopt a much wider perspective in this study. In fact, our aim is to obtain a deep understanding on how the adoption of this technology in Europe will lead to changes over multiple dimensions, ranging from business to culture and society, policy and regulation, economy and technology. Thus, our research aims at exploring if a convergence between the two divergent perspectives on blockchain can be found, bringing together experts currently working on blockchain projects to explore the possible changes that the technology will bring to the society by 2030.

Our study outlines an overall agreement among experts that the blockchain technology will have a deep impact on multiple dimensions. In the near future people will likely start using and exploit the blockchain technology potential, without really knowing how the technology behind works, in the same way as they send emails today, ignoring how the digital architecture that allows to exchange bytes of information works. Policy makers and governments will play a crucial role in this respect, by enabling productivity boosts and competitive gains from the companies operating under their jurisdictions. As such, a tight and cooperative relationship between industrial actors and regulatory bodies will be extremely important and auspicial. To this aim, it will be of key importance for all players to understand the real competitive advantage that blockchain can bring to their own industry and market.

This work aims at contributing to the raising blockchain literature by offering a holistic view on possible blockchain-enabled future scenarios in Europe, and to investigate which of the proposed scenarios is more likely to occur. As widely agreed by the academic literature, technological developments dictate the speed and pace at which societies change [ 14 ]. Under this assumption, technological forecasting appears to be a method of fundamental importance to understand “ex-ante” the potential development of technological changes, and their impact on different societal aspects [ 15 ]. Foreseeing future technological trends could help society in understanding possible future scenarios, thus contributing to a better knowledge of the new paradigms our society is heading towards. The work is structured as follows. Section 2 provides an overview on the main research streams upon which this work is based. Section 3 presents the methodology. Results are described in Section 4 and Section 5 concludes the work.

2 Background literature

2.1 the blockchain technology.

As defined by Crosby et al. [ 3 ] a blockchain can be conceptualized as a shared and decentralized ledger of transactions. This chain grows as new blocks (i.e. read transactions or digital events) are appended to it continuously [ 16 , 17 ]. Each transaction in the ledger must be confirmed by the majority of the participants in the system [ 3 , 18 – 21 ]. This means for the community to verify the truthfulness of the new piece of information and to keep the blockchain copies synchronized between all the nodes (i.e. between all the participants to the network) in such a way that everybody agrees which is the chain of blocks to follow [ 19 ]. Thus, when a client executes a transaction (e.g. when it sends some value to another client), it broadcasts the transaction encrypted with a specific technique to the entire network, so that all users in the system receive a notification of the transaction in a few seconds. At that moment, the transaction is “unconfirmed”, since it has not yet been validated by the community. Once the users verify the transaction with a process called mining, a new block is added to the chain. Usually, the miner (i.e. the user participating to the verification process) receives a reward under the form of virtual coins, called cryptocurrencies. Examples of cryptocurrencies are Bitcoins, Ether, Stellar Lumens and many others. Virtual coins can then be used on the blockchain platform to transfer value between users [ 17 – 19 ].

Thanks to a combination of mathematics and cryptography, the transactions between users (i.e. exchange of data and value), once verified by the network and added to the chain, are “almost” unmodifiable and can be considered true with a reasonable level of confidence [ 17 , 19 , 22 ]. These attributes of the technology make it extremely efficient in transferring value between users, solving the problem of trust and thus potentially eliminating the need of a central authority (e.g. a bank) that authorizes and certifies the transactions [ 7 , 23 , 24 ].

The technology can be easily applied to form legally binding agreements among individuals. The digitalized asset, which is the underlying asset of the contract, is called token. A token can be a digitalized share of a company, as well as a real estate property or a car. Through the setting of smart contracts (i.e. digitalized contracts between two parties), the blockchain technology allows users to freely trade digital tokens, and consequently to trade their underling physical assets without the need of a central authority to certify the transaction (OECD, 2020).

2.2 Blockchain technology applications

The academic literature has investigated a wide range of possible blockchain applications within specific domains, such as finance [ 6 – 8 ], logistics [ 9 ], healthcare [ 10 , 11 ] and education [ 12 ].

As mentioned, one of the undoubted advantages of the blockchain technology is the possibility to overcome the problem of trust while transferring value [ 25 ]. Not surprisingly, the technology seems to find more applications in markets where intermediation is currently high, like the financial sector, and in particular the FinTech sector, that has recently experienced a consistent make-over thanks to the diffusion of digital technologies [ 7 , 26 , 27 ]. The implementation of the blockchain technology in the financial markets could provide investors and entrepreneurs with new tools to successfully exchange value and capitals without relying on central authorities, ideally solving the problem of trust. This is among the reasons why many observers believe that the blockchain would become a potential mainstream financial technology in the future [ 28 ]. Blockchain represents an innovation able to completely remodel our current financial system, breaking the old paradigm requiring trusted centralized parties [ 6 – 8 ]. With new blockchain-based automated forms of peer-to-peer lending, individuals having limited or no access to formal financial services could gain access to basic financial services previously reserved to individuals with certified financial records [ 29 ]. Indeed, blockchain technology can provide value across multiple dimensions, by decreasing information asymmetries and reducing related transactional costs [ 30 ]. Initial coin offerings (ICOs) represent one of the most successful blockchain-based applications for financing which has been currently developed. Virtual currencies like Bitcoins can disruptively change the way in which players active in the business of financing new ventures operate [ 7 , 30 – 33 ]. Through an ICO, a company in need of new capital offers digital stocks (named token) to the public. These digital tokens will then be used by investors to pay the future products developed by the financed company [ 30 , 34 , 35 ]. ICOs represents a disruptive tool: entrepreneurs can now finance their ventures without intermediaries and consequently lower the cost of the capital raised [ 31 , 36 ]. However, some threats coming from the technology adoption can also be identified, as blockchain can also lead to higher risks related to the lower level of control intrinsically connected to the technology, especially in the case of asymmetric information between the parties involved.

Disintermediation plays a key role in the healthcare sector as well, where blockchain has recently found numerous applications. Indeed, many players currently need to exchange a huge amount of information to effectively manage the whole sector: from hospitals, to physicians, to patients. The ability to trustfully exchange data and information becomes of undoubted value in this context [ 10 , 11 ]. It should not be difficult to envision blockchain applications in other fields as well. In every sector in which information, value, or goods are supposed to flow between parties, blockchain can enable a trustful connection between the players, with the need of a central body entrusting the transaction. Within supply chain, it can increase security and traceability of goods [ 9 , 37 ]. Within education, it can help in certifying students’ acquired skills, reducing, for example, degree fraud [ 12 ]. To conclude, a recent work from Lumineau et al. [ 38 ] highlights possible implications of the technology in the way collaborations are ruled and executed, shading light on new organizational paradigms. Indeed, the authors show how the intrinsically diverse nature of the technology could strongly affect organizational outcomes, heavily influencing and modifying (possibly improving) the way in which different entities cooperate and collaborate.

3 Research methodology

3.1 forecasting technique: the delphi method.

In the past decade, an increasing number of forecasting techniques has been employed in the academic literature to predict the potential developments induced by technological changes. In particular, the Delphi method, whose term derives from the Greek oracle Delphos, is a systematic and interactive method of prediction, which is based on a panel of experts and is carried out through a series of iterations, called rounds. Many academic works have adopted this method since its development [ 14 , 39 – 44 ]. As the core of the Delphi approach, experts are required to evaluate projections (representations of possible futures) and assess their societal impact and the likelihood that they will occur within a specific time horizon.

While the majority of forecasting methods does not account for the technological implications on the social, economic and political contexts, the Delphi technique allows subjective consideration of changes in interrelated contexts [ 45 ]. Many different variants of the Delphi methodology have been developed according to the needs and goals of each research. For the purpose of this research, we decided to follow the four-steps procedure suggested by Heiko and Darkow [ 46 ] ( Fig 1 ).

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0258995.g001

The first step of the method requires to develop and envisage projections and possible scenarios that might arise through the adoption of the technology. These projections must be short, unequivocal, and concise [ 14 ]. This phase requires researchers to deeply understand the technology by analyzing the existing literature, attending courses and workshops and conducting a number of face-to-face interviews with experts ( Fig 2 ). Once the insights are gathered, the results are synthetized in future projections that will help develop the survey. The second step consists in presenting the study to the panel of selected experts who will take part in the first round of the survey. The main challenge during this phase is to select an appropriate panel of experts and maintain their commitment and response rate. The third step consists in a statistical and quantitative analysis of the answers received and in the selection of the second-round scenarios that experts will need to evaluate again. Through the analysis of the second round of answers, updated scenarios are developed adding to the projections the qualitative and quantitative insights provided by the research. The ultimate goal of this iterative process is to reach consensus among the experts on the scenarios that are most likely to happen in the future.

https://doi.org/10.1371/journal.pone.0258995.g002

3.2 Formulation of the Delphi projections

The formulation of the projections represents a key aspect of the methodology and requires a particular attention and effort. In this phase, the projections that are later tested by the panel of experts are generated. Vagueness and inaccuracy might generate confusion in experts, leading to less meaningful results. To avoid this situation, we developed the projections by means of triangulation: literature review, interviews with experts and participation to workshops and conferences. The analysis of the literature on blockchain technology (and its benefits) allowed us to understand which industries and businesses will be mainly impacted by the technology.

We chose 2030 as a time horizon for the generation of the scenarios. This is a recommended time span for a Delphi study, since a superior period would have become unmanageable to provide relevant advice for strategic development. As reported in Table 1 , projections span among different areas. To the scope of the work, i.e. to grasp a holistic view of the most likely scenarios, it was necessary to investigate a number of multiple dimensions. Projections are related to socio-cultural, policy and regulations, economic, technological and business aspects. As it can be noticed, projections are all structured in the same way, to facilitate their understanding by experts.

https://doi.org/10.1371/journal.pone.0258995.t001

3.2.1 Interviews with experts.

Twelve blockchain experts were interviewed among academics, startups’ founders and professionals working in consultancy firms, banks and legal institutions. The selection of the experts was made in order to get different points of view and a high level of expertise, as provided by the Delphi method guidelines. We conducted interviews that took between thirty and forty-five minutes on average, according to the interviewee’s availability. Each single interview was tailored for each participant by providing guidelines and reflection tips to encourage discussion. However, a certain degree of freedom was given to the expert to allow his/her spontaneous contribution and to gain some original insights that helped in the final design of the future scenarios. Some common aspects were discussed in all interviews generating redundancy and repetition of already emerged scenarios (e.g. ICOs, business model evolution, security and utility tokens, and legal issues). This is one of the reasons why twelve interviews were considered to be sufficient for the purposes of our research.

3.2.2 Conferences.

One of the authors attended three main events in order to strengthen the knowledge about blockchain and have a broader view of its implications in different fields and industries: one in Milan and two in Paris. Of particular notice, the Community Blockchain Week, a blockchain tech-focused initiative organized voluntarily by actors engaged into the technology and with the will and vision to spread the knowledge among citizens. Thanks to various workshops and speeches during the week, it was possible to dive deeper into many aspects of the technology, as well as to meet some knowledgeable experts of various fields, some of which agreed in participating to the research. The event was extremely useful not only to understand how the technology is evolving, but also to see how the community engages itself to spread the knowledge in order to generate more and more interest around it.

3.2.3 Desk research.

We performed desk research to formulate the initial set of projections. Through the survey of the literature, we gained a comprehensive view of all the potential scenarios of the technology. The analysis of consulting companies’ reports also offered a broader vision of future scenarios, thanks to their strategic rather than technical approach [ 1 , 2 ]. This process led to identify 76 projections that represented the basis for a reflection during the expert face-to-face interviews. After screening the relevant articles and reports, a first filtering of the identified 76 projections was made in order to dismiss redundant or incomplete projections, and to keep only the most complete and varied ones. This process reduced the number of projections to 33 and to 20 after the review of two experts.

3.3 The Delphi projections

The formulation of the projections represents the most sensitive part of the research since it influences the whole study. A detailed analysis was carried out in order to avoid mistakes and confusion. In order to facilitate the respondents filling the questionnaire and to avoid any kind of ambiguity, an introduction explaining the meaning of the terminology used in the questionnaire was presented before starting the survey. The developed scenarios were broken down into six macro categories (the same as proposed by Heiko and Darkow [ 46 ]) to guarantee a more complete and systemic view of how the blockchain ecosystem and community can change and shape the future. The choice of 20 projections to be evaluated by experts is in line with prior studies exploiting the Delphi method [ 46 , 47 ]. Parente and Anderson-Parente [ 47 ] have proposed to limit the number of Delphi questions (e.g. to 25 questions) in order to guarantee a high response rate and properly filled-in questionnaires, including only closed answers. We decided to add the possibility to comment the given answers in order to gather additional qualitative data to improve the quality of the results, in line with the methodology proposed by Heiko and Darkow [ 46 ].

3.4 Selection of the panel of experts

As blockchain experts that took part to the survey, we selected individuals working in companies and institutions on the basis of their experience and knowledge of the field. Following Adler and Ziglio [ 48 ] and Heiko and Darkow [ 46 ] four requirements for “expertise” were considered:

• knowledge and experience on blockchain technology;
• capacity and willingness to participate to the Delphi study;
• sufficient time to participate to the Delphi study;
• effective communication skills.

A minimum panel size of 15–25 participants is often required to lead to consistent results. In our case, a panel of 35 experts was reached for the first round. For the reliability of the study the panelists were selected with different backgrounds and profiles. To be aligned with the European focus of the study, we considered experts working in twelve European countries, being France and Italy the ones with the highest number of respondents. The panel characteristics are reported in Figs 3 , 4 and 5 .

https://doi.org/10.1371/journal.pone.0258995.g003

https://doi.org/10.1371/journal.pone.0258995.g004

https://doi.org/10.1371/journal.pone.0258995.g005

3.5 Execution of the Delphi surveys

In line with the methodology proposed by Heiko and Darkow [ 46 ], two rounds of surveys were executed. We decided to carry no more than two rounds because participating to a Delphi study requires a lot of effort and is a time-consuming task for panelists. By limiting the rounds to two, we reached a sufficient number of respondents that led to have valuable results and consistent conclusions. Moreover, since for each scenario the possibility to include a qualitative argumentation was included, the smaller number of iterations worked as a stimulus for the experts to explain the reasons of their quantitative answers.

The survey was carried out following the standards of the Internet-based Delphi, also called e-Delphi [ 39 , 40 ]. Giving the possibility to respondents to answer digitally allowed experts to be more flexible in responding to the survey, ensuring a greater participation. The way the questionnaire was structured was exactly as the e-Delphi website suggests, but for practical reasons we edited the survey using Google Form. Other standards, such as the real-time Delphi solution proposed by several studies [ 14 , 42 , 43 , 49 ] could have led to a better comparison among experts, but would have likely caused more withdraws to the survey.

3.5.1 First round.

In the first round of the survey, the experts assessed the expected probability and impact of the twenty outlined projections. Some Delphi studies [ 50 , 51 ] include a third factor that helps to assess the desirability of a scenario (i.e. how much an expert is in favour of the realization of a prediction). However, we decided not to include this last aspect to make the questionnaire lighter and faster to be filled in, and to reduce drop-outs ( Table 2 ).

https://doi.org/10.1371/journal.pone.0258995.t002

Impact, evaluated at the industry level, was measured on a five-point Likert scale [ 52 ]. Since there is not a general consensus among experts regarding the number of points the scale should have, and due to the general nature of the scenarios, we preferred to use a five-point Likert scale. The corresponding probabilities are: 0%, 25%, 50%, 75% and 100%. Gathering quantitative data allowed to perform a first set of analyses based on descriptive statistics (e.g. mean, median and interquartile range-IQR). We used qualitative data, instead, to build the final scenarios during the fourth step of the forecasting technique. Even though the literature regarding the Delphi method does not suggest a standardized way to analyze consensus, central tendency measures, such as median and mean values, are useful to grasp a first understanding and are frequently accepted and adopted ( Table 3 ). Scenarios with an IQR equal or lower than 1.5 were considered as having reached an acceptable degree of consensus. It should be noticed that most of the projections that achieved the highest probability, having a median value of 75% achieved also the consensus, i.e. IQR below 1.5. This was the case for projections 3, 4, 8, 9, 10, 13, 15, 19, 20.

https://doi.org/10.1371/journal.pone.0258995.t003

These results show that it was easier for experts to find a consensus over the projections that resulted as very likely to occur. Only projection number 18 achieved a high probability score but could not reach a consensus.

3.5.2 Second round.

During the Delphi’s second round only the projections with an IQR above 1.5 (i.e. which did not reach consensus in the first round) were tested. In order to allow the respondents to easily understand the answers that the panel gave as a whole in round one, for each projection a quantitative report was provided. This report was made of a bar chart with the distribution of the first round’s answers and the correspondent qualitative details, i.e. some of the argumentations provided by some of the panelists. Experts were asked to reconsider the likelihood of occurrence of the projections number 1, 5, 7, 11, 12, 14 and 18. The second round was again structured using Google Form. Following the Delphi’s approach, we did not ask again to estimate the impact for each projection, since this would have presumably been not subject to any change. Moreover, we decided to leave the opportunity to offer again some qualitative comments in support of the answers for a better analysis of the results. The number of experts who successfully completed the second round of the survey dropped to 28, i.e. the 80% of the experts that completed Round 1 and 56% of the selected initial panel. Again, we evaluated the central tendency measures for the projections tested during the second round ( Table 4 ).

https://doi.org/10.1371/journal.pone.0258995.t004

In order to provide a more effective and structured analysis of the results, we first report the final summary table of the Delphi survey and then describe the insights obtained from the analysis. It has to be noticed that Table 5 reports quantitative data only, while during the survey qualitative data were collected as well. In presenting the results of this research, both quantitative and qualitative data are used to provide the best possible picture of what the blockchain-based future will look like. Alongside with standard statistics, we build on qualitative insights obtained during the interviews carried on with experts.

https://doi.org/10.1371/journal.pone.0258995.t005

Firstly, it is interesting to analyze which projections, out of the initial 20, reached a significant consensus (IQR <1.5 after the two rounds of the surveys) and were given a high probability of occurrence by the experts. We can summarize the findings in this domain around three major axes: efficiency, security, and innovation.

By 2030, it will be easier, faster and leaner to exchange value and data among users, institutions and countries. Efficiency will boost and uncover innovation potential within companies and societies if these latter will be able to exploit such a new opportunity. Policies will be a necessary pre-requisite for companies to be able to build a competitive edge globally. From this perspective, the capability of central governments to spur innovation with lean and flexible regulations will be a key driver in explaining the ex-post productivity differential among companies belonging to different countries. From the interview with an investment banker part of the BPCE French group (one of the largest banks in France), it emerged how efficiency is often hampered by the lack of an equally efficient regulation. To provide the reader with an interesting example, in 2018, Natixis, the international corporate and investment banking, asset management, insurance and financial services arm of BPCE, entered the Marco Polo consortium, an initiative born to provide a newly conceived trade and supply chain finance platform, leveraging Application Programming Interfaces (APIs) and blockchain technology. Many other leading banks joined the consortium as well. However, as highlighted by the investment banker, the main limiting factor of the consortium, strongly hampering its efficiency and ability to provide a competitive edge, was the “old-style” bureaucracy linked to it. Although transactions were in principle to be executed smoothly, a bulk of legal paperwork was required to approve them formally. In this case, it appears evident that technology often runs faster than policy, consistently lowering its potential. Interestingly, this view is also shared by regulatory bodies. An experienced lawyer and notary, also member of a panel of experts elected by the Italian government to define the national strategy on blockchain, highlighted that, sometimes, regulators working on blockchain-related policies are trying to adapt existing regulations to the new paradigm. Due to the intrinsically different nature of the technology, this could represent a wrong approach. At the same time, building a new set of policies from scratches could represent a challenging task. From this perspective, projections 4 and 5 confirm this insight: policy and technology should come hand in hand to synergically boost productivity. The three projections reached consensus after the two rounds and were assigned a high probability of occurrence. Overall, it is evident that regulatory aspects linked to the adoption of this new technology shall not be underestimated.

As previously mentioned, security, and specifically cybersecurity, is another dimension around which blockchain could bring consistent advantages, as projections 3, 10, 11 and 15 suggest. On this specific aspect, we interviewed a project leader of the World Economic Forum who previously worked for the United Nations for more than ten years. She dealt specifically with digital regulations, justice, and cybersecurity, and in the last three years before the interview, she specifically worked on blockchain implications and how the technology could be implemented in existing ecosystems. Thanks to her experience in the domain, she clearly explained how the blockchain represents a meaningful technology to avoid cyberattacks to sensitive data and digital files. In her opinion, the avoidance of a single point of failure is the main reason behind a possible blockchain adoption over the next years, since cyberattacks are becoming more frequent and dangerous and related costs for companies are exponentially increasing (e.g. 2020 has been a record year for cyber attacks). Consequently, companies will be increasingly investing in distributed ledgers as a form of contingency budget to lower the cybersecurity risk and its related cost. Given the centrality of data in today’s businesses, serious attacks and loss of data could represent a serious threat to business long-term sustainability.

The third relevant aspect on which blockchain will have a strong impact is, not surprisingly, innovation. Although regulation could represent a non-negligible limiting factor, experts foresee many sectors to be impacted by the technology adoption. For example, the financial sector could be heavily affected by this new paradigm. Particularly, companies’ capital structures and their strategic interlink with business models will drive a differential competitive power. Most likely, enterprises will have to rethink their business models to account for the possibility to digitize/tokenize their assets (Projections 8 and 18). The capability in flexibly adapting their service offerings to the new opportunity and the ability to raise, and re-invest, new capitals will shape the global competition landscape across different industrial sectors and geographies. From one side, blockchain will enable new strategic decisions, from the other side, it will be of fundamental importance to build technological capabilities to enable these decisions. The underlying technology behind transactions, equity offering and equity share transfers will most likely be the blockchain (Projections 13 and 16). Disintermediation and the ability to exchange value, information, and data trustfully without a central authority will enable a new way of funding and cooperation on open-source projects (Projection 19). Most likely, people will refer to blockchain systems as they now refer to browsers such as Chrome, Firefox or Internet Explorer. Many blockchains are already available and are constantly improved and developed, and it is foreseeable that this will remain the case in the future. Users will just need to know the characteristics that a blockchain provides to choose the most suitable one for their business and purposes. Blockchain-based systems will require new skills and knowledge that developers and engineers will need to develop. Big efforts will be needed to make the blockchain more and more user friendly and attractive for those who just want to benefit from the immutability, traceability, and security that it intrinsically brings. At the time of the writing and in line with the Abernathy and Utterback model [ 53 ] many players are currently investing and innovating on blockchain to provide services that will satisfy the new market needs.

The opportunity for people to deal freely will in fact generate opportunities that were unforeseeable before. Self-enforcing smart contracts (Projection 20) will let parties to buy and sell products or to rent them with pay-for-use schemes in an automated way, the digitization of shares and assets will allow companies to raise capital in new ways, without the need to rely on banks, venture capitals or traditional IPOs. Indeed, it is important to understand how the digitization of assets can challenge existing investments and the funding industry represented by traditional private equity firms and banks. Blockchain could allow the creation of platforms for the issuance of traditional financial products on a tokenized nature, making it easier, more transparent and cheaper to manage and access these tools for everyone, including both individual savers and SMEs. Two different types of companies can and will operate in the market: those which have blockchain at their core since their foundation, and those which have (or will have) to embark in a digital transformation process to reconvert themselves into blockchain-based enterprises. In both cases, companies are investing to get a competitive advantage over competitors, betting on the technology that is promising to reduce costs and increase efficiency. Once a dominant design in product and services will be achieved, companies that took a different path will likely exit the market, letting firms following the dominant design to gain market shares.

To conclude and to conceptualize the insights we obtained from both quantitative and qualitative data, we derived four scenarios that we organized in a matrix framework, reported in Table 6 . The framework was built around two main dimensions: on one hand the digitization of assets, and on the other hand the change in business models. The proposed framework leads to the identification of four quadrants: scenarios which envision both the digitization of assets and business model changes and scenarios which do not foresee neither of these two changes. These four main development scenarios were completed and analyzed in the light of the conducted interviews and of the quantitative and qualitative data gathered through the Delphi survey. Each quadrant was given a label: Internal Processes, Flow-less Coopetition, Suppliers Potential and Investment Opportunities. When discussing the quadrants, we try to highlight which of the three improvement areas previously identified (efficiency, security, and innovation) are exploited in the discussed scenario.

https://doi.org/10.1371/journal.pone.0258995.t006

To derive relevant insights from the framework, it is useful to start from the bottom left quadrant, Internal Processes. This name was chosen to highlight the absence of any particular evolution for the company at a strategic level through the blockchain adoption. In this case, it is conceivable to use the technology to incrementally improve firms’ operation performances. Blockchain’s main benefits are to increase traceability of transactions and guarantee their immutability. All these characteristics adopted on today’s processes will result in an automation of routine business functions, such as settlements and reconciliation, customs clearance, heavy payments, invoicing, and documentation, boosting operational efficiency and cost performance. In this scenario, security and efficiency will see a consistent improvement.

The top-left scenario shows instead a different perspective, by considering a broader adoption of blockchain that generates new cooperative business models among different stakeholders, potentially even among competitors. This is why it is called Flow-Less Coopetition. In this case, the benefits of blockchain will help at generating a more democratic ecosystem in terms of information. Those actors that base their business models on information asymmetry, having access to key information before others, will need to revisit their business models if they want to stay competitive. It is of interest to notice how big financial institutions, traditionally competing, are now exploring potential collaboration models in the light of this new technology (e.g. JP Morgan Chase, Morgan Stanley). This quadrant envisages an advance in all three blockchain-enabled dimensions: efficiency, security, and innovation.

The bottom-right scenario, called Suppliers Potential, highlights how, thanks to the digitization that blockchain allows, many actors could jump in the market providing solutions to those companies that would like to benefit from the advantages of digitizing their assets, but are lacking means and competences to internally develop them. Those companies would rather outsource the development of blockchain-based solutions. For this reason, the potential for the creation of a remunerative B2B market exists. Even though there are already protocols that are leaders in the market (Hyperledger Fabric and Ethereum), new solutions with different configurations will likely be needed to support different industries and use case solutions. As for the first scenario, also in this context efficiency and security will be mainly affected.

Finally, the last scenario (Investment Opportunities) focuses on the combination between the complete digitization of the assets of a company and the new business models that this major change could generate. As already mentioned in previous paragraphs, industries are experimenting many ways to facilitate the access to capital. Since the explosion of ICOs in 2017, new and easier ways to access capital have become possible and achievable. However, due to their unregulated nature, ICOs still present numerous potential threats (Projection 14 did not reach consensus). For this reason, other solutions, such as STOs (Security Token Offerings), are on the way of being tested. Bringing a higher degree of freedom to investments will allow companies to receive funds from diverse and non-traditional investors, and it will also boost investments by private individuals into early-stage companies. Efficiency and innovation will be at the core of this last scenario.

5 Conclusions

In this paper, we studied different blockchain-based projections and we assessed their likelihood and impact thanks to the participation of a pool of experts. We built our findings around three dimensions (efficiency, security, and innovation) and we derived four scenarios based on experts’ shared vision. Being the current literature widely fragmented, we believe this research represents a useful starting for conceptualizing blockchain potential and implications. While many research papers focus on blockchain specific applications or general reviews of the state of the art, we try to propose a unifying framework building on different typologies of insights and analyses. We merged quantitative observations derived from standard statistics with qualitative insights obtained directly from experts’ opinions.

Overall, we believe our research can constitute a useful tool for many practitioners involved in the innovation ecosystem and for managers of small, medium and large enterprises to look at future possible scenarios in a more rational and systematic way. From one side, a company’s management can use these forecasts as a starting point for the implementation of new strategies. As previously highlighted, blockchain offers endless possibilities. However, the ability to focus on activities and projects with a positive return on investment will be crucial. Firstly, managers will face the choice between insourcing or outsourcing the technological development of the platform. While the former choice ensures higher flexibility, it also generates high development and maintenance costs. Companies which will identify blockchain as their core service will be entitled to adopt this first strategy, while the majority of the enterprises will probably gain better competitive advantages adopting Blockchain as a Service (BaaS) solution. This latter approach will boost companies’ performances, by enhancing new service offerings as well as a new level of operational efficiency, without carrying the burden and costs of technological complexity.

As mentioned, we believe this research provides useful insights for policy makers as well. The adoption of blockchain represents a tremendous technological change bringing along interesting and tangible opportunities. However, different threats can be foreseen. Central authorities do not only solve the problem of trust in certifying value transactions. They also provide essential supervision on the process itself, for example ensuring that information asymmetry is kept at reasonable levels between parties engaging in any sort of contracts, especially in the financial world. Letting people directly exchange value between themselves or allowing companies to easily raise capitals can boost financial efficiency, but also provides room for frauds and ambiguous behaviours. Today, companies which are interested in raising capitals both through innovative tools such as crowdfunding or through traditional entities such as public financial markets, have the duty to disclose relevant information and usually go through a deep process of due diligence. Regulators should ensure the same level of control on companies that will raise money through Initial Coin Offerings or other sort of blockchain-enabled offerings. We believe that the first step towards a fair regulation of this newly born technology is the understanding of its foreseeable impact on the society in the near future. This work aims to be a precious enabler in this direction. As highlighted in the body of this research, it appears fundamental for policy makers, regulators and government to deeply understand the potential upsides and threats of this new technology, and to correctly navigate the different possible blockchain-enabled scenarios. The successful cooperation between companies’ management and regulators could enable significant productivity shifts in the economic tissue of many countries. Failing in efficiently grasping and enhancing these new paradigms from a regulatory perspective could result into a heavy deficit for the competitive edge and productivity of the industrial sectors of the governments’ respective countries, potentially leading to macroeconomic differentials in productivity.

To conclude, this research could be a useful reference for orienting into this complex and dynamic environment, reducing the perceived uncertainty associated to such a new technology. Thanks to the experts’ advice, it is now possible to have a clearer picture of the evolution of blockchain technologies and of the opportunities and threats that the technology will generate. Certain limitations and characteristics of this study must be considered to correctly and effectively take advantage of its results. The main objective of this work was to examine the most disrupting aspects that are likely to occur in Europe by 2030, with a particular focus on how the technology will facilitate financing, reduce costs, increase transparency and, in general, influence firms’ business models. From this point of view, the objectives and assumptions presented at the beginning of this paper can be considered as fully achieved, but further works exploring other industries and geographies are required to get an organic understanding of the new enhanced paradigms.

Our research only paves the way for a better understanding of what a blockchain-based future will look like, as the differences between industries are too large to be analyzed in a single work. Organizations and businesses in the financial world are consistently changing, but it will be necessary also for companies belonging to different sectors to completely rethink their core activities. From this perspective, we believe further works are needed in these directions. We hope researchers will use and explode our framework to further characterize and meticulously describe the new possible paradigms around the multiple dimensions examined in this work.

Supporting information

https://doi.org/10.1371/journal.pone.0258995.s001

• View Article
• Google Scholar
• 9. Dujak D, Sajter D. Blockchain applications in supply chain. In SMART supply network 2019 (pp. 21–46). Springer, Cham.
• PubMed/NCBI
• 15. Firat AK, Woon WL, Madnick S. Technological forecasting–A review. Composite Information Systems Laboratory (CISL), Massachusetts Institute of Technology. 2008 Sep:20.
• 18. Narayanan A, Bonneau J, Felten E, Miller A, Goldfeder S. Bitcoin and cryptocurrency technologies: a comprehensive introduction. Princeton University Press; 2016 Jul 19.
• 28. Jagtiani J, John K. Fintech: the impact on consumers and regulatory responses.
• 35. Catalini C, Gans JS. Initial coin offerings and the value of crypto tokens. National Bureau of Economic Research; 2018 Mar 16.
• 45. Porter AL, Cunningham SW, Banks J, Roper AT, Mason TW, Rossini FA. Forecasting and management of technology. John Wiley & Sons; 2011 Jun 9.
• 48. Adler M, Ziglio E. Gazing into the oracle: The Delphi method and its application to social policy and public health. Jessica Kingsley Publishers; 1996.
• 50. Linstone HA, Turoff M, editors. The delphi method. Reading, MA: Addison-Wesley; 1975 Dec.

Blockchain in accounting research: current trends and emerging topics

Accounting, Auditing & Accountability Journal

ISSN : 0951-3574

Article publication date: 19 October 2021

Issue publication date: 22 August 2022

This paper provides a structured literature review of blockchain in accounting. The authors identify current trends, analyse and critique the key topics of research and discuss the future of this nascent field of inquiry.

Design/methodology/approach

This study’s analysis combined a structured literature review with citation analysis, topic modelling using a machine learning approach and a manual review of selected articles. The corpus comprised 153 academic papers from two ranked journal lists, the Association of Business Schools (ABS) and the Australian Business Deans Council (ABDC), and from the Social Science Research Network (SSRN). From this, the authors analysed and critiqued the current and future research trends in the four most predominant topics of research in blockchain for accounting.

Blockchain is not yet a mainstream accounting topic, and most of the current literature is normative. The four most commonly discussed areas of blockchain include the changing role of accountants; new challenges for auditors; opportunities and challenges of blockchain technology application; and the regulation of cryptoassets. While blockchain will likely be disruptive to accounting and auditing, there will still be a need for these roles. With the sheer volume of information that blockchain records, both professions may shift out of the back-office toward higher-profile advisory roles where accountants try to align competitive intelligence with business strategy, and auditors are called on ex ante to verify transactions and even whole ecosystems.

Research limitations/implications

The authors identify several challenges that will need to be examined in future research. Challenges include skilling up for a new paradigm, the logistical issues associated with managing and monitoring multiple parties all contributing to various public and private blockchains, and the pressing need for legal frameworks to regulate cryptoassets.

Practical implications

The possibilities that blockchain brings to information disclosure, fraud detection and overcoming the threat of shadow dealings in developing countries all contribute to the importance of further investigation into blockchain in accounting.

Originality/value

The authors’ structured literature review uniquely identifies critical research topics for developing future research directions related to blockchain in accounting.

• Literature review
• Machine-learning approach
• Future trends

Garanina, T. , Ranta, M. and Dumay, J. (2022), "Blockchain in accounting research: current trends and emerging topics", Accounting, Auditing & Accountability Journal , Vol. 35 No. 7, pp. 1507-1533. https://doi.org/10.1108/AAAJ-10-2020-4991

Emerald Publishing Limited

Copyright © 2021, Tatiana Garanina, Mikko Ranta and John Dumay

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

Blockchain is a technology for storing and verifying transactional records that works by adding “blocks” of data to a ledger, called the blockchain, that is maintained across a network of peer-to-peer computers ( Coyne and McMickle, 2017 ). It is a potentially disruptive technology that has begun to have dramatic impacts on the business models and market structures of many industries ( Casey and Vigna, 2018 ), including accounting ( Bonsón and Bednárová, 2019 ; Deloitte, 2016 ). However, the wealth of information produced about blockchain can make it challenging for researchers to stay up-to-date with the latest developments ( Cai et al. , 2019 ; Linnenluecke et al. , 2020 ). In these circumstances, the role of a structured literature review (SLR) of emerging research of blockchain in accounting should be a helpful tool ( Cai et al. , 2019 ; Moro et al. , 2015 ).

There are published literature reviews on how blockchain might be applied in a wide variety of academic disciplines, including business and management ( Xu et al. , 2019 ), supply chains ( Wang et al. , 2019 ; Gurtu and Johny, 2019 ), FinTech ( Cai, 2018 ; Rabbani et al. , 2020 ), the Internet of things ( Conoscenti et al. , 2016 ), and even cities ( Shen and Pena-Mora, 2018 ) but there has only been one for accounting and it was limited to 16 articles and 20 industry reports/websites ( Schmitz and Leoni, 2019 ). Other authors have also proposed different ways of applying blockchain technology in accounting and auditing (e.g. Yu et al. , 2018 ; Kokina et al. , 2017 ; Faccia and Mosteanu, 2019 ; Bonsón and Bednárová, 2019 ), without offering a comprehensive overview. Similarly, Bonsón and Bednárová (2019 , p. 737) conclude that “blockchain is an under-explored phenomenon, [and] future research is necessary to obtain a full understanding of this emerging technology and its implications for the accounting and auditing sphere”.

What are the current major research trends and topics related to blockchain for accounting?

What is the focus and critique of the key research topics?

What are the future research trends related to blockchain in accounting?

The studies collected for the review were drawn from accounting journals indexed by the Association of Business Schools (ABS), the Australian Business Deans Council (ABDC) and the Social Science Research Network (SSRN). To help analyse the corpus, we enlist the support of machine learning as found in other studies ( Cai et al. , 2019 ; El-Haj et al. , 2019 ; Black et al. , 2020 ; Bentley et al. , 2018 ). From this, we contribute and provide a comprehensive picture and critique of the literature on blockchain in accounting. This includes an analysis of impact; an examination of the four most widely-examined topics, being the changing role of accountants, new challenges for auditors, the opportunities and challenges of blockchain technology application and the regulation of cryptoassets; and a discussion on areas for future research. Identifying emerging topics in the field is an important element in generating insights for future research ( Small et al. , 2014 ) and leading research innovations ( Cozzens et al. , 2010 ). Understanding what we have learnt and how blockchain technology is impacting accounting is of benefit to everyone connected to this area. It may also help to guide future research in this exciting area.

The remainder of the paper is as follows. In Section 2 , we discuss the concept of blockchain as an accounting technology. Section 3 outlines the methodology used for the review, followed by the results in Section 4 . The most representative articles are analysed in Section 5 , with future research directions discussed in Section 6 . Section 7 concludes the paper with the implications of this research for theory, practice and policy, along with the limitations of the study.

2. Blockchain in accounting

The main advantage of blockchain technology is that once a transaction is approved by the nodes in the network, it cannot be reversed or re-sequenced. The inability to modify a transaction is essential for the blockchain's integrity and ensures that all parties have accurate and identical records. Because blockchain is a distributed system, all changes to a ledger are transparent to all the members of a network.

Hence, if transparency is key, implementing blockchain may help to enhance a company's competitive advantage ( Deloitte, 2019 ), and it should certainly help to cultivate trust between market participants ( Yu et al. , 2018 ). In blockchain, the transaction verification process is not managed centrally. Rather, it involves all the computers in the network, so blockchain does not suffer from point of failure events. Nor can individuals collude to override controls or illicitly change or delete official accounting records ( Wang and Kogan, 2018 ). Companies that incorporate blockchain into their accounting systems therefore may reduce their risk of fraud ( Dai et al. , 2017 ). Using blockchain might also mean more transactions can be automated, less data are lost, transactions can be tracked better and users' needs throughout the process can be detected more easily ( Fullana and Ruiz, 2021 ; Bonsón and Bednárová, 2019 ). However, the primary and most valuable difference between traditional databases and blockchain is its novel solution to control whereby transactions cannot be deleted or changed ( Coyne and McMickle, 2017 ; Dai et al. , 2017 ).

Even though, for most industries, blockchain is still a new and not yet well-established technology, the World Economic Forum estimates that, by 2025, at least 10% of global gross domestic product (GDP) will rely on blockchains. And, by 2030, blockchains will have created $3.1tn in business value ( Panetta, 2018 ). It should therefore be unsurprising to consider that this revolution will start to change the nature of accounting and, in turn, the work of its practitioners and theorists (e.g. Yermack, 2017 ; Schmitz and Leoni, 2019 ; Yu et al. , 2018 ).

As such, a literature review on the status of blockchain in accounting is both topical and timely. The insights provided into this emerging technology will have implications for the accounting ecosystem–some beneficial, others challenging. Hopefully, this SLR will serve as a helpful baseline for practitioners, professionals and academics as we navigate the next potential revolution in accounting information systems.

3. Methodology

Massaro et al. (2016 , p. 2) characterise an SLR as “a method for studying a corpus of scholarly literature, to develop insights, critical reflections, future research paths and research questions”. The review process is conducted in several steps.

3.1 The research questions

RQ1. What are the major trends and topics developing within the research related to blockchain in accounting?

RQ2. What is the focus and critique of the key identified research topics?

RQ3. What are the future research trends related to blockchain in accounting?

3.2 Defining a set of articles for further analysis

Phase 1. We first composed a list of all accounting journals from the 2018 Chartered Association of Business Schools rankings (the ABS rankings), which amounted to 87 journals. We did the same for the 2019 Australian Business Deans Council Journal Quality List (the ABDC rankings). This netted 157 journals.

Phase 2. After removing duplicate journals covered in both ranking systems, we were left with 149 journals. In these, we looked for relevant papers published in the period Jan 2008 till June of 2020. We started our search in 2008 as this was when Satoshi Nakamoto first mentioned blockchain in his paper ( Nakamoto, 2008 ). Using the EBSCO, Scopus and Web of Science databases, we searched for any article with the key words “blockchain” or “distributed ledger technology” in the title or abstract. From 2,335 documents, we identified 112 papers that matched our criteria for publication source.

Phase 3. Massaro et al. (2016) outline that when undertaking an SLR, researchers should broaden the boundaries if there is very little published research. They also warn that what is published may already be out of date because of the long lead times involved in publishing academic articles. Massaro et al. (2016) bring clarity to “broadening the boundaries”, arguing that researchers need to search for sources other than academic journals, which may provide valuable insights into emerging research fields. The other sources might include conferences and open-source publishing platforms that offer researchers greater opportunities to disseminate their research to practice ( Massaro et al. , 2015 ).

Since blockchain is just such an emerging topic in the accounting literature ( Schmitz and Leoni, 2019 ; Bonsón and Bednárová, 2019 ; Yu et al. , 2018 ), we decided to add papers not yet published in the accounting journals but uploaded to the SSRN. SSRN is the leading social science and humanities repository and online community that provides “tomorrow's research today” ( Gordon, 2016 ). With more than 950,000 papers from over half a million authors in the e-library, SSRN offers an extensive pool of research ideas that can be tracked before publication to detect emerging research topics and current trends. These papers added an important contribution to our literature review. Here, we searched for “accounting” AND “blockchain” or “accounting AND distributed ledger” over the same period and found 68 papers, some of which overlapped with papers already retrieved. These were excluded, plus we also excluded any of the papers that had subsequently been published in a non-accounting journal or an accounting journal not ranked by ABS or ABDC. This left 41 additional articles to add to the corpus. Thus, our final sample comprised 153 papers on blockchain for accounting.

Portable Document Format  (PDF) versions of each of the articles were downloaded and stored in a Mendeley database with full referencing details. The sources and number of papers from each source are given in Table 1 .

3.3 Methods of analysis: Latent Dirichlet Allocation combined with manual analysis

In machine learning, there are many different text mining techniques, each designed to suit different types of data and different end purposes (see Wanner et al. , 2014 for a comprehensive review). We used a Latent Dirichlet Allocation (LDA) model, which is well-suited to providing a systematic and non-biased method of investigating a body of literature ( Cai et al. , 2019 ; El-Haj et al. , 2019 ; Black et al. , 2020 ; Bentley et al. , 2018 ; Fligstein et al. , 2017 ). El-Haj et al. (2019 , p. 266) explain that LDA leads to “wider generalizability, greater objectivity, improved replicability, enhanced statistical power, and scope for identifying ‘hidden’ linguistic features”. Research shows LDA to be a relevant and useful tool for working with both big and small literature corpora (e.g. Li, 2010 ; Asmussen and Møller, 2019 ; El-Haj et al. , 2019 ). Asmussen and Møller (2019 , p. 16) highlight that applying LDA to even small sets of papers provides “greater reliability than competing exploratory review methods, as the code can be rerun on the same papers, which will provide identical results”. For these reasons and more, the LDA method is currently one of the most commonly employed topic identification methods that does not simply rely on a static word frequency measure ( Blei et al. , 2003 ). Moreover, El-Haj et al. (2019 , p. 292) recommend employing machine learning methods and high-quality manual analysis in conjunction as they “represent complementary approaches to analyzing financial discourse”. We followed this advice, applying a hybrid approach that comprised LDA analysis, citation analysis and a manual review.

LDA allows us to explore latent relationships between terms and topics in a sample, identify the most representative articles for each topic and identify the trends within the topics. Using LDA helps us capture the idea of a document being composed of a (predetermined) number of topics that represent a probability distribution over a vocabulary. The number of topics is optimised using grid-search and coherence of topics ( Röder et al. , 2015 ). The model also supplies a list of articles that most strongly “belong” to each topic.

The text mining procedure is straightforward. In a Python environment ( www.python.org ), the articles are first converted from PDF documents into text files. The text is then converted into lower case, and all characters other than letters are removed. Next, stop words, such as the , and , but , if , or , are removed, and the remaining words are lemmatised into their dictionary word. Additionally, all words other than nouns are discarded. Finally, the documents are turned into a bag-of-words format and fed into the LDA model.

The results showed that the four topics with the highest marginal distribution accounted for more than half of the overall content of the sample. To test the validity and reliability of this result, we applied several other types of analysis suggested by researchers working with literature reviews. For example, Dumay and Cai (2014) and Jones and Alam (2019) argue that citation impact factors are increasingly important because they identify the most influential articles. Highly cited articles represent a “corpus of scholarly literature” that can help “develop insights, critical reflections, future research paths and research questions” ( Massaro et al. , 2016 , p. 767). To conduct a citation analysis, we use citation counts based on Google Scholar data, based on queries employing Harzing's Publish or Perish software as of 5 March 2021. This step also helped us validate that the papers and topics identified by the LDA analysis were among the most cited.

Although the LDA method helped us to identify past and current trends in the literature, Cai et al. (2019 , p. 710) contend that “the human researcher is potentially better equipped to evaluate future trends in the literature”. Hence, we also manually reviewed the 15 articles identified in the LDA analysis as the most representative of each topic. This review affirmed the results of the LDA analysis and gave us the opportunity to offer a critique and gain more insights while identifying future research directions.

This section provides answers to RQ1 : What are the current research trends and topics in blockchain for accounting?

Figure 1 demonstrates that the volume of articles on the topic is increasing annually. The first articles began to appear in 2015 and, by 2019, 4 articles had increased to 40 papers, with 35 already published just in the first half of 2020.

Of the top-ranked journals–either 4-star ABS or A* ABDC–only two have each published one paper on blockchain. This is a clear indication that the phenomenon has not yet fallen into mainstream research. Given its relatively recent appearance in the literature, this is not surprising. Additionally, most of the articles that have been published are normative in approach and look at the future applications of blockchain in accounting. From this, we can assume that, in future, more cases of blockchain applications in accounting practice will be researched. Once the literati start to read of blockchain having a real influence on the profession, we expect the number of papers published in the leading journals will increase.

4.1 Results of LDA analysis

The LDA analysis unearthed ten topics, which we needed to find appropriate names for. This we did in a two-step procedure. First, we looked at the terms listed against each topic, then we read the most representative articles for each group identified by the model. One author then developed a descriptive title, which was reviewed and perhaps modified before being approved by the remaining authors. The final topic names are listed in Table 2 , along with the 20 most important words for each topic and the marginal distribution of each topic.

As shown in Table 2 , the most widely analysed topics are: the changing role of accountants; new challenges for auditors; the opportunities and challenges of applying blockchain technology and the regulation of cryptoassets. These account for more than half of the papers. No other topic amounts to more than 10% of papers on its own. Figure 2 shows the representation of the different topics from 2016 to 2020. Since there were so few papers in 2015, we did not include this year in the chart.

Two of the most widely discussed topics–“the changing role of accountants” and “the new challenges for auditors”–only seem to be getting more popular. These two subjects account for the highest proportion of the articles. Although “new skills for teams” began to attract attention in 2019, papers on this topic still only account for a small portion of the sample. Interesting, even over such a short period, interest in some topics is already waning, e.g. “FinTech in banking”, “cryptocurrencies and cryptoassets”, and “blockchain and taxation”. With this in mind, and given the overwhelming interest in just a handful of topics, we focused the rest of our analysis on the top four topics.

4.2 Article impact

As mentioned in the methodology, we checked the validity and reliability of the topic results using citation analysis ( Dumay et al. , 2018 ). Table 3 shows the total citation counts for the top 10 articles as listed in Google Scholar citations (5 March 2021).

As shown, all but one of the ten most-cited articles were published in ranked accounting journals. In fact, three were published in the Journal of Emerging Technologies in Accounting. The one exception was found on SSRN. Additionally, the topics cited match the topics revealed by the LDA analysis, particularly new challenges for auditors, opportunities and challenges of blockchain applications, and the regulation of cryptoassets.

Dumay and Cai (2014 , p. 270) note that “One problem with determining the impact from citations alone is that older articles can accumulate more citations”. To overcome this problem and to identify emerging articles, in Table 4 , we also calculated the citations per year (CPY). Six articles are common to both rankings: Kim and Laskowski (2018) , Fanning and Centers (2016) , O'Leary (2017) , La Torre et al. (2018) , Kokina et al. (2017) , Issa et al. (2016) . This offers clear support for the results of the LDA analysis. Further, two of the articles were published in 2019 and are already in the top 10, which is a sign of just how strong the interest in blockchain technology is.

The results of Table 4 allow us to confirm our choice of the topics for further analysis. The top 10 papers with the highest citations per year belong to one of the four research topics that have the marginal distribution over 10% represented in Table 2 and account for more than a half of the overall distribution.

5. Key research topics: focus and critique

In this section, we answer RQ2 : What is the focus and critique of the key identified research topics?

While the LDA analysis revealed ten topics, much of the literature is focussed on four of these: the changing role of accountants, new challenges for auditors, opportunities and challenges of blockchain technology application and the regulation of cryptoassets. In the next sections, we analyse and critique these subject areas in more detail, paying attention to the papers that the model deemed to be strongly representative of each topic.

5.1 The changing role of accountants

Each of the papers on this topic discusses ideas about how the role of accountants and accounting treatments would change if/when blockchain becomes a mainstream technology. For example, several authors discuss the advantages of using blockchain to record transactions on a real-time basis ( Yermack, 2017 ; Dai and Vasarhelyi, 2017 ). Routine accounting data would be recorded permanently with a timestamp, preventing it from being altered ex-post, which Alles (2018) argues would further ensure the reliability of current accounting information systems. Real-time accounting would also reduce the potential opportunities for earnings management ( Yermack, 2017 ). Additionally, using blockchain means anyone can review all transactions, even those that may be suspicious or related to conflicts of interest. Irreversible transactions also mean accountants could not backdate sales or report depreciation expenses in future periods when they should be expensed immediately. As a tool for accuracy and transparency, blockchain places pressure on accountants to justify their accounting choices. It also creates a closer link between accounting and a company's responsibilities to its stakeholders and makes it more challenging for financially-distressed companies to hide their situation ( Smith, 2017 ).

Anyone could aggregate the firm's transactions into the form of an income statement and balance sheet at any time, and they would no longer need to rely on quarterly financial statements prepared by the firm.

We agree that blockchain will impact how accounting information is recorded, but we do not expect that accounting functions will disappear. Rather, accountants will likely retain some old functions, either as-is or modified to suit the new paradigm, and find they have an entirely new set of responsibilities, some of which will require them to develop new skills. For example, well-developed IT competencies may become a prerequisite for the accounting profession, at least in the interim period where firms are prepared to face the changes brought about by integrating blockchain ( Uwizeyemungu et al. , 2020 ; McGuigan and Ghio, 2019 ). That said, we do not think that such changes will happen overnight. It will take time before companies implement blockchain as a ‘foundational technology’, and any disruptions to the profession will take place over years ( Iansiti and Lakhani, 2017 , p. 4).

What could be an even more profound transformation of the profession is how the work of accountants might no longer involve only recording transactions. In future, accountants may need to provide professional judgements during the accounting process ( McGuigan and Ghio, 2019 ; Dai and Vasarhelyi, 2017 ). Even if blockchain takes over the recording and storing of basic accounting transactions, there will be a need to decide on the choice of the most appropriate amortisation and depreciation methods, the length of the useful life of property, plant and equipment, the accounting policies regarding accounting for inventories and fair-value accounting. Moreover, with an increase in the number of cryptoassets and initial coin offerings (ICOs) accountants may also need to develop their skills as advisors and consultants on how to report these kinds of assets and transactions. Further, if blockchain is implemented on a broad scale, accountants will not only have more information for planning and control, they may be required to synthesise it. This, too, will change the role of accountants, particularly management accountants. No longer relegated to the back office, accountants would likely take a much more prominent position as agents of intelligence, advising, communicating and attempting to closely link their firm's activities to strategic decision-making.

Blockchain may also lead to more disclosures of non-financial information, such as that related to sustainability and corporate social responsibility. The transparency of blockchain might prompt companies to do more explaining. They may wish to quantify and make visible “feel-good” information as a counterpart to the financial ( Smith, 2017 ). Additionally, blockchain provides opportunities to collect qualitative social and environmental data, which will continue to require assurance in the future. La Torre et al. (2018) argue that blockchain will generate an automatic assurance system for non-financial information that could substantially modify the current assurance paradigm. Therefore, blockchain may help accountants move away “from traditional accounting assumptions, such as monetary unit[s], economic entit[ies] and time periods, leading organisations more towards holistic views of their relations with the society” ( McGuigan and Ghio, 2019 , p. 800).

Lev and Gu (2016) argue that blockchain may reduce information asymmetry and lead to more effective decision-making. They put forward that the relevance of information disclosed only in financial statements is diminishing because of the growing importance of non-financial information and that blockchain's ability to store quantified non-financial information may see accountants working more closely with other decision-making bodies.

The disruptive potential of accounting technologies can only be fully realised with a similarly profound revolution in accounting thinking. Without an accompanying “mental revolution”, new technologies may result in incremental as opposed to step change.

5.2 New challenges for auditors

Blockchain may also disrupt the auditing profession. With the ability to autonomously execute some audit procedures based on blockchain, smart contracts will provide stakeholders with already partly verified information ( Rozario and Vasarhelyi, 2018 ). La Torre et al. (2018) claim that participants in the accounting ecosystem may act as auditors themselves. Accounting information may be verified by different actors thanks to the assurance abilities of blockchain and because companies can continuously share information. Moreover, there is the possibility to automate some external auditing functions over the blockchain to improve audit quality and narrow the expectation gap between auditors, financial statement users and regulatory bodies ( Rozario and Vasarhelyi, 2018 ). Some authors call for the appearance of a new brand of auditor that can offer attestation services for independent evaluations of blockchain controls ( Canelón et al. , 2019 ; Sheldon, 2019 ).

However, some researchers are not convinced that blockchain will dramatically impact the auditing profession. Rather, they suggest that auditing will take on new features and become more complicated ( Dai et al. , 2019 ; Issa et al. , 2016 ). Distributed public recording on the blockchain will allow real-time audits in many locations and organisations simultaneously ( Issa et al. , 2016 ). These authors argue that auditors will need improved skills to audit the data not only for one company but also for the whole accounting ecosystem.

… continuously collect data from the real world, create a variety of intelligent modules for real-time auditing, monitoring, fraud detection, etc., and thereby improve the effectiveness and efficiency of assurance services.

Blockchain will require auditors to gain new IT skills and technical knowledge as without an improved understanding of blockchain, they will not be able “to design efficient and effective audit processes, to collect accurate audit evidence, and to review the system for potential risks and frauds” ( Dai et al. , 2019 , p. 38). Of course, for blockchain technology to enable continuous auditing and for it to give auditors a better understanding of their clients' businesses, companies will need to record all transactions on the blockchain ( Schmitz and Leoni, 2019 ). After all, “real-time auditing” can only be delivered to the degree that transactions are recorded on the blockchain.

Auditors should be concerned about the risks of privacy breaches deriving not only from both external unauthorised access but also from accessing and using certain corporate and external data to perform audit activities; the latter being a task that needs to engage principles that go beyond legal prohibitions.

Blockchains do not provide a guarantee for transactions taking place in the real world. Even if they are recorded onto blockchains, transactions may still be fraudulent, illegal or unauthorised. Hence, given the need for auditors to detect and investigate transaction errors or fraud, the argument of auditors becoming obsolescent is not evident.

Essential roles for auditors in the future will be assuring the reliability, credibility and authorisation process of blockchain transactions.

Implementing blockchain may benefit most accountants and auditors, but it may be negatively perceived by those who work in the black economy, those who are keen on earnings management, and those who need to manipulate the appearance of illicit transactions. Therefore, we assume that automating data collection and storage using blockchain will not mean the auditing profession disappears. Rather, we see it evolving into a new role within companies and the ecosystem of blockchain accounting.

5.3 Opportunities and challenges of blockchain technology application

Papers on this topic are mostly written from the perspective of a company implementing blockchain. Opportunities range from improved efficiency, transparency and trust to the high potential of new business models and ecosystems that evolve due to blockchain. Challenges include potential risks related to blockchain implementation, the influence of context and a high demand for energy consumption.

Because blockchain eliminates the need to enter and reconcile information in multiple databases, efficiency gains are a key strength. Blockchain also saves time by increasing the speed of transactions, reducing human error and minimising fraud ( Kokina et al. , 2017 ; O'Leary, 2017 ). The use of smart contracts may also improve processes in a range of industries. Smart contracts on the blockchain execute when certain conditions are met without the need for trusted intermediaries to verify the fact ( Coyne and McMickle, 2017 ; Kokina et al. , 2017 ). There is already evidence to show how blockchain may reduce costs in the finance industry (e.g. Fanning and Centers, 2016 ; Kokina et al. , 2017 ).

One of the challenges for implementing blockchain is context ( Stratopoulos and Calderon, 2018 ). It is unlikely that small firms would want to make their transactions publicly available or that they would benefit from blockchain accounting as much as big companies. Distributed ledgers may not be attractive or even needed by every company, so there is a real need to ascertain exactly what the up and downsides of implementing blockchain are. As O'Leary (2019) observes, the opportunities for using blockchain may be limited by the desire and ability of all agents in the ecosystem to implement it. For example, some companies may wish to use a private blockchain, but we do not yet know how to accommodate multiple private blockchains with different levels of secrecy and different kinds of trading partners, some of whom may be members of a public blockchain ( O'Leary, 2019 ; Kim and Laskowski, 2018 ).

It is also important to understand all the advantages and disadvantages of joining a public or a private blockchain ( O'Leary, 2017 ). There are many different configurations of blockchain, e.g. peer-to-peer and public, cloud-based, private and these all need to be analysed before they can be soundly implemented in different settings. Further, those investigations must include analyses at the accounting, auditing and supply chain levels. For example, O'Leary (2017) argues that public blockchains are not the best approach to capturing accounting or supply chain transactions. Instead, he believes private and cloud-based blockchain configurations will dominate the corporate landscape. In a private blockchain, only a preselected number of nodes are authorised to use the ledger. Hence, not everyone has access to all company's data. Yet many researchers speak positively about how blockchain technology will mean provenance in the supply chain that is much more traceable ( Kim and Laskowski, 2018 ). In our opinion, it will be important for all the agents in the ecosystem to understand how blockchain provides similar benefits. For example, due to the potential risks of disclosing information, we assume that blockchain will have a more restrictive effect on business entities than non-profit organisations, because non-profits tend not to hold as many commercial secrets.

Moreover, Kokina et al. (2017) note that the scalability of blockchain is an issue from a technical perspective, as blockchain is computationally intensive and requires a lot of energy. This raises sustainability questions and may not be an issue that gets resolved until renewable energy accounts for most of our energy production ( Coyne and McMickle, 2017 ). Three further risks are often raised, each surrounding changing business processes ( Canelón et al. , 2019 ; Coyne and McMickle, 2017 ; Kokina et al. , 2017 ). The first relates to the centralisation of computing power, also called the “51% attack risk”, which can happen when most of the computing power in a blockchain's network is centralised. In this case, whoever controls that power can, with impunity, discard a valid link in the chain or substitute an invalid block for a valid one. The second risk is transaction malleability, which occurs when an attacker copies a transaction and modifies it to receive tokens (payment) then claims that no tokens were ever received. The third risk relates to flawed smart contracts that can hide malicious code or another contract with a weakness. This risk highlights the need for independent external auditors to approve transactions before the contract enters the blockchain. In short, the ability of blockchain to store records makes it a target for potential cyberattacks. Therefore, to ensure the security of information in a blockchain, there is a need to implement internal and cybersecurity controls that consider privacy preservation issues ( Chohan, 2017 ; Coyne and McMickle, 2017 ; O'Leary, 2017 ).

To gain real efficiencies in the use of blockchain or any technology, there is a need to reengineer, rather than just automate, existing processes. Unfortunately, many of the proposals for the use of blockchain are aimed at automating existing processes, typically in an approach to leverage the immutability and digitisation of paper, but generally do not propose or use changes in the processes.

Unless existing processes and systems are truly scrutinised for their potential to benefit from blockchain technology, the full range of opportunities that blockchain presents will not be realised. Blockchain will only become a “game-changer” if all parties involved in the accounting ecosystem are open to its potential.

5.4 Regulation of cryptoassets

The papers devoted to this topic analyse a variety of questions related to the regulation of cryptoassets (also called tokens), including cryptocurrencies and ICOs (e.g. Gurrea-Martínez and Remolina, 2018 ; Wiśniewska, 2018 ). These assets are not addressed by any accounting standards, that leads to challenges in their classification and measurement and reflects the lack of economic characteristics for a “standard” intangible asset ( Procházka, 2018 ) or a financial asset ( Smith et al. , 2019 ). There are several regulatory issues that need to be solved: classification of cryptoassets in accounting; the kinds of insolvency that affect buyers and sellers of tokens; and the regulation of potential money laundering via blockchain ( Pimentel et al. , 2019 ; Zhang et al. , 2021 ). Moreover, with the increased competitiveness of the market, questions related to data protection and data safety on the blockchain become extremely important for further regulation ( Cai, 2018 ).

The uncertainty linked to valuing cryptoassets is affecting the development of proper regulations, as this issue affects the fundamental qualitative aspects of financial accounting, such as relevance and faithful representation. Moreover, as highlighted in the Conceptual Framework for Financial Reporting , the principles of prudence, neutrality and conservatism continue to pose challenges for properly presenting cryptoassets in financial statements ( FRC, 2018 ; The Interpretations Committee, 2019 ).

There is no commonly shared point of view among researchers on the best way to regulate cryptoassets. Some say that they fit in with the existing accounting standards, while others state there is a need to develop a new regulatory framework that will decrease the probability of fraud ( Auer, 2019 ; Pimentel et al. , 2019 ). For example, there is a high demand for developing regulations for ICOs, cryptoassets that do not offer investors concrete products or services but provide an opportunity for capital gains from reselling cryptocurrencies in the future ( Zhang et al. , 2021 ). In December 2017, SEC Chairman Jay Clayton stated that ICOs are vulnerable to fraud and manipulation because there is less investor protection than in the stock market ( Clayton, 2017 ). We think that as the tokenisation of securities would be a useful tool in capital markets in the future (as already reflected by their fast development in Asian markets) and because ICOs and crowdsourced platforms represent a legitimate means of exchange in ecosystems, the regulatory issues need to be resolved to make this instrument available to wider markets participants ( Gurrea-Martínez and Remolina, 2018 ; Zhang et al. , 2021 ; Sixt and Himmer, 2019 ).

Currently, regulators monitor the field of cryptoassets on a case-by-case basis, but not to the extent that investors, or would-be-investors, could determine with certainty how cryptoassets may be treated ( Smith et al. , 2019 ). Nor are all market participants eager to treat cryptoassets as a security due to their volatility, making it difficult to ascertain an appropriate value to record for income statement and balance sheet purposes ( Smith et al. , 2019 ; Tan and Low, 2019 ). Finally, it is worth noting that financial accounting is characterised by accounting prudence and conservatism, which can lead to differences between a company's market and book value ( Dumay and Guthrie, 2019 ). As cryptoassets are often characterised as a potential future economic benefit, their acquisition may lead to even greater discrepancies between the market and book values of companies, especially in markets with optimistic valuations of intangible assets.

Thus, the uncertainty on measuring cryptoassets leads to the problems of comparability, verifiability, timeliness and understandability in financial accounting ( IASB, 2018 , p. 6). Therefore, in line with Smith et al. (2019 , p. 166), we conclude that for now, “this innovative technology has the potential to change internal management systems …; however, lack of regulation and information makes investment planning for cryptoassets complex and forbidding”. The divergence of crypto classifications means that worldwide regulation and availability of information on cryptoassets will be the most important factors for their spread. As a result, we see the need for a proactive regulatory framework rather than merely reacting to questions regarding the regulation and accountability of cryptoassets.

6. Future research directions

This section answers RQ3 : What are the future research trends related to blockchain in accounting?

The following views regarding the future research trends were framed by the insights in the previous section and reviewing the most representative papers for each topic.

6.1 The changing role of accountants

As discussed in Section 5.1 , most papers on the changing role of accountants are normative. They talk mainly about various assumptions over how blockchain may influence accounting. One of the main changes frequently discussed is how blockchain will change the way accountants collect information. Given this, we think the future will result in more case studies and practically-oriented papers that empirically test blockchain's impact on accounting ( Alles, 2018 ). According to Zhang et al. (2017) , new business reporting models, such as triple-entry accounting, will demand investigations into how blockchain strengthens or alters functions like valuations and contracting. Further, the monitoring role of accountants in managing information for the benefit of stakeholders will need to be established ( Zhang et al. , 2017 ). However, Alles (2018) warns that there is a danger of the “empirical takeover” effect when papers become empirically driven. Thus, there is a need to establish a solid theoretical and conceptual background for how blockchain will disrupt accountancy.

The role of management in implementing blockchain is very important. According to Jarvenpaa and Ives (1991 , p. 205), “Few nostrums have been prescribed so religiously and ignored as regularly as top management support in the development and implementation of IT.” A high degree of support for specific IT innovations is needed to ensure companies hold fast to a long-term vision and optimally manage their resources to see it through. At the same time, these innovations can create a favourable organisational climate that can overcome barriers and resistance to change ( Clohessy and Acton, 2019 ). Future research might therefore investigate the structure of management bodies and the role of top management in blockchain implementation.

Prior research points to a growing trend in the topic of new skills for teams when implementing blockchain and using this technology in day-to-day work ( Changati and Kansal, 2019 ). Fang and Hope (2021) indicate that blockchain is more effectively implemented in teams comprising accountants, managers and experienced analysts as opposed to teams consisting only of highly experienced analysts. We expect that blockchain will involve more multi-tasked teams with diverse knowledge and skills to generate additional synergies. Therefore, future research may analyse the characteristics of teams and government bodies that work better together for the most efficient implementation and decision-making using blockchain.

6.2 New challenges for auditors

In the realm of auditing, future research could explore how different types of blockchain (public, private and permissioned) could be used in accounting and Audit 4.0 to improve the quality of the data collected ( Dai et al. , 2019 ). The dilemma of adopting blockchain in accounting and auditing is in finding the right trade-off between information confidentiality and transparency. The simultaneous protection of data privacy and maintenance of data accuracy is an important area for future research. Further, the ways of creating effective smart audit contracts and smart reporting contracts should also be studied with a special focus on executing traces and enforceability ( Schmitz and Leoni, 2019 ).

More extensive analysis is also needed on the auditing ecosystems based on blockchain ( Smith, 2020 ). For example, if a client is a part of several blockchains, any engagement to audit or attest that information must include an examination of all associated blockchains. In the case of supply chains, cross-border payments, and transfers of intellectual capital, the chains–be they digital or physical in nature–can include dozens, if not hundreds, of organisations. How to conduct an effective and successful audit of such systems should attract the attention of researchers.

Additionally, more real cases will need to be explored to see how technology might disrupt the auditing community ( Marrone and Hazelton, 2019 ). Researchers might also address data protection issues as well as the new skills and competencies needed to remain relevant and add value ( Moll and Yigitbasioglu, 2019 ). Some, like Siew et al. (2020) , argue that, while digitising the validation process will reduce errors, and the immutability of the blockchain will minimise the opportunity to commit fraud, blockchain accounting does not guarantee that financial reports will be true and fair; the processes still need to be tested and the various accounting judgements still need to be reviewed. Moreover, blockchain will not resolve questions over issues like reconciling accounting standards. Hence, accountants will still need to be involved in the process ( Cai, 2018 ). Thus, many of the benefits and challenges of blockchain for auditing still need to be analysed.

6.3 Opportunities and challenges of blockchain technology application

A more fundamental area of future research is the role of financial intermediaries and how their role might change. In the future, we expect to see competition and cooperation among traditional and new intermediaries, and research needs to explore these phenomena to provide guidance to all participants such as incumbents, new entries and regulators ( Cai, 2018 ). The influence of blockchain on risk management and companies' performance indicators is another promising area for future research as there is a need to identify how stakeholders' value creation may be affected by implementing blockchain ( Cai, 2018 ). It would also be worth examining whether the response of managers towards blockchain varies in different industries ( Cao et al. , 2018 ). Burragoni (2017) argues that implementing blockchain in the finance industry might help overcome the threat of a shadow economy, given the improved transparency and legitimacy on offer, but this is an assumption that needs further justification.

Analysing the role of blockchain in changing business models in different industries is sure to be a topic of great interest to researchers ( Johannessen, 2013 ). The efficiency of new business models in comparison to traditional ones may also bring new insights for academics and practitioners. Researchers should test new business models in a market and evaluate transaction efficiency and the degree of novelty in the transaction's content, structure, steering, resource use, network effects and value creation for stakeholders. Researchers can analyse the efficiency of blockchain implementation in different areas and focus on “the benefits of the first-mover advantage” ( Karajovic et al. , 2019 , p. 322). In the future, it will be important to monitor the progress of the implementation of blockchain in different types of organisations ( Gietzmann and Grossetti, 2019 ).

Researchers should analyse how blockchain ecosystems evolve and are applied ( Benjaafar et al. , 2018 ). Blockchain enables real-time, verifiable and transparent accounting, making it reasonable to assume that accounting information systems will become ecosystems. In a data ecosystem that progressively integrates a nearly infinite set of initially disconnected data, the ability to integrate coherently and apply software agents will be of high importance. With an almost infinite supply of new data, novel methods of measuring business performance will inevitably emerge ( Cho et al. , 2019 ). Understanding how blockchain distributes the power of transaction verification and how data are stored and managed to prevent any unauthorised data changes in ecosystems are also key questions in need of investigation.

The challenges of blockchain regarding sustainability and environmental issues should also be a focus in future research. On the one hand, a distributed carbon ledger system based on blockchain technology will not only strengthen the corporate accounting system for carbon asset management but also will fit within existing market-based emissions trading schemes ( Tang and Tang, 2019 ). Blockchain will help integrate national emission trading schemes and corporate carbon asset management into a single synthesised mechanism, making it possible to analyse the overall efficiency of carbon trading markets in some great amount of detail. On the other hand, Nyumbayire (2017) points to environmental sustainability as an issue, explaining that the algorithms that run blockchain require a great deal of electricity. Moreover, as the technology grows, the algorithms become more complicated, and more time and energy are required to validate transactions. We argue that in the future, researchers should investigate the sustainability and environmental issues related to blockchain in more detail.

6.4 Regulation of cryptoassets

To date, the growth of blockchain technology has not led to the building of a corresponding regulatory framework. Thus, there are many questions that need to be resolved surrounding the legal and accounting frameworks for accounting, recognising and valuing cryptoassets. Further, when these frameworks are developed, they will need to be analysed. Researchers will also likely want to determine whether the standard-setting bodies have developed credible reporting conventions over the financial implications of cryptocurrency transactions ( Raiborn and Sivitanides, 2015 ; Tan and Low, 2019 ). Future research could explore whether blockchain has or will have a positive effect on the timeliness of disclosures; how financial reporting standards welcome new types of assets; and how the uncertainty associated with cryptoassets can be overcome.

Academics, together with practitioners, should work on specifying how these regulatory dimensions need to be developed, what type of disclosures are relevant to cryptocurrencies and how disclosure costs may further impact market uncertainty ( Cao et al. , 2018 ). Clarifying the regulatory framework will probably also lead to more ICOs, as initiators will be better prepared and be able to respond to uncertainty in blockchain policy by increasing their voluntary disclosures ( Zhang et al. , 2021 ; Gurrea-Martínez and Remolina, 2018 ). Research on the efficiency and effectiveness of ICOs will be of high interest in the future.

How cryptoassets and cryptocurrencies should be taxed is also open to question ( Ram, 2018 ). Once clarified, researchers will be able to study the taxation policies applicable to this new class of assets in detail. One related research question for the future involves whether blockchain-based instant tax allocation helps to decrease the cost of tax compliance for companies or not ( Karajovic et al. , 2019 ). As the role of external contexts and legal frameworks is highly important to blockchain development ( Allen et al. , 2020 ; Stratopoulos and Calderon, 2018 ), researchers may study the differences in blockchain implementation in environments that are (and are not) “crypto-friendly”.

7. Conclusion

Our aim with this paper was to define the key topics and trends, past, present and future, that concern researchers in blockchain for accounting. Our analysis systematically identified these topics by analysing 153 relevant papers. By combining machine-learning methods with more traditional approaches, we were able to draw a holistic picture of the critical advances and trends in the corpus of literature. The results indicate that the most widely discussed topics are the changing role of accountants, new challenges for auditors, the opportunities and challenges of blockchain technology application, and the regulation of cryptoassets.

This paper provides a compact snapshot of the state of blockchain papers in accounting research. The trends and identified research directions may help predict future citation impact and informed our suggestions for future research. They may also help journal editors decide on calls for special issues as interest in this topic grows.

7.1 Implications for academics

Our analysis reveals that more than two-thirds of the papers under review were published in journals, while less than a third represent works in progress uploaded to SSRN. The top accounting journals from the ABS and ABDC rankings appear to be resistant to the blockchain field of research, as they have published only a few papers devoted to the technology. This could be because those journals are less friendly towards phenomenon-based research ( Von Krogh et al. , 2012 ) than fundamental research or that the publication process takes much longer, and we will see more papers in the upcoming years. Another reason could be that most existing articles are normative and are looking at the future applications of blockchain. We may assume that, in the future, when there will be more cases examining the actual application of blockchain in accounting practices and real examples of the influence of blockchain on the accounting and auditing field, the number of papers in the leading journals may increase. For now, we observe that, with the blockchain landscape changing daily, and ideas and research needing to reach the target audience faster than the traditional journal route allows, researchers are turning to SSRN to share their tentative findings ( Holub and Johnson, 2017 ). We also observe that Australian scholarship is now leading the blockchain research in accounting, as more papers were published in journals included in the ABDC ranking compared to the ABS ranking. Moreover, Australian journals such as the Australian Accounting Review and Meditari Accounting Research are among the top tiers of those who welcome such research.

It will be important to monitor the progress in the take-up of blockchain in the future ( Bonsón et al. , 2019 ; Gietzmann and Grossetti, 2019 ; Bonsón and Bednárová, 2019 ). More papers applying machine learning techniques will help to gather information from reports, and web crawlers will be able to discover new aspects of how blockchain technologies have been implemented in practice. Combined with manual analysis, these data will help to chart new paths forward for researchers.

7.2 Implications for accounting practice

Even though we anticipate that blockchain will influence accounting and auditing, we do not assume they will be totally replaced. Most expect that these professions will be augmented rather than fully automated, and the need for accountants and auditors will not disappear ( Agnew, 2016 ; Marrone and Hazelton, 2019 ). There will still be a need for professional judgement, and, further, issues such as reconciliation are almost impossible to perform at the current stage of blockchain's development. In line with McGuigan and Ghio (2019) , we argue that accountants will not only have to understand the data on blockchain, they will also have to interpret and explain the implications of this information to management and other decision-makers. As a result, accountancy is likely to become a much more strategically oriented profession.

However, the skills required of accountants are likely to change, and there may be a need for fewer entry-level accountants ( Kokina and Davenport, 2017 ; Marrone and Hazelton, 2019 ). There may be a shift towards notions such as creativity, innovation, holistic thinking, complex decision-making and sense-making. The ability to adapt to keep pace with an increasingly evolving business environment and technological context will also be important. Addressing such changes in education through content and delivery is necessary to ensure that graduates have up-to-date and workplace-relevant knowledge and can keep up with global accreditation standards and professional qualifications ( Al-Htaybat et al. , 2018 ). Teams, management and government bodies implementing blockchain and making decisions based on data obtained from blockchain will also need new skills to adapt to the changing environment ( Pimentel et al. , 2019 ; Siew et al. , 2020 ). Therefore, we propose that universities and higher education institutions should change and improve the curriculum of accounting and finance programmes to help students develop the above-mentioned skills. It is essential to start making the changes now as current students will soon become accounting and auditing practitioners as well as managers working with blockchain and other disruptive technologies.

7.3 Implications for policy

The literature review reveals a pressing need for legal frameworks to govern blockchain technologies and regulate cryptoassets. Comprehensive work by regulators and policymakers may help implement and spread these technological innovations further, opening new sources of financing for companies. There is also a need to work on legal and taxation policies for tokens, bitcoins and other cryptocurrencies so that they become valuable tools and stable assets in capital markets. With the improved regulatory framework, we also propose that in the future governments may develop national cryptocurrencies, e.g. crypto-euros or crypto dollars, that will be easier and faster to use compared to existing currencies. A well-developed regulatory framework may help tokens become a legitimate means of exchange in ecosystems that will start growing in the future. Further work is required from accounting bodies to accept new types of digital assets and develop standards that will solve the issues related to their recognition, measurement and disclosure. In the future, the implementation of blockchain may also raise questions related to the regulation of social and environmental accounting that becomes possible with this technology. All this will help to improve transparency further and decrease information asymmetry in the market.

7.4 Limitations

This study has several limitations. First, the sample only covers the period till June 2020. Extending this timeline could be an option for future research. Second, other machine learning techniques could be applied while working with the corpus of literature. Although our LDA approach is much more advanced than mere word count or word cloud methods, it still models documents using a bag-of-words representation. A similar topic model using more advanced neural natural language processing (NLP) architectures like Bidirectional Encoder Representations from Transformers (BERT) ( Devlin et al. , 2018 ) or Generative Pre-trained Transformer 3 (GPT-3) ( Brown et al. , 2020 ) that also consider the context and semantics of words might result in different fields of inquiry or a more revealing combination of topics. Third, we included articles uploaded to the SSRN database as well as published articles in ranked journals. We are aware that the peer-review process is accepted as a proxy for the quality of published works, especially with respect to academic journal articles ( Hart, 1999 ; Massaro et al. , 2015 ). However, we believe that, given the speed of new knowledge development, especially in the areas of disruptive technologies like blockchain, papers from SSRN added an important contribution to the topics identified. Finally, the validity of the results can only be considered at the time of the analysis, as literature reviews “are not a panacea” ( Massaro et al. , 2015 , p. 546). They only identify the current state of the field, and they only offer pathways for future research directions at a particular point in time.

The number of articles per year

Publication trends of the topics

Frequency distribution of articles

List of topics

Top 10 articles by number of citations

The top 10 articles by CPY

Agnew , H. ( 2016 ), “ Auditing: pitch battle ”, retrieved 20 June 2019, available at: www.ft.com/content/268637f6-15c8-11e6-9d98-00386a18e39d ( accessed 30 January 2021 ).

Al-Htaybat , K. , von Alberti-Alhtaybat , L. and Alhatabat , Z. ( 2018 ), “ Educating digital natives for the future: accounting educators' evaluation of the accounting curriculum ”, Accounting Education , Vol. 27 No. 4 , pp. 333 - 357 .

Allen , D.W. , Berg , C. , Markey-Towler , B. , Novak , M. and Potts , J. ( 2020 ), “ Blockchain and the evolution of institutional technologies: implications for innovation policy ”, Research Policy , Vol. 49 No. 1 , p. 103865 .

Alles , M. ( 2018 ), “ Examining the role of the AIS research literature using the natural experiment of the 2018 JIS conference on cloud computing ”, International Journal of Accounting Information Systems , Vol. 31 , pp. 58 - 74 .

Alvesson , M. and Deetz , S. ( 2000 ), Doing Critical Management Research , Sage , London .

Asmussen , C.B. and Møller , C. ( 2019 ), “ Smart literature review: a practical topic modelling approach to exploratory literature review ”, Journal of Big Data , Vol. 6 No. 1 , pp. 1 - 18 .

Auer , R. ( 2019 ), “ Embedded supervision: how to build regulation into blockchain finance ”, available at: https://ssrn.com/abstract=3463885 ( accessed 30 June 2020 ).

Benjaafar , S. , Chen , X. , Taneri , N. and Wan , G. ( 2018 ), “ A permissioned blockchain business model for green sourcing ”, available at: https://ssrn.com/abstract=3305792 ( accessed 30 June 2020 ).

Bentley , J.W. , Christensen , T.E. , Gee , K.H. and Whipple , B.C. ( 2018 ), “ Disentangling managers' and analysts' non-GAAP reporting ”, Journal of Accounting Research , Vol. 56 No. 4 , pp. 1039 - 1081 .

Black , D.E. , Black , E.L. , Christensen , T.E. and Gee , K.H. ( 2020 ), “ Comparing non-GAAP EPS in earnings announcements and proxy statements ”, available at: https://ssrn.com/abstract=2343140 ( accessed November 2020 ).

Blei , D.M. , Ng , A.Y. and Jordan , M.I. ( 2003 ), “ Latent dirichlet allocation ”, Journal of Machine Learning Research , Vol. 3 Nos 4-5 , pp. 993 - 1022 .

Bonsón , E. and Bednárová , M. ( 2019 ), “ Blockchain and its implications for accounting and auditing ”, Meditari Accountancy Research , Vol. 27 No. 5 , pp. 725 - 740 .

Bonsón , E. , Perea , D. and Bednárová , M. ( 2019 ), “ Twitter as a tool for citizen engagement: an empirical study of the Andalusian municipalities ”, Government Information Quarterly , Vol. 36 No. 3 , pp. 480 - 489 .

Brown , T.B. , Mann , B. , Ryder , N. , Subbiah , M. , Kaplan , J. , Dhariwal , P. and Amodei , D. ( 2020 ), “ Language models are few-shot learners ”, available at: https://arxiv.org/pdf/2005.14165.pdf?ref=hackernoon.com ( accessed 25 May 2021 ).

Burragoni , V. ( 2017 ), “ Financial innovations: a deeper literature review with focus on India ”, available at: https://ssrn.com/abstract=2894973 ( accessed 30 June 2020 ).

Cai , C.W. ( 2018 ), “ Disruption of financial intermediation by FinTech: a review on crowdfunding and blockchain ”, Accounting and Finance , Vol. 58 No. 4 , pp. 965 - 992 .

Cai , C.W. , Linnenluecke , M.K. , Marrone , M. and Singh , A.K. ( 2019 ), “ Machine learning and expert judgement: analysing emerging topics in accounting and finance research in the Asia–Pacific ”, Abacus , Vol. 55 No. 4 , pp. 709 - 733 .

Canelón , J. , Huerta , E. , Incera , J. and Ryan , T. ( 2019 ), “ A cybersecurity control framework for blockchain ecosystems ”, The International Journal of Digital Accounting Research , Vol. 19 , pp. 103 - 144 .

Cao , S.S. , Ma , G. , Tucker , J.W. and Wan , C. ( 2018 ), “ Technological peer pressure and product disclosure ”, The Accounting Review , Vol. 93 No. 6 , pp. 95 - 126 .

Casey , M.J. and Vigna , P. ( 2018 ), “ In blockchain we trust ”, MIT Technology Review , Vol. 121 No. 3 , pp. 10 - 16 .

Changati , V. and Kansal , P. ( 2019 ), “ Factors influencing technology acceptance in the banking sector: a binary recursive partitioning approach ”, Journal of Commerce and Accounting Research , Vol. 8 No. 1 , pp. 68 - 82 .

Cho , S. , Vasarhelyi , M.A. and Zhang , C. ( 2019 ), “ The forthcoming data ecosystem for business measurement and assurance ”, Journal of Emerging Technologies in Accounting , Vol. 16 No. 2 , pp. 1 - 21 .

Chohan , U.W. ( 2017 ), “ The double spending problem and cryptocurrencies ”, available at: https://ssrn.com/abstract=3090174 ( accessed 30 June 2020 ).

Clayton , J. ( 2017 ), “ Statement on cryptocurrencies and initial coin offerings ”, available at: https://www.sec.gov/news/public-statement/statement-clayton-2017-12-11 ( accessed 10 May 2021 ).

Clohessy , T. and Acton , T. ( 2019 ), “ Investigating the influence of organisational factors on blockchain adoption: an innovation theory perspective ”, Industrial Management and Data Systems , Vol. 119 No. 7 , pp. 1457 - 1491 .

Conoscenti , M. , Vetro , A. and De Martin , J.C. ( 2016 ), “ Blockchain for the Internet of Things: a systematic literature review ”, 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA) , pp. 1 - 6 , available at: http://www.antoniovetro.it/authorsversion/conferences/2016-iotsms-bk.pdf ( accessed 15 May 2020 ).

Coyne , J.G. and McMickle , P.L. ( 2017 ), “ Can blockchains serve an accounting purpose? ”, Journal of Emerging Technologies in Accounting , Vol. 14 No. 2 , pp. 101 - 111 .

Cozzens , S. , Gatchair , S. , Kang , J. , Kim , K.S. , Lee , H.J. , Ordóñez , G. and Porter , A. ( 2010 ), “ Emerging technologies: quantitative identification and measurement ”, Technology Analysis and Strategic Management , Vol. 22 No. 3 , pp. 361 - 376 .

Dai , J. and Vasarhelyi , M.A. ( 2017 ), “ Toward blockchain-based accounting and assurance ”, Journal of Information Systems , Vol. 31 No. 3 , pp. 5 - 21 .

Dai , J. , Wang , Y. and Vasarhelyi , M. ( 2017 ), “ Why blockchain has the potential to serve as a secure accounting information system ”, The CPA Journal , Vol. 2 , available at: www.cpajournal.com/2017/09/20/blockchain-potential-serve-secureaccounting-information-system-cpe-season/ ( accessed 3 May 2021 ).

Dai , J. , He , N. and Yu , H. ( 2019 ), “ Utilising blockchain and smart contracts to enable Audit 4.0: from the perspective of accountability audit of air pollution control in China ”, Journal of Emerging Technologies in Accounting , Vol. 16 No. 2 , pp. 23 - 41 .

Deloitte ( 2016 ), “ Blockchain technology: a game-changer in accounting? ”, available at: https://www2.deloitte.com/content/dam/Deloitte/de/Documents/Innovation/Blockchain_A%20game-changer%20in%20accounting.pdf ( accessed 3 July 2020 ).

Deloitte ( 2019 ), “ Deloitte global blockchain survey ”, available at: https://www2.deloitte.com/content/dam/Deloitte/se/Documents/risk/DI_2019-global-blockchain-survey.pdf ( accessed 3 July 2020 ).

Devlin , J. , Chang , M.W. , Lee , K. and Toutanova , K. ( 2018 ), “ Bert: pre-training of deep bidirectional transformers for language understanding ”, available at: https://arxiv.org/pdf/1810.04805.pdf&usg=ALkJrhhzxlCL6yTht2BRmH9atgvKFxHsxQ ( accessed 25 May 2021 ).

Dumay , J. and Cai , L. ( 2014 ), “ A review and critique of content analysis as a methodology for inquiring into IC disclosure ”, Journal of Intellectual Capital , Vol. 15 No. 2 , pp. 264 - 290 .

Dumay , J. and Guthrie , J. ( 2019 ), “ Reflections on interdisciplinary critical intellectual capital accounting research ”, Accounting, Auditing & Accountability Journal , Vol. 32 No. 8 , pp. 2282 - 2306 .

Dumay , J. , de Villiers , C. , Guthrie , J. and Hsiao , P.C. ( 2018 ), “ Thirty years of Accounting, Auditing and Accountability Journal: a critical study of the journal's most cited articles ”, Accounting, Auditing and Accountability Journal , Vol. 31 No. 5 , pp. 1510 - 1541 .

El‐Haj , M. , Rayson , P. , Walker , M. , Young , S. and Simaki , V. ( 2019 ), “ In search of meaning: lessons, resources and next steps for computational analysis of financial discourse ”, Journal of Business Finance and Accounting , Vol. 46 Nos 3-4 , pp. 265 - 306 .

Faccia , A. and Mosteanu , N.R. ( 2019 ), “ Accounting and blockchain technology: from double-entry to triple-entry ”, The Business and Management Review , Vol. 10 No. 2 , pp. 108 - 116 .

Fang , B. and Hope , O.K. ( 2021 ), “ Analyst teams ”, Review of Accounting Studies , Vol. 26 , pp. 425 - 467 .

Fanning , K. and Centers , D.P. ( 2016 ), “ Blockchain and its coming impact on financial services ”, Journal of Corporate Accounting and Finance , Vol. 27 No. 5 , pp. 53 - 57 .

Fligstein , N. , Stuart Brundage , J. and Schultz , M. ( 2017 ), “ Seeing like the Fed: culture, cognition, and framing in the failure to anticipate the financial crisis of 2008 ”, American Sociological Review , Vol. 82 No. 5 , pp. 879 - 909 .

Financial Reporting Council (FRC) ( 2018 ), “ FRC submission to the treasury select committee digital currencies inquiry ”, available at: https://www.frc.org.uk/getattachment/52cdb6cb-7498-4a92-9e67-c1f4f8fbb3f7/130418-FRC-response-Treasury-Select-Committee-Digital-Currencies-Inquiry.pdf ( access 17 May 2021 ).

Fullana , O. and Ruiz , J. ( 2021 ), “ Accounting information systems in the blockchain era ”, International Journal of Intellectual Property Management , Vol. 11 No. 1 , pp. 63 - 80 .

Gietzmann , M.B. and Grossetti , F. ( 2019 ), “ Blockchain and other distributed ledger technologies: where is the accounting? ”, available at: https://ssrn.com/abstract=3507602 ( accessed 30 June 2020 ).

Gordon , G. ( 2016 ), “ SSRN—the leading social science and humanities repository and online community—joins Elsevier ”, available at: https://www.elsevier.com/connect/ssrn-the-leading-social-science-and-humanities-repository-and-online-community-joins-elsevier ( accessed 15 April 2020 ).

Gurrea-Martínez , A. and Remolina , N. ( 2018 ), “ The law and finance of initial coin offerings ”, available at: https://ssrn.com/abstract=3182261 ( accessed 30 June 2020 ).

Gurtu , A. and Johny , J. ( 2019 ), “ Potential of blockchain technology in supply chain management: a literature review ”, International Journal of Physical Distribution and Logistics Management , Vol. 49 No. 9 , pp. 881 - 900 .

Hart , C. ( 1999 ), Doing Literature Review , Sage Publications , London , p. 230 .

Holub , M. and Johnson , J. ( 2017 ), “ Mapping bitcoin's influence on academic research ”, available at: https://ssrn.com/abstract=3094492 ( accessed 30 June 2020 ).

Iansiti , M. and Lakhani , K.R. ( 2017 ), “ The truth about blockchain ”, Harvard Business Review , Vol. 95 No. 1 , pp. 3 - 11 .

IASB ( 2018 ), IFRS® Conceptual Framework Project Summary , International Accounting Standards Board , London .

Issa , H. , Sun , T. and Vasarhelyi , M.A. ( 2016 ), “ Research ideas for artificial intelligence in auditing: the formalisation of audit and workforce supplementation ”, Journal of Emerging Technologies in Accounting , Vol. 13 No. 2 , pp. 1 - 20 .

Jarvenpaa , S.L. and Ives , B. ( 1991 ), “ Executive involvement and participation in the management of information technology ”, MIS Quarterly , June , pp. 205 - 227 .

Johannessen , J.A. ( 2013 ), “ Innovation: a systemic perspective–developing a systemic innovation theory ”, Kybernetes , Vol. 42 No. 8 , pp. 1195 - 1217 .

Jones , S. and Alam , N. ( 2019 ), “ A machine learning analysis of citation impact among selected Pacific Basin journals ”, Accounting and Finance , Vol. 59 No. 4 , pp. 2509 - 2552 .

Karajovic , M. , Kim , H.M. and Laskowski , M. ( 2019 ), “ Thinking outside the block: projected phases of blockchain integration in the accounting industry ”, Australian Accounting Review , Vol. 29 No. 2 , pp. 319 - 330 .

Kim , H.M. and Laskowski , M. ( 2018 ), “ Toward an ontology‐driven blockchain design for supply‐chain provenance ”, Intelligent Systems in Accounting, Finance and Management , Vol. 25 No. 1 , pp. 18 - 27 .

Kokina , J. and Davenport , T.H. ( 2017 ), “ The emergence of artificial intelligence: how automation is changing auditing ”, Journal of Emerging Technologies in Accounting , Vol. 14 No. 1 , pp. 115 - 122 .

Kokina , J. , Mancha , R. and Pachamanova , D. ( 2017 ), “ Blockchain: emergent industry adoption and implications for accounting ”, Journal of Emerging Technologies in Accounting , Vol. 14 No. 2 , pp. 91 - 100 .

Kwilinski , A. ( 2019 ), “ Implementation of blockchain technology in accounting sphere ”, Academy of Accounting and Financial Studies Journal , Vol. 23 , pp. 1 - 6 .

La Torre , M. , Sabelfeld , S. , Blomkvist , M. , Tarquinio , L. and Dumay , J. ( 2018 ), “ Harmonising non-financial reporting regulation in Europe ”, Meditari Accountancy Research , Vol. 26 No. 4 , pp. 598 - 621 .

La Torre , M. , Botes , V.L. , Dumay , J. and Odendaal , E. ( 2021 ), “ Protecting a new Achilles heel: the role of auditors within the practice of data protection ”, Managerial Auditing Journal , Published Online , Vol. 36 No. 2 , pp. 218 - 239 .

Lev , B. and Gu , F. ( 2016 ), The End of Accounting and the Path Forward for Investors and Managers , John Wiley and Sons , Hoboken, New Jersey, NJ .

Li , F. ( 2010 ), “ Textual analysis of corporate disclosures: a survey of the literature ”, Journal of Accounting Literature , Vol. 29 , pp. 143 - 165 .

Linnenluecke , M.K. , Marrone , M. and Singh , A.K. ( 2020 ), “ Conducting systematic literature reviews and bibliometric analyses ”, Australian Journal of Management , Vol. 45 No. 2 , pp. 175 - 194 .

Marrone , M. and Hazelton , J. ( 2019 ), “ The disruptive and transformative potential of new technologies for accounting, accountants and accountability ”, Meditari Accountancy Research , Vol. 27 No. 5 , pp. 677 - 694 .

Massaro , M. , Dumay , J. and Garlatti , A. ( 2015 ), “ Public sector knowledge management: a structured literature review ”, Journal of Knowledge Management , Vol. 19 No. 3 , pp. 530 - 558 .

Massaro , M. , Dumay , J. and Guthrie , J. ( 2016 ), “ On the shoulders of giants: undertaking a structured literature review in accounting ”, Accounting, Auditing & Accountability Journal , Vol. 29 No. 5 , pp. 767 - 801 .

McGuigan , N. and Ghio , A. ( 2019 ), “ Art, accounting and technology: unravelling the paradoxical in-between ”, Meditari Accountancy Research , Vol. 27 No. 5 , pp. 789 - 804 .

Moll , J. and Yigitbasioglu , O. ( 2019 ), “ The role of internet-related technologies in shaping the work of accountants: new directions for accounting research ”, The British Accounting Review , Vol. 51 No. 6 , p. 100833 .

Moro , S. , Cortez , P. and Rita , P. ( 2015 ), “ Business intelligence in banking: a literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation ”, Expert Systems with Applications , Vol. 42 No. 3 , pp. 1314 - 1324 .

Nakamoto , S. ( 2008 ), “ Bitcoin: a peer-to-peer electronic cash system ”, available at: https://bitcoin.org/bitcoin.pdf ( accessed 20 June 2020 ).

Nyumbayire , C. ( 2017 ), “ Blockchain technology innovations part 1 ”, available at: www.interlogica.it/en/insight/blockchain-technology-innovations-part-i/ ( accessed 1 August 2021 ).

O'Leary , D.E. ( 2017 ), “ Configuring blockchain architectures for transaction information in blockchain consortiums: the case of accounting and supply chain systems ”, Intelligent Systems in Accounting, Finance and Management , Vol. 24 No. 4 , pp. 138 - 147 .

O'Leary , D.E. ( 2019 ), “ Some issues in blockchain for accounting and the supply chain, with an application of distributed databases to virtual organisations ”, Intelligent Systems in Accounting, Finance and Management , Vol. 26 No. 3 , pp. 137 - 149 .

Panetta , K. ( 2018 ), “ Why blockchain matters to supply chain executives ”, available at: https://www.gartner.com/smarterwithgartner/why-blockchain-matters-to-supply-chain-executives/ ( accessed 15 May 2020 ).

Pimentel , E. , Boulianne , E. , Eskandari , S. and Clark , J. ( 2019 ), “ Systemising the challenges of auditing blockchain-based assets ”, available at: https://ssrn.com/abstract=3359985 ( accessed 30 June 2020 ).

Procházka , D. ( 2018 ), “ Accounting for bitcoin and other cryptocurrencies under IFRS: a comparison and assessment of competing models ”, The International Journal of Digital Accounting Research , Vol. 18 No. 24 , pp. 161 - 188 .

Rabbani , M.R. , Khan , S. and Thalassinos , E.I. ( 2020 ), “ FinTech, blockchain and Islamic finance: an extensive literature review ”, International Journal of Economics and Business Administration , Vol. 8 No. 2 , pp. 65 - 86 .

Raiborn , C. and Sivitanides , M. ( 2015 ), “ Accounting issues related to bitcoins ”, Journal of Corporate Accounting and Finance , Vol. 26 No. 2 , pp. 25 - 34 .

Ram , A.J. ( 2018 ), “ Taxation of the bitcoin: initial insights through a correspondence analysis ”, Meditari Accountancy Research , Vol. 26 No. 2 , pp. 214 - 240 .

Röder , M. , Both , A. and Hinneburg , A. ( 2015 ), “ Exploring the space of topic coherence measures ”, Proceedings of the Eighth ACM International Conference on Web Search and Data Mining , pp. 399 - 408 .

Rozario , A.M. and Vasarhelyi , M.A. ( 2018 ), “ Auditing with smart contracts ”, International Journal of Digital Accounting Research , Vol. 18 , pp. 1 - 27 .

Schmitz , J. and Leoni , G. ( 2019 ), “ Accounting and auditing at the time of blockchain technology: a research agenda ”, Australian Accounting Review , Vol. 29 No. 2 , pp. 331 - 342 .

Sheldon , M.D. ( 2019 ), “ A primer for information technology general control considerations on a private and permissioned blockchain audit ”, Current Issues in Auditing , Vol. 13 No. 1 , pp. 15 - 29 .

Shen , C. and Pena-Mora , F. ( 2018 ), “ Blockchain for cities—a systematic literature review ”, available at: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8531608 ( accessed 20 May 2020 ).

Siew , E.G. , Rosli , K. and Yeow , P.H. ( 2020 ), “ Organisational and environmental influences in the adoption of computer-assisted audit tools and techniques (CAATTs) by audit firms in Malaysia ”, International Journal of Accounting Information Systems , Vol. 36 , March , 100445 .

Sixt , E. and Himmer , K. ( 2019 ), “ Accounting and taxation of cryptoassets ”, available at: https://ssrn.com/abstract=3419691 ( accessed 30 June 2020 ).

Small , H. , Boyack , K.W. and Klavans , R. ( 2014 ), “ Identifying emerging topics in science and technology ”, Research Policy , Vol. 43 No. 8 , pp. 1450 - 1467 .

Smith , S.S. ( 2017 ), “ Sustainability: how accountants can add value and deliver results ”, Management Accounting Quarterly , Vol. 19 No. 1 , pp. 19 - 30 .

Smith , S.S. ( 2020 ), “ Blockchains impact on risk assessment procedures ”, Journal of Forensic and Investigative Accounting , Vol. 12 No. 1 , pp. 55 - 65 .

Smith , S.S. , Petkov , R. and Lahijani , R. ( 2019 ), “ Blockchain and cryptocurrencies-considerations for treatment and reporting for financial services professionals ”, International Journal of Digital Accounting Research , Vol. 19 , pp. 59 - 78 .

Stratopoulos , T.C. and Calderon , J. ( 2018 ), “ Introduction to blockchain with R ”, available at: https://ssrn.com/abstract=3189518 ( accessed 30 June 2020 ).

Tan , B.S. and Low , K.Y. ( 2019 ), “ Blockchain as the database engine in the accounting system ”, Australian Accounting Review , Vol. 29 No. 2 , pp. 312 - 318 .

Tang , Q. and Tang , L.M. ( 2019 ), “ Toward a distributed carbon ledger for carbon emissions trading and accounting for corporate carbon management ”, Journal of Emerging Technologies in Accounting , Vol. 16 No. 1 , pp. 37 - 46 .

The Interpretations Committee ( 2019 ), “ Holdings of cryptocurrencies ”, available at: https://www.ifrs.org/projects/completed-projects/2019/holdings-of-cryptocurrencies/ ( accessed 17 May 2021 ).

Tiberius , V. and Hirth , S. ( 2019 ), “ Impacts of digitisation on auditing: a Delphi study for Germany ”, Journal of International Accounting, Auditing and Taxation , Vol. 37 , p. 100288 .

Uwizeyemungu , S. , Bertrand , J. and Poba-Nzaou , P. ( 2020 ), “ Patterns underlying required competencies for CPA professionals: a content and cluster analysis of job ads ”, Accounting Education , Vol. 29 No. 2 , pp. 109 - 136 .

Von Krogh , G. , Rossi-Lamastra , C. and Haefliger , S. ( 2012 ), “ Phenomenon-based research in management and organisation science: when is it rigorous and does it matter? ”, Long Range Planning , Vol. 45 No. 4 , pp. 277 - 298 .

Wang , Y. and Kogan , A. ( 2018 ), “ Designing confidentiality-preserving blockchain-based transaction processing systems ”, International Journal of Accounting Information Systems , Vol. 30 , pp. 1 - 18 .

Wang , Y. , Han , J.H. and Beynon-Davies , P. ( 2019 ), “ Understanding blockchain technology for future supply chains: a systematic literature review and research agenda ”, Supply Chain Management: An International Journal , Vol. 24 No. 1 , pp. 62 - 84 .

Wanner , F. , Stoffel , A. , Jäckle , D. , Kwon , B.C. , Weiler , A. , Keim , D.A. , Isaacs , K.E. , Giménez , A. , Jusufi , I. and Gamblin , T. ( 2014 ), “ State-of-the-art report of visual analysis for event detection in text data streams ”, Conference presentation at the EuroVis 2014: The Eurographics Conference on Visualization , Swansea, Wales, UK , 9-13 June .

Wiśniewska , A. ( 2018 ), “ The initial coin offering–challenges and opportunities ”, Copernican Journal of Finance and Accounting , Vol. 7 No. 2 , pp. 99 - 110 .

Xu , M. , Chen , X. and Kou , G. ( 2019 ), “ A systematic review of blockchain ”, Financial Innovation , Vol. 5 No. 1 , pp. 1 - 14 .

Yermack , D. ( 2017 ), “ Corporate governance and blockchains ”, Review of Finance , Vol. 21 No. 1 , pp. 7 - 31 .

Yu , T. , Lin , Z. and Tang , Q. ( 2018 ), “ Blockchain: the introduction and its application in financial accounting ”, Journal of Corporate Accounting and Finance , Vol. 29 No. 4 , pp. 37 - 47 .

Zhang , L. , Pei , D. and Vasarhelyi , M.A. ( 2017 ), “ Toward a new business reporting model ”, Journal of Emerging Technologies in Accounting , Vol. 14 No. 2 , pp. 1 - 15 .

Zhang , S. , Zhang , D. , Zheng , J. and Aerts , W. ( 2021 ), “ Does policy uncertainty of the blockchain dampen ICO markets? ”, Accounting and Finance , Vol. 61 No. S1 , pp. 1625 - 1637 .

Corresponding author

Related articles, we’re listening — tell us what you think, something didn’t work….

Report bugs here

All feedback is valuable

Please share your general feedback

Join us on our journey

Platform update page.

Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

Questions & More Information

Answers to the most commonly asked questions here