research areas in blockchain technology

• Privacy Policy

Home » Blockchain Research – Methods, Types and Examples

Blockchain Research – Methods, Types and Examples

Table of Contents

Blockchain Research

Blockchain research is a multidisciplinary field that explores the principles, applications, and implications of blockchain technology. The field is new, with many avenues for exploration, given that the technology underpinning blockchain has potential to transform several industries. The research on this topic spans several disciplines, including but not limited to computer science, economics, law, and business.

Areas of Research

Here are several areas within blockchain research:

Computer Science and Engineering

This aspect of blockchain research includes developing new protocols and consensus algorithms, improving the efficiency and scalability of blockchain networks, ensuring security against various attacks, and exploring interoperability between different blockchains.

Cryptography

Blockchain relies heavily on cryptographic techniques for securing transactions and maintaining anonymity. Research in this field could involve designing new cryptographic methods to improve the security of blockchains.

Economics and Finance

The use of blockchain for cryptocurrencies has sparked interest in how blockchain could affect traditional financial systems and markets. Topics in this field might include the impact of decentralized finance (DeFi), economic modeling of blockchain-based markets, and understanding the economic incentives in blockchain systems.

Law and Ethics

There’s ongoing debate about how blockchain should be regulated and the ethical implications of its use. Legal and ethical research might address issues such as the governance of blockchain systems, data privacy, and the use of blockchain for illegal activities.

Business and Management

This area of research looks at how blockchain can be applied in different industries, such as supply chain, healthcare, energy, etc. It also studies the managerial and strategic implications of adopting blockchain technology in businesses.

Sociology and Anthropology

Blockchain technology, by promoting decentralization and peer-to-peer interactions, can bring about new social and cultural dynamics. Researchers in these fields might study the societal implications of widespread blockchain adoption, or how the technology is used in different cultural contexts.

Types of Blockchain Research

The types of blockchain research can be broadly classified according to the fields of study or specific aspects of the technology they focus on. These types include but are not limited to:

Protocol Development and Improvement

Research in this area focuses on the design, testing, and development of new blockchain protocols and improvements to existing ones. This can include work on scalability, interoperability, and privacy enhancements, among other things.

Cryptography and Security

This type of research is focused on the cryptographic algorithms and security protocols that underpin blockchain technology. It can include studying vulnerabilities in current systems, creating new, more secure cryptographic algorithms, and developing new methods for maintaining privacy and security on the blockchain.

Consensus Mechanisms

Researching different mechanisms used to achieve consensus in a blockchain network is another key area. Proof-of-Work (PoW) and Proof-of-Stake (PoS) are two well-known mechanisms, but researchers are exploring others that could potentially be more efficient, secure, and sustainable.

Economic and Financial Studies

This type of research analyzes the financial aspects of blockchain, such as cryptocurrency markets, decentralized finance (DeFi), token economics, and the impact of blockchain technology on traditional financial systems.

Governance and Legal Research

This research explores the legal and governance aspects of blockchain technology, including regulation, smart contracts, intellectual property issues, data privacy, and the enforcement of legal norms in decentralized systems.

Societal Impact

This branch of research investigates how blockchain technology impacts society at large. It includes studies on blockchain in areas such as education, politics, social justice, and more.

Blockchain in Industry

This type of research focuses on how blockchain can be applied to specific industries (like supply chain management, healthcare, energy, etc.) and the impact it can have. This involves not only technical applications but also strategic considerations for businesses and institutions.

Usability and Human-Computer Interaction (HCI)

This research focuses on the user interface and user experience aspects of blockchain applications. This includes understanding how to make these applications more accessible and easier to use for the general population, improving their design, and evaluating their usability.

Environmental Impact

This type of research looks at the environmental implications of blockchain technology, particularly energy-intensive processes like Bitcoin mining.

Blockchain Research Techniques

Research techniques used in blockchain research vary according to the domain of the study. Here are some techniques that are often used in different areas of blockchain research:

• Simulations and Modelling : Simulations are often used in technical research to model the behavior of blockchain systems under different conditions. This can be used to test new protocols, consensus mechanisms, or security measures before implementing them in a live system.
• Cryptography Techniques : Cryptographers develop and use advanced mathematical techniques to ensure the security and privacy of blockchain transactions. They might use techniques from number theory, algebra, and other areas of mathematics.
• Data Analysis : Many types of blockchain research involve analyzing data. This could include transaction data from a blockchain, price data from cryptocurrency markets, or other types of data relevant to the study. Techniques might include statistical analysis, machine learning, and network analysis.
• Qualitative Research Methods : Interviews, case studies, and participant observation are some of the qualitative techniques that can be used in blockchain research, especially when exploring the societal impacts, user experiences, and regulatory aspects of blockchain technology.
• Legal Analysis : Researchers studying the legal aspects of blockchain might use techniques such as statutory interpretation, case law analysis, and comparative legal analysis.
• Experimental Research : Particularly in areas like usability and human-computer interaction (HCI), researchers may conduct experimental studies to test different designs or interfaces, and measure their effectiveness.
• Benchmarking : To compare the performance of different blockchain systems or protocols, researchers often use benchmarking. This involves running a series of standard tests on each system and comparing the results.
• Surveys and Questionnaires : Particularly in business, management, and sociological studies, researchers might conduct surveys or use questionnaires to gather data on people’s perceptions and uses of blockchain technology.

Examples of Blockchain Research

Examples of Blockchain Research are as follows:

• The Bitcoin Lightning Network: Scalable Off-Chain Instant Payments (2016) by Joseph Poon and Thaddeus Dryja. This paper proposes the Lightning Network as a solution to Bitcoin’s scalability problem. The Lightning Network is a second-layer solution that enables faster transactions by creating payment channels off the main Bitcoin blockchain.
• SoK: Research Perspectives and Challenges for Bitcoin and Cryptocurrencies (2015) by Bonneau et al. This paper offers a systematic review of the existing research on Bitcoin and other cryptocurrencies, and identifies the main challenges and potential future directions for the field.
• Decentralizing Privacy: Using Blockchain to Protect Personal Data (2015) by Zyskind, Nathan, and Pentland. This paper proposes using blockchain technology to improve data privacy. The authors suggest a system that would use blockchain to store personal data securely, allowing individuals to control who can access their data.
• Smart Contracts and the Cost of Inflexibility (2016) by Jeremy Clark and others. This research looks into smart contracts – self-executing contracts with the terms directly written into code – and examines how their immutable and autonomous nature can lead to unforeseen complications and potential vulnerabilities.
• On or Off the Blockchain? Insights on Off-Chaining Computation and Data (2019) by Harald Crouch and others. This research discusses off-chain transactions and computation, an important topic for scalability and efficiency of blockchains.
• Blockchain technology for healthcare: Facilitating the transition to patient-driven interoperability (2018) by Kevin Peterson and others. This paper reviews the potential of blockchain technology to create a patient-centered approach in the healthcare industry by enabling interoperability, security, and integrity of healthcare data.

Advantages of Blockchain Research

Blockchain research holds many advantages and potential benefits for academia, industry, and society at large. Here are a few key ones:

• Technological Advancements : Blockchain research is the foundation for enhancing the technology itself. Through research, improvements can be made in areas such as security, scalability, interoperability, and efficiency of blockchain systems. This leads to the development of more robust and practical blockchain applications.
• Innovation Across Industries : By exploring how blockchain can be applied in various sectors, research can stimulate innovation. From finance to supply chain, healthcare, energy, and beyond, research helps discover novel uses for blockchain technology, potentially transforming entire industries.
• Regulation and Policy Making : Blockchain research, especially into the legal, ethical, and societal implications of the technology, provides crucial insights for policymakers. As blockchain becomes more mainstream, appropriate regulation will be needed to ensure it is used ethically and responsibly. Research informs this regulation and helps avoid potential pitfalls.
• Economic Understanding : The rise of cryptocurrencies and decentralized finance (DeFi) are creating entirely new economic systems. Research helps us understand these systems, their implications for traditional finance, and how they can be used safely and effectively.
• Workforce Development : As blockchain technology grows, so does the need for individuals skilled in its use. Blockchain research in academic settings contributes to the training and development of a workforce equipped to implement and manage blockchain systems.
• Societal Impact : Researching the potential societal impacts of blockchain can help maximize its benefits and mitigate possible negative effects. This might include studying the potential of blockchain for social good, its environmental impact, or how it might affect power dynamics within societies.

Disadvantages of Blockchain Research

While blockchain research carries a number of benefits, there are also challenges and potential disadvantages associated with it. Some of these include:

• Rapidly Evolving Technology : The fast pace of change in blockchain technology can make it difficult for research to stay current. By the time a research study is completed and published, it’s possible that the technology has already advanced or shifted significantly.
• Lack of Standardization : Blockchain technology lacks standardized practices and frameworks. This means that researchers can have difficulty comparing results or building upon previous research.
• Legal and Regulatory Uncertainty : The legal status and regulatory environment for blockchain technology are still in flux in many jurisdictions. This can complicate research, especially when it involves practical applications that may be subject to regulation.
• Complexity of the Field : Blockchain combines concepts from computer science, economics, law, and other fields. This interdisciplinary nature can make it a challenging area to research, requiring expertise in several different fields.
• Lack of Funding : Despite its potential, blockchain research can be underfunded. This can be due to a variety of factors, including the perceived riskiness of the technology, its association with illicit activities, and a lack of understanding about its potential applications.
• Access to Data : Blockchains are designed to be secure and private. While some data is publicly available on blockchains, accessing it in a meaningful way can be challenging. In addition, some valuable data might be kept private by companies or individuals, making it unavailable for research.
• Environmental Concerns : Some types of blockchain research, particularly those involving proof of work consensus mechanisms like Bitcoin, can be resource-intensive and contribute to environmental degradation, due to the high energy consumption of these systems.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Digital Ethnography – Types, Methods and Examples

Diagnostic Analytics – Methods, Tools and...

Predictive Analytics – Techniques, Tools and...

Prescriptive Analytics – Techniques, Tools and...

Social Network Analysis – Types, Tools and...

Descriptive Analytics – Methods, Tools and...

The Stanford Center for Blockchain Research

The Center for Blockchain Research (CBR) is a focused research effort on crypto-currencies and blockchain technologies. The center brings together engineering, law, and economics faculty, as well as post-docs, students, and visitors, to work on technical challenges in the field. The center's primary mission is to support the thriving ecosystem by developing new technologies needed to advance the field. Beyond its research mission, the center runs an extensive education and outreach program, including on-campus courses, MOOCs, workshops, and conferences for the general blockchain community.

The 6th Stanford Blockchain Conference (SBC) will take place on Aug. 28-30, 2023.

New Research

• Collaborative ZK proofs. Learn more ...
• Ebb and flow protocols. Learn more ...
• Learn more about the center's research ...

Blockchain Seminar

A monthly research seminar on blockchain topics. The schedule is available online. Please join our mailing list, on the seminar home page, to receive talk announcements.

Dan Boneh    (co-director)

Clark Barrett

Joe Grundfest

Laurie Hodrick

David Mazières    (co-director)

John Mitchell

Andrew Hall

Education and Outreach

• CS251 : Cryptocurrencies and blockchain technologies. The course covers decentralized applications, consensus protocols, cryptography, and security used in blockchain systems. The course is intended for advanced undergraduate Computer Science students as well as graduate students.
• CS255 : Cryptography. The course is an undergraduate introduction to cryptography and its correct use in real world systems. The course is intended for advanced undergraduates and graduate students.
• EE374 : Scaling blockchains. The course explains how to design blockchains that are decentralized and secure, and at the same time have scalable performance.
• MOOC : Free online cryptography course open to the public. The course provides an overview of cryptography and its correct use in real world systems. The course is self contained.
• Textbook : Free online graduate textbook on applied cryptography. The textbook covers all things cryptographic.

Outreach Activities

The stanford blockchain conference.

Following the success of the previous Stanford blockchain conferences in 2022 , 2020 , 2019 , 2018 , and 2017 , the next conference will be held on Aug. 28-30 2023, at Stanford University.

The Stanford DAO Symposium

A three day online event (May 2-4, 2022) exploring all aspects of DAOs: building a DAO, growing the community, DAO governance, and much more.

A monthly seminar on the latest projects and blockchain research. The seminar is open to the public.

The Stanford Journal of Blockchain Law and Policy

A journal for articles on policy and legal issues about blockchains.

The Real-World Cryptography conference

RWC 2019 will take place on Jan. 9-11, 2019. The conference covers new developments in real-world applications of cryptography.

The Stanford Blockchain Club

The Blockchain Group at the Stanford Law School

The center's research mission is focused on technical aspects of cryptocurrencies and blockchains. We work on research topics that support the thriving ecosystem of projects.

Check out the center's research page .

The center is supported by the leading projects and funds in the space.

Ethereum Foundation

Protocol Labs

Interchain Foundation

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

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Topic Information

Participating journals, topic editors.

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

Recent Trends in Blockchain and Its Applications

Dear Colleagues

Blockchain technology and its applications have significantly progressed since the introduction of Bitcoin in 2008. Today, innovators in various fields have realized the advantages of blockchain. From medicine to finance, many sectors are now looking for ways to integrate blockchain into their infrastructures and technologies. This Special Issue aims to gather high-quality scientific articles on the theoretical and practical aspects of blockchain technologies in the following areas:

• Blockchain applications (finance, medical, global warming, and climate chain, security, lending, insurance, money transfer, real estate, voting, logistics, supply chains, IoT, energy, gaming, etc.);
• Blockchain technology;
• Blockchain and AI;
• Blockchain and big data;
• Blockchain and data mining;
• Public blockchain and its applications;
• Private blockchain and its applications;
• Blockchain security and testing.

Dr. Hossein Hassani Dr. Nadejda Komendantova Topic Editors

• blockchain and its application
• private blockchain
• public blockchain
• data mining
• machine learning
• advanced technology
• intelligence

• Immediately share your ideas ahead of publication and establish your research priority;
• Protect your idea from being stolen with this time-stamped preprint article;
• Enhance the exposure and impact of your research;
• Receive feedback from your peers in advance;
• Have it indexed in Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers (13 papers)

Further Information

Mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

Submit your Manuscript

Submit your abstract.

• Architecture and Design
• Asian and Pacific Studies
• Business and Economics
• Classical and Ancient Near Eastern Studies
• Computer Sciences
• Cultural Studies
• Engineering
• General Interest
• Geosciences
• Industrial Chemistry
• Islamic and Middle Eastern Studies
• Jewish Studies
• Library and Information Science, Book Studies
• Life Sciences
• Linguistics and Semiotics
• Literary Studies
• Materials Sciences
• Mathematics
• Social Sciences
• Sports and Recreation
• Theology and Religion
• Publish your article
• The role of authors
• Promoting your article
• Abstracting & indexing
• Publishing Ethics
• Why publish with De Gruyter
• How to publish with De Gruyter
• Our book series
• Our subject areas
• Your digital product at De Gruyter
• Contribute to our reference works
• Product information
• Tools & resources
• Product Information
• Promotional Materials
• Orders and Inquiries
• FAQ for Library Suppliers and Book Sellers
• Repository Policy
• Free access policy
• Open Access agreements
• Database portals
• For Authors
• Customer service
• People + Culture
• Journal Management
• How to join us
• Working at De Gruyter
• Mission & Vision
• De Gruyter Foundation
• De Gruyter Ebound
• Our Responsibility
• Partner publishers

Your purchase has been completed. Your documents are now available to view.

A Systematic Overview of Blockchain Research

Blockchain has been receiving growing attention from both academia and practices. This paper aims to investigate the research status of blockchain-related studies and to analyze the development and evolution of this latest hot area via bibliometric analysis. We selected and explored 2451 papers published between 2013 and 2019 from the Web of Science Core Collection database. The analysis considers different dimensions, including annual publications and citation trends, author distribution, popular research themes, collaboration of countries (regions) and institutions, top papers, major publication journals (conferences), supportive funding agencies, and emerging research trends. The results show that the number of blockchain literature is still increasing, and the research priorities in blockchain-related research shift during the observation period from bitcoin, cryptocurrency, blockchain, smart contract, internet of thing, to the distributed ledger, and challenge and the inefficiency of blockchain. The findings of this research deliver a holistic picture of blockchain research, which illuminates the future direction of research, and provides implications for both academic research and enterprise practice.

1 Introduction

With the era of bitcoin, digital cash denoted as BTC makes it possible to store and transmit value through the bitcoin network [ 1 ] . And therewith, blockchain, the technology underlying bitcoin, which adopts a peer-to-peer network to authenticate transactions, has been gaining growing attention from practices, especially Libra, a global currency and financial infrastructure launched by Facebook, and digital currency electronic payment. Currently, blockchain is also an increasingly important topic in the academic field. Blockchain research has considerably progressed, attracting attention from researchers, practitioners, and policy-makers [ 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ] .

Considering the huge potential benefits that blockchain would bring in various aspects of industries, for instance, finance and economy [ 10 , 11 , 12 ] , internet of things [ 13 , 14 , 15 ] , energy [ 16 , 17 ] , supply chain [ 18 , 19 ] , and other areas. It is often compared with the Internet and is even referred to as a new form of the Internet. As a result, the number of publications in the blockchain is growing rapidly. According to an initial search on the Web of Science Core Collection, over 2000 scientific papers published are related to blockchain.

Under the circumstances where the number of research publications in the blockchain is quickly increasing, although studies have tried to provide some insights into the blockchain research via literature reviews [ 20 , 21 , 22 , 23 , 24 ] . Comprehensive scientometric analysis of academic articles published in influential journals are beneficial to the further development of blockchain research. This research conducts a bibliometric visualization review and attempts to deliver an overview of the research in this fast-growing field.

The objectives of this research are as follows. First, we intend to build an overview of the distribution of blockchain-related research by time, authors, journals, institutions, countries (regions), and areas in the blockchain academic community. Second, we probe the key research topics of blockchain study, for which purpose, we conduct keyword co-occurrence analysis. Third, we picture the intellectual structure of blockchain study based on co-citation analysis of articles and author co-citation analysis. Finally, we identify the direction for the evolution of blockchain study. We adopt Citespace to detect and visualize emerging trends in blockchain study. To achieve these targets, we posed the following research questions:

Q1: What is the distribution pattern of blockchain publications and citations over recent years? Q2: Which are the main international contributing countries (regions) and institutions in blockchain research, and the collaboration network among them? Q3: What are the characteristics of the authorship distribution pattern? Q4: What are the key blockchain subjects based on the number of publications? Q5: Which are the major journals or conferences for blockchain-related research? Q6: Which are the most influential papers in blockchain research based on the number of citations? Q7: Who are the most influential authors in blockchain research according to the author co-citation network? Q8: What are the research trends in blockchain? Q9: What are the most supportive funding agencies for blockchain research?

Our intended contributions in this research are twofold. First, it is an attempt of adopting co-citation analysis to provide comprehensive and up-to-date developing trends in the lasted hot area, blockchain. Second, this study depicts a state-of-the-art blockchain research development and gives enlightenment on the evolution of blockchain. The findings of this research will be illuminating for both academic researchers, entrepreneurs, as well as policymakers.

The rest of the article is organized as follows. The literature review mainly summarizes related work. The “Data and methodology” section describes the data source and methodological process. The “Results” section presents the main results based on the bibliometric analysis as well as statistical analysis. “Conclusions and implications” conclude this research provides answers to the aforementioned research questions and poses directions for further work.

2 Literature Review

Scientometric analysis, also known as bibliometric network visualization analysis has been widely adopted in numerous areas to identify and visualize the trends in certain fields. For instance, Bonilla, et al. analyzed the development of academic research in economics in Latin America based on a scientometric analysis [ 25 ] . Li, et al. conducted research on emerging trends in the business model study using co-citation analysis [ 26 ] . Gaviriamarin, et al. applied bibliometric analysis to analyze the publications on the Journal of Knowledge Management [ 27 ] .

Since the birth of bitcoin, as the foundation of which, blockchain has gained an increasing amount of attention in academic research and among practices. The research papers focus on the blockchain are quite abundant and are continuing to emerge. Among a host of papers, a few studies investigate the research trend of blockchain-based on a bibliometric analysis [ 22 , 23 , 28 , 29 , 30 ] .

Table 1 presents a summary of these bibliometric studies that summarized some findings on blockchain research, yet very few investigated the co-citation network and the evolution of popular topics in a timeline view. The number of papers these articles analyzed is relatively small, which may be because they used simple retrieval formula in searching blockchain-related articles, and it could pose a threat to bibliometric analysis. Therefore, this research aims to conduct a comprehensive analysis of the status of blockchain research, which is beneficial to future research and practices.

An overview of existing bibliometric studies on blockchain research

Note: NP = number of publications; WOS = Web of Science Core Collection; CNKI = China National Knowledge Infrastructure Databases; EI = EI Compendex, an engineering bibliographic database published by Elsevier; Scopus = Elsevier’s abstract and citation database.

3 Data and Methodology

This section elaborates steps to conduct a comprehensive bibliometric-based analysis: 1) data collection, 2) methodological process. The overall approach and methodology are shown in Figure 1 , the details could be seen as follows.

Research methodology

3.1 Data and Collection

As the leading database for science and literature, the Web of Science Core Collection has been widely used in bibliometrics analysis. It gives access to multidisciplinary information from over 18,000 high impact journals and over 180,000 conference proceedings, which allows for in-depth exploration of the complete network of citations in any field.

For the sake of acquiring enough articles that are relative to the blockchain, we select keywords from Wikipedia and industry information of blockchain, and some existing research literature [ 1 , 20 , 23 , 30 ] . Moreover, in consideration of that, there are a host of blockchain research papers in various fields, in fact, although some papers use keywords in abstract or the main body, blockchain is not the emphasis of the researches. Therefore, in order to get more accurate research results, we choose to conduct a title search instead of a topic search. Table 2 presents the retrieval results with different keywords in the titles, we find that among publications that are relative to the blockchain, the number of Proceeding Papers is the biggest, which is closely followed by articles, and a few reviews. Based on the comparison of five search results in Table 2 . In addition, for accuracy and comprehensiveness, we manually go through the abstract of all the papers form conducting a title search, and choose papers that are related to blockchain. Finally, a dataset with 2451 articles is used in the subsequent analysis.

The dataset we choose has good representativeness, although it may not completely cover all papers on the blockchain, it contains core papers, and in bibliometric analysis, core papers are enough to provide a holistic view for a comprehensive overview of blockchain research.

Blockchain research article characteristics by year from 2013 to 2019

Note: Document type include: Article(A), Proceedings Paper(P), Review(R); Timespan = 2013 ∼ 2019, download in May 31, 2019; Indexes = SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, ESCI, CCR-EXPANDED, IC.

3.2 Methodological Process

The bibliometric approach has received increasing attention in many research domains. In this study, the methodological process mainly includes three methods: 1) descriptive statistical analysis, 2) article co-citation, author co-citation, and cluster analysis on co-cited articles; 3) time-zone analysis on co-cited keywords.

Descriptive statistical analysis displays an overall status of the research development in the target field, which mainly presents an overview by publication years, document types, the research area of published journals, number of citations, and in terms of most cited paper, influential author, institutions and countries. Co-citation analysis helps to identify the frequency of co-cited papers and authors and provides crucial insights into the intellectual structure of certain research fields [ 31 ] . Time-zone analysis helps to understand the flow of information and research trends in the target area [ 32 ] .

Various visualization tools have been designed and developed as computer software such as Citespace and VOSviewer. In this study, we use Citespace for co-citation analysis and timezone analysis, VOSviewer is adopted for social network analysis and visualization, we also apply other tools such as Excel and Tableau for basic statistical analysis and the visualization of the bibliometric results. Notably, in Citespace, core nodes are displayed as “citation tree-rings”, which contain abundant information of an article, for instance, the color of a citation ring denotes the year of corresponding citations, and the rule of colors in Citespace is the oldest in dark blue and newest in light orange with a spectrum of colors in between, the thickness of a ring is proportional to the number of citations in a time slice [ 33 ] . Figure 2 illustrates the details of the citation tree-rings. In addition, Citespace adopts a time-slicing mechanism to produce a synthesized network visualization [ 34 ] .

Citation tree-rings [ 33 ]

4.1 Distribution by Publication Year

Table 3 illustrates several characteristics of blockchain-related publications sorted by the year of publication. The annual number of articles and countries has been growing continuously since the proposing of Nakamoto’s paper in 2008 [ 1 ] , and the first blockchain research paper was published in 2013. By examining the published papers over time, there were only eight articles published in 2013. Afterward, with a continuous increase, a peak of 1,148 articles was published in 2018, and the number of publications is likely to grow ever since. Meanwhile, the annual number of countries taking part in blockchain research has also rapidly increased from 6 to 93 between 2013 and 2017, whereas the average number of Times Cited for single articles declined from 34.00 to 1.73 between 2013 and 2018. Over the observation period, 97 countries took part in the research on the blockchain with a sample of 44 in the H-index of our paper.

Statistical description of Blockchain research article from 2013 to 2019

Note: NP = number of publications; No.CO = number of countries; AV.TC = average number of Times Cited.

Figure 3 presents the cumulative numbers of published articles and citations from 2013 to 2019. There was a drastic increase in the number of papers published annually after 2016. As for the cumulative number of citations, there was no citation of blockchain literature before 2013, and 272 citations in 2013. By 2018, this number has grown over 10,000, which implies a widespread influence and attention of blockchain study in recent years.

Cumulative growth in blockchain publications and citations, 2013–2019

The exponential growth is a typical characteristic of the development of research fields [ 35 ] . The model can be expressed as:

where C is the cumulative number of articles or citations, Y is the publication or citation year, α , and β are parameters. In this study period, the cumulative articles and citations in the filed grow exponentially by R articles  2 = 0.9463 and R citations  2 = 0.8691 respectively. This shows that the research quantity curve of the blockchain is like an exponential function, which means the attention of academic circles on the blockchain has been increasing in recent years.

4.2 Distribution and International Collaboration Among Countries/Regions

A total of 97 countries/areas have participated in blockchain research during the observation period. Table 4 shows the number of articles for each country (region) contributing to publications. Remarkably, an article may be written by several authors from different countries/areas, therefore, the sum of articles published by each country is large than the total number of articles. As can be seen from Table 4 , the USA and China play leading roles amongst all countries/areas observed, with publications of 532 (20.94%) and 489 (19.24%) articles respectively, followed by the UK, which published 214 (8.42%) articles.

Blockchain research country (region) ranked by number of articles (top 25)

Note: NP = number of publications; No.TC = number of total Times Cited; AV.TC = average number of Times Cited; No.CA = number of Citing Articles.

From the perspective of citations, according to country/area distribution in Table 4 , we also find that USA-authored papers were cited by 1,810 papers with 3,709 (36.57%) citations, accounting for 36.57% of total citations. Meanwhile, articles from the USA also have a very high average number of citations per paper with a frequency of 6.97, which ranks third among the top 25 countries/ areas. Interestingly, the articles from Austria and Singapore appeared with the highest average number of citations per paper, with a frequency of 7.44 and 7.16 respectively, whereas the number of publications from these two countries was relatively low compared with the USA. The second was China, following the USA, papers were cited by 753 articles with 1,357 (13.38%) citations. Although the number of articles from China is close to the USA, the average number of citations per paper is lower with a frequency of 2.78. The subsequent countries include the UK, Germany, and Italy. The results indicate that the USA is the most influential country in blockchain.

International collaboration in science research is both a reality and a necessity [ 36 ] . A network consisting of nodes with the collaborating countries (regions) during the observation period is shown in Figure 4 . The network is created with the VOS viewer in which the thickness of the linking lines between two countries (regions) is directly proportional to their collaboration frequency. We can see from Figure 4 that the USA has the closest collaborative relationships with China, the UK, Australia, Germany, and Canada. China has the closest collaborative relationships with the USA, Australia, Singapore, UK, and South Korea. UK has the closest collaborative relationships with the USA, China, France, and Switzerland. Overall, based on the collaboration network, collaboration mainly emerges in highly productive countries (regions).

International collaboration network of the top 25 countries (territories), 2013–2019

4.3 Institution Distribution and Collaboration

A total of 2,190 institutions participated in blockchain-related research, and based on the number of publications, the top 25 of the most productive institutions are shown in Table 5 . Chinese Academy of Sciences had the highest number of publications with 43 papers, followed by the University of London with 42 papers, and Beijing University of Posts Telecommunications ranked third with 36 papers. The subsequent institutions included the University of California System and the Commonwealth Scientific Industrial Research Organization (CSIRO). In terms of the number of total Times Cited, Cornell University is cited most with 499 citations, and the average number of Times Cited is 20.79. Massachusetts Institute of Technology followed closely with 407 citations and with an average number of Times Cited of 22.61. The University of California System ranks third with 258 citations and an average number of Times Cited of 8.06. ETH Zurich ranked fourth with 257 citations and an average number of Times Cited of 10.28. It is notable that the National University of Singapore also had a high average number of Times Cited of 12.56. These results indicate that most of the influential institutions are mainly in the USA and Europe and Singapore. The number of publications from institutions in China is large, whereas few of the papers are highly recorded in average Times Cited. Papers from the National University of Defense Technology China took the highest of average Times Cited of 7.79.

Blockchain research country (territory) ranked by number of articles (top 25)

To further explore data, the top 186 institutions with at least 5 articles each are chosen for collaboration network analysis. The collaboration network map is shown in Figure 5 , the thickness of linking lines between two institutions is directly proportional to their collaboration frequency. As seen from the cooperation network in the Chinese Academy of Sciences, Cornell University, Commonwealth Scientific Industrial Research Organization (CSIRO), University of Sydney, and ETH Zurich cooperated widely with other institutions. This shows that collaboration between institutions may boost the research of blockchain which echoes with extant research that proposes with-institution collaboration and international collaboration may all contribute to article quality [ 37 ] .

Collaboration network for institutions, 2013–2019

4.4 Authorship Distribution

The total number of authors who contribute to the publications of blockchain is 5,862. Remarkably, an article may be written by several authors from different countries (regions) or institutions. Therefore, the total number of authors is bigger than the total number of articles. In fact, during the observation period, the average number of authors per paper is 2.4 articles. Reveals the distribution of the number of authors with different numbers of papers. As seen from the results, most of the authors had a tiny number of papers, i.e., among 5,862 authors, 4,808 authors have only one paper, 662 authors have two papers, and 213 authors have three papers.

According to the participation number of articles, the most productive author in the blockchain is Choo, Kim-Kwang Raymond from Univ Texas San Antonio, who took part in 14 articles in blockchain, followed by Marchesi, Michele from Univ of Cagliari, who took part in 13 articles related to blockchain. The third most productive author is Bouri, Elie from the Holy Spirit University of Kaslik, and David Roubaud from Montpellier Business School. Miller, Andrew, Shetty, Sachin, and Xu, Xiwei ranked fourth, who took part in 10 articles related to blockchain.

The distribution of number of author with different numbers of articles

Note: No.AU = number of author; No.AR = number of articles.

Figure 6 displays the collaboration network for authors. The thickness of the linking lines between the two authors is directly proportional to their collaboration frequency. As we can see from Figure 6 , it indicates the most productive authors cooperate widely with others.

Collaboration network for authors, 2013–2019

4.5 Distribution of Subject Categories

Table 7 presents the top 25 blockchain categories ranked in terms of the number of articles published. As can be seen from Table 7 , among the top 10 categories, six are related to the Computer Science field, which indicates that blockchain-related researches are more abundant in the field of Computer Science compared with other research fields. Besides, there are also publications in the category of Business & Economics with 385 records.

The top 25 blockchain categories ranked by the number of publications

Figure 7 illustrates the betweenness centrality network of papers of the above categories by using Citespace after being simplified with Minimum Spanning Tree network scaling, which remains the most prominent connections. We can see from Figure 7 , the centrality of Computer Science, Engineering Electrical Electronic, Telecommunications, Engineering, and Business & Economics are notable.

Categories involved in blockchain, 2013–2019

4.6 Journal Distribution

The research of blockchain is published in 1,206 journals (conferences), the top 25 journals (conferences) are displayed in Table 8 . Blockchain research papers are concentrated in these top journals (conferences) and with a concentration ratio of nearly 20%. The major blockchain research journals include Lecture Notes in Computer Science, IEEE Access, Economics Letters, Future Generation Computer Systems, and Finance Research Letters, with more than 20 articles in each one. Meanwhile, the major blockchain research conferences include IEEE International Conference on Hot Information-Centric Networking, International Conference on Parallel and Distributed Systems Proceedings, International Conference on New Technologies Mobility, and Security, and Financial Cryptography and Data Security, with at least 14 articles published in each of these.

The top 25 blockchain publication journals (conferences)

Note: NP = number of papers; No.TC = number of total Times Cited; Italic represents conference.

4.7 Intellectual Structure of Blockchain

Since the notion of co-citation was introduced, there are a host of researchers have adopted the visualization of co-citation relationships. The work is followed by White and Griffith [ 38 ] , who identified the intellectual structure of science, researches then broaden the unit of analysis from articles to authors [ 39 , 40 ] . There are two major types of co-citation analysis, namely, article cocitation analysis and author co-citation analysis, which are commonly adopted to visualize the intellectual structure of the research field. In this study, we explore the intellectual structure of blockchain by using both article co-citation analysis and author co-citation analysis. We apply Citespace to analyze and visualize the intellectual structure [ 41 ] .

In this study, mining spanning trees was adopted to present the patterns in the author cocitation network, a visualization of the network of author co-citation is demonstrated in Figure 8 . In the visualization of the co-citation network, pivot points are highlighted with a purple ring, and landmark nodes are identified with a large radius. From Figure 8 , there are six pivot nodes and landmark nodes: Nakamoto S, Buterin V, Eyal I, Wood G, Swan M, Christidis K. These authors truly played crucial roles during the development of blockchain research. Table 9 shows the ranking of author citation counts, as well as their prominent publications.

Network of author co-citation, 2013–2019

The top 15 co-cited author ranked by citation counts

Nakamoto S, as the creator of bitcoin, authored the bitcoin white paper, created and deployed bitcoin’s original reference implementation, is not surprised at the top of the co-citation count ranking, and has 1,202 citations in our dataset. Buterin V, a Russian-Canadian programmer, and writer primarily are known as a co-founder of ethereum and as a co-founder of Bitcoin Magazine, follows Nakamoto S, receives 257 citations. Eyal I, an assistant professor in technion, is a third of the ranking, with a representative article is “majority is not enough: Bitcoin mining is vulnerable”. Wood G, the ethereum founder, and free-trust technologist ranks fourth with 244 citations. The other core author with high citations includes Swan M, Christidis K, Bonneau J, Szabo N, Zyskind G, Castro M, and Meiklejohn S, with more than 150 citations of each person, and the typical publications of there are present in Table 9 .

To further investigate the features of the intellectual structure of blockchain research, we conducted an article co-citation analysis, using cluster mapping of co-citation articles networks to complete a visualization analysis of the evolution in the research field of blockchain. According to the article co-citation network, we adopted Citespace to divide the co-citation network into several clusters of co-cited articles. The visualization of clusters of co-cited articles is displayed in Figure 9 .

Clusters of co-cited articles, 2013–2019

As we mentioned earlier in the “Data and Methodology” section, the colors of citation rings and links are corresponding to the different time slices. Therefore, the deeper purple cluster (Cluster #1) is relatively old, and the prominent clusters (Cluster #0 and #2) are more recent. Cluster #0 is the youngest and Cluster #1 is the oldest. Cluster labels are identified based on burst terms extracted from titles, abstracts, keywords of bibliographic records [ 26 , 41 ] . Table 10 demonstrates six predominant clusters by the number of members in each cluster.

Results show that the research priorities of the clusters keep changing during the observation period. From the earlier time (Cluster # 1), bitcoin and bitcoin network are the major priorities of researchers, then some researchers changed the focuses onto cryptocurrency in blockchain research. Notably, more researchers are most interested in blockchain technology and public ledger recently.

According to the characteristics of pivot nodes and landmark nodes in the co-citation article network. The landmark and pivot nodes in co-citation articles are shown in Figure 10 , Five pivot nodes are Nakamoto S [ 1 ] , Wood G [ 44 ] , Kosba A [ 51 ] , Eyal I [ 12 ] and Maurer B [ 55 ] . The main landmark nodes are Christidis K [ 45 ] . Swan M [ 2 ] , Zyskind G [ 48 ] Nakamoto S [ 1 ] , Kosba A [ 51 ] , Notably, some nodes can be landmark and pivot at the same time.

Landmark and pivot nodes, 2013–2019

Summary of the largest 6 blockchain clusters

Details of the largest cluster (Cluster #0, top10)

Details of the largest cluster (Cluster #1, top10)

Details of the largest cluster (Cluster #2, top10)

As seen from Table 10 , Cluster #0 is the largest cluster, containing 36 nodes, for the sake of obtaining more information about these clusters, we explored the details of the largest clusters. Table 11 illustrates the details of the Cluster 0#.

We also explored Cluster #1 and #2 in more detail. Table 12 and Table 13 present the details of Cluster #1 and Cluster #2 respectively, it is notable that the most active citation in Cluster #1 is “bitcoin: A peer-to-peer electronic cash system”, and the most active citation in Cluster #2 is “bitcoin: Economics, technology, and governance”. The core members of Cluster #1 and Cluster #2 deliver milestones of blockchain research related to the bitcoin system and cryptocurrency.

Table 14 lists the first 10 most cited blockchain research articles indexed by the Web of Science. These articles are ranked according to the total number of citations during the observation period. Among these articles, the publication of “blockchains and smart contracts for the internet of things” by Christidis is identified as the most cited paper of 266 citations. The paper also has the highest average number of citations per year.

The top 10 cited blockchain articles

4.8 Keywords Co-Citation Analysis

According to Callon, et al. [ 77 ] co-word analysis is a useful way of examining the evolution of science. In our study, among 2,451 articles related to blockchain, we obtained 4,834 keywords, 594 keywords appeared 3 times, 315 keywords appeared 5 times, and 130 keywords appeared 10 times. Table 15 presents the most important keywords according to frequency. As seen, ‘blockchain’ ranks first with an occurrence frequency of 1,105, followed by ‘bitcoin’ of 606. The other high occurrence frequency keywords include: ‘cryptocurrency’, ‘smart contract’, and ‘iot’ (internet of thing).

The top 25 keywords ranked by frequency

For the sake of further exploration of the relation amongst the major keywords in blockchain research papers, we adopted the top 315 keywords with a frequency no less than 5 times for co-occurrence network analysis. The keywords co-occurrence network is illustrated in Figure 11 . In a co-occurrence network, the size of the node represents the frequency of the keywords co-occurrence with other keywords. The higher the co-occurrence frequency of the two keywords, the closer the relationship between them.

The keywords co-occurrence network, 2013–2019

We can see from Figure 11 , the size of blockchain and bitcoin are the largest among all keywords. This means, in general, blockchain and bitcoin have more chances to co-occurrence with other keywords. Besides, blockchain is closer with a smart contract, iot, Ethereum, security, internet, and privacy, whereas bitcoin is closer with digital currency and cryptocurrency.

Figure 12 displays the time-zone view of co-cited keywords, which puts nodes in order from left to right according to their years being published. The left-sided nodes were published in the last five years, and on the right-hand side, they were published in recent two years. Correspondingly, some pivot nodes of keywords are listed in the boxes. We hope to show the evolution of blockchain in general and the changes of focuses in blockchain study.

The time-zone view of co-cited keywords, 2013–2019

The results suggest that, in 2013, when blockchain research begins to surface, bitcoin dominated the blockchain research field. Reasonably, the bitcoin is the first cryptocurrency based on blockchain technology, and the influential essays include quantitative analysis of the full bitcoin transaction graph [ 54 ] ; a fistful of bitcoins: Characterizing payments among men with no

names [ 50 ] ; and bitcoin meets google trends and Wikipedia: Quantifying the relationship between phenomena of the internet era [ 69 ] . Afterward, as various altcoins appeared, cryptocurrency and digital currency are widely discussed in blockchain-related research. The high-citation article is Zerocash: Decentralized anonymous payments from bitcoin [ 74 ] and privacy, which is the prominent characteristic of cryptocurrency. In 2015, blockchain and smart contract become a hotspot, the core publications include blockchain: A blueprint for a new economy [ 2 ] ; decentralizing privacy: Using blockchain to protect personal data [ 48 ] ; at the same time, some researchers also focus on the volatility and mining of cryptocurrency. In 2016, a growing number of researchers focus on the internet of things. The most popular article is blockchains and smart contracts for the internet of things [ 45 ] . In 2017, distributed ledger and blockchain technology become a research focus point. From 2018 onward, research focus on the challenge, and the inefficiency of blockchain appear.

4.9 Funding Agencies of Blockchain-Related Research

Based on all 2451 funding sources we analyzed in this study, the National Natural Science Foundation of China (NSFC) has supported the biggest number of publications with 231 papers, followed by the National Key Research and Development Program of China, which supported the publication of 88 papers. Comparatively, the National Science Foundation of the USA has only supported 46 papers. It is remarkable that the “Ministry of Science and Technology Taiwan” supported 22 papers, which is more than the European Union. Table 16 illustrates the top 20 funding agencies for blockchain research ranked by the number of supported papers. The results indicate that China is one of the major investing countries in Blockchain research with the biggest number of supporting articles.

The top 20 funding agencies of blockchain-related research

5 Conclusions and Implications

5.1 conclusions.

This research comprehensively investigates blockchain-related publications based on the Web of Science Core Collection and provides a quick overview of blockchain research. In this study, a coherent comprehensive bibliometric evaluation framework is adopted to investigate the hot and promising blockchain domain. We outline the core development landscape of blockchain, including the distribution of publications over time, by authors, journals, categories, institutions, countries (territories), intellectual structure, and research trends in the blockchain academic community. Combining the results of statistical analysis and co-cited articles, authors, and keywords, we formulate the answers to the following research questions:

RQ1 What is the distribution pattern of blockchain publications and citations over recent years?

The published blockchain papers significantly increased since 2013, when the first blockchain paper was published. An increasing number of articles were published since. In 2018, 1,148 articles were published at the peak, and the number of publications is likely to continuously grow. As for the cumulative number of citations, there were only 272 citations in 2013. By 2018 this number has grown to more than 10,000, which implies a widespread influence and attention attracted by blockchain study in recent years.

RQ2 Which are the main international contributing countries (regions) and institutions in blockchain research, as well as collaboration networks among them?

A total of 97 countries (regions) participated in blockchain research during the observation period. USA and China play the leading roles among all countries (regions), with publications of 532 (20.94%) and 489 (19.24%) articles respectively, followed by the UK, Germany, Italy, and Australia. From the aspect of citations, USA-authored papers were cited by 1,810 papers with 3,709 (36.57%) citations, accounting for 36.57% of total citations. Articles from the USA also have a very high average number of citations per paper with a frequency of 6.97. Although the number of articles from China is close to the USA, the average number of citations per paper is lower with a frequency of 2.78. The results indicate that the USA is the most influential country in the field of blockchain.

A total of 2,190 institutions participated in blockchain-related research. Among them, the Chinese Academy of Sciences has the highest number of publications with 43 papers, followed by the University of London, Beijing University of Posts Telecommunications, University of California System, Commonwealth Scientific Industrial Research Organization (CSIRO), Beihang University, University of Texas System, ETH Zurich. In respect of the number of total Times Cited and the average number of Times Cited, Cornell University is cited the most with 499 citations, and the average number of Times Cited is 20.79. followed by the Massachusetts Institute of Technology, University of California System, and ETH Zurich. The number of publications forms institutions in China is large, whereas few papers own high average Times Cited.

In terms of collaboration networks among different institutions, we found that the Chinese Academy of Sciences, Cornell University, Commonwealth Scientific Industrial Research Organization (CSIRO), University of Sydney, and ETH Zurich cooperated widely with other institutions.

RQ3 What are the characteristics of the authorship distribution?

The total number of authors who contribute to the publications of blockchain is 5,862. the average number of authors per paper is 2.4. Among 5,862 authors, 4,808 authors have only one paper, 662 authors have two papers, and 213 authors have three papers. Based on the number of participated papers, the most productive author in the field of blockchain is Choo, Kim-Kwang Raymond from Univ Texas San Antonio, who participated in 14 articles in the field of blockchain, followed by Marchesi M, Bouri E, David R, Miller A, Shetty S and Xu X.

RQ4 What are the core blockchain subjects and journals based on the number of publications?

Blockchain-related researches are more abundant in the field of Computer Science compared with other categories. Other major fields include Engineering, Business & Economics, Telecommunications, and Business & Economics.

RQ5 What are the major journals or conferences for blockchain-related research?

The research of blockchain is published in 1,206 journals (conferences), the major blockchain research journals include Lecture Notes In Computer Science, IEEE Access, Economics Letters, Future Generation Computer Systems, and Finance Research Letters. Meanwhile, the major blockchain research conferences include IEEE International Conference on Hot Information-Centric Networking, International Conference on Parallel and Distributed Systems Proceedings, International Conference on New Technologies Mobility and Security, and Financial Cryptography and Data Security.

RQ6 What are the most influential papers in blockchain research based on the number of citations?

Ranked by the total number of citations during the observation period, the publication: “blockchains and smart contracts for the internet of things” by Christidis and Devetsikiotis [ 45 ] is identified as the most cited paper with 266 citations, which also has a highest average number of citation per year, followed by decentralizing privacy: Using blockchain to protect personal data [ 48 ] with 169 citations and 33.80 average number of citations per year.

According to the number of times co-cited, the top five influential publications are as follows: Bitcoin: A peer-to-peer electronic cash system [ 1 ] , A next-generation smart contract and decentralized application platform [ 42 ] , Majority is not enough: Bitcoin mining is vulnerable [ 12 ] , Ethereum: A secure decentralised generalised transaction ledger [ 44 ] , Blockchain: Blueprint for a new economy [ 2 ] .

RQ7 Who are the most influential authors in blockchain research according to the author co-citation network?

Some authors played a crucial role during the development of blockchain research, Nakamoto S, as the creator of Bitcoin, and the author of the bitcoin white paper, created and deployed bitcoin’s original reference, therefore is not surprised at the top of the co-citation count ranking and got 1,202 citations in our dataset. Buterin V, a Russian-Canadian, programmer, and writer, primarily known as a co-founder of Ethereum and as a co-founder of Bitcoin Magazine who follows Nakamoto S and receives 257 citations. Other core authors with high citations include Eyal I, Wood G, Swan M, Christidis K, Bonneau J, Szabo N, Zyskind G, Castro M, and Meiklejohn S.

According to co-cited articles clusters, the research priorities in blockchain-related research keep changing during the observation period. Bitcoin and bitcoin network are the main priorities of researchers, then some researchers changed to focus on cryptocurrency in blockchain research.

RQ8 What are the research trends of blockchain?

The research priorities in blockchain-related research evolve during the observation period. As early as 2013, when the research on blockchain first appears, bitcoin dominated the blockchain research field. Then only one year later, as various altcoins begin to appear, cryptocurrency and digital currency are widely discussed in blockchain-related research. In 2015, blockchain and smart contracts become a hotspot till 2016 when a growing body of researches begin to focus on the internet of things. In 2017, distributed ledger and blockchain technology become the research focal point. From 2018 onward, research focus on the challenge and inefficiency of blockchain.

RQ9 What are the most supportive funding agencies of blockchain research?

The most supportive funding agency of blockchain research is the National Natural Science Foundation of China (NSFC) which has supported the publication of 231 papers. The results indicate that China is one of the major investing countries in Blockchain research with the biggest number of supporting articles.

Given the potential power of blockchain, it is noticeable that governments, enterprises, and researchers all pay increasing attention to this field. The application of blockchain in various industries, the supervision of cryptocurrencies, the newly rising central bank digital currency and Libra, are becoming the central issues of the whole society.

In our research, we conducted a comprehensive exploration of blockchain-related research via a bibliometrics analysis, our results provide guidance and implications for academic research and practices. First, the findings present a holistic view of research in the blockchain domain which benefits researchers and practitioners wanting to quickly obtain a visualized overview of blockchain research. Second, according to our findings of the evolution and trends in blockchain research, researchers could better understand the development and status of blockchain, which is helpful in choosing valuable research topics, the distributed ledger, the discussions on the inefficiency and challenges of blockchain technology, the supervision of cryptocurrencies, the central bank digital currency are emerging research topics, which deserve more attention from the academic community.

5.2 Limitations and Future Work

As with any research, the design employed incorporates limitations that open avenues for future research. First, this study is based on 2,451 articles retrieved from the Web of Science of Core Collection, although the Web of Science of Core Collection is truly a powerful database for bibliometric analysis, we can’t ignore the limitation brought by a unique data source. Future research can deal with this limitation by merging the publications from other sources, for instance, Scopus, CNKI, as well as patent database and investment data of blockchain, and it could help to validate the conclusion. Second, we mainly adopt the frequency indicator to outline the state-of-the art of blockchain research, although the frequency is most commonly used in the bibliometric analysis, and we also used H-index, citation to improve our analysis, some other valuable indicators are ignored, such as sigma and between centrality, therefore, it’s beneficial to combine those indicators in future research. Besides, it should be noted that, in co-citation analysis, a paper should be published for a certain period before it is cited by enough authors [ 26 ] , the newest published papers may not include in co-citation analysis, it’s also an intrinsic drawback of bibliometric methods.

Supported by the National Natural Science Foundation of China (71872171), and the Open Project of Key

Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences

[1] Nakamoto S. Bitcoin: A peer-to-peer electronic cash system. https://bitcoin.org/bitcoin.eps 2008. Search in Google Scholar

[2] Swan M. Blockchain: Blueprint for a new economy. O’Reilly, 2015. Search in Google Scholar

[3] Weber I, Xu X, Riveret R, et al. Untrusted business process monitoring and execution using blockchain. Business Process Management, 2016: 329–347. 10.1007/978-3-319-45348-4_19 Search in Google Scholar

[4] Mettler M. Blockchain technology in healthcare: The revolution starts here. International Conference on E-health Networking, Applications and Services, 2016: 1–3. 10.1109/HealthCom.2016.7749510 Search in Google Scholar

[5] Paech P. The governance of blockchain financial networks. Modern Law Review, 2016, 80(6): 1073–1110. 10.1111/1468-2230.12303 Search in Google Scholar

[6] Yue X, Wang H, Jin D, et al. Healthcare data gateways: Found healthcare intelligence on blockchain with novel privacy risk control. Journal of Medical Systems, 2016, 40(10): 1–8. 10.1007/s10916-016-0574-6 Search in Google Scholar PubMed

[7] Maupin J. Mapping the global legal landscape of blockchain and other distributed ledger technologies. https://ssrn.com/abstract=2930077 2017. 10.2139/ssrn.2930077 Search in Google Scholar

[8] Sachin K, Angappa G, Himanshu A. Understanding the blockchain technology adoption in supply chains. International Journal of Production Research, 2018: 1–25. Search in Google Scholar

[9] Tasca P, Tessone C J. A taxonomy of blockchain technologies: Principles of identification and classification. Ledger, 2019, 4: 140. 10.5195/ledger.2019.140 Search in Google Scholar

[10] Catalini C, Gans J S. Some simple economics of the blockchain. Communications of the ACM, 2016, 63(7): 80–90. 10.3386/w22952 Search in Google Scholar

[11] Csoka P, Herings P J. Decentralized clearing in financial networks. Management Science, 2017, 64(5): 4681–4699. 10.1287/mnsc.2017.2847 Search in Google Scholar

[12] Eyal I. Blockchain technology: Transforming libertarian cryptocurrency dreams to finance and banking realities. Computer, 2017, 50(9): 38–49. 10.1109/MC.2017.3571042 Search in Google Scholar

[13] Huckle S, Bhattacharya R, White M, et al. Internet of things, blockchain and shared economy applications. Procedia Computer Science, 2016: 461–466. 10.1016/j.procs.2016.09.074 Search in Google Scholar

[14] Bahga A, Madisetti V K. Blockchain platform for industrial internet of things. Journal of Software Engineering and Applications, 2016, 9(10): 533–546. 10.4236/jsea.2016.910036 Search in Google Scholar

[15] Dorri A, Kanhere S S, Jurdak R. Towards an optimized blockchain for IoT. IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation (IoTDI), 2017: 173–178. 10.1145/3054977.3055003 Search in Google Scholar

[16] Aitzhan N Z, Svetinovic D. Security and privacy in decentralized energy trading through multi-signatures, blockchain and anonymous messaging streams. IEEE Transactions on Dependable and Secure Computing, 2018, 15(5): 840–852. 10.1109/TDSC.2016.2616861 Search in Google Scholar

[17] Mengelkamp E, Notheisen B, Beer C, et al. A blockchain-based smart grid: Towards sustainable local energy markets. Computer Science — Research and Development, 2018: 207–214. 10.1007/s00450-017-0360-9 Search in Google Scholar

[18] Korpela K, Hallikas J, Dahlberg T. Digital supply chain transformation toward blockchain integration. Hawaii International Conference on System Sciences, 2017: 1–10. 10.24251/HICSS.2017.506 Search in Google Scholar

[19] Toyoda K, Mathiopoulos P T, Sasase I, et al. A novel blockchain-based product ownership management system (POMS) for anti-counterfeits in the post supply chain. IEEE Access, 2017: 17465–17477. 10.1109/ACCESS.2017.2720760 Search in Google Scholar

[20] Yuan Y, Wang F Y. Blockchain: The state of the art and future trends. Acta Automatica Sinica, 2016, 42(4): 481–494. Search in Google Scholar

[21] Yli-Huumo J, Ko D, Choi S, et al. Where is current research on blockchain technology? — A systematic review. PLoS One, 2016, 11(10): e0163477. 10.1371/journal.pone.0163477 Search in Google Scholar PubMed PubMed Central

[22] Zeng S, Ni X. A bibliometric analysis of blockchain research. IEEE Intelligent Vehicles Symposium, 2018: 102–107. 10.1109/IVS.2018.8500606 Search in Google Scholar

[23] Miau S, Yang J. Bibliometrics-based evaluation of the blockchain research trend: 2008–2017. Technology Analysis & Strategic Management, 2018, 30(9): 1029–1045. 10.1080/09537325.2018.1434138 Search in Google Scholar

[24] Hawlitschek F, Notheisen B, Teubner T. The limits of trust-free systems: A literature review on blockchain technology and trust in the sharing economy. Electronic Commerce Research and Applications, 2018: 50–63. 10.1016/j.elerap.2018.03.005 Search in Google Scholar

[25] Bonilla C A, Merigo J M, Torres-Abad C. Economics in Latin America: A bibliometric analysis. Scientometrics, 2015, 105(2): 1239–1252. 10.1007/s11192-015-1747-7 Search in Google Scholar

[26] Li X, Qiao H, Wang S. Exploring evolution and emerging trends in business model study: A co-citation analysis. Scientometrics, 2017, 111(2): 869–887. 10.1007/s11192-017-2266-5 Search in Google Scholar

[27] GaviriamarinM,Merigo JM, Popa S. Twenty years of the journal of knowledge management: A bibliometric analysis. Journal of Knowledge Management, 2018, 22(8): 1655–1687. 10.1108/JKM-10-2017-0497 Search in Google Scholar

[28] Faming W, Meijuan Z. Bibliometric analysis on the research hotspots of blockchain in China. Journal of Intelligence, 2017, 36(12): 69–74. Search in Google Scholar

[29] Mu-Nan L. Analyzing intellectual structure of related topics to blockchain and bitcoin: From co-citation clustering and bibliographic coupling perspectives. Acta Automatica Sinica, 2017, 43(9): 1501–1519. Search in Google Scholar

[30] Dabbagh M, Sookhak M, Safa N S. The evolution of blockchain: A bibliometric study. IEEE Access, 2019: 19212–19221. 10.1109/ACCESS.2019.2895646 Search in Google Scholar

[31] Chen C, Ibekwesanjuan F, Hou J. The structure and dynamics of co citation clusters: A multiple perspective co-citation analysis. Journal of the Association for Information Science and Technology, 2010, 61(7): 1386–1409. Search in Google Scholar

[32] Chen C. Visualizing scientific paradigms: An introduction. Journal of the Association for Information Science and Technology, 2003, 54(5): 392–393. 10.1002/asi.10224 Search in Google Scholar

[33] Chen C. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the Association for Information Science and Technology, 2006, 57(3): 359–377. 10.1002/asi.20317 Search in Google Scholar

[34] Chen C, Morris S A. Visualizing evolving networks: Minimum spanning trees versus pathfinder networks. IEEE Symposium on Information Visualization, 2003: 67–74. Search in Google Scholar

[35] Guan J, Ma N. China’s emerging presence in nanoscience and nanotechnology: A comparative bibliometric study of several nanoscience giants. Research Policy, 2007, 36(6): 880–886. 10.1016/j.respol.2007.02.004 Search in Google Scholar

[36] Wagner C S, Leydesdorff L. Network structure, self-organization, and the growth of international collaboration in science. Research Policy, 2005, 34(10): 1608–1618. 10.1016/j.respol.2005.08.002 Search in Google Scholar

[37] He Z, Geng X, Campbellhunt C. Research collaboration and research output: A longitudinal study of 65 biomedical scientists in a New Zealand University. Research Policy, 2009, 38(2): 306–317. 10.1016/j.respol.2008.11.011 Search in Google Scholar

[38] White H D, Griffith B C. Author cocitation: A literature measure of intellectual structure. Journal of the American Society for Information Science, 1981, 32(3): 163–171. 10.1002/asi.4630320302 Search in Google Scholar

[39] Chen C. Searching for intellectual turning points: Progressive knowledge domain visualization. Proceedings of the National Academy of Sciences of the United States of America, 2004: 5303–5310. 10.1073/pnas.0307513100 Search in Google Scholar PubMed PubMed Central

[40] Borner K, Chen C, Boyack K W. Visualizing knowledge domains. The Artist and Journal of Home Culture, 2005, 37(1): 179–255. 10.1002/aris.1440370106 Search in Google Scholar

[41] Chen C. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the Association for Information Science and Technology, 2006, 57(3): 359–377. 10.1002/asi.20317 Search in Google Scholar

[42] Buterin V. A next-generation smart contract and decentralized application platform. https://ethereum.org/en/whitepaper/ 2014. Search in Google Scholar

[43] Eyal I, Sirer E G. Majority is not enough: Bitcoin mining is vulnerable. International Conference on Financial Cryptography and Data Security, 2014: 436–454. 10.1145/3212998 Search in Google Scholar

[44] Wood G. Ethereum: A secure decentralised generalised transaction ledger. Ethereum Project Yellow Paper, 2014, 151: 1–32. Search in Google Scholar

[45] Christidis K, Devetsikiotis M. Blockchains and smart contracts for the internet of things. IEEE Access, 2016: 2292–2303. 10.1109/ACCESS.2016.2566339 Search in Google Scholar

[46] Bonneau J, Miller A, Clark J, et al. Sok: Research perspectives and challenges for bitcoin and cryptocurrencies. IEEE Symposium on Security and Privacy, 2015: 104–121. 10.1109/SP.2015.14 Search in Google Scholar

[47] Szabo N. Formalizing and securing relationships on public networks. First Monday, 1997. 10.5210/fm.v2i9.548 Search in Google Scholar

[48] Zyskind G, Nathan O, Pentland A. Decentralizing privacy: Using blockchain to protect personal data. IEEE Security and Privacy Workshops, 2015: 180–184. 10.1109/SPW.2015.27 Search in Google Scholar

[49] Castro M, Liskov B. Practical byzantine fault tolerance and proactive recovery. ACM Transactions on Computer Systems (TOCS), 2002, 20(4): 398–461. 10.1145/571637.571640 Search in Google Scholar

[50] Meiklejohn S, Pomarole M, Jordan G, et al. A fistful of bitcoins: Characterizing payments among men with no names. Internet Measurement Conference, 2013: 127–140. 10.1145/2504730.2504747 Search in Google Scholar

[51] Kosba A, Miller A, Shi E, et al. Hawk: The blockchain model of cryptography and privacy-preserving smart contracts. IEEE Symposium on Security and Privacy, 2016: 839–858. 10.1109/SP.2016.55 Search in Google Scholar

[52] Reid F, Harrigan M. An analysis of anonymity in the bitcoin system. Security and Privacy in Social Networks, 2013: 197–223. 10.1109/PASSAT/SocialCom.2011.79 Search in Google Scholar

[53] Luu L, Narayanan V, Zheng C, et al. A secure sharding protocol for open blockchains. ACM SIGSAC Conference on Computer and Communications Security, 2016: 17–30. 10.1145/2976749.2978389 Search in Google Scholar

[54] Ron D, Shamir A. Quantitative analysis of the full bitcoin transaction graph. International Conference on Financial Cryptography and Data Security, 2013: 6–24. 10.1007/978-3-642-39884-1_2 Search in Google Scholar

[55] Maurer B, Nelms T C, Swartz L. When perhaps the real problem is money itself? The practical materiality of bitcoin. Social Semiotics, 2013, 23(2): 261–277. 10.1080/10350330.2013.777594 Search in Google Scholar

[56] Tschorsch F, Scheuermann B. Bitcoin and beyond: A technical survey on decentralized digital currencies. IEEE Communications Surveys & Tutorials, 2016, 18(3): 2084–2123. 10.1109/COMST.2016.2535718 Search in Google Scholar

[57] Radziwill N. Blockchain revolution: How the technology behind bitcoin is changing money, business, and the world. The Quality Management Journal, 2018, 25(1): 64–65. 10.1080/10686967.2018.1404373 Search in Google Scholar

[58] Azaria A, Ekblaw A, Vieira T, et al. Medrec: Using blockchain for medical data access and permission management. International Conference on Open and Big Data (OBD), 2016: 25–30. 10.1109/OBD.2016.11 Search in Google Scholar

[59] Narayanan A, Bonneau J, Felten E, et al. Bitcoin and cryptocurrency technologies: A comprehensive introduction. Princeton University Press, 2016. Search in Google Scholar

[60] Miers I, Garman C, Green M, et al. Zerocoin: Anonymous distributed e-cash from bitcoin. IEEE Symposium on Security and Privacy, 2013: 397–411. 10.1109/SP.2013.34 Search in Google Scholar

[61] Ober M, Katzenbeisser S, Hamacher K. Structure and anonymity of the bitcoin transaction graph. Future Internet, 2013, 5(2): 237–250. 10.3390/fi5020237 Search in Google Scholar

[62] Moore T, Christin N. Beware the middleman: Empirical analysis of bitcoin-exchange risk. International Conference on Financial Cryptography and Data Security, 2013: 25–33. 10.1007/978-3-642-39884-1_3 Search in Google Scholar

[63] Androulaki E, Karame G O, Roeschlin M, et al. Evaluating user privacy in bitcoin. International Conference on Financial Cryptography and Data Security, 2013: 34–51. 10.1007/978-3-642-39884-1_4 Search in Google Scholar

[64] Barber S, Boyen X, Shi E, et al. Bitter to better — How to make bitcoin a better currency. International International Conference on Financial Cryptography and Data Security, 2012: 399–414. 10.1007/978-3-642-32946-3_29 Search in Google Scholar

[65] Böhme R, Christin N, Edelman B, et al. Bitcoin: Economics, technology, and governance. Journal of Economic Perspectives, 2015, 29(2): 213–238. 10.1257/jep.29.2.213 Search in Google Scholar

[66] Cheah E T, Fry J. Speculative bubbles in bitcoin markets? An empirical investigation into the fundamental value of bitcoin. Economics Letters, 2015, 130: 32–36. 10.1016/j.econlet.2015.02.029 Search in Google Scholar

[67] Urquhart A. The inefficiency of bitcoin. Economics Letters, 2016, 148: 80–82. 10.1016/j.econlet.2016.09.019 Search in Google Scholar

[68] Dyhrberg A H. Bitcoin, gold and the dollar — A GARCH volatility analysis. Finance Research Letters, 2016, 16: 85–92. 10.1016/j.frl.2015.10.008 Search in Google Scholar

[69] Ciaian P, Rajcaniova M, Kancs D A. The economics of bitcoin price formation. Applied Economics, 2016, 48(19): 1799–1815. 10.1080/00036846.2015.1109038 Search in Google Scholar

[70] Kristoufek L. BitCoin Meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the internet era. Scientific Reports, 2013, 3(1): 3415–3415. 10.1038/srep03415 Search in Google Scholar PubMed PubMed Central

[71] Dwyer G P. The economics of bitcoin and similar private digital currencies. Journal of Financial Stability, 2015, 17: 81–91. 10.1016/j.jfs.2014.11.006 Search in Google Scholar

[72] Nadarajah S, Chu J. On the inefficiency of bitcoin. Economics Letters, 2017, 150: 6–9. 10.1016/j.econlet.2016.10.033 Search in Google Scholar

[73] Katsiampa P. Volatility estimation for bitcoin: A comparison of GARCH models. Economics Letters, 2017, 158: 3–6. 10.1016/j.econlet.2017.06.023 Search in Google Scholar

[74] Bouri E, Gupta R, Tiwari A K, et al. Does bitcoin hedge global uncertainty? Evidence from wavelet-based quantile-in-quantile regressions. Finance Research Letters, 2017, 23: 87–95. 10.1016/j.frl.2017.02.009 Search in Google Scholar

[75] Sasson E B, Chiesa A, Garman C, et al. Zerocash: Decentralized anonymous payments from bitcoin. IEEE Symposium on Security and Privacy, 2014: 459–474. 10.1109/SP.2014.36 Search in Google Scholar

[76] Garay J, Kiayias A, Leonardos N. The bitcoin backbone protocol: Analysis and applications. International Conference on the Theory and Applications of Cryptographic Techniques, 2015: 281–310. 10.1007/978-3-662-46803-6_10 Search in Google Scholar

[77] Callon M, Courtial J P, Laville F. Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics, 1991, 22(1): 155–205. 10.1007/BF02019280 Search in Google Scholar

© 2021 Walter de Gruyter GmbH, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

• X / Twitter

Supplementary Materials

Please login or register with De Gruyter to order this product.

Journal and Issue

Articles in the same issue.

REVIEW article

How blockchain technology can benefit marketing: six pending research areas.

• 1 Doctoral School of Regional Sciences and Business Administration, Széchenyi István University, Győr, Hungary
• 2 Henley Business School, University of Reading Greenlands, Henley-on-Thames, United Kingdom
• 3 Department of International Management, Modul University Vienna, Vienna, Austria

The proliferation of sophisticated e-commerce platforms coupled with mobile applications has ignited growth in business-to-consumer (B2C) commerce, reshaped organizational structures, and revamped value creation processes. Simultaneously, new technologies have altered the dynamics of brand marketing, enabling a broader reach and more personalized targeting aimed at increasing brand trust and enhancing customer loyalty. Today, the Internet allows marketers to penetrate deeper into their existing markets, create new online marketplaces and to generate new demand. This dynamic market engagement uses new technologies to target consumers more effectively. In this conceptual paper, we discuss how blockchain technology can potentially impact a firm's marketing activities. More specifically, we illustrate how blockchain technology acts as incremental innovation, empowering the consumer-centric paradigm. Moreover, blockchain technology fosters disintermediation, aids in combatting click fraud, reinforces trust and transparency, enables enhanced privacy protection, empowers security, and enables creative loyalty programs. We present six propositions that will guide future blockchain-related research in the area of marketing.

Introduction

Customer-centric marketing is crucial for firms who want to survive in fiercely contested B2C environments ( Sheth et al., 2000 ). Marketing helps companies to understand and explain the value a consumer perceives and derives from a product or service ( Larivière et al., 2013 ). The communication methods a firm selects might differ from one industry to another. However, the fundamental objectives and challenges related to consumer engagement remain the same. The proliferation of new technologies often has a democratizing effect for companies and consumers alike, transcending the reach and size of the firm and making new technologies more affordable to smaller firms. Despite uncertain financial returns, small firms are now investing in fee-based technologies and platforms that they perceive as essential for sustaining a competitive position in their markets ( Rishel and Burns, 1997 ). Given this trend, the emergence of “Mar-tech” as a mix of marketing automation and technology solutions has positively impacted the way firms reach and engage with their customers ( Cvitanović, 2018 ). Not only do they reshape the modus operandi for a firm's outreach, but they alter and raise customers' expectations, thus changing the dynamics of customer-brand relationships ( Treiblmaier and Strebinger, 2008 ).

In the new economy, brands are no longer focusing solely on running one campaign after the other. Instead, they are capitalizing on new forms of consumer engagement and dialogue to extend their market coverage and enforce a more synergistic and attuned marketing communication strategy ( Santomier, 2008 ). Firms today are building a portfolio of technologies and exploiting various media channels and publicity methods to position their brands, as well as sell their products, services, and ideas ( McAllister and Turow, 2002 ). Digital marketing is leveraging new channels across social media that provide firms with new, innovative, cost-effective and influential capabilities to engage with customers ( Melewar et al., 2017 ). In turn, customers are becoming an integral part of the evolving engagement dialogue and are strengthening their influence on the marketing process ( Berman and McClellan, 2002 ).

The growth of the Internet, along with emerging technologies, has made a substantial impact on the traditional marketing mix (i.e., product, price, place, and promotion). For example, advanced technologies often termed as big data analytics have allowed firms to aggregate large and complex data sets and use sophisticated analytics to gain additional consumer insights ( Stone and Woodcock, 2014 ). Likewise, retailers and online businesses are increasingly investing in social media as part of their marketing communications practices and attempts to outperform their competitors ( Vend, 2018 ). In this regard, DeMers (2016) forecasted that the trend toward cyber shopping is likely to intensify with an increased future consumer propensity to engage in online shopping experiences. As a consequence, more people in the United States prefer to do their shopping online than to purchase from brick and mortar stores ( Marketo, 2017 ). Modern technologies put consumers at the forefront of security, privacy, trust, and transparency challenges. Prabhaker (2000) argues that each time individuals engage in an online transaction, they leave behind a digital trail of detailed information about their identity, their buying preferences, spending habits, credit card details, and other personally identifiable information (PII) (i.e., data that can be used to identify a particular person). From a privacy perspective, this situation has worsened over the years as data collection practices have become more versatile and ubiquitous. Online businesses regularly fail to meet regulatory requirements, and privacy leaks are frequent and have a lasting impact on consumers' trust ( Ingram et al., 2018 ; Martin, 2018 ; Bodoni, 2019 ). As a result, consumer awareness heightens, their suspicions raise, and they are more prudent about online transactions as their PII can be used or sold for monetary gain without their permission ( Norman et al., 2016 ). Avoiding online purchases is not a solution since brick and mortar retailers also encourage the use of loyalty cards and maintain a centralized database which may be vulnerable to hacking or misuse. Moreover, many developing countries do not have privacy regulations in place to protect consumers PII. Therefore, brands must keep abreast of the latest privacy regulations, understand consumer expectations, and keep up-to-date with technology innovation and best practices. Advocates for enhanced consumer privacy suggest that systems should be built with a “privacy-by-design” framework ( Cavoukian, 2011 ).

The recent hype around blockchain technology has led to promising use cases in areas such as finance, supply chain management, healthcare, tourism, real estate, and the marketing field is no exception. Initially launched for underpinning the cryptocurrency Bitcoin, the primary feature of blockchain technology is peer-to-peer communication, eliminating the need for centralized third parties to control the flow of transactions ( Yli-Huumo et al., 2016 ). Treiblmaier (2018 , p. 547) defines blockchain as a “ digital, decentralized and distributed ledger in which transactions are logged and added in chronological order with the goal of creating permanent and tamperproof records .” A specific blockchain configuration is usually a combination of multiple technologies, tools and methods that address a particular problem or business use case ( Rejeb et al., 2018 ). Thus, marketing managers need to understand the possibilities of blockchain technology as a protocol of communication that marks the transition from the Internet of information to the Internet of value and trust ( Twesige, 2015 ; Zamani and Giaglis, 2018 ).

In this paper, we discuss the possibilities of blockchain technology from a marketing perspective. Despite the growing literature on the potentials of blockchain applications, more rigorous academic research is needed to illustrate how this emerging technology can potentially provide a foundational layer for enhanced transparency and trust in marketing activities. The structure of this paper is as follows: In Features of Blockchain Technology, we briefly review the concept of blockchain technology and some of its key features. In Disrupting Marketing with Blockchain Technology, we discuss various areas in which the technology can impact marketing activities and benefit brands and consumers alike. In the final part, we summarize the paper and highlight future research directions. In this paper, we refer to personally identifiable information as PII and the terms “consumers” and “customers” may be used interchangeably unless otherwise specified.

Features of Blockchain Technology

Following the 2007–08 global financial crisis, a marked fall in public trust in the conventional banking system prevailed ( Ehrmann et al., 2010 ). Technology enthusiasts and software developers envisioned and created an alternative financial system that falls outside the sphere of influence of conventional trusted third parties. The pseudonymous Satoshi Nakamoto proposed the digital currency Bitcoin as a peer-to-peer electronic cash system ( Nakamoto, 2008 ). This new technology relies on a protocol of cryptographic rules and techniques for processing transactions ( Papadopoulos, 2015 ). These include the use of hashing, time-stamping, consensus mechanisms (a collection of rules that allow network nodes to reach mutual agreement), and asymmetric encryption using public and private keys. Not only has the proposed cryptocurrency model ingeniously solved the double-spending problem ( Treiblmaier, 2019a ), but it sets out a new paradigm for performing transactions and exchanging value in an online environment ( Clohessy et al., 2019 ). More precisely, any transaction triggered on the blockchain follows a set of predefined rules that are based on security, verifiability and peer consensus to ensure the validity of transactions ( Münsing et al., 2017 ). All transactions are time-stamped, captured in datasets called blocks, and sequentially chained (i.e., each block header contains the hash of the previous block header) to form the ledger (see Figure 1 ). Tampering with a public transaction record is technically tricky and viewed as infeasible because it requires substantial computing power to attempt to alter the cryptographic hash of previous blocks on the chain ( Hackius and Petersen, 2017 ).

Figure 1 . Blockchain structure.

Beyond the cryptocurrency jargon, a blockchain is not only a combination of technologies but also the integration of multiple technologies ( Lu, 2019 ). Most scholars and practitioners commonly understand blockchain as one method within the distributed ledger technology family ( Fosso Wamba et al., 2020 ). Moreover, the ledger is a virtual book or a unique collection of all transactions carried out by the blockchain's exchange parties. The technology can be viewed as a new way of authenticating assets used in a transaction and can be applied to many business activities and functions ( Ertemel, 2018 ; Rejeb et al., 2019 ). In the following sections, we will elaborate on how the core characteristics of blockchain technology enable functions and applications that can fundamentally change marketing strategies.

Disrupting Marketing With Blockchain Technology

Rigorous academic studies on blockchain applications in support of marketing activities are scarce. Despite this, in the practitioner-based literature, the benefits of blockchain are viewed as indisputable ( Ghose, 2018 ). In this paper, we lay the foundation for future academic studies by identifying several important research areas, as shown in Figure 2 . First and foremost, blockchain technology is based on peer-to-peer communication which alters market structures by fostering disintermediation, namely the removal of intermediaries who process and filter data streams and add cost. By creating immutable and shared data records, blockchain technology can also help to improve data quality and facilitate data access. From a consumer-centric perspective, blockchain technology has the potential to substantially transform consumer relationships by enhancing data and information transparency and improving privacy and security. It also allows for innovative forms of consumer loyalty programs which might help to create additional value. All these features will be discussed in more detail in the sections below.

Figure 2 . Impact of blockchain on marketing.

Fostering Disintermediation

The advent of the Internet has enabled disintermediation and drastically changed the way companies distribute their products and services ( Buhalis and Licata, 2002 ). New technologies have displaced traditional trading mechanisms, reduced the reliance on traditional intermediaries, and introduced new forms of electronic intermediaries ( Cort, 1999 ). Simultaneously, the Internet has led to the emergence of new online intermediaries which offer a new range of products and services ( McCole, 2004 ). The process of realigning the value-adding role through information and shifting the control in the value chain to different players is called re-intermediation ( Pineda and Paraskevas, 2004 ). Examples of services offered by new e-commerce intermediaries are information brokering, online search capabilities, advertising, communication, and trust provision. Moreover, the prevalence of social media has emphasized the growing need for businesses to reach out to customers through social networks and messaging platforms such as Facebook, Twitter, and YouTube. Instead of generating revenues through customers' payments for content and services, these platforms rely on income through data and targeted advertisements. They have also developed a virtuous cycle in which further interaction with consumers results in the accumulation of knowledge and better integration of content ( Nieves and Diaz-Meneses, 2016 ). While these electronic intermediaries support businesses and consumers by personalizing their brands and products, they also gain the power to lock them into their proprietary platforms.

On the one hand, businesses exhibit a heavy reliance and dependency on intermediaries to recognize their potential customers' needs and wants. On the other hand, businesses seek to attract consumers' attention but often rely on communication channels served by many information intermediaries as they provide a wealth of information about the demand for goods and services (e.g., the quantity and type of those goods and services, prices as well as existing trade requirements; Tönnissen and Teuteberg, 2019 ). It may occur that these intermediaries do not allow brands to make their own dissemination decisions and therefore impede their innovativeness and their ability to generate new prospects and target offerings ( Hübner and Elmhorst, 2008 ). Moreover, if the channels are not efficiently managed, the spin-off will lead to misunderstandings, loss of customers and foment ill will ( Boyer and Hult, 2005 ). On the other hand, consumers may dislike the monetization of their data by e-intermediaries. This intermediated approach often precludes consumers from reaping the benefits of directly engaging with brands, such as co-creation, more customer-centered support, as well as increased and dynamic personalization.

To address the aforementioned concerns, blockchain technologies can be a propitious tool enabling brands and consumers to bypass intermediation and to forge stronger relationships. The technology allows brands to expand their advertising campaigns, improve their customer targeting capabilities, and enhance service responsiveness. Its interactive and ubiquitous features allow marketers to efficiently communicate their commercial content and reduce costs by bypassing intermediaries ( Sarkar et al., 1995 ). For example, retailers routinely pay credit card companies +3% payment processing, and many online platforms charge listing fees or sales commissions ( Harvey et al., 2018 ). With blockchain technology, brands can limit or remove costs and eliminate non-value adding activities at the intermediation layer. Brands can then incentivize their customers to disclose and share information through loyalty rewards (i.e., points, cryptocurrency rewards, micropayments, and cash-back incentives). Therefore, blockchain technology can potentially strengthen the direct relationship between brands and consumers. Blockchain technology unfolds a new model for enhanced consumer engagement and collaboration. Consumers can interact and engage directly with the brand or firm while responding to their marketing campaigns with an authentic and verified product or service reviews ( Deighton and Kornfeld, 2008 ). We, therefore, suggest our first research proposition:

RP 1 : Blockchain technology creates new market structures by fostering disintermediation.

Combating Click Fraud

The emergence of the Internet as a marketing channel and an advertising platform has enabled brands to promote their products and services online and to establish and maintain relationships with their clients ( Geiger and Martin, 1999 ). The Internet is also an efficient communication tool that allows firms to interact directly with consumers and keep them informed about their latest products, services and firm developments. Although the importance of having an online presence is undisputed, the reputation of the marketing and advertising industry has been plagued by a never-ending series of frauds, scandals, and deceptive campaigns ( Hongwei and Peiji, 2011 ). As online sponsored search dominates the business model for a majority of search engines ( Jain et al., 2010 ), click fraud considerably tarnishes the credibility of the online advertising landscape. This phenomenon is a result of the automated nature of online advertising and the increasing sophistication of target marketing. Click fraud is an intentional act in which a natural person or organization tries to obtain illegitimate interests or drain a competitor's advertising budget using automated scripts, computer programs or employing natural persons to mimic legitimate web users to click on online advertising ( Hongwei and Peiji, 2011 ). Click fraud has been identified as a severe threat to online advertising, with additional costs for advertisers amounting to $44 billion by 2022 ( Juniper Research, 2017 ). Of prime importance is the economic incentive of fraud perpetrator and publishers who have been accused of committing click fraud to increase their revenues ( Haddadi, 2010 ).

Although some search engines try to compensate advertisers for click fraud, reports have shown that they have attempted to understate its magnitude ( Click Quality Team, 2006 ). To combat click fraud, numerous solutions were suggested, such as selling a particular percentage of all impressions to advertisers or the application of pay-per-click advertising models ( Goodman, 2005 ; Mungamuru et al., 2008 ). However, these preventive measures are not sufficient ( Kshetri and Voas, 2019 ). The pervasiveness of click fraud is due to a lack of intermediaries who track online advertising and provide third party measurement approaches capable of increasing trust and reducing some of the concerns. That is to say, advertisers must engage with independent click fraud monitoring companies to resolve the ambiguity surrounding the divergence in the reported click fraud rates. Even though an external audit service might be beneficial, it can also be unaffordable for small and medium-sized companies. Besides, it is highly likely that search engines refuse to compensate an advertiser based on click fraud metrics generated by an independent audit firm, especially in cases reporting significant click fraud numbers. Also, the lack of transparency in search engine efforts to fight click fraud has created the impression that they have not done enough to track or prevent click fraud ( Dinev et al., 2008 ). The advertisers are still unable to gain full, trusted knowledge and control over the state of their online ads.

The consequences of click fraud for marketing and advertising are severe since it jeopardizes advertising's effectiveness of targeting potential customers involved in content, service, or product-related information search ( Schultz and Olbrich, 2007 ). Search engine marketing tactics may diminish trust and the reputation of network media. The impact of click fraud manifests itself in increasing advertising costs. Moreover, unsuccessful advertising campaigns are caused by the reliance on unreliable, inadequate, and untrusted analytical data. For example, Pearce et al. (2014) estimate that advertising losses caused by a botnet's fraudulent activities will amount to USD $100,000 per day (a botnet is a term derived from “robot” and “network” to mean a collection of internet-enabled devices running code or “bots” usually with a malicious intent). The losses span from financial to brand reputational damage and can be significant in the case of peer-to-peer botnets, which use an overlay network for exchanging and controlling data, making their detection challenging ( Alauthaman et al., 2018 ). Therefore, brands need to embrace resilient defense mechanisms as the online environment is rife with high traffic botnets.

Blockchain technology can mitigate certain risks associated with the potentially devastating impact of click fraud by creating a more trustworthy digital marketing environment for consumers and brands alike. A blockchain-based platform can motivate stakeholders in the advertising industry to operate in an open and collaborative environment where each party acts with honesty and integrity ( Chartier-Rueg and Zweifel, 2017 ). For example, information asymmetry (i.e., when one party has more or more accurate information than the other party) is one of the motivations for click fraud which can be addressed in a blockchain ecosystem. More precisely, supervision and control over the publishers can be reinforced by leveraging the comprehensive analysis of qualifications, credibility and historical information, and by creating a collaborative modus operandi ( Hongwei and Peiji, 2011 ). Much of this is owing to the immutable, transparent, and auditable nature of transactions that the technology enables. For instance, it is possible to ensure end-to-end transparency over online advertising-related activities such as the authentication of clicks. The “adChain” platform serves as a transformative protocol within the advertising technology industry which allows ad space users to benefit from campaign auditing and near-real-time impression tracking ( Goldin et al., 2017 ). The platform draws on the strength of blockchains immutability to curb the attempts of pay-per-click providers to benefit from fraudulent ad clicks and traffic. Another novel advertising platform called “Ubex” harnesses blockchain technology along with other critical emerging technologies such as Artificial Intelligent and neural networks to achieve more precise media marketing data for advertisers, publishers and target consumers ( Ubex, 2019 ). In this model, blockchain assists in eliminating irrelevant ads and better managing data clicks, impressions, and revenues for each web site linked to the system, thus helping advertisers to optimize their budgets.

Apart from promoting transparency, the prevention of click fraud allows advertisers to more effectively assess consumers' habits online. As such, the traceability features provided by the technology ( Alvarenga et al., 2018 ) guarantee genuine customer visits. Practically, this can be achieved by assigning customers to authenticated and verified profiles on the blockchain. This removes the possibility of using device emulation software to fake installs from the advertising model and will result in higher accuracy in targeting and personalization due to real-time ads traceability. This approach enables marketers to obtain reliable data, generate more enhanced analytics, and thus to craft compelling marketing campaigns. By way of illustration, Lucidity's blockchain pilot with the Japanese car manufacturer Toyota resulted in a 21% increase in campaign performance ( Lucidity, 2018 ). A blockchain-based platform marks the transition from the probabilistic measurement of clicks and impressions to a deterministic data model. Likewise, Pinmo integrates blockchain infrastructure into its overall media advertising strategy aimed at better ad campaign tracking and more precise analytics ( Pinmo, 2019 ). These examples are illustrative of the blockchain's potential to prevent click fraud and to promote enhanced trust and transparency in the marketing and advertising industry. We therefore propose:

RP 2 : Blockchain technology helps to combat click fraud.

Reinforcing Trust and Transparency

The academic literature has recognized that trust is vitally important in B2C e-commerce ( Lee and Turban, 2001 ). Despite this strong assertion, consumer confidence and trust in brands have been severely eroded ( Quelch, 2009 ). According to the 2018 Edelman Trust Barometer, brands witnessed a significant decline in consumer trust in 2017 ( Jones, 2018 ). To a large extent, the level of trust is determined by the quality of the technological infrastructure ( Koenig-Lewis et al., 2010 ). Today, the Internet enables transactions in the absence of face-to-face contact. For this reason, a brand's success is contingent on the level of trust and transparency that it can generate ( Strebinger and Treiblmaier, 2004 ; Tapscott and Tapscott, 2016 ). To empower trust and transparency in digital marketing, blockchain technology can allow brands and consumers to operate in a more secure and transparent ecosystem. Building on features such as the consistency of information, transparency, and immutability, blockchain technology helps to establish trust in the system itself (i.e., “trust by design”). The trust protocol of blockchain guarantees consumers (e.g., potential buyers) and the firm's existing customers that brands and marketers are behaving with integrity and honesty ( Chapron, 2017 ). In this context, blockchain-enabled trust is both an antecedent and an outcome of consumer-centric transparency, especially when consumers share their PII. Blockchain can help to avoid malicious marketing of counterfeit products that infringe upon the intellectual property (IP) rights of the original manufacturer and violate copyright laws. This is owing to the ability of the technology to facilitate end-to-end product traceability ( Galvez et al., 2018 ) and strict monitoring rules. Furthermore, blockchain-enabled transparency breeds trust because consumers have greater visibility and verifiability over the compliance obligations of brand claims. This can include the verification of credence claims such as organic, halal, and other third party certifications, the firm's business practices, and even their involvement in corporate social responsibility activities (e.g., fair trade, ethics, and sustainability measures; Treiblmaier, 2019a ). Ensuring this high level of transparency, marketers will be able to signal several positive traits, emphasizing their altruistic motive to look out for the best interest of consumers ( DeCarlo, 2005 ). The example of NYIAX (New York Interactive Advertising Exchange) demonstrates the role of blockchain technology to promote a transparent marketplace where a matching engine ensures a fair exchange of future premium advertising inventory as guaranteed contracts ( Epstein, 2017 ). We thus propose:

RP 3 : Blockchain technology can help to reinforce consumers' trust in brands.

Enhancing Privacy Protection

Privacy is a complex issue that potentially amplifies individuals' anxiety about using an online technology service ( Compeau and Higgins, 1995 ). Research has repeatedly shown that customers worry about their transaction anonymity and confidentiality ( Ratnasingham, 1998 ). These concerns are caused by the increased risk of improperly obtaining, misusing, and divulging their PII. Privacy issues have increased since website cookies capture personal information and store them in information systems ( McParland and Connolly, 2007 ). Moreover, vast improvements in data collection technologies coupled with new data mining techniques enable brands to more easily identify, track, collect and process consumer information. This creates new problems of intrusiveness in the privacy of online shoppers. To counteract these threats, consumers express a strong desire to control their personal information. This is confirmed by a survey which found that 87% of respondents ( n = 2,136) decided to protect their privacy by requesting that companies remove their PII from their databases ( Harris Poll, 2004 ). Additionally, consumers sometimes chose to purposely supply false information on a web site, in order to block online-ad targeting techniques or to disable cookies ( Culnan and Milne, 2001 ).

While the need for heightened online privacy protection is rising, blockchain technology can alleviate many issues impeding consumers from shopping online. For example, consumers can entrust their PII on a blockchain platform since transactions are not bound to real identities once they are routed to a random set of points in the network ( Jesus et al., 2018 ). Online privacy of consumers can be adequately engineered to control the access of network members to the information contained in the blocks. Transactions can be entirely private, but at the same time, they are verified by a consensus of participants in the shared network. Moreover, the blockchain platform can be an effective privacy-enhancing or privacy-by-design technology as it appeals to the technological savviness of online consumers by allowing them to encrypt their credentials resiliently (e.g., users' IDs, passwords, electronic IDs cards). Consequently, consumers can gain more control over their PII in digital marketing because their PII cannot easily be commoditized ( Kosba et al., 2016 ). Consumers can rely on the blockchain's transactional history to generate more robust analytics and precise forecasting regarding their expectations, tastes, and brand perceptions. Additionally, there are new opportunities for consumers to securely and effectively trade their PII with brands ( Travizano et al., 2018 ), which leads to our proposition:

RP 4 : Blockchain technology can enhance privacy protection.

Empowering Digital Marketing Security

Kalakota and Whinston (1997 , p. 853) define a security threat as a “ circumstance, condition, or event with the potential to cause economic hardship to data or network resources in the form of destruction, disclosure, modification of data, denial of service and/or fraud, waste and abuse ”. Information security can be viewed as the heart of information systems, both at the technological and organizational levels ( Dubois et al., 2010 ). This implies that ensuring a high level of preventative measures and transaction security is a crucial differentiator for many businesses. In the digital world, the delivery of products and services with well-communicated and adequate security is a crucial success factor for brand trust. Similarly, information security is turning into a must-have feature as brands become the stewards of consumers' PII ( Madhavaram et al., 2005 ). This development is referred to by Greenlow (2018) as “Marketing security” which is the real-time control and management of consumers' PII to prevent data leakages and abuses.

Previous research has shown that information security concerns are a significant barrier to online marketing ( Sathye, 1999 ; Udo, 2001 ). This is because online shopping and e-commerce are based on individuals' credentials and sensitive information such as home address and credit card details (collectively PII), much of which consumers are very reluctant to provide. The reason for this negative perception is the multitude of potential online threats, which involves data loss or theft, identity theft, credit card information theft, content manipulation, unauthorized account access, database attacks, patent and copyright violations ( Chehrehpak et al., 2014 ). In the online marketing context, Internet banking still faces security threats through data transaction and transmission attacks or unauthorized uses of bank cards enabled through false authentication ( Yousafzai et al., 2003 ). Moreover, the application of behavioral targeting ( Beales, 2010 ) requires the need for cookies that are susceptible to cloning or misappropriation by a malicious party. A cookies-based approach and weblog records for tracking shoppers online activities might compromise consumers' privacy ( Lee et al., 2019 ). The many security threats are now so prevalent that by 2021 the costs of cybercrimes are expected to reach $6 trillion annually ( Empius marketing, 2019 ).

Prior to incorporating information security into the marketing narrative, brands have to establish a robust technological infrastructure that addresses existing security loopholes and enhances consumers' confidence in the digital marketing environment. In this respect, the emergence of blockchain technology can benefit both brands and consumers, ensuring an unprecedented level of security. The power of blockchain security is based on its distributed and decentralized storage of data ( Yanik and Kiliç, 2018 ). Besides, the usage of several security mechanisms such as asymmetric encryption, digital signatures and access control (i.e., assigning reading and writing permissions) can secure the appropriate storage, transmission, and retrieval of large amounts of consumer information. The technology aligns well with the factors listed by Ma et al. (2008) for implementing a resilient information security management system: integration of information, information availability, information reliability, and accountability. Not only does the technology entail a new way of decentralizing and self-organizing the business ecosystem of brands, it can help to synchronize and integrate marketing-related information across the members of the network. This includes pricing policies, product listings, advertisements, outputs of market research and analysis, discounts and promotional benefits, and marketing plans. Decentralization can help to ensure that every party is economically better off and more secure ( Epstein, 2017 ). For instance, consumers will have a single version of the truth and precise insights about a brand's values and traits. They would also maintain more control over their PII. Besides, the decentralized approach of blockchain technology allows brands to remove a single point of failure, thus achieving a high level of resistance against Denial of Services (DoS) attacks ( Helebrandt et al., 2018 ) and ensuring network availability. In case of errors and misappropriation, information ubiquity and availability enabled by blockchain technology increases accountability and provides more accurate monitoring and evaluation ( Omran et al., 2017 ). This means that the technology can provide consumers and brands with some redress and counteract measures in worst-case scenarios. For example, promoting marketing convenience and new secure models of advertisements, Keybase.io is a blockchain platform which has been developed to check the integrity of social media users' signature chains and to identify malicious rollbacks ( Keybase.io., 2019 ). We propose:

RP 5 : Blockchain technology can empower digital marketing security.

Enabling Creative Loyalty Programs

In an increasingly competitive market environment, brands strive to ensure consumers remain loyal to their products and services. To enhance consumer retention, brands have been systematically collecting and storing their customer data, primarily through loyalty programs ( Cvitanović, 2018 ). These tools serve to increase brand loyalty, reduce price sensitivity, encourage word of mouth, and enlarge their customer base ( Uncles et al., 2003 ). Moreover, customer loyalty programs may significantly benefit brands as they can generate higher sales and profits. Increasingly, marketers have implemented loyalty programs in a wide variety of industries ( Blattberg and Deighton, 1996 ). They continuously seek to understand which tactics are ideal for reaching consumers and which reward schemes serve them effectively.

Technological advancement has facilitated the collection of consumers' data (e.g., purchasing patterns, transactional history, preferences) and the tailoring of effective loyalty programs. For example, the use of database management software has paved the way for a new era in loyalty marketing by allowing sophisticated and personalized tracking of customers ( Buss, 2002 ). The same is true for mobile marketing, which develops a customer-centric paradigm where loyalty programs are instantly communicated to prospective members. Similarly, the Internet has been a conducive environment for the growth of customer loyalty programs ( Ha, 2007 ). The emergence of these technologies has intensified consumers' interest and access to information regarding loyalty rewards information, although gaining loyal customers is still a challenge for brands ( Shaw and Lin, 2006 ). Furthermore, discussions in Internet forums have long revealed that participating members are often frustrated with some loyalty programs ( Stauss et al., 2005 ; Lee and Jung, 2017 ).

Even though loyalty programs shift from an aggregate level to an individual level ( Kumar et al., 2013 ), they are still very limited in terms of program components. Instead of diversifying reward program features to appeal to new potential members, many firms are adopting loyalty programs aimed at retaining their existing member base ( Omar et al., 2011 ). Customers appreciate being involved in attractive and flexible loyalty programs. However, some brands tend to lock in their customers and exert monopoly power on them ( Varian, 1999 ). The situation is exacerbated if loyalty points are unused or unredeemed. For instance, a report by Bond Brand Loyalty indicated that more than 25% of the participants in loyalty programs never redeem their reward points ( Bond Brand Loyalty, 2016 ). The low redemption rates result from stringent, time-based procedures to redeem rewards. This strategy might invoke a state of significant frustration among loyal members, especially when a potential reward expires ( Colman, 2015 ). The lack of integration of loyalty programs between brands is also a common problem as many loyalty programs are still fragmented and unable to generate information about members attitudes toward the programs themselves ( Allaway et al., 2006 ). For the reasons mentioned above, several scholars in marketing have started questioning the effectiveness of loyalty programs in customer retention ( Magatef and Tomalieh, 2015 ).

Blockchain technology has the potential to reform how loyalty programs are designed, tracked, and communicated to consumers. In a blockchain-based marketing ecosystem, loyalty programs are fully integrated. All participating parties in such programs such as loyalty programs operators, marketers, consumers, information system managers, call centers, sales offices, and other organizations will be efficiently integrated and interlinked. Instead of being fragmented, loyalty program partners could work synergistically to improve the members' experience and to attract different consumer segments. For example, blockchain technology can help to address the problem of incompatibility in many loyalty programs systems ( Meyer-Waarden and Benavent, 2001 ), resulting in increased channel harmony and consistent experience among brands. Different partners of loyalty programs can exploit the interactive features of the technology to leverage operations like the joint development and design of loyalty programs, the inter-convertibility of reward points, and exchange transactions. More precisely, blockchain technology can create a more secure, and interoperable environment that is unattainable with centralized loyalty databases ( Zhang et al., 2017 ). The technology appeals for both B2B and B2C loyalty programs as auditability of critical transactions and data is necessary to curb fraudulent activities and support customer advocacy ( Lacey and Morgan, 2008 ).

Through real-time access to the blockchain platform, marketers can gain visibility over members' profiles, points, purchase patterns, payment history, and promotion responses, which will help them to craft more attractive, valuable, and customized loyalty programs. For example, American Express has integrated the Hyperledger blockchain to provide reward points to members based on individual products, instead of the spending behavior at a particular merchant ( Coleman, 2018 ). Besides, the decentralized nature of blockchain technology also allows members to track their loyalty and reward points, freeing them and marketers from the physical possession of coupons ( Chatterjee and McGinnis, 2010 ). Additionally, the technology can help to create more value for members by enabling them to trade and exchange their loyalty points. We propose:

RP 6 : Blockchain technology can enable creative loyalty programs.

Conclusion and Limitations

Rapid technological progress and the growth of e-business and e-commerce have significantly shaped the process of value creation. Many businesses exhibit a heavy reliance on technologies to offer seamless products and services to their existing customers. Emerging technologies can assist in better designing new products and services, improving data quality, and making the production process more responsive and economical ( Cavalieri et al., 2013 ). New technologies have also significantly reshaped the marketing discipline, and they have brought new marketing terms and tactics ( Bordonaba-Juste et al., 2012 ). Today, brands are increasingly using technology to leverage their global reach by penetrating new marketplaces and creating consumer demand. In this process, the Internet has enabled marketers to reach consumers with enhanced electronic communications and interactive media ( Peltier et al., 2010 ). Meanwhile, consumers have become more knowledgeable about available offers and can make informed decisions in a convenient manner ( Spann and Tellis, 2006 ). Businesses have benefited from data mining techniques and big data to draw conclusions regarding consumers' needs and wants. Analyzing large data sets help businesses to gain actionable insights through predictive analytics ( Johnston, 2014 ). Blockchain technology is one technological advancement that can help brands to gain a better understanding and target their customers, but at the same time allow customers to regain control over their PII.

In this paper, we discussed several blockchain possibilities in the marketing landscape and presented six research propositions. The current online marketing world is rife with intermediaries (or so-called e-mediaries) who fail to configure active alliance networks ( Dale, 2003 ) and lock both brands and consumers into platforms with limited capabilities. In doing so, they hamper the creativity of brands and deprive consumers of potential benefits of direct engagement. In this context, blockchain technology promises disintermediated markets where consumers can transact directly without passing through intermediary layers. Instead of operating in an opaque environment where information asymmetry prevails and dominates the relationship between brands and consumers, blockchain technology can create a new topology of enhanced transaction trust and information transparency, resulting in more trusted campaigns and customer-centricity ( Shah et al., 2006 ). Moreover, the high level of technological sophistication and the intrinsic features of blockchain have demonstrated viability for protecting consumers' privacy and enhancing security in digital marketing. Not only that, the technology can assist in combating the widespread phenomenon of click fraud, thus creating a healthier marketing space for consumers, brands, and other participants involved in the value creation and delivery process. From a company's perspective, establishing loyalty is often challenging, since consumers always consider switching costs and economic benefits in their purchases ( Reinartz, 2006 ). Blockchain technology can bring a renewed approach of crafting, integrating, and promoting marketing loyalty programs. Blockchain-based reward programs allow members to gain benefits from their brand loyalty, resulting in a more sustainable brand attachment.

This research has some limitations. It was our goal to present future blockchain applications in marketing in a concise way and to derive several research propositions. Consequently, we were not able to elaborate on the many intricacies and subtleties of blockchain technologies which we see as an excellent opportunity for future research. We also recommend that future research discusses the architecture as well as the operational environment in some detail to foster the understanding of how blockchain can help to create organizational value. Furthermore, it was our goal to highlight the potentials of blockchain in marketing, but we also need to mention potential challenges that might emerge from the (inter-)organizational integration of blockchain technology. Blockchains are not silver bullets or a panacea for all contemporary marketing issues but rather exhibit several shortcomings and potential negative consequences ( Treiblmaier, 2019b ). Compared to conventional databases, blockchain technology has several downsides. Storing information and transactions on the blockchain is still complicated and expensive ( Baldimtsi et al., 2017 ). The cost of blockchain security and redundancy may far outweigh the values derived from its applications for marketing. As such, the redundant nature of blockchain offers increased costs since the processing of transactions on the blockchain takes longer than single-source transactions ( Smith, 2017 ). Moreover, the adoption of blockchain is hampered by the lack of a suitable governance structure, the cost of blockchain maintenance and the high energy consumption where a proof-of-work consensus protocol on a public blockchain is used. According to Truby (2018) , the initial application of blockchain, namely Bitcoin, has been designed with no consideration of the potential impacts on the environment. Aside from the insufficient built-in consumer protections and the high price volatility, the leveraging of Bitcoin in companies' marketing activities can cause undue environmental damage through high rates of electricity consumption and emissions ( Truby, 2018 ), which might prevent organizations from adopting blockchain.

From an architectural perspective, it is noteworthy that different types of blockchains exist that can be applied to marketing activities such as private, consortium or public blockchains. Private blockchains can establish different levels of permission for the parties involved in the network. They aim at providing a better degree of privacy, handle large amounts of data, optimize existing and future recordkeeping, smoothen the audit process and compliance reporting and provide decision-makers with the unified data they need ( Poberezhna, 2018 ). Brands wishing to retain their traditional business and governance models may, therefore, consider the adoption of private blockchains. However, according to Prasad and Rohokale (2019) , consortium blockchains are the most suitable solutions for interdisciplinary, cross-industry applications in areas such as financial services, media, and telecommunication. Consortium models give brands the opportunity to reap the benefits of a distributed network while restricting access and consensus to particular users. In addition, these platforms are able to significantly support the co-creative interactions and collaborative marketing relationships between a brand and its stakeholders. Public blockchains are especially useful for brands that seek to capitalize on transparency in order to deliver consumer value. For example, creating product packaging with blockchain-based information transparency can enhance green marketing efforts ( Kouhizadeh and Sarkis, 2018 ) as consumers will likely purchase products that they are sufficiently well informed about. Overall, the choice of blockchain type is a critical decision that should respond to the requirements of different marketing applications.

From the technological innovation perspective, we consider the adoption of blockchain to represent an incremental innovation that can lead to substantial changes in marketing. The cumulative gains from this technology can significantly reshape existing marketing practices and improve established business processes. However, as stated by Christensen (2013) , new technologies could have sustaining or disruptive effects on organizations depending on the firm's resources, processes, and values. Therefore, new technologies, if not strategically approached and adequately embedded in the organizational structure, can erode the competitive position of brands in general and shrink their marketing edge in particular. Future research needs to explore and analyze the barriers to blockchain adoption in marketing. The six propositions we suggest provide starting points for further research and more refinement is needed to identify enablers and barriers as well as antecedents and consequences of blockchain application in marketing. A further note relates to PII retention and the immutability of blockchain technology. Some regulators are exploring consumer-based policies where the consumers' right to be “digitally forgotten” is central. In this latter scenario, researchers could explore privacy in the context of “mutable” blockchains to meet evolving regulatory requirements.

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

The publication of this work was supported by EFOP- 3.6.1-16-2016-00017 (Internationalization, initiatives to establish a new source of researchers and graduates and development of knowledge and technological transfer as instruments of intelligent specializations at Széchenyi István University).

Conflict of Interest

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

Acknowledgments

AR is grateful to Dr. Katalin Czakó and Mrs. Tihana Vasic for their valuable support.

Alauthaman, M., Aslam, N., Zhang, L., Alasem, R., and Hossain, M. A. (2018). A P2P botnet detection scheme based on decision tree and adaptive multilayer neural networks. Neural Comput. Appl . 29, 991–1004. doi: 10.1007/s00521-016-2564-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Allaway, A. W., Gooner, R. M., Berkowitz, D., and Davis, L. (2006). Deriving and exploring behavior segments within a retail loyalty card program. Eur. J. Mark . 40, 1317–1339. doi: 10.1108/03090560610702830

CrossRef Full Text | Google Scholar

Alvarenga, I. D., Rebello, G. A., and Duarte, O. C. M. (2018). “Securing configuration management and migration of virtual network functions using blockchain,” in NOMS 2018-2018 IEEEIFIP Network Operations and Management Symposium (Taipei: IEEE), 1–9. doi: 10.1109/NOMS.2018.8406249

Baldimtsi, F., Kiayias, A., and Samari, K. (2017). “Watermarking public-key cryptographic functionalities and implementations,” in Information Security Lecture Notes in Computer Science , eds P. Q. Nguyen and J. Zhou (Cham: Springer International Publishing), 173–191. doi: 10.1007/978-3-319-69659-1_10

Beales, H. (2010). The value of behavioral targeting. Netw . Advert. Initiat . 1, 1–23. Available online at: https://www.networkadvertising.org/pdfs/Beales_NAI_Study.pdf

Berman, S. J., and McClellan, B. E. (2002). Ten strategies for survival in the attention economy. Strategy Leadersh . 30, 28–33. doi: 10.1108/10878570210697513

Blattberg, R. C., and Deighton, J. (1996). Manage marketing by the customer equity test. Harv. Bus. Rev . 74, 136–144.

PubMed Abstract | Google Scholar

Bodoni, S. (2019). Mastercard Alerts Privacy Watchdogs After Loyalty Program Leak. Bloomberg.Com . Available online at: https://www.bloomberg.com/news/articles/2019-08-23/mastercard-tells-belgian-german-privacy-watchdogs-of-breach (accessed August 22, 2019).

Google Scholar

Bond Brand Loyalty (2016). The 2016 Bond Loyalty Report . Available online at: https://cdn2.hubspot.net/hubfs/352767/Resources/2016_Bond_Loyalty_Report_Executive_Summary_CAN_Launch_Edition.pdf (accessed September 10, 2019).

Bordonaba-Juste, V., Lucia-Palacios, L., and Polo-Redondo, Y. (2012). Antecedents and consequences of e-business adoption for european retailers. Internet Res . 22, 532–550. doi: 10.1108/10662241211271536

Boyer, K. K., and Hult, G. T. M. (2005). Welcome home: innovating the forward supply chain. Bus. Strategy Rev . 16, 31–37. doi: 10.1111/j.0955-6419.2005.00360.x

Buhalis, D., and Licata, M. C. (2002). The future ETourism intermediaries. Tour. Manag . 23, 207–220. doi: 10.1016/S0261-5177(01)00085-1

Buss, D. (2002). As Loyalty Programs Expand, Customer Fatigue Forces Creativity and Caution. Resource Center Article, MCI.COM.

Cavalieri, S., Romero, D., Strandhagen, J. O., and Schönsleben, P. (2013). “Interactive business models to deliver product-services to global markets,” in IFIP International Conference on Advances in Production Management Systems (Berlin; Heidelberg: Springer), 186–193. doi: 10.1007/978-3-642-41263-9_23

Cavoukian, A. (2011). Privacy by Design: The 7 Foundational Principles . Available online at: https://www.ipc.on.ca/wp-content/uploads/Resources/7foundationalprinciples.pdf (accessed September 5, 2019).

Chapron, G. (2017). The environment needs cryptogovernance. Nat. News 545, 403–405. doi: 10.1038/545403a

Chartier-Rueg, T. C., and Zweifel, T. D. (2017). Blockchain, leadership and management: business as usual or radical disruption. EUREKA Soc. Humanit . 4, 76–110. doi: 10.21303/2504-5571.2017.00370

Chatterjee, P., and McGinnis, J. (2010). Customized online promotions: moderating effect of promotion type on deal value, perceived fairness, and purchase intent. J. Appl. Bus. Res . 26, 13–20. doi: 10.19030/jabr.v26i4.302

Chehrehpak, M., Afsharian, S. P., and Roshandel, J. (2014). Effects of implementing information security management systems on the performance of marketing and sales departments. IJBIS 15, 291–306. doi: 10.1504/IJBIS.2014.059752

Christensen, C. M. (2013). The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail . Boston, MA: Harvard Business Review Press.

Click Quality Team (2006). How Fictitious Clicks Occur in Third-Party Click Fraud Audit Reports. Google Inc. 1–17 . Available online at: https://static.googleusercontent.com/media/www.google.hu/fr/hu/adwords/ReportonThird-PartyClickFraudAuditing.pdf (accessed June 5, 2019).

Clohessy, T., Acton, T., and Rogers, N. (2019). “Blockchain adoption: technological, organisational and environmental considerations,” in Business Transformation Through Blockchain , Vol. I, eds H. Treiblmaier and R. Beck (Cham: Springer International Publishing), 47–76. doi: 10.1007/978-3-319-98911-2_2

Coleman, L. (2018). American Express Gives Loyalty Program a Blockchain Upgrade. CCN . Available online at: https://www.ccn.com/american-express-taps-hyperledger-blockchain-for-rewards-program-revamp (accessed April 25, 2019).

Colman, A. M. (2015). The Oxford Dictionary of Psychology , 2014th Edn. Oxford: Oxford University Press.

Compeau, D. R., and Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Q. 19, 189–211. doi: 10.2307/249688

Cort, S. G. (1999). Industry corner: industrial distribution: how goods will go to market in the electronic marketplace. Bus. Econ . 34, 53–55.

Culnan, M. J., and Milne, G. R. (2001). Culnan-Milne Survey on Consumers and Online Privacy Notices . Available online at: https://www.bentley.edu/newsroom/latest-headlines/culnan-milne-survey-on-consumers-and-online-privacy-notices-reveals-onli-0 (accessed April 22, 2019).

Cvitanović, P. L. (2018). “New technologies in marketing as competitive advantage,” in 2018 ENTRENOVA Conference Proceedings (Split: ECONSTOR), 294–302.

Dale, C. (2003). The competitive networks of tourism e-mediaries: new strategies, new advantages. J. Vacat. Mark . 9, 109–118. doi: 10.1177/135676670300900201

DeCarlo, T. E. (2005). The effects of sales message and suspicion of ulterior motives on salesperson evaluation. J. Consum. Psychol . 15, 238–249. doi: 10.1207/s15327663jcp1503_9

Deighton, J., and Kornfeld, L. (2008). Digital Interactivity: Unanticipated Consequences for Markets, Marketing, and Consumers. Boston, MA: Harvard Business School. Availble online at: http://weigend.com/files/teaching/tsinghua/readings/DeightonKornfeldHBS2007.pdf (accessed September 22, 2019).

DeMers, J. (2016). New Technologies Shaping Online Marketing for the Better. Forbes. Availble online at: https://www.forbes.com/sites/jaysondemers/2016/08/15/7-new-technologies-shaping-online-marketing-for-the-better-we-hope/#3a801a9f61fd (accessed September 22, 2019).

Dinev, T., Hu, Q., and Yayla, A. (2008). Is there an on-line advertisers' dilemma? A study of click fraud in the pay-per-click model. Int. J. Electron. Commer . 13, 29–60. doi: 10.2753/JEC1086-4415130202

Dubois, É., Heymans, P., Mayer, N., and Matulevičius, R. (2010). “A systematic approach to define the domain of information system security risk management,” in Intentional Perspectives on Information Systems Engineering , eds S. Nurcan, C. Salinesi, C. Souveyet, and J. Ralyté (Berlin; Heidelberg: Springer), 289–306. doi: 10.1007/978-3-642-12544-7_16

Ehrmann, M., Michel, S., and Livio, S. (2010). Explaining the Fall in Citizens ‘Trust in the ECB During the Global Financial Crisis . Available online at: https://scholar.google.fr/scholar?hl=en&as_sdt=0%2C5&q=+Explaining+the+fall+in+citizens+%27trust+in+the+ECB+during+the+global+financial+crisis&btnG= (accessed April 20, 2019).

Empius marketing (2019). Website Security . Available online at: https://empiusmarketing.com/website-security/ (accessed April 22, 2019).

Epstein, J. (2017). Blockchain and the CMO. Whitepaper. Availble online at: https://s3.us-east-2.amazonaws.com/brightline-website/downloads/reports/Brightline_Epstein_Blockchain-and-the-CMO_Blockchain-Research-Institute.pdf?utm_source=resource-page&utm_medium=skip-link (accessed September 22, 2019).

Ertemel, A. V. (2018). Implications of blockchain technology on marketing. J. Int. Trade Logist. Law 4, 35–44. Available online at: http://jital.org/index.php/jital/article/view/98/pdf_61

Fosso Wamba, S., Kamdjoug, J. R. K., Bawack, R. E., and Keogh, J. G. (2020). Bitcoin, blockchain and fintech: a systematic review and case studies in the supply chain. Prod. Plan. Control 31, 115–142. doi: 10.1080/09537287.2019.1631460

CrossRef Full Text

Galvez, J. F., Mejuto, J. C., and Simal-Gandara, J. (2018). Future challenges on the use of blockchain for food traceability analysis. Trends Anal. Chem . 107, 222–232. doi: 10.1016/j.trac.2018.08.011

Geiger, S., and Martin, S. G. (1999). The internet as a relationship marketing tool-some evidence from irish companies. Ir. Mark. Rev . 12, 24–36.

Ghose, A. (2018). What blockchain could mean for marketing. Harv. Bus. Rev . 2–5. Available online at: https://hbr.org/2018/05/what-blockchain-could-mean-for-marketing

Goldin, M., Soleimani, A., and Young, J. (2017). The Adchain Registry. Whitepaper . Available online at: https://blockchain-x.eu/wp-content/uploads/2018/02/The_adChain_Registry_ENG.pdf (accessed January 27, 2020).

Goodman, J. (2005). “Pay-per-Percentage of impressions: an advertising method that is highly robust to fraud,” in Workshop Spons . Search Auctions. Citeseer.

Greenlow, M. (2018). Marketing Security: The Phrase Every Executive Needs to Understand in 2019. Availble online at: https://www.martechadvisor.com/articles/marketing-analytics/marketing-security-the-phrase-every-executive-needs-to-understand-in-2019/ (accessed April 22, 2019).

Ha, S. (2007). How customer loyalty programs can influence relational marketing outcomes: using customer-retailer identification to build relationships (Ph.D. thesis). The Ohio State University, Columbus, OH, United States of America.

Hackius, N., and Petersen, M. (2017). Blockchain in Logistics and Supply Chain: Trick or Treat? Digit. Supply Chain Manag. Logist. Proc. Hambg. Int. Conf. Logist . 3–18. doi: 10.15480/882.1444

Haddadi, H. (2010). Fighting online click-fraud using bluff Ads. ACM SIGCOMM Comput. Commun. Rev . 40, 21–25. doi: 10.1145/1764873.1764877

Harris Poll (2004). Privacy and American Business. Availble online at: https://www.epic.org/privacy/survey/ (accessed April 26, 2019).

Harvey, C. R., Moorman, C., and Toledo, M. (2018). How blockchain can help marketers build better relationships with their customers. Harv. Bus. Rev . Availble online at: https://hbr.org/2018/10/how-blockchain-can-help-marketers-build-better-relationships-with-their-customers (accessed April 21, 2019).

Helebrandt, P., Bellus, M., Ries, M., Kotuliak, I., and Khilenko, V. (2018). “Blockchain adoption for monitoring and management of enterprise networks,” in 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference IEMCON (Vancouver, BC: IEEE), 1221–1225. doi: 10.1109/IEMCON.2018.8614960

Hongwei, L., and Peiji, S. (2011). The study on supervision model for online advertising click fraud. Manag. Sci. Eng . 5, 111–119. doi: 10.3968/j.mse.1913035X20110503.1z413

Hübner, U., and Elmhorst, M. A. (2008). eBusiness in Healthcare: From eProcurement to Supply Chain Management . London: Springer-Verlag. doi: 10.1007/978-1-84628-879-1

Ingram, D., Panchadar, A., and Auchard, E. (2018). Facebook Privacy Scandal Widens as Data Leak Hits 87 Million Users. CIO . Available online at: https://www.cio.com.au/article/635768/facebook-privacy-scandal-widens-data-leak-hits-87-million-users/ (accessed September 5, 2019).

Jain, V., Midha, V., and Animesh, A. (2010). Whose click fraud data do you trust? effect of click fraud on advertiser's trust and sponsored search advertising decisions. In ECIS 2010 Proc . 1–10.

Jesus, E. F., Chicarino, V. R., de Albuquerque, C. V., and Rocha, A. A. (2018). A survey of how to use blockchain to secure internet of things and the stalker attack. Secur. Commun. Netw . 2018, 1–27. doi: 10.1155/2018/9675050

Johnston, W. J. (2014). The future of business and industrial marketing and needed research. J. Bus. Mark. Manag . 7, 296–300. Available online at: https://www.econstor.eu/bitstream/10419/96103/1/783119623.pdf

Jones, K. (2018). How Much Will Blockchain Really Affect Digital Marketing? Forbes. Availble online at: https://www.forbes.com/sites/forbesagencycouncil/2018/10/04/how-much-will-blockchain-really-affect-digital-marketing/ (accessed April 21, 2019).

Juniper Research (2017). Ad Fraud to Cost Advertisers $19 Billion in 2018. Availble online at: https://www.juniperresearch.com/press/press−releases/ad−fraud−to−cost−advertisers−19-billion-in-2018 (accessed June 24, 2019).

Kalakota, R., and Whinston, A. B. (1997). Electronic Commerce: A Manager's Guide . Boston, MA: Addison-Wesley Professional.

Keybase.io. (2019). Keybase. Availble online at: https://keybase.io/docs/server_security (accessed April 23, 2019).

PubMed Abstract

Koenig-Lewis, N., Palmer, A., and Moll, A. (2010). Predicting young consumers' take up of mobile banking services. Int. J. Bank Mark . 28, 410–432. doi: 10.1108/02652321011064917

Kosba, A., Miller, A., Shi, E., Wen, Z., and Papamanthou, C. (2016). “Hawk: the blockchain model of cryptography and privacy-preserving smart contracts,” in Proceedings - 2016 IEEE Symposium on Security and Privacy. SP 2016 (San Jose, CA: IEEE), 839–858. doi: 10.1109/SP.2016.55

Kouhizadeh, M., and Sarkis, J. (2018). Blockchain practices, potentials, and perspectives in greening supply chains. Sustainability 10:3652. doi: 10.3390/su10103652

Kshetri, N., and Voas, J. (2019). Online advertising fraud. Computer 52, 58–61. doi: 10.1109/MC.2018.2887322

Kumar, V., Dalla Pozza, I., and Ganesh, J. (2013). Revisiting the satisfaction–loyalty relationship: empirical generalizations and directions for future research. J. Retail . 89, 246–262. doi: 10.1016/j.jretai.2013.02.001

Lacey, R., and Morgan, R. M. (2008). Customer advocacy and the impact of B2B loyalty programs. J. Bus. Ind. Mark . 24, 3–13. doi: 10.1108/08858620910923658

Larivière, B., Joosten, H., Malthouse, E. C., Van Birgelen, M., Aksoy, P., Kunz, W. H., et al. (2013). Value fusion: the blending of consumer and firm value in the distinct context of mobile technologies and social media. J. Serv. Manag . 24, 268–293. doi: 10.1108/09564231311326996

Lee, M. K., and Turban, E. (2001). A trust model for consumer internet shopping. Int. J. Electron. Commer . 6, 75–91. doi: 10.1080/10864415.2001.11044227

Lee, S. H., and Jung, K. S. (2017). Loyal customer behaviors: identifying brand fans. Soc. Behav. Personal. Int. J. 46, 1285–1304. doi: 10.2224/sbp.6482

Lee, W., Chen, H., Chang, S., and Chen, T. (2019). Secure and efficient protection for HTTP cookies with self-verification. Int. J. Commun. Syst . 32, 1–10. doi: 10.1002/dac.3857

Lu, Y. (2019). The Blockchain: state-of-the-art and research challenges. J. Ind. Inf. Integr . 15, 80–90. doi: 10.1016/j.jii.2019.04.002

Lucidity (2018). Lucidity's Blockchain Pilot with Toyota Results in 21% Lift in Campaign Performance. Availble online at: https://www.prnewswire.com/news-releases/luciditys-blockchain-pilot-with-toyota-results-in-21-lift-in-campaign-performance-300731983.html (accessed April 24, 2019).

Ma, Q., Johnston, A. C., and Pearson, J. M. (2008). Information security management objectives and practices: a parsimonious framework. Inf. Manag. Comput. Secur . 16, 251–270. doi: 10.1108/09685220810893207

Madhavaram, S., Badrinarayanan, V., and McDonald, R. E. (2005). Integrated marketing communication (IMC) and brand identity as critical components of brand equity strategy: a conceptual framework and research propositions. J. Advert . 34, 69–80. doi: 10.1080/00913367.2005.10639213

Magatef, S. G., and Tomalieh, E. F. (2015). The impact of customer loyalty programs on customer retention. Int. J. Bus. Soc. Sci . 6, 78–93. Available online at: https://www.uop.edu.jo/download/Research/members/loyalty%20programs.pdf

Marketo (2017). Stark Contrasts in Technology Priorities for U.S. and International Marketers, Marketo Survey Finds . Available online at: https://www.prnewswire.com/news-releases/stark-contrasts-in-technology-priorities-for-us-and-international-marketers-marketo-survey-finds-30039 (0070).html (accessed April 20, 2019).

Martin, K. (2018). The penalty for privacy violations: how privacy violations impact trust online. J. Bus. Res. 82, 103–16. doi: 10.1016/j.jbusres.2017.08.034

McAllister, M. P., and Turow, J. (2002). New media and the commercial sphere: two intersecting trends, five categories of concern. J. Broadcast. Electron. Media 46, 505–514. doi: 10.1207/s15506878jobem4604_1

McCole, P. (2004). Marketing is not dead: a response to “Elegy on the death of marketing.” Eur. J. Mark. 38, 1349–1354. doi: 10.1108/03090560410560137

McParland, C., and Connolly, R. (2007). “Online privacy concerns: threat or opportunity,” in Proceedings of 2007 Mediterranean and Middle Eastern Conference on Information Systems. EMCIS2007. Citeseer. 64-1_64-11. Valencia, 24–26 June 2007. Polytechnic University of Valencia.

Melewar, T. C., Foroudi, P., Gupta, S., Kitchen, P. J., and Foroudi, M. M. (2017). Integrating identity, strategy and communications for trust, loyalty and commitment. Eur. J. Mark . 51, 572–604. doi: 10.1108/EJM-08-2015-0616

Meyer-Waarden, L., and Benavent, C. (2001). Loyalty programs: strategies and practice. FEDMA Res. Day Madr. Sept . 14, 1–33. Available online at: https://www.researchgate.net/profile/Lars_Meyer-Waarden/publication/228396280_Loyalty_programs_Strategies_and_practice/links/546204250cf2c1a63c028a41/Loyalty-programs-Strategies-and-practice.pdf

Mungamuru, B., Weis, S., and Garcia-Molina, H. (2008). Should Ad Networks Bother Fighting Click Fraud? (Yes, They Should.). Technical Report. Stanford Infor Lab.

Münsing, E., Mather, J., and Moura, S. (2017). “Blockchains for decentralized optimization of energy resources in microgrid networks,” in 2017 IEEE Conference on Control Technology and Applications (CCTA) (Mauna Lani, HI: IEEE), 2164–2171. doi: 10.1109/CCTA.2017.8062773

Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System | Satoshi Nakamoto Institute . Available online at: http://nakamotoinstitute.org/bitcoin/ (accessed February 3, 2019).

Nieves, J., and Diaz-Meneses, G. (2016). Antecedents and outcomes of marketing innovation: an empirical analysis in the hotel industry. Int. J. Contemp. Hosp. Manag . 28, 1554–1576. doi: 10.1108/IJCHM-11-2014-0589

Norman, G., Pepall, L., Richards, D., and Tan, L. (2016). Competition and consumer data: the good, the bad, and the ugly. Res. Econ. 70, 752–65. doi: 10.1016/j.rie.2016.09.002

Omar, N. A., Alam, S. S., Aziz, N. A., and Nazri, M. A. (2011). Retail loyalty programs in Malaysia: the relationship of equity, value, satisfaction, trust, and loyalty among cardholders. J. Bus. Econ. Manag . 12, 332–352. doi: 10.3846/16111699.2011.573297

Omran, Y., Henke, M., Heines, R., and Hofmann, E. (2017). Blockchain-Driven Supply Chain Finance: Towards a Conceptual Framework from a Buyer Perspective. Working paper . Available online at: https://www.alexandria.unisg.ch/251095/1/WP29-Blockchain-driven%20supply%20chain%20finance%20Towards%20a%20conceptual%20framework%20from%20a%20buyer%20perspective.pdf

Papadopoulos, G. (2015). “Blockchain and digital payments: an institutionalist analysis of Cryptocurrencies,” in Handbook of Digital Currency, Bitcoin, Innovation, Financial Instruments, and Big Data , ed D. L. K. Chuen (Boston, MA: Elsevier), 153–172.

Pearce, P., Dave, V., Grier, C., Levchenko, K., Guha, S., McCoy, D., et al. (2014). “Characterizing large-scale click fraud in zeroaccess,” in Proceedings of 2014 ACM SIGSAC Conference on Computer and Communications Security (Scottsdale, AZ; New York, NY: ACM), 141–152. doi: 10.1145/2660267.2660369

Peltier, J. W., Milne, G. R., Phelps, J. E., and Barrett, J. T. (2010). Teaching information privacy in marketing courses: key educational issues for principles of marketing and elective marketing courses. J. Mark. Educ . 32, 224–246. doi: 10.1177/0273475309360164

Pineda, J. M., and Paraskevas, A. (2004). “Web analytics: a missed opportunity for hotel online strategy?” in Proceedings of 11th ENTER Conference (Vienna: Springer Verlag), 623–633. doi: 10.1007/978-3-7091-0594-8_58

Pinmo (2019). How Pinmo Will Utilize Blockchain to Revolutionize the Advertising Industry. Pinmo . Available online at: http://blog.pinmo.ca/advertising-industry/ (accessed September 22, 2019).

Poberezhna, A. (2018). “Chapter 14 - Addressing water sustainability with blockchain technology and green finance,” in Transforming Climate Finance and Green Investment with Blockchains , ed A. Marke (Cambrige, MA: Academic Press), 189–196. doi: 10.1016/B978-0-12-814447-3.00014-8

Prabhaker, P. R. (2000). Who owns the online consumer? J. Consum. Mark . 17, 158–171. doi: 10.1108/07363760010317213

Prasad, R., and Rohokale, V. (2019). “Blockchain Technology,” in Cyber Security: The Lifeline of Information and Communication Technology (Springer Series in Wireless Technology) , eds R. Prasad and V. Rohokale (Cham: Springer International Publishing), 249–62. doi: 10.1007/978-3-030-31703-4_17

Quelch, J. (2009). Improving Market Research in a Recession. Harvard Business School Working Knowledge. doi: 10.1002/ltl.340

Ratnasingham, P. (1998). Trust in web-based electronic commerce security. Inf. Manag. Comput. Secur . 6, 162–166. doi: 10.1108/09685229810227667

Reinartz, W. J. (2006). “Understanding Customer Loyalty Programs,” in Retail. 21st Century , eds M. Krafft and M. K. Mantrala (Heidelberg: Springer), 361–379. doi: 10.1007/3-540-28433-8_23

Rejeb, A., Keogh, J. G., and Treiblmaier, H. (2019). Leveraging the internet of things and blockchain technology in supply chain management. Future Internet 11:161. doi: 10.3390/fi11070161

Rejeb, A., Sűle, E., and Keogh, J. G. (2018). Exploring new technologies in procurement. Transp. Logist. Int. J . 18, 76–86. Available online at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3319424

Rishel, T. D., and Burns, O. M. (1997). The impact of technology on small manufacturing firms. J. Small Bus. Manag . 35, 2–10.

Santomier, J. (2008). New media, branding and global sports sponsorship. Int. J. Sports Mark. Spons . 10, 9–22. doi: 10.1108/IJSMS-10-01-2008-B005

Sarkar, M. B., Butler, B., and Steinfield, C. (1995). Intermediaries and cybermediaries. J. Comput. Mediat. Commun . 1:JCMC132. doi: 10.1111/j.1083-6101.1995.tb00167.x

Sathye, M. (1999). Adoption of internet banking by australian consumers: an empirical investigation. Int. J. Bank Mark . 17, 324–334. doi: 10.1108/02652329910305689

Schultz, C. D., and Olbrich, R. (2007). Consequences of Click Fraud on the Effectiveness of Search Engine Advertising . Available online at: http://citeseerx.ist.psu.edu/viewdoc/download? (accessed September 23, 2019).

Shah, D., Rust, R. T., Parasuraman, A., Staelin, R., and Day, G. S. (2006). The path to customer centricity. J. Serv. Res . 9, 113–124. doi: 10.1177/1094670506294666

Shaw, C. W., and Lin, S. W. (2006). “The antecedents of consumers' loyalty toward online stores,” in 11th Annu. Conf. Asia Pac. Decis. Sci. Inst (Hong Kong), 14–18.

Sheth, J. N., Sisodia, R. S., and Sharma, A. (2000). The antecedents and consequences of customer-centric marketing. J. Acad. Mark. Sci. 28, 55–66. doi: 10.1177/0092070300281006

Smith, T. D. (2017). “The Blockchain Litmus Test,” in 2017 IEEE International Conference on Big Data 2299-2308 (Botson, MA: IEEE). doi: 10.1109/BigData.2017.8258183

Spann, M., and Tellis, G. J. (2006). Does the internet promote better consumer decisions? The case of name-your-own-price auctions. J. Mark . 70, 65–78. doi: 10.1509/jmkg.2006.70.1.65

Stauss, B., Schmidt, M., and Schoeler, A. (2005). Customer frustration in loyalty programs. Int. J. Serv. Ind. Manag . 16, 229–252. doi: 10.1108/09564230510601387

Stone, M. D., and Woodcock, N. D. (2014). Interactive, direct and digital marketing: a future that depends on better use of business intelligence. J. Res. Interact. Mark . 8, 4–17. doi: 10.1108/JRIM-07-2013-0046

Strebinger, A., and Treiblmaier, H. (2004). E-adequate branding: building offline and online brand structure within a polygon of interdependent forces. Electron. Mark. 14, 153–164. doi: 10.1080/10196780410001675095

Tapscott, D., and Tapscott, A. (2016). Blockchain Revolution: How the Technology behind Bitcoin Is Changing Money, Business, and the World . Toronto, ON: Penguin.

Tönnissen, S., and Teuteberg, F. (2019). Analysing the impact of blockchain-technology for operations and supply chain management: an explanatory model drawn from multiple case studies. Int. J. Inf. Manag. 1–10. doi: 10.1016/j.ijinfomgt.2019.05.009

Travizano, M., Minnoni, M., Ajzenman, G., Sarraute, C., and Della Penna, N. (2018). Wibson: A Decentralized Marketplace Empowering Individuals to Safely Monetize Their Personal Data. Whitepaper . Available online at: https://wibson.org/wp-content/uploads/2019/04/Wibson-Technical-Paper-v1.1.pdf (accessed September 23, 2019).

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

Treiblmaier, H. (2019a). Combining blockchain technology and the physical internet to achieve triple bottom line sustainability: a comprehensive research agenda for modern logistics and supply chain management. Logistics 3, 1–13. doi: 10.3390/logistics3010010

Treiblmaier, H. (2019b). Toward more rigorous blockchain research: recommendations for writing blockchain case studies. Front. Blockchain 2:3. doi: 10.3389/fbloc.2019.00003

Treiblmaier, H., and Strebinger, A. (2008). The effect of E-commerce on the integration of IT structure and brand architecture. Inf. Syst. J . 18, 479–498. doi: 10.1111/j.1365-2575.2007.00288.x

Truby, J. (2018). Decarbonizing bitcoin: law and policy choices for reducing the energy consumption of blockchain technologies and digital currencies. Energy Res. Soc. Sci . 44, 399–410. doi: 10.1016/j.erss.2018.06.009

Twesige, R. L. (2015). A Simple Explanation of Bitcoin and Blockchain Technology . Available online at: https://www.researchgate.net/profile/Richard_Twesige/publication/270287317_Bitcoin_A_simple_explanation_of_Bitcoin_and_Block_Chain_technology_JANUARY_2015_RICHARD_LEE_TWESIGE/links54a7836f0cf267bdb90a0ee6/Bitcoin-A-simple-explanation-of-Bitcoin-and-Block-Chain-technology-JANUARY-2015-RICHARD-LEE-TWESIGE.pdf (accessed September 23, 2019).

Ubex (2019). Artificial Intelligence in Advertising . Available online at: https://www.ubex.com (accessed April 24, 2019).

Udo, G. J. (2001). Privacy and security concerns as major barriers for E-commerce: a survey study. Inf. Manag. Comput. Secur . 9, 165–174. doi: 10.1108/EUM0000000005808

Uncles, M. D., Dowling, G. R., and Hammond, K. (2003). Customer loyalty and customer loyalty programs. J. Consum. Mark . 20, 294–316. doi: 10.1108/07363760310483676

Varian, H. R. (1999). Market Structure in the Network Age . Cambridge, MA: MIT Press, 137–150.

Vend (2018). Vend's retail trends and predictions for 2018 . Available online at: https://www.vendhq.com/2018-retail-trends-predictions (accessed April 24, 2019).

Yanik, S., and Kiliç, A. S. (2018). “A framework for the performance evaluation of an energy blockchain,” in Energy Management—Collective and Computational Intelligence with Theory and Applications , eds C. Kahraman and G. Kayakutlu (Cham: Springer), 521–543. doi: 10.1007/978-3-319-75690-5_23

Yli-Huumo, J., Ko, D., Choi, S., Park, S., and Smolander, K. (2016). Where is current research on blockchain technology?—A systematic review. PLoS ONE 10:e163477. doi: 10.1371/journal.pone.0163477

Yousafzai, S. Y., Pallister, J. G., and Foxall, G. R. (2003). A proposed model of E-trust for electronic banking. Technovation 23, 847–860. doi: 10.1016/S0166-4972(03)00130-5

Zamani, E. D., and Giaglis, G. M. (2018). With a little help from the miners: distributed ledger technology and market disintermediation. Ind. Manag. Data Syst . 118, 637–652. doi: 10.1108/IMDS-05-2017-0231

Zhang, P., White, J., Schmidt, D. C., and Lenz, G. (2017). Applying Software Patterns to Address Interoperability in Blockchain-Based Healthcare Apps. ArXiv170603700 [Preprint].

Keywords: blockchain, marketing, brand, customer-centric paradigm, trust, loyalty, e-commerce

Citation: Rejeb A, Keogh JG and Treiblmaier H (2020) How Blockchain Technology Can Benefit Marketing: Six Pending Research Areas. Front. Blockchain 3:3. doi: 10.3389/fbloc.2020.00003

Received: 26 September 2019; Accepted: 20 January 2020; Published: 19 February 2020.

Reviewed by:

Copyright © 2020 Rejeb, Keogh and 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, horst.treiblmaier@modul.ac.at

† These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• 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

98k Accesses

314 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

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.

Home » Blockchain Research Topics for PhD

Blockchain Research Topics for PhD

A blockchain system is envisioned to store, process, and trace the resources regardless of central authority approval. For this purpose, each activity of transaction is registered in the distributed ledger of the blockchain. So, this technology is secure, robust, and scalable to share the resources fairly among peer nodes. For the most part, it eases the bottleneck of many-to-one network traffic. This page mainly deals with the current Blockchain Research Topics for PhD with its creative research areas and open issues!!!

In addition, it overcomes the single point failure because of its decentralized structure. Though it is one of the security mechanisms, it has few shortcomings when it is applied in real-world scenarios. And they are the issues related to privacy, consensus protocol, scalability, security, interoperability, governance, and standards.

4 Layers of Blockchain Technology

• Smart contract
• Cryptocurrency
• Digital Copy
• Proof of Stake (PoS)
• Delegated Proof of Stake (DPoS)
• Proof of Work (PoW)
• Data Storage
• Merkle tree
• Communication Mechanism
• Peer-to-Peer (P2P) Network

Our researchers have years of experience in working with blockchain technology. So, they have vast knowledge in all recent research areas. From our recent study on the blockchain , we have listed the following areas as an innovative domain to handpick the best Blockchain Research Topics for PhD.

What are the research areas of Blockchain Technology?

• Blockchain Technology for precision agriculture
• Social Blockchain Network
• Blockchain-based 5G / 6G Communication Networks
• Blockchain in Internet of Things (IoT) Security
• Blockchain solutions for Intelligent Transportation System
• Integration of Blockchain with Advance Smart Grids
• Blockchain Standards. Tools, Testbeds, and Platforms
• Artificial intelligence (AI) in Blockchain Technology
• Private blockchain Decentralized Storage Systems
• Wireless Cellular Blockchain Networks
• Blockchain-enabled Information-centric Network
• Computing (cloud, fog, edge) Services in Blockchain Network

For your add-on information, we have also listed a few research ideas for Blockchain technology projects. All these notions are collected from budding research areas to give you up-to-date research facts.

Top 10+ Blockchain Research Topics for PhD Scholars

• Impact of Blockchain in Social Networks
• Advanced Cryptographic Technologies in Blockchain
• Blockchain Smart Contracts Applications
• Data Consistency, Transparency and Privacy in Blockchain
• Emerging Blockchain Models for Digital Currencies
• Blockchain for Advance Information Governance Models
• Blockchain in Future Wireless Mobile Networks
• Blockchain Law and Regulation Issues
• Blockchain Transaction Processing and Modifying
• Collaboration of Bigdata with Blockchain Network
• Blockchain-based Public Registries Record Maintenance and Replacement 
• Blockchain in Internet of Things Applications
• Network Security Issues in Blockchain Architectures
• Accountability, Data Integrity and Privacy Issues in Blockchain Solutions
• New Blockchain Taxonomies and Trust Models in Government and Public Services

Next, we can what is consensus algorithm in blockchain and why it is important. Attainment of the smart contract is the most challenging process ever in blockchain technologies . Though it is a challenging process, it is an important task performed by a consensus algorithm in the entire system. When the new block is created is over the network, it must be added to the chain once the peer nodes are admitted. Even if the small change is done in transaction/block, it needs to be updated with peers.

As a result, it stops the attackers to hack the block and do changes until the majority of peers are compromised. Also, the blockchain structure is intended to verify the reliability of the network to ensure security. On account of this security need, several consensus algorithms are developed and some of them are given as follows, 

Blockchain Consensus Algorithms

• Proof of Activity
• Proof of Burn (PoB)
• Proof of Weight (PoWeight)
• Proof of Importance
• Proof of Capacity
• Proof of Elapsed Time
• Proof of State (PoS)
• Delegated Proof of Stake (PoS)
• Practical Byzantine Fault Tolerance
• Delegated Practical Byzantine Fault Tolerance
• Directed Acyclic Graphs

How to evaluate the performance of blockchain?

Further, we can discuss how the blockchain system is assessed. Once, the blockchain application is developed then the overall efficiency of the system is needed to assess for weighting the performance. For that, it has several performance metrics to measure the system scalability, quality, and many more. This helps to create a new standard for new blockchain in comparison with other versions. Below, we have specified a few general parameters followed in run-time blockchain execution.

• It measures the number of transactions/records that are submitted and stored every second where the submission and storage values are computed independently
• Also, it helps to know the capacity of the blockchain system for scalability
• It measures the ratio of active full and partial nodes in the network
• Through this measurement, it can avoid historical data loss due to zero active node
• For keeping enough ledger redundant copies, it is used to trace the data
• It measures the number of active nodes in the network for a certain duration (per day/week/month)
• The count of the active node should be open to all other nodes in the network
• If there are more nodes are currently active then it means many nodes are trusting that blockchain application
• It measures the time taken by the transaction to record, submit and store in blockchain
• In other words, it measures the execution time of the consensus algorithm
• To compute the number of processing blocks, it needs to be measured
• Based on the timestamp of the block, the number of blocks is determined for a particular period (per hour/day)  
• Overall, this metric help to calculate the performance and scalability of the blockchain system
• It measures the time for validating and adding the blocks to the chain
• For that, it divides the total number of transactions (commit and validate) with the total time taken by the transaction (validate and store)
• It measures the time taken between submission and registration (i.e., included/excluded in a ledger)
• Based on the transaction timestamp, it compares the time of submission and storage
• It also exposes the fastness of the consensus algorithm

Further, we have given you the three most essential factors that are required to compute the total account score. Also, these factors play a significant role in increasing the score value . Let’s have a look at the following factors,

• Transaction Number and Size : A transaction higher than the minimum size will increase the score. Also, the repeated transaction will create a positive impact
• A partnership of Transaction : Look for transactions made with other NEM accounts where more transactions will increase the score
• Vesting : Count the vested coins for a specific period where more numbers will increase the score

As you know well, consensus algorithm has high importance in the blockchain system . So, we have given the list of parameters/criteria used for evaluating the performance of the consensus mechanism/protocol.

Criteria for Consensus Algorithms Assessment

• Trust Model
• Permission Model
• Blockchain Governance
• Sybil Attack
• Double Spending Attack
• Block Creation or Latency
• Transactions per Second (TPS)
• Verification Time
• Transaction Fees
• Power Utilization
• Special Hardware Dependency
• Mining Reward

So far, we have discussed the blockchain system research point of view. Now, from the development point of view, our developers have given a few platforms that are well-suited for effectively implementing blockchain applications.

Blockchain-Based Platforms

Further, they have also listed a few widely important programming languages which support blockchain projects development. More than this, we also give you information on other blockchain programming languages.

Top 5 Blockchain Programming Languages

• Python : Hyperledger Fabric, NEO, Ethereum and Steem
• C++ : Litecoin, EOS, Bitcoin, Steller, QTUM, Ripple and Monero
• Java : NEM, NEO, IOTA, Ethereum, and Hyperledger Fabric
• Solidity – Ethereum-assisted smart contracts and other inherited models
• Go (Go language): Hyperledger Fabric, GoChain, Ethereum, and Dero
• C# : NEO, IOTA and Stratis

From the above, Python, Java, and C++ are highly used languages in developing the blockchain system. Then, Go and solidity languages are newly developed languages for blockchain projects where solidity support only ethereum projects.

            Last but not least, for the demonstration purpose, we have given the sample which gives an idea of in what way the blockchain is developed using python language. In specific, it gives information on basic requirements, implementation phases, functions, and block structure .

How to construct a Blockchain System using Python?

Basic Necessities

• Fundamental skills in coding
• IDE / Text Editors – Sublime Text and PyCharm
• Flask –Micro Web Framework (in Python)
• Python – Programming Language (Multi-paradigm)

Steps for Developing Blockchain

• At first, create the blockchain
• Then,  establish the communication with blockchain
• At last, integrate the API with blockchain

Key Methods for blockchain

• _init_(self)  –  To initialize the blockchain
• register_node() – To record a node to the network
• new_block(self)  –  To build and append a new block in the chain
• hash(block) – To implement hash function over a block
• new_transaction() – To create new transaction / record
• valid_chain() – To authenticate the chain
• poof_of_work() – To apply proof of work (PoW) consensus protocol
• valid_proof() – To authenticate block before adding to the chain

Block Structure

• Previous Block Hash
• Timestamp in Unix Time
• Transaction List

Further, if you require more Blockchain Research Topics for PhD projects , then contact our team. We will complete support to fulfill your requirements on time through our friendly guidance.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Springer Nature - PMC COVID-19 Collection

A Systematic Literature Review of Blockchain Technology for Smart Villages

Parminder kaur.

Thapar Institute of Engineering and Technology, Patiala, Punjab India

Anshu Parashar

According to the United Nations, Sustainable Development Goals are framed for improving rural health, hunger, poverty issues, environmental conditions, and illiteracy globally. With the upcoming technology, there have been many advances in the lifestyle of people all around the world. Comparatively, more emphasis has been given to the development of urban areas than rural. The sustainable development of a country depends on the growth of its rural areas. Countless technological and theoretical models, projects, and frameworks have been proposed and implemented to help overcome sundry issues and challenges faced by rural people in quotidian life. New technological methods are deemed to be the future of livability, therefore; a technologically advanced solution for sustainable rural development is called for. Blockchain Technology is the next step for innovation and development and it has far many applications in sustainable rural development that are yet to be discovered. The objective of this paper is to explicitly review research conducted in rural development to fill the undone work in the future with better research ideas, to make rural areas a livable and advanced place while also maintaining their integrity leading to sustainable development. To conduct such a review, a systematic research methodology is applied following regulations in the conduction of standardized but explorative analysis. Within the timeline of 2010–2021, 112 papers are carefully selected to perform the systematic review. This review will provide a comprehensible as well as concise research compendium for all applications proposed, implemented, and possible in the future to realize the concept of smart villages for the development of rural areas using blockchain technology.

Graphic Abstract

Introduction

The development of a country partly depends on how well connected are its rural areas to the global chain and how technologically advanced they are. Rural areas as we know of are geographical locations sited outside town or cities with fewer populations. Essentially, we also know it as a place unprivileged of vital necessities, stricken by poverty [ 1 ], and unemployment. For many years, rural areas have been developing consecutively in Technology, Education, Housing, Governance, Human rights. Accordingly, the world’s rural population has dropped from 66.389 percent in 1960–44.286 [ 2 ] percent in 2019 due to various transformations. Years ago, people in rural areas were deprived of necessities such as water, electricity, and education. Even getting a reliable source of electricity was a strenuous effort. Moreover, female rights, reliable healthcare and subsequently securing a job were more of a dream. According to the United Nations, there can be seen a steady drop in the percentage of people residing in rural areas from 1960 to 2019 [ 3 ]. What was the core reason behind it? A general example of the reason can be migration, rural decline, demographic qualities, natural disasters, and infrastructure: transportation or socio-economic. These can further be exploited into many explanations as to what leads to those choices. Rural–Urban migration itself directs catastrophic changes in the environment and economy. Rural Decline is another consequence of migration that drains the area of services, businesses, and social capital forcing the development of the rural area to halt or probably diminish [ 4 ]. Even then, almost half of the world’s population comes under rural areas and it consists of many more issues than resolvable.

This section explores the interdependent backdrops of the rural area and a feasible solution through the concept of smart villages. Sustainable development goals with respect to Blockchain Technology are discussed in sub-Sect.  1.1.2 and a brief introduction on Blockchain Technology and development techniques are mentioned in sub-Sect.  1.1.3 .

Rural Development

Sustainable Development Goals (SDGs) were framed for improving rural health, hunger, poverty issues, environmental conditions, and illiteracy globally. The present situation of rural areas brings us to a list of issues (Fig.  1 ) that can further promote the eradication of rural areas from the global chain if not technologically. Beginning with poverty which has been an issue unresolved regardless of the various monetary schemes provided by the government drives the young generation out of the community to find jobs to sustain daily needs. Many of them fail to finish even high school, which leads to securing menial jobs in urban regions. This brings us to the second issue in the rural community, illiteracy [ 5 ]. Education that plays a vital role in the overall development of humans, as well as the community, is often disregarded to fulfill contemporary requirements such as money. In many cases, the parents exploit their children into working on the farm or small family businesses.

Issues in rural areas

Typical issues in a rural school can be enumerated as teacher’s absenteeism, unhygienic school premises, and distant schools, technologically backward, absence of school records, inexperienced teachers, and teachers with false degrees. Those who get themselves educated, consider it better to get a job in urban areas because of job opportunities and better pay which is at times difficult since most villages lack communication between employees and job availability [ 6 ]. Basic hygiene and pollution are other issues in rural areas that deplete life expectancy and give birth to numerous diseases. Many rural communities do not have proper sanitation facilities, dumping grounds, or recycling plants. Not having the basic facilities drives people into a lack of personal hygiene such as bathing, washing, and cleanliness [ 7 ]. Pollution of land and soil is prevalent due to unhealthy sanitary practices. Hundreds of people still live without washing their hands leading to diarrhea, cholera, and the death of children [ 8 ]. Acknowledging the fact that medical practitioners, physicians are scarce on top of that reaching a nearby multispecialty hospital takes a lot of time [ 9 ]. The primary activity of rural people is said to be agriculture. It is considered to be the basic source of income for the dwellers. Farmers in many areas remain uninformed about the recent advancements in agro-technologies. The core reason for this incomprehension is the lack of broadband connection and incentives. Even though the Government provides various monetary as well as agricultural schemes, more than half of the farmers fail to enroll in one [ 10 ]. In addition to that from the consumer’s point, there is a whole heap of issues relating to the certification of quality produce, improper monitoring of crops, traceability of farm produce, and unsustainable agro-activities. Besides, the involvement of middlemen leaves the farmers with the minimal price of agricultural produce [ 11 ]. Further, given the aspects of daily needs, approximately 940 million [ 12 ] people around the world live without access to electricity, most of which belong to rural areas. In a generation where electricity is the basic need in every household, industry, medical center without which the whole institution of Earth would come to a halt, there are still people who do their daily activities without it [ 8 , 9 ]. About 1.7 billion [ 13 ] people in the world are still unbanked. The banking facility is essential for financial assistance especially much needed to financially excluded dwellers of the rural community. However, due to unreachable banking locations, time-consuming Banking processes, and in many cases lacking identity proof constrains the adults from applying for a bank account further reducing the chances of obtaining a loan or funding from government schemes [ 14 ].

The concept of a smart village [ 15 ] is to develop a rural area using technology as a medium. The biggest problems in rural areas are financial exclusion, poverty, hygiene, and education [ 16 ]. All the issues are interconnected and co-dependent, such as due to poverty, children in rural areas fail to get an education [ 17 ]. Due to illiteracy, the villagers do not come to know about various financial schemes. People seem to care very less about hygiene. Not only the waste is disposed of incorrectly, but it is also burnt giving rise to environmental pollution. Most of the time people do not find encouragement to learn how to properly discard waste material, to get educated, or find a solution to their financial problems [ 18 ].

Sustainable Development and Blockchain

The development of an economically backward area without jeopardizing the natural assets or future necessities is termed sustainable development. According to the United Nations, Sustainable Development Goals (SDG) [ 19 ] were adopted in 2015 for improving rural health, hunger, poverty issues, environmental conditions, and illiteracy globally (Fig.  2 ). The sustainable development goals that balance the socio-economic and environmental factors are:

Sustainable development goals

For rural development, World Bank has provided programs in public administration, agricultural markets, commercialization, and agriculture business, agricultural extension, research, and many other support activities along with social protection and transportation programs for rural communities [ 2 ]. IFAD projects for eliminating poverty and hunger, activism against gender-based violence, boosting development, investing in rural people in Papua, Food and nutrition security in Latin America boosting millet value chain, income security, and nutritional security in East Africa, Climate Risk Analysis in East and Southern Africa, Climate finance gap examination for small-scale agriculture, etcetera [ 20 ]. The IEEE smart village is an approach to empowering underserved communities, providing the power, education, entrepreneur opportunities. Following are the project initiatives by IEEE Smart Village Initiative: Mural Net(MNAZ)- Broadband to underserved on tribal lands, Regis University(RGU)- measurement and evaluation Praxis Course scholarships, Sirona Cares Foundation (SCF)- SunBlazer deployment in Haiti, Village Help for South Sudan(VHSS)- South Sudan rural electrification, Lichi community solutions (LCS)- sustainable energy kiosk for rural development, Green village electricity (GVE)- Electricity project expansion in Nigeria, Global Himalayan Expedition (GHE)- Electrification of remote Himalayan villages, Seva-Bharati India (SBI)- Sustainable development of community villages, Shakti Empowerment Solutions(SES)- sustainable energy distribution for rural consumers in eastern Uttar Pradesh, India [ 21 ].

Challenges of achieving Sustainable Development Goals (SG’s) in rural areas can be elucidated in terms of different regions. As per the research [ 22 ], in Ukraine, control over the large businesses and their impact over the agribusiness structures in addition to shrinking the number of farms, jeopardizing rural population, poverty, and fewer efforts in social cohesion improvements or remote development are the principal challenges of achieving SDG.

Similarly, as per the methodology applied by the author in [ 23 ], the major challenges faced by Romania over achieving SDG are the Socio economic discrepancy among the rural dwellers’ lives as well as the Environmental incongruity.

A few of the Sustainable Development challenges faced by the Iranian Rural communities as per the authors [ 24 ] are economic setbacks, improper management, and under-planned developments, environmental factors, social concerns, and infrastructural challenges were determined. Overall implications of the studies provide us with a concise picture of significant challenges of achieving sustainable development goals in rural areas.

Sustainability and blockchain both are the call for the future to reduce cost, increase productivity, improving health, better environmental state, and availability of food, water, and sanitation. Blockchain holds the ability for long-term and inclusive progress in sustainable development and to achieve SDGs.

Blockchain Technology

In 2008 when Satoshi Nakamoto [ 25 ] (pseudonym) proposed Bitcoin, its expansion was doubted. The rise of Blockchain was such unforeseen that some enthusiasts asserted it as the biggest invention since the Internet [ 26 ]. Although W Scott Stornetta and Stuart Haber described the first cryptographically secured chain of blocks in 1991, it wasn’t until 2009 that Blockchain was implemented as the public ledger for bitcoin transactions by Nakamoto. For a substantial amount of time, Blockchain technology was only preferred for a cryptocurrency (Fig.  3 ). However, after the introduction of scripting language into the blocks by Ethereum Blockchain to work as bonds, which are now known as Smart Contracts the inventory of applications widely opened. In his paper Nakamoto proposed to create a peer-to-peer form of electronic cash that did not require a financial institution as an intermediary and would be transferred directly between one party and another. He improved the double-spending problem in Digital Signatures by implementing timestamps on the transaction and hashing them onto the ongoing chain of hash-based proof-of-work which changed the proof-of-work if tampered with hence forming an immutable record.

Centralized and decentralized systems

Blockchain, even though it uses pseudonyms as account identifiers, has four key trust characteristics that eliminate the need for third-party authenticators. Firstly, a ledger in which after successful verification and authentication the transaction details are stored. Secondly, it is Secure since its transactions are time-stamped and hashed to the previous blocks; it makes the blockchain cryptographically secure (Fig.  4 ). Thirdly, the shared characteristic of involving multiple users provides transparency amongst all participants in the distributed ledger. Lastly, its property of being distributed eliminates operational inefficiencies, provides more security as the more the number of nodes the more resilient it is towards attacks [ 27 ].

Blockchain technology diagram

The complexity of the working of blockchain can be simplified by exploring the components that make up its architecture [ 28 ]. The main components can be enumerated as Node, Cryptographic hash functions, Transactions, Asymmetric-key cryptography, Ledgers, Blocks, Miners, and Consensus (Fig.  5 ).

Blockchain components

Node : A device possibly a computer forming the structure of a blockchain. A node is where the blockchain exists. Copies, as well as original records of the blockchain, are stored in a node. Classified as Full node and Light nodes, where Full node is a server in a decentralized network that contains the Block chain’s block history, and Light nodes are used for simple payment verification such as a wallet that queries the current status of a block.

Ledgers : A decentralized blockchain uses a ledger for record-keeping. As it is decentralized, it keeps many copies of the transaction including providing a copy to each user of their transaction.

Blocks : A block resembles a page in a record book (ledger). The first block is called the generic block. A block comprises a block header and block data where the block header consists of the history of the blockchain (previous hash value, timestamp, size of the block, and nonce) and miners perform hashing to validate the block, and block data keeps the record of recent transactions that are yet to enter the blocks.

Cryptographic hash functions : A digest or an algorithm that takes up an arbitrary amount of data and produces a hash value or hash which is an output of fixed size. It eliminates the use of a password, instead uses enciphered text that provides more security from attackers.

Transactions : A transaction is what the components work about. When two parties interact in blockchain, a transaction takes place. Authorization is required to approve a transaction between two parties. In a public blockchain, the transaction is inserted by consensus which happens when the majority of nodes validate the transaction.

Asymmetric-key cryptography : It is public-key cryptography that is used to enable certitude between the transacting parties who are unsure about each other’s integrity. Asymmetric-key cryptography uses mathematically related keys to ensure safety as well as the secrecy of data. The public key and Private key, even though relative is used for decryption and encryption, respectively.

Miners : When two users create a transaction, the miners validate that transaction in the block data before putting it on the ledger. The average time it takes for a miner to mine a block is 10 min. Since miners use their energy and hardware to solve a block, they also require an incentive for their work which is mostly paid in cryptocurrency.

Consensus : A consensus can be identified as a decision-making criterion. It makes sure that all the nodes validate a block and no such duplicity exists in the ledger that hasn’t been agreed upon. The discussion involved in consensus is used to solve identity-issue, clarify altercations, and establish a similar viewpoint between the participants by applying a set of rules.

Ethereum : introduced by Vitalik Buterin [ 29 ] addressed various limitations of the scripting language in the blockchain. The platform is used to build and publish distributed applications by using a programming language. It is said to be an improvement over the blockchain structure. It provides data-friendly services to all and sundry no matter their location or background. Ethereum consists of full nodes that run the Ethereum Virtual machine to deploy distributed programs such as smart contracts. Application development in blockchain can be done through Ethereum which can also call multiple other blockchain, protocols, and cryptocurrencies [ 30 ]. Ethereum uses the chain of global computers to operate and runs smart contracts that are free of intermediaries or third-party censorships. Ethereum uses an incentive mechanism [ 31 ] to encourage programmers who run the Ethereum functions to compensate for hardware and energy used in running decentralized digital applications (dapps). These incentives are called Ether which is a cryptocurrency in the Ethereum protocol.

Blockchain Development Platforms and Tools

To simplify the blockchain processes and to ease the development various tools and programming languages have been introduced.

Ethereum Virtual Machine (EVM)

The executing code and the Executing machine consist of an abstraction which is referred to as virtual machines, and Ethereum virtual machines increase the intended code execution chances, and the consensus is maintained on it [ 32 ].

Remix Integrated Development Environment is open-source software for web or desktop development. An intuitive and appealing interface remix allows smart contract development and Ethereum interaction [ 33 ]. Remix IDE has multiple plugin options such as Web3 integration, embedded Web3, and Javascript for running the contract locally. Solidity smart contract programming language is used for development in Remix IDE.

Smart Contracts

Simple programs stored on the blockchain comprise some predefined conditions [ 34 ]. Upon meeting the conditions the contract is self-executed giving the edge of non-intermediary processes as well as time efficiency. Multiple programming languages are used to develop smart contracts for blockchain; a few of them have been discussed below:

• Solidity [ 35 ]: A highly preferred object-oriented design-based, high-level language conveniently made for developing smart contracts. Most of the solidity syntax inspiration came from C ++ , Javascript, and Python programming languages. Solidity, along with being the top smart contract language focusing on EVM in certain also supports inheritance and user-defined types.
• Vyper [ 36 ]: Highly influenced by python and the second-best after Solidity, vyper is based on three important principles namely auditability to ensure the readability and understandability of the code for the user, Security to ensure secure smart contracts, and Simplicity of the language and the implementation.
• Yul [ 37 ]: An intermediate smart contract development language that includes the bytecode compilation according to different backend needs. The main focuses of Yul are simplicity in bytecode translation, understandability, and readability of the scripted programs. Yul supports stack machines and is specifically tailored for them, whole-program optimization, and static type reference and value nature.

Hyperledger

A Linux framework for blockchain development that provides standards and tools for open-source blockchain applications [ 38 ]. Hyperledger enterprise helps build permissioned blockchain solutions for businesses and services. Under the Hyperledger Framework, multiple projects have been introduced:

• Hyperledger Fabric : A modular permissioned and private framework for blockchain technology used for developing solutions for businesses and private enterprises. Fabric has a well updated smart contract interaction, faster transactions, and efficient data sharing.
• Hyperledger Explorer : Explorer is a user-friendly blockchain development web application tool. The interface provides detailed information about the blocks, transactions, network nodes, and the state of the blocks. Hyperledger Explorer uses visualization tools for representing the blockchain data in a user-friendly and readable manner.
• Hyperledger Sawtooth : By separating the core system, that is, specifying the business rules without interacting with the application domain is the main task of hyperledger sawtooth. It supports the Practical Byzantine Fault Tolerance (PBFT) as well as the Proof of Elapsed Time (POET). The smart contracts can be developed and run on the platform without actually knowing the core system’s design.
• Hyperledger Caliper : A blockchain benchmark tool, the caliper used pre-defined uses cases to test the blockchain solutions along with a test result of its performance. Caliper has a very proficient success rate for testing the successful and failed transactions, provides the maximum, minimum, and average latency of transaction and read data for the test cycle.

Limitations of Blockchain are limited but cannot be disregarded [ 39 ]. From the creation of the node to the validation by miners, Blockchain consumes a lot of energy. Splitting of the chain is another problem where a node does not accept the transactions in a new chain if it is operating to the old software. The computing requirements increase as the blockchain grows. Since all the nodes cannot provide the necessary capacity, the node breaks, and the immutability and transparency of the blockchain cease to exist.

Blockchain for Smart Village Applications

The scenario in a typical village is such, in terms of the infrastructure most of it is inadequately built, there exists schools and colleges but poorly maintained, poorly built houses with no constraints for disaster management. In terms of necessities, normal villages lack stable electricity supplies, or a secure income to support electricity bills, and non-purified water. People in villages are often neglected and most of the dwellers don’t have any personal or national identity. The healthcare system in villages is simple and inefficient which does not help during major problems. Normal villages lack any technological advancement and people there live in history because of the lacking development. Sustainable development with the concept of smart villages can give a secure and feasible future to the villages.

Beyond the conventional use of blockchain in finance using cryptocurrency, numerous applications can change the way we perceive digitization. According to Kandaswamy [ 40 ], blockchain can have four types of initiatives: blockchain disruptor, digital asset, efficiency play, and record-keeper (Fig.  6 ). With similar inventiveness some of the blockchain applications with the concept of a smart village can be enumerated as:

Blockchain elements

Healthcare : Blockchain with its record-keeping characteristics and smart contract with its privacy and security has greatly assisted the medical area by providing a solution for publicly or semi-private sharing of the medical data of patients. This can help the researchers and students to elicit a new solution or use it for clinical trials [ 41 ]. The solution for missing health documents or previous clinic visit records can be improved through blockchain. The potential of Blockchain to store patient’s record on the ledger make it possible to get treatment across the globe. Furthermore, the problem of counterfeit drugs in the market can be resolved through the traceability solution from blockchain through which fake medicines can be traced and removed from the supply chain.

International payments and insurance : Accelerated payment to international locations is possible through blockchain technology. Several Bitcoin-operated services make it easier to transfer money cross-border. The process includes converting the payer’s local currency into Bitcoin bypassing the existing banking infrastructure and then converting that Bitcoin into the receiver’s local currency. This saves the trade cost and speeds up the transaction. Apart from that, the insurance industry can also be benefitted from blockchain technology [ 42 ]. Blockchain can provide a transparent and trustworthy system to overcome the challenges of the insurance industry. Fraudulent claims, intermediary payment transactions, and big data handling are some of the many issues faced by insurance companies. Blockchain can resolve the issues through its security and transparency provided by the distributed ledger which also furnishes the authenticity of the participants. Besides, its characteristic of record-keeping comes in handy with the huge amount of customer data that is immutable in the blockchain ledger. Additionally, by using the smart contracts real-time data of the claims, reimbursements or payments can be fetched from multiple systems in no time.

Personal Identity Record-keeping : Identity is an integral part of society that provides a unique character and sense of acceptability in a country. However, physical forms of national identity are not accessible to many people around the world. The absence of identity makes it difficult for people to participate in voting, banking, employment and limits the chances of access to the financial system. Here blockchain steps in by providing identity solutions through digital identity. Additionally, self-sovereign identity arranges options to store one's identity on devices accessible across the world [ 43 ].

Supply chain and logistics : Blockchain can bring great usability to supply chain management. Procurement, traceability, digital payments, and logistics are some areas that have benefitted from blockchain technology. The distributed ledger can reduce the sharing of operational data by providing a full view of the sale/purchase data, accessible from any device. Fraud in the food supply chain is prevalent in many countries. Counterfeit products selling in the market prove hazardous to the consumer. The Block chain’s QR tracking system along with digitized physical products can be used to track products from production to delivery [ 44 ]. This technology has started benefiting the agricultural sector to develop food safety and smart farming increasing the income of small farms and food producers.

Education : Keeping physical records and transcripts can be a hassle. This blockchain provides a solution for digitizing student records, transcripts, and payment receipts [ 45 ]. Digital record-keeping can benefit a student as it will be acceptable by universities across the globe, free of manipulation, and handy. Blockchain can also be used to incentivize students through a course credit system. The credit can be translated to cryptocurrency, which can be further used as fee payment.

Blockchain with the Internet of Things (IoT) : Powerful union of two futuristic technologies makes machine-to-machine transactions easier. The decentralized authority of blockchain combined with the smart devices run by IoT allows a function to autonomously execute without a central authority [ 46 ]. Smart IoT run devices can be implemented on edge devices, reducing data transfer costs, and security issues with the blockchain collaboration [ 47 ]. Blockchain integration with IoT can highly change the agricultural sector. Supply chain traceability could benefit the farmers in eliminating the intermediaries through traceability and RFID tag-based applications. Water, soil, climate, and other sensory-type IoT devices can help in monitoring the agricultural activities and gathering the farm data and activities such as cultivation and livestock data in the blockchain ledger. IoT with blockchain will certainly revolutionize and transform many rural and urban sectors.

Motivation and Major Contributions

Sustainable Rural development starts with the participation of rural people in improving their lifestyle. Without the people working for their development, any implementation or help is incomplete. Economic and technological sector links are important for rural areas to develop. Along with that, a healthy agricultural sector improves the dweller’s linkage to the global supply sector. By managing the social, economic, environmental, and health objectives the development can be fast-forwarded. There is a considerable amount of potential in rural people which can be applied to employment issues, social disparities, E-governance, women's rights etcetera. Developing rural areas can benefit nationally, economically, and financially. This systematic literature review aims to provide extensive literature related to blockchain’s application in rural development and sustainable living. A plethora of blockchain review papers available does not provide a collective literature review of blockchain applications divided into different areas directed towards rural and sustainable development. Therefore, clear and concise information can be gained about blockchain’s work in improving rural development providing scope for future research in this direction. The primary contributions are mentioned below:

• A systematic review of relevant literature for research trends, key applications, and areas of implementing Blockchain Technology for smart villages for sustainable rural development.
• Identification of major issues in rural development and how they can be addressed using Blockchain Technology.
• Exploration of the existing software, platforms, and tools for the implementation of Blockchain in Rural Development.
• Identifications of the research gaps and future research directions for applying Blockchain Technology to Rural Development.

To conduct a fair and precise literature review, the studies have been selectively chosen after processing through the query string, and inclusion and exclusion criteria. The relevant set of research questions are formulated as depicted in Table ​ Table3 3 and also addressed in their relevant sections. The complete review methodology process is elucidated in Sect.  2 .

Research questions

The remaining paper is organized as follows: Sect.  2 presents the details and process of the review methodology adopted to include relevant studies for literature review. Section  3 presents an extensively reviewed literature study of the papers selected through review methodology. Section  4 , presents the critical analysis and discussion of the reviewed papers for a clear perspective on the existing work in Blockchain Technology pertaining to rural development and for future research directions. In Sect.  5 , the limitation of this work is mentioned. Section  6 , finally, presents the conclusion and future scope.

Review Methodology

The systematic review was conducted with relevant articles on blockchain technology in rural development. To perform a systematic review, Kitchenham’s and other related guidelines were followed [ 48 – 50 ]. To provide a transparent, systematic, understandable review of papers multiple sites and journals were visited, segregating articles into the various application of blockchain technology. The main objective of a systematic review is to write a planned article to relay a comprehensible, clearly stated literature after repeated analysis to define a problem, be replicated, or identify research gaps. To find a relevant article miscellaneous Journals, digital libraries, and web sources were delved into.

Search Strings

To find a relevant article, the following sources were considered: ACM Digital Library, IEEE, Science Direct, Elsevier, and Springer. Along with that Google Scholar was used as a web source where a broad search for scholarly articles is possible. The keywords and strings are listed in Table ​ Table1 1 .

Search criteria

Selection Criteria

To search for articles best suited for the review, the following (Table ​ (Table2) 2 ) selection criteria were applied.

Inclusion or exclusion criteria

Process Flow

The process of forming a literature review consisted of selecting relevant papers, applying inclusion or exclusion criteria on them, and reviewing them (Fig.  7 ). In the process, a total of 157 articles were considered out of which 112 papers were reviewed pertaining to the keywords specified in Table ​ Table1 1 .

Systematic review process

Research Questions

To identify the scope of the systematic literature review, few research questions have been formed. The research questions along with the explanation on the depiction of the answers are shown in Table ​ Table3 3 .

Relevant Literature Trend

From all the papers reviewed consisting of applications of blockchain in rural development, the following applications were recognized: Agriculture, Banking, healthcare, energy, Environment, and Employment. Additionally, the articles consisting of incentive mechanisms were segregated (Fig.  8 ). From each of the applications, different areas were identified concerning each application (Fig.  11 ). Table ​ Table4 4 is a detailed table with application areas and its definition concerning Blockchain in rural development.

Distribution of Blockchain applications in rural development

Relevant literature: blockchain application for sustainable rural development

Areas of blockchain application in rural development

Publication Distribution

To provide a simplified view of the literature review for better understanding the articles are distributed according to the peer-reviewed journals, conference papers, and chapters as shown in Fig.  9 .

Publication distribution

The articles are further distributed according to the applications type while also displaying the number of articles and their publication year in Fig.  10 .

Number of articles and their area of publications (2016–2020)

For further classification, the geographic distribution of papers was performed with 112 papers (Fig.  11 ), distributed in 37 countries as shown in Fig.  12 with India, China, and the USA is the largest publishing countries followed by Italy, Spain, and Pakistan for blockchain applications in rural development.

Geographical distribution of articles

Publication Type

The distribution of the articles according to different publication types was found (Fig.  13 ) with the largest number of publications (61) in The Institute of Electrical and Electronics Engineers (IEEE), followed by (27) in Springer, (16) in Elsevier, (3), and (5) in ACM digital library and Science direct respectively.

Distribution of articles by journal type

Literature Review on Blockchain Technology for Sustainable Rural Development

The literature review consists of the collective work of blockchain in rural development. A total of 6 areas of application were identified after careful extraction of data and transformation globally namely: Agriculture, Banking, Environment, Energy, Employment, and Healthcare. A detailed discussion on the related work is discussed in the subsections.

Agriculture

In the agriculture sector, most of the application areas included supply chain traceability, facilitation of smart agriculture, and incentivization of services (Fig.  14 ). A detailed summary is given in Tables ​ Tables5, 5 , ​ ,6, 6 , and ​ and7 7 .

Agriculture supply chain traceability diagram

Comparison of blockchain in agriculture supply chain traceability

Comparison of Blockchain application areas

Comparison of Blockchain applications in Incentivization

Supply Chain Traceability

The author F. Tian, [ 51 ] studied the integration of RFID (Radio-frequency Identification) and blockchain technology in building the agri-food supply chain traceability system. With the help of blockchain technology, the information shared and traceability is guaranteed. Apart from the supply chain, it also regulates food safety and quality supervision. This system can enhance the credibility and reliability of agri-food safety information. With the depletion of an application cost, this system can effectively change the current supply chain to be more quality-enhanced and safe. Similarly, Hua et al. proposed an agriculture [ 65 ] provenance system based on blockchain featured by decentralization, collective maintenance, consensus trust, and reliable data to solve the trust crisis in the product supply chain. The system’s Target is to record information related to the production supply chain: production, processing, storage, transportation, and distribution of agricultural products. It also facilitates Recordkeeping from basic planting information to provenance records. The proposed work solved the issue of the credibility of data and the difficulty of integrating the subsystem of each company.

The paper by Casado-Vara et al., [ 58 ] addressed the issues of the current supply chain such as communication gaps between vendors or the opacity of the origin of the product. The author has proposed a new model of the supply chain via blockchain where all the members of the supply chain save all their transactions in the blockchain to ensure higher security. This model also enables a circular economy that is a make-use-recycle model. With this model, all products can be traced from their origin to their sale and subsequent recycling.

Further, Caro et al., [ 70 ] presented AgriBlockIoT which is a fully decentralized blockchain-based traceability solution for agricultural food supply chain management. The proposed architecture based on API includes a controller to convert high-level function calls to corresponding for the blockchain layer and blockchain itself which is the main component of the system. The collaboration of IoT and blockchain can create transparent, fault-tolerant, immutable, and auditable agri-food traceability records. The authors Li and Wang, [ 85 ] characterized the research applications of blockchain in food supply traceability. With the help of blockchain technology and various radiofrequency devices can be integrated to collect data from farms, deploy sensors, and create intelligent contracts to implement server logic. The new system can change the traditional food supply system by making it more convenient, efficient, and trustable. Kim et al., [ 54 ] presented a theoretical, end-to-end, vis a vie “farm-to-fork”, food traceability application named Harvest Network with the integration of Blockchain technology and Internet-of-things. The process includes tracing the products from processing, grading, transportation, temperature, and contractual payment all with blockchain, IoT, and smart contracts. This can help consumers gain field-level insight into the products. Lin et al., [ 63 ] proposed an IoT and blockchain integrated self-organized, open, and ecological food traceability system. The proposed model consisted of trade, logistics, delivery, and warehousing information as well as data from IoT devices such as soil humidity, soil pH, and soil nutrition. The concept was to enable a user to get detailed information about the product they buy with the help of a trusted, self-organized smart agriculture ecosystem.

Galvez et al., [ 78 ] review the potential of blockchain technology in guaranteeing traceability and authenticity in the food supply chain. The review included blockchain solutions to traceability problems. It explained the use of a chronological distributed database to coordinate individual activities. By using a probabilistic approach to enable transparency and verifiability without a central authority, enabling consensus on a transaction to secure legitimate transactions, and time-stamped blocks providing immutable records to preserve records the traceability issues were solved. The paper also discussed the Block chain’s concept on the food supply chain which provides transparency, efficiency, security, and safety to the food produce. According to Kamble et al., [ 55 ], the supply chain practitioners found a lack of efficiency and transparency which leads to constant threats to formers and consumers. The system deployed the ISM methodology to identify Blockchain technology enablers in the agriculture supply chain. The findings implied the acceptance of blockchain technology as an innovative tool to ensure an efficient agriculture supply chain by the practitioners. To achieve further traceability the farmers could capture relevant information about the agricultural events onto the blockchain to enable transparent and trusting sources of information for the farmers. Kamilaris et al., [ 60 ] explored how the food supply chain and agriculture were impacted by blockchain technology. The stages of the supply chain with blockchain technology has been identified as (1) the provider (2) producer, (3) processing, (4) distribution, (5) retailer, and (6) consumer where a web application or device can be used to scan the item’s QR code to view its detailed information. Along with this, the author explored various challenges and benefits of the agricultural supply chain and Blockchain’s collaboration. Salah et al., [ 66 ] proposed a solution of eliminating the third parties and centralized authorities in the food supply chain along with a security system for food traceability, transparent records, and governance of interactions and transactions between the users. The model entities are related to providing secure tracking of the product and payment with Ethereum smart contracts. Thus, the presented model for traceability can be used to trace and track the soybean supply chain. S. Missineo, [ 75 ] proposed a model to secure storage origin provenance for food data. The proposed system aims to certify the production and the supply chain concerning food local products by using Blockchain Technology and Smart Contracts. The author aimed to ensure the authenticity of typical Sardinian products and to sell them online or offline. The platform ensured the consumer to check the authenticity of the product before the purchase giving details on both the production chain and supply chain. Jaiswal et al., [ 86 ] proposed multiple smart contracts deployed on the Ethereum blockchain for decentralized trading of food grains. The framework included Peer-to-peer trading, the security of food grain data, transparency, user anonymity, trust, and incentives as key features. The design of the framework consisted of four contracts namely food grain supply, bidding, trading, and utilization for the supply chain management. Dong et al., [ 56 ] proposed a collaborative model of blockchain and IoT in the agriculture sector. The data collection and transmission can be distinguished through a unique identity card given to each agricultural product. All the environmental aspects of the agricultural process can be gathered at the source. Along with that crop growth information, circulation of the product using an RFID tag and distribution process can also be recorded and stored on the distributed ledger. A QR code attached to the product can be scanned by the consumer to view product information in details.

Withal, Madumidha et al., [ 145 ] proposed the use of blockchain technology to maintain tamper-proof records, avoid intermediaries and provide security to the transactions which in turn reduces transaction costs and improves the quality of the products. The food products are labeled with RFID tags to maintain the supply chain. The author explained the revolutionary changes blockchain technology can bring to the supply chains and how it can increase the economic conditions of a country by reducing corruption rates and increasing the satisfaction of producers and consumers. Paul et al., [ 83 ] proposed a way to eliminate intermediaries between farmers and consumers to provide the right amount for the farm produce. The proposed system consists of blockchain nodes namely Supply companies, landowners, markets, and farmers. The farmer node sets the amount after the agreement period, the market node collects and stores crops and stops intermediaries from manipulating the prices, the landlord node collects the money from the land on lease, and the supply company node sells extra agricultural products to the farmers. This platform named KHET where all the nodes are interconnected through Ethereum blockchain is beneficial for farmers, landlords, and markets.

Musah et al., [ 62 ] main objective in proposing the role of blockchain in Ghana’s cocoa beans food supply chain was to evaluate the contributions made by applications of blockchain technology in the supply chain. The system provides a global traceability platform, supply chain intelligence and visibility, Africa cocoa village; impact the investing for smallholder farmer and uses Bean tracker. The author carefully studied the tools and platforms benefiting the cocoa bean production and supply chain processes.

Additionally, Baralla et al., [ 146 ] proposed a blockchain-based generic agri-food supply chain traceability system for implementing the farm-to-fork model. In this system, a QR code scan can allow the consumer to reconstruct the product history to verify product health and quality. The main contribution of this article was the authentication and verification of shared data’s integrity in supply chain management. With the help of this system, the involved operators could identify any new participants along with the supply chain which increased the degree of trust between organizations and individuals. Dakshayini et al., [ 87 ] proposed an integrated model based on Blockchain, big data, and cloud to efficiently manage crops that achieve effective demand-based decision support, simplified, transparent, and secure agricultural supply chain. The proposed model has a higher percentile of achieving demand and supply of crops which avoids the farmer’s loss, catering to consumer’s needs, provides sustainable agricultural practices, reducing middlemen involvement, and reducing price inflation problems. Saji et al., [ 88 ] proposed a model to enhance the supply chain performance by using a blockchain network. The proposed model provides security food safety, traceability, and opens new markets. The system improved farming profitability and endorsed the financial stability of cultivators. It also provided health benefits, reduced food wastage, eliminated manipulation, and adulteration, and supports the supply chain of agro-products. Saurabh and Dey, [ 69 ] identified the potential divers of blockchain concerning the grape wine supply chain. The smart contract-based module was constructed to ensure trust between participants during transactions. The proposed model enhanced the customization, competitiveness, and usability of the supply chain.

Iqbal and Butt, [ 84 ] proposed a model to save the farmer’s crops from animals at night. A repelling and notifying system (RNS) is installed in the field that receives signals during an animal attack. Human-safe ultrasonic waves are produced by this RNS which drives the animals away. This proposal also consists of a farm management system that receives the report regarding the hazards caused in the fields. This system enabled timely data delivery, efficient multi-hop communication, dependable data transmission, and low-cost technology. Chun-Ting et al., [ 73 ] proposed a blockchain-based agricultural traceability service platform for tamper-proof data storing and backup. The system design consists of Data collecting layer where IoT sensors collect environmental data, the blockchain layer takes data from the formal layer and sends them to blockchain nodes and later to blocks, and the application layer handles the requests to access transaction data based on the transaction hash. Hegde et al., [ 81 ] presented different ways of implementing blockchain with the agricultural supply chain. With the use of blockchain, the producers can get data and income security, and keep track of environmental changes that affect the crops. The traceability option provides clarity in any damage that occurred to the product and an overall increase in efficiency can be achieved by producing only required products hence reducing wastage. Peña et al., [ 89 ] presented a systematic review on blockchain in food supply chain management in Ecuador. According to the review, most of the work was done in Hyperledger composer, models for business interactions and human interactions, Traceability, Security, and Blockchain Information.

Additionally, M. Kumarathunga, [ 57 ] after reviewing presented the way to reduce transaction costs and improve farmer’s involvement in agricultural supply chains. To reduce transaction costs farmers can participate in Information sharing, goal congruence, decision synchronization, incentive alignment, resource sharing, collaborative communication, joint knowledge creation. Xu et al., [ 80 ] reviewed the working principle of blockchain technology in the agri-food sector. Blockchain technology provided data transparency, data traceability, food safety, and quality monitoring, and agriculture finance. Additionally, food safety and quality can be secured by digitizing products. According to the review, blockchain revealed a better approach to the future of the agri-food supply chain which is safer, healthier, sustainable, and reliable. Mirabelli and Solina, [ 71 ] collected and analyzed the applications of blockchain technology and its contribution to agricultural food traceability issues. The review showed that the usability of blockchain technology in the agricultural sector was still in the early stage. The review highlighted three main aspects namely starting problem, area of interest, and contribution. Blockchain can be a valid way to minimize fraud and errors in agricultural supply chains by increasing the quality and safety of food products. Shahid et al., [ 53 ] have proposed a complete solution to the blockchain-based agricultural and food supply chain. The paper aimed to provide an end-to-end solution to the growing blockchain-based agri-food supply chains. Further, it achieved the following properties: accountability, credibility, auditability, autonomy, and authenticity. The system also acted as a better alternative to the existing supply chain system by enabling a scalable and auditable system. Awan et al., [ 79 ] proposed a smart agricultural model as a transformation to the traditional agricultural supply chain. The system consists of Seed seller, Farmer, Crop buyer, Processor, Crop storage, Distributor, Retailer, Customer. To improve the food supply chain’s productivity and reliability the smart model was proposed. The model allowed farmers to enter and monitor the data in the plant. The main objective of this model was to provide equal opportunities to the participants of the agricultural food supply chain. Thejaswini and Ranjitha, [ 64 ] proposed a model that explores the problems faced by people in agriculture production and its solutions based on blockchain technology. Blockchain solutions for traceability of crops, disclosure of data, clarity in food production, and authentic agricultural products was proposed by the author. This proposed model ensured food safety, benefitted farmers, and stakeholders.

Yadav et al., [ 67 ] reviewed the blockchain adoption barriers in the Indian agricultural supply chain. The barriers can be enumerated as Lack of proper government regulation and regularity uncertainty, Huge resource, and initial capital requirement, security and privacy concerns, lack of interoperability and standardization, etc. Further, the barriers were modeled using an integrated ISM-DEMATEL approach which provided limited interpretative logic. W. Lin, [ 59 ] provided a survey to study the techniques and applications of blockchain technology. The application categories of blockchain in agriculture are Provenance traceability and food authentication, smart farming data management, trade finance in the supply chain management, and other information management systems. The paper also indicated possible future developments and applications of blockchain. Dutta et al., [ 61 ] reviewed articles related to blockchain technology’s integration with various supply chain operations. The benefits of Blockchain in supply chains can be enumerated as Data management, Improvement in transparency, Improvement in response time smart contract management, Operational efficiency, and Disintermediation, Immutability, and Intellectual Property management. According to the review, the main supply chain functions were identified as supply chain provenance, supply chain resilience, supply chain re-engineering, security enhancement, business process management, and product management. The work also examined various challenges and impacts of blockchain in the supply chain. Shahid et al., [ 77 ] proposed a solution for a blockchain-based reputation system in the agriculture and food supply chain. The system model consisted of invoking smart contracts to provide reviews based on the services to the providers. The reviews are requested by buyers and the sellers’ review the transactions and perform other transactions based on that. The system was proposed to maintain the immutability and integrity of the registered review. Torky and Hassanein, [ 82 ] presented a comprehensive survey on IoT and blockchain and their importance in developing smart applications. According to the review, crops overseeing, livestock grazing, and food supply chain are a few subsectors in precision agriculture managed by blockchain platforms. Apart from that, a novel blockchain model was also proposed to use as an important solution for major challenges in IoT-based precision agricultural systems. The objectives of Skender and Zaninović, [ 74 ] in their paper were to analyze blockchain technology’s overall perspective, investigate its potential in a sustainable supply chain to replace the shortcomings in the traditional supply chain. The traceability and transparency in the agricultural supply chain can be improved with blockchain.

To better understand the benefits and challenges and the perspective for sustainable blockchain, the author provided a conceptual framework. Borah et al., [ 68 ] proposed a novel blockchain-based Farmer and Rely called FARMAR. The system could provide fair prices and reduce duping by middlemen. The assets can be traced from farmers to consumers, reducing the artificial inflation of prices. Ferrag et al., (2020) [ 76 ] reviewed the research challenges on IoT-based agriculture and its security and privacy issues. The rest of the paper identified threat models against green IoT-based agriculture analyzed the privacy-oriented blockchain-based solutions and consensus algorithms for green IoT-based agriculture. Enescu and Ionescu, [ 52 ] proposed a model for farmers in the agri-food sector using blockchain. This system ensures a credible supply chain for producers and consumers, guaranteed timely payments between the participants. The authors proposed this system to provide transparency, security, and trust in the trading process. Chaudhari et al., [ 90 ] proposed a framework for a secure and transparent supply chain with the help of blockchain technology. With the help of this system, the farmers can get a fair price for their products. This transparent and tamper-proof supply chain system generates a bill at the end including the commissioning price as well as the total price after sold product hence benefiting the farmers in knowing the selling and market price. Xie et al., [ 91 ] proposed to construct a traceability framework For fresh E-commerce agricultural product quality and safety based on blockchain technology. To access the key control points the author used the FMECA (failure model effect and key analysis) to analyze the failure mode, impact, and hazards in the traceability chain. This system can promote agricultural development through decentralization, consensus trust, maintenance, and reliable database features.

Furthermore, Li et al., [ 92 ] proposed a blockchain-based Traceability of the fresh food supply chain With the help of business process reengineering (BPR). The overall traceability architecture is based on key links’ product quality data and participants’ transactions. The objective of this traceability system was to ensure data integrity. Flores et al., [ 93 ] proposed a model for decentralization of data and provide traceability of agricultural products with blockchain technology. Using this method could guarantee transparency of the supply chain and other operations as well as the transactions involved. Fernandez et al., [ 94 ] proposed a Blockchain-based model to improve farmer’s profits. The author aimed to improve the output primitives of the supply chain. Farmer-to-consumer product tracking and cost were the main factors in improving traceability in the supply chain. Cortez-Zaga et al., [ 95 ] proposed a model used in the Peruvian agricultural sector using blockchain. When using blockchain it can eliminate dependence on a central entity, provides integrity of the process, transactions become irrevocable, secure, and private, and provides transparency and immutability. G. Zhao, [ 96 ] presented a systematic literature review that explored the advances in the agri-food supply chain. The paper also pointed out the challenge of the applications of blockchain technology enumerated as storage capacity and scalability, privacy leakage, high-cost problem, regulation problem, throughput and latency issues, and lack of skills.

Land record maintenance using blockchain was also proposed by Bhorshetti et al., for easy maintenance of land records in real-time. The database proved to be a non-failure system and the work provided intermediary-less land title transfer and processing between owners. This system provided security, transparency, and a broker-free land management system [ 97 ]. The paper by Thakur et al. presented the issues related to land records maintenance, registration, settlements, and banks. The system ensured better land management, lesser fraudulent transactions while strengthening the sustainable development goals (SDG) and increasing the GDP of the country [ 98 ].

Agriculture Security System

Tse et al., [ 102 ] proposed food supply information security based on blockchain technology. The use of blockchain in this system can regain the people’s trust in the food market, the government can collect statistics on various kinds of food, and adulterated and fake food in the market can be eliminated. This type of technology can benefit the customer, manufacturers, and supervision departments of the food supply chain. Wu and Tsai, [ 103 ] proposed an intelligent agriculture network security system by applying dark web technology to monitor packet transmission frequency in order to prevent DDOS attacks. The system applied a darknet mechanism to identify anyone who attempts to access blockchain data. It also incorporated IoT sensors to gather data regarding temperature, humidity, and soil. This model was proposed to keep track of the farms and cultivation factors related to an environment and to establish network security for IoT networks.

Organic Farming

Reddy and Kumar, [ 101 ] presented the article based on the sustainability of the food supply chain. The author's objective was to achieve Fair Trading and a circular economy with the help of blockchain technology. With this framework, the following results but achieved: Automatic hashing for less electricity consumption, product malfunctioning and add alteration, the involvement of middlemen, availability of farming jobs, and facilitating development and unity among farmers. According to Basnayake and Rajapakse, [ 104 ], the purpose of the research was to implement a Blockchain-based solution to verify food quality. The process included Farmers issuing a product contract to control the quality of each product. For each deployment of the product contract, it would return an address that was used to generate the QR code to identify the physical product. Lastly, Consumers were also eligible to rate the product quality to ensure trust.

Smart Agriculture

To overcome remote monitoring challenges and provide security and privacy in agriculture, Patil et al., [ 105 ] proposed a lightweight architecture for smart greenhouse farming. The model consisted of four groups showing the integration of blockchain with IoT namely (1) smart greenhouse, (2) overlay network, (3) Cloud storage, and (4) End-user. This model can be used to successfully monitor the secure transmission of greenhouse data. Umamaheshwari et al., [ 106 ] proposed a model for Buying and selling crops and land. The model used Ethers as a cryptocurrency. According to the paper, the recordkeeping of crops grown in the land was useful to know the history of plantations in the land. With the help of this model, users were able to access real-time data about crops, eliminate the need for middlemen, and establish a transparent and efficient system. Voutos et al., [ 107 ] proposed the integration of IoT and smart contracts to develop smart agriculture to deliver higher quality agricultural products. It also focuses on improving the associated supply chain and logistics benefiting the participants involved. The author discussed the factors of smart agriculture as soil factors, climate, sensors, research, supply chain, storage, analytics, and smart contracts. Miloudi et al., [ 100 ] proposed IoT, Blockchain, and Geospatial technology-based Smart farming to manage the farming practices more smartly and sustainably. The system proposed smart farming management in 4 stages namely (1) Integrated blockchain with IoT platform where various IoT sensors apply analytics and sends data to the blockchain, (2) Blockchain Working Methodology where data visibility is provided through smart contracts, (3) Integrating GIS with blockchain where the data sent from IoT sensors are improvised and accuracy is facilitated through GIS geospatial tools, and (4) certifying farmers in blockchain stage facilitates authorities and privileges to the farmers through smart contracts which could greatly benefit farmers and food production industry.

Furthermore, Devi Et al., [ 108 ] Proposed a design architecture by merging IoT and BC for smart agriculture. The nodes involved in the blockchain received the information from the sensors that were connected to the things involved in the Smart Agriculture monitoring process. The design architecture enhanced the security and data transparency performance of smart agriculture. Vangala et al., [ 109 ] reviewed blockchain technology and its information security schemes. The application areas covered by the authors were agriculture monitoring, controlled agriculture/smart greenhouses, food supply chain tracking, and precision farming/smart farming. The review also presented a thorough analysis of the security attributes, application areas, advantages, drawbacks, and competing schemes’ cost of computation and communication. Branco et al., [ 110 ] proposed a conceptual approach with the integration of IoT and blockchain for a mushroom farm distribution process control system. The proposed system allowed the collection of distributed data on the environmental factors contributing to mushroom production providing collection, storage, and processing of mushroom farm data to be scalable, immutable, transparent, auditable, and secure.

Dairy Farming

Misra and Das, [ 111 ] presented a conceptual framework using blockchain to bring feasibility and efficiency in E-governance. The architecture consisted of a service-oriented architecture framework to store details of stakeholders involved in user services on demand, a blockchain architecture that would allow stakeholders to authenticate and perform transactions on the ledger, and digital identity architecture to act as a regulator in the architecture. With a dairy farmer as a user or participant in the architecture who would benefit from the transactions while having voting rights and leadership entities in the system the author conceptually explored the prototype of the dairy cooperative sector in India. Similarly, Rambim and Awuor, [ 112 ] proposed a model for dairy farmers in Kenya that explores the potential use of blockchain technology in milk delivery in rural areas. From the Naitiri Dairy farmers’ cooperative (NADAFA) in Kenya, the author introduced a Milk Delivery Blockchain Manager (MDBM) which is a decentralized platform to automatically capture the quantity and quality of milk delivered by the farmers. The delivery data stored in the blockchain is immutable, cryptographically hashed, and digitally signed. The details of delivery are accessible to the farmers. The NADAFA facilitates the system and provides payment to the dairy farmers on time. The consortium-based network provides leveraging blockchain solutions for farmers.

Under Livestock monitoring, Alonso et al., [ 113 ] worked on important trends in the applications of IoT and edge computing paradigms in the smart farming field. This helps producers to optimize processes, provides the origin of the product, and guarantees the quality to its consumers. The state of dairy cattle and feed grain can be monitored in real-time by using artificial intelligence and blockchain technology. This is to ensure the traceability and sustainability of different processes of farming. The implementation of smart farming contributed to the reduction of data traffic and reliable communications between IoT-Edge layers and the Cloud. According to Hang et al., [ 114 ], the uncertain data quality of analysts’ data can be solved through blockchain. The proposed structure brings scalability, off-chain storage, privacy, and high throughput as advancement to the previous version. Various IoT data is fetched from fish farms such as temperature, water level, oxygen, and PH data. The data storage can be a database or cloud and end-user can view the fish farm’s detailed information through smart devices. Leme et al., [ 147 ] proposed a novel infrastructure based on the integration of cloud storage and blockchain technology to monitor the overall health of livestock. The components of the architecture can be named as (1) Administrator, (2) Users, (3) Cloud service, and (4) blockchain network. With the help of RFID tags attached to the cattle, various entities can be monitored to ensure that cattle go through necessary procedures. Yang et al., [ 115 ] proposed a novel method to ensure traceability and authenticity in the livestock supply chain using blockchain. The model uses RFID-sensor-based livestock monitoring in the food industry where the sensors augment the physical tracking and solved the RFID’s inherent computational capacity limitation by using cloud services. The data is then made accessible to the end consumer through Block chain’s transparent ledger.

E-Agriculture

The analysis proposed by Li et al., [ 116 ] Investigated the convenience of sustainable electronic agriculture based on Blockchain technology and analyzed the application likelihood and challenges of Blockchain in the agricultural field. The authors selected 5 villages with similar development rates in china and Blockchain technology was applied using data statistics to the sustainable e-agriculture for exploring its convenience. Results showed that sustainable electronic agriculture based on Blockchain Technology brought great convenience to the farmer’s sales, increasing by 25% on average compared with traditional electronic agriculture. Song et al. [ 117 ], to improve the biased point of view, higher initial costs, and lack of transparency and trust proposed a system for providing sustainability in the current agri-food supply chain. The paper discussed blockchain adoption in rural areas and relative energy consumption from supply and demand perspectives.

Agriculture Monitoring

Arshad et al., [ 99 ] proposed a private blockchain-based secure access control for agriculture to monitor climatic parameters. Private Blockchain access control (PBAC) was used to guarantee secure communications where a user usually goes through initialization, authentication, and revocation. The farms monitoring system consists of the login phase, system setup phase, user/farm professional registration phase, password authentication and session key agreement phase, update or change phase, and addition of node phase. The whole system stores access records and lessen the computational and communication overhead. Forbye, N. Bore, [ 118 ] proposed a model to improve the shortcomings of existing digitized farming models through the AG-Wallet System (AGWS). The AGWS design consisted of (1) digitizing the far demand–supply, (2) The farm information pipeline was to ensure secure storage and validate events received from IoT, and (3) data analytic services that make the information visible to the participants. The system proposed by Osmanoglu et al., [ 119 ] uses a blockchain-based yield estimation solution. Farmers can share the farming plans for the upcoming harvesting season with other participants, or learn from other’s plans to review their plans. Smart contracts can be employed by participants to share their yield commitments. The author improvised a censorship-resistant, tamper-proof, and immutable public ledger of time-stamped transactions.

Talreja et al., (2020) [ 121 ] proposed a farmer’s portal with the help of blockchain technology and python to preserve the contract of trade between farmers and consumers. The farmer’s portal is a way to access farm activities. The proposed work enhanced the degree of participation, reduced intermediary cost, simplified process, provided ease of selling crops, and greater efficiency. The immutability of blockchain technology fortified farmers for getting a fair price for their crops and reduced operational costs. Abraham and Kumar, [ 120 ] proposed a blockchain-based data security system to preserve farmer’s data. The proposed work was based on a private-permissioned blockchain for controlled participation, hyper ledger fabric to support smart contracts, and system design to safely store farm data. The widened blockchain data helps farmer’s data to be accessed by other participants which can allow the government to sanction schemes based on farmer’s data. Topart et al., [ 122 ] proposed an interoperable ecosystem of farmer’s consent management. The model used a permissioned blockchain to allow only a specific group of people to access the services. The immutability of consent allows the data to be non-manipulative, distributed, signed transactions, and transparent. The consent verification for each data allows only valid users to request data. The model was proposed to respect the privacy, security, transparency, and consent of the farmer’s data.

Incentivization

Blockchain has been using incentive mechanisms since bitcoin to incentivize miners, but recently many authors have presented ways of promoting work for a reward. Incentives to promote sustainable agricultural practices by Giaffreda et al., [ 123 ]. Objectives include savings and increasing market value plus monitoring the use of water in the fields. Farmers have been relying on satellite data as it is a cheap source of agricultural services. With the use of LPWAN networks, accuracy in fields is increased along with a tensiometer-a sensing unit that is used to wirelessly communicate the data related to the humidity of the soil and a mini-meteo station that is used to measure temperature, air humidity, and air pressure. Smart contracts record the transactions from the calculated results in the cloud and release the incentives to the farmer according to their deal with the stakeholder. The proposal includes EnvCoins as the incentives, which can be further used to buy technologies for sustainable agricultural practices, for cash, or investment. Esmaeilian et al., [ 124 ] proposed an incentive mechanism for green behavior such as waste disposal, using re-furbished products, purchasing energy-efficient products, saving energy, recover, repair, and maintain. The tokens gained from sustainable behavior can be further used to access services on blockchain. Incentivization can ameliorate some of the environmental issues in rural areas with the help of rural people by motivating them to clean the areas. OpenLitterMap by S. Lynch, [ 125 ] uses geospatial analysis to geotag various types of litter. It uses LitterCoins as an incentive mechanism for the proof of work. This is to motivate people to submit correct data. It also rewards for uploading litter images from a new location. Apart from plastic and other homogenous litter, a proposal to eliminate solid waste from small municipalities in return for a reward is given by França et al., [ 148 ]. The provision was to change the original system from attack risk, data loss, power outage, and other such problems. The new digitized system proves to be a handier as it is in the form of a mobile application. The reward for selling solid waste to the collecting agent is in Green Coins, a cryptocurrency sent to the seller’s virtual wallet. This initiative led to computerization gains, information integrity, and the use of crypto-currency. Additionally, in [ 128 ] D. Zhang, worked on a similar solution to efficiently use rural waste in incentivizing rural people. The process includes the installation of smart bins and when they are full, the collection trucks will swap the waste for a digital coupon which the farmer can use to either get agricultural products from the waste to the energy plant or cash them. Blockchain makes it an easier process to transfer and record data faster with maximum transparency. Other applications of incentives for waste include Recereum, SwachhCoin, Plastic Bank, 4New, and OILSC [ 129 ].

The motivational incentive mechanism can also transform the way medical data is shared for research and diagnosis. In the paper by Zhu et al., [ 126 ], the authors gave a solution to actuate people into sharing medical data by providing them rewards for doing so. The rewards system is based on the access provided by the owner of the medical file. Through Smart contracts, a trusted payment money flow can be devised between the third party and the owner. The Shapley value was considered for the revenue distribution of medical data sharing and to study the impact of consensus on the miner’s income. Furthermore, an incentive mechanism for the accident alert system, proposed by Devi and Pamila, [ 127 ] is another blockchain-based medical application. According to the authors, most of the accidents occurs near rural places where medical help is unreachable on time. To eliminate the privacy issue of the nearby user who receives the accident report, a blockchain-based incentive method is implemented for the user who receives the accident alert to send the location of the victim to a close-by emergency service. Then the message initiator gets rewarded incentives for alerting about the accident. A similar report system mobile application for anonymous reporting is proposed by Zou et al., [ 130 ] in which reporting any incident can earn people rewards. The design goal of the author was to implement an anonymous report system, to provide privacy to the person who reports, without having to give their personal information to the system. This model induces incentive named Rcoins to whoever published the report information, the repliers, and the consenting miners. The Blockchain and Kudos by Sharples and Dominigue, [ 131 ], a reward-based permanent solution as the digital record-keeping model. The author proposed the use of blockchain to store digital certificates, achievements, and credits. Stored as a public record it can be accessed by the institutions or the student online. The model uses Kudos an educational reputation currency as a reward. The reward can be earned through uploading certificates on the blockchain, passing a test, or on course completion. Another application of blockchain-based incentive system is EduCTX by Turkanović et al., [ 132 ] which is proposed to globally enable the higher education credit platform. For potential stakeholders such as educational institutions, companies, and organizations a unified view of student’s higher education credits and grading system is placed on the global ledger through blockchain. ECTX tokens will be credited based on the completion of courses which will act as proof of completed courses.

Environment

In the environment sector, the most emphasis was given on blockchain applications in Natural hazards, Water, and Waste management in rural areas (Fig.  15 ). A detailed summary is given in Table ​ Table8 8 .

Blockchain applications in Environment

Comparison of Blockchain applications in Environment

Waste Management

From the articles proposed, in D. Zhang, [ 128 ] the author worked on a similar solution to efficiently use rural waste in incentivizing rural people. This framework is based on China’s Yitong system which is waste to energy plant for agricultural waste and the use of blockchain to provide digital coupons or cryptocurrency in return for waste. The author proposed the use of a web application to use a QR code scanner when the waste is collected from a smart bin, also encouraging segregation of agricultural waste and residential waste. The serves receive the weight of waste, lodges it on the global ledger, and the coupon is rewarded based on the weight. Apart from plastic and other homogenous litter, a proposal to eliminate solid waste from small municipalities in return for a reward is given by França et al., [ 148 ]. The provision was to change the original system from attack risk, data loss, power outage, and other such problems. The new digitized system proves to be a handier as it is in the form of a mobile application. The reward for selling solid waste to the collecting agent is in Green Coins, a cryptocurrency sent to the seller’s virtual wallet. This initiative led to computerization gains, information integrity, and the use of crypto-currency.

Latif et al., [ 133 ] have addressed the smart waste management system with the integration of IoT and blockchain. The proposed model included identification of waste material, trace location, send to trash, categorize waste, transfer waste, recycling, and decision-making process. The sensor nodes in the model were used for waste identification, and adding new blocks and the admin and waste management offices were responsible for collecting, executing recycling, and delivering products. The recyclable wastes are transformed into useful products and share with the customers and send the non-recyclable wastes to the trash.

Natural Hazard

Additionally, Nguyen et al., [ 134 ] proposed a blockchain-based weather-based index framework based on smart contracts. In this system, a NEO smart contract with an oracle server was introduced. In the process of the farmer’s request for an insurance enrolment, the insurance entity accepts the requests, the agreement is formed based on a policy scheme, Irrigation water companies release the water reports based on which the smart contracts execute the claims to the farmers. Deployment of the system can ensure water supply in rural areas and accessibility of insurance in case of droughts or floods.

Water Management

The intelligent smart watering system proposed by Munir et al., [ 135 ] is a blockchain-based system for the smart consumption of water. The system uses IoT for capturing real-time environment conditions such as soil moisture level, light intensity, air humidity, and air temperature. The main focus of the proposed system was to develop a healthy ecosystem while efficiently using water in plantations and gardening. Forbye, A water control system to efficiently manage and coordinate the use of water in irrigation communities is proposed by Bordel et al., [ 136 ]. The prosumer environment in the model is composed of a rule definition module where users can create irrigation recipes using ECA (Event-Condition-Action) rules. These rules are executable and easily transformed into other programming languages. Inputs are taken by a transformation engine, to create, compile, and deploy a set of Smart Contracts coding all the irrigation and management logic. Finally, irrigation recipes are executed by an execution engine, which invokes deployed Smart Contracts to interact with the infrastructure. From the perspective of Dogo et al., [ 137 ] proposed convergence of IoT and Blockchain. Objectives of smart water solutions include smart measuring and monitoring across the water distribution, enhanced security, better analysis of the generated data, and enhanced revenue and efficiency.

Similarly, Hassija et al., [ 138 ] proposed a drone-mounted base station in the tactile internet environment based on blockchain. The drone-mounted small cell station was based on a Permissioned peer-to-peer blockchain. To take strategic decisions, a game theory model was deployed. The decision was based on user association; transmit power level, drone speed, and altitude. Additionally, smart contracts can add parameters and conditions based on requirements. The model’s results showed that the low network areas can experience better bandwidth with the proposed system.

Further, the proposed model by Pincheira et al., [ 139 ] presented a trustless water management system-based software architecture. The system proposed presented a decentralized water management system that could incentivize virtuous behavior in agricultural practices. Smart contracts were used for their intermediary-less characteristic. The authors also implemented a cross-platform software library to allow constrained devices to interact with blockchain directly. The author’s goal was to enable sustainable behavior between irrigation communities for reducing water consumption.

This section reviewed the application of blockchain in the electrification of rural areas (Fig.  16 ). A detailed summary is given in Table ​ Table9 9 .

Blockchain applications in Smart Energy

Comparison of Blockchain applications in Energy

Energy Grid

In the energy sector, rural electrification and the use of renewable energy were mainly focused on in the articles. Enescu et al., [ 140 ] proposed a study on the use of photovoltaic energy. The paper showed the use of photovoltaic panels to power a power plant for the improvement of abandoned land. According to the authors, photovoltaic panels can easily pump water and is a more appropriate use of solar energy. Blockchain can help reduce the intermediary distributors hence making the selling and buying of energy more profitable. Additionally, Kulkarni and Kulkarni, [ 141 ], considering the lack of electricity in rural India, proposed a model to solve rural electrification problems. The model introduces peer-to-peer energy trading through blockchain suitable for small and remote micro-grids. A reliable and profitable electricity supply can be obtained through micro-grids. Smart contract-based meters allow transparency in the daily usage of energy used hence encouraging rural people into investing in blockchain-based electrification.

Renewable Energy

Levi-Oguike et al., [ 142 ] have presented the challenges and modalities for the adoption of blockchain technologies and to ensure energy efficiency as an advancement to the sub-Saharan Africa environment. In the case study performed by the authors, the following factors affected its use to a large extent in sub-Saharan Africa: Employment and education, displacement and resettlement, financing the technology, regulatory provisions, operational modalities, and paranoia and wariness. The overall objective of the paper was to ensure that the sub-Saharan region was involved in the innovative and industrial revolution wave. From Krajnakova et al., [ 143 ] author’s perspective following Scientific induction and deduction were made: The proposed Biomass blockchain structure is based on the use of traditional resources but the transactions are processed exclusively in a digital environment. The user can know the precise amount of energy and time when it is transferred to the consumer also ensuring real-time payment for the energy. According to the system Deal signed between biomass energy producer and consumer and transaction are based on cryptocurrency hence digitizing transaction accounting, payment and deposit mechanism, transaction security verification.

In the banking sector, most of the solutions were about issues in banking availability in rural areas, loan sanctions to under-documented people, and methods of transferring money (Fig.  17 ). A detailed summary is given in Table ​ Table10 10 .

Blockchain applications in Banking

Comparison of blockchain applications in Banking

Guo et al., [ 151 ] proposed a novel poverty alleviation loan management called the Loan On Blockchain (LoC). In the LoC, the participating roles can be named as the Financial department to check the identity and application information of the participants, bank to provide loan to the customer, Customer to provide identity and apply for loan, civil affairs department to audit the customer identity and loan applications, Regulator to monitor fund flow and inspect ledger. This digital account model was proposed for decentralized and centralized transfer of assets. Similarly, Jain et al., [ 152 ] presented a solution named Bit-score for credit scoring for underprivileged (rural) people with the help of blockchain. The authors’ model used a self-sovereign model for identity, distributed ledger storage, credit score calculation without any extra charges, and non-financial factor for acquiring credit score. With bit-score being an improvisation over traditional credit scoring techniques it makes the transactions more transparent, decentralized, secure, and intermediary-free.

Mobile Money

Y. Hu, [ 150 ] proposed a blockchain-based digital payment system to deliver reliable services on unreliable network services in rural areas. The system management contract to record account types, user balances to avoid forks during disconnection with the help of smart contracts. True transparency can be obtained through digitization and economic growth can be boosted in poor countries. Ghatpande et al., [ 149 ] proposed a way of moving Secure, interoperable mobile money in sub-Saharan Africa (SIGMMA) to support semi-offline payments through blockchain. The model provides unreachable areas a monetary transaction solution without having to provide any identity proof while ensuring trust between parties along with not having to physically visit any bank.

Cash Transfer

Another proposal is to provide banking solutions to rural areas where a chit fund system has been designed by Kumar and Sangal, [ 154 ]. Chit fund being a traditional saving scheme in India is an easier way to have access to credit. The purpose of this system is to remove geographical barriers and provide credit scores to each user based on their transaction behavior. Unlike other anonymous blockchain applications, this system requires identity registration. Unlike traditional co-lateral systems, blockchain generates credit history to prohibit manipulation. Lastly, Jaffer et al., [ 153 ] proposed a blockchain-based distributed system that is immutable and secures the transaction logs. The self-executing smart contracts were used to automatically execute real-world contracts for auto disbursement of subsidies on meeting specific conditions. This system overcoming traditional cash transfers, and corruption and manipulation related to it can benefit rural or deserving people.

In the healthcare sector, smart healthcare systems, telemedicine, and privacy in medical data sharing to provide security and transparency in the healthcare system between doctors and patients were the commonly addressed areas in related work (Fig.  18 ). A detailed summary is given in Table ​ Table11 11 .

Blockchain applications in Healthcare

Comparison of blockchain applications in Healthcare

Medical Data

Kaur et al., [ 157 ] proposed a blockchain-based electronic medical record storage and management system. The proposed model consisted of three main components: Domain experts (doctors, lab technicians, pharmacists, and drug manufacturers), health insurance providers, and patients. To ensure the privacy of medical data which contains most of the private information blockchain distributed data storage for heterogeneous data was proposed having a single source for data storage and access while providing high security and privacy to the users and researchers. Similarly, Zhang et al., [ 158 ] proposed secure and scalable clinical data sharing using FHIR Chain, a blockchain-based system meeting ONC (office of the national coordinator for health information technology) requirements. The technical requirements for blockchain-based clinical data sharing were verifying identity and authenticating all participants, Storing and exchanging data securely, consistent Permissioned access to data sources, applying consistent data formats, maintaining modularity. FHIRChain facilitates clinical data exchange while maintaining ownership.

Telemedicine

Guo et al., [ 161 ] proposed an ABE scheme to achieve dynamic authentication and authorization with higher flexibility and efficiency for the Medical on Demand services in the telemedicine system. The system uses a Consortium Blockchain managed by multiple authorities. Medical examinations are uploaded to the database provided by Cloud Service Provider (CSP). The medical results are downloadable from Cloud only by Medical specialists. All the data is stored in Blocks of Blockchain hence preventing any manipulation in health records. Through this system independence of choice should be provided to the patient whether they want to enroll, leave, or change access policies. Nusrat et al., [ 160 ] proposed a model of a telemedicine system for medical care and security of data of rural people by using blockchain technology. The system consisted of stations for primary treatment tests while storing data directly in the blockchain. This system ensured communication and data privacy to doctors and patients while also giving reliable medical care and benefits to underserved (rural) people.

Forbye, Yong et al., [ 159 ] have proposed a blockchain and machine learning system for vaccine supply chain traceability. The novel intelligent system based on the blockchain can be used for vaccine supervision in the vaccine supply chain. Additionally, using smart contracts for the vaccine supply chain can provide the following advantages: detection of expired vaccines, vaccine information, and vaccine coin.

Smart Healthcare System

Machine Learning holds the power to change the perception of understanding and analyzing data and decision-making in multifarious sectors. Since, the blockchain with its decentralized network focus on secure data sharing, its integration with machine learning would provide a very meticulous outcome. Few of the ways through which blockchain’s integration with machine learning and benefit the healthcare system are [ 162 ]:

• Blockchain ledger with legitimate data collection can feed the machine learning models with highly accurate and dependable data.
• Real data can be used to train machine learning models to increase efficiency and precision, therefore, saving cost and time.
• Models can be trained to give the same health advice to multiple patients with alike symptoms.
• Models can also be trained to give better clinical solutions to doctors based on the patient’s symptoms.
• Training the models on the patient history and storing them on blockchain ledger can predict outbreaks.

For implementing the integration, Jain et al., [ 156 ] proposed an integrated model of blockchain and machine learning to detect diseases. These models can be implemented in a hospital or rural medical camps. The proposed system consisted of IoT, blockchain, cybersecurity, and machine learning. Various components measure basic parameters of the human body such as weight, pulse, blood pressure, and automatically saved the data in the ledger. The system has the potential to expand medical parameters while making it adaptive. The complete system can collect, store, and analyze the data of the patient and benefit the doctors, patients, and medical institutions.

Similarly, Tripathi et al., [ 155 ] have proposed a safe and convenient use of medical data and its user through blockchain technology. The proposed work is an improvement on issues and challenges faced regarding security and privacy. The clinical data are recorded in the blockchain ledger with access to legitimate users only. For a doctor to access a patient’s data a request has to be made and only when the patient approves the request does the data become visible. The goal of this model is to provide secure and reliable services to insurance companies, drug supply chains, and medical researchers. Lastly.

This application area mainly focused on employment visibility and temporary employment for rural job security (Fig.  19 ). Therefore, the following related research articles were identified and a detailed summary is given in Table ​ Table12 12 .

Blockchain applications in Employment

Comparison of blockchain applications in Employment

Temporary Employment

Pinna and Ibba, [ 163 ] proposed a decentralized employment system to process employment contracts with a fully automated and fast procedure. The model consists of a new job offer event in which awaiting employers apply for jobs, an application event where a smart contract acquires the application request, a hiring event where the applicant worker meets the employer, a relationship event to enable the workers to check working situation and details, the workday event which describes the maturation of workdays, a payment event where the employee gets paid. The transparent ledger can make sure that the employment contracts were deployed with unchangeable information.

Employment Visibility

Similarly, the paper’s proposal by M. et al., [ 164 ] ensures supply chain visibility to seamlessly connect all stakeholders of the supply chain network who are a part of the Blockchain ecosystem. The paper defined two modules in BC design: the Supply module and the demand module. Supply module to collect worker's data and smart contracts to perform transactions through an application interface and store them on the ledger. Demand module to implement job allocation. The aggregators are given direct access to help track worker’s information from the ledger.

Existing Systematic Literature Reviews

A tabular representation of a few major existing works of blockchain in rural development has been done in Table ​ Table13. 13 . This table communicates the area of literature reviews, and their main contributions in the review regarding blockchain in rural or agriculture.

Existing literature reviews

An extensive literature review was done in this section which portrayed the enormous amount of work done in blockchain technology pertaining to rural development. All the functional areas and sub-areas were compared and discussed in tabular form. Multiple novel ideas and theories were identified during the literature review. At last, a small tabular representation was made for the existing systematic literature reviews and surveys in a similar area to identify the depth of the work done. In the upcoming sections, critical analysis and detailed discussion have been done based on the literature study, followed by the limitations of the survey and conclusion.

Critical Analysis Existing Technologies and Discussion

Blockchain Technology possesses much competence and futuristic hold towards rural development. In this review, all possible applications of blockchain that facilitated rural development were found, reviewed, compared, and summarized. With Agriculture being the predominant application of blockchain, various areas under it were analyzed that worked on the relief of agricultural issues in rural areas.

Starting with Supply chain traceability, the study showed integration of blockchain technology with Internet of Things [ 51 , 54 , 56 , 58 , 63 , 64 , 69 , 70 , 73 , 76 , 82 , 84 , 85 , 89 , 100 , 145 ], Cloud computing [ 65 , 87 ], Big Data [ 87 ], and Geospatial Technology [ 100 ]. Among the papers discussed, this area consisted of papers pertinent to tracing agricultural produce from the beginning of the process till it reached the consumer. The range of traceability options comprised all agricultural products as well as specifically certain products such as soybean [ 60 ], grape wine [ 69 ], and cocoa beans [ 62 ]. Furthermore, blockchain’s integration with IoT provided sensing and sharing of private data with blockchain without intermediary support. Additionally, some proposed work used QR codes [ 56 , 60 , 146 ] for viewing data directly related to the attached product. Articles supporting IoT devices were implemented for tracing agricultural produce, encouraging circular economy, fault-tolerant, and immutable APIs. A few were reviews on agriculture traceability [ 53 , 58 , 60 , 61 ] barriers [ 67 ], challenges [ 59 , 71 , 76 ] contribution [ 80 ], IoT based solutions, and future scopes [ 78 , 96 ]. Some agricultural prototypes included AgriBlockIoT [ 70 ], KHET [ 83 ], and FARMAR [ 68 ]. A few land record management articles were also discussed that implied security and broker-free methods for land titling and transferring [ 97 , 98 ]. Most of the platforms used were Ethereum Smart Contracts, Hyperledger, REST, JavaScript (Web3, node, angular), Truffle Framework APIs, and MySQL and MongoDB for cloud storage.

While traceability of agricultural produce is important, the agriculture security system is also a necessity. In this review, the articles for agriculture security systems included prevention of farm data from cyber-attacks using IoT [ 103 ] and supervision of agricultural products and food information [ 102 ]. In both the works acquired, it used Smart contracts and Ethereum Blockchain respectively, along with IoT-based sensors for farm monitoring.

Organic Farming as a part of agriculture application for sustainable farming and quality food production included two articles for analyzing the effectiveness of supply chain [ 101 ], and identifying product quality and transparency of organic food supply chain using decentralized applications and QR codes for tracing product data [ 104 ].

Furthermore, using smart methods to enhance the agricultural process was discusses in the smart agriculture Sect.  3.1.4 where farm controlling, recordkeeping, improved logistics, farm managing and improvising, and monitoring using Blockchain Technology and IoT [ 106 – 110 ] as well as cloud computing [ 105 ] and geospatial technology [ 100 ] in some articles were covered. Most emphases were given towards improving the quality of farming and its management while providing utmost security to data. Mostly used platforms to implement the proposed work were JavaScript(Node, Ganache, Truffle), Ethereum Smart Contracts, and IoT-based sensors.

Apart from the supply chain in farming, the dairy sector was one of the application areas covered in the review comprising of E-governance in the dairy sector implemented on smart contracts [ 111 ], and quality and quantity assurance of milk with a delivery platform [ 112 ] using Blockchain Technology. In addition to the dairy sector, blockchain applications in livestock management using Blockchain Technology [ 114 ], IoT and Cloud Computing [ 113 , 115 , 147 ] to monitor livestock, observe cattle using RFID tags, storing detailed information on fishes, along with livestock traceability were discussed in the review. Integration with IoT provided real-time monitoring and traceability of livestock and its by-products in the supply chain.

Similarly, to share informative farming data and techniques a review on convenience analysis of the blockchain in agriculture [ 116 ], and exploratory data planning and management of agricultural food supply chain for sustainable development [ 117 ] was given to explore the work done in E-agriculture using blockchain technology. Since one of the main motives towards implementing blockchain in agriculture is to monitor the faring process and products till it reaches the consumer, therefore, agriculture monitoring section covered farm monitoring system[ 99 ], a yield estimation system to share farming plans implemented on smart contracts [ 119 ], and an IoT based AG Wallet system to track farm activity implemented using IBM enterprise blockchain platform [ 118 ]. Penultimately, the application area was divided into farmer Sect.  3.1.9 where blockchain’s reviews to facilitate farmers such as farmer’s portal to capture farm activities using HTML and Python [ 121 ], farmer’s data storage to provide transparency for government scheme using smart contracts [ 120 ], and farmer’s data accessing using their consent [ 122 ] were discussed.

Lastly, an overall blockchain application area covering the use of incentives for numerous activities was discussed in Sect.  3.1.10 . The review included a reward-based system in return for solid waste [ 148 ], rural waste [ 128 ], anonymously reporting an activity [ 130 ], reporting an accident [ 127 ], storing educational records in ledger [ 132 ], green behavior [ 123 , 124 ], geotagging litters [ 125 ], and to safely share medical data [ 126 ]. The incentive mechanism works when an activity is performed, therefore in return for good behaviors or activity, cryptocurrency-based tokens are rewarded that can be stored in a blockchain wallet. Most of the platforms used were smart contracts while some of the systems also used ARK Blockchain, Laravel PHP, and JavaScript.

Looking through the applications of blockchain in rural areas, usage of blockchain in reinforcing environmental conditions and changing people's outlook on preserving the environment was the outcome of factors affecting rural people as they were much likely also related to environmental conditions. From this view, the environmental application areas were discovered and discussed to be Water management, Waste management, and Natural hazards.

To begin with, under Sect.  3.2.3 water management, smart measuring and monitoring [ 137 ], smart consumption [ 135 ], management [ 139 ], and control system [ 136 ] of water were discussed. These articles provided smart ways of implementing blockchain for efficient use of water in irrigation, distribution, and consumption, preventing environmental deterioration while also providing security and digitization.

Secondly, under Sect.  3.2.1 waste management, the reward system in return for waste collection and selling [ 128 , 148 ], and waste management [ 133 ] using Blockchain Technology were discussed. Covered under the integration of Blockchain Technology, Cloud Computing, and IoT, the implementation used smart contracts in the first two proposals and UML, TLA + for the latter.

Lastly, as per the research criteria, only one article contributing to the environment and natural hazards was discovered and reviewed explaining the insurance system for drought-affected farms based on the farm data stored in the blockchain ledger [ 134 ]. The model was implemented on NEO virtual machine, smart contracts, and used Oracle server as database.

Similarly, from the challenges faced by rural people acquiring an electric line, energy-efficient methods, to secure, and transparent payments issues were covered and reviewed under the energy section. The blockchain application areas in the energy sector were discovered to be Renewable energy and the Energy grid. With blockchain’s integration with renewable energy a smart contract-based energy transfer credibility system of biomass energy grid [ 143 ], and a case study of sub-Saharan Africa and its challenges and adoption of renewable energy access were discussed [ 142 ]. Whereas in the energy grid section, the blockchain’s application in providing peer-to-peer electrification with secure payments, transparent energy usage [ 144 ], and the use of smart energy grids for farming and irrigation using Ethereum Blockchain [ 140 ] were reviewed.

Besides, from the traditional use of blockchain in Finance, the banking solutions for rural people were discussed in Sect.  3.4 . From the banking applications of blockchain, the use of mobile money for semi-offline payments in sub-Saharan Africa without identity proof using a secure, interoperable mobile money system [ 149 ], and a delay-tolerant digital payment system based on Ethereum blockchain [ 150 ] were discussed. A simpler way of getting a loan with the help of blockchain is by using a hyper ledger fabric-based Loan On Blockchain(LOC) system using smart contracts [ 151 ], and a credit scoring system called Bit-score using Ethereum Blockchain [ 152 ] were discussed. Finally, a Cash Transfer area where a distributed system for automatic subsidy delivery and fund release using JavaScript and Hyperledger composer [ 153 ], and a chit fund system based on smart contracts to provide credit to rural people [ 154 ] were reviewed.

Under the Healthcare applications of blockchain, A Smart Healthcare System, Medical Data sharing, and Telemedicine were the areas discovered. Under smart healthcare, the articles reviewed were a smart model to detect diseases and measure basic health parameters using Ethereum blockchain and Raspberry Pi [ 156 ] and protected access to medical data using smart contracts [ 155 ]. For the recordkeeping of medical data and share it legitimately an electronic medical record storage management system based on ethereum and cloud storage [ 157 ], and a permissioned clinical data sharing called FHIRChain using smart contracts [ 158 ] was reviewed. Lastly, under Telemedicine, vaccine supervision and traceability for safe vaccine supply [ 159 ], secure data storage using telemedicine system based on smart contracts [ 160 ], and a telemedicine system to prevent health records manipulation using Blockchain and Cloud Database [ 161 ] were the articles reviewed.

Another challenge faced by rural people implemented to recuperate from unemployment using blockchain technology was discussed in Sect.  3.6 . Using smart contracts an employment contracts processing, handling, and safe payment system for temporary employment contracts [ 163 ], and a blockchain aggregator to perform worker data transactions and employment visibility [ 164 ] were the works reviewed in this section.

Limitations of Existing Works and Research Gaps

In this section, the limitations of the existing literature review on blockchain in rural development along with a comparison of existing systematic literature reviews have been discussed. The comparison has been shown in Table ​ Table14, 14 , and a few research gaps have been mentioned in this section as well.

Comparison of existing reviews

While Blockchain technology is leading in security and transparency, providing ways of applying its technology in disparate areas its limitations and gaps can still be identified in the proposed and implemented work. While most of the work in agriculture is for ensuring transparency and traceability in the supply chain, there are far more factors in agriculture that affect farmers and crops. Blockchain inevitably uses excessive energy in execution, but its execution in rural areas may become worrisome due to the lack of energy and load in those areas.

Collecting farm data and storing them on the ledger in small farms is easier. However, in the case of big farms, the data collection and integration may consume much time and probably manpower in accumulating and loading it in the ledger. Apart from that, IoT-based services require sensors as well as collecting livestock DNA to trace them and load their information may cost a fortune to small-scale farmers.

Teaching the application usage to laymen, that too uneducated farmers or rural people may become a troubling task. Not only that, the availability of news of the latest technologies is hardly accessible to underdeveloped countries, introducing blockchain-based applications to those areas may toil the deployment and utilization.

Mistakes can prove disadvantageous to poor people while making blockchain transactions. A lost private key or a mistakenly added extra digit to the payment can cause irreversible damage.

Thereafter, a data breach of medical data and inappropriate access to medical histories are some issues that may decrease people’s trust in the blockchain-based healthcare system for medical data privacy.

Security threat is another limitation that can affect any type of application that requires recordkeeping. Here the blockchain’s main characteristics may itself prove faulty to find the intruder as it gives total anonymity to users. With both pros and cons, robust and reliable technology can still be deployed for many usages, making livability easier and people technologically advanced.

Multiple issues pertaining to rural areas have been addressed by authors with the help of blockchain. Agriculture is the most economic factor, solutions for blockchain-based supply chain traceability provided secure, transparent, beneficial product delivery. It also ensured timely payments to farmers and quality products to consumers. Banking solutions have also been made easier with blockchain technology, providing remote banking solutions, credit and loan easiness, and easy and transparent banking. Hygiene issues that led to many diseases, generational disabilities have also been given a solution through blockchain which also incentivizes rural people for participating in waste and water management. Rural electrification solutions were also proposed with blockchain for people unable to obtain energy resources, basic electrical amenities, and expensive bills. People who were unable to receive treatments, had to travel long distances for medical assistance, were also provided a blockchain solution with which telemedicine, privacy to medical data usage, and medical-on-demand were made available. Blockchain has also been useful in providing employment solutions to the truly underserved, using a global chain for employment visibility, and secure payment for jobs [ 168 – 172 ].

The Systematic Literature Review’s objective is to provide information on the research proposed related to blockchain in rural development to provide new research opportunities, extensive knowledge about each development area, and the possibility for future development in rural areas. After distinctly reviewing every research article variant areas of applications were identified relating to the development of rural areas with the help of Blockchain Technology. Overall, 6 disparate applications in rural development were picked out; from which each of these applications has a total of 23 divergent areas combined. These areas contribute to all the research that has been done in the blockchain in the rural development sector and are distributed across 37 countries obtained from 6 journals and 1 web source ranging from the years 2010 to 2020. After searching through journals, applying more than 16 keywords, 112 articles were found in aggregate. From analyzing each article, the primary application of blockchain was identified as agriculture with 67% of research articles relative to blockchain in agriculture whence 60% were associated with supply chain traceability. About 55% of those papers were from the Institute of Electrical and Electronics Engineers (IEEE). Furthermore, in 112 research papers, 8 technologies were implemented with a total of 58 platforms and tools combined.

Research Questions Addressed

From the Research Questions defined (Table ​ (Table3), 3 ), the following inference can be made:

What are the main applications and areas of implementing Blockchain Technology in Rural Development?

Various extensively researched applications are defined in Tables ​ Tables5, 5 , ​ ,6, 6 , ​ ,7, 7 , ​ ,8, 8 , ​ ,9, 9 , ​ ,10, 10 , ​ ,11 11 and ​ and12. 12 . These applications define the Blockchain’s applications in rural development that impact the rural areas, provide security, opportunities, availability of resources, and a better lifestyle. The areas (Fig.  20 ) gave extensive knowledge about the domains of application-defined from several research articles related to it.

Blockchain Applications and their Areas in rural development

What are the major issues in Rural Development and how they can be addressed using Blockchain Technology?

Numerous issues in rural areas are explained in Sect.  1.1.1 and the blockchain applications for the eradication of those issues are addressed in Sect.  3 .

What are the targeted software, platforms, and tools for the implementation of blockchain in rural development?

Throughout the applications, for implementation following (Table ​ (Table15) 15 ) technologies’ integration, and software and platforms were used:

Blockchain development platforms and tools

Following the review, in agriculture, most emphases were stated towards supply chain traceability and less or no work in natural resource management, overproduction, yield stagnation, and international trade. In regards to the sociological factor, research on work belonging to blockchain development for rural education, housing, women empowerment, crime reduction, brain drain, and craftsmanship is missing. For the implementation of banking, healthcare, and many other applications the required government and technological assist are still lacking. In some cases, the research proposed could be administered only in the far future, therefore contemporary work was absent. Some more gaps and future research directions are given in Sects.  4.2 and 6.1 .

The research questions mentioned in Table ​ Table3 3 are addressed in the following section (Table ​ (Table16 16 ):

Addressed locations of the Research Questions

Threat to Validity and Limitation of the Survey

While reviewing the issues in rural areas, blockchain technology, and the applications of blockchain technology in rural development certain limitations can be considered existing. All the articles were selected according to the review process and criteria implied in Sects.  2.1 , 2.2 , and 2.3 . During exclusion, some articles were not considered fit for this review, were missed, or were not found. Six applications were considered in this review, there could be more applications that we couldn’t figure or that couldn’t make the cut of criteria. A total of 23 sub-areas of all the applications were determined. Conclusively, as per our knowledge, there wasn’t any systematic review that reviewed all the application areas of blockchain technology in rural and sustainable development nevertheless there could have been a few rural and sustainable development articles that weren’t included in this review.

Conclusion and Future Work

Blockchain Technology has presented a considerable amount of work in the rural sector. While its implementation was few, the ideology is enough to motivate people into changing the lifestyle of rural people leading to the overall country’s development. In this systematic literature review, numerous applications of blockchain technology in sustainable rural development were discussed with diverse areas in each application. A comparative study of each application in all the areas pertaining to different approaches has been portrayed with differing attributes elucidating the technology, process, and techniques behind each article. The paper provides extensive literature towards each of the articles sorted after applying the review process consisting of relevant articles and keywords. The primary findings of the systematic literature review were as follows:

• From the review, we were able to identify common and exceptional uses of blockchain technology that would help uplift the rural community and lead to sustainable rural development.
• Various distinct approaches to implementing blockchain technology for rural welfare were discovered.
• Platforms and tools that would facilitate the use of these applications for farmers and uninstructed agrestic people were identified and reviewed.
• Blockchain’s integration with multiple powerful technologies for rural development was reviewed.
• An overall idea for a collaborative approach leading to a smart village framework was constructed.

The gaps determined from reviewing the articles broadly would help researchers explore additional as well as alternative utilization of blockchain technology for sustainable rural development.

Future Work

Blockchain’s characteristics are exceptionally conducive to safety, privacy, integrity, traceability, efficiency, and transparency in every area limited by such advantages. While diverse blockchain applications for the welfare of rural community has been discussed nevertheless future work can comprise of facilitating applications in making use of blockchain incentives for a collaborative framework incorporating several services in rural areas namely Smart Village. Blockchain technology in terms of providing incentive mechanisms could lead to a better motivational unit in many areas. Incentivizing rural or urban people for education, data sharing, green farming, green behavior, and environment conservation are real future demands. Apart from emphasizing rural areas, blockchain’s integration with networking, cybersecurity, and digital advertising is also a future insistence.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declarations

Publisher's Note

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

Contributor Information

Parminder Kaur, Email: ude.rapaht@91em_edokamp .

Anshu Parashar, Email: ude.rapaht@rahsarapa .

• DOI: 10.54097/wrv05909
• Corpus ID: 270597407

An ESG Evaluation System Based on New Quality Productivity and Blockchain Application

• Published in Academic Journal of Science… 21 May 2024
• Business, Computer Science, Economics

Tables from this paper

13 References

Application of blockchain technology in supply chain finance, related papers.

Showing 1 through 3 of 0 Related Papers

Breaking News

What is Blockchain’s Potential for Managing Data, Compute, and Models for AI?

• Copy Link URL Copied!

Rapidly evolving AI, and humans’ experience with it, unearths a litany of economic and societal issues related to intellectual property rights, individual privacy, transparency, security and other ethical pillars on a continuous basis.

The convergence of blockchain and artificial intelligence (AI) may be a very promising opportunity for groundbreaking advancements in AI data management, computation, and model distribution related to the critical economic and societal issues. As people become increasingly better at using AI and adoption increases, the need for secure, transparent, and efficient systems to manage data, compute resources, and AI models has never been more pressing.

Blockchain technology, which offers a decentralized and immutable ledger system, holds immense potential for revolutionizing how we handle AI-powered technologies, systems, and processes. Renowned to date for its role in enabling cryptocurrencies like Bitcoin, is essentially a distributed ledger system that records transactions across a network of computers. Each transaction is encrypted, time-stamped, and linked to the previous one, creating a chain of blocks that cannot be altered retroactively. This inherent transparency and security make blockchain an ideal solution for managing sensitive data and ensuring the integrity of AI models and computations.

Smart contracts are digital contracts stored on a blockchain that are automatically executed when predetermined terms and conditions are met. They are an invaluable feature of blockchain and provide a reliable framework for distributing and monetizing AI models.

By leveraging smart contracts, AI assets can be securely marketed and distributed to users while ensuring fair compensation to their owners. This opens up new avenues for monetization and collaboration in the AI ecosystem, empowering investors, developers, and users with a means to manage their intellectual property, private and public data, and compute resources. This also creates avenues for commercialization that don’t exist today, and which can stimulate innovations and contribute to the further advancement of AI technologies.

A solution to big data and compute resource challenges One of the key challenges in AI development is the infrastructural governance and management of vast amounts of data. Traditional centralized systems often struggle with issues such as data silos, privacy concerns, and data ownership disputes. Blockchain’s decentralized nature offers a solution, enabling secure data sharing and collaborative model training while safeguarding privacy through techniques like homomorphic encryption and zero-knowledge proofs. By leveraging blockchain, AI researchers gain access to diverse datasets without compromising data security or ownership, fostering a collaborative ecosystem conducive to innovation.

Blockchain technology also facilitates the efficient allocation and utilization of compute resources for AI tasks. Cryptocurrency investors have already begun investing in the development of blockchain-based platforms that provide access to a decentralized network of computing power, eliminating the need for expensive hardware investments and reducing computational bottlenecks. This democratization of compute resources enables greater scalability and flexibility in AI development, allowing researchers and organizations to tackle complex problems with ease.

AI is becoming increasingly integrated into technologies at the edge of networks, in contrast to a centralized cloud location where many of today’s AI applications run. For this reason, blockchain is a natural complement given its fully decentralized nature that puts data, compute, and models all within the edge devices and connected through the internet of things (IoT).

Users want their AI to provide personalized, private, and integrated experiences with the growing number of these technologies that are always or often by our side. Blockchain will allow them to have that.

Despite this immense potential, the integration of blockchain with AI is not without its challenges. Scalability, interoperability, and regulatory concerns are among the key hurdles that must be addressed to realize the full benefits.

However, with ongoing investment in research and development efforts, these challenges can be overcome, and pave the way for a future where blockchain-governed AI systems drive greater access, collaboration, and innovation across society.

–Michael A. Cohen