Systematic Literature Review of Blockchain Technology’s Technical Challenges: A Tertiary Study

Abstract

Research into blockchain technology has expanded significantly due to its potential to enhance transparency and trust in business operations, yet adoption is limited by technical challenges like scalability, consensus mechanisms, and security, as well as non-technical barriers such as governance and standardization. This study synthesizes findings from 21 systematic literature reviews (SLR) published between January 2009 and January 2024, focusing on the technical performance of blockchain and its integration with technologies like cloud computing and machine learning. The analysis highlights advancements in scalability, security, privacy, and smart contracts alongside areas needing more research, such as interoperability and integration with legacy systems. This comprehensive review aims to map current technological developments, identify ongoing limitations, and identify specific technical challenges that impede broader adoption. The findings direct future research towards overcoming these barriers, facilitating the smoother implementation of blockchain across various business sectors.

1. Introduction

Blockchain technology is a distributed digital ledger known for its non-repudiable nature, eliminating the need for a centralized authority [1]. The characteristic that sets it apart is the immutability and transparency of data, providing businesses with opportunities to enhance performance. Nevertheless, like any other information technology, blockchain technology encounters challenges and is continuously evolving to address business-specific issues.

Researchers across various industries, such as healthcare, agriculture, academia, supply chain management, pharmaceuticals, and others, have investigated its application in a multitude of business scenarios. It is anticipated that additional sectors will integrate blockchain technology in the future to instill transparency and trust in their business operations and financial transactions [2]. Research indicates that blockchain technology is estimated to have reached a market value of USD 10.02 billion in 2022, and it is forecasted to generate a revenue of USD 1.43 trillion by 2030, experiencing a compound annual growth rate of 85.9% from 2022 to 2030 [3].

Blockchain stands out as one of the most extensively studied subjects in information technology. Findings from a search for “blockchain technology” in the Scopus database, widely utilized by research communities, indicate exponential growth over the past few years. This trend is mirrored in literature reviews, highlighting blockchain’s significant potential to enhance transparency, traceability, efficiency, and reliability across various industries in the future [4]. Hence, comprehending the existing technical hurdles affecting blockchain’s implementation in industries is crucial. The blockchain comprises a blend of different information technologies, including hashing mechanisms, consensus mechanisms, distributed ledgers, and smart contracts. This amalgamation enables blockchain to attain data transparency and immutability.

With growing interest in technology, there is a plethora of literature available on blockchain technology and its applications across scientific domains. While surveys and reviews discuss various technical challenges of blockchain, there is a limited number of systematic literature reviews (SLRs) that provide a comprehensive overview of the technology’s current progress. Despite a significant increase in the number of SLR research papers on blockchain applications in business and management domains over the past decade, technical challenges have not been substantially addressed. However, there is a lack of aggregate reviews on this topic in the literature. This review aims to fill this gap by offering an aggregate review of existing SLRs on blockchain technical challenges. Additionally, we identify key challenges and propose potential research directions for future work.

2. Methods

This study employed the systematic literature review (SLR) method. An SLR offers a structured approach for reviewing and ensuring the quality of primary studies on specific topics to address defined research questions. Initially utilized in medical research during the early nineties, the SLR method facilitated evidence-based research practices, aiding researchers in making informed decisions regarding treatment options within the medical field. Over time, SLR methods have been adopted across various research domains, including business, engineering, and social sciences. They have become increasingly prevalent in diverse research fields, serving to assess the current state of research within specified study areas and providing insights to guide future exploration for fellow researchers.

The tertiary study encompasses review articles, mapping studies, and scoping studies focusing on technical challenges related to the blockchain. Mapping studies seek to identify research within specified primary studies and pinpoint research gaps. Similarly, scoping studies aim to classify research within primary studies and identify research gaps. However, these three literature review methods share similarities and can be distinguished primarily by their approaches to analyzing and presenting the literature.

This study presents a review of primary studies, making this study a secondary study, also known as an overview of primary studies. This study follows the SLR guidelines of Kitchenham and Charters [5]. As per this guideline, there are four main steps in SLR. The first step is to define a research question and then search for relevant articles from the scientific database, followed by a screening of extracted articles based on predetermined criteria and a review of the selected article.

2.1. Research Questions

The research questions addressed in this study are a combination of general SLR questions recommended by Kitchenham et al. [6] for all tertiary studies (RQ1, 2, and 5) and technology-specific questions that this study is set to answer (RQ3–4).

Table 1. Research questions.

S. No.	Research Question
RQ1	How many SLRs have been published since the emergence of blockchain as Bitcoin (2009) to date (2022), and what is their quality?
RQ2	What were the research areas addressed in the SLRs on blockchain technical challenges?Which technical challenges are the most researched?
RQ3	What are the major technical factors that challenge the integration of blockchain technology in various industries?
RQ4	Which technical challenges require more attention to put blockchain technology forward into mainstream technology used in various business verticals?
RQ5	What progress is achieved in the course from one study to another in the research timeline, and how does it address the challenges that business faces in technology integration?

presents the research questions.

2.2. Search Process

The search for a relevant article starts with the relevant search term. Searches were performed in different scientific databases, including Scopus, which houses many scientific journals and conference papers. Scopus, Willey, MDPI, and IEEE Xplore were also searched to broaden the search database and to remove any possibility of missing relevant articles. All three databases provide union and intersection options in search criteria, which helps find the relevant research article. The search was performed on 22 January 2024 and subscribed to for future publications with the same filtration to remove any chance of missing articles in the future before the completion of this article.

The search string used to find the relevant articles was compiled from keywords of existing systematic literature reviews on blockchain technology reviews. The search should match the primary objective, which was to find recent research in blockchain technology. This study used three recent bibliometric studies on the blockchain to determine the most relevant search terms.

Table 2. Search string.

Topic	Search String
Blockchain	“Blockchain, OR “Distributed Ledger” OR “Decentralized Ledger”.
Systematic literature review	“Systematic review” OR “systematic literature review” OR “systematic map” OR “systematic mapping” OR “mapping study” OR “scoping review” OR “meta-analysis”

shows the search string used in this study.

2.3. Selection Process

The search conducted across four databases was refined based on the inclusion and exclusion criteria outlined in Section 2.3.1. Only articles published in English were considered for further examination. Articles with only abstracts available were excluded from the review process. Additionally, survey studies were omitted because they did not adhere to systematic guidelines and lacked critical reviews. Articles solely focusing on reviewing blockchain applications without addressing technical challenges were excluded from consideration, aligning with the scope of this study. This was achieved by filtering the subject area to encompass only computer science, as this paper specifically examines the technical aspects of blockchain technology. The selection process of the relevant article according to the preliminary study is depicted in Figure 1.

Articles were chosen based on predetermined exclusion and inclusion criteria, established in accordance with the objectives of this study and to ensure high-quality research. These criteria were implemented to enhance the rigor of the research process.

2.3.1. Inclusion and Exclusion Criteria

The inclusion criteria were as follows:

• Studies published after 2009, as blockchain-related research started after Bitcoin came into existence in 2009.
• Type of publication, either a peer-reviewed journal article or proceeding in a reputed conference.
• The subject area is limited to computer science.
• The language of publication is English.
• Studies relevant to blockchain technical challenges.
• Systematic reviews, scoping studies, and mapping studies. Reviews that contain a meta-analysis in addition to the SLR [1].
• Technical reviews on specific blockchain technical challenges, e.g., [7,8,9].

The exclusion criteria were as follows:

• Not peer-reviewed publications such as newspapers, book reviews, and dissertations.
• Repeated entries in the search output.
• Papers that contain “false positives”, e.g., the term “interoperability” found in a medical-data research paper.
• Only abstracts are available.
• Non-systematic literature reviews, comparative studies, or surveys on blockchain technology [4,10,11].
• Articles not specifically related to blockchain technology in general.
• Specific blockchain-technology application reviews, but with no links to technical challenges, e.g., [12,13].

2.3.2. Quality Assessment

The search outcomes were further assessed for their quality based on the criteria mentioned in [6]. The first eight criteria were added for a more rigorous quality assessment of the article. The last two questions were slightly adjusted to align with the research objectives of this study based on quality criteria detailed in [7], as depicted in

Table 3. Quality assessment criteria.

S. No.	Assessment Criteria
QA1	Is the publisher reputable? E.g., Elsevier, Emerald, IEEE, Springer, Taylor & Francis, ACM.
QA2	Have the research questions been clearly defined?
QA3	What type of review is being carried out?
QA4	Have specific SLR guidelines been reported to be followed in the review?
QA5	Have the search strings been reported, and how detailed are they in describing the blockchain?
QA6	Is the literature search likely to have covered all relevant studies? How many online databases were searched, and are the years covered in the review known?
QA7	The review’s inclusion and exclusion criteria are described and are appropriate.
QA8	Did the reviewers assess the quality/validity of the included studies? How were the number and quality of primary studies reported?
QA9	How many blockchain technical challenges were reviewed?
QA10	Were the basic data/studies adequately described?

. These criteria measured the articles’ quality, as depicted in Table 3.

The score point for each quality question was categorized into three columns: “yes”, “partially”, and “no”. For “yes”, the score was 1, whereas for “partially”, the score was 0.5, and for the “no” answer, it was 0 points, and the scoring criteria are presented in

Table 4. Scoring criteria.

QA1	Yes (1)	Partial (0.5)	No (0)
1	Top publisher	Reputable OA (Open Access) and professional bodies	Other
2	Yes	But the objective of the review is implicit	No
3	SLR	Mapping or scoping study	Other
4	Yes	No, but the review was based on an existing review.	No
5	Yes (3 and more)	Yes (1–2 terms)	No
6	Three or more databases and search years mentioned	Two or fewer databases and no specific search year	Not reported
7	Yes	Implicit	No
8	Yes (explicitly defined)	Implicit	No
9	Three or more	Two or less	None
10	Yes	Implicit derived	No

. The average of the total points related to each paper was analyzed. The quality score range of the selected paper varied from 3 to 9.5 (

Table 5. Quality assessment score of the selected articles.

SLR ID	1	2	3	4	5	6	7	8	9	10	Total
R1	1	1	0.5	1	0.5	1	1	0.5	1	1	8.5
R2	1	1	0.5	0.5	1	1	1	0	0.5	1	7.5
R3	0.5	1	0.5	0.5	0.5	0.5	0	0.5	0.5	0	4.5
R4	1	1	1	1	0	1	1	0	1	1	8.0
R5	1	1	1	0.5	1	1	1	1	1	1	9.5
R6	1	0	0.5	1	1	1	0	0	1	0.5	6.0
R7	1	1	1	1	1	1	1	0	0.5	0.5	8.0
R8	1	1	1	1	1	1	1	1	0.5	0.5	9.0
R9	1	1	1	1	1	1	1	1	0.5	0.5	9.0
R10	0.5	1	1	1	0.5	1	0.5	0	0.5	0.5	6.5
R11	0.5	1	0.5	0	0.5	0.5	0.5	0	0.5	0.5	4.5
R12	0.5	1	0.5	0.5	0.5	0.5	1	0	0.5	0.5	5.5
R13	0.5	1	1	1	0.5	0.5	1	0	0.5	1	7.0
R14	0.5	1	1	1	1	1	0.5	0	0.5	1	7.5
R15	0.5	1	1	1	1	0.5	1	0	0.5	0.5	7.0
R16	1	1	0.5	1	1	1	0.5	0	1	0.5	7.5
R17	1	1	0.5	1	1	1	1	0	0.5	0.5	7.5
R18	1	1	1	0.5	1	1	0	0	0.5	0.5	6.5
R19	0.5	0	1	0.5	0.5	1	0	0	0	0	3.5
R20	0.5	1	1	1	0.5	0.5	1	0.5	0.5	0.5	7.0
R21	1	1	1	1	1	0.5	0.5	0.5	0.5	1	8.0
R22	0.5	1	0.5	1	1	0.5	1	0	0.5	0.5	6.5
R23	1	1	1	1	0.5	0.5	0.5	0.5	0.5	0.5	7.0
R24	0.5	1	0.5	1	0.5	0.5	0.5	0.5	0.5	0.5	6.0
R25	1	0	0.5	1	1	1	1	0	0.5	1	7.0
R26	0.5	0	0.5	0	0.5	0.5	0	0	0.5	0.5	3.0
R27	0.5	0	1	1	0.5	0.5	0	0	0.5	0.5	4.5
R28	1	1	1	1	1	1	1	1	0.5	0.5	9.0
R29	1	1	1	1	1	1	1	0	0.5	0.5	8.0

).

The SLRs with a quality score lower than 6.5 were expressively excluded from this study due to low quality (Appendix A). The articles’ quality scores are shown in Table 5 and presented in the bar graph in Figure 2.

2.4. Data Extraction and Analysis

The data were extracted from the selected 21 articles into a spreadsheet for further analysis. Information extracted from each article was classified into three categories: (1) bibliographic details including author name, title, abstract, publication year and type, and keywords; (2) quality of systematic literature review, including publisher, type, search string, number of databases searched, guidelines used for SLR, search string used, analysis method, and research questions; (3) research question-related information, including which blockchain challenges were studied as well as the aim of the study and its findings.

The data were arranged into three separate spreadsheets category-wise, as defined previously. A thematic analysis of the collected data was conducted. This study used an inductive approach to analyze the selected review articles and categorize them based on themes through an iterative process of reading, interpreting, summarizing, and grouping them based on themes, including scalability, blockchain, smart contract, interoperability, security, and privacy.

3. Findings

This section describes the findings in detail. The results are presented according to the research questions mentioned in Section 2.

RQ1. 

How many SLRs have been published since blockchain technology emerged as Bitcoin (2009) to date (2023), and what is their quality?

This study identified 29 articles that met the criteria for objective and selection criteria. Following a thorough quality assessment, 21 articles were selected for a detailed review, comprising 17 peer-reviewed journal articles, three conference papers, and one book chapter (

Table 6. Article reviews.

SLR ID	Area	Publication Year	Publication Type	Publisher	Type of Review	Primary Studies	Years Covered	SLR Guidelines	Data Analysis Method
R1	BC	2016	Journal	PLOS ONE	MA + SLR	41	2012–2015	KC & Petersen et al.	Narrative + CA
R2	SC	2018	Journal	Elsevier (Telematics and Informatics)	MA	64	2008–2018	Petersen et al.	Narrative + CA
R4	SC	2019	Journal	Elsevier (Computers & Security)		35	2015–2019	KC	Narrative
R5	BC	2020	Journal	ACM (ACM Computing Surveys)	SMLR	111	Till 2018	KC & Garousi et al.	FCA, GT
R7	PV	2020	Journal	MDPI (Sensor)	SLR	28	2016–2020	KC	Narrative
R8	SC	2020	Journal	IEEE (IEEE Access)	SLR	25	2019–2020	KC	Narrative + CA
R9	SC	2020	Journal	Elsevier (The Journal of Systems & Software)	SLR	96	2016–2020	KC	Narrative + CA
R10	SC	2020	Journal	EverScience (IJCNA)	SMA	>100	2007–2018	KC	Narrative
R13	CP	2020	Conference	IEEE (CONISOFT)	MLR	27	2015–2020	KC & Garousi et al.	Narrative
R14	SC	2021	Journal	CellPress (Patterns)	SLR	159	2008–2020	KC	Narrative
R15	BC	2021	Journal	IEEE (IEEE Access)	SLR	39	2017–2020	KC	Narrative
R16	SC	2019	Journal	IEEE (IEEE Access)	SLR	90	Till 2018	KC & Petersen et al.	Narrative & MA
R17	SA	2021	Journal	MDPI (Applied Science)	SLR	121	2010–2019	PRISMA & KC	Narrative
R18	SA	2021	Journal	Elsevier (JNCA)	SLR	351	2012–2020		Narrative
R20	CP	2021	Conference	Springer (IFIP)	SLR	35	2016–2020	KC	Narrative
R21	CP	2022	Journal	IEEE (IEEE Access)	SLR	87	2018–2020	KC	Narrative +QA
R22	BC	2022	Conference	IEEE (ICSA-C)	SMA	19	2016–2019	Petersen et al.	Narrative
R23	IO	2021	Book Chapter	Springer (Trust models for Next-Generation Blockchain)	SLR	76	2015–2020	KC	Narrative
R25	SA	2022	Journal	Elsevier (Future Generation computer system)	SR	63	2015–2020	KC	Narrative
R28	BC	2023	Journal	Elsevier (The Journal of Systems & Software)	SLR	37	2008–2020	KC	Narrative
R29	SA	2023	Journal	Elsevier (Blockchain: Research and Applications)	SLR	114	2016–2022	PRISMA	Narrative

BC—blockchain, SC—smart contract, PV—privacy, CP—consensus protocol, SA—scalability, IO—interoperability, MA—mapping analysis, SMA—systematic mapping analysis, KC—Kitchenham and Charters [5], GT—ground theory, CA—critical analysis.

). The quality scores for these articles ranged between 6.5 and 9.5, as shown in Table 5. Table 7 lists the articles selected for further review and analysis.

The first systematic literature review addressing technical challenges in blockchain was published in 2016 [1]. Despite the absence of relevant reviews in 2017, the volume of review articles saw a significant increase by 2020 (Figure 3). Only four conference papers met both the selection and quality criteria. No umbrella review that encompassed all blockchain challenges was identified. Among the articles, only two peer-reviewed and one conference paper covered more than one technical challenge. It was noted that smart contracts, a critical component of blockchain technology, received extensive coverage (Table 6). Other aspects, such as consensus mechanisms, privacy, and interoperability, were less frequently reviewed, though there was an abundance of survey literature addressing these challenges.

Smart contracts emerged as the most extensively reviewed blockchain element, particularly focusing on their security and coding language interoperability. This intense scrutiny is primarily due to their widespread use in the business sector and their role in enabling distributed applications (dApps) [1].

RQ2. 

What research areas are addressed in the SLRs on blockchain technical challenges?

A multitude of technical challenges in blockchain technology has been systematically examined in the literature, including security, scalability, smart contract integrity, privacy, data storage, governance, and interoperability [1,8,9,10,11,12]. Security concerns, particularly the threat of a 51% attack and the vulnerabilities associated with private and public key infrastructures, represent the most extensively reviewed topics within blockchain research [1,8]. Moreover, the security of smart contracts has been a focal point, with studies highlighting that the integrity of decentralized applications (dApps) hinges critically on the robustness of smart contract frameworks; any compromise can potentially destabilize the entire system [13,14].

Scalability challenges have also been a major point of discussion, particularly in industrial applications of blockchain, where the demands on system capacity often exceed what decentralized architectures can typically support, especially when contrasted with centralized systems [12]. Within second-generation blockchain platforms, issues around smart contract security and privacy have been rigorously debated [14,15,16,17,18].

Blockchain interoperability, described as a pivotal hurdle, affects the seamless integration of blockchain systems across varied business domains, aiming to create a decentralized internet-like network [10]. Additional challenges reviewed include data privacy and governance issues related to consensus mechanisms, performance bottlenecks, data storage constraints, and the synchronization time required for block confirmation [1,19].

Moreover, the literature has extensively covered the technical difficulties associated with smart contract implementation and execution [11,13,14,15,16,17,18]. These discussions have dissected various components of smart contract functionality, such as security vulnerabilities [14], code flaws [18], susceptibility to hacking, and the limitations inherent in executing contracts drafted in natural language. The translation of natural language into executable smart contract code remains a particularly daunting challenge, given the nuanced and context-dependent nature of legal language in various sectors [17,18]. This area, vital for ensuring that smart contracts serve as valid and legally binding agreements, continues to require significant advancements to bridge the gap between legal stipulations and technical execution.

RQ3. 

What are the major technical factors that challenge the integration of blockchain technology in various industries?

One of the principal technical challenges limiting industry-specific blockchain applications is interoperability—the capability of different systems to exchange and use information effectively [8,10]. The isolated nature of blockchain development often results in “islanding”, which disrupts the seamless transmission of data between different blockchains, undermining core features such as immutability and transparency [10]. Another significant challenge is scalability, which, in comparison to traditional centralized systems used in industries, tends to be lower due to the intensive consensus mechanisms like Proof of Work and the decentralized architecture of blockchain systems [8,9,12,20]. Various new methodologies have been proposed in the literature to enhance scalability through both on-chain and off-chain models, including approaches like pipelining, content delivery networks, payment channels, sharding, parallel mining, system redesign, and hardware-assisted strategies [12]. However, these scalability solutions introduce their own set of challenges, such as the rational behavior of nodes and the need for trusted hardware in various sharding methods, which may not always be feasible [12]. Additionally, issues like blockchain size and data redundancy have been identified as factors discouraging the wider adoption of blockchain technology across different industries [12].

RQ4. 

What technical challenges need more attention to implement mainstream blockchain technology in various business verticals?

One of the least examined technical challenges in blockchain research concerns interoperability and integration with existing legacy systems. Various interoperability schemes have been discussed in the studies, such as [7,15]. Blockchain systems often operate as isolated distributed ledgers, making it difficult to integrate and manage data across different blockchain systems. Industries might benefit from adopting blockchain solutions with interoperability features that facilitate interactions with sub-vendors and partners within their supply chains [10]. Additionally, integrating legacy systems with blockchain technology has received inadequate attention. Developing an efficient and effective bridge that facilitates data transactions between legacy and blockchain systems is crucial for future blockchain advancements. It is essential to establish an interoperability protocol that allows for a seamless, cost-effective transition from legacy database systems to blockchain, benefiting various industries.

Another underexplored area is the impact of the blockchain on data protection regulations, such as the General Data Protection Regulation (GDPR) implemented by several European Union countries. As consumer data privacy becomes increasingly critical and more countries consider similar regulations allowing users to request data deletion, the immutable nature of blockchain presents challenges in this aspect [21]. The blockchain does not naturally allow for data modification or deletion. However, the literature proposes several methods to address these issues, such as pseudonymization, which allows for the removal of partial user data [22]. Additionally, off-chain approaches store sensitive data outside the blockchain, using cryptographic techniques that preserve identity privacy, such as zero-knowledge proofs, attribute-based signatures, and ring signatures [19]. Despite these methods, no one currently offers a complete solution for the “Right to Forget” or the complete deletion of data on a blockchain.

RQ5. 

What progress has been achieved in the course from one study to another in the research timeline, and how does it address the challenges that business faces in technology integration?

The blockchain is an emerging field of research that has been expanding rapidly as efforts intensify to address its limitations and enhance its performance to meet industry needs. In previous studies, such as [1], only a few technical challenges have been addressed, including issues related to throughput, latency, size, bandwidth, security, resource wastage, usability, and forks. Many of these challenges, such as resource wastage, forks, and usability issues, are specifically linked to first-generation blockchains like Bitcoin. However, second-generation blockchains like Hyperledger have addressed usability problems by incorporating REST APIs into the blockchain framework. Additionally, the shift from a proof of work consensus mechanism to more efficient ones like proof of stake or Raft consensus [8] has mitigated issues related to resource wastage. Subsequent reviews have broadened the scope of challenges addressed, recognizing the need for interoperability among different blockchain systems and data transferability between blockchain and traditional systems [10] to support globally integrated business models.

While significant progress has been noted in addressing scalability, user interaction, security, and privacy within blockchain technology, other critical aspects such as interoperability, data immutability in compliance with the “Right to Forget” laws, and the integration of oracles (which allow external data to be used as inputs in blockchain smart contracts) have been less thoroughly explored. Although various mechanisms to achieve interoperability have been proposed, there is no widely accepted standard method yet. Furthermore, the issue of user data privacy is increasingly concerning due to rising cybersecurity attacks and data thefts, prompting governments to enact legislation like the GDPR to enhance user control over their data [22]. However, only a limited number of studies have reviewed this aspect [21,22].

Table 7. Articles included for review.

ID	Title	Year	Ref
R1	Where is current research on Blockchain technology?—A systematic review	2016	[1]
R2	Smart contract applications within blockchain technology: A systematic mapping study	2018	[15]
R4	Blockchain smart contracts formalisation: Approaches and challenges to address vulnerabilities	2019	[16]
R5	Blockchains: A Systematic Multivocal Literature Review	2020	[8]
R7	Blockchain from the Perspective of Privacy and Anonymisation: A Systematic Literature Review	2020	[19]
R8	Model-Based Software Design and Testing in Blockchain Smart Contracts: A Systematic Literature Review	2020	[11]
R9	A systematic literature review of blockchain and smart contract development: Techniques, tools, and open challenges	2020	[17]
R10	An empirical review on blockchain smart contracts: Application and challenges in implementation	2020	[13]
R13	Consensus Mechanisms in Distributed Ledgers for the Protection of Confidential Data: A Multivocal Literature Review	2020	[23]
R14	A comprehensive survey on smart contract construction and execution: paradigms, tools, and systems	2021	[18]
R15	GDPR Compliant Blockchains—A Systematic Literature Review	2021	[21]
R16	Security, Performance, and Applications of Smart Contracts: A Systematic Survey	2019	[14]
R17	Systematic Literature Review of Challenges in Blockchain Scalability	2020	[9]
R18	A systematic review of blockchain scalability: Issues, solutions, analysis and future research	2021	[20]
R20	A Systematic Literature Review of Blockchain Consensus Protocols	2021	[24]
R21	A Systematic Literature Review Toward a Blockchain Benchmarking Framework	2022	[25]
R22	Blockchain Architectural Concerns: A Systematic Mapping Study	2022	[26]
R23	Interoperability Among Heterogeneous Blockchains: A Systematic Literature Review	2021	[10]
R25	Scalable blockchains—A systematic review	2022	[12]
R28	A systematic literature review on blockchain governance	2023	[27]
R29	A systematic literature review of the tension between the GDPR and public blockchain systems	2023	[22]

Table 7. Articles included for review.

ID	Title	Year	Ref
R1	Where is current research on Blockchain technology?—A systematic review	2016	[1]
R2	Smart contract applications within blockchain technology: A systematic mapping study	2018	[15]
R4	Blockchain smart contracts formalisation: Approaches and challenges to address vulnerabilities	2019	[16]
R5	Blockchains: A Systematic Multivocal Literature Review	2020	[8]
R7	Blockchain from the Perspective of Privacy and Anonymisation: A Systematic Literature Review	2020	[19]
R8	Model-Based Software Design and Testing in Blockchain Smart Contracts: A Systematic Literature Review	2020	[11]
R9	A systematic literature review of blockchain and smart contract development: Techniques, tools, and open challenges	2020	[17]
R10	An empirical review on blockchain smart contracts: Application and challenges in implementation	2020	[13]
R13	Consensus Mechanisms in Distributed Ledgers for the Protection of Confidential Data: A Multivocal Literature Review	2020	[23]
R14	A comprehensive survey on smart contract construction and execution: paradigms, tools, and systems	2021	[18]
R15	GDPR Compliant Blockchains—A Systematic Literature Review	2021	[21]
R16	Security, Performance, and Applications of Smart Contracts: A Systematic Survey	2019	[14]
R17	Systematic Literature Review of Challenges in Blockchain Scalability	2020	[9]
R18	A systematic review of blockchain scalability: Issues, solutions, analysis and future research	2021	[20]
R20	A Systematic Literature Review of Blockchain Consensus Protocols	2021	[24]
R21	A Systematic Literature Review Toward a Blockchain Benchmarking Framework	2022	[25]
R22	Blockchain Architectural Concerns: A Systematic Mapping Study	2022	[26]
R23	Interoperability Among Heterogeneous Blockchains: A Systematic Literature Review	2021	[10]
R25	Scalable blockchains—A systematic review	2022	[12]
R28	A systematic literature review on blockchain governance	2023	[27]
R29	A systematic literature review of the tension between the GDPR and public blockchain systems	2023	[22]

4. Limitations

This article reviews systematic literature reviews (SLRs) published in scientific journals and conferences, purposely excluding gray literature. Many articles within the gray literature discuss enhancements in blockchain efficiency and performance by various businesses and startups. However, this review is confined strictly to scholarly publications. The blockchain sector is still evolving, and its industry adoption faces hurdles due to technical complexities. While numerous survey papers exist across different blockchain application domains, they were not considered here due to their lack of systematic review methodologies or in-depth critical discussions.

The paper examined SLRs addressing technical challenges in the blockchain; however, the application of blockchain is rapidly growing in diverse business contexts. Notably, this study did not cover technical challenges specifically related to business use cases, such as consensus mechanisms. Blockchain consensus mechanisms, which are tailored based on business needs, exemplify the necessity of integrating both technical and non-technical reviews to address future research and development opportunities, especially in areas like system governance rules and individual roles within the system.

The current SLR reviewed only a limited set of technical challenges, typically no more than four. There is a distinct need for an SLR that comprehensively reviews all technical challenges and their interdependencies, enhancing understanding of how solutions to one issue might influence others. For example, interoperability could enhance both scalability and data privacy, and an efficient consensus mechanism might also improve scalability.

Future research should particularly focus on challenges like interoperability, data immutability, and security. With the rising incidence of cyberattacks leading to private data breaches, it becomes crucial for global legislation to empower consumers with greater data control and the right to be forgotten. However, the blockchain’s foundational architecture does not support data deletion. Thus, future studies must develop blockchain architectures that maintain core characteristics like data immutability while complying with such legislative requirements. Additionally, the advent of quantum computing poses new challenges to the blockchain’s hashing mechanisms, warranting a focused investigation in future research.

5. Conclusions

Research on blockchain technology has accelerated significantly over the past ten years, with numerous scientific articles being published. However, the focus has predominantly been on the application of the blockchain rather than its technical underpinnings. The blockchain’s appeal largely stems from its capabilities like transparency, smart contracts, and a decentralized IT infrastructure that supports various business domains. Despite this, the practical deployment of the blockchain across industries remains confined to areas such as finance (digital currencies and crowdfunding), supply chain management (financial transactions), healthcare (personal health records), real estate (land registry), and voting (fraud prevention). Nevertheless, the blockchain holds considerable potential to enhance areas like supply chain management, sustainability information management, the service sector (freelancing platforms), identity verification, interbank transactions, legal systems (judicial records), academia (certificate issuing and validation), and carbon credit. Despite its promise, blockchain technology remains largely experimental due to numerous technical challenges that hinder broader implementation.

This article reviews systematic literature reviews (SLRs) focused on the technical challenges that blockchain technology faces, assessing the current research landscape. While some technical issues have been thoroughly explored, with innovative solutions being proposed, other critical areas, such as interoperability between legacy systems and the blockchain, have received less attention. Although there are several survey papers available, there are relatively few SLRs. The research has primarily concentrated on technical aspects, the security of smart contracts, and their execution and performance. Meanwhile, important topics like smart contract code interoperability, system interoperability, and data immutability have been underexplored. Given the nascent state of blockchain technology and the ongoing efforts by various companies to advance this field, there is a clear need for more comprehensive SLRs that incorporate gray literature in their analyses.