Cited by 104Blockchain Technology Applications and SecuritySmart Cities and TechnologiesBlockchain Technology in Education and Learning

The DOI matches its Crossref record; 125 of the 128 references it cites were found in a registry or an index; none of the 41 sources its claims cite is checked for support yet.

Blockchain technology in the smart city: a bibliometric review

Open access

Abstract

Blockchain can function as a foundational technology with numerous applications in smart cities. The objective of this paper is twofold. First, it provides a detailed overview of the extant literature on blockchain applications in smart cities; second, it reveals the trends and suggests future research directions for scholars who wish to contribute to this rapidly growing field. We conducted a bibliometric review using a keyword co-occurrence network and article co-citation analysis. The analysis includes the assessment of 148 articles published between 2016 and 2020 in 76 academic journals. The review results demonstrate that the number of articles devoted to the study of blockchain applications and smart cities has increased exponentially in recent years. More importantly, the research identifies some of the most influential studies in this area. The paper discusses trends and highlights the challenges related to the deployment of blockchain in smart cities. To the authors’ best knowledge, this represents the first study to review the literature from leading journals on blockchain applications in smart cities using bibliometric techniques.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This bibliometric review maps 148 journal articles published between 2016 and 2020 on blockchain applications in smart cities, identifying publication trends, leading countries and journals, keyword clusters, and co-cited works. It reports exponential growth in the field and highlights challenges including scalability, lack of standards, and technological immaturity.

Key findings

  • The review analyzed 148 articles published from 2016 to 2020 in 76 academic journals; annual output peaked in 2020 with 92 papers.
  • Leading contributing countries were China (32 papers), India (27), and the USA (27), followed by South Korea (17), the UK (15), Australia (13), and Spain (11); countries with fewer than five papers totaled 35 papers.
  • Leading journals were IEEE Access (15 articles), IEEE Internet of Things Journal (10), and Future Generation Computer Systems (6); 66 “Other” journals published 85 papers.
  • Keyword co-occurrence produced six clusters with 89 nodes; article co-citation with a threshold of at least two citations displayed 58 nodes in four clusters. The most cited articles were Khan and Salah (2018) with 548 citations, Sharma et al. (2017) with 189, and Sun et al. (2016) with 172.

Methods

  • Bibliometric review using Scopus, searching title, abstract, and keywords with `Blockchain AND "smart cit*"`; limited to English journal articles published before 2021 in engineering, computer science, social sciences, business/management/accounting, decision sciences, and economics. Scopus returned 162 documents, reduced to 150, then screened to 148 final articles.
  • Descriptive analysis of publication year, country, and journal, plus keyword co-occurrence network and article co-citation analysis using VOSviewer and Bibexcel with LinLog/modularity normalization. Keyword co-occurrence threshold was a minimum of two; co-citation threshold was at least two citations per article.

Limitations

  • Stated: the review covers a short period (2016–2020) and specific subject areas; the collection is not exhaustive; only article co-citation analysis was used, not bibliographic coupling, author co-citation, or co-authorship; results depend on the search keywords; only journal articles were selected, excluding conference proceedings, books, and book chapters; and only Scopus was used because VOSviewer cannot merge multiple databases.
  • Evident: the study is a bibliometric and network analysis rather than an empirical test of blockchain outcomes; the paper itself notes that some application fields, such as healthcare, data sharing, and sharing economy services, have received less empirical attention.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1007/s11135-021-01251-2

Cites

125 of 125 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Fig. 1 The literature review procedure and eligibility criteria
Fig. 1 The literature review procedure and eligibility criteriaCC BY · PubMed Central
Fig. 2 Year-wise distribution of publications
Fig. 2 Year-wise distribution of publicationsCC BY · PubMed Central
Fig. 3 Country-wise distribution of publications
Fig. 3 Country-wise distribution of publicationsCC BY · PubMed Central
Fig. 4 Distribution of publications by professional journals
Fig. 4 Distribution of publications by professional journalsCC BY · PubMed Central
Fig. 5 The keyword co-occurrence network
Fig. 5 The keyword co-occurrence networkCC BY · PubMed Central
Fig. 6 Article co-citation network
Fig. 6 Article co-citation networkCC BY · PubMed Central

Verification

Claims the paper makes

34 Own result · 30 Own interpretation · 27 Not checked yet · 17 No basis given · 8 Own method · 1 Sources not found

Verify all 40 references — free account

Show all 41 claims

  • It may state two separate claims as one. 43
  • Probably not a substantial claim. 58
  • The quote only partly states this claim. 1
76 of 76
  • The paper relies on this without support.

    No previous study has reviewed blockchain and smart city research using bibliometric tools such as keyword co-occurrence network and article co-citation analyses.

    “Previous studies have attempted to review the existing applications of blockchain in the context of smart cities (Bernabe et al. 2019; Li et al. 2019), but to the best of our knowledge, no previous study has reviewed blockchain and smart city research using bibliometric tools such as keyword co-occurrence network and article co-citation analyses.”
  • The paper relies on this without support.

    Current database technologies do not effectively manage and securely store voluminous data.

    “However, current database technologies do not effectively manage and securely store voluminous data.”
  • The paper relies on this without support.

    Bitcoin blockchain is widely used for cryptocurrency and not appropriate for general purpose applications.

    “This blockchain is widely used for cryptocurrency and not appropriate for general purpose applications.”
  • The paper relies on this without support.

    Bitcoin provides a safe and strong payment system that outperforms any other blockchains.

    “Nevertheless, being the initial and largest public blockchain, Bitcoin provides a safe and strong payment system that outperforms any other blockchains.”
  • The paper relies on this without support.

    The technology's infancy does not constitute a problematic issue since blockchain applications are expected to mature with time.

    “However, the technology's infancy does not constitute a problematic issue since blockchain applications are expected to mature with time.”
  • The paper relies on this without support.

    Smart cities are endangered by a wide array of security and privacy threats.

    “Nevertheless, smart cities are still endangered by a wide array of security and privacy threats.”
  • The paper relies on this without support.

    Many different methods exist to perform co-citation analyses, such as bibliographic coupling, author co-citation analysis, and co-authorship analysis.

    “Many different methods exist to perform co-citation analyses, such as bibliographic coupling, author co-citation analysis, and co-authorship analysis.”
7 of 7

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

2 of 2

Citations

Cites

Show all 128 references

Research works printed but not linked: 2

  1. Rejeb, A., Sűle, E., Keogh, J.G.: Exploring new technologies in procurement. Transp. Logis. Int. J. 18(45), 76–86 (2018)
  2. Szabo, N.: Smart contracts: building blocks for digital free markets. Extropy J. Trans. Thought 16, 1–10 (1996)

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Metadata

Authors
Rejeb, A., Rejeb, K., Simske, S. J., & Keogh, J. G.
Affiliations
  • Széchenyi István University (HU)
  • Tunis El Manar University (TN)
  • Colorado State University (US)
  • University of Reading (GB)
Corresponding author
  • Rejeb, Abderahman
  • Rejeb, Karim
  • Simske, Steven J.
  • Keogh, John G.
Venue
Quality & Quantity
Published
2021-10-06
Volume
56
Issue
5
Pages
2875-2906
ISSN
  • 0033-5177 (ISSN-L)
  • 1573-7845
OpenAlex
W3204566152
Cited by
104
References
128
Citations by year
2026: 13 · 2025: 25 · 2024: 28 · 2023: 25 · 2022: 11 · 2021: 1
FWCI
14.68
Type
journal article
Language
en
Open access
Locations
  • Quality & Quantity (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Greater South Information System
Funders
Széchenyi István University
Topics
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Social Sciences › Urban Studies › Smart Cities and Technologies
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
Keywords
blockchain, smart cities, blockchain applications, research trends, research directions, keyword co-occurrence network, co-citation analysis

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-10-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-10-09 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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