Application of Blockchain Technology in Emergency Management Systems: A Bibliometric Analysis

Abstract

Blockchain technology has emerged as a transformative solution to address specific aspects of emergency management systems by providing a decentralized and distributed ledger infrastructure that enhances data immutability, transparency, and traceability. This study presents a comprehensive bibliometric analysis of blockchain applications in emergency management covering the period from 2017 to 2024 and based on 248 research articles indexed in the Web of Science Core Collection. The analysis examines collaboration networks, co-citation patterns, citation bursts, and keyword trends to uncover key research clusters and emerging themes. Seven major clusters were identified, with their intellectual core built around influential publications that highlight blockchain’s role in improving transparency, efficiency, and trust in emergency response systems. The findings emphasize the growing impact of blockchain technology in enhancing preparedness and resilience during crises while identifying gaps in global collaboration and interdisciplinary innovation.

1. Introduction

Emergency management systems play a critical role in the protection of populations during incidents, including natural disasters, conflicts, human-caused emergencies, technological hazards, and other circumstances [1,2,3,4]. These systems depend on efficient coordination, transparent resource distribution, and rapid response mechanisms to mitigate risks and provide timely assistance [5,6,7]. However, traditional state-controlled emergency management frameworks often suffer from inefficiencies, lack of transparency, bureaucratic delays, and susceptibility to corruption [1,8,9].

Recent examples of global crises underscore and confirm these claims. During the COVID-19 pandemic, many countries faced delays in the distribution of medical supplies and vaccines, with opaque allocation processes and corruption in procurement [10,11]. Similarly, the Beirut port explosion revealed serious delays in emergency response, a lack of transparency in aid distribution, and corruption in the management of hazardous materials [12]. The response to Cyclone Idai in 2019 was marked by poor coordination, delayed aid delivery, and allegations of corruption and misallocation of resources by local governments [13]. The ongoing war in Ukraine further illustrates these challenges, as both military and humanitarian efforts have been hampered by bureaucratic inefficiencies, delays in aid distribution, and problems with transparency of resource allocation, with some reports indicating that corrupt practices have affected the delivery of international aid [14,15]. These cases highlight significant systemic flaws that hinder the effectiveness of civil protection efforts in times of crisis.

Blockchain technology has been proposed as a promising solution to address these limitations by providing a decentralized, transparent, and secure framework for data management and resource tracking [16,17,18]. According to Kramer et al., blockchain is “a software protocol that governs the rules for securely transferring assets incorruptibly over the Internet. It enables peer-to-peer collaboration in decentralized networks, eliminating the need for third-party intermediaries or a centrally coordinating trust entity” [19]. In blockchain technology, transactions and data are stored in the form of blocks that are distributed and decentralized across the network [16,20]. A defining feature of blockchains is the immutability of data recorded in previous blocks, as each block contains a hash of the preceding block that serves as a unique identifier. This structural characteristic ensures a high level of security and transparency within blockchain systems [20,21,22]. The concept of decentralization implies that no single individual or organization has full control over the network; instead, all network participants are collectively responsible for validating and recording transactions [20,23,24]. Moreover, blockchain systems are transparent and publicly accessible while maintaining data confidentiality through the secure handling of transaction details [20,21,22,24]. This combination enhances security and resilience against fraud and manipulation.

Depending on the level of access and centralization, blockchains can be categorized into three main types: public, private, and consortium [25,26]. Public blockchains are highly decentralized and open to any user; as such, they fully utilize the foundational capabilities of the technology, though often at the cost of efficiency and performance [25,26,27]. In contrast, private blockchains are governed by a central authority, offering greater operational efficiency and flexibility but limiting accessibility and innovation potential [25]. Consortium blockchains represent a hybrid model, combining the advantages of both public and private systems to achieve a balanced approach [26].

When integrated into emergency management systems, blockchain technology can help humanitarian organizations, emergency response agencies, and government bodies to improve accountability, streamline resource distribution, and enhance coordination among stakeholders by enabling smart contracts that automatically execute predefined actions as well as by supporting decentralized applications (dApps) that leverage these contracts and other blockchain features to address practical challenges in crisis response [28,29,30,31,32,33].

Ultimately, emergency management systems can be made more resilient, efficient, and transparent by leveraging blockchain technology, resulting in stronger overall preparedness and response capabilities [1,34,35].

The aim of this study is to provide a comprehensive bibliometric analysis of the application of blockchain technology in emergency management systems. To achieve this, we utilized CiteSpace 6.4.R1 to analyze 248 research articles published between 2017 and 2024 and indexed in the Web of Science Core Collection (WoSCC). This approach enabled a systematic mapping of the knowledge structure, development trends, and key challenges within this rapidly evolving field.

The study focuses on the following research questions (RQs):

RQ1: Which countries, institutions, and authors collaborate in research on blockchain technology applications in emergency management systems, and what are their contributions to advancing this field?

RQ2: What are the main research clusters, hotspots, and evolving trends in the application of blockchain technology within emergency management systems?

RQ3: How has blockchain technology transformed emergency management practices, what challenges remain, and what are the prospective frontiers for future research?

This study is significant in that it offers unique contributions and innovations to the field of blockchain technology in emergency management systems, which distinguishes it from previous reviews and analyses. The main contributions are as follows:

First, from a methodological perspective, this study is innovative in its use of a comprehensive bibliometric approach to systematically analyze the research landscape of blockchain technology in emergency management systems. The bibliometric method supported by CiteSpace 6.4.R1 enables visualization and quantification of collaboration networks, co-citation patterns, and keyword trends, providing vivid and intuitive insights into the intellectual landscape of the field. This approach is relatively new for this research area and allows for the capture of critical information that might be overlooked in traditional narrative reviews.

Second, from a viewpoint perspective, this study stands out by delivering objective and comprehensive results based on quantitative data from 248 research articles indexed in the WoSCC. The data-driven nature of the analysis minimizes subjective bias and offers an integrated understanding by combining both static (e.g., publication output, leading countries, institutions, authors) and dynamic (e.g., emerging clusters, citation bursts, evolving trends) aspects of the research domain. This comprehensive viewpoint enables readers to grasp both the current state and developmental trajectory of blockchain research in emergency management.

Third, from a theoretical and practical perspective, this study constructs a macro-level knowledge framework for the field and identifies future research directions.

These contributions collectively offer valuable guidance for researchers, practitioners, and policymakers aiming to accelerate the adoption and integration of blockchain technology in emergency management systems.

The rest of the paper is organized as follows: Section 2 reviews the related work; Section 3 outlines the research methodology; Section 4 presents the results of the bibliometric analysis (co-citation clustering, emerging trends, and highly cited references) and describes the analysis of co-citation clustering; Section 5 discusses the findings and outlines directions for future research; finally, Section 6 provides the conclusions of the study.

2. Related Work

In recent years, there has been a surge of interest in the application of blockchain technology to emergency management systems, with numerous surveys and reviews highlighting both the opportunities and challenges in this field.

Traditional reviews in this domain primarily offer qualitative syntheses of the literature, focusing on summarizing the challenges, opportunities, and specific applications of blockchain technology in emergency contexts. These reviews typically:

• Discuss blockchain’s potential to enhance transparency, security, and coordination in emergency response [35,36,37,38].
• Explore specific use cases, including the healthcare sector [39,40,41,42], optimizing humanitarian supply chains [43,44], enhancing disaster response coordination [37,45], ensuring data integrity in crisis communication systems [45,46], and others.
• Highlight technical and operational challenges, including scalability, interoperability, and regulatory issues [35,37].
• Provide and discuss conceptual frameworks and identify practical implications for emergency management stakeholders [1,47,48].

While these reviews are valuable for understanding the current state of the field, they are often limited by their subjective nature and lack of quantitative analysis, which can obscure broader research dynamics and long-term trends.

In contrast, bibliometric reviews employ quantitative methods to examine publication patterns, collaboration networks, citation dynamics, and emerging research trends. These approaches offer objective and data-driven insights that complement traditional reviews by revealing the structural and temporal evolution of the research landscape.

In the context of blockchain in emergency management, existing bibliometric studies tend to focus on narrow subsets of applications [49,50]. Some of these studies are limited in scope due to factors such as geographic focus or restricted time frames [34,51]. Moreover, many previous works do not concentrate specifically on blockchain technology [52,53,54].

In summary, while the existing literature confirms the significant potential of blockchain technology to improve efficiency, transparency, and resilience in emergency management applications, there is a clear lack of comprehensive bibliometric analyses that systematize current knowledge, evaluate scientific collaboration, and identify future research directions. The present study addresses that gap by providing an integrated and objective overview intended to inform both academic research and practical implementations.

3. Materials and Methods

3.1. Data Sources

All analyzed data were downloaded from the WoSCC on 25 March 2025, resulting in a dataset of 248 articles. We selected the WoSCC as the data source due to its comprehensive and interdisciplinary coverage of high-impact academic publications across various fields [55]. The WoSCC is widely regarded as the gold standard for research discovery and analysis, linking publications and researchers to databases that span a multitude of disciplines [56]. The platform’s rigorous indexing criteria and extensive database of citations and references make it an invaluable resource for bibliometric analysis, ensuring the credibility and quality of the papers included in our study.

The retrieval strategy employed a search using Boolean operators, expressed as follows: (TS = (“Emergency Management”) AND TS = (“Blockchain”)). Here, TS stands for topic search, which queries the title, abstract, author keywords, and keywords-plus of each publication.

3.2. Study Criteria

The inclusion criteria for this study comprised literature related to the application of blockchain technology in emergency management systems, encompassing both original research articles and reviews published in English. Exclusion criteria included meeting abstracts, editorial materials, letters, news items, and duplicate records.

3.3. Analytical Methods

Our bibliometric analysis process is illustrated in Figure 1.

As revealed by our analysis of the dataset from the WoSCC, the first papers on the application of blockchain technology in emergency management emerged in 2017. This marks a pivotal point when blockchain technology began to be explored as a viable solution for enhancing emergency response systems. The year 2024 was chosen as the endpoint because it represents the most recent completed year of data available at the time of this review. This approach ensures that the analysis is based on the most up-to-date and comprehensive dataset, capturing the latest trends and developments in the field.

We utilized CiteSpace 6.4.R1 to systematically map the knowledge domain of blockchain technology in emergency management from 2017 to 2024. Our decision to use CiteSpace was grounded in its robust capabilities for visualizing and analyzing scientific knowledge structures. CiteSpace provides powerful visual and temporal analysis tools such as co-citation networks, keyword bursts, and time-sliced mapping that can reveal complex scholarly patterns and trends, aligning closely with our research focus on the dynamics of scholarly collaboration and the structure of scientific knowledge [57].

This analysis examined various dimensions, including the following: annual publication and citation trends; collaboration networks among authors, institutions, and countries; co-citation patterns; and evolving keyword trends. By detecting keywords with significant citation bursts, our approach also identified emerging research directions, methodological innovations, and persistent challenges in the field.

The analysis began by downloading and exporting the WoSCC records in RefWorks format, including cited references. The data were then converted into text format to create a comprehensive dataset. After excluding duplicates, the remaining literature was visualized using CiteSpace 6.4.R1. A cluster analysis based on keyword co-occurrence was performed to reveal the principal topics in the domain. Clusters were considered significant if the modularity value (Q) exceeded 0.3 and the silhouette value (S) was greater than 0.7 [58].

4. Results

4.1. Publication and Citation Trends by Year

A preliminary analysis using CiteSpace 6.4.R1 revealed that publications in this domain have been released annually since 2017, with no prior records before this time.

The dataset spans from 2017 to 2024 and comprises a total of 227 articles and 21 reviews, with a combined citation count of 3948, yielding an average of 15.9 citations per item. Figure 2 illustrates the trends in annual publication volume in the domain.

Over the analyzed period, there has been a noticeable increase in both the number of publications and the corresponding citations, indicating growing research interest and impact in this rapidly evolving field. In the early years, publication output was relatively modest; only three articles were published in 2017 and a single article in 2018, which garnered minimal citations. However, the volume began to rise significantly from 2019 onward, with 18 publications in 2019 and a substantial increase to 32 in 2020. The trend continued upward with 39 articles in 2021 and peaked in 2022 at 57 publications. Although there was a slight decline to 43 articles in 2023, the citations increased dramatically to 959, demonstrating the high impact of these contributions. In 2024, the field maintained a high publication rate with 55 articles and the highest citation count of 1178.

4.2. Analysis of the Country Cooperation Network

Table 1. Leading countries contributing to the research domain.

#	Countries	Year	Count	Centrality
1	China	2017	92	0.23
2	USA	2019	33	0.30
3	India	2019	32	0.32
4	Saudi Arabia	2020	19	0.16
5	Italy	2019	18	0.19
6	Australia	2019	14	0.11
7	Pakistan	2020	12	0.18
8	Taiwan	2021	12	0.06
9	Canada	2019	11	0.17
10	France	2017	9	0.20

presents the leading countries contributing to publications in the domain, revealing notable trends over time. The ranking is based on the publication count and betweenness centrality score, offering insights into both research productivity and influence within the field. The “Year” column represents the year of the country’s first publication within the analyzed dataset, indicating that country’s entry point into this research area.

The People’s Republic of China leads with 92 publications, with activity commencing in 2017 and a centrality of 0.23. In contrast, the USA and India, both of which started their research efforts in 2019, have 33 and 32 publications respectively, and exhibit higher centrality values (0.30 and 0.32), indicating that they are influential hubs within the scholarly network. Other significant contributors include Saudi Arabia with 19 publications, Italy with 18 publications, and Australia with 14 publications. Additional countries such as Pakistan, Taiwan, Canada, and France further enhance the international diversity of the field.

Figure 3 depicts the collaboration network between countries.

The network in Table 1 comprises 69 nodes and 256 edges, with a density of 0.1091. In particular, the largest connected component includes 94% of the nodes, indicating strong interconnectivity. A modularity Q of 0.3971 suggests a moderate division into clusters, while a weighted mean silhouette score of 0.8498 confirms that these clusters are well-defined and internally consistent. The harmonic mean of Q and S (0.5413) further supports the robustness of the network structure. In conclusion, these metrics demonstrate a well-structured and cohesive scholarly network, underscoring the reliability of the bibliometric analysis.

4.3. Analysis of the Institutional Cooperation Network

Table 2. Leading institutions contributing to the research domain.

#	Institution	Country	Count	Year
1	Anhui University	China	7	2023
2	Anhui University of Science and Technology	China	6	2023
3	Chinese Academy of Sciences	China	6	2021
4	Wuhan University	China	6	2023
5	Beihang University	China	3	2017
6	Charles Darwin University	Australia	3	2021
7	Southwestern University of Finance and Economics	China	3	2022
8	King Saud University	Saudi Arabia	3	2024
9	Beijing Jiaotong University	China	3	2022
10	Zhejiang University	China	3	2023
11	China University of Mining and Technology	China	3	2022
12	Nanjing University of Science and Technology	China	3	2019
13	Egyptian Knowledge Bank	Egypt	3	2022
14	Beijing Institute of Technology	China	3	2021
15	COMSATS University Islamabad	Pakistan	3	2022

presents the top fifteen institutions that contributed to publications in the research domain.

The data reveal a strong dominance of Chinese institutions. For example, Anhui University leads with seven publications after beginning its research activities in 2023, while Anhui University of Science and Technology, Chinese Academy of Sciences, and Wuhan University follow with six publications. Other major contributors include Chinese institutions such as Beihang University, Beijing Jiaotong University, Zhejiang University, China University of Mining and Technology, and Nanjing University of Science and Technology, which further emphasizes China’s strong involvement in this area.

Outside China, institutions such as Charles Darwin University (Australia), King Saud University (Saudi Arabia), Egyptian Knowledge Bank (Egypt), and COMSATS University Islamabad (Pakistan) also contributed to the field, although with lower publication counts.

The examined network of institutions consists of 166 nodes and 142 links, yielding a low density of 0.0104 (Figure 4).

This suggests that while many institutions are active, the interconnections among them are relatively sparse, indicating an opportunity for improved global collaboration. Strengthening international partnerships could help to integrate diverse perspectives and accelerate the development of effective blockchain solutions for emergency management systems.

4.4. Analysis of the Author Collaboration Network

The bibliometric analysis of the collaboration network between authors provides insights into the key contributors and the overall structure of scholarly interactions within the research domain.

Table 3. Leading authors contributing to the research domain.

#	Author	Institution	Country	Count
1	Cui Jie	Anhui University	China	6
2	Gu Chengjie	Anhui University of Science and Technology	China	6
3	Zhang Qingyang	Anhui University	China	6
4	Zhong Hong	Anhui University	China	6
5	He Debiao	Wuhan University	China	5
6	Zhang Yun	Xi’an University of Posts and Telecommunications	China	5
7	Jayaraman Raja	Khalifa University	UAE	4
8	Li Jian	Xidian University	China	4
9	Li Yu	Chinese Academy of Sciences	China	4
10	Liu Y	Tsinghua University	China	4

presents the leading authors who contributed significantly to the field together with their institutional affiliations, country of origin, and publication count.

The data reveal that research in this domain is predominantly driven by Chinese institutions, with eight out of the ten most prolific authors affiliated with universities in China.

CiteSpace network analysis provides a deeper understanding of the collaborative relationships between authors. The network consists of 183 nodes (authors) and 157 edges (collaborative links), resulting in a low network density of 0.0094. This indicates that while a significant number of researchers are engaged in the field, direct collaborations between them are relatively sparse, which may hinder knowledge dissemination and interdisciplinary innovation.

The largest connected component in the network includes only nine authors (4% of the total network), suggesting that the majority of researchers are either working independently or forming small loosely connected groups. This lack of a strongly connected core implies that collaboration is not yet fully optimized, potentially slowing the progression of research in the domain. Furthermore, only 1.0% of nodes are labeled, which indicates that most collaborative structures within the network are not well-defined or recognized.

The co-citation analysis of the top ten most frequently cited authors highlights the dominance of foundational blockchain researchers such as Satoshi Nakamoto and Gavin Wood, whose work remains highly influential (

Table 4. Top ten most frequently co-cited authors.

#	Author	Institution	Count	Centr.	Year
1	Satoshi Nakamoto	-	40	0.09	2017
2	Gavin Wood	Ethereum Foundation, UK	18	0.01	2020
3	Asaph Azaria	MIT, USA	17	0.15	2019
4	Yang Liu	University of Montpellier, France	15	0.02	2022
5	Hanyi Wang	Kunming University, China	13	0.01	2020
6	Dinh C. Nguyen	University of Alabama in Huntsville, USA	12	0.05	2021
7	Lu Yang	University of Kentucky, USA	11	0.02	2023
8	Zibin Zheng	Sun Yat-Sen University, China	10	0.03	2020
9	Xiao Yue	Huaqiao University, China	10	0.01	2020
10	Sara Saberi	Foisie School of Business, USA	9	0.04	2020

).

Researchers such as Asaph Azaria and Sara Saberi highlight an increasing focus on the use of blockchain technology across various fields, including healthcare and supply chain management.

The analysis also reveals a growing global research network, with significant contributions from China, the USA, the UK, and France. While some authors exhibit high citation counts, their low centrality values suggest limited cross-disciplinary integration.

4.5. Keyword Co-Occurrence Analysis

Analyzing the keyword co-occurrence network provides key insights into the conceptual framework and thematic progression of research within this field. This network was visualized using CiteSpace, with keywords displayed as nodes and their co-occurrence frequency in academic publications as edges (Figure 5).

The importance of a keyword is shown by node size, while the strength of keyword relationships is shown by edge thickness. This visualization can effectively detail the research domain’s semantic structure.

As shown in the network analysis (

Table 5. Top keywords in the research domain.

#	Keyword	Count	Centrality	Year
1	management	32	0.29	2017
2	internet	25	0.19	2019
3	blockchain	25	0.11	2019
4	technology	18	0.18	2020
5	artificial intelligence	18	0.12	2019
6	internet of things	17	0.11	2019
7	system	16	0.13	2020
8	challenges	15	0.08	2020
9	scheme	15	0.07	2022
10	blockchain technology	14	0.07	2020

), “management” emerges as the keyword that occurs most frequently, appearing 32 times with the highest centrality score of 0.29, indicating its pivotal role in the research landscape.

The second-most prominent keywords are “internet” and “blockchain”, each with 25 occurrences, underscoring their interconnectedness as well as their foundational role in technological advancements. Other significant keywords include “technology” (18 occurrences), “artificial intelligence” (18 occurrences), and “internet of things” (17 occurrences). These keywords reflect a strong orientation toward emerging technological trends and interdisciplinary research.

The burst detection analysis provides valuable insights into the shifting focus and emerging trends within the research domain over time. Figure 6 presents the top ten keywords with the strongest citation bursts from 2017 to 2024, highlighting distinct phases of heightened academic interest in this domain.

These bursts indicate periods of rapid development and innovation, offering a detailed perspective on how the field has responded to evolving technological advancements and real-world challenges.

From a temporal perspective, the bursts can be grouped into three primary phases:

• 2019–2020: This period was characterized by a surge in interest in “augmented reality” and “big data”, reflecting the early integration of blockchain with immersive technologies and large-scale data processing.
• 2020–2021: The focus shifted towards core technological aspects, as seen in the bursts of “technology” and “things”, emphasizing the role of blockchain in the IoT.
• 2021–2024: Research priorities transitioned towards security and operational applications, with bursts in “smart contracts”, “secure”, and “networks”, underscoring the importance of trust and reliability in decentralized ecosystems. The extended burst of “scheme” and “COVID-19” until 2024 further demonstrates the long-term relevance of these themes.

These findings illustrate how research priorities have evolved in response to technological advancements and global challenges, emphasizing the adaptability of blockchain-based solutions in diverse applications.

4.6. Research Hotspots and Evolution Trend Analysis

This subsection employs co-citation analysis to explore the evolution of research and identify emerging trends within blockchain use cases for emergency management.

4.6.1. Mapping Research Clusters in the Co-Citation Network

CiteSpace software was employed to perform a clustering analysis of co-cited references, generating a co-citation network map that revealed seven major clusters. The resulting co-citation network, depicted in Figure 7, comprises 317 nodes and 1045 connections organized into the following clusters: personal health records (#0), humanitarian supply chain management (#1), patient journey (#2), collaborative emergency management (#3), emergency logistics (#6), smart cities (#7), and central gateway (#8).

These clusters are labeled based on their log-likelihood ratios (LLR) for optimal representation [59].

Each cluster visualizes individual publications as dots, with the most prominent publications labeled directly within the diagram.

The robustness of this analysis is supported by strong network quality metrics. A high mean silhouette value (S) of 0.8459, significantly above the 0.7 threshold, indicates that the identified clusters are highly homogeneous; similarly, the modularity value (Q) of 0.7857 is well in excess of the 0.3 threshold, confirming the distinctiveness of the different research streams and validating the intellectual structure of the field.

Table 6. Summary of the largest clusters.

#	Size	Silhouette	Label (LLR)	Year
0	48	0.843	personal health record	2017
1	40	0.956	humanitarian supply chain management	2019
2	32	0.904	patient journey	2020
3	31	0.898	collaborative emergency management	2020
6	21	0.974	emergency logistics	2021
7	17	0.969	smart cities	2016
8	12	0.979	central gateway	2019

presents the clusters organized by size. Larger clusters indicate a higher number of cited references, reflecting their greater influence.

Silhouette scores are used to gauge cluster quality, with higher scores indicating greater homogeneity [60]. All of the clusters exhibit high credibility scores, with clusters #1, #6, #7, and #8 achieving the highest silhouette scores.

Reflecting their recency, cluster #6 contains the most recent publications, with an average publication date of 2021; conversely, cluster #0 represents the least recent publications, with an average publication date of 2019.

4.6.2. Temporal Evolution of Research Themes in the Co-Citation Network

This section presents a timeline analysis that captures the dynamic evolution of research clusters. By visualizing frequently cited references across publication years, the timeline map (Figure 8) reveals how specific research themes have emerged, evolved, and gained prominence over time.

In this figure, frequently cited references are plotted by publication year on the horizontal axis, co-citation relationships are represented by connecting lines, and citation frequency is indicated by point size. This timeline map effectively demonstrates how burst patterns appear within the overall intellectual framework of the field.

The analysis illustrates the evolution of the research landscape from early studies focused on personal health records (#0) and smart cities (#7) to a notable surge in recent years within the clusters of patient journey (#2), emergency logistics (#6), and collaborative emergency management (#3), reflecting the growing need for resilient and efficient solutions in crisis response and healthcare systems.

4.6.3. Citation Burst Analysis

The analysis of reference citation bursts offers valuable insights into the most influential studies shaping blockchain research for emergency management. Figure 9 highlights the top references that experienced significant citation bursts between 2017 and 2024, reflecting shifts in research priorities and the evolving intellectual framework of the field.

The temporal distribution of the reference bursts reveals distinct patterns: 40% of the high-impact references were published in 2016, 20% in 2018, 20% in 2019, and 10% in each of 2017 and 2020. This distribution suggests that foundational works published in 2016 have had a delayed but substantial impact on the field, with their citation bursts occurring primarily between 2019 and 2021. The visualization clearly demonstrates two distinct waves of citation bursts, with the first occurring from 2019–2021 for earlier publications and a second wave spanning 2022–2024 for more recent works.

The article with the strongest citation burst (strength = 3.57) was authored by Azaria A et al. [61], followed by Yue X et al. [62] with a burst strength of 2.55 and Mettler M et al. [63] with a strength of 2.18. These findings indicate that the integration of big data approaches with blockchain technology has emerged as a dominant theme in the development of emergency management systems.

In particular, works that focus on medical systems and blockchain-based healthcare solutions feature prominently among high-impact references, including publications in the Journal of Medical Systems (Yue X et al. [62]; Griggs KN et al. [64]), the International Journal of Medical Informatics (Abu-Elezz I et al. [65]), and the Journal of Medical Internet Research (Hylock RH et al. [66]). This highlights a significant emphasis on healthcare emergency management within the broader landscape of blockchain use cases.

The extended burst periods (2022–2024) associated with the most recent works by Abu-Elezz I et al. [65] and Hylock RH et al. [66] indicate sustained interest in medical data management using blockchains, particularly in areas related to data privacy, interoperability, and emergency response coordination during health crises. Despite being published earlier, these works have maintained their relevance, underscoring their seminal contributions to the evolving discourse.

4.6.4. In-Depth Analysis of Major Clusters

As shown in Figure 7, the intellectual framework of this study is built upon seven major clusters, each representing a distinct thematic area. The intellectual core of the identified clusters was established through an analysis of the most frequently cited works and the major citing articles within each cluster. These core publications define the methodological foundations of each thematic area, while the major citing articles reflect the evolution and diversification of research approaches within the field. In this study, we provide a more detailed analysis of each cluster.

The largest cluster (#0) has 48 members with a silhouette value of 0.843. The intellectual core of this cluster is built upon several seminal studies focusing on the management of personal health records through blockchain [61,62,64,71,72]. Notably, Azaria et al. [61] established a robust framework with their MedRec model, laying the groundwork for secure medical data access and permission management. Complementary contributions by Yue X et al. [62] and Griggs KN et al. [64] further advanced the integration of blockchain technologies into healthcare systems. Major citing articles such as those by Saeed H et al. [73] and Tandon A et al. [74] have diversified these approaches by systematically reviewing and extending the application of blockchain technologies to enhance healthcare resilience and emergency management.

Cluster (#1), the second-largest cluster, consists of 40 members and has a high silhouette value of 0.956. This cluster examines the application of blockchain technology in the context of humanitarian supply chain management, emphasizing the potential of blockchain to overcome barriers and optimize logistics during emergencies and humanitarian crises.

The key studies in this cluster explore a variety of approaches to utilizing blockchains to improve the efficiency, transparency, and security of supply chains. Ozdemir et al. discussed the role of blockchains in mitigating the challenges faced by humanitarian supply chains, highlighting the ability to enhance transparency and traceability in disaster relief operations [75]. Erol et al. investigated the feasibility of implementing blockchains in various industries, including humanitarian logistics, offering insights into the challenges and opportunities of blockchain adoption in these contexts [76]. In [77,78], the authors addressed the impact of blockchain technology on risk management in supply chains, particularly in the digital transformation era. Lhermitte et al. proposed a blockchain-enabled framework for sharing logistics resources during emergency operations while facilitating faster and more efficient response times [79].

The most cited works within this group include Saberi’s study [80] on the role of blockchains in improving supply chain performance, Dubey’s research [81] focusing on sustainable supply chain management, Kshetri et al.’s work [82] on the barriers and benefits of blockchain technology in supply chains, and Queiroz’s study [83] on the role of blockchains in supply chain transparency. These contributions collectively underscore the growing recognition of the potential of blockchain technology to transform humanitarian logistics by improving the effectiveness of supply chain management, ensuring greater resource efficiency, and facilitating faster and more transparent responses during crises.

Cluster (#2), the third-largest cluster, comprises 32 members with a silhouette value of 0.904, reflecting strong cohesion and relevance within its field. This cluster is primarily focused on the integration of blockchain technology to enhance patient-centered healthcare, with a specific emphasis on improving the patient journey. This cluster particularly emerges in the context of emergency medicine and healthcare management during the COVID-19 pandemic.

The key publications within this cluster explore diverse applications of blockchain, ranging from the transformation of emergency medicine to the development of patient-centric healthcare frameworks. Notably, Wu et al. [84] provided a comprehensive scoping review of blockchain’s impact on the patient journey through emergency departments, while Khatri et al. [85] introduced a patient-centric architectural framework leveraging Hyperledger Fabric to optimize healthcare management during the pandemic. Other significant studies [86,87,88] investigated blockchain’s role in environmental management in hospitals and its potential in supporting COVID-19 contact tracing and vaccine distribution, respectively. This cluster also addresses broader implications of blockchain in healthcare, including challenges related to privacy, data security, and system interoperability [89,90].

The most cited works in this cluster include Nakamoto’s foundational technical report [20], which continues to serve as a cornerstone for much of the research in blockchain technology. Other highly influential studies include McGhin et al.’s work [89] exploring the use of blockchains to enhance network security and safeguard data privacy and Kalla et al.’s study [91] on blockchain’s integration with engineering management in healthcare. Collectively, these works underscore the growing recognition of blockchain’s potential to revolutionize healthcare systems by enhancing data management, improving security, and optimizing patient outcomes.

Cluster (#3) consists of 31 members and has a silhouette value of 0.898. This cluster primarily explores the role of blockchain technology in enhancing collaborative emergency management, particularly through multi-agent participation and the integration of emerging technologies such as unmanned aerial vehicles and 6G networks.

The major studies in this cluster investigate how blockchain can improve the coordination and performance of disaster response systems. Wang et al. discussed the potential of blockchains to optimize collaborative emergency management, particularly through multi-agent systems that enhance cooperation between various stakeholders [1]. The studies by Xie et al., Pauu et al., and Shah et al. [92,93,94] examined the integration of blockchain with 6G and UAV technologies to ensure secure and decentralized management of tasks and data during disaster response efforts. The works by Bine et al. and Zhao et al. [95,96] focused on how blockchains can be applied in conjunction with the Internet of Drones and vehicular ad hoc networks to enhance trust and efficiency in disaster scenarios.

The most cited works in this cluster include Marbouh et al.’s study [97] proposing a blockchain system using Ethereum to track COVID-19 data from reliable sources, ensuring data integrity and transparency for stakeholders; Chamola et al.’s research [98] on blockchain’s role in securing UAV communication networks; and Rajput et al.’s work [99] on blockchain for vehicular networks. These contributions highlight the growing recognition of blockchain’s potential to revolutionize emergency management by facilitating secure decentralized communication, enhanced coordination among agents, and more effective disaster response operations.

The fifth-largest cluster (#6) includes 21 members and has a high silhouette value of 0.974, indicating strong thematic consistency. This cluster focuses on the integration of blockchain technology into emergency logistics, particularly in improving the efficiency, traceability, and coordination of supply chain activities during disaster scenarios.

The most cited article in this cluster presents a two-stage evolutionary game model on the use of complex networks to analyze decision-making processes in emergency logistics systems facilitated by a blockchain platform [100]. Zekhnini et al. examined the role of Industry 4.0 enablers in enhancing humanitarian supply chains, emphasizing blockchain as a foundational technology for improving coordination, transparency, and efficiency in emergency logistics [101]. Zeng et al. proposed a blockchain-based traceability system designed for cold-chain medicine logistics, focusing on real-time monitoring and ensuring data reliability through advanced multi-sensor data fusion to improve the efficiency and accuracy of emergency medicine management [102]. Additionally, Xiong et al. applied evolutionary game theory to analyze the dynamics of collaborative transportation for emergency materials, exploring how blockchain infrastructure can address information asymmetry and improve the stability of logistics enterprises’ strategies in emergency management [103]. Sassaoui et al. offered a comprehensive bibliometric analysis of the use of blockchain in emergency logistics, highlighted key research trends and influential contributors, and advocated for future studies on integrating blockchain with emerging technologies and dynamic modeling in disaster response [49].

Highly cited foundational contributions include [1,37,104], which collectively explore the strategic role of blockchain in disaster logistics, cost-effective distribution, and resilience-building in emergency supply chains. Other research has extended this analysis to production resilience and socio-technical systems, reinforcing the relevance of blockchain as a transformative tool in logistics under uncertainty [105,106].

Collectively, this cluster highlights the growing importance of blockchain-based innovations for overcoming logistical bottlenecks in disaster response and ensuring the integrity and transparency of emergency supply chains.

Cluster (#7) includes 17 members and has a high silhouette value of 0.969. This cluster explores the role of blockchain technology in enhancing the resilience, transparency, and efficiency of smart city systems. This cluster demonstrates how blockchain can be a transformative enabler for secure data sharing, citizen participation, and operational efficiency in smart urban environments.

The leading cited article outlines a comprehensive vision for integrating smart technologies such as IoT, big data, and blockchain into civil engineering practices, highlighting new professional roles to support the development and management of smart infrastructure in cities [107]. Other notable studies assesd blockchain’s feasibility in industrial settings [76] and its application in participatory IoT to improve safety and situational awareness [108]. Tang et al. explored a blockchain-based system using Hyperledger Fabric to enhance the traceability and management of blood donations in smart city healthcare, addressing challenges in supply, demand, and quality control [109].

The most cited foundational works in this cluster include Crosby et al. on the fundamentals of blockchain [67], Lin and Liao on blockchain security [68], and Zheng et al. on integration with big data [21]. These works establish the technological basis for deploying blockchains in diverse urban systems.

The smallest cluster (#8) includes only 12 members and exhibits a high silhouette value of 0.979, indicating strong internal consistency. This cluster investigates the use of blockchain technology to eliminate central points of failure in IoT networks, promoting decentralized, secure, and autonomous system designs.

The leading cited article by Liu et al. introduces NetDAO, a blockchain-based architecture that addresses the lack of trust between IoT gateways and sensors by eliminating the need for centralized gateways. NetDAO utilizes a security rating algorithm to assign reputation values to entities and mitigate malicious flooding and data manipulation, ensuring secure packet forwarding through a proof-of-reputation mechanism [110]. Other significant contributions include Alam et al., who explored blockchain’s role in integrating fog computing and the Internet of Medical Things for reliable healthcare delivery [111], and Corradini et al., who proposed a two-tier blockchain framework to enhance the autonomy and security of smart objects in IoT environments [112].

The most frequently cited foundational works in this cluster highlight critical challenges and propose innovative solutions for secure and scalable IoT systems. Dwivedi et al. [113] addressed the management of medical big data in IoT-based wearable technologies for remote patient monitoring and proposed a blockchain-based framework to ensure data security and patient privacy. Nguyen et al. [114] introduced a secure data-sharing system for electronic health records. Their approach combines mobile cloud platforms with blockchain-based access control to protect sensitive health information. Singh et al. [115] explored the convergence of blockchain and artificial intelligence in IoT architectures, laying a foundation for addressing key issues such as centralized control, data privacy, and system scalability.

5. Discussion

5.1. Theoretical Insights and Practical Applications

The findings of the bibliometric analysis provide a comprehensive understanding of the evolving landscape of blockchain technology in emergency and crisis management, integrating both theoretical constructs and real-world applications. Through the identification and analysis of seven major research clusters, this study constructs a macro-level knowledge framework that illuminates the logical structure of the field and emphasizes key themes such as transparency, efficiency, trust, and interdisciplinary collaboration. The clusters span diverse yet interrelated domains such as humanitarian logistics, patient-centered healthcare, smart cities, emergency logistics, collaborative multi-agent systems, IoT networks, and next-generation communication infrastructures, thereby demonstrating blockchain’s potential to support decentralized trust mechanisms, enhance data security, and improve operational coordination during crises. Theoretically, this study contributes to a better understanding of how blockchain redefines digital trust and coordination paradigms across complex systems. Practically, it offers insights into how blockchain-enabled solutions are being piloted or proposed in domains requiring resilient infrastructure and secure information flow. Moreover, this study highlights the persistence of critical challenges such as limited global collaboration, insufficient standardization, and a gap between theoretical frameworks and real-world implementations.

Across all clusters, blockchain technology emerges as a foundational element of digital infrastructure that supports the three core pillars of modern emergency and crisis response systems: decentralization, transparency, and security. Moreover, the high silhouette values across clusters, ranging from 0.898 to 0.979, indicate strong thematic cohesion and maturity within each research stream.

Below, we summarize the implications as integrated and organized by thematic domain.

5.1.1. Healthcare and Emergency Medicine

Clusters #0 and #2 demonstrate the growing role of blockchains in health system transformation. Theoretically, this body of research explores patient-centric models, architectural frameworks for data sharing, and system interoperability, particularly in the COVID-19 pandemic context [61,63,64,66,71,72,84,85,86,87,88,89,91].

From a practical standpoint, blockchain technologies have demonstrated significant value in the healthcare sector by supporting vaccine distribution, contact tracing, and real-time sharing of medical records across institutions. Blockchains can enable secure medical data exchange, patient-controlled access management, and remote monitoring solutions, with prototype electronic health record systems already being tested in pilot projects [61,62,63,64,66,71,72]. Frameworks based on Hyperledger Fabric and Ethereum provide decentralized infrastructures for secure, scalable, and privacy-respecting health data management [85,89]. These innovations are particularly valuable in emergency medicine, where rapid and secure access to data can be life-saving.

5.1.2. Supply Chain and Emergency Logistics Management

Clusters #1 and #6 collectively underscore blockchain’s transformative role in humanitarian supply chains and emergency logistics. Theoretically, these studies contribute to the development of decentralized models that improve visibility, traceability, and resilience in logistics networks [75,76,77,78,79,80,81,82,83,100,101,102,103,104,105,106]. Game theory, systems modeling, and evolutionary dynamics are some of the different approaches employed to conceptualize decision-making and coordination in complex emergencies [100,101,102,103].

Practically, blockchains can enhance logistical efficiency by enabling real-time tracking of resources, secure sharing of logistics data, and streamlined collaboration between stakeholders. Use cases include cold-chain medicine tracking, resource allocation during disasters, and coordination among humanitarian actors [79,101,102]. These improvements address long-standing challenges such as fraud, lack of transparency, and information asymmetry.

5.1.3. Collaborative Emergency Management and Communication Systems

Cluster #3 explores blockchain integration with emerging technologies such as 6G, UAVs, and vehicular ad hoc networks. Theoretical contributions include multi-agent systems, decentralized governance models, and secure consensus mechanisms for disaster communication [1,92,93,94,95,96,98]. These frameworks demonstrate how blockchain can enhance coordination, accountability, and decision-making in complex emergency scenarios.

In practice, blockchain ensures secure task assignment and data exchange between heterogeneous agents (e.g., drones, vehicles, and command centers) during crises [94,95,98].

5.1.4. Smart Cities and Urban Emergency Resilience

Cluster #7 illustrates the integration of blockchains with smart city infrastructure to support data sharing, civic engagement, and emergency services. Theoretical models emphasize the role of blockchains in enabling secure, tamper-proof, and transparent urban data ecosystems [94,107,108]. Foundational works explore how blockchain technology can support system interoperability, automation, and smart governance in civil infrastructure and public health.

On the practical side, applications include blockchain-based systems for enhancing safety through participatory IoT [47,108] and managing smart infrastructure with improved data security and responsiveness [107]. The immutability and auditability of blockchains can improve trust between citizens, service providers, and government bodies during urban emergencies.

5.1.5. IoT Systems and Infrastructure Decentralization

Cluster #8 highlights the convergence of blockchain and IoT technologies, focusing on eliminating central points of failure and enabling secure autonomous devices. Theoretical models have explored concepts such as proof-of-reputation, distributed trust, and smart contract-based control in large-scale IoT networks [110,111,112,113,114,115].

Practically, blockchains can facilitate secure data exchange in healthcare IoT, wearable devices, and fog computing environments [111,113]. Solutions such as NetDAO [110] demonstrate how decentralized architectures can address trust issues between devices and gateways, ensure data provenance, and reduce susceptibility to cyberattacks. These features are vital in emergency response systems where reliability and security of sensor networks are critical.

5.2. Limitations

Although this study provides a comprehensive bibliometric analysis of blockchain technology applications in emergency management systems, it is important to acknowledge certain limitations.

First, the scope of data resources was restricted to the WoSCC. Although the WoSCC is a widely respected and comprehensive database, limiting the data source to a single platform may have excluded relevant publications indexed in other databases such as Scopus, IEEE Xplore, or Google Scholar.

Second, limiting the type of article meant that this paper focuses solely on peer-reviewed research articles and reviews within the Science Citation Index and Social Sciences Citation Index. This criterion excluded other potentially valuable sources such as conference proceedings, books, and gray literature, which could provide additional insights into emerging trends and practical implementations.

Third, the effect of language introduces a bias towards English-language publications. By excluding studies published in other languages such as Chinese, Spanish, or French, the analysis may have overlooked significant regional contributions and diverse perspectives on blockchain-based solutions in emergency management.

Finally, there are limitations involving the research software. Although this study used CiteSpace 6.4.R1, which is a well-established and specialized tool for bibliometric analysis, the obtained results can vary depending on the chosen parameters, algorithms, and visualization techniques. Alternative software or analytical approaches may yield different but equally valid interpretations.

5.3. Future Directions

Building upon the bibliometric analysis presented in this study, several promising avenues for future research can be identified. These directions aim to address gaps, enhance theoretical understanding, and accelerate practical implementation:

• Interdisciplinary integration and technological convergence: Future research should focus on the synergies between blockchain and other cutting-edge technologies such as artificial intelligence, IoT, and next-generation communication networks (5G/6G). Exploring how these technologies can collectively enhance data analytics, predictive modeling, real-time monitoring, and automated response mechanisms in emergency scenarios is crucial.
• Scalability and interoperability solutions: Addressing scalability challenges and ensuring interoperability between different blockchain platforms and legacy systems are essential for widespread adoption. Future studies should investigate the feasibility of layer-2 scaling solutions, cross-chain protocols, and standardized data formats to enable seamless data exchange and collaboration across diverse emergency management stakeholders. Additionally, exploring how interoperability between different platform types (public, private, and consortium blockchains) can optimize coordination and resource allocation during crises will be a critical area of research.
• Regulatory and governance frameworks: Further research is needed to examine the regulatory landscape surrounding blockchain adoption in emergency management, including issues of data privacy, security, liability, and compliance. Developing clear guidelines and governance frameworks will be critical for fostering trust and encouraging public-private partnerships.
• Real-world pilot implementations: Despite the theoretical potential of blockchain technology, there is a lack of real-world pilot implementations and comprehensive case studies in emergency management settings. Future research should prioritize the design, deployment, and evaluation of blockchain-based solutions in diverse emergency contexts such as natural disasters, public health crises, and humanitarian relief operations.
• Social and ethical considerations: As blockchain technology becomes more integrated into emergency management systems, it is important to address the social and ethical implications, including issues of digital inclusion, data bias, algorithmic transparency, and the potential for unintended consequences. Future research should explore these dimensions to ensure that blockchain solutions are equitable, responsible, and aligned with societal values.
• Global collaboration and knowledge sharing: The bibliometric analysis revealed limited global collaboration in blockchain research for emergency management. Future initiatives should promote international collaboration, knowledge sharing, and capacity building, particularly in developing countries, in order to foster a more inclusive and coordinated approach to leveraging blockchain technology for humanitarian purposes.

5.4. Comparison with Existing Literature

As discussed in Section 2, previous literature reviews have predominantly offered qualitative syntheses or summarized challenges, opportunities, and use cases across diverse sectors such as healthcare [39,40,41,42], humanitarian logistics [37,43,44,45], and crisis communication [45,46]. While these contributions offer valuable conceptual overviews and practical insights, they are inherently limited by their subjective nature and lack of quantitative rigor. As such, previous reviews often fail to capture the broader research dynamics and long-term trends shaping the field.

In contrast, bibliometric reviews such as the present study address the above-mentioned limitations by employing quantitative methods to systematically analyze publication patterns, collaboration networks, citation dynamics, and emerging research themes. These techniques allow for a more comprehensive and objective understanding of the field’s intellectual landscape.

Compared to the bibliometric reviews discussed in Section 2, many prior studies demonstrate limitations in practical focus. For instance, the works in [51,52,54] do not concentrate specifically on blockchain, instead addressing emergency response more broadly. Other studies examine narrow applications such as emergency logistics [49] or health emergencies [50]. In contrast, our study is uniquely centered on blockchain technologies within the domain of emergency management systems, filling a notable gap in the literature.

Furthermore, few reviews have conducted in-depth analysis of major research clusters, keyword bursts, or co-citation networks, all of which are critical methods for uncovering intellectual structures and evolving trends. For example, Zhongqi et al. [34] and Sassaoui [49] omitted cluster analysis and burst detection entirely; similarly, Minas et al. [53] did not employ a full range of quantitative techniques such as publication and citation trend analysis, institutional collaboration mapping, or co-citation analysis, limiting the objectivity and depth of their findings.

In contrast, our study introduces several methodological enhancements that distinguish it from earlier works. It spans the years 2017 to 2024, offering one of the most up-to-date perspectives available in the literature. This extended time frame is particularly relevant given the rapid pace of technological innovation and evolving regulatory contexts surrounding blockchain applications in emergency management.

In terms of data sourcing, our review adheres to scientometric best practices by drawing from the WoSCC, a widely accepted and authoritative database. While some earlier reviews, such as that by Sassaoui et al. [49], also incorporate Scopus, WoSCC remains the dominant source across most comparable studies.

Moreover, our analytical approach represents a significant advancement. Unlike previous reviews [49,51,52,54] that predominantly relied on VOSviewer, a tool that is limited in its temporal and structural analytical capabilities, our study employs CiteSpace, enabling a deeper exploration of thematic evolution through techniques such as co-citation and citation burst detection, keyword burst analysis, and institutional collaboration mapping. These methods permit us to offer a more comprehensive understanding of the intellectual landscape and to provide insights that are often absent from earlier bibliometric analyses.

In terms of depth of analysis, only Oh et al. [51] and our study provide comprehensive examinations of major research clusters, which allow for nuanced insights into thematic evolution. This dimension is vital for understanding structural shifts in the field over time, but is underexplored in most prior works.

Although several studies [34,49,51,53] claim practical relevance, few have addressed theoretical implications or proposed a conceptual foundation. Our work contributes meaningfully in this regard by identifying theoretical gaps and mapping knowledge clusters, an approach previously seen only in Oh et al. [51]. Lastly, the articulation of future research directions is limited in earlier reviews, with only Wen et al. [50], Hou et al. [52], and our current study providing detailed pathways for further investigation. This forward-looking component positions our work as an agenda-setting contribution in the field.

5.5. Main Findings

Below are the findings responding to the research questions outlined earlier in the paper.

RQ1: Which countries, institutions, and authors collaborate in the research on blockchain technology applications in emergency management systems, and what are their contributions to advancing this field?

Our analysis of the country cooperation network identified significant international interaction, reflected in the large number of nodes (69) and edges (256). The high proportion of nodes (94%) in the largest connected component indicates strong interconnectedness among research groups from different countries. While China leads in the number of publications (92), the USA (33 publications, centrality 0.30) and India (32 publications, centrality 0.32) demonstrate higher betweenness centrality scores, indicating their key role in connecting different research directions within the international network. Other countries such as Saudi Arabia (19 publications), Italy (18), Australia (14), Pakistan (12), Taiwan (12), Canada (11), and France (9) also make notable contributions, highlighting the global interest in this research area. The moderate modularity score (Q = 0.3971) suggests the presence of certain research clusters that are well-defined and internally consistent, as indicated by the high weighted mean silhouette score (0.8498). Overall, the international collaboration network demonstrates a robust and cohesive structure, facilitating knowledge exchange and the development of the field.

Our analysis of the institutional cooperation network revealed a large number of active institutions (166 nodes) but a relatively low density of connections (0.0104), indicating limited direct collaboration between them. Among the leaders in publication count, Chinese institutions such as Anhui University (7 publications), Anhui University of Science and Technology (6), and the Chinese Academy of Sciences (6) dominate. At the same time, institutions from other countries, including Charles Darwin University (Australia), King Saud University (Saudi Arabia), Egyptian Knowledge Bank (Egypt), and COMSATS University Islamabad (Pakistan) also contribute, albeit with fewer publications. The low density of the institutional cooperation network indicates significant potential for expanding international partnerships to integrate diverse expertise and accelerate the development of effective blockchain solutions for emergency management systems.

Our analysis of the author collaboration network (183 nodes, 157 edges) also reveals low network density (0.0094), indicating limited direct collaboration between researchers. Most authors work independently or in small, loosely connected groups, as evidenced by the small size of the largest connected component (only nine authors). Among the leaders in publication count, authors affiliated with Chinese institutions prevail, reflecting the overall trend of Chinese research dominance in this field. The co-citation analysis identified key authors whose work is foundational to research in blockchain technologies. These include Satoshi Nakamoto (40 co-citations, centrality 0.09) and Gavin Wood (18 co-citations, centrality 0.01), whose work continues to have a significant impact. The increasing number of co-citations of authors such as Asaph Azaria (17 co-citations, centrality 0.15) and Sara Saberi (9 co-citations, centrality 0.04) indicates growing interest in the application of blockchain technologies in various fields, including emergency management. Although some authors have high citation counts, their low centrality values suggest limited interdisciplinary integration within the author network.

RQ2: What are the main research clusters, hotspots, and evolving trends in the application of blockchain technology within emergency management systems?

The co-citation analysis performed using CiteSpace software identified seven major clusters: personal health records (#0), humanitarian supply chain management (#1), patient journey (#2), collaborative emergency management (#3), emergency logistics (#6), smart cities (#7), and central gateway #8). The quality of the clustering is confirmed by high metrics; the average silhouette value S = 0.8459 indicates cluster homogeneity, while the modularity Q = 0.7857 demonstrates clear thematic separation. The largest cluster by the number of publications is cluster #0 (48 items), while cluster #6 is the most recent in terms of average publication year (2021). The clusters with the highest homogeneity are #1, #6, #7, and #8 (S > 0.95).

Our analysis of co-citation dynamics demonstrates that early research focused on the topics of personal health records (cluster #0) and smart cities (cluster #7). In the later period, there is a growing interest in themes such as patient journey (#2), emergency logistics (#6), and collaborative emergency management (#3), reflecting the need for more resilient and integrated solutions in crisis response and healthcare.

The citation burst analysis allows for the identification of the most influential publications in the field. Two main bursts are observed in the periods 2019–2021 and 2022–2024. The strongest bursts were identified for the following works: Azaria A et al. (strength = 3.57) [61]; Yue X et al. (strength = 2.55) [62]; and Mettler M et al. (strength = 2.18) [63]. The main theme of these works is the integration of blockchain technology with big data in medical systems, with a focus on privacy, interoperability, and coordination in emergency situations.

The analysis of keyword citation bursts also revealed periods of intense scientific interest in specific research topics. Overall, three main stages of interest evolution were identified in the period from 2017 to 2024. The most recent stage falls in the period 2021–2024, when there is a significant interest in topics related to operational security and reliability. This is reflected in the growing interest in key concepts such as “smart contracts”, “secure”, and “networks”. In addition, the long-term interest in the terms “scheme” and “COVID-19” indicates the pandemic challenges that forced the scientific community to focus on developing secure decentralized solutions for managing crisis situations, particularly in the context of healthcare and global crisis responses.

RQ3: How has blockchain technology transformed emergency management practices, what challenges remain, and what are the prospective frontiers for future research?

Blockchain technology demonstrates profound transformative potential in emergency management, as evidenced by our analysis of research clusters that highlight several key areas of impact:

• Clusters #0 and #2 underscore blockchain’s ability to create secure and interoperable systems for managing sensitive health data, which is particularly crucial during pandemics and other health crises. This includes secure sharing of medical records, efficient vaccine distribution tracking, and reliable contact tracing, leading to more effective and timely responses.
• Clusters #1 and #6 demonstrate blockchain’s capacity to revolutionize humanitarian supply chains by providing real-time tracking of resources, ensuring transparency in aid distribution, and enhancing coordination among diverse stakeholders. This addresses critical issues such as fraud and information asymmetry, leading to more efficient and accountable disaster relief efforts.
• Cluster #3 highlights blockchain’s potential to enable secure and coordinated communication and task assignment among various actors, including drones, vehicles, and command centers. This fosters more efficient and accountable multi-agency responses during complex emergencies.
• Cluster #7 illustrates how blockchains can enhance the security and transparency of urban data ecosystems, improving the responsiveness and reliability of emergency services within smart cities. This includes applications in participatory IoT for safety and the management of critical infrastructure.
• Cluster #8 showcases blockchain’s role in creating more resilient and secure IoT networks by eliminating central points of failure, particularly vital in healthcare IoT and sensor networks crucial for emergency monitoring and response.

Despite the significant transformative potential, several challenges continue to hinder the widespread adoption of blockchain technology in emergency management:

• Limited global collaboration and standardization: As highlighted in Section 4, the research landscape still exhibits limited global collaboration at the institutional and author levels. This lack of unified effort can impede the development of standardized protocols and interoperable solutions crucial for effective cross-jurisdictional emergency response.
• Gap between theory and real-world implementation: While theoretical frameworks and pilot projects demonstrate promise, there remains a significant gap in large-scale real-world deployments and comprehensive case studies that validate the effectiveness and scalability of blockchain-based solutions in diverse emergency scenarios.
• Scalability and interoperability issues: As identified as a key future research direction, current blockchain technologies often face challenges in terms of scalability and interoperability between different platforms and legacy systems. Addressing these technical limitations is crucial for seamless data exchange and collaboration among various emergency management stakeholders.
• Regulatory and governance uncertainties: The lack of clear regulatory frameworks and governance guidelines surrounding blockchain adoption in emergency management creates uncertainty and can impede investment and widespread implementation. Issues related to data privacy, security, liability, and compliance need to be addressed.
• Social and ethical considerations: Integrating blockchain into emergency management systems raises important social and ethical considerations, including digital inclusion, data bias, algorithmic transparency, and potential unintended consequences, which require careful consideration and mitigation.

Building upon the current state and acknowledging existing challenges, several frontiers for future research emerge as critical to fully realizing blockchain’s transformative potential in this field: interdisciplinary integration and technological convergence; development of scalable and interoperable solutions; establishing clear regulatory and governance frameworks; prioritizing real-world pilot implementations and case studies; addressing social and ethical implications; and fostering global collaboration and knowledge sharing, all of which are discussed in detail in Section 5.2.

6. Conclusions

This bibliometric analysis highlights the transformative potential of blockchain technology in emergency management systems. By examining 248 research articles from 2017 to 2024, seven major research clusters were identified, representing the intellectual core of this rapidly evolving field. These clusters reveal diverse applications of blockchain technology ranging from securing personal health records to optimizing humanitarian supply chains and enabling collaborative frameworks for disaster response.

The analysis underscores the significant contributions of influential works which have laid the foundation for blockchain integration into emergency management systems. Citation burst patterns demonstrate sustained interest in these topics, particularly during global crises such as the COVID-19 pandemic. Furthermore, the findings reveal strong contributions from countries such as China, the USA, and India, but highlight sparse collaboration networks among institutions and authors.

Despite the promising advancements in the use of blockchain technology for emergency management, challenges remain in achieving global collaboration and interdisciplinary innovation. Strengthening partnerships between researchers and institutions across diverse regions can accelerate knowledge dissemination and foster innovative solutions.

The results of this study emphasize the need for future research to focus on the integration of blockchain with other digital technologies such as artificial intelligence and IoT. Moreover, addressing challenges related to scalability, interoperability, regulatory compliance, and ethical considerations will be essential for the successful adoption of blockchain technology in real-world emergency management scenarios.