Blockchain Technology in Tourism Industry: A Bibliometric Analysis

Abstract

The integration of Industry 4.0 (I4.0) technologies has significantly transformed the tourism industry. Additionally, the COVID-19 pandemic has accelerated the adoption of I4.0 technologies in this sector. However, there is limited evidence on how specific I4.0 technologies, such as blockchain, support the tourism industry, particularly in the post-pandemic era. This review seeks to provide insights into emerging research trends that incorporate blockchain technology into the tourism sector. To achieve this, a systematic literature network analysis (SLNA) was conducted, combining a systematic literature review (SLR) with bibliometric analysis. The analysis was based on a corpus of 163 studies published from 2017 to 2024, sourced from the Scopus database, and was carried out using the Biblioshiny tool in R-studio. The findings indicate that blockchain technology has gained popularity in recent years, with most research focusing on developed economies, while there is a notable gap in studies from emerging and developing economies. Tourism practitioners should consider the results of this study from multiple perspectives to enhance their current and future operations and strategies. This study introduces several novel areas, particularly concerning methodology and research context. The innovative SLNA approach was used to review blockchain applications in the tourism industry, though the study was limited to this sector. Future research could explore related topics, such as cryptography, ecosystems, and technology adoption, which are still developing in this and other fields.

Full text

Vol.14, No. 2 (2024) eISSN 2180-1681
https://doi.org/10.53840/jmm.v14i2.158
1
Blockchain Technology in Tourism Industry: A Bibliometric Analysis
Du Yiqun, Rosmah Mohamed* & Yee Choy Leong
Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan
*Corresponding author: m_rosmah@upm.edu.my
ABSTRACT
The integration of Industry 4.0 (I4.0) technologies has significantly
transformed the tourism industry. Additionally, the COVID-19 pandemic
has accelerated the adoption of I4.0 technologies in this sector. However,
there is limited evidence on how specific I4.0 technologies, such as
blockchain, support the tourism industry, particularly in the post-
pandemic era. This review seeks to provide insights into emerging
research trends that incorporate blockchain technology into the tourism
sector. To achieve this, a systematic literature network analysis (SLNA)
was conducted, combining a systematic literature review (SLR) with
bibliometric analysis. The analysis was based on a corpus of 163 studies
published from 2017 to 2024, sourced from the Scopus database, and was
carried out using the Biblioshiny tool in R-studio. The findings indicate
that blockchain technology has gained popularity in recent years, with
most research focusing on developed economies, while there is a notable
gap in studies from emerging and developing economies. Tourism
practitioners should consider the results of this study from multiple
perspectives to enhance their current and future operations and strategies.
This study introduces several novel areas, particularly concerning
methodology and research context. The innovative SLNA approach was
used to review blockchain applications in the tourism industry, though
the study was limited to this sector. Future research could explore related
topics, such as cryptography, ecosystems, and technology adoption,
which are still developing in this and other fields.
Keywords: Blockchain, Industry 4.0, SLNA, Tourism, Bibliometric
Received:
Nov 6, 2023
Accepted:
Nov 8, 2024
Online
Published:
Nov 30, 2024
INTRODUCTION
In the digital age, advanced technologies have revolutionized organizations across multiple
dimensions, including consumer interactions, human resource management, operational
processes, and strategic planning (Ali & Johl, 2023). The contemporary economy,
characterized by shorter product life cycles and increased internationalization, has amplified
the importance of human-related factors for organizational survival and success (Khan et al.,
2023). As a result, organizations are increasingly reliant on stakeholders to provide strategies

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
2
for the adoption of emerging technologies. Moreover, the only viable path to achieving a
sustainable competitive advantage lies in the comprehensive implementation of these new
technologies across all organizational levels (Pilkington, 2016; Yaga et al., 2019; Zheng et al.,
2017). The concept of digitalization, or Industry 4.0 (I4.0), was first introduced in Germany in
2011 and has since garnered significant interest from both researchers and practitioners. In
recent years, I4.0 has evolved into an umbrella term encompassing a range of transformative
technologies, including big data, smart manufacturing, artificial intelligence (AI), and
blockchain technology (Sony et al., 2021). These emerging technologies have the potential to
fundamentally disrupt existing industries, processes, and markets, with blockchain, introduced
in 2008, serving as a notable example (Nakamoto, 2008; Lustenberger et al., 2021).
Since its establishment in 2009, blockchain technology has garnered significant attention,
largely due to Satoshi Nakamoto's introduction of Bitcoin in 2008, a pioneering form of
cryptocurrency (Thurner, 2018; Bogart & Rice, 2015; Thees et al., 2020). The first
implementation of blockchain technology in 2009, with the creation of the initial block
containing transaction records, marked the commencement of the blockchain era. Today,
blockchain has evolved into an indispensable tool for both organizations and consumers
(Narayanan et al., 2016). At its core, blockchain technology is a distributed ledger system that
employs cryptography to securely link blocks of transaction data in a manner that is resistant
to tampering (Kwok & Koh, 2019). Each block contains a record of transactions, forming a
chain that, once added to the ledger, is distributed across the entire network (White, 2017). This
decentralized structure enables businesses and organizations to operate with enhanced
transparency and trust, eliminating the need for a centralized control node (Seffinga et al.,
2017). Additionally, the system generates a unique identifier for each block, ensuring both the
accuracy of data tracking and the security of the system (Kumar et al., 2020). On a broader
scale, blockchain technology functions within a novel distributed infrastructure and computing
paradigm, characterized by its data validation and storage structure, consensus algorithms,
cryptography, and the deployment of self-executing digital contracts (Nakamoto, 2008).
The integration of blockchain technology with smart contracts has the potential to significantly
disrupt traditional financial transaction methods within the travel and tourism industry, and it
is poised to exert a profound influence on this sector in the near future (Bell & Hollander, 2018;
Treiblmaier & Önder, 2019). This technology offers enhanced security and efficiency for both
business-to-business (B2B) and business-to-consumer (B2C) transactions, particularly through
the use of digital payments and cryptocurrencies (Lindman et al., 2017). Several leading airline
companies, including Amadeus, Avinoc, and Eurowings, as well as tourism enterprises, have
already developed blockchain-based platforms to facilitate booking, baggage tracking, tourist
identity management, and bed load optimization. Additionally, advancements in information
and communication technologies (ICTs) are providing financial support to tourism businesses,
thereby enabling these companies to invest in and enhance the overall visitor experience.
Technologies such as blockchain and other emerging digital solutions present significant
opportunities for the tourism industry to innovate and expand its service offerings, while
simultaneously enhancing service quality (Bolici et al., 2019). Blockchain technology,
recognized as one of the major trends with profound implications for the future of the tourism
sector, has the potential to address several of the industry's longstanding challenges, including
inadequate infrastructure management, limited business credit, and opaque pricing
mechanisms. These challenges can be mitigated through blockchain's exceptional attributes,
such as high transparency, resistance to tampering, data provenance, and traceability (Nam et

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
3
al., 2021). The adoption of blockchain technology in the hospitality and tourism sectors is
therefore not only vital for optimizing current services but also essential for ensuring
sustainable future development.
The current application of blockchain technology remains largely experimental, with limited
empirical data supporting its adoption (Ying et al., 2018). This is particularly evident in the
tourism sector, where there is a notable lack of empirical research on blockchain adoption
(Korže, 2019; Önder & Treiblmaier, 2018; Sigala, 2017). Moreover, to date, no bibliometric
studies have specifically investigated the role of blockchain technology within the tourism
industry. The majority of existing research on blockchain implementation tends to be
theoretical or conceptual in nature (Kwok & Koh, 2019; Nam et al., 2021; Pilkington, 2017;
Rejeb & Karim, 2019; Treiblmaier, 2018; Treiblmaier & Önder, 2019; Tyan et al., 2021;
Wahab et al., 2020). While previous studies have predominantly focused on the adoption of
blockchain technology in supply chain management (Jardim et al., 2021; Queiroz & Wamba,
2019; Wong et al., 2020), they have largely overlooked the perspectives of tourists regarding
the adoption and operation of blockchain systems. The increasing implementation of
blockchain technology underscores the necessity of investigating and elucidating its potential
benefits for tourism businesses (Vistro et al., 2021). Given the scarcity of research in this area,
further studies are crucial for deepening our understanding of the relevant concepts and
frameworks (Wahab et al., 2020). Thus, the following research questions were developed:
RQ1. What are the current states and trends of publications on blockchain technology in the
field of tourism?
RQ2. What are the highly cited documents in this study domain?
RQ3. Who are the most productive contributors among these publications?
RQ4. How is the collaboration between countries in this field of study?
RQ5. What is the current state of knowledge structure?
RQ6. What are the themes involved in research on blockchain technology in tourism?
This study is organized as follows: The first section provides an introduction and background
on blockchain technology, along with its application within the tourism sector. The subsequent
section offers a comprehensive literature review that traces the development of blockchain
technology in the tourism industry. Section three details the bibliometric technique employed,
utilizing the Biblioshiny tool, and includes references and a flowchart outlining the process for
conducting bibliometric analysis. Following this, the study presents a detailed analysis
addressing the research questions, which is then followed by a discussion of the findings,
contributions to the field, limitations of the study, and recommendations for future research.
LITERATURE RESEARCH
Blockchain Technology in Tourism Industry
Previous studies have explored and identified the causes and impediments to blockchain
technology adoption, as well as demonstrated cause-effect correlations, which contribute to
avoiding failures in its implementation (Sharma et al., 2021). Pilkington (2017) examined the
application of blockchain technology in Moldova’s medical tourism sector, discussing its
practical implications for supply chain management, customer reviews, and heritage protection
within the context of medical tourism. Mofokeng and Matima (2018) investigated the adoption

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
4
of blockchain technology in virtual environments for digital tourism marketing, revealing that
its application in virtual reality (VR)-based tourism could positively impact the industry. Willie
(2019) recommended that discussions on blockchain technology adoption be extended to the
destination level, noting that blockchain has already been implemented in the hotel industry for
both strategic and practical purposes, with significant benefits including increased operational
efficiency, effectiveness, and overall profitability. However, regarding the broader acceptance
of blockchain technology, Korže (2019) argued that the tourism sector lags behind other
industries.
Furthermore, the findings of Kwok and Koh (2019) offer valuable insights into how small
island economies, such as those in the Caribbean and Aruba, benefit from the implementation
of blockchain technology. They highlighted the potential for increasing stakeholder
engagement through blockchain, along with improved data management practices, particularly
in the context of privacy considerations.
Bolici et al. (2019) investigated ongoing discussions on the major social network platform,
Twitter, revealing a growing interest in blockchain and cryptocurrencies. The content of the
tweets provided preliminary, yet potentially significant, insights into how blockchain and
cryptocurrencies could be leveraged to drive innovation in tourism services.
Past Bibliometric Studies
Guo et al. (2021) provided a comprehensive overview of blockchain technology using
bibliometric analysis tools such as CiteSpace and VOSviewer, highlighting a significant
increase in blockchain research since 2016. Despite this growing body of work, there remains
a notable lack of bibliometric research specifically addressing blockchain technology in the
tourism sector. While bibliometric studies on blockchain can be found in adjacent fields, such
as smart cities, there is a gap in the tourism context. A recent study by Rejeb, Rejeb, Simske,
and Keogh (2021) employed bibliometric analysis to explore blockchain applications in smart
cities, examining 48 articles published between 2016 and 2020. They found that blockchain
technology could enhance the sustainability of smart cities, particularly in sectors such as
logistics and supply chain management, transportation, and public administration. Additionally,
in related fields such as logistics and supply chain management, Rejeb, Rejeb, Simske, and
Treiblmaier (2021) conducted a bibliometric review of blockchain research and observed that
most studies still emphasize the conceptualization of blockchain rather than its practical
applications.
MATERIALS AND METHODS
Study Design
This study aims to explore the application of blockchain technology within the tourism industry
and to delineate future research agendas. While numerous studies have examined blockchain
technology, they have largely overlooked its implications in the context of tourism. To address
this gap, this study employs a systematic methodology that has been previously lacking in the
literature. Specifically, it utilizes a novel research design that integrates a systematic literature
review (SLR) with a bibliometric approach known as “systematic literature network analysis”
(SLNA) (Colicchia & Strozzi, 2012). Developed a decade ago, the SLNA approach has

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
5
garnered attention in fields such as safety climate (Bamel et al., 2020), information systems
(Zeng et al., 2020), and circular economy (Khitous et al., 2020). This approach was chosen to
effectively address the research questions and objectives. By combining the SLR and
bibliometric methodologies, this study aims to maximize the advantages of both approaches
while mitigating their respective limitations (Colicchia & Strozzi, 2012).
Initially, data were collected through a systematic process, which offers a robust and effective
mechanism for selecting the most pertinent literature across broad research domains.
Concurrently, bibliometric analysis provides insights into authors' contributions and
publication trends (Donthu et al., 2021). This bibliometric approach is well-suited for
uncovering statistical patterns and gaining deeper insights into specific research areas, such as
tourism, thereby enhancing understanding in related academic disciplines (Koseoglu et al.,
2016). The technique has gained popularity for its ability to deliver a comprehensive and
nuanced understanding of a particular field through science mapping on a database of
publications (Rahman et al., 2022).
Data Collection
This section highlights the data collection procedures involving defining the search terms,
inclusion, and exclusion criteria, which are outlined in the following sub-sections.
Defining keywords
The search was conducted using the article title as the primary search criterion, thereby
facilitating the retrieval of precise and relevant results related to blockchain technology in the
tourism industry. For data collection, a search string was crafted incorporating two key sets of
terms to identify relevant articles. The first set included keywords related to blockchain, such
as "blockchain," "block-chain," "smart contract," "digital ledger," and "cryptocurrency." The
second set comprised terms associated with tourism, including "tourism," "travel," and
"tourist," which are sometimes used interchangeably. Consequently, the search in the title field
utilized the following keywords: TITLE ("blockchain" OR "block-chain" OR "smart contract"
OR "digital ledger" OR "cryptocurrency") AND ("tourism" OR "travel" OR "tourist").
Search Strategy and Protocols
The second step of data collection involved developing search protocols. Referring to Casino
et al. (2019), “Preferred Reporting Items for Systematic Reviews and Meta-Analysis”
(PRISMA) was adopted as a review protocol. Page et al., (2021) stated that the PRISMA
statement facilitates gaining an in-depth understanding, transparency, and reproducibility of
the studies (Ali & Johl, 2022). Figure 1 illustrates the PRISMA diagram, which highlights the
study selection process.
The three major research databases are Scopus, Web of Science (WOS), and Google Scholar
(Sureka et al., 2022). Unlike Google Scholar, both Scopus and WOS offer functionalities to
download datasets that are compatible with bibliometric software. Scopus is an extensive
abstract and citation database that spans a wide array of academic fields, including the sciences,
social sciences, arts, and humanities. It aggregates a broad spectrum of academic publications
and conference proceedings, making it highly suitable for bibliometric analysis across various
disciplines. As a comprehensive resource, Scopus is invaluable for researchers, academics, and

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
6
institutions aiming to stay abreast of the latest developments and understand the broader
research context. Maintained by Elsevier, Scopus is recognized as one of the largest abstract
and citation databases available, employing a sophisticated algorithm to assess the quality and
relevance of articles, thereby providing users with a detailed overview of specific research
landscapes. Its extensive coverage across multiple fields makes it particularly useful for
investigating interdisciplinary patterns and overarching themes. Consequently, Scopus was
selected for gathering publications related to the application of blockchain technology in the
tourism sector.
The inclusion and exclusion criteria were identified in the final step. The search strings were
used to extract data from Scopus. The research inclusion criteria include several steps. First,
articles published from 2017 to 2024 were selected. The year 2017 was chosen as the base year
as the first study of blockchain in tourism was published during that time. The search query
found a total of 172 documents, comprising a compilation of academic works focused on the
application of blockchain technology in the tourism industry. The information presented herein
serves as the foundation for our systematic evaluation, enabling a precise depiction of the
current state of the subject and the discernment of upcoming trends and issues. Additionally,
only English-written articles were included in the dataset, hence two articles in Spanish were
excluded from the dataset. In order to maintain the focus of our study on original research
publications, certain document types were excluded from the dataset, resulting in further
refinement. The dataset consisted of many categories of documents, specifically review (5),
letter (1), and erratum (1), that were subsequently eliminated. Therefore, the review dataset
comprised articles (81), conference paper (56), book chapter (25) and a book (1) published
between 2017 and 2024.
Following the completion of the exclusion procedure, the dataset consisted of a total of 163
original research papers. These publications were employed to assess the current state of
blockchain research within the tourism industry and to identify key patterns, challenges, and
opportunities in this field. This approach ensured that our study was rooted in primary sources,
capturing recent and relevant advancements in the application of blockchain technology in
tourism. The procedure is depicted in Figure 1.

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
7
Figure 1
The PRISMA Flow Diagram of the Search Strategy
Data Cleaning and Harmonisation
For conducting bibliometric analysis, it is crucial to clean and harmonize datasets to ensure the
accuracy, consistency, and reliability of the results. Data cleaning involves identifying and
rectifying errors, inconsistencies, missing values, or outliers in the dataset, with categories
requiring attention including keywords, author names, affiliations, countries, and references.
This process is essential for ensuring that the information used in the analysis is both accurate
and dependable. Harmonizing data involves standardizing different attributes or variables to
ensure they are measured or represented consistently. Effective cleaning and harmonization
help to mitigate biases that may arise from inconsistencies, errors, or variations within the
dataset. These steps are fundamental in transforming raw data into a standardized, consistent,
and reliable format, thereby enabling researchers to derive accurate insights and conclusions
from their analyses.
Database: Scopus
Search Field: Article Title
Time Frame: All
Language: English
TITLE ("blockchain" OR "block-chain" OR "smart contract" OR
"digital ledger" OR "cryptocurrency" AND "tourism" OR "travel"
OR "tourist")
Keywords and Search
String
n = 172
Record Identified and
Screened
Blockchain in tourism
Screening
Included
Topic, Scope & Eligibility
Topic
Scope and Coverage
Record Included for
Bibliometric Analysis
n = 9
Record Removed
n = 163
24 July 2024
Date Extracted
Remove review (5), letter (1),
erratum (1) and Spanish (2)

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
8
In this study, the raw dataset obtained from Scopus was cleaned and harmonized using
specialized bibliometric software, namely biblioMagika 2.3 (Ahmi, 2023) and OpenRefine.
This process involved addressing inconsistencies in author names, affiliations, countries,
keywords, and references. The thoroughly cleaned and harmonized data were then exported
and prepared for further bibliometric analysis. By ensuring that the data are clean and
harmonized, we enable more robust statistical analysis, visualization, and modeling, which
facilitates the extraction of meaningful insights, identification of trends and patterns, and more
accurate conclusions.
Tool and Data Analysis
To achieve the research objective and address the research questions, the bibliometric analysis
was performed using Biblioshiny, which is a shiny app for the Bibliometric R package
developed by Aria and Cuccurullo (2017). This app can integrate with a wide range of
databases and citation management tools combined with its robust set of organisational and
collaboration features, which provide a comprehensive solution for managing and sharing
research information. One of the crucial features of Biblioshiny is its ability to integrate with
an extensive range of citation management tools and databases, such as Scopus. Figure 2
displays the bibliometric analysis process using Biblioshiny.
Figure 2
Detail Steps for Bibliometric Analysis using Biblioshiny
ANALYSIS AND RESULTS
This section presents a study overview of blockchain technology and tourism containing
publications from 2017 to 2024 and all information about the present status of publications,
research tendencies, highly cited papers, publishing sources, nations, institutions, and prolific
authors, and the authors’ keyword selections.
Main Information
The first study that discussed blockchain technology in the tourist business emerged in 2017
under the Scopus database. The analysis reveals an average annual growth rate of 56.51% in
Step 3: Analyze data
Step 1: Open RStudio, load ‘Bibliometric’ library and run ‘Biblioshiny’
Step 2: Upload dataset
Step 4: Discuss and summarize results

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
9
the number of publications. Table 1 provides a comprehensive summary of all articles
published on blockchain technology in the field of tourism from 2017 to 2024. This table
includes metrics such as average citations per document, average citations per year, document
types, document contents, author information, and patterns of author collaboration.
Table 1
Sample Based on Industry
Description
Results
MAIN INFORMATION ABOUT THE DATA
Time span
2017:2024
Sources (journals, books and etc.)
108
Documents
163
Annual Growth Rate %
56.51
Document Average Age
2.09
Average citations per doc
16.46
References
6933
DOCUMENT TYPES
Article
81
Book
1
Book chapter
25
Conference paper
56
DOCUMENT CONTENTS
Keywords plus (ID)
537
Author’s keywords (DE)
396
AUTHORS
Authors
450
Authors of single-authored documents
23
Authors of multi-authored documents
427
AUTHORS COLLABORATION
Single-authored documents
25
Co-authors per document
3.22
International co-authorships %
24.25
Annual Publication Trends
The yearly publishing trends for 2017 to 2024 are illustrated in Table 2 and Figures 3 and 4
along with the details of total publication, total citation, citation per document, and citation per
year. The bibliometric analysis found that the peak publications on blockchain in tourism were
in 2023, with 47 articles.

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
10
Figure 3
Annual Publication Trends
Table 2
Annual Publication Trends
Year
Total publications
Total citations
Citation per publication
Citation per year
Citable Years
2017
1
49.00
49.00
6.12
8
2018
3
206.01
68.67
9.81
7
2019
7
212.03
30.29
5.05
6
2020
22
764.06
34.73
6.95
5
2021
26
746.98
28.73
7.18
4
2022
34
503.88
14.82
4.94
3
2023
47
178.13
3.79
1.90
2
2024
23
23.00
1.00
1.00
1
Figure 4
Growth and Publications Impact Per Year
0
5
10
15
20
25
30
35
40
45
50
0.00
100.00
200.00
300.00
400.00
500.00
600.00
700.00
800.00
900.00
2017 2018 2019 2020 2021 2022 2023 2024
total publication total citation

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
11
Most Productive Authors
Figure 5 displays the top 10 authors by publication count. Treiblmaier stands out with seven
papers, making him a notable contributor in blockchain technology for tourism, followed by
Önder and Hariadi, with six and four articles each.
Figure 5
Most Relevant Authors
Most Cited Papers
Figure 6 and Table 3 present the most referenced papers globally and regionally. The top-cited
paper, authored by Önder and Treiblmaier (2018), explores blockchain's impact on tourism
with 163 citations. Following closely is a paper by Nuryyev et al. (2020) delving into
blockchain adoption in tourism and hospitality SMEs, gathering 162 citations. Nam et al.'s
(2021) work on blockchain in smart city and smart tourism follows with 152 citations.

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
12
Figure 6
Most Globally Cited Documents
Table 3
Top 10 Highly Cited Papers
No
Author(s)
Title
Total
Citations
Citations
per Year
1
Önder and
Treiblmaier (2018)
Blockchain and tourism: Three research
propositions
163
23.29
2
Nuryyev et al.
(2020)
Blockchain technology adoption behaviour and
sustainability of the business in tourism and
hospitality SMEs: An empirical study
162
32.40
3
Nam et al. (2021)
Blockchain technology for smart city and smart
tourism: latest trends and challenges
152
38.00
4
Rashideh (2020)
Blockchain technology framework: current and
future perspectives for the tourism industry
147
29.40
5
Valeri and Baggio
(2021)
A critical reflection on the adoption of blockchain
in tourism
118
29.50
6
Bodkhe et al. (2019)
BloHosT: Blockchain enabled smart tourism and
hospitality management
109
18.17
7
Ozdemir et al.
(2020)
Assessment of blockchain applications in travel
and tourism industry
85
17.00
8
Baralla et al. (2021)
Ensuring transparency and traceability of food
local products: A blockchain application to a
Smart Tourism Region
82
20.50
9
Sharma et al. (2021)
Technology assessment: Enabling Blockchain in
hospitality and tourism sectors
75
18.75
10
Tham and Sigala
(2020)
Road block (chain): bit (coin) s for tourism
sustainable development goals?
55
11.00

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
13
Most Productive Countries
Table 4 presents the top 10 most productive nations. China, Austria, the United States, Italy,
the United Arab Emirates, , Turkey, Korea, the United Kingdom, India, and Spain had the most
published papers on blockchain technology in the tourism industry.
Table 4
The Top 10 Most Productive Countries
Country
Total publication
Total Citations
Average Article Citations
CHINA
90
284
12.30
AUSTRIA
82
269
44.80
USA
45
216
30.90
ITALY
40
161
26.80
UNITED ARAB EMIRATES
29
152
152.00
TURKEY
19
132
26.40
KOREA
19
121
20.20
UNITED KINGDOM
18
119
39.70
INDIA
15
112
6.20
SPAIN
12
95
19.00
Most Productive Affiliations
Biblioshiny can identify the most productive academic institution or affiliations. The number
of papers produced by the most prolific affiliations or institutions is depicted in Table 5, which
includes the top 10 affiliations for convenience. CHRIST and Modul University Vienna are the
leading institutions, each publishing 8 articles on blockchain technology in the tourism.
Table 5
Top 10 Productive Institutions
Most Frequent Journals
Biblioshiny also determines the most prevalent journals. In Figure 7, the 10 most-cited journals
are shown. Spring Proceedings in Business and Economics and Sustainability with eight
Affiliations
Total publication
CHRIST (DEEMED TO BE UNIVERSITY)
8
MODUL UNIVERSITY VIENNA
8
NANJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS
7
JEJU NATIONAL UNIVERSITY
6
NATIONAL SUN YAT-SEN UNIVERSITY
6
O. P. JINDAL GLOBAL UNIVERSITY
6
UNIVERSITAS PENDIDIKAN NASIONAL
6
UNIVERSITY OF MALAGA
6
UNIVERSITY OF SURREY
6
UNIVERSITY OF TEHRAN
6

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
14
relevant articles are the two journals with the highest frequency of debates and publications on
blockchain technology in the tourism industry.
Figure 7
Top 10 Most Cited Journals
Most Frequent Keywords
Table 6 compiles the most frequent keywords in this bibliometric study on blockchain
technology in the tourism industry and summarises the top 10 authors’ and indexed keywords.
Meanwhile, Figure 8 depicts the keyword word cloud. The analysis revealed that blockchain,
tourism, tourism development, tourism industry are among the most frequently occurring terms
used in blockchain technology in the tourism.
Table 6
Top 10 Keywords
Author’s keywords
Occurrences
Indexed keywords
Occurrences
blockchain
95
blockchain
53
tourism
41
tourism
37
blockchain technology
20
block-chain
36
smart tourism
18
tourism development
14
hospitality
11
tourism industry
12
smart contract
10
tourism market
11
cryptocurrency
9
leisure industry
8
bitcoin
8
china
7
sustainability
7
innovation
7
tourism industry
7
smart tourism
7

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
15
Figure 8
Word Cloud of Indexed Keywords
Co-citation Analysis
Research clusters emerge when numerous researchers co-cite the same pairs of publications,
thereby highlighting thematic similarities within the literature. Co-citation analysis, combined
with single-link clustering and multidimensional scaling methods, maps the structure of
specialized research fields and the broader scientific landscape. Figure 9 illustrates the co-
citation network of publications concerning blockchain technology within the tourism sector.
Notably, three significant clusters of co-cited works are evident in the dataset, with nodes of
the same color typically representing similar topics. This network visualizes the structure of
frequent citations in blockchain research related to tourism. The highly referenced publications
listed in Table 3 are integral to the co-citation network for this subject.

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
16
Figure 9
Collaboration Network of Documents
Collaboration Analysis
Figure 10 illustrates an overview of major cooperation between countries on blockchain
technology in tourism. The researchers from China are the ones who are cultivating the
partnership followed by those from India and the United State. These three prominent countries
work together with other nations, such as Korea, Spain, Indonesia, and Italy.
Figure 10
Collaboration Network of Countries

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
17
Co-word Analysis
Co-occurrence refers to the frequency with which comparable terms appear in proximity across
multiple publications, a concept also known as a semantic network. This analysis encompasses
terms that are related and centered on the same subject but do not necessarily correspond
directly. Figure 11 depicts the co-occurrence network of authors' keywords. In this graphic, a
thicker line between keywords indicates a stronger relationship, while the absence of
connecting lines signifies no evident link between the terms.
The words will be displayed on the network map closer to the centre of the map if the co-
occurrences are discovered. The utilisation of closely related keywords by writers signifies a
stronger connection, which leads to enhanced relationships. A larger bubble representing a
keyword suggests a greater frequency with which it was used. The results revealed five
thematic clusters. A unique colour is assigned to each cluster to ease identification. Moreover,
the following themes were identified:
(1) Blockchain (purple bubbles)
(2) Tourism development (green bubbles)
(3) Tourism economics (red bubbles)
(4) Technology adoption (blue bubbles)
(5) Travel demand (orange bubbles)
Figure 11 indicates that the most important network or the most significant cluster of themes
explored is blockchain, including tourism, smart tourism, service provider, cryptocurrency, and
smart contract as some of its keywords. Meanwhile, the second network of tourism
development, innovation and sustainability are the relevant keywords employed by the
previous research.
Figure 11
Co-occurrence Network of Author’s Keywords

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
18
Three Fields Plot
Figure 12 is based on a three-field plot or a Sankey diagram, which illustrates the relationships
between the most prolific writers, keywords, and nations. The term “blockchain” appeared 95
times, thus being the most used term overall. Similarly, authors have published several research
using the terms “tourism” (41), “blockchain technology” (20) and “smart tourism” (18). The
word “blockchain” was used the most by authors from China.
Figure 12
Three Field Plots
Thematic Evolution
Figure 13 displays the development of a specific theme based on the authors’ keywords about
blockchain technology application within the tourism industry. The field plots depict how the
topics connected to blockchain technology in the tourism industry have developed from 2017
to 2021 and 2022 to 2024. The seven recurring themes in the earlier era have evolved into four
underlying themes in the current period.
Figure 13
Thematic Evolution Based on the Author’s Keywords

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
19
Figure 14 depicts the specific thematic map for these respective periods, which outlines the
motor themes in the upper-right quadrant of the figure. The themes are characterised by high
centrality and density, which is the most developed topic in the literature and the primary focus
in blockchain technology research on the tourism business.
Blockchain is the primary focus of this section. Nonetheless, the upper-left quadrant displays
high-density topics linked to minor external sources, hence only producing a limited impact on
the field (low centrality). The themes that are developing or becoming less prominent may be
observed in the lower-left quadrant. The tourism economics and tourism destination are some
of the topics that fit within this quadrant. Those motor themes such as tourism industry and
covid-19 are in the upper-right quadrant. Lastly, the themes that are fundamental and pervasive
are observed in the lower-right quadrant.
Figure 14
Thematic Map
DISCUSSION AND CONCLUSION
The bibliometric analysis of blockchain studies focusing on the tourism sector has revealed a
notable increase in publications, indicating a growing demand for further research into
blockchain technology. This surge reflects the rising interest in blockchain applications.
Scholars have increasingly highlighted concerns regarding blockchain-based privacy and
security solutions, particularly as this technology integrates with smart applications in tourism
and hospitality (Bodkhe et al., 2020). However, there is a paucity of studies addressing policy
discussions. The expanding prevalence and evolution of blockchain technology underscore the
need for research focusing on its policy implications. Additionally, the limited volume of
research on blockchain technology within the tourism sector, with only 163 papers identified
in this bibliometric study (Nam et al., 2021), points to a gap in the literature. Future research
should also explore other related themes, such as cryptography, ecosystem development, and
technology adoption, particularly in the context of tourism recovery post-COVID-19.

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
20
This study employs bibliometric analysis using R-software to scientifically map the
development and current status of blockchain technology within the tourism industry. The
findings offer valuable insights for academics, scholars, and stakeholders actively engaged with
blockchain applications in tourism. The analysis constructs a timeline of the trend's evolution,
providing detailed information on the articles examined, including publication years, types of
articles, sources, and content. Additionally, the bibliometric analysis yields critical insights into
annual publication trends, leading authors, highly cited papers, influential countries, productive
institutions, and prominent sources. It also identifies the top keywords and includes analyses
such as co-citation, co-citation network, collaboration, thematic evolution, and thematic
mapping. Recently, several countries have prioritized blockchain technology to enhance their
tourism sectors, with China, Austria, and the United States emerging as major contributors due
to their high output and citation rates. However, the majority of research is concentrated in
developed economies, with a significant gap in studies from emerging and developing countries.
To foster growth in the tourism sector, other economies should intensify their exploration of
blockchain implementations and related issues, thereby contributing to the accelerated and
efficient advancement of blockchain technology in tourism.
This study provides novel insights into blockchain technology for stakeholders in the tourism
sector, including both academics and practitioners. It offers a comprehensive overview of the
current state of blockchain technology in the tourism industry and suggests potential future
research directions. However, several limitations warrant consideration in future investigations.
Notably, this study was limited to documents published in the Scopus database; future research
should incorporate additional databases to broaden the scope of analysis. Furthermore, while
this study identified key research hotspots and emerging trends, a more in-depth exploration of
specific research topics, such as governance and security, is necessary to fully understand the
complexities and nuances of blockchain technology.
ACKNOWLEDGEMENT
The authors express their gratitude to Universiti Putra Malaysia for their support and extend
their appreciation to the anonymous reviewers for their valuable contributions in improving
this work.
REFERENCES
Ahmi, A. (2023). biblioMagika. Retrieved from: https://aidi-
ahmi.com/index.php/bibliomagika.
Alhadhrami, Z., Alghfeli, S., Alghfeli, M., Abedlla, J. A., & Shuaib, K. (2017). Introducing
blockchains for healthcare. International Conference on Electrical and Computing
Technologies and Applications (ICECTA).
Ali, K., & Johl, S. K. (2022). Soft and hard TQM practices: Future research agenda for industry
4.0. Total Quality Management & Business Excellence, 33(13-14), 1625-1655.
Aria, M., & Cuccurullo, C. (2017). bibliometric: An R-tool for comprehensive science mapping
analysis. Journal of Informetrics, 11(4), 959-975.
Aung, Y. N., & Tantidham, T. (2017). Review of Ethereum: Smart home case study. 2nd
International Conference on Information Technology (INCIT).

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
21
Baralla, G., Ibba, S., Marchesi, M., Tonelli, R., & Missineo, S. (2019). A blockchain based
system to ensure transparency and reliability in food supply chain. European
Conference on Parallel Processing.
Baralla, G., Pinna, A., Tonelli, R., Marchesi, M., & Ibba, S. (2021). Ensuring transparency and
traceability of food local products: A blockchain application to a smart tourism region.
Concurrency and Computation: Practice and Experience, 33(1), e5857.
Bodkhe, U., Bhattacharya, P., Tanwar, S., Tyagi, S., Kumar, N., & Obaidat, M. S. (2019).
BloHosT: Blockchain enabled smart tourism and hospitality management.
International Conference on Computer, Information and Telecommunication Systems
(CITS).
Bodkhe, U., Tanwar, S., Parekh, K., Khanpara, P., Tyagi, S., Kumar, N., & Alazab, M. (2020).
Blockchain for industry 4.0: A comprehensive review. IEEE Access, 8, 79764-79800.
Bolici, F., Acciarini, C., Marchegiani, L., & Pirolo, L. (2019). Blockchain acceptance and
adoption in the tourism industry. Conference Proceedings, 43-56.
Casino, F., Dasaklis, T. K., & Patsakis, C. (2019). A systematic literature review of blockchain-
based applications: Current status, classification and open issues. Telematics and
Informatics, 36, 55-81.
Filimonau, V., & Naumova, E. (2020). The blockchain technology and the scope of its
application in hospitality operations. International Journal of Hospitality Management,
87, 102383.
Guo, Y.-M., Huang, Z.-L., Guo, J., Guo, X.-R., Li, H., Liu, M.-Y., Ezzeddine, S., & Nkeli, M.
J. (2021). A bibliometric analysis and visualization of blockchain. Future Generation
Computer Systems, 116, 316-332.
Jardim, L., Pranto, S., Ruivo, P., & Oliveira, T. (2021). What are the main drivers of blockchain
adoption within supply chain? – An exploratory research. Procedia Computer Science,
181, 495-502.
Khan, S., Kaushik, M.K., Kumar, R. and Khan, W. (2023). Investigating the barriers of
blockchain technology integrated food supply chain: a BWM approach. Benchmarking:
An International Journal, 30 (3), pp. 713-735. https://doi.org/10.1108/BIJ-08-2021-
0489
Kizildag, M., Dogru, T., Zhang, T. C., Mody, M. A., Altin, M., Ozturk, A. B., & Ozdemir, O.
(2019). Blockchain: A paradigm shift in business practices. International Journal of
Contemporary Hospitality Management, 32(3), 953-975.
Korže, S. Z. (2019a). From industry 4.0 to tourism 4.0. Innovative Issues and Approaches in
Social Sciences, 12(3), 29-52.
Korže, S. Z. (2019b). How smart tourism embrace blockchains and smart contracts.
Mednarodno inovativno poslovanje. Journal of Innovative Business and Management,
11(2), 32-40.
Koseoglu, M. A., Rahimi, R., Okumus, F., & Liu, J. (2016). Bibliometric studies in tourism.
Annals of Tourism Research, 61, 180-198.
Kwok, A. O., & Koh, S. G. (2019). Is blockchain technology a watershed for tourism
development? Current Issues in Tourism, 22(20), 2447-2452.
Line, N. D., Dogru, T., El-Manstrly, D., Buoye, A., Malthouse, E., & Kandampully, J. (2020).
Control, use and ownership of big data: A reciprocal view of customer big data value
in the hospitality and tourism industry. Tourism Management, 80, 104106.
Mofokeng, N. E. M., & Matima, T. K. (2018). Future tourism trends: Virtual reality based
tourism utilizing distributed ledger technologies. African Journal of Hospitality,
Tourism and Leisure, 7(3), 1-14.

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
22
Nam, K., Dutt, C. S., Chathoth, P., & Khan, M. S. (2021). Blockchain technology for smart
city and smart tourism: Latest trends and challenges. Asia Pacific Journal of Tourism
Research, 26(4), 454-468.
Nuryyev, G., Wang, Y.-P., Achyldurdyyeva, J., Jaw, B.-S., Yeh, Y.-S., Lin, H.-T., & Wu, L.-
F. (2020). Blockchain technology adoption behavior and sustainability of the business
in tourism and hospitality SMEs: An empirical study. Sustainability, 12(3), 1256.
Önder, I., & Treiblmaier, H. (2018). Blockchain and tourism: Three research propositions.
Annals of Tourism Research, 72(C), 180-182.
Ozdemir, A. I., Ar, I. M., & Erol, I. (2020). Assessment of blockchain applications in travel
and tourism industry. Quality & Quantity, 54(5), 1549-1563.
Pilkington, M. (2017). Can blockchain technology help promote new tourism destinations? The
example of medical tourism in Moldova. SSRN Electronic.
http://dx.doi.org/10.2139/ssrn.2984479.
Pilkington, M., Crudu, R., & Grant, L. G. (2017). Blockchain and bitcoin as a way to lift a
country out of poverty-tourism 2.0 and e-governance in the Republic of Moldova.
International Journal of Internet Technology and Secured Transactions, 7(2), 115-143.
Pilkington, M. (2016). Blockchain technology: principles and applications. In Olleros, F. A. &
Zhegu, M. (Eds.) Research handbook on digital transformations (pp. 225-253). Edward
Elgar Publishing.
Queiroz, M. M., & Wamba, S. F. (2019). Blockchain adoption challenges in supply chain: An
empirical investigation of the main drivers in India and the USA. International Journal
of Information Management, 46, 70-82.
Rahman, N. A. A., Ahmi, A., Jraisat, L., & Upadhyay, A. (2022). Examining the trend of
humanitarian supply chain studies: Pre, during and post COVID-19 pandemic. Journal
of Humanitarian Logistics and Supply Chain Management (ahead-of-print).
Rashideh, W. (2020). Blockchain technology framework: Current and future perspectives for
the tourism industry. Tourism Management, 80, 104125.
Rejeb, A., & Karim, R. (2019). Blockchain technology in tourism: Applications and
possibilities. World Scientific News, 137, 119-144.
Rejeb, A., Rejeb, K., Simske, S., & Treiblmaier, H. (2021). Blockchain technologies in
logistics and supply chain management: A bibliometric review. Logistics, 5(4), 72.
Rejeb, A., Rejeb, K., Simske, S. J., & Keogh, J. G. (2021). Blockchain technology in the smart
city: A bibliometric review. Quality & Quantity, 1-32.
Reyes-Menendez, A., Saura, J. R., & Filipe, F. (2019). The importance of behavioral data to
identify online fake reviews for tourism businesses: A systematic review. PeerJ
Computer Science, 5, e219.
Sharma, M., Sehrawat, R., Daim, T., & Shaygan, A. (2021). Technology assessment: Enabling
blockchain in hospitality and tourism sectors. Technological Forecasting and Social
Change, 169, 120810.
Sigala, M. (2017). Collaborative commerce in tourism: Implications for research and industry.
Current Issues in Tourism, 20(4), 346-355.
Tham, A., & Sigala, M. (2020). Road blockchain: Bitcoins for tourism sustainable development
goals? Journal of Hospitality and Tourism Technology, 11(2), 203-222.
Treiblmaier, H. (2018). The impact of the blockchain on the supply chain: A theory-based
research framework and a call for action. Supply Chain Management: An International
Journal, 23(6), 545-559.
Treiblmaier, H., & Önder, I. (2019). The impact of blockchain on the tourism industry: A
theory-based research framework. Business Transformation through Blockchain:
Volume II, 3-21.

Journal of Management & Muamalah, Vol. 14, No. 2 (2024)
23
Tyan, I., Guevara-Plaza, A., & Yagüe, M. I. (2021). The benefits of blockchain technology for
medical tourism. Sustainability, 13(22), 12448.
Valeri, M., & Baggio, R. (2021). A critical reflection on the adoption of blockchain in tourism.
Information Technology & Tourism, 23(2), 121-132.
Varriale, V., Cammarano, A., Michelino, F., & Caputo, M. (2020). The unknown potential of
blockchain for sustainable supply chains. Sustainability, 12(22), 9400.
Vistro, D. M., Farooq, M. S., Rehman, A. U., & Bilal, M. (2021). A framework for the
promotion of tourism industry using blockchain technology. 3rd International
Conference on Integrated Intelligent Computing Communication & Security (ICIIC
2021).
Wahab, S. N., Loo, Y. M., & Say, C. S. (2020). Antecedents of blockchain technology
application among Malaysian warehouse industry. International Journal of Logistics
Systems and Management, 37(3), 427-444.
Willie, P. (2019). Can all sectors of the hospitality and tourism industry be influenced by the
innovation of blockchain technology? Worldwide Hospitality and Tourism Themes.
Wong, L.-W., Leong, L.-Y., Hew, J.-J., Tan, G. W.-H., & Ooi, K.-B. (2020). Time to seize the
digital evolution: Adoption of blockchain in operations and supply chain management
among Malaysian SMEs. International Journal of Information Management, 52,
101997.
Xu, M., Chen, X., & Kou, G. (2019). A systematic review of blockchain. Financial Innovation,
5(1), 1-14.
Yamazaki, T. (2020). Advanced space service access application tool: ASTRAX universal user
interface (U2U) 71st International Astronautical Congress, IAC 2020, International
Space Services, Inc., ASTRAX, Inc., 2-23-17 Komachi, Kamakura, Kanagawa, 248-
0006, Japan.
Yaga, D., Mell, P., Roby, N., & Scarfone, K. (2019). Blockchain technology overview. arXiv
preprint arXiv:1906.11078.
Ying, W., Jia, S., & Du, W. (2018). Digital enablement of blockchain: Evidence from HNA
Group. International Journal of Information Management, 39, 1-4.
Zheng, Z., Xie, S., Dai, H., Chen, X., & Wang, H. (2017, June). An overview of blockchain
technology: Architecture, consensus, and future trends. IEEE International Congress
on Big Data (BigData congress), 557-564.