Elvis Salouw
| Bakti Setiawan | Muhammad Sani Roychansyah* | Ahmad Sarwadi
© 2024 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
This study aims to provide a bibliometric analysis of tourism and community participation based on the Scopus and WOS databases. As studies on community participation have developed in the last decade, it is important to map and compare research progress on community participation. This study uses the two most popular databases to analyze and provide an overview of the scope of overlap and singularity databases and the popularity of documents and authors in the two databases. Data collection was carried out from May 23 to 25, 2022. Therefore, 457 and 350 documents from Scopus and WOS were compared using bibliometric analysis to determine growth, overlap, prolific and influential author, most cited document and keywords, as well as productivity of country and institutions. The data collected were analyzed using Excel and VOSViewers applications. The results showed that the growth trend of tourism and community participation research continues to increase in both databases. However, Scopus has a broader scope in tourism and community participation fields and more unique documents. Wall G and Tosun C are the most prolific and influential authors, while China is the most productive country. Developing countries significantly contribute to international publications related to tourism and community participation.
tourism, community participation, Web of Science, Scopus, bibliometric
The idea of community participation became popular through the study of Arnstein [1], who used citizen participation in democratic and political discussions. This has been applied by several studies in the tourism context. Community participation is an approach that involves members in solving societal problems [2].
In tourism, community participation is a topic of interest in various countries. Several previous studies have been carried out in this field [3-5]. Community participation refers to members' involvement in tourism activities oriented toward economic, social, and environmental benefits [6, 7].
Bibliometrics is a statistical-based valuable method for mapping a research topic and discerning the evolution of journals and their scientific structure and patterns [8-10]. According to study [11], bibliometrics approach using rigorous protocols to obtain quality information. The bibliometric method is applied in various fields of science because it focuses on quantitative studies [12].
This bibliometric study focuses on tourism and community participation using the Scopus and WOS databases. VOSviewers software was used to explore and construct bibliometric maps [13]. Furthermore, the use of this method in tourism has developed quite rapidly. Several previous studies have been carried out by studies [14-25]. Sánchez et al. [26] stated that bibliometric methods had been used to carry out tourism studies since 1989.
As a broad scientific study concerning community participation, tourism requires further exploration. Iqbal et al. [27] conducted a bibliometric analysis on community participation topic.
However, this study employed only the Scopus database limited to 2020. The limitations of previous research were addressed in this study by comparing the Scopus and WOS databases covering 2021. This study presents the latest scientific evolution of tourism and community participation by comparing the Scopus and WOS databases.
This bibliometric research employed seven steps, with the first used to determine the field of study, tourism related to community participation. The second is discerning the search platform, Scopus and WOS, considering the scope of knowledge and ease of accessing these databases. The third is mining bibliometric data, and the Boolean logic used is "tourism" AND "community participation". The fourth step is that the dataset file is exported to the application and processed using Excel and VOSViewers. The fifth step involves analyzing and interpreting the data based on the findings. The sixth is mapping as well as grouping gaps and trends, while the seventh step is a conclusion.
Data collection was carried out from May 23 to 25, 2022. The keywords regularly searched on the Scopus and WOS platforms are tourism and community participation. The initial search was used to obtain 717 and 657 documents from WOS and Scopus, respectively. This simply proves that the keywords cover various scientific fields, including chemistry, medicine, and mathematics. Consequently, the search was repeated based on the protocol shown in Table 1.
Table 1. The search criteria
|
|
Scopus |
WOS |
|
Keywords |
“Tourism” AND “Community participation” |
“Community participation” AND “Tourism”) |
|
Document Type |
Articles, Reviews, Book chapters, proceedings |
Articles, Reviews, Book chapters, proceedings |
|
Author |
Exclude anonymous and undefined |
Exclude anonymous and undefined |
|
Year |
Exclude 2022 |
Exclude 2022 |
|
Subject area |
Social Sciences, Business, Management, and Accounting |
Hospitality Leisure Sport Tourism and Management |
|
Search date |
May 23, 2022 |
May 25, 2022 |
Source: Author's Elaboration.
After applying the search criteria, the results obtained were pretty significant. The Scopus and WOS databases produced 457 and 350 documents, respectively. Figure 1 shows the comparison of the documents for each database.
Figure 1. Publication trends related to tourism and community participation in the Scopus and WOS databases
Source: Author's Elaboration.
The search results show that publications related to tourism and community participation in the Scopus database have been in existence since 1986. On the other hand, those with the exact keywords were published in the WOS database eight years later, in 1994. The search data also shows that more documents were published in the Scopus database in the last five years than in the WOS.
In the next step, 162 duplicate documents out of 807 were found in both databases. Afterward, this is followed by statistical and thematic analyses, specific overlap and singularity, prolific and influential author, most cited document, used author keywords, and productive country and institutions.
Meyer's Index was used to review the search results in the database. It is also referred to as a relative index of singularities [28], used to assess the extent to which a database covers a subject. A unique document is highly valuable and tends to be gradually reduced if there are duplicates (weight=0.5), triplicates (weight=0.3), and others. The higher the Index, the larger the singularity, which implies more unique documents.
$Meyer's\text { Index} =\frac{\sum \text { Sources } * \text { Weight }}{\text { Total Sources }}$
where, ∑Sources*Weight=total number of documents or sources multiplied by the rate of duplication.
Traditional overlap (TO) (Gluck, 1990) was used to measure the database overlap.
$\% T O=100 *\left(\frac{|A \cap B|}{|A \cup B|}\right)$
where, %TO=percentage of the ratio of the number of documents at the intersection of two secondary databases to the number at their union; |A∩B|=the intersection of documents between database A and database B; |A∪B|=the union of documents between database A and database B.
The higher the TO value, the greater the level of similarity between the databases. For example, a coefficient of 0.15 indicates a 15% similarity level however, there is an 85% difference.
The Relative Overlap is used to measure the coverage of a database (A), as well as its relationship with that of (B).
$\begin{gathered}\% Overlap \, in \, A=100 *\left(\frac{|A \cap B|}{|A|}\right) \\ \% Overlap\, in\, B=100 *\left(\frac{|A \cap B|}{|B|}\right)\end{gathered}$
where, A=Database A; B=Database B; %Overlap in A=the percentage of overlap documents or sources in database A; %Overlap in B=the percentage of overlap documents or sources in database A; |A∩B|=the intersection of documents between source A and source B.
3.1 Overlap and singularity
Based on Table 2, 457 and 350 documents were identified from the Scopus and WOS databases, respectively. After all the necessary calculations, it was discovered that 156 documents were overlapping (found in both databases). Additionally, these were also perceived as duplicates, representing 34.14% and 44.57% of the Scopus and WOS databases. The rest are non-duplicates, in which 301 (65.86%) and 194 (55.43%) documents were obtained from Scopus and WOS, respectively. Figure 2 shows the comparison of documents and sources in the Scopus and WOS databases.
Figure 2. Number of shared documents and sources in the Scopus and WOS databases
Source: Author’s elaboration
Table 2. Study phase
|
Phase |
Description |
|
Phase 1: Determine study criteria |
This research employed the bibliometric method by mapping the science fields and performance analysis. |
|
Phase 2: Document searching and selection |
Database: Scopus and WOS Search strings: "tourism" AND "community participation" Initial search: Scopus (n=657), WOS (n=717) Dataset selection after refinement: Scopus (n=457), WOS (n=350) |
|
Phase 3: Software and data extraction |
Microsoft Excel: used for statistical analysis VOSViewers: used for processing and displaying data |
|
Phase 4: Analyze and conclusions |
Database: overlap and singularity Author: influential author Document: most cited document Keywords: co-occurrences of author keywords Country and institution: most productive country and institution |
Source: Author's Elaboration.
Table 3. Singularity database
|
Databases |
% Of Single Document/Source |
Meyer’s Index |
|
|
|
Documents |
Sources |
Documents |
Sources |
|
|
Scopus |
66% |
82% |
0.47 |
0.57 |
|
WOS |
55% |
69% |
0.34 |
0.31 |
Source: author’s elaboration
Table 3 shows the singularity of the Scopus and WOS databases. Furthermore, 23.96% was obtained as the traditional overlap calculation, which is shown as follows:
$\begin{gathered}\% T O=100\left(\frac{\text { Scopus } \cap W o S}{\text { Scopus } \cup W o S}\right)=>\% T O=\frac{156}{457+350-156}= >\% T O=23.96 \%\end{gathered}$
where, %TO=the percentage of the ratio of the number of documents at the intersection of two secondary databases to the number at their union; |Scopus∩WoS|=the intersection of documents between Scopus and WoS; |Scopus∪WoS|=the union of documents between Scopus and WoS.
These results indicate that 23.96% of the documents in the two databases are similar. In other words, 76.04% of the documents are unique and only exist in each database. Furthermore, to measure the percentage of Scopus coverage to WOS and vice versa, a relative overlap was used as follows:
$\begin{gathered}\% \text { TO WoS }=100 *\left(\frac{\mid \text { WoS $\cap$ Scopus } \mid}{\text { WoS }}\right)=>\% \text { TO WoS }= 100 *\left(\frac{156}{350}\right)=>45 \% \\ \% \text { TO Scopus }=100 *\left(\frac{\mid \text { WoS $ \cap$ Scopus } \mid}{\text { Scopus }}\right)=>\% \text { TO Scopus }= 100 *\left(\frac{156}{457}\right)=>34 \%\end{gathered}$
where, % TO WoS=the percentage of the traditional overlap in WoS; |Scopus∩WoS|=the intersection of documents between Scopus and WoS; % TO Scopus=percentage of the traditional overlap in Scopus.
Based on the calculated results, Scopus covers 45% of documents in WOS. Meanwhile, 34% of documents in the Scopus database are covered by WOS. This indicates that the Scopus database has more unique documents and covers numerous sources. Similarly, several other studies reported that the singularity of Scopus is higher than WOS. For example, research carried out on wine [26], innovation [29] and community-based tourism [30].
3.2 Influential and prolific author
Interestingly, 950 and 736 authors from the Scopus and WOS databases were identified. The most productive author based on the number of publications is Wall G, who has nine documents on Scopus with a total of 156 citations and nine on WOS with a total of 236 citations. Tosun C has the highest average citation per document among all authors.
A relatively large percentage of authors only have one document in both databases, namely 94% and 87% on Scopus and WOS. The average productivity in the Scopus database is 2.07 authors per article. On the other hand, that of WOS is 1.83 authors per document. The ten most productive authors as shown in Table 4 contributed 12.03% and 15.14% of the documents in the Scopus and WOS databases.
Based on Table 4, it is evident that in terms of tourism and community participation, the most prolific and influential writers are Wall G and Tosun C, respectively. However, when further examined, it was discovered that Wall G was not the first author. Tosun C single-handed wrote three of the four papers, all of which are regarded as the first authors.
3.3 Most cited document
Every research subject always has an author and document that plays an important role. The number of citations is used to judge the relevance of the related document. Based on the Scopus and WOS databases, ten documents with the most citations in tourism and community participation were selected, as shown in Table 5.
Table 4. Most influential and productive author
|
R |
Scopus |
WOS |
||||||
|
Name |
F |
TC |
C/F |
Name |
TP |
TC |
C/F |
|
|
1 |
Wall G. |
8 |
158 |
19,8 |
Wall, G |
9 |
238 |
26,4 |
|
2 |
Jaafar M. |
7 |
350 |
50,0 |
Jaafar, M |
8 |
412 |
51,5 |
|
3 |
Stone M.T. |
7 |
123 |
17,6 |
Rasoolimanesh, Sm |
6 |
389 |
64,8 |
|
4 |
Bao J. |
5 |
52 |
10,4 |
Woosnam, Km |
5 |
71 |
14,2 |
|
5 |
Lovelock B. |
5 |
128 |
25,6 |
Marzuki, A |
5 |
78 |
15,6 |
|
6 |
Stone L.S. |
5 |
105 |
21,0 |
Butcher, J |
4 |
13 |
3,3 |
|
7 |
Sun J. |
5 |
52 |
10,4 |
Tosun, C |
4 |
846 |
211,5 |
|
8 |
Wang Y. |
5 |
54 |
10,8 |
Su, Mm |
4 |
115 |
28,8 |
|
9 |
Ramachandran S. |
4 |
45 |
11,3 |
Stone, Ls |
4 |
90 |
22,5 |
|
10 |
Tosun C. |
4 |
1190 |
297,5 |
Lovelock, B |
4 |
58 |
14,5 |
Note: R=rank; F=frequency (number of articles); TC=total citation (number of citations received by authors; C/F=average citations received by authors.
Source: Author’s elaboration
Table 5. Most cited document
|
R |
Document Title |
Document Type |
Authors |
TC in Scopus |
TC in WOS |
TC Scopus+WOS |
Source |
|
1 |
Limits to community participation in the tourism development process in developing countries |
Journal Article |
Tosun (2000) |
650 |
543 |
1193 |
Tourism Management |
|
2 |
New directions in tourism for Third World development |
Journal Article |
Brohman (1996) |
482 |
371 |
853 |
Annals of Tourism Research |
|
3 |
Tourism routes as a tool for the economic development of rural areas - vibrant hope or impossible dream? |
Journal Article |
Briedenhann (2004) |
402 |
348 |
750 |
Tourism Management |
|
4 |
Expected nature of community participation in tourism development |
Journal Article |
Tosun (2006) |
329 |
303 |
632 |
Tourism Management |
|
5 |
Stakeholders in Sustainable Tourism Development and their Roles: Applying Stakeholder Theory to Sustainable Tourism Development |
Journal Article |
Byrd (2007) |
329 |
287 |
616 |
Tourism Review |
|
6 |
A Community-Based Tourism Model: Its Conception and Use |
Journal Article |
Okazaki (2008) |
272 |
292 |
564 |
Journal of Sustainable Tourism |
|
7 |
Residents’ attitudes toward sustainable community tourism |
Journal Article |
Choi (2010) |
283 |
265 |
548 |
Journal of Sustainable Tourism |
|
8 |
Community Participation in Tourism Planning |
Journal Article |
Simmons D.G. (1994) |
301 |
232 |
533 |
Tourism Management |
|
9 |
Community-based tourism ventures, benefits, and challenges: Khama Rhino Sanctuary Trust, Central District, Botswana |
Journal Article |
Sebele (2010) |
211 |
189 |
400 |
Tourism Management |
|
10 |
Volunteer tourism, development, and education in a postcolonial world: conceiving global connections beyond aid |
Journal Article |
Palacios (2010) |
204 |
189 |
393 |
Journal of Sustainable Tourism |
Note: R=rank; F=frequency (number of articles); TC=total citation (number of citations received by authors.
Source: Author’s elaboration
The document with the most citations is an article written by Cevat Tosun in 2000. It was cited 650 and 543 times on the Scopus and WOS databases. Generally, the ten documents with the most citations are articles without book chapters, proceedings, and reviews. Relatively 50% of the ten most-cited documents were published in Tourism Management journals.
An article by Tosun [31] and published in the journal Tourism Management discusses the normative concept of specific developmental approaches in developed countries. Specifically, it also describes the limitations of participatory tourism development in developing countries. Secondly, the article by Brohman [32] discussed the problems of community participation in tourism, especially in third-world countries. The third most cited document is an article by Briedenhann and Wickens [33], which outlined their opinion on developing rural routes and grouping activities capable of stimulating inter-regional cooperation. Additionally, it also reviews community participation in small-scale tourism development in less developed areas.
The fourth position is the second article written by Tosun [34], which is categorized as one of the ten most cited documents. A conceptual framework was developed based on the typology of community participation. The article written by Byrd [35] was ranked fifth as the most cited document. It discussed the management perspective and public participation in sustainable tourism. The sixth-ranked article was written by Okazaki [36], which reviewed theories in the discussion of community participation. In the seventh place, an article by Choi and Murray [37] examined the variables used in determining community attitudes in tourism development. Furthermore, in the eighth place, another article written by Simmons [38] is a report on the implementation and evaluation of a three-stage participation program by county residents. In the ninth place, an article by Sebele [39] is aimed to investigate the benefits and challenges of community-based tourism in Botswana. Lastly, an article written by Palacios [40] described the participation of Western youth in tourism development in developing nations.
3.4 Co-occurrence of author keywords
The co-occurrence of author keywords in bibliometrics analysis is useful for displaying certain study topics in a state-of-the-art manner [17] and providing information about documents in the database [26]. In addition, the 10 most used author keywords in the Scopus and WOS databases were analyzed.
There are 1,152 and 1,009 author keywords in the Scopus and WOS databases. The one with the highest coverage in both databases is community participation, namely 41.13% and 35.34% in the Scopus and WOS databases, respectively.
Based on Table 6, keyword occurrences in the first and second ranks of the Scopus and WOS databases have certain similarities, namely Community Participation and tourism. There are three unique keywords in these databases. In the Scopus database, three keywords are not included in the ten most used searches of the WOS, namely Community Development, Community, and Community Based Tourism. Meanwhile, in the WOS database, three keywords are not included in that of the Scopus, namely China, Participation, and tourism planning. China is the only keyword with a country name in the top 10 most used ones. The occurrence of China as a keyword indicates that it is an important country in the community participation discourse.
Table 6. Occurrences of author keywords
|
R |
Scopus |
|
|
WOS |
|
|
|
Keywords |
F |
C (%) |
Keywords |
F |
C (%) |
|
|
|
Community Participation |
188 |
41.13 |
Community Participation |
124 |
35.43 |
|
|
Tourism |
40 |
8.75 |
Tourism |
27 |
7.71 |
|
|
Sustainable Tourism |
40 |
8.75 |
Tourism Development |
24 |
6.86 |
|
|
Tourism Development |
33 |
7.22 |
Rural Tourism |
24 |
6.86 |
|
|
Ecotourism |
25 |
5.47 |
Sustainable Tourism |
23 |
6.57 |
|
|
Rural Tourism |
23 |
5.03 |
China |
20 |
5.71 |
|
|
Sustainability |
20 |
4.37 |
Tourism Planning |
19 |
5.43 |
|
|
Community Development |
19 |
4.15 |
Ecotourism |
17 |
4.86 |
|
|
Community |
18 |
3.93 |
Participation |
15 |
4.29 |
|
|
Community-Based Tourism |
18 |
3.93 |
Sustainability |
14 |
4.00 |
Note: R=rank; F=frequency (number of occurrences of keywords); C=coverage (percentage coverage of keywords in database).
Source: Author’s elaboration
3.5 Most productive country and institution
Document production analysis of a country is used to determine the level of productivity and number of citations. In the Scopus and WOS databases, China was ranked first with more than 13% coverage. The highest number of citations is the United Kingdom with 1,970 and 1,727 in the Scopus and WOS databases, respectively.
In the Scopus and WOS databases, 77 and 71 countries contributed, respectively. Country classification (United Nations, 2022) is used to discern the contributions of diverse nations. The results in Figure 3 show that publications related to tourism and community participation are dominated by developing countries, with a total of 48 and 41 contributor countries in the Scopus and WOS databases.
In addition to analyzing the country's productivity, and evaluation of the number of documents and citations in institutions was also performed. The results in Table 7 show that the University of Johannesburg has the most publications in the Scopus database. Meanwhile, in the WOS database, the University of Otago published the most documents related to tourism and community participation. The University of Sains Malaysia had the highest average citations of 280 per document in the Scopus database, while the University of Otago also had the highest average in the WOS database.
China's position as the most productive country in publications on community participation cannot be separated from its population, which is ranked first in the world until 2022. The USA, as a developed country, in several studies that apply country productivity comparisons, shows that it dominates various countries in terms of research [16, 17, 41]. Table 8 shows the most productive countries in terms of number of publications.
Table 7. Top 10 most productive institution
|
R |
Scopus |
|
WOS |
|
||||
|
Institution |
F |
TC |
TC/F |
Institution |
TP |
TC |
TC/F |
|
|
1. |
University Johannesburg |
16 |
272 |
17,0 |
University of Otago |
5 |
117 |
23,4 |
|
2. |
University Sains Malaysia |
12 |
549 |
45,8 |
Renmin University of China |
3 |
89 |
29,7 |
|
3. |
University Waterloo |
10 |
238 |
23,8 |
University of Botswana |
3 |
47 |
15,7 |
|
4. |
Lincoln University |
6 |
113 |
18,8 |
Durban University of Technology |
3 |
12 |
4,0 |
|
5. |
University Georgia |
6 |
219 |
36,5 |
University Johannesburg |
3 |
11 |
3,7 |
|
6. |
University Otago |
6 |
61 |
10,2 |
Sun Yat-Sen University |
3 |
7 |
2,3 |
|
7. |
University Teknologi Mara |
6 |
21 |
3,5 |
University of Botswana |
2 |
150 |
75,0 |
|
8. |
Bournemouth University |
5 |
440 |
88,0 |
Mzuzu University |
2 |
86 |
43,0 |
|
9. |
Texas A&M University |
5 |
334 |
66,8 |
University of Guelph |
2 |
42 |
21,0 |
|
10. |
University Botswana |
5 |
279 |
142 |
University of Chinese Academy of Sciences |
2 |
26 |
13,0 |
Note: R=rank; F=frequency (number of articles); TC=total citation (number of citations received by Institution); C/F=average citations received by Institution; C=coverage (percentage coverage paper by an institution in database); TC/F=Average citations received by authors/institutions.
Source: Author’s elaboration
Table 8. Most productive country based on the number of publications
|
R |
Scopus |
|
WOS |
|
||||||
|
Country |
F |
TC |
C/F |
Coverage % |
Country |
F |
TC |
C/F |
Coverage % |
|
|
|
China |
63 |
1265 |
20,1 |
13.79 |
China |
62 |
1237 |
20,0 |
13.57 |
|
|
USA |
54 |
1744 |
32,3 |
11.82 |
USA |
53 |
1400 |
26,4 |
11.60 |
|
|
South Africa |
49 |
392 |
8,0 |
10.72 |
England |
38 |
1727 |
45,4 |
8.32 |
|
|
United Kingdom |
48 |
1970 |
41,0 |
10.50 |
Malaysia |
36 |
804 |
22,3 |
7.88 |
|
|
Malaysia |
39 |
636 |
16,3 |
8.53 |
Australia |
35 |
1201 |
34,3 |
7.66 |
|
|
Canada |
32 |
1999 |
62,5 |
7.00 |
Canada |
28 |
899 |
32,1 |
6.13 |
|
|
Indonesia |
32 |
167 |
5,2 |
7.00 |
South Africa |
25 |
354 |
14,2 |
5.47 |
|
|
Australia |
25 |
1036 |
41,4 |
5.47 |
New Zealand |
13 |
304 |
23,4 |
2.84 |
|
|
Thailand |
23 |
143 |
6,2 |
5.03 |
India |
11 |
95 |
8,6 |
2.41 |
|
|
New Zealand |
20 |
785 |
39,3 |
4.38 |
Italy |
11 |
260 |
23,6 |
2.41 |
|
|
India |
19 |
63 |
3,3 |
4.16 |
Spain |
11 |
228 |
20,7 |
2.41 |
Note: R=rank; F=frequency (number of articles); TC=total citation (number of citation received by country); C/F=average citations received by country; C=coverage (percentage coverage paper by a country in database).
Source: Author’s elaboration
Figure 3. Distribution of contributing countries based on their categories related to tourism and community participation
Source: Author's Elaboration.
Bibliometric studies used to analyze scientific publications are important because they are able to provide information on its evolution, trends as well as compare the Scopus and WOS databases. This study aimed to carry out a bibliometric analysis of documents published in the Scopus and WOS databases.
The search results in both databases show that the trend of publications on tourism and community participation continues to increase even though related documents have been published since 1986 in Scopus. However, the publications made in the last five years have contributed more than 50% of the total number since the issuance of the first document. The publications related to tourism and community development in the WOS database were published in 1994, but in the last five years, there have been only 39%. Based on publication trends, Scopus has a faster growth rate and a more significant number of published documents.
In terms of singularities, Scopus has more unique documents. The level of duplication in the two databases included in this research is lower (23.96%) compared to other studies, for example, wine (34%) (Sánchez et al., 2017), community-based (43.54%) (lvarez-García et al., 2018) and tourism innovation (54.15%), (Durán-Sánchez et al., 2019). The higher the duplication level, the stronger the correlation between the two databases.
The most influential author is Tosun C, although he only produced four documents in each database. His high citation rate included two of his four documents in the ten most cited ones. Wall G is in first place among the top 10 most productive authors, but all the documents he produces are co-authorship documents. Furthermore, the occurrences of author keywords in both databases show that they have certain similarities. In the ten most used keywords, there are seven similar ones in each database.
In country and institutional analysis, China is the most productive country according to both databases. However, none of the ten most productive institutions in the Scopus list originated from China. Meanwhile, in the WOS database, two institutions emanated from China, namely, the Renmin University of China and the University of Chinese Academy of Sciences, which produced 3 and 2 documents, respectively. This indicates a uniform amount of productivity in institutions located in this country. Additionally, nations in the developing country category contributed the most to the discussion of tourism and community participation.
Although this study explored and compared two databases in the context of community participation, it has several limitations. First, this study only used two databases; future studies should use more than two. Second, bibliometric studies can be followed by a qualitative systematic literature review that examines each publication in more depth. Finally, several analyses in the context of bibliometric studies have yet to be elaborated upon in this study. In the future, it will be important to elaborate on all aspects of bibliometric studies to obtain more comprehensive results.
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