Publication activity
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
Research across participating journals · All insights follow your collection filters.
Publication activity alongside incoming citations.
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Leading affiliations and themes in this collection.
Full distributions & methodology ↓Independent sources. Clear time scales.
Crossref and OpenAlex · separate totals for the same publication cohorts
Hover over a year or focus the chart and use arrow keys to inspect values.
Latest lifetime totals, grouped by the cited article’s year. These are not citations received in that year.
OpenAlex · incoming citation links grouped by citing-work year
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.
Articles by publication year
Latest lifetime totals · grouped by publication year
Latest lifetime totals · grouped by publication year
By year of the citing work · 2017–2026
2026 is year to date. Crossref and OpenAlex lifetime charts share a citation scale. Unknown observations appear as gaps; known zero stays zero. Annual receipts use available OpenAlex histories and may not sum to lifetime totals. 0 undated publications excluded from publication-year charts.
Crossref citation coverage: 5 / 5 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 UTC. Means and percentages use records with known counts.
DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.
Observation range: 21 Oct 2026 07:22 UTC — 22 Oct 2026 12:59 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.
OpenAlex affiliations and primary-topic classification. Each publication counts once per institution or country; multi-affiliated publications appear in multiple groups, so percentages can sum above 100%. Countries describe author affiliations, not nationality. Topics use one primary topic per publication.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
Citations are the latest recorded totals for articles published in each year, not citations received during that year. Crossref and OpenAlex remain separate and share the same citation scale. 2026 is incomplete; newer articles have had less time to receive citations.
0 undated publications excluded. Unknown citation counts are shown as —, never as zero. Partial coverage can understate totals; expand each table for known / total records.
| Publication year | Journal / scope | Publications | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 12 | 5 | 5/5 | 5/5 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 22 | 5 | 5/5 | 5/5 |
Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.
The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.
Annual history available for 5 / 5 selected publications. Supported display window: 2017–2026; 2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Missing histories and years beyond a saved observation’s window remain unknown (—); partial coverage can understate totals.
Annual-history observations (UTC): 2026-10-21T07:22:43.102851+00:00 — 2026-10-22T12:59:01.203396+00:00. Older observations may be retained after failed or incomplete refreshes.
| Citation year | Journal / scope | OpenAlex · Citations received by year | Publications | Annual history known |
|---|---|---|---|---|
| 2017 | All selected publications | 0 | 5 | 5/5 |
| 2018 | All selected publications | 0 | 5 | 5/5 |
| 2019 | All selected publications | 0 | 5 | 5/5 |
| 2020 | All selected publications | 0 | 5 | 5/5 |
| 2021 | All selected publications | 0 | 5 | 5/5 |
| 2022 | All selected publications | 0 | 5 | 5/5 |
| 2023 | All selected publications | 6 | 5 | 5/5 |
| 2024 | All selected publications | 8 | 5 | 5/5 |
| 2025 | All selected publications | 6 | 5 | 5/5 |
| 2026 | All selected publications | 2 | 5 | 5/5 |
Counts represent citation links, not unique citing papers across a journal: one paper citing two selected articles contributes two links. Older citations outside this window are excluded, so annual sums need not equal lifetime totals. OpenAlex methodology ↗
Publications by publication year. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2022 | 5 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| International Journal of Research in Business and Social Science SSBFNET | 5 | 12 | 22 | 5/5 | 2.4 | 1 | 60.0 | 5/5 · 100.0% |
* Percentage among publications with a known citation count.
In the context of cittaslow (slow city), this research attempts to examine the effects of memorable tourism experience (MTE) on tourist satisfaction and revisiting intention. The research used a structured questionnaire and collected 605 valid responses from tourists that visited Sanyi Cittaslow. Analyses of the measurement model and structural model by AMOS 22.0 were used to find the associations between each MTE dimension and satisfaction, and revisit intention. Test results revealed that all MTE dimensions are predictors of tourist satisfaction, among which knowledge and involvement are the strongest predictors; satisfaction is the strongest predictor for revisiting and is the mediator for the associations of most MTE dimensions and revisiting. Since the cittaslow movement was closely related to sustainable tourism, research finding from this research provide a good reference with evidence for the promotion of cittaslow through MTE creation.
This study seeks to measure the effectiveness of traditional media in promoting tourism in this digital age in KwaZulu-Natal, South Africa. This study employed a descriptive research design and a questionnaire was used to collect the data. The findings revealed that traditional and online media are more or less equally competitive in promoting tourism. Traditional media is still effective in promoting tourism in this digital age, especially in the domestic market. The study concluded and recommended that tourism marketers and authorities must come to terms with coexistence with traditional media and online media. There is no need to rely on one media to do it all. Where traditional media is lacking, online media must be there to make up for the difference and enhance the tourist experience.
The aim of this study is to determine smart governance, smart tourism, smart mobility, and smart sustainability are used by stakeholders in Lake Toba tourism objects to prepare smart tourism destinations (STD) for the effects of covid-19. This research is in line with the strategic plan of the Medan State University research which focuses on the development of tourism areas in North Sumatra. This study uses a Research and Development type with a basic-based research approach through needs analysis, model confirmation, and evaluation. Tourists that visited Lake Toba attractions in April 2022 were given questionnaires, and data were analyzed using pls-sem. The study shows that smart governance influences smart travel, smart tourism, and smart sustainability. On the other hand, smart mobility does not have a positive effect on smart sustainability, smart tourism has a positive and significant effect on smart sustainability. Overall, further research are needed to use other variables.
Tour operators have ensured the success of the Kenyan tourism sector, poised to contribute to achieving key government economic policies like the Tourism Agenda 2018-2022, the National Tourism Blueprint 2030, and the Big-Four Agenda. However, due to the volatility of the tourism industry, stiff competition, rigid tourism policies, and pandemics, tour operators’ performance has recorded a 2% steady decline since 2011. Therefore, this paper explores the upscaling of performance using a differentiation strategy among tour operator companies in Nairobi City County. The study followed a descriptive design approach, with the balanced scorecard and Porter’s generic strategies forming the theoretical basis. Fifteen (15) company owners and 210 managers participated in the study. Data were collected using structured questionnaires and interviews. Stratified simple random sampling was used to sample respondents from the companies while purposive sampling was used to select company owners. Data collected were analyzed in SPSS (Ver.26) using descriptive statistics to infer variable characteristics. Inferential statistics; Pearson correlation, ANOVA, and simple linear regression were used to detect the strength of the relationship and test the hypothesis. Correlation analysis revealed a strong positive relationship between differentiation strategy and organizational performance (r=0.77, P=0.000), leading to the rejection of the null hypothesis. Regression analysis revealed an adjusted R2(0.602) indicating that differentiation strategy explains 60.2% of organizational performance’s variation (b=0.594, P=.000). The study recommends that tour operator companies should develop innovative packages based on place and price and significantly invest in R&D to enhance a strong brand for optimal performance. This study provides policymakers with an avenue to scrutinize levels of organizational performance using a strategic management approach.
Sustainable tourism has emerged as a growing tourism facet in recent years, gaining acceptance among tourism developers and stakeholders; as a tourism development model that is economically viable, socially acceptable, and environmentally friendly. Nonetheless, tourism development faces numerous challenges, including displacement of people, cultural commercialization, organic dilapidation, and economic dependency resulting from social-economic development. As a result, many countries have begun to embrace long-term sustainable tourism development goals, an essential component of achieving Vision 2030. Therefore, this paper propagates the discussions surrounding corroboration approaches, tourism infrastructure, stakeholders' role, and government policies' influence on sustainable tourism development. To support its thesis, the paper develops a conceptual framework to guide tourism practitioners and other stakeholders in understanding and dissecting sustainable tourism models and knowledge. The findings emphasize stakeholders’ collaboration framework, the need for adequate and supportive tourism infrastructure, and the foundational basis of public-private initiatives to enhance tourism growth.
Tour operators have ensured the success of the Kenyan tourism sector, poised to contribute to achieving key government economic policies like the Tourism Agenda 2018-2022, the National Tourism Blueprint 2030, and the Big-Four Agenda. However, due to the volatility of the tourism industry, stiff competition, rigid tourism policies, and pandemics, tour operators’ performance has recorded a 2% steady decline since 2011. Therefore, this paper explores the upscaling of performance using a differentiation strategy among tour operator companies in Nairobi City County. The study followed a descriptive design approach, with the balanced scorecard and Porter’s generic strategies forming the theoretical basis. Fifteen (15) company owners and 210 managers participated in the study. Data were collected using structured questionnaires and interviews. Stratified simple random sampling was used to sample respondents from the companies while purposive sampling was used to select company owners. Data collected were analyzed in SPSS (Ver.26) using descriptive statistics to infer variable characteristics. Inferential statistics; Pearson correlation, ANOVA, and simple linear regression were used to detect the strength of the relationship and test the hypothesis. Correlation analysis revealed a strong positive relationship between differentiation strategy and organizational performance (r=0.77, P=0.000), leading to the rejection of the null hypothesis. Regression analysis revealed an adjusted R2(0.602) indicating that differentiation strategy explains 60.2% of organizational performance’s variation (b=0.594, P=.000). The study recommends that tour operator companies should develop innovative packages based on place and price and significantly invest in R&D to enhance a strong brand for optimal performance. This study provides policymakers with an avenue to scrutinize levels of organizational performance using a strategic management approach.
This study seeks to measure the effectiveness of traditional media in promoting tourism in this digital age in KwaZulu-Natal, South Africa. This study employed a descriptive research design and a questionnaire was used to collect the data. The findings revealed that traditional and online media are more or less equally competitive in promoting tourism. Traditional media is still effective in promoting tourism in this digital age, especially in the domestic market. The study concluded and recommended that tourism marketers and authorities must come to terms with coexistence with traditional media and online media. There is no need to rely on one media to do it all. Where traditional media is lacking, online media must be there to make up for the difference and enhance the tourist experience.
Sustainable tourism has emerged as a growing tourism facet in recent years, gaining acceptance among tourism developers and stakeholders; as a tourism development model that is economically viable, socially acceptable, and environmentally friendly. Nonetheless, tourism development faces numerous challenges, including displacement of people, cultural commercialization, organic dilapidation, and economic dependency resulting from social-economic development. As a result, many countries have begun to embrace long-term sustainable tourism development goals, an essential component of achieving Vision 2030. Therefore, this paper propagates the discussions surrounding corroboration approaches, tourism infrastructure, stakeholders' role, and government policies' influence on sustainable tourism development. To support its thesis, the paper develops a conceptual framework to guide tourism practitioners and other stakeholders in understanding and dissecting sustainable tourism models and knowledge. The findings emphasize stakeholders’ collaboration framework, the need for adequate and supportive tourism infrastructure, and the foundational basis of public-private initiatives to enhance tourism growth.
The aim of this study is to determine smart governance, smart tourism, smart mobility, and smart sustainability are used by stakeholders in Lake Toba tourism objects to prepare smart tourism destinations (STD) for the effects of covid-19. This research is in line with the strategic plan of the Medan State University research which focuses on the development of tourism areas in North Sumatra. This study uses a Research and Development type with a basic-based research approach through needs analysis, model confirmation, and evaluation. Tourists that visited Lake Toba attractions in April 2022 were given questionnaires, and data were analyzed using pls-sem. The study shows that smart governance influences smart travel, smart tourism, and smart sustainability. On the other hand, smart mobility does not have a positive effect on smart sustainability, smart tourism has a positive and significant effect on smart sustainability. Overall, further research are needed to use other variables.
In the context of cittaslow (slow city), this research attempts to examine the effects of memorable tourism experience (MTE) on tourist satisfaction and revisiting intention. The research used a structured questionnaire and collected 605 valid responses from tourists that visited Sanyi Cittaslow. Analyses of the measurement model and structural model by AMOS 22.0 were used to find the associations between each MTE dimension and satisfaction, and revisit intention. Test results revealed that all MTE dimensions are predictors of tourist satisfaction, among which knowledge and involvement are the strongest predictors; satisfaction is the strongest predictor for revisiting and is the mediator for the associations of most MTE dimensions and revisiting. Since the cittaslow movement was closely related to sustainable tourism, research finding from this research provide a good reference with evidence for the promotion of cittaslow through MTE creation.
Source coverage refers to this result set; a publication may occur in several sources. Sync times refer to contributing journals.
Missing abstracts: 0 · Missing authors: 0 · Missing publication dates: 0 · Dates without day precision: 0
| Source | Most recent successful journal sync | Latest attempt |
|---|---|---|
| crossref | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |
| ojs-rest | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 06:46 UTC |
| oai-pmh | 20 Oct 2026 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |