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: 4 / 4 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 08:07 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.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 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 |
|---|---|---|---|---|---|
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 9 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 6 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
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 4 / 4 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): 2026-10-21T07:22:58.482660+00:00 — 2026-10-22T08:07:48.369441+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 | 4 | 4/4 |
| 2018 | All selected publications | 0 | 4 | 4/4 |
| 2019 | All selected publications | 0 | 4 | 4/4 |
| 2020 | All selected publications | 0 | 4 | 4/4 |
| 2021 | All selected publications | 2 | 4 | 4/4 |
| 2022 | All selected publications | 2 | 4 | 4/4 |
| 2023 | All selected publications | 2 | 4 | 4/4 |
| 2024 | All selected publications | 5 | 4 | 4/4 |
| 2025 | All selected publications | 3 | 4 | 4/4 |
| 2026 | All selected publications | 3 | 4 | 4/4 |
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 |
|---|---|
| 2020 | 1 |
| 2021 | 1 |
| 2024 | 2 |
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 | 4 | 7 | 17 | 4/4 | 1.75 | 2.0 | 75.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
The analysis aims to empirically the role of resilience towards burnout through mindfulness in money management firms in Jakarta-Indonesia. The participants of this study were 250 workers from the money management company in Jakarta-Indonesia. The method of data assortment uses the instrument burnout scale, resiliency scale, and mindfulness scale. Variable intervening is employed to realize direct and indirect influence. Information analysis techniques in analysis exploitation the ways of applied statistical descriptive and exploitation Amos version twenty-four. There are four hypotheses projected during this study. The results showed that the role of mindfulness important as a go-between to reduced burnout
Healthcare delivery relies on human resource management to ensure quality. However, employee performance dropped from 2019 to 2022, highlighting the need to address job fatigue, which lowers performance. This study examines how mindfulness and emotional intelligence mediate the effects of occupational fatigue on medical and paramedic performance. This integrated study intends to understand healthcare job performance and improve medical professionals' competency and well-being in Indonesia. A 5% margin of error was used to choose 213 medical staff and paramedics from the Mojokerto City Government Health Agency in Indonesia using the Slovin algorithm. The Sobel Test and SEM with AMOS were used to analyse data. Mindfulness and emotional intelligence decreased considerably with job burnout, affecting job performance. Mindfulness and emotional intelligence also improved job performance. The results also showed that emotional intelligence and mindfulness moderate the job burnout-performance link. These findings show that emotional and psychological aspects are crucial to understanding how job fatigue affects employee performance.
Burnout is a condition of mental, and physical fatigue of a worker caused by a person's professional life. Engagement is the attachment that exists in an employee to a job where the employee works. The relationship between burnout and engagement in a company significantly affects the employees' performance and the company's results. This study aims to digitally record burnout, and engagement that exists in a company in improving its product quality. Digital-based monitoring is one of the tools that can be used to monitor employee performance activities in a measured manner to produce information that companies can use in decision-making. The method used quantitative research method approach using LISREL. Results achieved several variables that affect burnout and engagement related to employee work at that company. Implications for companies with the existence of employee digital data minimize burnout and increase employee engagement in the company. This digital data can be used as accurate information in looking at the condition of employees in a company.
The study examines burnout and the factors that influence it, namely job satisfaction and well-being as mediators or intervening. This study used a descriptive quantitative approach to test three hypotheses, a data collection tool using a psychological scale. To collect research data, the authors adopted sources adapted to local culture and developed research instruments using psychological scales with Likert type. For data analysis, use SPSS and SEM-PLS. The research finding is that job satisfaction can directly affect burnout and indirectly, from job satisfaction to well-being (as an intervening variable), then to burnout. The magnitude of direct influence is 0.135, while the magnitude of indirect influence is 0.540. Since the coefficient of an indirect relationship is greater than that of a direct relationship, the actual relationship is indirect. Thus, the role of well-being as a mediator function optimally or fully.
Healthcare delivery relies on human resource management to ensure quality. However, employee performance dropped from 2019 to 2022, highlighting the need to address job fatigue, which lowers performance. This study examines how mindfulness and emotional intelligence mediate the effects of occupational fatigue on medical and paramedic performance. This integrated study intends to understand healthcare job performance and improve medical professionals' competency and well-being in Indonesia. A 5% margin of error was used to choose 213 medical staff and paramedics from the Mojokerto City Government Health Agency in Indonesia using the Slovin algorithm. The Sobel Test and SEM with AMOS were used to analyse data. Mindfulness and emotional intelligence decreased considerably with job burnout, affecting job performance. Mindfulness and emotional intelligence also improved job performance. The results also showed that emotional intelligence and mindfulness moderate the job burnout-performance link. These findings show that emotional and psychological aspects are crucial to understanding how job fatigue affects employee performance.
The study examines burnout and the factors that influence it, namely job satisfaction and well-being as mediators or intervening. This study used a descriptive quantitative approach to test three hypotheses, a data collection tool using a psychological scale. To collect research data, the authors adopted sources adapted to local culture and developed research instruments using psychological scales with Likert type. For data analysis, use SPSS and SEM-PLS. The research finding is that job satisfaction can directly affect burnout and indirectly, from job satisfaction to well-being (as an intervening variable), then to burnout. The magnitude of direct influence is 0.135, while the magnitude of indirect influence is 0.540. Since the coefficient of an indirect relationship is greater than that of a direct relationship, the actual relationship is indirect. Thus, the role of well-being as a mediator function optimally or fully.
Burnout is a condition of mental, and physical fatigue of a worker caused by a person's professional life. Engagement is the attachment that exists in an employee to a job where the employee works. The relationship between burnout and engagement in a company significantly affects the employees' performance and the company's results. This study aims to digitally record burnout, and engagement that exists in a company in improving its product quality. Digital-based monitoring is one of the tools that can be used to monitor employee performance activities in a measured manner to produce information that companies can use in decision-making. The method used quantitative research method approach using LISREL. Results achieved several variables that affect burnout and engagement related to employee work at that company. Implications for companies with the existence of employee digital data minimize burnout and increase employee engagement in the company. This digital data can be used as accurate information in looking at the condition of employees in a company.
The analysis aims to empirically the role of resilience towards burnout through mindfulness in money management firms in Jakarta-Indonesia. The participants of this study were 250 workers from the money management company in Jakarta-Indonesia. The method of data assortment uses the instrument burnout scale, resiliency scale, and mindfulness scale. Variable intervening is employed to realize direct and indirect influence. Information analysis techniques in analysis exploitation the ways of applied statistical descriptive and exploitation Amos version twenty-four. There are four hypotheses projected during this study. The results showed that the role of mindfulness important as a go-between to reduced burnout
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 |