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: 3 / 3 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 — 28 Oct 2026 23:50 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.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 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 | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 0 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 0 | 3 | 3/3 | 3/3 |
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 3 / 3 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): 2026-10-21T07:22:43.956819+00:00 — 2026-10-28T23:50:51.823969+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 | 3 | 3/3 |
| 2018 | All selected publications | 0 | 3 | 3/3 |
| 2019 | All selected publications | 0 | 3 | 3/3 |
| 2020 | All selected publications | 0 | 3 | 3/3 |
| 2021 | All selected publications | 0 | 3 | 3/3 |
| 2022 | All selected publications | 0 | 3 | 3/3 |
| 2023 | All selected publications | 0 | 3 | 3/3 |
| 2024 | All selected publications | 0 | 3 | 3/3 |
| 2025 | All selected publications | 0 | 3 | 3/3 |
| 2026 | All selected publications | 0 | 3 | 3/3 |
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 | 3 |
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 | 3 | 0 | 0 | 3/3 | 0.0 | 0 | 0.0 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
This study aims to determine the influence of work specialization on realization of superordinate goals in selected NGOs in Naivasha sub-county, Kenya. The study was underpinned by the systems-thinking and McKinsey’s 7s models. A descriptive survey research design was adopted. The target population consisted of 120 managers and members of the board of directors of eight NGOs in the Naivasha sub-county, Kenya. Using the Krejcie and Morgan formula and the stratified sampling technique, 92 respondents were selected to participate in the study. The research instrument was a self-administered questionnaire consisting of closed and open-ended questions. The thematic analysis method was used for qualitative data analysis, presented using narratives, while quantitative data was analyzed using frequencies and percentages. Inferential statistics analysis involved Pearson correlation and multiple linear regression analysis in establishing the relationship between work specialization and the realization of superordinate goals. The data was presented using tables. Research ethics were upheld when carrying out the study. This study found that work specialization had a statistically significant relationship with realization of superordinate goals in selected NGOs in Naivasha Sub-county, Kenya. Also, work specialization had a statistically significant influence on the realization of superordinate goals in selected NGOs in the Naivasha sub-county, Kenya, with a p-value of (p<0.05). This study recommends that a similar study be conducted to get other employees' and NGO beneficiaries’ perspectives on work specialization and realization of superordinate goals. The findings of this study will help NGOs to understand the cruciality of work specialization elements in realization of superordinate goals.
Mental health is an important developmental aspect of any society. This study sought to assess the effect of the county legal framework on the implementation of mental health programmes in Nakuru County. The study was guided by the General Systems Theory. A descriptive survey design was used which involved a mixed-methods approach. The target population was the 80 respondents who are directly associated with the implementation of mental health programmes in Nakuru County. Due to the small population, a census procedure was utilized. Primary data was collected through the use of a questionnaire and interview guide. Quantitative data was analyzed through the SPSS software (v25). Descriptive statistics were analyzed through the use of frequencies and percentages while inferential statistics were analyzed through the Pearson Correlation and linear regression analysis and the findings were presented in form of tables. The qualitative data were analyzed thematically and presented through narratives. The study found that the county legal framework had a positive relationship with the implementation of mental health programmes in Nakuru County, Kenya (r=0.428; p=0.000). The county legal framework positively and significantly affected the implementation of mental health programmes in Nakuru County, Kenya. Also, improving the county's legal framework would have a positive impact on the implementation of mental health programmes in Nakuru County, Kenya. This study recommends that a study should be conducted on the implementation of mental health programmes focusing on the service-users of mental health services and programmes in county governments in Kenya. It is hoped that the findings of this study will increase awareness of mental health services in the county as well as help policymakers formulate effective policies and strategies on mental health programmes, services and public service delivery in Nakuru County.
Team diversity management helps to improve the cohesion of a team and ultimately, organizational development is enhanced. The purpose of this study was to determine the effect of team diversity management on team cohesion at St. Martin Catholic Social Apostolate, Kenya. The study adopted a descriptive research design. The target population for the study was 115 employees at the St. Martin Catholic Social Apostolate in Kenya. Stratified and simple random sampling procedures were used to sample 92 employees. Data was collected using a questionnaire and the collected data was analyzed through the use of the Statistical Package for Social Scientists (SPSS) version 21. Descriptive statistical analysis involved the calculation of percentages and frequencies while inferential statistical analysis involved Pearson correlation in establishing the association of the variables under investigation. and Chi-square tests. Data was presented in the form of tables and charts. Qualitative data were analysed thematically and presented in the form of narratives. The study ensured that ethical considerations were adhered to. The study found a statistically significant relationship between team diversity management and team cohesion (p<0.05). The study concludes that each team member is held accountable for their activities and the decisions they make regarding the team and is included in team activities. The study recommends that the team leaders ensure that all team members are included in all team activities. This can be achieved through creating environments and opportunities that allow the team members to provide their opinions openly.
This study aims to determine the influence of work specialization on realization of superordinate goals in selected NGOs in Naivasha sub-county, Kenya. The study was underpinned by the systems-thinking and McKinsey’s 7s models. A descriptive survey research design was adopted. The target population consisted of 120 managers and members of the board of directors of eight NGOs in the Naivasha sub-county, Kenya. Using the Krejcie and Morgan formula and the stratified sampling technique, 92 respondents were selected to participate in the study. The research instrument was a self-administered questionnaire consisting of closed and open-ended questions. The thematic analysis method was used for qualitative data analysis, presented using narratives, while quantitative data was analyzed using frequencies and percentages. Inferential statistics analysis involved Pearson correlation and multiple linear regression analysis in establishing the relationship between work specialization and the realization of superordinate goals. The data was presented using tables. Research ethics were upheld when carrying out the study. This study found that work specialization had a statistically significant relationship with realization of superordinate goals in selected NGOs in Naivasha Sub-county, Kenya. Also, work specialization had a statistically significant influence on the realization of superordinate goals in selected NGOs in the Naivasha sub-county, Kenya, with a p-value of (p<0.05). This study recommends that a similar study be conducted to get other employees' and NGO beneficiaries’ perspectives on work specialization and realization of superordinate goals. The findings of this study will help NGOs to understand the cruciality of work specialization elements in realization of superordinate goals.
Mental health is an important developmental aspect of any society. This study sought to assess the effect of the county legal framework on the implementation of mental health programmes in Nakuru County. The study was guided by the General Systems Theory. A descriptive survey design was used which involved a mixed-methods approach. The target population was the 80 respondents who are directly associated with the implementation of mental health programmes in Nakuru County. Due to the small population, a census procedure was utilized. Primary data was collected through the use of a questionnaire and interview guide. Quantitative data was analyzed through the SPSS software (v25). Descriptive statistics were analyzed through the use of frequencies and percentages while inferential statistics were analyzed through the Pearson Correlation and linear regression analysis and the findings were presented in form of tables. The qualitative data were analyzed thematically and presented through narratives. The study found that the county legal framework had a positive relationship with the implementation of mental health programmes in Nakuru County, Kenya (r=0.428; p=0.000). The county legal framework positively and significantly affected the implementation of mental health programmes in Nakuru County, Kenya. Also, improving the county's legal framework would have a positive impact on the implementation of mental health programmes in Nakuru County, Kenya. This study recommends that a study should be conducted on the implementation of mental health programmes focusing on the service-users of mental health services and programmes in county governments in Kenya. It is hoped that the findings of this study will increase awareness of mental health services in the county as well as help policymakers formulate effective policies and strategies on mental health programmes, services and public service delivery in Nakuru County.
Team diversity management helps to improve the cohesion of a team and ultimately, organizational development is enhanced. The purpose of this study was to determine the effect of team diversity management on team cohesion at St. Martin Catholic Social Apostolate, Kenya. The study adopted a descriptive research design. The target population for the study was 115 employees at the St. Martin Catholic Social Apostolate in Kenya. Stratified and simple random sampling procedures were used to sample 92 employees. Data was collected using a questionnaire and the collected data was analyzed through the use of the Statistical Package for Social Scientists (SPSS) version 21. Descriptive statistical analysis involved the calculation of percentages and frequencies while inferential statistical analysis involved Pearson correlation in establishing the association of the variables under investigation. and Chi-square tests. Data was presented in the form of tables and charts. Qualitative data were analysed thematically and presented in the form of narratives. The study ensured that ethical considerations were adhered to. The study found a statistically significant relationship between team diversity management and team cohesion (p<0.05). The study concludes that each team member is held accountable for their activities and the decisions they make regarding the team and is included in team activities. The study recommends that the team leaders ensure that all team members are included in all team activities. This can be achieved through creating environments and opportunities that allow the team members to provide their opinions openly.
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 |