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: 2 / 2 publications (100.0%). Latest observation: 21 Oct 2026, 00:14 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 00:14 UTC — 21 Oct 2026 00:14 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.
2 / 2 with data · 0 missing or unmatched. Percentages use all 2 selected publications.
2 / 2 with data · 0 missing or unmatched. Percentages use all 2 selected publications.
2 / 2 with data · 0 missing or unmatched. Percentages use all 2 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 |
|---|---|---|---|---|---|
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
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 2 / 2 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): 2026-10-21T00:14:32.869875+00:00 — 2026-10-21T00:14:36.454005+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 | 2 | 2/2 |
| 2018 | All selected publications | 0 | 2 | 2/2 |
| 2019 | All selected publications | 0 | 2 | 2/2 |
| 2020 | All selected publications | 0 | 2 | 2/2 |
| 2021 | All selected publications | 0 | 2 | 2/2 |
| 2022 | All selected publications | 0 | 2 | 2/2 |
| 2023 | All selected publications | 0 | 2 | 2/2 |
| 2024 | All selected publications | 0 | 2 | 2/2 |
| 2025 | All selected publications | 0 | 2 | 2/2 |
| 2026 | All selected publications | 0 | 2 | 2/2 |
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 |
|---|---|
| 2025 | 1 |
| 2026 | 1 |
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 Business Ecosystem & Strategy Bussecon International Academy | 2 | 0 | 0 | 2/2 | 0.0 | 0.0 | 0.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
Agriculture has advanced from subsistence farming to a dynamic, market-oriented sector fuelled by agripreneurship. The use of modern technology, such as artificial intelligence, the Internet of Things, and precision farming, is changing agricultural productivity and sustainability. Despite these developments, the adoption of such technology by agripreneurs remains unequal, particularly in developing countries. Structural inequities, limited access to resources, and insufficient technical skills continue to impede the efficient use of technology. The study adopted a qualitative desktop review to analyse the existing literature on integrated technologies to increase agripreneurship productivity. The secondary data sources were journal articles, online books and government reports. The timeframe of the included data ranges from 2018 to 2026, while data from 2017 and earlier were excluded. Lastly, keywords such as agripreneurship and integrated technologies were used to search for data across sources, including Google Scholar and Web of Science. The findings show that integrated technologies improve agricultural output, efficiency, and resource optimisation among agripreneurs. The study also found that perceived usefulness substantially influences readiness to accept technology, although perceived ease of use remains a significant issue due to insufficient technical abilities. Furthermore, extrinsic problems such as poor infrastructure, budgetary constraints, and insufficient institutional backing impede wider adoption. Based on the Technology Acceptability Model, the findings show that tackling these hurdles is critical to improving technology acceptability and maximising agribusiness outcomes. The integration of technology into agripreneurship plays an important role in mitigating socio-economic challenges by creating jobs, boosting the local economy, and helping agripreneurs manage their farms effectively. Various technologies are adopted to minimise the impacts of climate change, improve pest control, and increase productivity and efficiency.
This study evaluates the barriers to employment among beneficiaries of the Youth Entrepreneurship and Agribusiness Support (YEASA) program in Ekiti State, Nigeria. Using quantitative descriptive and inferential methods, the study investigates how the YEASA program influences employment, local economic development, and participants’ quality of life. A purposive sample of 125 beneficiaries provided data through structured questionnaires analyzed with SPSS. Findings reveal that 94% of participants acknowledged YEASA’s contribution to job creation, 85% reported improved living standards, and 90% noted increased confidence in managing agribusiness ventures. Despite these achievements, systemic barriers persist—particularly limited funding (55% dissatisfaction) and weak market linkages (60% concern)—which hinder the program’s overall impact. The study recommends improved funding mechanisms, stronger government involvement, and the introduction of tailor-made training programs to enhance sustainability and entrepreneurial outcomes among youth.
Agriculture has advanced from subsistence farming to a dynamic, market-oriented sector fuelled by agripreneurship. The use of modern technology, such as artificial intelligence, the Internet of Things, and precision farming, is changing agricultural productivity and sustainability. Despite these developments, the adoption of such technology by agripreneurs remains unequal, particularly in developing countries. Structural inequities, limited access to resources, and insufficient technical skills continue to impede the efficient use of technology. The study adopted a qualitative desktop review to analyse the existing literature on integrated technologies to increase agripreneurship productivity. The secondary data sources were journal articles, online books and government reports. The timeframe of the included data ranges from 2018 to 2026, while data from 2017 and earlier were excluded. Lastly, keywords such as agripreneurship and integrated technologies were used to search for data across sources, including Google Scholar and Web of Science. The findings show that integrated technologies improve agricultural output, efficiency, and resource optimisation among agripreneurs. The study also found that perceived usefulness substantially influences readiness to accept technology, although perceived ease of use remains a significant issue due to insufficient technical abilities. Furthermore, extrinsic problems such as poor infrastructure, budgetary constraints, and insufficient institutional backing impede wider adoption. Based on the Technology Acceptability Model, the findings show that tackling these hurdles is critical to improving technology acceptability and maximising agribusiness outcomes. The integration of technology into agripreneurship plays an important role in mitigating socio-economic challenges by creating jobs, boosting the local economy, and helping agripreneurs manage their farms effectively. Various technologies are adopted to minimise the impacts of climate change, improve pest control, and increase productivity and efficiency.
This study evaluates the barriers to employment among beneficiaries of the Youth Entrepreneurship and Agribusiness Support (YEASA) program in Ekiti State, Nigeria. Using quantitative descriptive and inferential methods, the study investigates how the YEASA program influences employment, local economic development, and participants’ quality of life. A purposive sample of 125 beneficiaries provided data through structured questionnaires analyzed with SPSS. Findings reveal that 94% of participants acknowledged YEASA’s contribution to job creation, 85% reported improved living standards, and 90% noted increased confidence in managing agribusiness ventures. Despite these achievements, systemic barriers persist—particularly limited funding (55% dissatisfaction) and weak market linkages (60% concern)—which hinder the program’s overall impact. The study recommends improved funding mechanisms, stronger government involvement, and the introduction of tailor-made training programs to enhance sustainability and entrepreneurial outcomes among youth.
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 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |
| ojs-rest | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:02 UTC |
| oai-pmh | 20 Oct 2026 19:49 UTC · ijbes | complete · ijbes · 20 Oct 2026 19:48 UTC |
| openalex-enrichment | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |