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: 22 Oct 2026 01:17 UTC — 22 Oct 2026 02:27 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 |
|---|---|---|---|---|---|
| 2021 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 11 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 12 | 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): 2026-10-22T01:17:21.361172+00:00 — 2026-10-22T02:27:13.911705+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 | 3 | 3 | 3/3 |
| 2025 | All selected publications | 5 | 3 | 3/3 |
| 2026 | All selected publications | 4 | 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 |
|---|---|
| 2021 | 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 Business Ecosystem & Strategy Bussecon International Academy | 1 | 5 | 4 | 1/1 | 5.0 | 5 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 6 | 8 | 2/2 | 3.0 | 3.0 | 100.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
Nowadays, the non-farm sector gives more attention and high expectations in reducing poverty in sub-Saharan African. Because participation of farm households in the none-farm sector out of their farm activities will play a great role to reduce poverty. Cross-sectional data were used to collect data in 2020 from farm household heads of 371 respondents with the mixed methodology to investigate the effect of demographic factors in none/off-farm economic activities on gender perspective in Ethiopia. In this study, we employ a Logistic regression model to explore the probabilities of household heads' participation in none/off-farm economic activities out of their farm. The result indicated, age and education level have a positive effect and statistically significant effect on increasing non-farm activities with the coefficients of 3.406, 1.956 respectively, confirmed that these variables should take into account in policy development to increase their impact on livelihood diversification. And Gender has a negatively significant on livelihood diversification. FHH is more participants in non-farm economic activities than MHH. Credit access does not contribute to increasing livelihood diversification instead; it contributes to agricultural specialization, not diversification. Surprisingly, family size has insignificant results in non-farm economic activities The outcome indicated it has its implications for the Ethiopian policy and strategy. The government should give more attention to the progressive aspects of non-farm economic activities to eradicate poverty. Whereas, decreasing its negative impact on poorer households by controlling obstacles of non-farm activities.
This study examines the effect of credit access on both agricultural and off-farm activities based on a household survey of 371 rural farmer respondents in Ethiopia.it was analyzed using a logistic regression model and statistical description. Findings demonstrated that the demographic factors; gender, age, level of education, and family size have a positive and significant effect on credit access. Agricultural credit access is impacted by each of the demographic variables as independent variables. On the other hand, the result indicated that the relationship between credit access and non-farm economic activities has a negative relationship. Credit access has a significant effect on agricultural intensification and specialization rather than diversification. Therefore, a comprehensive policy and strategy needs for credit access in both the agricultural and non-agricultural sectors. The Ethiopian government should follow the integration policy between both sectors and participate in livelihood diversification strategies and achieve sustainable development goals by 2030 at large.
There is a high expectation that urban-rural linkage in general and the function of small towns, in particular, has a great role in livelihood diversification and poverty reduction in rural areas than sectoral development. However, the previous empirical studies give little attention to the function of small towns and the livelihood diversification of rural communities. We analyze the function of a small town and participating in non-farm economic activities from a rural farm household survey of 371 farmer household heads in Ethiopia. The data was analyzed using a logistic regression model and statistical description. The study found that rural households who have road access have likely participated in none-farm activities and it has positive and significant effects. Education and FHH has also a significant relationship with the function of a small town. Distance from the small town has a significant and positive impact on the non-farm economic activities of rural communities. Overall, benefits from the function of small towns such as the provision of road access, agricultural extension, financial credit services, administrative services, educational and health services are some of the provisions of a small town. Therefore, a comprehensive integrated urban-rural linkage strategy could empower rural farm smallholders to diversify their livelihoods through strengthening small town functions is mandatory. The role of small towns needs to be integrated into rural communities. Participate in livelihood diversification strategies and achieve sustainable development goals by 2030 at large.
There is a high expectation that urban-rural linkage in general and the function of small towns, in particular, has a great role in livelihood diversification and poverty reduction in rural areas than sectoral development. However, the previous empirical studies give little attention to the function of small towns and the livelihood diversification of rural communities. We analyze the function of a small town and participating in non-farm economic activities from a rural farm household survey of 371 farmer household heads in Ethiopia. The data was analyzed using a logistic regression model and statistical description. The study found that rural households who have road access have likely participated in none-farm activities and it has positive and significant effects. Education and FHH has also a significant relationship with the function of a small town. Distance from the small town has a significant and positive impact on the non-farm economic activities of rural communities. Overall, benefits from the function of small towns such as the provision of road access, agricultural extension, financial credit services, administrative services, educational and health services are some of the provisions of a small town. Therefore, a comprehensive integrated urban-rural linkage strategy could empower rural farm smallholders to diversify their livelihoods through strengthening small town functions is mandatory. The role of small towns needs to be integrated into rural communities. Participate in livelihood diversification strategies and achieve sustainable development goals by 2030 at large.
This study examines the effect of credit access on both agricultural and off-farm activities based on a household survey of 371 rural farmer respondents in Ethiopia.it was analyzed using a logistic regression model and statistical description. Findings demonstrated that the demographic factors; gender, age, level of education, and family size have a positive and significant effect on credit access. Agricultural credit access is impacted by each of the demographic variables as independent variables. On the other hand, the result indicated that the relationship between credit access and non-farm economic activities has a negative relationship. Credit access has a significant effect on agricultural intensification and specialization rather than diversification. Therefore, a comprehensive policy and strategy needs for credit access in both the agricultural and non-agricultural sectors. The Ethiopian government should follow the integration policy between both sectors and participate in livelihood diversification strategies and achieve sustainable development goals by 2030 at large.
Nowadays, the non-farm sector gives more attention and high expectations in reducing poverty in sub-Saharan African. Because participation of farm households in the none-farm sector out of their farm activities will play a great role to reduce poverty. Cross-sectional data were used to collect data in 2020 from farm household heads of 371 respondents with the mixed methodology to investigate the effect of demographic factors in none/off-farm economic activities on gender perspective in Ethiopia. In this study, we employ a Logistic regression model to explore the probabilities of household heads' participation in none/off-farm economic activities out of their farm. The result indicated, age and education level have a positive effect and statistically significant effect on increasing non-farm activities with the coefficients of 3.406, 1.956 respectively, confirmed that these variables should take into account in policy development to increase their impact on livelihood diversification. And Gender has a negatively significant on livelihood diversification. FHH is more participants in non-farm economic activities than MHH. Credit access does not contribute to increasing livelihood diversification instead; it contributes to agricultural specialization, not diversification. Surprisingly, family size has insignificant results in non-farm economic activities The outcome indicated it has its implications for the Ethiopian policy and strategy. The government should give more attention to the progressive aspects of non-farm economic activities to eradicate poverty. Whereas, decreasing its negative impact on poorer households by controlling obstacles of non-farm activities.
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 |