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: 6 / 6 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 02:17 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.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 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 | 2 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 6 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 4 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 8 | 2 | 2/2 | 2/2 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 5 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 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 6 / 6 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): 2026-10-21T07:22:49.808268+00:00 — 2026-10-22T02:17:24.716186+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 | 6 | 6/6 |
| 2018 | All selected publications | 0 | 6 | 6/6 |
| 2019 | All selected publications | 0 | 6 | 6/6 |
| 2020 | All selected publications | 0 | 6 | 6/6 |
| 2021 | All selected publications | 0 | 6 | 6/6 |
| 2022 | All selected publications | 0 | 6 | 6/6 |
| 2023 | All selected publications | 0 | 6 | 6/6 |
| 2024 | All selected publications | 3 | 6 | 6/6 |
| 2025 | All selected publications | 7 | 6 | 6/6 |
| 2026 | All selected publications | 3 | 6 | 6/6 |
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 | 2 |
| 2023 | 2 |
| 2024 | 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 Research in Business and Social Science SSBFNET | 6 | 10 | 13 | 6/6 | 1.67 | 0.5 | 50.0 | 6/6 · 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.
Cassava (Manihot esculenta Crantz) has remained a major source of food security and income generation for most developing countries including Tanzania due to its ability to drought and disease resistance. At present, its production in Tanzania stands at 630,000 tons while the country's market demand is expected to grow at 7% by 2026. Therefore, this study assessed the contribution of cassava production and marketing on the livelihood of smallholder farmers in Tanzania particularly in the Dodoma region, so as to explore its potential contributions to the society welfare. A cross-sectional research design was employed whereby a multi-stage sampling procedure was used in selecting a sample of 240 cassava smallholder farmers from four districts in the Dodoma region namely Kondoa, Chemba, Kongwa, and Mpwapwa. Quantitative data were collected through self-administered structured questionnaires and focus group discussion, interview and observation methods also were used in collecting qualitative data from the study area. Content analysis was used in analyzing qualitative data. A binary logistic regression model was employed to estimate the contribution of cassava production and marketing on smallholder farmers’ livelihoods in the region. The findings from the study indicated that family size, farmers’ experience, land size, education, number of visits by extension, and market access statistically were significant with showed a positive relationship with the improvement in the livelihood of farmers in the selected districts. On the other hand, transportation costs showed a negative relation with the improvement of farmers’ livelihood. Generally, it can be concluded that an increase in production and improvement in marketing variables could contribute much to the improvement of smallholder farmers’ livelihood. Based on these findings, it is recommended that Ministries responsible for cassava production and marketing which included the Ministry of Agriculture and the Ministry of Industry and Trade focus more on the design, promotion, and implementation of policies and programs that are intended to enhance cassava production in rural areas and increase the provision of best farming practices through employing more extension officers.
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.
Smallholder agriculture is crucial for sustaining rural livelihoods across South Africa; nevertheless, involvement in global value chains (GVCs) is still restricted. This study examines the socio-economic determinants affecting the incorporation of smallholder maize farmers into global value chains in the Eastern Cape, a region marked by significant rural poverty and dependence on agriculture. The study evaluates the engagement levels of 200 farmers by a cross-sectional survey and multinomial logistic regression analysis. Findings indicate that elevated education levels and income substantially enhance the probability of moderate involvement in value chains; yet, no farmers attained complete participation owing to institutional impediments, including the absence of export permits. These findings indicate that human characteristics alone are inadequate; structural barriers are also essential. The report advocates for structural reforms, particularly those aimed at enhancing education, broadening market access, and eliminating licensing obstacles, to foster inclusive and sustainable participation of smallholder farmers in global value chains.
The poultry industry is the fasted growing sub-sector of agriculture in the developing world and this is attributed to several pulling and pushing factors. On the demand side, the issue of urbanisation, income increase and animal protein requirements particularly for chicken has a positive influence on the growth of poultry production. Poultry farming is highly practised in rural households in Lesotho, and it constitutes an important contribution to the development of the rural economy in most developing countries. The poultry industry remains an important sub-sector of agriculture like in many other developing countries and it remains the main source of livelihood for village people and other small-scale farmers in the economy. Many rural communities are keeping poultry as a source of meat and eggs to feed their families, raise income from the surplus and create employment opportunities. However, access to formals markets remains a critical challenge for the farmers. This study examined the socio-economic, market and institutional factors that influenced broiler farmers’ market participation and intensity of participation in the Leribe district in Lesotho. A two-stage sampling technique was employed to select 114 respondents from five villages and the survey data was collected through a structured questionnaire. Heckman's two-stage model was used to analyse factors influencing farmers' market participation and the intensity of market participation. Gender, farmer income, storage access, production experience, extension service, credit access and information access were significant and influenced farmers’ market participation decisions. The study recommends interventions that will increase access and formal market participation.
Smallholder agriculture is crucial for sustaining rural livelihoods across South Africa; nevertheless, involvement in global value chains (GVCs) is still restricted. This study examines the socio-economic determinants affecting the incorporation of smallholder maize farmers into global value chains in the Eastern Cape, a region marked by significant rural poverty and dependence on agriculture. The study evaluates the engagement levels of 200 farmers by a cross-sectional survey and multinomial logistic regression analysis. Findings indicate that elevated education levels and income substantially enhance the probability of moderate involvement in value chains; yet, no farmers attained complete participation owing to institutional impediments, including the absence of export permits. These findings indicate that human characteristics alone are inadequate; structural barriers are also essential. The report advocates for structural reforms, particularly those aimed at enhancing education, broadening market access, and eliminating licensing obstacles, to foster inclusive and sustainable participation of smallholder farmers in global value chains.
The poultry industry is the fasted growing sub-sector of agriculture in the developing world and this is attributed to several pulling and pushing factors. On the demand side, the issue of urbanisation, income increase and animal protein requirements particularly for chicken has a positive influence on the growth of poultry production. Poultry farming is highly practised in rural households in Lesotho, and it constitutes an important contribution to the development of the rural economy in most developing countries. The poultry industry remains an important sub-sector of agriculture like in many other developing countries and it remains the main source of livelihood for village people and other small-scale farmers in the economy. Many rural communities are keeping poultry as a source of meat and eggs to feed their families, raise income from the surplus and create employment opportunities. However, access to formals markets remains a critical challenge for the farmers. This study examined the socio-economic, market and institutional factors that influenced broiler farmers’ market participation and intensity of participation in the Leribe district in Lesotho. A two-stage sampling technique was employed to select 114 respondents from five villages and the survey data was collected through a structured questionnaire. Heckman's two-stage model was used to analyse factors influencing farmers' market participation and the intensity of market participation. Gender, farmer income, storage access, production experience, extension service, credit access and information access were significant and influenced farmers’ market participation decisions. The study recommends interventions that will increase access and formal market participation.
This paper uses a multinomial endogenous treatment effect model and data from a sample of 470 farming households to assess the impacts of adopting sustainable agricultural practices (SAPs) on farm yield and household incomes among smallholder maize farmers in Morogoro region. Results show that combination of improved maize and crop residual significantly increased maize yield by 46%, while intercropping with crop residual (65%), improved maize seeds with manure use (58%), and maize rotation with intercropping (57%). The model estimates indicate that individual elements of SAPs increased yield by crop residual (30%), crop rotation (38%), improved maize varieties (85%), intercropping (58%), and manure (43%) whereas, the application of bundled SAPs had significant impacts on the household income via the following combinations; maize-legume rotation and crop residual (50%), improved maize and crop residual (46%), improved maize and manure (70%), maize-legumes rotation and improved maize (46%), maize rotation and intercropping (68%), maize rotation, improved maize, crop residual, and intercropping (41%), and lastly improved maize, intercropping, manure, crop residual, and crop rotation (55%). The study recommends actors involved in the design, promotion and dissemination of SAPs to find a suitable mix or combination of these practices that will enhance maize productivity and incomes, while simultaneously addressing issues related to the dis-adoption of SAPs, and climate change, by raising awareness and educating to farmers about the benefits of using SAPs and implementing mitigative measures for climate change. This includes providing financial incentives such as loans and subsidies, as well as conducting policy reforms to evaluate and adjust policies that currently favor the use of conventional practices in Tanzania.
Cassava (Manihot esculenta Crantz) has remained a major source of food security and income generation for most developing countries including Tanzania due to its ability to drought and disease resistance. At present, its production in Tanzania stands at 630,000 tons while the country's market demand is expected to grow at 7% by 2026. Therefore, this study assessed the contribution of cassava production and marketing on the livelihood of smallholder farmers in Tanzania particularly in the Dodoma region, so as to explore its potential contributions to the society welfare. A cross-sectional research design was employed whereby a multi-stage sampling procedure was used in selecting a sample of 240 cassava smallholder farmers from four districts in the Dodoma region namely Kondoa, Chemba, Kongwa, and Mpwapwa. Quantitative data were collected through self-administered structured questionnaires and focus group discussion, interview and observation methods also were used in collecting qualitative data from the study area. Content analysis was used in analyzing qualitative data. A binary logistic regression model was employed to estimate the contribution of cassava production and marketing on smallholder farmers’ livelihoods in the region. The findings from the study indicated that family size, farmers’ experience, land size, education, number of visits by extension, and market access statistically were significant with showed a positive relationship with the improvement in the livelihood of farmers in the selected districts. On the other hand, transportation costs showed a negative relation with the improvement of farmers’ livelihood. Generally, it can be concluded that an increase in production and improvement in marketing variables could contribute much to the improvement of smallholder farmers’ livelihood. Based on these findings, it is recommended that Ministries responsible for cassava production and marketing which included the Ministry of Agriculture and the Ministry of Industry and Trade focus more on the design, promotion, and implementation of policies and programs that are intended to enhance cassava production in rural areas and increase the provision of best farming practices through employing more extension officers.
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.
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 |