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: 9 / 9 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 02:04 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.
8 / 9 with data · 1 missing or unmatched. Percentages use all 9 selected publications.
8 / 9 with data · 1 missing or unmatched. Percentages use all 9 selected publications.
9 / 9 with data · 0 missing or unmatched. Percentages use all 9 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 | 9 | 9 | 9/9 | 9/9 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 5 | 9 | 9/9 | 9/9 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 6 | 9 | 9/9 | 9/9 |
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 9 / 9 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): 2026-10-21T07:22:59.970106+00:00 — 2026-10-22T02:04:54.508992+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 | 9 | 9/9 |
| 2018 | All selected publications | 0 | 9 | 9/9 |
| 2019 | All selected publications | 0 | 9 | 9/9 |
| 2020 | All selected publications | 0 | 9 | 9/9 |
| 2021 | All selected publications | 0 | 9 | 9/9 |
| 2022 | All selected publications | 0 | 9 | 9/9 |
| 2023 | All selected publications | 0 | 9 | 9/9 |
| 2024 | All selected publications | 0 | 9 | 9/9 |
| 2025 | All selected publications | 1 | 9 | 9/9 |
| 2026 | All selected publications | 5 | 9 | 9/9 |
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 | 9 |
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 | 5 | 1 | 1 | 5/5 | 0.2 | 0 | 20.0 | 5/5 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 2 | 3 | 4 | 2/2 | 1.5 | 1.5 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 1 | 1 | 2/2 | 0.5 | 0.5 | 50.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
In the quest to achieve SDG 1 on eradicating poverty, improving savings rates in East Africa is crucial, as it lays the foundation for reducing financial vulnerability and achieving economic resilience. This paper investigated the determinants of individual savings in selected East African countries. Specifically, internet access, financial inclusion, and borrowing were the covariates while individual savings in East Africa were the predicted. This study utilized data from the Global Findex 2021 World Bank database. This dataset was selected because it is one of the most comprehensive databases on financial inclusion, providing a comprehensive view of adults' savings, borrowing, payments, and risk management across global and regional contexts. This study used a basic framework to explore the factors influencing individual savings by examining production, income distribution, and accumulation. A panel data logistic regression model was utilized, and Instrumental Variables (2SLS) regression was employed to test endogeneity. The Sargan and Basmann tests assessed overidentification restrictions to validate the instruments. Shea’s partial R-squared measured the unique contribution of each instrument in explaining the variation in endogenous variables, accounting for the influence of other instruments and endogenous variables. The Hausman test which model was suitable for panel data modeling. The 2SLS regression showed no evidence of endogeneity, as internet access was insignificant with a high p-value (> 0.05). Overidentification tests confirmed instrument validity with p-values of 0.1018 and 0.1016. However, Shea’s partial R-squared revealed weak instruments, especially for borrowing, with an adjusted value of 0.0328. Results revealed that borrowing is strongly and positively associated with saving. The higher the borrowing, the more the savings. In East Africa, most borrowers are savers. These use the borrowed funds to create an injection of income flow through capital accumulation. Internet access significantly predicts savings in East Africa today. In this digital era, most businesses are run online. Therefore, it is almost impossible to save with no internet access. Similarly, those who use digital payment systems are most likely to enhance their savings. Age and gender do not influence the saving of an individual in East Africa. Likely, owning a financial account does not translate to more savings. Most East Africans have non-functional bank accounts. Education levels significantly influence the savings of individuals in East Africa. Highly educated people utilize financial literacy skills to save more. Being out of the workforce reduces individual savings since most of these are out of the working age.
Financial inclusion aims to include the unbanked population in the official financial system. To quickly serve the unbanked population, this study aims to investigate the concept of agent banking as a means of financial inclusion and to assess the elements that influence the acceptance of agent banking in Bangladesh. The study also covered the main advantages of agent banking and pertinent barriers to its adoption. Using a basic judgmental sampling technique, 195 respondents from the Chittagong region made up the study's sample. Face-to-face interviews and a structured questionnaire were used to collect the data. The impact was investigated using statistical measures such as mean, standard deviation, correlation, and regression. Kendall's W test, also known as Kendall's coefficient of concordance, was utilized to evaluate the benefits and drawbacks of accepting agent banking in this study. According to the result, there is a significant positive correlation between acceptance of agent banking and independent variables - perceived trust, convenience, perceived risk, awareness, and service quality. The study also found that easy banking is the key reason for agent banking, marked by the respondents, followed by the nearest location and adding new customers. Lack of training is the major challenge, followed by a lack of logistic support and cyber security risk in implementing agent banking in Bangladesh.
In emerging economies, women entrepreneurs play a critical role in job creation and social and economic progress, particularly in townships. However, the specific context of women's township entrepreneurship has mainly been overlooked in South African research, which remains fragmented and lacks cohesive insights. This study explores the role of microfinance in fostering women's township entrepreneurship within a South African context. Research has repeatedly demonstrated that microfinance institutions hold a vital position in the economic advancement of women, resulting in elevated female participation in business activities and ultimately fostering their overall empowerment. The investigation focused on women entrepreneurs within the marginalised township of Mdantsane, located in the Eastern Cape Province of South Africa. Using a qualitative approach, the study involved in-depth interviews with 15 women entrepreneurs selected through purposive sampling. The data was analysed using thematic analysis, revealing five key themes: empowerment through financial independence, building entrepreneurial skills and networks, increased business volume and turnover, overcoming socioeconomic barriers, and reduction in gender inequalities. The findings suggest that an intervention mapping approach is crucial for policymakers to design tailored microfinance programs for women entrepreneurs in township economies. This approach involves a systematic process that begins with a thorough assessment of the specific financial needs and challenges faced by women in these communities, followed by the development of targeted interventions that address those needs.
A country's ability to develop depends on the empowerment of its women. Evidence from several countries indicates that giving Self-Help Group (SHG) member’s microcredit can help empower rural women. The main objective of the study is impact of creation of SHGs on rural women in Assam. Also purpose of this research was to determine how well SHGs in Assam contribute to women's economic empowerment. The study's primary data came from interviews with SHG beneficiaries conducted in the Bongaigaon District of Assam. In all, sixty samples are gathered from two blocks of the Bongaigaon district. According to the survey, the majority of respondents are between the ages of 25 and 45, and they have completed elementary and middle level of school. After joining SHGs, participants engaged in a variety of income-generating activities. The outcome demonstrated a favorable shift in economic empowerment metrics, such as income, employment, and savings, following SHG membership. For the economic indicators, the estimated value of the Wilcoxon signed Ranks Test was significant. It was found that, in comparison to the pre-SHG scenario, the majority of the respondents' income, employment days, and savings amount rose in the post-SHG scenario. Therefore, the study came to the conclusion that SHGs were essential to rural women's empowerment in the study region.
SMEs play a critical role in employment generation and improving economic growth but continue to be excluded from the financial systems. However, the emergence of financial technologies such as mobile money provides a critical tool to address financial exclusion. As such, this study investigates the impact of mobile money on access to finance by small and medium enterprises (SMEs) in Sub-Saharan Africa (SSA). Using a sample of thirteen sub–Saharan African countries, covering the period between 2015 to 2022, the study utilised secondary data and employed panel data regression techniques in estimation. This study demonstrated that mobile money impedes access to financial services at commercial banks by SMEs. To promote financial inclusivity, this study proffers policy advice as it recommends partnering of mobile money providers and traditional financial institutions to develop financial products which are tailor-made to SMEs using mobile money platforms to take advantage of its popularity in the SSA region.
In any economy, Small, Medium, and Micro Enterprises (SMMEs) are essential for creating employment opportunities, which in turn help to eradicate poverty and high unemployment rates. Access to credit from several banks is essential for SMMEs to be sustainable. Since this finance is the lifeblood of these small businesses, its importance cannot be understated. Therefore, it was crucial for this study to assess the significance of the funding of SMMEs from banks and their impact on the sustainability of these small businesses. The research methodology used in the study was qualitative. SMMEs from different industries, such as agriculture, tourism, etc, and banking officials in the Vhembe District Municipality region made up the population used in this study. Ten research participants were chosen as a sample using stratified random sampling. Data was collected from the participants using an interview guide, and Atlas.ti was used for analysis. The results of this study revealed that the significance of financing SMMEs is grounded on job creation, poverty alleviation, and SMME development in the Vhembe district. The study also revealed that the funding assistance provided by banks provides the basis to develop their operations and enhance business sustainability.
SMEs play a critical role in employment generation and improving economic growth but continue to be excluded from the financial systems. However, the emergence of financial technologies such as mobile money provides a critical tool to address financial exclusion. As such, this study investigates the impact of mobile money on access to finance by small and medium enterprises (SMEs) in Sub-Saharan Africa (SSA). Using a sample of thirteen sub–Saharan African countries, covering the period between 2015 to 2022, the study utilised secondary data and employed panel data regression techniques in estimation. This study demonstrated that mobile money impedes access to financial services at commercial banks by SMEs. To promote financial inclusivity, this study proffers policy advice as it recommends partnering of mobile money providers and traditional financial institutions to develop financial products which are tailor-made to SMEs using mobile money platforms to take advantage of its popularity in the SSA region.
Globally, financial inclusion is regarded as being crucial for balancing an economy's financial system. However, despite the significance of financial inclusion, it still needs to be clarified to what extent it is practiced. In this study, the assessment of the performance of the 49 Sub Saharan Africa (SSA) countries as regards financial inclusion was carried out through the construction of a single composite Financial Inclusion Index (FII) to capture the four dimensions of financial inclusion. Z-sum score and Principal Component Analysis (PCA) was deployed to analyse the secondary data spanning from 1999 to 2023. The decision rule deployed was that if a value for Financial Inclusion Index (FII) from zero to forty-nine (0-49) this shows that there is low financial inclusion; medium financial inclusion from fifty to sixty-nine (50-69) while, a value from seventy and above (70- above) denotes the high financial inclusion) for the study period. The result revealed that all SSA countries are low that is they fall into between zero (0) to forty-nine (49) in the composite financial inclusion index in line with the decision rule. Also, the result indicated that Sao-Tome and Principe was the best performing SSA country with the highest financial inclusion penetration per thousand considered during the period of the study.
In emerging economies, women entrepreneurs play a critical role in job creation and social and economic progress, particularly in townships. However, the specific context of women's township entrepreneurship has mainly been overlooked in South African research, which remains fragmented and lacks cohesive insights. This study explores the role of microfinance in fostering women's township entrepreneurship within a South African context. Research has repeatedly demonstrated that microfinance institutions hold a vital position in the economic advancement of women, resulting in elevated female participation in business activities and ultimately fostering their overall empowerment. The investigation focused on women entrepreneurs within the marginalised township of Mdantsane, located in the Eastern Cape Province of South Africa. Using a qualitative approach, the study involved in-depth interviews with 15 women entrepreneurs selected through purposive sampling. The data was analysed using thematic analysis, revealing five key themes: empowerment through financial independence, building entrepreneurial skills and networks, increased business volume and turnover, overcoming socioeconomic barriers, and reduction in gender inequalities. The findings suggest that an intervention mapping approach is crucial for policymakers to design tailored microfinance programs for women entrepreneurs in township economies. This approach involves a systematic process that begins with a thorough assessment of the specific financial needs and challenges faced by women in these communities, followed by the development of targeted interventions that address those needs.
This study examined the demographic and operational attributes of Small and Medium Enterprises (SMEs) in Windhoek, Namibia, and their ramifications for bank funding. The study analysed a sample of 66 small and medium-sized enterprise (SME) owners and operators, focussing on gender, education, age, company experience, yearly income, sector type, and business registration status. Findings indicate a prevalence of female entrepreneurs, a well-educated business populace, and an emphasis on middle-aged business proprietors. The data indicates that although a considerable number of SMEs were in the nascent phases of operation, the majority of enterprises were registered with the Business and Intellectual Property Authority (BIPA). The findings highlighted the capacity of financial institutions (FIs) to offer customised assistance to SMEs, particularly in varied and non-traditional industries, to foster sustainable economic growth in Windhoek. The study finishes with recommendations for banks to enhance services and assess the funding requirements of these enterprises according to their distinct characteristics and challenges
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 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |