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.
Top 5 in the selected collection · Ranked by Crossref lifetime citations. Only articles with at least one known citation are included; source totals are never combined.
2017 · Jane Gathiga Muriithi · Kennedy Munyua Waweru
2020 · Severinah Wanjiru Mwangi · James Ndegwa
2021 · Eltigani Ahmed · James Kilika · Clare Gakenia
2020 · Henry Mugisha · Job Omagwa · James Kilika
2021 · Halldess nguta Munene · James Ndegwa
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: 23 / 25 publications (92.0%). Latest observation: 21 Oct 2026, 00:21 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 00:49 UTC — 27 Oct 2026 19:04 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.
25 / 25 with data · 0 missing or unmatched. Percentages use all 25 selected publications.
25 / 25 with data · 0 missing or unmatched. Percentages use all 25 selected publications.
25 / 25 with data · 0 missing or unmatched. Percentages use all 25 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 |
|---|---|---|---|---|---|
| 2013 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2014 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2019 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2020 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| 2021 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 2 | 2 | 0/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 8 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 3 | 2 | 2/2 | 2/2 |
| 2019 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2020 | All selected publications | 15 | 5 | 5/5 | 5/5 |
| 2021 | All selected publications | 9 | 6 | 6/6 | 6/6 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 1 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | — | 2 | 0/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 1 | 2 | 2/2 | 2/2 |
| 2014 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 17 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 4 | 2 | 2/2 | 2/2 |
| 2019 | All selected publications | 9 | 3 | 3/3 | 3/3 |
| 2020 | All selected publications | 34 | 5 | 5/5 | 5/5 |
| 2021 | All selected publications | 17 | 6 | 6/6 | 6/6 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 1 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 2 | 0/2 | 2/2 |
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 25 / 25 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): 2026-10-22T00:49:24.531355+00:00 — 2026-10-27T19:04:50.688962+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 | 1 | 25 | 25/25 |
| 2018 | All selected publications | 0 | 25 | 25/25 |
| 2019 | All selected publications | 2 | 25 | 25/25 |
| 2020 | All selected publications | 6 | 25 | 25/25 |
| 2021 | All selected publications | 4 | 25 | 25/25 |
| 2022 | All selected publications | 16 | 25 | 25/25 |
| 2023 | All selected publications | 28 | 25 | 25/25 |
| 2024 | All selected publications | 13 | 25 | 25/25 |
| 2025 | All selected publications | 10 | 25 | 25/25 |
| 2026 | All selected publications | 4 | 25 | 25/25 |
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 |
|---|---|
| 2013 | 2 |
| 2017 | 1 |
| 2018 | 2 |
| 2019 | 3 |
| 2020 | 5 |
| 2021 | 6 |
| 2022 | 1 |
| 2023 | 1 |
| 2024 | 2 |
| 2026 | 2 |
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 Finance & Banking Studies SSBFNET | 25 | 40 | 84 | 25/25 | 1.74 | 1 | 60.9 | 23/25 · 92.0% |
* Percentage among publications with a known citation count.
<p>Operational risk threatens banks financial viability and long-term sustainability. The purpose of this paper is to explore the effect of operational risk on financial performance of commercial banks in Kenya. The qualitative research design and ordered logistic model were employed. The data was analysed with the aid of STATA software. The conclusion of the study was that there exists an inverse relationship between operational risk and financial performance. The study also finds that bank size moderates the effect internal and external fraud on financial performance of commercial banks in Kenya by shrinking it. Bank size moderates the effect execution, delivery and process management on financial performance of commercial banks in Kenya by enhancing it. The guidelines and procedures provided by the Central bank of Kenya on operational risk management should be fully adhered into.</p>
This study sought to establish the influence of fraud risk management practices in regard to preventive, detective and corrective controls on the level of fraud occurrence on listed firms in Kenya. This is because limited research had been conducted in the context of listed firms in Kenya and limited attention paid on how corrective controls influences fraud occurrence. A causal research design was applied. Data was obtained from a sample of 275 senior managers by using structured questionnaires. The findings revealed that only preventive and corrective controls had a profound negative effect on the degree of fraud occurrence on listed companies in Kenya. Conversely, detective controls did not considerably reduce fraud occurrence on listed companies in Kenya. The key implication of the findings noted by this study is that the proper implication of the most effectual anti-fraud measures can only be realized when the management are committed to do so. Additionally, corrective controls must be seriously looked into as an effective strategy of curbing fraud since they indeed are instrumental in curbing fraud. Future studies should be extended to the public sector in regard to the government ministries and the distinctive partitions of the private sector such as the insurance, real estate, manufacturing, automobile sectors among others respectively. Moreover, future studies can explore how firm size in terms of asset size or employee size moderates the relationship between fraud risk management practices and the level of fraud occurrence.
The theory of dynamic resource orchestration explains the differentiated response of homogeneous ecosystem organizations to systemic disruptive shocks. The Covid-19 precautionary measures in Kenya have exempted some essential service providers and government agencies, resulting in a differentiated Covid-19 impact across the national SMEs landscape. This article adopted an extractive thematic analysis technique to draw insights from in-depth interviews and discussions with owners and managers of 6 broad-range SMEs considered non-essential services providers excluded from the Covid-19 cessation of movement waiver. The article advanced insights on SMEs' resilience through dynamic resource orchestration capability. It sought to establish whether the possession and orchestration of dynamic resources capabilities differentiated highly resilient SMEs from non-resilient ones. The article identified business diversification, slack finance, intra-stakeholder collaboration, self-reinvention, positive psychology, technology leverage, and cost management as precursory resilience agents within Kenyan SMEs. Research gaps were identified, and recommendations for future research were proposed.
Short-term debt is regarded as an important source of financing for Small and Medium-sized enterprises (SMEs). This is because it can be easily accessed and useful during times of emergent working capital shortage. However, short-term debt is the least researched among the components of capital structure, which explains why its contribution to the financial performance of small and medium-sized businesses still lacks empirical validation especially in the Ugandan context. This paper sought to determine the effect of short-term debt on financial performance of Small and Medium Enterprises in Uganda. The study adopted a descriptive cross-sectional research design to collect and analyse the data. Stratified random sampling technique was used to select SMEs while purposive sampling technique was used to select one key respondent from each of the sampled 453 SMEs in Uganda. Primary data was collected using survey questionnaire. Data was analysed using descriptive statistics and simple linear regression analysis. The findings indicted that short-term debt had a negative and significant effect on financial performance of SMEs as measured by return on assets. The study provides empirical evidence to support the propositions in the extant literature that short-term debt significantly hampers financial performance of SMEs. The study recommends that SMEs should adopt low cost operation procedures to improve profitability. This would lead to accumulated profits that can be used for investment purposes as a means of driving growth among the SMEs without resorting to borrowing. This paper suggests that further research should be conducted to establish the justification for the negative and significant effect of short-term debt on financial performance using qualitative approaches.
The upper Echelons Theory reiterates the importance of top management in an organization and recognizes that the mangers make decisions that grow the entity. Before the establishment of this theory, the premise was that larger firms which drive high amounts of income, are capable of running themselves without failure. Although Organizations that command large amounts of income are deemed to be successful the upper echelons theory holds that these entities cannot be successful without proper management and guidance by top management where the board of directors in this case is considered as top management organ for SACCOs. Savings and Credit Cooperatives (SACCOs) have evolved over time from mobilizing savings and granting loans to become established entities that provide banking services to their customers. They require good governance to avoid the experience of financial distress. The current research was therefore aimed at establishing the influence of firm revenue on the relationship between board characteristics and financial distress of deposit taking SACCOs in Nairobi County. Large entities command more revenue as compared to small firms. Board Characteristics is of importance to this study because it influences Corporate Governance which according to previous research has shown that the practice helps revolutionize performance of various institutions. The study is guided by upper echelons theory which reiterates the importance of top management. Descriptive research design was adopted while Nairobi County was purposively chosen and a census was carried out on deposit taking SACCOs in the county. Secondary data was collected from SASRA using a data collection sheet and a panel data analysis performed using STATA software and findings were presented using tables. The study concluded that firm revenue does not mediate the relationship between board characteristics and financial distress of Deposit Taking SACCOs. Though firm revenue should be enhanced, governance should be improved since it remains a critical success factor in alleviation of financial distress.
This study examines whether Islamic banks in SSA exhibit convergence in operational efficiency or whether performance disparities persist over time. Specifically, it evaluates whether less efficient banks catch up with more efficient peers within the region’s emerging Islamic banking sector. The study adopts a two-stage empirical framework using panel data from 35 Islamic banks across SSA over the period 2010–2024. In the first stage, operational efficiency scores are estimated using a bias-corrected Data Envelopment Analysis (DEA) model following the Simar and Wilson two-stage approach. An input-oriented specification under Variable Returns to Scale (VRS) is employed to reflect cost minimization behaviour and heterogeneity in bank size. Bias correction is implemented using a bootstrap procedure to obtain consistent efficiency estimates. In the second stage, convergence dynamics are analysed using sigma (σ) and beta (β) convergence models, alongside conditional convergence regressions incorporating bank size, age, and market concentration. The results reveal significant β-convergence, with the baseline model yielding a coefficient of −0.267 (p < 0.01), while the conditional model confirms robust convergence (β = −0.2836, p < 0.01), indicating that banks with lower initial efficiency improve at a faster rate than more efficient institutions, consistent with catch-up dynamics. However, σ-convergence results show that efficiency dispersion declined between 2010 and 2019 but increased after 2020, indicating that convergence was time-varying rather than uniform. This suggests that while convergence forces exist, structural differences and external shocks continue to sustain efficiency gaps across banks. The findings highlight the need for stronger regulatory harmonization, improved financial infrastructure, and targeted capacity-building initiatives to accelerate efficiency convergence across Islamic banks in SSA.
This study investigates whether inefficiencies in Islamic banking in Sub-Saharan Africa (SSA) are primarily driven by managerial limitations or by suboptimal scale of operations. While existing studies largely report aggregate efficiency scores, limited attention has been given to decomposing efficiency into its underlying components in emerging Islamic banking systems, particularly within the SSA context. The study employs a balanced panel of 35 fully fledged Islamic banks operating in SSA over the period 2010–2024. Operational efficiency is estimated using a bias-corrected Data Envelopment Analysis (DEA) model under an input-oriented Variable Returns to Scale (VRS) framework. To enhance statistical reliability, the Simar–Wilson bootstrap procedure with 2,000 replications is applied. Efficiency scores are decomposed into pure technical efficiency and scale efficiency to distinguish between managerial inefficiencies and structural scale constraints. The results indicate that overall efficiency levels remain low, with inefficiencies largely driven by scale factors rather than managerial performance. A significant proportion of banks operate under increasing returns to scale, suggesting suboptimal size linked to structural constraints such as limited market depth, fragmented regulatory environments, and underdeveloped financial infrastructure. Although pure technical efficiency shows moderate improvement over time, managerial gains are insufficient to offset these systemic limitations. The findings highlight the need for regulatory harmonization, market integration, and strategic expansion or consolidation to enable Islamic banks to achieve optimal scale and improve operational efficiency in SSA. This study provides one of the first comprehensive efficiency decomposition analyses of Islamic banks in SSA using bias-corrected DEA, offering new insights into the relative importance of structural versus managerial sources of inefficiency in emerging financial systems.
This study analyses the impact of external debt on the financial performance of commercial banks in Kenya for the period 2008-2022. Employing descriptive, correlational, and inferential research designs, the study reviewed data from the Central Bank of Kenya, the World Bank, KNBS, and IMF on a quarterly basis. By employing the Augmented Dickey-Fuller test, ROE and external debt were further qualified to be stationary at first difference. The results highlighted by the Autoregressive Distributed Lag (ARDL) analysis indicated a statistically significant negative relationship between external debt and financial performance; the coefficients (-0.8998) confirmed that for every unit of increase in external debt, there would be a decline in ROE by 0.8998 units. The study establishes that external debt has been detrimental to the financial health of Kenyan banks due to the economic pressure it brings to the sector. For this purpose, it suggests that the government should avoid borrowing from external sources, and it has advised the development of measures that encourage overseas investors to invest in the country's banking sector. The policy of attracting FDI can enhance capital availability and alleviate the financial load on banking institutions. Relaxing regulations that restrict foreign investors would pave the way for this and help increase the bank’s performance, thus enhancing long-term economic growth.
Dividend payout is one of financial options that Saccos consider as part of the key performance indicators for Saccos. Deposit taking Saccos in Kenya have faced numerous challenges namely, governance, managerial and operational such that the performance of a number of them continues to be sub optimal according to the report by SASRA. Therefore, this study sought to examine the influence of board characteristics on dividend policy of deposit taking Saccos in Kenya under guidance by agency cost theory. The study utelized causal design and descriptive survey design. The targeted population was 403 stakeholders sampling 201 through stratified simple random sampling. The sacco directors/chairpersons and the CFO/CEOs formed unit of analysis. Closed ended questionnaires were applied for primary data. A list of 20 Saccos in Starehe Sub County, Nairobi County were basis for pilot test to establish reliability and validity of research instruments. Cronbach Alpha was employed to ascertain reliability, whereas content and construct validity were utilized to attain validity. The data underwent analysis through the application of descriptive as well as inferential statistics. The investigation ensured that the assumptions of linear regression were satisfied before conducting numerous linear regressions. Tables were used to present data. The results indicated a positive significant association between board characteristics practices and dividend policy P:0.000<0.05 hence conclusive that deposit-taking Saccos in Kenya focused on board characteristics as envisaged. The study recommended that Sacco’s should diverse the board features to ensure they accommodate the dividend policy framework.
Fee collection tactics are measures that school administrators do to achieve the school's objectives by putting together the sum thought appropriate for school fees charges, such as creating automatic fee payment plans and sending out reminders to parents. There are challenges associated with fee payment as parents are the main contributors, yet they are in different economic position. The government has consistently delayed funding their portion which is still below required standards. Therefore, this study was focused on school fee collection strategies and financial accountability of Public Secondary Schools in Khwisero Sub County. The study was guided by agency theory. The research design used in this study was a descriptive survey. The 25 public secondary schools in the Khwisero sub-county of Kenya represented the 50 stakeholders who were the focus of the study. The county schools auditor, who oversaw all of the schools in the research, was also a part of the census survey that included all 50 stakeholders. Data was gathered with the help of standardized questionnaires. Mean and standard deviation were used for descriptive statistics, while Pearson correlation and simple linear regression were used for inferential statistics. SPSS, a statistical program used in the social sciences, helped with this. Tables were used to present the data. The financial transparency of public secondary schools in Khwisero sub County, Kakamega County, was significantly influenced by the collection tactics with an R2 of 0.504. The research suggests that public secondary schools should incorporate school factors that have a significant impact on financial accountability into their main key elements that should be considered when handling school fund accounts and find ways in which fee collection can be enhanced to ensure there is adequate cashflow.
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 00:21 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:21 UTC |
| ojs-rest | 21 Oct 2026 00:21 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:14 UTC |
| oai-pmh | 20 Oct 2026 19:56 UTC · ijfbs | complete · ijfbs · 20 Oct 2026 19:55 UTC |
| openalex-enrichment | 21 Oct 2026 00:22 UTC · ijfbs | complete · ijfbs · 21 Oct 2026 00:21 UTC |