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: 11 / 11 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 01:07 UTC — 22 Oct 2026 18:24 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.
11 / 11 with data · 0 missing or unmatched. Percentages use all 11 selected publications.
11 / 11 with data · 0 missing or unmatched. Percentages use all 11 selected publications.
11 / 11 with data · 0 missing or unmatched. Percentages use all 11 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 |
|---|---|---|---|---|---|
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2017 | All selected publications | 8 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 9 | 6 | 6/6 | 6/6 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2017 | All selected publications | 17 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2019 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 1 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 19 | 6 | 6/6 | 6/6 |
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 11 / 11 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): 2026-10-22T01:07:25.145353+00:00 — 2026-10-22T18:24:12.171470+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 | 11 | 11/11 |
| 2018 | All selected publications | 0 | 11 | 11/11 |
| 2019 | All selected publications | 1 | 11 | 11/11 |
| 2020 | All selected publications | 4 | 11 | 11/11 |
| 2021 | All selected publications | 2 | 11 | 11/11 |
| 2022 | All selected publications | 7 | 11 | 11/11 |
| 2023 | All selected publications | 9 | 11 | 11/11 |
| 2024 | All selected publications | 9 | 11 | 11/11 |
| 2025 | All selected publications | 6 | 11 | 11/11 |
| 2026 | All selected publications | 1 | 11 | 11/11 |
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 |
|---|---|
| 2017 | 1 |
| 2018 | 1 |
| 2019 | 1 |
| 2020 | 2 |
| 2021 | 6 |
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 | 4 | 10 | 21 | 4/4 | 2.5 | 1.0 | 50.0 | 4/4 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 7 | 9 | 19 | 7/7 | 1.29 | 1 | 57.1 | 7/7 · 100.0% |
* 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 aimed at evaluating the effect of organizational culture on strategy implementation in Private chartered universities in Kenya. The objective of this study was to ascertain the effect of hierarchy culture on the strategy implementation in Private chartered universities in Kenya. A cross-sectional survey research design was adopted and it used both quantitative and qualitative data as it seeks the effect of organizational culture on the implementation of corporate strategy. The accessible population included University and students’ leaders. This study used both stratified random sampling and the target sample size was 194 employees. The statistical package for social sciences (SPSS) version 21 was used to describe the relationships between dependent and independent variables. The study used correlation and regression techniques as well as the analysis of variance (ANOVA) to test the study hypotheses. A multiple linear regression model was also used to derive inferential statistical indicators like the correlation, coefficient of determination, F-statistics, t-test statistic, and the p-value. In this research Pearson’s correlation analysis was used to test for the existence of multicollinearity. Normality testing was done to compare the cumulative distribution of the data. Factor analysis was also carried out on all items in each variable in order to reduce the measurable and observable variables. The key finding based on the tests conducted in the study was that the variable: Hierarchy culture had an effect on the dependent variable: Strategy implementation. The p-value published showed that there was a positive effect of hierarchy culture on strategy implementation in Private chartered universities in Kenya
Liquidity risk is the potential that an entity will be unable to acquire the cash required to meet its short and intermediate-term obligations. Deposit-taking Savings and Credit Cooperative Organisation (SACCOs) face liquidity risk when they are unable to fund their operations and lending requirements to their members as and when circumstances demand. Given that liquidity is a key phenomenon on the optimal functioning and financial performance of deposit-taking SACCOs, this study critically analyzed the effect of liquidity risk on the financial performance of DT SACCOs in Kenya. The study used a descriptive survey design and employed regression methods to model the relationship between liquidity risk and financial performance of DT SACCOs. The data were analyzed at a 5% level of significance. The study findings revealed that at a 5% level of significance, liquidity risk had a statistically significant influence on the financial performance of deposit-taking SACCOs. Basing on the findings, DT SACCOs are encouraged to focus on enhancing the mobilization of deposits to ensure that an asset portfolio that minimizes liquidity risk is maintained.
Capital structure management is one of the most crucial corporate financial management functions in a firm since appropriate debt policy is reported to maximize the value of a firm. Kenya is ranked second in Africa after South Africa in regards to financial deepness. This means that the cost of debt should not have adverse effect financial performance. This observation raises fundamental question: does debt financing leads to poor financial performance in Kenya? This research sought to investigate the role of observed leverage on financial performance of listed non- financial firms in Kenya. The study tested capital structure theories and therefore adopted a positivists approach, guided by causal research design. The study population was 35 non-financial sub-sector firms out of the 65 firms listed at the NSE, Kenya. 18 firms were excluded in this study since they belong to banking and insurance sub-sectors, which have a highly regulated capital structure. Secondary data collection sheet was used to collect data for each of the variables from audited financial statements of the listed firms for a 10-year period (2006-2015). Panel regression analysis revealed that observed leverage measured by (LDR) had a significant positive coefficient with performance metrics. However, the leverage measure using TDR showed a negative and significant role on performance metrics. This study recommends that for listed firms to improve their financial performance, they should use more long-term debts than short-term debts.
The purpose of the study was to determine the moderating effect of environmental uncertainties on the relationship between lean supply chain strategy and the performance of manufacturing firms in Kenya. The study utilized a descriptive research design. The target population was 829 supply chain managers or directors from manufacturing firms around the country. A sample of 270 supply chain or procurement managers was selected using stratified random sampling. Results indicated that lean supply chain strategy explained 60.7% of the total variations in the performance of manufacturing firms. In addition, lean supply chain strategy had a positive and significant effect on the performance of manufacturing firms. With the introduction of moderating variables (environmental uncertainties); lean supply chain strategy explained 33% of the total variations in the performance of manufacturing firms. This denoted those environmental uncertainties had a negative moderating effect on the relationship between lean supply chain strategy and performance of manufacturing firms in Kenya. The study concluded that lean supply chain strategy had a positive and statistically significant effect on the performance of manufacturing firms in Kenya.
Collapse of companies in Kenya has been on the rise in the recent past. Far reaching endeavors to resuscitate these liquidating and ailing firms have generally been attributed on their corporate financial management decisions. Multinationals and KTDA managed tea firms in Kenya have been performing poorly in the recent past where audited financial statements and reports revealed a warning signal on its financial performance. Specific objectives of the study were to determine the effect of the accounts receivables period, accounts payables period, inventory conversion period, cash conversion cycle, financing policy, investing policy and moderating effect of ownership structure on financial performance. The study illustrated that accounts receivables collection period is negatively related to return on assets (? = -0.1299, p=0.0160), accounts payables payment period is negatively related to return on assets (? = -0.0843, p = 0.0070), inventory conversion period is negatively related to return on assets (?= -0.0623, p=0.0180), cash conversion cycle is negatively related to return on assets (? = -0.1107, p = 0.0030), financing policy is positively related to return on assets (? = 0.1589, p = 0.0000), investing policy is positively related to return on assets (? = 0.0291, p = 0.0000).
The purpose of the study was to determine the moderating effect of environmental uncertainties on the relationship between lean supply chain strategy and the performance of manufacturing firms in Kenya. The study utilized a descriptive research design. The target population was 829 supply chain managers or directors from manufacturing firms around the country. A sample of 270 supply chain or procurement managers was selected using stratified random sampling. Results indicated that lean supply chain strategy explained 60.7% of the total variations in the performance of manufacturing firms. In addition, lean supply chain strategy had a positive and significant effect on the performance of manufacturing firms. With the introduction of moderating variables (environmental uncertainties); lean supply chain strategy explained 33% of the total variations in the performance of manufacturing firms. This denoted those environmental uncertainties had a negative moderating effect on the relationship between lean supply chain strategy and performance of manufacturing firms in Kenya. The study concluded that lean supply chain strategy had a positive and statistically significant effect on the performance of manufacturing firms in Kenya.
Liquidity risk is the potential that an entity will be unable to acquire the cash required to meet its short and intermediate-term obligations. Deposit-taking Savings and Credit Cooperative Organisation (SACCOs) face liquidity risk when they are unable to fund their operations and lending requirements to their members as and when circumstances demand. Given that liquidity is a key phenomenon on the optimal functioning and financial performance of deposit-taking SACCOs, this study critically analyzed the effect of liquidity risk on the financial performance of DT SACCOs in Kenya. The study used a descriptive survey design and employed regression methods to model the relationship between liquidity risk and financial performance of DT SACCOs. The data were analyzed at a 5% level of significance. The study findings revealed that at a 5% level of significance, liquidity risk had a statistically significant influence on the financial performance of deposit-taking SACCOs. Basing on the findings, DT SACCOs are encouraged to focus on enhancing the mobilization of deposits to ensure that an asset portfolio that minimizes liquidity risk is maintained.
The study aimed at assessing the influence of Access to credit as provided by Youth Enterprises Development Fund (YEDF) on the growth of entrepreneurial youth group-based enterprises and moderating effect of group dynamics on the relationship between access to credit and the growth of entrepreneurial youth group-based enterprises. A cross-sectional survey research design was adopted and it used both quantitative and qualitative data. The accessible population comprised group leaders and Youth development Officers. This study employed stratified random sampling on a population of 255 subjects and a sample size was 156 group leaders out of which 121(77%) questionnaires were returned. The statistical package for social sciences (SPSS) version 21 was used to analyze data. YEDF is a government fund initiative with a nationwide presence in Kenya with Nairobi County as the smallest, most populous, has the highest uptake of the YEDF loans amounting to 2.3 billion, and has the highest loan repayment rate of 48%. The analysis of data revealed that access to credit was significant in explaining the growth of entrepreneurial youth group-based enterprises in Nairobi County. Access to credit had an R of 0.222 and contributed only 4.9% to the growth of entrepreneurial youth group-based enterprise. The study established that when group dynamics was introduced the model remained significant and R improved from 0.222 to 0.390. The study concludes that Access to credit significantly influences the growth of Entrepreneurial youth group-based enterprises in Nairobi county while group dynamics have a predictive effect but has no moderating effect.
This study aimed at evaluating the effect of organizational culture on strategy implementation in Private chartered universities in Kenya. The objective of this study was to ascertain the effect of hierarchy culture on the strategy implementation in Private chartered universities in Kenya. A cross-sectional survey research design was adopted and it used both quantitative and qualitative data as it seeks the effect of organizational culture on the implementation of corporate strategy. The accessible population included University and students’ leaders. This study used both stratified random sampling and the target sample size was 194 employees. The statistical package for social sciences (SPSS) version 21 was used to describe the relationships between dependent and independent variables. The study used correlation and regression techniques as well as the analysis of variance (ANOVA) to test the study hypotheses. A multiple linear regression model was also used to derive inferential statistical indicators like the correlation, coefficient of determination, F-statistics, t-test statistic, and the p-value. In this research Pearson’s correlation analysis was used to test for the existence of multicollinearity. Normality testing was done to compare the cumulative distribution of the data. Factor analysis was also carried out on all items in each variable in order to reduce the measurable and observable variables. The key finding based on the tests conducted in the study was that the variable: Hierarchy culture had an effect on the dependent variable: Strategy implementation. The p-value published showed that there was a positive effect of hierarchy culture on strategy implementation in Private chartered universities in Kenya
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 |