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: 5 / 5 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 01:51 UTC — 29 Oct 2026 10:44 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.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 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 |
|---|---|---|---|---|---|
| 2018 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2018 | All selected publications | 8 | 5 | 5/5 | 5/5 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2018 | All selected publications | 18 | 5 | 5/5 | 5/5 |
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 5 / 5 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): 2026-10-22T01:51:47.967129+00:00 — 2026-10-29T10:44:16.313263+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 | 5 | 5/5 |
| 2018 | All selected publications | 0 | 5 | 5/5 |
| 2019 | All selected publications | 4 | 5 | 5/5 |
| 2020 | All selected publications | 0 | 5 | 5/5 |
| 2021 | All selected publications | 5 | 5 | 5/5 |
| 2022 | All selected publications | 1 | 5 | 5/5 |
| 2023 | All selected publications | 6 | 5 | 5/5 |
| 2024 | All selected publications | 1 | 5 | 5/5 |
| 2025 | All selected publications | 1 | 5 | 5/5 |
| 2026 | All selected publications | 0 | 5 | 5/5 |
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 |
|---|---|
| 2018 | 5 |
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 | 2 | 3 | 4 | 2/2 | 1.5 | 1.5 | 100.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 3 | 5 | 14 | 3/3 | 1.67 | 1 | 100.0 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
In today’s competitive retail market, as service quality improves, the customer’s expectation and lateral demand on service level is increased from time to time. Dairy milk processing firms in Kenya are struggling to get it right in providing service quality. This has created dissatisfied consumers and this has led to merging of some dairy milk processing firms and loss of jobs due to closure of some dairy milk processing firms. Therefore, this study aimed at filling this knowledge gap by examining the influence of perceived service quality on consumer satisfaction amongst dairy milk processors in Kenya. The study was guided by cross-sectional research design. The study population comprised of consumers who purchase processed dairy milk from major supermarket chains in Kenya. Primary data was collected from 384 respondents using a semi-structured questionnaire which was self-administered. Descriptive statistics and regression analysis were used to analyse data with the help of SPSS version 21. The results showed a positive and significant relationship between the perceived service quality and consumer satisfaction. Respondents indicated that, perceived service quality was consistent to their satisfaction. The findings showed that, consumers of dairy milk products had a high rating of service quality offered to them by dairy milk processors hence high satisfaction levels. The study therefore concluded that, perceived service quality is an important predictor of customer satisfaction. Milk processors must therefore strive to match and even exceed their customer’s product-service quality with what customers expect.
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.
Worldwide, Small and medium-size enterprises (SMEs) exhibit inimitable financial needs. While SMEs remain fundamental to economic growth, their mortality rate in Kenya approaches 90% by the second year, mainly owing to lack of credit. However, scholarly endeavors exploring the impact of alternative finance (AF) on managerial competency - efficiency nexus for manufacturing SMEs have received little attention in Kenya. To resolve this conundrum, a thorough study to investigate how AF impacts managerial competency - efficiency nexus is necessary. The study used a cross-sectional research design, employing both qualitative and quantitative research approaches. The target population was 171 SMEs registered with Kenya Association of Manufacturers. The accessible population was 136 SMEs owners/managers. A semi-structured questionnaire was used to collect primary and secondary data. Data envelopment analysis was used to measure efficiency, multiple regression modeling used to analyze the direct relationships while hierarchical moderated multiple regression analysis employed to test moderation. Partial Least Squares Structural Equation Modeling was used to test robustness of our results. The findings of this study demonstrate that managerial competency positively influences efficiency (? = 0.150, t-value =10.246, P<0.05), and that alternative finance does moderate managerial competency relationships with efficiency (R-Square change of 21.7%). We suggest trainings for manufacturing SME owners/managers in Kenya on the pivotal role of alternative finance to facilitate SMEs achieve higher efficiencies and accelerate economic growth.
Globally, countries are strategically positioning themselves for market leadership due to dynamic business environment. Entrepreneurial spirit is seen as the strategy that will deliver this agenda. This spirit, is believed to be behind the innovative business that revolutionizes the business world. In a dynamic and complex environment, the success of any business is pegged on the entrepreneurial operations of a firm. Entrepreneurial-oriented firms have been proven to be ahead of competition because they are always introduced new products and services and in turn improve their financial results. Scholars believe that learning and development can occur amongst people who actively engage in a common enterprise. This makes learning empowering and productive and thus sustains entrepreneurial orientation. This in turn produces communities of entrepreneurial practice. The role of the entrepreneurial manager is to nurture communities of growth-oriented firms where entrepreneurial learning takes place. The purpose of this study is to assess the relationship between entrepreneurial management and performance of incubator centres in Kenya. The study used a correlation design because it focused on a causal-effect relationship. The study population was 41 incubator managers in Kenya. After missing data analysis two respondents were expunged leaving 39 respondents. Secondary data was obtained from published sources such as company reports, manuals and research done by other scholars. Structural Equation Modelling (SEM) approach was used to analyze the measurement model and test the hypothesized relationship in this study. Simple linear regression model was used to measure the strength of the relationship between entrepreneurial management and performance incubator centre in Kenya. The joint effect model results indicated that entrepreneurial management had a significant relationship with performance of incubator centre.
Business incubators are regarded as entrepreneurial hubs, unleashing entrepreneur’s ideas and businesses into the market, in turn, jobs are created and the economy of the area is improved. Due to the stiff competition for placement into an incubator program it is imperative for incubator management come-up with strategies of being more efficient and effective in utilizing resources to achieve superior performance. Hence the need to critically select clients, whose ideas fit the incubator’s mission and upon graduation create high growth businesses, with a higher survival rate of 90%. The study is anchored on Resource Based Theory. The study used a correlation design that focused on causal relationship of client selection criteria and incubator centre performance (ICP). The study population was 41 incubator managers in Kenya. After missing data analysis two respondents were expunged leaving 39 respondents. Secondary data was obtained from published sources such as company reports, manuals and research done by other scholars. Structural Equation Modelling (SEM) approach was used to analyze the measurement model and test the hypothesized relationship in this study. Simple linear regression model was used to measure the strength of the relationship between client selection criteria and performance incubator centre in Kenya. The results of the combined effect model indicated that client selection criteria had a significant relationship with performance of incubator centres.
In today’s competitive retail market, as service quality improves, the customer’s expectation and lateral demand on service level is increased from time to time. Dairy milk processing firms in Kenya are struggling to get it right in providing service quality. This has created dissatisfied consumers and this has led to merging of some dairy milk processing firms and loss of jobs due to closure of some dairy milk processing firms. Therefore, this study aimed at filling this knowledge gap by examining the influence of perceived service quality on consumer satisfaction amongst dairy milk processors in Kenya. The study was guided by cross-sectional research design. The study population comprised of consumers who purchase processed dairy milk from major supermarket chains in Kenya. Primary data was collected from 384 respondents using a semi-structured questionnaire which was self-administered. Descriptive statistics and regression analysis were used to analyse data with the help of SPSS version 21. The results showed a positive and significant relationship between the perceived service quality and consumer satisfaction. Respondents indicated that, perceived service quality was consistent to their satisfaction. The findings showed that, consumers of dairy milk products had a high rating of service quality offered to them by dairy milk processors hence high satisfaction levels. The study therefore concluded that, perceived service quality is an important predictor of customer satisfaction. Milk processors must therefore strive to match and even exceed their customer’s product-service quality with what customers expect.
Worldwide, Small and medium-size enterprises (SMEs) exhibit inimitable financial needs. While SMEs remain fundamental to economic growth, their mortality rate in Kenya approaches 90% by the second year, mainly owing to lack of credit. However, scholarly endeavors exploring the impact of alternative finance (AF) on managerial competency - efficiency nexus for manufacturing SMEs have received little attention in Kenya. To resolve this conundrum, a thorough study to investigate how AF impacts managerial competency - efficiency nexus is necessary. The study used a cross-sectional research design, employing both qualitative and quantitative research approaches. The target population was 171 SMEs registered with Kenya Association of Manufacturers. The accessible population was 136 SMEs owners/managers. A semi-structured questionnaire was used to collect primary and secondary data. Data envelopment analysis was used to measure efficiency, multiple regression modeling used to analyze the direct relationships while hierarchical moderated multiple regression analysis employed to test moderation. Partial Least Squares Structural Equation Modeling was used to test robustness of our results. The findings of this study demonstrate that managerial competency positively influences efficiency (? = 0.150, t-value =10.246, P<0.05), and that alternative finance does moderate managerial competency relationships with efficiency (R-Square change of 21.7%). We suggest trainings for manufacturing SME owners/managers in Kenya on the pivotal role of alternative finance to facilitate SMEs achieve higher efficiencies and accelerate economic growth.
Globally, countries are strategically positioning themselves for market leadership due to dynamic business environment. Entrepreneurial spirit is seen as the strategy that will deliver this agenda. This spirit, is believed to be behind the innovative business that revolutionizes the business world. In a dynamic and complex environment, the success of any business is pegged on the entrepreneurial operations of a firm. Entrepreneurial-oriented firms have been proven to be ahead of competition because they are always introduced new products and services and in turn improve their financial results. Scholars believe that learning and development can occur amongst people who actively engage in a common enterprise. This makes learning empowering and productive and thus sustains entrepreneurial orientation. This in turn produces communities of entrepreneurial practice. The role of the entrepreneurial manager is to nurture communities of growth-oriented firms where entrepreneurial learning takes place. The purpose of this study is to assess the relationship between entrepreneurial management and performance of incubator centres in Kenya. The study used a correlation design because it focused on a causal-effect relationship. The study population was 41 incubator managers in Kenya. After missing data analysis two respondents were expunged leaving 39 respondents. Secondary data was obtained from published sources such as company reports, manuals and research done by other scholars. Structural Equation Modelling (SEM) approach was used to analyze the measurement model and test the hypothesized relationship in this study. Simple linear regression model was used to measure the strength of the relationship between entrepreneurial management and performance incubator centre in Kenya. The joint effect model results indicated that entrepreneurial management had a significant relationship with performance of incubator centre.
Business incubators are regarded as entrepreneurial hubs, unleashing entrepreneur’s ideas and businesses into the market, in turn, jobs are created and the economy of the area is improved. Due to the stiff competition for placement into an incubator program it is imperative for incubator management come-up with strategies of being more efficient and effective in utilizing resources to achieve superior performance. Hence the need to critically select clients, whose ideas fit the incubator’s mission and upon graduation create high growth businesses, with a higher survival rate of 90%. The study is anchored on Resource Based Theory. The study used a correlation design that focused on causal relationship of client selection criteria and incubator centre performance (ICP). The study population was 41 incubator managers in Kenya. After missing data analysis two respondents were expunged leaving 39 respondents. Secondary data was obtained from published sources such as company reports, manuals and research done by other scholars. Structural Equation Modelling (SEM) approach was used to analyze the measurement model and test the hypothesized relationship in this study. Simple linear regression model was used to measure the strength of the relationship between client selection criteria and performance incubator centre in Kenya. The results of the combined effect model indicated that client selection criteria had a significant relationship with performance of incubator centres.
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.
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 |