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: 126 / 126 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 — 01 Nov 2026 22:30 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.
126 / 126 with data · 0 missing or unmatched. Percentages use all 126 selected publications.
126 / 126 with data · 0 missing or unmatched. Percentages use all 126 selected publications.
126 / 126 with data · 0 missing or unmatched. Percentages use all 126 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 | 1 | 1 | 1/1 | 1/1 |
| 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 | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2019 | All selected publications | 19 | 19 | 19/19 | 19/19 |
| 2020 | All selected publications | 29 | 29 | 29/29 | 29/29 |
| 2021 | All selected publications | 31 | 31 | 31/31 | 31/31 |
| 2022 | All selected publications | 26 | 26 | 26/26 | 26/26 |
| 2023 | All selected publications | 10 | 10 | 10/10 | 10/10 |
| 2024 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 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 | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 5 | 4 | 4/4 | 4/4 |
| 2019 | All selected publications | 20 | 19 | 19/19 | 19/19 |
| 2020 | All selected publications | 43 | 29 | 29/29 | 29/29 |
| 2021 | All selected publications | 41 | 31 | 31/31 | 31/31 |
| 2022 | All selected publications | 38 | 26 | 26/26 | 26/26 |
| 2023 | All selected publications | 11 | 10 | 10/10 | 10/10 |
| 2024 | All selected publications | 3 | 5 | 5/5 | 5/5 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2013 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 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 | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 9 | 4 | 4/4 | 4/4 |
| 2019 | All selected publications | 50 | 19 | 19/19 | 19/19 |
| 2020 | All selected publications | 80 | 29 | 29/29 | 29/29 |
| 2021 | All selected publications | 79 | 31 | 31/31 | 31/31 |
| 2022 | All selected publications | 65 | 26 | 26/26 | 26/26 |
| 2023 | All selected publications | 16 | 10 | 10/10 | 10/10 |
| 2024 | All selected publications | 7 | 5 | 5/5 | 5/5 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.
The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.
Annual history available for 126 / 126 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): 2026-10-21T07:22:43.080591+00:00 — 2026-11-01T22:30:20.598139+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 | 126 | 126/126 |
| 2018 | All selected publications | 0 | 126 | 126/126 |
| 2019 | All selected publications | 3 | 126 | 126/126 |
| 2020 | All selected publications | 4 | 126 | 126/126 |
| 2021 | All selected publications | 23 | 126 | 126/126 |
| 2022 | All selected publications | 43 | 126 | 126/126 |
| 2023 | All selected publications | 61 | 126 | 126/126 |
| 2024 | All selected publications | 83 | 126 | 126/126 |
| 2025 | All selected publications | 57 | 126 | 126/126 |
| 2026 | All selected publications | 34 | 126 | 126/126 |
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 | 1 |
| 2018 | 4 |
| 2019 | 19 |
| 2020 | 29 |
| 2021 | 31 |
| 2022 | 26 |
| 2023 | 10 |
| 2024 | 5 |
| 2025 | 1 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| Bussecon Review of Social Sciences Bussecon International Academy | 2 | 5 | 5 | 2/2 | 2.5 | 2.5 | 100.0 | 2/2 · 100.0% |
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 7 | 13 | 21 | 7/7 | 1.86 | 2 | 71.4 | 7/7 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 12 | 11 | 24 | 12/12 | 0.92 | 1.0 | 66.7 | 12/12 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 105 | 133 | 258 | 105/105 | 1.27 | 1 | 73.3 | 105/105 · 100.0% |
* Percentage among publications with a known citation count.
This paper aims to develop a critical approach to the conceptualization of start-ups in emerging markets from a Kenyan perspective. This study used a theoretical route to conceptualize start-ups in emerging markets like Kenya. From the findings, it is important to note that the conceptualization of start-up is based on western concepts and might be flawed and poorly applicable to businesses in Kenya. Hence in the Kenyan context, a start-up should be viewed as an innovative business entity, which is scalable and has survived up to 3-5 years. To support the growth of the start-up ecosystem in Kenya, policymakers should promote start-ups through the formation of relevant legislation and provide incentives that stimulate their survival and growth. The study has brought out some interesting findings which can generate more debate. The study used an exploratory research design which is not conclusive in nature therefore future research should consider using a research design that is conclusive in nature and robust.
Kenya is rapidly urbanizing at an annual rate of about 4.3%. One of the consequences of urbanization has been the problem of food insecurity in peri-urban areas. Increased migration to urban from rural areas has enhanced food insecurity in these areas. The peri-urban area of Kangundo-Tala in Machakos County is one of the fastest-growing peri-urban areas due to its proximity to the capital city of Nairobi. This study investigated the impact of home gardening in enhancing food security in the rapidly urbanizing middle-income Kangundo–Tala peri-urban areas of Machakos County, Kenya. The specific objectives of the study were: to identify the causes of households’ food insecurity in the study area; to examine the factors influencing the adoption of home gardening and; to establish the role of home gardening as a measure of households’ food security. To measure food security, three consumption behaviors were analyzed: consumption changes, food expenditure reduction and income expansion. A qualitative approach was adopted where a total of 120 newly settled households were interviewed. The three main causes of food insecurity were identified (i) small land sizes, (ii) low and erratic rainfall and, (iii) the socialization of peri-urban dwellers. About 68% of the households were practicing at least one form of home gardening. The need for safe and nutritious food, seasonal unavailability, and inaccessibility of food encouraged the establishment of home gardens. From the gardens, households were able to diversify their diets, access safe food and have food readily available. With enhanced stability in food availability, accessibility, and utilization, the study concluded that home gardens played a major role in enhancing food. However, the production was at a very small scale. Up-scaling of home gardening by the Ministry of Agriculture through training was recommended.
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
Talent management impacts on service delivery in the hospitality industry. The aim of the study was to assess the effect of learning and development on service delivery in the hospitality industry in Nyeri County, Kenya. The study employed a cross-sectional survey design to determine the relationship between the variables. The target population was 310 employees of three hotels who comprised of supervisors, room stewards, food and beverage managers, waiters, storekeepers, and chefs in three hospitality establishments in Nyeri County. The research used a stratified sampling technique to select 104 participants for the study. The main instrument for data collection was a semi-structured questionnaire. The findings of the study revealed that learning and development have a significant and positive influence on service delivery. The study recommends that organizations should stress and develop robust learning and development interventions to mitigate performance-related challenges, realize the desired quality service delivery and stability, and gain a competitive edge. It is hoped and desired that this journal will lead to a supplementary examination of the bene?ts of this refocus on talent and management, including the development of useful de?nitions.
Sub-Saharan Africa lags other regions in the adoption of both Patient-Centered (PC) and Facility Centered (FC) mobile health (m-health) applications. Transformational Leadership Style (TLS) of Hospital Management Boards (HMBs) is catalytic for the adoption of disruptive technologies such as m-health by hospitals. There is limited evidence on the effect of TLS of HMBs in the adoption of innovations in Low- and Middle-Income Countries (LMICS). This study investigated the moderating role of TLS of HMBs on the adoption of PC and FC m-health by hospitals in Kenya. It used the Logit Regression Model to test null hypotheses that the four constructs of TLS (Idealized Influence (II), Individualized Consideration (IC), Inspirational Motivation (IM), Intellectual Stimulation (IS)) individually or combined had no significant moderating effect on adoption of PC and FC m-health applications. Primary data was collected from a representative sample size of 211 Top Executives (TEs) of level 4 to 6 hospitals who evaluated the TLS of their HMBs on m-health adoption. At a 5% level of significance, the study found that only the combined application of the four constructs (II, IC, IM, IS) significantly moderated the adoption of PC m-health (p=0.046) but did not moderate FC m-health (p=0.345). Each incremental application of TLS would increase the odds of adopting PC m-health by 1.002 but not for FC. Therefore, this study recommends the capacity strengthening of HMBs in TLS to scale up PC m-health adoption in Kenya and other LMICs. It also recommends a differentiated approach to policies, practices, and theories of adoption of innovations using the PC-FC models.
The banking industry in Kenya must adopt digital transformation to sustain competitiveness and improve customer experience in the context of rapidly evolving digital technologies. Despite the increasing focus on digitisation in the sector, the particular initiatives undertaken by commercial banks and their resulting impact on competitive advantage are not sufficiently comprehended. This study analysed the impact of digital transformation strategies on competitive advantage within commercial banks in Kenya. The primary aim was to evaluate the impact of service automation, data analytics, mobile banking applications, employee upskilling, and digital payment solutions on the competitiveness of banks. The study employed a descriptive design, focussing on 39 commercial banks categorised by tiers, which included 412 functional heads. A multi-stage sampling method integrating proportionate stratified and simple random sampling techniques was utilised to guarantee equitable representation. Employing Yamane’s formula, a sample of 203 respondents was determined. Primary data were collected using structured questionnaires that were pretested with 15 participants and validated by subject experts to ensure content relevance and clarity. Reliability testing employing Cronbach’s Alpha produced satisfactory results (? ? 0.7), signifying robust internal consistency. The analysis of data encompassed both descriptive and inferential statistics. The results were presented visually through charts, graphs, and tables to facilitate interpretation. The findings indicated that all five digital transformation strategies impacted competitive advantage, although their contributions differed in magnitude. The findings indicate that commercial banks must move beyond the simple implementation of digital technologies and prioritise strategic integration to improve customer experience and value creation. Banks ought to implement targeted automation that preserves human engagement for intricate services while improving feedback systems. Banks must enhance data governance and invest in sophisticated, customer-centric analytical tools. Ongoing innovation in mobile banking is advisable, encompassing feature enhancements and improved interoperability, underpinned by robust cybersecurity standards. Prioritising employee upskilling is essential through structured training, digital leadership development, and industry-wide certification. Finally, banks must reassess their digital payment strategies to prioritise user experience, fraud prevention, and differentiated services, while regulators encourage secure and innovation-friendly environments.
Management by Objectives (MBO) is a performance management approach where employees and managers collaborate to set individual goals aligned with broader organizational objectives. While MBO's potential benefits are recognized, its effectiveness particularly in the context of varying organizational cultures and appraisal purposes, remains unclear. The general objective of the study was to investigate the relationship between MBO and employee performance within Isiolo County Government. The study specifically examined the influence of evaluation on employees’ performance in Isiolo County. The study was grounded on image theory. The population of study was 260 employees across seven county ministries. Data was collected using a questionnaire subjected to pilot study. Quantitative data was analyzed using both descriptive and inferential statistics. The study showed that overall evaluation (with a p-value of 0.897) does not significantly contribute to employee performance within the County Government of Isiolo. Therefore, the null hypothesis for evaluation was accepted. Because the study found no significant influence of evaluation on employee performance, there is a critical need for organization to refine their evaluation systems. To gain a deeper understanding of the long-term impact of evaluation on employee performance in Kenyan county governments, longitudinal research is warranted. The study recommends need for Isiolo County Government to improve its evaluation processes. Evaluators should provide valuable input to aid in performance improvement in employees of Isiolo county government.
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.
Commercial banks in Kenya operate in quite dynamic financial market environment and continue to experience stiff competition in the provision of financial services. The liberation of the financial markets has resulted into an upsurge in the number of institutions providing financial products and services, threatening the future of Kenyan commercial banks. This study aimed at determining the effect of strategic alliances on competitive advantage of commercial banks in Kenya. The objectives were to determine effect of joint ventures, equity alliances, and joint research and development on the competitiveness of Kenyan banks. The following theories informed this research; Resource Based View theory, competitive theory, and resource dependence theory. Causal research design was adopted where all the 42 Kenyan commercial banks formed the target population. Census survey sampling design was applied and semi-structured questionnaire used. Reliability and validity results were used to improve the research instrument prior to the actual data collection. Data was analyzed using descriptive and inferential statistics. Study found that joint venture (?=0.435, p=0.000) equity alliances (?=0.227, p=0.018), and joint research and development (?=0.0.612, p=0.000) had positive significant effects on competitive advantage. With a coefficient of determination (R-square) of 68.9% and overall p-value of 0.000, the study concluded strategic alliances have a statistical significant effect on competitive advantage. The study recommends that managements of commercial banks should fast-truck implementation of such alliances to for improved competitiveness.
Kenya has seen a boom in road building during the last couple of years as a result of the government's significant investments in the construction industry to upgrade infrastructure, such as road networks. Road network construction is one of the key pillar of the country long term vision 2030. However, the performance of the road projects has experienced various challenges leaving some roads uncompleted, others poorly done after huge investment of public resources. This study sought to evaluate the influence of financial resources scheduling on the performance of road construction projects in Nairobi Metropolitan, Kenya. The research was based on resource dependence theory. A descriptive design as well as the cross-sectional survey was used. The population of interest for this study consisted of 39 road construction projects being implemented by Kenya Urban Roads Authority and Kenya National Highway Authority within the Nairobi metropolitan area. A semi structured questionnaire was utilized to collect primary data. The quantitative data was analyzed using descriptive and inferential statistics. The study results revealed projects resource scheduling had a positive and significant effect on project performance of road construction projects in Nairobi Metropolitan, Kenya. The study concludes that effective financial resource scheduling enables that organization to manage risk that may occur from changes in the project’s outcome. Financial resource scheduling starts from developing the project budget which is a process for allocating administered and departmental funds necessary to build a financial foundation for producing stated project deliverables.
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 |