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: 10 / 10 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 00:49 UTC — 22 Oct 2026 07:34 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.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 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 |
|---|---|---|---|---|---|
| 2021 | All selected publications | 10 | 10 | 10/10 | 10/10 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 22 | 10 | 10/10 | 10/10 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 37 | 10 | 10/10 | 10/10 |
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 10 / 10 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): 2026-10-22T00:49:58.615405+00:00 — 2026-10-22T07:34:31.596138+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 | 10 | 10/10 |
| 2018 | All selected publications | 0 | 10 | 10/10 |
| 2019 | All selected publications | 0 | 10 | 10/10 |
| 2020 | All selected publications | 0 | 10 | 10/10 |
| 2021 | All selected publications | 1 | 10 | 10/10 |
| 2022 | All selected publications | 8 | 10 | 10/10 |
| 2023 | All selected publications | 11 | 10 | 10/10 |
| 2024 | All selected publications | 7 | 10 | 10/10 |
| 2025 | All selected publications | 4 | 10 | 10/10 |
| 2026 | All selected publications | 6 | 10 | 10/10 |
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 |
|---|---|
| 2021 | 10 |
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 | 6 | 10 | 2/2 | 3.0 | 3.0 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 8 | 16 | 27 | 8/8 | 2.0 | 1.0 | 62.5 | 8/8 · 100.0% |
* Percentage among publications with a known citation count.
The objective of this paper was to present a dynamic resource orchestration framework as a source of organizational resilience through blended orchestration of the firm's dynamic and static resources to generate sustained value during disruptive shocks. We adopted an integrative literature review methodology and proposed a dynamic resource orchestration framework as a managerial option to create and sustain firm value. Conceptually, a dynamic resource orchestration framework was presented as the integration of firm resources and managerial capability. We proposed dynamic resource orchestration as a model input impacting organizational resilience through the combined effects of resource accumulation, resource orchestration, and managerial capabilities. Through a thorough examination of the literature production anchored on dynamic capabilities framework and organizational resilience, we advanced a perspective that the ultimate source of combined firm resilience and sustainable competitive advantage does not necessarily accrue from the resources at a firm's disposal but by how management dynamically blends and orchestrates the existing resources, thereby creating an optimal source of capability. Our proposed conceptualization was based on the assumption that dynamic capabilities are part of firm resources and, therefore, strategic orchestration of dynamic capabilities leads to superior firm resourcefulness and consequential sustained resilience. We identified gaps and proposed directions for future research.
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.
This study aims to investigate the effect of demographic factors on the turnover intentions of teachers in public secondary schools in Murang’a county Kenya. The study was guided by the following specific objectives: To investigate the association between age and education and turnover intentions; to establish the association between gender and turnover intentions; to determine the association between tenure and turnover intentions and to establish the association between educational level and turnover intentions. The study was guided by the Social exchange and Organization equilibrium theories. This study was a cross-sectional study and adopted descriptive and explanatory research designs. The target population was 3752 Teachers Service Commission (TSC) teachers in 304 public secondary schools in Murang’a county Kenya. The study thus used multi-stage random to select a sample size of 400 teachers and 40 schools. A self-administered questionnaire was used to collect the demographic data. Data were analyzed using cross-tabulation and Pearson Chi-square statistics. The study findings indicated that age has a significant association with turnover intentions while employee tenure, gender, and educational level have no significant association with turnover intentions.
The Micro Small and Medium Enterprises (MSMEs) are important for every nation’s economic development. They provide employment and spur the growth of multiple sectors in the economy. The Covid-19 pandemic has negatively affected MSMEs' performance. The study seeks to demonstrate why COVID 19 may lead to the terminal quarantining of MSMEs. The study is anchored on decision usefulness and information asymmetry theories. The study adopted a descriptive research methodology and sampled MSMEs within Nairobi City County. The study used SPSS to analyze data in addition to Microsoft excel. The study found that over 70% of MSMEs had their sales decline by over 65% while 95% of them had their sales decline by over 30%. The study found that about 68% of MSMEs lacked financial management skills. The study recommends that with legal and institutional reforms, the government needs to develop a financing framework for MSMEs.
Organizations are experiencing increased challenges due to changed environmental circumstances that threaten their survival including institutions of higher learning. There is therefore a growing concern for universities to be strategically aligned so as to meet the growing challenges of the societies in which they operate by creating ecosystems that drive industrialization through the generation of new knowledge, technology transfer and support of new start-ups. Additionally, concerns have been raised as regards the quality and relevance of services offered by the universities in Kenya. Owing to these limitations, there is a need for the higher education sector to consider inspirational motivation practices between the leaders and their followers so as to enhance performance. This study, therefore, sought to establish the effect of inspirational motivation on the academic performance of selected universities in Kenya. The study was anchored on transformational leadership theory. Positivism research philosophy was adopted where explanatory and descriptive research designs were used for guiding the collection and analysis of data. Primary data was collected from deans of schools and chairmen of departments in the selected universities. The study established a significant positive effect of inspirational motivation on academic performance of universities at p<0.05; t=8.057 and hence concluded that inspirational motivation positively affects university academic performance of selected universities in Kenya.
The objective of this paper was to present a dynamic resource orchestration framework as a source of organizational resilience through blended orchestration of the firm's dynamic and static resources to generate sustained value during disruptive shocks. We adopted an integrative literature review methodology and proposed a dynamic resource orchestration framework as a managerial option to create and sustain firm value. Conceptually, a dynamic resource orchestration framework was presented as the integration of firm resources and managerial capability. We proposed dynamic resource orchestration as a model input impacting organizational resilience through the combined effects of resource accumulation, resource orchestration, and managerial capabilities. Through a thorough examination of the literature production anchored on dynamic capabilities framework and organizational resilience, we advanced a perspective that the ultimate source of combined firm resilience and sustainable competitive advantage does not necessarily accrue from the resources at a firm's disposal but by how management dynamically blends and orchestrates the existing resources, thereby creating an optimal source of capability. Our proposed conceptualization was based on the assumption that dynamic capabilities are part of firm resources and, therefore, strategic orchestration of dynamic capabilities leads to superior firm resourcefulness and consequential sustained resilience. We identified gaps and proposed directions for future research.
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.
The study sought to assess the importance of classifying incubators based on the programs offered for optimum performance. Client selection criteria were assessed through three constructs namely: models that fit program goals, uniqueness of ideas, and standard selection tool. A mixed cross-sectional and causal design was adopted and a census was carried out targeting all the 51 incubators. Primary data was collected with an incubator program as a grouping/ cluster variable yielding a multilevel data structure with incubator centres nested in programs. Linear mixed effect models were fitted using Stata to assess the study objective taking into account the fixed effects for the incubator centre level (level-1) and random effects for the program level (level-2). The uniqueness of ideas was found to have a significant fixed effect on performance at level one while at level two, the study found significant random intercepts of incubator centre performance across the programs. Models that match program goals and standard selection tools were also found to have significant random slopes as level two random covariates in the model. Based on the findings of significant random slopes, the study concluded that incubator classification is key for client selection criteria and enhances incubator performance.
The collective investment schemes in Kenya have witnessed increased volatility in their earnings, resulting in irregular growth in the industry. This necessitates the need to understand the factors contributing to poor financial returns from collective investment schemes. Hence this study sought to investigate the effect of equity investments and bond investments on Kenyan CIS’s performance. The specific objectives were: To assess the effect of equity investments, bond investments on financial performance of collective investment schemes in Kenya. The study was anchored on: modern portfolio theory and the efficient market hypothesis. The positivism philosophy was applied, with the firms adopting an explanatory research design. The target population was 17 Collective Investment Schemes registered by the Capital Markets Authority and were operational in the period 2010 to 2018. Secondary data was sought from the Capital Markets Authority Annual reports and from the respective websites of the CIS’. Data was analyzed using descriptive statistics, correlational analysis and panel regression analysis. Hypotheses were tested at a significance level of 0.05. Findings indicate that equity investment, bond investments have an insignificant effect on CIS’ return on assets. Further, equity investments had a positive and significant effect on liquidity whereas bond investments had an insignificant effect on liquidity. The study recommends that CISs actively revise their equity investments and bond investments to stimulate financial returns.
Policymakers and scholars acknowledge the significance of small and medium enterprises in stirring the economic growth and development in developing and developed economies. In spite of the generally fast pace by which access to financial services for small and medium enterprises is being established, significant segments of the small and medium enterprises sector do not yet benefit from the expansion. This study, therefore, investigated the effect of relationship lending on access to financial services by small and medium enterprises in Kenya. The study was based on credit rationing theory and information asymmetry theory. The target population comprised 4,253 small and medium enterprises in Kenya. A sample size of 366 SMEs was used by the study. The study adopted a multistage sampling technique to obtain the SME respondents. Primary data was utilized and was acquired through semi-structured questionnaires. Data were analyzed using descriptive and inferential statistics utilizing Heckman two-stage regression model. The study findings showed that relationship lending had a positive and significant effect on access to financial services among SMEs in Kenya. The study concluded that relationship lending plays a critical role in access to financial services by SMEs in Kenya. The study recommends that SMEs owners should strive to meet the terms and conditions provided by lending institutions in their various financing practices while management of the lending institutions should adopt financing practices favorable to SMEs to increase their access to financial services.
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 |