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: 7 / 7 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 — 23 Oct 2026 10:30 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.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 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 | 2 | 2 | 2/2 | 2/2 |
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2018 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2018 | All selected publications | 5 | 2 | 2/2 | 2/2 |
| 2019 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.
The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.
Annual history available for 7 / 7 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): 2026-10-21T07:22:51.961802+00:00 — 2026-10-23T10:30:17.928852+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 | 7 | 7/7 |
| 2018 | All selected publications | 0 | 7 | 7/7 |
| 2019 | All selected publications | 1 | 7 | 7/7 |
| 2020 | All selected publications | 0 | 7 | 7/7 |
| 2021 | All selected publications | 3 | 7 | 7/7 |
| 2022 | All selected publications | 1 | 7 | 7/7 |
| 2023 | All selected publications | 3 | 7 | 7/7 |
| 2024 | All selected publications | 2 | 7 | 7/7 |
| 2025 | All selected publications | 2 | 7 | 7/7 |
| 2026 | All selected publications | 2 | 7 | 7/7 |
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 | 2 |
| 2019 | 1 |
| 2020 | 1 |
| 2021 | 1 |
| 2023 | 2 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| International Journal of Research in Business and Social Science SSBFNET | 7 | 8 | 14 | 7/7 | 1.14 | 1 | 85.7 | 7/7 · 100.0% |
* Percentage among publications with a known citation count.
This paper was anchored on a pragmatic research paradigm. The study used a cross-sectional survey where a self-semi structured questionnaire was administered to collect the primary data from the target population who were youth-owned SMEs. The study was limited to 135 youth-owned enterprises where 357 employees were selected randomly to form the study sample; the key respondents of the study were limited to owner-managers of small and micro enterprises and top management employees. The questionnaires were tested for reliability and validity. Data were analyzed using descriptive and inferential statistics. The study revealed that there is a significant relationship between youth-owned. The study revealed that entrepreneurship networking has a significant effect on the performance of the agro-processing SMEs owned by the youths. However, there is a need for SMEs to further establish networks outside their business circle and seek networks with other bigger firms in the market. The study, therefore, recommends that there is a need for SMEs to invest more in social media marketing and networking of the SMEs for improved performance.
Firms are driven to maximize profits, requiring specialized techniques to improve performance. Firms can handle chaotic conditions by acting strategically. Global studies show high early-stage SME death rates. Hospitality studies have not examined how lean-green methods boost performance and competitiveness. Lean-green methods affect the entrepreneurial spirit and performance of medium-sized hotels in Kenyan cities. The paper relies on discovery and dynamic capability theory. The article used mixed-methods, concurrent triangulation, and pragmatic philosophy. 534 medium hotel managers in Mombasa, Nairobi, and Kisumu were studied, and 229 were sampled using stratified random sampling. Data was collected by questionnaire and saved in MS Excel for case-variable screening and cleaning. SPSS 22 was used for data analysis. Pearson's correlation and regression models analyzed quantitative data. In Kenyan cities, entrepreneurial attitude positively affects medium hotel performance (=.775, t = 17.499, p.05). Lean-green synergy positively impacted performance (? =.527, t = 12.497, p ?.05) and moderated the connection between entrepreneurial mentality and business performance. The study found that lean-green techniques boost performance. Lean-green production strategies are recommended by the study. These findings benefit hotel entrepreneurs, managers, academia, and legislators. The study proposes studying other industries besides hospitality to see whether comparable findings are found.
The study explores the impact of entrepreneurial passion on process innovation and firm performance, based on self-efficacy theory. Relevant hypotheses were proposed, and the promotion mechanism of entrepreneurial passion on process innovation and enterprise performance was analyzed. A survey of 150 Kenyan firm owners/managers was conducted, and the results showed that process innovation has a significant positive effect on performance. Entrepreneurial passion is a significant moderator of the relationship between process innovation and performance, with firms with higher levels of passion achieving greater performance from implementing process innovation. This suggests that entrepreneurial passion can guide entrepreneurial persistence and promote enterprise performance by stimulating positive emotions and creativity. The study suggests that effective management of process innovation can enhance performance and encourage more entrepreneurial behavior in competitive business environments.
Non-Governmental Organizations (NGOs) play a critical role in addressing social ills like poverty, employment, and food insecurity; therefore, their growth prospects enhance their ability to address these social ills. Discovery of entrepreneurial opportunities amongst the agro-based NGOs has not got the desired attention, and it is the least researched area in social entrepreneurship. This study investigated the relationship between Entrepreneurial Opportunity Discovery Dimensions and Growth of Non-Governmental Organizations in Kenya. It employed correlation design and was anchored on the Kirznerian Entrepreneurship Theory. The target population was 135 agro-based NGOs in Kenya. A mixed-method approach was used, combined qualitative and quantitative techniques. Statistical Package for Social Sciences (SPSS) version 21 and Analysis of Moment Structures (AMOS graphic-25) aided in the analysis. Structural Equation Modeling (SEM) using AMOS and Simple linear regression analysis were the primary analysis techniques used to evaluate the relationship between entrepreneurial opportunity discovery dimensions and the growth of NGOs. The results indicated that alertness0.372, p=0.033)and prior knowledge (0.163, p=0.031) have a significant favorable influence on growth, while social networks 0.047, p=0.713) showed an insignificant effect on the growth of NGOs. Investing in acquiring alert individuals and helping them gain relevant knowledge in the 21sttechnologies and emerging issues can lead to increased NGO ability to continue serving the community effectively and be engines of development for the general good of Kenya.
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.
Firms are driven to maximize profits, requiring specialized techniques to improve performance. Firms can handle chaotic conditions by acting strategically. Global studies show high early-stage SME death rates. Hospitality studies have not examined how lean-green methods boost performance and competitiveness. Lean-green methods affect the entrepreneurial spirit and performance of medium-sized hotels in Kenyan cities. The paper relies on discovery and dynamic capability theory. The article used mixed-methods, concurrent triangulation, and pragmatic philosophy. 534 medium hotel managers in Mombasa, Nairobi, and Kisumu were studied, and 229 were sampled using stratified random sampling. Data was collected by questionnaire and saved in MS Excel for case-variable screening and cleaning. SPSS 22 was used for data analysis. Pearson's correlation and regression models analyzed quantitative data. In Kenyan cities, entrepreneurial attitude positively affects medium hotel performance (=.775, t = 17.499, p.05). Lean-green synergy positively impacted performance (? =.527, t = 12.497, p ?.05) and moderated the connection between entrepreneurial mentality and business performance. The study found that lean-green techniques boost performance. Lean-green production strategies are recommended by the study. These findings benefit hotel entrepreneurs, managers, academia, and legislators. The study proposes studying other industries besides hospitality to see whether comparable findings are found.
The study explores the impact of entrepreneurial passion on process innovation and firm performance, based on self-efficacy theory. Relevant hypotheses were proposed, and the promotion mechanism of entrepreneurial passion on process innovation and enterprise performance was analyzed. A survey of 150 Kenyan firm owners/managers was conducted, and the results showed that process innovation has a significant positive effect on performance. Entrepreneurial passion is a significant moderator of the relationship between process innovation and performance, with firms with higher levels of passion achieving greater performance from implementing process innovation. This suggests that entrepreneurial passion can guide entrepreneurial persistence and promote enterprise performance by stimulating positive emotions and creativity. The study suggests that effective management of process innovation can enhance performance and encourage more entrepreneurial behavior in competitive business environments.
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.
This paper was anchored on a pragmatic research paradigm. The study used a cross-sectional survey where a self-semi structured questionnaire was administered to collect the primary data from the target population who were youth-owned SMEs. The study was limited to 135 youth-owned enterprises where 357 employees were selected randomly to form the study sample; the key respondents of the study were limited to owner-managers of small and micro enterprises and top management employees. The questionnaires were tested for reliability and validity. Data were analyzed using descriptive and inferential statistics. The study revealed that there is a significant relationship between youth-owned. The study revealed that entrepreneurship networking has a significant effect on the performance of the agro-processing SMEs owned by the youths. However, there is a need for SMEs to further establish networks outside their business circle and seek networks with other bigger firms in the market. The study, therefore, recommends that there is a need for SMEs to invest more in social media marketing and networking of the SMEs for improved performance.
Non-Governmental Organizations (NGOs) play a critical role in addressing social ills like poverty, employment, and food insecurity; therefore, their growth prospects enhance their ability to address these social ills. Discovery of entrepreneurial opportunities amongst the agro-based NGOs has not got the desired attention, and it is the least researched area in social entrepreneurship. This study investigated the relationship between Entrepreneurial Opportunity Discovery Dimensions and Growth of Non-Governmental Organizations in Kenya. It employed correlation design and was anchored on the Kirznerian Entrepreneurship Theory. The target population was 135 agro-based NGOs in Kenya. A mixed-method approach was used, combined qualitative and quantitative techniques. Statistical Package for Social Sciences (SPSS) version 21 and Analysis of Moment Structures (AMOS graphic-25) aided in the analysis. Structural Equation Modeling (SEM) using AMOS and Simple linear regression analysis were the primary analysis techniques used to evaluate the relationship between entrepreneurial opportunity discovery dimensions and the growth of NGOs. The results indicated that alertness0.372, p=0.033)and prior knowledge (0.163, p=0.031) have a significant favorable influence on growth, while social networks 0.047, p=0.713) showed an insignificant effect on the growth of NGOs. Investing in acquiring alert individuals and helping them gain relevant knowledge in the 21sttechnologies and emerging issues can lead to increased NGO ability to continue serving the community effectively and be engines of development for the general good of 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 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |