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: 4 / 4 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 — 22 Oct 2026 01:51 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.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 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 |
|---|---|---|---|---|---|
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 6 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 6 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 7 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 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 4 / 4 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): 2026-10-21T07:22:56.412730+00:00 — 2026-10-22T01:51:33.216318+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 | 4 | 4/4 |
| 2018 | All selected publications | 0 | 4 | 4/4 |
| 2019 | All selected publications | 0 | 4 | 4/4 |
| 2020 | All selected publications | 1 | 4 | 4/4 |
| 2021 | All selected publications | 2 | 4 | 4/4 |
| 2022 | All selected publications | 0 | 4 | 4/4 |
| 2023 | All selected publications | 2 | 4 | 4/4 |
| 2024 | All selected publications | 3 | 4 | 4/4 |
| 2025 | All selected publications | 3 | 4 | 4/4 |
| 2026 | All selected publications | 2 | 4 | 4/4 |
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 |
|---|---|
| 2019 | 1 |
| 2020 | 1 |
| 2024 | 1 |
| 2026 | 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 |
|---|---|---|---|---|---|---|---|---|
| International Journal of Research in Business and Social Science SSBFNET | 4 | 8 | 13 | 4/4 | 2.0 | 1.0 | 50.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
The study sought to determine the influence of human resource planning on firm performance of firms listed in the Nairobi Securities Exchange in Kenya. The study was anchored on human capital theory and shareholder value maximization theory. The research design used was a cross-sectional survey while the study population constituted all the 68 listed firms at the Nairobi Stock Exchange (NSE) as in May 2017. The target population included the head of human resources and finance directors in all the listed firms. The sample size comprised of 136 respondents, and data was collected through structured questionnaires to meet the objectives of the study. Responses were tabulated, coded, and processed by the use of a computer Statistical Package for Social Science (SPSS) to analyze the data. Both descriptive and inferential statistical techniques were used to analyze the data. To test hypotheses, a simple linear model was used to test significance between the independent and dependent variable. The study findings revealed that the relationship between human resource planning and firm performance was positive and statistically significant and hence rejected the null hypothesis. The study concluded that the type and strategy of the firm, succession planning, matching skills with jobs and skills inventory are human resource planning indicators influencing the performance of firms listed in the NSE. It is therefore recommended that firms should continue to practice and maintain adequate human resource planning as it plays a fundamental role in achieving the objectives of the organizations.
Previous studies have established that the telecommunications industry in Kenya is characterized by decreasing voice revenues, many regulations, technological progress and varying consumer needs. This phenomenon has resulted in industry companies developing sound innovation strategies to make sure they form a competitive advantage over their rivals with the aim of ensuring their survival and growth in the evermore cut-throat marketplace. Nevertheless, in spite of the essential part played by these innovation strategies to safeguard competitive advantage, several companies have failed to translate the plans into reality. Therefore, the major objective of this study was to investigate the influence of technological innovation on the competitive advantage of telecommunication companies in Kenya. Technological innovation was measured by expansion of Global System for Mobile Communications (GSM) networks; new equipment and software; and partnerships and synergies. To satisfy the objective of this paper, a positivist philosophical stance was adopted and research design using cross-sectional survey data used. Data was collected using proportionate sampling from 247 managers. The results indicate that technological innovation improves the competitive advantage of telecommunication companies in Kenya. However, with government regulation as a moderating variable, only the new equipment, and software constructs had a positive and significant influence on the dependent variable. Ultimately, the findings suggest that government regulation moderates the influence of technological innovation on the competitive advantage of telecommunication companies in Kenya.
Access to clean and safe water remains a critical development priority under Sustainable Development Goal (SDG) 6. However, water service providers in Sub-Saharan Africa, including Kenya, continue to experience performance challenges associated with governance, infrastructure limitations, and leadership effectiveness. This study examined the moderating effect of employee engagement on the relationship between exemplary transformational leadership and the performance of selected water and sewerage companies in Kenya. Grounded in transformational leadership theory, the three-component theory of work engagement, and the balanced scorecard framework, the study adopted a positivist philosophy and a quantitative cross-sectional survey design. Data were collected from 328 employees drawn from 13 public water companies operating under the Athi Water Works Development Agency using structured questionnaires. Exemplary transformational leadership was measured through three practices—modeling the way, challenging the process, and empowering followers—while employee engagement was assessed through vigor, dedication, and absorption. Organizational performance was evaluated using indicators of service quality, economic efficiency, and operational sustainability. Descriptive statistics, Pearson correlation, and moderated multiple regression analysis were conducted using SPSS version 27. The findings revealed that exemplary transformational leadership and employee engagement significantly and positively influenced water company performance. Importantly, employee engagement significantly moderated the relationship between exemplary transformational leadership and performance (β = −0.689, p < .05), indicating a buffering effect in which leadership had a stronger impact under conditions of low engagement. The study contributes to leadership and public sector management literature by empirically validating the moderating role of employee engagement within Kenya’s water sector. It recommends integrating employee engagement strategies with leadership development initiatives to enhance service delivery, operational efficiency, and long-term sustainability in water utilities.
Abstract Resources and capabilities in SMEs are only advantageous when the SMEs have the potential to execute the right strategies and processes. SMEs must analyze their business environments and understand the resources available to operate efficiently and effectively and achieve a sustained performance. This study is the subject of the influence of valuable resources on performance of SMEs. This study used a cross-sectional survey design. The target population for this study comprised of 121, 680 SMEs. The research used stratified random sampling technique. The sample size of this study was 399 SMEs. A structured questionnaire was used to collect data. Findings showed that there was a positive significant correlation between valuable resource and SMEs performance (r=.270; p<.01). According to the linear regression analysis valuable resources account for 7.3% of SMEs performance. According to the regression coefficients, one-unit increase in valuable resources improved SMEs performance by 0.269 units (? = 0.269). The t-statistics results showed that t = 4.778, p<0.05. Therefore, there was enough evidence to reject the null hypothesis and conclude that valuable resources have a statistically significant influence on SMEs Performance. The study concluded that valuable resource has a significant relationship with SMEs Performance. Valuable resources have a statistically significant influence on SMEs Performance. Increasing valuable resources in an SMEs will help the enterprise register higher performance. Key Words: Organizational Resources, Valuable Resources, Performance
Access to clean and safe water remains a critical development priority under Sustainable Development Goal (SDG) 6. However, water service providers in Sub-Saharan Africa, including Kenya, continue to experience performance challenges associated with governance, infrastructure limitations, and leadership effectiveness. This study examined the moderating effect of employee engagement on the relationship between exemplary transformational leadership and the performance of selected water and sewerage companies in Kenya. Grounded in transformational leadership theory, the three-component theory of work engagement, and the balanced scorecard framework, the study adopted a positivist philosophy and a quantitative cross-sectional survey design. Data were collected from 328 employees drawn from 13 public water companies operating under the Athi Water Works Development Agency using structured questionnaires. Exemplary transformational leadership was measured through three practices—modeling the way, challenging the process, and empowering followers—while employee engagement was assessed through vigor, dedication, and absorption. Organizational performance was evaluated using indicators of service quality, economic efficiency, and operational sustainability. Descriptive statistics, Pearson correlation, and moderated multiple regression analysis were conducted using SPSS version 27. The findings revealed that exemplary transformational leadership and employee engagement significantly and positively influenced water company performance. Importantly, employee engagement significantly moderated the relationship between exemplary transformational leadership and performance (β = −0.689, p < .05), indicating a buffering effect in which leadership had a stronger impact under conditions of low engagement. The study contributes to leadership and public sector management literature by empirically validating the moderating role of employee engagement within Kenya’s water sector. It recommends integrating employee engagement strategies with leadership development initiatives to enhance service delivery, operational efficiency, and long-term sustainability in water utilities.
Abstract Resources and capabilities in SMEs are only advantageous when the SMEs have the potential to execute the right strategies and processes. SMEs must analyze their business environments and understand the resources available to operate efficiently and effectively and achieve a sustained performance. This study is the subject of the influence of valuable resources on performance of SMEs. This study used a cross-sectional survey design. The target population for this study comprised of 121, 680 SMEs. The research used stratified random sampling technique. The sample size of this study was 399 SMEs. A structured questionnaire was used to collect data. Findings showed that there was a positive significant correlation between valuable resource and SMEs performance (r=.270; p<.01). According to the linear regression analysis valuable resources account for 7.3% of SMEs performance. According to the regression coefficients, one-unit increase in valuable resources improved SMEs performance by 0.269 units (? = 0.269). The t-statistics results showed that t = 4.778, p<0.05. Therefore, there was enough evidence to reject the null hypothesis and conclude that valuable resources have a statistically significant influence on SMEs Performance. The study concluded that valuable resource has a significant relationship with SMEs Performance. Valuable resources have a statistically significant influence on SMEs Performance. Increasing valuable resources in an SMEs will help the enterprise register higher performance. Key Words: Organizational Resources, Valuable Resources, Performance
Previous studies have established that the telecommunications industry in Kenya is characterized by decreasing voice revenues, many regulations, technological progress and varying consumer needs. This phenomenon has resulted in industry companies developing sound innovation strategies to make sure they form a competitive advantage over their rivals with the aim of ensuring their survival and growth in the evermore cut-throat marketplace. Nevertheless, in spite of the essential part played by these innovation strategies to safeguard competitive advantage, several companies have failed to translate the plans into reality. Therefore, the major objective of this study was to investigate the influence of technological innovation on the competitive advantage of telecommunication companies in Kenya. Technological innovation was measured by expansion of Global System for Mobile Communications (GSM) networks; new equipment and software; and partnerships and synergies. To satisfy the objective of this paper, a positivist philosophical stance was adopted and research design using cross-sectional survey data used. Data was collected using proportionate sampling from 247 managers. The results indicate that technological innovation improves the competitive advantage of telecommunication companies in Kenya. However, with government regulation as a moderating variable, only the new equipment, and software constructs had a positive and significant influence on the dependent variable. Ultimately, the findings suggest that government regulation moderates the influence of technological innovation on the competitive advantage of telecommunication companies in Kenya.
The study sought to determine the influence of human resource planning on firm performance of firms listed in the Nairobi Securities Exchange in Kenya. The study was anchored on human capital theory and shareholder value maximization theory. The research design used was a cross-sectional survey while the study population constituted all the 68 listed firms at the Nairobi Stock Exchange (NSE) as in May 2017. The target population included the head of human resources and finance directors in all the listed firms. The sample size comprised of 136 respondents, and data was collected through structured questionnaires to meet the objectives of the study. Responses were tabulated, coded, and processed by the use of a computer Statistical Package for Social Science (SPSS) to analyze the data. Both descriptive and inferential statistical techniques were used to analyze the data. To test hypotheses, a simple linear model was used to test significance between the independent and dependent variable. The study findings revealed that the relationship between human resource planning and firm performance was positive and statistically significant and hence rejected the null hypothesis. The study concluded that the type and strategy of the firm, succession planning, matching skills with jobs and skills inventory are human resource planning indicators influencing the performance of firms listed in the NSE. It is therefore recommended that firms should continue to practice and maintain adequate human resource planning as it plays a fundamental role in achieving the objectives of the organizations.
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 |