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: 11 / 11 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 04:45 UTC — 29 Oct 2026 16:45 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.
11 / 11 with data · 0 missing or unmatched. Percentages use all 11 selected publications.
11 / 11 with data · 0 missing or unmatched. Percentages use all 11 selected publications.
11 / 11 with data · 0 missing or unmatched. Percentages use all 11 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 | 11 | 11 | 11/11 | 11/11 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 14 | 11 | 11/11 | 11/11 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 36 | 11 | 11/11 | 11/11 |
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 11 / 11 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): 2026-10-22T04:45:14.697858+00:00 — 2026-10-29T16:45:58.490269+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 | 11 | 11/11 |
| 2018 | All selected publications | 2 | 11 | 11/11 |
| 2019 | All selected publications | 5 | 11 | 11/11 |
| 2020 | All selected publications | 7 | 11 | 11/11 |
| 2021 | All selected publications | 2 | 11 | 11/11 |
| 2022 | All selected publications | 4 | 11 | 11/11 |
| 2023 | All selected publications | 6 | 11 | 11/11 |
| 2024 | All selected publications | 4 | 11 | 11/11 |
| 2025 | All selected publications | 1 | 11 | 11/11 |
| 2026 | All selected publications | 3 | 11 | 11/11 |
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 | 11 |
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 | 4 | 6 | 22 | 4/4 | 1.5 | 1.5 | 75.0 | 4/4 · 100.0% |
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 5 | 5 | 8 | 5/5 | 1.0 | 1 | 80.0 | 5/5 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 1 | 3 | 5 | 1/1 | 3.0 | 3 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 1 | 0 | 1 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
* Percentage among publications with a known citation count.
This study investigates how the development of human capital is related to economic growth in Nigeria from 1980 to 2015. Data were sourced from the Central Bank of Nigeria and the National Bureau of Statistics. The study employed Augmented Dickey-Fuller (ADF) to estimate the relationship among the variables used in this study which revealed that there is a positive long-run relationship among public expenditure on education and health, total school enrolment, gross capital formation, employment rate, life expectancy rate and economic growth. The study recommended that the government should put in place the required education and training policy that would guarantee quality schooling for different level of education. Government should also commit more funds to health sector to enhance human capital formation. It was also recommended there should be more pragmatic means to develop human capabilities.
This paper investigated this disparity in the literature using Nigeria data from 1980 to 2016. In doing this, energy consumption was disaggregated, and their impacts on economic growth investigated using a modified Ordinary Least Square technique which allows for time gaps in the model. It was observed that only renewable energy impacted on economic growth in the long-run whereas non-renewable energy component impacted on economic growth in the short-run. Therefore, the study sees the impact of energy consumption on economic growth to be indistinct in Nigeria within the period under review. This further buttresses the need for improvement in electricity production and distribution in Nigeria. Given the importance of energy consumption on productivity, the study, therefore, suggests policies/measures that will bring about increasing the supply or improvement of energy production in the country.
This research analyzed the insurance industry and economic growth in Nigeria between 1980 and 2015. Secondary data ranging from real gross domestic product, the premium of the insurance business, claim expenditure of insurance industry and inflation rate were utilized and sourced from Central Bank of Nigeria (CBN). The Ordinary Least Squares (OLS) multiple regression techniques, Descriptive statistics, Augmented Dickey-Fuller (ADF) test of stationarity and ARDL Bound Test Co-Integration were adopted for the model in the Study. The findings revealed that the premium of the insurance industry (PMI) impacts negatively on economic growth both in the extended and short run period. The claim expenditure of the insurance industry (CEX) revealed a progressive relationship with economic growth in the long run and a negative relation with growth in the short run. We therefore conclude following the Keynesian theory of aggregate demand which states that, ‘’if we will have to wait till the long run, we will all be dead’’, that insurance industry in Nigeria has not impacted positively on economic growth of Nigeria within the period under review and its operations and investment have not been prominent and contributory to the growth and development of Nigeria. Based on these outcomes, we recommend amongst others, that more investment ought to be made towards the insurance industry in Nigeria especially in terms of proper policy formulation by the government that would channel funds and encourage competition among the players in the industry and invariably contribute to the growth of the economy.
This paper examined the effect of power supply and the performances of Small and Medium Scale Enterprises (SMEs). In doing this, the paper used durations of public power supply, bills paid for public power and cost paid for private power supply as measures of power supply on the performances index of the SMEs in Port Harcourt. The performance indexes are employed in the models as the dependent variables while the power supply indexes are the explanatory variables. The data were sourced primarily through a well-structured questionnaire and the samples determined by the Cochran sampling techniques. The data were analyzed with the Qualitative Respond Model. It was revealed that a lower duration of public power supply significantly reduces the profitability, productivity and revenue, as well as the storage of products of the SMSEs, examined. Hence, the study recommended among others that there is a need to allocate more electric power to the industrial area of Rivers state- Port Harcourt, especially in the day light to encourage productivity, profitability and employment generation in the state.
Agriculture is the bedrock for combating poverty and developing rural areas. This motivated government policies on agriculture. This paper evaluated the performance of Fadama III in addressing food productivity and rural development in Rivers State. A critical review of secondary materials from Rivers State National Fadama III Development Programme Coordinating Office Report on implementation of National Fadama III projects in Rivers State formed the methodology for the study. It revealed the concept, approaches and implementation process of economic interest groups and government financial commitments to various farming activities in the local government areas. There were remarkable improvements in rural development in the participated local government areas. The assessment further revealed committed efforts by officers and management of the program which ensured effective implementation of rural infrastructure in participated communities. It is recommended that expenditure control measures adopted by the management of fadama program in Rivers State should be applied in future agricultural projects to ensure quality deliverables. The government should pursue only rural development-oriented agricultural policies, and finance projects that have certified Local Development Plans. Seemingly bottleneck criterion that would delay the release of funds should be relaxed for agricultural program managers to be proactive to beneficiaries’ requests and function effectively. Finally, the fadama program should be extended to increase communities’ dual opportunities of experiencing both agricultural and rural development.
The study examined the dynamic responses of profitability indexes to capital adequacy ratios of authorized internationalized deposit money banks in Nigeria. The data were sourced from the financial year books of the deposit money banks and analyzed with static and dynamic panel estimators. The static estimator shows that the banks have differences in managerial style, size and profitability. Also, it was revealed that return on asset and return on equity responded positively to asset size, efficiency of the use of asset and current ratio in the static models and they were highly significant. However, they were insignificant in the dynamic specifications except asset size that was significant in the return on asset model showing a weak dynamic response of profitability to capital adequacy ratios. Hence the study recommended that Banks should improve their share based as to increase the asset as this will improve profitability.
This paper investigated the impact of tax revenue on private domestic investment in Nigeria from 1980 to 2018 using the modified ordinary least squares- Autoregressive distributed lag (ARDL). The paper used oil revenue, non-oil revenue, and Corporate Income Tax (CIT) as the independent variables while Private Domestic Investment (PDI) is the dependent variable. Oil revenue and non-oil revenue were used as a proxy for oil and non-oil tax. These data were obtained from secondary sources- central Bank of Nigeria, World Bank database and Federal Inland Revenue service statistical bulletin. The result showed that a long-run relationship exists between the aforementioned variables. Also, the paper revealed that oil and non-oil do not have a significant impact on PDI but CIT has a positive and significant impact on PDI. The paper recommends that proper measures/reforms should be put in place in order to reduce the impact of tax on private domestic investment in Nigeria.
This paper investigated this disparity in the literature using Nigeria data from 1980 to 2016. In doing this, energy consumption was disaggregated, and their impacts on economic growth investigated using a modified Ordinary Least Square technique which allows for time gaps in the model. It was observed that only renewable energy impacted on economic growth in the long-run whereas non-renewable energy component impacted on economic growth in the short-run. Therefore, the study sees the impact of energy consumption on economic growth to be indistinct in Nigeria within the period under review. This further buttresses the need for improvement in electricity production and distribution in Nigeria. Given the importance of energy consumption on productivity, the study, therefore, suggests policies/measures that will bring about increasing the supply or improvement of energy production in the country.
The primary objective of this paper is to test the hypothesis that the population age structure could contribute to carbon dioxide emission levels (environmental degradation) in Nigeria. Real income (Gross Domestic Product) was used as another determinant of CO2 emissions to test the EKC hypothesis in this study. Also, the autoregressive distributed lag (ARDL) econometric technique was applied in this paper to annual time series data from 1970 to 2018. The results show that age structure’s influence on the environment is significant. As expected, young adults (LOGYONG, i.e., ages 15-64) and children (LOGCHIL, i.e., ages 0-14) are environmentally intensive (due to energy-intensive goods consumed). But the older age group (LOGOLD i.e., ages 65 and above) exert a negative effect. The results of long-term estimation for the population structure-induced EKC hypothesis show that none of the coefficients of economic growth were statistically significant at any of the conventional levels. In other words, this finding did not prove the existence of EKC hypothesis. However, appropriate macroeconomic policies, technological innovations, and institutional developments are very important in maintaining a sound environment in Nigeria.
This paper x-rayed the concept, measurement and, patterns of economic development. In doing this, the paper reviewed a vast literature on concepts, measurement of economic development and, economic development patterns and their effects on growth indicators as well as on the quality of life components. This literature was sourced from known academic databases. From the overview of the concept, measurement of economic development and, economic development patterns and their relationship between growth indicators as well as the quality of life components the following were found; as new challenges emerge, the horizon of the concept of economic development expands to accommodate the prevailing challenges. Economic development has no conventional measure/indicator that completely captures it process and, there are various economic development patterns use in tackling the problem of economic growth and quality of life, some of which are; knowledge-based, trade-based, saving-based and ethnic-religious-based pattern. Future studies may use these concepts/measurements of economic development and patterns of economic development and, validate their significance using statistical methods.
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 |