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: 26 / 26 publications (100.0%). Latest observation: 21 Oct 2026, 00:14 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 01:14 UTC — 29 Oct 2026 10:17 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.
24 / 26 with data · 2 missing or unmatched. Percentages use all 26 selected publications.
24 / 26 with data · 2 missing or unmatched. Percentages use all 26 selected publications.
26 / 26 with data · 0 missing or unmatched. Percentages use all 26 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 | 26 | 26 | 26/26 | 26/26 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 57 | 26 | 26/26 | 26/26 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 108 | 26 | 26/26 | 26/26 |
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 26 / 26 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): 2026-10-22T01:14:00.029076+00:00 — 2026-10-29T10:17:09.758461+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 | 26 | 26/26 |
| 2018 | All selected publications | 2 | 26 | 26/26 |
| 2019 | All selected publications | 6 | 26 | 26/26 |
| 2020 | All selected publications | 16 | 26 | 26/26 |
| 2021 | All selected publications | 18 | 26 | 26/26 |
| 2022 | All selected publications | 22 | 26 | 26/26 |
| 2023 | All selected publications | 19 | 26 | 26/26 |
| 2024 | All selected publications | 11 | 26 | 26/26 |
| 2025 | All selected publications | 9 | 26 | 26/26 |
| 2026 | All selected publications | 3 | 26 | 26/26 |
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 | 26 |
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 | 9 | 6 | 27 | 9/9 | 0.67 | 0 | 33.3 | 9/9 · 100.0% |
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 17 | 51 | 81 | 17/17 | 3.0 | 1 | 64.7 | 17/17 · 100.0% |
* Percentage among publications with a known citation count.
Nowadays, effective business performance depends on digital competitive factors and its ability to transform corporate capabilities in the light of digitalization. In this study, the evolving role of automated systems for global business operations in the era of Industry 4.0 has been assessed from a theoretical perspective with a practical approach. It is aimed to demonstrate the role of high technologies in an effective supply chain management system with new technological components and cyber-security issues of automated vehicles in SCM. This study highlights that developments in Artificial Neural Networks, Image Processing, Multi-Purpose Decision-Making, Blurred Linguistic Variables, and automated systems increase the performance of the supply chain management system and boost business performance. It is also shown that the evolving role of the automated system requires capital investments on Research and Development efforts
The term high-tech, covering the high-tech industry and the information-intensive service sector, is based on advanced scientific and technological expertise that requires science, technology, and innovation (STI), and is based on Research & Development expenditure. Sectoral, product and patent approaches are used for classification by OECD and European Union. Literature review on high-tech show that countries focusing on Research and Development Expenditures and new patents have succeeded in increasing their high-tech exports as well. Turkey is one of the countries where the levels of high-tech export is not at the desired levels yet therefore the government must give incentives for Research and Development expenditures and new patents for innovation, as high-tech export affects GDP growth positively.
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.
Despite the theoretical foundation that links Transformational leadership (TFL) with innovation behavior, previous studies have overlooked on Transformational leadership and innovation behavior at the individual level relationship but paid less attention to how transformational leadership qualities of top leaders would advance innovative work behavior within the organizational setting. To date, the impact of Transformational leadership at a top executive level on employee’s innovative work behavior (IWB) within an organizational setting has not been dealt with in-depth. However, using transformational leadership theory, this study uncovers the pivotal role of innovation culture (IC) and managerial innovation (MI) in the relationship between CEO transformational leadership and employee’s innovation behavior in SMEs. A cross-sectional design with a total of 434 employees from 24 SMEs operating from Rwanda was analyzed using structural equation modeling to evaluate the relationship between the variables developed in the study. The findings of this study support our hypothesized model.
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.
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.
The purpose of this study was to assess the effect of indirect investment on the performance of real estate in Nairobi County Kenya. The independent variables for indirect investment were: investment trusts, exchange-traded funds, commingled funds, and infrastructure funds. The dependent variable was the performance of real estate in Nairobi County Kenya. Secondary data was collected from the real estate’s online sources and some from the company offices and analyzed using multiple regression analysis. Both descriptive statistics and inferential statistics were determined. The study was only able to collect secondary data from 45 real estate companies out of the target population of 69 registered by KPDA in 2015 as it was hard to get data of the rest either from online sources or from the company offices. With the aid of STATA 12.0 software and Excel software, quantitative results were tabulated and presented in the form of charts, bar graphs, and narratives. The study found an existing relationship between the performance of the real estate sector and the Investment Trust Fund, the Exchange Trust Fund, the Commingled Fund, Infrastructure Fund. The study concludes that most of the coefficients were significant. The study also concludes that there is a relationship between the performance of the real estate sector and the Investment Trust Fund, Exchange Trust Fund, Commingled Fund, Infrastructure Fund when these components are considered together, they affect Performance.
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.
MSMEs contribute more than 60% of economic growth. 99% of business operators in Indonesia are MSMEs. However, the contribution of MSMEs in tax revenue is still low. The government has sought to improve tax compliance for the MSME sector by the existence of an Account Representative position (AR) and an online reporting system, namely E Filling. This study aims to determine whether the role of Account representative (AR) and the use of E Filling can affect the compliance of MSMEs in reporting tax. The data used are MSMEs in the area of the Primary Tax Office in Duren Sawit. The number of questionnaires distributed was 120 and could be processed was 95 questionnaires. The analytical tool used is the Structure Equation Model (SEM). The results conclude that the value of the role of AR and the use of E-Filling affect the compliance of MSMEs in reporting taxes partially and simultaneously.
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.
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 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |
| ojs-rest | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:02 UTC |
| oai-pmh | 20 Oct 2026 19:50 UTC · brss | complete · brss · 20 Oct 2026 19:49 UTC |
| openalex-enrichment | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |