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: 5 / 5 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 00:14 UTC — 21 Oct 2026 07:23 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.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 selected publications.
5 / 5 with data · 0 missing or unmatched. Percentages use all 5 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 | 0 | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2026 | All selected publications | 0 | 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 5 / 5 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): 2026-10-21T00:14:27.763796+00:00 — 2026-10-21T07:23:07.443935+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 | 5 | 5/5 |
| 2018 | All selected publications | 0 | 5 | 5/5 |
| 2019 | All selected publications | 0 | 5 | 5/5 |
| 2020 | All selected publications | 0 | 5 | 5/5 |
| 2021 | All selected publications | 0 | 5 | 5/5 |
| 2022 | All selected publications | 0 | 5 | 5/5 |
| 2023 | All selected publications | 0 | 5 | 5/5 |
| 2024 | All selected publications | 1 | 5 | 5/5 |
| 2025 | All selected publications | 1 | 5 | 5/5 |
| 2026 | All selected publications | 1 | 5 | 5/5 |
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 |
| 2023 | 1 |
| 2024 | 1 |
| 2026 | 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 Business Ecosystem & Strategy Bussecon International Academy | 2 | 1 | 1 | 2/2 | 0.5 | 0.5 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 3 | 2 | 2 | 3/3 | 0.67 | 0 | 33.3 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
The issue of road tolling is a topical subject, especially for developing countries who are being affected by paltry budgetary allocations towards highway infrastructure investment. The Zimbabwean Government took almost a decade before implementing road tolling. It was thus needful to come up with innovative, long-lasting solutions to address the financial constraints towards highway infrastructure investment hence the introduction of road tolling systems in Zimbabwe. To this effect, the study unpacks the drivers and the utility of road tolling in Zimbabwe. Through the usage of a case study research design which triangulates both the qualitative and quantitative methods, the study collected data using a survey questionnaire, document analysis and in-depth interviews with key informants. Data was analysed using the SPSS, content analysis and thematic analysis techniques. The results revealed that the dwindling budgetary allocations towards highway infrastructure investment, hyperinflation, and backlog in the maintenance and construction of trunk roads were the key factors that led the Zimbabwean Government to introduce road tolling. Additionally, the study highlighted that road tolling was introduced primarily to generate revenue for the construction, rehabilitation, and maintenance of highway infrastructure in Zimbabwe. Recommendations were made to enhance the adoption and operationalisation of road tolling systems.
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 article seeks to empirically examine the dynamic relationship between government expenditure and private sector investment in South Africa. The research employed a Vector Autoregression (VAR) methodology to experimentally investigate the crowding impacts of government spending on private sector investment, utilising time series data from 1960 to 2021. The study evaluates single equation methods, including Dynamic Ordinary Least Squares, Fully Modified Ordinary Least Squares, and Canonical Cointegrating Regression, to analyse the long-term cointegrating relationship between government expenditure and private sector investment. The results offer robust empirical evidence of a beneficial relationship between government expenditure and private sector investment, suggesting that an increase in government spending stimulates private sector investment in South Africa's economy. The impulse response function (IRF) indicated that private sector investment reacts favourably to unexpected fluctuations in government expenditure and GDP growth. The study's findings indicate that governments should allocate substantial funds to productive sectors to stimulate economic activities, encourage private sector investment through robust public-sector collaboration, and ultimately promote job creation and economic growth.
Transport infrastructure is an integral part of economic and social development in many countries, including South Africa. Economic growth theories state that a sound transport system enhances accessibility and output. Despite this, rural areas in South Africa face widespread poverty, poor infrastructure and limited access to essential services. This paper aims to examine the impact of transportation infrastructure investment on the output growth of rural nodal district municipalities in South Africa. This study focuses on two main objectives 1) investigating the relationship between transport infrastructure investment and output growth in rural nodal district municipalities and 2) understanding the causal relationship between transportation infrastructure investment and output growth in rural nodal district municipalities—this analysis uses panel data from 2012 to 2019. We used Fisher type (ADF and PP) panel unit root tests (Maddala & Wu,1999) to determine if the variables were stationary. Additionally, we employed Pedroni tests (1999) to ascertain the presence of cointegration among the variables. Once cointegration was confirmed, our study utilised the Panel VECM. A Panel Granger was then conducted to analyse the direction of causality between transportation infrastructure investment and output growth. This study recommends that the government should improve investments in transportation to improve the output of rural nodal district municipalities.
This paper investigates whether government consumption becomes more growth-enhancing after institutional capacity crosses a minimum level in North Africa. Government consumption is a narrower measure than total public expenditure and excludes some capital spending and transfers. A panel of Algeria, Egypt, Libya, Mauritania, Morocco, Sudan, and Tunisia for 2003–2024 is assembled from the World Development Indicators and Worldwide Governance Indicators. The empirical design profiles candidate threshold values separately for government effectiveness and control of corruption in a dynamic common-factor panel model. It enforces a 15% minimum regime share and uses all 128 country-level Rademacher sign assignments for wild-cluster threshold tests. Candidate breakpoints occur at −1.336 for government effectiveness and −1.267 for corruption control. Conditional spending-growth slopes are larger above both candidates, but the threshold tests do not reject linearity (p = 0.217 and p = 0.388). Cutoffs and regime slopes also move substantially when Libya or Sudan is excluded, when the five-country core is used, and across alternative time windows. H1–H3 are therefore not supported: the evidence does not identify a stable institutional minimum at which public consumption reliably changes its growth effect. Policy should improve specific expenditure-conversion mechanisms rather than treat sample-specific governance breakpoints as targets.
This paper investigates whether government consumption becomes more growth-enhancing after institutional capacity crosses a minimum level in North Africa. Government consumption is a narrower measure than total public expenditure and excludes some capital spending and transfers. A panel of Algeria, Egypt, Libya, Mauritania, Morocco, Sudan, and Tunisia for 2003–2024 is assembled from the World Development Indicators and Worldwide Governance Indicators. The empirical design profiles candidate threshold values separately for government effectiveness and control of corruption in a dynamic common-factor panel model. It enforces a 15% minimum regime share and uses all 128 country-level Rademacher sign assignments for wild-cluster threshold tests. Candidate breakpoints occur at −1.336 for government effectiveness and −1.267 for corruption control. Conditional spending-growth slopes are larger above both candidates, but the threshold tests do not reject linearity (p = 0.217 and p = 0.388). Cutoffs and regime slopes also move substantially when Libya or Sudan is excluded, when the five-country core is used, and across alternative time windows. H1–H3 are therefore not supported: the evidence does not identify a stable institutional minimum at which public consumption reliably changes its growth effect. Policy should improve specific expenditure-conversion mechanisms rather than treat sample-specific governance breakpoints as targets.
This article seeks to empirically examine the dynamic relationship between government expenditure and private sector investment in South Africa. The research employed a Vector Autoregression (VAR) methodology to experimentally investigate the crowding impacts of government spending on private sector investment, utilising time series data from 1960 to 2021. The study evaluates single equation methods, including Dynamic Ordinary Least Squares, Fully Modified Ordinary Least Squares, and Canonical Cointegrating Regression, to analyse the long-term cointegrating relationship between government expenditure and private sector investment. The results offer robust empirical evidence of a beneficial relationship between government expenditure and private sector investment, suggesting that an increase in government spending stimulates private sector investment in South Africa's economy. The impulse response function (IRF) indicated that private sector investment reacts favourably to unexpected fluctuations in government expenditure and GDP growth. The study's findings indicate that governments should allocate substantial funds to productive sectors to stimulate economic activities, encourage private sector investment through robust public-sector collaboration, and ultimately promote job creation and economic growth.
Transport infrastructure is an integral part of economic and social development in many countries, including South Africa. Economic growth theories state that a sound transport system enhances accessibility and output. Despite this, rural areas in South Africa face widespread poverty, poor infrastructure and limited access to essential services. This paper aims to examine the impact of transportation infrastructure investment on the output growth of rural nodal district municipalities in South Africa. This study focuses on two main objectives 1) investigating the relationship between transport infrastructure investment and output growth in rural nodal district municipalities and 2) understanding the causal relationship between transportation infrastructure investment and output growth in rural nodal district municipalities—this analysis uses panel data from 2012 to 2019. We used Fisher type (ADF and PP) panel unit root tests (Maddala & Wu,1999) to determine if the variables were stationary. Additionally, we employed Pedroni tests (1999) to ascertain the presence of cointegration among the variables. Once cointegration was confirmed, our study utilised the Panel VECM. A Panel Granger was then conducted to analyse the direction of causality between transportation infrastructure investment and output growth. This study recommends that the government should improve investments in transportation to improve the output of rural nodal district municipalities.
The issue of road tolling is a topical subject, especially for developing countries who are being affected by paltry budgetary allocations towards highway infrastructure investment. The Zimbabwean Government took almost a decade before implementing road tolling. It was thus needful to come up with innovative, long-lasting solutions to address the financial constraints towards highway infrastructure investment hence the introduction of road tolling systems in Zimbabwe. To this effect, the study unpacks the drivers and the utility of road tolling in Zimbabwe. Through the usage of a case study research design which triangulates both the qualitative and quantitative methods, the study collected data using a survey questionnaire, document analysis and in-depth interviews with key informants. Data was analysed using the SPSS, content analysis and thematic analysis techniques. The results revealed that the dwindling budgetary allocations towards highway infrastructure investment, hyperinflation, and backlog in the maintenance and construction of trunk roads were the key factors that led the Zimbabwean Government to introduce road tolling. Additionally, the study highlighted that road tolling was introduced primarily to generate revenue for the construction, rehabilitation, and maintenance of highway infrastructure in Zimbabwe. Recommendations were made to enhance the adoption and operationalisation of road tolling systems.
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.
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 |