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: 6 / 6 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 07:26 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.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 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 |
|---|---|---|---|---|---|
| 2024 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 4 | 6 | 6/6 | 6/6 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 5 | 6 | 6/6 | 6/6 |
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 6 / 6 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): 2026-10-21T07:22:55.694995+00:00 — 2026-10-23T07:26:31.038984+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 | 6 | 6/6 |
| 2018 | All selected publications | 0 | 6 | 6/6 |
| 2019 | All selected publications | 0 | 6 | 6/6 |
| 2020 | All selected publications | 0 | 6 | 6/6 |
| 2021 | All selected publications | 0 | 6 | 6/6 |
| 2022 | All selected publications | 0 | 6 | 6/6 |
| 2023 | All selected publications | 0 | 6 | 6/6 |
| 2024 | All selected publications | 0 | 6 | 6/6 |
| 2025 | All selected publications | 3 | 6 | 6/6 |
| 2026 | All selected publications | 2 | 6 | 6/6 |
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 |
|---|---|
| 2024 | 6 |
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 | 6 | 4 | 5 | 6/6 | 0.67 | 0.0 | 16.7 | 6/6 · 100.0% |
* Percentage among publications with a known citation count.
A recurring theme in the literature and discussion of stock market analysis is the concept of the January effect which essentially implies buy in December and sell in January. The January effect is based on the perceived seasonality trend where short term investors hope to take advantage of the arbitrage opportunity between December and January. However, this perceived anomaly continues is seen as a myth and has been strongly rejected by many market participants in the current dispensation. The purpose of this paper was to investigate the January effect in the Nikkei 225, JSE, CAC 40, DAX, and the NASDAQ Index from February 2019 to February 2024. A F-test statistics was used to explore the phenomenon. The findings indicated that there is no significant difference between the realised returns in January and those of the other month for the most recent five years. This led to the conclusion that, while the January effect may have been observed, it is no longer evident in financial markets, hence market participants should avoid using this type of arbitrage approach because it may result in massive losses
The market resilience of a stock is an integral component of financial market because it supports smooth trading and absorb market shocks. However, the contention has always been to effectively determine the level of resilience in stocks with the application of proper methodology to make informed decisions. Therefore, aim of this study was to examine the level of market resilience in selected stocks in the Johannesburg stock exchange. Using a fixed effect model, the findings of this study indicates that most securities trading on the exchange lack market resilience. This was evident in the significant relationship between the specific independent and dependent variables. A risk coefficient should therefore be assigned to bid and ask to spread to enhance market resilience. These risk coefficients will induce the bid and ask prices to be close to the fundamental price.
The market tightness of equity securities is an integral component of financial market because it supports smooth trading and absorb market shocks. However, the contention has always been to effectively determine the level of tightness in equity securities with the application of proper methodology in order to make informed decisions. Therefore, aim of this study was to examine the level of market tightness in selected stocks in the Johannesburg stock exchange. Using a variance ratio model, the findings of this study indicates that most securities trading on the exchange lack market tightness. This was evident in the difference between the one, two and three months variances that were not equal to 1 . Therefore, a specialist system should be introduced in order to facilitate the execution of trades without significantly moving the prices of equity securities. This study improves the frontier of knowledge regarding liquidity management, by empirically investigating the market tightness of equity securities.
Internationally, migrants encounter a multitude of obstacles in the countries they settle in, including being denied access to essential services and economic prospects due to restrictive laws that undermine their ability to contribute to the fulfilment of the 2030 global agenda. While it is crucial to incorporate migration into development goals at all levels, the integration at the local government level is still incomplete. This research utilises the notion of global governance and employs a qualitative case study approach to conduct an explorative investigation of the difficulties pertaining to the integration of migration into municipal development plans. A total of 20 individuals engaged in municipal development planning were interviewed. The data was collected by reviewing municipal strategic plans. Thematic analysis was employed for data analysis. The study findings indicate that the lack of current migration data, negative attitudes towards migration, and insufficient coordination among parties responsible for development planning are the primary obstacles to integrating migration into municipal development planning. The exclusion of migrants has significant ramifications for municipal planning. Not only does it contradict the 2030 global goal, which recognises migrants as catalysts for sustainable development, but it also renders municipal planning inadequate and unsustainable. The discoveries aided in the creation of the Migration and Municipal Development Planning Framework. The framework has substantial ramifications for municipal planning since it delineates the actions that local municipalities could take to seamlessly incorporate migration issues into development planning, along with the anticipated results. The framework is a unique and valuable addition to the existing knowledge since it offers a fresh viewpoint on the relationship between migration and sustainable development, specifically at the level of local government.
The efficient market hypothesis assumes that financial markets fully incorporate all available information, rendering past information irrelevant for predicting future prices. However, numerous studies challenge this notion and suggest the presence of long-term memory in market dynamics. Understanding long-term memory in financial markets has important implications for investors and policymakers. The aim of this study was to empirically investigate long term memory in financial markets. This study employed a Hurst model for a sample of 5 financial markets from June 1, 2018, to June 1, 2023. The findings revealed that four out of the five sampled financial market exhibits long term memory which challenges the efficient market hypothesis concept. Therefore, portfolio managers and active market participants can utilize long-term memory to optimize asset allocation decisions by considering the persistent effects of past returns and adjust portfolio weights to take advantage of potential return predictability and manage risk.
The market resilience of a stock is an integral component of financial market because it supports smooth trading and absorb market shocks. However, the contention has always been to effectively determine the level of resilience in stocks with the application of proper methodology to make informed decisions. Therefore, aim of this study was to examine the level of market resilience in selected stocks in the Johannesburg stock exchange. Using a fixed effect model, the findings of this study indicates that most securities trading on the exchange lack market resilience. This was evident in the significant relationship between the specific independent and dependent variables. A risk coefficient should therefore be assigned to bid and ask to spread to enhance market resilience. These risk coefficients will induce the bid and ask prices to be close to the fundamental price.
The market tightness of equity securities is an integral component of financial market because it supports smooth trading and absorb market shocks. However, the contention has always been to effectively determine the level of tightness in equity securities with the application of proper methodology in order to make informed decisions. Therefore, aim of this study was to examine the level of market tightness in selected stocks in the Johannesburg stock exchange. Using a variance ratio model, the findings of this study indicates that most securities trading on the exchange lack market tightness. This was evident in the difference between the one, two and three months variances that were not equal to 1 . Therefore, a specialist system should be introduced in order to facilitate the execution of trades without significantly moving the prices of equity securities. This study improves the frontier of knowledge regarding liquidity management, by empirically investigating the market tightness of equity securities.
Internationally, migrants encounter a multitude of obstacles in the countries they settle in, including being denied access to essential services and economic prospects due to restrictive laws that undermine their ability to contribute to the fulfilment of the 2030 global agenda. While it is crucial to incorporate migration into development goals at all levels, the integration at the local government level is still incomplete. This research utilises the notion of global governance and employs a qualitative case study approach to conduct an explorative investigation of the difficulties pertaining to the integration of migration into municipal development plans. A total of 20 individuals engaged in municipal development planning were interviewed. The data was collected by reviewing municipal strategic plans. Thematic analysis was employed for data analysis. The study findings indicate that the lack of current migration data, negative attitudes towards migration, and insufficient coordination among parties responsible for development planning are the primary obstacles to integrating migration into municipal development planning. The exclusion of migrants has significant ramifications for municipal planning. Not only does it contradict the 2030 global goal, which recognises migrants as catalysts for sustainable development, but it also renders municipal planning inadequate and unsustainable. The discoveries aided in the creation of the Migration and Municipal Development Planning Framework. The framework has substantial ramifications for municipal planning since it delineates the actions that local municipalities could take to seamlessly incorporate migration issues into development planning, along with the anticipated results. The framework is a unique and valuable addition to the existing knowledge since it offers a fresh viewpoint on the relationship between migration and sustainable development, specifically at the level of local government.
A recurring theme in the literature and discussion of stock market analysis is the concept of the January effect which essentially implies buy in December and sell in January. The January effect is based on the perceived seasonality trend where short term investors hope to take advantage of the arbitrage opportunity between December and January. However, this perceived anomaly continues is seen as a myth and has been strongly rejected by many market participants in the current dispensation. The purpose of this paper was to investigate the January effect in the Nikkei 225, JSE, CAC 40, DAX, and the NASDAQ Index from February 2019 to February 2024. A F-test statistics was used to explore the phenomenon. The findings indicated that there is no significant difference between the realised returns in January and those of the other month for the most recent five years. This led to the conclusion that, while the January effect may have been observed, it is no longer evident in financial markets, hence market participants should avoid using this type of arbitrage approach because it may result in massive losses
The efficient market hypothesis assumes that financial markets fully incorporate all available information, rendering past information irrelevant for predicting future prices. However, numerous studies challenge this notion and suggest the presence of long-term memory in market dynamics. Understanding long-term memory in financial markets has important implications for investors and policymakers. The aim of this study was to empirically investigate long term memory in financial markets. This study employed a Hurst model for a sample of 5 financial markets from June 1, 2018, to June 1, 2023. The findings revealed that four out of the five sampled financial market exhibits long term memory which challenges the efficient market hypothesis concept. Therefore, portfolio managers and active market participants can utilize long-term memory to optimize asset allocation decisions by considering the persistent effects of past returns and adjust portfolio weights to take advantage of potential return predictability and manage risk.
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 |