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: 3 / 3 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 01:43 UTC — 22 Oct 2026 04:44 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.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 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 |
|---|---|---|---|---|---|
| 2021 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 9 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 14 | 3 | 3/3 | 3/3 |
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 3 / 3 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): 2026-10-22T01:43:37.319474+00:00 — 2026-10-22T04:44:42.968506+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 | 3 | 3/3 |
| 2018 | All selected publications | 0 | 3 | 3/3 |
| 2019 | All selected publications | 0 | 3 | 3/3 |
| 2020 | All selected publications | 0 | 3 | 3/3 |
| 2021 | All selected publications | 2 | 3 | 3/3 |
| 2022 | All selected publications | 8 | 3 | 3/3 |
| 2023 | All selected publications | 3 | 3 | 3/3 |
| 2024 | All selected publications | 1 | 3 | 3/3 |
| 2025 | All selected publications | 0 | 3 | 3/3 |
| 2026 | All selected publications | 0 | 3 | 3/3 |
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 |
|---|---|
| 2021 | 3 |
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 | 3 | 9 | 14 | 3/3 | 3.0 | 2 | 100.0 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
This paper aims to examine the impact of Covid-19 pandemic on stock markets. This paper also analyses the stock market cointegration of selected global equity indices that performed better and have a quick speed of recovery during the pandemic. This paper also questions how increasing uncertainty and volatility deters investors’ perception of the diversification of equity investments. The dataset for the selected 12 global equity indices has been used from Thompson Reuters’s EIKON database in a given period of time between 2010 and 2021. This paper employs Vector Error Correction Models to assess the relationship among the selected global equity indices. Findings demonstrate that (i) there is an adverse impact of Covid-19 on the Global Equity markets, (ii) there is a clear sign of cointegration in global equity indices, (ii) investors can benefit from investing in particular equity indices that have exhibited quick speed of recovery from the pandemic records lows. The findings finally provide a strong foundation for constructing a resilient equity portfolio in a highly uncertain market environment.
The Micro Small and Medium Enterprises (MSMEs) are important for every nation’s economic development. They provide employment and spur the growth of multiple sectors in the economy. The Covid-19 pandemic has negatively affected MSMEs' performance. The study seeks to demonstrate why COVID 19 may lead to the terminal quarantining of MSMEs. The study is anchored on decision usefulness and information asymmetry theories. The study adopted a descriptive research methodology and sampled MSMEs within Nairobi City County. The study used SPSS to analyze data in addition to Microsoft excel. The study found that over 70% of MSMEs had their sales decline by over 65% while 95% of them had their sales decline by over 30%. The study found that about 68% of MSMEs lacked financial management skills. The study recommends that with legal and institutional reforms, the government needs to develop a financing framework for MSMEs.
In this study, the fear created by the Covid-19 global epidemic on consumers (general fear of viruses and fear of activity), spending (cleaning products, preventive health products, fresh and organic food and vitamin/mineral support, clothing, education, home purchasing, vehicle, loan. The relationship between buying, rental, fashion, vacation, travel, entertainment, electronics, home decor/furniture, mobile phone, activity and general) and savings have been tested. For this purpose, in order to test the relationship between fear, saving, and spending during the Covid-19 pandemic process, a Likert-scale online survey link was shared on social networks (Twitter, LinkedIn). The total of 385 surveys was analyzed using Google Form and SPSS program (Anova, Regression). As a result of the analysis, fear (general fear and fear of activity), spending (education, vehicles/cars, monopoly products, and tobacco products, games of chance, home buying and renting, loans, luxury/fashion, games, and toys, vitamins, minerals, and food support, public services, home, and furniture décor, electronic products (including mobile phones) expenditures remained the same, protective healthcare products, cleaning products, fresh and organic food expenditures increased, travel, public transportation expenditures decreased, holiday and entertainment expenditures decreased significantly). In the research, it was determined that 42% of the participants increased their savings by 30.5% slightly, and the amount of savings did not change at all for 27% of the participants. According to the results, as consumers' fear of Covid-19 increases, some spending categories (health products, cleaning products, fresh and organic food spending) and savings rate increase. In addition, it was observed that 90% of the participants canceled their expenses due to Covid-19. As a result of the research, significant relationships were found between the variables of fear, saving, and spending during the Covid-19 pandemic process.
This paper aims to examine the impact of Covid-19 pandemic on stock markets. This paper also analyses the stock market cointegration of selected global equity indices that performed better and have a quick speed of recovery during the pandemic. This paper also questions how increasing uncertainty and volatility deters investors’ perception of the diversification of equity investments. The dataset for the selected 12 global equity indices has been used from Thompson Reuters’s EIKON database in a given period of time between 2010 and 2021. This paper employs Vector Error Correction Models to assess the relationship among the selected global equity indices. Findings demonstrate that (i) there is an adverse impact of Covid-19 on the Global Equity markets, (ii) there is a clear sign of cointegration in global equity indices, (ii) investors can benefit from investing in particular equity indices that have exhibited quick speed of recovery from the pandemic records lows. The findings finally provide a strong foundation for constructing a resilient equity portfolio in a highly uncertain market environment.
The Micro Small and Medium Enterprises (MSMEs) are important for every nation’s economic development. They provide employment and spur the growth of multiple sectors in the economy. The Covid-19 pandemic has negatively affected MSMEs' performance. The study seeks to demonstrate why COVID 19 may lead to the terminal quarantining of MSMEs. The study is anchored on decision usefulness and information asymmetry theories. The study adopted a descriptive research methodology and sampled MSMEs within Nairobi City County. The study used SPSS to analyze data in addition to Microsoft excel. The study found that over 70% of MSMEs had their sales decline by over 65% while 95% of them had their sales decline by over 30%. The study found that about 68% of MSMEs lacked financial management skills. The study recommends that with legal and institutional reforms, the government needs to develop a financing framework for MSMEs.
In this study, the fear created by the Covid-19 global epidemic on consumers (general fear of viruses and fear of activity), spending (cleaning products, preventive health products, fresh and organic food and vitamin/mineral support, clothing, education, home purchasing, vehicle, loan. The relationship between buying, rental, fashion, vacation, travel, entertainment, electronics, home decor/furniture, mobile phone, activity and general) and savings have been tested. For this purpose, in order to test the relationship between fear, saving, and spending during the Covid-19 pandemic process, a Likert-scale online survey link was shared on social networks (Twitter, LinkedIn). The total of 385 surveys was analyzed using Google Form and SPSS program (Anova, Regression). As a result of the analysis, fear (general fear and fear of activity), spending (education, vehicles/cars, monopoly products, and tobacco products, games of chance, home buying and renting, loans, luxury/fashion, games, and toys, vitamins, minerals, and food support, public services, home, and furniture décor, electronic products (including mobile phones) expenditures remained the same, protective healthcare products, cleaning products, fresh and organic food expenditures increased, travel, public transportation expenditures decreased, holiday and entertainment expenditures decreased significantly). In the research, it was determined that 42% of the participants increased their savings by 30.5% slightly, and the amount of savings did not change at all for 27% of the participants. According to the results, as consumers' fear of Covid-19 increases, some spending categories (health products, cleaning products, fresh and organic food spending) and savings rate increase. In addition, it was observed that 90% of the participants canceled their expenses due to Covid-19. As a result of the research, significant relationships were found between the variables of fear, saving, and spending during the Covid-19 pandemic process.
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 |