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 00:49 UTC — 22 Oct 2026 03:19 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 |
|---|---|---|---|---|---|
| 2022 | All selected publications | 5 | 5 | 5/5 | 5/5 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 2 | 5 | 5/5 | 5/5 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 12 | 5 | 5/5 | 5/5 |
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): 2026-10-21T00:49:39.722324+00:00 — 2026-10-22T03:19:06.965030+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 | 1 | 5 | 5/5 |
| 2023 | All selected publications | 4 | 5 | 5/5 |
| 2024 | All selected publications | 6 | 5 | 5/5 |
| 2025 | All selected publications | 1 | 5 | 5/5 |
| 2026 | All selected publications | 0 | 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 |
|---|---|
| 2022 | 5 |
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 | 1 | 1 | 2 | 1/1 | 1.0 | 1 | 100.0 | 1/1 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 2 | 0 | 5 | 2/2 | 0.0 | 0.0 | 0.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 1 | 5 | 2/2 | 0.5 | 0.5 | 50.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
The purpose of this study is to empirically analyze the performance of liquidity, leverage, profitability, and activities of firms on the Indonesia Stock Exchange during the Covid-19 pandemic based on a quantitative approach. This study uses secondary data from financial reports of firms listed on the Indonesia Stock Exchange that are included in the LQ45 index, which represents the movement of the capital market based on specific criteria. The results reveal that the Covid-19 pandemic has hurt the Indonesian firm’s financial performance. The worst condition has increased the leverage ratio, and the profitability and activity ratio declined, as experienced in several emerging countries. The findings of this research can be a bunch of information for investors in making decisions that these financial ratios are sensitive to economic volatility. In addition, this finding also adds insight to the company's management, especially LQ45 companies, that the company is expected to be able to maintain its financial fundamentals of these ratios. Further research needs to be carried out on how the effects of the Covid-19 pandemic influence financial performance according to the sector type of the firm and conducted in more time series periods.
This study was conducted to find out whether there are differences in the financial performance of the Primary Consumer Goods Sector Companies before and during the Covid-19 outbreak. This study uses a probability sampling technique called the Slovin formula to determine the number of samples, the final result obtained is 72 samples of companies. The research period is one year before Covid-19 (2nd quarter of 2019 to 2nd quarter of 2020) and one year during Covid-19 occurs (2nd quarter of 2021 to 2nd quarter of 2022). Data processing in this study uses SPSS 28 with the Wilcoxon signed-rank test analysis technique. The results in the study state that there are differences for profitability and activity variable, while for liquidity and solvency variables shows that there are no differences before and during Covid-19.
This study aims to analyze the development and soundness of banks from financial performance ratios in banking companies listed on the IDX in 2016-2021 using the RGEC approach; analyze the effect of the ratios used in RGEC on stock returns in banking companies listed on the IDX in 2016-2019 or before Covid19; analyzed the effect of the ratios used in RGEC on stock returns in banking companies listed on the IDX in 2020-2021 or during the Covid-19 pandemic. The sample consisted of the banking sub-sector listed on the IDX in the period 2016 to 2021. The data analyzed using the RGEC method. Based on the calculation of bank rating (bank soundness level), it can be seen that the key figures for the risk profile, GCG, earning and equity (RGEC) in the banking sub-sector listed on the IDX developed well in 2016-2021 in the banking sector on average from 39 banks studied. There are 11 Banks that are in Composite Rating 1 (Very Healthy), 25 Banks are on Composite Rating 2 (Healthy) and 3 Banks are on Composite Rating 3 (Sufficiently Healthy). Based on the results of panel regression tests in 2016-2019 (before Covid-19), bank rating (bank soundness level) which include risk profile (NPL and LDR), GCG, earnings (ROA and NIM) and equity (CAR) together have an effect of 28.89% of bank stock returns and 71.11% of stock returns are influenced by other factors outside the variables studied. However, based on the p-value results, the variables NPL, GCG, NIM and CAR have no significant effect on bank stock returns, while the LDR and ROA variables have a significant effect on stock returns. In general, the soundness of banks listed on the IDX is in a healthy condition. Whereas the results of panel regression tests in 2020-2021 (after Covid-19), bank rating (bank soundness level) which include risk profile (NPL and LDR), GCG, earnings (ROA and NIM) and equity (CAR) together have an effect of 4.93% of bank stock returns and 95.07% of stock returns are influenced by other factors outside the variables studied. However, based on the results of the p-value variables, NPL, LDR, GCG, ROA, NIM and CAR have no significant effect on bank stock returns. However, in general, the health level of banks listed on the IDX during the Covid-19 pandemic is in a healthy condition.
The objective of this study is to understand the influence of capital structure, sales growth and firm size on firm value in the automotive and component sub-sectors that are registered on the Indonesia Stock Exchange during 2016-2020 period. The research method used in this research is descriptive and verification methods. The findings of the study state that capital structure significantly and positively influences firm value, while there is no effect of sales growth and firm size on firm value in the automotive and component industry sub-sector companies that are registered on the Indonesia Stock Exchange during 2016-2020 period.
This research is in the form of quantitative research that aims to determine differences in stock prices, abnormal returns, and stock trading volumes before and after the stock split. The sample selection in this study was carried out using a purposive sampling method and obtained a sample of 58 companies from companies that listed on the Indonesia Stock Exchange and carried out stock split corporate actions during 2016 until 2020 period. Hypothesis testing in this study used the SPSS version 28 program using the Paired Sample T-test method for data that is normally distributed and the Wilcoxon Signed-Rank Test for data that is not normally distributed. The result of the research is that there is no difference between stock prices before and after the stock split, while there is a difference between abnormal returns before and after the stock split, and there is a difference between the stock trading volume before and after the stock split.
This study aims to analyze the development and soundness of banks from financial performance ratios in banking companies listed on the IDX in 2016-2021 using the RGEC approach; analyze the effect of the ratios used in RGEC on stock returns in banking companies listed on the IDX in 2016-2019 or before Covid19; analyzed the effect of the ratios used in RGEC on stock returns in banking companies listed on the IDX in 2020-2021 or during the Covid-19 pandemic. The sample consisted of the banking sub-sector listed on the IDX in the period 2016 to 2021. The data analyzed using the RGEC method. Based on the calculation of bank rating (bank soundness level), it can be seen that the key figures for the risk profile, GCG, earning and equity (RGEC) in the banking sub-sector listed on the IDX developed well in 2016-2021 in the banking sector on average from 39 banks studied. There are 11 Banks that are in Composite Rating 1 (Very Healthy), 25 Banks are on Composite Rating 2 (Healthy) and 3 Banks are on Composite Rating 3 (Sufficiently Healthy). Based on the results of panel regression tests in 2016-2019 (before Covid-19), bank rating (bank soundness level) which include risk profile (NPL and LDR), GCG, earnings (ROA and NIM) and equity (CAR) together have an effect of 28.89% of bank stock returns and 71.11% of stock returns are influenced by other factors outside the variables studied. However, based on the p-value results, the variables NPL, GCG, NIM and CAR have no significant effect on bank stock returns, while the LDR and ROA variables have a significant effect on stock returns. In general, the soundness of banks listed on the IDX is in a healthy condition. Whereas the results of panel regression tests in 2020-2021 (after Covid-19), bank rating (bank soundness level) which include risk profile (NPL and LDR), GCG, earnings (ROA and NIM) and equity (CAR) together have an effect of 4.93% of bank stock returns and 95.07% of stock returns are influenced by other factors outside the variables studied. However, based on the results of the p-value variables, NPL, LDR, GCG, ROA, NIM and CAR have no significant effect on bank stock returns. However, in general, the health level of banks listed on the IDX during the Covid-19 pandemic is in a healthy condition.
The purpose of this study is to empirically analyze the performance of liquidity, leverage, profitability, and activities of firms on the Indonesia Stock Exchange during the Covid-19 pandemic based on a quantitative approach. This study uses secondary data from financial reports of firms listed on the Indonesia Stock Exchange that are included in the LQ45 index, which represents the movement of the capital market based on specific criteria. The results reveal that the Covid-19 pandemic has hurt the Indonesian firm’s financial performance. The worst condition has increased the leverage ratio, and the profitability and activity ratio declined, as experienced in several emerging countries. The findings of this research can be a bunch of information for investors in making decisions that these financial ratios are sensitive to economic volatility. In addition, this finding also adds insight to the company's management, especially LQ45 companies, that the company is expected to be able to maintain its financial fundamentals of these ratios. Further research needs to be carried out on how the effects of the Covid-19 pandemic influence financial performance according to the sector type of the firm and conducted in more time series periods.
This research is in the form of quantitative research that aims to determine differences in stock prices, abnormal returns, and stock trading volumes before and after the stock split. The sample selection in this study was carried out using a purposive sampling method and obtained a sample of 58 companies from companies that listed on the Indonesia Stock Exchange and carried out stock split corporate actions during 2016 until 2020 period. Hypothesis testing in this study used the SPSS version 28 program using the Paired Sample T-test method for data that is normally distributed and the Wilcoxon Signed-Rank Test for data that is not normally distributed. The result of the research is that there is no difference between stock prices before and after the stock split, while there is a difference between abnormal returns before and after the stock split, and there is a difference between the stock trading volume before and after the stock split.
The objective of this study is to understand the influence of capital structure, sales growth and firm size on firm value in the automotive and component sub-sectors that are registered on the Indonesia Stock Exchange during 2016-2020 period. The research method used in this research is descriptive and verification methods. The findings of the study state that capital structure significantly and positively influences firm value, while there is no effect of sales growth and firm size on firm value in the automotive and component industry sub-sector companies that are registered on the Indonesia Stock Exchange during 2016-2020 period.
This study was conducted to find out whether there are differences in the financial performance of the Primary Consumer Goods Sector Companies before and during the Covid-19 outbreak. This study uses a probability sampling technique called the Slovin formula to determine the number of samples, the final result obtained is 72 samples of companies. The research period is one year before Covid-19 (2nd quarter of 2019 to 2nd quarter of 2020) and one year during Covid-19 occurs (2nd quarter of 2021 to 2nd quarter of 2022). Data processing in this study uses SPSS 28 with the Wilcoxon signed-rank test analysis technique. The results in the study state that there are differences for profitability and activity variable, while for liquidity and solvency variables shows that there are no differences before and during Covid-19.
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 |