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: 4 / 4 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 23:32 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.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 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 |
|---|---|---|---|---|---|
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 9 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2020 | All selected publications | 20 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 20 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 21 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
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 4 / 4 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): 2026-10-21T07:22:59.998441+00:00 — 2026-10-23T23:32:52.926849+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 | 4 | 4/4 |
| 2018 | All selected publications | 0 | 4 | 4/4 |
| 2019 | All selected publications | 0 | 4 | 4/4 |
| 2020 | All selected publications | 0 | 4 | 4/4 |
| 2021 | All selected publications | 1 | 4 | 4/4 |
| 2022 | All selected publications | 11 | 4 | 4/4 |
| 2023 | All selected publications | 20 | 4 | 4/4 |
| 2024 | All selected publications | 18 | 4 | 4/4 |
| 2025 | All selected publications | 8 | 4 | 4/4 |
| 2026 | All selected publications | 4 | 4 | 4/4 |
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 |
|---|---|
| 2020 | 1 |
| 2021 | 1 |
| 2022 | 1 |
| 2025 | 1 |
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 | 4 | 15 | 62 | 4/4 | 3.75 | 2.5 | 100.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
This study aims to determine the effect of earnings management on tax avoidance and the role of political connections in moderating those relationships. The population in this study are manufacturing companies listed on the Indonesia Stock Exchange for the 2016-2020 period. There are 234 samples out of 835 total observations, produced by using purposive sampling. This study was tested by using Multiple Linear Regression Analysis and Moderated Regression Analysis. The results show that earnings management has a significant positive effect on tax avoidance and political connections strengthen the effect of earnings management on tax avoidance. This research used several control variables as well, which are firm size, leverage, profitability, firm value, and firm age, and the results show that profitability has a significant negative effect on tax avoidance, the firm value partially has a significant positive effect on tax avoidance, while firm size, leverage, and firm age have no significant effect on tax avoidance.
This study aims to analyze the effect of executive characteristics and family ownership as a stimulus factor for tax avoidance and to see the existence of a political relationship as a moderating variable in the effect of executive characteristics and family ownership on tax avoidance. This research was conducted on manufacturing companies listed on the Indonesia Stock Exchange during 2017-2019. In this study, the sample was determined based on the purposive sampling technique with the criteria that the sample company was manufacture listed on the IDX for three consecutive years from 2017-2019, published an annual report in the 2017-2019 period sequentially, did not experience delisting, was not a company the IPO in 2018-2019, did not experience any losses and did not have an ETR value of more than 1. The research sample was obtained from as many as 138 companies with 3 years of observation. This study uses multiple linear regression analysis (Multiple Regression Analysis) and Moderate Regression Analysis (MRA) using the Statistical Product and Service Solution (SPSS) program. The results showed (I) executive characteristics had a significant positive effect on tax avoidance (II) family ownership had a significant negative effect on tax avoidance (III) political connections were not able to strengthen the executive's positive influence on tax avoidance (IV) political connections weakened family ownership on tax avoidance. This study can also show that the sample companies tend to comply with tax rules, they avoid sanctions and fines, and consider the risk of loss that must be faced by the company when proven to do tax avoidance.
This study aims to verify the correlation between financial distress and earnings management of tax aggressiveness moderated by corporate governance. This study uses a population of manufacturing companies that publish their financial statement on the Indonesia Stock Exchange from 2017 until 2018. Sample collection was performed using a purposive sampling method, resulting in a total of 212 populations that published complete financial reports. This study was tested by using the Multiple Regression Analysis test. This research gave empirical proofs that financial distress and real earnings management positively influenced the tax aggressiveness was supported, the proportion of independent commissioners weakened the financial distress and negatively impacted the tax aggressiveness was supported, the total audit committees weakened the financial distress and negatively influenced the tax aggressiveness was not supported, the proportion of independent commissioners and total audit committees weakened the real earnings management and negatively affected the tax aggressiveness was not supported
The aim of the study is to determine factors contribute to tax avoidance in Indonesia, an emerging economy in Southeast Asia. It also looks for analyze how the profitability, corporate growth, Corporate Social Responsibility, and firm characteristics (size and age) relate to tax avoidance. It analyses manufacturing company collected from Indonesia Stock Exchange between 2016-2019 period using multivariate analysis. It applied effective tax rate as a proxy for corporate tax avoidance, CSR performance disclosure index for CSR and Return on Assets for profitability. The results of this study confirmed that the effect of sales growth and corporate size on tax avoidance is statistically supported. Contrarily, profitability, CSR, and corporate age have not significant associated with corporate tax avoidance. Our findings suggest that in manufacture sectors, CSR instrument is applied not only as a strategic tool to increase firm reputation, but also to increase tax saving. Future study is highly recommended to exploit the role of corporate governance on tax avoidance by comparing developed and emerging economies.
The aim of the study is to determine factors contribute to tax avoidance in Indonesia, an emerging economy in Southeast Asia. It also looks for analyze how the profitability, corporate growth, Corporate Social Responsibility, and firm characteristics (size and age) relate to tax avoidance. It analyses manufacturing company collected from Indonesia Stock Exchange between 2016-2019 period using multivariate analysis. It applied effective tax rate as a proxy for corporate tax avoidance, CSR performance disclosure index for CSR and Return on Assets for profitability. The results of this study confirmed that the effect of sales growth and corporate size on tax avoidance is statistically supported. Contrarily, profitability, CSR, and corporate age have not significant associated with corporate tax avoidance. Our findings suggest that in manufacture sectors, CSR instrument is applied not only as a strategic tool to increase firm reputation, but also to increase tax saving. Future study is highly recommended to exploit the role of corporate governance on tax avoidance by comparing developed and emerging economies.
This study aims to determine the effect of earnings management on tax avoidance and the role of political connections in moderating those relationships. The population in this study are manufacturing companies listed on the Indonesia Stock Exchange for the 2016-2020 period. There are 234 samples out of 835 total observations, produced by using purposive sampling. This study was tested by using Multiple Linear Regression Analysis and Moderated Regression Analysis. The results show that earnings management has a significant positive effect on tax avoidance and political connections strengthen the effect of earnings management on tax avoidance. This research used several control variables as well, which are firm size, leverage, profitability, firm value, and firm age, and the results show that profitability has a significant negative effect on tax avoidance, the firm value partially has a significant positive effect on tax avoidance, while firm size, leverage, and firm age have no significant effect on tax avoidance.
This study aims to analyze the effect of executive characteristics and family ownership as a stimulus factor for tax avoidance and to see the existence of a political relationship as a moderating variable in the effect of executive characteristics and family ownership on tax avoidance. This research was conducted on manufacturing companies listed on the Indonesia Stock Exchange during 2017-2019. In this study, the sample was determined based on the purposive sampling technique with the criteria that the sample company was manufacture listed on the IDX for three consecutive years from 2017-2019, published an annual report in the 2017-2019 period sequentially, did not experience delisting, was not a company the IPO in 2018-2019, did not experience any losses and did not have an ETR value of more than 1. The research sample was obtained from as many as 138 companies with 3 years of observation. This study uses multiple linear regression analysis (Multiple Regression Analysis) and Moderate Regression Analysis (MRA) using the Statistical Product and Service Solution (SPSS) program. The results showed (I) executive characteristics had a significant positive effect on tax avoidance (II) family ownership had a significant negative effect on tax avoidance (III) political connections were not able to strengthen the executive's positive influence on tax avoidance (IV) political connections weakened family ownership on tax avoidance. This study can also show that the sample companies tend to comply with tax rules, they avoid sanctions and fines, and consider the risk of loss that must be faced by the company when proven to do tax avoidance.
This study aims to verify the correlation between financial distress and earnings management of tax aggressiveness moderated by corporate governance. This study uses a population of manufacturing companies that publish their financial statement on the Indonesia Stock Exchange from 2017 until 2018. Sample collection was performed using a purposive sampling method, resulting in a total of 212 populations that published complete financial reports. This study was tested by using the Multiple Regression Analysis test. This research gave empirical proofs that financial distress and real earnings management positively influenced the tax aggressiveness was supported, the proportion of independent commissioners weakened the financial distress and negatively impacted the tax aggressiveness was supported, the total audit committees weakened the financial distress and negatively influenced the tax aggressiveness was not supported, the proportion of independent commissioners and total audit committees weakened the real earnings management and negatively affected the tax aggressiveness was not supported
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 |