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: 19 / 19 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 07:22 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.
17 / 19 with data · 2 missing or unmatched. Percentages use all 19 selected publications.
17 / 19 with data · 2 missing or unmatched. Percentages use all 19 selected publications.
19 / 19 with data · 0 missing or unmatched. Percentages use all 19 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 |
|---|---|---|---|---|---|
| 2014 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2015 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| 2023 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2014 | All selected publications | 1 | 2 | 2/2 | 2/2 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 5 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 7 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 13 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | 12 | 4 | 4/4 | 4/4 |
| 2023 | All selected publications | 4 | 3 | 3/3 | 3/3 |
| 2024 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 1 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2014 | All selected publications | 5 | 2 | 2/2 | 2/2 |
| 2015 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2016 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 15 | 1 | 1/1 | 1/1 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 8 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 20 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 38 | 3 | 3/3 | 3/3 |
| 2022 | All selected publications | 38 | 4 | 4/4 | 4/4 |
| 2023 | All selected publications | 9 | 3 | 3/3 | 3/3 |
| 2024 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 1 | 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 19 / 19 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): 2026-10-21T00:14:27.797674+00:00 — 2026-10-21T07:22:59.998441+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 | 19 | 19/19 |
| 2018 | All selected publications | 0 | 19 | 19/19 |
| 2019 | All selected publications | 3 | 19 | 19/19 |
| 2020 | All selected publications | 3 | 19 | 19/19 |
| 2021 | All selected publications | 4 | 19 | 19/19 |
| 2022 | All selected publications | 17 | 19 | 19/19 |
| 2023 | All selected publications | 40 | 19 | 19/19 |
| 2024 | All selected publications | 35 | 19 | 19/19 |
| 2025 | All selected publications | 21 | 19 | 19/19 |
| 2026 | All selected publications | 13 | 19 | 19/19 |
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 |
|---|---|
| 2014 | 2 |
| 2016 | 1 |
| 2017 | 1 |
| 2019 | 1 |
| 2020 | 1 |
| 2021 | 3 |
| 2022 | 4 |
| 2023 | 3 |
| 2024 | 1 |
| 2025 | 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 | 1 | 0 | 3 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 6 | 3 | 10 | 6/6 | 0.5 | 0.0 | 33.3 | 6/6 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 12 | 44 | 123 | 12/12 | 3.67 | 3.0 | 100.0 | 12/12 · 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.
Taxes form a significant portion of a company’s expenses and in order to increase probable returns, tax planning is vital to financing and investment decisions of an entity. This study sought to find out the influence of tax avoidance on financial performance of all the nine manufacturing firms listed on the Nairobi Securities Exchange during the period 2010-2017. The study was anchored on tax planning theory, capital structure trade-off theory, agency cost theory and political power theory. The study adopted a positivism research philosophy and an explanatory research design. SPSS version 23 was used to analyze data where both descriptive and inferential statistics was done. Multiple linear regression model was adopted to study the association between the variables while utilizing panel data. The study findings showed that there is no significant statistical association between tax planning and financial performance of the manufacturing companies listed in the Nairobi Securities Exchange. The findings indicated that capital intensity, research and development expenditure and company size have a positive insignificant association with financial performance. Further, debt to equity ratio indicated an insignificant negative relationship with financial performance. The study points out that the manufacturing companies should invest more in non-current assets and increase expenditure on the research and development expenditure to realize significant positive impact on financial performance. They should also manage their debt to equity ratios to avoid excess financing costs that may be detrimental to their financial performance.
This paper examines the effect of tax avoidance, bonus mechanism, debt covenant, tunneling incentive, audit quality, multinationality, foreign ownership, and company size on transfer pricing. This research population is all manufacturing companies that list at Indonesia Stock Exchange on the period of 2016-2018 but the collected data are on a period of 2015-2019. The sampling technique uses a purposive method to obtain 275 samples in the observation period of 2016-2018. The method of this research involves descriptive statistic test, classical assumption test, and hypothesis test. A regression test is used for testing the hypotheses. The result of the research shows that tax avoidance, debt covenant, and company size have a significant effect on transfer pricing decision. The factors are multinationality, foreign ownership and audit quality also have a significant effect on transfer pricing decisions. Meanwhile, bonus mechanism and tunneling incentives do not significantly affect transfer pricing decisions. Conclusions from this research is a lot of factors involved in the transfer pricing decision. One from inside the company and the others from an outside company. Transfer pricing is a tool to achieve certain goals. The purpose of transfer pricing can be categorized as internal goals and external goals. The manufacturing companies when deciding about transfer pricing must be careful because there are two perceptive about transfer pricing. One perceptive from a business that transfer pricing is something useful because a company can save money related tax but the other perceptive from the government side, transfer pricing has believed to be able to have reduced or even disappearing potential for a country’s tax revenue.
The research’s first purpose is to analyze directly conservatism accounting influence towards book tax differences and tax avoidance. The second purpose is to analyse indirect influence towards tax avoidance through book tax differences. The research is conducted to companies enlisted in Indonesian Stock Exchange and belongs to LQ45 during 2013 to 2015. The number of companies sample taken by purposive sampling is 23 corporations, therefore total observation is 69 observations. The acquired data analysed by path analysis. This research conclude that conservatism accounting practice significantly influence book tax difference practice but did not influence tax avoidance. Conservatism accounting practice is also having no influence towards tax avoidance committed by book tax differences. This book tax difference is only significantly influential to commit tax avoidance. This research can contribute in taxation field as input in tax planning formulation.
This study aims to examine does independence of the Board of Commissioner (BOC) is still relevant as a corporate governance mechanism regarding monitoring managers’ activity, such as aggressive in financial reporting and tax avoidance during financial distress condition. The focus of this study is listed companies on the Indonesia Stock Exchange (IDX), particularly on Mining and Consumer Good Industry sector for period 2016 until 2018. Using multiple linear regression analysis, this study documents that Independency of board commissioner has significant effect on manager’s activity in avoiding tax, however this study failed to document that independency moderates the effect of financial distress and financial reporting aggressiveness on tax avoidance. In addition, this study find that financial distress and financial re-porting aggressiveness positively affect tax avoidance. This study contributes on two ways, first, it adds empirical evidence regarding the relevancy of board of commissioner’s independency as a measure of corporate governance mechanism to monitor managers’ activities in avoiding tax. Second, it also adds evidence that independence is unable to moderates the effect of financial distress and financial reporting aggressiveness on tax avoidance activities performed by managers. In brief, this study implies that the independence of BoC, solely as a measure of corporate governance mechanism is less relevant in a current situation especially when the company facing financial distress conditions and managers’ aggressiveness in financial reporting. Managers should more pay attention to the discretion of tax avoidance activities particularly when facing financial distress condition. The results also imply that regulatory bodies, for instance, Stock Exchange Supervisory Board under the Indonesian Financial Services Authority should reconsider or reformation the concept of independence of Board Commissioners.
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 examines the relationship between audit quality and tax avoidance practices among listed banking companies in Bangladesh. The investigation utilized secondary data from the published annual reports of 36 listed banks on the Dhaka Stock Exchange, covering the period from 2018 to 2022. Therefore, the final dataset consists of 170 firm-year observations. In this research, audit quality was measured using four different variables: audit fees, audit tenure, the presence of a Big4 audit firm, and the disclosure of Key Audit Matters (KAM). The findings indicate that both the audit fees and KAM disclosure have a statistically significant positive relationship with tax avoidance. Conversely, while the presence of a Big4 auditor and audit tenure also demonstrate a positive relationship with tax avoidance, but this relation is not statistically significant. These findings suggest that rigorous auditing practices are essential for maintaining tax compliance within financial systems. Conducting audits with integrity, thoroughness, and adherence to professional standards can significantly impact tax compliance. Furthermore, the results highlight the need for tax authorities to identify and close the tax loopholes that companies exploit for tax avoidance. Promoting collaboration between regulatory bodies, tax authorities, and auditing firms is necessary to reduce tax avoidance activities by the firms.
This study intends to examine the influence of ownership structure and political connections on tax avoidance using the Book Tax Differences (BTD) method. The data used is industrial entities registered on the IDX for the 2018-2022 period. By utilizing the proportional sampling method, the study sample that fulfilled the criteria was only 40 companies so 200 observational data were obtained which were used as the study sample. Panel data regression analysis is the chosen analytical method in this research which includes the Chow test, Hausman test, and hypothesis testing using Eviews as a data analytics tool. The test results imply that (i) government ownership negatively impacts tax avoidance, (ii) institutional ownership positively impacts tax avoidance, (iii) family ownership positively impacts tax avoidance, (iv) foreign ownership shows a non-significant positive impact on tax avoidance, and (v) political connections exhibit a non-significant negative impact on tax avoidance.
This research aims to find out and analyze the effect of the bonus mechanism, tunneling incentive, and exchange rate on company decisions to perform transfer pricing practices in 35 manufacturing and mining sector companies listed on the Indonesia Stock Exchange for the 2018–2020 period. The population of this research is used in the manufacturing and mining sectors listed on the Indonesia Stock Exchange (IDX). This research is a type of quantitative research using secondary data in the form of the company’s annual report and financial statement. The Random Effect Model (REM) with panel data regression was used in this study using STATA version 16. Based on the test results and analysis, it can be concluded that the bonus mechanism has a significant positive effect on transfer pricing, the exchange rate has a significant negative effect on transfer pricing, and the tunneling incentive has no effect on transfer pricing.
This research aims to contribute to solving the problem of tax evasion, by examine the impact of shareholders, intellectual capital, auditor reputation, and level of liabilities on tax evasion. The population is taken from manufacturing companies operating in consumer goods from 2017 to 2021 at IDX (Indonesia). The sample was selected using purposive sampling method. The dependent variable of this research is tax evasion. The independent variables are: type of shareholders, intellectual capital, auditor reputation and level of liabilities. The data analysis technique uses multiple linear regression, and it is processed using statistical software. The results found that domestic private shareholder, foreign private, the government, and individuals’ share holder have a significant negative impact on the Earnings Tax Ratio (ETR), which is a proxy for tax evasion. This means that all types of shareholders seek to avoid taxes, even in state-owned enterprises. Tax avoidance in Indonesia is difficult to eradicate because it is carried out by various parties, specifically tax officers, tax consultants, and taxpayers. The discussion of this research is limited to various factors that influence tax evasion. Subsequent research can identify how much the state loses due to tax evasion, which is carried out by tax officers, consultants, or by taxpayers. This research found that all types of owners avoid taxes. This can be prevented if the Indonesian government can 1) enforce the law, 2) increase the trust of taxpayers, 3) avoid showing off the luxurious life of tax officials and their families. 4) uphold honesty and avoid corrupt behaviour.
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 |