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: 22 Oct 2026 01:25 UTC — 22 Oct 2026 03:18 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 |
|---|---|---|---|---|---|
| 2015 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2015 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2015 | All selected publications | 8 | 1 | 1/1 | 1/1 |
| 2016 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2021 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2022 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2024 | All selected publications | 0 | 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 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): 2026-10-22T01:25:14.968522+00:00 — 2026-10-22T03:18:43.059962+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 | 1 | 5 | 5/5 |
| 2022 | All selected publications | 1 | 5 | 5/5 |
| 2023 | All selected publications | 1 | 5 | 5/5 |
| 2024 | All selected publications | 3 | 5 | 5/5 |
| 2025 | All selected publications | 1 | 5 | 5/5 |
| 2026 | All selected publications | 1 | 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 |
|---|---|
| 2015 | 1 |
| 2020 | 1 |
| 2022 | 1 |
| 2023 | 1 |
| 2024 | 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 Business Ecosystem & Strategy Bussecon International Academy | 1 | 0 | 0 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 3 | 2 | 9 | 3/3 | 0.67 | 0 | 33.3 | 3/3 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 1 | 0 | 0 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
* Percentage among publications with a known citation count.
In this paper, we examine the impact of CEO power on auditor choice. We are motivated by the competing financial reporting incentives arising from CEO power. Our empirical finding suggests that powerful CEOs are more likely to hire high-quality auditors as a signal of superior financial reporting quality. We contribute to the literature of auditor switch and extend the research on the links between CEO power and firm behaviors.
We examine the value relevance of intangibles reported by technology firms in electronics industries and any regional difference between Southern and non-Southern firms in the relative importance of how value relevance is reported. For technology firms, the essential asset in their valuation is intellectual property, which idiosyncratic accounting practices could have either capitalized or expensed. We are interested in the intangible assets and goodwill on balance sheets and amortization expenses from income statements, which together capture the magnitude of a firm’s intellectual property. We present evidence that the market value of a firm is negatively associated with the size of its intangibles but positively associated with the size of goodwill and amortization expenses. We find that this relationship between the market value of a firm and measures of intangibles is statistically stronger for Southern firms than for non-Southern firms. We interpret this finding as a manifestation of stronger accounting conservatism among Southern firms due to regional cultural differences. We find that the value relevance of intangibles weakened significantly during the 2008 financial crisis, and we interpret the intertemporal difference as a spillover effect of the stringent application of the fair value accounting standard (SFAS 157) to financial assets.
To improve audit reports' transparency and information content, China implemented new auditing standards in 2017. The standards, which include disclosing key audit matters, were applied to A+H share companies in 2017 and A-share companies in 2018. This paper uses A+H-share companies as the experimental group and A-share companies as the control group and applies the difference-in-differences method to test the market response to the new auditing standards. We find a statistically significant positive cumulative abnormal return (CAR) during the report release event window for the A+H share companies. The results indicate a greater investor reaction to the release of audit reports under the new standards implying that the audit reforms enhanced the information of the reports. Furthermore, the positive CAR indicates that the reports reassured investors that the audit did not reveal significant problems or that existing weaknesses were addressed. We also found a statistically insignificant difference in the volatility of stock prices during the event window for the experimental and control group.
AS5[v.Dec:2017] issued by the Public Company Accounting Oversight Board [PCAOB] requires the use of Analytical Procedures [AP] at the Planning and Substantive Phases of Assurance Audits for firms traded on active exchanges. We argue that one aspect of AP, relative to risk-setting, should be vetting the information that is produced/published by the audit client pertaining to Regulation G [v.SEC:2003] called: Non-GAAP information. In our research, we intend to leverage the longstanding Reg[G] requirements to extend the Non-GAAP information to firm performance profiles reported for the Environment, Social, and Governance[ESG]Platform on BloombergÒ. There are two research foci: (1) Offer an AP-Model that uses GAAP & ESG variables to contribute audit evidence useful in making the decision to launch an AP-Extended Procedures examination of the firm’s Enterprise Resource Planning & Control [ERP&C] protocols, and (2) Profile a random accrual-set of firms indexed on Bloomberg so as to offer population parameter estimates for refining the AP-Model. The AP-Model is based upon correlational associations for the ESG- & GAAP-variables from the: Income, Balance Sheet & Cash Flow Statements. If there seems to be a disconnect between the nature of these associations for the ESG-variables and those of the GAAP-variables, the auditor may use this as audit evidence in making the decision to conduct an Extended Procedures Examination of the firm’s [ERP&C] protocols. As for the other focus, we found that for the accrual of firms tested there is no inferential evidence that the ERP&C-protocols are consistent drivers for both the ESG- and the GAAP variable sets.
Controlling corporate governance decision-making RISK is one of the prime safeguarding directives in the PCAOB’s requirement that the financials of Market Trading Firms [MTFs] are reasonably free from material error and thus are reliable indications of the results of operations. In this Corporate Governance Risk [CGR] context, it is important to understand the Interacting- & Integrated-Systemic Components of CGR and how they have evolved over time. We examine these aspects from Circa 1985 to date. We argue that the Driving Control System is: The Firm’s decision-making system of Internal Control over Financial Reporting [ICoFR] that impacts the Nature of CGR—to wit, Increasing CGRisk results as management experiences Increasing difficulties in maintaining adequate ICoFR. We examine the historical development of these systemic components and how they have spawned an Economic Sector of Firms that Rate & Score MTFs on the nature of their CGR profile, one currently predominate aspect of which is: The Nature of the MTF’s Caretaker Persona. With this as context, we present a duel-effect inferential design that examines the reliability of the Bloomberg™ Market Navigation Platform’s Institutional Shareholder Services™ [ISS]-Profiler as an information-link to be used in selecting MTFs to create CGR-sensitive Investment Portfolios. Our inferential results suggest for the MTFs in the ISS-Groups [{1: Lowest CGR} & {5: Mid-Level CGR} & {10: Highest CGR]}, it is likely that: (i) The decisions made by all involved in Management’s System of ICoFR, in its current COSO-version, are reflective of these MTF’s Caretaker Personas, (ii) The effects of these Caretaker Personas are analytically perceptible as reflected in the MTF’s Financials, and (iii) are aligned with the expected Nature of the ISS-Groups.
Controlling corporate governance decision-making RISK is one of the prime safeguarding directives in the PCAOB’s requirement that the financials of Market Trading Firms [MTFs] are reasonably free from material error and thus are reliable indications of the results of operations. In this Corporate Governance Risk [CGR] context, it is important to understand the Interacting- & Integrated-Systemic Components of CGR and how they have evolved over time. We examine these aspects from Circa 1985 to date. We argue that the Driving Control System is: The Firm’s decision-making system of Internal Control over Financial Reporting [ICoFR] that impacts the Nature of CGR—to wit, Increasing CGRisk results as management experiences Increasing difficulties in maintaining adequate ICoFR. We examine the historical development of these systemic components and how they have spawned an Economic Sector of Firms that Rate & Score MTFs on the nature of their CGR profile, one currently predominate aspect of which is: The Nature of the MTF’s Caretaker Persona. With this as context, we present a duel-effect inferential design that examines the reliability of the Bloomberg™ Market Navigation Platform’s Institutional Shareholder Services™ [ISS]-Profiler as an information-link to be used in selecting MTFs to create CGR-sensitive Investment Portfolios. Our inferential results suggest for the MTFs in the ISS-Groups [{1: Lowest CGR} & {5: Mid-Level CGR} & {10: Highest CGR]}, it is likely that: (i) The decisions made by all involved in Management’s System of ICoFR, in its current COSO-version, are reflective of these MTF’s Caretaker Personas, (ii) The effects of these Caretaker Personas are analytically perceptible as reflected in the MTF’s Financials, and (iii) are aligned with the expected Nature of the ISS-Groups.
We examine the value relevance of intangibles reported by technology firms in electronics industries and any regional difference between Southern and non-Southern firms in the relative importance of how value relevance is reported. For technology firms, the essential asset in their valuation is intellectual property, which idiosyncratic accounting practices could have either capitalized or expensed. We are interested in the intangible assets and goodwill on balance sheets and amortization expenses from income statements, which together capture the magnitude of a firm’s intellectual property. We present evidence that the market value of a firm is negatively associated with the size of its intangibles but positively associated with the size of goodwill and amortization expenses. We find that this relationship between the market value of a firm and measures of intangibles is statistically stronger for Southern firms than for non-Southern firms. We interpret this finding as a manifestation of stronger accounting conservatism among Southern firms due to regional cultural differences. We find that the value relevance of intangibles weakened significantly during the 2008 financial crisis, and we interpret the intertemporal difference as a spillover effect of the stringent application of the fair value accounting standard (SFAS 157) to financial assets.
To improve audit reports' transparency and information content, China implemented new auditing standards in 2017. The standards, which include disclosing key audit matters, were applied to A+H share companies in 2017 and A-share companies in 2018. This paper uses A+H-share companies as the experimental group and A-share companies as the control group and applies the difference-in-differences method to test the market response to the new auditing standards. We find a statistically significant positive cumulative abnormal return (CAR) during the report release event window for the A+H share companies. The results indicate a greater investor reaction to the release of audit reports under the new standards implying that the audit reforms enhanced the information of the reports. Furthermore, the positive CAR indicates that the reports reassured investors that the audit did not reveal significant problems or that existing weaknesses were addressed. We also found a statistically insignificant difference in the volatility of stock prices during the event window for the experimental and control group.
AS5[v.Dec:2017] issued by the Public Company Accounting Oversight Board [PCAOB] requires the use of Analytical Procedures [AP] at the Planning and Substantive Phases of Assurance Audits for firms traded on active exchanges. We argue that one aspect of AP, relative to risk-setting, should be vetting the information that is produced/published by the audit client pertaining to Regulation G [v.SEC:2003] called: Non-GAAP information. In our research, we intend to leverage the longstanding Reg[G] requirements to extend the Non-GAAP information to firm performance profiles reported for the Environment, Social, and Governance[ESG]Platform on BloombergÒ. There are two research foci: (1) Offer an AP-Model that uses GAAP & ESG variables to contribute audit evidence useful in making the decision to launch an AP-Extended Procedures examination of the firm’s Enterprise Resource Planning & Control [ERP&C] protocols, and (2) Profile a random accrual-set of firms indexed on Bloomberg so as to offer population parameter estimates for refining the AP-Model. The AP-Model is based upon correlational associations for the ESG- & GAAP-variables from the: Income, Balance Sheet & Cash Flow Statements. If there seems to be a disconnect between the nature of these associations for the ESG-variables and those of the GAAP-variables, the auditor may use this as audit evidence in making the decision to conduct an Extended Procedures Examination of the firm’s [ERP&C] protocols. As for the other focus, we found that for the accrual of firms tested there is no inferential evidence that the ERP&C-protocols are consistent drivers for both the ESG- and the GAAP variable sets.
In this paper, we examine the impact of CEO power on auditor choice. We are motivated by the competing financial reporting incentives arising from CEO power. Our empirical finding suggests that powerful CEOs are more likely to hire high-quality auditors as a signal of superior financial reporting quality. We contribute to the literature of auditor switch and extend the research on the links between CEO power and firm behaviors.
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 |