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: 7 / 7 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 — 29 Oct 2026 10:45 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.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 selected publications.
7 / 7 with data · 0 missing or unmatched. Percentages use all 7 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 | 7 | 7 | 7/7 | 7/7 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 11 | 7 | 7/7 | 7/7 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 12 | 7 | 7/7 | 7/7 |
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 7 / 7 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): 2026-10-21T07:22:46.011486+00:00 — 2026-10-29T10:45:17.373878+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 | 7 | 7/7 |
| 2018 | All selected publications | 0 | 7 | 7/7 |
| 2019 | All selected publications | 0 | 7 | 7/7 |
| 2020 | All selected publications | 0 | 7 | 7/7 |
| 2021 | All selected publications | 0 | 7 | 7/7 |
| 2022 | All selected publications | 0 | 7 | 7/7 |
| 2023 | All selected publications | 2 | 7 | 7/7 |
| 2024 | All selected publications | 4 | 7 | 7/7 |
| 2025 | All selected publications | 4 | 7 | 7/7 |
| 2026 | All selected publications | 2 | 7 | 7/7 |
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 ↗
Records with full publication dates only. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2022-01 | 2 |
| 2022-06 | 1 |
| 2022-08 | 1 |
| 2022-09 | 1 |
| 2022-10 | 1 |
| 2022-12 | 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 Finance & Banking Studies SSBFNET | 5 | 1 | 1 | 5/5 | 0.2 | 0 | 20.0 | 5/5 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 10 | 11 | 2/2 | 5.0 | 5.0 | 100.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
The proliferation of technology has innovated new ways of saving and investing money: online savings and investment platforms [OSIPs]. Predicting the intention to adopt Fintech has triggered the interest of many researchers in academia and industries. The primary objective of this study was to examine factors influencing the intention to adopt OSIPs in Nigeria by using data gathered from 640 digitally active citizens from selected cities in Nigeria. Reliability and validity tests were conducted through construct reliability and discriminant validity, respectively, through WarpPLS. Data were computed with the Statistical Package for the Social Sciences (version) 24 and analyzed with structural equation modeling via WarpPLS. The findings of this study showed that performance expectancy, effort expectancy, and social influence significantly affect attitude while facilitating conditions predict intention to adopt. It was also found that attitude significantly influences the intention to adopt OSIPs. The paper also discusses the study’s research limitations and presents implications for theory and practice.
To obtain a comprehensive view of the apparel disposal behaviors of young U.S. consumers, this study evaluated antecedents of apparel disposal behaviors using a framework based on the theory of reasoned action (TRA), categorization theory, and prior literature. Data were obtained from a convenience sample of undergraduate students at a large U.S. Midwestern university through a self-administered online survey. A final sample of 358 usable surveys was analyzed through the use of structural equation modeling (SEM) with Amos. The results supported the proposed relationships between environmental apparel knowledge and attitude toward sustainable methods of apparel disposal. In addition, the proposed relationships between attitude and apparel disposal intention (intention to discard, donate, reuse, or resell) were all supported except for intention to resell. While the results showed a significant and positive relationship between subjective norms and intention to resell or donate apparel, no significant relationship was shown between subjective norms and intention to reuse or discard apparel. In addition, subjective norms were a positive and significant antecedent of attitude. Lastly, respondents’ intention to engage in a particular apparel disposal behavior corresponded with the actual apparel disposal behavior.
Advocates of blockchain claim widespread impact will be forthcoming shortly. However, the path of innovation in blockchain is uncharted. Investors will assess where blockchain innovation will profit first and most. The timing and impact of each blockchain innovation is a key consideration for business managers. Link, Ruhm, and Siegel (2014) suggest private equity investments forecast which innovations are likely to succeed. Previous research on private equity gives insight on why that ownership structure is especially successful. Private equity investments are collected for two periods and categorized according to basic blockchain components, basic cryptocurrency payment components, and decentralized applications, particularly applications in financial services. The results suggest investors have acted prudently, investing strongly in building blocks, payment systems and fundamental applications, showing a primary emphasis on refining blockchain and realizing standard blockchain protocols before investing in highly complex applications. Further, financial services applications dominate, suggesting investors see financial services as far and away the most likely industry for imminent deconstruction.
Previous study finds that the firms with inferior growth options tend to issue callable bonds. Typically, these firms are characterized by stock underperformance. Previous study also finds that the floating rate as a superior alternative to the call provision, which is restrictive, when the interest rates are likely to fall. We study the long-term stock performance of floating rate notes (FRNs) issuing firms, issued when the interest rates are high. Stock overperformance would suggest floating rate as a preferred choice by the firms with high growth options rather the call option. We find that the FRNs are generally investment grade with extremely rare presence of a call option. We perform the analysis using Buy and hold abnormal return (BHAR) as the proxy for the long-term stock overperformance/underperformance. A sample of floating rate notes issued (1654) from 1992 to 2007, a period of high interest rates, reveals significant overperformance by the floating rate notes issuing firms in the high-rate paradigm. High growth firms, in the high-rate environment, significantly benefit from the floating rate provision which is less restrictive and less costly than the call option, which typically provides call protection period and pays a call premium. Floating rate provision better mitigates the interest rate risk for the firms in the high-rate environment. We find that the smaller, high growth, higher leverage, less profitable firms with greater agency issues benefit more from issuing FRNs in the high-rate environment. Our study has relevance to the stock portfolio construction and performance. We also perform a comparative analysis using the sample of floating rate notes issued (270) during 2008 to 2018, a period of low interest rates, and find stock underperformance. The implications are that the call option likely is a better choice for the firm since the firm preserves the right to forego exercising the option.
This paper aims to analyse the effects of financial statement indicators and off-balance sheet items affecting risk measures among Indian banks employing both panel data regression and a non-parametric decision tree approach. We explore the effects of bank size, leverage, exposure to contingent liabilities including off-balance sheet derivatives usage and macroeconomic factors on risk measures for banks. In this paper, it is also aimed to examine the effects of the major financial liberalization policy period in the domestic market in India that started in the mid-1990s and ended around 2004 as well as impacts of the 2008 global financial crisis on the risk measures of banks operating in India. As risk measures, we present a comparative analysis of liquidity, solvency, and interest rate risk measures of Indian banks across public (government) and private ownership categories. Main findings from our study demonstrate (i) significant impact of capital adequacy and the bank size on all the risk measures, (ii) contingent liabilities (including derivatives usage) at banks is observed to significantly impact the asset management measure of liquidity risk and the solvency risk of banks, (iii) GDP growth is observed to impact the asset management and liability management measure of liquidity risk, (iv) the global financial crisis is found to have a significant impact on the liquidity risk measures and interest rate risk, but a weak effect on solvency risk of Indian banks, (v) bank ownership category (government owned versus private sector banks) is observed to have a significant impact on all the risk measures, and finally (vi) financial liberalization reforms had a highly significant effect on the liquidity risk at banks.
The proliferation of technology has innovated new ways of saving and investing money: online savings and investment platforms [OSIPs]. Predicting the intention to adopt Fintech has triggered the interest of many researchers in academia and industries. The primary objective of this study was to examine factors influencing the intention to adopt OSIPs in Nigeria by using data gathered from 640 digitally active citizens from selected cities in Nigeria. Reliability and validity tests were conducted through construct reliability and discriminant validity, respectively, through WarpPLS. Data were computed with the Statistical Package for the Social Sciences (version) 24 and analyzed with structural equation modeling via WarpPLS. The findings of this study showed that performance expectancy, effort expectancy, and social influence significantly affect attitude while facilitating conditions predict intention to adopt. It was also found that attitude significantly influences the intention to adopt OSIPs. The paper also discusses the study’s research limitations and presents implications for theory and practice.
Previous study finds that the firms with inferior growth options tend to issue callable bonds. Typically, these firms are characterized by stock underperformance. Previous study also finds that the floating rate as a superior alternative to the call provision, which is restrictive, when the interest rates are likely to fall. We study the long-term stock performance of floating rate notes (FRNs) issuing firms, issued when the interest rates are high. Stock overperformance would suggest floating rate as a preferred choice by the firms with high growth options rather the call option. We find that the FRNs are generally investment grade with extremely rare presence of a call option. We perform the analysis using Buy and hold abnormal return (BHAR) as the proxy for the long-term stock overperformance/underperformance. A sample of floating rate notes issued (1654) from 1992 to 2007, a period of high interest rates, reveals significant overperformance by the floating rate notes issuing firms in the high-rate paradigm. High growth firms, in the high-rate environment, significantly benefit from the floating rate provision which is less restrictive and less costly than the call option, which typically provides call protection period and pays a call premium. Floating rate provision better mitigates the interest rate risk for the firms in the high-rate environment. We find that the smaller, high growth, higher leverage, less profitable firms with greater agency issues benefit more from issuing FRNs in the high-rate environment. Our study has relevance to the stock portfolio construction and performance. We also perform a comparative analysis using the sample of floating rate notes issued (270) during 2008 to 2018, a period of low interest rates, and find stock underperformance. The implications are that the call option likely is a better choice for the firm since the firm preserves the right to forego exercising the option.
This paper aims to analyse the effects of financial statement indicators and off-balance sheet items affecting risk measures among Indian banks employing both panel data regression and a non-parametric decision tree approach. We explore the effects of bank size, leverage, exposure to contingent liabilities including off-balance sheet derivatives usage and macroeconomic factors on risk measures for banks. In this paper, it is also aimed to examine the effects of the major financial liberalization policy period in the domestic market in India that started in the mid-1990s and ended around 2004 as well as impacts of the 2008 global financial crisis on the risk measures of banks operating in India. As risk measures, we present a comparative analysis of liquidity, solvency, and interest rate risk measures of Indian banks across public (government) and private ownership categories. Main findings from our study demonstrate (i) significant impact of capital adequacy and the bank size on all the risk measures, (ii) contingent liabilities (including derivatives usage) at banks is observed to significantly impact the asset management measure of liquidity risk and the solvency risk of banks, (iii) GDP growth is observed to impact the asset management and liability management measure of liquidity risk, (iv) the global financial crisis is found to have a significant impact on the liquidity risk measures and interest rate risk, but a weak effect on solvency risk of Indian banks, (v) bank ownership category (government owned versus private sector banks) is observed to have a significant impact on all the risk measures, and finally (vi) financial liberalization reforms had a highly significant effect on the liquidity risk at banks.
The crux of bank accounting is how to measure and disclose ex ante credit risk, as loan yields and cost of funds are determined by managerial effectiveness and the financial market. This paper examines how the practice of setting up provisions for loan losses by bank managers had changed to preserve regulatory capitals around the 2008 financial crisis. This paper examines the empirical relationship between ex ante credit loss, which is proxied by loan losses provisions, and realized credit loss, which is measured by net charge-off. The empirical relations are examined before, during, and after the 2008 financial crisis to find the patterns of prediction errors of the incurred loss model. This paper obtains evidence that the empirical relation between non-performing assets and provisions for loan losses weakened at the time of a financial crisis. The relations of net charge-offs and allowance for loan losses on provisions for loan losses amplified during a financial crisis by accounting design. After the financial crisis is over, the empirical relation between non-performing assets and provisions for loan losses does not return back to the pre-crisis relation, but to a different, new post-crisis relation. This paper obtains evidence that financially stable banks in terms of the tier 1 capital ratio, return on assets, market-to-book ratio, or dividend payout ratio tend to adjust provisions for loan losses in a larger scale in response to a financial crisis than less stable banks.
Advocates of blockchain claim widespread impact will be forthcoming shortly. However, the path of innovation in blockchain is uncharted. Investors will assess where blockchain innovation will profit first and most. The timing and impact of each blockchain innovation is a key consideration for business managers. Link, Ruhm, and Siegel (2014) suggest private equity investments forecast which innovations are likely to succeed. Previous research on private equity gives insight on why that ownership structure is especially successful. Private equity investments are collected for two periods and categorized according to basic blockchain components, basic cryptocurrency payment components, and decentralized applications, particularly applications in financial services. The results suggest investors have acted prudently, investing strongly in building blocks, payment systems and fundamental applications, showing a primary emphasis on refining blockchain and realizing standard blockchain protocols before investing in highly complex applications. Further, financial services applications dominate, suggesting investors see financial services as far and away the most likely industry for imminent deconstruction.
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 |