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: 10 / 10 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 01:12 UTC — 29 Oct 2026 10:47 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.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 selected publications.
10 / 10 with data · 0 missing or unmatched. Percentages use all 10 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 |
|---|---|---|---|---|---|
| 2019 | All selected publications | 10 | 10 | 10/10 | 10/10 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 10 | 10 | 10/10 | 10/10 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2019 | All selected publications | 19 | 10 | 10/10 | 10/10 |
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 10 / 10 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): 2026-10-22T01:12:10.977412+00:00 — 2026-10-29T10:47:57.057148+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 | 10 | 10/10 |
| 2018 | All selected publications | 0 | 10 | 10/10 |
| 2019 | All selected publications | 2 | 10 | 10/10 |
| 2020 | All selected publications | 4 | 10 | 10/10 |
| 2021 | All selected publications | 1 | 10 | 10/10 |
| 2022 | All selected publications | 1 | 10 | 10/10 |
| 2023 | All selected publications | 5 | 10 | 10/10 |
| 2024 | All selected publications | 3 | 10 | 10/10 |
| 2025 | All selected publications | 1 | 10 | 10/10 |
| 2026 | All selected publications | 2 | 10 | 10/10 |
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 |
|---|---|
| 2019-02 | 1 |
| 2019-04 | 1 |
| 2019-05 | 2 |
| 2019-07 | 4 |
| 2019-08 | 1 |
| 2019-10 | 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 | 7 | 3 | 11 | 7/7 | 0.43 | 0 | 42.9 | 7/7 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 3 | 7 | 8 | 3/3 | 2.33 | 1 | 66.7 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
The study sought to determine the influence of human resource planning on firm performance of firms listed in the Nairobi Securities Exchange in Kenya. The study was anchored on human capital theory and shareholder value maximization theory. The research design used was a cross-sectional survey while the study population constituted all the 68 listed firms at the Nairobi Stock Exchange (NSE) as in May 2017. The target population included the head of human resources and finance directors in all the listed firms. The sample size comprised of 136 respondents, and data was collected through structured questionnaires to meet the objectives of the study. Responses were tabulated, coded, and processed by the use of a computer Statistical Package for Social Science (SPSS) to analyze the data. Both descriptive and inferential statistical techniques were used to analyze the data. To test hypotheses, a simple linear model was used to test significance between the independent and dependent variable. The study findings revealed that the relationship between human resource planning and firm performance was positive and statistically significant and hence rejected the null hypothesis. The study concluded that the type and strategy of the firm, succession planning, matching skills with jobs and skills inventory are human resource planning indicators influencing the performance of firms listed in the NSE. It is therefore recommended that firms should continue to practice and maintain adequate human resource planning as it plays a fundamental role in achieving the objectives of the organizations.
Mid-cap funds invest in stocks with a market cap between $2 billion and $10 billion. Some of the mid-cap firms recently overcame their small-cap status, but are still in the high growth mode with a better market positioning and stronger balance sheet. Because of their size and status, mid-cap stocks offer a unique platform to portfolio managers of mid-cap funds to earn superior returns by using their selectivity skills. This study analyzes the performance and persistence of performance of 257 U.S. domiciled retail mid-cap funds from January 2000 to December 2017. The results of this study suggest that despite the interesting platform offered by these stocks, it is not easy for fund managers to pick the stocks that beat the market. The results of this study show that mid-cap funds do not outperform the market and their poor performance persists over time.
There have been three major tax cuts in the modern US history: 1) the Tax Cuts and Jobs Act of 2017; 2) the Economic Growth and Tax Relief Reconciliation Act of 2001; and 3) the Economic Recovery Act of 1981. Each of the first two major tax cuts had increased the federal debt. Just about everybody agrees that US federal debt is on an unsustainable path. Can we afford another major tax cut without trigging a major economic disaster such as the Great Recession of 2007-2009? This article discusses an overview of this new law, the impact of the first two major tax cuts on the federal debt, the impact of the Tax Cuts and Job Acts on the US government debt, and its consequences.
This study utilizes hand-collected ownership data to re-examine the signaling, agency and wealth effect theories in a matched-sample of initial public offerings (IPOs) issued in the U.S. prior to and following the passage of the Sarbanes-Oxley Act of 2002 (SOX). SOX provides some motivation for revisiting these topics because evidence exists that it may have affected the types of firms going public and ultimately the relatively importance of adverse selection and moral hazard, the asymmetric information problems with which these theories are concerned. Results on both the pre- and post-SOX samples are consistent with the signaling theory and evidence of a wealth effect exists in both eras. However, in contrast to results of studies conducted prior to SOX, both the pre- and post-SOX results give little credence to the agency theory, suggesting that SOX has not impacted investors’ concerns regarding moral hazard. Rather, the difference between the pre-SOX results and the results of previous studies suggests that SOX appeared to reduce moral hazard concerns only through its effect on the self-selection of firms going public.
Univariate Time Series Models [TSM] use only a Panel of historical data to produce forecasts. The tacit belief in using TSM is that the past information portends the future of the longitudinal data-stream. This is likely in certain cases such as strictly Ergodic Panel segments of sufficient size in the overall Panel. A question of interest is: Is the success of TSM in these contexts generalizable? The test of this question used a Litmus-Test design to examine the performance profile of TSM for a longitudinal time series the last point of which is a Turning Point [TP]. Specifically, the inference measure will use the Relative Absolute Error [RAE] of the TSM tested over three forecasting horizons. In this testing, five TSM configurations were employed; the TPs are identified using a fixed screening filter applied to randomly selected firm Panels actively traded on the S&P500 from 2005 through 2013. There is no evidence that any of the five TSM outperformed the RW model which is incidentally the TP. The impact of these results is that one cannot assume that the effectiveness of TSM generalizes to all domains—in particular—forecasting after TPs that seems to be a Domain Lacuna where the effectiveness of TSM will be compromised.
The object of this study is to explore the effect of cultural distance on both the long run and short run performance of cross border mergers and acquisitions undertaken by Indian acquiring firms. We utilize buy and hold returns (BHAR), cumulative abnormal returns (CAR) and cross-sectional regression analysis in our study. Adopting the traditional Hofstede measure of cultural distance and other pertinent variables, commonly used to measure cultural differences, we document a negative and statistically significant influence of cultural distance on Indian cross-border M&As and corroborate some of other findings reported in prior research. Also, we find that the BHAR is nevertheless higher when the acquisitions are friendly, paid for 100% cash, and the acquiring firm is large, older and belongs to a business group. The inclusion of the variable ‘business group’ along with industry relatedness and acquirer size provides valuable insights into the Indian cross border acquisition landscape, wherein business groups dominate to a great extent.
The study sought to determine the influence of human resource planning on firm performance of firms listed in the Nairobi Securities Exchange in Kenya. The study was anchored on human capital theory and shareholder value maximization theory. The research design used was a cross-sectional survey while the study population constituted all the 68 listed firms at the Nairobi Stock Exchange (NSE) as in May 2017. The target population included the head of human resources and finance directors in all the listed firms. The sample size comprised of 136 respondents, and data was collected through structured questionnaires to meet the objectives of the study. Responses were tabulated, coded, and processed by the use of a computer Statistical Package for Social Science (SPSS) to analyze the data. Both descriptive and inferential statistical techniques were used to analyze the data. To test hypotheses, a simple linear model was used to test significance between the independent and dependent variable. The study findings revealed that the relationship between human resource planning and firm performance was positive and statistically significant and hence rejected the null hypothesis. The study concluded that the type and strategy of the firm, succession planning, matching skills with jobs and skills inventory are human resource planning indicators influencing the performance of firms listed in the NSE. It is therefore recommended that firms should continue to practice and maintain adequate human resource planning as it plays a fundamental role in achieving the objectives of the organizations.
This paper investigates whether false confidence, as characterized by a high level of personal mastery and a low level of intelligence (IQ), results in frequent investor trading and subsequent investor wealth erosion across time. Using the National Longitudinal Survey (NLSY79), change in wealth and asset allocation across time is modeled as a function of various behavioral, socio-economic and demographic variables drawn from prior literature. Findings of this research reveal that false confidence is indeed a predictor of trading activity in individual investment assets, and it also has a negative impact on individual wealth creation across time.
This study aims to evaluate the effect of regulatory corporate governance mandates on the valuation of equity-issuing firms in the U.S. Using a matched sample, we examine how the Exchange Listing Requirements, specifically, and the Sarbanes-Oxley Act (SOX), generally, affect IPO valuations. Board structure compliance provides no consistent valuation benefit. We find some evidence of negative effects for firms whose board structure is significantly altered by Reform and among small firms. The absence of increased valuations post-Reform suggests that there is little to offset the loss of private control benefits that Reform represents (post-Reform insider ownership and founder involvement are lower) and, thus, at the margin, Reform creates incentives for some firms to stay private. While the 2012 JOBS Act reduced the burden of registration, reporting and accounting requirements of SOX for small firms, it did nothing to change the board structure requirements of these firms. The results of this study together with those of Wintoki (2007) and Rhodes (2018) suggest that regulations pertaining to the board structure requirements of small equity-issuing firms should either be modified to allow more flexibility or repealed altogether. If lawmakers ultimately relax these requirements, future studies may focus on changes in board structures, private benefits of control, and the rates at which firms access public equity markets.
Mid-cap funds invest in stocks with a market cap between $2 billion and $10 billion. Some of the mid-cap firms recently overcame their small-cap status, but are still in the high growth mode with a better market positioning and stronger balance sheet. Because of their size and status, mid-cap stocks offer a unique platform to portfolio managers of mid-cap funds to earn superior returns by using their selectivity skills. This study analyzes the performance and persistence of performance of 257 U.S. domiciled retail mid-cap funds from January 2000 to December 2017. The results of this study suggest that despite the interesting platform offered by these stocks, it is not easy for fund managers to pick the stocks that beat the market. The results of this study show that mid-cap funds do not outperform the market and their poor performance persists over time.
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 |