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 01:04 UTC — 29 Oct 2026 19:39 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 | 5 | 5 | 5/5 | 5/5 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2015 | All selected publications | 44 | 5 | 5/5 | 5/5 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2015 | All selected publications | 95 | 5 | 5/5 | 5/5 |
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): 2026-10-22T01:04:38.938722+00:00 — 2026-10-29T19:39:30.467301+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 | 10 | 5 | 5/5 |
| 2018 | All selected publications | 12 | 5 | 5/5 |
| 2019 | All selected publications | 23 | 5 | 5/5 |
| 2020 | All selected publications | 9 | 5 | 5/5 |
| 2021 | All selected publications | 12 | 5 | 5/5 |
| 2022 | All selected publications | 13 | 5 | 5/5 |
| 2023 | All selected publications | 7 | 5 | 5/5 |
| 2024 | All selected publications | 0 | 5 | 5/5 |
| 2025 | All selected publications | 4 | 5 | 5/5 |
| 2026 | All selected publications | 0 | 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 | 5 |
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 | 1 | 29 | 68 | 1/1 | 29.0 | 29 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 4 | 15 | 27 | 4/4 | 3.75 | 3.0 | 100.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
This paper demonstrates the relationship between CAMELS ratios and credit ratings of deposit banks in Turkey. Annual data was used for the period between 2004 and 2014 in this study. Moreover, 20 deposit banks of Turkey were analyzed and 21 different ratios of CAMELS components were used. In addition to that, credit ratings of these banks were provided from Moody’s corporation or annual activity reports of the banks. After that, we created multi nominal logistic regression analysis in order to illustrate the relationship. The major finding in this study is that three components (Asset Quality, Management Quality, and Sensitivity to Market Risk) of CAMELS have effects on credit ratings whereas the ratios related to Capital Adequacy and Earnings are not effective. As a result, it was recommended that Turkish deposit banks should concentrate on the percentage of fixed assets and interest income to have a better rating. Moreover, having high market share with respect to total assets and lower interest expense are also other important points for this purpose. On the other hand, Turkish deposit banks should control the proportion of financial assets and increase the amount of FX liquid assets to prevent credit ratings to decrease. Additionally, market share of banks for loans should not reach at high level for this objective.
In modern age, positive psychological capital is as important as financial capital for organizational development and sustainability. Efficacy, hope, optimism, and resilience are the dimensions of positive psychological capital. Emotional labor is defined by Hochschild as control of self emotions at work by workers who have a high degree of contact with coworkers within the organization or with external clients, so as to create an expression, voice or body gesture which is acceptible to the clients. Emotional labor is analysized under three components: surface acting, deep acting and naturally felt emotions. This study is aimed to investigate the impact of positive psychological capital on emotional labor. So a research is conducted with the aim of exploring the relationship between the sub-dimensions of psychological capital and emotional labour.
In a data set, an outlier refers to a data point that is considerably different from the others. Detecting outliers provides useful application-specific insights and leads to choosing right prediction models. Outlier detection (also known as anomaly detection or novelty detection) has been studied in statistics and machine learning for a long time. It is an essential preprocessing step of data mining process. In this study, outlier detection step in the data mining process is applied for identifying the top 20 outlier firms. Three outlier detection algorithms are utilized using fundamental analysis variables of firms listed in Borsa Istanbul for the 2011-2014 period. The results of each algorithm are presented and compared. Findings show that 15 different firms are identified by three different outlier detection methods. KCHOL and SAHOL have the greatest number of appearances with 12 observations among these firms. By investigating the results, it is concluded that each of three algorithms makes different outlier firm lists due to differences in their approaches for outlier detection.
Innovation is the only way of solution to achieve sustainable growth, social welfare and employment in a country. This study principally focuses on the relationship between growth and innovation in the light of information derived from a general literature review about definition, sources and risks of innovation, and measurement of innovation performance. Then, the contributions of innovative capability on economic growth and employment as well as innovation systems on a country basis have been discussed, and accordingly, actions to be taken, including a shift in paradigm, for a growth-innovation-national innovation system and its sustainability have been addressed. In addition, current innovation performance indicators of Turkey have been discussed in the light of a scope which is outlined in the initial sections of the study, and the change in such performance indicators between 1998 and 2009 has been examined. After analysis of the above mentioned criteria and comparisons against practices in developed countries and communities, suggestions have been made about the activities to be carried out in order to make Turkey’s current innovation system “sustainable”, to support and improve innovation. In the study, a research application has been conducted using the content analysis method on the “President’s Message” letters of 158 state and foundation universities that are located in Turkey and that have a website, and the importance accorded to innovation by the universities has been determined.
This research paper examines the corporate dividend payout behaviors of non-financial firms from Istanbul Stock Exchange (Borsa Istanbul). Survey method is conducted to investigate managerial views on corporate dividend policy. The study investigates whether the evidence in Turkish stock market on dividend policy is similar to the European and the U.S. firms’ results which are reported earlier by other studies, and moreover in what extent Lintner’s (1956) findings on dividends is supported by today’s listed firms in an emerging market. The financial managers from 38 firms out of 216 non-financial companies responded the survey. The results show that there is a significant positive relationship between cash dividends and earnings. Earnings are viewed as the most important factor in dividend decision like in European and the U.S. firms. Sustainable change in earnings, stability and level of future earnings, and the desire to distribute a proportion of earnings to shareholders are the common determinants of dividend policy. The majority of the respondents reports that they target dividends. Dividend yield is the most common measure for dividend targeting. Share repurchases are not viewed as alternative to dividend payouts unlike the U.S. firms. The study finds supporting evidences for bird-in-the-hand and signaling hypotheses, and Lintner’s model.
Innovation is the only way of solution to achieve sustainable growth, social welfare and employment in a country. This study principally focuses on the relationship between growth and innovation in the light of information derived from a general literature review about definition, sources and risks of innovation, and measurement of innovation performance. Then, the contributions of innovative capability on economic growth and employment as well as innovation systems on a country basis have been discussed, and accordingly, actions to be taken, including a shift in paradigm, for a growth-innovation-national innovation system and its sustainability have been addressed. In addition, current innovation performance indicators of Turkey have been discussed in the light of a scope which is outlined in the initial sections of the study, and the change in such performance indicators between 1998 and 2009 has been examined. After analysis of the above mentioned criteria and comparisons against practices in developed countries and communities, suggestions have been made about the activities to be carried out in order to make Turkey’s current innovation system “sustainable”, to support and improve innovation. In the study, a research application has been conducted using the content analysis method on the “President’s Message” letters of 158 state and foundation universities that are located in Turkey and that have a website, and the importance accorded to innovation by the universities has been determined.
This paper demonstrates the relationship between CAMELS ratios and credit ratings of deposit banks in Turkey. Annual data was used for the period between 2004 and 2014 in this study. Moreover, 20 deposit banks of Turkey were analyzed and 21 different ratios of CAMELS components were used. In addition to that, credit ratings of these banks were provided from Moody’s corporation or annual activity reports of the banks. After that, we created multi nominal logistic regression analysis in order to illustrate the relationship. The major finding in this study is that three components (Asset Quality, Management Quality, and Sensitivity to Market Risk) of CAMELS have effects on credit ratings whereas the ratios related to Capital Adequacy and Earnings are not effective. As a result, it was recommended that Turkish deposit banks should concentrate on the percentage of fixed assets and interest income to have a better rating. Moreover, having high market share with respect to total assets and lower interest expense are also other important points for this purpose. On the other hand, Turkish deposit banks should control the proportion of financial assets and increase the amount of FX liquid assets to prevent credit ratings to decrease. Additionally, market share of banks for loans should not reach at high level for this objective.
This research paper examines the corporate dividend payout behaviors of non-financial firms from Istanbul Stock Exchange (Borsa Istanbul). Survey method is conducted to investigate managerial views on corporate dividend policy. The study investigates whether the evidence in Turkish stock market on dividend policy is similar to the European and the U.S. firms’ results which are reported earlier by other studies, and moreover in what extent Lintner’s (1956) findings on dividends is supported by today’s listed firms in an emerging market. The financial managers from 38 firms out of 216 non-financial companies responded the survey. The results show that there is a significant positive relationship between cash dividends and earnings. Earnings are viewed as the most important factor in dividend decision like in European and the U.S. firms. Sustainable change in earnings, stability and level of future earnings, and the desire to distribute a proportion of earnings to shareholders are the common determinants of dividend policy. The majority of the respondents reports that they target dividends. Dividend yield is the most common measure for dividend targeting. Share repurchases are not viewed as alternative to dividend payouts unlike the U.S. firms. The study finds supporting evidences for bird-in-the-hand and signaling hypotheses, and Lintner’s model.
In a data set, an outlier refers to a data point that is considerably different from the others. Detecting outliers provides useful application-specific insights and leads to choosing right prediction models. Outlier detection (also known as anomaly detection or novelty detection) has been studied in statistics and machine learning for a long time. It is an essential preprocessing step of data mining process. In this study, outlier detection step in the data mining process is applied for identifying the top 20 outlier firms. Three outlier detection algorithms are utilized using fundamental analysis variables of firms listed in Borsa Istanbul for the 2011-2014 period. The results of each algorithm are presented and compared. Findings show that 15 different firms are identified by three different outlier detection methods. KCHOL and SAHOL have the greatest number of appearances with 12 observations among these firms. By investigating the results, it is concluded that each of three algorithms makes different outlier firm lists due to differences in their approaches for outlier detection.
In modern age, positive psychological capital is as important as financial capital for organizational development and sustainability. Efficacy, hope, optimism, and resilience are the dimensions of positive psychological capital. Emotional labor is defined by Hochschild as control of self emotions at work by workers who have a high degree of contact with coworkers within the organization or with external clients, so as to create an expression, voice or body gesture which is acceptible to the clients. Emotional labor is analysized under three components: surface acting, deep acting and naturally felt emotions. This study is aimed to investigate the impact of positive psychological capital on emotional labor. So a research is conducted with the aim of exploring the relationship between the sub-dimensions of psychological capital and emotional labour.
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 |