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: 13 / 13 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 04:47 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.
13 / 13 with data · 0 missing or unmatched. Percentages use all 13 selected publications.
13 / 13 with data · 0 missing or unmatched. Percentages use all 13 selected publications.
13 / 13 with data · 0 missing or unmatched. Percentages use all 13 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 | 13 | 13 | 13/13 | 13/13 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2015 | All selected publications | 55 | 13 | 13/13 | 13/13 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2015 | All selected publications | 125 | 13 | 13/13 | 13/13 |
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 13 / 13 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 — 2026-10-29T04:47:35.933471+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 | 12 | 13 | 13/13 |
| 2018 | All selected publications | 15 | 13 | 13/13 |
| 2019 | All selected publications | 25 | 13 | 13/13 |
| 2020 | All selected publications | 14 | 13 | 13/13 |
| 2021 | All selected publications | 15 | 13 | 13/13 |
| 2022 | All selected publications | 15 | 13 | 13/13 |
| 2023 | All selected publications | 11 | 13 | 13/13 |
| 2024 | All selected publications | 4 | 13 | 13/13 |
| 2025 | All selected publications | 6 | 13 | 13/13 |
| 2026 | All selected publications | 0 | 13 | 13/13 |
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 |
|---|---|
| 2015-01 | 6 |
| 2015-04 | 1 |
| 2015-05 | 1 |
| 2015-07 | 1 |
| 2015-10 | 4 |
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 | 3 | 30 | 74 | 3/3 | 10.0 | 1 | 66.7 | 3/3 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 10 | 25 | 51 | 10/10 | 2.5 | 1.0 | 70.0 | 10/10 · 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.
The aim of this study is to investigate the relationship between teamwork and organizational trust. In the implementation section the data from the survey of 250 workers is employed in call centers in Erzurum by using relevant statistical methods. Consequently, it is found that there is a positive and significant relationship between teamwork and organizational trust. Thus, the hypothesis of the study is supported as it was expected. Besides, it is found that there are positive and significant relationships between communication, openness to innovation, participation-trust in teamwork and organizational trust, trust in management, trust in co-workers, and trust in workplace.
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.
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.
The employment policy is one of the most disputable areas between Turkey and the EU. The EU declared two opening conditions, one about union rights and the other one about preparing an action plan displaying step by step the transposing of EU laws. Although Turkey claims that she met those criteria, the EU insists on keeping the accession negotiations in this area closed. However, there is serious gap between Turkish and European employment policies and in order to comply with the EU’s, there is a strong need of enthusiasm in Turkey for proper implementation of changes made in legal and institutional structures. Simultaneously, the EU has to offer a considerable incentive, e.g. membership, for Turkey to encourage her to adapt EU rules in employment policy. Unfortunately, it is argued in this paper that the current situation is the opposite, i.e. there is no substantial incentive from the EU to encourage Turkey and thus, no enthusiasm from Turkey to comply with the EU policy. In order to analyze the impact of the EU on Turkey’s employment policy the main question designed in this paper is: ‘To what extent does the EU have influence on policy convergence in a candidate country that does not have a clear membership perspective? ‘. It is argued in this study that “without a concrete incentive, European Union’s impact on a candidate country would be limited”. Thus, the patterns of policy change at the national level are the dependent variable to be observed. The European Union’s conditionality is the independent variable that is expected to alter the national patterns.
Conditionality is mostly defined as the EU policy engendered for candidate countries. However, the mere use of conditionality by the EU does not essentially explain transferring of policies and EU rules towards the candidate countries. EU conditionality may be considered as a comprising approach but in certain policy areas or countries it might not be as successful as it was on other ones. The EU conditionality basically defined as a bargaining policy of affecting through reward, under which the EU provides inducements to candidate or neighbor countries to aligning with the conditions of the EU. In this study the explanatory power of conditionality would be questioned; so the main question will be “to what extent does the EU have influence on policy convergence in a candidate country that does not have a clear membership perspective? Taxation chapter in accession negotiations between Turkey and the EU has been chosen as the case of this research as providing to have an answer on this question. The main objective of this paper is ‘analyzing the extent of EU conditionality on Turkish taxation policy.’ Furthermore, it is argued in this study that “without a concrete incentive, European Union’s impact on a candidate country would be limited.”
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 paper examines the relationship between the lobbying power of different interest groups and public education spending in a panel data estimation during the period 1996-2009 for 132 countries. The resource rents, manufacture exports, and agriculture value added are used as proxy variables for the lobbying power of the natural resource owners, manufacturers, and landowners, respectively, in order to substantiate the definition of the lobbying power of the interest groups more with economic fundamentals. As lobbying power is mediated through political institutions, different governance indicators are used individually and in interaction terms with the proxy variables in the estimations. It is found that when the country is more politically stable and the more the rule of law applies, the negative (positive) effect of the lobbying power of natural resource owners (manufacturers) on public education spending intensifies. The negative effect of landowners’ lobbying power diminishes as institutional quality as measured by governance indicators improves.
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 |