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: 6 / 6 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 00:49 UTC — 21 Oct 2026 00:49 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.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 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 |
|---|---|---|---|---|---|
| 2016 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2017 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2016 | All selected publications | 21 | 2 | 2/2 | 2/2 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 5 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 17 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2016 | All selected publications | 55 | 2 | 2/2 | 2/2 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 6 | 1 | 1/1 | 1/1 |
| 2020 | All selected publications | 38 | 2 | 2/2 | 2/2 |
| 2021 | All selected publications | 1 | 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 6 / 6 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): 2026-10-21T00:49:29.357430+00:00 — 2026-10-21T00:49:36.287065+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 | 1 | 6 | 6/6 |
| 2018 | All selected publications | 7 | 6 | 6/6 |
| 2019 | All selected publications | 4 | 6 | 6/6 |
| 2020 | All selected publications | 11 | 6 | 6/6 |
| 2021 | All selected publications | 12 | 6 | 6/6 |
| 2022 | All selected publications | 17 | 6 | 6/6 |
| 2023 | All selected publications | 20 | 6 | 6/6 |
| 2024 | All selected publications | 12 | 6 | 6/6 |
| 2025 | All selected publications | 11 | 6 | 6/6 |
| 2026 | All selected publications | 5 | 6 | 6/6 |
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 |
|---|---|
| 2016 | 2 |
| 2019 | 1 |
| 2020 | 2 |
| 2021 | 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 Research in Business and Social Science SSBFNET | 6 | 43 | 100 | 6/6 | 7.17 | 2.5 | 50.0 | 6/6 · 100.0% |
* Percentage among publications with a known citation count.
The aim of this research is to understand the factors behind smartphone purchase decisions of consumers. Nowadays companies make use of various strategies in order to attract new customers, retain existing customers and differentiate their products from those of their competitors. Perhaps, the most important and effective strategy to influence consumer behavior in the product selection is emphasizing the “brand name” of the products. Our aim in this paper is to investigate how smartphone brands can influence consumers’ buying decisions. Brand equity is a set of brand assets and liabilities linked to a brand name and symbol, which add to or subtract from the value provided by a product or service. It enhances the customer’s ability to interpret and process information, improves confidence in the purchase decision and affects the quality of the user experience. Using this construct widely discussed in the literature, we use and build our hypothesis based on Aaker model about the brand equity, including perceived quality, brand awareness, brand association and brand loyalty. The study involved a questionnaire administered to 171 smartphone consumers between December 2015 and March 2016. The consumers were chosen by convenience sampling among the students from a prestigious university in the Istanbul district of Turkey. Our findings indicate that a majority of the smartphone buyers’ decisions are mainly influenced by brand loyalty and brand awareness. Perceived quality and brand association do not seem to influence purchase decisions for the sample of this study.
In this study, 396 university students in Turkey are surveyed online regarding their attitudes towards financial issues, their level of financial knowledge, and their financial behavior. The latest version of OECD/INFE Financial Literacy Survey (2018) is used in the study. Using SPSS and LISREL. Factor analysis, Cronbach's Alpha, and Structural Equation Modeling (SEM) are used to analyze the relationship between financial knowledge of the participants with their financial attitude and behavior as well as the mediation effect of financial attitude in this relationship. In line with the common wisdom that the relationship between knowledge and behavior is higher if knowledge is better reflected in the attitude of the individual, the mediation effect of financial attitude strengthens the financial knowledge and financial behavior relationship.
We measure the level of financial literacy in Turkey using the OECD/International Network on Financial Education (INFE) methodology and compare our results with the ones obtained in 14 other countries that has used the same methodology. In our sample, financial knowledge and financial behavior levels are lower than the average of the 14 countries, whereas financial attitude level is around the average. The overall financial literacy score, which is a combination of the three aforementioned aspects, is also lower than the average of the 14 countries. We find that financial behavior is positively related with financial knowledge, female respondents are lagging behind the male respondents in financial literacy, and this lag is bigger than those in the 14 countries. Very young respondents and old respondents are less financially literate, financial literacy score is positively related with income, education, and income stability.
The purpose of this study is to investigate the impact of stock splits on the return, riskiness, and liquidity of stocks. Utilizing a sample of 94 stock splits taken place between 2010 and 2019 at Borsa Istanbul, the study analyzes the daily abnormal returns, change in volatility, and changes in volume around the stock split announcement and execution dates. The results display significant positive abnormal returns around the announcement date but not significant abnormal returns around the execution. The volatility and liquidity of stocks increase significantly around both announcement and execution dates. The findings are in line with the positive signaling, and liquidity hypotheses of stock split and with most of the observations reported in the empirical literature. The new evidence provided points out the lack of semi-strong form of market efficiency at Borsa Istanbul as far as the stock splits are considered.
In this study, 403 participants were asked questions to determine the preventive measures being taken and anxiety levels during COVID-19 Pandemic. Participants were almost equally divided between women (55%) and men (45%). The rate of most worried persons about the pandemic was 62%. The risk of anxiety of women compared to men has been calculated as 2.1 times higher (95% CI 1.20–3.84). The Cramer’s V value of the change in hand-washing habit before and after COVID-19 outbreak is 0.706, indicates the existence of a strong relationship. The data is analysed by using SPSS 24.0. ODDS Ratio values are calculated to determine the impact levels, and Cramer’s V value is calculated to determine the relationship in behavior change in hand-washings habits.
The purpose of this study is to investigate the impact of stock splits on the return, riskiness, and liquidity of stocks. Utilizing a sample of 94 stock splits taken place between 2010 and 2019 at Borsa Istanbul, the study analyzes the daily abnormal returns, change in volatility, and changes in volume around the stock split announcement and execution dates. The results display significant positive abnormal returns around the announcement date but not significant abnormal returns around the execution. The volatility and liquidity of stocks increase significantly around both announcement and execution dates. The findings are in line with the positive signaling, and liquidity hypotheses of stock split and with most of the observations reported in the empirical literature. The new evidence provided points out the lack of semi-strong form of market efficiency at Borsa Istanbul as far as the stock splits are considered.
In this study, 403 participants were asked questions to determine the preventive measures being taken and anxiety levels during COVID-19 Pandemic. Participants were almost equally divided between women (55%) and men (45%). The rate of most worried persons about the pandemic was 62%. The risk of anxiety of women compared to men has been calculated as 2.1 times higher (95% CI 1.20–3.84). The Cramer’s V value of the change in hand-washing habit before and after COVID-19 outbreak is 0.706, indicates the existence of a strong relationship. The data is analysed by using SPSS 24.0. ODDS Ratio values are calculated to determine the impact levels, and Cramer’s V value is calculated to determine the relationship in behavior change in hand-washings habits.
In this study, 396 university students in Turkey are surveyed online regarding their attitudes towards financial issues, their level of financial knowledge, and their financial behavior. The latest version of OECD/INFE Financial Literacy Survey (2018) is used in the study. Using SPSS and LISREL. Factor analysis, Cronbach's Alpha, and Structural Equation Modeling (SEM) are used to analyze the relationship between financial knowledge of the participants with their financial attitude and behavior as well as the mediation effect of financial attitude in this relationship. In line with the common wisdom that the relationship between knowledge and behavior is higher if knowledge is better reflected in the attitude of the individual, the mediation effect of financial attitude strengthens the financial knowledge and financial behavior relationship.
We measure the level of financial literacy in Turkey using the OECD/International Network on Financial Education (INFE) methodology and compare our results with the ones obtained in 14 other countries that has used the same methodology. In our sample, financial knowledge and financial behavior levels are lower than the average of the 14 countries, whereas financial attitude level is around the average. The overall financial literacy score, which is a combination of the three aforementioned aspects, is also lower than the average of the 14 countries. We find that financial behavior is positively related with financial knowledge, female respondents are lagging behind the male respondents in financial literacy, and this lag is bigger than those in the 14 countries. Very young respondents and old respondents are less financially literate, financial literacy score is positively related with income, education, and income stability.
The aim of this research is to understand the factors behind smartphone purchase decisions of consumers. Nowadays companies make use of various strategies in order to attract new customers, retain existing customers and differentiate their products from those of their competitors. Perhaps, the most important and effective strategy to influence consumer behavior in the product selection is emphasizing the “brand name” of the products. Our aim in this paper is to investigate how smartphone brands can influence consumers’ buying decisions. Brand equity is a set of brand assets and liabilities linked to a brand name and symbol, which add to or subtract from the value provided by a product or service. It enhances the customer’s ability to interpret and process information, improves confidence in the purchase decision and affects the quality of the user experience. Using this construct widely discussed in the literature, we use and build our hypothesis based on Aaker model about the brand equity, including perceived quality, brand awareness, brand association and brand loyalty. The study involved a questionnaire administered to 171 smartphone consumers between December 2015 and March 2016. The consumers were chosen by convenience sampling among the students from a prestigious university in the Istanbul district of Turkey. Our findings indicate that a majority of the smartphone buyers’ decisions are mainly influenced by brand loyalty and brand awareness. Perceived quality and brand association do not seem to influence purchase decisions for the sample of this study.
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 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |