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: 4 / 4 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 01:10 UTC — 22 Oct 2026 02:54 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.
3 / 4 with data · 1 missing or unmatched. Percentages use all 4 selected publications.
3 / 4 with data · 1 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 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 |
|---|---|---|---|---|---|
| 2017 | All selected publications | 4 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2017 | All selected publications | 9 | 4 | 4/4 | 4/4 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2017 | All selected publications | 15 | 4 | 4/4 | 4/4 |
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 4 / 4 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): 2026-10-22T01:10:47.272045+00:00 — 2026-10-22T02:54:13.622383+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 | 4 | 4/4 |
| 2018 | All selected publications | 0 | 4 | 4/4 |
| 2019 | All selected publications | 2 | 4 | 4/4 |
| 2020 | All selected publications | 0 | 4 | 4/4 |
| 2021 | All selected publications | 3 | 4 | 4/4 |
| 2022 | All selected publications | 4 | 4 | 4/4 |
| 2023 | All selected publications | 0 | 4 | 4/4 |
| 2024 | All selected publications | 3 | 4 | 4/4 |
| 2025 | All selected publications | 3 | 4 | 4/4 |
| 2026 | All selected publications | 0 | 4 | 4/4 |
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 |
|---|---|
| 2017 | 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 Research in Business and Social Science SSBFNET | 4 | 9 | 15 | 4/4 | 2.25 | 2.0 | 50.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
The online retail business has grown substantially. Given distinctive product categories (e.g. search or experience goods), owners must put an effort in the design of websites so every visit may end with a purchase. Clickstream panel data allowing examination into website visiting behavior (i.e. the number of pages viewed (or pageview) or the visit duration) are increasingly accessible. However, it is unclear whether the differences of the two visiting behavior between purchase outcome or product categories are significant. The present study hopes to fill the void. An analysis of 27,528 visit sessions extracted from ComScore verifies that (1) the difference of page views between purchase outcomes and that between product categories were significant and (2) only the difference of visit duration between the product categories was significant but that between purchase outcomes was insignificant. In addition to theoretical insight into online behavior across purchasing horizons and product categories using clickstream data, online retail practitioners could apply the findings to enhance the possibility of the purchases at their online stores.
In today’s business world, social media tools (i.e. facebook, twitter, Linkedin, etc.) begin to play an important role in reaching and communicating with customers for businesses. However, the importance of using social media can’t be still understood by SMEs so far. Businesses use different social media tools in various purposes in their life. In this research we aim to investigate the ideas of SMEs about social media and their aims of using social media tools. Data were collected from SMEs operating in Burdur by simple random sampling. The data obtained from the 84 questionnaires was entered to computer and statistical analysis was carried out by using SPSS 20 statistical program. In this study, reliability analysis was used firstly. Then, some descriptive analyses were carried out about using social media for SMEs. Finally, a frequency table regarding the social media usage in SMEs was given. As a result, it was seen that 82.1% of SMEs participating in this study have a social network page. Secondly, SMEs are using facebook social media network mostly. In addition, SMEs have expressed that they attend all statements involved in the use of social media scale.
Social media sites are becoming more popular throughout the world. These sites are adopting advertisement supported business models to generate revenues and become profitable. Advertisement supported models are the preferred choice for these site with regards to the belief that users are not willing to pay money to use these ever free sites. In this study this belief was questioned and Facebook, the most popular of social media sites was chosen as the setting of the study. The attitudes towards social media advertisements and their antecedents were measured and their potential effects on users’ willingness to pay for not seeing ads were tested. A questionnaire was developed using well-cited and tested scales from the relevant literature and it was implemented over Internet to Facebook users. 281 out of 327 collected questionnaires were used in the analysis following a screening process. The analysis was carried out using structural equation modelling. The findings indicate that attitudes and its antecedents affect th intentions to pay for not seeing ads negatively.
Kullanımları dünya genelinde yaygınlaşan sosyal medya siteleri ciro yaratarak karlı birer işletme haline gelebilmek için günümüzde reklam destekli iş modelleri kullanmaktadır. Kullanıcıların ücretsiz olarak kullanmaya alıştığı bu platformlara erişim için ücret ödemek istemeyecekleri varsayımıyla reklam destekli modeller tercih edilmektedir. Bu çalışma içerisinde sosyal medya sitelerinin en yaygın kullanılanı olan Facebook üzerinde gösterilen reklamlara kullanıcıların tutumları ölçümlenmiş ve bu tutum ve tutumu oluşturan faktörlerin Facebook reklamlarını görmemek için para ödemeye etkisi test edilmiştir. Ödeme eğiliminde olan ve olmayan kullanıcılar arasında farklılar irdelenmiştir. Literatürde kabul görmüş ölçekler yardımıyla hazırlanan anket formu İnternet üzerinden Facebook kullanıcılarına dağıtılmış, elde edilen 327 soru formu bir ön-analiz sürecinden geçirilerek düşük kaliteli ve tam doldurulmamış anketler ayıklanarak 281 kullanılabilir soru formuna ulaşılmıştır. Verilerin analizinde yapısal eşitlik modellemesi kullanılmıştır. Gerçekleştirilen analiz sonuçlarına göre Facebook reklamlarına olan tutum ve tutumun öncülleri reklamları görmemek için ödeme niyetine olumsuz yönde etki etmektedir.
The online retail business has grown substantially. Given distinctive product categories (e.g. search or experience goods), owners must put an effort in the design of websites so every visit may end with a purchase. Clickstream panel data allowing examination into website visiting behavior (i.e. the number of pages viewed (or pageview) or the visit duration) are increasingly accessible. However, it is unclear whether the differences of the two visiting behavior between purchase outcome or product categories are significant. The present study hopes to fill the void. An analysis of 27,528 visit sessions extracted from ComScore verifies that (1) the difference of page views between purchase outcomes and that between product categories were significant and (2) only the difference of visit duration between the product categories was significant but that between purchase outcomes was insignificant. In addition to theoretical insight into online behavior across purchasing horizons and product categories using clickstream data, online retail practitioners could apply the findings to enhance the possibility of the purchases at their online stores.
Kullanımları dünya genelinde yaygınlaşan sosyal medya siteleri ciro yaratarak karlı birer işletme haline gelebilmek için günümüzde reklam destekli iş modelleri kullanmaktadır. Kullanıcıların ücretsiz olarak kullanmaya alıştığı bu platformlara erişim için ücret ödemek istemeyecekleri varsayımıyla reklam destekli modeller tercih edilmektedir. Bu çalışma içerisinde sosyal medya sitelerinin en yaygın kullanılanı olan Facebook üzerinde gösterilen reklamlara kullanıcıların tutumları ölçümlenmiş ve bu tutum ve tutumu oluşturan faktörlerin Facebook reklamlarını görmemek için para ödemeye etkisi test edilmiştir. Ödeme eğiliminde olan ve olmayan kullanıcılar arasında farklılar irdelenmiştir. Literatürde kabul görmüş ölçekler yardımıyla hazırlanan anket formu İnternet üzerinden Facebook kullanıcılarına dağıtılmış, elde edilen 327 soru formu bir ön-analiz sürecinden geçirilerek düşük kaliteli ve tam doldurulmamış anketler ayıklanarak 281 kullanılabilir soru formuna ulaşılmıştır. Verilerin analizinde yapısal eşitlik modellemesi kullanılmıştır. Gerçekleştirilen analiz sonuçlarına göre Facebook reklamlarına olan tutum ve tutumun öncülleri reklamları görmemek için ödeme niyetine olumsuz yönde etki etmektedir.
In today’s business world, social media tools (i.e. facebook, twitter, Linkedin, etc.) begin to play an important role in reaching and communicating with customers for businesses. However, the importance of using social media can’t be still understood by SMEs so far. Businesses use different social media tools in various purposes in their life. In this research we aim to investigate the ideas of SMEs about social media and their aims of using social media tools. Data were collected from SMEs operating in Burdur by simple random sampling. The data obtained from the 84 questionnaires was entered to computer and statistical analysis was carried out by using SPSS 20 statistical program. In this study, reliability analysis was used firstly. Then, some descriptive analyses were carried out about using social media for SMEs. Finally, a frequency table regarding the social media usage in SMEs was given. As a result, it was seen that 82.1% of SMEs participating in this study have a social network page. Secondly, SMEs are using facebook social media network mostly. In addition, SMEs have expressed that they attend all statements involved in the use of social media scale.
Social media sites are becoming more popular throughout the world. These sites are adopting advertisement supported business models to generate revenues and become profitable. Advertisement supported models are the preferred choice for these site with regards to the belief that users are not willing to pay money to use these ever free sites. In this study this belief was questioned and Facebook, the most popular of social media sites was chosen as the setting of the study. The attitudes towards social media advertisements and their antecedents were measured and their potential effects on users’ willingness to pay for not seeing ads were tested. A questionnaire was developed using well-cited and tested scales from the relevant literature and it was implemented over Internet to Facebook users. 281 out of 327 collected questionnaires were used in the analysis following a screening process. The analysis was carried out using structural equation modelling. The findings indicate that attitudes and its antecedents affect th intentions to pay for not seeing ads negatively.
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 |