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: 3 / 3 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 00:01 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.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 selected publications.
3 / 3 with data · 0 missing or unmatched. Percentages use all 3 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 | 1 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2016 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 3 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2016 | All selected publications | 4 | 1 | 1/1 | 1/1 |
| 2017 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2018 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2019 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2020 | All selected publications | 4 | 2 | 2/2 | 2/2 |
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 3 / 3 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): 2026-10-21T00:01:59.931339+00:00 — 2026-10-21T00:49:33.583216+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 | 3 | 3/3 |
| 2018 | All selected publications | 1 | 3 | 3/3 |
| 2019 | All selected publications | 1 | 3 | 3/3 |
| 2020 | All selected publications | 2 | 3 | 3/3 |
| 2021 | All selected publications | 0 | 3 | 3/3 |
| 2022 | All selected publications | 0 | 3 | 3/3 |
| 2023 | All selected publications | 0 | 3 | 3/3 |
| 2024 | All selected publications | 4 | 3 | 3/3 |
| 2025 | All selected publications | 0 | 3 | 3/3 |
| 2026 | All selected publications | 0 | 3 | 3/3 |
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 | 1 |
| 2020 | 2 |
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 |
|---|---|---|---|---|---|---|---|---|
| Bussecon Review of Social Sciences Bussecon International Academy | 1 | 3 | 4 | 1/1 | 3.0 | 3 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 0 | 4 | 2/2 | 0.0 | 0.0 | 0.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
This article seeks to explore the conflict between Samsung and Apple. The conflict has been one of the most outstanding patent wars in the history of the smartphone industry. Apple and Samsung are among the most popular manufacturers of commonly used smartphones and tablets. The conflict began when Apple decided to file a federal lawsuit in the US district court, accusing Samsung of copying some of its iPhone features in the Samsung Galaxy S II smartphone. The court ascertained that the gadget had similar characteristics to Apple, thus ordering Samsung to pay Apple for the damages. In response, Samsung reacted by filing countersuits. The two firms, almost fifty cases in different nations and regions. The issues lasted for seven years, starting from 2011 and ending in 2016, in which both companies benefited and lost at the same time. The conflict emanated because of each firm pursuing its competitive advantage in the market. Apart from following market shares, third parties, like consumers, instigated the conflict, with international politics and the media playing a role.
The research and development (R&D) process is critical to a firm’s competitive advantage and often requires external funding. Yet, we know little about how different types of investors respond to the cash needs of established R&D intensive firms nor about how external financial analysts influence those decisions. We address these gaps by examining how a firm’s patenting activity affects its ability to raise cash. We distinguish the motivations of two investor groups: open-market and alliance partners. We focus on how patents based on emergent technologies impact two types of investors and their willingness to fund the R&D process. We develop theory and test our hypotheses using data from publicly traded biopharmaceutical firms by drawing upon knowledge-based view, alliance, and investment theories. We find evidence that patents built upon emergent technologies are viewed differently by the two types of investors. We find open market investors were less likely to invest in emergent technologies and invested less when they did. Conversely, alliance partner investors would be more appreciative of the opportunities new technology inputs present, thus, more likely to invest in firms using emergent technologies and invest more.
The importance given by the governments to building a sound intellectual property infrastructure is increasing in developing countries and especially in Central Asian countries. This infrastructure is continuously improved to live up to a common standard in collaboration with government agencies, educational institutions and international agencies. In this paper, the infrastructure developments that took place in the Central Asian countries is going to be elaborated and furthermore some statistical analyses will be used in order to compare the differences and similarities between the Central Asian republics within themselves and the rest of the world. Patent based statistical data reveal a broad range of information concerning the innovative capability of countries, regions and firms. The number of patents that a country obtains in different technological fields and the change in this number over the years may provide useful information regarding the growth potential of the country and the ability to follow technological advances. For this purpose, patent statistics collected by institutions like World Intellectual Property Organization (WIPO) have been analyzed using statistical techniques. In addition to basic statistics, multidimensional scaling analysis (MDS) has been applied to the data sets.
This article seeks to explore the conflict between Samsung and Apple. The conflict has been one of the most outstanding patent wars in the history of the smartphone industry. Apple and Samsung are among the most popular manufacturers of commonly used smartphones and tablets. The conflict began when Apple decided to file a federal lawsuit in the US district court, accusing Samsung of copying some of its iPhone features in the Samsung Galaxy S II smartphone. The court ascertained that the gadget had similar characteristics to Apple, thus ordering Samsung to pay Apple for the damages. In response, Samsung reacted by filing countersuits. The two firms, almost fifty cases in different nations and regions. The issues lasted for seven years, starting from 2011 and ending in 2016, in which both companies benefited and lost at the same time. The conflict emanated because of each firm pursuing its competitive advantage in the market. Apart from following market shares, third parties, like consumers, instigated the conflict, with international politics and the media playing a role.
The research and development (R&D) process is critical to a firm’s competitive advantage and often requires external funding. Yet, we know little about how different types of investors respond to the cash needs of established R&D intensive firms nor about how external financial analysts influence those decisions. We address these gaps by examining how a firm’s patenting activity affects its ability to raise cash. We distinguish the motivations of two investor groups: open-market and alliance partners. We focus on how patents based on emergent technologies impact two types of investors and their willingness to fund the R&D process. We develop theory and test our hypotheses using data from publicly traded biopharmaceutical firms by drawing upon knowledge-based view, alliance, and investment theories. We find evidence that patents built upon emergent technologies are viewed differently by the two types of investors. We find open market investors were less likely to invest in emergent technologies and invested less when they did. Conversely, alliance partner investors would be more appreciative of the opportunities new technology inputs present, thus, more likely to invest in firms using emergent technologies and invest more.
The importance given by the governments to building a sound intellectual property infrastructure is increasing in developing countries and especially in Central Asian countries. This infrastructure is continuously improved to live up to a common standard in collaboration with government agencies, educational institutions and international agencies. In this paper, the infrastructure developments that took place in the Central Asian countries is going to be elaborated and furthermore some statistical analyses will be used in order to compare the differences and similarities between the Central Asian republics within themselves and the rest of the world. Patent based statistical data reveal a broad range of information concerning the innovative capability of countries, regions and firms. The number of patents that a country obtains in different technological fields and the change in this number over the years may provide useful information regarding the growth potential of the country and the ability to follow technological advances. For this purpose, patent statistics collected by institutions like World Intellectual Property Organization (WIPO) have been analyzed using statistical techniques. In addition to basic statistics, multidimensional scaling analysis (MDS) has been applied to the data sets.
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 |