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: 2 / 2 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 07:22 UTC — 21 Oct 2026 07:22 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.
2 / 2 with data · 0 missing or unmatched. Percentages use all 2 selected publications.
2 / 2 with data · 0 missing or unmatched. Percentages use all 2 selected publications.
2 / 2 with data · 0 missing or unmatched. Percentages use all 2 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 |
|---|---|---|---|---|---|
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 3 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | 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 2 / 2 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): 2026-10-21T07:22:47.364998+00:00 — 2026-10-21T07:22:48.095228+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 | 2 | 2/2 |
| 2018 | All selected publications | 0 | 2 | 2/2 |
| 2019 | All selected publications | 0 | 2 | 2/2 |
| 2020 | All selected publications | 0 | 2 | 2/2 |
| 2021 | All selected publications | 0 | 2 | 2/2 |
| 2022 | All selected publications | 0 | 2 | 2/2 |
| 2023 | All selected publications | 0 | 2 | 2/2 |
| 2024 | All selected publications | 2 | 2 | 2/2 |
| 2025 | All selected publications | 2 | 2 | 2/2 |
| 2026 | All selected publications | 0 | 2 | 2/2 |
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 |
|---|---|
| 2023 | 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 |
|---|---|---|---|---|---|---|---|---|
| International Journal of Research in Business and Social Science SSBFNET | 2 | 3 | 4 | 2/2 | 1.5 | 1.5 | 100.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
Digital transformation destination is much easier when a clear vision is communicated up and down the organization. This study seeks to explore the effect of visioning on digital transformation in the insurance industry. The study used a positivist research philosophy and a quantitative research approach. The research used primary data, which was collected using a questionnaire. Data analysis was done using regression analysis, descriptive statistics and paired sample t-tests. Normality and reliability were tested using the Shapiro-Wilk test and Cronbach’s alpha, respectively. The study findings revealed that visioning significantly influences digital transformation (t=1.129, p=0.000<0.05). Visioning is the art of modeling an organization's culture and is the critical variable towards digital transformation. The study recommends the regulator, the Insurance and Pension Commission, might need to enforce digital transformation within the insurance space. Visioning is critical in the insurance sector’s digital transformation process.
The digital transformation in business schools during the COVID-19 pandemic is unique since external factors, not internal initiatives, drive it. This event is called 'forced digital transformation.' It raises new challenges for business schools to ensure that the transformation continues in the future since the post-pandemic situation has encouraged social and economic activities to return offline. As the situation begins normal, less external pressure can result in declining creative initiatives from business schools to explore more opportunities from digital technologies. Consequently, the digital transformation process that started during the pandemic could stagnate. One of the essential factors that play a role in encouraging continuous digital transformation is leadership. Leadership is believed to be the core of every digital innovation process. However, research investigating the role of leadership in business schools' digital transformation during the COVID-19 pandemic is still limited. Therefore, this study aims to describe leadership's role in structural and behavioral changes during forced digital transformation in business schools by applying a systematic literature review.
The digital transformation in business schools during the COVID-19 pandemic is unique since external factors, not internal initiatives, drive it. This event is called 'forced digital transformation.' It raises new challenges for business schools to ensure that the transformation continues in the future since the post-pandemic situation has encouraged social and economic activities to return offline. As the situation begins normal, less external pressure can result in declining creative initiatives from business schools to explore more opportunities from digital technologies. Consequently, the digital transformation process that started during the pandemic could stagnate. One of the essential factors that play a role in encouraging continuous digital transformation is leadership. Leadership is believed to be the core of every digital innovation process. However, research investigating the role of leadership in business schools' digital transformation during the COVID-19 pandemic is still limited. Therefore, this study aims to describe leadership's role in structural and behavioral changes during forced digital transformation in business schools by applying a systematic literature review.
Digital transformation destination is much easier when a clear vision is communicated up and down the organization. This study seeks to explore the effect of visioning on digital transformation in the insurance industry. The study used a positivist research philosophy and a quantitative research approach. The research used primary data, which was collected using a questionnaire. Data analysis was done using regression analysis, descriptive statistics and paired sample t-tests. Normality and reliability were tested using the Shapiro-Wilk test and Cronbach’s alpha, respectively. The study findings revealed that visioning significantly influences digital transformation (t=1.129, p=0.000<0.05). Visioning is the art of modeling an organization's culture and is the critical variable towards digital transformation. The study recommends the regulator, the Insurance and Pension Commission, might need to enforce digital transformation within the insurance space. Visioning is critical in the insurance sector’s digital transformation process.
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 |