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 07:23 UTC — 22 Oct 2026 01:46 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 |
|---|---|---|---|---|---|
| 2025 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 2 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2025 | All selected publications | 2 | 3 | 3/3 | 3/3 |
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): 2026-10-21T07:23:01.997992+00:00 — 2026-10-22T01:46:13.002461+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 | 0 | 3 | 3/3 |
| 2019 | All selected publications | 0 | 3 | 3/3 |
| 2020 | All selected publications | 0 | 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 | 0 | 3 | 3/3 |
| 2025 | All selected publications | 0 | 3 | 3/3 |
| 2026 | All selected publications | 2 | 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 |
|---|---|
| 2025 | 3 |
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 | 2 | 1 | 1 | 2/2 | 0.5 | 0.5 | 50.0 | 2/2 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 1 | 1 | 1 | 1/1 | 1.0 | 1 | 100.0 | 1/1 · 100.0% |
* Percentage among publications with a known citation count.
There are growing concerns about ongoing digital innovation in the private sector, which poses the possibility of central banks losing their autonomy and even being backward in payment efficiency. Hence, CBDC has become the reality of central banks with several economies' ongoing digitalization and adaptation. This review explores the growing literature on CBDC design, its emergence, variations, potentials, and challenges for smooth future applications. It addressed research articles and gray literature to accumulate the current implementation concerns. Findings show that CBDC poses prospects for exploiting emerging technology, efficient payment systems, tax collections, and tracking illegal financial activities. However, there were mixed expectations regarding financial inclusion, financial stability, bank runs, disintermediation, monetary policy, privacy, security, technology, sustainability, and regulatory framework. Finally, as CBDCs will reduce the influence of private money creation and digital alternatives, they ensure that the central bank remains at the center of the financial system in the future.
The banking industry in Kenya must adopt digital transformation to sustain competitiveness and improve customer experience in the context of rapidly evolving digital technologies. Despite the increasing focus on digitisation in the sector, the particular initiatives undertaken by commercial banks and their resulting impact on competitive advantage are not sufficiently comprehended. This study analysed the impact of digital transformation strategies on competitive advantage within commercial banks in Kenya. The primary aim was to evaluate the impact of service automation, data analytics, mobile banking applications, employee upskilling, and digital payment solutions on the competitiveness of banks. The study employed a descriptive design, focussing on 39 commercial banks categorised by tiers, which included 412 functional heads. A multi-stage sampling method integrating proportionate stratified and simple random sampling techniques was utilised to guarantee equitable representation. Employing Yamane’s formula, a sample of 203 respondents was determined. Primary data were collected using structured questionnaires that were pretested with 15 participants and validated by subject experts to ensure content relevance and clarity. Reliability testing employing Cronbach’s Alpha produced satisfactory results (? ? 0.7), signifying robust internal consistency. The analysis of data encompassed both descriptive and inferential statistics. The results were presented visually through charts, graphs, and tables to facilitate interpretation. The findings indicated that all five digital transformation strategies impacted competitive advantage, although their contributions differed in magnitude. The findings indicate that commercial banks must move beyond the simple implementation of digital technologies and prioritise strategic integration to improve customer experience and value creation. Banks ought to implement targeted automation that preserves human engagement for intricate services while improving feedback systems. Banks must enhance data governance and invest in sophisticated, customer-centric analytical tools. Ongoing innovation in mobile banking is advisable, encompassing feature enhancements and improved interoperability, underpinned by robust cybersecurity standards. Prioritising employee upskilling is essential through structured training, digital leadership development, and industry-wide certification. Finally, banks must reassess their digital payment strategies to prioritise user experience, fraud prevention, and differentiated services, while regulators encourage secure and innovation-friendly environments.
There is a limited understanding of the emerging technologies, such as blockchain, artificial intelligence (AI), Internet of Things (IoT), and machine learning (ML) and their effect on the insurance sector in the Saudi Arabian market. A structural equational modelling was implemented to investigate the impact of emerging technology on customer experience, business productivity, risk management, and financial performance in Saudi insurance companies. Online surveys were directed to the insurance sector to explore their perceptions of the use of technology and its effect in 2024. The sample includes 102 valid responses in the data analysis. The findings show that the development and integration of technology in the Saudi Arabian insurance sector significantly improve customer experience, business productivity, risk management, and financial performance, which aligns with accelerated transformation in the market to achieve the main goals of the Saudi Vision 2030.
The banking industry in Kenya must adopt digital transformation to sustain competitiveness and improve customer experience in the context of rapidly evolving digital technologies. Despite the increasing focus on digitisation in the sector, the particular initiatives undertaken by commercial banks and their resulting impact on competitive advantage are not sufficiently comprehended. This study analysed the impact of digital transformation strategies on competitive advantage within commercial banks in Kenya. The primary aim was to evaluate the impact of service automation, data analytics, mobile banking applications, employee upskilling, and digital payment solutions on the competitiveness of banks. The study employed a descriptive design, focussing on 39 commercial banks categorised by tiers, which included 412 functional heads. A multi-stage sampling method integrating proportionate stratified and simple random sampling techniques was utilised to guarantee equitable representation. Employing Yamane’s formula, a sample of 203 respondents was determined. Primary data were collected using structured questionnaires that were pretested with 15 participants and validated by subject experts to ensure content relevance and clarity. Reliability testing employing Cronbach’s Alpha produced satisfactory results (? ? 0.7), signifying robust internal consistency. The analysis of data encompassed both descriptive and inferential statistics. The results were presented visually through charts, graphs, and tables to facilitate interpretation. The findings indicated that all five digital transformation strategies impacted competitive advantage, although their contributions differed in magnitude. The findings indicate that commercial banks must move beyond the simple implementation of digital technologies and prioritise strategic integration to improve customer experience and value creation. Banks ought to implement targeted automation that preserves human engagement for intricate services while improving feedback systems. Banks must enhance data governance and invest in sophisticated, customer-centric analytical tools. Ongoing innovation in mobile banking is advisable, encompassing feature enhancements and improved interoperability, underpinned by robust cybersecurity standards. Prioritising employee upskilling is essential through structured training, digital leadership development, and industry-wide certification. Finally, banks must reassess their digital payment strategies to prioritise user experience, fraud prevention, and differentiated services, while regulators encourage secure and innovation-friendly environments.
There is a limited understanding of the emerging technologies, such as blockchain, artificial intelligence (AI), Internet of Things (IoT), and machine learning (ML) and their effect on the insurance sector in the Saudi Arabian market. A structural equational modelling was implemented to investigate the impact of emerging technology on customer experience, business productivity, risk management, and financial performance in Saudi insurance companies. Online surveys were directed to the insurance sector to explore their perceptions of the use of technology and its effect in 2024. The sample includes 102 valid responses in the data analysis. The findings show that the development and integration of technology in the Saudi Arabian insurance sector significantly improve customer experience, business productivity, risk management, and financial performance, which aligns with accelerated transformation in the market to achieve the main goals of the Saudi Vision 2030.
There are growing concerns about ongoing digital innovation in the private sector, which poses the possibility of central banks losing their autonomy and even being backward in payment efficiency. Hence, CBDC has become the reality of central banks with several economies' ongoing digitalization and adaptation. This review explores the growing literature on CBDC design, its emergence, variations, potentials, and challenges for smooth future applications. It addressed research articles and gray literature to accumulate the current implementation concerns. Findings show that CBDC poses prospects for exploiting emerging technology, efficient payment systems, tax collections, and tracking illegal financial activities. However, there were mixed expectations regarding financial inclusion, financial stability, bank runs, disintermediation, monetary policy, privacy, security, technology, sustainability, and regulatory framework. Finally, as CBDCs will reduce the influence of private money creation and digital alternatives, they ensure that the central bank remains at the center of the financial system in the future.
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 |