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: 21 Oct 2026 07:23 UTC — 22 Oct 2026 17:01 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.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 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 |
|---|---|---|---|---|---|
| 2022 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2022 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 2 | 1 | 1/1 | 1/1 |
| 2025 | All selected publications | 2 | 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 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): 2026-10-21T07:23:00.668672+00:00 — 2026-10-22T17:01:32.655478+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 | 0 | 4 | 4/4 |
| 2020 | All selected publications | 0 | 4 | 4/4 |
| 2021 | All selected publications | 0 | 4 | 4/4 |
| 2022 | All selected publications | 0 | 4 | 4/4 |
| 2023 | All selected publications | 0 | 4 | 4/4 |
| 2024 | All selected publications | 1 | 4 | 4/4 |
| 2025 | All selected publications | 2 | 4 | 4/4 |
| 2026 | All selected publications | 3 | 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 |
|---|---|
| 2022 | 1 |
| 2024 | 1 |
| 2025 | 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 | 4 | 5 | 6 | 4/4 | 1.25 | 1.0 | 100.0 | 4/4 · 100.0% |
* Percentage among publications with a known citation count.
Consumer decisions are influenced by various variables, including compliance with society’s social norms and by involvement by consumers with the issue under consideration. Both variables have influenced consumers’ actions during previous pandemics. Therefore, this study investigated involvement with the Covid-19 pandemic, together with social norm compliance (SNC), their mutual influence, and how demographic characteristics and country of residence influenced these three issues. The methodology involved a quantitative descriptive cross-sectional survey, with a quota sample of 1096 responses, based on age, gender, education, habitation, and income. The research was conducted with populations representing the consumers who patronize major retailers in a developed country (Germany) and a developing one (South Africa). Data was collected via questionnaires e-mailed to commercial consumer panels covering both countries. The findings showed that involvement is influenced by gender, age, education, habitation, and country of residence, but that SNC is not influenced by demographics but does differ according to country. Further findings were that involvement with Covid-19 strongly influences SNC and, similarly, SNC also strongly influences involvement with Covid-19. Furthermore demographics, excluding habitation, also influence these variables. However, the relationship between the involvement and SNC variables does not differ between the two countries. This study has provided a better understanding of consumers’ involvement with Covid-19 and SNC as components of consumer behavior, which is important since, during the Covid-19 pandemic, retailers have been instrumental in implementing health protocols. Therefore, understanding the relationship between involvement with Covid-19 and SNC, and how they are influenced by consumer demographics, is important.
Small to Medium Enterprises (SMEs) are a key part of socio-economic development in South Africa by providing employment, generating incomes, and alleviating poverty. Despite their significance, South African SMEs continue to register high failure rates, low growth rates, and short lifespan, particularly in unstable industries. Existing research has consistently cantered on the determinants of firm performance but has been remiss in considering the combined effect of firm size, financial turnover, and performance on lifespan in SMEs—specifically in diversified industrial settings. Bridging the research gap in extant research, the present research considered the interrelationship between the aforementioned variables in the best-performing and poorest-performing industries in South Africa, Manufacturing and Construction industries. The study used a correlational research design and collected data from 204 SMEs using structured questionnaires to gauge the number of employees, turnover per year, and operation period in years. Pearson correlation analysis established that in the Manufacturing industry, longevity was weakly and significantly interrelated with turnover and size but in the Construction industry was weak or statistically non-significant. Contrastingingly, when both industries were combined together, weak but statistically significant interrelationship was established between longevity and both turnover and size, but a strongly positive interrelationship was established between turnover and size. The results conclude that firm size and financial performance are key drivers of the lifespan of SMEs, especially in more stable industries.
This paper evaluates how the perceptions of consumers from different demographic backgrounds influence their adoption and use of digital personal banking, and suggests marketing activities required to increase digital banking by these different demographic target groups. The method involved an online survey of a sample of 400 respondents with bank accounts in the iLembe district of KwaZulu-Natal, South Africa, focusing on the demographic dimensions of age, gender, education and income. The study found that high digital banking users were older (24+), with higher education and a higher income, while low digital banking users were younger (18-23), with a lower level of education and a lower income. No differences according to gender were found. The convenience of digital banking and a good online banking experience were the factors that most encouraged digital banking use by high users, while perceptions of high cost and having low control over their online banking activities were factors that discouraged low users from more digital banking use. These findings confirmed the previous research about the influence of age and education on digital banking use, but contributed new knowledge about the influence of income, and the lack of influence of gender, on digital banking adoption and use. Comprehensive recommendations for banks, policy makers and other stakeholders are provided.
This study examines the relationship between contextual and personality factors and leadership behavior. Understanding the dynamics of explorative and exploitative leadership behavior is critical in today's organizations. Data from an empirical study of N=139 German leaders from different industries show significant positive correlations between emotional stability, openness to experience and explorative leadership behavior. In addition, perceived environmental uncertainty and autonomy are significant factors that positively influence explorative leadership behavior. These findings offer recommendations for leaders and organizations in turbulent times and highlight the complex interplay of context, personality and leadership behavior.
Small to Medium Enterprises (SMEs) are a key part of socio-economic development in South Africa by providing employment, generating incomes, and alleviating poverty. Despite their significance, South African SMEs continue to register high failure rates, low growth rates, and short lifespan, particularly in unstable industries. Existing research has consistently cantered on the determinants of firm performance but has been remiss in considering the combined effect of firm size, financial turnover, and performance on lifespan in SMEs—specifically in diversified industrial settings. Bridging the research gap in extant research, the present research considered the interrelationship between the aforementioned variables in the best-performing and poorest-performing industries in South Africa, Manufacturing and Construction industries. The study used a correlational research design and collected data from 204 SMEs using structured questionnaires to gauge the number of employees, turnover per year, and operation period in years. Pearson correlation analysis established that in the Manufacturing industry, longevity was weakly and significantly interrelated with turnover and size but in the Construction industry was weak or statistically non-significant. Contrastingingly, when both industries were combined together, weak but statistically significant interrelationship was established between longevity and both turnover and size, but a strongly positive interrelationship was established between turnover and size. The results conclude that firm size and financial performance are key drivers of the lifespan of SMEs, especially in more stable industries.
This paper evaluates how the perceptions of consumers from different demographic backgrounds influence their adoption and use of digital personal banking, and suggests marketing activities required to increase digital banking by these different demographic target groups. The method involved an online survey of a sample of 400 respondents with bank accounts in the iLembe district of KwaZulu-Natal, South Africa, focusing on the demographic dimensions of age, gender, education and income. The study found that high digital banking users were older (24+), with higher education and a higher income, while low digital banking users were younger (18-23), with a lower level of education and a lower income. No differences according to gender were found. The convenience of digital banking and a good online banking experience were the factors that most encouraged digital banking use by high users, while perceptions of high cost and having low control over their online banking activities were factors that discouraged low users from more digital banking use. These findings confirmed the previous research about the influence of age and education on digital banking use, but contributed new knowledge about the influence of income, and the lack of influence of gender, on digital banking adoption and use. Comprehensive recommendations for banks, policy makers and other stakeholders are provided.
This study examines the relationship between contextual and personality factors and leadership behavior. Understanding the dynamics of explorative and exploitative leadership behavior is critical in today's organizations. Data from an empirical study of N=139 German leaders from different industries show significant positive correlations between emotional stability, openness to experience and explorative leadership behavior. In addition, perceived environmental uncertainty and autonomy are significant factors that positively influence explorative leadership behavior. These findings offer recommendations for leaders and organizations in turbulent times and highlight the complex interplay of context, personality and leadership behavior.
Consumer decisions are influenced by various variables, including compliance with society’s social norms and by involvement by consumers with the issue under consideration. Both variables have influenced consumers’ actions during previous pandemics. Therefore, this study investigated involvement with the Covid-19 pandemic, together with social norm compliance (SNC), their mutual influence, and how demographic characteristics and country of residence influenced these three issues. The methodology involved a quantitative descriptive cross-sectional survey, with a quota sample of 1096 responses, based on age, gender, education, habitation, and income. The research was conducted with populations representing the consumers who patronize major retailers in a developed country (Germany) and a developing one (South Africa). Data was collected via questionnaires e-mailed to commercial consumer panels covering both countries. The findings showed that involvement is influenced by gender, age, education, habitation, and country of residence, but that SNC is not influenced by demographics but does differ according to country. Further findings were that involvement with Covid-19 strongly influences SNC and, similarly, SNC also strongly influences involvement with Covid-19. Furthermore demographics, excluding habitation, also influence these variables. However, the relationship between the involvement and SNC variables does not differ between the two countries. This study has provided a better understanding of consumers’ involvement with Covid-19 and SNC as components of consumer behavior, which is important since, during the Covid-19 pandemic, retailers have been instrumental in implementing health protocols. Therefore, understanding the relationship between involvement with Covid-19 and SNC, and how they are influenced by consumer demographics, is important.
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 |