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, 00:14 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 02:41 UTC — 02 Nov 2026 13:06 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 |
|---|---|---|---|---|---|
| 2024 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 2 | 3 | 3/3 | 3/3 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 3 | 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): 2026-10-22T02:41:18.898659+00:00 — 2026-11-02T13:06:08.130704+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 | 1 | 3 | 3/3 |
| 2025 | All selected publications | 2 | 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 |
|---|---|
| 2024 | 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 Business Ecosystem & Strategy Bussecon International Academy | 3 | 2 | 3 | 3/3 | 0.67 | 1 | 66.7 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
Motivation is a critical factor that impacts the performance of both employees and organisations. Consequently, it is imperative that supervisors and management ascertain the motivating factors that significantly influence employee performance. The motivation levels of administrative employees were assessed in this study to determine the factors that influence them. The current study is focused on evaluating the motivational level of administrative employees and determining the sequence in which these motivational factors are ranked by administrative employees in the same department. A quantitative research methodology was implemented. An adapted questionnaire was implemented to implement a survey research design. The sample was comprised of 150 administrative employees from a total of 463 employees. The non-probability convenience sampling method was employed to select the respondents for this study. The motivational level of administrative personnel was analysed using descriptive statistics. The study's primary findings indicated that employees were most motivated by job security, job responsibility, goal setting, working conditions, leadership, feedback, salary, and job characteristics. The following was also determined: the most significant motivational factors for employees were ranked in the following order: leadership (1), salary (2), training and development (3), job security (4), feedback (5), rewards (6), working conditions (7), the opportunity for advancement (8), recognition and appreciation (9), job characteristics (10), job responsibility (11), performance appraisal (12), and goal setting 13.
MSMEs are widely regarded as important building blocks for economic prosperity and broader social well-being for both developed and developing nations. However, MSMEs face several challenges that impede their ability to fully provide the much-needed boost to the socio-economic development of countries. Tourism MSMEs are often significantly impacted by crises that include economic downturns, natural disasters, and public health emergencies that destroy infrastructure and affect human movement, notably the outbreak of pandemics and epidemics. The Covid-19 pandemic altered every business operation across the globe. This was mainly because the pandemic was new and no reference case for the Covid-19 crisis existed in living memory. As such the survival of all businesses was at high risk, particularly, the tourism MSMEs in South Africa. The industry’s operations were severely affected by the restrictions imposed by the government of South Africa especially in the year 2020 and 2021. Despite operating their businesses in a crisis, the tourism MSMEs entrepreneurs exhibited resilience as they navigated the pandemic, through being agile, adaptive, and exploring new opportunities of operating and utilising government support. It is in this regard that gaining a deeper understanding of the resilience strategies that were employed by the tourism MSMEs during and strategies being employed during post Covid-19 pandemic crisis is of paramount significance. The study adopted qualitative interpretivist approach through document analysis. Collected data was analysed using the ATLAS.ti.software. The study concludes that even though the Covid-19 had some devastating effects on the MSMEs tourism entrepreneurs, that are still being felt now, it forced the entrepreneurs to adapt and be innovative. It is in this regard that the study concludes that the identified strategies are very vital for the survival of the effects of the Covid-19 pandemic. The study also concludes that the tourism MSMEs entrepreneurs became more resilient to the pandemic as it progressed hence, they implemented the identified strategies revealed by the study findings.
Intra-SADC trade has not met the target that was set by the African Continental Trade Agreement (AfCFTA) of achieving 22% by the year 2022 due to a myriad of various trade-related challenges. This present study aims to compare the results of using a Poisson Maximum Likelihood Estimator (PPML) with Random Effects (RE), Fixed Effects (FE), and an Ordinary Least Squares (POLS) model on a balanced panel of select eight Southern African Development Community (SADC) members that trade with South Africa over the period 2010-2022. The paper empirically examines how South Africa’s overlapping Regional Economic Community (REC) membership affects bilateral trade. Also, the examination of how the impact of distance between South Africa and its trading partners impacts bilateral trade. The study findings are that PPML provides more robust results than other estimation techniques in estimating the gravity model for a balanced micro panel. From the PPML results, distance has a significant negative impact at a 5% level on bilateral exports from South Africa which implies that SADC countries that are relatively far in terms of distance from South Africa and landlocked tend to experience a relative fall in exports from South Africa. However, multiple REC membership has a positive and significant impact of 1% level of significance on bilateral trade contrary to the negative relationship that was expected. The study recommends the speedy conclusion of outstanding AfCFTA issues for member states to effectively benefit from the economies that economic geography presents.
Motivation is a critical factor that impacts the performance of both employees and organisations. Consequently, it is imperative that supervisors and management ascertain the motivating factors that significantly influence employee performance. The motivation levels of administrative employees were assessed in this study to determine the factors that influence them. The current study is focused on evaluating the motivational level of administrative employees and determining the sequence in which these motivational factors are ranked by administrative employees in the same department. A quantitative research methodology was implemented. An adapted questionnaire was implemented to implement a survey research design. The sample was comprised of 150 administrative employees from a total of 463 employees. The non-probability convenience sampling method was employed to select the respondents for this study. The motivational level of administrative personnel was analysed using descriptive statistics. The study's primary findings indicated that employees were most motivated by job security, job responsibility, goal setting, working conditions, leadership, feedback, salary, and job characteristics. The following was also determined: the most significant motivational factors for employees were ranked in the following order: leadership (1), salary (2), training and development (3), job security (4), feedback (5), rewards (6), working conditions (7), the opportunity for advancement (8), recognition and appreciation (9), job characteristics (10), job responsibility (11), performance appraisal (12), and goal setting 13.
MSMEs are widely regarded as important building blocks for economic prosperity and broader social well-being for both developed and developing nations. However, MSMEs face several challenges that impede their ability to fully provide the much-needed boost to the socio-economic development of countries. Tourism MSMEs are often significantly impacted by crises that include economic downturns, natural disasters, and public health emergencies that destroy infrastructure and affect human movement, notably the outbreak of pandemics and epidemics. The Covid-19 pandemic altered every business operation across the globe. This was mainly because the pandemic was new and no reference case for the Covid-19 crisis existed in living memory. As such the survival of all businesses was at high risk, particularly, the tourism MSMEs in South Africa. The industry’s operations were severely affected by the restrictions imposed by the government of South Africa especially in the year 2020 and 2021. Despite operating their businesses in a crisis, the tourism MSMEs entrepreneurs exhibited resilience as they navigated the pandemic, through being agile, adaptive, and exploring new opportunities of operating and utilising government support. It is in this regard that gaining a deeper understanding of the resilience strategies that were employed by the tourism MSMEs during and strategies being employed during post Covid-19 pandemic crisis is of paramount significance. The study adopted qualitative interpretivist approach through document analysis. Collected data was analysed using the ATLAS.ti.software. The study concludes that even though the Covid-19 had some devastating effects on the MSMEs tourism entrepreneurs, that are still being felt now, it forced the entrepreneurs to adapt and be innovative. It is in this regard that the study concludes that the identified strategies are very vital for the survival of the effects of the Covid-19 pandemic. The study also concludes that the tourism MSMEs entrepreneurs became more resilient to the pandemic as it progressed hence, they implemented the identified strategies revealed by the study findings.
Intra-SADC trade has not met the target that was set by the African Continental Trade Agreement (AfCFTA) of achieving 22% by the year 2022 due to a myriad of various trade-related challenges. This present study aims to compare the results of using a Poisson Maximum Likelihood Estimator (PPML) with Random Effects (RE), Fixed Effects (FE), and an Ordinary Least Squares (POLS) model on a balanced panel of select eight Southern African Development Community (SADC) members that trade with South Africa over the period 2010-2022. The paper empirically examines how South Africa’s overlapping Regional Economic Community (REC) membership affects bilateral trade. Also, the examination of how the impact of distance between South Africa and its trading partners impacts bilateral trade. The study findings are that PPML provides more robust results than other estimation techniques in estimating the gravity model for a balanced micro panel. From the PPML results, distance has a significant negative impact at a 5% level on bilateral exports from South Africa which implies that SADC countries that are relatively far in terms of distance from South Africa and landlocked tend to experience a relative fall in exports from South Africa. However, multiple REC membership has a positive and significant impact of 1% level of significance on bilateral trade contrary to the negative relationship that was expected. The study recommends the speedy conclusion of outstanding AfCFTA issues for member states to effectively benefit from the economies that economic geography presents.
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 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |
| ojs-rest | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:02 UTC |
| oai-pmh | 20 Oct 2026 19:49 UTC · ijbes | complete · ijbes · 20 Oct 2026 19:48 UTC |
| openalex-enrichment | 21 Oct 2026 00:14 UTC · ijbes | complete · ijbes · 21 Oct 2026 00:14 UTC |