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: 6 / 6 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 — 23 Oct 2026 16:30 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.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 selected publications.
6 / 6 with data · 0 missing or unmatched. Percentages use all 6 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 |
| 2025 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 3 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2024 | All selected publications | 4 | 3 | 3/3 | 3/3 |
| 2025 | All selected publications | 0 | 2 | 2/2 | 2/2 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
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 6 / 6 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): 2026-10-21T07:22:54.104385+00:00 — 2026-10-23T16:30:04.689211+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 | 6 | 6/6 |
| 2018 | All selected publications | 0 | 6 | 6/6 |
| 2019 | All selected publications | 0 | 6 | 6/6 |
| 2020 | All selected publications | 0 | 6 | 6/6 |
| 2021 | All selected publications | 0 | 6 | 6/6 |
| 2022 | All selected publications | 0 | 6 | 6/6 |
| 2023 | All selected publications | 0 | 6 | 6/6 |
| 2024 | All selected publications | 0 | 6 | 6/6 |
| 2025 | All selected publications | 3 | 6 | 6/6 |
| 2026 | All selected publications | 1 | 6 | 6/6 |
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 |
| 2025 | 2 |
| 2026 | 1 |
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 | 4 | 1 | 1 | 4/4 | 0.25 | 0.0 | 25.0 | 4/4 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 2 | 2 | 3 | 2/2 | 1.0 | 1.0 | 50.0 | 2/2 · 100.0% |
* Percentage among publications with a known citation count.
Various studies have been carried out to establish the key drivers impacting small enterprise sustainable performance in developing countries. Despite many policy-oriented studies to uncover the factors influencing SME resilience in emerging markets, these firms continue to register high failure rate, which has been further exacerbated by the Covid-19 pandemic. Guided by a history of linear- and log-linear econometric model estimation that ignores potential network effects, our study extends the literature by implicating SMME resilience as a production network. Utilising data from both incubated and non-incubated SMMEs, marking a departure from traditional linear econometric models, radial basis function artificial neural network algorithm was invoked to establish the drivers of SMME resilience during Covid-19 regime. The study extends the literature by implicating eXplainable Artificial Intelligence (XAI) methods. Specifically, optimal SHapley Additive Explanations values (SHAP values) were computed to enhance the prediction output from the machine learning algorithm. The XAI analytics provide insightful findings on the key drivers which influenced the resilience of SMMEs during the Covid-19 pandemic. The importance of innovation through introduction of new products, company age and higher number of marketing mediums is confirmed however total assets, analytics, educational level and number of workers surfaced as a threat to these enterprises’ sustainable performance. The study recommends that both the government and SMEs should leverage XAI to identify their heterogeneous attributes and inform intelligent decision-making which necessities their resilient performance.
The Covid-19 crisis has disrupted businesses of Small, Medium and Micro Enterprises (SMMEs) globally, particularly in rural areas such as KwaZulu-Natal (KZN), South Africa. This study investigated the social media marketing strategies adopted by rural SMMEs to survive and grow during the Covid-19 crisis. Furthermore, it aims to recommend the social media marketing strategies that can be used by SMMEs as a critical tool for their survival and grow during the Covid-19 crisis in rural KZN. The quantitative design was adopted, and data was collected from 374 rural SMMEs in KZN by a closed-ended 5-point Likert scale questionnaire. The collected data was analysed by means of statistical social sciences software 27.0. Data was analyzed using descriptive statistics, factor analysis, and correlation analysis to identify the determinants of social media strategies and its impact on business performance. Key findings include a significant positive relationship between creating awareness of products and services and increased sales, where r = 0.708, p <0.01 and a significant correlation between customers’ needs and complaints and use of social media to retain customers, where r =0.653, p < 0.001. Recommendations suggested that rural SMMEs must gain technical competencies to use social media marketing strategies to gain competitive advantage to sustain their businesses during the Covid-19 crisis.
The COVID-19 pandemic significantly impacted Small, Medium, and Micro Enterprises (SMMEs) in South Africa, revealing their inadequate financial reserves and insufficient strategic assistance. In response, the government implemented financial and non-financial measures to promote innovation and enhance corporate resilience. This study assessed the efficacy of these approaches in aiding SMMEs during and post-pandemic, emphasising innovation uptake and sustainability results. A positivist paradigm and quantitative design were utilised, surveying 201 small, medium, and micro enterprise (SMME) owners and managers in eThekwini Municipality via structured questionnaires. Data analysis utilising SPSS (version 28.0) identified significant deficiencies in governmental assistance frameworks, especially with accessibility and communication. Participants indicated inadequate communication regarding funding initiatives, challenges in accessing newly implemented programs, and minimal influence on business recovery and innovation. The findings reveal a continual disparity between policy objectives and actual support, emphasising the necessity for enhanced communication tactics and more accessible tools to bolster SMME resilience during crises
Globally, SMEs were severely disrupted by the COVID-19 pandemic, especially in developing nations where systemic vulnerabilities are more noticeable. This study examines the growth and survival tactics used by SMEs in South Africa's eThekwini Metropolitan Area during the pandemic's peak and the subsequent recovery period. The study, which was based on a quantitative design, used a structured questionnaire to survey 304 managers and owners of SMEs. The results show that SMEs used a variety of survival tactics, such as lowering operating costs, integrating digital technology, and making short-term changes to their business models. Product diversification, strategic alliances, and the adoption of e-commerce were among the growth strategies. The Resource-Based View (RBV) and Dynamic Capabilities Theory, which shed light on how SMEs used internal resources and adjusted to external shocks, serve as the foundation for this study. Recovery efforts were, however, hampered by obstacles like a lack of digital infrastructure, difficulty accessing relief funds, and complicated regulations. A post-crisis policy reflection and a SWOT analysis provide strategic insight into enhancing the resilience of SMEs. The study ends with specific managerial and policy suggestions that can be applied to urban SME ecosystems in developing nations.
This study investigates the critical factors influencing social media adoption by rural Small, Medium, and Micro Enterprises (SMMEs) in KwaZulu-Natal (KZN), South Africa, with a focus on supporting business survival and growth during the Covid-19 crisis. The Covid-19 crisis intensified existing challenges such as limited digital connectivity, financial constraints, and poor market access, highlighting the need for adaptive, cost-effective solutions. Social media became a vital tool for these businesses, enabling expanded market reach, improved customer engagement, and continued product promotion during uncertain times. A quantitative research approach was employed, gathering data from 374 rural SMMEs using a structured 5-point Likert scale questionnaire. Analysis revealed a strong positive correlation (r = 0.779, p < 0.001) between broadband internet access, financial resources, and social media use, all critical factors for maintaining digital engagement and ensuring business continuity. The study advocates for increased public and private investment in rural broadband infrastructure to address the digital divide and emphasises capacity building programmes to enhance digital literacy and social media marketing skills among rural entrepreneurs. The findings offer actionable insights for policy and practice, supporting the long-term sustainability of rural SMMEs and promoting inclusive digital development in rural KZN. A Social Media Adoption Model is proposed to enhance the survival and growth of rural SMMEs during the Covid-19 crisis in KZN.
Globally, SMEs were severely disrupted by the COVID-19 pandemic, especially in developing nations where systemic vulnerabilities are more noticeable. This study examines the growth and survival tactics used by SMEs in South Africa's eThekwini Metropolitan Area during the pandemic's peak and the subsequent recovery period. The study, which was based on a quantitative design, used a structured questionnaire to survey 304 managers and owners of SMEs. The results show that SMEs used a variety of survival tactics, such as lowering operating costs, integrating digital technology, and making short-term changes to their business models. Product diversification, strategic alliances, and the adoption of e-commerce were among the growth strategies. The Resource-Based View (RBV) and Dynamic Capabilities Theory, which shed light on how SMEs used internal resources and adjusted to external shocks, serve as the foundation for this study. Recovery efforts were, however, hampered by obstacles like a lack of digital infrastructure, difficulty accessing relief funds, and complicated regulations. A post-crisis policy reflection and a SWOT analysis provide strategic insight into enhancing the resilience of SMEs. The study ends with specific managerial and policy suggestions that can be applied to urban SME ecosystems in developing nations.
The COVID-19 pandemic significantly impacted Small, Medium, and Micro Enterprises (SMMEs) in South Africa, revealing their inadequate financial reserves and insufficient strategic assistance. In response, the government implemented financial and non-financial measures to promote innovation and enhance corporate resilience. This study assessed the efficacy of these approaches in aiding SMMEs during and post-pandemic, emphasising innovation uptake and sustainability results. A positivist paradigm and quantitative design were utilised, surveying 201 small, medium, and micro enterprise (SMME) owners and managers in eThekwini Municipality via structured questionnaires. Data analysis utilising SPSS (version 28.0) identified significant deficiencies in governmental assistance frameworks, especially with accessibility and communication. Participants indicated inadequate communication regarding funding initiatives, challenges in accessing newly implemented programs, and minimal influence on business recovery and innovation. The findings reveal a continual disparity between policy objectives and actual support, emphasising the necessity for enhanced communication tactics and more accessible tools to bolster SMME resilience during crises
This study investigates the critical factors influencing social media adoption by rural Small, Medium, and Micro Enterprises (SMMEs) in KwaZulu-Natal (KZN), South Africa, with a focus on supporting business survival and growth during the Covid-19 crisis. The Covid-19 crisis intensified existing challenges such as limited digital connectivity, financial constraints, and poor market access, highlighting the need for adaptive, cost-effective solutions. Social media became a vital tool for these businesses, enabling expanded market reach, improved customer engagement, and continued product promotion during uncertain times. A quantitative research approach was employed, gathering data from 374 rural SMMEs using a structured 5-point Likert scale questionnaire. Analysis revealed a strong positive correlation (r = 0.779, p < 0.001) between broadband internet access, financial resources, and social media use, all critical factors for maintaining digital engagement and ensuring business continuity. The study advocates for increased public and private investment in rural broadband infrastructure to address the digital divide and emphasises capacity building programmes to enhance digital literacy and social media marketing skills among rural entrepreneurs. The findings offer actionable insights for policy and practice, supporting the long-term sustainability of rural SMMEs and promoting inclusive digital development in rural KZN. A Social Media Adoption Model is proposed to enhance the survival and growth of rural SMMEs during the Covid-19 crisis in KZN.
Digital marketing has profoundly altered the marketing techniques utilised by merchants. Although a growing number of rural retail enterprises in South Africa are starting to implement these techniques, the comprehensive effect of digital marketing on their sustainability is still inadequately examined. This study seeks to investigate the impact of internet marketing on retail operations in the rural community of Flagstaff. A quantitative research methodology was utilised, distributing questionnaires to all 52 major merchants via a census technique, yielding 45 replies and an 87% response rate. The results demonstrate that merchants employ several digital marketing strategies, such as social media marketing, email marketing, and mobile marketing, to engage with customers and present sales propositions. This engagement is constrained by the minimal acceptance of digital marketing among consumers, restricted e-commerce utilisation, and inadequate digital literacy, preventing both sides from fully leveraging its advantages. The report advises businesses to persist in using digital marketing methods, including social media and email marketing, into their promotional efforts. This strategy will enable them to engage the niche population that prefers these platforms and maintain alignment with market trends, so assuring competitiveness. Furthermore, it is essential to assist rural areas in improving their digital marketing adoption to sustain retail enterprises and maintain relevance in the contemporary digital environment.
The Covid-19 crisis has disrupted businesses of Small, Medium and Micro Enterprises (SMMEs) globally, particularly in rural areas such as KwaZulu-Natal (KZN), South Africa. This study investigated the social media marketing strategies adopted by rural SMMEs to survive and grow during the Covid-19 crisis. Furthermore, it aims to recommend the social media marketing strategies that can be used by SMMEs as a critical tool for their survival and grow during the Covid-19 crisis in rural KZN. The quantitative design was adopted, and data was collected from 374 rural SMMEs in KZN by a closed-ended 5-point Likert scale questionnaire. The collected data was analysed by means of statistical social sciences software 27.0. Data was analyzed using descriptive statistics, factor analysis, and correlation analysis to identify the determinants of social media strategies and its impact on business performance. Key findings include a significant positive relationship between creating awareness of products and services and increased sales, where r = 0.708, p <0.01 and a significant correlation between customers’ needs and complaints and use of social media to retain customers, where r =0.653, p < 0.001. Recommendations suggested that rural SMMEs must gain technical competencies to use social media marketing strategies to gain competitive advantage to sustain their businesses during the Covid-19 crisis.
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 |