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: 9 / 9 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 11:30 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.
9 / 9 with data · 0 missing or unmatched. Percentages use all 9 selected publications.
9 / 9 with data · 0 missing or unmatched. Percentages use all 9 selected publications.
9 / 9 with data · 0 missing or unmatched. Percentages use all 9 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 |
|---|---|---|---|---|---|
| 2021 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | 6 | 6 | 6/6 | 6/6 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 3 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | 2 | 6 | 6/6 | 6/6 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2021 | All selected publications | 8 | 1 | 1/1 | 1/1 |
| 2022 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2023 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2024 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2025 | All selected publications | 2 | 6 | 6/6 | 6/6 |
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 9 / 9 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): 2026-10-21T07:22:57.116646+00:00 — 2026-10-23T11:30:49.055158+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 | 9 | 9/9 |
| 2018 | All selected publications | 0 | 9 | 9/9 |
| 2019 | All selected publications | 0 | 9 | 9/9 |
| 2020 | All selected publications | 0 | 9 | 9/9 |
| 2021 | All selected publications | 0 | 9 | 9/9 |
| 2022 | All selected publications | 2 | 9 | 9/9 |
| 2023 | All selected publications | 4 | 9 | 9/9 |
| 2024 | All selected publications | 2 | 9 | 9/9 |
| 2025 | All selected publications | 2 | 9 | 9/9 |
| 2026 | All selected publications | 2 | 9 | 9/9 |
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 |
|---|---|
| 2021 | 1 |
| 2024 | 2 |
| 2025 | 6 |
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 | 2 | 3/3 | 0.67 | 0 | 33.3 | 3/3 · 100.0% |
| International Journal of Finance & Banking Studies SSBFNET | 1 | 3 | 8 | 1/1 | 3.0 | 3 | 100.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 5 | 2 | 2 | 5/5 | 0.4 | 0 | 40.0 | 5/5 · 100.0% |
* Percentage among publications with a known citation count.
The purpose of the study is aimed at determining the financial socialisation of accounting students at South African universities and the factors that influence financial socialisation. The research used statistical techniques such as the structural equation modelling methodology to identify financial socialisation influencers and regression analysis to analyse associations between financial socialisation and socio-demographic variables among 1582 students. The study's results indicate that financial socialisation agents such as relatives, friends, and social media have little impact on most students' financial decisions. The majority of accounting students are often found to be financially socialised by their immediate family members rather than peers or social media factors. The regression analysis results confirmed this observation, revealing a statistically significant association between the parents' level of education and the students' financial socialisation. This study recommends that financial socialisation can be greatly improved by raising parents' educational levels and instilling financial education in university students' curricula, especially in South Africa.
Small, Medium, and Micro Enterprises (SMMEs) are the foundation of South Africa's economy, driving job creation, innovation, and local economic growth. However, these businesses frequently face challenges in critical areas such as bookkeeping and financial literacy, which have a direct impact on operational performance and sustainability. Limited financial knowledge and inadequate record-keeping practices have long been issues for Alice's SMMEs, posing significant challenges to effective financial management. These gaps in financial literacy and bookkeeping make it difficult for SMMEs to manage cash flow, make informed decisions, and plan for growth, limiting their ability to fully contribute to the local economy. Addressing these challenges has become critical for SMMEs, as improved financial management practices are required for success and resilience in a competitive market. The study's exploring the impact of bookkeeping and financial literacy on the performance of SMMEs in the context of Alice. Data was collected qualitatively through in-depth interviews with 15 SMME operators and analysed thematically to gain a thorough understanding of their experiences and practices. The findings show that both accurate bookkeeping and financial literacy improve business performance, allowing owners to make data-driven decisions, avoid cash flow issues, and lay the groundwork for future growth. Those who fall short in these areas suffer from financial mismanagement, which harms their businesses. Despite the challenges, the study identified strategies implemented by SMMEs owners to improve both bookkeeping and financial literacy such as digital bookkeeping tools, external financial advisory support, and collaborative financial management across teams. Finding from this study are crucial for enhancing SMMEs’ operational performance and fostering economic resilience within South Africa's competitive market.
The contributions of entrepreneurs to wellbeing have been recognised in both industrialised and non-industrialised nations for engaging in solving socio-economic issues. In both economies, financial knowledge seems to be a significant instrument for assisting entrepreneurs, especially women, and other latent entrepreneurs to attain access to finance and reinforce money management skills. However, there is a lack of commitment to understand challenges affecting women’s economic activities. The purpose of this paper is to analyse the impact of financial knowledge on the economic empowerment of women entrepreneurs in KwaZulu-Natal, South Africa. This study utilised a quantitative research design rooted in positivism philosophy. The study focused on surveying 500 women entrepreneurs including refugees and migrants, ultimately receiving responses from 400 participants. Respondents were selected using convenience quota sampling technique who are operating in the Durban Metropolitan areas. A Likert Scale model has been used in the quantitative questions and respondents had to select answers to the close-ended questions. With the help of 10% of the participants who served as pilot respondents and research professionals in the area of entrepreneurship, the instrument was updated and modified. Statistical Package for the Social Sciences (SPSS) version 26.0 was used to cross-check, clean, code, and analyze data collected from the target population. The findings show that entrepreneurial activities empower women economically, poor business skills such as insufficient financial literacy skills, access to finance, education and training hinder their economic development. Recognising the valuable contribution of women entrepreneurs to socioeconomic growth, it is essential to implement policies that promote financial literacy among female business owners. This contributes to the sustainability of women-led small and medium-sized enterprises, enhances their empowerment, and promotes economic growth.
This study examines the relationship between financial sustainability and the financial well-being of SME owners in Durban, South Africa. Utilising a quantitative research design, data were gathered through close-ended surveys from a diverse cross-section of SME owners, employing a cross-sectional approach.The study adopted a positivist philosophical framework, emphasising quantitative data analysis to derive conclusions. A total of 250 responses were collected, yielding a robust response rate of 82%. The analysis involved descriptive statistics and correlation analysis, with the correlation matrix revealing a positive, statistically significant correlation (r = 0.504, p < 0.05) between financial sustainability and financial well-being. The findings indicate that higher levels of financial sustainability are associated with greater financial well-being among SME owners, though the strength of this relationship is moderate. The regression analysis further supports this positive association, suggesting that interventions aimed at enhancing financial sustainability may significantly improve the financial well-being of SME owners. These results align with the theoretical framework of the Easterlin Paradox, which highlights the relative importance of financial stability in enhancing overall well-being. Based on these findings, several recommendations are proposed, including fostering financial literacy, enhancing access to financial resources, and promoting entrepreneurial collaboration.
In the context of rapid technological advancement and evolving financial ecosystems, this study investigates the interplay between financial literacy, digital finance, and financial behaviour among high school teachers in KwaZulu-Natal (KZN), South Africa. Structural equation modelling (SEM) approach was used to describe intricate relationships between latent constructs, namely, financial literacy, financial Behaviour and, digital finance Knowledge as well as observed variables (B7 to B22, C23 to C44, D45 to D56, demographics). Demographic variables include Gender, Age Category, Qualification Type, Teaching Duration, Financial Literacy Course and Field Employed. The model defined each construct as a linear combination of its observed variables as well as demographic variables under its measurement component, and hypothetical relationships among three latent variables under its structural component. We used Python software and machine learning code to create and estimate the model using observed data. The missing values in each observed variable were imputed with averages of the variables’ data. The tests of normality assumption for SEM were performed using histogram and q-q plots, Shapiro-Wilk test D'Agostino and Pearson's test. Most data vectors violated the normality assumption. Diagonally Weighted Least Squares (DWLS) was used for parameter estimation as a suitable method that can provide better estimation for more complex models with many parameters. This method has an additional advantage of being less sensitive to outliers. The DWLS parameter estimation results, based on p-values, suggest that financial literacy and financial behaviour have a negative association which means that lacking financial behaviour results in financial literacy. A positive association between has been identified between financial behaviour and digital finance knowledge. Financial literacy and digital finance knowledge have a weak or no relationship. Thus, having or not having digital finance knowledge does not necessarily determine the possibility of experiencing financial literacy. Furthermore, among demographic variables, the financial literacy Course is the only demographic variable that has a significant impact, and only on Financial Behaviour and Financial literacy. The rest of the variables do not significantly influence the latent constructs. This study uniquely applies SEM using the DWLS estimator to explore personal finance dynamics in an emerging economy, offering concise insights into key relationships.
In the context of rapid technological advancement and evolving financial ecosystems, this study investigates the interplay between financial literacy, digital finance, and financial behaviour among high school teachers in KwaZulu-Natal (KZN), South Africa. Structural equation modelling (SEM) approach was used to describe intricate relationships between latent constructs, namely, financial literacy, financial Behaviour and, digital finance Knowledge as well as observed variables (B7 to B22, C23 to C44, D45 to D56, demographics). Demographic variables include Gender, Age Category, Qualification Type, Teaching Duration, Financial Literacy Course and Field Employed. The model defined each construct as a linear combination of its observed variables as well as demographic variables under its measurement component, and hypothetical relationships among three latent variables under its structural component. We used Python software and machine learning code to create and estimate the model using observed data. The missing values in each observed variable were imputed with averages of the variables’ data. The tests of normality assumption for SEM were performed using histogram and q-q plots, Shapiro-Wilk test D'Agostino and Pearson's test. Most data vectors violated the normality assumption. Diagonally Weighted Least Squares (DWLS) was used for parameter estimation as a suitable method that can provide better estimation for more complex models with many parameters. This method has an additional advantage of being less sensitive to outliers. The DWLS parameter estimation results, based on p-values, suggest that financial literacy and financial behaviour have a negative association which means that lacking financial behaviour results in financial literacy. A positive association between has been identified between financial behaviour and digital finance knowledge. Financial literacy and digital finance knowledge have a weak or no relationship. Thus, having or not having digital finance knowledge does not necessarily determine the possibility of experiencing financial literacy. Furthermore, among demographic variables, the financial literacy Course is the only demographic variable that has a significant impact, and only on Financial Behaviour and Financial literacy. The rest of the variables do not significantly influence the latent constructs. This study uniquely applies SEM using the DWLS estimator to explore personal finance dynamics in an emerging economy, offering concise insights into key relationships.
The literature reveals that have poor spending habits arising from poor budgeting skills and lack financial knowledge, among others. However, it is unclear which individual lifestyles and attitudes influence the students' spending habits. This study, therefore, fills this gap with empirical evidence from accounting students in South Africa. Specifically, the study aims to investigate the existence of relationships between socio-demographic, attitudinal and lifestyle factors on the one hand and students' spending behaviour, on the other. Using an online structured questionnaire, we collected data from 290 accounting students at the University of KwaZulu-Natal in South Africa, which was analysed using descriptive and inferential statistical techniques. The study finds that socio-demographic factors such as students' age and parental income have the greatest influence on students’ spending habits. Students' spending habits were also found to be influenced by attitudinal factors such as confidence in investment decision-making and shopping for necessities. Finally, it was observed that living an extravagant lifestyle, which includes purchasing branded clothing, compulsive shopping, the latest cell phones, and excessive alcohol purchases, were the primary cause of students' poor spending habits. These findings primarily support the social learning theory, implying that parents and/or guardians play an important role in shaping their children's spending habits.
Small, Medium, and Micro Enterprises (SMMEs) are the foundation of South Africa's economy, driving job creation, innovation, and local economic growth. However, these businesses frequently face challenges in critical areas such as bookkeeping and financial literacy, which have a direct impact on operational performance and sustainability. Limited financial knowledge and inadequate record-keeping practices have long been issues for Alice's SMMEs, posing significant challenges to effective financial management. These gaps in financial literacy and bookkeeping make it difficult for SMMEs to manage cash flow, make informed decisions, and plan for growth, limiting their ability to fully contribute to the local economy. Addressing these challenges has become critical for SMMEs, as improved financial management practices are required for success and resilience in a competitive market. The study's exploring the impact of bookkeeping and financial literacy on the performance of SMMEs in the context of Alice. Data was collected qualitatively through in-depth interviews with 15 SMME operators and analysed thematically to gain a thorough understanding of their experiences and practices. The findings show that both accurate bookkeeping and financial literacy improve business performance, allowing owners to make data-driven decisions, avoid cash flow issues, and lay the groundwork for future growth. Those who fall short in these areas suffer from financial mismanagement, which harms their businesses. Despite the challenges, the study identified strategies implemented by SMMEs owners to improve both bookkeeping and financial literacy such as digital bookkeeping tools, external financial advisory support, and collaborative financial management across teams. Finding from this study are crucial for enhancing SMMEs’ operational performance and fostering economic resilience within South Africa's competitive market.
This paper investigated the financial management practices among Small, Medium, and Micro Enterprises (SMMEs) in the Thulamela Local Municipality using a qualitative approach. The research focused on a sample of forty-eight respondents from the informal sector, which was deemed representative of the SMME landscape. Interviews were conducted with SMME owners, guided by an interview framework, and recorded for transcription and thematic analysis. Findings revealed that competition is perceived as the primary cause of business failures; however, inadequate financial management emerged as a significant underlying issue. The study emphasizes the urgent need for intervention from government, banks, and academic institutions to offer financial management training and improve access to funding for SMMEs. Recommended actions include the establishment of workshops and seminars designed to enhance financial literacy among business owners. Such training would provide them with essential accounting and budgeting skills, ultimately enabling them to meet loan requirements from financial institutions and reducing the risk of cash flow issues and business failure.
Financial literacy is a critical factor that significantly impacts the success and achievement of small and medium enterprises' (SMEs) objectives. Unfortunately, many SMEs struggle with inadequate financial literacy, which hinders their ability to make informed decisions, manage resources effectively and drive growth. This knowledge gap can lead to poor financial planning, inefficient resource allocation and a lack of resilience, ultimately threatening the long-term sustainability of these businesses. By prioritising financial literacy, SMEs can enhance their capacity to develop realistic financial projections and budgets. This study investigated the level of financial literacy among small and medium enterprises (SMEs), examining both their knowledge and practical applications of financial concepts. Additionally, the research explored the correlation between SMEs' financial literacy and their socio-demographic characteristics, such as business size, industry, owner's age, education, and experience. A quantitative research approach was employed to achieve the study's objectives and primary data was collected through a questionnaire survey administered to a sample of 105 small and medium enterprises (SMEs) located in the uMgungundlovu District of KwaZulu-Natal, South Africa. The data analysis was conducted using SPSS version 23, leveraging both descriptive and inferential statistics to extract insights and meaning from the data. The findings of this study indicate that small and medium enterprises (SMEs) in the uMgungundlovu District exhibit low levels of financial knowledge and practice. Notably, the research revealed significant positive correlations between financial knowledge and various factors, including: age, qualifications, number of employees and annual turnover. A positive relationship was also established between financial practice and annual turnover. This study recommends that stakeholders, for instance, government agencies and banks should organise financial education programmes that invest in improving financial practices of small and medium enterprises. It is also recommended that small and medium enterprises pursue short courses in basic accounting to improve their knowledge base.
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 |