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International Journal of Business Ecosystem & Strategy

ISSN 2687-2293 • Journal website ↗

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OpenAlex coverage 100.0% · 9/9 recordsLast OpenAlex observation 27 Oct 2026, 19:03 UTC
PUBLICATIONS9In the selected collection
CROSSREF CITATIONS09/9 with known counts
OPENALEX CITATIONS09/9 with known counts
OPENALEX MEAN0.0Per article with a known count
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Annual history: 9/9 articles. Latest history observation: 2026-10-27T19:03:47.823183+00:00. Source totals are never added together.
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International Journal of Business Ecosystem & Strategy

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9 MATCHING PUBLICATIONSExplore results →Export CSV ↓
INDEXED PUBLICATIONS9
CROSSREF CITATIONS0
CROSSREF · CITED PUBLICATIONS0.0%
CROSSREF · MEAN CITATIONS0.0

Crossref citation coverage: 9 / 9 publications (100.0%). Latest observation: 21 Oct 2026, 00:14 UTC. Means and percentages use records with known counts.

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OPENALEX CITATIONS0
DOI MATCH COVERAGE100.0%9 / 9 publications
MEAN · KNOWN COUNTS ONLY0.09 known · 0 unknown
MEDIAN · KNOWN COUNTS ONLY0

Observation range: 22 Oct 2026 02:27 UTC — 27 Oct 2026 19:03 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.

OpenAlex citation distributionNo citations91–506–20021+0Unknown0

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Citations received over time

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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): 2026-10-22T02:27:50.349300+00:00 — 2026-10-27T19:03:47.823183+00:00. Older observations may be retained after failed or incomplete refreshes.

OpenAlex · Citations received by year

10.50 2017 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 9/92018 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 9/92019 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 9/92020 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 9/92021 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 9/92022 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 9/92023 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 9/92024 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 9/92025 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 9/92026 · All selected publications · OpenAlex · Citations received by year: 0 · Annual history coverage 9/9 2017201820192020202120222023202420252026
View openalex · citations received by year data & coverage
Citation yearJournal / scopeOpenAlex · Citations received by yearPublicationsAnnual history known
2017All selected publications099/9
2018All selected publications099/9
2019All selected publications099/9
2020All selected publications099/9
2021All selected publications099/9
2022All selected publications099/9
2023All selected publications099/9
2024All selected publications099/9
2025All selected publications099/9
2026All selected publications099/9

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 ↗

Crossref citation distribution

Latest Crossref totals for the selected publications; not citations received in the selected years.

Mean0.0
Median0
No citations91–506–20021+0Unknown0

Unknown counts are excluded from the mean, median and cited-publication rate.

Journal comparison

Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.

Journal / publisherPublicationsCrossref citationsOpenAlex citationsOpenAlex coverageCrossref meanCrossref medianCrossref cited %*Crossref coverage
International Journal of Business Ecosystem & Strategy
Bussecon International Academy
9009/90.000.09/9 · 100.0%

* Percentage among publications with a known citation count.

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Most cited · Crossref

JOURNAL ARTICLE

Can artificial intelligence produce lawyers or merely law graduates? The crisis of competency in South African legal education

Melisa M. Chawaremera

International Journal of Business Ecosystem & Strategy · 2026

Read abstract

The rapid integration of Artificial Intelligence (AI) into higher education is fundamentally reshaping how students access and present knowledge. Within legal education particularly, AI tools increasingly enable students to generate summaries, conduct research, draft legal content and retrieve information with minimal engagement in traditional legal reasoning processes. At the same time, South African law faculties remain tasked with cultivating industry ready candidate legal practitioners who possess critical thinking abilities, ethical judgment, persuasive communication skills as well as strong legal research competencies. This creates an important pedagogical tension. While AI may enhance efficiency and technological fluency, its uncritical use may simultaneously undermine the intellectual rigour required for competent legal practice. This paper critically examines whether the growing integration of AI in legal education supports or compromises the cultivation of graduate attributes required within the South African legal profession. Using a doctrinal and conceptual methodology, the study analyses the graduate competency frameworks advanced by the Council on Higher Education and the South African Qualifications Authority. It further interrogates whether AI tools meaningfully contribute toward the development of legal reasoning, ethical sensitivity, drafting proficiency and contextual interpretation, all of which remain central to professional legal readiness. The paper argues that although AI presents significant opportunities for enhancing legal research efficiency and technological competence, overreliance on these tools risks producing graduates who are technologically capable yet jurisprudentially underdeveloped. It contends that AI cannot replace the human processes of critical engagement, ethical reflection and contextual legal interpretation that define legal education within a constitutional democracy. The study concludes that responsible AI integration in legal education requires careful pedagogical design and ethical oversight to ensure that innovation does not come at the expense of professional competence and intellectual integrity.

DOI 10.36096/ijbes.v8i4.13560 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Examining the Relationship between Enterprise Risk management Practices and the Perceived Sustainability of the Emerging and Junior Mining Sector in South Africa

Crossman Mayavo

International Journal of Business Ecosystem & Strategy · 2026

Read abstract

The study sought to relationship between enterprise risk management practices (ERM) and perceived sustainability of emerging and junior mining sector in South Africa as it creates employments and mineral diversification. This sector remains vulnerable to various risks factors including financial and regulatory among others.  The objective of the study was to examine the relationship between enterprise risk management practices and perceived sustainability of emerging and junior mining sector in South Africa. The study was anchored upon the governance theory. The study adopted the use of a quantitative methodology with a cross-sectional design using a secondary data panel downloaded from Kaggle data repository. The sample size of the study was 500 which included 262 males and 238 females who work in different mining organisational sizes. Regression analysis and structural equation modeling were tested and run to test the hypothesised statements. The results of OLS regression model 1 show that ERM_Governance has a positive and significant effect on sustainability and ERM_Value shows a negative and significant association, and other ERM dimensions are positive but not statistically significant. OLS regression Model 2 for perceived socio-economic importance shows that ERM_learning is a positive and significant predictor of socio-economic importance, and other ERM dimensions are not significant in this model. On the SEM front, ERM practices exhibited strong positive effects on both perceived sector sustainability and socio-economic importance (p < 0.001). Perceived sector sustainability significantly mediated the relationship between ERM practices and socio-economic importance (p < 0.001). Additionally, organisations size and mining experience were found to significantly moderate the ERM-sustainability relationship (p < 0.05), indicating the presence of contextual effects within the emerging and junior mining sector. The theoretical implication suggests that ERM should be taken as a monolithic construct but rather as a set of complementary dimensions with distinct outcome pathways. Practically, the results imply that policymakers and mining executives should prioritise strong governance and accountability systems to enhance sustainability perceptions while simultaneously investing in learning and collaborative capabilities to maximise socio-economic impact.

DOI 10.36096/ijbes.v8i4.13500 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Privacy-Preserving Machine Learning Techniques for Cross-Sector Fraud Detection in the South African Financial and Telecommunications Sectors

Lufungula Osembe · Mukosi Lucky Mashudu

International Journal of Business Ecosystem & Strategy · 2026

Read abstract

Cross-sector fraud between South Africa’s financial and telecommunications sectors has intensified, driven by sophisticated criminal networks that exploit operational disparities between these industries. Traditional fraud detection systems, which depend on centralised data sharing and siloed organisational structures, encounter substantial legal and practical obstacles under the Protection of Personal Information Act (POPIA). These include restrictions on cross-entity data transfer, data minimisation requirements, and transparency obligations for automated decision-making. This study developed and evaluated a privacy-preserving framework that integrates Federated Learning (FL) and Explainable Artificial Intelligence (XAI) to enable collaborative fraud detection while safeguarding customer privacy and ensuring regulatory compliance. A mixed-method approach was employed. Quantitative experiments were conducted on a dataset of 35,675 credit card transactions linked to telecommunications parameters, training a federated global model across simulated financial and telecommunications providers. A qualitative systematic literature review identified key barriers to cross-sector collaboration and distilled lessons from prior Federated Learning and Explainable Artificial Intelligence implementations. The federated model demonstrated strong detection performance, achieving a ROC-AUC of 0.98, near-perfect precision and recall for legitimate transactions, and an F1-score of 0.89 for the minority fraud class, all without exchanging raw customer data between institutions. SHAP analysis identified TransactionAmt and card1 as the most influential features, thereby satisfying POPIA's transparency mandates. While federated approaches did not consistently surpass siloed models in raw accuracy, this marginal trade-off reflects the essential privacy-utility equilibrium required for legal compliance. The framework effectively reconciled collective security with individual privacy, confirming that POPIA adherence need not diminish detection efficacy. This study provides a validated blueprint for financial and telecommunications providers in South Africa to collaboratively counter cross-sector fraud within regulatory constraints. The framework further supports audit trail generation and decision rationales, addressing compliance obligations. Drawing on systematic literature review insights, particularly regarding collaboration barriers and prior Federated Learning and Explainable Artificial Intelligence implementations, the findings offer regulators and investors practical guidance for meeting statutory requirements without compromising privacy rights.

DOI 10.36096/ijbes.v8i4.13510 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

The Innovative Approach Adopted by Entrepreneurship in Fostering Sustainable Economic Growth in South Africa

Andrew Enaifoghe · Trisha Ramsuraj

International Journal of Business Ecosystem & Strategy · 2026

Read abstract

The study examined the critical approach adopted by entrepreneurship and policy development in promoting socio-economic development. In this review. It also looked at the difficulties small, micro, and medium-sized businesses in South Africa face. The conceptual research looked at the influence of small, micro, and medium-sized companies (SMMEs) on South African development. The study's objective was to evaluate how small, medium-sized businesses (SMMEs) are now driving economic growth and solving social issues in a setting where big businesses and governments appear to be doing very little. As a result, the study examines how SMMEs might help the nation solve persistent societal evils, including poverty, inequality, and social isolation. A desktop literature review research design was adopted to collect data on the role of entrepreneurship in South Africa. The study further looks at policies and practices of big business and government that exacerbate social issues in communities and impede socio-economic development, as well as the specific roles that SMMEs play in achieving socio-economic development goals. The findings reveal that, among various developmental outcomes, SMMEs are at the forefront of generating employment and promoting social and political justice within the nation. Future empirical studies should account for and evaluate the importance of SMME contributions to constructing economic, social, and political justice in the nation.

DOI 10.36096/ijbes.v8i4.12860 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Exploring the relationship between consumerism, corporate social responsibility and ethical performance in Zimbabwe: A survey analysis

Lionel Muchirahondo

International Journal of Business Ecosystem & Strategy · 2026

Read abstract

This study explored the relationship between consumerism, corporate social responsibility (CSR), and ethical performance in Zimbabwe through a survey analysis. The research explored the differences in consumerism between developed and less developed countries and identified various influence consumerism, including economic situation, level of consumer education and awareness, and cultural considerations. The concept of consumerism was familiar to Zimbabwean consumers, but they lacked a comprehensive understanding of how it could be used to hold businesses accountable. Consumerism is in its infancy in Zimbabwe, and citizens lack awareness of their rights and obligations. This research relied on the understanding and perceptions of consumers to examine the relationship between consumerism, CSR, and ethical performance in Zimbabwe, as well as the effects of consumer activism on corporate behaviour. The data for this exploratory study was collected and analysed using qualitative methodologies from a representative sample of 200 Zimbabwean consumers chosen at random. The collected questionnaires were carefully analysed and structured to identify themes and key differences, providing a holistic understanding of the study. The findings indicated that consumers in Zimbabwe prioritise price, brand, quality, and country of origin over CSR and the ethical performance of organisations. This suggests that businesses in Zimbabwe have little incentive to prioritise CSR and ethical behaviour unless it aligns with the demands of consumers. The research highlighted the need for more education and awareness-raising efforts around CSR and ethical business practices in Zimbabwe. Overall, the study underscored the importance of consumerism and its impact on corporate social responsibility and ethical performance in Zimbabwe.  

DOI 10.36096/ijbes.v7i6.9370 Crossref citations0 OpenAlex citations

Selected results

JOURNAL ARTICLE

Can artificial intelligence produce lawyers or merely law graduates? The crisis of competency in South African legal education

Melisa M. Chawaremera

International Journal of Business Ecosystem & Strategy · 2026

Read abstract

The rapid integration of Artificial Intelligence (AI) into higher education is fundamentally reshaping how students access and present knowledge. Within legal education particularly, AI tools increasingly enable students to generate summaries, conduct research, draft legal content and retrieve information with minimal engagement in traditional legal reasoning processes. At the same time, South African law faculties remain tasked with cultivating industry ready candidate legal practitioners who possess critical thinking abilities, ethical judgment, persuasive communication skills as well as strong legal research competencies. This creates an important pedagogical tension. While AI may enhance efficiency and technological fluency, its uncritical use may simultaneously undermine the intellectual rigour required for competent legal practice. This paper critically examines whether the growing integration of AI in legal education supports or compromises the cultivation of graduate attributes required within the South African legal profession. Using a doctrinal and conceptual methodology, the study analyses the graduate competency frameworks advanced by the Council on Higher Education and the South African Qualifications Authority. It further interrogates whether AI tools meaningfully contribute toward the development of legal reasoning, ethical sensitivity, drafting proficiency and contextual interpretation, all of which remain central to professional legal readiness. The paper argues that although AI presents significant opportunities for enhancing legal research efficiency and technological competence, overreliance on these tools risks producing graduates who are technologically capable yet jurisprudentially underdeveloped. It contends that AI cannot replace the human processes of critical engagement, ethical reflection and contextual legal interpretation that define legal education within a constitutional democracy. The study concludes that responsible AI integration in legal education requires careful pedagogical design and ethical oversight to ensure that innovation does not come at the expense of professional competence and intellectual integrity.

DOI 10.36096/ijbes.v8i4.13560 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Examining the Relationship between Enterprise Risk management Practices and the Perceived Sustainability of the Emerging and Junior Mining Sector in South Africa

Crossman Mayavo

International Journal of Business Ecosystem & Strategy · 2026

Read abstract

The study sought to relationship between enterprise risk management practices (ERM) and perceived sustainability of emerging and junior mining sector in South Africa as it creates employments and mineral diversification. This sector remains vulnerable to various risks factors including financial and regulatory among others.  The objective of the study was to examine the relationship between enterprise risk management practices and perceived sustainability of emerging and junior mining sector in South Africa. The study was anchored upon the governance theory. The study adopted the use of a quantitative methodology with a cross-sectional design using a secondary data panel downloaded from Kaggle data repository. The sample size of the study was 500 which included 262 males and 238 females who work in different mining organisational sizes. Regression analysis and structural equation modeling were tested and run to test the hypothesised statements. The results of OLS regression model 1 show that ERM_Governance has a positive and significant effect on sustainability and ERM_Value shows a negative and significant association, and other ERM dimensions are positive but not statistically significant. OLS regression Model 2 for perceived socio-economic importance shows that ERM_learning is a positive and significant predictor of socio-economic importance, and other ERM dimensions are not significant in this model. On the SEM front, ERM practices exhibited strong positive effects on both perceived sector sustainability and socio-economic importance (p < 0.001). Perceived sector sustainability significantly mediated the relationship between ERM practices and socio-economic importance (p < 0.001). Additionally, organisations size and mining experience were found to significantly moderate the ERM-sustainability relationship (p < 0.05), indicating the presence of contextual effects within the emerging and junior mining sector. The theoretical implication suggests that ERM should be taken as a monolithic construct but rather as a set of complementary dimensions with distinct outcome pathways. Practically, the results imply that policymakers and mining executives should prioritise strong governance and accountability systems to enhance sustainability perceptions while simultaneously investing in learning and collaborative capabilities to maximise socio-economic impact.

DOI 10.36096/ijbes.v8i4.13500 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Privacy-Preserving Machine Learning Techniques for Cross-Sector Fraud Detection in the South African Financial and Telecommunications Sectors

Lufungula Osembe · Mukosi Lucky Mashudu

International Journal of Business Ecosystem & Strategy · 2026

Read abstract

Cross-sector fraud between South Africa’s financial and telecommunications sectors has intensified, driven by sophisticated criminal networks that exploit operational disparities between these industries. Traditional fraud detection systems, which depend on centralised data sharing and siloed organisational structures, encounter substantial legal and practical obstacles under the Protection of Personal Information Act (POPIA). These include restrictions on cross-entity data transfer, data minimisation requirements, and transparency obligations for automated decision-making. This study developed and evaluated a privacy-preserving framework that integrates Federated Learning (FL) and Explainable Artificial Intelligence (XAI) to enable collaborative fraud detection while safeguarding customer privacy and ensuring regulatory compliance. A mixed-method approach was employed. Quantitative experiments were conducted on a dataset of 35,675 credit card transactions linked to telecommunications parameters, training a federated global model across simulated financial and telecommunications providers. A qualitative systematic literature review identified key barriers to cross-sector collaboration and distilled lessons from prior Federated Learning and Explainable Artificial Intelligence implementations. The federated model demonstrated strong detection performance, achieving a ROC-AUC of 0.98, near-perfect precision and recall for legitimate transactions, and an F1-score of 0.89 for the minority fraud class, all without exchanging raw customer data between institutions. SHAP analysis identified TransactionAmt and card1 as the most influential features, thereby satisfying POPIA's transparency mandates. While federated approaches did not consistently surpass siloed models in raw accuracy, this marginal trade-off reflects the essential privacy-utility equilibrium required for legal compliance. The framework effectively reconciled collective security with individual privacy, confirming that POPIA adherence need not diminish detection efficacy. This study provides a validated blueprint for financial and telecommunications providers in South Africa to collaboratively counter cross-sector fraud within regulatory constraints. The framework further supports audit trail generation and decision rationales, addressing compliance obligations. Drawing on systematic literature review insights, particularly regarding collaboration barriers and prior Federated Learning and Explainable Artificial Intelligence implementations, the findings offer regulators and investors practical guidance for meeting statutory requirements without compromising privacy rights.

DOI 10.36096/ijbes.v8i4.13510 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

The Innovative Approach Adopted by Entrepreneurship in Fostering Sustainable Economic Growth in South Africa

Andrew Enaifoghe · Trisha Ramsuraj

International Journal of Business Ecosystem & Strategy · 2026

Read abstract

The study examined the critical approach adopted by entrepreneurship and policy development in promoting socio-economic development. In this review. It also looked at the difficulties small, micro, and medium-sized businesses in South Africa face. The conceptual research looked at the influence of small, micro, and medium-sized companies (SMMEs) on South African development. The study's objective was to evaluate how small, medium-sized businesses (SMMEs) are now driving economic growth and solving social issues in a setting where big businesses and governments appear to be doing very little. As a result, the study examines how SMMEs might help the nation solve persistent societal evils, including poverty, inequality, and social isolation. A desktop literature review research design was adopted to collect data on the role of entrepreneurship in South Africa. The study further looks at policies and practices of big business and government that exacerbate social issues in communities and impede socio-economic development, as well as the specific roles that SMMEs play in achieving socio-economic development goals. The findings reveal that, among various developmental outcomes, SMMEs are at the forefront of generating employment and promoting social and political justice within the nation. Future empirical studies should account for and evaluate the importance of SMME contributions to constructing economic, social, and political justice in the nation.

DOI 10.36096/ijbes.v8i4.12860 Crossref citations0 OpenAlex citations
JOURNAL ARTICLE

Exploring the relationship between consumerism, corporate social responsibility and ethical performance in Zimbabwe: A survey analysis

Lionel Muchirahondo

International Journal of Business Ecosystem & Strategy · 2026

Read abstract

This study explored the relationship between consumerism, corporate social responsibility (CSR), and ethical performance in Zimbabwe through a survey analysis. The research explored the differences in consumerism between developed and less developed countries and identified various influence consumerism, including economic situation, level of consumer education and awareness, and cultural considerations. The concept of consumerism was familiar to Zimbabwean consumers, but they lacked a comprehensive understanding of how it could be used to hold businesses accountable. Consumerism is in its infancy in Zimbabwe, and citizens lack awareness of their rights and obligations. This research relied on the understanding and perceptions of consumers to examine the relationship between consumerism, CSR, and ethical performance in Zimbabwe, as well as the effects of consumer activism on corporate behaviour. The data for this exploratory study was collected and analysed using qualitative methodologies from a representative sample of 200 Zimbabwean consumers chosen at random. The collected questionnaires were carefully analysed and structured to identify themes and key differences, providing a holistic understanding of the study. The findings indicated that consumers in Zimbabwe prioritise price, brand, quality, and country of origin over CSR and the ethical performance of organisations. This suggests that businesses in Zimbabwe have little incentive to prioritise CSR and ethical behaviour unless it aligns with the demands of consumers. The research highlighted the need for more education and awareness-raising efforts around CSR and ethical business practices in Zimbabwe. Overall, the study underscored the importance of consumerism and its impact on corporate social responsibility and ethical performance in Zimbabwe.  

DOI 10.36096/ijbes.v7i6.9370 Crossref citations0 OpenAlex citations

Data coverage & freshness

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

SourceMost recent successful journal syncLatest attempt
crossref21 Oct 2026 00:14 UTC · ijbescomplete · ijbes · 21 Oct 2026 00:14 UTC
ojs-rest21 Oct 2026 00:14 UTC · ijbescomplete · ijbes · 21 Oct 2026 00:02 UTC
oai-pmh20 Oct 2026 19:49 UTC · ijbescomplete · ijbes · 20 Oct 2026 19:48 UTC
openalex-enrichment21 Oct 2026 00:14 UTC · ijbescomplete · ijbes · 21 Oct 2026 00:14 UTC
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