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Dr. David Mhlanga
University of Johannesburg, South Africa

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Research Keywords & Expertise

0 Agricultural Economics
0 Artificial Intelligence
0 Development Economics
0 Educational Technology
0 Financial Economics

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Financial Inclusion
Artificial Intelligence
Poverty
Industry 4.0
FinTech

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Short Biography

David Mhlanga currently works at the University of Johannesburg in South Africa as a Postdoctoral Research Fellow in the Department of Accountancy. David does research in Econometrics, Development Economics, Health Economics Agricultural Economics, and Consumer Economics. Current Projects include the analysis of Household Financial Inclusion(FinTech), Food Security, Analysis of Poverty Theories, Industry 4.0- Artificial intelligence(AI) in Finance, AI in Agriculture, AI and Poverty Reduction.

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Journal article
Published: 27 July 2021 in International Journal of Financial Studies
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In banking and finance, credit risk is among the important topics because the process of issuing a loan requires a lot of attention to assessing the possibilities of getting the loaned money back. At the same time in emerging markets, the underbanked individuals cannot access traditional forms of collateral or identification that is required by financial institutions for them to be granted loans. Using the literature review approach through documentary and conceptual analysis to investigate the impact of machine learning and artificial intelligence in credit risk assessment, this study discovered that artificial intelligence and machine learning have a strong impact on credit risk assessments using alternative data sources such as public data to deal with the problems of information asymmetry, adverse selection, and moral hazard. This allows lenders to do serious credit risk analysis, to assess the behaviour of the customer, and subsequently to verify the ability of the clients to repay the loans, permitting less privileged people to access credit. Therefore, this study recommends that financial institutions such as banks and credit lending institutions invest more in artificial intelligence and machine learning to ensure that financially excluded households can obtain credit.

ACS Style

David Mhlanga. Financial Inclusion in Emerging Economies: The Application of Machine Learning and Artificial Intelligence in Credit Risk Assessment. International Journal of Financial Studies 2021, 9, 39 .

AMA Style

David Mhlanga. Financial Inclusion in Emerging Economies: The Application of Machine Learning and Artificial Intelligence in Credit Risk Assessment. International Journal of Financial Studies. 2021; 9 (3):39.

Chicago/Turabian Style

David Mhlanga. 2021. "Financial Inclusion in Emerging Economies: The Application of Machine Learning and Artificial Intelligence in Credit Risk Assessment." International Journal of Financial Studies 9, no. 3: 39.

Journal article
Published: 17 June 2021 in Nursing Reports
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The study aimed to investigate the drivers of demand for healthcare in South Africa 26 years after democracy. The pattern healthcare demand by households in South Africa is that most households use public healthcare services particularly public clinics compared to private and traditional healthcare facilities. Using conditional probability models, the logit model to be more specific, the results revealed that households head who is unemployed, households who do not have a business, households who were not receiving pension money, had a greater probability of demand for public healthcare institutions. On the other hand, being male, being White, Indian and Coloured, being a property owner and being not a grant beneficiary, reduces the probability of demand for public healthcare facilities in South Africa. As a result, the study recommends more investment in public healthcare but more in public clinics in South Africa due to the high percentage of households using these services. Also, the government must consider investing more in the maintenance and improvement of the welfare of nurses in the country considering the huge role they play in the delivery of healthcare to the citizens.

ACS Style

David Mhlanga. A Dynamic Analysis of the Demand for Health Care in Post-Apartheid South Africa. Nursing Reports 2021, 11, 484 -494.

AMA Style

David Mhlanga. A Dynamic Analysis of the Demand for Health Care in Post-Apartheid South Africa. Nursing Reports. 2021; 11 (2):484-494.

Chicago/Turabian Style

David Mhlanga. 2021. "A Dynamic Analysis of the Demand for Health Care in Post-Apartheid South Africa." Nursing Reports 11, no. 2: 484-494.

Journal article
Published: 31 May 2021 in Journal of Economic and Financial Sciences
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Orientation: Financial inclusion is becoming one of the attractive topics at the global level with policymakers, development partners, governments and financial institutions developing interest in understanding it more deeply.Research purpose: The study sought to establish the drivers of financial inclusion in South Africa with a focus on factors that influences ownership of an investment account.Motivation for the study: Motivated by the increase in the evidence of the importance of financial inclusion in fighting poverty and the fact that by merely having a bank account, financial inclusion cannot be guaranteed, the study interrogated the factors that influence households to have an investment account.Research approach/design and method: As the dependent variable of financial inclusion was binary, the logistic regression was used to estimate the drivers of financial inclusion. The variable assumed two values 0 and 1, where 1 represents access to an investment account and 0 otherwise.Main findings: Using the logit model, the study discovered that financial inclusion is driven by age, education level, the total salary proxy of income, race, and marital status.Practical/managerial implications: The differences in the probability of demand for financial products and services amongst the different races mean that products and services tailor-made to satisfy the needs of the different races, for coloured and black people these products and services should be designed to improve financial inclusion amongst them.Contribution/value-add: The study managed to discover the factors that influences households to have an investment account in South Africa.

ACS Style

David Mhlanga; Steven H. Dunga; Tankiso Moloi. Understanding the drivers of financial inclusion in South Africa. Journal of Economic and Financial Sciences 2021, 14, 8 .

AMA Style

David Mhlanga, Steven H. Dunga, Tankiso Moloi. Understanding the drivers of financial inclusion in South Africa. Journal of Economic and Financial Sciences. 2021; 14 (1):8.

Chicago/Turabian Style

David Mhlanga; Steven H. Dunga; Tankiso Moloi. 2021. "Understanding the drivers of financial inclusion in South Africa." Journal of Economic and Financial Sciences 14, no. 1: 8.

Journal article
Published: 21 May 2021 in Sustainability
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Artificial intelligence in the fourth industrial revolution is beginning to live up to its promises of delivering real value necessitated by the availability of relevant data, computational ability, and algorithms. Therefore, this study sought to investigate the influence of artificial intelligence on the attainment of Sustainable Development Goals with a direct focus on poverty reduction, goal one, industry, innovation, and infrastructure development goal 9, in emerging economies. Using content analysis, the result pointed to the fact that artificial intelligence has a strong influence on the attainment of Sustainable Development Goals particularly on poverty reduction, improvement of the certainty and reliability of infrastructure like transport making economic growth and development possible in emerging economies. The results revealed that Artificial intelligence is making poverty reduction possible through improving the collection of poverty-related data through poverty maps, revolutionizing agriculture education and the finance sector through financial inclusion. The study also discovered that AI is also assisting a lot in education, and the financial sector allowing the previously excluded individuals to be able to participate in the mainstream economy. Therefore, it is important that governments in emerging economies need to invest more in the use of AI and increase the research related to it so that the Sustainable Development Goals (SDGs) related to innovation, infrastructure development, poverty reduction are attained.

ACS Style

David Mhlanga. Artificial Intelligence in the Industry 4.0, and Its Impact on Poverty, Innovation, Infrastructure Development, and the Sustainable Development Goals: Lessons from Emerging Economies? Sustainability 2021, 13, 5788 .

AMA Style

David Mhlanga. Artificial Intelligence in the Industry 4.0, and Its Impact on Poverty, Innovation, Infrastructure Development, and the Sustainable Development Goals: Lessons from Emerging Economies? Sustainability. 2021; 13 (11):5788.

Chicago/Turabian Style

David Mhlanga. 2021. "Artificial Intelligence in the Industry 4.0, and Its Impact on Poverty, Innovation, Infrastructure Development, and the Sustainable Development Goals: Lessons from Emerging Economies?" Sustainability 13, no. 11: 5788.

Journal article
Published: 01 December 2020 in Studia Universitatis Babes-Bolyai Oeconomica
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The study sought to establish the drivers of financial inclusion in Southern Africa with a specific focus on South Africa. Financial inclusion has been a topic of global interest due to the negative impact of financial exclusion in addressing socio-economic issues like poverty. Using the logit model, the study discovered that financial inclusion is driven by age, education level, the total salary proxy of income, race, gender, and marital status. The variable gender was the only factor with a negative influence on financial inclusion all other significant variables had a positive influence on financial inclusion. As a result, governments in Africa should encourage the use of financial services and products among women, Black Africans, Coloureds and the youths. Products and services tailor-made to satisfy the needs of these groups should be designed to improve financial inclusion among them. This initiative will go a long way in addressing poverty, inequality, and unemployment in the country.

ACS Style

David Mhlanga; Varaidzo Denhere. Determinants of Financial Inclusion in Southern Africa. Studia Universitatis Babes-Bolyai Oeconomica 2020, 65, 39 -52.

AMA Style

David Mhlanga, Varaidzo Denhere. Determinants of Financial Inclusion in Southern Africa. Studia Universitatis Babes-Bolyai Oeconomica. 2020; 65 (3):39-52.

Chicago/Turabian Style

David Mhlanga; Varaidzo Denhere. 2020. "Determinants of Financial Inclusion in Southern Africa." Studia Universitatis Babes-Bolyai Oeconomica 65, no. 3: 39-52.

Preprint
Published: 16 September 2020
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Though the share of the world population living in extreme poverty declined to 10 percent in 2015, from 16 percent in 2010 and 36 percent in 1990, data shows that the world is not on track in achieving the target of less than 3 percent of people living in extreme poverty by 2030. Hence the study sought to investigate the influence of AI on poverty reduction. Using content analysis one of the unobtrusive research techniques, the study found out that, the availability of relevant data is making AI be able to deliver value to humanity and AI has a strong influence on poverty in areas of relevant data collection through poverty maps, its ability to revolutionize agriculture, education, and the financial sector through digital financial inclusion. The study also discovered that many countries especially developing nations are not collecting as much data to identify the number of poor people and the regions where these people are located. However, the existence of AI is assisting to change this, or instance the study discovered that the research team at Stanford University is using satellite images to provide an alternative to map poverty, to identify the regions where poverty is more concentrated. Also, various robotics and AI programs such as Google and Stanford University’s Sustainability and Artificial Intelligence Lab, are coming forth with AI programs in agriculture which are doing a lot to improve farming, through the identification of diseases, prediction of crop yields, and location of areas prone to a scarcity among several other notable signs of progress in education. Therefore, the study recommends that governments, development institutions and other organizations that are striving to fight poverty to invest more in AI as well as adopting and scaling up its use as it presents benefits in the quest to ensure that poverty is reduced.

ACS Style

David Mhlanga. Artificial Intelligence (AI) and Poverty Reduction in the Fourth Industrial Revolution (4IR). 2020, 1 .

AMA Style

David Mhlanga. Artificial Intelligence (AI) and Poverty Reduction in the Fourth Industrial Revolution (4IR). . 2020; ():1.

Chicago/Turabian Style

David Mhlanga. 2020. "Artificial Intelligence (AI) and Poverty Reduction in the Fourth Industrial Revolution (4IR)." , no. : 1.

Journal article
Published: 28 July 2020 in International Journal of Financial Studies
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This study sought to investigate the impact of AI on digital financial inclusion. Digital financial inclusion is becoming central in the debate on how to ensure that people who are at the lower levels of the pyramid become financially active. Fintech companies are using AI and its various applications to ensure that the goal of digital financial inclusion is realized that is to ensure that low-income earners, the poor, women, youths, small businesses participate in the mainstream financial market. This study used conceptual and documentary analysis of peer-reviewed journals, reports and other authoritative documents on AI and digital financial inclusion to assess the impact of AI on digital financial inclusion. The present study discovered that AI has a strong influence on digital financial inclusion in areas related to risk detection, measurement and management, addressing the problem of information asymmetry, availing customer support and helpdesk through chatbots and fraud detection and cybersecurity. Therefore, it is recommended that financial institutions and non-financial institutions and governments across the world adopt and scale up the use of AI tools and applications as they present benefits in the quest to ensure that the vulnerable groups of people who are not financially active do participate in the formal financial market with minimum challenges and maximum benefits.

ACS Style

David Mhlanga. Industry 4.0 in Finance: The Impact of Artificial Intelligence (AI) on Digital Financial Inclusion. International Journal of Financial Studies 2020, 8, 45 .

AMA Style

David Mhlanga. Industry 4.0 in Finance: The Impact of Artificial Intelligence (AI) on Digital Financial Inclusion. International Journal of Financial Studies. 2020; 8 (3):45.

Chicago/Turabian Style

David Mhlanga. 2020. "Industry 4.0 in Finance: The Impact of Artificial Intelligence (AI) on Digital Financial Inclusion." International Journal of Financial Studies 8, no. 3: 45.

Journal article
Published: 14 July 2020 in International Journal of Environmental Research and Public Health
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The study sought to analyse the influence of racial differences in the demand for public healthcare in South Africa, using the 2018 General Household Survey (GHS) data. This was completed to understand if race still plays a role in access to healthcare in post-apartheid South Africa. Logistic regression analysis revealed that race significantly explained the variance in demand for public healthcare, with White populations having the lowest probability of demand for public healthcare compared to other races. Consequently, the study noted that racial differences still play a critical role in affording one access to healthcare after assessing the situation obtaining in public healthcare. Therefore, the study recommends that the government of South Africa should create policies that encourage equal access to basic services in addressing racial inequality in the country.

ACS Style

David Mhlanga; Rufaro Garidzirai. The Influence of Racial Differences in the Demand for Healthcare in South Africa: A Case of Public Healthcare. International Journal of Environmental Research and Public Health 2020, 17, 5043 .

AMA Style

David Mhlanga, Rufaro Garidzirai. The Influence of Racial Differences in the Demand for Healthcare in South Africa: A Case of Public Healthcare. International Journal of Environmental Research and Public Health. 2020; 17 (14):5043.

Chicago/Turabian Style

David Mhlanga; Rufaro Garidzirai. 2020. "The Influence of Racial Differences in the Demand for Healthcare in South Africa: A Case of Public Healthcare." International Journal of Environmental Research and Public Health 17, no. 14: 5043.

Journal article
Published: 09 July 2020 in Education Sciences
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The study sought to assess the influence of the COVID-19 pandemic in motivating digital transformation in the education sector in South Africa. The study was premised on the fact that learning in South Africa and the rest of the world came to a standstill due to the lockdown necessitated by COVID-19. To assess the impact, the study tracked the rate at which the Fourth Industrial Revolution (4IR) tools were used by various institutions during the COVID-19 lockdown. Data were obtained from secondary sources. The findings are that, in South Africa, during the lockdown, a variety of 4IR tools were unleashed from primary education to higher and tertiary education where educational activities switched to remote (online) learning. These observations reflect that South Africa generally has some pockets of excellence to drive the education sector into the 4IR, which has the potential to increase access. Access to education, particularly at a higher education level, has always been a challenge due to a limited number of spaces available. Much as this pandemic has brought with it massive human suffering across the globe, it has presented an opportunity to assess successes and failures of deployed technologies, costs associated with them, and scaling these technologies to improve access.

ACS Style

David Mhlanga; Tankiso Moloi. COVID-19 and the Digital Transformation of Education: What Are We Learning on 4IR in South Africa? Education Sciences 2020, 10, 180 .

AMA Style

David Mhlanga, Tankiso Moloi. COVID-19 and the Digital Transformation of Education: What Are We Learning on 4IR in South Africa? Education Sciences. 2020; 10 (7):180.

Chicago/Turabian Style

David Mhlanga; Tankiso Moloi. 2020. "COVID-19 and the Digital Transformation of Education: What Are We Learning on 4IR in South Africa?" Education Sciences 10, no. 7: 180.

Preprint
Published: 14 April 2020
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The article revisits previous viruses such as Ebola to extrapolate the socio-economic implications of the COVID-19. Using secondary sources and the Sustainable Livelihoods Framework (SLF) to guide understanding, the article argues that unless measures are put in place to safeguard smallholder activities in Zimbabwe, COVID-19 has the potential to reproduce the same catastrophic implications created by Ebola in West African countries where peasant food systems where shattered and livelihoods strategies maimed. With a perceptible withdrawal of the government from small-scale farming towards large-scale capital intensive operations, smallholders could now be even more vulnerable. The article concludes that social assistance should now be intensified to protect its vulnerable population from the ravages of COVID-19.

ACS Style

David Mhlanga; Emmanuel Ndhlovu. Socio-economic Implications of the COVID-19 Pandemic on Smallholder Livelihoods in Zimbabwe. 2020, 1 .

AMA Style

David Mhlanga, Emmanuel Ndhlovu. Socio-economic Implications of the COVID-19 Pandemic on Smallholder Livelihoods in Zimbabwe. . 2020; ():1.

Chicago/Turabian Style

David Mhlanga; Emmanuel Ndhlovu. 2020. "Socio-economic Implications of the COVID-19 Pandemic on Smallholder Livelihoods in Zimbabwe." , no. : 1.

Preprint
Published: 12 April 2020
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The study sought to gauge the impact of COVID-19 pandemic in unleashing digital transformation in the education sector in South Africa. In order to gauge the impact, the study tracked the rate at which the 4IR tools were used by various institutions during the COVID-19 lockdown. Data were obtained from secondary sources, mainly newspaper articles, magazines and peer-reviewed journals. The findings are that, in South Africa, during the lockdown, a variety of 4IR tools were unleashed from primary education to higher and tertiary education where educational activities switched to remote learning (online learning). These observations point to the fact that South Africa generally has, some pockets of excellence to drive the education sector into the 4IR, which has the potential to increase access. Access to education, particularly at a higher education level, has always been a challenge due to a limited number of spaces available. Much as this pandemic has brought with it massive human suffering across the globe, there is an opportunity to assess successes and failures of deployed technologies, costs associated with them, and scaling these to technologies improve access.

ACS Style

David Mhlanga; Tankiso Moloi. COVID-19 and the Digital Transformation of Education: What We Are Learning in South Africa. 2020, 1 .

AMA Style

David Mhlanga, Tankiso Moloi. COVID-19 and the Digital Transformation of Education: What We Are Learning in South Africa. . 2020; ():1.

Chicago/Turabian Style

David Mhlanga; Tankiso Moloi. 2020. "COVID-19 and the Digital Transformation of Education: What We Are Learning in South Africa." , no. : 1.