Darrold Cordes

Poverty elimination by 2030 is the major initiative of the United Nations Sustainable Development Goals. However, poverty in Sub-Saharan Africa is rising. There is an absence of structural reform for transformational change across the region. E-commerce is an enabler of small and large businesses in developed economies. Community-led initiatives for poverty alleviation may benefit from the transactional capabilities of e-commerce for direct trade with suppliers and consumers. Well-structured small and medium-size enterprises (SMEs) can foster local innovation and entrepreneurship, and collaboration between SMEs can enhance product development and marketing strategies. This review aims to discover formal research into the application of e-commerce in sustainable development models for poverty alleviation in Sub-Saharan Africa, and the extent of innovation, entrepreneurship, and collaboration among SMEs. The review found an absence of formal research into theories and practical strategies for sustainability innovations across the low-income spectrum. Organizational structures have not been developed to stimulate outreach, to foster innovation and entrepreneurship, or to embrace technology. Further, there is limited discussion on the importance of collaboration for the sharing of knowledge and joint business activities, but there is acknowledgement that SMEs can provide spatially diversified sustainable development. This article proposes a framework for the implementation and management of networks of SMEs focused on the sustainable development of low-income communities.

Sub-Saharan Africa is currently experiencing growth in the number of people living in poverty, and the situation is worsening due to climate change and the COVID-19 pandemic. Cities are increasingly under stress because of urbanization and the demand for low-cost housing. Slum dwellers face daunting social, environmental, and economic challenges. Geospatial analysis of remote sensing, demographic, economic, social, and environmental data is being used to delineate slums. The application of circular economy guidelines for an intelligent transformation of slums combines technical and social innovation that reaches beyond the slums to the whole urban ecosystem. Examples of contributions to the circular economy are provided. Finally, some ideas are introduced on how the internet of things can improve access to goods and services and strengthen interconnectedness through the ability to participate more readily in the social dialogue of the city. The city of Accra in Ghana, West Africa, is discussed as a potential slum city to functional intelligent city transformation.

Chebyshev polynomials have unique properties that place them in a class of functions that are highly efficient in the approximation of non-linear functions. Machine learning techniques are being applied to solve complex non-linear problems in the financial markets where there is a proliferation of financial products. The techniques for valuing diverse portfolios of these products can be time consuming and expensive. Formal research has been conducted to determine how machine learning can considerably reduce the computational effort without losing accuracy. The objective of this systematic literature review is to discover evidence of research on the optimal use of Chebyshev polynomials in machine learning and neural networks that may be used for the estimation of generalized financial outcomes of large clusters of small economic units in low-income communities in sub-Saharan Africa. Scopus, ProQuest, and Web of Science databases were queried with search criteria designed to recover peer-reviewed research articles that addressed this objective. Many articles discussing broader applications in engineering, computer science, and applied mathematics were found. Several articles provided insights into the challenges of forecasting stock price outcomes from unpredictable market activities, and in investment portfolio valuations. One article addressed specific environmental issues relating to energy, biology, and ecological situations, and presented encouraging results. While the literature search did not find any similar articles that address economic forecasting for low-income communities, the applications and techniques used in stock market forecasting and portfolio valuations can contribute to formative theory on sustainable development. There is currently no theoretical underpinning of sustainable development initiatives in developing countries. A framework for small business structures, data collection, and near real-time processing is proposed as a potential data-driven approach to guide policy decisions and private sector involvement.