The food supply chain in South Africa faces significant challenges related to transparency, traceability, and consumer trust. As concerns about food safety, quality, and sustainability grow, there is an increasing need for innovative solutions to address these issues. Blockchain technology has emerged as a promising tool to enhance transparency and accountability across various industries, including the food sector. This study sought to explore the potential of blockchain technology in revolutionizing through promoting transparency that enable the achievement of sustainable food supply chain infrastructure in South Africa. The study found that blockchain technology used in food supply chain creates an immutable and decentralized ledger of transactions that has the capacity to provide real-time, end-to-end visibility of food products from farm to table. This increased transparency can help mitigate risks associated with food fraud, contamination, and inefficiencies in the supply chain. The study found that blockchain technology can be leveraged to enhance supply chain efficiency and trust among stakeholders. This technology used and/or applied in South Africa can reshape the agricultural sector by improving production and distribution processes. Its integration in the food supply chain infrastructure can equally improve data management and increase transparency between farmers and food suppliers.There is need for policy-makers and scholars in the fields of service delivery and food security to conduct more research in blockchain technology and its roles in creating a more transparent, efficient, and trustworthy food supply chain infractructure that address food supply problems in South Africa. The paper adopted a qualitative methodology to collect data, and document and content analysis techniques were used to interpret collected data. 

The Agriculture Trading Platform (ATP) represents a significant innovation in the realm of agricultural trade in Malaysia. This web-based platform is designed to address the prevalent inefficiencies and lack of transparency in the current agricultural trading environment. By centralizing real-time data on agricultural production, consumption, and pricing, ATP provides a comprehensive dashboard that facilitates data-driven decision-making for all stakeholders in the agricultural supply chain. The platform employs advanced deep learning algorithms, including Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to forecast market trends and consumption patterns. These predictive capabilities enable producers to optimize their market strategies, negotiate better prices, and access broader markets, thereby enhancing the overall efficiency and transparency of agricultural trading in Malaysia. The ATP’s user-friendly interface and robust analytical tools have the potential to revolutionize the agricultural sector by empowering farmers, reducing reliance on intermediaries, and fostering a more equitable trading environment.

Smallholder paprika farmers in Zimbabwe contribute to local economies and food security but face supply chain challenges like limited market access and poor infrastructure which lead to post harvest losses and unpredictable prices. To survive, these farmers must adopt sustainable value networks to reduce operational costs and improve performance. This study sought to establish the effect of sustainable value networks on the operational performance of smallholder paprika farming in Zimbabwe. This study, using a positivist research philosophy and a quantitative approach, surveyed 288 smallholder paprika farmers in Zimbabwe. Exploratory factor analysis and partial least squares structural equation modelling were used to validate the constructs and test the hypothesised relationships. Results demonstrate a moderate level of implementation of value networks in smallholder paprika farming characterised by successes and challenges. The findings illustrated resource sharing among smallholder farmers, facilitated by initiatives, such as recycled seed exchanges and financial support through village savings and loan associations. However, results show that challenges persist, particularly with market access and financial support. Results indicate that there is a significant awareness and implementation of green supply chain management practices among smallholder paprika farmers even though they do not have access to resources and live in rural areas. The findings demonstrate that value networks significantly influence the adoption of green supply chain management practices, which in turn positively impact operational performance, environmental performance, and social performance. Green supply chain management practices were found to mediate the relationship between value networks and environmental performance, social performance, and operational performance, underlining the critical role of sustainable practices in enhancing performance outcomes. While environmental performance showed a positive effect on operational performance, the direct influence of social performance on operational performance was found to be statistically insignificant, suggesting the need for further exploration of the factors linking social benefits to operational efficiency. The research contributes to both theory and practice by presenting a sustainable value network model for smallholder paprika farmers, integrating value network, green supply chain management practices and environmental performance to enhance operational performance. Practical implications include policy recommendations to strengthen collaboration between smallholder farmers and other stakeholdersand address power imbalances with intermediaries. Future research should extend the study to other agricultural sectors and incorporate more diverse stakeholder perspectives to validate and generalise the proposed sustainable value network model.

Managing business development related to the innovation of intelligent supply chains is an important task for many companies in the modern world. The study of management mechanisms, their content and interrelations of elements contributes to the optimization of business processes and improvement of efficiency. This article examines the experience of China in the context of the implementation of intelligent supply chains. The study uses the methods of thematic search and systematic literature review. The purpose of the article is to analyze current views on intelligent supply chain management and identify effective business management practices in this area. The analysis included publications devoted to various aspects of supply chain management, innovation, and the implementation of digital technologies. The main findings of the article are as follows: Firstly, the key elements of intelligent supply chain management mechanisms are identified, secondly, successful experiences are summarized and the main challenges that companies face in their implementation are identified. In addition, the article focuses on the gaps in research related to the analysis of successful experiences and the reasons for achieving them.

Food safety in supply chains remains a critical concern due to the complexity of global distribution networks. This study develops a conceptual framework to evaluate how food safety risks influence supply chain performance through predictive analytics. The framework identifies and minimizes food safety risks before they cause serious problems. The study examines the impact of food safety practices, supply chain transparency, and technological integration on adopting predictive analytics. To illustrate the complex dynamics of food safety and supply chain performance, the study presents supply chain transparency, technological integration, and food safety practices and procedures as independent variables and predictive analytics as a mediator. The results show that supply chain managers’ capacity to anticipate and control risks related to food safety can be improved by predictive analytics, leading to safer food production and distribution methods. The research recommends that businesses create scalable cloud-based predictive model solutions, combine data sources, and employ cutting-edge AI and machine learning tools. Companies should also note that strong, data-driven approaches to food safety require cooperative data sharing, regulatory compliance, training initiatives and ongoing improvement.

With its inherent characteristics of decentralization, immutability, and transparency, blockchain technology presents a promising opportunity to revolutionize the South African food supply chains. Blockchain technology, with its decentralized, immutable, and secure nature, offers solutions to these challenges by improving traceability and accountability across the supply chain. This study investigates the role of blockchain technology in enhancing transparency in the food supply chain among small and medium enterprises in South Africa. SMEs form a critical part of the country’s agri-food sector but face challenges such as food fraud, inefficient inventory management, and lack of transparency, which impact food safety and trust. The research adopts a mixed-method approach, utilizing the Technology-Organization-Environment framework and Institutional Theory to explain blockchain adoption among SMEs. The results demonstrate that blockchain-enabled practices, such as smart contracts, records traceability, production tracking, and distribution monitoring, significantly enhance supply chain transparency. The findings highlight blockchain’s potential to increase operational efficiency, regulatory compliance, and stakeholder trust. This research provides valuable insights for policymakers and practitioners, emphasizing the need for regulatory support and strategic investment in blockchain solutions to promote sustainability and competitiveness in the agri-food sector.