This research explores the role of digital economy in driving agricultural development in the BIMSTEC region, which includes Thailand, Myanmar, Sri Lanka, Nepal, India, Bangladesh and Bhutan (with Bhutan excluded due to data limitations) with a particular focus on mobile technologies, computing capacity and internet connectivity which were the most readily available data points for BIMSTEC. Using a combination of document analysis, and panel data analysis with the data covering 10 years (2012–2021), the study examines the interplay of key digital technologies with agricultural growth while controlling for factors including water usage, fertilizer consumption, and land temperature and agricultural land area. The analysis incorporates additional variables such as infrastructure development, credit to agriculture, investment in agricultural research, and education level. The findings reveal a strong positive correlation between mobile technology, Internet and computing capacity in BIMSTEC. This study underscores that digital tools are pivotal in enhancing agricultural productivity, yet their impact is significantly combined with investment in infrastructure and education. This study suggests that digital solutions, when strategically integrated with broader socio-economic factors can effectively challenges in developing countries, particularly in rural and underserved regions. This research contributes to the growing body of literature on digital economy in agriculture, highlighting how digital technologies can foster agricultural productivity in developing countries.

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.

In the context of globalization and urbanization, rural development faces many challenges, such as population loss and uneven distribution of resources. This paper analyzes the similarities and differences in sustainable rural development strategies between China and Europe through a comparative perspective. China has optimized land use by relying on land policy innovations, such as the household contract responsibility system and the “separation of three rights”, as well as the construction of small towns; while Europe focuses on private ownership and market mechanisms, and supports agricultural and rural development through the Common Agricultural Policy (CAP). Using literature review, comparative research and policy analysis, the study shows that the policy innovations in China and Europe, each with its own focus, have been effective in promoting agricultural output and rural social development. Particularly noteworthy is that the “three rights” policy has increased agricultural productivity through the liberalization of management rights, while the European CAP has contributed to the diversification of the rural economy and environmental protection through continuous reforms. This study emphasizes that through policy innovation and international cooperation, combining the strengths of China and Europe, it is possible to provide a new model of sustainable development for the global countryside. Specifically, through the establishment of Sino-European R&D centers for agricultural science and technology, exchange of talents, and cooperation in green infrastructure development, technology transfer and application can be accelerated, cultural exchange and understanding can be promoted, and the sustainable development agenda for global rural areas can be jointly advanced.

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. 

Farm households in developing countries are often involved in a variety of livelihood income-generating activities to achieve basic needs and enhance food security. However, little attention has been given to investigating the effect of livelihood diversification strategies on the adoption of agricultural land management practices. This study explored the nexus between livelihood diversification and Agricultural Land Management (ALM) practices in the Southern Ethiopian Highlands. Data for this study were gathered through a structured questionnaire, interviews, and focus group discussions. A total of 423 sample respondents were selected by using multistage random sampling techniques. The data were analyzed using the Inverse Herfindahl Hirschman Diversity Index (IHHDI), the multinomial logit model (MNL), and the probit regression model. The findings of the study revealed that on-farm income activities are the most dominant livelihood income strategies (69.1%), followed by non-farm (21%) and off-farm (9.64%). The multinomial logit model analysis demonstrated that variables such as sex, education, family size, distance to market, land size, extension contact, membership in cooperatives, and household income were the major drivers of farmers income diversification activities (p<0.05). The results of the probit analysis indicated that income from crop production, daily labor work, rents from farmland, and farm assets have a positive and significant effect on households' decisions to implement ALM practices. In contrast, incomes from remittance and migrant sources have a negative but statistically significant impact on the adoption of ALM measures. The farm household sources of income-generating strategies substantially affected the adoption intensity of ALM measures. Income generated from the on-farm sector alone cannot be considered a core income-generating activity for households or a means of achieving food security. Therefore, land management policies and program implementations should consider farmers’ livelihood diversification and income-generating strategies. In addition, such interventions need to promote sustainable farming practices, enhance innovation, and related measures for the adoption of ALM measures to ensure land sustainability.