The stability of food supply chains is crucial to the food security of people around the world. Since the beginning of 2020, this stability has been undergoing one of the most vigorous pressure tests ever due to the COVID-19 outbreak. From a mere health issue, the pandemic has turned into an economic threat to food security globally in the forms of lockdowns, economic decline, food trade restrictions, and rising food inflation. It is safe to assume that the novel health crisis has badly struck the least developed and developing economies, where people are particularly vulnerable to hunger and malnutrition. However, due to the recency of the COVID-19 problem, the impacts of macroeconomic fluctuations on food insecurity have remained scantily explored. In this study, the authors attempted to bridge this gap by revealing interactions between the food security status of people and the dynamics of COVID-19 cases, food trade, food inflation, and currency volatilities. The study was performed in the cases of 45 developing economies distributed to three groups by the level of income. The consecutive application of the autoregressive distributed lag method, Yamamoto’s causality test, and variance decomposition analysis allowed the authors to find the food insecurity effects of COVID-19 to be more perceptible in upper-middle-income economies than in the least developed countries. In the latter, food security risks attributed to the emergence of the health crisis were mainly related to economic access to adequate food supply (food inflation), whereas in higher-income developing economies, availability-sided food security risks (food trade restrictions and currency depreciation) were more prevalent. The approach presented in this paper contributes to the establishment of a methodology framework that may equip decision-makers with up-to-date estimations of health crisis effects on economic parameters of food availability and access to staples in food-insecure communities.

For a long time, the majority of China, which has the world’s largest population, has been immobile and lived in rural areas. However, over recent decades, with the economic rise of China, rural labor has demonstrated a trend of moving to rapidly industrializing regions in search of higher income and better employment opportunities. Along with the labor cutback, out-migration introduces negatives to the sustainable development of rural areas, i.e., depopulation, the abandonment of rural settlements and agricultural lands, and the aging of the population, among others. Due to the threats of labor outflow to sustainability, studying the causes of China’s rural out-migration can reveal lessons on how state policies can be designed to reduce the negative impacts of out-migration on rural communities. The purpose of this paper is to identify the major causes of migration movements among the rural areas of northern China that are considered to be the best-performing among the provinces of the country in terms of rural development, agricultural production, and the wealth of rural dwellers. A two-stage survey of a panel of experts involved: (1) respondents representing government officials and universities of the Heilongjiang, Jilin, and Liaoning provinces and the Inner Mongolia Autonomous Region, and (2) regional and district levels of administration, and research and public establishments of Heilongjiang Province. In stage three, drawing on the authors’ own survey of 128 rural households in three counties of Heilongjiang Province, the major migration drivers have been identified, and the portfolio of a typical rural migrant has been developed. Some of the key findings are that migration intentions are fueled by the rural–urban income gap, poverty, a reduction of demand for labor in rural areas, underdeveloped infrastructure, the low quality of social services in rural settlements, and the low social standing of rural dwellers. The approach allows monitoring the dynamics of migration attitudes as responses to the policy interventions that are aimed at the sustainable development of rural areas.

Over the past decades, both the quantity and quality of food supply for millions of people have improved substantially in the course of economic growth across the developing world. However, the number of undernourished people has resumed growth in the 2010s amid food supply disruptions, economic slowdowns, and protectionist restrictions to agricultural trade. Having been common to most nations, these challenges to the food security status of the population still vary depending on the level of economic development and national income of individual countries. In order to explore the long-run determinants of food supply transformations, this study employs five-stage multiple regression analysis to identify the strengths and directions of effects of agricultural production parameters, income level, price indices, food trade, and currency exchange on supply of calories, proteins, and fats across 11 groups of agricultural products in 1980–2018. To address the diversity of effects across developing nations, the study includes 99 countries of Asia, Europe, Latin America, the Middle East, and Africa categorized as low-income, lower-middle-income, and upper-middle-income economies. It is found that in low-income countries, food supply parameters are more strongly affected by production factors compared to economic and trade variables. The effect of economic factors on the food supply of higher-value food products, such as meat and dairy products, fruit, and vegetables, increases with the rise in the level of income, but it stays marginal for staples in all three groups of countries. The influence of trade factors on food supply is stronger compared to production and economic parameters in import-dependent economies irrelevant of the gross national income per capita. The approach presented in this paper contributes to the research on how food supply patterns and their determinants evolve in the course of economic transformations in low-income countries.

The scarcity of water resources, climate change, and water-wasting behavior have contributed to a worsening water crisis in many countries. This has raised concerns among farmers and increased pressure on governments. Digital technologies provide effective solutions to reduce resource waste; therefore, exploring farmers’ willingness to implement water-smart farming technologies to reduce waste, especially in developing countries, requires further analysis. To address this gap, this paper aims to investigate the factors that influence farmers’ intention to minimize water waste in Algeria. The theory of planned behavior was extended with the constructs of perceived usefulness of water-smart farming and knowledge of water waste reduction. Primary data were collected from 202 farmers to test the model. The empirical evidence suggests that attitudes, knowledge about water waste reduction, perceived usefulness, and perceived behavioral control significantly predict farmers’ intention to reduce waste. These factors explained 54.6% of the variation in intention. However, social influence was not found to be a significant antecedent of intentions. This paper’s findings can provide useful insights for various stakeholders on how to encourage farmers to reduce water waste and offer guidance on strategies for achieving sustainability in agriculture.

Improving the performance and economic sustainability of agricultural producers requires the integration of many dimensions, one of which is logistics. Establishing efficient and cost-effective transportation is a key element of establishing sustainable linkages along food supply chains between farmers, storage and transport companies, and consumers. In this regard, infrastructural constraints to sustainability in agricultural production exacerbate transportation costs and risks, and thus result in lower performance of agricultural producers. As fuel consumption is, first, the most significant cost in agricultural logistics and, second, particularly sensitive to disruptions of transport, loading, and storage infrastructure, management of fuel costs is crucial to assure profit margin of an agricultural enterprise. By transforming the standard economic order quantity (EOQ) model, the authors attempt to build an approach to the optimization of fuel costs. The analysis made in the cases of twelve large crop farms in three territories of Southern Russia allowed the consideration of: (1) fragmentation in storage infrastructure; (2) variations in fuel consumption depending on the vehicle load ratio; (3) the use of their own fleet of vehicles against the outsourcing of transport operations. The authors find that the tactics of optimization of fuel costs vary depending on the location of a farm in relation to grain storage facilities. Particularly, the farms located in areas of high concentration of storage facilities benefit from using their own fleet of vehicles, while those experiencing longer distances of transportation should outsource the performance of logistics operations to third parties. To overcome a site-specific nature, the transformed EOQ model should accommodate country-specific requirements, specifically, the level of fragmentation of transport and storage infrastructure, average distance of transportation from a farm to receival site, and average fuel consumption rates depending on the types of trucks commonly used by farmers. The key recommendation is that sustainability-aimed management of logistics costs should consider combining the operation of trucks by a farm with the outsourcing of transportation operations to address the fragmentation of transport and storage infrastructure.

Fisheries has always played a vital role in supporting livelihoods and ensuring food security and sustainable economic and social development in Southeast Asia. Historically, rural and coastal communities across the region have heavily relied on the fish trade as an indispensable source of income and employment. With the establishment of the Regional Comprehensive Economic Partnership (RCEP) between Association of Southeast Asian Nations (ASEAN) economies and large fish traders like China, Japan, South Korea, Australia, and New Zealand, there is a threat for smaller countries to lose competitive advantages in the regional market. By studying bilateral trade flows between fifteen RCEP members in 2010–2019 and matching indicative untapped trade potentials (ITP method) with revealed comparative (RCA method), relative trade (RTA method), and competitive (Lafay index) advantages across 210 pairs of countries, the authors found substantial misbalances between potential values of country-to-country trade and actual advantages of RCEP economies. To optimize gains from intraregional trade for both smaller and larger RCEP members, this study identified advantageous and disadvantageous trading destinations and product categories for individual countries. The recommendations were then generalized along the four groups of economies based on their level of income, contribution to overall RCEP trade in fish, and the share of fishery products in the national trade turnover. From a practical side, the study adds to the knowledge about the fish trade in Asia by detailing how countries can better utilize individual combinations of advantages. From a methodological side, the approach can be employed widely outside the RCEP to establish a reliable picture of potential gains or losses of a particular country in trade with its counterparts across varied sets of competitive advantages.