Advancing models for accurate estimation of food production is essential for policymaking and managing national plans of action for food security. This research proposes two machine learning models for the prediction of food production. The adaptive network-based fuzzy inference system (ANFIS) and multilayer perceptron (MLP) methods are used to advance the prediction models. In the present study, two variables of livestock production and agricultural production were considered as the source of food production. Three variables were used to evaluate livestock production, namely livestock yield, live animals, and animal slaughtered, and two variables were used to assess agricultural production, namely agricultural production yields and losses. Iran was selected as the case study of the current study. Therefore, time-series data related to livestock and agricultural productions in Iran from 1961 to 2017 have been collected from the FAOSTAT database. First, 70% of this data was used to train ANFIS and MLP, and the remaining 30% of the data was used to test the models. The results disclosed that the ANFIS model with generalized bell-shaped (Gbell) built-in membership functions has the lowest error level in predicting food production. The findings of this study provide a suitable tool for policymakers who can use this model and predict the future of food production to provide a proper plan for the future of food security and food supply for the next generations.

The Russian–Ukrainian conflict has been proven to cause significant losses of life and goods on both sides. This may have potentially impacted the agricultural sector. This study examines the impact of the conflict between Russia and Ukraine on the global food situation. We performed a descriptive analysis and literature review to answer this objective. Russia and Ukraine play essential roles in world food production and trade. However, the war has disrupted food production in Ukraine. Estimated Ukrainian wheat, soybean, and maize production in 2022–2023 fell precipitously. On the other hand, Russian production of these three food products shows positive growth during the same period. Furthermore, the global supply chain and food trade are hampered, causing an increase in the world’s food prices. From March to May 2022, the average global price of wheat, soybeans, and maize increased dramatically compared to during and before the COVID-19 pandemic. Finally, this poses a danger to global food security, particularly for low-income countries that depend heavily on food imports from both countries. Therefore, all countries must be prepared for the possibility that the Sustainable Development Goals cannot be achieved.

Until recently, many countries’ policies were motivated by economic growth; however, few strategies were developed to prevent environmental deterioration including reducing the ecological footprint. In this context, the purpose of this study was to analyze the role of natural resource rents, technological innovation, and financial development on the ecological footprint in 90 Belt and Road Initiative (BRI) economies. This research divided the BRI economies into high income, middle-income, and low-income levels to capture income differences. This research used the second-generation panel unit root, cointegration, and augmented mean group estimators to calculate the robust and reliable outcomes. Based on the annual data from 1991 to 2018, the findings show that natural resource rents drastically damage the quality of the environment, whereas technological innovations are helpful in reducing ecological footprint. Moreover, the outcome of the interaction term (natural resource rents and technological innovations) negatively impacts the ecological footprint. Interestingly, these findings were similar in the three income groups. In addition, financial development improved environmental quality in the middle-income BRI economies, but reduced it in high-income, low-income, and full sample countries. Furthermore, the Environmental Kuznets Curve (EKC) concept has been validated across all BRI economies. Policymakers in BRI countries should move resources away from resource-rich sectors of industries/manufacturing sectors to enhance/promote economic growth and use these NRRs efficiently for a progressive, sustainable environment. Based on these findings, several efficient policy suggestions are proposed.

The aim of this paper is to identify and analyze the four core driving forces that shaped the complex picture of rural tourist businesses. These driving forces are marketability, participatory, crisis mitigation and sustainability. This study focused on the scholarly perspective to study and analyze the rural tourism businesses’ literature and its link with these four driving forces. By using the bibliometric analysis technique and VosViewer as a visualization tool, the results revealed that less than 50% of rural tourism literature was concerned with local businesses. Regarding the four driving forces, sustainability was the most linked force with the rural tourism businesses’ scientific production. Contrarily, a relatively small body of the rural tourism businesses’ literature discussed marketability, participatory and crisis mitigation, despite their significant role in the development of these local rural businesses. In addition, the results of this study showed the interest of rural tourism articles in the crisis mitigation pillar, especially recently after the COVID-19 pandemic.

Organic farming is functionally integrated and serves as the foundation for circular agriculture. It guarantees resource efficiency in the deployment of nature-based initiatives to mitigate climate change. Organic farming is the most cost-efficient strategy for fighting climate change. Primarily the intensive generation of waste due to strong urbanization effects, the expression of consumer response is particularly powerful while purchasing organic items. This analysis’s major purpose is to examine which various aspects may be applied to consumers’ perspectives towards circular agriculture when buying organic foods. In this research, a well-constructed questionnaire was produced. Of the 1030 participants who participated in the survey, 1001 samples were examined. The major study question was, “Would the customer purchase organic food product that is good environment?” The second issue is, how do eco-label foods, knowledge about climate change, consumer education, and specific socio-demographic features impact the value of organic food consumption? According to the study’s findings, in the case of the studied customers, people’s concerns about climate change, trust, and eco-labels demonstrate a stronger preference for purchasing organic food. It is also a surprise that customer trust has a big effect on consumer buying intention. The new scientific result of the research is that, in the case of emerging countries, due to the significantly lower price level difference between organic products and traditional foods, the healthy properties of foods with an eco-label, as well as the communication of knowledge about climate change, have a significant effect on the level of consumption of organic foods.

Climate change is undeniably one of the long-term challenges confronting humanity across the globe. Various nations have taken initiatives that help reduce greenhouse gas emissions to the environment as well as accelerate financial flows to clean and sustainable projects. The paper provides an overview of green finance after the Paris Agreement by adopting a bibliometric analysis of the selected literature. The study reviewed the literature from the Web of Science database between 2015 and 2022. Data cleaning, formatting, and analysis was performed using VOSviewer and R-studio. Our study indicates increased scholarly interest on the issue of green financing. Most scientific research has been published in climate policy and sustainability journals but lacks mainstream interest in economic and finance journals. Based on our results, it is recommended that further studies on green financing be carried out from the economic and financial perspective using quantitative approaches to supplement the existing literature and provide a wider view to policy makers and regulators.