In recent times, there has been a growing interest in the role of food trade in achieving food security. This study presents a comprehensive analysis of the relationship between food trade and food security within the context of the Belt and Road Initiative (BRI). This study employs complex networks alongside the quadratic assignment procedure (QAP) regression method on trade data of 46 countries under BRI for the period 2008 to 2018. The resulting complex network showed an enhancement in the food trade relationships and food security levels after BRI, indicating a mutually positive effect. In addition, the closeness centrality measure showed a strong correlation with food security, indicating that food trade has positive spillovers on food security in the proximate countries. Using geographical distance as an instrumental variable, the QAP regression model proved the positive effects of food trade on food security. More investment in trade infrastructure is recommended to reduce the negative effect of geographical distance on food security.

This study analyzes the relationship between agricultural foreign direct investment (FDI) and food security on Belt and Road Initiative (BRI) countries in a panel framework over the period 2006–2015 using correlation analysis, the specific-effect model, and the 2SLS technique. The study aims to: first, analyze the correlation between agricultural FDI and food security for each country, individually; then, investigate whether there is a direct relationship, using the specific-effect model. Finally, by taking one step further, this study uses the 2SLS method to determine whether there is an indirect relationship through agricultural productivity. Our results show that the sampled countries have clear differences in the direction of the relationship between food security and agricultural FDI. But, in general, the agricultural FDI has a positive direct and indirect effect on food security; this effect is seen clearly when the country attracts agricultural FDIs steadily.

This study uses Bayesian networks besides the regression model to analyse the relationship between scholarship inflows and food security in 46 of Belt and Road Initiative countries. Our main contributions are: 1 – Analysing the relationship between scholarship inflows and food security. 2 – Using Bayesian networks to analyse this relationship. 3 – Comparing Bayesian networks results with regression model results. The regression model resulted that scholarship inflows have a significant positive effect on food security with small coefficient value. On the other hand, Bayesian networks showed that food security conditionally depends on scholarship inflows given the percentage of agricultural value add of GDP. In addition, Bayesian networks had higher prediction accuracy than the regression model. Whereas the constraint-based approach of network structure learning showed the highest prediction power, the information theory measures of network quality, including Entropy and Mutual Information, revealed better performance than Bayesian measures. Finally, we concluded that using Bayesian networks beside linear models could enhance our results.

This study investigates the impact of foreign capital inflow and the number of contracted foreign direct investment projects on urbanization. The study focused on the less-explored provinces of Liaoning, Jilin, and Heilongjiang, covering the period from 2007 to 2021. The definition of urbanization was expanded to include three elements: the urbanized labor force, emission and pollution levels, and the productivity of services in the economy. Most importantly, an urbanization index was generated to estimate the total effect of foreign capital investment on sustainable green urbanization. The analysis employs both random and fixed effects regression models, complemented by robustness checks using the generalized least squares (GLS) method. The findings indicate that while foreign capital investments contribute positively to labor urbanization and service productivity, they have a notably adverse impact on environmental quality in the examined cities. Moreover, our findings confirm an overall inverse relationship between foreign capital investment and the urbanization index: the negative impact is primarily driven by inadequate procedures for emissions control in the northeastern Chinese cities. In conclusion, this research provides insights and strategic recommendations for promoting sustainable green urbanization.

The Impact of Government Assistance to State-owned Enterprises on Foreign Start-ups: Evidence from Yangtze River Delta-New Foreign Firms, State-owned Enterprises, Core？periphery, Yangtze River Delta

The research presents Fuzzy set multi-criteria decision-making approach combined by Delphi method (ADM) to facilitate location decision. Whereas the preference ranking of alternatives importance of the criteria was obtained by (ADM) then obtained the right decision by applying Fuzzy set method. The applicability of the recommended methods was given on NAFFCO firefighting company location selection problem. The importance of this study is that it presented as followed: it is the first usage of the mixed methodologies in the area of location selection (Jiangsu province) that focusing on market size(MS), labor productivity(LP), knowledge(KN), and transportation(T) to facilitate location decision. Second the presented content of methodologies can be used to decide the important weight of the existed variables. Third, reduce the risks that can be faced in making the location decision to gain a fruitful location decision. Fourth, it can be used to facilitate location selection within unlimited locations and unlimited criteria.