The importance of this research stems from the need to ensure the sustainability of cross-border cooperation through a better understanding of its determinants and causal relationships. While having common features and patterns, cross-border cooperation is always expressed through the relations of specific countries and peoples. Therefore, based upon the PLS-SEM methodology, the authors consider the fundamental factors influencing the external cooperation of Hungary’s transboundary regions. The advantage of the PLS-SEM method is that it enables researchers to simultaneously identify and approximate hidden connections between input data and to construct a regression model describing the relationship between input data. Despite widespread application in economic studies, the authors have not found the use of PLS-SEM for studying cross-border cooperation issues in the current scientific literature. The authors have built a model to assess the hidden factors of cross-border cooperation and to identify the indirect influence of certain factors. The novelty of the research is to identify the determinants of sustainable cross-border cooperation and the relationship between them in a multi-level system of cross-border interaction between businesses, people, and the State. In the Hungarian context, transport infrastructure and business travel are shown to have a direct positive impact on cross-border cooperation. For the first time, tourism and socio-economic conditions have been shown to have powerful but indirect impacts. This work could be the beginning of gathering new evidence on the determinants and causation of cross-border cooperation in the context of other countries. An important finding of the study is the growing importance of indicators of the new, post-industrial economy. As for recommendations, the authors focus on state, regional, and municipal support measures, awareness of the possibilities of cross-border cooperation, the need to develop e-commerce, and alternative energy as a modern basis for converting Hungary’s cross-border position into a competitive advantage.

This study examines the potential of grain trade within the context of global commerce, highlighting its role as a primary component of the worldwide agricultural market and a crucial factor in ensuring global food security and price stability. To achieve the research objectives, we utilized panel data from Russia, a leading player in the grain market, and employed a gravity model along with Poisson pseudo-maximum likelihood (PPML) to analyze the impact of demand factors and the economic openness of importing countries, as well as the effects of distance, sea access, borders, language, trade unions, and tariffs on exports. Our research challenges the notion that an increase in the wealth of countries leads to a corresponding rise in trade between them. In the case of grain, evidence indicates a negative contribution of GDP per capita in importing countries. The gravity model and PPML enabled us to assess individual country effects and quantitatively evaluate the potential for increasing Russian grain exports to Asian and African nations. We propose recommendations for enhancing domestic grain production and improving the effectiveness of marketing strategies in countries with underutilized export potential.