The Brazilian Soybean Complex

Crop Production/Industries, Q13, O54, Q56, 013,

Global Shifts in Agro-Industrial Capital and the Case of Soybean Crushing: Implications for Managers and Policy Makers

Tremendous shifts are occurring in the location of agro-industrial capital around the globe. To focus discussion on this topic a session was convened at the annual meeting of the International Food and Agribusiness Management Association in Montreux, Switzerland in June of 2004. The session brought together researchers and industry leaders to better understand these dramatic shifts and the implications they hold for the agri-food system. The following article emerges from that session. The first part of the article provides the context for the discussion by looking at global shifts in soybean processing investment. The second part entails reaction by three industry panelists.Soybeans, Processing, Investment, Global strategy, Agribusiness, Agricultural and Food Policy,

On the topology of higher-order age-dependent random connection models

In this paper, we investigate the potential of the age-dependent random connection model (ADRCM) with the aim of representing higher-order networks. A key contribution of our work are probabilistic limit results in large domains. More precisely, we first prove that the higher-order degree distributions have a power-law tail. Second, we establish central limit theorems for the edge counts and Betti numbers of the ADRCM in the regime where the degree distribution is light tailed. Moreover, in the heavy-tailed regime, we prove that asymptotically, the recentered and suitably rescaled edge counts converge to a stable distribution. We also propose a modification of the ADRCM in the form of a thinning procedure that enables independent adjustment of the power-law exponents for vertex and edge degrees. To apply the derived theorems to finite networks, we conduct a simulation study illustrating that the power-law degree distribution exponents approach their theoretical limits for large networks. It also indicates that in the heavy-tailed regime, the limit distribution of the recentered and suitably rescaled Betti numbers is stable. We demonstrate the practical application of the theoretical results to real-world datasets by analyzing scientific collaboration networks based on data from arXiv.Comment: 28 page