Modelagem sistêmica e prospecção de cenários para a cadeia etanol do Rio Grande do Sul

Abstract

Although the recognized expertise in the field of Brazil's ethanol production, Rio Grande do Sul, located in the southern region of the country, produces less than 1% of its domestic demand current reality that obliges the state to import ethanol from other states, committing so that resources could generate wealth and investments in the local economy. Added to this the interest of the State Government in developing this chain by 2016. Although this favorable scenario, a regional chain of ethanol does not demonstrate growth remaining in a condition embryo. The model of ethanol production in Rio Grande do Sul, unlike the agribusiness model applied in other Brazilian states, is based on the cooperative model in smallholder farming family. The study of a production chain of this important biofuel applied to a production model based on production units multi cultures and family labor production, offers a unique opportunity to generate knowledge about this model that can be applied to other regions and countries to present this particularity. The present work aims to contribute to this discussion by developing an understanding of the interrelationships of actors within this complex structure, through a study of dynamic systems as proposed by Sterman (2000) with a view to prospecting scenarios proposed by Van Der Heijden (2004). The study used a combination of literature research to collect qualitative and quantitative data obtained through documentary and bibliographical references, and two rounds of interviews. From the mental models identified in the interviews, we used the concepts of Sterman (2000) for construction of the system model chain. The work then converged to study scenarios where the systemic model served as the basis to simulate the influence of the driving forces contextual identifying impacts along the chain. The final product of this work is to analyze the behavior of the chain in respect of potential scenarios and additionally proposing actions to prepare the ethanol chain state to minimize the effects of possible events that can be predicted.