Inovações tecnológicas e a complexidade do sistema econômico / / Carolina Marchiori Bezerra.

• VerfasserIn: Bezerra, Carolina Marchiori,
• Place / Publishing House: São Paulo, Brazil : : Editora UNESP,, 2010.
• Year of Publication: 2010
• Language: Portuguese
• Physical Description: 1 online resource (122 pages) :; digital, PDF file(s).

The objective of this work is to analyze how the process of technological innovations is treated by the Theory of Complex Systems. The traditional neoclassical approach, based on very restrictive assumptions about agents and markets, is unable to provide plausible explanations for the various economic problems in real life. By disregarding the dynamics of economic phenomena, this approach was unable to incorporate aspects of the process of innovation and technological change. The evolutionary approach, in this sense, when considering the limited rationality, uncertainty and heterogeneity present in environments that exhibit innovation, was able to provide a treatment closer to reality. The innovation is, then, understood as a discontinuous change that alters the structural conditions generating development, progress and evolution in the system. The approach of complex systems, on the other hand, by presenting a non-reductionist framework and based on an evolutionary and systemic perspective, conceives the economy as a system composed of heterogeneous agents that interact with each other. Despite the environment of uncertainty in the decisions made, the agents try to adapt to the information received from the environment and to organize themselves, thereby generating new patterns of self-ordering and emerging structures. The modeling, in this sense, has as main objective to discover the emergent properties resulting from the interaction between the agents in the system. Finally, the conclusion is reached that technological innovations have presented more satisfactory and more consistent results when analyzed within this agent-based perspective. presenting a non-reductionist framework that is based on an evolutionary and systemic perspective, it conceives the economy as a system composed of heterogeneous agents that interact with each other. Despite the environment of uncertainty in the decisions made, the agents try to adapt to the information received from the environment and to organize themselves, thereby generating new patterns of self-ordering and emerging structures. The modeling, in this sense, has as main objective to discover the emergent properties resulting from the interaction between the agents in the system. Finally, the conclusion is reached that technological innovations have presented more satisfactory and more consistent results when analyzed within this agent-based perspective. presenting a non-reductionist framework that is based on an evolutionary and systemic perspective, it conceives the economy as a system composed of heterogeneous agents that interact with each other. Despite the environment of uncertainty in the decisions made, the agents try to adapt to the information received from the environment and to organize themselves, thereby generating new patterns of self-ordering and emerging structures. The modeling, in this sense, has as main objective to discover the emergent properties resulting from the interaction between the agents in the system. Finally, the conclusion is reached that technological innovations have presented more satisfactory and more consistent results when analyzed within this agent-based perspective. conceives the economy as a system composed of heterogeneous agents that interact with each other. Despite the environment of uncertainty in the decisions made, the agents try to adapt to the information received from the environment and to organize themselves, thereby generating new patterns of self-ordering and emerging structures. The modeling, in this sense, has as main objective to discover the emergent properties resulting from the interaction between the agents in the system. Finally, the conclusion is reached that technological innovations have presented more satisfactory and more consistent results when analyzed within this agent-based perspective. conceives the economy as a system composed of heterogeneous agents that interact with each other. Despite the environment of uncertainty in the decisions made, the agents try to adapt to the information received from the environment and to organize themselves, thereby generating new patterns of self-ordering and emerging structures. The modeling, in this sense, has as main objective to discover the emergent properties resulting from the interaction between the agents in the system. Finally, the conclusion is reached that technological innovations have presented more satisfactory and more consistent results when analyzed within this agent-based perspective. agents seek to adapt to the information received from the environment and self-organize, thereby generating new patterns of self-organization and emerging structures. Modeling, in this sense, has as main objective to discover the emergent properties resulting from the interaction between agents in the system. Finally, the conclusion is reached that technological innovations have presented more satisfactory and more consistent results when analyzed within this agent-based perspective. agents seek to adapt to the information received from the environment and self-organize, thereby generating new patterns of self-organization and emerging structures. The modeling, in this sense, has as main objective to discover the emergent properties resulting from the interaction between the agents in the system. Finally, the conclusion is reached that technological innovations have presented more satisfactory and more consistent results when analyzed within this agent-based perspective.