O uso da teoria de opções reais na avaliação de projetos de investimentos para implementação de sistemas ERP

• Ano de defesa: 2014
• Autor(a) principal: Souza, Márcio Barros
• Orientador(a): Basso, Leonardo Fernando Cruz
• Banca de defesa: Nakamura, Wilson Toshiro , Forte, Denis , Peleias, Ivam Ricardo
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Presbiteriana Mackenzie
• Programa de Pós-Graduação: Administração de Empresas
• Departamento: Administração
• País: BR
• Palavras-chave em Português: teoria de opções reais; ERP (Enterprise Resource Planning); programação estocástica; otimização
• Palavras-chave em Inglês: real options theory; ERP (Enterprise Resource Planning); stochastic programming; optimization
• Área do conhecimento CNPq: CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO::ADMINISTRACAO DE EMPRESAS
• Link de acesso: http://dspace.mackenzie.br/handle/10899/23224

The aim of this study was to develop an analytical model of full stochastic programming, grounded on the Real Options Theory (ROT) for the analysis of the value of the investment opportunity in project to implement Enterprise Resource Planning (ERP) system. The proposed model is a modified extension of Wu et al. (2008), incorporating the possibility of a catastrophic event (or contingent event), as discussed in Schwartz and Zozaya-Gorostiza (2003). While a programming and stochastic optimization model, it is inserted in the context of Operational Research, whose nature, as the name implies, is the use of analytical scientific method to address operational problems in organizations. The managerial flexibility of the model was treated as a real option, in which there is the right, but not the obligation, to perform an action (for instance, postpone, expand, contract or abandon. The strategic decision concerned the possibility of purchasing and implementing the system as a whole package or through modules. Revenue estimates for the project were modeled as a stochastic process of the Geometric Brownian Motion type, while costs were modeled as a function of the characteristics of each cash outflow type, resulting in the choice of a probability distribution. The model uses Latin hypercube simulation to obtain the expected values of the parameters for generating a decision tree that guides the optimization process. Given the parameters and constraints of the model, the optimization searches for the optimal investment decision. Considering the model configuration and parameters adopted, the figures indicate that the process of purchasing and implementing the modules result in an optimal decision for the value of the investment opportunity. Furthermore, the sensitivity analysis of the parameters allowed the identification of the most sensitive parameters in the model that need careful analysis, to avoid distortions in the projections.