Identificação e análise de fatores críticos de sucesso em projetos de bens de capital com tipologia "Engineering-to-order"

• Ano de defesa: 2011
• Autor(a) principal: Pacagnella Júnior, Antônio Carlos
• Orientador(a): Silva, Sérgio Luis da
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Produção - PPGEP
• País: BR
• Palavras-chave em Português: Engenharia de produção; Gestão de projetos; Estatística multivariada
• Palavras-chave em Inglês: Capital goods; Project management; Engineering-to-order; Critical success factors; Multivariate data analysis
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA DE PRODUCAO
• Link de acesso: https://repositorio.ufscar.br/handle/ufscar/3388

Projects of capital goods with Engineering-to-Order (ETO) productive typology are usually complex due to its size and level of customization and technology. Because of these aspects the achievement of success demands a management effort and can be conditioned by several elements, among which are the Critical Success Factors (CSF). In this sense, the proposal for this research involves the identification and analysis of the relationship of these factors with the success obtained in ETO projects using a multidimensional concept that involves efficiency, organizational learning, preparing for the future and customer satisfaction. From these principles a survey was conducted involving 67 companies and 182 projects with above characteristics. Data analysis was initially performed by the technique of Factorial analysis, whose results led to combine 38 Critical Success Factors identified in the literature on 12 new factors with better ability to explain the observed phenomenon, namely: Uncertainty management, Organization and Planning, Productivity management, Robustness of the team, Management of technical performance, Learning and adaptation, Integration with external stakeholders, Reliability of the team, Schedule optimization, Precaution against technical failures, Guidance capacity and Precaution against supply failure. These new factors led to an analysis by multinomial logistic regression technique, which identified significant factors to explain each of the success dimensions. For the efficiency dimension this factors are Planning and organization, Reliability of the team, the Guidance capacity, Integration with external stakeholders, the Technical performance management and Schedule optimization, to the extent organizational learning are the optimization schedule, Productivity management and Precaution against technical failure. To the preparing for the future dimension this factors are the Management of the technical performance, the Reliability of the team, Schedule optimization, the Precaution against technical failures, the Learning and adaptation, and the Organization and Planning, the Guidance capacity. For the customer satisfaction are the Reliability of the team, the Learning and adaptation, Precaution against failure of supply, Organization and planning, Precaution against technical failures and Contingency management. Thus, from a scientific standpoint, the results obtained in this thesis extends the understanding of the topic studied and provide from the managerial point of view a framework that can guide and support decision making by managers of this type of project.