Mensuração da capacidade absortiva mediante conjuntos fuzzy: uma aplicação para a indústria de transformação com dados da PINTEC

• Autor(a) principal: Silva, Uxi Maia da
• Data de Publicação: 2018
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Manancial - Repositório Digital da UFSM
• dARK ID: ark:/26339/0013000000c94
• Texto Completo: http://repositorio.ufsm.br/handle/1/15915
• topic: Capacidade absortiva; Conjuntos fuzzy; Inovação; Economia do conhecimento; PINTEC; Absorptive capacity; Fuzzy sets; Innovation; Knowledge economy; CNPQ::CIENCIAS SOCIAIS APLICADAS::ECONOMIA

This research presents a study on the absorptive capacity within the firm. Therefore, it is based on the conceptual analysis of the neo-Schumpeterian firm to understand the relationship between technological knowledge and innovation in a dynamic competitive environment. From this approach the absorptive capacity is considered as a dynamic capacity. In this context, the relationships between innovation, learning, productive skills and interaction in an environment with rapid technological changes can develop the capacity for the firm to absorb new knowledge and, if this happens, it will help in identifying new technological opportunities and trajectories, increasing its innovative capacity and, consequently, its market performance. In this sense, to measure the absorptive capacity, two methods of fuzzy sets are proposed, one of comparative analysis of causal combinations and the other by means of an inference system. Thus, the methods fsQCA and the Mamdani system are presented to measure a set of antecedent data, through fuzzy logic and "If ... Then" rules, which result in a set of consequential dimensions of the absorptive capacity. In order to test the operability of the measurement propositions, the Mamdani system of inference was applied in the analysis of data from the Innovation Survey (PINTEC) for the Brazilian manufacturing industry for the years 2011 and 2014. With this procedure it was possible to measure the absorptive capacity for the 24 sectors of the manufacturing industry in terms of low, medium and high capacity, with values between 0 for no absorptive capacity and 1 for total absorption capacity. The results indicated that the textile manufacturing sector had the highest absorptive capacity for the analyzed period, this means that this sector has a combination of potential and realized capacities that allows a high absorption of new knowledge aimed at innovation.