Importação de bens de capital: melhorias operacionais por meio de soluções digitais

Abstract

This dissertation investigates how digital solutions improve capital goods import processes in Brazil, as well as the challenges faced by importers. The methodology used was a qualitative, exploratory, and inductive approach, based on a literature review and semi-structured interviews with importers, exporters, and digital solutions experts. The data were analyzed using content analysis. The results reveal that the adoption of digital solutions, such as Blockchain, Machine Learning (ML), Big Data Analytics (BDA), and logistics simulation platforms, increases the efficiency of import processes, reducing costs and operational errors, optimizing customs clearance, and promoting integration among stakeholders in the logistics chain. Furthermore, these technologies strengthen real-time decision-making and increase companies' competitiveness in the international arena. This work contributes to the advancement of knowledge about the integration between capital goods imports and digital transformation in the context of international logistics. The academic advance concerns the proposal of a list of theoretical recommendations that relate the main challenges of importing capital goods to emerging digital solutions, providing support for future research. The managerial contribution concerns the identification of practices and tools that can be implemented to improve the operational, strategic, and technological management of importing companies.