Market share analysis and demand forecasting for the imported equipment to the healthcare market

• Autor(a) principal: Silva, Reginaldo Pereira da
• Data de Publicação: 2022
• Outros Autores: Galegale, Napoleão Verardi
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/29055
• topic: Ensino; Equipamentos médico-hospitalares; Dados governamentais abertos; Market share; Machine learning; Data analytics; Sistemas produtivos.; Enseñanza; Equipos medico-hospitalares; Datos Governamentales abiertos; Market share; Machine learning; Data analytics; Sistemas productivos.; Teaching; Medical products; Open government data; Market share; Machine learning; Data analytics; Productive systems.

Understand the market economic behaviors of a market or a specific segment requires innumerous processes, which goes from each source of data capture, technological standardization. From the data format on the origin to the consolidation itself, its homogenization and even in the enrichment that can transform it into market information, as well as gauge the demand and adequate levels of inventories. The current work aims to develop a prototype and present it as a computational solution based on Machine Learning algorithms, which allows determining the Market Share of the equipment industries imported to the health market in Brazil as well as improving demand management and inventory of these productive systems. The nature of the object of this research is Design Science Research (DSR) to produce the referred prototype, which was developed based on the requirements raised through a field study with companies that import hospital medical equipment. The database was obtained through open government data (DGA) on product imports, available on the website of the Brazilian government website, using Robotic Process Automation (RPA) resources. The prototype presented as results: 90% accuracy in the calculation of Market Share, and a R2 factor in the simple linear regression of 0.97 in the demand forecast, for an estimated market growth of 50%.