Aprimoramento de modelo de regressão linear para precificação e investimentos imobiliários em Fortaleza - Siebra, Nélio Vitor Alves (2024)
The study investigates the enhancement of a linear regression model for real estate pricing and investment in Fortaleza, Ceará, addressing recent economic and social transformations, particularly after the COVID-19 pandemic. The research proposes the inclusion of new social and economic variables into the traditional model, such as quality of life, public transportation accessibility, proximity to green areas, and internet infrastructure, aiming to better reflect current market demands. Using data from major real estate companies operating in the city and the Civil Construction Industry Union of Ceará (Sinduscon-CE) between 2020 and 2024, the study seeks to update and enrich real estate valuation practices. Additionally, this work analyzes the presence of Competitive Intelligence (CI) as a strategic tool, enabling companies to anticipate trends, identify opportunities, and mitigate risks in the regional sector. The results reveal a significant increase in property values in Fortaleza, particularly in 2023, driven by factors such as infrastructure investments and demand for high-end properties. However, a slight decline observed in 2024 suggests a potential market correction or stabilization. The enhanced model aims not only to improve pricing accuracy but also to provide strategic insights for decision-making. Ultimately, the research contributes to increasing the competitiveness of companies in the local real estate market by proposing a more robust model aligned with the contemporary needs of Fortaleza's real estate sector, with practical implications for investors and industry professionals.