The Evolution of Romanian Transportation Companies: Insights from Financial Data through a Machine Learning Approach

The financial data of the companies reflects their performance, presenting the evolution and stability of the organization. Transportation area represents one of the most important sectors in the Romanian economy, thanks to the expansion of commercial international exchanges which is developing significantly in the recent years, thanks to the government investments in the highways and railways, that optimized the routes and minimized the costs. Multiple studies suggested that the transportation sector evolved in a significant manner in Romania, road transportation having numerous advantages compared with other types of transportation. The focus of the present research is on the transportation companies, which are characterized from the point of view of location, date of establishment, and county, together with the financial data such as Net Profit, Liabilities, Turnover, Fixed Assets, Current Assets, Shareholders Equity and Average number of Employees. Using Power BI and Jupyter Notebook, an overview on the data is performed with the purpose of identifying patterns among the companies based on the county, average number of employees or date of establishment. Using Python programming language, statistical information of the selected companies has been explored, as well as the clusters formed based on the considered features. The outcome of the research could be useful for researchers, aiming to contribute to the investigated area by highlighting the importance of the transportation sector in the Romanian economy.