Analysis of the efficiency and profitability of Ecuadorian manufacturing companies: An application of unsupervised algorithms
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Abstract
This research focuses on the analysis of the efficiency and profitability of Ecuadorian manufacturing companies using unsupervised clustering techniques. Through a methodological approach that includes algorithms such as K-means, DBSCAN, Hierachical Clustering, the companies of the different sub-branches were segmented into various clusters based on key financial variables such as profit margin, operating profit margin, return on assets (ROA), return on equity (ROE) and asset turnover.
The results reveal a high level of efficiency in the use of assets, however, for the most part, the clusters present profit margins close to zero, which suggests focusing attention on the cost structure. A notable finding is that some sub-branches of the manufacturing industry are in a transition stage, where they are beginning to show efficiency but have not yet reached levels of sustainable profitability, considering the reactivation of economic activities after the pandemic.
In addition, clusters with different characteristics were identified that allow understanding the market and opportunities for improvement through the formulation of public policies aimed at the sustainable development of the sector.
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