Morales Ramos, Karla
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Morales Ramos, Karla
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Ambato

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Optimization of Working Capital for Financial Sustainability in Manufacturing Companies: A Statistical Model

2026 , Morales Ramos, Karla , Edison Roberto Valencia-Nuñez , Josselyn Paredes-León , Freddy Armijos-Arcos

Working capital management plays a critical role in ensuring business liquidity and financial sustainability. However, few studies in developing economies have employed multivariate statistical techniques to optimize working capital decisions. This study addresses this gap by applying discriminant analysis to classify Ecuadorian manufacturing firms according to their financial sustainability and business continuity. Methods: A quantitative approach was applied to a sample of 112 manufacturing companies located in Zone 3 of Ecuador, covering the 2017–2020 period. The model incorporated working capital indicators and the Z-Score index as independent variables, while company size served as the categorical dependent variable. Results: The discriminant function retained two significant predictors—Working Capital (2019) and Z-Score (2017)—with an eigenvalue of 0.191, a canonical correlation of 0.400, and an overall classification accuracy of 71.4%. Box’s M test (p = 0.000) indicated unequal covariance matrices, suggesting cautious interpretation but acceptable robustness of the model. Conclusions: This study concludes that working capital and Z-Score are effective indicators for assessing financial sustainability and predicting firm continuity. The findings provide practical insights for managers and policymakers to enhance financial efficiency and resource allocation. The originality of this work lies in the application of discriminant analysis to model financial sustainability in Ecuador’s manufacturing sector, offering a statistical foundation for future optimization models.

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Sustainability models in Zone 3 manufacturing SMEs

2025 , Morales Ramos, Karla , Pamela de Los Ángeles Sánchez Rosero , Christian Alberto López Valencia , Freddy Marco Armijos Arcos

In this research, the objective was to determine the optimal financial sustainability model for manufacturing SMEs in zone 3 for the years 2017 - 2020. For the development of the study, 107 medium and small companies that met the requirements of complete information obtained from the Superintendence of Companies, Securities, and Insurance were taken into account. Observation sheets were used to classify the information in the financial statements and allow understanding of their financial situation by applying the solvency prediction models, Z-Altman, Springate, Fulmer, and CA-Score. In the analysis of the financial indicators of manufacturing, SMEs evidenced a strong correlation with their financial sustainability, especially in the year 2019. A comparative analysis of the effectiveness of the four models of financial sustainability is made, for the selection of the most optimal model. In addition, a SWOT analysis was performed in order to identify the strengths and weaknesses of each of them, so, it is revealed that the most optimal and reliable model is Springate, due to its multidimensional approach, adaptability for manufacturing SMEs, simplicity and ability to provide a clear and truthful score. However, it is always advisable to consider the specific context of other models to each company.

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Working capital management and financial economic performance of manufacturing SMEs: A PanelMix statistical model

2025 , Morales Ramos, Karla , Edison Roberto Valencia-Nuñez , Annette Solange Ocaña-Ortiz , Freddy Marco Armijos-Arcos

The present research aimed to determine the economic-financial performance and working capital for capital management of manufacturing SMEs in Zone 3 during the period 2017-2020. So, using a descriptive-explanatory approach, secondary data from the Superintendence of Companies were analyzed. In the first instance, an initial sample of 112 companies was considered; however, they did not meet the requirements to carry out this study. Therefore, under purely appropriate criteria, the sample was reduced to 92 companies. In addition, the study incorporated three control variables, which were the components of the ROE indicator, such as net margin, asset turnover, and financial leverage, essential to carry out the panel data methodology. Therefore, using SPSS software, frequency tables, measures of central tendency, and dispersion were generated, which made it possible to evaluate the behavior of the DuPont index and working capital during the aforementioned period. In addition, a panel data model was incorporated, where the results showed that the approach that best suited the conditions of this research was by fixed effects, demonstrating that the control variables were significant, except for the main variable contemplated as working capital, concluding that it does not have a major impact on the profitability of a company.

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