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

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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Publication Details

Journal
Heritage and Sustainable Development ISSN 2712-0554
Published
2025-08-04
DOI
https://doi.org/10.37868/hsd.v7i2.1144
Primary Topic
Working Capital and Financial Performance
Type
article
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article

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

Edison Roberto Valencia Núñez, Freddy Armijos-Arcos, Karla Estefanía Morales-Ramos, Annette Solange Ocaña-Ortiz
Heritage and Sustainable Development ISSN 2712-0554
Working Capital and Financial Performance
article

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

Edison Roberto Valencia Núñez, Freddy Armijos-Arcos, Karla Estefanía Morales-Ramos, Annette Solange Ocaña-Ortiz
article en

Abstract

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.

Heritage and Sustainable Development ISSN 2712-0554Vol. 7(2)
Universidad Indoamérica (EC), Escuela Superior Politécnica del Chimborazo (EC), Universidad Técnica de Ambato (EC)
Openalex Percentile: Top 71%
Working Capital and Financial Performance
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Working capital management and financial economic performance of manufacturing SMEs: A PanelMix statistical model — Edison Roberto Valencia Núñez, Freddy Armijos-Arcos, et al. · Heritage and Sustainable Development ISSN 2712-0554 (2025) | TGRS Research Map | TGRS