Abstract
The growth of Mexican companies is measured by increasing sales, and some of their determinants are, according to the literature review, accounting and financial data such as total assets, financing alternatives, and profitability. We seek to know the weight of the evidence of each of the mentioned variables in order to identify if they are good predictors of growth. The applied methodology uses the weight of evidence and information value to rank variable importance. The most important variables are used to generate three different predictive models. Our results show that the main variables affecting growth are EBIT, consolidated net worth, and total assets. The best predictive model is artificial neural networks.
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Bernal-Domínguez, D., Vega-López, I.F. (2021). Analysis of Business Growth in Mexico Using Weight of Evidence. Period: 2008–2017. In: León-Castro, E., Blanco-Mesa, F., Gil-Lafuente, A.M., Merigó, J.M., Kacprzyk, J. (eds) Intelligent and Complex Systems in Economics and Business. Advances in Intelligent Systems and Computing, vol 1249. Springer, Cham. https://doi.org/10.1007/978-3-030-59191-5_8
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