Artificial neural network for finances in MYPES according to internal factors in response to the demand of the Chancay Megaport.

Abstract

Abstract: This research aimed to evaluate the artificial neural network as a predictor of financial operations in MYPES according to internal factors, which allows meeting the demand of the Megaport located in Chancay-Perú 2024. Therefore, the dependent variable "Finance" was evaluated with its three dimensions (Profitability, Revenue Growth and Operational Efficiency) and the independent variable “Internal Factors” with its five dimensions (Sales Management, Production-Operation, Logistics, Market Analysis and Human Resources). A census sample of 107 MYPES from Huaral, Peru, was used and the data was analyzed using the STEM (Science, Technology, Engineering and Mathematics) method with SPSS 25, Risk Simulator versión 7.0 2023 and an Artificial Neural Network (ANN). The results reveal that the Sales Management and Human Resources variables are the most influential in the Finance of MYPES. Prospectively, the Neural Network predicts that there will be a financial collapse of 53.2% of MYPES due to the demand for the Chancay Megaport. In addition, a Logistics Regression equation was developed, with Finance=2.3859+0.0469SalesManagement+0.0128ProductionOperation+0.0165Logistics+0.0070MarketAnalysis+0.0341HumanResources, which explains Finance in MYPES, and the ANN predicted the financial collapse with an accuracy of 90.9%. In conclusion, Internal Factors, especially Sales Management and Human Resources, are critical for the financial stability of MYPES. Keywords: artificial neural network, finance, financial collapse, internal factors and Megaport.