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

Chávez-Zavaleta R.; Azabache-Rojas M.G.; Medina-Ordoñez L.G.D.; Leon-Julca M.A.; Ochoa-Cuartas B.P.; Palomino-Tiznado M.D.; Cáceda-Farfán A.R. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2024) · DOI: 10.18687/laccei2024.1.1.1569

Resumen

This research aimed to evaluate the Artificial Neural Network as a predictor of financial operations in MYPES according to internal factors, which allowed meeting the demand of the Mega port located in Chancay-Perú 2024.Consequently, the dependent variable “Finance” 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 for data analysis.The research was of an applied type, non-experimental design, predictive level, with a qualitative approach to describe the study variables and the STEM (Science, Technology, Engineering and Mathematics) methodology was applied, in conjunction with the Risk Simulator software version 7.0 2023 to carry out logistic regression.In addition, IBM SPSS Statistics 25.0 was used to perform Multilayer Artificial Neural Network (ANN-MLP) in data analysis.The results reveal that the Sales Management (X1) and Human Resources (X5) dimensions are the most influential in the Finances of MYPES.Prospectively, the (RNA-MLP) predicts that there will be a financial collapse of 53.2% of the MYPES due to the demand for the Mega port of Chancay.In addition, a Logistics Regression equation was developed, with Finance=2.3859+0.0469SalesManagement+0.0128ProductionOper ation+0.0165Logistics+0.0070MarketAnalysis+0.0341HumanResou rces, which explains Finance in MYPES, and the (RNA-MLP) predicted the financial collapse with an accuracy of 90.9%.In conclusion, Internal Factors, X1 and X5, are critical for the financial stability of MYPES.

Instituciones: Universidad Nacional de Ingeniería; Universidad Nacional José Faustino Sánchez Carrión