Artificial neural network with perceptron competitive advantage according to internal and external factors in response to demand: Chancay Megaport.

Abstract

The main objective of the research was to evaluate the artificial neural network with perceptron in the competitive advantage according to internal and external business factors, which allows predicting whether the demand is met to cover the needs of the Megaport that will come into operation in the month of November 2024. A study was carried out using descriptive, correlation and econometric methodology applying the STEM (science, technology, engineering and math) methodology, carrying out a field study using a census survey of 107 MYPES, which are in activity. in the year 2022. The results indicate a relevant or important connection between “Competitive advantage” and “Internal and external factors”, which were found in the results of the logistic regression test and feel this equal to 0.545 with respect to one of the dimensions “Internal and External Factors” this indicates that there is a moderate positive connection or link between competitive advantage and marketing (X4). At the same time, the following equation was made for “Competitive advantage” in the Logistic Regression part, this being: Competitive advantage = 0,6792+0,0364*X2+0,1984*X3 + 0,1226*X4 + 0,2239*X5 + -0,1081*X6 + 0,1867*X7 + 0,0174*X8 + 0,0002*X9 + -0,0024*X10. Finally, the multilayer neural network was applied, in which a percentage of 58,9% of “competitive failure” and 41.1% of “Competitive takeoff” was obtained in MYPES. These results support the need to strategically address these elements to stand out in a dynamic environment. Keywords—Artificial neural network, Methodology, Competitive defeat, Competitive advantages, Internal and external factors.