Uso de redes bayesianas para calcular la variable que más influye en la decisión de compra de repuestos automotrices

This project studies the best way to calculate the variable that allows analyzing strategies to increase the sales of spare parts in the automotive industry, by collecting data on what happens when a person arrives at the warehouse and asks for a product, several groups of variables according to characteristics that may affect the likelihood of the sale occurring and according to the contribution of each variable to success, different proposals are filtered; until identifying the most relevant when buying automotive parts such as: the price, product availability, level of customer service, presentation or aesthetics of the product, warranty, durability, brand and after-sales service. Then, Bayesian networks are used to know which of these mentioned variables increases the probability that the sale will occur, next, with the help of a software specialized in Bayesian networks called Genie, the data is simulated according to evidence of successful sales or product availability. Finally, it is concluded that the most important variable is customer service.

• Autores: Muñoz Pineda, Juan David
• Fecha de publicación: 2020
• Institución: Universidad de San Buenaventura
• Repositorio: Repositorio USB
• Idioma: spa
• OAI Identifier: oai:bibliotecadigital.usb.edu.co:10819/7984
• Acceso en línea: http://hdl.handle.net/10819/7984
• Palabra clave: Estadística bayesiana; Redes bayesianas; Probabilidad; Variable; Ventas; Bayesian statistics; Bayesian networks; Probability; Variable; Sales
• License: Atribución-NoComercial-SinDerivadas 2.5 Colombia