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 cha...

Full description

Autores:
Muñoz Pineda, Juan David
Tipo de recurso:
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
Rights
License
Atribución-NoComercial-SinDerivadas 2.5 Colombia
Description
Summary: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.