Percepción de la calidad en restaurantes: un análisis mixto con redes neuronales

Asdrúbal López-Chau; J. Patricia Muñoz-Chávez; David Valle-Cruz

doi:10.18046/j.estger.2022.165.5235

Authors

Asdrúbal López-Chau Profesor de Tiempo Completo, CU UAEM Zumpango, Laboratorio de Tecnologías Computacionales Aplicadas, Universidad Autónoma del Estado de México, Zumpango, México.
J. Patricia Muñoz-Chávez Profesora de Tiempo Completo, Área Académica de Desarrollo de Negocios, Universidad Tecnológica de la Zona Metropolitana del Valle de México, Tizayuca Hidalgo, México.
David Valle-Cruz Profesor Investigador, Unidad Académica Profesional Tianguistenco, Universidad Autónoma del Estado de México, Santiago Tianguistenco, México.

DOI:

https://doi.org/10.18046/j.estger.2022.165.5235

Keywords:

quality, restaurants, tourism, artificial neural networks, artificial intelligence

Abstract

This study focuses on identify the factors that influence consumer perception of quality in table service restaurants in the magical town of Real del Monte Hidalgo, Mexico. The methodology is based on two perspectives, firstly, on the analysis of the most important factors of the results of a 22-item survey by means of artificial neural networks applied to 320 diners and, secondly, on the application of semi-structured interviews to eight diners. The findings show that the key aspects influencing perceptions of consumers are the ability of the staff to answer questions, the background music, and the food quality and taste.

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