Restaurant Quality Perception: A Mixed Analysis with Neural Networks

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.