Experiential-Adaptative Hybrid Model for Hospitality Based on CNN Neural Networks, Case-Based Reasoning (CBR) and 360° VR

Abstract

In this work, an Experiential-Adaptive Hybrid model for hospitality based on Convolutional Neural Networks (CNN) neural networks, Case-Based Reasoning (CBR) and 360° VR, is proposed for generating experiences in hotel marketing and promotion activities. The model is based on CBR, which considers user profiles and immersive 360° videos. The work also improves and automates the video tagging process, using CNN, transitioning from a manual to an automated process. The 360° Virtual Reality (VR) experiences can elicit responses across behavioral, affective, cognitive, and attitudinal dimensions; therefore, they are evaluated within an immersive 360° VR environment. To validate the results obtained from this approach, a quasi-experimental study was conducted using various visual experiences, including surrounding landscapes, facilities, environments, and services of a boutique hotel. This study employed a random sample of young participants. This work aims to contribute to the use of 360° VR videos for visualizing the characteristics, environments, and services of hotels in a tour tailored to user profiles, with the goal of evaluating attitudinal and behavioral, cognitive and affective responses as well, and the potential influence on booking and purchase intentions. Conclusions and recommendations for future research are established.