A Novel Methodology for Evaluating Authenticity Perceptions in Andalusian Paradores Through Machine Learning

This study emphasises the pivotal role of emotions and cultural backgrounds in shaping tourists’ perceptions of authenticity within Andalusian Paradores. By employing an innovative machine learning method to analyse an extensive database of User-Generated Content, this research study reveals that certain emotions significantly diminish perceived authenticity. It also demonstrates that cultural and gender differences markedly influence authenticity perceptions. Notably, domestic tourists apply more stringent criteria for authenticity compared with international visitors, who may rely on idealised representations of Spanish culture. SHAP analysis further elucidates the contribution of various characteristics to authenticity perceptions, highlighting the predominance of emotional responses over demographic factors. These insights provide valuable guidance for tourism managers seeking to enhance visitor satisfaction. The findings advocate for the development of nuanced marketing strategies that cater to both international and domestic tourists, thereby fostering deeper engagement with cultural heritage and supporting the long-term sustainability of Andalusian Paradores.

Authors

Institutions

Publication Details

Journal
Heritage
Published
2024-12-19
DOI
https://doi.org/10.3390/heritage7120335
Citations
2
Primary Topic
Diverse Aspects of Tourism Research
Type
article
Field-Weighted Citation Impact
2.26
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Novel Methodology for Evaluating Authenticity Perceptions in Andalusian Paradores Through Machine Learning

Ignacio Rodríguez‐Rodríguez, Víctor Miguel Fernández, Miguel Puig-Cabrera, Víctor Calderón-Fajardo
2 citations
Heritage
Diverse Aspects of Tourism Research
2.26
article

A Novel Methodology for Evaluating Authenticity Perceptions in Andalusian Paradores Through Machine Learning

Ignacio Rodríguez‐Rodríguez, Víctor Miguel Fernández, Miguel Puig-Cabrera, Víctor Calderón-Fajardo
article en
2 citations

Abstract

This study emphasises the pivotal role of emotions and cultural backgrounds in shaping tourists’ perceptions of authenticity within Andalusian Paradores. By employing an innovative machine learning method to analyse an extensive database of User-Generated Content, this research study reveals that certain emotions significantly diminish perceived authenticity. It also demonstrates that cultural and gender differences markedly influence authenticity perceptions. Notably, domestic tourists apply more stringent criteria for authenticity compared with international visitors, who may rely on idealised representations of Spanish culture. SHAP analysis further elucidates the contribution of various characteristics to authenticity perceptions, highlighting the predominance of emotional responses over demographic factors. These insights provide valuable guidance for tourism managers seeking to enhance visitor satisfaction. The findings advocate for the development of nuanced marketing strategies that cater to both international and domestic tourists, thereby fostering deeper engagement with cultural heritage and supporting the long-term sustainability of Andalusian Paradores.

HeritageVol. 7(12)
Universidad Rey Juan Carlos (ES), Universidad Internacional De La Rioja (ES), Universidad de Málaga (ES)
Decent work and economic growth
Openalex Percentile: Top 9%
Diverse Aspects of Tourism Research
2.26
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Novel Methodology for Evaluating Authenticity Perceptions in Andalusian Paradores Through Machine Learning — Ignacio Rodríguez‐Rodríguez, Víctor Miguel Fernández, et al. · Heritage (2024) | TGRS Research Map | TGRS