Measuring the relationship between museum attributes and visitors: An application of topic model on museum online reviews.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 21 01 2024
accepted: 21 05 2024
medline: 8 7 2024
pubmed: 8 7 2024
entrez: 8 7 2024
Statut: epublish

Résumé

In recent years, cultural tourism has increasingly embraced museum visits. Museums serve as both cultural heritage guardians and integral parts of tourist destinations, significantly impacting visitor satisfaction and experience. Moreover, online museum reviews have become a crucial indicator of museum service quality, visitor experience, and public feedback in the digital age. An analysis of online reviews on major tourism websites and social media platforms can assist museums in developing appropriate management strategies. This study employed the structural topic model (STM) to analyze online museum reviews, identifying three primary attributes of museums and visitors' personal experiences, as well as 19 sub-attributes. The study confirmed that core offerings have a positive impact on visitor experience and satisfaction, while peripheral services and overall ambiance are also positively related to visitor experience and satisfaction. Furthermore, the results of structural equation modeling demonstrated that visitors' personal experiences have a positive impact on satisfaction. The results of structural equation modeling analysis support all seven hypothesized relationships. These findings will assist museum managers in developing effective management strategies and future plans.

Identifiants

pubmed: 38976674
doi: 10.1371/journal.pone.0304901
pii: PONE-D-24-02778
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0304901

Informations de copyright

Copyright: © 2024 Huo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Hong Huo (H)

School of Management, Harbin University of Commerce, Harbin, China.

Keqin Shen (K)

School of Management, Harbin University of Commerce, Harbin, China.

Chunjia Han (C)

Department of Management, Birkbeck, University of London, London, United Kingdom.

Mu Yang (M)

Department of Management, Birkbeck, University of London, London, United Kingdom.

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Classifications MeSH