IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-05362542.html

Predicting Museum Visitors Intention through Nonverbal Cues : the Potential of Facial Expressions

Author

Listed:
  • Charlotte De Sainte Maresville

    (UBS - Université de Bretagne Sud, UBS Vannes - Université de Bretagne Sud - Vannes - UBS - Université de Bretagne Sud, LEGO - Laboratoire d'Economie et de Gestion de l'Ouest - UBS - Université de Bretagne Sud - UBO EPE - Université de Brest - IMT - Institut Mines-Télécom [Paris] - IBSHS - Institut Brestois des Sciences de l'Homme et de la Société - UBO EPE - Université de Brest - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris])

  • Christine Petr

    (LEGO - Laboratoire d'Economie et de Gestion de l'Ouest - UBS - Université de Bretagne Sud - UBO EPE - Université de Brest - IMT - Institut Mines-Télécom [Paris] - IBSHS - Institut Brestois des Sciences de l'Homme et de la Société - UBO EPE - Université de Brest - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris], UBS - Université de Bretagne Sud, MARSOUIN - Môle Armoricain de Recherche sur la SOciété de l'information et des usages d'INternet - UR - Université de Rennes - UBS - Université de Bretagne Sud - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - Groupe ENSAE-ENSAI - Groupe des Écoles Nationales d'Économie et Statistique - UBO EPE - Université de Brest - IMT - Institut Mines-Télécom [Paris] - UR2 - Université de Rennes 2 - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris])

Abstract

Understanding museum visitor engagement is crucial for optimizing communication strategies and exhibition design. Museums need to anticipate visit intentions and potential visitors. This study explores facial expression analysis as a nonverbal predictor of museum visit intentions, focusing on joy intensity in response to promotional exhibition visuals. Using a mixed-effects logistic regression model on 61 participants, we demonstrate that joy expression significantly predicts visit intention, particularly among undecided visitors. The results highlight variations across age, gender, and cultural background, suggesting tailored marketing strategies. By integrating facial emotion recognition into predictive models, this research contributes to anticipating cultural engagement and emphasizing the potential of nonverbal cues in enhancing audience segmentation and communication effectiveness in cultural institutions. These findings provide new avenues for museum marketing and visitor experience management

Suggested Citation

  • Charlotte De Sainte Maresville & Christine Petr, 2025. "Predicting Museum Visitors Intention through Nonverbal Cues : the Potential of Facial Expressions," Post-Print hal-05362542, HAL.
    • Handle: RePEc:hal:journl:hal-05362542
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-05362542. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.