IDEAS home Printed from https://ideas.repec.org/a/taf/tbitxx/v43y2024i16p4016-4032.html
   My bibliography  Save this article

Using AI chatbots in climate change mitigation: a moderated serial mediation model

Author

Listed:
  • Seyoung Lee
  • YounJung Park
  • Gain Park

Abstract

This study examined the effect of chatbots’ emotional expression on climate-change-mitigation behaviour intention and the individual and serial mediating roles of social presence and guilt in the main effect. This study further tested the moderating role of custom addressing in direct and indirect relationships between the aforementioned variables. To that end, 577 American adults were recruited through Amazon Mechanical Turk. After eliminating incomplete responses, the remaining 549 participants were assigned to four conditions (factual vs. emotional conditions x control vs. custom addressing conditions), conversed briefly with a chatbot agent, and responded to a questionnaire. The findings showed that chatbots’ emotional expression yielded higher climate-change-mitigation behavioural intention than factual information and that social presence mediated this relationship. The results did not support the mediating role of guilt but supported serial mediation through social presence and guilt. The results further support the moderating role of custom addressing in the indirect relationship through social presence and serially through social presence and guilt. However, the results do not support the moderating role of custom addressing in direct and indirect relationships through guilt.

Suggested Citation

  • Seyoung Lee & YounJung Park & Gain Park, 2024. "Using AI chatbots in climate change mitigation: a moderated serial mediation model," Behaviour and Information Technology, Taylor & Francis Journals, vol. 43(16), pages 4016-4032, December.
    • Handle: RePEc:taf:tbitxx:v:43:y:2024:i:16:p:4016-4032
    DOI: 10.1080/0144929X.2023.2298305
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0144929X.2023.2298305
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0144929X.2023.2298305?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    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:taf:tbitxx:v:43:y:2024:i:16:p:4016-4032. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tbit .

    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.