IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v76y2024ics0969698923003296.html
   My bibliography  Save this article

Customer experience in AI-enabled products: Scale development and validation

Author

Listed:
  • Wang, Ping
  • Li, Kunyang
  • Du, Qinglong
  • Wang, Jianqiong

Abstract

Artificial Intelligence (AI) is an enabling technology that can be integrated into products to provide emerging capabilities and craft novel customer experience (CX); many companies have widely adopted AI-enabled products to provide customers with service interactions. However, meager researchers have studied CX in AI-enabled products. Utilizing qualitative and quantitative methods, this study developed a scale of CX in AI-enabled products using Churchill's (1979) scale development framework. The scale underwent several stages of development including item generation, scale purification, scale validation, cross-testing, and nomological validity testing. Finally, five dimensions were identified to represent CX in AI-enabled products, such as data capture experience, classification experience, delegation experience, social experience, and anthropomorphic experience. Based on assemblage theory, the study develops the scale from the perspective of integrating human-centric and object-oriented anthropomorphic metaphors. Establishment of this scale extends traditional CX research, expands emerging CX research, and presents the first operationalized definition of the CX in AI-enabled products. The development of this scale provides a framework for marketers to enhance the CX in emerging consumer environments.

Suggested Citation

  • Wang, Ping & Li, Kunyang & Du, Qinglong & Wang, Jianqiong, 2024. "Customer experience in AI-enabled products: Scale development and validation," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    • Handle: RePEc:eee:joreco:v:76:y:2024:i:c:s0969698923003296
    DOI: 10.1016/j.jretconser.2023.103578
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969698923003296
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jretconser.2023.103578?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.

    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:eee:joreco:v:76:y:2024:i:c:s0969698923003296. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-retailing-and-consumer-services .

    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.