IDEAS home Printed from https://ideas.repec.org/a/eee/ininma/v50y2020icp325-336.html
   My bibliography  Save this article

Conceptualization of omnichannel customer experience and its impact on shopping intention: A mixed-method approach

Author

Listed:
  • Shi, Si
  • Wang, Yi
  • Chen, Xuanzhu
  • Zhang, Qian

Abstract

Advances in information and communication technologies (ICT) have led to the revolution in retail industry through integrating multiple available channels to enhance seamless customer experience, promoting a shift from multichannel to omnichannel business. This phenomenon has gained increasing attention in both academia and industry due to growing challenges to serve customers effectively. This study adopted a mixed-method approach to firstly conceptualize omnichannel customer experience and develop a survey instrument. Then, this study draws on the innovation diffusion theory to develop a nomological model that posits perceived compatibility and perceived risk as key linking mechanisms between omnichannel experience and omnichannel shopping intention. To achieve our research objective, we collected two data sets including pretest (n = 141) and model test (n = 377). We found that the constructs that represented our omnichannel experience conceptualization were good predictors of perceived compatibility and perceived risk, which further impact customers’ shopping intention. This study provides a rich conceptualization of an instrument for omnichannel customer experience that can serve as a springboard for future research to investigate the antecedents and impacts of omnichannel experience and can be used as a guide to design effective omnichannel retailing strategy.

Suggested Citation

  • Shi, Si & Wang, Yi & Chen, Xuanzhu & Zhang, Qian, 2020. "Conceptualization of omnichannel customer experience and its impact on shopping intention: A mixed-method approach," International Journal of Information Management, Elsevier, vol. 50(C), pages 325-336.
    • Handle: RePEc:eee:ininma:v:50:y:2020:i:c:p:325-336
    DOI: 10.1016/j.ijinfomgt.2019.09.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0268401219302130
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijinfomgt.2019.09.001?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:ininma:v:50:y:2020:i:c:p:325-336. 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/international-journal-of-information-management .

    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.