IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v35y2024i1p16-27.html
   My bibliography  Save this article

Improving Convenience or Saving Face? An Empirical Analysis of the Use of Facial Recognition Payment Technology in Retail

Author

Listed:
  • Jia Gao

    (Institute of Supply Chain Analytics, Dongbei University of Finance and Economics, Dalian, Liaoning 116025, China)

  • Ying Rong

    (Antai College of Economics and Management, Data-Driven Management Decision-Making Lab, Shanghai Jiao Tong University, Shanghai 200030, China)

  • Xin Tian

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China; Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100190, China)

  • Yuliang Yao

    (College of Business, Lehigh University, Bethlehem, Pennsylvania 18015)

Abstract

Although facial recognition (FR) payment technology can be more convenient for customers, it is still not consistently used by many customers in retail. Using transaction data from three retail chains, we develop econometric models and an estimation strategy for examining the social presence and herding effects that affect FR payment technology use. Our key findings are as follows: (1) Customers are less likely to use FR payment technology when more customers are in line behind them, waiting and potentially watching—the social presence effect. (2) Customers are more likely to use FR payment technology when more preceding customers use FR payment technology—the herding effect. (3) Customers with more experience using FR payment technology are subject to a weaker social presence effect. The marginal social presence effect can result in a 4.75% reduction in the probability of the focal customer using FR payment technology, and the potential social presence effect can be as high as 48.42%. When the focal customer has one additional experience in using FR payment technology, the social presence effect is reduced by 7.79%. The herding effect can result in a 20.90% increase in the probability of the focal customer using FR payment technology. Theoretical and managerial implications are discussed.

Suggested Citation

  • Jia Gao & Ying Rong & Xin Tian & Yuliang Yao, 2024. "Improving Convenience or Saving Face? An Empirical Analysis of the Use of Facial Recognition Payment Technology in Retail," Information Systems Research, INFORMS, vol. 35(1), pages 16-27, March.
  • Handle: RePEc:inm:orisre:v:35:y:2024:i:1:p:16-27
    DOI: 10.1287/isre.2023.1205
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.2023.1205
    Download Restriction: no

    File URL: https://libkey.io/10.1287/isre.2023.1205?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
    ---><---

    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:inm:orisre:v:35:y:2024:i:1:p:16-27. 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 Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.