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Towards Digital Transformation in Fashion Retailing: A Design-Oriented IS Research Study of Automated Checkout Systems

Author

Listed:
  • Matthias Hauser

    (University of Würzburg)

  • Sebastian A. Günther

    (University of Bamberg)

  • Christoph M. Flath

    (University of Würzburg)

  • Frédéric Thiesse

    (University of Würzburg)

Abstract

Automated checkout systems promise greater sales due to an improved customer experience and cost savings because less store personnel is needed. The present design-oriented IS research study is concerned with an automated checkout solution in fashion retail stores. The implementation of such a cyberphysical system in established retail environments is challenging as architectural constraints, well-established customer processes, and customer expectations regarding privacy and convenience impose limits on system design. To overcome these challenges, the authors design an IT artifact that leverages an RFID sensor infrastructure and software components (data processing and prediction routines) to jointly address the central problems of detecting purchases in a reliable and timely fashion and assigning these purchases to individual shopping baskets. The system is implemented and evaluated in a research laboratory under real-world conditions. The evaluation indicates that shopping baskets can indeed be detected reliably (precision and recall rates greater than 99%) and in an expeditious manner (median detection time of 1.03 s). Moreover, purchase assignment reliability is 100% for most standard scenarios but falls to 42% in the most challenging scenario.

Suggested Citation

  • Matthias Hauser & Sebastian A. Günther & Christoph M. Flath & Frédéric Thiesse, 2019. "Towards Digital Transformation in Fashion Retailing: A Design-Oriented IS Research Study of Automated Checkout Systems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(1), pages 51-66, February.
    • Handle: RePEc:spr:binfse:v:61:y:2019:i:1:d:10.1007_s12599-018-0566-9
    DOI: 10.1007/s12599-018-0566-9
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    References listed on IDEAS

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    Cited by:

    1. Hauser, Matthias & Flath, Christoph M. & Thiesse, Frédéric, 2021. "Catch me if you scan: Data-driven prescriptive modeling for smart store environments," European Journal of Operational Research, Elsevier, vol. 294(3), pages 860-873.
    2. Pinto, Marcelo Rezende & Salume, Paula Karina & Barbosa, Marcelo Werneck & de Sousa, Paulo Renato, 2023. "The path to digital maturity: A cluster analysis of the retail industry in an emerging economy," Technology in Society, Elsevier, vol. 72(C).
    3. Lian, Jiunn-Woei, 2021. "Determinants and consequences of service experience toward small retailer platform business model: Stimulus–organism–response perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    4. Michel Muschkiet & Tobias Wulfert & Robert Woroch & Gero Strobel & Leonardo Banh, 2023. "Unleashing the digital building bricks," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.

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