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

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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.

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Notes

  1. Meuter et al. (2000) found that causes of dissatisfaction with self-service technologies were failure of the technology, design problems in regard to both the technological interface and the service that it offered, and customer-based failures (e.g., forgetting one’s personal identification number).

  2. Although Amazon has not published any technical details about their system, information on the company’s website and two patents filed by the company (Kumar et al. 2015; Puerini et al. 2015) provide insights into the implementation of this cyberphysical retail system.

  3. RFID identifies products at the item level without a direct line of sight. Furthermore, it facilitates the simultaneous bulk detection of multiple objects.

  4. The proposed system can be applied in retail environments that are larger than our experimental shopping area because the automated checkout solution we propose requires only observation by RFID systems of the area in front of the store exit and not observation of the entire store.

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Author information

Authors and Affiliations

  1. University of Würzburg, Josef-Stangl-Platz 2, 97070, Würzburg, Germany

    Matthias Hauser &  Frédéric Thiesse

  2. University of Bamberg, Kapuzinerstraße 16, 96047, Bamberg, Germany

    Sebastian A. Günther

  3. University of Würzburg, Sanderring 2, 97070, Würzburg, Germany

    Christoph M. Flath

Authors
  1. Matthias Hauser
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  2. Sebastian A. Günther
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  3. Christoph M. Flath
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  4. Frédéric Thiesse
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Corresponding author

Correspondence to Matthias Hauser.

Additional information

Accepted after two revisions by the editors of the special issue.

Appendix: Feature descriptions

Appendix: Feature descriptions

Table 6 describes the features used in the item detection model (see Sect. 3.4); Table 7 the features used in the localization model (see Sect. 3.5.1).

Table 6 Item detection model features
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Table 7 Localization model features
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Hauser, M., Günther, S.A., Flath, C.M. et al. Towards Digital Transformation in Fashion Retailing: A Design-Oriented IS Research Study of Automated Checkout Systems. Bus Inf Syst Eng 61, 51–66 (2019). https://doi.org/10.1007/s12599-018-0566-9

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