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

Matthias Hauser (), Sebastian A. Günther (), Christoph M. Flath () and Frédéric Thiesse ()
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Matthias Hauser: University of Würzburg
Sebastian A. Günther: University of Bamberg
Christoph M. Flath: University of Würzburg
Frédéric Thiesse: University of Würzburg

Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, 2019, vol. 61, issue 1, No 5, 66 pages

Abstract: 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.

Keywords: Design-oriented IS research; Digital innovation; Internet of things; Cyberphysical systems; Retail industry; Radio frequency identification; Machine learning; Automated checkout systems (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s12599-018-0566-9

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