IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v294y2021i3p860-873.html
   My bibliography  Save this article

Catch me if you scan: Data-driven prescriptive modeling for smart store environments

Author

Listed:
  • Hauser, Matthias
  • Flath, Christoph M.
  • Thiesse, Frédéric

Abstract

The increasing adoption of omnichannel strategies in recent years has led retail companies worldwide to fundamentally rethink the future role of their network of brick-and-mortar stores. One strategic option being pursued by many retailers is the transformation of the stationary store into a “smart store,” augmented by various digital services. However, an essential prerequisite for the success of smart store services is high quality of the underlying data generated through the use of technologies for tracking products and customer behavior. As a means of investigating the use of machine learning to improve data quality, the present study considers the example of Radio Frequency Identification (RFID) as a technological infrastructure for tracking products in fashion retail. We examine electronic article surveillance and automated checkouts as practical use cases enabled by a classification model for the detection of product movements on the store floor. In order to identify an economically optimal configuration of the classifier, we develop a complementary service operations model that allows for determining the respective cost impact. In addition to the specific results for the considered use cases, the study thus points to a general and novel prescriptive analytics approach.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ejores:v:294:y:2021:i:3:p:860-873
    DOI: 10.1016/j.ejor.2020.12.047
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221720310936
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2020.12.047?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.

    References listed on IDEAS

    as
    1. Herhausen, Dennis & Binder, Jochen & Schoegel, Marcus & Herrmann, Andreas, 2015. "Integrating Bricks with Clicks: Retailer-Level and Channel-Level Outcomes of Online–Offline Channel Integration," Journal of Retailing, Elsevier, vol. 91(2), pages 309-325.
    2. Gary S. Becker, 1974. "Crime and Punishment: An Economic Approach," NBER Chapters, in: Essays in the Economics of Crime and Punishment, pages 1-54, National Bureau of Economic Research, Inc.
    3. A. Krishnamoorthy & P. Pramod & S. Chakravarthy, 2014. "Queues with interruptions: a survey," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(1), pages 290-320, April.
    4. Jiang, Yangzi & Abouee-Mehrizi, Hossein & Diao, Yuhe, 2020. "Data-driven analytics to support scheduling of multi-priority multi-class patients with wait time targets," European Journal of Operational Research, Elsevier, vol. 281(3), pages 597-611.
    5. Nikolai Stein & Jan Meller & Christoph M. Flath, 2018. "Big data on the shop-floor: sensor-based decision-support for manual processes," Journal of Business Economics, Springer, vol. 88(5), pages 593-616, July.
    6. 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.
    7. Wong, W.K. & Leung, S.Y.S. & Guo, Z.X. & Zeng, X.H. & Mok, P.Y., 2012. "Intelligent product cross-selling system with radio frequency identification technology for retailing," International Journal of Production Economics, Elsevier, vol. 135(1), pages 308-319.
    8. Grewal, Dhruv & Roggeveen, Anne L. & Nordfält, Jens, 2017. "The Future of Retailing," Journal of Retailing, Elsevier, vol. 93(1), pages 1-6.
    9. Corne, David & Dhaenens, Clarisse & Jourdan, Laetitia, 2012. "Synergies between operations research and data mining: The emerging use of multi-objective approaches," European Journal of Operational Research, Elsevier, vol. 221(3), pages 469-479.
    10. Verhoef, Peter C. & Kannan, P.K. & Inman, J. Jeffrey, 2015. "From Multi-Channel Retailing to Omni-Channel Retailing," Journal of Retailing, Elsevier, vol. 91(2), pages 174-181.
    11. Anonymous, 2014. "Introduction to the Issue," Journal of Wine Economics, Cambridge University Press, vol. 9(1), pages 1-2, May.
    12. Caro, Felipe & Sadr, Ramin, 2019. "The Internet of Things (IoT) in retail: Bridging supply and demand," Business Horizons, Elsevier, vol. 62(1), pages 47-54.
    13. Vidya Mani & Saravanan Kesavan & Jayashankar M. Swaminathan, 2015. "Estimating the Impact of Understaffing on Sales and Profitability in Retail Stores," Production and Operations Management, Production and Operations Management Society, vol. 24(2), pages 201-218, February.
    14. De Vany, Arthur S, 1976. "Uncertainty, Waiting Time, and Capacity Utilization: A Stochastic Theory of Product Quality," Journal of Political Economy, University of Chicago Press, vol. 84(3), pages 523-541, June.
    15. Fei Gao & Xuanming Su, 2017. "Omnichannel Retail Operations with Buy-Online-and-Pick-up-in-Store," Management Science, INFORMS, vol. 63(8), pages 2478-2492, August.
    16. Li, Gang & Zhang, Tao & Tayi, Giri Kumar, 2020. "Inroad into omni-channel retailing: Physical showroom deployment of an online retailer," European Journal of Operational Research, Elsevier, vol. 283(2), pages 676-691.
    17. David R. Bell & Santiago Gallino & Antonio Moreno, 2018. "Offline Showrooms in Omnichannel Retail: Demand and Operational Benefits," Management Science, INFORMS, vol. 64(4), pages 1629-1651, April.
    18. Olafsson, Sigurdur & Li, Xiaonan & Wu, Shuning, 2008. "Operations research and data mining," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1429-1448, June.
    19. Teck H. Ho & Yu-Sheng Zheng, 2004. "Setting Customer Expectation in Service Delivery: An Integrated Marketing-Operations Perspective," Management Science, INFORMS, vol. 50(4), pages 479-488, April.
    20. Paul R. Messinger & Chakravarthi Narasimhan, 1997. "A Model of Retail Formats Based on Consumers' Economizing on Shopping Time," Marketing Science, INFORMS, vol. 16(1), pages 1-23.
    21. Velibor V. Mišić & Georgia Perakis, 2020. "Data Analytics in Operations Management: A Review," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 158-169, January.
    22. K. Thiruvengadam, 1963. "Queuing with Breakdowns," Operations Research, INFORMS, vol. 11(1), pages 62-71, February.
    23. Anonymous, 2014. "Introduction to the Issue," Journal of Wine Economics, Cambridge University Press, vol. 9(2), pages 109-110, August.
    24. Ronald W. Wolff, 1982. "Poisson Arrivals See Time Averages," Operations Research, INFORMS, vol. 30(2), pages 223-231, April.
    25. Dimitris Bertsimas & Nathan Kallus, 2020. "From Predictive to Prescriptive Analytics," Management Science, INFORMS, vol. 66(3), pages 1025-1044, March.
    26. Yina Lu & Andrés Musalem & Marcelo Olivares & Ariel Schilkrut, 2013. "Measuring the Effect of Queues on Customer Purchases," Management Science, INFORMS, vol. 59(8), pages 1743-1763, August.
    27. Meisel, Stephan & Mattfeld, Dirk, 2010. "Synergies of Operations Research and Data Mining," European Journal of Operational Research, Elsevier, vol. 206(1), pages 1-10, October.
    28. Walter Y. Oi, 1992. "Productivity in the Distributive Trades: The Shopper and the Economies of Massed Reserves," NBER Chapters, in: Output Measurement in the Service Sectors, pages 161-193, National Bureau of Economic Research, Inc.
    29. Rogelio Oliva & John D. Sterman, 2001. "Cutting Corners and Working Overtime: Quality Erosion in the Service Industry," Management Science, INFORMS, vol. 47(7), pages 894-914, July.
    30. Mortenson, Michael J. & Doherty, Neil F. & Robinson, Stewart, 2015. "Operational research from Taylorism to Terabytes: A research agenda for the analytics age," European Journal of Operational Research, Elsevier, vol. 241(3), pages 583-595.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gaurav Nagpal & Anup Kumar Ray & Nitisha Kharkwal & Naga Vamsi Krishna Jasti & Ankita Nagpal, 2022. "Challenges in Adoption of Business Analytics by Small Retailers: An Empirical Study in the Indian Context," International Journal of E-Adoption (IJEA), IGI Global, vol. 15(2), pages 1-14, December.
    2. Hübner, Alexander & Hense, Jonas & Dethlefs, Christian, 2022. "The revival of retail stores via omnichannel operations: A literature review and research framework," European Journal of Operational Research, Elsevier, vol. 302(3), pages 799-818.
    3. Han, Shuihua & Chen, Linlin & Su, Zhaopei & Gupta, Shivam & Sivarajah, Uthayasankar, 2024. "Identifying a good business location using prescriptive analytics: Restaurant location recommendation based on spatial data mining," Journal of Business Research, Elsevier, vol. 179(C).
    4. Erkip, Nesim Kohen, 2023. "Can accessing much data reshape the theory? Inventory theory under the challenge of data-driven systems," European Journal of Operational Research, Elsevier, vol. 308(3), pages 949-959.
    5. Jiahe Chen & Yu-Wei Chang, 2023. "How smart technology empowers consumers in smart retail stores? The perspective of technology readiness and situational factors," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-24, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cai, Ya-Jun & Lo, Chris K.Y., 2020. "Omni-channel management in the new retailing era: A systematic review and future research agenda," International Journal of Production Economics, Elsevier, vol. 229(C).
    2. Christiane Lehrer & Manuel Trenz, 2022. "Omnichannel Business," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(2), pages 687-699, June.
    3. von Briel, Frederik, 2018. "The future of omnichannel retail: A four-stage Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 217-229.
    4. Yini Chen & Ting Chi, 2021. "How Does Channel Integration Affect Consumers’ Selection of Omni-Channel Shopping Methods? An Empirical Study of U.S. Consumers," Sustainability, MDPI, vol. 13(16), pages 1-29, August.
    5. Julián Chaparro-Peláez & Emiliano Acquila-Natale & Ángel Hernández-García & Santiago Iglesias-Pradas, 2020. "The Digital Transformation of the Retail Electricity Market in Spain," Energies, MDPI, vol. 13(8), pages 1-18, April.
    6. 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.
    7. Baier, Daniel & Rese, Alexandra, 2020. "How to increase multichannel shopping satisfaction? An adapted Kano based stage-gate approach to select new technologies," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    8. Willems, Kim & Smolders, Annelien & Brengman, Malaika & Luyten, Kris & Schöning, Johannes, 2017. "The path-to-purchase is paved with digital opportunities: An inventory of shopper-oriented retail technologies," Technological Forecasting and Social Change, Elsevier, vol. 124(C), pages 228-242.
    9. Kim, Sehoon & Connerton, Timothy Paul & Park, Cheongyeul, 2022. "Transforming the automotive retail: Drivers for customers' omnichannel BOPS (Buy Online & Pick up in Store) behavior," Journal of Business Research, Elsevier, vol. 139(C), pages 411-425.
    10. Cheah, Jun-Hwa & Lim, Xin-Jean & Ting, Hiram & Liu, Yide & Quach, Sara, 2022. "Are privacy concerns still relevant? Revisiting consumer behaviour in omnichannel retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    11. Mirzabeiki, Vahid & Saghiri, Soroosh Sam, 2020. "From ambition to action: How to achieve integration in omni-channel?," Journal of Business Research, Elsevier, vol. 110(C), pages 1-11.
    12. Gambella, Claudio & Ghaddar, Bissan & Naoum-Sawaya, Joe, 2021. "Optimization problems for machine learning: A survey," European Journal of Operational Research, Elsevier, vol. 290(3), pages 807-828.
    13. Saghiri, Soroosh & Wilding, Richard & Mena, Carlos & Bourlakis, Michael, 2017. "Toward a three-dimensional framework for omni-channel," Journal of Business Research, Elsevier, vol. 77(C), pages 53-67.
    14. Quach, Sara & Barari, Mojtaba & Moudrý, Dann Vit & Quach, Ken, 2022. "Service integration in omnichannel retailing and its impact on customer experience," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    15. Park, Joonyong & Kim, Renee B., 2022. "Importance of offline service quality in building loyalty of OC service brand," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    16. Xu, Xun & Jackson, Jonathan E., 2019. "Investigating the influential factors of return channel loyalty in omni-channel retailing," International Journal of Production Economics, Elsevier, vol. 216(C), pages 118-132.
    17. Irene Y. L. Chen & Yi-Shun Wang & Bo-Ruei Li, 2021. "Investigating the Relative Performance of Bricks-and-Mortar, Clicks-and-Mortar, and Pure-Click Firms in Taiwan," Sustainability, MDPI, vol. 13(6), pages 1-17, March.
    18. Kong, Ruixiao & Luo, Li & Chen, Liuxin & Keblis, Matthew F., 2020. "The effects of BOPS implementation under different pricing strategies in omnichannel retailing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    19. Hänninen, Mikko & Mitronen, Lasse & Kwan, Stephen K., 2019. "Multi-sided marketplaces and the transformation of retail: A service systems perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 380-388.
    20. Hallikainen, Heli & Alamäki, Ari & Laukkanen, Tommi, 2019. "Individual preferences of digital touchpoints: A latent class analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 50(C), pages 386-393.

    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:ejores:v:294:y:2021:i:3:p:860-873. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: http://www.elsevier.com/locate/eor .

    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.