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Data-driven simulation modeling of the checkout process in supermarkets: Insights for decision support in retail operations

Author

Listed:
  • Tomasz Antczak
  • Rafal Weron
  • Jacek Zabawa

Abstract

We build a realistic agent-based model for simulating customer decisions of picking lines in supermarkets. The model is calibrated to actual point of sale (POS) data from three supermarkets of one of major European retail chains and is implemented in the open-access NetLogo simulation platform. The model can provide insights as to the impact of individual customer decisions of picking lines on the overall efficiency of the checkout process. In particular, we show that when customers pick a line by minimizing the expected waiting time, not only is this choice beneficial for the customers themselves, as it leads to shorter waiting times in queues, but also for the supermarket management, since it yields shorter working times of the cashiers.

Suggested Citation

  • Tomasz Antczak & Rafal Weron & Jacek Zabawa, 2020. "Data-driven simulation modeling of the checkout process in supermarkets: Insights for decision support in retail operations," WORking papers in Management Science (WORMS) WORMS/20/16, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    • Handle: RePEc:ahh:wpaper:worms2016
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    File URL: https://worms.pwr.edu.pl/RePEc/ahh/wpaper/WORMS_20_16.pdf
    File Function: Original version, 2020
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    References listed on IDEAS

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    1. Weiss, Elliott N. & Tucker, Chad, 2018. "Queue management: Elimination, expectation, and enhancement," Business Horizons, Elsevier, vol. 61(5), pages 671-678.
    2. Sorensen, Herb & Bogomolova, Svetlana & Anderson, Katherine & Trinh, Giang & Sharp, Anne & Kennedy, Rachel & Page, Bill & Wright, Malcolm, 2017. "Fundamental patterns of in-store shopper behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 37(C), pages 182-194.
    3. Garaus, Marion & Wagner, Udo, 2019. "Let me entertain you – Increasing overall store satisfaction through digital signage in retail waiting areas," Journal of Retailing and Consumer Services, Elsevier, vol. 47(C), pages 331-338.
    4. H. A. Eiselt & C. -L. Sandblom, 2007. "Linear Programming and its Applications," Springer Books, Springer, number 978-3-540-73671-4, July.
    5. 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.
    6. Sezer Ülkü & Chris Hydock & Shiliang Cui, 2020. "Making the Wait Worthwhile: Experiments on the Effect of Queueing on Consumption," Management Science, INFORMS, vol. 66(3), pages 1149-1171, March.
    7. Borges, Adilson & Herter, Márcia Maurer & Chebat, Jean-Charles, 2015. "“It was not that long!†: The effects of the in-store TV screen content and consumers emotions on consumer waiting perception," Journal of Retailing and Consumer Services, Elsevier, vol. 22(C), pages 96-106.
    8. Ju-Sung Lee & Tatiana Filatova & Arika Ligmann-Zielinska & Behrooz Hassani-Mahmooei & Forrest Stonedahl & Iris Lorscheid & Alexey Voinov & J. Gareth Polhill & Zhanli Sun & Dawn C. Parker, 2015. "The Complexities of Agent-Based Modeling Output Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(4), pages 1-4.
    9. Chun (Martin) Qiu & Wenqing Zhang, 2016. "Managing long queues for holiday sales shopping," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(1), pages 52-65, February.
    10. Jingqi Wang & Yong-Pin Zhou, 2018. "Impact of Queue Configuration on Service Time: Evidence from a Supermarket," Management Science, INFORMS, vol. 64(7), pages 3055-3075, July.
    11. Aringhieri, Roberto & Duma, Davide & Fragnelli, Vito, 2018. "Modeling the rational behavior of individuals on an e-commerce system," Operations Research Perspectives, Elsevier, vol. 5(C), pages 22-31.
    12. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.
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    Cited by:

    1. Yong Li & Yu Sun & Chengcheng Zeng & Jinxing Li & Yanping Gao & Haisheng Li, 2022. "Research on the Influencing Factors for the Use of Green Building Materials through the Number Growth of Construction Enterprises Based on Agent-Based Modeling," Sustainability, MDPI, vol. 14(19), pages 1-13, October.
    2. Paul M. Torrens, 2023. "Agent models of customer journeys on retail high streets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 18(1), pages 87-128, January.
    3. Tomasz Antczak & Bartosz Skorupa & Mikolaj Szurlej & Rafal Weron & Jacek Zabawa, 2021. "Simulation modeling of epidemic risk in supermarkets: Investigating the impact of social distancing and checkout zone design," WORking papers in Management Science (WORMS) WORMS/21/05, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    4. Njomane, Linda & Telukdarie, Arnesh, 2022. "Impact of COVID-19 food supply chain: Comparing the use of IoT in three South African supermarkets," Technology in Society, Elsevier, vol. 71(C).

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    More about this item

    Keywords

    Retail operations; Customer analytics; Decision support; Checkout process; Queue management system; Agent-based simulation; NetLogo;
    All these keywords.

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