IDEAS home Printed from https://ideas.repec.org/p/ahh/wpaper/worms2016.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: https://worms.pwr.edu.pl/RePEc/ahh/wpaper/WORMS_20_16.pdf
    File Function: Original version, 2020
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Weiss, Elliott N. & Tucker, Chad, 2018. "Queue management: Elimination, expectation, and enhancement," Business Horizons, Elsevier, vol. 61(5), pages 671-678.
    4. 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.
    5. 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.
    6. H. A. Eiselt & C. -L. Sandblom, 2007. "Linear Programming and its Applications," Springer Books, Springer, number 978-3-540-73671-4, November.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    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. 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.
    2. 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.
    3. 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.
    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).

    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. 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.
    2. Delasay, Mohammad & Ingolfsson, Armann & Kolfal, Bora & Schultz, Kenneth, 2019. "Load effect on service times," European Journal of Operational Research, Elsevier, vol. 279(3), pages 673-686.
    3. Ladeira, Wagner Junior & de Oliveira Santini, Fernando & Pinto, Diego Costa, 2022. "Clockwise versus counterclockwise turning bias: Moderation effects of foot traffic and cognitive experience on visual attention," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    4. Pascucci, Federica & Nardi, Lorenzo & Marinelli, Luca & Paolanti, Marina & Frontoni, Emanuele & Gregori, Gian Luca, 2022. "Combining sell-out data with shopper behaviour data for category performance measurement: The role of category conversion power," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    5. Kristiaan Kerstens & Ignace Van de Woestyne, 2018. "Enumeration algorithms for FDH directional distance functions under different returns to scale assumptions," Annals of Operations Research, Springer, vol. 271(2), pages 1067-1078, December.
    6. John Sherwood & Anthony Ditta & Becky Haney & Loren Haarsma & Michael Carbajales-Dale, 2017. "Resource Criticality in Modern Economies: Agent-Based Model Demonstrates Vulnerabilities from Technological Interdependence," Biophysical Economics and Resource Quality, Springer, vol. 2(3), pages 1-22, September.
    7. Ernesto Carrella & Richard M. Bailey & Jens Koed Madsen, 2018. "Indirect inference through prediction," Papers 1807.01579, arXiv.org.
    8. Sigurdsson, Valdimar & Larsen, Nils Magne & Alemu, Mohammed Hussen & Gallogly, Joseph Karlton & Menon, R. G. Vishnu & Fagerstrøm, Asle, 2020. "Assisting sustainable food consumption: The effects of quality signals stemming from consumers and stores in online and physical grocery retailing," Journal of Business Research, Elsevier, vol. 112(C), pages 458-471.
    9. Nils Engelbrecht & Tim-Benjamin Lembcke & Alfred Benedikt Brendel & Kilian Bizer & Lutz M. Kolbe, 2021. "The Virtual Online Supermarket: An Open-Source Research Platform for Experimental Consumer Research," Sustainability, MDPI, vol. 13(8), pages 1-25, April.
    10. Vandin, Andrea & Giachini, Daniele & Lamperti, Francesco & Chiaromonte, Francesca, 2022. "Automated and distributed statistical analysis of economic agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 143(C).
    11. Eyster, Erik & Galeotti, Andrea & Kartik, Navin & Rabin, Matthew, 2014. "Congested observational learning," Games and Economic Behavior, Elsevier, vol. 87(C), pages 519-538.
    12. Zeynep Akşin & Baris Ata & Seyed Morteza Emadi & Che-Lin Su, 2017. "Impact of Delay Announcements in Call Centers: An Empirical Approach," Operations Research, INFORMS, vol. 65(1), pages 242-265, February.
    13. Linda Dezso & Gergely Hajdu & Yossef Tobol, 2024. "Unexpected Waiting Corrupts," Department of Economics Working Papers wuwp358, Vienna University of Economics and Business, Department of Economics.
    14. Bolandifar, Ehsan & DeHoratius, Nicole & Olsen, Tava, 2023. "Modeling abandonment behavior among patients," European Journal of Operational Research, Elsevier, vol. 306(1), pages 243-254.
    15. Wesley Marcos Almeida & Claudimar Pereira Veiga, 2023. "Does demand forecasting matter to retailing?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 219-232, June.
    16. Mirko Kremer & Francis de Véricourt, 2022. "Mismanaging diagnostic accuracy under congestion," ESMT Research Working Papers ESMT-22-01, ESMT European School of Management and Technology.
    17. Larsen, Nils Magne & Sigurdsson, Valdimar & Breivik, Jørgen & Orquin, Jacob Lund, 2020. "The heterogeneity of shoppers’ supermarket behaviors based on the use of carrying equipment," Journal of Business Research, Elsevier, vol. 108(C), pages 390-400.
    18. Corrado Monti & Marco Pangallo & Gianmarco De Francisci Morales & Francesco Bonchi, 2022. "On learning agent-based models from data," Papers 2205.05052, arXiv.org, revised Nov 2022.
    19. Sezer Ülkü & Chris Hydock & Shiliang Cui, 2022. "Social Queues (Cues): Impact of Others’ Waiting in Line on One’s Service Time," Management Science, INFORMS, vol. 68(11), pages 7958-7976, November.
    20. Martin, James & Nenycz-Thiel, Magda & Dawes, John & Tanusondjaja, Arry & Cohen, Justin & McColl, Bruce & Trinh, Giang, 2020. "Fundamental basket size patterns and their relation to retailer performance," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).

    More about this item

    Keywords

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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ahh:wpaper:worms2016. 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: Anna Kowalska-Pyzalska (email available below). General contact details of provider: https://edirc.repec.org/data/kbpwrpl.html .

    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.