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Operational planning for public holidays in grocery retailing - managing the grocery retail rush

Author

Listed:
  • Elisabeth Obermair

    (Department of Logistics Management, Hochschule Geisenheim University)

  • Andreas Holzapfel

    (Department of Logistics Management, Hochschule Geisenheim University)

  • Heinrich Kuhn

    (Chair of Supply Chain Management & Operations, Catholic University Eichstätt-Ingolstadt)

Abstract

Public holiday weeks cause specific challenges in grocery retailing as sales are raising and working days for logistics processes are reduced. The paper analyzes the operational planning challenges and solutions for demand planning and disposition as well as for warehouse and transportation management of grocery retailers in public holiday seasons. A total of 22 top managers representing 20 sales lines of 17 of the top 30 grocery retailers in Germany participated in the study. Semi-structured, face-to-face interviews with logistics managers were conducted and analyzed. Uncertainties and missing resources can be identified as the two main challenges of public holiday seasons in grocery retailing. Retailers implement numerous measures that can be summarized in three categories, i.e., the adjustment of workload profiles, the adaptation of resources and modifying processes. Literature has so far considered public holidays only to a limited extent, e.g., as a parameter in forecasting models or for the application of marketing instruments. This study is the first developing a framework and providing insights into operational planning in grocery retailing.

Suggested Citation

  • Elisabeth Obermair & Andreas Holzapfel & Heinrich Kuhn, 2023. "Operational planning for public holidays in grocery retailing - managing the grocery retail rush," Operations Management Research, Springer, vol. 16(2), pages 931-948, June.
    • Handle: RePEc:spr:opmare:v:16:y:2023:i:2:d:10.1007_s12063-022-00342-z
    DOI: 10.1007/s12063-022-00342-z
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    References listed on IDEAS

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    1. Ehrenthal, J.C.F. & Honhon, D. & Van Woensel, T., 2014. "Demand seasonality in retail inventory management," European Journal of Operational Research, Elsevier, vol. 238(2), pages 527-539.
    2. Karel H. van Donselaar & Vishal Gaur & Tom van Woensel & Rob A. C. M. Broekmeulen & Jan C. Fransoo, 2010. "Ordering Behavior in Retail Stores and Implications for Automated Replenishment," Management Science, INFORMS, vol. 56(5), pages 766-784, May.
    3. Sara Martins & Pedro Amorim & Bernardo Almada-Lobo, 2018. "Delivery mode planning for distribution to brick-and-mortar retail stores: discussion and literature review," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 785-812, December.
    4. Holzapfel, Andreas & Kuhn, Heinrich & Sternbeck, Michael G., 2018. "Product allocation to different types of distribution center in retail logistics networks," European Journal of Operational Research, Elsevier, vol. 264(3), pages 948-966.
    5. Gur Ali, Ozden & Pinar, Efe, 2016. "Multi-period-ahead forecasting with residual extrapolation and information sharing — Utilizing a multitude of retail series," International Journal of Forecasting, Elsevier, vol. 32(2), pages 502-517.
    6. Cesar Augusto Henao & Juan Carlos Munoz & Juan Carlos Ferrer, 2015. "The impact of multi-skilling on personnel scheduling in the service sector: a retail industry case," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(12), pages 1949-1959, December.
    7. Gu, Jinxiang & Goetschalckx, Marc & McGinnis, Leon F., 2007. "Research on warehouse operation: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 177(1), pages 1-21, February.
    8. Fildes, Robert & Kolassa, Stephan & Ma, Shaohui, 2022. "Post-script—Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1319-1324.
    9. Petersen, Charles G. & Aase, Gerald, 2004. "A comparison of picking, storage, and routing policies in manual order picking," International Journal of Production Economics, Elsevier, vol. 92(1), pages 11-19, November.
    10. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
    11. Teun van Gils & Katrien Ramaekers & An Caris & Mario Cools, 2017. "The use of time series forecasting in zone order picking systems to predict order pickers’ workload," International Journal of Production Research, Taylor & Francis Journals, vol. 55(21), pages 6380-6393, November.
    12. van Gils, Teun & Ramaekers, Katrien & Caris, An & de Koster, René B.M., 2018. "Designing efficient order picking systems by combining planning problems: State-of-the-art classification and review," European Journal of Operational Research, Elsevier, vol. 267(1), pages 1-15.
    13. 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.
    14. Piecyk, Maja I. & McKinnon, Alan C., 2010. "Forecasting the carbon footprint of road freight transport in 2020," International Journal of Production Economics, Elsevier, vol. 128(1), pages 31-42, November.
    15. Susanne Wruck & Iris F.A. Vis & Jaap Boter, 2017. "Risk control for staff planning in e-commerce warehouses," International Journal of Production Research, Taylor & Francis Journals, vol. 55(21), pages 6453-6469, November.
    16. Frank, Markus & Ostermeier, Manuel & Holzapfel, Andreas & Hübner, Alexander & Kuhn, Heinrich, 2021. "Optimizing routing and delivery patterns with multi-compartment vehicles," European Journal of Operational Research, Elsevier, vol. 293(2), pages 495-510.
    17. Klibi, Walid & Martel, Alain & Guitouni, Adel, 2010. "The design of robust value-creating supply chain networks: A critical review," European Journal of Operational Research, Elsevier, vol. 203(2), pages 283-293, June.
    18. Kaveh Azadeh & René De Koster & Debjit Roy, 2019. "Robotized and Automated Warehouse Systems: Review and Recent Developments," Transportation Science, INFORMS, vol. 53(4), pages 917-945, July.
    19. Chethana Dharmawardane & Ville Sillanpää & Jan Holmström, 2021. "High-frequency forecasting for grocery point-of-sales: intervention in practice and theoretical implications for operational design," Operations Management Research, Springer, vol. 14(1), pages 38-60, June.
    20. Holzapfel, Andreas & Hübner, Alexander & Kuhn, Heinrich & Sternbeck, Michael G., 2016. "Delivery pattern and transportation planning in grocery retailing," European Journal of Operational Research, Elsevier, vol. 252(1), pages 54-68.
    21. Dekker, Mark & van Donselaar, Karel & Ouwehand, Pim, 2004. "How to use aggregation and combined forecasting to improve seasonal demand forecasts," International Journal of Production Economics, Elsevier, vol. 90(2), pages 151-167, July.
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