Analyzing store features for online order picking in grocery retailingan experimental study

  1. Vazquez-Noguerol, Mar 1
  2. Riveiro-Sanroman, Sara 1
  3. Portela-Caramés, Iago 1
  4. Prado-Prado, J. Carlos 1
  1. 1 Universidade de Vigo
    info

    Universidade de Vigo

    Vigo, España

    ROR https://ror.org/05rdf8595

Revista:
International Journal of Production Management and Engineering (IJPME)

ISSN: 2340-4876 2340-5317

Ano de publicación: 2022

Volume: 10

Número: 2

Páxinas: 183-193

Tipo: Artigo

DOI: 10.4995/IJPME.2022.17207 DIALNET GOOGLE SCHOLAR lock_openAcceso aberto editor

Outras publicacións en: International Journal of Production Management and Engineering (IJPME)

Resumo

The digital transformation is having a major impact on the consumer product market, pushing food retailers to foster online sales. To avoid large investments, e-grocers are tending to use their existing physical stores to undertake the online order picking process. In this context, these companies must choose in which traditional stores must prepare online orders. The aim of this study is to identify which store features affect order preparation times. The action research approach has been used at a Spanish e-grocer to analyze the characteristics that differentiate picking stores from each other; furthermore, the preparation times for a sample of online orders have been measured. The data were analyzed statistically using one-way ANOVA to define the optimal store in terms of size, assortment, backroom and congestion. The study shows that three of the four characteristics are significant on the preparation time. Therefore, e-grocers using a store-based model can use this information to focus their efforts on optimizing this process, assigning online order picking to the most appropriate stores. The approach used allows the study to be suitable for different retail context. Moreover, the results serve as support for strategic decision-making of researchers and e-grocers seeking to become more competitive in this continually growing market.

Referencias bibliográficas

  • Broekmeulen, R.A., Sternbeck, M.G., van Donselaar, K.H., & Kuhn, H. (2017). Decision support for selecting the optimal product unpacking location in a retail supply chain. European Journal of Operational Research, 259(1), 84-99. https://doi.org/10.1016/j.ejor.2016.09.054
  • Chintagunta, P.K., Chu, J., & Cebollada, J. (2012). Quantifying transaction costs in online/off-line grocery channel choice. Marketing Science, 31(1), 96-114. https://doi.org/10.1287/mksc.1110.0678
  • Dias, F.F., Lavieri, P.S., Sharda, S., Khoeini, S., Bhat, C.R., Pendyala, R.M., & Srinivasan, K.K. (2020). A comparison of online and in-person activity engagement: The case of shopping and eating meals. Transportation Research Part C: Emerging Technologies, 114, 643-656. https://doi.org/10.1016/j.trc.2020.02.023
  • Do, V.C., & Omdahl, K. (2018). Efficiency of e-grocery: Challenges and suggestions. (Doctoral thesis). University of Stavanger, Norway.
  • Fernie, J., Sparks, L., & McKinnon, A.C. (2010). Retail logistics in the UK: past, present and future. International Journal of Retail & Distribution Management, 38(11/12), 894-914. https://doi.org/10.1108/09590551011085975
  • Forbes Techonology Council Homepage, David Mounts, The digital transformation of retail grocery, https://www.forbes.com/sites/forbestechcouncil/2020/06/26/the-digital-transformation-of-retail-grocery/?sh=11e66b287300. Accessed: February 2021.
  • Gallino, S., & Moreno, A. (2019). Operations in an omnichannel world. Springer International Publishing. https://doi.org/10.1007/978-3-030-20119-7
  • Hailu, G. (2020). Economic thoughts on COVID-19 for Canadian food processors. Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, 68(2), 163-169. https://doi.org/10.1111/cjag.12241
  • Hendrickson, M.K. (2020). Covid lays bare the brittleness of a concentrated and consolidated food system. Agriculture and Human Values, 37(3), 579-580. https://doi.org/10.1007/s10460-020-10092-y
  • Hofmann, M., & Meyer-Nieberg, S. (2018). Time to dispense with the p-value in OR?. Central European Journal of Operations Research, 26(1), 193-214. https://doi.org/10.1007/s10100-017-0484-9
  • Hübner, A., Holzapfel, A., & Kuhn, H. (2015). Operations management in multi-channel retailing: an exploratory study. Operations Management Research, 8(3), 84-100. https://doi.org/10.1007/s12063-015-0101-9
  • Hübner, A., Holzapfel, A., Kuhn, H., & Obermair, E. (2019). Distribution in omnichannel grocery retailing: An analysis of concepts realized. Operations in an Omnichannel World. Springer. https://doi.org/10.1007/978-3-030-20119-7_12
  • Ishfaq, R., & Bajwa, N. (2019). Profitability of online order fulfillment in multi-channel retailing. European Journal of Operational Research, 272(3), 1028-1040. https://doi.org/10.1016/j.ejor.2018.07.047
  • Komijan, A.R., & Delavari, D. (2017). Vehicle routing and scheduling problem for a multi-period, multi-perishable product system with time window: A case study. International Journal of Production Management and Engineering, 5(2), 45-53. https://doi.org/10.4995/ijpme.2017.5960
  • Kumar, A., Mangla, S.K., Kumar, P., & Song, M. (2021). Mitigate risks in perishable food supply chains: Learning from COVID-19. Technological Forecasting and Social Change, 166, 120643. https://doi.org/10.1016/j.techfore.2021.120643
  • Mahajan, K., & Tomar, S. (2021). COVID-19 and supply chain disruption: evidence from food markets in India. American journal of agricultural economics, 103(1), 35-52. https://doi.org/10.1111/ajae.12158
  • Mangiaracina, R., Perego, A., Seghezzi, A., & Tumino, A. (2018). Optimizing store-based picking in the e-grocery: a model to assess costs and benefits. Industrial Systems Engineering.
  • Mishra, N., & Mukherjee, S. (2019). Effect of artificial intelligence on customer relationship management of amazon in Bangalore. International Journal of Management, 10(4), 168-172. https://doi.org/10.34218/IJM.10.4.2019.016
  • Paul, J., Agatz, N., & Savelsbergh, M. (2019). Optimizing omni-channel fulfillment with store transfers. Transportation Research Part B: Methodological, 129, 381-396. https://doi.org/10.1016/j.trb.2019.10.002
  • Pires, M., Pratas, J., Liz, J., & Amorim, P. (2017). A framework for designing backroom areas in grocery stores. International Journal of Retail & Distribution Management. 45(3), 230-252. https://doi.org/10.1108/IJRDM-01-2016-0004
  • Pires, M., Silva, E., & Amorim, P. (2021). Solving the grocery backroom layout problem. International Journal of Production Research, 59(3), 772-797. https://doi.org/10.1080/00207543.2019.1708990
  • Prado-Prado, J.C., García-Arca, J., Fernández-González, A.J., & Mosteiro-Añón, M. (2020). Increasing competitiveness through the implementation of lean management in healthcare. International Journal of Environmental Research and Public Health, 17(14), 4981. https://doi.org/10.3390/ijerph17144981
  • Rai, H.B., Verlinde, S., Macharis, C., Schoutteet, P., & Vanhaverbeke, L. (2019). Logistics outsourcing in omnichannel retail: State of practice and service recommendations. International Journal of Physical Distribution & Logistics Management.49(3), 267-286. https://doi.org/10.1108/IJPDLM-02-2018-0092
  • Rodríguez-García, M., González-Romero, I., Bas, Á.O., & Prado-Prado, J.C. (2021). E-grocery retailing: from value proposition to logistics strategy. International Journal of Logistics Research and Applications, 1-20. https://doi.org/10.1080/13675567.2021.1900086
  • Rodríguez-García, M., Domínguez-Caamano, P., & Prado-Prado, J.C. (2016) The New Supply Chain in the Era of E-Retailers: A State-of-the-art Literature Review Dirección y Organización, 59, 18-31. https://doi.org/10.37610/dyo.v0i59.491
  • Rooderkerk, R.P., & Kök, A.G. (2019). Omnichannel assortment planning. Operations in an omnichannel world.
  • Salgado, T.M.F.D.N. (2015). In-store Order Picking Routing: A Biased Random-Key Genetic Algorithm Approach. (Doctoral thesis). University of Porto, Portugal.
  • Schoen, Q., Sanchis, R., Poler, R., Lauras, M., Fontanili, F., & Truptil, S. (2018). Categorisation of the Main Disruptive Events in the Sensitive Products Transportation Supply Chains. International Journal of Production Management and Engineering, 6(2), 79-89. https://doi.org/10.4995/ijpme.2018.10369
  • Seidel, S. (2021). One goal, one approach? A comparative analysis of online grocery strategies in France and Germany. Case Studies on Transport Policy, 9(4), 1922-1932. https://doi.org/10.1016/j.cstp.2021.10.013
  • Seidel, S., Blanquart, C., & Ehrler, V. (2016). Same-same but different? A comparison of food retail and distribution structures in France and Germany. Case Studies on Transport Policy, 4(1), 29-37. https://doi.org/10.1016/j.cstp.2015.09.001
  • Shani, A.B., & Coghlan, D. (2021). Action research in business and management: A reflective review. Action Research, 19(3), 518-541. https://doi.org/10.1177/1476750319852147
  • Suel, E., Daina, N., & Polak, J.W. (2018). A hazard-based approach to modelling the effects of online shopping on intershopping duration. Transportation, 45(2), 415-428. https://doi.org/10.1007/s11116-017-9838-3
  • Tompkins, J.A., White, J.A., Bozer, Y.A., & Tanchoco, J.M.A. (2010). Facilities planning. John Wiley & Sons.
  • Vazquez-Noguerol, M., Comesaña-Benavides, J., Poler, R., & Prado-Prado, J.C. (2020). An optimisation approach for the e-grocery order picking and delivery problem. Central European Journal of Operations Research. https://doi.org/10.1007/s10100-020-00710-9
  • Vazquez-Noguerol, M., González-Boubeta, I., Portela-Caramés, I., & Prado-Prado, J.C. (2021). Rethinking picking processes in e-grocery: a study in the multichannel context. Business Process Management Journal. 27(2), 565-589. https://doi.org/10.1108/BPMJ-04-2020-0139
  • Wollenburg, J., Hübner, A., Kuhn, H., & Trautrims, A. (2018). From bricks-and-mortar to bricks-and-clicks: Logistics networks in omni-channel grocery retailing. International Journal of Physical Distribution & Logistics Management. https://doi.org/10.1108/IJPDLM-10-2016-0290
  • Zhao, G., Liu, S., Lopez, C., Chen, H., Lu, H., Mangla, S.K., & Elgueta, S. (2020). Risk analysis of the agri-food supply chain: A multi-method approach. International Journal of Production Research, 58(16), 4851-4876. https://doi.org/10.1080/00207543.2020.1725684