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Online Grocery Retail: Revenue Models and Environmental Impact

Author

Listed:
  • Elena Belavina

    (Booth School of Business, University of Chicago, Chicago, Illinois 60637)

  • Karan Girotra

    (Technology and Operations Management, INSEAD, 77305 Fontainebleau Cedex, France)

  • Ashish Kabra

    (Technology and Operations Management, INSEAD, 77305 Fontainebleau Cedex, France)

Abstract

This paper compares the financial and environmental performance of two revenue models for the online retailing of groceries: the per-order model, where customers pay for each delivery, and the subscription model, where customers pay a set fee and receive free deliveries. We build a stylized model that incorporates (i) customers with ongoing uncertain grocery needs and who choose between shopping offline or online and (ii) an online retailer that makes deliveries through a proprietary distribution network. We find that subscription incentivizes smaller and more frequent grocery orders, which reduces food waste and creates more value for the customer; the result is higher retailer revenues, lower grocery costs, and potentially higher adoption rates. These advantages are countered by greater delivery-related travel and expenses, which are moderated by area geography and routing-related scale economies. Subscription also leads to lower food waste–related emissions but to higher delivery-related emissions. Ceteris paribus, the per-order model is preferable for higher-margin retailers with higher-consumption product assortments that are sold in sparsely populated markets spread over large, irregular areas with high delivery costs. Geographic and demographic data indicate that the subscription model is almost always environmentally preferable because lower food waste emissions dominate higher delivery emissions.

Suggested Citation

  • Elena Belavina & Karan Girotra & Ashish Kabra, 2017. "Online Grocery Retail: Revenue Models and Environmental Impact," Management Science, INFORMS, vol. 63(6), pages 1781-1799, June.
    • Handle: RePEc:inm:ormnsc:v:63:y:2017:i:6:p:1781-1799
    DOI: 10.1287/mnsc.2016.2430
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    References listed on IDEAS

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    1. Vishal V. Agrawal & Mark Ferguson & L. Beril Toktay & Valerie M. Thomas, 2012. "Is Leasing Greener Than Selling?," Management Science, INFORMS, vol. 58(3), pages 523-533, March.
    2. Steven Nahmias, 2011. "Perishable Inventory Systems," International Series in Operations Research and Management Science, Springer, edition 1, number 978-1-4419-7999-5, April.
    3. Peter J. Danaher, 2002. "Optimal Pricing of New Subscription Services: Analysis of a Market Experiment," Marketing Science, INFORMS, vol. 21(2), pages 119-138, February.
    4. Pradeep K. Chintagunta & Junhong Chu & Javier Cebollada, 2012. "Quantifying Transaction Costs in Online/Off-line Grocery Channel Choice," Marketing Science, INFORMS, vol. 31(1), pages 96-114, January.
    5. Emre Berk & Ülkü Gürler, 2008. "Analysis of the ( Q , r ) Inventory Model for Perishables with Positive Lead Times and Lost Sales," Operations Research, INFORMS, vol. 56(5), pages 1238-1246, October.
    6. Daganzo, Carlos F., 1984. "The length of tours in zones of different shapes," Transportation Research Part B: Methodological, Elsevier, vol. 18(2), pages 135-145, April.
    7. Howard J. Weiss, 1980. "Optimal Ordering Policies for Continuous Review Perishable Inventory Models," Operations Research, INFORMS, vol. 28(2), pages 365-374, April.
    8. Il-Horn Hann & Christian Terwiesch, 2003. "Measuring the Frictional Costs of Online Transactions: The Case of a Name-Your-Own-Price Channel," Management Science, INFORMS, vol. 49(11), pages 1563-1579, November.
    9. Gérard P. Cachon, 2014. "Retail Store Density and the Cost of Greenhouse Gas Emissions," Management Science, INFORMS, vol. 60(8), pages 1907-1925, August.
    10. Gérard P. Cachon & Pnina Feldman, 2011. "Pricing Services Subject to Congestion: Charge Per-Use Fees or Sell Subscriptions?," Manufacturing & Service Operations Management, INFORMS, vol. 13(2), pages 244-260, June.
    11. Carlos F. Daganzo, 1984. "The Distance Traveled to Visit N Points with a Maximum of C Stops per Vehicle: An Analytic Model and an Application," Transportation Science, INFORMS, vol. 18(4), pages 331-350, November.
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