The impact of committing to customer orders in online retail

Goncalo Figueira, Willem van Jaarsveld, Pedro Amorim, Jan C. Fransoo*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review


Problem definition: Online retailers are on a consistent drive to increase on-time delivery and reduce customer lead time. However, in reality, an increasing share of consumers places orders early. Academic/practical relevance: Such advance demand information can be deployed strategically to reduce costs and improve the customer service experience. This requires inventory and allocation policies that make optimal use of this information and that induce consumers to place their orders early. An increasing number of online retailers not only offer customers a choice of lead time but also, actively back-order missing items from a consumer basket. Methodology: We develop new allocation policies that commit to a customer order upon arrival of the order rather than at the moment the order is due. We provide analytical results for the performance of these allocation policies and evaluate their behavior with real data from a large food retailer. Results: Our policy leads to a higher fill rate at the expense of a slight increase in average delay. The analysis based on real-life data suggests a sizeable impact that should impact current best practices in online retail. Managerial implications: With the changing landscape in online retail, customers increasingly place baskets of orders that they would like to receive at a planned and confirmed moment in time. Especially in grocery, this has grown fast. This fundamentally changes the strategic management of inventory. We demonstrate that online retailers should commit early to customer orders to enhance the customer service experience and eventually, to also create opportunities for reducing the cost of operations.

Superscript/Subscript Available

Original languageEnglish
Pages (from-to)307-322
JournalManufacturing and Service Operations Management
Issue number1
Early online dateSept 2022
Publication statusPublished - Jan 2023


  • online retail
  • inventory control
  • advance demand information
  • allocation policies
  • backordering


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