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I’ll have the ice cream soon and the vegetables later: A study of online grocery purchases and order lead time

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Abstract

How do decisions made for tomorrow or 2 days in the future differ from decisions made for several days in the future? We use data from an online grocer to address this question. In general, we find that as the delay between order completion and delivery increases, grocery customers spend less, order a higher percentage of “should” items (e.g., vegetables), and order a lower percentage of “want” items (e.g., ice cream), controlling for customer fixed effects. These field results replicate previous laboratory findings and are consistent with theories suggesting that people’s should selves exert more influence over their choices the further in the future outcomes will be experienced. However, orders placed for delivery tomorrow versus 2 days in the future do not show this want/should pattern, and we discuss a potential explanation.

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Notes

  1. Note that a considerable body of work has demonstrated that people behave more impulsively when making choices for now rather than for later (see Milkman et al. 2008 for a review).

  2. Details about the number of unique customers, total number of grocery orders, and average number of orders per customer in our data set are not provided in order to preserve the anonymity of our data provider.

  3. This allows us to control for how much time has elapsed since a customer’s last order in our analyses.

  4. More details on the seasonality of order lead time are available upon request.

  5. Lengthy concept definitions were provided to participants and they were also quizzed on their understanding of these concepts. Full materials are available upon request. The final summary of a “want” grocery read: “The ‘want’ score is intended to reflect the extent to which someone’s decision to consume this type of grocery would be indulgent and pleasure-based.” The final summary of a “should” grocery read: “The ‘should’ score ought to reflect the extent to which someone’s choice to consume the grocery would be made for virtuous, self-improving reasons, regardless of other potential factors.”

  6. Wilks’ lambdas from multivariate analysis of variances run to examine potential ordering effects were all insignificant at the 5% level.

  7. Because the choice to look at ten categories rather than some other number is somewhat arbitrary, we replicate all results examining the top five categories of should and want groceries as a robustness check.

  8. Ibid.

  9. Regressions examining the percent spending on the five grocery categories receiving the highest and lowest should minus want scores reveal the same patterns and are available upon request. These results also hold if grocery categories containing alcohol and/or cigarettes are removed.

  10. Although it is possible that people only buy a healthier bundle of groceries when they order further in the future and do not actually eat healthier groceries, it seems likely that purchases are highly correlated with consumption.

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Acknowledgments

The authors thank John Beshears, George Loewenstein, Kathleen McGinn, Nava Ashraf, David Parkes, Carey Morewedge, Bill Simpson, Sarah Woolverton, and a very helpful set of reviewers for their assistance with this project. We are also grateful to the employees of the online grocer who generously shared their time, data and ideas with us.

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Authors and Affiliations

  1. The Wharton School, 3730 Walnut Street, 561 Jon M. Huntsman Hall, Philadelphia, PA, 19104, USA

    Katherine L. Milkman

  2. Analyst Institute, Washington, DC, USA

    Todd Rogers

  3. Harvard Business School, Baker Library 453, Soldiers Field Road, Boston, MA, 02163, USA

    Max H. Bazerman

Authors
  1. Katherine L. Milkman
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  2. Todd Rogers
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  3. Max H. Bazerman
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Corresponding author

Correspondence to Katherine L. Milkman.

Appendix

Appendix

Table 6 Average should minus want scores for grocery categories in our data set
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Milkman, K.L., Rogers, T. & Bazerman, M.H. I’ll have the ice cream soon and the vegetables later: A study of online grocery purchases and order lead time. Mark Lett 21, 17–35 (2010). https://doi.org/10.1007/s11002-009-9087-0

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  • DOI: https://doi.org/10.1007/s11002-009-9087-0

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