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

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. 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. 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. 3.

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

  4. 4.

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

  5. 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. 6.

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

  7. 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. 8.

    Ibid.

  9. 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. 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.

References

  1. Ainslie, G. (1975). Specious reward: A behavioral theory of impulsiveness and impulse control. Psychological Bulletin, 82, 463–496.

    Article  Google Scholar 

  2. Ashraf, N., Karlan, D., & Yin, W. (2006). Tying Odysseus to the mast: Evidence from a commitment savings product in the Philippines. Quarterly Journal of Economics, 121(2), 635–672.

    Article  Google Scholar 

  3. Bazerman, M. H., Tenbrunsel, A. E., & Wade-Benzoni, K. (1998). Negotiating with yourself and losing: Making decisions with competing internal preferences. Academy of Management Review, 23(2), 225–241.

    Article  Google Scholar 

  4. Benzion, U., Rapopport, A., & Yagil, Y. (1989). Discount rates inferred from decisions: An experimental study. Management Science, 35(3), 270–284.

    Article  Google Scholar 

  5. comScore Press Release (2007) comScore Networks reports total non-travel e-commerce spending reaches $102 billion in 2006; up 24 percent versus 2005. comScore Press Release. January 3, 2007. Accessed April 30, 2008: http://www.comscore.com/press/release.asp?press=1166.

  6. Drewnowski, A., & Barratt-Fornell, A. (2004). Do healthier diets cost more? Nutrition Today, 39(4), 161–168.

    Article  Google Scholar 

  7. Heilman, C. M., Nakamoto, K., & Rao, A. G. (2002). Pleasant surprises: Consumer response to unexpected in-store coupons. Journal of Marketing Research, 39(2), 242–252.

    Article  Google Scholar 

  8. Khan, U., Dhar, R., & Wertenbroch, K. (2005). A behavioral decision theory perspective on hedonic and utilitarian choice. In S. Ratneshwar & D. G. Mick (Eds.), Inside consumption: Frontiers of research on consumer motives, goals, and desires (pp. 144–165). London: Routledge.

    Google Scholar 

  9. Loewenstein, G. F. (1996). Out of control: Visceral influences on behavior. Organizational Behavior and Human Decision Processes, 65(3), 272–292.

    Article  Google Scholar 

  10. Loewenstein, G. F., & Prelec, D. (1992). Anomalies in intertemporal choice: Evidence and an interpretation. Quarterly Journal of Economics, 107, 573–597.

    Article  Google Scholar 

  11. Malmendier, U., & Della Vigna, S. (2006). Paying not to go to the gym. American Economic Review, 96(3), 694–719.

    Article  Google Scholar 

  12. Martin, J. M., Beshears, J., Milkman, K. L., Bazerman, M. H., & Sutherland, L. (2009). Modeling expert opinions on food healthiness: A nutrition metric. Journal of the American Dietetic Association, 109(6), 1088–1091.

    Article  Google Scholar 

  13. Milkman, K. L., & Beshears, J. (2009). Mental accounting and small windfalls: Evidence from an online grocer. Journal of Economic Behavior and Organization, 71(2), 384–394.

    Article  Google Scholar 

  14. Milkman, K. L., Rogers, T., & Bazerman, M. H. (2008). Harnessing our inner angels and demons: What we have learned about want/should conflicts and how that knowledge can help us reduce short-sighted decision making. Perspectives on Psychological Science, 3, 324–338.

    Article  Google Scholar 

  15. Milkman, K. L., Rogers, T., & Bazerman, M. H. (2009). Highbrow films gather dust: Time-inconsistent preferences and online DVD rentals. Management Science, 55(6), 1047–1059.

    Article  Google Scholar 

  16. Oster, S., & Scott Morton, F. M. (2005). Behavioral biases meet the market: The case of magazine subscription prices. BE Journals Economic Analysis and Policy—Advances, 5(1), 1323.

    Google Scholar 

  17. Read, D. (2001). Intrapersonal dilemmas. Human Relations, 54(8), 1093–1117.

    Article  Google Scholar 

  18. Rogers, T., & Bazerman, M. H. (2008). Future lock-in: Future implementation increases selection of should choices. Organizational Behavior and Human Decision Processes, 106(1), 1–20.

    Article  Google Scholar 

  19. Schelling, T. C. (1984). Choice and consequence: Perspectives of an errant economist. Cambridge: Harvard University Press.

    Google Scholar 

  20. Shefrin, H., & Thaler, R. H. (1988). The behavioral life-cycle hypothesis. Economic Inquiry, 26(4), 609–643.

    Article  Google Scholar 

  21. Shrout, P. E., & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 86(2), 420–428.

    Article  Google Scholar 

  22. Sunstein, C. R., & Thaler, R. H. (2003). Libertarian paternalism is not an oxymoron. University of Chicago Law Review, 70, 1159–1199.

    Article  Google Scholar 

  23. Trope, Y., & Liberman, N. (2003). Temporal construal. Psychological Review, 110, 403–421.

    Article  Google Scholar 

  24. Van Duyn, M. A. S., & Pivonka, E. (2000). Overview of the health benefits of fruit and vegetable consumption for the dietetics profession: Selected literature. Journal of the American Dietetic Association, 100(12), 1511–1521.

    Article  Google Scholar 

  25. Willet, W. C. (1994). Diet and health: What should we eat? Science, 264(5158), 532–537.

    Article  Google Scholar 

  26. Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge: MIT.

    Google Scholar 

  27. Zauberman, G., & Lynch, J. G. (2005). Resource slack and propensity to discount delayed investments of time versus money. Journal of Experimental Psychology: General, 134(1), 23–37.

    Article  Google Scholar 

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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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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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Keywords

  • Lead time
  • Intertemporal choice
  • Want/should
  • E-commerce
  • Intrapersonal conflict