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Consumer Response to Package Downsizing: Evidence from the Chicago Ice Cream Market

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  • Çakır, Metin
  • Balagtas, Joseph V.

Abstract

It is common among producers of consumer packaged goods to reduce the volume of product per package such that the new size replaces the old one. This tactic is commonly referred to as package downsizing. In this article, we investigate the extent to which consumers have different sensitivities to package price and package size in order to shed light on the managerial implications of package downsizing. To do so, we estimate a random utility model of demand to measure consumer response to price and package size using household scanner panel data on bulk ice cream purchases in Chicago. The estimation framework involves modeling household heterogeneity, addressing price endogeneity and accounting for unbalanced choice alternatives. Our main finding is that consumers are less responsive to package size than to price; the demand elasticity with respect to package size is approximately one-fourth the magnitude of the demand elasticity with respect to price. This result implies that marketing managers can use downsizing as a hidden price increase in order to pass through increases in production costs, that is, cost of raw materials, and maintain, or increase, their profits.

Suggested Citation

  • Çakır, Metin & Balagtas, Joseph V., 2014. "Consumer Response to Package Downsizing: Evidence from the Chicago Ice Cream Market," Journal of Retailing, Elsevier, vol. 90(1), pages 1-12.
  • Handle: RePEc:eee:jouret:v:90:y:2014:i:1:p:1-12
    DOI: 10.1016/j.jretai.2013.06.002
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    Cited by:

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    2. Lai, Yufeng & Yue, Chengyan & Watkins, Eric & Barnes, Mike, 2023. "Investigating the Efficacy of Government Rebates: A Case of the Smart Irrigation System," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 48(3), September.
    3. Jun Yao & Harmen Oppewal & Di Wang, 2020. "Cheaper and smaller or more expensive and larger: how consumers respond to unit price increase tactics that simultaneously change product price and package size," Journal of the Academy of Marketing Science, Springer, vol. 48(6), pages 1075-1094, November.
    4. Secor, William & Çakır, Metin, 2016. "Impacts from a retail grocery acquisition: Do national and store brand prices respond differently?," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235945, Agricultural and Applied Economics Association.
    5. Anna-Liesa Lange & Philipp Otto, 2016. "Bayes’sche Statistik in der Dienstleistungsforschung [Bayesian statistics in service research]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(4), pages 247-267, December.
    6. Petit, Olivia & Lunardo, Renaud & Rickard, Bradley, 2020. "Small is beautiful: The role of anticipated food waste in consumers’ avoidance of large packages," Journal of Business Research, Elsevier, vol. 113(C), pages 326-336.
    7. Metin Çakır & Joseph V. Balagtas & Abigail M. Okrent & Mariana Urbina‐Ramirez, 2021. "Effects of Package Size on Household Food Purchases," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(2), pages 781-801, June.
    8. Afif, Karima & Rebolledo, Claudia & Roy, Jacques, 2022. "Evaluating the effectiveness of the weight-based packaging tax on the reduction at source of product packaging: The case of food manufacturers and retailers," International Journal of Production Economics, Elsevier, vol. 245(C).
    9. Metin Çakır, 2022. "Retail pass‐through of package downsizing," Agribusiness, John Wiley & Sons, Ltd., vol. 38(2), pages 259-278, April.
    10. Rudi, Jeta & Çakır, Metin, 2017. "Vice or virtue: How shopping frequency affects healthfulness of food choices," Food Policy, Elsevier, vol. 69(C), pages 207-217.
    11. Robert Sinclair & Jess Diamond, 2022. "Basic food and drink price distributions transcend time and culture," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-7, December.
    12. Yonezawa, Koichi & Richards, Timothy J., 2016. "Competitive Package Size Decisions," Journal of Retailing, Elsevier, vol. 92(4), pages 445-469.
    13. Qin, Fei & Ma, Meilin, 2022. "Unit Pricing Regulation and Non-Price Responses of Retailers: Evidence from the U.S. Yogurt Market," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322243, Agricultural and Applied Economics Association.
    14. Nicole Koschate-Fischer & Katharina Wüllner, 2017. "New developments in behavioral pricing research," Journal of Business Economics, Springer, vol. 87(6), pages 809-875, August.
    15. Ketron, Seth, 2018. "Perceived Product Sizes in Visually Complex Environments," Journal of Retailing, Elsevier, vol. 94(2), pages 154-166.
    16. Cakir, Metin & Balagtas, Joseph Valdes & Okrent, Abigail M., 2014. "The impact of package size on consumption," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182776, European Association of Agricultural Economists.
    17. Peng, Jing & Zhang, Jianghua & Nie, Tengfei & Zhu, Yangguang & Du, Shaofu, 2020. "Pricing and package size decisions in crowdfunding," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    18. Viktor Vojtko, 2014. "Rethinking the Concept of Just Noticeable Difference in Online Marketing," Acta Informatica Pragensia, Prague University of Economics and Business, vol. 2014(2), pages 204-218.

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    More about this item

    Keywords

    Consumer behavior; Package downsizing; Demand analysis; Discrete choice model; Hierarchical Bayesian analysis;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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