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Mind the gap: How the numerical precision of exercise-data-based food labels can nudge healthier food choices

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  • Zhou, Li
  • Zhu, Guowei

Abstract

Presenting calorie-equivalent exercise data (hereafter, “exercise data”) has been proven to be an effective alternative to nudge better food-consumption behavior. The present paper examines how the numerical precision of exercise-data-based food labels impacts food-consumption intention and choice. We propose that precise exercise data can trigger a salient violation of expectation on numeric format. This in turn can induce a (mis)attribution process that intensifies negative emotions linked to unhealthy food consumption, thus decreasing consumers’ consumption intentions. The results of five studies show supports to our proposition. Specifically, consumers showed lower consumption intention on unhealthy food when the food label contains precise (vs. rounded) exercise data. In addition, a real-life behavioral study indicates that the precision effect of exercise data is more prominent when the food is unhealthy versus healthy. These findings shed light for policymakers and food enterprises on the potential managerial applications of food labeling.

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  • Zhou, Li & Zhu, Guowei, 2022. "Mind the gap: How the numerical precision of exercise-data-based food labels can nudge healthier food choices," Journal of Business Research, Elsevier, vol. 139(C), pages 354-367.
    • Handle: RePEc:eee:jbrese:v:139:y:2022:i:c:p:354-367
    DOI: 10.1016/j.jbusres.2021.09.056
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