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

Li Zhou and Guowei Zhu

Journal of Business Research, 2022, vol. 139, issue C, 354-367

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.

Keywords: Numerical precision; Discrepancy; Negative emotion; Calorie-equivalent exercise data; Food labeling; Food choices (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0148296321007074
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:139:y:2022:i:c:p:354-367

DOI: 10.1016/j.jbusres.2021.09.056

Access Statistics for this article

Journal of Business Research is currently edited by A. G. Woodside

More articles in Journal of Business Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().